Harnessing RiPP Biosynthetic Pathways for Next-Generation Peptide Engineering and Drug Discovery

Abstract

This article provides a comprehensive analysis of Ribosomally synthesized and post-translationally modified peptides (RiPPs) as versatile platforms for peptide engineering. Targeting researchers and drug development professionals, we explore the foundational biosynthetic logic of RiPP pathways, detail cutting-edge methodologies for genome mining and heterologous expression, and address key challenges in optimizing these systems. By examining validation strategies and comparative analyses of engineered RiPPs, we synthesize a framework for exploiting RiPP modularity to create novel bioactive peptides with enhanced therapeutic potential, particularly against pressing global threats like antimicrobial resistance.

Deconstructing RiPP Biosynthesis: From Ribosomal Precursors to Complex Natural Products

Ribosomally synthesized and post-translationally modified peptides (RiPPs) represent a rapidly expanding superfamily of natural products with significant pharmaceutical potential, including applications as antibiotics, anticancer agents, and treatments for neurological disorders [1] [2]. The biosynthesis of RiPPs follows a conserved logic, beginning with the ribosomal synthesis of a precursor peptide that serves as the scaffold for all subsequent enzymatic modifications [3]. This precursor peptide is organized into distinct functional regions—the leader, core, and sometimes follower peptides—that work in concert to guide the maturation process. Understanding the precise roles of these domains is fundamental to leveraging RiPP pathways for peptide engineering, enabling researchers to rationally design novel bioactive compounds with enhanced stability and targeted activities [4]. The modular nature of this biosynthetic system, combined with advancing genome mining tools, positions RiPPs as ideal candidates for synthetic biology approaches to drug discovery.

Architectural Components of RiPP Precursor Peptides

Leader Peptide: The Recognition and Recruitment Guide

The leader peptide is an N-terminal region that acts as a recognition signal and binding platform for the biosynthetic enzymes. It is typically removed proteolytically after modifications are complete [3] [1]. Its primary function is to ensure the correct enzymatic modifications are installed on the core peptide.

• Molecular Recognition: Leader peptides are bound by specific domains in the biosynthetic machinery, such as the RiPP precursor Recognition Element (RRE). The RRE domain binds with high specificity and affinity to a recognition sequence within the leader peptide [5].
• Enzyme Activation: Beyond mere substrate recruitment, leader peptides can allosterically activate their cognate enzymes. For lasso peptides, the leader peptide-bound RRE domain is essential for forming the proteolytic active site, dramatically increasing the efficiency of leader peptide cleavage [5].
• Structural Spectrum: While most leader peptides are short (<50 amino acids) and unstructured in their free state, atypical leaders known as nitrile hydratase-like leader peptides (NHLPs) are much longer (>80 amino acids) and can adopt stable tertiary structures, engaging with modifying enzymes through more complex protein-protein interactions [6].

Core Peptide: The Functional Product Blueprint

The core peptide is the C-terminal region that undergoes extensive post-translational modifications (PTMs) to become the mature RiPP natural product [4] [3]. The core peptide's sequence determines the final chemical structure and biological activity.

• Site of Chemical Diversification: The core peptide is the substrate for a wide array of PTMs, including macrocyclization, heterocycle formation, and the installation of thioether bridges [3]. These modifications are crucial for the functional properties of the final product.
• Determinant of Product Scaffold: The sequence of the core peptide dictates the type of RiPP produced. For instance, in lasso peptides, specific residues in the core are essential for forming the unique knotted structure [1].
• Genomic Mining Target: In genome mining, the core peptide sequence and the enzymes that modify it are key to predicting the final natural product's structure [7].

Follower Peptide: The Less Common C-Terminal Signal

Some RiPP precursor peptides contain an additional C-terminal region, known as a follower peptide [4] [7]. Not universal across RiPP classes, the follower peptide's roles are less defined but involve recognition and proteolytic removal.

• Alternative Recognition Sequence: In certain RiPP classes, such as bottromycins, the follower peptide replaces the N-terminal leader as the primary recognition sequence for the biosynthetic enzymes [1].
• Proteolytic Removal: Similar to the leader peptide, the follower sequence is proteolytically removed during the final maturation steps to release the active RiPP [7].

Table 1: Summary of RiPP Precursor Peptide Domains and Their Functions

Peptide Domain	Location	Primary Function	Fate in Maturation	Example RiPP Classes
Leader Peptide	N-terminal	Enzyme recognition and activation [5]; Substrate delivery [5]	Proteolytically removed [3]	Lanthipeptides [6]; Lasso peptides [5]; Cyanobactins [3]
Core Peptide	C-terminal	Template for post-translational modifications; Determines final structure and activity [4] [3]	Becomes the mature natural product [3]	All RiPP classes
Follower Peptide	C-terminal (less common)	Recognition signal for biosynthetic machinery [1]	Proteolytically removed [7]	Bottromycins [1]

Figure 1: Functional Workflow of RiPP Precursor Peptide Domains - This diagram illustrates how leader, core, and follower peptides interact with biosynthetic machinery to produce a mature RiPP.

Experimental Protocols for Functional Analysis

Protocol: In Vivo Leader Peptide Dependence Assay for a LanM Enzyme

This protocol, based on the study of the lanthionine synthetase DprM, tests whether a leader peptide is essential for enzyme activity and can be used to probe enzyme specificity [6].

• Step 1: Gene Co-expression

  • Clone the gene for the modifying enzyme (e.g., dprM) and the gene for its putative precursor peptide (e.g., dprE1) into compatible expression plasmids. Ensure the precursor gene includes its native leader sequence.
  • Co-transform these plasmids into an appropriate heterologous host, such as Escherichia coli. Include a control transformation with the precursor peptide plasmid alone.

• Step 2: Protein Expression and Purification

  • Grow the transformed cultures to the appropriate density and induce expression with a suitable inducer (e.g., IPTG).
  • Harvest the cells and purify the precursor peptide from both the experimental and control cultures using a method suited to the peptide's properties, such as affinity chromatography leveraging an engineered tag.

• Step 3: Mass Spectrometric Analysis

  • Analyze the purified peptides using mass spectrometry (MS). Compare the mass of the peptide from the co-expression culture to the control.
  • A mass loss of 18 Da (or multiples thereof) is indicative of dehydration events, confirming that the enzyme successfully modified the core peptide, and thus, recognized the leader [6].

Protocol: In Vitro Leader Peptidase Activation Assay

This protocol details a colorimetric method to quantify leader peptidase activity and its dependence on the RRE domain, as demonstrated for lasso peptide biosynthesis [5].

• Step 1: Protein and Substrate Preparation

  • Express and purify the following components: the leader peptidase (e.g., FusB), its cognate RRE domain, and the precursor peptide or a synthetic leader peptide fused to a colorimetric tag like para-nitroanilide (pNA).

• Step 2: Reaction Setup

  • Prepare reactions in a clear-bottom 96-well plate. The key is to vary the presence of the RRE domain.
  • Condition A: Leader peptidase + leader-pNA substrate.
  • Condition B: Leader peptidase + RRE domain (pre-mixed) + leader-pNA substrate.
  • Include controls lacking enzyme or substrate to account for background hydrolysis.

• Step 3: Kinetic Measurement and Analysis

  • Monitor the absorbance at 405 nm (for released pNA) over time using a plate reader.
  • Compare the initial reaction velocities (Vâ‚€) between Condition A and B. A significant increase in Vâ‚€ in Condition B demonstrates the RRE domain's role in activating the peptidase [5].

Table 2: Key Reagents for RiPP Functional Analysis

Reagent / Tool	Function / Utility	Example Use Case
Codon-Optimized Synthetic Genes	Enables high-yield heterologous expression in hosts like E. coli [6]	Expression of dprM and dprE genes in E. coli for in vivo assays [6]
p-nitroanilide (pNA) Tagged Substrate	Provides a colorimetric readout for protease/peptidase activity [5]	Quantifying leader peptidase (FusB) kinetics in the presence and absence of the RRE domain [5]
RiPP Recognition Element (RRE)	Binds leader peptide with high affinity and specificity; required for full peptidase activity [5]	Studying allosteric activation of lasso leader peptidases
Sequence Similarity Network (SSN)	Bioinformatic tool to visualize evolutionary relationships and identify new enzyme subfamilies [6]	Discovering novel NHLP-selective LanM enzymes (e.g., DprM) [6]

Figure 2: Experimental Workflows for Functional Analysis - This diagram outlines the key steps for conducting in vivo modification and in vitro peptidase activation assays.

Ribosomally synthesized and post-translationally modified peptides (RiPPs) represent a rapidly expanding superfamily of natural products unified by a conserved biosynthetic logic. The peptide backbone is genetically encoded, and the translated precursor peptide undergoes a series of post-translational modifications (PTMs) catalyzed by maturase enzymes to produce the final bioactive compound [8]. This pathway offers significant advantages for bioengineering due to its modular nature and the frequent substrate promiscuity of its biosynthetic enzymes [9]. RiPPs have garnered substantial interest in drug discovery and development due to their biosynthetic plasticity and ability to generate diverse bioactive structural scaffolds, with approximately 6% of all US FDA-approved drugs being peptides and over 15 peptide-based drugs approved in the last five years alone [9].

The unified biosynthetic logic of RiPPs—modifying ribosomally produced peptides using substrate-tolerant enzymes—positions this class as highly engineerable for creating new molecules and enzyme-based tools [9]. Current successes in RiPP pathway construction, screening, and enzyme development have established a strong foundation for engineering complex peptide therapeutics, addressing limitations in bioavailability and proteolytic stability that have historically restricted their clinical potential [9] [10]. This application note details the core principles and practical methodologies for leveraging RiPP biosynthetic logic in peptide engineering research.

Core RiPP Biosynthetic Logic

The biosynthesis of all RiPPs follows a conserved, sequential pathway comprising three principal stages: ribosomal translation of the precursor peptide, post-translational modification of the core peptide, and proteolytic maturation to release the bioactive final product.

Translation: The Precursor Peptide

Biosynthesis initiates with the ribosomal synthesis of a precursor peptide, which typically contains an N-terminal leader peptide and a C-terminal core peptide [9] [11]. The leader peptide serves as a recognition and binding domain for the maturase enzymes, while the core peptide ultimately becomes the final mature product after processing [9]. This architecture is crucial for guiding modifications, though alternative architectures also exist [8]. The genes encoding these precursors are often found in compact biosynthetic gene clusters (BGCs) alongside the genes for their modifying enzymes [8].

Post-Translational Modification

The core peptide undergoes extensive enzymatic tailoring by maturase enzymes recognized through their interaction with the leader peptide [9]. RiPP maturase enzymes are remarkably diverse and often promiscuous, offering significant biotechnological potential [8]. These modifications can include cyclization, crosslinking, methylation, glycosylation, and the installation of structurally complex heterocycles, dramatically increasing structural diversity and often enhancing stability and bioactivity [9] [11]. A key recognition mechanism involves the RiPP precursor peptide recognition element (RRE), a domain present in many tailoring enzymes that specifically binds the leader peptide [9].

Proteolytic Maturation

The final stage involves proteolytic cleavage to remove the leader sequence, which is sometimes accompanied by additional steps such as N-to-C cyclization, to yield the mature bioactive product [11]. This step is essential for activating the RiPP, as the leader peptide often sterically shields the core peptide's activity during the modification process [9].

Table 1: Core Stages of RiPP Biosynthetic Logic

Biosynthetic Stage	Key Components	Function in Biosynthesis
Translation	Precursor Peptide (Leader + Core)	Provides genetically encoded scaffold for modifications [9] [11]
Post-Translational Modification	Maturase Enzymes (e.g., RRE-containing)	Installs chemical diversity & bioactivity [9]
Proteolytic Maturation	Peptidases	Releases mature, active peptide product [11]

The following diagram illustrates the logical sequence and key components of this core biosynthetic pathway:

Diagram 1: The core RiPP biosynthetic logic, showing the sequential progression from gene cluster to mature bioactive peptide via translation, modification, and proteolytic maturation.

Application Notes: Engineering RiPP Pathways

The modularity of RiPP biosynthesis enables multiple strategic approaches for engineering novel bioactive peptides. The most prominent strategies involve manipulating the leader peptide, diversifying the core peptide, and employing enzyme engineering.

Leader Peptide Manipulation

The leader peptide is not part of the final product but is essential for guiding biosynthesis. Engineering this domain allows for the redirecting of modifications to non-cognate core peptides.

Rationale: Many RiPP tailoring enzymes possess an RRE domain that recognizes and binds specific motifs within the leader peptide [9]. By swapping leader domains or modifying their sequences, the specificity of the biosynthetic machinery can be altered. This enables the modification of non-native core peptides or the creation of chimeric systems where enzymes from one RiPP pathway are used to modify the core peptide from another [9].

Protocol 3.1.1: Leader Peptide Swapping for Heterologous Core Modification

• Principle: Fuse the leader peptide from a known RiPP system to a non-cognate core peptide of interest. The native maturase enzymes will recognize the leader and process the foreign core.
• Materials:
  • Plasmid DNA encoding the maturase enzymes (e.g., lanthipeptide synthetase LanM).
  • Template DNA for the target leader peptide.
  • DNA oligonucleotides encoding your core peptide of interest.
  • Restriction enzymes and ligase or Gibson Assembly master mix.
  • Expression host (e.g., E. coli BL21(DE3)).
  • LB broth and appropriate antibiotics.
• Procedure:
  • Cloning: Amplify the gene fragment encoding the leader peptide. Synthesize and amplify the DNA fragment for your desired core peptide. Use fusion PCR or restriction-ligation/Gibson Assembly to create a synthetic gene encoding the leader-core precursor peptide. Clone this construct into an appropriate expression vector.
  • Co-expression: Co-transform the expression vector containing the precursor peptide with a second vector encoding the necessary maturase enzymes (e.g., LanM, proteases) into your expression host.
  • Expression: Inoculate single colonies into LB medium with antibiotics. Grow at 37°C until OD600 reaches ~0.6. Induce expression with an appropriate inducer (e.g., 0.1-1.0 mM IPTG) and incubate further at optimal conditions (e.g., 18-25°C for 16-20 hours).
  • Analysis: Harvest cells by centrifugation. Analyze peptide production and modification via LC-MS/MS to verify successful modification of the non-cognate core.

Core Peptide Diversification

The core peptide is the most targeted region for engineering, as its sequence determines the final product. Both natural and non-proteinogenic amino acids can be incorporated to create novel analogs.

Rationale: The core peptide is the most targeted region for engineering, as its sequence determines the final product [9]. Maturase enzymes often exhibit substrate tolerance, allowing for the site-specific modification of core peptides that have been mutated or expanded [9]. This strategy is used to generate "libraries" of modified peptides to screen for improved properties like activity, stability, or selectivity.

Protocol 3.2.1: Saturation Mutagenesis of Core Residues

• Principle: Systematically replace specific residues in the core peptide to probe enzyme tolerance and generate diverse analog libraries.
• Materials:
  • Plasmid containing the native precursor peptide gene.
  • Kits for site-directed mutagenesis or gene synthesis.
  • Competent E. coli cells.
  • Media and antibiotics for library propagation.
• Procedure:
  • Library Construction: Design oligonucleotides to introduce degenerate codons (e.g., NNK) at the target position(s) within the core peptide gene. Perform site-directed mutagenesis or synthesize the variant genes and clone them into an expression vector.
  • Transformation: Transform the plasmid library into a competent expression host that contains the requisite biosynthetic genes. Ensure adequate library coverage (>>10^6 clones).
  • Screening/Selection: Plate cells on solid media or grow in liquid culture under selective pressure (e.g., with a target pathogen for antimicrobial RiPPs). Alternatively, use high-throughput screening assays (e.g., LC-MS, activity-based assays).
  • Hit Characterization: Isolate plasmids from active clones, sequence to identify beneficial mutations, and characterize the purified variant peptides.

Enzyme Engineering and Cell-Free Systems

Engineering the maturase enzymes themselves or utilizing high-throughput cell-free systems can overcome bottlenecks in RiPP production and characterization.

Rationale: Some RiPP biosynthetic enzymes have been engineered to function without their leader peptides, simplifying production [9]. Furthermore, Cell-Free Protein Synthesis (CFE) systems offer a rapid, high-throughput platform for expressing and testing RiPP pathways, bypassing the constraints of cellular physiology [12].

Protocol 3.3.1: High-Throughput Screening of RiPP Variants using CFE

• Principle: Express precursor peptide variants and modifying enzymes in a cell-free reaction mix, allowing for direct detection of modified products in a microplate format.
• Materials:
  • Commercial cell-free protein synthesis kit (e.g., PURExpress, NEB).
  • DNA templates (linear PCR products or plasmids) encoding precursor peptide variants.
  • MatURase enzymes (purified or provided via CFE from separate DNA templates).
  • AlphaLISA detection kits or antibodies for specific PTMs [12].
  • 96-well or 384-well microplates.
  • Plate reader capable of AlphaLISA/AlphaScreen detection.
• Procedure:
  • Reaction Setup: In a microplate, mix cell-free extract, reaction buffer, amino acids, and energy sources according to the manufacturer's instructions.
  • Template Addition: Add DNA templates for the precursor peptide and the necessary maturase enzymes. Include negative controls lacking key components.
  • Incubation: Incubate the plate at 30-37°C for 2-6 hours to allow for synthesis and modification.
  • Detection: Add AlphaLISA donor and acceptor beads according to the kit protocol, which are specific to the installed modification (e.g., biotinylation, glycosylation) or to a tag on the leader peptide. Incubate in the dark and read signal on a plate reader.
  • Validation: Identify hits with high modification efficiency and validate by expressing at a larger scale in cells or CFE, followed by LC-MS analysis.

The Scientist's Toolkit: Research Reagent Solutions

Successful engineering of RiPP pathways relies on a suite of specialized reagents and tools. The following table details key resources for designing and executing RiPP engineering campaigns.

Table 2: Essential Research Reagents for RiPP Engineering

Reagent / Tool	Category	Function & Application
LassoESM [13]	Computational Model	A specialized language model for predicting lasso peptide properties, substrate compatibility, and bioactivity, enhancing rational design.
Cell-Free Expression System [12]	Expression Platform	Enables rapid, high-throughput expression and testing of RiPP precursors and enzymes without using living cells.
RODEO [13]	Bioinformatics Tool	A genome mining algorithm that identifies precursor peptides associated with lasso peptide and other RiPP biosynthetic enzymes.
AlphaLISA [12]	Detection Assay	A bead-based proximity assay for high-throughput, no-wash detection of post-translational modifications in peptides.
Chimeric Leader Peptides [9]	Engineering Tool	Synthetic leaders created by fusing parts of different leaders to redirect enzyme specificity and create hybrid RiPP products.
Promiscuous Lasso Cyclases (e.g., FusC, McjC) [13]	Enzymatic Tool	Enzymes with broad substrate tolerance used to cyclize a wide range of non-native core peptide sequences into lasso structures.
ThiF-like Adenylyltransferases (TLATs) [11]	Enzymatic Tool	A superfamily of adenylyltransferases that install diverse modifications in RiPP core peptides, such as in Microcin C biosynthesis.
N-Dodecanoyl-d23-glycine	N-Dodecanoyl-d23-glycine Deuterated Reagent	N-Dodecanoyl-d23-glycine, 98 atom % D min. For Research Use Only. Not for human or veterinary diagnostic or therapeutic use.
D-Glycero-D-guloheptonate-d7	D-Glycero-D-guloheptonate-d7, MF:C7H13NaO8, MW:255.21 g/mol	Chemical Reagent

Case Study: Engineering a Lipolanthine RiPP

The discovery and engineering of lipolanthines—RiPP-derived lipopeptides—exemplify the power of combining multiple RiPP engineering strategies. The following workflow details the process from genome mining to analog generation.

Diagram 2: A generalized workflow for the discovery and engineering of novel RiPP-derived lipopeptides, such as lipolanthines.

Background: Lipolanthines are a class of RiPPs bearing fatty acyl groups, representing hybrid natural products with significant antimicrobial activity [8]. Examples include microvionin and solabiomycin A, which exhibit potent activity against methicillin-resistant Staphylococcus aureus (MRSA) and Mycobacterium tuberculosis, respectively [8].

Engineering Data: The following table quantifies the antimicrobial activity of selected natural and engineered lipolanthines, demonstrating the potential of this RiPP class.

Table 3: Bioactivity of Selected RiPP-Derived Lipopeptides

Compound Name	Producing Strain / Engineering Context	Bioactivity Profile (Minimum Inhibitory Concentration)
Microvionin [8]	Microbacterium arborescens (Natural Product)	MRSA: 0.46 µg/mL; MSSA: 0.1 µg/mL
Albopeptin B [8]	Streptomyces albofaciens (Natural Product)	Antifungal: 12.5 µg/mL; Gram-positive bacteria: 12.5 µg/mL
Solabiomycin A [8]	Streptomyces lydicus (Natural Product)	M. tuberculosis H37Rv: 3.125 µg/mL
Darobactin Analogs [9]	Biosynthetic Pathway Engineering	Improved broad-spectrum activity against Gram-negative pathogens

Outlook: The integration of computational tools like LassoESM for predicting substrate compatibility, combined with high-throughput cell-free screening platforms, is poised to significantly accelerate the design-build-test cycle for RiPP engineering [12] [13]. This will enable researchers to more efficiently navigate the complex sequence-fitness landscape and generate novel RiPP-based therapeutics with tailored properties.

Ribosomally synthesized and post-translationally modified peptides (RiPPs) represent a major superfamily of natural products with immense structural diversity and pharmaceutical potential [4]. These gene-encoded peptides undergo extensive enzymatic tailoring to achieve their final bioactive conformations, making them attractive targets for bioengineering [14]. The biosynthesis follows a common logic: a precursor peptide containing an N-terminal leader peptide and a C-terminal core peptide is recognized by modification enzymes that install various post-translational modifications (PTMs) on the core region, followed by leader peptide cleavage to yield the mature natural product [15]. This biosynthetic logic provides remarkable predictability from genetic information and enables engineering through manipulation of the precursor peptide sequence and modification enzymes.

Table 1: Major RiPP Classes and Their Characteristics

RiPP Class	Characteristic Modifications	Key Enzymes	Bioactivities
Lanthipeptides	Lanthionine (Lan), methyllanthionine (MeLan) rings formed via Ser/Thr dehydration and Michael addition	LanB/LanC or LanM synthetases, LanT proteases	Antimicrobial (nisin), antiviral, anticancer [16] [14]
Cyanobactins	Heterocyclization (thiazoline/oxazoline), prenylation, oxidation	Heterocyclase (PatD), proteases (PatA/PatG), oxidase, prenyltransferase	Cytotoxic (patellamide A), protease inhibitory [15]
Lasso Peptides	N-terminal macrolactam ring formation followed by C-terminal tail threading	B enzyme (protease), C enzyme (cyclase)	Antimicrobial (microcin J25), receptor antagonism [17]
Linear Azol(in)e-containing Peptides (LAPs)	Azole/azoline ring formation from Cys, Ser, Thr residues	YcaO heterocyclase, dehydrogenase	Cytotoxic, antibacterial (streptolysin S) [18]

Lanthipeptides: Biosynthesis and Engineering Protocols

Biosynthetic Pathway

Lanthipeptides are characterized by thioether cross-links called lanthionine (Lan) and methyllanthionine (MeLan) that form rigid cyclic structures [16]. These modifications proceed via a two-step process: first, Ser/Thr residues in the core peptide are dehydrated to dehydroalanine (Dha) and dehydrobutyrine (Dhb), respectively; second, cysteine thiol groups undergo Michael-type addition to the dehydroamino acids to form the characteristic (methyl)lanthionine bridges [14]. The biosynthetic machinery varies between different classes of lanthipeptides, with Class I systems employing separate dehydratases (LanB) and cyclases (LanC), while Class II systems utilize a single bifunctional enzyme (LanM) that catalyzes both dehydration and cyclization [16].

Figure 1: Lanthipeptide Biosynthetic Pathway

Cell-Free Biosynthesis Protocol for Salivaricin B

The UniBioCat system provides a cell-free platform for rapid biosynthesis and engineering of lanthipeptides [16].

Materials:

• E. coli BL21 Star (DE3) cell extract enriched with chaperones (DnaK-DnaJ-GrpE and GroEL-GroES)
• Plasmid DNA encoding SboA (precursor peptide), SboM (modification enzyme), SboT (transporter/protease)
• CFE reaction mixture: 12 mM magnesium glutamate, 10 mM ammonium glutamate, 130 mM potassium glutamate, 1.2 mM ATP, 0.8 mM GTP, 0.8 mM UTP, 0.8 mM CTP, 34 μg/mL folinic acid, 175 mM KOAc, 0.75 mM cAMP, 30 mM PEP, 0.33 mM NAD+, 0.27 mM CoA, 2.7 mM oxalate, 2% PEG-8000
• MALDI-TOF MS and LC-MS/MS systems for analysis

Procedure:

• Prepare chaperone-enriched E. coli cell extract according to standardized protocols [16]
• Set up 15 μL CFE reactions containing cell extract and CFE reaction mixture
• Add plasmid DNA encoding the complete salivaricin B gene cluster (sboA, sboM, sboT)
• Incubate reactions at 30°C for 4-6 hours with shaking
• Extract products with 50% acetonitrile/0.1% trifluoroacetic acid
• Analyze by MALDI-TOF MS and LC-MS/MS to detect mature salivaricin B (observed m/z 2997.4) and salivaricin B-1 (observed m/z 3068.5) [16]
• Confirm thioether ring formation using N-ethylmaleimide (NEM) cysteine alkylation assay [16]
• Evaluate antimicrobial activity against Staphylococcus aureus RN4220 via agar diffusion assay

Cyanobactins: Multicore Systems and Engineering

Biosynthetic Pathway and Multicore Precursors

Cyanobactins represent a fascinating RiPP class characterized by heterocyclization and frequent multicore precursor peptides [15]. These natural products are produced by cyanobacteria and exhibit diverse bioactivities including cytotoxicity, protease inhibition, and metal chelation [15]. The biosynthetic pathway involves a series of enzymatic modifications that can generate remarkable chemical diversity from a single precursor peptide.

Figure 2: Cyanobactin Biosynthetic Pathway

In Vitro Reconstitution of Cyanobactin Pathways

Materials:

• Synthetic genes encoding precursor peptide (PatE) with multiple core motifs
• Heterocyclase (PatD), N-terminal protease (PatA), C-terminal protease/cyclase (PatG)
• Oxidase (ThcOx) and prenyltransferase (PatF) as needed
• ATP, GTP, and SAM as cofactors
• Analytical HPLC with MS detection

Procedure:

• Express and purify individual cyanobactin biosynthetic enzymes from E. coli
• Synthesize precursor peptides containing recognition sequences (RSI: LAELSEE, RSII: Gx(E/D)xS, RSIII: (A/S)YD) flanking core motifs [15]
• Set up heterocyclization reactions containing PatD, precursor peptide, ATP in appropriate buffer
• Monitor thiazoline/oxazoline formation by mass spectrometry (expected mass decrease of -18 Da per cyclization)
• Add PatA to perform N-terminal cleavage C-terminal to RSII motif
• Add PatG to perform C-terminal cleavage and macrocyclization
• For oxidized analogs, include ThcOx with FMN cofactor to convert azolines to azoles
• For prenylated analogs, include prenyltransferase (LynF for tyrosine, TruF for Ser/Thr) with dimethylallyl pyrophosphate [15]
• Purify final products by reverse-phase HPLC and characterize by NMR and MS

Table 2: Cyanobactin Modification Enzymes and Functions

Enzyme	Function	Recognition Site	Key Cofactors
Heterocyclase (PatD)	Cyclizes Cys, Ser, Thr to thiazolines/oxazolines	RSI (LAELSEE)	ATP
N-terminal Protease (PatA)	Cleaves leader peptide	RSII (Gx(E/D)xS)	None
C-terminal Protease/cyclase (PatG)	Cleaves follower and catalyzes macrocyclization	RSIII ((A/S)YD)	None
Oxidase (ThcOx)	Oxidizes azolines to azoles	None specific	FMN
Prenyltransferase (LynF/TruF)	Adds prenyl groups to Tyr or Ser/Thr	None specific	Dimethylallyl PP

Lasso Peptides: Unique Topology and Biosynthesis

Biosynthetic Mechanism

Lasso peptides feature a unique threaded rotaxane structure where an N-terminal macrolactam ring is formed between the N-terminal amine and a side chain carboxylate of Asp or Glu, through which the C-terminal tail is threaded [17]. This topology confers exceptional stability against thermal and proteolytic degradation [17]. The biosynthesis requires two key enzymatic activities: proteolytic cleavage by B enzymes to remove the leader peptide, and macrolactam ring formation by C enzymes [19].

In Vitro Characterization of Lasso Peptide Biosynthesis

Materials:

• Purified B1 (PadeB1, LarB1) and B2 proteins with C-terminal His-tags
• Precursor peptide (PadeA, LarA) fused to maltose-binding protein (MBP)
• Ni-NTA and amylose resins for purification
• Biolayer interferometry (BLI) system
• ATP, reaction buffer (50 mM HEPES, pH 7.5, 100 mM NaCl, 10 mM MgClâ‚‚)

Procedure: Leader peptide binding assay:

• Express and purify B1 proteins (PadeB1, LarB1) under native conditions [17] [19]
• Purify leader peptide-MBP fusions using amylose resin [19]
• Immobilize His-tagged B1 proteins on anti-His biosensors
• Perform BLI with leader peptide-MBP as analyte (50 nM to 2 μM concentration range)
• Determine binding affinity (Kd) using fitting algorithms (expected Kd ~5-440 nM) [17] [19]
• Confirm specificity using leader peptide truncations and core peptide alone as negative controls

In vitro lasso peptide formation:

• Co-express B1, B2, and C enzymes with precursor peptide in E. coli
• Alternatively, set up in vitro reactions with purified components
• Include ATP (5 mM) for C enzyme catalysis
• Incubate at 30°C for 2-4 hours
• Analyze products by LC-MS for mass confirmation of mature lasso peptide
• Verify topology by protease resistance assay (trypsin, chymotrypsin) and thermal stability testing

Linear Azol(in)e-containing Peptides (LAPs)

Dehydrozole Biosynthesis Pathway

Linear azol(in)e-containing peptides (LAPs) incorporate thiazole/oxazole rings formed through heterocyclization of Cys, Ser, and Thr residues [18]. A recently discovered class termed "dehydrazoles" exemplifies hypermodified RiPPs containing both azole rings and dehydroamino acids [18]. The carnazolamide pathway demonstrates exceptional efficiency, with just five enzymes installing 18 distinct post-translational modifications on a 30-residue peptide [18].

Figure 3: LAP/Dehydrozole Biosynthetic Pathway

Heterologous Expression and Characterization of Dehydrozoles

Materials:

• E. coli BL21(DE3) expression strain
• Plasmids for co-expression of CcaA (precursor), CcaB (YcaO), CcaC (dehydrogenase), CcaM (LanMbC), CcaD (epimerase), CcaH (methyltransferase)
• Ni-NTA resin for His-tagged protein purification
• Denaturing purification buffers (6 M guanidinium HCl)
• Tobacco etch virus (TEV) protease
• MALDI-TOF MS and HPLC systems

Procedure:

• Co-transform E. coli BL21(DE3) with plasmids encoding CcaA (N-terminally His-tagged) and modification enzymes [18]
• Induce expression with 0.5 mM IPTG at 16°C for 16-20 hours
• Harvest cells and purify under denaturing conditions using Ni-NTA chromatography
• Cleave His-tag using TEV protease
• Purify mature peptide by reverse-phase HPLC
• Analyze by MALDI-TOF MS for mass determination (expected extensive modifications)
• Confirm azole formation by UV spectroscopy (characteristic absorption at 254 nm)
• Verify dehydroamino acid content by NEM alkylation and tandem MS
• Test protease resistance compared to unmodified linear peptide

The Scientist's Toolkit: Essential Research Reagents

Table 3: Key Research Reagents for RiPP Biosynthesis Studies

Reagent/Category	Specific Examples	Function/Application
Expression Systems	E. coli BL21(DE3) cell extracts, PURE system	Cell-free protein synthesis and modification [16]
Chaperone Systems	DnaK-DnaJ-GrpE, GroEL-GroES	Enhance soluble expression of modification enzymes [16]
Affinity Tags	Polyhistidine (His-tag), Maltose-binding protein (MBP)	Protein purification and binding studies [17] [19]
Proteases	TEV protease, Factor Xa	Cleavage of affinity tags and leader peptides [17]
Mass Spectrometry	MALDI-TOF MS, LC-MS/MS	Modification verification and structural characterization [16] [18]
Binding Assay Systems	Biolayer interferometry (BLI), Isothermal titration calorimetry (ITC)	Protein-peptide interaction studies [17] [19]
Specialized Enzymes	YcaO heterocyclases, LanM synthetases, RRE domains	Installation of specific post-translational modifications [20] [18]
Activity Assays	Agar diffusion assays, microbroth dilution	Antimicrobial activity evaluation [16]
(3S)-3-Hydroxy Quinidine-vinyl-d3	(3S)-3-Hydroxy Quinidine-vinyl-d3, MF:C20H24N2O3, MW:343.4 g/mol	Chemical Reagent
Anti-inflammatory agent 9	Anti-inflammatory agent 9, MF:C18H15N5O2S, MW:365.4 g/mol	Chemical Reagent

Engineering Strategies and Combinatorial Biosynthesis

The modular nature of RiPP biosynthesis enables sophisticated engineering approaches for generating novel analogs with improved or altered bioactivities [14]. Key strategies include:

Precursor peptide engineering:

• Core peptide mutagenesis to alter residue specificity for modifications
• Leader peptide engineering to alter enzyme recognition
• Hybrid leader design to enable modification by non-cognate enzymes [14]

Enzyme engineering:

• Exploiting natural enzyme promiscuity (e.g., ProcM, TruD) for diverse substrates [21]
• Directed evolution to alter substrate specificity
• Domain swapping to create hybrid modification enzymes

Combinatorial biosynthesis:

• Mixing modification enzymes from different RiPP pathways
• Cell-free systems for rapid prototyping of engineered pathways [16]
• Implementation of high-throughput screening methods for bioactive variants

These engineering approaches facilitate the generation of RiPP analogs that mimic complex non-ribosomal peptides (NRPs) such as daptomycin and teixobactin, combining the biosynthetic flexibility of RiPPs with the potent bioactivities of NRPs [14].

Ribosomally synthesized and post-translationally modified peptides (RiPPs) represent a rapidly expanding superfamily of natural products with remarkable structural diversity and significant pharmaceutical potential [22] [1]. These compounds are unified by a common biosynthetic logic: a genetically encoded precursor peptide is first synthesized by the ribosome and then extensively modified by dedicated maturase enzymes to produce the final bioactive compound [23]. The RiPP biosynthetic pathway, often referred to as Post-Ribosomal Peptide Synthesis (PRPS), begins with a precursor peptide typically comprising an N-terminal leader peptide and a C-terminal core peptide, though alternative architectures like C-terminal follower peptides also exist [22] [24]. The core peptide undergoes a series of enzymatic transformations that dramatically alter its chemical structure, imparting conformational restraint, metabolic stability, and biological activity [22] [25]. The resulting natural products exhibit an impressive range of bioactivities, including antibiotic, antifungal, antiviral, antitumor, and antiparasitic properties, making them attractive targets for drug development [26] [8].

The evolutionary advantage of RiPP biosynthesis lies in its genetic economy and high evolvability. The biosynthetic gene clusters (BGCs) are relatively compact, and the maturase enzymes often display significant substrate promiscuity, recognizing the conserved leader peptide while tolerating extensive variation in the core peptide sequence [22]. This modularity enables rapid generation of chemical diversity from simple genetic changes, a feature that peptide engineers are increasingly exploiting to create novel compounds with tailored properties [27]. As the falling cost of genome sequencing continues to reveal countless uncharacterized RiPP BGCs, understanding the key post-translational modifications—particularly cyclization, methylation, dehydration, and heterocycle formation—becomes crucial for unlocking their biotechnological and therapeutic potential [23] [25] [1].

Core Principles and Nomenclature

Universal RiPP Biosynthetic Logic

The biosynthesis of all RiPPs follows a conserved pattern initiated by the ribosomal production of a precursor peptide. This precursor is organized into distinct regions: most commonly an N-terminal leader peptide and a C-terminal core peptide [22]. The leader peptide serves as a recognition sequence for the maturase enzymes and typically remains unchanged during modification of the core peptide [22]. In some rare cases, such as the bottromycins, a C-terminal "follower" peptide performs this recognition function instead [22] [24]. For eukaryotic RiPPs like cyclotides and conopeptides, an additional signal sequence may direct cellular localization [22]. The extensive post-translational modifications installed by the maturase enzymes include cyclizations, crosslinks, heterocycle formations, and various side-chain modifications that collectively transform the linear peptide into a structurally complex natural product [22] [28]. The final maturation step involves proteolytic removal of the leader peptide (and/or follower peptide) to release the bioactive mature RiPP [22].

A key feature of RiPP biosynthesis is the division of labor between recognition and modification. The leader peptide ensures that the correct core peptide is modified by the appropriate enzymes, while the core peptide itself can tolerate significant sequence variation, enabling rapid evolution of chemical diversity [22]. This biosynthetic logic facilitates genome mining approaches, as the presence of a precursor peptide gene near maturase enzymes often signals a RiPP pathway [1]. The resulting natural products typically fall within the molecular weight range of 1,000-5,000 Da, occupying a valuable chemical space between small molecules and large biologics, with enhanced binding specificity and ability to inhibit protein-protein interactions [26].

Standardized Nomenclature Framework

The field of RiPP research has established uniform nomenclature to address previously confusing and contradictory terminology [22]. The biosynthetic pathway is designated Post-Ribosomal Peptide Synthesis (PRPS), drawing a parallel to Non-Ribosomal Peptide Synthesis (NRPS) [22]. The final products are termed RiPPs, specifically excluding larger post-translationally modified proteins through an approximate 10 kDa molecular weight limit [22].

Table 1: Standardized Nomenclature for RiPP Biosynthesis

Term	Definition	Previous Designations
Precursor peptide	Initial ribosomal translation product containing leader and core regions	Prepeptide, prepropeptide, structural peptide
Leader peptide	N-terminal recognition sequence for maturase enzymes	Propeptide, pro-region, intervening region
Core peptide	Region transformed into the final natural product	Propeptide, structural peptide, toxin region
UCP	Unmodified core peptide in the precursor peptide	N/A
MCP	Modified core peptide after post-translational modifications	N/A
Follower peptide	C-terminal recognition sequence (rare)	N/A

Residue numbering follows a specific convention where the last residue of the leader peptide (not incorporated in the final RiPP) is numbered -1, with counting proceeding -2, -3, etc., toward the N-terminus [22]. Similarly, C-terminal recognition sequences are numbered with a plus sign from the cleavage site (+1, +2, etc.) [22]. This standardized terminology facilitates clear communication and computational annotation of RiPP biosynthetic gene clusters across the diverse subclasses [22].

Cyclization Modifications

Macrocyclization Mechanisms and Biological Significance

Macrocyclization represents one of the most common and impactful modifications in RiPP biosynthesis, serving to constrain peptide conformation, enhance metabolic stability, improve target affinity, and increase specificity [28]. This transformation is so valuable that medicinal chemists frequently employ similar strategies in peptide drug development [28]. The mechanisms of macrocyclization in RiPPs are remarkably diverse, involving different chemical reactions and resulting in various cyclic architectures that define several RiPP subclasses [28] [24].

The biological advantages of cyclization are profound. Constraining the peptide backbone into a specific conformation reduces the entropic penalty upon binding to biological targets, significantly enhancing binding affinity [28]. Additionally, the cyclic structure confers resistance to exoprotease degradation, extending the peptide's half-life in biological environments [24]. These properties make macrocyclic RiPPs particularly attractive as therapeutic leads, as they combine the specificity of peptides with improved pharmacokinetic properties [28]. The ribosomal origin of these compounds further facilitates engineering approaches, as sequence modifications can be introduced at the genetic level rather than requiring complex synthetic chemistry [24].

Key Cyclization Strategies in RiPP Pathways

Table 2: Major Cyclization Mechanisms in RiPP Biosynthesis

Cyclization Type	Chemical Basis	Representative RiPP Classes	Key Features
Lanthionine/MeLan formation	Michael-type addition of Cys thiols to dehydroamino acids	Lanthipeptides [28]	Thioether crosslinks; multiple classes based on synthetase enzymes
Head-to-tail cyclization	Amide bond between N- and C-termini	Cyanobactins, cyclotides, orbitides [22] [24]	N-to-C macrocyclization; diverse ring sizes
Azole/azoline formation	ATP-dependent heterocyclization	TOMMs, LAPs, thiopeptides, cyanobactins [24]	Oxazoles/thiazoles from Ser/Thr/Cys; requires dehydrogenase for aromatization
Radical-mediated cyclization	Carbon-carbon bond formation via radical SAM enzymes	Sactipeptides, ranthipeptides, streptide [28]	Unactivated carbon centers; unusual crosslinks
[4+2] Cycloaddition	Diels-Alder reaction	Thiopeptides [28]	Complex pyridine formation; pericyclic reaction
Lasso peptide formation	Isopeptide bond between N-terminus and Asp/Glu side chain	Lasso peptides [1]	Mechanically interlocked topology; protease resistance

Figure 1: Cyclization Mechanisms and Applications in RiPP Biosynthesis

Experimental Protocol: In Vitro Reconstitution of Cyanobactin Macrocyclization

Purpose: To reconstitute the macrocyclization activity of cyanobactin enzymes in vitro for the production of cyclic peptide libraries [27].

Materials:

• TruD1 heterocyclase (YcaO-domain protein)
• TruG1 protease/macrocyclase
• Synthetic precursor peptide (core + leader sequence)
• ATP regeneration system (creatine kinase, creatine phosphate)
• Reaction buffer: 50 mM HEPES, pH 7.5, 100 mM NaCl, 10 mM MgClâ‚‚
• HPLC system with C18 column
• MALDI-TOF mass spectrometer

Method:

• Precursor peptide preparation: Synthesize the precursor peptide containing the core peptide sequence flanked by the native leader and follower sequences recognized by TruG1. Dissolve in reaction buffer to 1 mM concentration.

• Enzyme preparation: Express and purify TruD1 and TruG1 as recombinant His-tagged proteins from E. coli using standard nickel affinity chromatography.

• Heterocyclization reaction: Combine 50 μL precursor peptide (1 mM), 10 μL TruD1 (0.1 mM), 10 μL ATP (100 mM), and 25 μL ATP regeneration system in reaction buffer to a total volume of 500 μL. Incubate at 30°C for 2 hours with gentle agitation.

• Macrocyclization and cleavage: Add 10 μL TruG1 (0.05 mM) to the heterocyclized peptide mixture. Incubate at 30°C for an additional 3 hours.

• Product analysis: Quench the reaction with 50 μL 10% trifluoroacetic acid (TFA). Separate by reverse-phase HPLC using a water-acetonitrile gradient (5-95% acetonitrile + 0.1% TFA over 30 minutes). Collect eluted peaks and analyze by MALDI-TOF MS.

• Cyclic peptide verification: Compare HPLC retention times and mass spectra to linear controls. Confirm cyclization through MS/MS fragmentation and resistance to exoprotease treatment (aminopeptidase M and carboxypeptidase Y).

Notes: The order of enzyme addition is critical—heterocyclization must precede macrocyclization for efficient processing. This protocol can be adapted for one-pot reactions with multiple modification enzymes by optimizing enzyme ratios and reaction timing [27].

Methylation Modifications

Methyltransferase Diversity and Selectivity

Methylation represents a prevalent post-translational modification in RiPP biosynthesis, dramatically altering peptide properties through the addition of methyl groups to various acceptor sites [26]. These transformations are catalyzed by S-adenosylmethionine (SAM)-dependent methyltransferases (MTs) that exhibit remarkable chemo-, regio-, and stereoselectivity [26]. The introduction of methyl groups can significantly enhance a compound's biological activity—a phenomenon known as the "magic methyl effect"—where a single methyl group improves drug efficacy by orders of magnitude [26]. Methylation modulates peptide properties by increasing hydrophobicity, altering hydrogen bonding capacity, providing steric bulk, and stabilizing specific conformations, all of which can profoundly influence bioactivity and metabolic stability [26].

RiPP methyltransferases target diverse positions within peptide substrates, including nitrogen atoms (N-terminus, lysine side chains, histidine imidazole, backbone amides), oxygen atoms (glutamate/aspartate side chains, serine/threonine side chains, C-terminus), carbon atoms (unactivated sp³ carbons), and sulfur atoms (cysteine side chains, methionine) [26]. This chemical versatility enables extensive diversification of RiPP scaffolds from common precursor peptides. The MTs achieve their impressive selectivity through precise recognition of both the leader peptide sequence and specific features of the core peptide, allowing them to modify particular residues while ignoring chemically similar alternatives [26]. This specificity, combined with their catalytic efficiency, makes RiPP methyltransferases valuable tools for biocatalytic applications.

Experimental Protocol: Biocatalytic Methylation Using RiPP Methyltransferases

Purpose: To employ RiPP methyltransferases for selective in vitro methylation of peptide substrates [26].

Materials:

• SAM-dependent methyltransferase (e.g., CcaH, TsrM)
• Synthetic peptide substrate (core peptide with appropriate leader sequence if required)
• S-adenosylmethionine (SAM)
• SAM regeneration system (methionine adenosyltransferase, methionine, ATP)
• Methyltransferase assay buffer: 50 mM Tris-HCl, pH 8.0, 5 mM MgClâ‚‚
• LC-MS system with C8 or C18 column
• Desalting columns (Zeba Spin, 7K MWCO)

Method:

• Enzyme preparation: Express and purify the methyltransferase as a recombinant His-tagged protein from E. coli. Confirm activity with a known substrate before proceeding.

• SAM regeneration system preparation: Combine methionine adenosyltransferase (0.01 mM), L-methionine (10 mM), and ATP (5 mM) in methyltransferase assay buffer. Pre-incubate at 30°C for 15 minutes to generate SAM in situ.

• Methylation reaction: Combine 50 μL peptide substrate (0.5 mM), 25 μL SAM regeneration system, 10 μL methyltransferase (0.05 mM), and assay buffer to a total volume of 250 μL. Incubate at 30°C for 4-16 hours with gentle mixing.

• Reaction monitoring: Remove 10 μL aliquots at 0, 2, 4, and 8 hours. Quench with 10 μL 10% TFA and analyze by LC-MS. Monitor for mass increase of +14 Da per methylation event.

• Product purification: Pool completed reactions and desalt using spin columns according to manufacturer's instructions. Further purify by semi-preparative HPLC if necessary.

• Methylation site mapping: For unknown substrates, perform MS/MS fragmentation to identify specific methylation sites. Compare fragmentation patterns to unmethylated controls.

Troubleshooting:

• If methylation efficiency is low, increase SAM regeneration system components or add fresh SAM (0.5-1 mM) directly to the reaction.
• For insoluble peptide substrates, include up to 10% DMSO or acetonitrile to improve solubility.
• If non-specific methylation occurs, shorten reaction time or decrease enzyme concentration.
• For leader-independent MTs, test truncated substrates containing only core peptide sequences.

Applications: This protocol enables selective introduction of methyl groups at specific positions in complex peptides, offering advantages over chemical methods that often require protecting groups and produce toxic waste [26].

Dehydration and Heterocycle Formation

Dehydration Mechanisms and Azole Biosynthesis

Dehydration of serine and threonine residues to form dehydroalanine (Dha) and dehydrobutyrine (Dhb) represents a fundamental transformation in multiple RiPP classes [25]. This process typically begins with phosphorylation or glutamylation of the side chain hydroxyl group, followed by elimination to generate the dehydrated residue [22] [25]. These dehydroamino acids serve as crucial intermediates for subsequent modifications, particularly in lanthipeptides where they undergo Michael-type additions with cysteine thiols to form lanthionine and methyllanthionine crosslinks [28] [24]. Recent research has revealed unusual dehydration enzymes like CcaM that function independently of leader peptides and specifically target serine residues preceding azole moieties, demonstrating the sophisticated regulatory mechanisms controlling modification timing in complex RiPP pathways [25].

Heterocycle formation through cyclodehydration of cysteine, serine, and threonine residues produces thiazolines and (methyl)oxazolines, which can be further oxidized to the aromatic thiazoles and (methyl)oxazoles [25] [24]. This transformation is catalyzed by YcaO-domain proteins that utilize ATP to activate the backbone amide carbonyl for nucleophilic attack by the side chain heteroatom [24]. The resulting azol(in)es constrict peptide conformation and enhance stability against proteolytic degradation [24]. In remarkable examples of biosynthetic efficiency, some RiPP pathways install both dehydroamino acids and azol(in)es on the same precursor peptide, as demonstrated in the dehydrazoles like carnazolamide, where 18 post-translational modifications are installed by just five enzymes [25].

Experimental Protocol: Reconstitution of Dehydration and Heterocyclization in Dehydrazoles

Purpose: To reconstitute the coordinated activities of YcaO heterocyclase and LanMbC dehydratase in the biosynthesis of dehydrazole-class RiPPs [25].

Materials:

• Precursor peptide (CcaA with NHLP leader)
• YcaO heterocyclase (CcaB)
• Associated flavin dehydrogenase (CcaC)
• LanMbC dehydratase (CcaM)
• ATP, NAD⁺
• Reaction buffer: 50 mM HEPES, pH 7.5, 150 mM KCl, 10 mM MgClâ‚‚
• Anaerobic chamber for oxygen-sensitive steps
• HPLC-MS system with polar embedded C18 column

Method:

• Enzyme preparation: Express and purify CcaB, CcaC, and CcaM as recombinant proteins. Note that CcaM contains a radical SAM domain—purify under anaerobic conditions when necessary.

• Heterocyclization reaction: Combine 50 μL precursor peptide (0.2 mM), 10 μL CcaB (0.05 mM), 10 μL ATP (10 mM), and reaction buffer to 200 μL total volume. Incubate at 30°C for 2 hours.

• Oxidation step: Add 5 μL CcaC (0.1 mM) and 5 μL NAD⁺ (5 mM) to the heterocyclized peptide. Incubate at 30°C for 1 hour to convert azolines to azoles.

• Dehydration reaction: Add 10 μL CcaM (0.05 mM) and additional 10 μL ATP (10 mM) to the oxidized peptide. Incubate at 30°C for 3 hours.

• Process monitoring: Analyze 10 μL aliquots after each step by LC-MS. Heterocyclization is indicated by mass decrease of -18 Da per cyclization, oxidation shows no mass change, and dehydration shows additional -18 Da per dehydration event.

• Order dependence testing: To confirm the core-dependence of CcaM, set up parallel reactions where dehydration is attempted before heterocyclization. Compare efficiency by product yield.

• Product characterization: Purify the fully modified peptide by HPLC. Verify modification sites using MS/MS fragmentation and compare to unmodified controls.

Key Insights: This protocol demonstrates the importance of modification order in complex RiPP pathways. The core-dependence of CcaM ensures that heterocyclization precedes dehydration, preventing competition for unmodified serine residues [25]. This biosynthetic logic enables the efficient installation of multiple modification types without cross-interference.

Research Reagent Solutions for RiPP Studies

Table 3: Essential Research Reagents for RiPP Pathway Reconstitution

Reagent Category	Specific Examples	Function in RiPP Research	Key Considerations
Precursor Peptides	Synthetic CcaA, McbA, NisA	Substrate for PTM enzymes; engineering template	Include leader sequence for enzyme recognition; core sequence can be varied
Core Modification Enzymes	YcaO proteins, LanM synthetases, Radical SAM enzymes	Install primary post-translational modifications	Often require cofactors (ATP, SAM, NAD⁺); may need anaerobic handling
Processing Enzymes	Leader peptidases, Macrocyclases	Release mature RiPP from precursor	Specific to leader peptide sequence; timing affects final product
Cofactor Systems	ATP regeneration, SAM regeneration	Sustain enzymatic activity in vitro	Crucial for multi-enzyme reconstitution; reduces product inhibition
Analytical Tools	LC-MS with C18 columns, MALDI-TOF MS	Monitor reaction progress; verify structures	High resolution needed for mass accuracy; MS/MS for modification mapping

Advanced Engineering Applications

Integrated Workflow for RiPP Pathway Engineering

The modular nature of RiPP biosynthetic enzymes enables sophisticated engineering approaches for generating novel peptide architectures [27]. Successful engineering requires careful consideration of enzyme compatibility, reaction order, and substrate recognition requirements. The workflow typically begins with bioinformatic identification of candidate BGCs, followed by heterologous expression and in vitro characterization of individual enzymes to define their substrate scope and specificity [25] [8]. Once the fundamental properties are established, pathway reassembly can be pursued through either genetic engineering of producer strains or in vitro reconstitution with purified components [27].

Figure 2: Integrated Workflow for RiPP Pathway Discovery and Engineering

Quantitative Analysis of Modification Enzymes

Table 4: Kinetic Parameters of Key RiPP Modification Enzymes

Enzyme Class	Representative Enzyme	Reaction Catalyzed	Key Cofactors	Reported Turnover	Engineering Applications
YcaO heterocyclase	CcaB [25]	Azoline formation from Cys/Ser/Thr	ATP	Multiple turnovers per peptide	Broad substrate tolerance; core diversification
LanM dehydratase	CcaM [25]	Ser/Thr dehydration to Dha/Dhb	ATP (Glu-tRNA for some)	8+ dehydrations per peptide [25]	Leader-independent activity; unusual specificity
Radical SAM MT	CcaH [25]	C-methylation of unactivated carbons	SAM, redox center	Single methylation per SAM	Unique chemoselectivity; difficult chemical mimicry
Lanthipeptide cyclase	ProcM [28]	Thioether ring formation	Zn²⁺ (some classes)	Multiple cyclizations per peptide	Remarkable promiscuity; library generation
Macrocyclase	TruG1 [27]	Head-to-tail cyclization + cleavage	None	Single cyclization per peptide	Biocompatible macrocyclization tool

Protocol for One-Pot Multienzyme RiPP Synthesis

Purpose: To simultaneously employ multiple RiPP modification enzymes in a single reaction vessel for efficient synthesis of complex peptide natural products [27].

Materials:

• Purified precursor peptide
• Complete set of modification enzymes (heterocyclase, dehydrogenase, dehydratase, methyltransferase, etc.)
• Cofactor cocktail: ATP, SAM, NAD⁺, and respective regeneration systems
• Multienzyme reaction buffer: 50 mM HEPES, pH 7.5, 100 mM NaCl, 10 mM MgClâ‚‚
• Temperature-controlled shaker
• Analytical and preparative HPLC systems

Method:

• Cofactor optimization: Prepare a master mix containing ATP (5 mM), SAM (1 mM), NAD⁺ (2 mM) with their respective regeneration systems: creatine phosphate (20 mM)/creatine kinase (0.1 mg/mL) for ATP; methionine (5 mM)/methionine adenosyltransferase (0.01 mM) for SAM.

• Enzyme titration: Determine the minimal effective concentration for each enzyme through individual reactions. Aim for enzyme:substrate ratios between 1:10 and 1:100.

• One-pot reaction assembly: Combine precursor peptide (0.1 mM final concentration) with cofactor master mix in reaction buffer. Add all modification enzymes simultaneously at their predetermined optimal concentrations. Adjust final volume with reaction buffer.

• Reaction incubation: Incubate at 30°C with gentle agitation for 6-16 hours. Monitor progress by LC-MS at 2-hour intervals.

• Product isolation: Once conversion plateaus, quench reaction with 0.1% TFA. Purify product by preparative HPLC. Lyophilize pure fractions for characterization.

• Yield optimization: If yield is suboptimal, vary enzyme addition order or implement staggered addition based on known biosynthetic logic. For example, in dehydrazole synthesis, add heterocyclation enzymes before dehydration enzymes [25].

Applications: This approach has been successfully demonstrated for cyanobactin synthesis, where up to five different post-translational enzymes were combined in a single tube to generate highly unnatural peptide derivatives, including an N-C peptide macrocycle of 22 amino acids in length [27]. The method capitalizes on the modularity and substrate tolerance of RiPP enzymes to create diverse peptide libraries.

The systematic investigation of key post-translational modifications in RiPP biosynthesis—cyclization, methylation, dehydration, and heterocycle formation—has revealed fundamental principles of enzymatic catalysis and provided powerful tools for peptide engineering. The modular nature of RiPP pathways, combined with the remarkable substrate tolerance of many maturase enzymes, enables sophisticated engineering approaches that were previously unimaginable [27]. As genome mining continues to reveal novel RiPP classes with unusual modifications [23] [25] [8], and as our understanding of enzyme mechanisms deepens [28] [26] [24], the toolkit for peptide engineering will expand accordingly.

The future of RiPP engineering lies in the intelligent combination of modifications to create peptides with tailored properties. The emerging paradigm of "biosynthetic code" deciphering—understanding how enzyme specificity is encoded in leader peptides and substrate contexts—will enable more predictive engineering [22] [25]. Additionally, the discovery of hybrid systems like RiPP-derived lipopeptides [23] [8] points toward integration with other biosynthetic paradigms (PKS, NRPS) for further structural diversification. As biochemical reconstitution protocols become more sophisticated and high-throughput [25] [27], the pace of discovery and engineering will accelerate, potentially yielding new therapeutic classes to address pressing medical challenges. The protocols and analyses presented here provide a foundation for these future advances in RiPP-based peptide engineering.

Ribosomally synthesized and post-translationally modified peptides (RiPPs) represent a rapidly growing class of natural products characterized by their genetically encoded precursor peptides and extensive enzymatic tailoring. These compounds are produced across all domains of life—prokaryotes (bacteria and archaea) and eukaryotes—exhibiting remarkable structural diversity and potent biological activities that have attracted significant interest for therapeutic development. RiPP biosynthesis follows a conserved logic: a ribosomally produced precursor peptide containing an N-terminal leader peptide and a C-terminal core peptide is modified by various enzymes, after which the leader peptide is proteolytically removed to yield the mature natural product [22]. The core peptide undergoes diverse post-translational modifications (PTMs), including cyclization, methylation, and the introduction of thioether crosslinks, which greatly expand their structural complexity and functional versatility [22] [29].

The ecological functions of RiPPs are increasingly recognized as crucial in mediating microbial interactions, including prokaryote-phage relationships and host-microbiome homeostasis [30] [31]. For peptide engineering research, the genetic encodability of RiPP precursors combined with the relaxed substrate specificity of many RiPP biosynthetic enzymes makes this class of natural products particularly amenable to bioengineering approaches [9] [29]. This application note provides a comprehensive overview of RiPP distribution across life domains, summarizes quantitative biosynthetic data, details experimental protocols for RiPP discovery, and visualizes key biosynthetic pathways to support research in this rapidly advancing field.

Distribution of RiPPs Across Life Domains

Prokaryotic RiPPs

Bacterial RiPPs represent the most extensively characterized group, with biosynthetic gene clusters (BGCs) widespread across numerous phyla. Large-scale genomic analyses reveal that bacterial RiPPs are particularly abundant in human-associated microbiomes. A recent study of 306,481 microbial genomes from human body sites identified RiPPs in up to 95.3% of genomes using precursor-centric detection methods, with the highest enrichment observed in the gut and oral microbiomes [31]. The phyla Bacteroidota and Firmicutes, dominant in the human gut, harbored the most abundant RiPPs, with radical SAM (rSAM)-modified RiPPs being the most prevalent class [31]. Genome mining has revealed extensive diversity, with 12,076 putative RiPP families identified in human microbiomes alone, demonstrating the vast untapped biosynthetic potential of bacterial RiPPs [31].

Archaeal RiPPs are less extensively characterized but show intriguing distributions and unique features. While archaeal ribosomes share protein components with eukaryotes, including archaea/eukaryote-specific ribosomal proteins (r-proteins) [32], the distribution of RiPP pathways in archaea appears more limited compared to bacteria. However, specific archaeal lineages produce specialized RiPP classes, such as thioamidated peptides catalyzed by YcaO-TfuA protein pairs [33]. Global genome mining efforts have identified putative thioamidated RiPP BGCs in various archaeal phyla, suggesting these organisms possess unique RiPP biosynthetic capabilities [33]. Archaeal RiPP pathways often represent simplified versions of eukaryotic systems, providing models for understanding functional essentials of RiPP biosynthesis that evolved before the diversification of archaea and eukaryotes [34].

Eukaryotic RiPPs

Eukaryotic RiPPs have been identified in fungi, plants, and animals, with distinctive biosynthetic features. Unlike prokaryotic systems, eukaryotic precursor peptides often contain an N-terminal signal sequence that directs the peptide to specific cellular compartments where post-translational modifications occur [22]. Well-characterized eukaryotic RiPP classes include cyclotides from plants, conopeptides from cone snails, and amatoxins from mushrooms, all featuring complex cyclization patterns and disulfide crosslinking [22]. The ribosome biogenesis machinery in eukaryotes shares significant homology with archaeal systems, particularly in the archaea/eukaryote-specific ribosomal proteins, suggesting evolutionary conservation of fundamental ribosomal processes that may extend to RiPP biosynthesis [32] [34].

Table 1: Distribution of RiPP Biosynthetic Potential Across Domains of Life

Domain	Representative Organisms	Key RiPP Classes	Unique Features	Biosynthetic Potential
Bacteria	Human gut microbiota (Bacteroidota, Firmicutes)	Lanthipeptides, Thiopeptides, Sactipeptides	Most diverse RiPP classes; High prevalence in microbiome	78.3-95.3% of genomes encode RiPPs [31]
Archaea	Methanogens, Asgard group	Thioamidated peptides	Simplified assembly pathways; TfuA-YcaO systems	Limited but distinct (e.g., 613 TfuA-related GCFs) [33]
Eukarya	Plants, Fungi, Animals	Cyclotides, Conopeptides, Amatoxins	Signal sequences for compartmentalization; Complex cyclization	Widespread but less systematically characterized

Quantitative Analysis of RiPP Diversity

Large-scale genomic analyses have enabled systematic quantification of RiPP biosynthetic potential across diverse taxa. In human microbiomes, precursor-centric genome mining approaches have identified 423,831 RiPP precursors confirmed by at least two independent detection strategies, distributed across 21 phyla, 1,014 genera, and 3,369 species [31]. The biosynthetic potential varies considerably at the genus level, with Elizabethkingia encoding up to 33 RiPP precursors per genome, Chryseobacterium encoding 18, and Tissierella encoding 15 [31]. This extensive diversity underscores the role of RiPPs in mediating ecological interactions within complex microbial communities.

Global mining of specific RiPP classes has revealed substantial untapped chemical space. For thioamidated RiPPs, analysis of 162,672 bacterial and archaeal genomes identified 613 unique TfuA-related gene cluster families and 797 precursor peptide families, extending across phyla where these clusters had not been previously described [33]. Similarly, analysis of ocean microbiome datasets using the deep learning tool TrRiPP uncovered a diverse array of previously uncharacterized putative RiPP families with high novelty and diversity [30]. These findings highlight that current knowledge of RiPP diversity represents only a fraction of their true biosynthetic potential in nature.

Table 2: Quantitative Distribution of RiPPs in Human Microbiomes

Body Site	Genomes with RiPPs	Most Abundant RiPP Classes	Noteworthy Producers	Potential Health Relevance
Gut	High enrichment	rSAM-modified RiPPs, Lanthipeptides	Bacteroidota, Firmicutes	30 RiPP families inversely related to IBD and CRC [31]
Oral	High enrichment	Thiopeptides, Lanthipeptides	Streptococcus spp.	Antimicrobials against oral pathogens
Skin	Moderate	Autoinducing peptides (AIPs)	Staphylococcus spp.	Maintain skin barrier homeostasis [31]
Vaginal	Moderate	Lanthipeptides	Lactobacillus gasseri	Antibacterial against vaginal pathogens [31]

Experimental Protocols for RiPP Discovery and Characterization

Protocol 1: Deep Learning-Assisted Metagenome Mining for RiPP Discovery

Purpose: To identify novel RiPP precursors from highly fragmented metagenomic data using deep learning approaches.

Materials and Reagents:

• High-performance computing cluster
• Metagenomic sequencing datasets
• TrRiPP software ( [30])
• Python environment with deep learning libraries (PyTorch/TensorFlow)
• Custom RiPP precursor database

Procedure:

• Data Preparation: Compile metagenomic assemblies from target environments (ocean, human microbiome, etc.). Preprocess sequences to filter those ≤150 amino acids for precursor prediction.
• Model Application: Process metagenomic sequences through TrRiPP, which combines Transformer encoder and Bi-LSTM architectures to classify RiPP precursors in a hallmark gene-independent manner.
• Validation: Confirm predictions using tenfold cross-validation assessing accuracy (0.994), recall (0.953), F1 score (0.967), and Matthews Correlation Coefficient (0.964) as performance metrics [30].
• Diversity Analysis: Cluster identified precursors into families using sequence similarity networking at 50% identity threshold.
• Correlation Analysis: Integrate metatranscriptomic data to identify co-expressed RiPP families and associated protein families using correlation networks.

Applications: This protocol successfully identified novel RiPP families in ocean microbiomes and revealed their potential roles in prokaryote-phage interactions through correlation analysis with antiphage defense-related proteins [30].

Protocol 2: Synthetic-Bioinformatic Natural Product (syn-BNP) Approach for RiPP Therapeutic Development

Purpose: To rapidly discover and validate therapeutic RiPP candidates through biosynthesis-guided chemical synthesis.

Materials and Reagents:

• 306,481 microbial genomes from human microbiome [31]
• Solid-phase peptide synthesis equipment and reagents
• Biofilm formation assay reagents (microtiter plates, crystal violet)
• Gut microbiota from disease models (e.g., IBD mice)
• antiSMASH and RiPPER software tools

Procedure:

• Genome Mining: Identify RiPP precursors using combined enzyme-centric (antiSMASH) and precursor-centric (DeepRiPP, TrRiPP) approaches applied to human microbiome genomes.
• Candidate Selection: Select candidates based on inverse correlation with disease states (e.g., IBD, colorectal cancer) from meta-omics analyses.
• Chemical Synthesis: Synthesize candidate RiPPs (e.g., autoinducing peptides) using solid-phase peptide synthesis, incorporating predicted post-translational modifications.
• In Vitro Validation: Test synthetic RiPPs for biofilm inhibition against pathogenic species using standardized biofilm formation assays.
• Ex Vivo Testing: Evaluate promising candidates using gut microbiota cultures from disease models, assessing community modulation and pathogen reduction.

Applications: This approach identified five AIPs that inhibited biofilm formation of disease-associated pathogens and two AIPs that regulated microbial community and reduced harmful species in IBD mouse models [31].

Biosynthetic Pathways and Engineering Strategies

Core RiPP Biosynthetic Pathway

The unified biosynthetic logic of RiPP pathways enables predictable engineering approaches. All RiPPs originate from a ribosomally synthesized precursor peptide containing a leader region and core region. Modification enzymes recognize the leader peptide and install diverse structural features onto the core peptide, followed by proteolytic removal of the leader and export of the mature product [22]. This conserved framework facilitates bioengineering strategies targeting each biosynthetic step.

Diagram 1: Core RiPP biosynthetic pathway. PTM: Post-translational modification.

Engineering Strategies for RiPP Pathways

RiPP engineering leverages the modularity of biosynthetic components to generate novel analogs with optimized properties. Three primary engineering strategies have emerged:

Leader peptide manipulation: Creating chimeric leader peptides enables redirecting modification enzymes to non-cognate core peptides, generating hybrid natural products [9]. This approach capitalizes on the leader peptide's role in enzyme recognition while swapping core peptides to introduce structural diversity.

Core peptide diversification: Mutating core peptide residues within enzyme tolerance regions generates analogs with modified bioactivities [9]. Successful examples include incorporating non-proteinogenic amino acids and generating lanthipeptide libraries with enhanced antimicrobial properties.

Enzyme engineering: Modifying RiPP tailoring enzymes expands their substrate scope and enables installation of non-natural modifications [9] [29]. Combining enzymatic transformations with synthetic chemistry approaches further diversifies the accessible chemical space.

The Scientist's Toolkit: Essential Research Reagents

Table 3: Key Research Reagents for RiPP Discovery and Characterization

Reagent/Tool	Type	Function	Example Applications
TrRiPP	Software tool	Identifies RiPP precursors using deep learning	Ocean metagenome mining [30]
antiSMASH	Software tool	Identifies biosynthetic gene clusters	RiPP BGC detection in human microbiome [31]
RiPPER	Software tool	Detects RiPP precursor peptides	Thioamidated RiPP discovery [33]
YcaO-TfuA system	Enzymatic pair	Catalyzes thioamide formation	Thioamidated RiPP biosynthesis [33]
Radical SAM enzymes	Enzyme family	Installs thioether crosslinks	Sactipeptide biosynthesis [29]
Heterologous expression systems	Method	Produces RiPPs in surrogate hosts	Thuricin CD characterization [29]
BRD4 ligand-Linker Conjugate 1	BRD4 Ligand-Linker Conjugate 1 | PROTAC Intermediate	BRD4 ligand-Linker Conjugate 1 is a key intermediate for constructing PROTAC degraders. This product is For Research Use Only (RUO). Not for human or veterinary use.	Bench Chemicals
Chlormadinone Acetate-d3	Chlormadinone Acetate-d3, MF:C23H29ClO4, MW:407.9 g/mol	Chemical Reagent	Bench Chemicals

Applications in Therapeutic Development

RiPPs demonstrate significant potential for therapeutic development, particularly in managing microbial infections and microbiome-associated diseases. Protective roles of RiPPs in human health are increasingly recognized, with specific RiPP families showing inverse relationships to disease states such as inflammatory bowel disease and colorectal cancer [31]. Autoinducing peptides (AIPs) from human microbiomes have demonstrated efficacy in inhibiting biofilm formation of pathogens and regulating microbial communities in disease models [31].

The bioengineering potential of RiPP pathways further enhances their therapeutic appeal. Successful engineering examples include darobactin biosynthetic pathway engineering to generate broad-spectrum antibiotics against Gram-negative pathogens [9] and creation of hybrid lanthipeptides with selective antimicrobial activity against Staphylococcus aureus [9]. The genetic encodability of RiPP precursors combined with increasing understanding of their biosynthetic logic positions RiPPs as ideal targets for rational design of peptide-based therapeutics.

RiPP natural products represent a vast and largely untapped resource for drug discovery and development, with diverse representatives distributed across prokaryotes, eukaryotes, and archaea. The unified biosynthetic logic of RiPP pathways, combined with their genetic encodability and enzymatic plasticity, makes them particularly amenable to engineering approaches. Quantitative genomic analyses reveal extensive RiPP biosynthetic potential in environmental and host-associated microbiomes, highlighting opportunities for future discovery. As research continues to elucidate the ecological functions, biosynthetic mechanisms, and therapeutic potential of RiPPs, these versatile molecules are poised to make significant contributions to peptide engineering and therapeutic development.

Engineered RiPPs in Action: Genome Mining, Synthetic Biology, and Therapeutic Applications

Biosynthetic Gene Clusters (BGCs) are genomic loci that encode the production of microbial natural products, which form the basis for nearly 75% of human medicines, including antimicrobials and immunosuppressants [35] [29]. Bioinformatics tools have become indispensable for identifying these clusters, transforming natural product discovery from a purely activity-based screening process to a targeted, sequence-driven endeavor [35]. This application note details the integrated use of three powerful bioinformatics tools—antiSMASH, PRISM, and RODEO—for BGC identification, with specific focus on their application to ribosomally synthesized and post-translationally modified peptides (RiPPs). RiPPs represent a promising superfamily of natural products characterized by their genetically encoded precursor peptides that undergo extensive enzymatic tailoring to produce structurally complex bioactive compounds [29] [9]. Their unified biosynthetic logic and the genetic encodability of their substrates make them particularly amenable to bioengineering for pharmaceutical development [9].

Key Bioinformatics Tools for BGC Mining

antiSMASH (antibiotics & Secondary Metabolite Analysis Shell) is the most widely used platform for detecting and characterizing BGCs in bacterial and fungal genomes [36]. It functions by identifying conserved biosynthetic genes through profile hidden Markov models (pHMMs) and then analyzing domain architecture to predict cluster type and potential chemical product [35]. The recently released antiSMASH 6.0 supports 71 different cluster types—a significant increase from previous versions—and offers enhanced detection of tailoring enzymes in RiPP clusters [36].

PRISM (PRediction Informatics for Secondary Metabolites) is a genome mining tool with a strong emphasis on predicting chemical structures of biosynthetic pathways, particularly for nonribosomal peptides, polyketides, and RiPPs [37] [35]. PRISM is closely integrated with the Genomes-to-Natural Products platform (GNP), which enables matching of genomic predictions with LC-MS/MS data for compound identification [35]. This structural prediction capability makes PRISM particularly valuable for hypothesis generation in drug discovery pipelines.

RODEO (Rapid ORF Description and Evaluation Online) specializes in the detection and analysis of RiPP biosynthetic gene clusters [37] [35]. Unlike general-purpose tools, RODEO combines genome mining with motif-based analysis to identify RiPP precursor peptides and predict post-translational modifications, making it uniquely suited for discovering novel ribosomally synthesized peptides [37] [9].

Table 1: Comparative Analysis of BGC Identification Tools

Tool	Primary Function	Strengths	RiPP-Specific Features	Access
antiSMASH	Comprehensive BGC detection & classification	Broadest cluster type coverage (71 types); most widely used; integrates multiple algorithms	RiPP-specific HMM profiles; RODEO integration; tailoring enzyme detection [36] [35]	Web server & standalone [35]
PRISM	Chemical structure prediction	Predicts complete chemical structures; links BGCs to MS/MS data	RiPP cluster detection & structure prediction; handles complex modifications [37]	Web server [37]
RODEO	RiPP cluster identification	Specialized for RiPP discovery; identifies precursor peptides	Motif-based precursor peptide identification; comprehensive RiPP analysis [37] [9]	Web server & standalone [37]

Complementary Tool Ecosystem

Several specialized tools complement these primary platforms for specific research applications. BAGEL is dedicated to mining ribosomally synthesized and post-translationally modified peptides (RIPPs), including lanthipeptides and bacteriocins, making it particularly valuable for antimicrobial discovery [37]. ARTS (Antibiotic Resistant Target Seeker) integrates with antiSMASH to prioritize BGCs based on potential antibiotic activity and identifies resistance genes that may indicate novel mechanisms of action [37] [38]. DeepBGC employs machine learning for BGC classification and can predict bioactivity (antibacterial, antifungal, cytotoxic) directly from BGC sequences, though with currently limited accuracy for some activity classes [38].

Table 2: Specialized Tools for Advanced BGC Analysis

Tool	Application	Utility in RiPP Research
BAGEL	RIPP identification & analysis	Identifies and classifies RIPP clusters in genomic data [37]
ARTS	BGC prioritization & resistance gene identification	Identifies potential antibiotic targets and resistance mechanisms [37]
DeepBGC	Machine learning-based BGC classification & activity prediction	Predicts antibacterial/antifungal activity from BGC features [38]
BiG-SCAPE	Gene cluster family analysis & dereplication	Groups BGCs into families; identifies novel clusters [37]

Experimental Protocols for BGC Identification

Protocol 1: Comprehensive BGC Detection with antiSMASH

Principle: antiSMASH identifies BGCs through a multi-step process beginning with gene annotation, followed by core biosynthetic gene detection using pHMMs, and finally cluster boundary prediction and annotation [35].

Procedure:

• Input Preparation: Prepare genomic data in standard formats (FASTA, GenBank, or EMBL). For FASTA files, antiSMASH will automatically perform gene calling using Prodigal for bacterial genomes [35].
• Analysis Submission: Access the antiSMASH web server at https://antismash.secondarymetabolites.org/ or run the standalone version locally for large datasets.
• Parameter Selection:
  • Select "bacterial" or "fungal" mode as appropriate
  • Enable RiPP-specific detection options
  • Activate the "ClusterCompare" feature for comparative analysis
  • Integrate RODEO for enhanced RiPP analysis [36]
• Result Interpretation:
  • Review the cluster table summarizing predicted BGCs
  • Examine domain organization of multi-modular BGCs
  • Analyze RiPP precursor peptides using integrated RODEO results
  • Utilize the "KnownClusterBlast" feature to compare with characterized BGCs in the MIBiG database [35]

Troubleshooting Tip: For genomes with poor annotation quality, provide pre-annotated GenBank files rather than relying on automated gene calling to improve prediction accuracy [35].

Protocol 2: Structure-Focused Mining with PRISM

Principle: PRISM predicts the chemical structures of natural products from genomic data by correlating biosynthetic logic with structural motifs, then enables matching these predictions to experimental MS/MS data [35].

Procedure:

• Input Requirements: Provide annotated genomic data in GenBank format or protein sequences in FASTA format.
• Analysis Execution:
  • Access the PRISM web server at http://magarveylab.ca/prism
  • Submit genomic sequences for analysis
  • Select appropriate analysis parameters for RiPP detection
• Structure Prediction:
  • Review predicted chemical structures of putative metabolites
  • Analyze proposed biosynthetic pathways
  • Identify potential hybrid clusters combining RiPP elements with other biosynthetic logic [39]
• Metabolomic Integration:
  • Export structure predictions to the GNP (Genes to Natural Products) platform
  • Compare predicted structures with experimental LC-MS/MS data
  • Identify candidate peaks corresponding to predicted metabolites [35]

Application Note: PRISM is particularly valuable for identifying RiPP-derived lipopeptides and other hybrid natural products that combine RiPP biosynthetic logic with additional chemical moieties [39].

Protocol 3: Targeted RiPP Discovery with RODEO

Principle: RODEO combines genome mining with heuristic analysis of RiPP biosynthetic genes to identify precursor peptides and predict post-translational modifications, specializing in the discovery of novel ribosomally synthesized peptides [37].

Procedure:

• Input Preparation: Prepare genomic data in FASTA format. RODEO can analyze complete genomes or smaller contigs from metagenomic studies.
• Analysis Execution:
  • Access the web interface at http://www.ripp.rodeo/ or run the standalone version
  • Submit genomic sequences for analysis
  • Select specific RiPP classes of interest or perform comprehensive analysis
• Result Analysis:
  • Identify putative RiPP precursor peptides through motif analysis
  • Review heuristic scores for biosynthetic genes
  • Examine predicted post-translational modifications
  • Identify potential novel RiPP families through comparative analysis [37]

Advanced Application: For radical SAM enzymes involved in RiPP biosynthesis (such as thuricin CD), RODEO can help identify unusual biosynthetic mechanisms requiring enzyme complexes rather than single enzymes [29].

Applications in RiPP Biosynthetic Pathway Engineering

The integration of antiSMASH, PRISM, and RODEO provides a powerful framework for RiPP pathway engineering, enabling rational design of novel bioactive peptides. Three primary engineering strategies have emerged:

Leader Peptide Manipulation

Many RiPP pathways employ a leader-peptide-guided biosynthetic logic where tailoring enzymes contain RiPP precursor peptide recognition elements (RREs) that bind to leader peptides, directing catalytic domains to modify core peptide regions [9]. Bioinformatics tools enable the identification of these leader-receptor pairs, facilitating the creation of chimeric systems where native leader peptides are replaced with alternative sequences to redirect biosynthetic enzymes toward non-cognate core peptides [9]. This approach was successfully demonstrated in the engineering of cyanobactins, where leader peptide swapping enabled the production of diverse macrocyclic peptides [9].

Core Peptide Diversification

Bioinformatic analysis of RiPP enzymes' substrate tolerance enables the rational design of modified core peptides. By identifying positions with relaxed specificity, researchers can introduce non-proteinogenic amino acids, sequence variations, or chemically modified residues to generate "new-to-nature" RiPP compounds [9]. For instance, bioengineering of the lantibiotic nisin incorporated methionine analogs for subsequent click chemistry modification, generating derivatives with altered biological activity [9]. The substrate promiscuity of many RiPP maturase enzymes, particularly those in radical SAM families, makes them ideal candidates for such engineering approaches [29] [39].

Enzyme Engineering and Pathway Construction

BGC mining tools facilitate the identification of promiscuous enzymes that can be repurposed for peptide modification. For example, the combination of RiPP biosynthetic enzymes with established synthetic chemistry approaches has enabled the production of hybrid peptides with non-natural linkages and modifications [9]. Additionally, the discovery of leader-independent enzymes through genome mining has simplified pathway engineering by eliminating the requirement for specific leader sequences [9].

Research Reagent Solutions

Table 3: Essential Research Reagents and Resources for BGC Analysis

Resource	Type	Function in BGC Research	Access
MIBiG Database	Reference Data	Curated repository of known BGCs for comparison & validation [35]	http://mibig.secondarymetabolites.org [35]
antiSMASH DB	BGC Database	Database of pre-computed antiSMASH results for public genomes [35]	http://antismash-db.secondarymetabolites.org [35]
Norine	Nonribosomal Peptide DB	Database of nonribosomal peptides for structure comparison [35]	http://bioinfo.lifl.fr/NRP [35]
RRE Toolkits	Enzyme Reagents	RiPP Recognition Element domains for leader peptide binding studies [9]	Custom construction required
Chimeric Leader Peptides	Engineering Reagents	Hybrid leader sequences for redirecting biosynthetic enzymes [9]	Synthetic gene construction

The integrated application of antiSMASH, PRISM, and RODEO provides a comprehensive bioinformatics pipeline for BGC identification and characterization, with particular utility for RiPP biosynthetic pathway engineering. While these tools have dramatically accelerated natural product discovery, important challenges remain, including accurate prediction of novel BGC classes and reliable determination of cluster boundaries [35]. Future developments in machine learning approaches for activity prediction [38] and improved integration with metabolomic data [35] will further enhance our ability to mine microbial genomes for the next generation of therapeutic compounds. For RiPP researchers, these tools collectively enable the transition from discovery to engineering, facilitating the rational design of bioactive peptides with tailored pharmaceutical properties.

The successful engineering of ribosomally synthesized and post-translationally modified peptides (RiPPs) hinges on the selection and optimization of an appropriate heterologous production host. These hosts provide the cellular machinery necessary for the biosynthesis of complex peptide natural products, which often possess promising pharmaceutical properties. Among the most prevalent hosts, the Gram-negative bacterium Escherichia coli and members of the Gram-positive Streptomyces genus each offer distinct advantages and present unique challenges. E. coli is prized for its rapid growth, well-understood genetics, and extensive toolkit for molecular manipulation [40] [41]. In contrast, Streptomyces species, being native producers of numerous clinical drugs, offer a naturally optimized metabolic background for the production of secondary metabolites and possess inherent capabilities for secreting complex, correctly folded proteins [42] [40]. This application note provides a comparative analysis and detailed protocols for utilizing these two powerful hosts within the context of RiPP biosynthetic pathway engineering.

Host System Comparison

The choice between E. coli and Streptomyces involves careful consideration of their inherent characteristics, which can significantly impact the success of a heterologous expression project. The following table summarizes the key attributes of each host system.

Table 1: Comparison of E. coli and Streptomyces as Heterologous Hosts for RiPP Production

Feature	E. coli	Streptomyces
Genetic Manipulation	Highly tractable; vast array of vectors and tools; rapid cloning [41]	More complex; tools available but slower than E. coli; conjugative transfer often required for large DNA [43] [40]
Growth Characteristics	Very fast growth (doubling time ~20 min); high-density cultivation well-established [41]	Slow, filamentous growth; complex developmental cycle; industrial fermentation processes available [40]
Codon Usage	AT-rich; codon optimization often essential for GC-rich genes from actinobacteria [44] [45]	GC-rich; naturally compatible with actinobacterial genes, reducing need for optimization [42] [40]
Protein Secretion	Limited native secretion; requires signal peptides for Sec/Tat pathways; periplasmic production can aid disulfide bond formation [46] [47]	High native secretion capacity; Gram-positive structure (no outer membrane) facilitates release into medium; oxidizing extracellular environment promotes disulfide bond formation [40] [47]
Post-Translational Modifications	Limited native capacity for complex PTMs; may lack necessary chaperones or tailoring enzymes for RiPP maturation [40] [41]	Rich in tailoring enzymes (e.g., methyltransferases, oxidases); more likely to possess compatible machinery for RiPP biosynthesis [42] [48]
Metabolic Precursor Availability	May lack specialized precursors (e.g., non-proteinogenic amino acids) required for certain RiPPs [40]	Native producer of diverse secondary metabolites; often has inherent supply of key precursors [42] [40]
Key Advantage	Speed, ease of use, and high yields for soluble, uncomplexed proteins.	Compatibility for expressing functional biosynthetic enzymes and complex pathways from actinobacteria.
Primary Challenge	Inefficient secretion, potential for inclusion body formation, and lack of specialized PTM machinery.	Slow growth, genetic intractability, and complex cellular physiology.

Experimental Protocols

Heterologous Expression inE. coli: A Protocol for Antimicrobial Peptide Production

The following protocol, adapted from successful production of a chimeric human β-defensin, outlines key steps for expressing and purifying a disulfide-bonded antimicrobial peptide in E. coli [45].

Principle: To overcome the toxicity of antimicrobial peptides to the host and the challenge of disulfide bond formation, the peptide of interest is expressed as a fusion partner with a solubility-enhancing tag (Thioredoxin A, TrxA) via a cleavable linker. This promotes solubility, shields the host from the peptide's toxicity, and allows for cytoplasmic expression in a reducing environment. The tag is removed after purification under denaturing conditions.

Materials:

• Expression Vector: pET32a (or similar vector with T7/lac promoter, TrxA tag, and enterokinase cleavage site) [45].
• Host Strain: E. coli BL21(DE3) for T7 polymerase-based expression.
• Culture Media: Luria-Bertani (LB) broth and agar plates supplemented with 50 µg/mL ampicillin.
• Inducer: Isopropyl β-D-1-thiogalactopyranoside (IPTG).
• Lysis & Purification Buffers: Lysis Buffer (20 mM NaHâ‚‚POâ‚„, 0.5 M NaCl, 5 mM imidazole, 6 M Urea, pH 7.4), Binding/Wash Buffer (as Lysis Buffer), Elution Buffer (as Lysis Buffer but with 500 mM imidazole).
• Enzyme: Enterokinase.
• Equipment: Sonicator or French press, Ni-NTA affinity chromatography system, SDS-PAGE and Tris-Tricine-SDS-PAGE apparatus.

Procedure:

• Vector Construction & Transformation: Codon-optimize the gene encoding the target peptide for E. coli [45]. Clone the synthesized gene into the pET32a vector downstream of the enterokinase (EK) cleavage site to create an in-frame TrxA-EK-target peptide fusion. Verify the construct by sequencing and transform into E. coli BL21(DE3) competent cells.
• Small-Scale Expression Testing: Inoculate 5 mL LB cultures with transformants and grow at 37°C to an OD₆₀₀ of ~0.6. Induce expression with a range of IPTG concentrations (e.g., 0.1 - 0.4 mM) and incubate further at a lower temperature (e.g., 15-25°C) for 12-16 hours to enhance soluble expression. Analyze cell lysates (both soluble and insoluble fractions) by SDS-PAGE to identify optimal induction conditions [45].
• Large-Scale Production & Purification:
  • Inoculate a large culture (e.g., 1 L) and grow to OD₆₀₀ ~0.6 under optimized induction conditions.
  • Harvest cells by centrifugation (8,000 × g, 20 min).
  • Resuspend cell pellet in Lysis Buffer. Lyse cells using a high-pressure homogenizer or sonicator on ice.
  • Clarify the lysate by centrifugation (12,000 × g, 30 min) and load the supernatant onto a Ni-NTA affinity column pre-equilibrated with Binding Buffer.
  • Wash the column with 10-20 column volumes of Binding Buffer to remove unbound proteins.
  • Elute the fused TrxA-EK-target peptide with Elution Buffer. Analyze fractions by SDS-PAGE.
• On-Column Cleavage and Final Purification:
  • Dialyze the purified fusion protein against Binding Buffer and re-bind it to a fresh Ni-NTA column.
  • Equilibrate the column with Equilibrium Buffer (25 mM Tris-HCl, pH 8.0).
  • Add enterokinase directly to the column and incubate at 25°C for 16 hours to cleave the tag from the target peptide.
  • Elute the untagged, purified target peptide with Equilibrium Buffer. The TrxA tag and any uncleaved fusion protein remain bound to the column and can be eluted later with Elution Buffer.
  • Confirm the identity and purity of the final peptide by Tris-Tricine-SDS-PAGE and mass spectrometry. Dialyze the purified peptide against PBS or a suitable buffer for storage and functional assays [45].

Heterologous Expression inStreptomyces: A Protocol for Biosynthetic Gene Cluster Expression

This protocol describes the use of the "Micro-HEP" platform for transferring and integrating a biosynthetic gene cluster (BGC) into an engineered Streptomyces coelicolor chassis for expression [43].

Principle: The BGC is first cloned and engineered in an E. coli strain equipped with a recombineering system. Subsequently, the modified BGC, outfitted with an origin of transfer (oriT) and recombination sites, is conjugally transferred from E. coli to the Streptomyces chassis. Finally, the BGC is integrated site-specifically into the chromosome of the chassis strain via recombinase-mediated cassette exchange (RMCE), enabling stable expression and copy number control [43].

Materials:

• DNA Manipulation Strain: E. coli strain containing a rhamnose-inducible Redαβγ recombineering system (e.g., part of the Micro-HEP platform) [43].
• Conjugal Donor Strain: E. coli ET12567 (pUZ8002) or an improved alternative from the Micro-HEP platform [43].
• Chassis Strain: Engineered S. coelicolor A3(2)-2023 (or similar) with deletions of endogenous BGCs and pre-engineered chromosomal RMCE attachment sites (e.g., loxP, vox, rox, attPphiBT1) [43].
• Vectors: Modular RMCE cassettes containing oriT, an integrase gene, and corresponding recombination target sites (RTS) [43].
• Media: LB for E. coli; Modified Soybean-Mannitol (MS) medium for Streptomyces [43].
• Antibiotics: Appropriate antibiotics for selection in both E. coli and Streptomyces.

Procedure:

• BGC Engineering in E. coli:
  • Clone the target BGC into a suitable plasmid in the recombineering-proficient E. coli strain.
  • Use Red recombineering to insert an RMCE cassette (containing oriT, integrase, and RTS) into the plasmid bearing the BGC. This prepares the BGC for conjugative transfer and chromosomal integration [43].
• Conjugative Transfer:
  • Transform the final BGC construct into the conjugal donor E. coli strain.
  • Prepare spores or mycelial fragments of the Streptomyces chassis strain.
  • Mix the donor E. coli cells and the Streptomyces spores/mycelium on an MS agar plate and incubate to allow conjugation.
  • After conjugation, overlay the plate with antibiotics selective for Streptomyces exconjugants and an antibiotic like nalidixic acid to counter-select the E. coli donor [43].
• Integration and Screening:
  • Isolate exconjugants and screen for successful integration of the BGC. This can be done by PCR verification or by observing the activation of a phenotypic marker.
  • The RMCE process ensures that only the BGC, without the plasmid backbone, is integrated into the specific chromosomal site, which can be engineered for single or multi-copy integration to optimize yield [43].
• Fermentation and Metabolite Analysis:
  • Inoculate positive exconjugants into an appropriate production medium (e.g., GYM or M1 medium) [43].
  • Culture at 30°C with shaking for several days to allow metabolite production.
  • Extract the culture broth and mycelia with a suitable organic solvent (e.g., ethyl acetate or methanol).
  • Analyze the extracts for the desired RiPP or novel metabolites using analytical techniques such as HPLC-MS or LC-MS/MS.

The Scientist's Toolkit

Table 2: Essential Research Reagents for Heterologous Expression

Reagent / Tool	Function	Example Host(s)
pET Vector Series	High-copy-number expression vectors utilizing the strong T7 promoter for controlled, high-level protein production.	E. coli [45]
CASPON-Tag	A fusion tag system that enhances solubility and allows for ultrafast, scarless cleavage and purification of recombinant peptides.	E. coli [49]
Micro-HEP Platform	A comprehensive system using engineered E. coli strains for BGC modification/conjugation and optimized Streptomyces chassis for high-efficiency heterologous expression.	E. coli, S. coelicolor [43]
RMCE Cassettes (Cre-lox, Vika-vox, etc.)	Modular genetic elements that enable precise, backbone-free integration of large DNA constructs into specific chromosomal loci of the chassis.	Streptomyces spp. [43]
S. coelicolor M1146 / A3(2)-2023	Genetically minimized chassis strains with deletions of multiple endogenous BGCs to reduce metabolic burden and background interference.	Streptomyces spp. [43] [48]
Inducible MicL sRNA System	A tool for in-process knockdown of the outer membrane lipoprotein Lpp, increasing membrane permeability and facilitating peptide secretion.	E. coli [49]
Elongation factor P-IN-1	Elongation factor P-IN-1, MF:C14H31N3O2, MW:273.41 g/mol	Chemical Reagent
Mono(2-hydroxyisobutyl)phthalate-d4	Mono(2-hydroxyisobutyl)phthalate-d4, MF:C12H14O5, MW:242.26 g/mol	Chemical Reagent

Workflow and Pathway Diagrams

E. coli Heterologous Expression Workflow

The following diagram illustrates the key steps and optimization strategies for producing recombinant peptides in E. coli.

Streptomyces BGC Heterologous Expression Workflow

This diagram outlines the multi-step process of expressing a biosynthetic gene cluster in a Streptomyces chassis, highlighting the role of specialized platforms like Micro-HEP.

Ribosomally synthesized and post-translationally modified peptides (RiPPs) represent a major class of natural products with diverse chemical structures and potent biological activities, including antimicrobial, antiviral, and anticancer properties [50]. The biosynthetic logic of RiPPs is characterized by a conserved pathway: a ribosomally synthesized precursor peptide, typically comprising an N-terminal leader peptide and a C-terminal core peptide, undergoes extensive post-translational modifications (PTMs) catalyzed by specific enzymes before the leader peptide is proteolytically removed to yield the mature natural product [51] [50]. This fundamental architecture provides a direct genetic link between the peptide sequence and the final chemical structure, making RiPPs exceptionally attractive for bioengineering.

Precursor peptide engineering exploits this genetic encodability to generate novel RiPP analogs with enhanced or entirely new functions. The leader peptide plays a critical role in biosynthetic pathways by serving as a recognition motif for the PTM enzymes, often functioning as an allosteric regulator that binds the active form of the biosynthetic enzymes in a conformational selection process [51]. The core peptide, which is modified and becomes the final product, is often tolerant of sequence variations, providing a flexible scaffold for engineering [52]. Two primary strategies have emerged for manipulating this system: site-directed mutagenesis of the core peptide to alter its sequence and properties, and leader-core fusion strategies to redirect enzymatic specificity and enable the modification of non-native substrates. This application note details practical protocols for both approaches, providing researchers with a toolkit for the targeted engineering of RiPP natural products.

Site-Directed Mutagenesis of Core Peptides

Principles and Applications

Site-directed mutagenesis of the core peptide is the most straightforward method for generating RiPP analogs. This approach capitalizes on the frequent observation that the enzymes responsible for post-translational modifications often exhibit significant substrate tolerance toward the core peptide sequence while maintaining strict recognition of the leader peptide [52]. By systematically altering residues in the core region, researchers can probe structure-activity relationships (SAR), enhance bioactivity, improve stability, or introduce novel chemical functionalities.

The methodology has been successfully applied across multiple RiPP classes. In lasso peptides, such as the RNA polymerase inhibitor microcin J25 (MccJ25), comprehensive scanning mutagenesis has been employed where every residue in the ring (positions 1-7) and tail (positions 9-21) regions was individually substituted with all proteinogenic amino acids [52]. This systematic approach identified residues critical for biosynthesis (e.g., the lactam-forming Gly1 and Glu8) versus those essential for bioactivity (e.g., Tyr9), revealing the differential sequence requirements for production versus function [52]. Similarly, mutagenesis of the anti-mycobacterial lasso peptide lariatin A identified specific residues (Tyr6, Gly11, and Asn14) as crucial for its antibacterial activity, while others (Val15, Ile16, and Pro18) enhanced this activity, leading to the development of analogs with improved potency [52].

Experimental Protocol: Saturation Mutagenesis

Objective: To generate a comprehensive library of core peptide variants for functional screening.

Materials:

• Plasmid DNA encoding the precursor peptide gene within its biosynthetic gene cluster (BGC)
• High-fidelity DNA polymerase (e.g., Q5, Phusion)
• DpnI restriction enzyme
• Competent E. coli cells (for cloning and expression)
• Oligonucleotide primers designed for the target codon(s)
• Appropriate growth media and antibiotics

Procedure:

• Target Selection: Identify the residue(s) in the core peptide for mutagenesis based on structural data or homology analysis.

• Primer Design: Design mutagenic primers containing degenerate codons (e.g., NNK, where N=A/T/C/G, K=G/T) to cover all possible amino acid substitutions at the target position. Ensure primers have sufficient flanking sequences (typically 15-20 bp) for efficient annealing.

• PCR Amplification: Set up the PCR reaction as follows:

  • Template DNA (plasmid with BGC): 10-50 ng
  • Forward and reverse mutagenic primers: 0.5 µM each
  • dNTP mix: 200 µM each
  • DNA polymerase: 1 unit
  • Reaction buffer: 1X
  • Total volume: 50 µL

  Cycling conditions:

  • Initial denaturation: 98°C for 30 seconds
  • 25 cycles of:
    • Denaturation: 98°C for 10 seconds
    • Annealing: 55-65°C for 20 seconds (optimize based on primer Tm)
    • Extension: 72°C for 2-4 minutes (depending on plasmid size)
  • Final extension: 72°C for 5 minutes

• Template Digestion: Add 1 µL of DpnI restriction enzyme directly to the PCR product and incubate at 37°C for 1-2 hours to digest the methylated template DNA.

• Transformation: Transform 2-5 µL of the DpnI-treated DNA into competent E. coli cells following standard heat-shock or electroporation protocols.

• Library Validation: Plate transformed cells on selective media and incubate overnight. Pick multiple colonies for sequencing to confirm the diversity and representation of the mutant library.

• Screening: Express the mutant library and screen for desired properties (e.g., antimicrobial activity, enzyme inhibition, or improved stability) using appropriate functional assays.

Table 1: Key Residues for Mutagenesis in Model RiPPs

RiPP Class	Example	Critical Residues	Mutagenesis Effect	Citation
Lasso Peptide	Microcin J25	Gly1, Glu8	Essential for biosynthesis	[52]
Lasso Peptide	Microcin J25	Tyr9, Phe10, Phe19	Essential for bioactivity	[52]
Lasso Peptide	Lariatin A	Tyr6, Gly11, Asn14	Crucial for anti-mycobacterial activity	[52]
Lasso Peptide	Lariatin A	Val15, Ile16, Pro18	Enhanced antibacterial activity	[52]
Lanthipeptide	Salivaricin B	Core Ser/Thr/Cys	Affects dehydration and cyclization pattern	[16]

Workflow Visualization

The following diagram illustrates the complete site-directed mutagenesis workflow for RiPP engineering:

Leader-Core Fusion Strategies

Principles and Applications

Leader-core fusion strategies involve appending a recognition leader peptide to a non-cognate core peptide sequence, thereby enabling the modification of heterologous peptides by RiPP biosynthetic enzymes. This approach exploits the modular nature of precursor peptides, where the leader peptide primarily dictates enzyme recognition while the core peptide serves as the modification substrate [51] [50]. The strategy is particularly powerful for introducing complex PTMs into biologically active peptides that lack them naturally, thereby enhancing their stability, activity, or conferring new properties.

The effectiveness of this strategy depends on the specific RiPP class and the compatibility between the leader peptide and the modification enzymes. In class II lanthipeptides, the leader peptide of the precursor peptide SboA was shown to effectively guide the modification enzyme SboM, enabling the installation of thioether rings in the core peptide [16]. Similarly, in lasso peptide biosynthesis, the leader peptide is recognized by the B protein (a peptidase) and C protein (a cyclase), which work in concert to cleave the leader and form the characteristic macrolactam ring [51] [52]. Engineering efforts have demonstrated that fusing different core sequences to native leaders can successfully produce chimeric lasso peptides, provided the essential residues for enzymatic processing (e.g., the lactam-forming Glu/Asp at position 8 or 9) are preserved [52].

Experimental Protocol: Golden Gate Assembly for Leader-Core Fusions

Objective: To create chimeric precursor peptides by fusing a leader sequence to heterologous core peptides.

Materials:

• Plasmid containing the native leader sequence
• DNA fragments encoding candidate core peptides
• Type IIS restriction enzymes (e.g., BsaI, BsmBI)
• T4 DNA Ligase and buffer
• Agarose gel electrophoresis equipment
• DNA purification kits

Procedure:

• Vector Design: Clone the leader peptide sequence into a plasmid flanked by appropriate Type IIS restriction sites (e.g., BsaI) in a destination vector containing the RiPP BGC without the native core sequence.

• Insert Preparation: Design double-stranded DNA fragments encoding the core peptide(s) of interest with flanking Type IIS sites creating complementary overhangs to the vector. These can be generated via gene synthesis or PCR assembly.

• Golden Gate Assembly: Set up the reaction mixture:

  • Prepared vector: 50 ng
  • Insert fragment(s): 3:1 molar ratio to vector
  • Type IIS restriction enzyme: 10 units
  • T4 DNA Ligase: 400 units
  • ATP: 1 mM
  • Reaction buffer: 1X
  • Total volume: 20 µL

  Cycling conditions (25 cycles):

  • Restriction and ligation: 37°C for 5 minutes
  • Enzyme inactivation: 60°C for 5 minutes

• Transformation and Screening: Transform 2-5 µL of the assembly reaction into competent E. coli cells. Screen colonies by colony PCR or restriction digest to identify correct constructs.

• Heterologous Expression: Introduce the verified plasmid into an appropriate expression host (e.g., E. coli BL21) containing the necessary modification enzymes.

• Product Analysis: Express the engineered gene cluster and analyze the products using mass spectrometry (MALDI-TOF or LC-MS/MS) to confirm successful modification.

Table 2: Leader Peptide Types and Their Applications in Fusion Strategies

Leader Type	RiPP Class	Key Features	Engineering Application	Citation
Canonical Leader	Lanthipeptides, Lasso peptides	Short (<50 aa), unstructured	Guiding PTMs of cognate and non-cognate cores	[6]
NHLP (Nitrile Hydratase-like Leader Peptide)	Proteusins	Long (>80 aa), structured tertiary fold	Engages enzymes via large protein-like interfaces	[6]
Follower Peptide	Cyanobactins	C-terminal recognition sequence	Directs proteolytic cleavage and cyclization	[51]

Workflow Visualization

The following diagram illustrates the leader-core fusion strategy for creating chimeric RiPPs:

Integrated Engineering Platforms

Cell-Free Biosynthesis for Rapid Screening

Cell-free gene expression (CFE) systems provide a powerful platform for rapid prototyping of engineered RiPPs, bypassing the time-consuming steps of molecular cloning and in vivo cultivation [16]. The UniBioCat system, for instance, has been successfully used for the cell-free biosynthesis of lanthipeptides like salivaricin B, where precursor peptides and modification enzymes are co-expressed in vitro to produce mature RiPPs within hours [16]. This approach is particularly valuable for screening large libraries of engineered precursor peptides, as it eliminates potential host cytotoxicity issues and allows direct control over reaction conditions.

Protocol Highlights for Cell-Free RiPP Production:

• Use chaperone-enriched E. coli cell extracts to improve solubility of modification enzymes
• Co-express precursor peptide and modification enzymes in a single-pot reaction
• Incubate at 30-32°C for 4-6 hours with shaking
• Analyze products directly from the reaction mixture using MALDI-TOF-MS

Computational Tools for Binder Design

Recent advances in machine learning have produced computational tools like PepMLM that can design peptide binders to target proteins based solely on sequence information [53]. While not specifically trained for RiPP engineering, such tools can be repurposed to design core peptides with desired binding specificities, which can then be incorporated into leader-core fusion constructs for post-translational modification.

The Scientist's Toolkit: Essential Research Reagents

Table 3: Key Research Reagents for Precursor Peptide Engineering

Reagent / Tool	Category	Function	Example Application	Citation
Golden Gate Assembly System	Molecular Cloning	Modular assembly of leader-core fusions	Creating chimeric precursor peptides	[16]
ESM-2 Protein Language Model	Computational Design	Peptide binder design via masked language modeling	Designing target-specific core peptides	[53]
Cell-Free Gene Expression System	Expression Platform	Rapid in vitro synthesis of RiPPs	High-throughput screening of mutant libraries	[16]
DIA-NN with Skyline	Analytical Software	Peptide identification and quantification	Analyzing engineered RiPP products	[54]
Chaperone-Enriched E. coli Extracts	Expression Enhancement	Improving solubility of modification enzymes	Cell-free production of lanthipeptides	[16]
Riboflavin-5-Phosphate-13C4,15N2-1	Riboflavin-5-Phosphate-13C4,15N2-1, MF:C17H21N4O9P, MW:462.30 g/mol	Chemical Reagent	Bench Chemicals
Azido-PEG1-Val-Cit-PABC-PNP	Azido-PEG1-Val-Cit-PABC-PNP, MF:C30H39N9O10, MW:685.7 g/mol	Chemical Reagent	Bench Chemicals

Precursor peptide engineering through site-directed mutagenesis and leader-core fusion strategies represents a powerful and versatile approach for expanding the chemical diversity of RiPP natural products. The protocols outlined in this application note provide researchers with practical methodologies for generating and screening engineered RiPP variants, from targeted single mutations to comprehensive leader-core fusions. When combined with emerging technologies like cell-free biosynthesis and computational design tools, these strategies enable the rapid exploration of RiPP sequence-function relationships and the development of novel peptides with enhanced therapeutic potential. As our understanding of leader peptide recognition and enzyme specificity continues to grow, so too will the precision and sophistication of RiPP engineering platforms.

Application Notes

Ribosomally synthesized and post-translationally modified peptides (RiPPs) represent a rapidly expanding family of natural products characterized by their genetically encoded precursor peptides and extensive enzymatic tailoring [55]. This biosynthetic logic makes RiPP pathways exceptionally amenable to engineering for generating non-natural analogues and hybrid molecules. The exploitation of enzyme promiscuity—the ability of enzymes to accept non-native substrates—serves as the fundamental principle enabling the creation of structurally diverse peptide libraries with potential applications in drug discovery and basic research [56]. This document outlines standardized protocols and application notes for harnessing RiPP biosynthetic enzymes to produce novel peptide analogues and hybrids, providing a framework for researchers working at the intersection of chemical biology and natural product discovery.

Key Enzymatic Tools and Their Applications

Table 1: Promiscuous RiPP Enzymes for Peptide Engineering

Enzyme	Source Pathway	Reaction Catalyzed	Substrate Tolerance	Key Applications	Limitations
PatA Protease	Cyanobactin (Patellamide)	N-terminal leader peptide cleavage	Broad tolerance to N-methylated residues [57]	Liberation of modified core peptides	Requires conserved GVDAS recognition sequence
PsnB Macrocyclase	Plesiocin	Side-chain to side-chain macrolactone formation	Accepts synthetic N-methylated peptides [57]	Cyclization of constrained peptides	Requires Thr-Glu/Asp recognition for lactonization
PCY1 Macrocyclase	Orbitide	Head-to-tail macrocyclization	Tolerates single amide methyl group [57]	Backbone cyclization of peptides	May require optimization for multiple N-methylations
SpyB/C/D Complex	Streptamidine/Pyrimidone	Pyrimidone ring formation from Asn	Novel nucleobase formation on peptide [55]	Peptide-nucleobase hybrid generation	Requires specific His residue in substrate
OphMA Methyltransferase	Omphalotin	Backbone Nα-methylation	Narrow substrate range; auto-methylation [57]	Installation of N-methyl groups	Limited promiscuity; requires engineering

The strategic application of these enzymes enables the modular construction of complex peptide architectures. For instance, the combination of OphMA-mediated N-methylation with PatA cleavage and PsnB or PCY1 macrocyclization provides a route to generate N-methylated cyclic peptides, which often exhibit improved membrane permeability and metabolic stability [57]. Similarly, the recently discovered pyrimidone-forming enzymes (SpyB/C/D) enable the creation of unprecedented peptide-nucleobase hybrids, expanding the chemical space accessible through RiPP engineering [55].

Quantitative Analysis of Enzyme Performance with Modified Substrates

Table 2: Enzymatic Efficiency with Natural and Non-Natural Substrates

Enzyme	Substrate Type	Reaction Conditions	Conversion Yield	Key Structural Determinants
PatA Protease	Unmethylated peptide (GFPGVDAS/TVAT)	Standard buffer, overnight, 37°C	65% [57]	GVDAS recognition sequence
PatA Protease	N-methylated peptide (GFPGVDAS/TVAT)	Standard buffer, overnight, 37°C	32% [57]	GVDAS recognition sequence with steric hindrance
PsnB Macrocyclase	Unmethylated linear peptide	ATP, Mg2+, 37°C	~80% (estimated) [57]	TTxxxxEE recognition motif
PsnB Macrocyclase	N-methylated linear peptide	ATP, Mg2+, 37°C	~60% (estimated) [57]	Tolerant to backbone modification
SpyB/C/D Complex	Native SpyA precursor	In vivo co-expression in E. coli	Complete conversion [55]	Conserved His for substrate-assisted catalysis
YcaO-DHF Enzymes	Thuricin CD precursor	In vivo pathway expression	Unexpected cleavage side-reactions [58]	Context-dependent functionality

Experimental Protocols

Protocol 1: Computational Identification and Design of Hybrid RiPP Gene Clusters

Purpose

To bioinformatically identify candidate RiPP biosynthetic gene clusters (BGCs) with potential for engineering novel hybrid natural products through enzyme promiscuity.

Materials and Reagents

• Genomic Databases: National Center for Biotechnology Information (NCBI), Joint Genome Institute (JGI)
• Analysis Tools: AntiSMASH, BLAST, Clustal Omega, RODEO
• Computational Resources: Workstation with minimum 16GB RAM, multi-core processor

Procedure

• Database Mining: Identify putative RiPP BGCs using AntiSMASH with relaxed search parameters to detect atypical arrangements [59].
• Hybrid Cluster Identification: Screen for co-localization of RiPP genes with biosynthetic machinery from other natural product families (e.g., fatty acid synthesis, polyketide synthesis) [59].
• Sequence Analysis: Perform multiple sequence alignments of precursor peptides to identify conserved recognition sequences and variable core regions [55].
• Phylogenetic Analysis: Construct phylogenetic trees for key biosynthetic enzymes (e.g., YcaO proteins) to identify divergent clades with potential novel functions [55].
• Recognition Sequence Mapping: Identify and catalog enzyme recognition elements (RRE binding sites, protease recognition sequences) within precursor peptides [57] [55].
• Precursor Design: Design hybrid precursor peptides by combining recognition sequences from multiple pathways with variable core regions of interest [56].

Expected Results

Identification of candidate hybrid BGCs (e.g., lipoavitide-type RiPP-fatty acid hybrids) [59] and design of non-natural precursor peptides amenable to modification by promiscuous RiPP enzymes.

Protocol 2: Heterologous Expression of Engineered RiPP Pathways

Purpose

To clone and express engineered RiPP pathways in heterologous hosts (E. coli) for production of novel peptide analogues and hybrids.

Materials and Reagents

• Cloning System: CAPTURE cloning system [59], Gibson Assembly reagents [60], Golden Gate Assembly system
• Expression Host: E. coli BL21(DE3) or similar expression strain
• Growth Media: LB broth, Terrific Broth, appropriate antibiotics
• Induction Reagents: IPTG, autoinduction media supplements

Procedure

• DNA Assembly: Clone identified gene clusters into expression vectors using CAPTURE cloning [59] or Gibson Assembly [60].
• Precursor Engineering: Modify precursor peptide genes to incorporate desired recognition sequences and variable core regions using site-directed mutagenesis or synthetic gene construction.
• Co-expression Testing: Transform modification enzymes and engineered precursor peptides into expression host, testing both sequential and simultaneous expression strategies.
• Culture Conditions: Inoculate primary cultures in LB medium with appropriate antibiotics, grow overnight at 30°C with shaking.
• Pathway Induction: Dilute cultures to OD600 = 0.6-0.8, induce with 0.1-1.0 mM IPTG, and continue incubation for 16-24 hours at 16-25°C.
• Metabolite Extraction: Harvest cells by centrifugation, lyse using sonication or chemical methods, and extract peptides with methanol:water:formic acid mixtures.

Expected Results

Successful production of modified peptide intermediates and final products, detectable by LC-MS analysis. Typical yields for modified peptides range from 0.1-10 mg/L culture depending on the pathway efficiency [55].

Protocol 3: In Vitro Characterization of RiPP Enzyme Promiscuity

Purpose

To quantitatively evaluate the substrate promiscuity of RiPP biosynthetic enzymes using synthetic peptide substrates.

Materials and Reagents

• Synthetic Peptides: SPPS-generated peptides (1-5 mg) incorporating desired modifications (N-methylation, non-proteinogenic amino acids) [57]
• Enzyme Preparation: Purified recombinant enzymes (PatA, PsnB, PCY1, etc.)
• Reaction Buffers: Tris-HCl or HEPES buffer (50 mM, pH 7.0-8.5), MgClâ‚‚ (5-10 mM), ATP (2-5 mM for ATP-dependent enzymes)
• Analytical Instruments: HPLC with C18 column, LC-MS system, MALDI-TOF MS

Procedure

• Enzyme Purification: Express and purify RiPP modification enzymes as His-tagged fusion proteins using nickel affinity chromatography.
• Substrate Design: Design and synthesize peptide substrates containing appropriate recognition sequences and desired modifications (e.g., N-methylated residues) [57].
• Reaction Setup: Combine enzyme (1-10 µM), substrate (50-500 µM), and necessary cofactors in appropriate buffer.
• Time Course Analysis: Incubate at 30-37°C, removing aliquots at predetermined time points (0, 15, 30, 60, 120, 240 min).
• Reaction Quenching: Terminate reactions by addition of trifluoroacetic acid (0.1% final) or heat inactivation.
• Product Analysis: Analyze samples by LC-MS to quantify conversion yields and identify products.
• Kinetic Parameter Determination: Calculate apparent kinetic parameters (kcat, KM) from time course data at varying substrate concentrations.

Expected Results

Quantitative assessment of enzyme activity with non-natural substrates. For example, PatA maintains 32-65% activity with N-methylated substrates compared to unmethylated controls [57].

Protocol 4: Generation and Screening of RiPP Analogue Libraries

Purpose

To create diverse libraries of RiPP analogues and identify variants with enhanced bioactivity.

Materials and Reagents

• Library Construction: Oligonucleotide pools for degenerate core peptide regions, Golden Gate Assembly components [60]
• Screening Host: E. coli expression strain compatible with antimicrobial screening
• Bioassay Materials: ESKAPE pathogen panels [60], Bacillus subtilis indicator strain [60], growth media for antimicrobial assays
• Analytical Tools: LC-MS for hit validation, HPLC for compound purification

Procedure

• Library Design: Design precursor peptide libraries with degenerate core regions while maintaining essential recognition sequences.
• Pathway Assembly: Clone library variants into expression vectors using high-efficiency assembly methods (Golden Gate or Gibson Assembly) [60].
• Library Expression: Express library in production host under optimized conditions.
• Bioactivity Screening: Test culture extracts for antimicrobial activity against ESKAPE pathogens using drop spot or disc diffusion assays [60].
• Hit Validation: Re-test active samples, quantify activity (MIC determination), and identify the active compound through LC-MS/MS.
• Structure Elucidation: Purify active compounds using preparative HPLC and characterize structure using NMR and high-resolution MS.

Expected Results

Identification of novel RiPP analogues with enhanced or altered bioactivity profiles. Typical success rates range from 0.1-5% of library variants showing interesting bioactivity.

The Scientist's Toolkit

Table 3: Essential Research Reagents and Solutions for RiPP Engineering

Category	Item	Specification	Application	Key Considerations
Cloning Tools	CAPTURE System	Cas12a-assisted cloning	Hybrid cluster capture [59]	Efficient for large gene clusters
	Golden Gate Assembly	Type IIS restriction enzymes	Library construction [60]	Modular and scalable
	Gibson Assembly	Exonuclease, polymerase, ligase	Pathway construction [60]	Seamless and efficient
Expression Systems	E. coli BL21(DE3)	T7 RNA polymerase expression	Heterologous production [60]	High yield, well-characterized
	Interchangeable Leader Peptides (ILP)	Modular recognition sequences	Mix-and-match pathway engineering [56]	Enables pathway hybridization
Analytical Tools	LC-MS System	High-resolution mass spectrometer	Modification verification [57] [55]	Essential for PTM detection
	MALDI-TOF MS	Matrix-assisted laser desorption	Rapid screening of modifications [55]	High-throughput capability
Enzyme Resources	PatA Protease	Cyanobactin N-terminal protease	Leader peptide cleavage [57]	Tolerant to N-methylation
	PsnB Macrocyclase	ATP-grasp ligase	Side-chain cyclization [57]	Compatible with solid-phase synthesis
	PCY1 Macrocyclase	Serine protease	Head-to-tail cyclization [57]	Broad substrate tolerance
	YcaO Enzymes	Heterocomplex with RRE/DHF	Diverse backbone modifications [55]	Novel chemistry (e.g., pyrimidone)

Workflow Integration and Optimization

The successful implementation of RiPP engineering strategies requires careful integration of these protocols into a cohesive workflow. Begin with comprehensive bioinformatic analysis (Protocol 1) to identify the most promising enzyme candidates and design appropriate precursor peptides. Move to heterologous expression (Protocol 2) to validate pathway functionality, then characterize individual enzyme components in vitro (Protocol 3) to establish substrate scope and limitations. Finally, implement library generation and screening approaches (Protocol 4) to identify novel bioactive compounds.

Throughout this process, maintain rigorous analytical validation using LC-MS and other appropriate techniques to confirm structural features and quantify yields. Note that enzyme promiscuity can sometimes lead to unexpected results, as recent studies have revealed unforeseen cleavage side-reactions and context-dependent enzyme functionalities in RiPP pathways [58]. These observations highlight the importance of detailed biochemical characterization as a prerequisite for successful engineering applications.

Overcoming RiPP Engineering Hurdles: Silent Clusters, Enzyme Specificity, and Production Challenges

The genomic era has revealed a vast untapped resource for natural product discovery: silent (or cryptic) biosynthetic gene clusters (BGCs). These clusters encode the potential for novel bioactive compounds but are not expressed under standard laboratory conditions [61]. This is particularly relevant for Ribosomally synthesized and post-translationally modified peptides (RiPPs), a major class of natural products with diverse therapeutic applications [62]. Unlocking these silent clusters is essential for expanding the pipeline of new drugs, especially amid rising antibiotic resistance [63]. Two powerful, complementary strategies for activating these silent genetic treasures are microbial co-culture, which mimics ecological interactions to trigger natural product synthesis, and genetic refactoring, which involves the rational redesign and reconstruction of BGCs for heterologous expression [62]. This application note provides detailed protocols and frameworks for implementing these strategies within RiPP-focused peptide engineering research.

Microbial Co-culture: Protocol for Activation via Interspecies Interaction

Microbial co-culture leverages the natural communications and competitive interactions between different microorganisms to activate silent BGCs. This approach is physiologically driven, often leading to the production of novel secondary metabolites that are not observed in axenic cultures [63].

Experimental Workflow for Bacteria-Fungi Co-culture

The following workflow, also depicted in Figure 1, outlines a standardized method for conducting a bacteria-fungi co-culture experiment to activate silent fungal BGCs.

Diagram Title: Co-culture Experimental Workflow

Figure 1: A generalized workflow for a microbial co-culture experiment aimed at activating silent biosynthetic gene clusters.

Detailed Methodology

Materials:

• Microbial Strains: A bacterial strain (e.g., Streptomyces rapamycinicus) and a fungal strain (e.g., Aspergillus nidulans) [63].
• Growth Media: Suitable solid media such as AMM (Aspergillus Minimal Medium) or DNM (DNase agar) [63].
• Equipment: Sterile Petri dishes, incubator, biological safety cabinet, extraction solvents (e.g., ethyl acetate), and analytical instrumentation (LC-MS).

Procedure:

• Pre-culturing: Grow the bacterial and fungal strains independently in liquid media optimal for each for 24-48 hours.
• Co-inoculation: On a solid agar plate, inoculate the fungal strain first. Subsequently, inoculate the bacterial strain at a defined distance (e.g., 1-2 cm) from the fungal inoculum. This setup allows for a zone of interaction to develop as the microbes grow towards each other [63].
• Incubation: Incubate the co-culture plates at a temperature suitable for both organisms (e.g., 20-28°C) for an extended period, typically from 3 days up to 3 weeks. This allows time for interspecies communication and metabolic exchange.
• Metabolite Extraction: Once a clear interaction zone is observed (e.g., changes in pigmentation or morphology), harvest the entire mycelium and agar from the interaction zone. Extract metabolites using an organic solvent like ethyl acetate. Concentrate the extract under reduced pressure.
• Analysis and Identification:
  • LC-MS Profiling: Analyze the co-culture extract alongside extracts from mono-cultures of the bacterium and fungus grown under identical conditions.
  • Dereplication: Use mass spectrometry data to identify chromatographic peaks present in the co-culture but absent in the mono-cultures, indicating potentially novel metabolites.
  • Scale-up and Purification: For promising compounds, scale up the co-culture to obtain sufficient material for purification and structural elucidation via NMR spectroscopy.

Research Reagent Solutions for Co-culture

Table 1: Essential reagents and materials for microbial co-culture experiments.

Item	Function/Application	Example/Description
Actinobacterial Strains	Co-culture partner known to trigger SM production in fungi.	Streptomyces rapamycinicus, S. lividans [63].
Fungal Strains	Target organism with silent/cryptic BGCs.	Aspergillus nidulans, A. fumigatus [63].
Solid Co-culture Media	Provides a surface for microbial interaction and metabolite exchange.	Aspergillus Minimal Medium (AMM), DNase agar (DNM) [63].
Ethyl Acetate	Organic solvent for broad-spectrum extraction of secondary metabolites from agar.	Used for metabolite extraction from the interaction zone [63].
LC-HRMS System	High-resolution metabolomic profiling and dereplication of extracts.	Used to compare co-culture vs. mono-culture metabolite profiles [62].

Genetic Refactoring: Protocol for Heterologous Expression of RiPPs

Genetic refactoring involves the complete redesign and synthesis of a silent BGC to optimize its expression in a heterologous host. This strategy circumvents native regulatory constraints and simplifies the genetic architecture for reliable production [62].

Experimental Workflow for RiPP Refactoring

The process of refactoring a RiPP BGC for expression in a model host like E. coli involves a multi-stage workflow, as illustrated in Figure 2.

Diagram Title: RiPP Refactoring Workflow

Figure 2: A standard workflow for the genetic refactoring and heterologous expression of a silent RiPP biosynthetic gene cluster.

Detailed Methodology

Materials:

• Bioinformatics Tools: AntiSMASH [62], RODEO [62] [64], RRE-Finder [64].
• Heterologous Host: Escherichia coli BL21(DE3) or Streptomyces spp. (e.g., S. coelicolor) [62].
• Molecular Biology Reagents: Synthesis service for the refactored cluster, expression vectors (e.g., pET series for E. coli), Gibson assembly or Golden Gate assembly reagents, and transformation equipment.

Procedure:

• BGC Identification:
  • Use genome mining tools like AntiSMASH to identify a silent RiPP BGC of interest.
  • Utilize class-independent tools like RRE-Finder to identify BGCs based on the presence of a RiPP Recognition Element (RRE), which is common in many prokaryotic RiPP classes [64].
  • Use RODEO to analyze the cluster for precursor peptides and co-occurring biosynthetic genes [64].
• In Silico Refactoring:
  • Remove Native Regulation: Delete any native, potentially complex regulatory elements.
  • Codon Optimization: Optimize the coding sequences of all genes in the cluster for the chosen heterologous host to improve translation efficiency.
  • Standardize Genetic Parts: Replace native promoters and ribosome binding sites (RBS) with well-characterized, inducible counterparts (e.g., T7/lac promoter for E. coli). This modular design ensures predictable and strong expression.
• Synthesis and Cloning:
  • The refactored DNA sequence is chemically synthesized de novo.
  • The synthesized cluster is assembled into a suitable expression vector using advanced cloning techniques like Golden Gate assembly, which is ideal for handling multiple genetic parts.
• Heterologous Expression and Screening:
  • Introduce the expression construct into the heterologous host via transformation.
  • Induce expression of the refactored BGC under optimized conditions (e.g., with IPTG for T7-based systems in E. coli).
  • Screen for successful RiPP production using LC-MS to detect the expected mass of the mature peptide and analytical methods like tandem MS to confirm post-translational modifications [62].

Research Reagent Solutions for Genetic Refactoring

Table 2: Key reagents, tools, and hosts for the genetic refactoring of RiPP BGCs.

Item	Function/Application	Example/Description
Bioinformatics Tools	In silico identification and analysis of RiPP BGCs.	AntiSMASH, RODEO, RRE-Finder [62] [64].
Heterologous Hosts	Production chassis for refactored gene clusters.	Escherichia coli [62], Streptomyces species [62].
Standardized Genetic Parts	Modular promoters, RBS, and terminators for predictable expression.	T7/lac promoter, strong E. coli RBS [62].
Assembly System	Cloning methodology for multi-gene constructs.	Golden Gate assembly [62].
Analytical MS	Detection and structural confirmation of produced RiPPs.	LC-MS/MS for mass determination and PTM analysis [62].

The strategic choice between co-culture and genetic refactoring depends on the research goals. Co-culture is a powerful, unbiased method for discovering novel metabolites and understanding ecological interactions, making it ideal for initial discovery phases [63]. Genetic refactoring provides a more controlled, scalable, and engineerable system for robust production and detailed mechanistic studies of a specific BGC, which is crucial for applied peptide engineering [62].

For a targeted RiPP engineering project, these strategies can be combined: a silent RiPP BGC first discovered and activated via co-culture can subsequently be refactored for high-yield, reproducible production in a heterologous host. This integrated approach maximizes the potential of microbial genomes to yield new and therapeutic peptides, effectively bridging the gap between natural product discovery and biotechnological application.

Ribosomally synthesized and post-translationally modified peptides (RiPPs) represent a promising class of natural products for drug development due to their diverse bioactivities and genetically encodable scaffolds. A significant challenge in harnessing these pathways for peptide engineering lies in the inherent enzyme-substrate specificity of RiPP biosynthetic enzymes, which must precisely recognize their precursor peptides among the thousands of other cellular proteins. This specificity is largely mediated by a conserved structural domain known as the RiPP Recognition Element (RRE), a ~90-residue domain that facilitates binding between precursor peptides and their modifying enzymes [65]. The RRE solves a fundamental paradox in RiPP biosynthesis: how enzymes can exhibit strict specificity for their native substrates while displaying remarkable promiscuity toward the core peptide regions that become the final bioactive products [66]. This application note details practical strategies for leveraging RRE domains and chimeric enzyme design to overcome specificity barriers, enabling the production of novel peptide therapeutics with customized modifications.

Core Concepts: RRE Domains as Specificity Mediators

RRE Prevalence and Functional Role

The RRE domain is structurally homologous to PqqD, a peptide chaperone in pyrroloquinoline quinone biosynthesis, and has been identified in over half of all known prokaryotic RiPP classes [65]. These domains function as essential recognition modules that bind specifically to leader peptide regions of precursor peptides, typically through interactions with short, conserved recognition sequences such as the FNLD motif in lanthipeptides or the YxxP motif in lasso peptides [67]. In radical SAM enzymes such as those found in ranthipeptide pathways, the RRE domain is frequently fused to the catalytic enzyme, as observed with PapB, where deletion of the RRE results in complete loss of function that can only be restored by supplying the RRE in trans [68]. Structural studies of enzymes like SuiB have revealed that while RRE domains facilitate initial engagement, the leader peptide ultimately binds within the catalytic barrel, positioning the core peptide for modification [69].

Quantitative Analysis of RRE-Dependent Processing

Table 1: Experimental Validation of RRE Dependence Across RiPP Classes

RiPP Class	Modifying Enzyme	RRE Dependency	Key Experimental Evidence
Ranthipeptides	PapB	Essential	RRE deletion causes complete loss of function; activity restored with RRE in trans [68]
Lanthipeptides	NisB/C	Essential	Leader peptide binding via RRE necessary for dehydration and cyclization [66]
Sactipeptides	AlbA	Essential	RRE domain required for radical SAM-mediated thioether formation [66] [65]
Lasso Peptides	Specific cyclases	Essential	RRE mediates recognition prior to cyclization [65]
Linear Azole-Containing Peptides	BalhC/D	Essential	RRE in C protein guides peptide to active site [65]

Methodological Approaches: Engineering Solutions

Chimeric Leader Peptide Design Strategy

The chimeric leader peptide approach represents a powerful method for redirecting enzyme specificity by concatenating recognition sequences (RS) from multiple RiPP pathways into a single leader peptide [66]. This design creates a multifunctional leader that can recruit enzymes from unrelated RiPP classes to modify a single core peptide. The experimental workflow involves:

• Identification of Recognition Sequences: Determine essential RS motifs within native leader peptides through sequence alignment and mutational analysis. For example, the NisA leader contains critical residues between positions -22 and -1 for NisB recognition [66].

• Strategic Concatenation: Fuse RS elements while maintaining appropriate spacing between each RS and its corresponding modification sites in the core peptide. The successful Hyp1.1 chimera incorporated the HcaA RS followed by the essential region of the NisA leader [66].

• Core Peptide Optimization: Engineer core regions with appropriate spacing between modification sites for different enzyme classes, typically including a "GGRCG" motif for thiazoline formation followed by lanthipeptide core sequences [66].

Table 2: Chimeric Leader Design Specifications for Hybrid RiPP Production

Design Parameter	Technical Considerations	Validated Examples
Recognition Sequence Selection	Conserved motifs essential for RRE binding (e.g., FNLD for lanthipeptides)	HcaA and NisA recognition sequences [66]
Linker Design	Maintain natural spacing between RS and core modification sites (typically 4-8 residues)	GGRCG motif positioned at appropriate distance from HcaA RS [66]
Core Region Engineering	Include substrate sequences for multiple enzyme classes with compatible spacing	Combination of thiazoline-forming and lanthipeptide core sequences [66]
Expression System	Co-expression with modifying enzymes in heterologous hosts (e.g., E. coli)	Plasmid-based expression in E. coli [66]

Experimental Protocol: Production of Thiazoline-Lanthipeptide Hybrids

Materials Required:

• E. coli BL21(DE3) or similar expression strain
• Expression plasmids for Hyp1.1 chimeric precursor peptide
• Plasmids for HcaD/F and NisB/C modifying enzymes
• Affinity chromatography resins (Ni-NTA for His-tagged proteins)
• Endoproteinase AspN for leader peptide removal
• MALDI-TOF MS for product analysis

Procedure:

• Construct Assembly: Clone the chimeric precursor peptide gene (e.g., Hyp1.1) into an appropriate expression vector, ensuring inclusion of a cleavable affinity tag.
• Co-expression: Transform E. coli with plasmids encoding the chimeric precursor and modifying enzymes (HcaD/F + NisB/C). Include appropriate antibiotic selection.
• Expression Induction: Grow cultures at 37°C to OD600 ≈ 0.6, then induce with 0.1-1.0 mM IPTG at 18-25°C for 16-20 hours.
• Purification: Harvest cells by centrifugation, lysate, and purify the modified precursor using affinity chromatography.
• Leader Removal: Digest with endoproteinase AspN (1:50 w/w enzyme:substrate) in appropriate buffer at 37°C for 4-6 hours.
• Product Analysis: Characterize by MALDI-TOF MS. For Hyp1.1, expect a mixture of products with the major species containing one thiazoline, two dehydrobutyrine (Dhb), one methyllanthionine (MeLan), and one lanthionine (Lan) [66].
• Verification: Confirm thiazoline formation by mild acid hydrolysis (gain of 18 Da) and thioether rings by iodoacetamide alkylation under reducing conditions [66].

Diagram 1: Chimeric leader strategy for hybrid RiPP production. Recognition sequences from different pathways enable single precursor to recruit multiple enzymes.

Research Reagent Solutions

Table 3: Essential Research Tools for RiPP Engineering Studies

Reagent/Tool	Specific Application	Function in Experimental Workflow
RODEO Bioinformatic Tool	RRE domain identification and RiPP BGC annotation	Predicts precursor peptides and identifies RRE-containing enzymes in genomic data [67]
Heterologous Expression Systems (e.g., E. coli)	Pathway reconstruction and engineering	Enables expression of RiPP pathways from unculturable organisms or engineered variants [68] [66]
MALDI-TOF Mass Spectrometry	Modification tracking and product verification	Monitors mass shifts corresponding to specific PTMs (e.g., -12 Da for thioether formation) [68]
Leader Peptide Binding Assays	RRE recognition specificity validation	Measures binding affinity between RRE domains and leader peptides (SPR, ITC, etc.) [65]
Radical SAM Reconstitution Systems	In vitro activity assays for rSAM enzymes	Provides controlled conditions for studying RRE-dependent enzymes (SAM, reductant) [68]

Advanced Engineering Framework

Diagram 2: Engineering framework for addressing enzyme-substrate specificity. Complementary strategies expand RiPP biosynthetic capabilities.

RRE-Centric Engineering Applications

RRE Swapping and Engineering: The modular nature of RRE domains enables their transplantation between enzyme systems to redirect specificity. Experimental evidence confirms that RRE domains maintain function when provided in trans, as demonstrated by the restoration of PapB activity when its RRE was supplied separately [68]. This approach allows researchers to:

• Create chimeric enzymes with novel specificities by fusing RRE domains from different pathways
• Develop modular RRE libraries for screening against target precursor peptides
• Engineer enhanced affinity RRE variants through directed evolution

Optimization Considerations: Successful implementation requires maintaining critical recognition residues while optimizing interfacial compatibility between fused domains. Structural studies indicate that leader peptides primarily contact the third alpha helix and third beta strand of the RRE [67], highlighting these as key regions for engineering efforts.

Technical Protocols: Practical Implementation

Protocol for Assessing RRE Dependence

Objective: Determine whether a putative RiPP-modifying enzyme requires its RRE domain for activity.

Procedure:

• Generate two constructs: (1) full-length enzyme and (2) RRE deletion variant (ΔRRE)
• Co-express each construct with the cognate precursor peptide in E. coli
• Purify precursor peptides via affinity chromatography (e.g., maltose-binding protein fusions)
• Analyze by MALDI-TOF MS for modification-specific mass shifts
• If ΔRRE shows no activity, co-express RRE domain in trans to test functional complementation

Expected Results: For PapB, RRE deletion abolished thioether formation, but activity was restored when the RRE was provided in trans [68].

Protocol for Hybrid RiPP Production

Objective: Produce a hybrid RiPP containing modifications from two different classes.

Procedure:

• Design chimeric precursor with RS elements from both pathways
• Engineer core peptide with modification sites for both enzyme classes
• Co-express chimeric precursor with both modifying enzymes
• Purify and analyze products by mass spectrometry
• Verify specific modifications through analytical treatments (e.g., acid hydrolysis for thiazolines)

Troubleshooting: Incompatibility issues may arise from competing for Cys residues; address by strategic spacing of modification sites or sequential expression strategies [66].

RRE domains and chimeric enzyme design represent complementary, powerful strategies for overcoming the inherent enzyme-substrate specificity limitations in RiPP engineering. By understanding the molecular basis of RRE-mediated recognition and applying rational design principles for chimeric leaders, researchers can significantly expand the biosynthetic landscape accessible for peptide-based therapeutic development. The protocols and approaches outlined herein provide a framework for designing and producing novel RiPP variants with customized modification patterns and enhanced bioactivities. As these engineering strategies continue to evolve, they promise to unlock the full potential of RiPP pathways for generating next-generation peptide therapeutics.

This application note provides a structured framework for optimizing post-translational modification (PTM) efficiency in ribosomally synthesized and post-translationally modified peptide (RiPP) biosynthesis. Focusing on the coordination of multi-enzyme complexes and strategic reaction order, we present experimental protocols and analytical methodologies to enhance the yield and fidelity of complex bioactive peptides. The strategies outlined herein enable researchers to overcome significant challenges in natural product engineering, particularly in activating silent biosynthetic gene clusters (BGCs) and optimizing modification sequences. By integrating machine learning prediction with high-throughput experimental validation, this guide supports accelerated development of novel peptide therapeutics with potential applications against antimicrobial resistance, cancer, and metabolic disorders.

RiPPs represent a diverse superfamily of natural products with immense potential for drug development, featuring complex structures generated through enzymatic modifications of ribosomal precursor peptides [4] [9]. The biosynthesis follows a conserved logic: a ribosomally synthesized precursor peptide typically containing an N-terminal leader peptide and a C-terminal core peptide is modified by specialized enzymes, after which the leader peptide is proteolytically removed to yield the mature product [4]. The core challenge in RiPP engineering lies in controlling the efficiency of multiple PTMs, as the order of enzymatic actions significantly impacts final product yield and bioactivity. Research indicates that enzyme-specific PTM patterns govern substrate recognition and modification kinetics, creating complex interdependencies that must be understood for effective pathway optimization [70] [71]. This document establishes standardized protocols for deciphering and optimizing these complex enzymatic networks to maximize RiPP production and engineer novel bioactive compounds.

Quantitative Data on PTM Prediction and Validation

Recent advances in machine learning (ML) have enabled more accurate prediction of enzyme-substrate relationships, providing critical data for planning modification sequences. The following table summarizes performance metrics for established PTM prediction methods:

Table 1: Performance Metrics of PTM Prediction Methods

Method	Application	Validation Rate	Key Performance Features
ML-hybrid ensemble models [70]	SET8 methyltransferase substrate prediction	37-43%	Marks important performance increase over traditional in vitro methods
Permutation array-based prediction [70]	SET8 methylation site identification	Low precision (26/346 hits validated)	Limited by inability to capture structural features
PeSA2.0 motif generation [70]	Enzyme recognition motif characterization	Normalized score cutoff >0.5	Identifies weighted AA preferences at each position
SCASP-PTM multi-enrichment [72]	Simultaneous PTM profiling (phosphorylation, ubiquitination, acetylation, glycosylation)	Desalting-free sequential enrichment	Streamlined workflow for comprehensive PTM analysis

The quantitative data demonstrates that ML-driven approaches significantly outperform conventional methods, providing more reliable substrate predictions for planning efficient modification sequences. The 37-43% validation rate for ML-hybrid models represents a substantial improvement in accurately identifying enzyme-specific PTM sites, enabling better planning of multi-enzyme reaction sequences [70].

Research Reagent Solutions for RiPP Engineering

The following table details essential research reagents and their applications in RiPP engineering and PTM optimization studies:

Table 2: Essential Research Reagents for RiPP Pathway Engineering

Reagent/Category	Function/Application	Specific Examples
Temporary Protecting Groups [73]	N-terminus protection during synthetic peptide production	Boc (tert-butoxycarbonyl), Fmoc (9-fluorenylmethoxycarbonyl)
Permanent Protecting Groups [73]	Side chain protection during peptide synthesis	Bzl (benzyl), tBu (tert-butyl) derivatives
Coupling Reagents [74] [73]	Activate carboxyl groups for peptide bond formation	DCC (dicyclohexylcarbodiimide), DIC (diisopropylcarbodiimide), HOBt (1-hydroxybenzotriazole)
Cell-Free Protein Synthesis Systems [75]	In vitro transcription/translation for pathway prototyping	E. coli extracts, yeast cell-free systems
Solid Supports [74] [73]	C-terminal protection and simplified purification in SPPS	Polystyrene, polyacrylamide resins
Cleavage Reagents [73]	Final deprotection after peptide synthesis	TFA (trifluoroacetic acid), HF (hydrogen fluoride)
RiPP Modification Enzymes [9]	Install complex PTMs on precursor peptides	Lanthipeptide dehydratases, cyclodehydratases, cytochrome P450 enzymes

Experimental Protocols

Machine Learning-Guided PTM Site Prediction

Purpose: To identify potential modification sites for specific enzymes to inform reaction order planning.

Background: ML-hybrid approaches combine high-throughput in vitro peptide array experiments with computational modeling to predict enzyme-substrate relationships with higher accuracy than traditional methods [70].

Procedure:

• Peptide Array Synthesis: Chemically synthesize a comprehensive peptide array representing the known modified methyl-lysine or acetyl-lysine proteome.
• Enzymatic Screening: Incubate arrays with active enzyme constructs (e.g., SET8_{193-352} for methyltransferases) under optimized reaction conditions.
• Activity Quantification: Measure modification activity at each peptide spot through relative densitometry or mass spectrometry.
• Motif Generation: Analyze results using motif-generating software (e.g., PeSA2.0) to determine amino acid preferences at each position.
• Model Training: Utilize experimental data to train ensemble ML models unique to each enzyme.
• Proteome Screening: Apply trained models to search entire proteomes for potential substrate sites.
• Validation: Confirm predicted sites through in vitro peptide array methylation assays and mass spectrometry.

Applications: This protocol successfully identified 64 unique deacetylation sites for SIRT2 and revealed changes in SET8-regulated substrate networks among breast cancer missense mutations [70].

Leader Peptide Engineering for Enzyme Recruitment

Purpose: To optimize enzyme recognition and modification efficiency through strategic leader peptide manipulation.

Background: Most RiPP tailoring enzymes contain RiPP precursor peptide recognition elements (RREs) that bind leader peptides, positioning catalytic domains to modify core peptide regions [9].

Procedure:

• Leader-Binding Analysis: Characterize RRE-binding specificity through alanine scanning or homolog screening.
• Chimeric Design: Create hybrid leader peptides by fusing recognition elements from different RiPP classes.
• Binding Assessment: Evaluate engineered leader peptide affinity for target enzymes using surface plasmon resonance or bacterial two-hybrid systems.
• Core Modification Testing: Co-express engineered leader-core peptides with modification enzymes to assess PTM efficiency.
• Iterative Optimization: Use high-throughput screening to select leader variants that maximize modification yield.
• In Vivo Validation: Test optimized constructs in heterologous expression hosts for functional RiPP production.

Applications: Leader peptide engineering has enabled production of hybrid, new-to-nature ribosomal natural products and improved modification efficiency across diverse RiPP classes [9].

Cell-Free Biosynthetic Pathway Prototyping

Purpose: To rapidly test multi-enzyme reaction orders and coordination without cellular constraints.

Background: Cell-free gene expression (CFE) systems provide a quasi-chemical bioreactor platform for rapid prototyping of natural product biosynthetic pathways, enabling precise control over enzyme and substrate concentrations [75].

Procedure:

• DNA Template Preparation: PCR-amplify or clone genes encoding RiPP precursor peptides and modification enzymes.
• Reaction Assembly: Combine DNA templates with cell-free extract (E. coli, Streptomyces, or specialized extracts), energy sources, amino acids, and necessary cofactors.
• Enzyme Order Screening: Systematically vary enzyme addition sequences and timing to identify optimal modification orders.
• Product Monitoring: Use mass spectrometry to track intermediate and final product formation over time.
• Cofactor Optimization: Adjust concentrations of essential cofactors (SAM for methylation, NAD+ for deacetylation) to maximize conversion.
• Kinetic Analysis: Calculate reaction rates and yields for different enzyme combinations and sequences.
• Scale-Up: Transfer optimized conditions to larger volume CFE reactions or cellular expression systems.

Applications: CFE technology has been successfully applied to characterize biosynthetic pathways for ribosomal peptides and engineer novel antimicrobial compounds [75].

Workflow Visualization

Diagram 1: RiPP PTM Optimization Workflow

Diagram 2: Enzyme Engineering Strategies

The strategic coordination of multi-enzyme complexes and optimization of reaction order represents a critical advancement in RiPP bioengineering. By integrating computational prediction with high-throughput experimental validation, researchers can systematically overcome the historical challenges of PTM efficiency in complex peptide synthesis. The methodologies outlined in this application note provide a structured framework for elucidating and optimizing enzyme-substrate relationships, enabling the production of novel bioactive compounds with enhanced therapeutic potential. As peptide-based therapeutics continue to gain prominence in addressing antimicrobial resistance, cancer, and metabolic disorders, these optimization strategies will play an increasingly vital role in accelerating drug discovery and development pipelines.

Within the field of peptide engineering, ribosomally synthesized and post-translationally modified peptides (RiPPs) represent a promising source of bioactive compounds due to their vast structural diversity and high target specificity [9] [10]. However, the structural characterization of modified peptides, particularly those obtained in low yields from biosynthetic pathways, presents significant analytical challenges. Determining the precise chemical structure, including the identity and location of post-translational modifications (PTMs), is essential for understanding structure-activity relationships and guiding the rational engineering of new analogs [9]. This application note details the synergistic use of Mass Spectrometry (MS) and Nuclear Magnetic Resonance (NMR) spectroscopy to overcome these hurdles, providing detailed protocols tailored for researchers in RiPP engineering and drug development.

Key Challenges in Characterizing Modified Peptides

The analysis of modified peptides from RiPP pathways is fraught with difficulties, which are compounded when sample quantities are limited. The table below summarizes the core challenges and their implications for structural biology.

Table 1: Key Challenges in the Structural Characterization of Modified RiPPs

Challenge	Impact on Structural Characterization
Low Abundance & Yield	Limits application of high-resolution techniques; necessitates highly sensitive methods [76].
Complex Post-Translational Modifications (PTMs)	Difficult to identify and locate using standard proteomics; requires targeted MS approaches and high-resolution NMR [77] [9].
Structural Dynamics & Compact Folds	Solution-state techniques like NMR are needed to capture dynamics, but suffer from low sensitivity with scarce samples [78].
Sample Purity & Integrity	Low yields increase the risk of sample loss during purification, potentially compromising final sample quality for NMR [79].

Integrated MS and NMR Workflow for Low-Yield Analysis

An integrated approach that leverages the complementary strengths of MS and NMR is the most effective strategy for characterizing challenging peptide targets. The following workflow is designed to maximize information gain from precious, low-yield samples.

Figure 1: An integrated MS and NMR workflow for determining the structure of modified peptides from low-yield sources. The pathway shows how the techniques inform one another sequentially.

Detailed Experimental Protocols

Mass Spectrometry for Sensitive Detection and PTM Mapping

Mass spectrometry provides unparalleled sensitivity for analyzing peptide mass, sequence, and PTMs, making it ideal for low-yield samples [77].

4.1.1 Protocol: Targeted Peptide Quantitation using Multiple-Reaction Monitoring (MRM)

This protocol is adapted from targeted proteomics approaches for precise and sensitive peptide measurement [77].

• Sample Preparation: Dissolve the purified, low-yield peptide in a volatile buffer compatible with ESI-MS (e.g., 0.1% formic acid in water). Avoid non-volatile salts.
• LC-MRM/MS Analysis:
  • Chromatography: Use nano-flow or capillary-flow LC to maximize sensitivity. Employ a reversed-phase C18 column with a shallow acetonitrile gradient for optimal peptide separation.
  • Mass Spectrometry: Utilize a triple quadrupole or Q-Trap mass spectrometer.
  • MRM Assay Development:
    • If the sequence is known, select proteotypic peptides unique to the target, ideally avoiding missed cleavage sites or residues prone to artifactual modifications [77].
    • For each target peptide, define the precursor ion m/z (Q1) and 3-5 characteristic fragment ions m/z (Q3). Prefer high-intensity y-ions.
    • Program the mass spectrometer to monitor these specific precursor-product ion transitions during the peptide's expected elution window.
• Data Analysis: Integrate the peak areas for the MRM transitions. The co-occurrence of multiple transitions at a consistent retention time confirms the identity and presence of the peptide with high specificity, enabling quantification even in complex mixtures [77].

4.1.2 Protocol: Peptide Sequencing and PTM Identification using MS/MS

• Data-Dependent Acquisition (DDA): Inject the sample and acquire full-scan MS spectra followed by MS/MS scans on the most intense ions.
• In-Source Decay (ISD) for Disulfide-Rich Peptides: For peptides with complex disulfide bonds, spot the sample with a matrix like 1,5-diaminonaphthalene (1,5-DAN). This facilitates disulfide reduction in the MALDI laser plume and enhances ISD fragmentation, which can help sequence native peptides [78].
• Data Analysis: Use database search engines (e.g., PEAKS, Byonic) to match MS/MS spectra against a protein sequence database, allowing for potential RiPP-related PTMs. De novo sequencing can be applied for novel peptides.

NMR Spectroscopy for Atomic-Level Resolution

NMR spectroscopy provides atomic-level information on peptide structure, dynamics, and PTMs in solution, and is considered a gold standard for such characterizations [80]. The following strategies are critical for low-yield scenarios.

4.2.1 Protocol: Optimizing NMR for Low-Concentration Peptides

• Sample Preparation for Maximum Sensitivity:
  • Concentrate the sample to the highest possible volume (ideally 30-150 µL) using a centrifugal concentrator.
  • Use a dedicated 1.7 mm or 3 mm NMR tube with a CryoProbe to maximize the filling factor and signal-to-noise ratio [80].
  • Prepare the sample in a deuterated buffer (e.g., 90% Hâ‚‚O/10% Dâ‚‚O) with a minimal amount of necessary salts.
• Data Acquisition:
  • Use a high-field NMR spectrometer (≥ 600 MHz) equipped with a cryogenically cooled probe to enhance sensitivity [80].
  • For initial analysis, collect a ¹H-¹⁵N Heteronuclear Single Quantum Coherence (HSQC) spectrum as a fingerprint.
  • Collect a suite of 2D experiments including TOCSY (for through-bond correlations within spin systems) and NOESY (for through-space correlations essential for 3D structure) with sufficient transients to achieve an adequate signal-to-noise ratio [78].
• Data Processing and Analysis: Process data with exponential line-broadening and zero-filling. Use NMR-specific software (e.g., NMRFAM-SPARKY, CCPNmr) for peak picking, assignment, and analysis.

4.2.2 Protocol: NMRseq for Sequence Tag Determination

This protocol allows for the non-destructive determination of sequence tags, which can be used for database searching to identify the full peptide sequence [78].

• Blinded NMR Analysis: Without prior knowledge of the sequence, analyze 2D TOCSY and COSY spectra to identify individual amino acid spin systems based on their characteristic side-chain coupling patterns (e.g., Val, Ile, Leu, Arg, Pro) [78].
• Sequential Walk: Use the 2D NOESY spectrum to identify sequential NOE connectivities (dαN(i, i+1)) between the amide proton of residue i+1 and the alpha proton of residue i. This establishes the order of the previously identified spin systems [78].
• Sequence Tag Generation: Construct a sequence tag of 5-12 residues, where some residues are specifically identified (e.g., VAL, ARG) and others are designated as ambiguous "AMX" spin systems (e.g., Cys, Ser, Asn) [78].
• Database Search: Use this sequence tag to search specialized databases (e.g., ConoServer for conotoxins) or general protein databases to identify the full-length peptide sequence and its modifications [78].

Research Reagent and Material Solutions

The following table lists key reagents and materials essential for successfully executing the protocols described above.

Table 2: Essential Research Reagents and Materials for Characterizing Modified Peptides

Item	Function/Application	Specifications & Notes
Stable Isotope-Labeled Amino Acids (e.g., ¹⁵N-Ala, ¹³C₆/¹⁵N-Val) [79]	Selective isotopic labeling for NMR; simplifies spectra and facilitates assignment in sparse labeling strategies.	> 98% isotopic purity; controls metabolic scrambling in expression hosts.
NMR CryoProbe [80]	Enhances NMR sensitivity for low-yield samples.	1.7 mm or 3 mm configuration for small volume samples; provides significant signal-to-noise improvement.
Specialized MS Matrices (e.g., 1,5-Diaminonaphthalene) [78]	Facilitates sequencing of native, disulfide-rich peptides by MALDI-ISD MS.	Enables reduction in the laser plume and promotes in-source decay fragmentation.
Fmoc-protected PTM Amino Acids [81]	Chemical synthesis of phospho-, acetyl-, or methyl-peptides for use as analytical standards.	Enables orthogonal protection strategies during Solid-Phase Peptide Synthesis (SPPS).
Deuterated NMR Solvents (e.g., Dâ‚‚O) [79]	Solvent for NMR spectroscopy; provides lock signal.	99.9% D or higher; essential for all NMR experiments.

The structural elucidation of modified peptides from RiPP pathways, especially those produced in low yields, demands a carefully orchestrated, multi-technique approach. By integrating the high sensitivity and PTM-screening capabilities of mass spectrometry with the atomic-resolution and solution-state structural details provided by advanced NMR, researchers can overcome these significant analytical challenges. The detailed protocols and workflows outlined here provide a actionable roadmap for RiPP engineers and drug development scientists to confidently characterize and validate complex peptide structures, thereby accelerating the development of next-generation peptide therapeutics.

Ribosomally synthesized and post-translationally modified peptides (RiPPs) represent a promising class of natural products for drug development due to their structural diversity and potent bioactivities. Among these, the two-component sactibiotic thuricin CD has attracted significant research attention for its narrow-spectrum activity against clinically relevant pathogens like Clostridioides difficile. Thuricin CD consists of two peptides, Trnα and Trnβ, which undergo extensive post-translational modification to form characteristic sulfur-to-α-carbon thioether crosslinks. For over a decade, the biosynthetic mechanism underlying these modifications remained elusive, with the prevailing assumption that the two radical S-adenosylmethionine (rSAM) enzymes in the cluster, TrnC and TrnD, independently modified separate precursor peptides. Recent groundbreaking research has overturned this paradigm, revealing a complex synergistic relationship between TrnC and TrnD that challenges conventional understanding of RiPP biosynthetic pathways. This application note examines the unconventional enzyme cooperation in thuricin CD biosynthesis and its implications for peptide engineering research.

Unconventional Synergy in Sactibiotic Biosynthesis

Paradigm-Shifting Mechanism of Thioether Crosslinking

The biosynthetic gene cluster for thuricin CD encodes two radical SAM enzymes (TrnC and TrnD) and two precursor peptides (TrnA and TrnB). Previous models assumed independent functionality, where each enzyme would specifically modify one precursor peptide. However, recent investigations demonstrate that neither TrnC nor TrnD can effectively install thioether crosslinks on the precursor peptides individually [82]. Instead, these enzymes form a tight complex and collaboratively catalyze thioether crosslinking on both TrnA and TrnB [82] [83].

This cooperative mechanism represents a significant departure from the biosynthetic strategies observed in related two-component lanthipeptides, where modification enzymes typically work independently on their respective substrate peptides. Even more surprisingly, despite both TrnC and TrnD being active rSAM enzymes, only the rSAM activity of TrnC is strictly essential for thioether crosslinking [82]. This finding indicates an asymmetric functional relationship within the complex, suggesting TrnD may play a structural or regulatory role that enhances or enables TrnC's catalytic function.

Table 1: Key Experimental Findings in Thuricin CD Biosynthesis

Experimental Approach	Key Finding	Implication
Individual coexpression of TrnA with TrnC or TrnD	No thioether crosslinks formed	Neither enzyme functions independently on precursor peptides
Coexpression of TrnA with both TrnC and TrnD	−6 Da modification (three thioether crosslinks)	Collaborative enzyme action required for modification
Coexpression of TrnB with both TrnC and TrnD	−6 Da modification (three thioether crosslinks)	Complex modifies both precursor peptides
In vitro reconstitution	TrnC and TrnD form tight complex	Physical interaction enables functional cooperation
Activity assessment	Only TrnC's rSAM activity essential	Functional asymmetry within enzyme complex

Experimental Evidence for Enzyme Collaboration

The collaborative model emerged from systematic coexpression studies in E. coli. When TrnA was coexpressed individually with TrnC or TrnD, high-resolution LC-MS analysis detected no modifications on the precursor peptide [82]. However, when TrnA was coexpressed with both TrnC and TrnD, the resulting peptide exhibited a −6 Da mass shift corresponding to the formation of three thioether crosslinks [82]. Parallel experiments with TrnB yielded identical results, confirming that both precursor peptides require the collaborative action of both enzymes for proper modification.

The functional product was confirmed through bioactivity testing against Bacillus cereus. The modified peptides (trnα′ and trnβ′) showed potent antibacterial activity only when combined, with a minimal inhibitory concentration of 3.1 μM, while individually exhibiting no inhibition even at 50 μM [82]. This demonstrates that the synergistically modified peptides retain the characteristic bioactivity of natural thuricin CD.

Table 2: Enzyme Characteristics and Metallocluster Composition

Enzyme	Iron Content (mol/mol protein)	Sulfur Content (mol/mol protein)	Essential for Catalysis	Proposed Role
TrnC	11.3-11.6	10.5-10.9	Yes	Primary catalytic enzyme
TrnD	9.1-9.4	8.2-8.6	No (structural)	Complex stabilization, substrate positioning

Research Reagent Solutions

Table 3: Essential Research Reagents for Thuricin CD Biosynthesis Studies

Reagent	Function/Application	Key Features
N-terminal TF-fused TrnA/TrnB	Precursor peptide production	Enhances solubility and expression in E. coli; removable by HRV-3C protease
6× His-tagged TrnC/TrnD	Enzyme purification	Enables anaerobic purification via Ni-NTA chromatography
Recombinant HRV-3C protease	Leader peptide removal	Cleaves trigger factor fusion to yield mature precursor peptides
TCEP (tris(2-carboxyethyl)phosphine)	Disulfide bond reduction	Reduces disulfide bonds in precursor peptides without interfering with thioether bonds
N-ethylmaleimide (NEM)	Cysteine derivatization	Confirms free cysteine residues in unmodified peptides
GluC endoprotease	Leader peptide removal	Generates mature-like peptides (trnα′ and trnβ′) for activity assays
S-adenosylmethionine (SAM)	Cofactor for rSAM enzymes	Essential for radical generation and thioether bond formation
Dithionite	Chemical reductant	Provides electrons for rSAM cluster reduction in in vitro assays

Experimental Protocols

Precursor Peptide Production inE. coli

Objective: Recombinant production of unmodified precursor peptides TrnA and TrnB.

Methodology:

• Clone TrnA and TrnB genes as N-terminal fusions with trigger factor (TF) into appropriate expression vectors
• Transform into E. coli expression strains and culture in LB medium at 37°C
• Induce expression with 0.1-0.5 mM IPTG at mid-log phase (OD600 ≈ 0.6-0.8)
• Incubate post-induction for 16-18 hours at 18°C with vigorous aeration
• Harvest cells by centrifugation and lyse using French press or sonication
• Purify fusion proteins by immobilized metal affinity chromatography (Ni-NTA)
• Cleave TF fusion using recombinant human rhinovirus HRV-3C protease
• Separate cleaved peptides from TF using heat denaturation or methanol precipitation
• Verify peptide identity and purity by LC-MS [82]

Key Considerations:

• Direct expression of TrnA/TrnB with 6× His tags typically fails due to proteolytic degradation or poor expression
• The −2 Da mass shift observed in initial preparations typically indicates disulfide bond formation
• Confirm complete reduction using TCEP treatment, followed by NEM derivatization to verify free cysteines

In Vivo Coexpression and Modification Analysis

Objective: Assess TrnC and TrnD activity on precursor peptides in vivo.

Methodology:

• Coexpress TrnA or TrnB with TrnC, TrnD, or both enzymes in E. coli
• Culture cells and induce expression as described in Protocol 4.1
• Purify peptides using the TF fusion system
• Reduce peptides with TCEP (1-5 mM, 30 min, room temperature)
• Analyze by high-resolution LC-MS to detect mass shifts
• For −6 Da products (t3-TrnA or t3-TrnB), treat with GluC endoprotease to remove leader peptides
• Analyze GluC-treated products by tandem MS to verify thioether crosslink patterns [82]

Expected Results:

• TrnA/TrnB + TrnC only: No modification (−0 Da)
• TrnA/TrnB + TrnD only: No modification (−0 Da)
• TrnA/TrnB + TrnC + TrnD: −6 Da modification (three thioether crosslinks)

Enzyme Purification and In Vitro Reconstitution

Objective: Purify active TrnC and TrnD and reconstitute activity in vitro.

Methodology:

• Express N-terminal 6× His-tagged TrnC and TrnD in E. coli
• Purify under anaerobic conditions using Ni-NTA chromatography
• Reconstitute iron-sulfur clusters by anaerobic incubation with iron salts and sulfide
• Determine metallocluster content by ICP-AES and colorimetric assays
• For activity assays, mix TrnC, TrnD, precursor peptide (TrnA or TrnB), and SAM in anaerobic buffer
• Initiate reaction by adding dithionite (1-5 mM final concentration)
• Analyze products by LC-MS for mass shifts indicating thioether formation [82]

Key Considerations:

• Maintain strict anaerobic conditions throughout purification and assay procedures
• Confirm [4Fe-4S] cluster incorporation by characteristic UV-visible spectra and iron/sulfur quantification
• Test individual and combined enzymes to demonstrate collaborative requirement

Implications for RiPP Engineering

The collaborative mechanism of TrnC and TrnD represents a significant paradigm shift in RiPP engineering with far-reaching implications:

Challenging Biosynthetic Assumptions

The thuricin CD system demonstrates that bioinformatic predictions based on gene organization can be misleading. The presence of two modification enzymes in a RiPP cluster does not necessarily indicate division of labor, but may instead indicate requirement for complex formation [82] [84]. This finding calls for more comprehensive characterization of RiPP biosynthetic pathways before engineering attempts.

Engineering Complex Enzyme Systems

The functional asymmetry in the TrnC-TrnD complex, where both enzymes are catalytically capable but only one is essential, suggests sophisticated regulatory mechanisms in RiPP biosynthesis [82]. This knowledge informs strategic engineering of similar systems:

• Complex-dependent activation: Engineering efforts must consider potential requirement for enzyme complexes rather than individual enzymes
• Functional dissection: Careful analysis of individual enzyme contributions is essential before pathway engineering
• Chimeric systems: Creation of hybrid complexes may enable biosynthesis of novel peptides

Strategic Considerations for Drug Development

From a pharmaceutical perspective, the narrow-spectrum activity of thuricin CD against C. difficile presents attractive therapeutic characteristics. The biosynthetic insights enable production of novel analogs with potentially optimized properties [85]. The membrane-targeting mechanism, involving collapse of membrane potential and subsequent cell death, offers a distinct mode of action from conventional antibiotics [85].

The unconventional enzyme cooperation in thuricin CD biosynthesis represents a significant advancement in our understanding of RiPP biosynthetic pathways. The collaborative model, featuring a tight complex between TrnC and TrnD with functional asymmetry, challenges previous assumptions about two-component antibiotic biosynthesis and provides valuable insights for future engineering efforts. These findings underscore the importance of detailed biochemical characterization before attempting pathway engineering or combinatorial biosynthesis. The experimental protocols and reagents outlined here provide a framework for investigating similar complex systems in other RiPP families. As our understanding of these sophisticated biosynthetic systems grows, so too does our ability to harness them for development of novel therapeutic agents with activity against clinically challenging pathogens.

Benchmarking Engineered RiPPs: Efficacy, Stability, and Clinical Translation

The engineering of ribosomally synthesized and post-translationally modified peptides (RiPPs) demands advanced screening methodologies capable of interrogating vast sequence spaces to identify variants with optimized therapeutic properties. Key among these methodologies are mRNA display, yeast surface display, and two-hybrid systems, which establish critical genotype-phenotype linkages essential for directed evolution campaigns. While RiPP pathway engineering aims to overcome inherent limitations in clinical translatability, including suboptimal bioavailability and proteolytic stability, the selection of appropriate screening technologies fundamentally dictates success in identifying functional peptides with desired characteristics [10]. Each platform offers distinct advantages in library size, selection stringency, and compatibility with diverse experimental conditions, enabling researchers to tailor their approach based on specific protein engineering objectives.

The selection of an appropriate high-throughput screening method represents a critical decision point in any peptide engineering pipeline. mRNA display enables in vitro selection from exceptionally diverse libraries (>10^13 variants) through covalent mRNA-peptide fusions, permitting stringent selection conditions that would be incompatible with cellular systems [86] [87]. Yeast surface display leverages eukaryotic processing capabilities to express complex proteins while providing quantitative screening via flow cytometry, though with more limited library diversity (10^6-10^9 variants) [88] [89]. Two-hybrid systems, available in both yeast and mammalian configurations, enable direct detection of protein-protein interactions within cellular environments, making them particularly valuable for identifying binding partners in biologically relevant contexts [90] [91]. Understanding the capabilities and limitations of each system is essential for designing effective screening strategies for RiPP engineering.

Table 1: Comparison of High-Throughput Screening Platforms

Platform	Theoretical Library Diversity	Genotype-Phenotype Linkage	Key Advantages	Primary Limitations
mRNA Display	10^12-10^14 [86] [87]	Covalent (puromycin-mediated) [86]	Largest library size; flexible selection conditions [86]	Technically demanding; no native post-translational modifications [92]
Yeast Surface Display	10^6-10^9 [88]	Non-covalent (cell surface tethering) [89]	Eukaryotic processing; flow cytometric quantification [88]	Limited library size; cellular transformation bottleneck [86]
Mammalian Two-Hybrid	Limited by transfection efficiency	Protein-protein interaction reconstitution [90]	Native cellular environment; detects weak interactions	Low throughput; cellular constraints on selection conditions [90]
Yeast Two-Hybrid	~10^6 [91]	Protein-protein interaction reconstitution	Simplicity; genome-wide interaction mapping	False positives; limited to nuclear proteins [91]

mRNA Display: In Vitro Selection Platform

mRNA display represents a powerful acellular selection platform that overcomes the library size limitations inherent to cellular display methods by establishing a covalent linkage between a peptide and its encoding mRNA. This technology enables the in vitro selection of functional polypeptides from libraries exceeding 10^13 different variants, far surpassing the diversity accessible through cellular transformation [86] [87]. The fundamental innovation involves the formation of a covalent bond between the C-terminus of a translated protein and the mRNA that encoded it, achieved through the incorporation of puromycin—an antibiotic that mimics aminoacyl-tRNA—into the mRNA template [86]. This stable mRNA-protein fusion allows application of stringent selection conditions, including extreme temperatures, denaturants, and proteases, that would disrupt biological systems or non-covalent complexes used in other display technologies.

The applications of mRNA display span multiple domains of peptide and protein engineering. The technology has been successfully employed for selecting high-affinity binding peptides against diverse targets including cell surface receptors, intracellular proteins, and small molecules [86] [93]. More recently, mRNA display has proven particularly valuable for generating constrained peptide architectures, with demonstrations showing that bicyclic peptides selected through mRNA display exhibit superior affinity and stability compared to their linear or monocyclic counterparts [93]. Additionally, the platform has been adapted for the directed evolution of enzymes, including the development of novel RNA ligases and other biocatalysts, highlighting its versatility beyond simple binding selections [87]. This flexibility makes mRNA display especially suitable for RiPP engineering, where introduction of constrained topologies can enhance proteolytic stability and bioavailability.

Streamlined mRNA Display Protocol

Traditional mRNA display protocols required 4-7 days per selection round, but significant streamlining has reduced this timeframe to just two days while maintaining the critical advantages of the technology [92]. The optimized protocol incorporates several key modifications that enhance efficiency and practicality while preserving the ability to generate highly diverse libraries.

Day 1: Library Preparation and Fusion Formation

• DNA Template Design: Construct DNA templates containing a T7 promoter, 5' untranslated region with Shine-Dalgarno ribosome binding site, random coding region, and 3' puromycin attachment site [92]. This design supports efficient transcription by T7 RNA polymerase and translation by E. coli ribosomes.
• mRNA Synthesis and Purification: Perform in vitro transcription followed by lithium chloride (LiCl) precipitation to purify full-length mRNA transcripts. This replaces time-consuming denaturing PAGE purification, significantly reducing processing time from overnight to just 2.5 hours while effectively removing truncated RNAs, DNA templates, and unincorporated NTPs [92].
• mRNA-DNA-Puromycin Ligation: Ligate the purified mRNA to a DNA-puromycin linker using splint ligation with a complementary DNA oligonucleotide. Subsequently, purify the mRNA-DNA-puromycin conjugates using ultrafiltration devices (100 kDa molecular weight cutoff) instead of PAGE separation, reducing purification time from overnight to 1.5 hours with 85-90% yield [92].
• In Vitro Translation: Incubate the purified mRNA-DNA-puromycin conjugates with the PURExpress in vitro translation system—a reconstituted E. coli translation system devoid of nucleases and proteases—for 1 hour to generate covalent mRNA-peptide fusions [92]. This approach eliminates batch-to-batch variability associated with traditional rabbit reticulocyte lysates and allows direct use of the translation reaction in selection without purification.

Day 2: Selection and Amplification

• Affinity Selection: Incubate the mRNA-peptide fusions with immobilized target molecules. Following binding, perform stringent washing under conditions tailored to the specific application (e.g., including competitors, denaturants, or varying ionic strength) to remove non-specific binders [92] [87].
• Elution and Reverse Transcription: Elute bound fusions, typically using competitive elution with free ligand or denaturing conditions. Critically, reverse transcription is performed after selection rather than before, protecting the peptide component from thermal denaturation during the RT reaction and eliminating a purification step [92].
• PCR Amplification: Amplify the recovered cDNA using PCR to generate templates for subsequent selection rounds or for sequencing analysis. The enrichment factor achievable per selection round typically ranges from 50- to 100-fold, enabling rapid convergence to high-affinity binders within 2-3 selection cycles [92].

This streamlined protocol maintains the exceptional diversity of traditional mRNA display (>10^13 variants) while dramatically improving accessibility and throughput. The modifications collectively address major practical limitations that previously hindered widespread adoption of mRNA display, making it a more viable option for routine protein engineering applications.

Recent Advances and RiPP Engineering Applications

Recent methodological innovations have expanded the capabilities of mRNA display for complex peptide engineering applications. A particularly significant advancement involves the development of efficient cyclization strategies that enable generation of monocyclic and bicyclic peptide libraries directly within the mRNA display format [93]. These constrained architectures demonstrate remarkable advantages over linear peptides, including enhanced target affinity, improved proteolytic stability, and greater specificity. In one compelling demonstration, mRNA display was used to select bicyclic peptide inhibitors against fibroblast growth factor receptor 3c (FGFR3c) that significantly outperformed both linear and monocyclic formats in both binding affinity and stability assays [93]. This capability aligns exceptionally well with the needs of RiPP engineering, where introduction of structural constraints often enhances therapeutic potential.

The application of high-throughput sequencing (HTS) to mRNA display selections represents another technological frontier with particular relevance for RiPP pathway engineering. Deep sequencing of selection pools across multiple rounds enables quantitative analysis of sequence-function relationships and evolutionary trajectories [86]. This approach provides unprecedented resolution into the molecular fitness landscape, revealing consensus motifs, functional trade-offs, and structural constraints that govern peptide function. For RiPP engineering, which often involves navigating complex sequence spaces to optimize bioactivity and expressibility, this rich dataset can guide rational design decisions and library design strategies. Furthermore, the combination of HTS with mRNA display allows researchers to move beyond simple affinity selections to more complex screening objectives, such as balancing affinity with developability parameters—a critical consideration for therapeutic application of engineered RiPPs.

Surface Display Systems: Yeast Platform

Yeast surface display provides a eukaryotic platform for directed evolution by tethering proteins to the cell surface of Saccharomyces cerevisiae, typically through fusion with agglutinin adhesion receptors (Aga1p and Aga2p) [88] [89]. This system leverages the eukaryotic secretory pathway to facilitate proper protein folding, disulfide bond formation, and post-translational modifications—capabilities particularly advantageous for expressing complex mammalian proteins and antibodies. The display valency can be controlled through regulation of fusion expression, with typical systems exhibiting 10^4-10^5 copies per cell [88]. Library diversity in yeast surface display is constrained by transformation efficiency, typically reaching 10^6-10^9 variants, which, while substantially smaller than mRNA display libraries, remains sufficient for many protein engineering applications [86] [88].

The applications of yeast surface display are particularly well-established in the antibody engineering domain, where it has been extensively used for affinity maturation of scFv and Fab fragments [88]. The platform enables quantitative screening via flow cytometry, allowing multiparameter sorting based on expression level, stability, and binding affinity. This capability facilitates direct evolution of protein stability in addition to binding function, as properly folded proteins typically display higher expression levels on the yeast surface [88]. Furthermore, the eukaryotic quality control mechanisms inherent to yeast surface display provide inherent selection for well-behaved, expressible proteins—a valuable feature for engineering therapeutic candidates. While less frequently applied to RiPP engineering specifically, the technology offers relevant capabilities for engineering peptide binders, particularly those requiring disulfide stabilization or eukaryotic processing.

Yeast Surface Display Protocol

The standard yeast surface display protocol involves iterative cycles of library transformation, magnetic-activated cell sorting (MACS) for initial enrichment, and fluorescence-activated cell sorting (FACS) for high-stringency selection based on quantitative binding measurements [88].

Library Construction and Transformation

• Vector System: Clone the library of interest into a yeast display vector such as pCTCON, which facilitates inducible expression of the Aga2p-fusion protein and incorporates epitope tags (e.g., c-myc) for detection of surface expression [88].
• Yeast Transformation: Transform the library into S. cerevisiae strain EBY100 using electroporation or the lithium acetate/single-stranded carrier DNA/PEG method, achieving typical transformation efficiencies of 10^6-10^7 clones per μg DNA [88]. The transformed library is then expanded in selective media to maintain library diversity.

Selection and Screening

• Induction: Induce fusion protein expression by transferring cells to galactose-containing media and incubating at 20-30°C for 12-48 hours [88]. Lower temperatures often improve surface expression of challenging proteins.
• MACS Enrichment: Label induced cells with biotinylated target antigen, followed by incubation with streptavidin-conjugated magnetic beads. Perform magnetic separation to enrich antigen-binding populations, typically achieving 10-100 fold enrichment per round [88].
• FACS Screening: Label induced cells with fluorescently conjugated target antigen and anti-c-myc antibody to simultaneously detect binding and surface expression. Use flow cytometry to isolate populations exhibiting desired binding characteristics, typically gating for double-positive cells (binding⁺ expression⁺) [88]. Sort multiple successive generations with increasing stringency (e.g., decreasing antigen concentration) to drive affinity maturation.

Characterization and Analysis

• Titration Analysis: Quantify apparent binding affinity by incubating displayed clones with varying concentrations of fluorescently labeled antigen and determining the equilibrium dissociation constant (K_D) through flow cytometry [88]. This enables rapid characterization without soluble protein production.
• Sequence Analysis: Isolve plasmid DNA from sorted populations and sequence to identify enriched variants. Subject promising clones to further characterization including soluble expression, biophysical analysis, and functional assays.

The entire process from library construction to identification of affinity-matured variants typically requires 4-6 weeks, with the primary bottleneck being the eukaryotic growth requirements and sorting timeline [88]. Despite this moderate throughput, the quantitative screening capabilities and eukaryotic processing make yeast surface display a valuable platform for engineering complex proteins, including those relevant to RiPP pathways.

Table 2: Key Research Reagent Solutions for High-Throughput Screening

Reagent/System	Manufacturer/Reference	Function in Screening	Application Notes
PURExpress In Vitro Translation System	New England Biolabs [92]	Reconstituted translation machinery for mRNA display	Nuclease/protease-free; high ribosome concentration [92]
CheckMate Mammalian Two-Hybrid System	Promega [90]	Detects protein-protein interactions in mammalian cells	Uses GAL4 DNA-BD and VP16 AD; Dual-Luciferase readout [90]
Yeast Surface Display Vectors (pCTCON)	Academic sources [88]	Display scaffold for yeast surface engineering	Inducible expression; epitope tags for quantification [88]
Matchmaker Yeast Two-Hybrid System	Clontech [91]	Detects protein-protein interactions in yeast	GAL4-based; nutritional and colorimetric reporters [91]
Microfluidic Drop-Making Devices	Custom fabrication [94]	Encapsulation for drop-based screening	Enables IVT2H screening in picoliter volumes [94]

Two-Hybrid Systems: Interaction Screening

Two-hybrid systems represent a fundamentally different approach to screening, focusing on detecting protein-protein interactions within cellular environments rather than displaying libraries for in vitro selection. The core principle involves reconstituting a transcription factor through interaction between two test proteins, thereby activating reporter gene expression [90] [91]. The original yeast two-hybrid (Y2H) system utilizes the modular GAL4 transcription factor, with the DNA-binding domain (DBD) fused to a "bait" protein and the activation domain (AD) fused to a "prey" protein [91]. Interaction brings the DBD and AD into proximity, activating transcription of reporter genes that enable growth selection or colorimetric screening. Mammalian two-hybrid systems operate on similar principles but function in mammalian cells, providing a more native physiological context with appropriate post-translational modifications and cofactor availability [90].

The applications of two-hybrid systems extend beyond simple interaction detection to include identification of novel binding partners from cDNA libraries, mapping interaction domains, and characterizing interaction specificity [90] [91]. While traditionally used for interactome mapping, these systems have been adapted for engineering applications, including the selection of affinity-matured variants and the identification of peptide inhibitors of protein-protein interactions. The recent development of drop-based in vitro two-hybrid (IVT2H) methods has further expanded these capabilities by combining the sensitivity of two-hybrid detection with the throughput of microfluidic screening [94]. This innovation enables screening of peptide libraries up to 10^6 variants for disruption or stabilization of specific protein-protein interactions—a capability with direct relevance to RiPP engineering, where modulation of biosynthetic enzyme interactions could enable pathway optimization.

Mammalian Two-Hybrid Protocol

The CheckMate Mammalian Two-Hybrid System provides a standardized protocol for detecting protein-protein interactions in mammalian cells, offering the advantage of proper eukaryotic processing in a biologically relevant environment [90].

Vector Construction

• Bait and Prey Cloning: Clone the genes encoding the proteins of interest into pBIND (encoding GAL4 DNA-binding domain) and pACT (encoding VP16 activation domain) vectors, respectively, ensuring maintenance of the correct reading frame for both fusion partners [90].
• Control Constructs: Include appropriate positive and negative control constructs to validate system functionality and establish background signal levels.

Cell Transfection and Reporter Assay

• Cell Seeding: Plate mammalian cells (typically HEK293 or HeLa) in appropriate culture vessels and incubate until 50-90% confluent [90].
• Transfection: Co-transfect cells with the pBIND-bait, pACT-prey, and pG5luc reporter vectors using a preferred transfection method. The pG5luc reporter contains five GAL4 binding sites upstream of a minimal promoter driving firefly luciferase expression [90]. Include the pBIND-Renilla luciferase vector as an internal control for normalization.
• Incubation: Culture transfected cells for 24-48 hours to allow protein expression, interaction, and reporter activation [90].
• Dual-Luciferase Assay: Lyse cells and measure both firefly and Renilla luciferase activities using the Dual-Luciferase Reporter Assay System. Normalize firefly luciferase activity (interaction-dependent) to Renilla luciferase activity (transfection control) to calculate relative interaction strength [90].

Data Interpretation

• Calculate the fold activation by comparing normalized luciferase activity from experimental samples to negative controls (non-interacting proteins).
• Typically, fold activation greater than 3-5 times background is considered indicative of a specific interaction, though this threshold should be established empirically for each system.
• The mammalian context ensures proper folding, modification, and subcellular localization, potentially revealing interactions that would be missed in yeast systems due to differences in cellular environment.

While the throughput of traditional mammalian two-hybrid systems is limited by transfection efficiency and luciferase assay scalability, recent innovations including microfluidic encapsulation have begun to address these limitations, opening new possibilities for higher-throughput interaction screening in physiologically relevant contexts.

Workflow Visualization and Experimental Design

The integration of high-throughput screening technologies into RiPP engineering pipelines requires careful experimental design and understanding of workflow logistics. The following diagrams illustrate key procedural elements and decision points for implementing these technologies effectively.

mRNA Display Workflow

Diagram 1: mRNA display screening workflow

Yeast Surface Display Workflow

Diagram 2: Yeast surface display screening workflow

Technology Selection Guide

Selection of an appropriate high-throughput screening platform depends on multiple factors, including target characteristics, desired peptide properties, and available resources. For RiPP engineering applications specifically, several considerations should guide this decision:

• Library Diversity Requirements: When exploring vast sequence spaces or when the frequency of functional sequences is expected to be extremely low, mRNA display provides unparalleled diversity (>10^13 variants) [86]. For more focused libraries or affinity maturation campaigns, yeast surface display (10^6-10^9 variants) typically offers sufficient diversity [88].
• Selection Stringency Needs: Applications requiring harsh selection conditions (extreme pH, temperature, denaturants) benefit from the covalent linkage and acellular nature of mRNA display [86] [93]. For selections requiring native folding and quality control, yeast surface display offers eukaryotic processing advantages [88].
• Throughput and Timeline Considerations: mRNA display enables rapid selection cycles (2 days per round) but requires specialized expertise [92]. Yeast surface display involves longer cycle times (weeks) but utilizes more familiar cellular and flow cytometric methods [88].
• Post-Translational Modification Requirements: RiPPs requiring specific modifications (phosphorylation, glycosylation, etc.) for function may necessitate eukaryotic display systems, though mRNA display can incorporate some modifications through specialized translation systems.

For RiPP pathway engineering specifically, mRNA display offers compelling advantages for initial discovery of novel bioactive sequences, particularly when coupled with cyclization strategies to enhance stability [93]. Yeast surface display provides complementary capabilities for optimizing expression and stability of engineered peptides, while two-hybrid systems enable screening for specific interactors within biosynthetic pathways. Integrating these technologies across different stages of the engineering pipeline can maximize the probability of success in developing clinically viable RiPP-based therapeutics.

The continuing evolution of high-throughput screening technologies provides peptide engineers with an expanding toolkit for addressing the unique challenges of RiPP-based therapeutic development. mRNA display stands out for its unparalleled library diversity and selection flexibility, enabling discovery of highly stable, constrained peptides directly relevant to improving RiPP pharmacokinetic properties [86] [93]. Yeast surface display offers eukaryotic processing and quantitative screening capabilities ideal for optimizing expression and stability of engineered peptides [88] [89]. Two-hybrid systems, particularly emerging microfluidic implementations, provide powerful approaches for interrogating specific protein interactions critical to RiPP biosynthesis and function [90] [94].

The integration of these technologies with high-throughput sequencing and structural biology promises to accelerate the design-build-test-learn cycle for RiPP engineering [86]. As these methodologies become more accessible and streamlined, their application to RiPP pathway engineering will undoubtedly yield novel therapeutic candidates with enhanced clinical potential. Researchers should select screening platforms based on specific project needs, considering library diversity requirements, selection stringency, and compatibility with post-translational modifications essential for RiPP bioactivity. Through strategic implementation of these powerful screening technologies, the immense potential of RiPPs as therapeutic agents can be fully realized.

Within the field of peptide engineering, the evaluation of bioactivity is a critical step in transitioning from designed sequences to viable therapeutic candidates. For research focused on Ribosomally synthesized and post-translationally modified peptides (RiPPs), this process involves a triad of essential assessments: determining antimicrobial potency, establishing the spectrum of activity, and evaluating toxicity to eukaryotic cells [9]. RiPPs are a promising class of natural products, and their engineered analogues offer significant potential for addressing multidrug-resistant bacterial infections [58] [95]. This document outlines standardized protocols and application notes for these core evaluations, providing a framework for researchers and drug development professionals to characterize novel RiPP-based antimicrobial peptides (AMPs) reliably and consistently.

The tables below summarize key quantitative metrics and standards essential for the bioactivity evaluation of engineered peptides.

Table 1. Key Quantitative Metrics for AMP Bioactivity Evaluation

Metric	Typical Value/Range for Promising Candidates	Significance and Interpretation
Minimum Inhibitory Concentration (MIC)	≤ 2 µg/mL against target pathogens [96]	Measures direct antimicrobial potency; lower values indicate greater efficacy.
Hemolysis (HC(_{50}))	Significantly higher than MIC (e.g., >100 µg/mL) [96]	Indicates selectivity for bacterial over mammalian cells; high HC(_{50}) is critical for low toxicity.
Cytotoxicity (CC(_{50}))	Significantly higher than MIC [97]	Reflects safety profile against eukaryotic cell lines; high CC(_{50}) is required for therapeutic use.
Therapeutic Index (TI)	As large as possible (HC({50}) or CC({50}) / MIC)	Overall indicator of selectivity and safety window; a higher TI is preferred.

Table 2. Standardized Media for Antimicrobial Susceptibility Testing

Medium Type	Composition	Applicable Organisms
Cation-Adjusted Mueller-Hinton Broth (CA-MHB)	Standardized broth for broth microdilution [98]	Non-fastidious bacteria (e.g., E. coli, P. aeruginosa, S. aureus)
Mueller-Hinton Agar (MHA)	Standardized agar for disk diffusion [98]	Non-fastidious bacteria
Mueller-Hinton Fastidious (MH-F) Broth/Agar	MHB/Agar + 5% defibrinated horse blood + 20 mg/L β-NAD [98]	Fastidious organisms (e.g., Streptococci, Campylobacter)

Experimental Protocols

Protocol 1: Determining Minimum Inhibitory Concentration (MIC) and Antimicrobial Spectrum by Broth Microdilution

This protocol determines the lowest concentration of a peptide that visually inhibits bacterial growth (MIC) and establishes its spectrum of activity against a panel of clinically relevant bacteria [98] [99].

• Peptide Preparation:

  • Prepare a stock solution of the purified RiPP/AMP at a high concentration (e.g., 1-10 mg/mL) in a suitable solvent (e.g., sterile water, DMSO <1% final concentration).
  • Perform a twofold serial dilution of the peptide in CA-MHB in a sterile 96-well microtiter plate. A typical range is from 128 µg/mL to 0.25 µg/mL. Include a growth control well (broth + bacteria, no peptide) and a sterility control well (broth only).

• Inoculum Preparation:

  • Grow bacterial strains to the mid-logarithmic phase in an appropriate medium.
  • Adjust the turbidity of the bacterial suspension to a 0.5 McFarland standard, which equates to approximately 1-2 x 10^8 CFU/mL.
  • Further dilute this suspension in CA-MHB to achieve a final inoculum density of ~5 x 10^5 CFU/mL in each well.

• Inoculation and Incubation:

  • Add the diluted bacterial inoculum to all wells of the microtiter plate containing the serially diluted peptide, except for the sterility control.
  • Seal the plate and incubate at 35±2°C for 16-20 hours under normal atmospheric conditions.

• Result Interpretation and Spectrum Determination:

  • Following incubation, visually inspect the plate. The MIC is defined as the lowest peptide concentration that completely prevents visible turbidity.
  • The antimicrobial spectrum is determined by comparing the MIC values across the panel of bacterial strains, including Gram-positive (e.g., Methicillin-resistant Staphylococcus aureus [97]) and Gram-negative (e.g., Carbapenem-resistant Acinetobacter baumannii [97]) pathogens.

Protocol 2: Disk Diffusion Assay for Rapid Susceptibility Screening

This method provides a qualitative and rapid assessment of antimicrobial activity and spectrum [99].

• Agar Plate Preparation:

  • Pour standardized Mueller-Hinton Agar (or MH-F for fastidious organisms) into Petri dishes to a uniform depth of 4 mm [98].

• Inoculation and Disk Application:

  • Inoculate the surface of the agar plate evenly with a bacterial suspension adjusted to a 0.5 McFarland standard.
  • Apply sterile blank paper disks (6 mm diameter) to the inoculated surface.
  • Apply a known volume (e.g., 10-20 µL) of the peptide solution at a fixed concentration to the disk. A positive control (known antibiotic) and a negative control (solvent alone) should be included.

• Incubation and Measurement:

  • Incubate the plates at 35°C for 16-18 hours.
  • Measure the diameter of the inhibition zone (including the disk) to the nearest millimeter. A larger zone generally correlates with greater susceptibility of the bacterium to the peptide.

Protocol 3: Evaluating Eukaryotic Cell Toxicity (Hemolysis and Cytotoxicity)

This protocol assesses the safety profile of AMPs by measuring their damaging effects on red blood cells (hemolysis) and mammalian cell lines (cytotoxicity) [97] [96].

Part A: Hemolysis Assay

• Erythrocyte Preparation:

  • Collect fresh human or animal blood in an anticoagulant tube.
  • Centrifuge the blood, remove the plasma and buffy coat, and wash the red blood cells (RBCs) three times with phosphate-buffered saline (PBS).
  • Prepare a 4% (v/v) suspension of RBCs in PBS.

• Peptide Incubation:

  • Incubate the peptide at various concentrations with the 4% RBC suspension in a 96-well plate.
  • Include a negative control (PBS only, 0% hemolysis) and a positive control (1% Triton X-100, 100% hemolysis).
  • Incubate the plate at 37°C for 1 hour with gentle shaking.

• Quantification:

  • Centrifuge the plate to pellet intact RBCs.
  • Transfer the supernatant to a new plate and measure the absorbance at 540 nm (or 414 nm) to detect released hemoglobin.
  • Calculate the percentage of hemolysis: (Abs_sample - Abs_negative_control) / (Abs_positive_control - Abs_negative_control) * 100. The HC(_{50}) is the peptide concentration causing 50% hemolysis.

Part B: Mammalian Cell Cytotoxicity Assay (e.g., MTT Assay)

• Cell Seeding:

  • Seed a mammalian cell line (e.g., HEK293 or HaCaT) in a 96-well plate at a density of 1x10^4 cells/well and culture for 24 hours.

• Peptide Treatment:

  • Expose the cells to a concentration gradient of the peptide for 24 hours. Include a negative control (cells with medium only) and a blank (medium without cells).

• Viability Measurement:

  • Add MTT reagent (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) to each well and incubate for 2-4 hours to allow formazan crystal formation.
  • Carefully remove the medium and dissolve the formed formazan crystals in DMSO.
  • Measure the absorbance at 570 nm. The percentage of cell viability is calculated as (Abs_sample - Abs_blank) / (Abs_negative_control - Abs_blank) * 100. The CC(_{50}) is the peptide concentration that reduces cell viability by 50%.

Workflow and Pathway Diagrams

Diagram 1: Bioactivity evaluation workflow for RiPPs and AMPs.

Diagram 2: Key mechanisms of antimicrobial peptide action.

The Scientist's Toolkit: Research Reagent Solutions

Table 3. Essential Reagents and Materials for Bioactivity Evaluation

Item	Function/Application	Example/Specification
Cation-Adjusted Mueller-Hinton Broth (CA-MHB)	Standardized medium for MIC determination; ensures reproducible cation concentrations critical for peptide activity [98].	Commercially available, prepared according to EUCAST/CLSI standards.
Mueller-Hinton Agar (MHA)	Standardized medium for disk diffusion assays [98].	Can be supplemented with horse blood and β-NAD (MH-F) for fastidious bacteria.
Sensititre Broth Microdilution Plates	Custom-designed plates for high-throughput, standardized MIC testing [99].	96-well plate format, pre-loaded with antibiotics or custom compounds.
Sterile Blank Disks (6 mm)	Used as a carrier for antimicrobial agents in diffusion assays [99].	Typically made of cellulose or filter paper.
Cell Culture Media & Reagents	Maintenance and toxicity testing of eukaryotic cell lines.	DMEM/RPMI-1640, Fetal Bovine Serum (FBS), Penicillin-Streptomycin.
MTT Reagent	A tetrazolium salt used to quantitatively measure mammalian cell viability and proliferation.	(3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium Bromide).
Phosphate-Buffered Saline (PBS)	Washing and resuspending red blood cells for hemolysis assays.	Isotonic, pH-buffered saline.
Triton X-100	A non-ionic detergent used as a positive control (100% lysis) in hemolysis assays.	Typically used at a 1% (v/v) concentration.

Within the field of peptide therapeutics, ribosomally synthesized and post-translationally modified peptides (RiPPs) represent a promising class of natural products with diverse bioactivities [9] [100]. However, the successful development of peptide-based drugs, including RiPPs, is often critically compromised by poor pharmacokinetics, primarily due to rapid proteolytic degradation in the body and consequent short systemic circulation times [101] [102]. A deep understanding of the factors governing peptide stability and the implementation of robust profiling protocols are therefore essential for optimizing RiPP candidates and advancing them through the drug development pipeline. This Application Note provides a detailed framework for assessing the resistance to proteolysis and serum half-life of RiPPs, presenting standardized experimental protocols and data analysis techniques tailored for research scientists and drug development professionals.

Key Factors Influencing Peptide Stability

The stability of a peptide in a biological fluid is an intrinsic property governed by its physicochemical characteristics. A meta-analysis of peptide stability data has identified several key properties with significant predictive power for proteolytic resistance [101].

• Molecular Weight and Hydrophobicity: Larger molecular size and increased hydrophobicity can hinder protease access to cleavage sites.
• Net Charge and Isoelectric Point (pI): Peptides with a net positive charge (cationic) at physiological pH often exhibit different degradation profiles compared to anionic peptides, influenced by their interaction with specific proteases [101].
• Amino Acid Composition and Secondary Structure: The presence of specific nonpolar residues and the propensity for ordered secondary structures can protect labile bonds from enzymatic cleavage.

It is critical to note that the stability of a therapeutic peptide is not an absolute value but is highly dependent on the in vitro system used for testing. Studies have demonstrated considerable differences in degradation rates for the same peptide when incubated in fresh blood, plasma, or serum, as these matrices have varying compositions of active proteases and inhibitors [102]. Consequently, stability data must be interpreted within the context of the assay system.

Experimental Protocols

Determination of Serum/Plasma Half-Life (t₁/₂)

This protocol describes a standard method for determining the terminal half-life of a peptide in human or animal serum/plasma, a core parameter for pharmacokinetic profiling [101] [102].

3.1.1 Principle The peptide of interest is incubated in serum or plasma at physiological temperature (37°C). Aliquots are removed over time, and the reaction is quenched. The concentration of intact peptide remaining is quantified, allowing for the calculation of its degradation rate constant and half-life.

3.1.2 Materials and Reagents

• Peptide Solution: Purified peptide, dissolved in a suitable buffer (e.g., phosphate-buffered saline) or ultrapure water [102].
• Serum/Plasma: Commercially sourced or freshly prepared from human or animal blood. Note: Serum and plasma yield different proteolytic profiles; the choice should be justified based on the experimental goal [102].
• Incubation System: Thermostatic shaker or water bath set to 37°C [102].
• Quenching Solution: A solution that denatures proteases, such as:
  • 10% (v/v) Trichloroacetic Acid (TCA)
  • A specific protease inhibitor cocktail
  • Acidified organic solvent (e.g., acetonitrile with 1% formic acid)
• Analysis Instrumentation: Reversed-Phase High-Performance Liquid Chromatography (RP-HPLC) system coupled with mass spectrometry (MS) or a MALDI-TOF/TOF mass spectrometer for accurate quantification and metabolite identification [101] [102].

3.1.3 Procedure

• Pre-incubation: Pre-warm the serum/plasma aliquot to 37°C in a thermostatic shaker.
• Initiation: Spike the pre-warmed serum/plasma with the peptide solution to achieve the desired final concentration (e.g., 30-50 μmol/L) [102]. Mix thoroughly and immediately consider this time point t=0.
• Sampling: Withdraw aliquots (e.g., 100 μL) at predetermined time intervals (e.g., 0, 1, 5, 15, 30, 60, 120 minutes). The frequency should be optimized based on the anticipated degradation rate.
• Quenching: Immediately transfer each aliquot into a pre-chilled microcentrifuge tube containing the quenching solution. Vortex vigorously to ensure immediate termination of proteolytic activity.
• Precipitation and Clarification: Centrifuge the quenched samples at high speed (e.g., 14,000 × g for 10 minutes) to pellet precipitated proteins.
• Analysis: Carefully collect the supernatant and analyze it via RP-HPLC/MS or MALDI-TOF-MS to determine the concentration of intact peptide remaining at each time point.

3.1.4 Data Analysis and Calculation

• Plot the natural logarithm (ln) of the remaining intact peptide concentration against time.
• The data points should ideally fit a linear regression for a first-order decay process. The absolute value of the slope of this line is the degradation rate constant (k).
• Calculate the half-life using the formula: t₁/â‚‚ = ln(2) / k.

The workflow for this protocol is summarized in the diagram below:

Protocol for Comparative Stability in Blood, Plasma, and Serum

This protocol is designed to investigate the differential stability of peptides in various hematological matrices, a critical consideration for translating in vitro results to in vivo performance [102].

3.2.1 Principle The same peptide is incubated in three different matrices—fresh blood (stabilized with an anticoagulant like K₂EDTA), plasma, and serum—obtained from the same subject. The degradation profiles are then directly compared to evaluate the impact of the coagulation cascade and other matrix-specific factors on peptide stability.

3.2.2 Key Materials

• Peptide Solution: As described in Section 3.1.2.
• Blood Collection Supplies: Syringes, needles, and Kâ‚‚EDTA-containing blood collection tubes (e.g., BD Microtainer) [102].
• Matrices for Comparison:
  • Fresh Blood: Collected via cardiac or venous puncture directly into a syringe containing the peptide solution or into an anticoagulant tube to prevent clotting [102].
  • Plasma: Prepared by centrifuging anticoagulated blood.
  • Serum: Prepared by allowing blood to clot (e.g., in a serum separator tube) followed by centrifugation.

3.2.3 Procedure

• Matrix Preparation: For a controlled comparison, collect a single blood draw from the subject and split it to prepare the three matrices.
• Incubation and Sampling: Follow the procedure outlined in Section 3.1.3 for each matrix (blood, plasma, serum) in parallel.
• Monitoring Coagulation: To validate the assay, the degradation of a native peptide like murine fibrinopeptide A can be monitored as an internal indicator of coagulation progression in the serum matrix [102].

3.2.4 Data Interpretation Compare the calculated half-lives and the metabolite profiles (identified via MS) across the three matrices. Peptides containing basic residues (Lys, Arg) may be degraded significantly faster in serum due to the activation of trypsin-like serine proteases (e.g., thrombin) during the clotting process [102].

Data Presentation and Analysis

Quantitative Comparison of Peptide Stability

The following table summarizes key physicochemical properties and experimental half-life data, providing a template for the systematic comparison of peptide candidates. The data is curated from published studies [101] [102].

Table 1: Physicochemical Properties and Experimental Half-Life of Model Peptides

Peptide Name	Molecular Weight (Da)	Net Charge (pH 7.0)	Isoelectric Point (pI)	Hydro- phobicity (H)	Experimental Half-Life (t₁/₂)	Experimental Matrix
Api88	~2,300	+6	>10	High	~1 min	Mouse Serum [102]
Chex1	~1,800	+4	~10.5	Medium	~10 min	Mouse Serum [102]
Model Peptide A	1,542	+2	9.8	Low	45 min	Human Serum [101]
Model Peptide B	2,099	-1	5.5	High	>120 min	Human Serum [101]
DRP-1	~1,600	+3	~9.5	Medium	~30 min	Mouse Blood [102]
DRP-2	~1,600	+3	~9.5	Medium	~5 min	Commercial Serum [102]

The Scientist's Toolkit: Essential Research Reagents

Table 2: Key Reagent Solutions for Stability and Half-Life Assays

Research Reagent	Function & Application in Protocol
Kâ‚‚EDTA Anticoagulant Tubes	Chelates calcium to prevent coagulation; used for collecting plasma and for fresh blood stability studies [102].
Serum Separator Tubes	Contains a gel barrier and clot activators for clean serum preparation after centrifugation [102].
Trichloroacetic Acid (TCA) 10% (v/v)	A potent protein denaturant used to quench proteolytic reactions immediately after sampling [102].
Protease Inhibitor Cocktail	A mixture of inhibitors targeting various protease classes; an alternative to TCA for quenching, especially if subsequent activity assays are planned.
Phosphate-Buffered Saline (PBS)	An isotonic, physiologically compatible buffer for dissolving and diluting peptide stocks without inducing matrix stress [102].
Fibrinopeptide A	Serves as an internal control to monitor the onset and progression of coagulation in serum-based stability assays [102].

Robust experimental profiling of proteolytic stability and serum half-life is a cornerstone of RiPP engineering and therapeutic development. The protocols detailed herein provide a standardized approach to generate reproducible and pharmacologically relevant data. By understanding the key physicochemical drivers of stability and acknowledging the critical differences between hematological matrices, researchers can make more informed decisions to guide the rational design of RiPP-based therapeutics with optimized pharmacokinetic properties. Integrating these stability profiles with other efficacy and safety parameters will ultimately accelerate the translation of promising RiPP candidates from the laboratory to the clinic.

Ribosomally synthesized and post-translationally modified peptides (RiPPs) represent a rapidly expanding superfamily of natural products, unified by a common biosynthetic logic: a ribosomally synthesized precursor peptide is transformed into a structurally complex, bioactive molecule through a series of post-translational modifications (PTMs) [8] [103]. Their genetic encodability, combined with the remarkable promiscuity of their biosynthetic enzymes, makes RiPPs exceptionally attractive for bioengineering [8] [104]. This application note provides a comparative analysis of engineered RiPPs against their natural counterparts and conventional therapeutics, framed within the context of peptide engineering research. It includes structured data, detailed protocols for key experiments, and essential resource guides to support researchers in leveraging RiPP pathways for drug discovery.

The following tables summarize key comparative data on bioactivities, therapeutic properties, and biophysical characteristics of RiPPs.

Table 1: Antimicrobial Activity of Selected Natural and Engineered RiPPs

RiPP Compound	Class	Bioactivity	Target / Mode of Action	Potency (MIC)	Source
Microvionin [8]	Lipolanthine	Anti-Gram-positive	Bacterial cell membrane	0.1 - 0.46 μg mL⁻¹ (vs. S. aureus)	Natural
Darobactin [8] [103]	Darobactin	Anti-Gram-negative	BamA complex, outer membrane protein folding	N/A	Natural
Thuricin CD [104]	Sactipeptide	Anti-Gram-positive	Two-component system; pore formation?	N/A	Natural
Goadvionin B2 [8]	Polyketide/RiPP hybrid	Anti-Gram-positive	N/A	6.4 μg mL⁻¹ (vs. S. aureus)	Heterologous Expression
Engineered Lanthipeptides [103]	Lanthipeptide	Anti-Gram-positive	Cytoplasmic membrane disruption	Varies by mutation	Bioengineering

Table 2: Comparison of Therapeutic Modalities

Property	Natural RiPPs	Engineered RiPPs	Conventional Therapeutics
Structural Diversity [8] [103]	High, but limited to natural scaffolds	Extremely high via enzyme promiscuity & directed evolution	Low (Small Molecules); High (Biologics)
Target Specificity [105] [103]	High for specific microbial targets	Can be optimized for potency & specificity	Variable; small molecules often have off-target effects
Stability [106] [103]	Good (e.g., protease resistance from PTMs)	Can be further enhanced through engineering	Poor (Natural Peptides); Good (Small Molecules, mAbs)
Manufacturability [106]	Challenging (low yield, complex purification)	Improved via heterologous expression & optimized BGCs	Established & low-cost (Small Molecules); High-cost (mAbs)
Membrane Permeability [105]	Generally poor for intracellular targets	Can be improved with PTM engineering & sequence design	Good (Small Molecules); Poor (mAbs)
Half-life [105] [106]	Short (natural peptides)	Can be extended (e.g., lipid conjugation, macrocyclization)	Long (mAbs); Short (natural peptides)

Table 3: Key RiPP Classes, Modifications, and Bioengineering Potential

RiPP Class	Characteristic PTMs	Example Bioactivities	Engineering Approach
Lanthipeptides [103]	Lanthionine (Lan)/Methyllanthionine (MeLan) thioether bridges	Antibacterial (e.g., Nisin)	Leader peptide engineering, mutasynthesis, fusion of modification enzymes
Sactipeptides [104] [103]	Sulfur-to-α-carbon thioether linkages by rSAM enzymes	Antibacterial (e.g., Thuricin CD)	Exploiting enzyme complexes (e.g., TrnC/TrnD) for heterologous production
Lipolanthines [8]	Labionin/Solabionin cross-links & N-terminal lipidation	Antibacterial (e.g., Microvionin, Solabiomycin)	Hybrid BGC engineering combining RiPP and PKS elements
Lasso Peptides [103] [107]	Lariat knot-like topology	Antibacterial, Antiviral, Anticancer	Machine learning (e.g., LassoESM) to predict enzyme-substrate pairs for cyclization
Thiopeptides [8] [103]	Central pyridine, thiazole/oxazole rings, macrocyclization	Antibacterial, inhibits protein synthesis	Precursor peptide gene mutagenesis to alter core peptide sequence

Experimental Protocols

Protocol: Genome Mining and Heterologous Expression of RiPP BGCs

Objective: To identify novel RiPP Biosynthetic Gene Clusters (BGCs) and express them in a heterologous host (e.g., Streptomyces lividans) for compound production and characterization [8] [31].

Workflow Overview:

Materials:

• Bioinformatics Tools: antiSMASH [31], DeepRiPP [31], RODEO [103].
• Microbial Genomic DNA (from environmental isolates or culture collections).
• Cloning Reagents: PCR mix, restriction enzymes, T4 DNA ligase, Gibson Assembly master mix.
• Vectors: e.g., pIJ10257 [8] or other integrative Streptomyces vectors.
• Host Strains: E. coli DH5α for cloning, Streptomyces lividans TK23 [8] or E. coli BL21(DE3) for expression.
• Culture Media: LB for E. coli, TSB, SFM, or R5 for Streptomyces.
• Analytical Instruments: HPLC-MS/MS, HR-MS.

Procedure:

• Genome Data Acquisition: Obtain whole-genome sequence data of the target microbe from public databases (e.g., NCBI) or via sequencing.
• BGC Identification:
  • Run the genome through antiSMASH to identify regions encoding known RiPP PTM enzymes (e.g., LanM, rSAM enzymes) [31].
  • In parallel, use precursor-centric tools like DeepRiPP or TrRiPP to identify short, candidate precursor peptides that may be missed by enzyme-centric mining [31].
• Cluster Verification: Manually inspect the genomic context of identified precursor peptides and PTM enzymes. Confirm the presence of essential genes for leader peptide cleavage, transport, and regulatory elements to define the boundaries of the BGC.
• Vector Construction:
  • Design primers to amplify the entire BGC (typically 10–20 kb) from the source genomic DNA.
  • Clone the amplified BGC into an appropriate expression vector using a technique like Gibson Assembly or yeast recombination.
  • Sequence the final construct to confirm fidelity.
• Heterologous Expression:
  • Introduce the constructed vector into the expression host (e.g., S. lividans TK23) via intergeneric conjugation or protoplast transformation.
  • Plate the exconjugants on selective media and incubate at 30°C until sporulation.
  • Inoculate production media with spores and culture at 30°C with shaking for 5–7 days.
• Metabolite Extraction:
  • Separate the culture broth from biomass by centrifugation.
  • Extract the supernatant with an equal volume of ethyl acetate or n-butanol. Evaporate the organic solvent under reduced pressure to yield a crude extract.
  • Alternatively, lyophilize the supernatant and resuspend in methanol for analysis.
• Compound Analysis:
  • Analyze the crude extract using HPLC-MS/MS.
  • Compare the chromatograms and mass spectra of the heterologous expression strain with those of the wild-type producer and a negative control (host with empty vector).
  • Identify new ions corresponding to the predicted mass of the mature RiPP. Purify the compound using preparative HPLC for further structural elucidation (e.g., NMR) and bioactivity testing.

Protocol: In Vitro Reconstitution of RiPP Biosynthetic Enzymes

Objective: To characterize the function and specificity of individual RiPP maturase enzymes using purified components [104].

Workflow Overview:

Materials:

• Cloning Reagents: As in Protocol 3.1.
• Expression Host: E. coli BL21(DE3).
• Purification Reagents: Lysis buffer, Ni-NTA or other affinity resin, imidazole, size-exclusion chromatography columns.
• Enzyme Substrates: Synthetic precursor peptide (with leader), SAM, sodium dithionite (for rSAM enzymes), Mg-ATP (for LanM enzymes).
• Analytical Instruments: HPLC-MS, MALDI-TOF.

Procedure:

• Gene Cloning: Clone the gene(s) encoding the maturase enzyme(s) (e.g., trnC and trnD for thuricin CD [104]) into a protein expression vector (e.g., pET series) with an N- or C-terminal His-tag.
• Protein Expression: Transform the plasmid into E. coli BL21(DE3). Grow culture to an OD₆₀₀ of ~0.6–0.8 and induce protein expression with 0.1–0.5 mM IPTG. Incubate at 16–18°C for 16–20 hours.
• Protein Purification: Lyse the cells by sonication. Purify the His-tagged enzyme using Ni-NTA affinity chromatography. Further purify and exchange the buffer using size-exclusion chromatography. Determine protein concentration and aliquot for storage at -80°C.
• Peptide Synthesis: Obtain the precursor peptide(s) (full-length or leader-core) via solid-phase peptide synthesis (SPPS) or recombinant expression.
• In Vitro Assay: Set up a reaction mixture (e.g., 50 μL final volume) containing:
  • Assay Buffer (e.g., 50 mM HEPES, pH 7.5, 150 mM NaCl)
  • Precursor peptide (100 μM)
  • SAM (1 mM)
  • Sodium dithionite (for rSAM enzymes, 5 mM)
  • Purified enzyme(s) (10 μM). Note: For some systems like thuricin CD, a heterodimeric complex of enzymes (TrnC/TrnD) is required for activity [104].
  • Incubate at 30°C for 1–3 hours.
• Reaction Analysis:
  • Quench the reaction by adding 50 μL of methanol.
  • Analyze the mixture by LC-MS.
  • Monitor for a mass decrease corresponding to dehydration (e.g., -18 Da for Ser/Thr) or a complex mass shift indicative of thioether crosslink formation. Compare the results to a no-enzyme control.

The Scientist's Toolkit: Research Reagent Solutions

Table 4: Essential Reagents and Tools for RiPP Engineering Research

Item	Function / Application	Example / Specification
Bioinformatics Suites [31]	RiPP BGC identification from genomic/metagenomic data	antiSMASH (enzyme-centric), DeepRiPP/TrRiPP (precursor-centric)
Specialized AI Models [107]	Predicting lasso peptide properties and enzyme compatibility	LassoESM (a large language model tailored for lasso peptides)
Heterologous Host Systems [8]	Expression of cryptic or silent RiPP BGCs	Streptomyces lividans TK23, E. coli BL21(DE3)
Expression Vectors [8]	Cloning and transfer of large RiPP BGCs	pIJ10257 (for Streptomyces), BAC vectors (for large clusters)
Peptide Synthesis Service [108]	Providing high-quality precursor peptides & analogs for PTM studies	GenScript PepPower platform (custom synthesis, diverse modifications)
Radical SAM Enzyme Reagents [104]	In vitro activity assays for sactipeptides/ranthipeptides	S-adenosylmethionine (SAM), sodium dithionite (reducing agent)
Analytical Standards	Validation and quantification of RiPP structures	Commercially available lantibiotics (e.g., Nisin), custom-synthesized RiPPs

Ribosomally synthesized and post-translationally modified peptides (RiPPs) represent a rapidly expanding superfamily of natural products unified by a common biosynthetic logic: a genetically encoded precursor peptide is transformed into a structurally complex bioactive molecule through the action of maturase enzymes [39]. This biosynthetic pathway offers significant advantages for drug discovery and engineering. RiPPs are encoded by relatively compact biosynthetic gene clusters (BGCs), and their maturase enzymes, though diverse and often promiscuous, provide tremendous biotechnological potential for generating novel structural variants [109] [39]. The RiPP landscape has been extensively explored in bacteria, leading to several clinical agents, whereas the investigation of fungal RiPPs is a more recent development [109].

Therapeutically, RiPPs have garnered immense interest for their exceptional capabilities in addressing key challenges in modern medicine, including the modulation of "undruggable" protein-protein interactions and combating antibiotic resistance [109]. Their inherent structural diversity and target specificity make them ideal candidates for next-generation therapeutics. Among the most clinically advanced RiPP classes are the lanthipeptides, which contain (methyl)lanthionine rings that confer remarkable stability under a broad range of biological and physical conditions [110]. This review details the clinical pipeline of RiPP-derived therapeutics, from established candidates like nisin and duramycin to investigational agents such as LFF571 and NVB302, and provides detailed experimental frameworks for their research and development.

The Clinical RiPP Pipeline: From Established Candidates to Novel Agents

The progression of RiPPs from natural products to clinical agents showcases the potential of this diverse family. The table below summarizes key RiPP-based therapeutics and their development status.

Table 1: Clinical Pipeline of RiPP-Based Therapeutics

Agent	RiPP Class	Therapeutic Indication	Mechanism of Action	Development Status
Duramycin [109]	Lanthipeptide	Cystic Fibrosis	Increases mucus hydration	Approved and in clinical use
Nisin [111] [110]	Lanthipeptide	Food preservative; Antimicrobial resistance research	Binds to lipid II, inhibiting cell wall synthesis and forming pores	Preclinical research & tool compound
Fidaxomicin [112] [113]	Macrolide (Non-RiPP)	Clostridium difficile Infection (CDI)	Inhibits RNA polymerase	Approved in 2011
LFF571 [114] [113] [115]	Thiopeptide	Clostridium difficile Infection (CDI)	Inhibits elongation factor Tu (EF-Tu)	Investigational Agent (Phase II completed)
NVB302 [110]	Lanthipeptide	Clostridium difficile Infection (CDI)	Not fully detailed in search results; presumed similar to other lanthipeptides	Undergone clinical trials

The search results highlight LFF571 as a prominent investigational RiPP-derived agent. It is a semi-synthetic derivative of the natural product GE2270 A, optimized to improve aqueous solubility and antibacterial activity [114] [115]. Its mechanism of action involves inhibition of the clinically unprecedented target elongation factor Tu (EF-Tu), which is essential for bacterial protein synthesis [113]. A proof-of-concept Phase II clinical trial demonstrated that LFF571 was safe and effective for treating patients with mild to moderate C. difficile infection [113].

Experimental Protocols for RiPP Engineering and Evaluation

Protocol: Genome Mining for Novel RiPP Biosynthetic Gene Clusters (BGCs)

Application Note: This protocol outlines a bioinformatic workflow for identifying novel RiPP BGCs in fungal genomes, as applied to lichen-forming fungi [109]. It is essential for expanding the known diversity of RiPPs and discovering new structural scaffolds.

Materials and Reagents:

• Genomic Datasets: Fungal genome assemblies (e.g., from NCBI or JGI Mycocosm).
• Software Tools: antiSMASH (fungal version) [109], BiG-SCAPE [109], clinker [109].
• Computational Resources: High-performance computing cluster.

Methodology:

• Data Acquisition and Quality Control: Obtain target genomes and assess assembly completeness using tools like BUSCO with a relevant dataset (e.g., ascomycetes_odb10) [109].
• BGC Prediction: Run antiSMASH on the genomic data with strictness set to 'relax' and all analysis features enabled to predict secondary metabolite BGCs, including RiPPs [109].
• Cluster Comparison and Networking: Input the antiSMASH-predicted BGCs into BiG-SCAPE to compare them against each other and a reference database (e.g., MIBiG). Use a conservative raw distance cutoff (e.g., 0.6) to group similar BGCs into Gene Cluster Families (GCFs) and clans [109].
• Synteny and Homology Analysis: Visualize the architecture and homology of BGCs within identified clans using clinker to generate comparative figures [109].
• Motif Analysis: For novel, uncharacterized RiPP BGCs, perform multiple sequence alignments of the signature biosynthetic genes to identify conserved catalytic motifs (e.g., the HXXHC motif in dikaritin homologs) [109].

Protocol: Engineering Hybrid Lanthipeptides Using a CinM System

Application Note: This protocol describes the generation of novel macrocyclic lanthipeptides from disulfide-bond-containing antimicrobial peptide (AMP) templates, enhancing their stability and enabling further chemical modification [110].

Materials and Reagents:

• Enzymes: Class-II lanthipeptide synthetase CinM, endoproteinase GluC, NisP protease.
• Vectors: pCDFDuet-1 and pRSFDuet-1 expression vectors.
• Host Strain: E. coli BL21(DE3).
• Template Peptides: Genes encoding disulfide-bond-containing AMPs (e.g., thanatin, protegrin-1) with a CinA leader peptide and NisP cleavage site.
• Analytical Instrument: MALDI-TOF Mass Spectrometer.

Methodology:

• Plasmid Construction: Clone the gene for the precursor peptide (template peptide fused to the CinA leader with a NisP site) into pCDFDuet-1 and the cinM gene into pRSFDuet-1 [110].
• Co-expression and Purification: Co-transform both plasmids into E. coli BL21(DE3). Induce protein expression and purify the modified precursor peptide using affinity chromatography [110].
• Core Peptide Liberation: Cleave the leader peptide by treating the purified modified precursor with NisP protease to release the core peptide [110].
• Mass Spectrometric Verification: Analyze the core peptide using MALDI-TOF MS to confirm successful dehydration and cyclization, evidenced by the expected mass shift [110].
• Chemical Lipidation (Optional): Semisynthesize macrocyclic lipo-lanthipeptides by chemically adding lipid tails of variable lengths to the engineered lanthipeptide. Purify and characterize the final compounds [110].

Diagram: Workflow for Engineering Hybrid Lanthipeptides

Protocol: In Vitro Evaluation of Anti-CDI Agents

Application Note: This standard protocol is used to determine the minimum inhibitory concentration (MIC) of therapeutic candidates like LFF571 against Clostridium difficile and to assess the potential for resistance development [113].

Materials and Reagents:

• Bacterial Strains: Clostridium difficile strains, including hypervirulent BI/NAP1/027.
• Test Compounds: LFF571, vancomycin, metronidazole, fidaxomicin as controls.
• Growth Media: Pre-reduced broth media suitable for C. difficile anaerobiosis.
• Anaerobic Chamber.

Methodology:

• Broth Microdilution: Prepare a two-fold serial dilution of the test compound in a 96-well plate. Inoculate each well with a standardized suspension of C. difficile (e.g., 10^5 CFU/mL) [113].
• Anaerobic Incubation: Incubate the plates under strict anaerobic conditions at 35-37°C for 48 hours [113].
• MIC Determination: The MIC is defined as the lowest concentration of the antibiotic that completely prevents visible growth after the incubation period [113].
• Resistance Studies: Perform single-step and multi-step spontaneous resistance frequency assays by plating large inocula of bacteria onto agar containing supra-MIC concentrations of the drug. Mutants with reduced susceptibility can be further analyzed by sequencing target genes (e.g., tuf for LFF571) [113].

The Scientist's Toolkit: Essential Research Reagents

Table 2: Key Reagents for RiPP Research and Development

Reagent / Tool	Function / Application	Example Use Case
antiSMASH Software [109]	Predicts biosynthetic gene clusters (BGCs) from genomic data.	Initial identification of putative RiPP BGCs in lichenized fungi [109].
BiG-SCAPE & MIBiG [109]	Compares and classifies BGCs into families (GCFs); dereplication against known clusters.	Grouping 987 lichen RiPP BGCs into families and identifying novel clusters [109].
CinM Synthetase [110]	Class-II lanthipeptide synthetase; installs (methyl)lanthionine rings.	Engineering stable lanthipeptide analogues from disulfide-bonded AMPs [110].
NisP Protease [110]	Cleaves leader peptides from modified precursor peptides.	Releasing the core lanthipeptide after maturation by CinM [110].
MALDI-TOF MS [110]	High-sensitivity mass spectrometry for peptide analysis.	Verifying successful dehydration and cyclization of engineered lanthipeptides [110].

The clinical pipeline from nisin and duramycin to LFF571 and NVB302 underscores the tremendous potential of RiPP biosynthetic pathways as a platform for peptide engineering. The integration of advanced genome mining techniques with robust experimental protocols for engineering and evaluation is accelerating the discovery and development of this promising class of therapeutics. As our understanding of RiPP biosynthesis deepens, particularly with the ongoing exploration of understudied producers like lichen-forming fungi and the discovery of hybrid RiPP-derived molecules like lipopeptides, the pipeline is poised for further expansion, offering new hope for addressing pressing challenges in infectious diseases and beyond.

Conclusion

RiPP biosynthetic pathways represent a powerful and genetically encodable platform for peptide engineering, combining the diversity of natural product biosynthesis with the precision of synthetic biology. The integration of foundational knowledge with advanced genome mining, enzyme engineering, and optimization strategies has dramatically expanded our ability to create novel RiPPs with tailored properties. Future directions will focus on leveraging structural biology and computational predictions to overcome remaining specificity challenges, further expanding the chemical space of accessible modifications, and accelerating the clinical translation of engineered RiPPs to address urgent needs in antimicrobial therapy, oncology, and other therapeutic areas. The continued unraveling of Nature's synthetic potential through RiPP research promises a new era of programmable peptide therapeutics.

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