Summary Statement Commensal bacteria are believed to play important roles in human health. The mechanisms by which they affect mammalian physiology are poorly understood; however, bacterial metabolites are likely to be key components of host interactions. Here, we use bioinformatics and synthetic biology to mine the human microbiota for N-acyl amides that interact with G-protein-coupled receptors (GPCRs). We found that N-acyl amide synthase genes are enriched in gastrointestinal bacteria and the lipids they encode interact with GPCRs that regulate gastrointestinal tract physiology. Mouse and cell-based models demonstrate that commensal GPR119 agonists regulate metabolic hormones and glucose homeostasis as efficiently as human ligands although future studies are needed to define their potential physiologic role in humans. This work suggests that chemical mimicry of eukaryotic signaling molecules may be common among commensal bacteria and that manipulation of microbiota genes encoding metabolites that elicit host cellular responses represents a new small molecule therapeutic modality (microbiome-biosynthetic-gene-therapy).

Here, we present a natural product discovery approach whereby structures are bioinformatically predicted from primary sequence and produced by chemical synthesis (synthetic-bioinformatic natural products, syn-BNPs), circumventing the need for bacterial culture and gene expression. When applied to nonribosomal peptide synthetase gene clusters from human-associated bacteria we identified the humimycins. These antibiotics inhibit lipid II flippase and potentiate β-lactam activity against methicillin-resistant Staphylococcus aureus in mice, potentially providing a new treatment regimen.

The trillions of bacteria that make up the human microbiome are believed to encode functions that are important to human health; however, little is known about the specific effectors that commensal bacteria use to interact with the human host. Functional metagenomics provides a systematic means of surveying commensal DNA for genes that encode effector functions. Here, we examine 3,000 Mb of metagenomic DNA cloned from three phenotypically distinct patients for effectors that activate NF-κB, a transcription factor known to play a central role in mediating responses to environmental stimuli. This screen led to the identification of 26 unique commensal bacteria effector genes (Cbegs) that are predicted to encode proteins with diverse catabolic, anabolic, and ligand-binding functions and most frequently interact with either glycans or lipids. Detailed analysis of one effector gene family (Cbeg12) recovered from all three patient libraries found that it encodes for the production of N-acyl-3-hydroxypalmitoyl-glycine (commendamide). This metabolite was also found in culture broth from the commensal bacterium Bacteroides vulgatus, which harbors a gene highly similar to Cbeg12. Commendamide resembles long-chain N-acyl-amides that function as mammalian signaling molecules through activation of G-protein–coupled receptors (GPCRs), which led us to the observation that commendamide activates the GPCR G2A/GPR132. G2A has been implicated in disease models of autoimmunity and atherosclerosis. This study shows the utility of functional metagenomics for identifying potential mechanisms used by commensal bacteria for host interactions and outlines a functional metagenomics-based pipeline for the systematic identification of diverse commensal bacteria effectors that impact host cellular functions.

The flippase MurJ is responsible for transporting the cell wall intermediate lipid II from the cytoplasm to the outside of the cell. While essential for the survival of bacteria, it remains an underexploited target for antibacterial therapy. The humimycin antibiotics are lipid II flippase (MurJ) inhibitors that were synthesized on the basis of bioinformatic predictions derived from secondary metabolite gene clusters found in the human microbiome. Here, we describe an SAR campaign around humimycin A that produced humimycin 17S. Compared to humimycin A, 17S is a more potent β-lactam potentiator, has a broader spectrum of activity, which now includes both methicillin resistant Staphylococcus aureus (MRSA) and vancomycin resistant Enterococcus faecalis (VRE), and did not lead to any detectable resistance when used in combination with a β-lactam. Combinations of β-lactam and humimycin 17S provide a potentially useful long-term MRSA regimen.

Bacterial natural products have inspired the development of numerous antibiotics in use today. As resistance to existing antibiotics has become more prevalent, new antibiotic lead structures and activities are desperately needed. An increasing number of natural product biosynthetic gene clusters, to which no known molecules can be assigned, are found in genome and metagenome sequencing data. Here we access structural information encoded in this underexploited resource using a synthetic-bioinformatic natural product (syn-BNP) approach, which relies on bioinformatic algorithms followed by chemical synthesis to predict and then produce small molecules inspired by biosynthetic gene clusters. In total, 157 syn-BNP cyclic peptides inspired by 96 nonribosomal peptide synthetase gene clusters were synthesized and screened for antibacterial activity. This yielded nine antibiotics with activities against ESKAPE pathogens as well as Mycobacterium tuberculosis. Not only are antibiotic-resistant pathogens susceptible to many of these syn-BNP antibiotics, but they were also unable to develop resistance to these antibiotics in laboratory experiments. Characterized modes of action for these antibiotics include cell lysis, membrane depolarization, inhibition of cell wall biosynthesis, and ClpP protease dysregulation. Increasingly refined syn-BNP-based explorations of biosynthetic gene clusters should allow for more rapid identification of evolutionarily inspired bioactive small molecules, in particular antibiotics with diverse mechanism of actions that could help confront the imminent crisis of antimicrobial resistance.

Bacterial culture broth extracts have been the starting point for the development of numerous therapeutics. However, only a small fraction of bacterial biosynthetic diversity is accessible using this strategy. Here, we apply a discovery approach that bypasses the culturing step entirely by bioinformatically predicting small molecule structures from the primary sequences of the biosynthetic gene clusters. These structures are then chemically synthesized to give synthetic-bioinformatic natural products (syn-BNPs). Using this approach, we screened syn-BNPs inspired by nonribosomal peptide synthetases against microbial pathogens, and discovered an antibiotic for which no resistance could be identified and an antifungal agent with activity against diverse fungal pathogens.

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Bioinformatic analysis of sequenced bacterial genomes has uncovered an increasing number of natural product biosynthetic gene clusters (BGCs) to which no known bacterial metabolite can be ascribed. One emerging method we have investigated for studying these BGCs is the synthetic-Bioinformatic Natural Product (syn-BNP) approach. The syn-BNP approach replaces transcription, translation, and in vivo enzymatic biosynthesis of natural products with bioinformatic algorithms to predict the output of a BGC and in vitro chemical synthesis to produce the predicted structure. Here we report on expanding the syn-BNP approach to the design and synthesis of cyclic peptides inspired by nonribosomal peptide synthetase BGCs associated with the human microbiota. While no syn-BNPs we tested inhibited the growth of bacteria or yeast, five were found to be active in the human cell-based MTT metabolic activity assay. Interestingly, active peptides were mostly inspired by BGCs found in the genomes of opportunistic pathogens that are often more commonly associated with environments outside the human microbiome. The cyclic syn-BNP studies presented here provide further evidence of its potential for identifying bioactive small molecules directly from the instructions encoded in the primary sequences of natural product BGCs.