Mode of action guided metagenomic natural product discovery reveals convergent evolution of a ClpP-targeting motif

Domain: neuroscience
Published: 2026-04-09
Editorial outcome: minor_revision

Abstract
The discovery of natural products with specific modes of action from metagenomes remains challenging. Here, we present resistance-CONKAT-seq, a pipeline that links biosynthetic gene clusters (BGCs) to self-resistance genes, enabling identification of metabolites with desired molecular targets. Using clpP-directed resistance-CONKAT-seq, we identify the calprotamides, which activate native ClpP and enhance its activity. Cryo-EM and bioinformatic analyses reveal that the calprotamides’ medium-chain N-acylphenylalanine substructure is a convergently evolved ClpP-targeting motif and identify additional BGCs predicted to encode this moiety, including some with co-localized clp genes. The synthesis of structures bioinformatically inspired by two such clp-linked BGCs, desmethyl jomthonic acid C and tuscamide, reveals that both enhanced ClpP activity. Extending our bioinformatically guided synthesis study to additional BGCs lacking nearby clp genes shows that ClpP activity enhancement correlated with antibacterial activity, with the strongest enhancers exhibiting narrow-spectrum antibiotic activity. These findings establish N-acylphenylalanine as a previously unrecognized but common natural motif for targeting ClpP, which should help guide the discovery of both natural and synthetic ClpP modulators for antibiotic and anticancer development. Resistance-CONKAT-seq offers a scalable method for exploring biosynthetic dark matter for metabolites with desired modes of action.

Introduction
The majority of bacteria present in the global microbiome are uncultured and remain an untapped reservoir of bioactive small molecules1, 2. Heterologous expression of biosynthetic gene clusters (BGCs) cloned using DNA extracted directly from environmental samples (metagenomic DNA) provides a means to access this chemical diversity. Although traditional culture-based natural product discovery programs have heavily relied on random screening to identify bioactive small molecules with clinically promising modes of action (MOAs), the large-scale heterologous expression and random screening of metagenomic BGCs is labor intensive. A targeted search for natural products with specific, high value MOAs is much more appealing for metagenomic discovery3-6. It is now well established that, in some instances, a natural product BGC encodes a mutated copy of its molecular target that evades antibiotic binding7-9. This resistance mechanism is known as self-resistance. As a result, focusing discovery efforts on BGCs that co-localize with genes that encode molecular targets of interest presents a strategy for prioritizing clusters that produce natural products with a desired MOA10-12. This approach has been used successfully with cultured isolates due to the ease with which individual bacteria genomes can be sequenced, assembled and bioinformatically interrogated13-15. Unfortunately, all three of these steps remain a challenge with metagenomes, preventing a similar target-directed search for natural products produced by the uncultured bacterial majority. Even when using recently developed long-read sequencing methods that can generate fully assembled, large contiguous metagenomic sequences16, the depth of sequencing is insufficient to capture the full diversity of soil metagenomes, making direct identification of rare BGCs difficult.

To overcome this limitation, we previously developed a targeted sequencing approach called CONKAT-seq (co-occurrence network analysis of targeted sequences). This workflow enables the identification of rare physically clustered biosynthetic genes (i.e. BGCs) from complex (meta)genomic samples17, 18. CONKAT-seq leverages PCR amplification of conserved biosynthetic domains to detect co-occurrence patterns among genes across arrayed (meta)genomic libraries. The ability to sequence amplicons at high depth makes this method both powerful and scalable, allowing the discovery of BGCs from low-abundance microbial populations that constitute the majority of soil biodiversity. This approach has proven effective for systematically uncovering natural product BGCs, both from environmental metagenomes and libraries of cultured bacterial genomes. The PCR amplicon sequencing data used by CONKAT-seq offers an unmatched scale of metagenomic exploration which we hypothesized would allow for the identification of rare resistance gene associated BGCs. Here we report the development of resistance-CONKAT-seq (Fig. 1a), which links potential self-resistance genes encoding resistant variants of molecular targets with biosynthetic gene amplicon networks. By tracking their co-localization, this approach enables the identification of metagenomic BGCs that may encode natural products with specific MOAs. This method can be applied to any conserved essential gene of interest, but as a test case we searched for clpP-associated BGCs in soil metagenomic libraries. ClpP is interesting because it is a validated yet underexplored antibiotic target, and although a growing number of ClpP-active molecules have been identified in recent years, no ClpP-targeting drug has reached clinical use. ClpP is a highly conserved serine protease that degrades damaged proteins and is important for maintaining a healthy cell, making it a promising target for both antibacterial and cancer therapies19-21. The ClpP protease complex comprises two heptameric rings that stack to form a functional tetradecameric proteolytic core, which associates with a hexameric ATP-dependent unfoldase (e.g. ClpX, ClpC). Unfoldases recognize, unfold, and translocate protein substrates into the ClpP catalytic chamber for degradation. Their association with ClpP is mediated by docking of a conserved tripeptide loop (I/LGF loop) from the unfoldase into a specific hydrophobic pocket (H pocket) located at the interfaces between adjacent ClpP protomers22-24.

In this work, we use ClpP directed resistance-CONKAT-seq and identify the calprotamide antibiotics which both activate native Mycobacterium tuberculosis (Mtb) ClpP and enhance its activity once activated. We further show that the medium-chain (C6-C8) N-acylphenylalanine substructure found in the calprotamides is a common, yet overlooked, natural motif for targeting ClpP. This N-acylphenylalanine substructure represents a case of convergent evolution, in which a chemical motif has independently evolved across distinct biosynthetic pathways to target ClpP. Our identification of this evolutionary convergence establishes a molecular handle for discovering ClpP-targeting compounds. Guided by this insight, we synthesize additional ClpP-active molecules, bioinformatically predicted from uncharacterized BGCs, some of which exhibit antibiotic activity. While here we target ClpP, by changing resistance gene specific degenerate primers, resistance-CONKAT-seq can be tuned to any potential molecular target thereby providing a generalized approach for the discovery of natural products with desired MOAs from complex metagenomes.

Results
Screen for clpP genes in arrayed metagenomic libraries
For this study, we used metagenomic DNA to develop a pair of degenerate primers that amplified diverse clpP genes (Supplementary discussion, Supplementary Fig. 1, Supplementary Table 1). Using this primer set, we screened an archived soil metagenomic DNA cosmid library containing >2 x 107 clones for clpP co-localized BGCs. This library was pre-arrayed in 384-well plates with ~25,000 clones per well (Supplementary Table 2)25. We used well-specific barcoded clpP degenerate primers to amplify clpP genes from each library well. To facilitate the identification of nonribosomal peptide synthetase (NRPS) and polyketide synthase (PKS) BGCs, adenylation (A-) and ketosynthase (KS-) domain sequences were previously amplified from each library sub pool using domain specific degenerate primers17 were retrieved. For resistance-CONKAT-seq we integrated this data into the CONKAT-seq algorithm to track co-localization of clpP genes with A- and KS- domain networks (Fig. 1a). Predicted resistance-CONKAT-seq networks were verified by PCR using primers targeting the clpP node and one biosynthetic node, confirming that the co-occurrence of clpP and biosynthetic gene amplicons matched the expected well patterns predicted by resistance-CONKAT-seq. This led to our identification of a verified network containing a clpP node and two KS-domain nodes (Fig. 1b). Cosmids associated with this network were recovered from the archived library, sequenced and annotated. The BGC, which we have called the CPA BGC (Supplementary Fig. 2), was recovered on two overlapping cosmids: AZ52-w347 and AZ52-w337 (Fig. 1c). It did not closely resemble a BGC associated with a known natural product or any uncharacterized BGCs found in publicly available databases.

To show the generality of resistance-CONKAT-seq, we expanded the screening by including two additional self-resistance genes, DNA gyrase subunit B (gyrB) and serine-tRNA ligase (serS), and applied the approach to two additional metagenomic soil libraries. This expanded screening identified four additional validated networks, corresponding to one gyrB-associated NRPS BGC, two serS-associated NRPS BGCs, and one serS-associated PKS BGC (Supplementary Fig. 3).

Expression and characterization of calprotamide A-C from the CPA BGC
Using transformation-associated recombination in yeast we re-assembled the CPA BGC into a single continuous fragment of DNA carried on an E. coli-Streptomyces-yeast bacterial shuttle vector (Fig. 1c, Supplementary Table 3). This construct, pTAR-CPA, was conjugated into Streptomyces albus J1074 for heterologous expression studies. Unfortunately, no clone specific metabolites were detected in cultures of this strain. In an effort to induce production, we used miCASTAR26 to introduce constitutive Streptomyces promoters into the CPA BGC. In one construct we inserted a promoter in front of cpaH, the first gene in the large NPRS/PKS operon (pTAR-CPA-v1), and in a second construct we inserted a bidirectional constitutive promoter cassette between a transcription factor (cpaG) and the clpP gene (cpaF) (pTAR-CPA-v2) (Fig. 1d). In cultures of S. albus transformed with these constructs, we detected a similar set of clone specific metabolites (Fig. 1e). The most intense signals corresponded to features with m/z values of 530, 655 and 673. The highest signal intensities were observed in cultures containing pTAR-CPA-v1 and therefore this construct was grown in large-scale for metabolite isolation studies. Each clone specific mass observed in the crude extract appeared as two distinct HPLC peaks which were independently purified (Fig. 1e). Once purified, each pair of peaks interconverted overtime (Supplementary Fig. 4). The structure of one isomer of each pair was elucidated by HRMS and NMR (Fig. 1f, Supplementary discussion, Supplementary Fig. 5-39, Supplementary Table 4). The 530 feature was determined to be an N-acylated β-methylphenylalanine-leucine-alanine tripeptide with a butyraldehyde moiety between its leucine and alanine residues. In the case of the 655 feature the C-terminal carboxylic acid of the hybrid peptide-polyketide structure was replaced with a bis-γ-lactam bicyclic moiety, and in the case of the 673 feature one γ-lactam was hydrolyzed (Supplementary Fig. 40). We have given these natural products the trivial names calprotamide A (1), B (2) and C (3), respectively. To the best of our knowledge the bis-γ-lactam bicyclic ring in calprotamide B has not been seen previously in any natural product.

To study the interconversion of isomers seen in the calprotamides, we incubated one isomer of calprotamide B in a mixture of D2O and DMSO (1:1) and then analyzed the sample by LCMS/MS. After 24 hours, the sample had converted to a mixture of two isomers with the new isomer gaining one mass unit (Supplementary Fig. 41a). A detailed MS/MS analysis of the new heavy isomer revealed that the deuterium was incorporated in the fragment containing the C21 methine (Supplementary Fig. 41b-c). The proton on this methine is surrounded by two carbonyls and therefore predicted to be acidic, likely leading to facile racemization of this center in all three calprotamides.

The biosynthesis of the calprotamides could be rationalized based on a detailed analysis of the CPA BGC (Fig. 2). The predicted biosynthetic scheme begins with an initiation module and a PKS elongation module giving rise to the monounsaturated lipid seen in all three structures. This is then extended with three NRPS modules and one PKS module to produce a tripeptide containing an intervening butyraldehyde moiety. Release of this intermediate would give calprotamide A. Further extension of one malonyl CoA and a serine would produce the precursor to calprotamide B. The CPA BGC does not encode a type I thioesterase, instead CpaM contains a C-terminal condensation (C) domain. We predict this C domain produces the bis-γ-lactam ring system from the precursor shown on CpaM. In this two-step cyclization scheme the C domain would first carryout a condensation between the serine alpha carbon and the alanine carbonyl to give one γ-lactam and then the second γ-lactam would form through condensation of the alanine amide and the terminal thioester. A similar terminal C-domain catalyzed process is proposed to yield the β-lactone/γ-lactam bicyclic ring system found in oxazolomycin27. For calprotamide B, we propose that the amine from the alanine is used to close the second ring instead of the hydroxyl as seen in oxazolomycin biosynthesis. Spontaneous hydrolysis of the second γ-lactam seen in calprotamide B would give calprotamide C (Supplementary Fig. 40).

Antibiotic activity
We tested the calprotamides for activity against a panel of common bacterial pathogens and eukaryotic cells. No growth inhibitory activity was observed for any of these organisms (Supplementary Table 5). Given that genes within the assembled DNA fragment containing the CPA BGC show highest identity to genes found in diverse Actinomycetes species, and the presence of the potential clpP self-resistance gene in the BGC, we hypothesized that the calprotamides might specifically inhibit the growth of Actinomycetes. We therefore expanded our test panel to include 10 diverse Streptomyces strains. Calprotamide A was inactive against this panel of bacteria; however, Calprotamide B inhibited the growth of 4 Streptomyces strains (Table 1). Calprotamide B appears to be cytostatic as after 72 to 96 hours inhibited wells began to show some growth, which we believe is likely due to the instability of the β-lactone/γ-lactam bicyclic ring in the culture broth.

ClpP activity
We initially tested the calprotamides for their effect on Mycobacterium tuberculosis (Mtb) Clp protease activity as this is most extensively studied ClpP system from Actinomycetes due to its appeal as an antibiotic target. The Mtb ClpP1/P2 complex can digest small peptides by itself (peptidase activity), and in the presences of an ATP dependent unfoldase (ClpC1), it can degrade larger protein substrates (protease activity). Interestingly, when the Mtb ClpP protease was first studied in vitro it was inactive28. Activity was only reconstituted with the serendipitous discovery of synthetic N-blocked dipeptides that activate the native protease29, 30. The most potent of these synthetic activators is benzoyl-leucine-leucine (Bz-LL)31. Although proposed to exist, no natural metabolites with Bz-LL-like activity had been identified30, 32. We therefore tested the calprotamides for their effect on both peptidase and protease activity, as well as their ability to activate native ClpP. As they have distinct binding sites and effects on Clp activity, the natural products metamarin33, which binds ClpC1 and restricts its dynamics34, and ADEP135, which binds ClpP2 and interfere with ClpC1 binding36, were used as controls.

Calprotamides A and B, like metamarin, enhanced the protease activity of ClpP1/P2:C1, whereas ADEP1 inhibited this activity (Fig. 3a). Both calprotamides also caused an ADEP-like increase in the peptidase activity of ClpP1/P2 alone (Fig. 3b). Metamarin had no effect on this activity, as it binds ClpC1, which is not present in the peptidase assay (Fig. 3b). Without Bz-LL, neither ADEP1 nor metamarin stimulated Mtb ClpP1/P2 activity at the highest concentration we tested (0.5 mM). However, both calprotamide A and B activated native ClpP. In fact, they were both more potent native ClpP activators than Bz-LL (Fig. 3c), indicating that the calprotamides represent a previously elusive example of a natural compound with the ability to activate native ClpP. While the calprotamides showed diverse Mtb ClpP activities, they had no effect on Staphylococcus aureus (Fig. 3d) or human mitochondria ClpP activity (Fig. 3e), consistent with their lack of cellular activity.

Interestingly, both calprotamide A and B exhibited similar activity in all three Mtb Clp enzyme assays; however, only calprotamide B demonstrated measurable antibiotic activity. We hypothesized that this discrepancy might be due to reduced cellular accumulation of the negatively charged calprotamide A. To investigate this, we used S. aureus as a model system, as neither compound affected it’s ClpP activity or inhibited its growth. In this context, we found that calprotamide B accumulated at approximately three times the level of calprotamide A (Supplementary Fig. 42), potentially explaining the observed difference in antibacterial activity.

Cryogenic electron microscopy (cryo-EM) structure
To explore how the calprotamides affect ClpP, we determined the cryo-EM structure of calprotamide A bound to Mtb ClpP1/P2. Given the comparable activity of calprotamide A and B in functional assays, we focused our analysis on calprotamide A, as calprotamide B is less stable and exhibited low solubility in protein buffer, making it a poor candidate for preparing high-quality grids. Based on our cryo-EM data, the full tetradecameric complex could not be resolved under C1 symmetry due to poorly defined density at the ligand binding sites. We therefore focused on the two-protomer complex and performed local refinement and intensive 3D classification, which yielded a class of two-protomer units with improved density at the binding site. All structural analyses reported here are based on the two-protomer complex.

In our structure, calprotamide A binds the apical surface of ClpP2 at the same general binding site as ADEP (Fig. 4a-b). The N-acylphenylalanine moiety, shared by both calprotamide A and ADEP, occupies the ClpP2 H pocket in each structure, and residues forming the H pocket show no major differences in their interactions with this fragment (Supplementary Fig. 44a). Beyond this common pharmacophore, the structural features of these two natural products largely extend in opposite directions (Fig. 4c). The electron density for the C-terminal portion of calprotamide A is less well-defined than that observed for the N-acylphenylalanine motif that binds the H pocket, suggesting that it is more conformationally flexible. Residues predicted to interact with the non-N-acylphenylalanine portions of each ligand show only minor side-chain rearrangements between the two structures (Supplementary Fig. 44b). The largest apparent difference occurs at R207; however, the electron density for this side chain in the ADEP-bound structure (PDB 6vgn) is insufficient to confirm a definitive structural change. To further compare the difference in binding between calprotamide A and ADEP, we performed alanine mutagenesis of two key residues in Mtb ClpP2, R207 and Q101. R207 forms a salt bridge with calprotamide A but not with ADEP, whereas Q101 forms a hydrogen bond with ADEP but not with calprotamide A (Supplementary Fig. 45a). As predicted by our model, the R207A mutation more strongly impaired calprotamide A-mediated enhancement of Mtb ClpP1P2 peptidase activity than it did ADEP-mediated enhancement. Conversely, the Q101A mutation had a greater effect on ADEP-mediated enhancement than on calprotamide A-mediated enhancement (Supplementary Fig. 45b). Whether the unusual bis-γ-lactam bicyclic moiety in calprotamide B forms additional interactions with Mtb ClpP2 or the ClpP1/P2:C1 complex remains to be determined. It is possible that the bis-γ-lactam serves primarily to mask the negative charge that would normally be generated upon release by the thioesterase, thereby improving bioavailability. This is consistent with the higher cellular accumulation of calprotamide B we observed (Supplementary Fig. 42) and may help explain its stronger antibacterial activity relative to calprotamide A (Table 1).

Although no major structural rearrangements were observed at the ligand binding site, calprotamide A binding induced two more distal conformational changes. Specifically, it promoted ordering of loops in both the ClpP2 N-terminal region and the ClpP2 handle region near the catalytic sites (Fig. 4d). Notably, changes in these regions have been independently observed in the ADEP- and Bz-LL-bound structures, respectively. However, while calprotamide A binding produced electron density consistent with only partial ordering, the corresponding regions in the ADEP and Bz-LL complexes adopt fully formed secondary structures (a β-hairpin and β-sheet, respectively). In both the ADEP and Bz-LL structures, all ligand binding sites are fully occupied, whereas only partial ligand occupancy was observed in our calprotamide A complex. Thus, the limited conformational changes observed in our structure may reflect an intermediate state resulting from incomplete ligand occupancy.

Calprotamide A and ADEP both enhance Mtb ClpP1/P2 peptidase activity. As calprotamide A and ADEP bind to the same region of ClpP2, this activity enhancement likely occurs through a shared mechanism. However, due to the limited conformational changes observed in Mtb ClpP upon binding either ligand, the underlying mechanism of activation remains unresolved. Interestingly, calprotamide A enhances ClpC1-dependent protease activity, whereas ADEP inhibits this activity by displacing ClpC1 from the ClpP1/P2 complex. Although both ligands bind the ClpP2 H pocket, they create distinct surfaces at the apical region of ClpP2, where ClpC1 interacts. Based on the structure of ClpP1/P2 alone, it remains unclear how the surface formed by the ClpP2-calprotamide A complex promotes enhanced ClpC1-dependent proteolysis.

Convergent evolution of a medium-chain N-acylphenylalanine motif for ClpP engagement
The closely related medium-chain (C6-C8) N-acylphenylalanine substructures found in calprotamide and ADEP antibiotics bind ClpP2 in the same orientation mimicking the IGF loop that endogenous unfoldases (e.g., ClpPC1 and ClpX) use to engage ClpP2. The phenylalanine residue fits into a conserved cleft typically occupied by the unfoldase’s IGF phenylalanine, and the acyl group mimics the hydrogen bonding pattern of the isoleucine-glycine backbone of the tripeptide anchoring these natural products to the protease. While structurally related, these two N-acylphenylalanine moieties are encoded by evolutionary distinct biosynthetic pathways (Fig. 5a, left). In the case of the calprotamides the lipid moiety arises from a type I PKS system, while the ADEP triene is produced by a type II PKS system. The methylphenylalanine in the calprotamides and phenylalanine in the ADEPs are then both added to their respective lipids by an NRPS module. The emergence of the medium-chain N-acylphenylalanine motif in biosynthetically unrelated natural products is a clear example convergent evolution for ClpP engagement. This shared substructure appears to serve as a key motif for interacting with the ClpP hydrophobic pocket, while divergence of the structures appended to it allow for differential modulation of ClpP activity (Fig. 5a, right).

Inspired by our discovery of the convergently evolved N-acylphenylalanine moiety for engaging ClpP, we conducted a bioinformatic search for other BGCs that might encode Clp active molecules with N-acylphenylalanine substructures. To do this, we scanned sequenced NRPS BGCs for the presence of a phenylalanine-specific A-domain and a co-localized clp gene (e.g., clpP, clpA/C or clpX). This subset of BGCs was then manually searched for phenylalanine-selective A-domains, either downstream of PKS modules or following a lipid incorporating initiation moiety (i.e., a coenzyme A ligase (CAL) containing module or a condensation starter (Cs) domain). This identified eight predicted N-acylphenylalanine encoding BGCs co-localized with a clp gene that could serve as a potential self-resistance gene (Fig. 5b, Supplementary Table 7). These BGCs were found in diverse Gram -positive and -negative bacteria, including members of the Actinomycetia, Betaproteobacteria, Clostridia, and Sphingobacteriia classes. Among the BGCs with co-localized clp genes, six appear to encode previously uncharacterized natural products. A BGC from Streptomyces hawaiiensis encodes the ClpP targeting antibiotic ADEP, and a BGC from Streptomyces caniferus encodes the jomthonic acids37, 38, a known natural product family that had not been previously reported to have ClpP activity.

To explore the possibility that jomthonic acid might possess overlooked ClpP activity, we synthesized desmethyl jomthonic acid C (4, Supplementary Fig. 46-49) and tested it for its effect on Mtb ClpP. Although less potent than the calprotamides, it enhanced Mtb ClpP1/P2 peptidase activity (Fig. 5c). To investigate whether other BGCs we identified encode uncharacterized natural products with ClpP activity, we bioinformatically predicted the product of the hybrid PKS-NRPS BGC from Mycobacterium tusciae JS617 (Supplementary Fig. 50-53). We then synthesized this predicted structure, which we named tuscamide (5), and assayed it for ClpP activity. Like desmethyl jomthonic acid C, tuscamide also enhanced Mtb ClpP1/P2 peptidase activity. In fact, it had comparable activity to both calprotamide A and B (Fig. 5d).

The identification of four structurally distinct ClpP active natural products, linked only by their medium-chain N-acylphenylalanine substructures, suggests that uncharacterized BGCs encoding this moiety are likely to represent an untapped reservoir of structurally diverse ClpP-targeting compounds. Notably, this shared substructure that engages the H pocket corresponds to the smallest ADEP fragment reported to retain antibacterial activity39. Together, our bioinformatic and activity analyses suggested that the N-acylphenylalanine moiety was likely a previously unappreciated, yet potentially common, ClpP targeting motif that has convergently evolved in diverse bacteria. As not all BGCs will contain a self-resistance gene, we carried out a broader search of sequenced BGCs for those that encode N-acylphenylalanine moieties. This search identified more than 100 previously uncharacterized BGCs containing an NRPS initiation module consisting of a phenylalanine-selective A-domain and Cs (condensation starter) domain, which initiates lipopeptide biosynthesis by appending a fatty acyl chain onto the first amino acid. Interestingly, a number of the BGCs we identified in both our original clp gene driven bioinformatic analysis and this broader search are hybrid NRPS-PKS systems indicating that they could encode both the lipid and the phenylalanine seen in a medium-chain (C6-C8) N-acylphenylalanine motif. In purely NRPS BGCs, the Cal or Cs initiation domain could instead introduce a primary metabolism derived medium-chain fatty acid and therefore no specific fatty acid biosynthesis genes would be required.

While not all these BGCs are expected to encode a ClpP-targeting molecule, this collection is potentially enriched for ClpP activity. We bioinformatically predicted the encoded peptide sequences and randomly selected ten uncharacterized BGCs whose products could be predicted from existing A-domain specificity data, were synthetically accessible, and contained a possible cyclization site (e.g., serine or threonine) (Supplementary Table 8-9). Most of these BGCs originated from Actinomycetes species, including four from Mycobacterium, two from Streptomyces, one from Microbispora, and one from Rhodococcus. The remaining two BGCs were derived from Paenibacillus and Mucilaginibacter. Each predicted lipopeptide was synthesized using Fmoc-based solid-phase peptide synthesis (SPPS) and with the 2-hexenoic acid lipid moiety from the calprotamides (Supplementary Table 10, Supplementary Fig. 54).

The resulting molecules ranged from five to ten amino acids in length, with ring sizes varying from four to eight residues. All compounds were evaluated for their ability to modulate Mtb ClpP peptidase activity and for antibiotic activity against a panel of Streptomyces and Mycobacterium strains (Fig. 6a). We used an expanded panel of Actinomycetes, as we had previously observed narrow-spectrum Actinomycete activity for N-acylphenylalanine containing structures, and most BGCs that inspired our synthetic efforts originated from this genus. Several molecules enhanced Mtb ClpP1/P2 peptidase activity, with 6 (myscamide, Fig. 6b, Supplementary Fig. 55-56) and 13 (paenilamide, Fig. 6c, Supplementary Fig. 57-58) producing the strongest enhancement at levels comparable to calprotamide B. Enhancement of ClpP1/P2 activity correlated with antibacterial activity, with both of these compounds exhibiting antibiotic activity against a narrow spectrum of Actinomycete species. Notably, myscamide showed potent activity against M. tuberculosis mc2 6206 with a minimum inhibitory concentration of 4 µg/mL.

Methods
Amplification of clpP genes and targeted sequencing
A soil metagenomic cosmid library was previously constructed and archived as glycerol stocks. The library was arrayed across two of 384-well plates with each well containing ~25,000 cosmid clones. Degenerate clpP primers barcoded to individual wells were used to generate clpP amplicons across the entire library using 10 μL PCR reactions. For detailed methods on degenerate primer design, see the Supplementary Information. The reaction mix included 5 μL of 2× GoTaq® Master Mix (Promega), 0.5 μL of barcoded primers (100 μM), 1 μL of template DNA (20 ng/μL), and 3 μL of H2O. PCR was performed using the following conditions: 95 °C for 5 minutes, followed by 35 cycles of 95 °C for 30 seconds, 55 °C for 30 seconds, and 72 °C for 30 seconds with a final extension at 72 °C for 5 minutes. Amplicons across a plate were pooled and gel-purified according to the expected amplicon size. The purified amplicons were used to seed a second-round PCR to add individual plate barcodes as well as Illumina adaptors. The PCR reactions were 10 μL of 2× FailSafe™ PCR PreMix G (Biosearch Technologies), 0.5 μL of Illumina universal forward primer (100 μM), 0.5 μL of Illumina indexed reverse primer (100 μM), 5 μL of purified DNA (100 ng), 0.4 μL of rTaq polymerase (Bulldog Bio), and 3.6 μL of H2O. The reaction conditions for the second-round PCR were an initial denaturing step of 95 °C for 5 minutes, followed by 6 cycles of 95 °C for 30 seconds, 70 °C for 30 seconds, and 72 °C for 45 seconds, with a final extension step at 72 °C for 5 minutes. The PCR products were purified using Agencourt AMPure XP magnetic beads (Beckman Coulter) and quantified using a 2200 TapeStation (Agilent Technologies). Amplicons were pooled equimolarly and sequenced at a final concentration of 10 nM on an Illumina NextSeq platform.

Resistance-CONKAT-seq analysis and selection criteria for clpP : AD/KS networks
To identify clpP genes which were associated with AD/KS network clusters, the clpP OTUs were analyzed using CONKAT-seq18, 48 together with OTUs for adenylation (AD) and ketosynthase (KS) domains. OTUs were required to share at least 3 common wells to be considered part of the same gene network. Generated networks were visualized using Cytoscape49 and candidates were selected based on containing at least one clpP OTU and at least one of an AD or KS domain. The following criteria were used to remove false positive networks: 1. to prevent highly prevalent amplicons across the whole library, networks with normal distribution of amplicons (less than 50% wells) were kept, 2. to prevent cross-contaminations, networks with normal distribution (not too close to each other) of clpP-AD/KS co-occurrences were kept, and 3. to prioritize the networks with high likelihood of real connections, networks with high (≥50%) co-occurrence rates were kept. Remaining networks were validated by PCR. For detailed methods about the recovery and assembly of the CPA BGC, see the Supplementary Information.

Heterologous expression
The TAR-assembled and a control pTAR-lys vector were individually transformed into E. coli S17 by heat shock and integrated into the genome of Streptomyces albus J1074. Validated conjugants were used to generate a spore stock which was then used to seed 5 mL of trypticase soy broth (Oxoid) followed by incubation at 30 °C and 200 rpm for 48 hours to promote robust mycelial growth. After the initial incubation, 0.05 mL of starter culture was used to inoculate 50 mL of R5a medium (100 g/L of sucrose, 5 g/L of yeast extract, 10.12 g/L of MgCl2·6H2O, 0.25 of g/L K2SO4, 0.1 g/L of casamino acids, 21 g/L of MOPS, 10 g/L of D-glucose, 2 g/L of NaOH, 5.88 mg/L of CaCl2, 80 μg/L of ZnCl2, 400 μg/L of FeCl3·6H2O, 20 μg/L of MnCl2, 20 μg/L of CuCl2, 20 μg/L of Na2B4O7·10H2O, 20 μg/L of (NH4)6Mo7O24·4H2O, pH 6.8) in 125 mL baffled flasks for incubation at 30 °C and 200 rpm for 10 days.

Crude extract LC-MS analysis
Fermentation cultures (500 μL) from the heterologous expression culture were extracted with ethyl acetate (1:1 v/v). The extract then dried under reduced pressure using a SpeedVac™ Vacuum Concentrator (Thermo Fisher Scientific) and dissolved in 100 μL of HPLC-grade methanol. Insoluble particulates were removed by centrifugation at 21,300 x g for 2 min and filtering using 0.22 μm membrane filter (Millipore). The material was analyzed by high-resolution mass spectrometry.

Biosynthetic gene cluster refactoring
The CPA BGC was refactored using miCASTAR as previously described26. Briefly, sgRNA primers targeting sequence regions for promoter replacement were designed and synthesized (IDT). The EnGen sgRNA Synthesis Kit (NEB) was then used to generate sgRNAs which were purified with an RNA Clean & Concentrator Kit (Zymo Research). The TAR-assembled CPA BGC (pTAR-lys vector) was digested with Cas9 Nuclease (NEB) and sgRNAs at 37 °C overnight. Linearized DNA was purified using the ZR Research BAC DNA Miniprep Kit (Zymo Research). A donor DNA fragment containing prototrophic markers, a strong Streptomyces promoter, and homology arms flanking the insertion site was amplified by PCR. For homologous recombination, the donor DNA and Cas9-digested CPA BGC were co-transformed into Saccharomyces cerevisiae BY4727 via the standard spheroplast method. Yeast colonies harboring correctly integrated constructs were selected on synthetic complete (SC) medium lacking specific amino acids. Positive clones were screened by PCR for precise insertion, followed by plasmid extraction. Validated constructs were electroporated into E. coli S17 cells and subsequently conjugated into Streptomyces albus J1074 for heterologous expression.

Scaled production and isolation of calprotamides
Spore of Streptomyces albus J1074 conjugated with the refactored CPA BGC v1 was inoculated into 5 mL of trypticase soy broth (Oxoid) and incubated at 30 °C and 200 rpm for 48 hours. Then, 100 μL of the starter culture was added to five 2.8 L baffled flasks containing 1 L of R5a medium, followed by incubating at 30 °C with shaking at 200 rpm for 6 days. The 5 L fermentation culture was extracted by two rounds of 1:1 v/v ethyl acetate, and the crude extract was concentrated using a rotary evaporator. The concentrated sample was then passed through a C18 column (50 g, RediSep Rf) and separated using a reverse-phase linear gradient method (5-100% H₂O/acetonitrile, 0.01% formic acid) over the course of 30 minutes. Fractions containing the desired compounds were purified by semipreparative high-performance liquid chromatography (HPLC) using an XSelect CSH Phenyl-Hexyl 130 Å column (150 mm × 10 mm, 5 µm, Waters) under the following conditions: 5% B for 0.1 min, 5-40% B from 0.1 to 5 min, 40-60% B from 5 to 40 min, 60-100% B from 40 to 45 min, 100% B from 45 to 50 min, 100-5% B from 50 to 55 min, and 5% B from 55 to 60 min. Fractions containing calprotamide A-C were purified using an XBridge semipreparative C18 column (150 mm × 10 mm, 5 µm, Waters) under different conditions. For calprotamide A: 5% B for 0.1 min, 5-40% B from 0.1 to 5 min, 40-55% B from 5 to 40 min, 55-100% B from 40 to 45 min, 100% B from 45 to 50 min, 100-5% B from 50 to 55 min, and 5% B from 55 to 60 min. For calprotamide B: 5% B for 0.1 min, 5-40% B from 0.1 to 5 min, 40-50% B from 5 to 40 min, 50-100% B from 40 to 45 min, 100% B from 45 to 50 min, 100-5% B from 50 to 55 min, and 5% B from 55 to 60 min. For Calprotamide C: 5% B for 0.1 min, 5-20% B from 0.1 to 5 min, 20-40% B from 5 to 40 min, 40-100% B from 40 to 45 min, 100% B from 45 to 50 min, 100-5% B from 50 to 55 min, and 5% B from 55 to 60 min. All HPLC purification steps were with an injection volume of 50 μL, water as solvent A and acetonitrile as solvent B in the presence of 0.1% (v/v) formic acid. The flow rate was 2.5 mL/min.

Minimum inhibitory concentration (MIC) assays
To obtain the saturated cultures, Streptomyces spores were seeded in 5 mL of trypticase soy broth (Oxoid) followed by incubation at 30 °C and 200 rpm for 48 hours. M. smegmatis mc2 155, M. avium subsp. paratuberculosis ATCC 43544, M. gallinarum ATCC 19710, and M. seoulense DSM 44998 glycerol stocks were seeded in 5 mL of 7H9 liquid medium (0.94 g/200 mL of 7H9 powder, 50% glycerol, and 40% glucose, pH=7) followed by incubation at 37 °C and 200 rpm for 48 hours. M. tuberculosis mc2 6206 glycerol stock was seeded in 10 mL of defined 7H9 medium (0.94 g/200 mL of 7H9 powder, 50% glycerol, 20 mL/200 mL of ADC, 10 mg/mL of leucine, and 5.76 mg/mL of calcium pantothenate, pH=7) followed by incubation at 37 °C with 5% CO2 for 14 days. Candida albicans glycerol stock was seeded in 5 mL of YPD medium followed by incubation at 30 °C and 200 rpm for 16 hours. Other tested bacterial glycerol stocks were seeded in 5 mL of LB medium followed by incubation at 37 °C and 200 rpm for 16 hours. The saturated cultures were then diluted by 1:10,000 folds in 10 mL of Production Medium (20 mL/L of glycerol, 10 g/L of peptone, 5 g/L of Meat extract, pH 7) for Streptomyces, 7H9 medium for M. smegmatis, M. avium, M. gallinarum, and M. seoulense, defined 7H9 medium for M. tuberculosis, YPD medium for Candida albicans, and LB medium for other tested bacteria. The stock solution of compounds was serial diluted 2-fold in a 96-well plate (ThermoFisher Scientific) containing corresponding culture media, then an equal amount of diluted culture was added to each well and mixed by pipetting. The plates containing Streptomyces were incubated at 30 °C for 48 hours. The plates containing M. smegmatis were incubated at 37 °C for 48 hours. The plates containing M. tuberculosis, M. avium, M. gallinarum, and M. seoulense were incubated at 37 °C with 5% CO2 for 7 days. The plates containing Candida albicans were incubated at 30 °C for 16 hours. The plates containing other bacteria were incubated at 37 °C for 16 hours. The top and bottom rows of plates contained an equal volume of media alone to prevent edge effect. The last column did not contain antibiotic to serve as a control for cell viability. The MIC of antibiotics was determined by visual inspection as the concentration in the well that prevents bacterial growth compared to control wells. The MIC assays were performed in at least duplicate.

Human cell cytotoxicity assay
The cytotoxicity of calprotamides was performed using MTT (3-(4,5-Dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide) assay. Briefly, HEK293 cells (ATCC CRL-1573) were diluted with DMEM medium (Gibco) add with 10% bovine serum and 1% glutamate at the density of 5,000 cells/well in a 96-well plate and incubated at 37 °C with 5% CO2 for 24 h. Compounds were serially diluted in DMEM medium and added to incubated cells and the mixture plate was incubated for 48 h. The supernatant in each well was aspirated and 100 μL of 0.5 mg/mL MTT solution in DPBS buffer (Gibco) was added with gently mixing. After 4 h incubation at RT, 100 μl of solubilization solution (40% DMF (v/v), 15% SDS (w/v), 2% acetic acid (v/v)) was added to cells and mixed using a mini shaker. After a final incubation at RT for 1 h, the plate was transferred to an Infinite M NANO+ (TECAN) and the absorbance of wells were measured at 570 nm. Paclitaxel and 0.2% DMSO were used as positive and negative control, respectively.

Overexpression and purification of Mtb ClpP1P2, ClpC1 and S. aureus ClpP
Escherichia coli BL21 (DE3) harboring plasmids encoding 14×HisTag-bdSUMO-ClpP1, 14×HisTag-bdSUMO-ClpP2, 14×HisTag-ClpC1 (Mtb), or 14×HisTag-ClpP (S. aureus) were cultivated in 1 L of LB medium at 37 °C and 200 rpm until an optical density at 600 nm (OD600) of 0.8. The cultures were then cooled to 4 °C for 20 min and induced with 1 mM of isopropyl β-D-1-thiogalactopyranoside (IPTG) and grown at 16 °C and 200 rpm overnight. Cells were harvested by centrifugation at 8,000 × g for 20 min and resuspended in 100 mL of lysis buffer (50 mM Tris-HCl pH 8, 250 mM NaCl, 1 mM β-mercaptoethanol (BME), 1% Triton X-100, 0.1 mg/mL DNase I, 0.1 mg/mL lysozyme, 1 mM phenylmethylsulfonyl fluoride (PMSF), 0.1 mg/mL trypsin inhibitor, 1 µg/mL pepstatin, 1 µg/mL leupeptin, and 1 mM benzamidine). The suspension was incubated on ice for 15 min and the cells were then lysed via sonication. Cell lysates were centrifuged at 20,000 × g for 30 min at 4 °C to remove cell debris. The supernatant was then applied to a 5 mL HiTrap chelating Ni²⁺ affinity column (GE Healthcare) pre-equilibrated with wash buffer (20 mM Tris-HCl pH 8.0, 250 mM NaCl, 30 mM imidazole, 1 mM BME). Column was subsequently washed with ~50 column-volume (CV) of Ni-wash buffer (20 mM Tris pH=8.0, 250 mM NaCl, 30 mM imidazole). Bound proteins were eluted using 50 mL elution buffer (20 mM Tris-HCl, pH 8.0, 250 mM NaCl, 300 mM imidazole, 1 mM BME). For ClpP1 and ClpP2, the bdSUMO tag was removed by incubation with 1 µg/mL bdSENP1 protease50. Eluted proteins were concentrated to 5 mL using an Amicon Ultra centrifugal filter unit (100 kDa cutoff, Millipore) and Mtb ClpP1 and ClpP2 were further purified by size-exclusion chromatography (SEC) on a Superdex 200 10/300 GL column (GE Healthcare) equilibrated in 20 mM HEPES (pH 7.3), 150 mM NaCl, 1 mM MgCl2, and 1 mM dithiothreitol (DTT). Fractions containing the purified proteins were pooled and concentrated using Amicon Ultra filters (100 kDa cutoff). Protein concentrations were determined using the Quick Start Bradford Protein Assay Kit (Bio-Rad). Purified proteins were aliquoted and stored at −80 until further use.

In vitro ClpP protease assays
Mtb ClpP protease activity was assessed using the Mtb ClpP Protease Assay Kit (ProFoldin) according to manufacturer instructions. For ClpP1P2 assays, 1 μM ClpP1P2 (monomer) was incubated in a 30 μL reaction with the Assay Buffer. For ClpP1P2C1 assays, 1 μM ClpP1P2 (monomer) and 1 μM ClpC1 (monomer) were combined in Assay Buffer supplemented with 8 mM MgCl2 and 2 mM ATP. Test compounds were pre-incubated with the ClpP1P2 or ClpP1P2C1 complexes for 5 min before the addition of 0.3 μL 100× ZVKM-AMC (for ClpP1P2 assay) or 200 μM FITC-casein (AAT Bioquest, for ClpP1P2C1 assay) as fluorogenic substrates. The human mitochondrial ClpP protease assay was performed using the Human Mitochondrial ClpP Protease Assay Kit Plus (ProFoldin) according to the manufacturer’s protocol. For the S. aureus ClpP assay, 1 μM S. aureus ClpP (monomer) was incubated in a 30 μL reaction mixture containing 100 mM HEPES (pH 7.0), 100 mM NaCl, and 200 μM Suc-LY-AMC (AAT Bioquest). Fluorescence signals were recorded using an Infinite M200 Pro plate reader (Tecan) at 37 °C with excitation/emission wavelengths of 380/460 nm (AMC) or 480/520 nm (FITC). All assays were performed in duplicate, and the data were plotted using GraphPad Prism 10.

Cryo-EM sample preparation and data acquisition
Cryo-EM grids (Quantifoil R 1.2/1.3 400 Mesh, Au) were prepared on a Vitrobot IV (Thermo Fisher Scientific) set to 100% humidity at 22 °C. To maintain humidity, two hydrated Kimwipes were affixed to the chamber walls. Complex of Mtb ClpP1P2 was reconstituted via mixing 0.2 mM Mtb ClpP1 and 0.2 mM Mtb ClpP2 in the presence of 1 mM calprotamide A (dissolved in DMSO) in Mtb ClpP1 and ClpP2 buffer (20 μL), followed by incubation at 37 oC for 30 min. Prior to freezing the mixture was supplemented with 0.05 % Digitonin and then incubated for 1 min on grids blotted at force 1 for 6–7 s before plunging into liquid ethane. Cryo-EM grids were first screened on a 200-kV Talos Arctica transmission electron microscope. Data were collected by SerialEM51 on a 300-kV Titan Krios transmission electron microscope operated at a nominal magnification of x105,000, corresponding to a calibrated pixel size of 0.663 Å (image dimensions of 5,760 x 4,092 px) on the specimen level. Images were collected using a slit width of 20 eV on the GIF Quantum energy filter (Gatan) and a defocus range from -1.0 to -2.0 μm with a K3 direct electron detector (Gatan) in super-resolution counting mode. Three movie stacks were recorded per hole in a 3×3 matrix of holes acquired using beam-image shift with a maximum shift of 3.5 μm. Exposures of 1.2 s were dose-fractionated into 40 frames (30 ms per frame) with an exposure rate of approximately 1.313 electrons per Å2 per frame, resulting in a total electron exposure of 52.52 electrons per Å2. The data collection parameters are summarized in Supplementary Table 6.

Cryo-EM image processing
Data were processed in CryoSPARC v4.6.2 (Structura Biotechnology Inc.)52, 53 with standardized preprocessing. Motion correction and contrast transfer function (CTF) estimation were conducted using CryoSPARC’s patch-based algorithms54. Particles were selected using CryoSPARC’s template picker (particle diameter: 180 Å; angular sampling: 2 degrees). Following extraction into ~250 Å boxes with 2x binning, particles were cleaned through four rounds of 2D classification to exclude extraneous particles resulting in 1,627,466 particles. These were subject to non-uniform refinement in CryoSPARC (C1 symmetry) with reference model (EMD-21196 REF) filtered to 40 Å. This yielded a 2.8 Å reconstruction which was further improved to 2.6 Å by CTF-refinement55 and reference-based motion correction (Bayesian polishing56) in CryoSPARC. The resulting map showed poorly resolved density for calprotamide A, likely reflecting partial ligand occupancy. To better resolve the ligand binding region, we performed C7 symmetry expansion (11,388,629 particles) followed by local refinement using a mask encompassing a single stacked two-protomer ClpP1/P2 unit. One round of 3D-classification without image alignment was performed using this two-protomer focused mask (4 classes). This yielded two key classes, one class (13%) shows improved density of calprotamide A (bound) while the other (20%) shows no occupancy (unbound). These two were subjected to the final round of local refinement which yielded the final reconstruction of calprotamide A bound complex (1,464,563 particles at 2.77 Å, Supplementary Fig. 43c) and calprotamide A-unbound complex (2,252,037 particles at 2.80 Å, Supplementary Fig. 43c), respectively. Mask-corrected FSC curves were calculated in CryoSPARC based on the 0.143 criterion (Supplementary Fig. 43d-e). Local resolution estimation was performed in CryoSPARC (Supplementary Fig. 43f) and representative densities of different regions were shown (Supplementary Fig. 43g).

Model building and refinement
For the calprotamide A-bound complex, the structure of apo-Mtb ClpP1P2 complex (PDB: 6VGK) was fit into our cryo-EM density and a model of our NMR-determined calprotamide A was docked into the corresponding density in Chimera57. This was subsequently refined iteratively using ISOLDE58, Coot59 and Phenix60. For the calprotamide A-unbound complex, calprotamide A-bound complex was docked into the corresponding cryo-EM density in Chimera and subsequently refined iteratively using ISOLDE, Coot and Phenix. The reported resolution for models was calculated in Phenix based on the 0.5 criterion. Structural model refinements and validations were summarized in Supplementary Table 6 and figures were prepared in ChimeraX61.

Compound accumulation assay
S. aureus cells were cultured overnight in LB at 37 °C and 200 rpm and normalized to approximately 10⁹ CFU/mL in fresh LB. Bacterial suspensions were incubated with 4 μg/mL of test compounds in 14 mL round-bottom tubes at 37 °C with agitation (200 rpm) for 1 hour. Following incubation, cells were harvested by centrifugation at room temperature (10,000 × g, 1 min), washed three times with phosphate-buffered saline (PBS), and resuspended in LB to match the initial supernatant volume. The cell suspension and supernatant were extracted separately with 1:1 v/v ethyl acetate. The organic phase was evaporated to dryness under reduced pressure, resuspended in 100 μL of methanol and centrifuged (12,000 × g, 2 min) to remove particles. Compounds were quantified via LC-HRMS using 5 μL injection volume, with concentrations calculated by integrating peak areas. Experiments were performed in duplicate and the data were analyzed using GraphPad Prism 10.

N-acyl phenylalanine search
Genomes downloaded from the NCBI assembly and the JGI GOLD databases were scanned using antiSMASH v6.1.0 to detect NRPS BGCs. Using the antiSMASH output, a simple text search of candidate BGC region GenBank files was used to filter only regions containing at least one predicted Phe module using the pattern ‘specificity.+phe.*’ and C-starter domain using the pattern ‘aSDomain.+Condensation_Starter’. BGC regions containing Clp genes were identified in one of two ways. For genomes that were fully annotated before the antiSMASH analysis, a text search was performed on the BGC region GenBank files using the pattern ‘gene=”clp’. For unannotated (or sparsely annotated) genomes, the open reading frames of the genomes were extracted and were analyzed using mmseqs v14.7e28462 and a profile alignment built from the seed alignment for ClpP in PFAM63 (PF00574), ClpX and ClpA/C in NCBIFAM64 (TIGR00382). These BGCs were then manually examined for likely N-acetylated Phe modules, characterized by phenylalanine-selective A-domains either downstream of PKS modules or following lipid incorporating initiation domains such as coenzyme A ligase (CAL) containing module or a condensation starter (Cs) module.

Prediction of tuscamide
The structure prediction of tuscamide was generated based on an analysis of PKS domains, A-domain specificities, and NRPS modification domains (epimerization and N-methylation domains) present in its BGC (Supplementary Fig. 50). A-domain substrate specificity codes were compared to both the antiSMASH output and an in-house specificity code table collated from previously characterized natural products. For A-domains with more than two mismatches (<80% identity) to reference Stachelhaus codes, predictions were made using the antiSMASH ‘NRPSpredictor2 small clusters prediction’ tool. The initial fatty acid substrate was predicted based on a conserved glycine residue (Supplementary Fig. 50c), which is associated with a preference for medium-chain fatty acids65.

Prediction of additional library compounds
Structural predictions of additional N-acylphenylalanine compounds were generated based on A-domain substrate specificity and the presence of additional modification domains (i.e. epimerization and N-methylation domains) present in each BGC. A-domain substrate specificity codes were compared to both the antiSMASH output and an in-house specificity code table collated from previously characterized natural products. Amino acid identity predictions were determined by the A-domain specificity code with the closest match. In cases where multiple amino acids shared the same code or there was more than one code with the same match percentage, one was selected from the consensus of predictions generated by the antiSMASH NRPSPredictor2 tool.

N-acylphenylalanine compound synthesis
Standard Fmoc-based solid-phase peptide synthesis was used to produce all synthetic compounds, for more detailed methods see the Supplementary Information.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The discovery of novel natural products from uncultured soil bacteria, a rich source of bioactive small molecules, is challenging. This manuscript by Kan et al. reports an interesting case of natural products mining from soil metagenomes. The authors developed a target-directed metagenomic mining approach, resistance-CONKAT-seq, which links self-resistance genes to biosynthetic gene clusters (BGCs) to enable the discovery of metabolites with specific modes of action. The authors applied the method to identify the Calprotamides (A/B/C), a previously uncharacterized family of natural products with an unusual bis-γ-lactam bicyclic ring and the ability to activate Mycobacterium tuberculosis ClpP. The authors further determined the cryo-EM structures of Mtb ClpP1/P2 and calprotamide A-bound complex, which suggests that a medium-chain N-acylphenylalanine moiety is a convergently evolved “warhead” for ClpP modulation. Two BGCs predicted to encode this moiety and contain co-localized Clp genes inspired the authors to synthesize two corresponding compounds, jomthonic acid and tuscamide, which were revealed to have the ClpP-enhancing activity.\nOverall, this work is a continuation of previous studies on CONKAT-seq by the same group (Nat Commun 2019, 10, 3848; Nat Commun 2022, 13, 5256), which contains a considerable amount of experimental results combining metagenomics, chemical characterization, enzymology, and structural biology. While the idea “resistance-CONKAT-seq” lacks originality, this study discovers natural metabolites that could activate ClpP for the first time, as such molecules have been postulated but not previously characterized. More significantly, the discovery of convergent evolution of a medium-chain N-acylphenylalanine moiety for engaging with ClpP could inspire broader exploration for novel ClpP-modulating natural products from metagenomes. Taken together, this reviewer suggests publication of this manuscript after revisions as outlined below.\nMajor Comments:\n(1) Inadequate background\nThe introduction is well-written, but the background is inadequately covered. The authors do not adequately discuss prior research, including but not limited to the principle and successful applications of “CONKAT-seq”, the basic knowledge of ClpP and its structural study, and the concept of convergent evolution.\n(2) Mechanistic insight into calprotamide A-bound Mtb ClpP1/P2 complex\nThe functional difference in modulating ClpP between calprotamide A and ADEP binding to the H-pocket of ClpP2 is intriguing. However, the mechanistic explanation for why calprotamides enhance rather than inhibit ClpP protease activity remains speculative. Does the binding of calprotamides make ClpP1 and ClpP2 stack more tightly? The authors also claimed “calprotamide A’s binding to the H-pocket may trigger long-range allosteric changes”. All these hypothesis need additional structural and biochemical evidence (e.g., key residues mutagenesis and MD simulations), to which the authors can refer (Nat Struct Mol Biol 2010, 17, 471–478). Although the authors proposed that “The additional bis-γ-lactam bicyclic moiety found in calprotamide B would likely extend even further away from the ADEP binding site”, this reviewer suggests that the authors dock calprotamide B with Mtb ClpP1/P2 to explore the detailed mechanism underlying the unusual ring system.\n(3) Generality of the method “Resistance-CONKAT-seq”\nAlthough the authors claimed that Resistance-CONKAT-seq is a general strategy for target-directed discovery of natural products, the only proof example is ClpP-targeted calprotamides, which would lead the audience to consider the discovery of calprotamides is just an isolated case study, and this method is only suited for PKS and NRPS mining. To convincingly demonstrate that Resistance-CONKAT-seq is broadly applicable, this reviewer suggests that the authors provide a second case prediction, such as aminoglycoside antibiotics, through preliminary computational analysis.\nMinor Comments:\n1. Line 103, how can resistance-CONKAT-seq networks be verified by primers targeting the clpP node and one biosynthetic node? The authors should explain it in detail or present it in Fig. 1.\n2. Extended Data Fig. 2 was not cited in the main text.\n3. Line 130, “γ-lactams” should be “γ-lactam”.\n4. Line 147, delete “with”.\n5. Line 158, do the 10 Streptomyces strains used to test the antibiotic activity of the calprotamides contain biosynthetic genes similar to or homologous to the CPA BGC? Did the authors test the antibiotic activity of the calprotamides toward Gram-negative bacteria? And, how about the antibiotic activity of calprotamide C?\n6. In Fig. 3, the authors need to clarify the terms “FITC-casein”, “ZVKM-AMC”, and “Suc-LY-AMC” in the legend. The order of the labels “c,d,e” is wrong. Please revise the original c,d,e in the figure to e,c,d.\n7. Line 180, did the authors test the activity of calprotamide C toward ClpP?\n8. The order of “Extended Data Fig.6” and “Extended Data Fig. 7” should be changed.\n9. Line 255-257, why do the authors choose Mycobacterium tusciae JS617 to predict the ClpP targeting product?\n10. Line 306, a reference is needed for the claim ”…in recent antibiotic development efforts, there has been a growing interest in narrow-spectrum compounds.”\n11. In the “Supplementary Discussion”, line 43, what is the “ rarefaction analysis”, and how to evaluate the primer pairs using the phylogenetic analysis? The authors need to give a detailed explanation here.\n12. Supplementary Fig. 21, in the description “The key 1H-13C HMBC correlations (blue arrows) and 1H-15N HMBC correlations (red arrows) observed for Calprotamide B1”, it should be Calprotamide B2.\n13. Supplementary Table 6: The defocus value is typically negative, “Defocus range” in the table should be “-1.2 to -2.2”; Add “Micrographs used” to the table; “Map Sharpening B-factor” is typically not “0”, please check it; In the section “Refinement”, B factors () of protein and ligand should be presented.", "reviewer_2": "In this manuscript, the authors present resistance CONKAT seq, a clever and significant extension of their previously published CONKAT seq methodology. By integrating the identification of self-resistance genes, this new pipeline impressively bridges the gap between biosynthetic gene cluster (BGC) discovery and functional characterization, enabling a targeted approach to uncover natural products with specific modes of action. The successful identification and validation of the calprotamides as ClpP activators serves as a strong proof of concept for the power of this approach. Overall, this is a very interesting and well executed study that represents a notable advance in the field of natural product discovery from metagenomes. The work is certainly worthy of publication in this journal, pending the satisfactory clarification of the following points.\n1, The title is impactful but could be optimized for accuracy. The term \"warhead\" strongly implies an inhibitory or destructive mechanism (e.g., covalent inactivation), which is contrary to the reported function of the calprotamides as activators that enhance ClpP activity. Using a term that more precisely reflects this modulatory role would prevent potential misinterpretation by readers.\n2, The rationale for selecting ClpP as the target resistance gene is not clearly explained. A protease is an unconventional choice for a self-resistance mechanism against a NRPS derived product, making the link non-obvious to the reader. A brief introduction explaining the hypothesis or prior evidence that motivated this specific target selection would significantly strengthen the manuscript's logic. This context is crucial for readers to fully appreciate the discovery pipeline and to adapt this powerful strategy for their own research.\n3, The manuscript should briefly discuss the apparent paradox of ClpP's role as a resistance gene. The finding that calprotamides activate ClpP makes its classification as a \"resistance\" gene counterintuitive, as resistance typically involves neutralizing or exporting a toxic compound. Addressing how activating a protease protects the producing organism is crucial. This discussion would provide a more nuanced understanding of self-resistance and help readers broaden their own definition of what constitutes a viable resistance target for discovery pipelines.\n4, In the CONKAT seq panel of Figure 1a, the use of different shapes for the nodes in the network diagram is a helpful way to visually distinguish different gene types. However, the legend does not explain what these shapes represent. For a reader unfamiliar with the original 2019 CONKAT seq paper, it isn't immediately clear what the different nodes (e.g., triangles vs. squares) signify.\n5，For Figure 2, which depicts the calprotamide biosynthetic gene cluster, the functions of key enzymes such as CpaH and CpaR are not defined in the legend. To fully understand the proposed biosynthetic pathway, the reader must currently refer to a supplementary table.\n6， The structural elucidation of the Calprotamide-MtbClpP1/P2 interaction is a highlight of the manuscript and provides a strong foundation for understanding this new class of activators. However, to fully capitalize on these findings, the structural analysis and its presentation could be substantially strengthened with the following additions:\na. Quantitative Interaction Details: In the model presented in Figure 4a, the key intermolecular interactions are difficult to assess quantitatively. To validate the proposed binding mode, the figure should be updated to include labels for important interaction distances (e.g., hydrogen bond lengths in Å).\nb. Justification for the Model's Scope: The analysis appears to be based on a model of only two protomers. The manuscript would benefit from either a clear justification for this limited approach or, ideally, an expansion of the modeling and analysis to the full oligomeric complex. An analysis of the complete complex would be more compelling, as it could reveal crucial inter-subunit allosteric effects that are central to the activation mechanism.\nc. Mechanistic Hypothesis through Comparative Analysis: The discussion of an \"H pocket\" (lines 210-213) is intriguing but difficult to follow as its location is not clearly indicated in the figures. A more powerful and impactful analysis would be to use the full structural model to perform a comparative analysis between the apo (unbound), the calprotamide-bound (activated), and the ADEP-bound (dysregulated/inhibited) states. This comparison, with a specific focus on conformational changes in the H pocket and other structural elements, would provide the necessary data to propose a clear, testable hypothesis explaining the divergent functional outcomes of these two different ligands."}, "author_response": "Major comments\nComment 1. Inadequate background\nThe introduction is well-written, but the background is inadequately covered. The authors do not adequately\ndiscuss prior research, including but not limited to the principle and successful applications of “CONKAT-seq”,\nthe basic knowledge of ClpP and its structural study, and the concept of convergent evolution.\nResponse: To provide a more comprehensive review of the background information, we have added\nrelevant background details to the introduction section, including discussions covering CONKAT-seq,\nClpP, and convergent evolution. The changes made to the introduction are shown below.\nChanges made to address reviewer’s concerns:\nExpanded introduction (text added in response to Reviewer 1 in blue, text added in response to Reviewer\n2 in red): “The majority of bacteria present in the global microbiome are uncultured and remain an\nuntapped reservoir of bioactive small molecules1, 2. Heterologous expression of biosynthetic gene\nclusters (BGCs) cloned using DNA extracted directly from environmental samples (metagenomic DNA)\nprovides a means to access this chemical diversity. Although traditional culture-based natural product\ndiscovery programs have heavily relied on random screening to identify bioactive small molecules with\nclinically promising modes of action (MOAs), the large-scale heterologous expression and random\nscreening of metagenomic BGCs is labor intensive. A targeted search for natural products with specific,\nhigh value MOAs is much more appealing for metagenomic discovery3-6. It is now well established that,\nin some instances, a natural product BGC encodes a mutated copy of its molecular target that evades\nantibiotic binding7-9. This resistance mechanism is known as self-resistance. As a result, focusing\ndiscovery efforts on BGCs that co-localize with genes that encode molecular targets of interest presents\na strategy for prioritizing clusters that produce natural products with a desired MOA10-12. This approach\nhas been used successfully with cultured isolates due to the ease with which individual bacteria genomes\ncan be sequenced, assembled and bioinformatically interrogated13-15. Unfortunately, all three of these\nsteps remain a challenge with metagenomes, preventing a similar target-directed search for natural\nproducts produced by the uncultured bacterial majority. Even when using recently developed long-read\nsequencing methods that can generate fully assembled, large contiguous metagenomic sequences16, the\ndepth of sequencing is insufficient to capture the full diversity of soil metagenomes, making direct\nidentification of rare BGCs difficult.\nTo overcome this limitation, we previously developed a targeted sequencing approach called CONKAT-\nseq (co-occurrence network analysis of targeted sequences). This workflow enables the identification of\nrare physically clustered biosynthetic genes (i.e. BGCs) from complex (meta)genomic samples17, 18.\nCONKAT-seq leverages PCR amplification of conserved biosynthetic domains to detect co-occurrence\npatterns among genes across arrayed (meta)genomic libraries. The ability to sequence amplicons at high\ndepth makes this method both powerful and scalable, allowing the discovery of novel BGCs from low-\nabundance microbial populations that constitute the majority of soil biodiversity. This approach has\nproven effective for systematically uncovering natural product BGCs, both from environmental\nmetagenomes and libraries of cultured bacterial genomes. The PCR amplicon sequencing data used by\nCONKAT-seq offers an unmatched scale of metagenomic exploration which we hypothesized would\nallow for the identification of rare resistance gene associated BGCs. Here we report the development of\nresistance-CONKAT-seq (Fig. 1a), which links potential self-resistance genes encoding resistant variants\nof molecular targets with biosynthetic gene amplicon networks. By tracking their co-localization, this\napproach enables the identification of metagenomic BGCs that may encode natural products with specific\nMOAs. This method can be applied to any conserved essential gene of interest, but as a test case we\nsearched for clpP-associated BGCs in soil metagenomic libraries. ClpP is interesting because it is a\nvalidated yet underexplored antibiotic target, and although a growing number of ClpP-active molecules\nhave been identified in recent years, no ClpP-targeting drug has reached clinical use. ClpP is a highly\nconserved serine protease that degrades damaged proteins and is important for maintaining a healthy\ncell, making it a promising target for both antibacterial and cancer therapies19-21. The ClpP protease\ncomplex comprises two heptameric rings that stack to form a functional tetradecameric proteolytic core,\nwhich associates with a hexameric ATP-dependent unfoldase (e.g. ClpX, ClpC). Unfoldases recognize,\nunfold, and translocate protein substrates into the ClpP catalytic chamber for degradation. Their\nassociation with ClpP is mediated by docking of a conserved tripeptide loop (I/LGF loop) from the\nunfoldase into a specific hydrophobic pocket (H pocket) located at the interfaces between adjacent ClpP\nprotomers22-24.\nUsing ClpP directed resistance-CONKAT-seq we identified the calprotamide antibiotics which both\nactivate native Mycobacterium tuberculosis (Mtb) ClpP and enhance its activity once activated. We\nfurther showed that the medium-chain (C6-C8) N-acylphenylalanine substructure found in the\ncalprotamides is a common, yet overlooked, natural motif for targeting ClpP. This N-acylphenylalanine\nsubstructure represents a case of convergent evolution, in which a chemical motif has independently\nevolved across distinct biosynthetic pathways to target ClpP. Our identification of this evolutionary\nconvergence establishes a molecular handle for discovering ClpP-targeting compounds. Guided by this\ninsight, we synthesized additional ClpP-active molecules, bioinformatically predicted from\nuncharacterized BGCs, some of which exhibit antibiotic activity. While here we targeted ClpP, by\nchanging resistance gene specific degenerate primers, resistance-CONKAT-seq can be tuned to any\npotential molecular target thereby providing a generalized approach for the discovery of natural products\nwith desired MOAs from complex metagenomes.” (Line 37-90)\nComment 2. Mechanistic insight into calprotamide A-bound Mtb ClpP1/P2 complex\nThe functional difference in modulating ClpP between calprotamide A and ADEP binding to the H-pocket of\nClpP2 is intriguing. However, the mechanistic explanation for why calprotamides enhance rather than inhibit\nClpP protease activity remains speculative.\n2a. Does the binding of calprotamides make ClpP1 and ClpP2 stack more tightly? The authors also claimed\n“calprotamide A’s binding to the H-pocket may trigger long-range allosteric changes”. All these hypotheses\nneed additional structural and biochemical evidence (e.g., key residues mutagenesis and MD simulations),\nto which the authors can refer (Nat Struct Mol Biol 2010, 17, 471–478).\nResponse: We thank the reviewer for this thoughtful comment. While we agree that further mechanistic\ninsight would be valuable, we were unfortunately not able to build a complete model of the 14-mer\ncomplex for calprotamide A-bound Mtb ClpP, which limited our ability to elucidate the detailed activation\nmechanism. Additional explanation of this limitation is provided in our response to Reviewer 2’s comment\n6b. Briefly, the full tetradecameric complex could not be resolved under C1 symmetry due to poorly\nresolved densities at the ligand binding sites, suggesting site heterogeneity likely arising from mixtures\nof bound and unbound states. To address this, we focused on the two-protomer complex and performed\nintensive 3D classification and local refinement, which yielded a class of two-protomer units that exhibited\nimproved density at the binding site. All structural analyses in this study are based on this calprotamide\nA-occupied two-protomer complex.\nAlignment of the two-protomer structures revealed no detectable difference in the protomer apical length\n(Fig. 4d). We therefore focused our analysis on characterizing the calprotamide A binding motif to guide\nfuture ClpP-targeting natural product discovery, rather than performing an in-depth structural\ninvestigation of long-range allosteric changes. In line with the reviewer’s suggestion, we performed key\nresidue mutagenesis experiments to show the binding position difference between calprotamide A and\nADEP and added this data in Supplementary Fig. 45.\nNote: A key hypothesis that emerged from our study is that the N-acylphenylalanine motif represents a\nscaffold for targeting ClpP. To further explore this hypothesis, we have synthesized and evaluated an\nadditional library of BGC-inspired N-acylphenylalanine containing compounds. These results have been\nadded to the revised manuscript. Please see our response to Reviewer 2, comment 6c for more details.\nChanges made to address reviewer’s concerns:\nUpdated text in blue: “…To further compare the difference in binding between calprotamide A and ADEP,\nwe performed alanine mutagenesis of two key residues in Mtb ClpP2, R207 and Q101. R207 forms a salt\nbridge with calprotamide A but not with ADEP, whereas Q101 forms a hydrogen bond with ADEP but not\nwith calprotamide A (Supplementary Fig. 45a). As predicted by our model, the R207A mutation more\nstrongly impaired calprotamide A-mediated enhancement of Mtb ClpP1P2 peptidase activity than it did\nADEP-mediated enhancement. Conversely, the Q101A mutation had a greater effect on ADEP-mediated\nenhancement than on calprotamide A-mediated enhancement (Supplementary Fig. 45b)….” (Line 227-\n233)\nSupplementary Fig. 45. Key site mutagenesis demonstrates distinct binding modes of\ncalprotamide A and ADEP. a. Side-by-side binding mode comparison of calprotamide A (yellow)\nand ADEP7 (purple) with mutated residues R207 and Q101 indicated. b. Initial rate ratio of ADEP\nto calprotamide A for Mtb ClpP2 WT and key residue mutants. The assay was performed using the\nMtb ClpP1P2 peptidase activity assay under the same conditions as described in Figure 3b.\nConcentration of all compounds is 10 μM. Experiment was done in triplicates, with individual data\npoints shown as dots. P values were calculated using one-way ANOVA in Prism 10.\n2b. Although the authors proposed that “The additional bis-γ-lactam bicyclic moiety found in calprotamide B\nwould likely extend even further away from the ADEP binding site”, this reviewer suggests that the authors\ndock calprotamide B with Mtb ClpP1/P2 to explore the detailed mechanism underlying the unusual ring system.\nResponse: We attempted to determine the structure of calprotamide B-bound Mtb ClpP1P2 by cryo-EM.\nHowever, despite multiple attempts, the ligand density remained poor, likely due to limited calprotamide\nB solubility. As recommended by the reviewer, we therefore performed molecular docking studies. The\nresulting model suggests that calprotamide B occupies a binding position similar to that of calprotamide\nA. Its N-acylphenylalanine moiety docks in the same position observed for calprotamide A in the cryo-\nEM structure, and the remainder of the PKS/NRPS-derived scaffold extends in the same general direction\nas that of calprotamide A (Review Fig. 1).\nThe bis-γ-lactam bicyclic moiety does not appear to form additional contacts with Mtb ClpP2. However,\nbecause it is positioned at the apical surface of ClpP2, it may participate in distinct interactions with ClpC1\nwhen the full ClpP1/P2:C1 complex is assembled. It is also possible that the bis-γ-lactam serves to mask\nthe negative charge that would normally be present after release by the thioesterase, thereby improving\nbioavailability. This is consistent with the higher cellular accumulation of calprotamide B we observed\n(Supplementary Fig. 42) and could help explain its stronger antibacterial activity relative to calprotamide\nA (Table 1).\nBecause any discussion of this docking analysis would be quite speculative, we have elected not to\ninclude it in the revised manuscript. We believe such analysis would be more appropriate for a follow-up\nstudy focused on the ClpP1/P2:C1 complex. We have removed the sentence speculating on the\npositioning of the bis-γ-lactam bicyclic moiety and replaced it with a more general discussion of the bis-\nγ-lactam feature.\nReview Fig. 1. Molecular docking of calprotamide B bound to Mtb ClpP. a. Superimposition of\ncalprotamide B binding position with calprotamide A. b. Key interactions between calprotamide B and\nresidues on Mtb ClpP2. Mtb ClpP2 protein is shown in yellow, calprotamide A is shown in orange, and\ncalprotamide B is shown in blue.\nNew text added to revised manuscript: “…Whether the unusual bis-γ-lactam bicyclic moiety in\ncalprotamide B forms additional interactions with Mtb ClpP2 or the ClpP1/P2:C1 complex remains to be\ndetermined. It is possible that the bis-γ-lactam serves primarily to mask the negative charge that would\nnormally be generated upon release by the thioesterase, thereby improving bioavailability. This is\nconsistent with the higher cellular accumulation of calprotamide B we observed (Supplementary Fig. 42) and\nmay help explain its stronger antibacterial activity relative to calprotamide A (Table 1).” (Line 233-238)\nComment 3. Generality of the method “Resistance-CONKAT-seq”\nAlthough the authors claimed that Resistance-CONKAT-seq is a general strategy for target-directed discovery\nof natural products, the only proof example is ClpP-targeted calprotamides, which would lead the audience to\nconsider the discovery of calprotamides is just an isolated case study, and this method is only suited for\nPKS and NRPS mining. To convincingly demonstrate that Resistance-CONKAT-seq is broadly applicable,\nthis reviewer suggests that the authors provide a second case prediction, such as aminoglycoside antibiotics,\nthrough preliminary computational analysis.\nResponse: We appreciate the reviewer’s valuable suggestion. Resistance-CONKAT-seq is designed to\ntarget biosynthetic systems that produce structurally diverse metabolites, and therefore molecules with\ndistinct modes of action. Unfortunately, aminoglycosides represent a narrow class of natural products\nwith limited structural variation, all of which target the 16S ribosomal RNA. As such, resistance-CONKAT-\nseq is not required for their discovery. Unlike aminoglycosides, NRPS and PKS systems generate\nstructurally diverse compounds with a wide range of biological targets, making resistance-CONKAT-seq\na powerful tool for deconvoluting their MOAs.\nThe methodology of resistance-CONKAT-seq can be expanded by searching for either different\nbiosynthetic systems or different targets. We elected to show the generality of the method by expanding\nthe set of self-resistance genes targeted. To demonstrate that the discovery of the calprotamides is not\nan isolated finding, we expanded the resistance-CONKAT-seq screening to include two additional self-\nresistance genes, DNA gyrase subunit B (gyrB) and serine-tRNA ligase (serS), and applied the approach\nto two additional soil metagenomic libraries. This expanded screening identified four additional validated\nnetworks, corresponding to one gyrB-associated NRPS BGC, two serS-associated NRPS BGCs, and\none serS-associated PKS BGC. These new results are presented in Supplementary Fig. 3, with a\ncorresponding description included in the results section of the main text.\nChanges made to address reviewer’s concerns:\nNew text in blue: “Cosmids associated with this network were recovered from the archived library,\nsequenced and annotated. The BGC, which we have called the CPA BGC (Supplementary Fig. 2), was\nrecovered on two overlapping cosmids: AZ52-w347 and AZ52-w337 (Fig. 1c). It did not closely resemble\na BGC associated with a known natural product or any uncharacterized BGCs found in publicly available\ndatabases.\nTo show the generality of resistance-CONKAT-seq, we expanded the screening by including two\nadditional self-resistance genes, DNA gyrase subunit B (gyrB) and serine-tRNA ligase (serS), and applied\nthe approach to two additional metagenomic soil libraries. This expanded screening identified four\nadditional validated networks, corresponding to one gyrB-associated NRPS BGC, two serS-associated\nNRPS BGCs, and one serS-associated PKS BGC (Supplementary Fig. 3).\nExpression and characterization of calprotamide A-C from the CPA BGC” (Line 106-118)\nSupplementary Fig. 3. Additional BGCs discovered from soil metagenomes using resistance-\nCONKAT-seq. Soil 1 is the soil sample used to discover the calprotamides. Each circle (node)\nrepresents a gene, and each connecting line indicates a co-occurrence event between two genes. AD:\ngene encoding adenylation domain; KS: gene encoding ketosynthase domain; gyrB: gene encoding\nDNA gyrase subunit B; serS: gene encoding serine-tRNA ligase.\nMinor comments\n1. Line 103, how can resistance-CONKAT-seq networks be verified by primers targeting the clpP node and one\nbiosynthetic node? The authors should explain it in detail or present it in Fig. 1.\nResponse: The details regarding the network verification step have been added to the corresponding\nsentence.\nNew text in blue: “…Predicted resistance-CONKAT-seq networks were verified by PCR using primers\ntargeting the clpP node and one biosynthetic node, confirming that the co-occurrence of clpP and\nbiosynthetic gene amplicons matched the expected well patterns predicted by resistance-CONKAT-\nseq.…” (Line 103-105)\n2. Extended Data Fig. 2 was not cited in the main text.\nResponse: Extended Data Fig. 2 has been changed to Supplementary Fig. 2 and is now cited in the\nsentence below.\nAdditional text in blue: “The BGC, which we have called the CPA BGC (Supplementary Fig. 2), was\nrecovered on two overlapping cosmids: AZ52-w347 and AZ52-w337 (Fig. 1c).” (Line 107-109)\n3. Line 130, “γ-lactams” should be “γ-lactam”.\nResponse: The word “γ-lactams” has been corrected to “γ-lactam”.\nAdditional text in blue: “In the case of the 655 feature the C-terminal carboxylic acid of the hybrid peptide-\npolyketide structure was replaced with a bis-γ-lactam bicyclic moiety, and in the case of the 673 feature\none γ-lactam was hydrolyzed (Supplementary Fig. 40).” (Line 137-139)\n4. Line 147, delete “with”.\nResponse: The word “with” has been deleted.\nChanged to: “Further extension of with one malonyl CoA and a serine would produce the precursor to\ncalprotamide B.” (Line 155-156)\n5. Line 158, do the 10 Streptomyces strains used to test the antibiotic activity of the calprotamides contain\nbiosynthetic genes similar to or homologous to the CPA BGC? Did the authors test the antibiotic activity of the\ncalprotamides toward Gram-negative bacteria? And, how about the antibiotic activity of calprotamide C?\nResponse: (1) No biosynthetic genes similar or homologous to the CPA BGC were identified in the\nStreptomyces strains used for antibiotic activity assays. (2) The antibiotic activity of the calprotamides\nagainst Gram-negative bacteria is summarized in Supplementary Table 5. (3) Calprotamide C is a\ndegradation product that accumulates only at low levels in culture broth; Therefore, aside from mass-\nspec analysis, we were unable to obtain sufficient quantities to perform antibiotic or enzyme assays.\n6. In Fig. 3, the authors need to clarify the terms “FITC-casein”, “ZVKM-AMC”, and “Suc-LY-AMC” in the legend.\nThe order of the labels “c,d,e” is wrong. Please revise the original c,d,e in the figure to e,c,d.\nResponse: (1) The terms “FITC-casein”, “ZVKM-AMC”, and “Suc-LY-AMC” have been clarified in the\nlegend of Figure 3. (2) The order of the labels has been corrected in Figure 3.\nNew text in blue: “Fig. 3. Calprotamides A and B enhance and activate Mtb ClpP. a. Mtb ClpP1/P2:C1\nprotease activity assay performed using FITC-casein and 2.5 mM of Bz-LL. b. Mtb ClpP1/P2 peptidase\nactivity assay performed using ZVKM-AMC and 2.5 mM of Bz-LL. c. S. aureus ClpP peptidase activity\nassay performed using Suc-LY-AMC. d. Human mitochondria ClpP peptidase assay. e. Mtb ClpP1/P2\npeptidase activity assay performed without Bz-LL. Each curve represents a single dataset from the\nreplicates. FITC-casein: fluorescein isothiocyanate labeled casein, used as the substrate for Mtb\nClpP1/P2:C1 protease activity. ZVKM-AMC: 7-amino-4-methylcoumarin labeled Z-Val-Lys-Met, used as\nthe substrate for Mtb ClpP1/P2 peptidase activity. Suc-LY-AMC: 7-amino-4-methylcoumarin labeled N-\nsuccinyl-Leu-Tyr, used as the substrate for S. aureus ClpP peptidase activity. AU: arbitrary units.” (Line\n832-840)\n7. Line 180, did the authors test the activity of calprotamide C toward ClpP?\nResponse: As with our response to point 5, we were unable to obtain sufficient quantities to perform\nenzyme assays.\n8. The order of “Extended Data Fig.6” and “Extended Data Fig. 7” should be changed.\nResponse: The order of “Extended Data Fig. 6” and “Extended Data Fig. 7” has been changed, the\nfigures have been moved to the Supplementary Information (Supplementary Fig. 42 and 43), and the\ncorresponding citations in the main text have been updated accordingly.\n9. Line 255-257, why do the authors choose Mycobacterium tusciae JS617 to predict the ClpP targeting product?\nResponse: Among all BGCs shown in Figure 5b, only the Mycobacterium tusciae JS617 BGC had a\nsufficiently confident structural prediction to justify compound synthesis.\n10. Line 306, a reference is needed for the claim ”…in recent antibiotic development efforts, there has been a\ngrowing interest in narrow-spectrum compounds.”\nResponse: References have been added for the claim.\nUpdated text in blue: “Although broad spectrum antibiotics have historically been prioritized, in recent\nantibiotic development efforts there has been a growing interest in narrow spectrum compounds25-29.”\n(Line 377-379)\n11. In the “Supplementary Discussion”, line 43, what is the “ rarefaction analysis”, and how to evaluate the primer\npairs using the phylogenetic analysis? The authors need to give a detailed explanation here.\nResponse: A detailed explanation of primer evaluation based on rarefaction and phylogenetic analyses\nhas been added to the Supplementary Discussion.\nOriginal text: “The resulting amplicons were sequenced, and primer pairs were ranked based on both\nrarefaction analysis (i.e., the number of unique gene variants) (Extended Data Fig. 1c) as well as\nphylogenetic analysis (i.e., the diversity of gene variants) (Extended Data Fig. 1d). The primer pair Deg-\nClpP-F2 and -R2, at an annealing temperature of 55 °C, provided the highest clpP diversity leading us to\nselect it for resistance-CONKAT-seq.”\nUpdated text: “…The resulting amplicons were sequenced and analyzed by rarefaction analysis\n(Supplementary Fig. 1c). At a sequencing depth of 6,000 amplicons per sample, the primer pair Deg-\nClpP-F2 and -R2 (ClpP-2-50 and ClpP-2-55) generated a higher number of OUT variants (OUT threshold\n= 97%) than the primer pair Deg-ClpP-F1 and -R1 (ClpP-1-50 and ClpP-1-55). Among all samples, Deg-\nClpP-F2 and -R2 at an annealing temperature of 55 °C generates the greatest number of OUT variants.\nTherefore, amplicons from these two samples were further analyzed using a phylogenetic tree\n(Supplementary Fig. 1d). The phylogenetic tree shows that ClpP-2-50 and ClpP-2-55 present similar\ndiversity of gene variants. Based on these results, the primer pair Deg-ClpP-F2 and -R2 at annealing\ntemperature of 55 °C was selected for resistance-CONKAT-seq.” (Supplementary Information, Line 61-\n68)\n12. Supplementary Fig. 21, in the description “The key 1H-13C HMBC correlations (blue arrows) and 1H-15N\nHMBC correlations (red arrows) observed for Calprotamide B1”, it should be Calprotamide B2.\nResponse: “Calprotamide B1” has been changed to “Calprotamide B2”.\n13. Supplementary Table 6: The defocus value is typically negative, “Defocus range” in the table should be “-1.2\nto -2.2”; Add “Micrographs used” to the table; “Map Sharpening B-factor” is typically not “0”, please check it; In\nthe section “Refinement”, B factors () of protein and ligand should be presented.\nResponse: Values have been checked and updated in Supplementary Table 6 according to the\nreviewer’s comment.\nUpdated text in blue:\nSupplementary Table 6. Cryo-EM data collection, refinement and validation statistics.\nMtb ClpP1P2 Mtb ClpP1P2\ncomplex with complex\ncalprotamide A\nEMDB ID EMD-71299 EMD-71300\nPDB ID 9P53 9P54\nData collection\nMicroscope Titan Krios\nDetector K3 summit\nVoltage (kV) 300\nPixel size (Å) 0.3315\nTotal electron exposure 52.52\n(e-/Å2)\nDefocus range (μm) -1.2 to -2.2\nMicrographs collected 10,195\nMicrographs used 9946\nReconstruction\nFinal particle images 1,464,663 2,252,037\nPixel size (Å) 0.98414 0.98414\nBox size (pixels) 256 256\nResolution (Å) 2.77 2.79\n(FSC = 0.143)\nMap Sharpening B-factor (Å2) -83.04 -93.47\nModel composition\nNon-hydrogen atoms 5,715 5,463\nProtein residues 7,41 713\nLigands 1 0\nMetals 0 0\nWaters 0 0\nRefinement\nResolution (Å)\n2.77 2.8\n(FSC = 0.5)\nModel-to-map CC (mask) 0.84 0.81\nModel-to-map CC (volume) 0.84 0.81\nR.m.s deviations\nBond length (Å) 0.009 0.013\nBond angles (°) 1.279 1.452\nProtein B factor 63.19/267.36/125.61 30.00/277.71/143.28\nLigand B factor 124.59/182.92/155.54\nValidation\nMolProbity score 1.77 1.72\nClash score 8.15 6.12\nRamachandran plot\nOutliers (%) 0.0 0.0\nAllowed (%) 2.87 3.60\nFavored (%) 97.13 96.40\nRotamer outliers (%) 1.67 1.57\nC-beta deviations (%) 0.14 0\nReviewer #2 (Remarks to the Author):\nIn this manuscript, the authors present resistance CONKAT seq, a clever and significant extension of their\npreviously published CONKAT seq methodology. By integrating the identification of self-resistance genes, this\nnew pipeline impressively bridges the gap between biosynthetic gene cluster (BGC) discovery and functional\ncharacterization, enabling a targeted approach to uncover natural products with specific modes of action. The\nsuccessful identification and validation of the calprotamides as ClpP activators serves as a strong proof of\nconcept for the power of this approach. Overall, this is a very interesting and well executed study that represents\na notable advance in the field of natural product discovery from metagenomes. The work is certainly worthy of\npublication in this journal, pending the satisfactory clarification of the following points.\n1, The title is impactful but could be optimized for accuracy. The term \"warhead\" strongly implies an inhibitory or\ndestructive mechanism (e.g., covalent inactivation), which is contrary to the reported function of the\ncalprotamides as activators that enhance ClpP activity. Using a term that more precisely reflects this modulatory\nrole would prevent potential misinterpretation by readers.\nResponse: We thank the reviewer for this thoughtful suggestion. To improve accuracy and avoid\npotential misinterpretation, we have replaced the term “warhead” with “motif” in our title and throughout\nthe manuscript.\n2, The rationale for selecting ClpP as the target resistance gene is not clearly explained. A protease is an\nunconventional choice for a self-resistance mechanism against a NRPS derived product, making the link non-\nobvious to the reader. A brief introduction explaining the hypothesis or prior evidence that motivated this specific\ntarget selection would significantly strengthen the manuscript's logic. This context is crucial for readers to fully\nappreciate the discovery pipeline and to adapt this powerful strategy for their own research.\nResponse:\nSelection of ClpP as our target\nWe developed resistance-CONKAT-seq to identify BGCs encoding natural products that interact with\nbiologically important protein targets. These targets can include any functionally essential proteins,\nwhether or not they have known natural product ligands, thereby providing access to new sources of\nbioactive molecules with distinct MOAs. We selected clpP for this study because ClpP is a validated yet\nunderexplored antibiotic target essential for maintaining cellular protein homeostasis, and no ClpP-\ntargeting compound has reached clinical use. We don’t anticipate any predictable limitations to the\ngeneralizability of the method beyond the need for an essential gene to which you can design degenerate\nprimers. We believe that resistance-CONKAT-seq can be broadly applied by other researchers to\ndiscover novel BGCs encoding natural products that act on diverse protein targets of interest. To\ndemonstrate its generality, we have expanded our screening to include two additional target genes, gyrB\nand serS, as described in our response to Reviewer 1’s Major Comment 3. We have also clarified the\nrationale for selecting clpP in the Introduction.\nConundrum of protease and NRPS-derived product\nWe thank the reviewer for this thoughtful observation. We had not previously considered the possibility\nthat an NRPS-derived product might be susceptible to degradation by the ClpP system. Fortunately, to\nour knowledge, no NRPS-derived natural product is known to be digested by a resistance ClpP protease,\nlikely due to modifications that limit accessibility to ClpP or the inherent peptide sequence specificity of\nthe ClpP system. Additionally, the ADEP BGC serves as a relevant precedent, as it contains a clpP\nresistance gene and encodes an NPRS product that directly targets ClpP without being cleaved by it.\nChanges made to address reviewer’s concerns:\nUpdated introduction (blue section updated for Reviewer 1, red section updated for Reviewer 2): “…This\nmethod can be applied to any conserved essential gene of interest, but as a test case we searched for\nclpP-associated BGCs in soil metagenomic libraries. ClpP is interesting because it is a validated yet\nunderexplored antibiotic target, and although a growing number of ClpP-active molecules have been\nidentified in recent years, no ClpP-targeting drug has reached clinical use. ClpP is a highly conserved\nserine protease that degrades damaged proteins and is important for maintaining a healthy cell, making\nit a promising target for both antibacterial and cancer therapies19-21. The ClpP protease complex\ncomprises two heptameric rings that stack to form a functional tetradecameric proteolytic core, which\nassociates with a hexameric ATP-dependent unfoldase (e.g. ClpX, ClpC). Unfoldases recognize, unfold,\nand translocate protein substrates into the ClpP catalytic chamber for degradation. Their association with\nClpP is mediated by docking of a conserved tripeptide loop (I/LGF loop) from the unfoldase into a specific\nhydrophobic pocket (H pocket) located at the interfaces between adjacent ClpP protomers22-24.” (Line 68-\n78)\n3, The manuscript should briefly discuss the apparent paradox of ClpP's role as a resistance gene. The finding\nthat calprotamides activate ClpP makes its classification as a \"resistance\" gene counterintuitive, as resistance\ntypically involves neutralizing or exporting a toxic compound. Addressing how activating a protease protects the\nproducing organism is crucial. This discussion would provide a more nuanced understanding of self-resistance\nand help readers broaden their own definition of what constitutes a viable resistance target for discovery pipelines.\nResponse: We thank the reviewer for this comment and apologize for the lack of clarity. The self-\nresistance mechanism we focus on involves BGCs that encode a resistant copy of their molecular target,\nwhich differs from traditional resistance mechanisms such as antibiotic neutralization or export. In cells\nexpressing resistant ClpP proteins, the ClpP tetradecamer likely forms a heteromeric complex that is\nresistant to activation by the compound it produces. We have revised the description of the method in\nthe introduction to better explain the approach and added a discussion to address how resistance clpP\nmay confer resistance to ClpP activators.\nChanges made to address reviewer’s concerns:\nUpdated Introduction text in blue: “…It is now well established that, in some instances, a natural product\nBGC encodes a mutated copy of its molecular target that evades antibiotic binding7-9. This resistance\nmechanism is known as self-resistance.…” (Line 43-45)\nUpdated Introduction text in blue: “…Here we report the development of resistance-CONKAT-seq (Fig.\n1a), which links potential self-resistance genes encoding resistant variants of molecular targets with\nbiosynthetic gene amplicon networks. By tracking their co-localization, this approach enables the\nidentification of metagenomic BGCs that may encode natural products with specific MOAs.…” (Line 64-\n68)\nUpdated Discussion text in blue: “Our discovery of the calprotamides validates the power of resistance-\nCONKAT-seq to target the discovery of natural products with specific molecular targets from\nmetagenomes. It also provides additional compelling evidence that the soil metagenome encodes\nunexplored biosynthetic diversity. The calprotamides represent a previously unreported natural product\nfamily with an unprecedented bis-γ-lactam bicyclic ring system. They also exhibit unique ClpP activity as\nthey enhance both Mtb protease and peptidase activities. In native cells expressing the self-resistant\nClpP protein, the ClpP tetradecamer may form a heteromeric complex that is resistant to activation by\nthe compound it produces. While ClpP activators like Bz-LL have been postulated to exist in nature30, 31,\nthere were no characterized examples before our discovery of the calprotamides. This type of Clp\nprotease activator is likely produced by other bacteria32; however, they may have been overlooked in\nprevious studies if they exhibit a narrow spectrum of activity, similar to the calprotamides. It will be\ninteresting to further explore the activity spectrum of the calprotamides to identify what factors contribute\nto their narrow range of activity. (Line 336-347)\n4, In the CONKAT seq panel of Figure 1a, the use of different shapes for the nodes in the network diagram is a\nhelpful way to visually distinguish different gene types. However, the legend does not explain what these shapes\nrepresent. For a reader unfamiliar with the original 2019 CONKAT seq paper, it isn't immediately clear what the\ndifferent nodes (e.g., triangles vs. squares) signify.\nResponse: To clarify the relationships among nodes, networks, genes, and BGCs, we labeled both the\nnetworks and the corresponding BGCs in Figure 1a and aligned them accordingly. We also added details\ndescribing the visualization of the resistance-CONKAT-seq networks in the legend of Figure 1a.\nChanges made to address reviewer’s concerns:\nUpdated Figure 1a:\nOriginal figure\nRevised figure\nUpdated figure legend (new text in blue)\nFig 1. Discovery of calprotamides using resistance-CONKAT-seq. a. CONKAT-seq leverages PCR\nand the partitioned nature of arrayed metagenomic libraries to identify networks of biosynthetic domains\nassociated with novel BGCs. BGCs that encoded metabolites with specific modes of action can be\nmined from complex metagenomes using resistance-CONKAT-seq which tracks the co-localization of\nresistance and biosynthetic genes in complex metagenomes. Visualization of the\n(Resistance-)CONKAT-seq networks: Each circle (node) represents a gene, and each connecting line\nindicates a co-occurrence event between two genes. b. Screening for clpP containing BGCs using\nresistance-CONKAT-seq data from a soil metagenomic library. c. The CPA BGC was recovered on two\noverlapping eDNA cosmids and reassembled using transformation-associated recombination in yeast.\nd. To induce the CPA BGC, Streptomyces promoters were introduced at various locations (red arrows).\ne. HPLC-MS trace of culture broth extracts from S. albus transformed with promoter engineered\nconstructs. Peaks associated with clone specific mass signals are labeled: 1 (m/z=530), 2 (m/z=655)\nand 3 (m/z=673). f. HRMS data and chemical structures of calprotamide A (1), B (2) and C (3).\n5，For Figure 2, which depicts the calprotamide biosynthetic gene cluster, the functions of key enzymes such\nas CpaH and CpaR are not defined in the legend. To fully understand the proposed biosynthetic pathway, the\nreader must currently refer to a supplementary table.\nResponse: We have added a note describing the predicted functions of CpaH and CpaR to the legend\nof Figure 2.\nChanges made to address reviewer’s concerns:\nUpdated text in blue: “Fig 2. Proposed biosynthesis of calprotamide A-C. The biosynthesis of the\ncalprotamides can be rationalized based on a detailed analysis of the 4 PKS and 4 NRPS modules\nencoded by the seven CPA megasynth(et)ase genes. AT: Acyltransferase domain, CP: carrier protein,\nKS: Ketosynthase domain, DH: Dehydratase domain, KR: Ketoreductase domain, C: Condensation\ndomain, A: Adenylation domain, nMT: N-methyltransferase, TE: Thioesterase domain, CpaH: predicted\nmethyl transferase, CpaR: predicted 3-methylcrotonyl-CoA carboxylase subunit.” (Line 825-830)\n6, The structural elucidation of the Calprotamide-MtbClpP1/P2 interaction is a highlight of the manuscript and\nprovides a strong foundation for understanding this new class of activators. However, to fully capitalize on these\nfindings, the structural analysis and its presentation could be substantially strengthened with the following\nadditions:\n6a. Quantitative Interaction Details: In the model presented in Figure 4a, the key intermolecular interactions are\ndifficult to assess quantitatively. To validate the proposed binding mode, the figure should be updated to include\nlabels for important interaction distances (e.g., hydrogen bond lengths in Å).\nResponse: Information on key interaction distances has been added to Figure 4b. The original Figure\n4b has been merged with Figure 4a to improve the figure’s overall clarity.\nChanges made to address reviewer’s concerns:\nUpdated Figure 4a-b:\nOriginal figure\nUpdated figure\nUpdated figure legend\nFig. 4. Cryo-EM analysis of calprotamide A binding to Mtb ClpP1/P2 complex. a. Binding site of\ncalprotamide A (yellow) on adjacent ClpP2 protomers. The zoomed-in view (red dashed box) highlights\nthe hydrophobic pocket at the ClpP2 interface. Cryo-EM density map (gray mesh) of calprotamide A\n(stick) is shown below the zoomed-in binding site view. b. Key interactions (hydrogen bonds and salt\nbridges) between calprotamide A and residues on Mtb ClpP2. Calprotamide A is shown in yellow, and\nthe interacting amino acid residues are shown in gold.\n6b. Justification for the Model's Scope: The analysis appears to be based on a model of only two protomers. The\nmanuscript would benefit from either a clear justification for this limited approach or, ideally, an expansion of the\nmodeling and analysis to the full oligomeric complex. An analysis of the complete complex would be more\ncompelling, as it could reveal crucial inter-subunit allosteric effects that are central to the activation mechanism.\nResponse: We appreciate the reviewer’s valuable comment and the opportunity to clarify this point. We\ninitially attempted to resolve the full tetradecameric complex using C1 symmetry; however, the resulting\nC1 map showed poorly resolved ligand density at all binding sites. This suggested heterogeneity across\nthe ligand binding sites, potentially due to mixtures of bound/unbound states. To improve the\nreconstruction of the ligand, we manually mixed two-protomer units and performed local refinement and\nintensive 3D classification. Through this approach, we identified one class of two-protomer units that\nshowed clear density at the binding site. This focused 3D classification inherently limited the density\nquality at the other binding sites. For this reason, we restricted our structural analysis to the two-protomer\nunit.\nOur current structure identifies a shared binding site for ADEP and calprotamide A but does not allow us\nto mechanistically explain their different functional outcomes. Because the structure reveals a common\nbinding site, our follow up studies focus on the ligand binding position and the binding motif that can be\ninterpreted from the data, rather than on the detailed activation process induced by ligand binding. We\nhave added text to both the Results and Methods sections to clarify this point, as shown below. For\nadditional information on this topic, please see our discussion of the testable hypothesis suggested by\nour structure in response to comment 6c below.\nChanges made to address reviewer’s concerns:\nUpdated Methods text in blue: “…This yielded a 2.8 Å reconstruction which was further improved to 2.6\nÅ by CTF-refinement33 and reference-based motion correction (Bayesian polishing34) in CryoSPARC.\nThe resulting map showed poorly resolved density for calprotamide A, likely reflecting partial ligand\noccupancy. To better resolve the ligand binding region, we performed C7-symmetry expansion\n(11,388,629 particles) followed by local refinement using a mask encompassing a single stacked two-\nprotomer ClpP1/P2 unit. One round of 3D-classification without image alignment was performed using\nthis two-protomer focused mask (4 classes). This yielded two key classes, one class (13%) shows\nimproved density of calprotamide A (bound) while the other (20%) shows no occupancy (unbound).\nThese two classes were subjected to a final round of local refinement which yielded a calprotamide A\nbound complex (1,464,563 particles at 2.77 Å, Supplementary Fig. 43c) and calprotamide A-unbound\ncomplex (2,252,037 particles at 2.80 Å, Supplementary Fig. 43c), respectively….” (Line 581-585)\nUpdated Results text in blue: “...Based on our cryo-EM data, the full tetradecameric complex could not\nbe resolved under C1 symmetry due to poorly defined density at the ligand binding sites. We therefore\nfocused on the two-protomer complex and performed local refinement and intensive 3D classification,\nwhich yielded a class of two-protomer units with improved density at the binding site. All structural\nanalyses reported here are based on the two-protomer complex.” (Line 211-215)\n6c. Mechanistic Hypothesis through Comparative Analysis: The discussion of an \"H pocket\" (lines 210-213) is\nintriguing but difficult to follow as its location is not clearly indicated in the figures. A more powerful and impactful\nanalysis would be to use the full structural model to perform a comparative analysis between the apo (unbound),\nthe calprotamide-bound (activated), and the ADEP-bound (dysregulated/inhibited) states. This comparison, with\na specific focus on conformational changes in the H pocket and other structural elements, would provide the\nnecessary data to propose a clear, testable hypothesis explaining the divergent functional outcomes of these\ntwo different ligands.\nResponse – H pocket clarification:\nTo clarify our discussion involving the “H pocket”, we have added a description in the Introduction (Line\n99) and included additional details in Figure 4c to highlight its location more clearly, as shown below.\nChanges made to clarify the location of the H pocket:\nOriginal text: “The Clp protease degrades damaged proteins and is important for maintaining a healthy\ncell, making it a promising target for both antibacterial and cancer therapies19-21.”\nUpdated text: “ClpP is a highly conserved serine protease that degrades damaged proteins and is\nimportant for maintaining a healthy cell, making it a promising target for both antibacterial and cancer\ntherapies19-21. The ClpP protease complex comprises two heptameric rings that stack to form a functional\ntetradecameric proteolytic core, which associates with a hexameric ATP-dependent unfoldase (e.g. ClpX,\nClpC). Unfoldases recognize, unfold, and translocate protein substrates into the ClpP catalytic chamber\nfor degradation. Their association with ClpP is mediated by docking of a conserved tripeptide loop (I/LGF\nloop) from the unfoldase into a specific hydrophobic pocket (H pocket) located at the interfaces between\nadjacent ClpP protomers22-24.” (Line 71-78)\nUpdated Figure 4c:\nOriginal figure 4c\nUpdated figure 4c\nUpdated figure legend\nc. Comparison of binding modes in the H pocket for the LGF tripeptide (green), calprotamide A (yellow),\nand ADEP7 (purple). Interacting residues are color-coded as follows: light blue, residues common to\nLGF, calprotamide A and ADEP7; yellow, residues unique to calprotamide A; Middle purple, residues\ncommon to LGF and ADEP7; and light purple, residues unique to ADEP7.\nResponse – Comparative analysis of structures and functional outcomes: In our revised manuscript\nwe now provide a more extensive description of calprotamide A binding to ClpP2 and the comparison of\ncalprotamide A and ADEP binding (see updated text below). Here we outline what we believe can be\ninterpreted from our structure as it relates to the activity of calprotamide A in each ClpP activity assay.\nPlease see the updated text below for how this is now addressed in our revised manuscript.\nPeptidase activity: Calprotamide A and ADEP both enhance Mtb ClpP1/P2 peptidase activity. As\ncalprotamide A and ADEP bind to the same region of ClpP2, this activity enhancement likely occurs\nthrough a shared mechanism. However, previous studies have not resolved the mechanism by which\nADEP enhances peptidase activity, likely due to the limited conformational changes observed in the\nMtb ClpP complex upon ADEP binding. The only notable change that occurs is the formation of an\nN-terminal β-hairpin, but no mechanistic hypothesis has linked this structural alteration to increased\npeptidase activity. Similarly, in our calprotamide A-bound structure we observed partial ordering of\nthe ClpP2 N-terminal region and few other conformational changes that might explain the activity\nenhancement. The electron density for calprotamide A in our structure indicated only partial ligand\noccupancy, which may have limited our ability to capture the full set of conformational rearrangements\ninduced by ligand binding. Further attempts to prepare cryo-EM grids using higher calprotamide A\nconcentrations were unsuccessful due to the compound’s low solubility.\nProtease activity: Calprotamide A enhances ClpC1-dependent protease activity, whereas ADEP\ninhibits this activity by displacing ClpC1 from the ClpP1/P2 complex. Although both ligands bind within\nthe ClpP2 H pocket, they generate distinct surfaces at the apical region of ClpP2, where ClpC1\ninteracts. These differing interaction surfaces likely underlie the opposing functional outcomes\nobserved upon ligand binding. However, without a structure of the full ClpC1–ClpP1/P2 complex, it is\nnot yet possible to determine how the unique surface formed by the ClpP2–calprotamide A complex\npromotes enhanced ClpC1-dependent proteolysis.\nActivation of native ClpP: Calprotamide A activates native ClpP, similar to Bz-LL, but this activation\nonly occurs at elevated ligand concentrations. As noted above, attempts to prepare cryo-EM grids\nusing higher calprotamide A concentrations were unsuccessful due to the compound’s low solubility.\nThe testable hypothesis suggested by our structure, which is the main focus of our study:\nOur structural analysis of calprotamide A bound to ClpP had the potential to address two different\nhypotheses: 1. The mechanistic difference between calprotamide A and ADEP and 2. The existence of\na conserved binding motif between calprotamide A and ADEP. Given the limitations of our structural data,\nwe were unable to resolve the mechanistic difference between calprotamide A and ADEP and therefore\nfocused our downstream studies on the second hypothesis. We appreciate the reviewer’s request to\npresent a deeper mechanistic study, unfortunately this is not possible with our present structure. In place\nof this we have expanded our exploration of the second hypothesis and now present an additional study\nleveraging the conserved N-acylphenylalanine motif to identify additional ClpP active structures.\nSummary of the new N-acylphenylalanine motif study included in our revised manuscript:\nIn the original manuscript, we focused on identifying N-acylphenylalanine containing molecules from\nclpP-associated BGCs. We also presented the observation that a large number BGCs that do not co-\nlocalize with clp genes are also predicted to encode N-acylphenylalanine containing molecules. In the\nexpanded study we present in our revised manuscript, we synthesized molecules predicted to arise from\na subset of these BGCs. This work identified additional N-acylphenylalanine containing ClpP active\nmolecules, including two narrow-spectrum antibiotics. One of these compounds inhibits M. tuberculosis\nmc2 6206 with a minimum inhibitory concentration of 4 µg/mL.\nNew text and figures added to the manuscript to address reviewer’s concerns:\nUpdated text about our structure and calprotamide mechanism (text added for Reviewer 1 in red,\ntext added in response to Reviewer 2 comment 6 in blue):\n“Cryogenic electron microscopy (cryo-EM) structure: To explore how the calprotamides affect\nClpP, we determined the cryo-EM structure of calprotamide A bound to Mtb ClpP1/P2. Given the\ncomparable activity of calprotamide A and B in functional assays, we focused our analysis on\ncalprotamide A, as calprotamide B is less stable and exhibited low solubility in protein buffer,\nmaking it a poor candidate for preparing high-quality grids. Based on our cryo-EM data, the full\ntetradecameric complex could not be resolved under C1 symmetry due to poorly defined density\nat the ligand binding sites. We therefore focused on the two-protomer complex and performed\nlocal refinement and intensive 3D classification, which yielded a class of two-protomer units with\nimproved density at the binding site. All structural analyses reported here are based on the two-\nprotomer complex.\nIn our structure, calprotamide A binds the apical surface of ClpP2 at the same general binding\nsite as ADEP (Fig. 4a-b). The N-acylphenylalanine moiety, shared by both calprotamide A and\nADEP, occupies the ClpP2 H pocket in each structure, and residues forming the H pocket show\nno major differences in their interactions with this fragment (Supplementary Fig. 44a). Beyond\nthis common pharmacophore, the unique structural features of these two natural products largely\nextend in opposite directions (Fig. 4c). The electron density for the C-terminal portion of\ncalprotamide A is less well-defined than that observed for the N-acylphenylalanine motif that binds\nthe H pocket, suggesting that it is more conformationally flexible. Residues predicted to interact\nwith the non-N-acylphenylalanine portions of each ligand show only minor side-chain\nrearrangements between the two structures (Supplementary Fig. 44b). The largest apparent\ndifference occurs at R207; however, the electron density for this side chain in the ADEP-bound\nstructure (PDB 6vgn) is insufficient to confirm a definitive structural change. To further compare\nthe difference in binding between calprotamide A and ADEP, we performed alanine mutagenesis\nof two key residues in Mtb ClpP2, R207 and Q101. R207 forms a salt bridge with calprotamide A\nbut not with ADEP, whereas Q101 forms a hydrogen bond with ADEP but not with calprotamide\nA (Supplementary Fig. 45a). As predicted by our model, the R207A mutation more strongly\nimpaired calprotamide A-mediated enhancement of Mtb ClpP1P2 peptidase activity than it did\nADEP-mediated enhancement. Conversely, the Q101A mutation had a greater effect on ADEP-\nmediated enhancement than on calprotamide A-mediated enhancement (Supplementary Fig.\n45b). Whether the unusual bis-γ-lactam bicyclic moiety in calprotamide B forms additional\ninteractions with Mtb ClpP2 or the ClpP1/P2:C1 complex remains to be determined. It is possible\nthat the bis-γ-lactam serves primarily to mask the negative charge that would normally be\ngenerated upon release by the thioesterase, thereby improving bioavailability. This is consistent\nwith the higher cellular accumulation of calprotamide B we observed (Supplementary Fig. 42)\nand may help explain its stronger antibacterial activity relative to calprotamide A (Table 1).\nAlthough no major structural rearrangements were observed at the ligand binding site,\ncalprotamide A binding induced two more distal conformational changes. Specifically, it promoted\nordering of loops in both the ClpP2 N-terminal region and the ClpP2 handle region near the\ncatalytic sites (Fig. 4d). Notably, changes in these regions have been independently observed in\nthe ADEP- and Bz-LL-bound structures, respectively. However, while calprotamide A binding\nproduced electron density consistent with only partial ordering, the corresponding regions in the\nADEP and Bz-LL complexes adopt fully formed secondary structures (a β-hairpin and β-sheet,\nrespectively). In both the ADEP and Bz-LL structures, all ligand binding sites are fully occupied,\nwhereas only partial ligand occupancy was observed in our calprotamide A complex. Thus, the\nlimited conformational changes observed in our structure may reflect an intermediate state\nresulting from incomplete ligand occupancy.\nCalprotamide A and ADEP both enhance Mtb ClpP1/P2 peptidase activity. As calprotamide A and\nADEP bind to the same region of ClpP2, this activity enhancement likely occurs through a shared\nmechanism. However, due to the limited conformational changes observed in Mtb ClpP upon\nbinding either ligand, the underlying mechanism of activation remains unresolved. Interestingly,\ncalprotamide A enhances ClpC1-dependent protease activity, whereas ADEP inhibits this activity\nby displacing ClpC1 from the ClpP1/P2 complex. Although both ligands bind the ClpP2 H pocket,\nthey create distinct surfaces at the apical region of ClpP2, where ClpC1 interacts. Based on the\nstructure of ClpP1/P2 alone, it remains unclear how the unique surface formed by the ClpP2-\ncalprotamide A complex promotes enhanced ClpC1-dependent proteolysis.” (Line 207-257)\nUpdated figures:\nOriginal figure 4d\nUpdated figure 4d\nUpdated figure legend\nd. Conformational changes in the Mtb ClpP1/P2 two-protomer complex upon calprotamide\nA binding, revealed through structural superposition of the calprotamide A-bound (yellow)\nand unbound (green) states. Zoomed-in views (black and red dashed boxes) highlight\nstructural rearrangements in the ClpP2 N-terminal region and handle region near the\ncatalytic site.\nSupplementary Fig. 44. Structural comparison of residues in the calprotamide A- and\nADEP- bound binding sites. a. Superposition of the H pocket residues (LGF loop and N-\nacylphenylalanine interacting) from calprotamide A-bound (yellow) and ADEP-bound (purple)\nClpP structures. b. Superposition of residues interacting with non-N-acylphenylalanine portions\nof calprotamide A-bound (yellow) and ADEP-bound (purple) ClpP.\nUpdated text and figure on our expanded study of the N-acylphenylalanine targeting hypothesis:\nUpdated results text (new text in blue)\n“The identification of four structurally distinct ClpP active natural products, linked only by their\nmedium-chain N-acylphenylalanine substructures, suggests that uncharacterized BGCs encoding\nthis moiety are likely to represent an untapped reservoir of structurally diverse ClpP-targeting\ncompounds. Notably, this shared substructure that engages the H pocket corresponds to the\nsmallest ADEP fragment reported to retain antibacterial activity35. Together, our bioinformatic and\nactivity analyses suggested that the N-acylphenylalanine moiety was likely a previously\nunappreciated, yet potentially common, ClpP targeting motif that has convergently evolved in\ndiverse bacteria. As not all BGCs will contain a self-resistance gene, we carried out a broader\nsearch of sequenced BGCs for those that encode N-acylphenylalanine moieties. This search\nidentified more than 100 previously uncharacterized BGCs containing an NRPS initiation module\nconsisting of a phenylalanine-selective A-domain and Cs (condensation starter) domain, which\ninitiates lipopeptide biosynthesis by appending a fatty acyl chain onto the first amino acid.\nInterestingly, a number of the BGCs we identified in both our original clp gene driven bioinformatic\nanalysis and this broader search are hybrid NRPS-PKS systems indicating that they could encode\nboth the lipid and the phenylalanine seen in a medium-chain (C6-C8) N-acylphenylalanine motif.\nIn purely NRPS BGCs, the Cal or Cs initiation domain could instead introduce a primary\nmetabolism derived medium-chain fatty acid and therefore no specific fatty acid biosynthesis\ngenes would be required.\nWhile not all these BGCs are expected to encode a ClpP-targeting molecule, this collection is\npotentially enriched for ClpP activity. We bioinformatically predicted the encoded peptide\nsequences and randomly selected ten uncharacterized BGCs whose products could be predicted\nfrom existing A-domain specificity data, were synthetically accessible, and contained a possible\ncyclization site (e.g., serine or threonine) (Supplementary Table 8-9). Most of these BGCs\noriginated from Actinomycetes species, including four from Mycobacterium, two from\nStreptomyces, one from Microbispora, and one from Rhodococcus. The remaining two BGCs\nwere derived from Paenibacillus and Mucilaginibacter. Each predicted lipopeptide was\nsynthesized using Fmoc-based solid-phase peptide synthesis (SPPS) and with the 2-hexenoic\nacid lipid moiety from the calprotamides (Supplementary Table 10, Supplementary Fig. 54).\nThe resulting molecules ranged from five to ten amino acids in length, with ring sizes varying from\nfour to eight residues. All compounds were evaluated for their ability to modulate Mtb ClpP\npeptidase activity and for antibiotic activity against a panel of Streptomyces and Mycobacterium\nstrains (Fig. 6a). We used an expanded panel of Actinomycetes, as we had previously observed\nnarrow-spectrum Actinomycete activity for N-acylphenylalanine containing structures, and most\nBGCs that inspired our synthetic efforts originated from this genus. Several molecules enhanced\nMtb ClpP1/P2 peptidase activity, with 6 (myscamide, Fig. 6b, Supplementary Fig. 55-56) and\n13 (paenilamide, Fig. 6c, Supplementary Fig. 57-58) producing the strongest enhancement at\nlevels comparable to calprotamide B. Enhancement of ClpP1/P2 activity correlated with\nantibacterial activity, with both of these compounds exhibiting antibiotic activity against a narrow\nspectrum of Actinomycete species. Notably, myscamide showed potent activity against M.\ntuberculosis mc2 6206 with a minimum inhibitory concentration of 4 µg/mL.” (Line 297-333)\nFig. 6. Bioinformatically guided prediction and synthesis of N-acylphenylalanine\ncompounds identifies Mtb ClpP enhancers with narrow-spectrum antibiotic activity. a. Mtb\nClpP1/P2 peptidase activity assays for the synthesized library of N-acylphenylalanine\ncompounds, measured using ZVKM–AMC in the presence of 2.5 mM Bz-LL. Initial rates (AU\nmin⁻¹) were calculated from the first five minutes of the assay and represent mean values from\nthree independent replicates. Antibacterial activity against a panel of Actinomycetes is shown as\nminimum inhibitory concentrations (MIC, μg/mL). Mycobacterium strains used are detailed in the\nMethods and Streptomyces strains used are listed in Table 1. b-c. Biosynthetic gene clusters\npredicted to encode myscamide (6) and paenilamide (13), and the corresponding synthesized\nstructures. Both compounds are ClpP enhancers and exhibit narrow-spectrum antibiotic activity\n(a). Cyclization sites are bolded.\nUpdated discussion text (new text in blue)\n“The N-acylphenylalanine motif should be broadly useful for identifying ClpP-targeting\ncompounds in both synthetic chemistry campaigns and natural product discovery efforts. The\nstrategy we used here to identify tuscamide, myscamide, and paenilamide likely represents a\nhybrid of these two approaches. While it is often possible to predict the peptide product of an\nNRPS BGC with reasonable confidence, it remains challenging to predict the specific lipid\nincorporated by a Cs domain. We used the 2-hexenoic acid lipid moiety from the calprotamides\nin our syntheses. Although these exact structures may not all occur in nature, we predict that a\nsubset of these BGCs will naturally incorporate similar medium-chain lipids for targeting ClpP.\nIn other cases, appending the ClpP-targeting motif to a naturally encoded NRPS scaffold may\nincrease the likelihood of identifying ClpP-active antibiotics, as the NRPS-derived core is likely to\nhave evolved for bioactivity and bioavailability.” (Line 363-372)\nUpdated abstract text (new text in blue)\n“The discovery of natural products with specific modes of action from metagenomes remains\nchallenging. Here, we present resistance-CONKAT-seq, a pipeline that links biosynthetic gene\nclusters (BGCs) to self-resistance genes, enabling identification of metabolites with desired\nmolecular targets. Using clpP-directed resistance-CONKAT-seq, we identified the calprotamides,\nwhich activate native ClpP and enhance its activity. Cryo-EM and bioinformatic analyses revealed\nthat the calprotamides’ medium-chain N-acylphenylalanine substructure is a convergently\nevolved ClpP-targeting motif and identified additional BGCs predicted to encode this moiety,\nincluding some with co-localized clp genes. The synthesis of structures bioinformatically inspired\nby two such clp-linked BGCs, desmethyl jomthonic acid C and tuscamide, revealed that both\nenhanced ClpP activity. Extending our bioinformatically guided synthesis study to additional\nBGCs lacking nearby clp genes found that ClpP activity enhancement correlated with antibacterial\nactivity, with the strongest enhancers exhibiting narrow-spectrum antibiotic activity. These\nfindings establish N-acylphenylalanine as a previously unrecognized but common natural motif\nfor targeting ClpP, which should help guide the discovery of both natural and synthetic ClpP\nmodulators for antibiotic and anticancer development. 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A Potent and Narrow-Spectrum Antibacterial against Clostridioides difficile Infection. J\nMed Chem 66, 13891-13899 (2023).\n30. Akopian, T. et al. The active ClpP protease from M. tuberculosis is a complex composed of a\nheptameric ClpP1 and a ClpP2 ring. EMBO J 31, 1529-1541 (2012).\n31. Famulla, K. et al. Acyldepsipeptide antibiotics kill mycobacteria by preventing the physiological\nfunctions of the ClpP1P2 protease. Mol Microbiol 101, 194-209 (2016).\n32. Vahidi, S. et al. An allosteric switch regulates Mycobacterium tuberculosis ClpP1P2 protease function\nas established by cryo-EM and methyl-TROSY NMR. Proc Natl Acad Sci U S A 117, 5895-5906 (2020).\n33. Zivanov, J., Nakane, T. & Scheres, S.H. Estimation of high-order aberrations and anisotropic\nmagnification from cryo-EM data sets in RELION-3.1. IUCrJ 7, 253-267 (2020).\n34. Zivanov, J., Nakane, T. & Scheres, S.H. A Bayesian approach to beam-induced motion correction in\ncryo-EM single-particle analysis. IUCrJ 6, 5-17 (2019).\n35. Carney, D.W. et al. A simple fragment of cyclic acyldepsipeptides is necessary and sufficient for ClpP\nactivation and antibacterial activity. Chembiochem 15, 2216-2220 (2014).\nReviewer #2 comment:\nThe text currently uses inconsistent hyphenation for symmetry descriptions, citing \"C1 symmetry\" and \"C7-\nsymmetry expansion\". Please adopt a consistent format throughout the manuscript.\nResponse: Symmetry descriptions have been updated for consistent hyphenation.\nOriginal Text: To better resolve the ligand binding region, we performed C7-symmetry expansion\n(11,388,629 particles) followed by local refinement using a mask encompassing a single stacked two-\nprotomer ClpP1/P2 unit.\nChanged to: To better resolve the ligand binding region, we performed C7 symmetry expansion\n(11,388,629 particles) followed by local refinement using a mask encompassing a single stacked two-\nprotomer ClpP1/P2 unit. (Line 620-622)"}, {"round": 2, "reviewer_comments": {"reviewer_1": "I thank the authors for their careful and comprehensive revisions. The authors have thoroughly and satisfactorily addressed all my previous concerns. The manuscript has been significantly strengthened and now meets the standards for publication in Nature Communications.", "reviewer_2": "The authors have comprehensively addressed the concerns raised in the initial review through significant revisions to the manuscript. The technical logic and experimental support for the resistance conkat-seq pipeline are now well defined and robust.\nMinor editorial concern:\nThe text currently uses inconsistent hyphenation for symmetry descriptions, citing \"C1 symmetry\" and \"C7-symmetry expansion\". Please adopt a consistent format throughout the manuscript.\nI recommend the manuscript for publication following this minor correction."}, "author_response": ""}]

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