Unveiling gut microbiota's role: Bidirectional regulation of drug transport for improved safety

Drug safety is a paramount concern in the field of drug development, with researchers increasingly focusing on the bidirectional regulation of gut microbiota in this context. The gut microbiota plays a crucial role in maintaining drug safety. It can influence drug transport processes in the body through various mechanisms, thereby modulating their efficacy and toxicity. The main mechanisms include: (1) The gut microbiota directly interacts with drugs, altering their chemical structure to reduce toxicity and enhance efficacy, thereby impacting drug transport mechanisms, drugs can also change the structure and abundance of gut bacteria; (2) bidirectional regulation of intestinal barrier permeability by gut microbiota, promoting the absorption of nontoxic drugs and inhibiting the absorption of toxic components; (3) bidirectional regulation of the expression and activity of transport proteins by gut microbiota, selectively promoting the absorption of effective components or inhibiting the absorption of toxic components. This bidirectional regulatory role enables the gut microbiota to play a key role in maintaining drug balance in the body and reducing adverse reactions. Understanding these regulatory mechanisms sheds light on novel approaches to minimize toxic side effects, enhance drug efficacy, and ultimately improve drug safety. This review systematically examines the bidirectional regulation of gut microbiota in drug transportation from the aforementioned aspects, emphasizing their significance in ensuring drug safety. Furthermore, it offers a prospective outlook from the standpoint of enhancing therapeutic efficacy and reducing drug toxicity, underscoring the importance of further exploration in this research domain. It aims to provide more effective strategies for drug development and treatment.

Human microbiota peptides: important roles in human health

Covering: 1974 to 2024Human microbiota consist of a diverse array of microorganisms, such as bacteria, Eukarya, archaea, and viruses, which populate various parts of the human body and live in a cooperatively beneficial relationship with the host. They play a crucial role in supporting the functional balance of the microbiome. The coevolutionary progression has led to the development of specialized metabolites that have the potential to substitute traditional antibiotics in combating global health challenges. Although there has been a lot of research on the human microbiota, there is a considerable lack of understanding regarding the wide range of peptides that these microbial populations produce. Particularly noteworthy are the antibiotics that are uniquely produced by the human microbiome, especially by bacteria, to protect against invasive infections. This review seeks to fill this knowledge gap by providing a thorough understanding of various peptides, along with their in-depth biological importance in terms of human disorders. Advancements in genomics and the understanding of molecular mechanisms that control the interactions between microbiota and hosts have made it easier to find peptides that come from the human microbiome. We hope that this review will serve as a basis for developing new therapeutic approaches and personalized healthcare strategies. Additionally, it emphasizes the significance of these microbiota in the field of natural product discovery and development.

Exploring nature's battlefield: organismic interactions in the discovery of bioactive natural products

Covering: up to March 2024.Microbial natural products have historically been a cornerstone for the discovery of therapeutic agents. Advanced (meta)genome sequencing technologies have revealed that microbes harbor far greater biosynthetic capabilities than previously anticipated. However, despite the application of CRISPR/Cas-based gene editing and high-throughput technologies to activate silent biosynthetic gene clusters, the rapid identification of new natural products has not led to a proportional increase in the discovery rate of lead compounds or drugs. A crucial issue in this gap may be insufficient knowledge about the inherent biological and physiological functions of microbial natural products. Addressing this gap necessitates recognizing that the generation of functional natural products is deeply rooted in the interactions between the producing microbes and other (micro)organisms within their ecological contexts, an understanding that is essential for harnessing their potential therapeutic benefits. In this review, we highlight the discovery of functional microbial natural products from diverse niches, including those associated with humans, nematodes, insects, fungi, protozoa, plants, and marine animals. Many of these findings result from an organismic-interaction-guided strategy using multi-omic approaches. The current importance of this topic lies in its potential to advance drug discovery in an era marked by increasing antimicrobial resistance.

Mapping Lipid C═C Isomer Profiles of Human Gut Bacteria through a Novel Structural Lipidomics Workflow Assisted by Chemical Epoxidation

The unsaturated lipids produced by human gut bacteria have an extraordinary range of structural diversity, largely because of the isomerism of the carbon-carbon double bond (C═C) in terms of its position and stereochemistry. Characterizing distinct C═C configurations poses a considerable challenge in research, primarily owing to limitations in current bioanalytical methodologies. This study developed a novel structural lipidomics workflow by combining MELDI (meta-chloroperoxybenzoic acid epoxidation for lipid double-bond identification) with liquid chromatography-tandem mass spectrometry for C═C characterization. We utilized this workflow to quantitatively assess more than 50 C═C positional and cis/trans isomers of fatty acids and phospholipids from selected human gut bacteria. Strain-specific isomer profiles revealed unexpectedly high productivity of trans-10-octadecenoic acid by Enterococcus faecalis, Bifidobacterium longum, and Lactobacillus acidophilus among numerous trans-fatty acid isomers produced by gut bacteria. Isotope-tracking experiments suggested that gut bacteria produce trans-10-octadecenoic acid through the isomeric biotransformation of oleic acid in vitro and that such isomeric biotransformation of dietary oleic acid is dependent on the presence of gut bacteria in vivo.

Integrated large-scale metagenome assembly and multi-kingdom network analyses identify sex differences in the human nasal microbiome

BACKGROUND

Respiratory diseases impose an immense health burden worldwide. Epidemiological studies have revealed extensive disparities in the incidence and severity of respiratory tract infections between men and women. It has been hypothesized that there might also be a nasal microbiome axis contributing to the observed sex disparities.

RESULTS

Here, we study the nasal microbiome of healthy young adults in the largest cohort to date with 1593 individuals, using shotgun metagenomic sequencing. We compile the most comprehensive reference catalog for the nasal bacterial community containing 4197 metagenome-assembled genomes and integrate the mycobiome, to provide a valuable resource and a more holistic perspective for the understudied human nasal microbiome. We systematically evaluate sex differences and reveal extensive sex-specific features in both taxonomic and functional levels in the nasal microbiome. Through network analyses, we capture markedly higher ecological stability and antagonistic potentials in the female nasal microbiome compared to the male's. The analysis of the keystone bacteria reveals that the sex-dependent evolutionary characteristics might have contributed to these differences.

CONCLUSIONS

In summary, we construct the most comprehensive catalog of metagenome-assembled-genomes for the nasal bacterial community to provide a valuable resource for the understudied human nasal microbiome. On top of that, comparative analysis in relative abundance and microbial co-occurrence networks identify extensive sex differences in the respiratory tract community, which may help to further our understanding of the observed sex disparities in the respiratory diseases.

Mining metagenomic data to gain a new insight into the gut microbial biosynthetic potential in placental mammals

Mammals host a remarkable diversity and abundance of gut microbes. Biosynthetic gene clusters (BGCs) in microbial genomes encode biologically active chemical products and play an important role in microbe-host interactions. Traditionally, the exploration of gut microbial metabolic functions has relied on the pure culture method. However, given the limited amounts of microbes being cultivated, insights into the metabolism of gut microbes in mammals continued to be very limited. In this study, we adopted a computational pipeline for mining the metagenomic data (named taxonomy-guided identification of biosynthetic gene clusters, TaxiBGC) to identify experimentally verified BGCs in 373 metagenomes across 53 mammalian species in an unbiased manner. We demonstrated that polyketides (PKs) and nonribosomal peptides (NRPs) are representative of mammals, and the products derived from them were associated with cell-cell communication and resistance to inflammation. Large carnivores had the highest number of BGCs, followed by large herbivores and small mammals. We also observed that the large mammals had more common BGCs that aid in the biosynthesis of a variety of natural products. However, small mammals not only had fewer BGCs but were also unique to each species. Our results provide novel insights into the mining of metagenomic data sets to identify active BGCs and their products across mammals.IMPORTANCEThe gut microbes host numerous biosynthetic gene clusters (BGCs) that biosynthesize natural products and impact the host's physiology. Historically, our understanding of BGCs in mammalian gut microbes was largely based on studies on cultured isolates; however, only a small fraction of mammal-associated microbes have been investigated. The biochemical diversity of the mammalian gut microbiota is poorly understood. Metagenomic sequencing contains data from a vast number of organisms and provides information on the total gene content of communities. Unfortunately, the existing BGC prediction tools are designed for individual microbial genomes. Recently, a BGC prediction tool called the taxonomy-guided identification of biosynthetic gene clusters (TaxiBGC) that directly mine the metagenome was developed. To gain new insights into the microbial metabolism, we used TaxiBGC to predict BGCs from 373 metagenomes across 53 mammalian species representing seven orders. Our findings elucidate the functional activities of complex microbial communities in the gut.

Integrating functional metagenomics to decipher microbiome-immune interactions

Microbial metabolites can be viewed as the cytokines of the microbiome, transmitting information about the microbial and metabolic environment of the gut to orchestrate and modulate local and systemic immune responses. Still, many immunology studies focus solely on the taxonomy and community structure of the gut microbiota rather than its functions. Early sequencing-based microbiota profiling approaches relied on PCR amplification of small regions of bacterial and fungal genomes to facilitate identification of the microbes present. However, recent microbiome analysis methods, particularly shotgun metagenomic sequencing, now enable culture-independent profiling of microbiome functions and metabolites in addition to taxonomic characterization. In this review, we showcase recent advances in functional metagenomics methods and applications and discuss the current limitations and potential avenues for future development. Importantly, we highlight a few examples of key areas of opportunity in immunology research where integrating functional metagenomic analyses of the microbiome can substantially enhance a mechanistic understanding of microbiome-immune interactions and their contributions to health and disease states.

Mechanisms of gastrointestinal toxicity in neuromyelitis optica spectrum disorder patients treated with mycophenolate mofetil: insights from a mouse model and human study

Mycophenolate mofetil (MMF) is commonly utilized for the treatment of neuromyelitis optica spectrum disorders (NMOSD). However, a subset of patients experience significant gastrointestinal (GI) adverse effects following MMF administration. The present study aims to elucidate the underlying mechanisms of MMF-induced GI toxicity in NMOSD. Utilizing a vancomycin-treated mouse model, we compiled a comprehensive data set to investigate the microbiome and metabolome in the GI tract to elucidate the mechanisms of MMF GI toxicity. Furthermore, we enrolled 17 female NMOSD patients receiving MMF, who were stratified into non-diarrhea NMOSD and diarrhea NMOSD (DNM) groups, in addition to 12 healthy controls. The gut microbiota of stool samples was analyzed using 16S rRNA gene sequencing. Vancomycin administration prevented weight loss and tissue injury caused by MMF, affecting colon metabolomes and microbiomes. Bacterial β-glucuronidase from Bacteroidetes and Firmicutes was linked to intestinal tissue damage. The DNM group showed higher alpha diversity and increased levels of Firmicutes and Proteobacteria. The β-glucuronidase produced by Firmicutes may be important in causing gastrointestinal side effects from MMF in NMOSD treatment, providing useful information for future research on MMF.

IMPORTANCE

Neuromyelitis optica spectrum disorder (NMOSD) patients frequently endure severe consequences like paralysis and blindness. Mycophenolate mofetil (MMF) effectively addresses these issues, but its usage is hindered by gastrointestinal (GI) complications. Through uncovering the intricate interplay among MMF, gut microbiota, and metabolic pathways, this study identifies specific gut bacteria responsible for metabolizing MMF into a potentially harmful form, thus contributing to GI side effects. These findings not only deepen our comprehension of MMF toxicity but also propose potential strategies, such as inhibiting these bacteria, to mitigate these adverse effects. This insight holds broader implications for minimizing complications in NMOSD patients undergoing MMF therapy.

Bacillus subtilis as a host for natural product discovery and engineering of biosynthetic gene clusters

Covering: up to October 2023Many bioactive natural products are synthesized by microorganisms that are either difficult or impossible to cultivate under laboratory conditions, or that produce only small amounts of the desired compound. By transferring biosynthetic gene clusters (BGCs) into alternative host organisms that are more easily cultured and engineered, larger quantities can be obtained and new analogues with potentially improved biological activity or other desirable properties can be generated. Moreover, expression of cryptic BGCs in a suitable host can facilitate the identification and characterization of novel natural products. Heterologous expression therefore represents a valuable tool for natural product discovery and engineering as it allows the study and manipulation of their biosynthetic pathways in a controlled setting, enabling innovative applications. Bacillus is a genus of Gram-positive bacteria that is widely used in industrial biotechnology as a host for the production of proteins from diverse origins, including enzymes and vaccines. However, despite numerous successful examples, Bacillus species remain underexploited as heterologous hosts for the expression of natural product BGCs. Here, we review important advantages that Bacillus species offer as expression hosts, such as high secretion capacity, natural competence for DNA uptake, and the increasing availability of a wide range of genetic tools for gene expression and strain engineering. We evaluate different strain optimization strategies and other critical factors that have improved the success and efficiency of heterologous natural product biosynthesis in B. subtilis. Finally, future perspectives for using B. subtilis as a heterologous host are discussed, identifying research gaps and promising areas that require further exploration.

The Discovery of Gut Microbial Metabolites as Modulators of Host Susceptibility to Acetaminophen-Induced Hepatotoxicity

The mammalian gut microbiota plays diverse and essential roles in modulating host physiology. Key mediators determining the outcome of the microbiota-host interactions are the small molecule metabolites produced by the gut microbiota. The liver is a major organ exposed to gut microbial metabolites, and it serves as the nexus for maintaining healthy interactions between the gut microbiota and the host. At the same time, the liver is the primary target of potentially harmful gut microbial metabolites. In this review, we provide an up-to-date list of gut microbial metabolites that have been identified to either increase or decrease host susceptibility to acetaminophen (APAP)-induced liver injury. The signaling pathways and molecular factors involved in the progression of APAP-induced hepatotoxicity are well-established, and we propose that the mouse model of APAP-induced hepatotoxicity serves as a model system for uncovering gut microbial metabolites with previously unknown functions. Furthermore, we envision that gut microbial metabolites identified to alter APAP-induced hepatotoxicity likely have broader implications in other liver diseases. SIGNIFICANCE STATEMENT: This review provides an overview of the role of the gut microbiota in modulating the host susceptibility to acetaminophen (APAP)-induced liver injury. It focuses on the roles of gut bacterial small molecule metabolites as mediators of the interaction between the gut microbiota and the liver. It also illustrates the utility of APAP-induced liver injury as a model to identify gut microbial metabolites with biological function.

Discovery of antimicrobial peptides in the global microbiome with machine learning

Novel antibiotics are urgently needed to combat the antibiotic-resistance crisis. We present a machine-learning-based approach to predict antimicrobial peptides (AMPs) within the global microbiome and leverage a vast dataset of 63,410 metagenomes and 87,920 prokaryotic genomes from environmental and host-associated habitats to create the AMPSphere, a comprehensive catalog comprising 863,498 non-redundant peptides, few of which match existing databases. AMPSphere provides insights into the evolutionary origins of peptides, including by duplication or gene truncation of longer sequences, and we observed that AMP production varies by habitat. To validate our predictions, we synthesized and tested 100 AMPs against clinically relevant drug-resistant pathogens and human gut commensals both in vitro and in vivo. A total of 79 peptides were active, with 63 targeting pathogens. These active AMPs exhibited antibacterial activity by disrupting bacterial membranes. In conclusion, our approach identified nearly one million prokaryotic AMP sequences, an open-access resource for antibiotic discovery.

Human gut Actinobacteria boost drug absorption by secreting P-glycoprotein ATPase inhibitors

Drug efflux transporters are a major determinant of drug efficacy and toxicity. A canonical example is P-glycoprotein (P-gp), an efflux transporter that controls the intestinal absorption of diverse compounds. Despite a rich literature on the dietary and pharmaceutical compounds that impact P-gp activity, its sensitivity to gut microbial metabolites remains an open question. Surprisingly, we found that the cardiac drug-metabolizing gut Actinobacterium Eggerthella lenta increases drug absorption in mice. Experiments in cell culture revealed that E. lenta produces a soluble factor that post-translationally inhibits P-gp ATPase efflux activity. P-gp inhibition is conserved in the Eggerthellaceae family but absent in other Actinobacteria. Comparative genomics identified genes associated with P-gp inhibition. Finally, activity-guided biochemical fractionation coupled to metabolomics implicated a group of small polar metabolites with P-gp inhibitory activity. These results highlight the importance of considering the broader relevance of the gut microbiome for drug disposition beyond first-pass metabolism.

Bacillamide D produced by Bacillus cereus from the mouse intestinal bacterial collection (miBC) is a potent cytotoxin in vitro

The gut microbiota influences human health and the development of chronic diseases. However, our understanding of potentially protective or harmful microbe-host interactions at the molecular level is still in its infancy. To gain further insights into the hidden gut metabolome and its impact, we identified a cryptic non-ribosomal peptide BGC in the genome of Bacillus cereus DSM 28590 from the mouse intestine ( www.dsmz.de/miBC ), which was predicted to encode a thiazol(in)e substructure. Cloning and heterologous expression of this BGC revealed that it produces bacillamide D. In-depth functional evaluation showed potent cytotoxicity and inhibition of cell migration using the human cell lines HCT116 and HEK293, which was validated using primary mouse organoids. This work establishes the bacillamides as selective cytotoxins from a bacterial gut isolate that affect mammalian cells. Our targeted structure-function-predictive approach is demonstrated to be a streamlined method to discover deleterious gut microbial metabolites with potential effects on human health.

Multi-omic analysis tools for microbial metabolites prediction

How to resolve the metabolic dark matter of microorganisms has long been a challenging problem in discovering active molecules. Diverse omics tools have been developed to guide the discovery and characterization of various microbial metabolites, which make it gradually possible to predict the overall metabolites for individual strains. The combinations of multi-omic analysis tools effectively compensates for the shortcomings of current studies that focus only on single omics or a broad class of metabolites. In this review, we systematically update, categorize and sort out different analysis tools for microbial metabolites prediction in the last five years to appeal for the multi-omic combination on the understanding of the metabolic nature of microbes. First, we provide the general survey on different updated prediction databases, webservers, or software that based on genomics, transcriptomics, proteomics, and metabolomics, respectively. Then, we discuss the essentiality on the integration of multi-omics data to predict metabolites of different microbial strains and communities, as well as stressing the combination of other techniques, such as systems biology methods and data-driven algorithms. Finally, we identify key challenges and trends in developing multi-omic analysis tools for more comprehensive prediction on diverse microbial metabolites that contribute to human health and disease treatment.

Natural products from the human microbiome: an emergent frontier in organic synthesis and drug discovery

Often referred to as the "second genome", the human microbiome is at the epicenter of complex inter-habitat biochemical networks like the "gut-brain axis", which has emerged as a significant determinant of cognition, overall health and well-being, as well as resistance to antibiotics and susceptibility to diseases. As part of a broader understanding of the nexus between the human microbiome, diseases and microbial interactions, whether encoded secondary metabolites (natural products) play crucial signalling roles has been the subject of intense scrutiny in the recent past. A major focus of these activities involves harvesting the genomic potential of the human microbiome via bioinformatics guided genome mining and culturomics. Through these efforts, an impressive number of structurally intriguing antibiotics, with enhanced chemical diversity vis-à-vis conventional antibiotics have been isolated from human commensal bacteria, thereby generating considerable interest in their total synthesis and expanding their therapeutic space for drug discovery. These developments augur well for the discovery of new drugs and antibiotics, particularly in the context of challenges posed by mycobacterial resistance and emerging new diseases. The current landscape of various synthetic campaigns and drug discovery initiatives on antibacterial natural products from the human microbiome is captured in this review with an intent to stimulate further activities in this interdisciplinary arena among the new generation.

Combinatorial discovery of antibacterials via a feature-fusion based machine learning workflow

The discovery of new antibacterials within the vast chemical space is crucial in combating drug-resistant bacteria such as methicillin-resistant Staphylococcus aureus (MRSA). However, the traditional approach of screening the entire chemical library in an ergodic manner can be laborious and time-consuming. Machine learning-assisted screening of antibacterials alleviates the exploration effort but suffers from the lack of reliable and related datasets. To address these challenges, we devised a combinatorial library comprising over 110 000 candidates based on the Ugi reaction. A focused library was subsequently generated through uniform sampling of the entire library to narrow down the preliminary screening scale. A novel feature-fusion architecture called the latent space constraint neural network was developed which incorporated both fingerprint and physicochemical molecular descriptors to predict the antibacterial properties. This integration allowed the model to leverage the complementary information provided by these descriptors and improve the accuracy of predictions. Three lead compounds that demonstrated excellent efficacy against MRSA while alleviating drug resistance were identified. This workflow highlights the integration of machine learning with the combinatorial chemical library to expedite high-quality data collection and extensive data mining for antibacterial screening.

A meta-analysis of the gut microbiome in inflammatory bowel disease patients identifies disease-associated small molecules

Changes in the gut microbiome have been associated with several human diseases, but the molecular and functional details underlying these associations remain largely unknown. Here, we performed a multi-cohort analysis of small molecule biosynthetic gene clusters (BGCs) in 5,306 metagenomic samples of the gut microbiome from 2,033 Inflammatory Bowel Disease (IBD) patients and 833 matched healthy subjects and identified a group of Clostridia-derived BGCs that are significantly associated with IBD. Using synthetic biology, we discovered and solved the structures of six fatty acid amides as the products of the IBD-enriched BGCs. Using two mouse models of colitis, we show that the discovered small molecules disrupt gut permeability and exacerbate inflammation in chemically and genetically susceptible mice. These findings suggest that microbiome-derived small molecules may play a role in the etiology of IBD and represent a generalizable approach for discovering molecular mediators of microbiome-host interactions in the context of microbiome-associated diseases.

Precision enzyme discovery through targeted mining of metagenomic data

Metagenomics has opened new avenues for exploring the genetic potential of uncultured microorganisms, which may serve as promising sources of enzymes and natural products for industrial applications. Identifying enzymes with improved catalytic properties from the vast amount of available metagenomic data poses a significant challenge that demands the development of novel computational and functional screening tools. The catalytic properties of all enzymes are primarily dictated by their structures, which are predominantly determined by their amino acid sequences. However, this aspect has not been fully considered in the enzyme bioprospecting processes. With the accumulating number of available enzyme sequences and the increasing demand for discovering novel biocatalysts, structural and functional modeling can be employed to identify potential enzymes with novel catalytic properties. Recent efforts to discover new polysaccharide-degrading enzymes from rumen metagenome data using homology-based searches and machine learning-based models have shown significant promise. Here, we will explore various computational approaches that can be employed to screen and shortlist metagenome-derived enzymes as potential biocatalyst candidates, in conjunction with the wet lab analytical methods traditionally used for enzyme characterization.

Commensal production of a broad-spectrum and short-lived antimicrobial peptide polyene eliminates nasal Staphylococcus aureus

Antagonistic bacterial interactions often rely on antimicrobial bacteriocins, which attack only a narrow range of target bacteria. However, antimicrobials with broader activity may be advantageous. Here we identify an antimicrobial called epifadin, which is produced by nasal Staphylococcus epidermidis IVK83. It has an unprecedented architecture consisting of a non-ribosomally synthesized peptide, a polyketide component and a terminal modified amino acid moiety. Epifadin combines a wide antimicrobial target spectrum with a short life span of only a few hours. It is highly unstable under in vivo-like conditions, potentially as a means to limit collateral damage of bacterial mutualists. However, Staphylococcus aureus is eliminated by epifadin-producing S. epidermidis during co-cultivation in vitro and in vivo, indicating that epifadin-producing commensals could help prevent nasal S. aureus carriage. These insights into a microbiome-derived, previously unknown antimicrobial compound class suggest that limiting the half-life of an antimicrobial may help to balance its beneficial and detrimental activities.

De Novo Synthesis of a Conjugative System from Human Gut Metagenomic Data for Targeted Delivery of Cas9 Antimicrobials

Metagenomic sequences represent an untapped source of genetic novelty, particularly for conjugative systems that could be used for plasmid-based delivery of Cas9-derived antimicrobial agents. However, unlocking the functional potential of conjugative systems purely from metagenomic sequences requires the identification of suitable candidate systems as starting scaffolds for de novo DNA synthesis. Here, we developed a bioinformatics approach that searches through the metagenomic "trash bin" for genes associated with conjugative systems present on contigs that are typically excluded from common metagenomic analysis pipelines. Using a human metagenomic gut data set representing 2805 taxonomically distinct units, we identified 1598 contigs containing conjugation genes with a differential distribution in human cohorts. We synthesized de novo an entire Citrobacter spp. conjugative system of 54 kb containing at least 47 genes and assembled it into a plasmid, pCitro. We found that pCitro conjugates from Escherichia coli to Citrobacter rodentium with a 30-fold higher frequency than to E. coli, and is compatible with Citrobacter resident plasmids. Mutations in the traV and traY conjugation components of pCitro inhibited conjugation. We showed that pCitro can be repurposed as an antimicrobial delivery agent by programming it with the TevCas9 nuclease and Citrobacter-specific sgRNAs to kill C. rodentium. Our study reveals a trove of uncharacterized conjugative systems in metagenomic data and describes an experimental framework to animate these large genetic systems as novel target-adapted delivery vectors for Cas9-based editing of bacterial genomes.

Systematic mining of the human microbiome identifies antimicrobial peptides with diverse activity spectra

Human-associated bacteria secrete modified peptides to control host physiology and remodel the microbiota species composition. Here we scanned 2,229 Human Microbiome Project genomes of species colonizing skin, gastrointestinal tract, urogenital tract, mouth and trachea for gene clusters encoding RiPPs (ribosomally synthesized and post-translationally modified peptides). We found 218 lanthipeptides and 25 lasso peptides, 70 of which were synthesized and expressed in E. coli and 23 could be purified and functionally characterized. They were tested for activity against bacteria associated with healthy human flora and pathogens. New antibiotics were identified against strains implicated in skin, nasal and vaginal dysbiosis as well as from oral strains selectively targeting those in the gut. Extended- and narrow-spectrum antibiotics were found against methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococci. Mining natural products produced by human-associated microbes will enable the elucidation of ecological relationships and may be a rich resource for antimicrobial discovery.

Unraveling Intestinal Microbial Shifts in ESRD and Kidney Transplantation: Implications for Disease-Related Dysbiosis

The composition of the gut microbiome is profoundly influenced by the accumulation of toxins in end-stage renal disease (ESRD) and specific medical treatments during kidney transplantation (KT). However, variations in results may arise due to factors such as genetics, dietary habits, and the strategy of anti-rejection therapy. Therefore, we conducted a 16S rRNA sequencing study to characterize intestinal microbiomes by using 75 fecal specimens obtained from 25 paired Chinese living donors (LDs) of kidneys and recipients before and after KT. Surprisingly, similar enterotypes were observed between healthy LDs and ESRD recipients. Nonetheless, following KT, the fecal communities of recipients exhibited distinct clustering, which was primarily characterized by Escherichia-Shigella and Streptococcus at the genus level, along with a reduction in the diversity of microbiota. To further explore the characteristics of gut microorganisms in early rejection episodes, two recipients with biopsy-proven borderline changes during follow-up were enrolled in a preliminary sub-cohort study. Our findings reveal a comparable construction of gut microbiota between ESRD patients and their healthy relatives while also highlighting the significant impact of KT on gut microbial composition.

Ice Cores as a Source for Antimicrobials: From Bioprospecting to Biodesign

The golden age has passed for antibiotic discovery, and while some antibiotics are currently in various phases of clinical trials in the United States, many pharmaceutical companies have abandoned antibiotic research. With the need for antibiotics, we should expand our horizon for therapeutic mining and can look toward understudied sources such as ice cores. Ice cores contain microorganisms and genetic material that have been frozen in time for thousands of years. The antibiotics used by these organisms are encoded in their genomes, which can be unlocked, identified, and characterized with modern advances in molecular biology, genetic sequencing, various computational approaches, and established natural product discovery pipelines. While synthetic biology can be used in natural product discovery approaches, synthetic biology and bioengineering efforts can also be leveraged in the selection and biodesign of increased compound yields, potency, and stability. Here, we provide the perspective that ice cores can be a source of novel antibiotic compounds and that the tools of synthetic biology can be used to design better antimicrobials.

Computational exploration of the global microbiome for antibiotic discovery

Novel antibiotics are urgently needed to combat the antibiotic-resistance crisis. We present a machine learning-based approach to predict prokaryotic antimicrobial peptides (AMPs) by leveraging a vast dataset of 63,410 metagenomes and 87,920 microbial genomes. This led to the creation of AMPSphere, a comprehensive catalog comprising 863,498 non-redundant peptides, the majority of which were previously unknown. We observed that AMP production varies by habitat, with animal-associated samples displaying the highest proportion of AMPs compared to other habitats. Furthermore, within different human-associated microbiota, strain-level differences were evident. To validate our predictions, we synthesized and experimentally tested 50 AMPs, demonstrating their efficacy against clinically relevant drug-resistant pathogens both in vitro and in vivo. These AMPs exhibited antibacterial activity by targeting the bacterial membrane. Additionally, AMPSphere provides valuable insights into the evolutionary origins of peptides. In conclusion, our approach identified AMP sequences within prokaryotic microbiomes, opening up new avenues for the discovery of antibiotics.

Discovering functional small molecules in the gut microbiome

The human microbiome has emerged as a source of bacterially produced, functional small molecules that help regulate health and disease, and their discovery and annotation has become a popular research topic. Identifying these molecules provides an essential step in unraveling the molecular mechanisms underlying biological outcomes. The relevance of specific bacterial members of the microbiome has been demonstrated in a variety of correlative studies, and there are many possible paths from these correlations to the responsible metabolites. Herein, we summarize two studies that have recently identified gut microbiome metabolites that modulate immune responses or promote physical activity. Aside from the deep insights gained, these studies provide blueprints for successfully uncovering the molecules and mechanisms that control important physiological pathways.

Emerging roles of low-molecular-weight thiols at the host-microbe interface

Low-molecular-weight (LMW) thiols are an abundant class of cysteine-derived small molecules found in all forms of life that maintain reducing conditions within cells. While their contributions to cellular redox homeostasis are well established, LMW thiols can also mediate other aspects of cellular physiology, including intercellular interactions between microbial and host cells. Here we discuss emerging roles for these redox-active metabolites at the host-microbe interface. We begin by providing an overview of chemical and computational approaches to LMW-thiol discovery. Next, we highlight mechanisms of virulence regulation by LMW thiols in infected cells. Finally, we describe how microbial metabolism of these compounds may influence host physiology.

A catalog of bacterial reference genomes from cultivated human oral bacteria

The oral cavity harbors highly diverse communities of microorganisms. However, the number of isolated species and high-quality genomes is limited. Here we present a Cultivated Oral Bacteria Genome Reference (COGR), comprising 1089 high-quality genomes based on large-scale aerobic and anaerobic cultivation of human oral bacteria isolated from dental plaques, tongue, and saliva. COGR covers five phyla and contains 195 species-level clusters of which 95 include 315 genomes representing species with no taxonomic annotation. The oral microbiota differs markedly between individuals, with 111 clusters being person-specific. Genes encoding CAZymes are abundant in the genomes of COGR. Members of the Streptococcus genus make up the largest proportion of COGR and many of these harbor entire pathways for quorum sensing important for biofilm formation. Several clusters containing unknown bacteria are enriched in individuals with rheumatoid arthritis, emphasizing the importance of culture-based isolation for characterizing and exploiting oral bacteria.

Natural products from reconstructed bacterial genomes of the Middle and Upper Paleolithic

Major advances over the past decade in the field of ancient DNA are providing access to past paleogenomic diversity, but the diverse functions and biosynthetic capabilities of this growing paleome remain largely elusive. Here, we investigated the dental calculus of 12 Neanderthals and 52 anatomically modern humans spanning 100 kya to the present and reconstructed 459 bacterial metagenome-assembled genomes (MAGs). We identified a biosynthetic gene cluster (BGC) shared by seven Middle and Upper Paleolithic individuals that allows for the heterologous production of a class of previously unknown metabolites we name paleofurans. This paleobiotechnological approach demonstrates that viable biosynthetic machinery can be produced from the preserved genetic material of ancient organisms, allowing access to natural products from the Pleistocene and providing a promising area for natural product exploration.

Links between Diet, Intestinal Anaerobes, Microbial Metabolites and Health

A dense microbial community resides in the human colon, with considerable inter-individual variability in composition, although some species are relatively dominant and widespread in healthy individuals. In disease conditions, there is often a reduction in microbial diversity and perturbations in the composition of the microbiota. Dietary complex carbohydrates that reach the large intestine are important modulators of the composition of the microbiota and their primary metabolic outputs. Specialist gut bacteria may also transform plant phenolics to form a spectrum of products possessing antioxidant and anti-inflammatory activities. Consumption of diets high in animal protein and fat may lead to the formation of potentially deleterious microbial products, including nitroso compounds, hydrogen sulphide, and trimethylamine. Gut anaerobes also form a range of secondary metabolites, including polyketides that may possess antimicrobial activity and thus contribute to microbe-microbe interactions within the colon. The overall metabolic outputs of colonic microbes are derived from an intricate network of microbial metabolic pathways and interactions; however, much still needs to be learnt about the subtleties of these complex networks. In this review we consider the multi-faceted relationships between inter-individual microbiota variation, diet, and health.

Evolutionary investigations of the biosynthetic diversity in the skin microbiome using lsaBGC

Bacterial secondary metabolites, synthesized by enzymes encoded in biosynthetic gene clusters (BGCs), can underlie microbiome homeostasis and serve as commercialized products, which have historically been mined from a select group of taxa. While evolutionary approaches have proven beneficial for prioritizing BGCs for experimental characterization efforts to uncover new natural products, dedicated bioinformatics tools designed for comparative and evolutionary analysis of BGCs within focal taxa are limited. We thus developed l ineage s pecific a nalysis of BGCs (lsa BGC; https://github.com/Kalan-Lab/lsaBGC ) to aid exploration of microdiversity and evolutionary trends across homologous groupings of BGCs, gene cluster families (GCFs), in any bacterial taxa of interest. lsa BGC enables rapid and direct identification of GCFs in genomes, calculates evolutionary statistics and conservation for BGC genes, and builds a framework to allow for base resolution mining of novel variants through metagenomic exploration. Through application of the suite to four genera commonly found in skin microbiomes, we uncover new insights into the evolution and diversity of their BGCs. We show that the BGC of the virulence-associated carotenoid staphyloxanthin in Staphylococcus aureus is ubiquitous across the genus Staphylococcus . While one GCF encoding the biosynthesis of staphyloxanthin showcases evidence for plasmid-mediated horizontal gene transfer (HGT) between species, another GCF appears to be transmitted vertically amongst a sub-clade of skin-associated Staphylococcus . Further, the latter GCF, which is well conserved in S. aureus , has been lost in most Staphylococcus epidermidis , which is the most common Staphylococcus species on human skin and is also regarded as a commensal. We also identify thousands of novel single-nucleotide variants (SNVs) within BGCs from the Corynebacterium tuberculostearicum sp. complex, a narrow, multi-species clade that features the most prevalent Corynebacterium in healthy skin microbiomes. Although novel SNVs were approximately 10 times as likely to correspond to synonymous changes when located in the top five percentile of conserved sites, lsa BGC identified SNVs that defied this trend and are predicted to underlie amino acid changes within functionally key enzymatic domains. Ultimately, beyond supporting evolutionary investigations of BGCs, lsa BGC also provides important functionalities to aid efforts for the discovery or directed modification of natural products.

The genomic landscape of reference genomes of cultivated human gut bacteria

Culture-independent metagenomic studies have revolutionized our understanding of the gut microbiota. However, the lack of full genomes from cultured species is still a limitation for in-depth studies of the gut microbiota. Here we present a substantially expanded version of our Cultivated Genome Reference (CGR), termed CGR2, providing 3324 high-quality draft genomes from isolates selected from a large-scale cultivation of bacterial isolates from fecal samples of healthy Chinese individuals. The CGR2 classifies 527 species (179 previously unidentified species) from 8 phyla, and uncovers a genomic and functional diversity of Collinsella aerofaciens. The CGR2 genomes match 126 metagenome-assembled genomes without cultured representatives in the Unified Human Gastrointestinal Genome (UHGG) collection and harbor 3767 unidentified secondary metabolite biosynthetic gene clusters, providing a source of natural compounds with pharmaceutical potentials. We uncover accurate phage-bacterium linkages providing information on the evolutionary characteristics of interaction between bacteriophages and bacteria at the strain level.

Turning Microbial AhR Agonists into Therapeutic Agents via Drug Delivery Systems

Developing therapeutics for inflammatory diseases is challenging due to physiological mucosal barriers, systemic side effects, and the local microbiota. In the search for novel methods to overcome some of these problems, drug delivery systems that improve tissue-targeted drug delivery and modulate the microbiota are highly desirable. Microbial metabolites are known to regulate immune responses, an observation that has resulted in important conceptual advances in areas such as metabolite pharmacology and metabolite therapeutics. Indeed, the doctrine of "one molecule, one target, one disease" that has dominated the pharmaceutical industry in the 20th century is being replaced by developing therapeutics which simultaneously manipulate multiple targets through novel formulation approaches, including the multitarget-directed ligands. Thus, metabolites may not only represent biomarkers for disease development, but also, being causally linked to human diseases, an unexploited source of therapeutics. We have shown the successful exploitation of this approach: by deciphering how signaling molecules, such as the microbial metabolite, indole-3-aldehyde, and the repurposed drug anakinra, interact with the aryl hydrocarbon receptor may pave the way for novel therapeutics in inflammatory human diseases, for the realization of which drug delivery platforms are instrumental.

Strategizing the human microbiome for small molecules: Approaches and perspectives

Studies of the human microbiome are providing a deeper understanding of its significance to human health, and increasing evidence links the microbiota with several diseases. Nevertheless, the exact mechanisms involved in human-microbe interactions are mostly undefined. The genomic potential of the human microbiome to biosynthesize distinct molecules outmatches its known chemical space, and small-molecule discovery in this context remains in its infancy. The profiling of microbiome-derived small molecules and their contextualization through cause-effect mechanistic studies may provide a better understanding of host-microbe interactions, guide new therapeutic interventions, and modulate microbiome-based therapies. This review describes the advances, approaches, and allied challenges in mining new microbial scaffolds from the human microbiome using genomic, microbe cultivation, and chemical analytic platforms. In the future, the complete biological characterization of a single microbe-derived molecule that has a specific therapeutic application could resolve the current limitations of microbiota-modulating therapies.

Metagenomic Data Reveal Type I Polyketide Synthase Distributions Across Biomes

Microbial polyketide synthase (PKS) genes encode the biosynthesis of many biomedically important natural products, yet only a small fraction of nature's polyketide biosynthetic potential has been realized. Much of this potential originates from type I PKSs (T1PKSs), which can be delineated into different classes and subclasses based on domain organization and structural features of the compounds encoded. Notably, phylogenetic relationships among PKS ketosynthase (KS) domains provide a method to classify the larger and more complex genes in which they occur. Increased access to large metagenomic datasets from diverse habitats provides opportunities to assess T1PKS biosynthetic diversity and distributions through the analysis of KS domain sequences. Here, we used the webtool NaPDoS2 to detect and classify over 35,000 type I KS domains from 137 metagenomic data sets reported from eight diverse biomes. We found biome-specific separation with soils enriched in modular cis -AT and hybrid cis -AT KSs relative to other biomes and marine sediments enriched in KSs associated with PUFA and enediyne biosynthesis. By extracting full-length KS domains, we linked the phylum Actinobacteria to soil-specific enediyne and cis -AT clades and identified enediyne and monomodular KSs in phyla from which the associated compound classes have not been reported. These sequences were phylogenetically distinct from those associated with experimentally characterized PKSs suggesting novel structures or enzyme functions remain to be discovered. Lastly, we employed our metagenome-extracted KS domains to evaluate commonly used type I KS PCR primers and identified modifications that could increase the KS sequence diversity recovered from amplicon libraries.

Importance

Polyketides are a crucial source of medicines, agrichemicals, and other commercial products. Advances in our understanding of polyketide biosynthesis coupled with the accumulation of metagenomic sequence data provide new opportunities to assess polyketide biosynthetic potential across biomes. Here, we used the webtool NaPDoS2 to assess type I PKS diversity and distributions by detecting and classifying KS domains across 137 metagenomes. We show that biomes are differentially enriched in KS domain classes, providing a roadmap for future biodiscovery strategies. Further, KS phylogenies reveal both biome-specific clades that do not include biochemically characterized PKSs, highlighting the biosynthetic potential of poorly explored environments. The large metagenome-derived KS dataset allowed us to identify regions of commonly used type I KS PCR primers that could be modified to capture a larger extent of KS diversity. These results facilitate both the search for novel polyketides and our understanding of the biogeographical distribution of PKSs across earth's major biomes.

Identification of PKS Gene Clusters from Metagenomic Libraries Using a Next-Generation Sequencing Approach

Microbial secondary metabolites have been an important source of bioactive compounds with diverse applications from medicine to agriculture, noticeably those encoded by polyketide synthase (PKS) clusters due to their astounding chemical diversity. While most discovered compounds originate from culturable microorganisms, yet-to-be cultured microbes represent a reservoir of previously inaccessible compounds. The advent and development of metagenomics have allowed not only the characterization of these microorganisms but also their metabolic potential, making viable the prospection of environmental PKS for natural product discovery.Study of environmental PKSs often relies on the construction of metagenomic libraries and their mining, with clones containing PKS clusters identified via amplification of conserved domains and then screened for an activity of interest. Compounds produced by clones exhibiting the desired bioactivity can be isolated and characterized. However, these approaches can be less sensitive and biased against more divergent clusters, in addition to precluding the use of bioinformatics for cluster characterization prior to expression. While direct shotgun sequencing of metagenomes has identified and profiled a great number of PKSs from different environments and yet-to-be cultured microorganisms, it does not lend itself well to heterologous expression, the cruxes of natural product discovery.Here, we describe a strategy for sequencing entire metagenomic libraries while maintaining correspondence between sequence and clone, allowing the full characterization and annotation of all clusters present in a library using bioinformatic tools and then seamlessly passing clones of interest for activity screening through heterologous expression. Once a library is sequenced, the methods herein can be adapted for the mining of any biosynthetic gene cluster of interest within a metagenomic library.

TaxiBGC: a Taxonomy-Guided Approach for Profiling Experimentally Characterized Microbial Biosynthetic Gene Clusters and Secondary Metabolite Production Potential in Metagenomes

Biosynthetic gene clusters (BGCs) in microbial genomes encode bioactive secondary metabolites (SMs), which can play important roles in microbe-microbe and host-microbe interactions. Given the biological significance of SMs and the current profound interest in the metabolic functions of microbiomes, the unbiased identification of BGCs from high-throughput metagenomic data could offer novel insights into the complex chemical ecology of microbial communities. Currently available tools for predicting BGCs from shotgun metagenomes have several limitations, including the need for computationally demanding read assembly, predicting a narrow breadth of BGC classes, and not providing the SM product. To overcome these limitations, we developed taxonomy-guided identification of biosynthetic gene clusters (TaxiBGC), a command-line tool for predicting experimentally characterized BGCs (and inferring their known SMs) in metagenomes by first pinpointing the microbial species likely to harbor them. We benchmarked TaxiBGC on various simulated metagenomes, showing that our taxonomy-guided approach could predict BGCs with much-improved performance (mean F1 score, 0.56; mean PPV score, 0.80) compared with directly identifying BGCs by mapping sequencing reads onto the BGC genes (mean F1 score, 0.49; mean PPV score, 0.41). Next, by applying TaxiBGC on 2,650 metagenomes from the Human Microbiome Project and various case-control gut microbiome studies, we were able to associate BGCs (and their SMs) with different human body sites and with multiple diseases, including Crohn's disease and liver cirrhosis. In all, TaxiBGC provides an in silico platform to predict experimentally characterized BGCs and their SM production potential in metagenomic data while demonstrating important advantages over existing techniques. IMPORTANCE Currently available bioinformatics tools to identify BGCs from metagenomic sequencing data are limited in their predictive capability or ease of use to even computationally oriented researchers. We present an automated computational pipeline called TaxiBGC, which predicts experimentally characterized BGCs (and infers their known SMs) in shotgun metagenomes by first considering the microbial species source. Through rigorous benchmarking techniques on simulated metagenomes, we show that TaxiBGC provides a significant advantage over existing methods. When demonstrating TaxiBGC on thousands of human microbiome samples, we associate BGCs encoding bacteriocins with different human body sites and diseases, thereby elucidating a possible novel role of this antibiotic class in maintaining the stability of microbial ecosystems throughout the human body. Furthermore, we report for the first time gut microbial BGC associations shared among multiple pathologies. Ultimately, we expect our tool to facilitate future investigations into the chemical ecology of microbial communities across diverse niches and pathologies.

Microbial Dark Matter: from Discovery to Applications

With the rapid increase of the microbiome samples and sequencing data, more and more knowledge about microbial communities has been gained. However, there is still much more to learn about microbial communities, including billions of novel species and genes, as well as countless spatiotemporal dynamic patterns within the microbial communities, which together form the microbial dark matter. In this work, we summarized the dark matter in microbiome research and reviewed current data mining methods, especially artificial intelligence (AI) methods, for different types of knowledge discovery from microbial dark matter. We also provided case studies on using AI methods for microbiome data mining and knowledge discovery. In summary, we view microbial dark matter not as a problem to be solved but as an opportunity for AI methods to explore, with the goal of advancing our understanding of microbial communities, as well as developing better solutions to global concerns about human health and the environment.

Molecular tools for probing the microbiome

The microbiome plays essential roles in health and disease. Our understanding of the imbalances that can arise in the microbiome and their consequences is held back by a lack of technologies that selectively knock out members of these microbial communities. Antibiotics and fecal transplants, the existing methods for manipulating the microbiota of the gastrointestinal tract, are not sufficiently pinpointed to reveal how particular microbial genes, strains, or species affect human health. A toolset for the precise manipulation of the microbiome could significantly advance disease diagnosis and treatment. Here, we provide an overview of current and future strategies for the development of molecular tools that can be used to probe the microbiome without producing off-target effects.

A structural metagenomics pipeline for examining the gut microbiome

Metagenomic sequencing data provide a rich resource from which to expand our understanding of differential protein functions involved in human health. Here, we outline a pipeline that combines microbial whole genome sequencing with protein structure data to yield a structural metagenomics-informed atlas of microbial enzyme families of interest. Visualizing metagenomics data through a structural lens facilitates downstream studies including targeted inhibition and probe-based proteomics to define at the molecular level how different enzyme orthologs impact in vivo function. Application of this pipeline to gut microbial enzymes like glucuronidases, TMA lyases, and bile salt hydrolases is expected to pinpoint their involvement in health and disease and may aid in the development of therapeutics that target specific enzymes within the microbiome.

Comparative Metagenomic Analysis of Biosynthetic Diversity across Sponge Microbiomes Highlights Metabolic Novelty, Conservation, and Diversification

Marine sponges and their microbial symbiotic communities are rich sources of diverse natural products (NPs) that often display biological activity, yet little is known about the global distribution of NPs and the symbionts that produce them. Since the majority of sponge symbionts remain uncultured, it is a challenge to characterize their NP biosynthetic pathways, assess their prevalence within the holobiont, and measure the diversity of NP biosynthetic gene clusters (BGCs) across sponge taxa and environments. Here, we explore the microbial biosynthetic landscapes of three high-microbial-abundance (HMA) sponges from the Atlantic Ocean and the Mediterranean Sea. This data set reveals striking novelty, with <1% of the recovered gene cluster families (GCFs) showing similarity to any characterized BGC. When zooming in on the microbial communities of each sponge, we observed higher variability of specialized metabolic and taxonomic profiles between sponge species than within species. Nonetheless, we identified conservation of GCFs, with 20% of sponge GCFs being shared between at least two sponge species and a GCF core comprised of 6% of GCFs shared across all species. Within this functional core, we identified a set of widespread and diverse GCFs encoding nonribosomal peptide synthetases that are potentially involved in the production of diversified ether lipids, as well as GCFs putatively encoding the production of highly modified proteusins. The present work contributes to the small, yet growing body of data characterizing NP landscapes of marine sponge symbionts and to the cryptic biosynthetic potential contained in this environmental niche. IMPORTANCE Marine sponges and their microbial symbiotic communities are a rich source of diverse natural products (NPs). However, little is known about the sponge NP global distribution landscape and the symbionts that produce them. Here, we make use of recently developed tools to perform untargeted mining and comparative analysis of sponge microbiome metagenomes of three sponge species in the first study considering replicate metagenomes of multiple sponge species. We present an overview of the biosynthetic diversity across these sponge holobionts, which displays extreme biosynthetic novelty. We report not only the conservation of biosynthetic and taxonomic diversity but also a core of conserved specialized metabolic pathways. Finally, we highlight several novel GCFs with unknown ecological function, and observe particularly high biosynthetic potential in Acidobacteriota and Latescibacteria symbionts. This study paves the way toward a better understanding of the marine sponge holobionts' biosynthetic potential and the functional and ecological role of sponge microbiomes.

Microenvironmental Factors that Shape Bacterial Metabolites in Inflammatory Bowel Disease

Inflammatory bowel disease (IBD) is a significant global health problem that involves chronic intestinal inflammation and can involve severe comorbidities, including intestinal fibrosis and inflammation-associated colorectal cancer (CRC). Disease-associated alterations to the intestinal microbiota often include fecal enrichment of Enterobacteriaceae, which are strongly implicated in IBD development. This dysbiosis of intestinal flora accompanies changes in microbial metabolites, shaping host:microbe interactions and disease risk. While there have been numerous studies linking specific bacterial taxa with IBD development, our understanding of microbial function in the context of IBD is limited. Several classes of microbial metabolites have been directly implicated in IBD disease progression, including bacterial siderophores and genotoxins. Yet, our microbiota still harbors thousands of uncharacterized microbial products. In-depth discovery and characterization of disease-associated microbial metabolites is necessary to target these products in IBD treatment strategies. Towards improving our understanding of microbiota metabolites in IBD, it is important to recognize how host relevant factors influence microbiota function. For example, changes in host inflammation status, metal availability, interbacterial community structure, and xenobiotics all play an important role in shaping gut microbial ecology. In this minireview, we outline how each of these factors influences gut microbial function, with a specific focus on IBD-associated Enterobacteriaceae metabolites. Importantly, we discuss how altering the intestinal microenvironment could improve the treatment of intestinal inflammation and associated disorders, like intestinal fibrosis and CRC.

Activating natural product synthesis using CRISPR interference and activation systems in Streptomyces

The rise of antibiotic-resistant bacteria represents a major threat to global health, creating an urgent need to discover new antibiotics. Natural products derived from the genus Streptomyces represent a rich and diverse repertoire of chemical molecules from which new antibiotics are likely to be found. However, a major challenge is that the biosynthetic gene clusters (BGCs) responsible for natural product synthesis are often poorly expressed under laboratory culturing conditions, thus preventing the isolation and screening of novel chemicals. To address this, we describe a novel approach to activate silent BGCs through rewiring endogenous regulation using synthetic gene regulators based upon CRISPR-Cas. First, we refine CRISPR interference (CRISPRi) and create CRISPR activation (CRISPRa) systems that allow for highly programmable and effective gene repression and activation in Streptomyces. We then harness these tools to activate a silent BGC by perturbing its endogenous regulatory network. Together, this work advances the synthetic regulatory toolbox for Streptomyces and facilitates the programmable activation of silent BGCs for novel chemical discovery.

Targeted Large-Scale Genome Mining and Candidate Prioritization for Natural Product Discovery

Large-scale genome-mining analyses have identified an enormous number of cryptic biosynthetic gene clusters (BGCs) as a great source of novel bioactive natural products. Given the sheer number of natural product (NP) candidates, effective strategies and computational methods are keys to choosing appropriate BGCs for further NP characterization and production. This review discusses genomics-based approaches for prioritizing candidate BGCs extracted from large-scale genomic data, by highlighting studies that have successfully produced compounds with high chemical novelty, novel biosynthesis pathway, and potent bioactivities. We group these studies based on their BGC-prioritization logics: detecting presence of resistance genes, use of phylogenomics analysis as a guide, and targeting for specific chemical structures. We also briefly comment on the different bioinformatics tools used in the field and examine practical considerations when employing a large-scale genome mining study.

Investigation of the Molecular Landscape of Bacterial Aromatic Polyketides by Global Analysis of Type II Polyketide Synthases

Aromatic polyketides biosynthesized by microorganisms are a prominent class of natural products widely used in clinical treatments. Although genome mining approaches have accelerated the discovery of these molecules, the molecular diversity, abundance, and distribution of bacterial aromatic polyketides at a global scale remain elusive. Here, we provide a global atlas of bacterial aromatic polyketides based on large-scale analysis of type II polyketide synthases. We first established the chain length factor protein as a marker that can predict both chemical class and molecular uniqueness of the biosynthetic product, and analyzed the abundance, taxonomic distribution, estimated structural diversity, and the total number of aromatic polyketides in bacteria. We further show the identification of oryzanaphthopyrans with an unprecedented angular naphthopyran scaffold from a rare actinobacterium by genome mining guided by the global atlas. These results serve as a compass for exploiting the entire type II polyketide synthase-derived aromatic polyketides in bacteria.

Microbial metabolites: cause or consequence in gastrointestinal disease?

Systems biology studies have established that changes in gastrointestinal microbiome composition and function can adversely impact host physiology. Notable diseases synonymously associated with dysbiosis include inflammatory bowel diseases, cancer, metabolic disorders, and opportunistic and recurrent pathogen infections. However, there is a scarcity of mechanistic data that advances our understanding of taxonomic correlations with pathophysiological host-microbiome interactions. Generally, to survive a hostile gut environment, microbes are highly metabolically active and produce trans-kingdom signaling molecules to interact with competing microorganisms and the host. These specialized metabolites likely play important homeostatic roles, and identifying disease-specific taxa and their effector pathways can provide better strategies for diagnosis, treatment, and prevention, as well as the discovery of innovative therapeutics. The signaling role of microbial biotransformation products such as bile acids, short-chain fatty acids, polysaccharides, and dietary tryptophan is increasingly recognized, but little is known about the identity and function of metabolites that are synthesized by microbial biosynthetic gene clusters, including ribosomally synthesized and posttranslationally modified peptides (RiPPs), nonribosomal peptides (NRPs), polyketides (PKs), PK-NRP hybrids, and terpenes. Here we consider how bioactive natural products directly encoded by the human microbiome can contribute to the pathophysiology of gastrointestinal disease, cancer, autoimmune, antimicrobial-resistant bacterial and viral infections (including COVID-19). We also present strategies used to discover these compounds and the biological activities they exhibit, with consideration of therapeutic interventions that could emerge from understanding molecular causation in gut microbiome research.

Cross-kingdom expression of synthetic genetic elements promotes discovery of metabolites in the human microbiome

Small molecules encoded by biosynthetic pathways mediate cross-species interactions and harbor untapped potential, which has provided valuable compounds for medicine and biotechnology. Since studying biosynthetic gene clusters in their native context is often difficult, alternative efforts rely on heterologous expression, which is limited by host-specific metabolic capacity and regulation. Here, we describe a computational-experimental technology to redesign genes and their regulatory regions with hybrid elements for cross-species expression in Gram-negative and -positive bacteria and eukaryotes, decoupling biosynthetic capacity from host-range constraints to activate silenced pathways. These synthetic genetic elements enabled the discovery of a class of microbiome-derived nucleotide metabolites-tyrocitabines-from Lactobacillus iners. Tyrocitabines feature a remarkable orthoester-phosphate, inhibit translational activity, and invoke unexpected biosynthetic machinery, including a class of "Amadori synthases" and "abortive" tRNA synthetases. Our approach establishes a general strategy for the redesign, expression, mobilization, and characterization of genetic elements in diverse organisms and communities.

Lessons learned by an organic chemist entering the microbiome field

Here, I reflect on my trajectory from a graduate student in organic chemistry to an early-career scientist in the microbiome field. I discuss strategies for discovering microbiome-derived molecules and their activities, and I contemplate how we will uncover which of the molecules we identify are responsible for driving host phenotypes.