A systematic analysis of biosynthetic gene clusters in the human microbiome reveals a common family of antibiotics

Commensal Oral Rothia mucilaginosa Produces Enterobactin, a Metal-Chelating Siderophore

Next-generation sequencing studies of saliva and dental plaque from subjects in both healthy and diseased states have identified bacteria belonging to the Rothia genus as ubiquitous members of the oral microbiota. To gain a deeper understanding of molecular mechanisms underlying the chemical ecology of this unexplored group, we applied a genome mining approach that targets functionally important biosynthetic gene clusters (BGCs). All 45 genomes that were mined, representing Rothia mucilaginosa, Rothia dentocariosa, and Rothia aeria, harbored a catechol-siderophore-like BGC. To explore siderophore production further, we grew the previously characterized R. mucilaginosa ATCC 25296 in liquid cultures, amended with glycerol, which led to the identification of the archetype siderophore enterobactin by using tandem liquid chromatography-mass spectrometry (LC-MS/MS), high-performance liquid chromatography (HPLC), and nuclear magnetic resonance (NMR) spectroscopy. Normally attributed to pathogenic gut bacteria, R. mucilaginosa is the first commensal oral bacterium found to produce enterobactin. Cocultivation studies including R. mucilaginosa or purified enterobactin revealed that enterobactin reduced growth of certain strains of cariogenic Streptococcus mutans and pathogenic strains of Staphylococcus aureus Commensal oral bacteria were either unaffected, reduced in growth, or induced to grow adjacent to enterobactin-producing R. mucilaginosa or the pure compound. Taken together with Rothia's known capacity to ferment a variety of carbohydrates and amino acids, our findings of enterobactin production add an additional level of explanation to R. mucilaginosa's prevalence in the oral cavity. Enterobactin is the strongest Fe(III) binding siderophore known, and its role in oral health requires further investigation.IMPORTANCE The communication language of the human oral microbiota is vastly underexplored. However, a few studies have shown that specialized small molecules encoded by BGCs have critical roles such as in colonization resistance against pathogens and quorum sensing. Here, by using a genome mining approach in combination with compound screening of growth cultures, we identified that the commensal oral community member R. mucilaginosa harbors a catecholate-siderophore BGC, which is responsible for the biosynthesis of enterobactin. The iron-scavenging role of enterobactin is known to have positive effects on the host's iron pool and negative effects on host immune function; however, its role in oral health remains unexplored. R. mucilaginosa was previously identified as an abundant community member in cystic fibrosis, where bacterial iron cycling plays a major role in virulence development. With respect to iron's broad biological importance, iron-chelating enterobactin may explain R. mucilaginosa's colonization success in both health and disease.

Applying microbial ecology to antimicrobial discovery

Introduction of antibiotics into clinical use has contributed to some of the greatest improvements to public health in the 20th century. Most antibiotics are based on antimicrobials that were isolated from environmental microorganisms over 50 years ago, but emerging resistance requires discovery of new molecules and development of these molecules into therapeutics. Bioinformatic analyses of microbial genomes indicate that many more microbial bioactive molecules remain undiscovered. Understanding when, where, and why these molecules are produced informs efforts to tap into the hidden unexplored chemical diversity. Expanding the search to undersampled ecological niches and improving culturing techniques will ensure discovery of new antibiotics.

Intestinal microbial metabolite stercobilin involvement in the chronic inflammation of ob/ob mice

It is crucial that the host and intestinal microflora interact and influence each other to maintain homeostasis and trigger pathological processes. Recent studies have shown that transplantation of the murine intestinal content to recipient germ-free mice enables transmission of the donor’s phenotypes, such as low level chronic inflammation associated with lifestyle-related diseases. These findings indicate that intestinal bacteria produce some molecules to trigger pathological signals. However, fecal microbial metabolites that induce obesity and the type II diabetic phenotype have not been fully clarified. Here, we showed that the intestinal bacterial metabolite stercobilin, a pigment of feces, induced proinflammatory activities including TNF-α and IL-1β induction in mouse macrophage RAW264 cells. Proinflammatory stercobilin levels were significantly higher in ob/ob mice feces than in the feces of control C57BL/6 J mice. Moreover, in this study, we detected stercobilin in mice plasma for the first time, and the levels were higher in ob/ob mice than that of C57BL/6 J mice. Therefore, stercobilin is potentially reabsorbed, circulated through the blood system, and contributes to low level chronic inflammation in ob/ob mice. Since, stercobilin is a bioactive metabolite, it could be a potentially promising biomarker for diagnosis. Further analyses to elucidate the metabolic rate and the reabsorption mechanism of stercobilin may provide possible therapeutic and preventive targets.

Recent development of antiSMASH and other computational approaches to mine secondary metabolite biosynthetic gene clusters

Many drugs are derived from small molecules produced by microorganisms and plants, so-called natural products. Natural products have diverse chemical structures, but the biosynthetic pathways producing those compounds are often organized as biosynthetic gene clusters (BGCs) and follow a highly conserved biosynthetic logic. This allows for the identification of core biosynthetic enzymes using genome mining strategies that are based on the sequence similarity of the involved enzymes/genes. However, mining for a variety of BGCs quickly approaches a complexity level where manual analyses are no longer possible and require the use of automated genome mining pipelines, such as the antiSMASH software. In this review, we discuss the principles underlying the predictions of antiSMASH and other tools and provide practical advice for their application. Furthermore, we discuss important caveats such as rule-based BGC detection, sequence and annotation quality and cluster boundary prediction, which all have to be considered while planning for, performing and analyzing the results of genome mining studies.

Cariogenic Streptococcus mutans Produces Tetramic Acid Strain-Specific Antibiotics That Impair Commensal Colonization

Streptococcus mutans is a common constituent of dental plaque and a major etiologic agent of dental caries (tooth decay). In this study, we elucidated the biosynthetic pathway encoded by muc, a hybrid polyketide synthase and nonribosomal peptide synthetase (PKS/NRPS) biosynthetic gene cluster (BGC), present in a number of globally distributed S. mutans strains. The natural products synthesized by muc included three N-acyl tetramic acid compounds (reutericyclin and two novel analogues) and an unacylated tetramic acid (mutanocyclin). Furthermore, the enzyme encoded by mucF was identified as a novel class of membrane-associated aminoacylases and was responsible for the deacylation of reutericyclin to mutanocyclin. A large number of hypothetical proteins across a broad diversity of bacteria were homologous to MucF, suggesting that this may represent a large family of unexplored acylases. Finally, S. mutans utilized the reutericyclin produced by muc to impair the growth of neighboring oral commensal bacteria. Since S. mutans must be able to out-compete these health-associated organisms to persist in the oral microbiota and cause disease, the competitive advantage conferred by muc suggests that this BGC is likely to be involved in S. mutans ecology and therefore dental plaque dysbiosis and the resulting caries pathogenesis.

Thiopeptide Defense by an Ant's Bacterial Symbiont

Fungus-growing ants and their microbial symbionts have emerged as a model system for understanding antibiotic deployment in an ecological context. Here we establish that bacterial symbionts of the ant Trachymyrmex septentrionalis antagonize their most likely competitors, other strains of ant-associated bacteria, using the thiopeptide antibiotic GE37468. Genomic analysis suggests that these symbionts acquired the GE37468 gene cluster from soil bacteria. This antibiotic, with known activity against human pathogens, was previously identified in a biochemical screen but had no known ecological role. GE37468's host-associated defense role in this insect niche intriguingly parallels the function of similar thiopeptides in the human microbiome.

Bacteria as genetically programmable producers of bioactive natural products

Next to plants, bacteria account for most of the biomass on Earth. They are found everywhere, although certain species thrive only in specific ecological niches. These microorganisms biosynthesize a plethora of both primary and secondary metabolites, defined, respectively, as those required for the growth and maintenance of cellular functions and those not required for survival but offering a selective advantage for the producer under certain conditions. As a result, bacterial fermentation has long been used to manufacture valuable natural products of nutritional, agrochemical and pharmaceutical interest. The interactions of secondary metabolites with their biological targets have been optimized by millions of years of evolution and they are, thus, considered to be privileged chemical structures, not only for drug discovery. During the last two decades, functional genomics has allowed for an in-depth understanding of the underlying biosynthetic logic of secondary metabolites. This has, in turn, paved the way for the unprecedented use of bacteria as programmable biochemical workhorses. In this Review, we discuss the multifaceted use of bacteria as biological factories in diverse applications and highlight recent advances in targeted genetic engineering of bacteria for the production of valuable bioactive compounds. Emphasis is on current advances to access nature's abundance of natural products.

Metabolites Produced by the Oral Commensal Bacterium Corynebacterium durum Extend the Lifespan of Caenorhabditis elegans via SIR-2.1 Overexpression

Human microbiota is heavily involved in host health, including the aging process. Based on the hypothesis that the human microbiota manipulates host aging via the production of chemical messengers, lifespan-extending activities of the metabolites produced by the oral commensal bacterium Corynebacterium durum and derivatives thereof were evaluated using the model organism Caenorhabditis elegans. Chemical investigation of the acetone extract of a C. durum culture led to the identification of monoamines and N-acetyl monoamines as major metabolites. Phenethylamine and N-acetylphenethylamine induced a potent and dose-dependent increase of the C. elegans lifespan, up to 21.6% and 19.9%, respectively. A mechanistic study revealed that the induction of SIR-2.1, a highly conserved protein associated with the regulation of lifespan, was responsible for the observed increased longevity.

Harnessing the gut microbiome in the fight against anthelminthic drug resistance

Intestinal helminth parasites present major challenges to the welfare of humans and threaten the global food supply. While the discovery of anthelminthic drugs empowered our ability to offset these harms to society, the alarming rise of anthelminthic drug resistance mitigates contemporary efforts to treat and control intestinal helminthic infections. Fortunately, emerging research points to potential opportunities to combat anthelminthic drug resistance by harnessing the gut microbiome as a resource for discovering novel therapeutics and informing responsible drug administration. In this review, we highlight research that demonstrates this potential and provide rationale to support increased investment in efforts to uncover and translationally utilize knowledge about how the gut microbiome mediates intestinal helminthic infection and its outcomes.

Synthetic Antimicrobial Peptide Tuning Permits Membrane Disruption and Interpeptide Synergy

The ribosomally produced antimicrobial peptides of bacteria (bacteriocins) represent an unexplored source of membrane-active antibiotics. We designed a library of linear peptides from a circular bacteriocin and show that pore-formation dynamics in bacterial membranes are tunable via selective amino acid substitution. We observed antibacterial interpeptide synergy indicating that fundamentally altering interactions with the membrane enables synergy. Our findings suggest an approach for engineering pore-formation through rational peptide design and increasing the utility of novel antimicrobial peptides by exploiting synergy.

Defensive Symbioses in Social Insects Can Inform Human Health and Agriculture

Social animals are among the most successful organisms on the planet and derive many benefits from living in groups, including facilitating the evolution of agriculture. However, living in groups increases the risk of disease transmission in social animals themselves and the cultivated crops upon which they obligately depend. Social insects offer an interesting model to compare to human societies, in terms of how insects manage disease within their societies and with their agricultural symbionts. As living in large groups can help the spread of beneficial microbes as well as pathogens, we examine the role of defensive microbial symbionts in protecting the host from pathogens. We further explore how beneficial microbes may influence other pathogen defenses including behavioral and immune responses, and how we can use insect systems as models to inform on issues relating to human health and agriculture.

Genome mining of biosynthetic and chemotherapeutic gene clusters in Streptomyces bacteria

Streptomyces bacteria are known for their prolific production of secondary metabolites, many of which have been widely used in human medicine, agriculture and animal health. To guide the effective prioritization of specific biosynthetic gene clusters (BGCs) for drug development and targeting the most prolific producer strains, knowledge about phylogenetic relationships of Streptomyces species, genome-wide diversity and distribution patterns of BGCs is critical. We used genomic and phylogenetic methods to elucidate the diversity of major classes of BGCs in 1,110 publicly available Streptomyces genomes. Genome mining of Streptomyces reveals high diversity of BGCs and variable distribution patterns in the Streptomyces phylogeny, even among very closely related strains. The most common BGCs are non-ribosomal peptide synthetases, type 1 polyketide synthases, terpenes, and lantipeptides. We also found that numerous Streptomyces species harbor BGCs known to encode antitumor compounds. We observed that strains that are considered the same species can vary tremendously in the BGCs they carry, suggesting that strain-level genome sequencing can uncover high levels of BGC diversity and potentially useful derivatives of any one compound. These findings suggest that a strain-level strategy for exploring secondary metabolites for clinical use provides an alternative or complementary approach to discovering novel pharmaceutical compounds from microbes.

Antimicrobial production by strictly anaerobic Clostridium spp

Antimicrobial resistance continues to rise on a global scale, affecting the environment, humans, animals and food systems. Use of natural antimicrobials has been favoured over synthetic molecules in food preservation owing to concerns over the adverse health effects of synthetic chemicals. The continuing need for novel natural antimicrobial compounds has spurred research to investigate natural sources, such as bacteria, for antimicrobials. The antimicrobial-producing potential of bacteria has been investigated in numerous studies. However, the discovery of antimicrobials has been biased towards aerobes and facultative anaerobes, and strict anaerobes such as Clostridium spp. have been largely neglected. In recent years, genomic studies have indicated the genetic potential of strict anaerobes to produce putative bioactive molecules and this has encouraged the exploration of Clostridium spp. for their antimicrobial production. So far, only a limited number of antimicrobial compounds have been isolated, identified and characterised from the genus Clostridium. This review discusses our current knowledge and understanding of clostridial antimicrobial compounds as well as recent genome mining studies of Clostridium spp. focused at identification of putative gene clusters encoding bacterial secondary metabolite groups and peptides reported to possess antimicrobial properties. Furthermore, opportunities and challenges in the identification of antimicrobials from Clostridium spp. using genomic-guided approaches are discussed. The limited studies conducted so far have identified the genus Clostridium as a viable source of antimicrobial compounds for future investigations.

Identification of a Human Skin Commensal Bacterium that Selectively Kills Cutibacterium acnes

The microbiome represents a vast resource for drug discovery, as its members engage in constant conflict to outcompete one another by deploying diverse strategies for survival. Cutibacterium acnes is one of the most common bacterial species on human skin and can promote the common disease acne vulgaris. By employing a combined strategy of functional screening, genetics, and proteomics we discovered a strain of Staphylococcus capitis (S. capitis E12) that selectively inhibited growth of C. acnes with potency greater than antibiotics commonly used in the treatment of acne. Antimicrobial peptides secreted from S. capitis E12 were identified as four distinct phenol-soluble modulins acting synergistically. These peptides were not toxic to human keratinocytes and the S. capitis extract did not kill other commensal skin bacteria but was effective against C. acnes on pig skin and on mice. Overall, these data show how a member of the human skin microbiome can be useful as a biotherapy for acne vulgaris.

The manifold roles of microbial ribosomal peptide-based natural products in physiology and ecology

The ribosomally synthesized and posttranslationally modified peptides (RiPPs), also called ribosomal peptide natural products (RPNPs), form a growing superfamily of natural products that are produced by many different organisms and particularly by bacteria. They are derived from precursor polypeptides whose modification by various dedicated enzymes helps to establish a vast array of chemical motifs. RiPPs have attracted much interest as a source of potential therapeutic agents, and in particular as alternatives to conventional antibiotics to address the bacterial resistance crisis. However, their ecological roles in nature are poorly understood and explored. The present review describes major RiPP actors in competition within microbial communities, the main ecological and physiological functions currently evidenced for RiPPs, and the microbial ecosystems that are the sites for these functions. We envision that the study of RiPPs may lead to discoveries of new biological functions and highlight that a better knowledge of how bacterial RiPPs mediate inter-/intraspecies and interkingdom interactions will hold promise for devising alternative strategies in antibiotic development.

Gut microbiota: a promising target against cardiometabolic diseases

Introduction: Cardiometabolic diseases (CMD) are a group of interrelated disorders such as metabolic syndrome, type 2 diabetes mellitus and cardiovascular diseases (CVD). As the prevalence of these diseases increases globally, efficient new strategies are necessary to target CMD and modifiable risk factors. In the past decade, evidence has accumulated regarding the influence of gut microbiota (GM) on CMD, providing new targets for therapeutic interventions.Areas covered: This narrative review discusses the pathophysiologic link between CMD, GM, and potential microbiota-based targets against atherosclerosis and modifiable risk factors for atherosclerosis. Low-grade inflammation can be induced through GM and its derived metabolites. CMD are influenced by GM and microbiota-derived metabolites such as short-chain fatty acids (SCFA), secondary bile acids, trimethylamine N-oxide (TMAO), and the composition of GM can modulate host metabolism. All of the above can lead to promising therapeutic targets.Expert opinion: Most data are derived from animal models or human association studies; therefore, more translational and interventional research in humans is necessary to validate these promising findings. Reproduced findings such as aberrant microbiota patterns or circulating biomarkers could be targeted depending on individual metabolic profiles, moving toward personalized medicine in CMD.

Microbiome as an Immunological Modifier

Humans are living ecosystems composed of human cells and microbes. The microbiome is the collection of microbes (microbiota) and their genes. Recent breakthroughs in the high-throughput sequencing technologies have made it possible for us to understand the composition of the human microbiome. Launched by the National Institutes of Health in USA, the human microbiome project indicated that our bodies harbor a wide array of microbes, specific to each body site with interpersonal and intrapersonal variabilities. Numerous studies have indicated that several factors influence the development of the microbiome including genetics, diet, use of antibiotics, and lifestyle, among others. The microbiome and its mediators are in a continuous cross talk with the host immune system; hence, any imbalance on one side is reflected on the other. Dysbiosis (microbiota imbalance) was shown in many diseases and pathological conditions such as inflammatory bowel disease, celiac disease, multiple sclerosis, rheumatoid arthritis, asthma, diabetes, and cancer. The microbial composition mirrors inflammation variations in certain disease conditions, within various stages of the same disease; hence, it has the potential to be used as a biomarker.

The Environmental Exposures and Inner- and Intercity Traffic Flows of the Metro System May Contribute to the Skin Microbiome and Resistome

The skin functions as the primary interface between the human body and the external environment. To understand how the microbiome varies within urban mass transit and influences the skin microbiota, we profiled the human palm microbiome after contact with handrails within the Hong Kong Mass Transit Railway (MTR) system. Intraday sampling time was identified as the primary determinant of the variation and recurrence of the community composition, whereas human-associated species and clinically important antibiotic resistance genes (ARGs) were captured as p.m. signatures. Line-specific signatures were notably correlated with line-specific environmental exposures and city characteristics. The sole cross-border line appeared as an outlier in most analyses and showed high relative abundance and a significant intraday increment of clinically important ARGs (24.1%), suggesting potential cross-border ARG transmission, especially for tetracycline and vancomycin resistance. Our study provides an important reference for future public health strategies to mitigate intracity and cross-border pathogen and ARG transmission.

Natural products discovery and potential for new antibiotics

Microbial natural products have been one of the most important sources for the discovery of potential new antibiotics. However, the decline in the number of new chemical scaffolds discovered and the rediscovery problem of old known molecules has become a limitation for discovery programs developed by an industry confronted by a lack of incentives and a broken economic model. In contrast, the emergence of multidrug resistance in key pathogens has continued to progress and this issue is compounded by a lack of new antibiotics in development to address most of the difficult to treat infections. Advances in genome mining have confirmed the richness of biosynthetic gene clusters (BGCs) in the majority of microbial sources, and this suggests that an untapped chemical diversity is waiting to be discovered. The development of new genome engineering and synthetic biology tools, and the implementation of comparative omic approaches is fostering the development of new integrated culture-based strategies and genomic-driven approaches aimed at delivering new chemical classes of antibiotics.

Antibiotics: past, present and future

The first antibiotic, salvarsan, was deployed in 1910. In just over 100 years antibiotics have drastically changed modern medicine and extended the average human lifespan by 23 years. The discovery of penicillin in 1928 started the golden age of natural product antibiotic discovery that peaked in the mid-1950s. Since then, a gradual decline in antibiotic discovery and development and the evolution of drug resistance in many human pathogens has led to the current antimicrobial resistance crisis. Here we give an overview of the history of antibiotic discovery, the major classes of antibiotics and where they come from. We argue that the future of antibiotic discovery looks bright as new technologies such as genome mining and editing are deployed to discover new natural products with diverse bioactivities. We also report on the current state of antibiotic development, with 45 drugs currently going through the clinical trials pipeline, including several new classes with novel modes of action that are in phase 3 clinical trials. Overall, there are promising signs for antibiotic discovery, but changes in financial models are required to translate scientific advances into clinically approved antibiotics.

Engineering bacteria for cancer therapy

The engineering of living cells and microbes is ushering in a new era of cancer therapy. Due to recent microbiome studies indicating the prevalence of bacteria within the human body and specifically in tumor tissue, bacteria have generated significant interest as potential targets for cancer therapy. Notably, a multitude of empirical studies over the past decades have demonstrated that administered bacteria home and grow in tumors due to reduced immune surveillance of tumor necrotic cores. Given their specificity for tumors, bacteria present a unique opportunity to be engineered as intelligent delivery vehicles for cancer therapy with synthetic biology techniques. In this review, we discuss the history, current state, and future challenges associated with using bacteria as a cancer therapy.

WMGHMDA: a novel weighted meta-graph-based model for predicting human microbe-disease association on heterogeneous information network

BACKGROUND

An increasing number of biological and clinical evidences have indicated that the microorganisms significantly get involved in the pathological mechanism of extensive varieties of complex human diseases. Inferring potential related microbes for diseases can not only promote disease prevention, diagnosis and treatment, but also provide valuable information for drug development. Considering that experimental methods are expensive and time-consuming, developing computational methods is an alternative choice. However, most of existing methods are biased towards well-characterized diseases and microbes. Furthermore, existing computational methods are limited in predicting potential microbes for new diseases.

RESULTS

Here, we developed a novel computational model to predict potential human microbe-disease associations (MDAs) based on Weighted Meta-Graph (WMGHMDA). We first constructed a heterogeneous information network (HIN) by combining the integrated microbe similarity network, the integrated disease similarity network and the known microbe-disease bipartite network. And then, we implemented iteratively pre-designed Weighted Meta-Graph search algorithm on the HIN to uncover possible microbe-disease pairs by cumulating the contribution values of weighted meta-graphs to the pairs as their probability scores. Depending on contribution potential, we described the contribution degree of different types of meta-graphs to a microbe-disease pair with bias rating. Meta-graph with higher bias rating will be assigned greater weight value when calculating probability scores.

CONCLUSIONS

The experimental results showed that WMGHMDA outperformed some state-of-the-art methods with average AUCs of 0.9288, 0.9068 ±0.0031 in global leave-one-out cross validation (LOOCV) and 5-fold cross validation (5-fold CV), respectively. In the case studies, 9, 19, 37 and 10, 20, 45 out of top-10, 20, 50 candidate microbes were manually verified by previous reports for asthma and inflammatory bowel disease (IBD), respectively. Furthermore, three common human diseases (Crohn's disease, Liver cirrhosis, Type 1 diabetes) were adopted to demonstrate that WMGHMDA could be efficiently applied to make predictions for new diseases. In summary, WMGHMDA has a high potential in predicting microbe-disease associations.

Yersiniabactin-Producing Adherent/Invasive Escherichia coli Promotes Inflammation-Associated Fibrosis in Gnotobiotic Il10-/- Mice

Fibrosis is a significant complication of intestinal disorders associated with microbial dysbiosis and pathobiont expansion, notably Crohn’s disease (CD). Mechanisms that favor fibrosis are not well understood, and therapeutic strategies are limited. Here we demonstrate that colitis-susceptible Il10-deficient mice develop inflammation-associated fibrosis when monoassociated with adherent/invasive Escherichia coli (AIEC) that harbors the yersiniabactin (Ybt) pathogenicity island.

Fibrosis is a significant complication of intestinal disorders associated with microbial dysbiosis and pathobiont expansion, notably Crohn’s disease (CD). Mechanisms that favor fibrosis are not well understood, and therapeutic strategies are limited. Here we demonstrate that colitis-susceptible Il10-deficient mice develop inflammation-associated fibrosis when monoassociated with adherent/invasive Escherichia coli (AIEC) that harbors the yersiniabactin (Ybt) pathogenicity island. Inactivation of Ybt siderophore production in AIEC nearly abrogated fibrosis development in inflamed mice. In contrast, inactivation of Ybt import through its cognate receptor FyuA enhanced fibrosis severity. This corresponded with increased colonic expression of profibrogenic genes prior to the development of histological disease, therefore suggesting causality. fyuA-deficient AIEC also exhibited greater localization within subepithelial tissues and fibrotic lesions that was dependent on Ybt biosynthesis and corresponded with increased fibroblast activation in vitro. Together, these findings suggest that Ybt establishes a profibrotic environment in the host in the absence of binding to its cognate receptor and indicate a direct link between intestinal AIEC and the induction of inflammation-associated fibrosis.

Metagenome Driven Discovery of Nonribosomal Peptides

Declining rates of novel natural product discovery and exponential rates of rediscovery heralded the end of the 1940s to 1960s "golden era" of antibiotic discovery. Fifty years later, the implementation of molecular screening methodologies revealed that standard culture-based screening approaches had failed to capture the vast majority of environmental bacteria and that even for the cultivable isolates only a small fraction of the biosynthetic potential had been tapped. A diversity of metagenomic screening and synthetic biology approaches have been developed to address these issues. The nonribosomal peptides have received particular focus, owing to their high levels of bioactivity and the predictability of the biosynthetic logic of the genetically encoded assembly lines that produce them. By uniting advances in next-generation sequencing and bioinformatic analysis with a diversity of traditional disciplines, several pioneering teams have proven that this previously inaccessible resource is no longer out of reach.

MetaMiner: A Scalable Peptidogenomics Approach for Discovery of Ribosomal Peptide Natural Products with Blind Modifications from Microbial Communities

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are an important class of natural products that contain antibiotics and a variety of other bioactive compounds. The existing methods for discovery of RiPPs by combining genome mining and computational mass spectrometry are limited to discovering specific classes of RiPPs from small datasets, and these methods fail to handle unknown post-translational modifications. Here, we present MetaMiner, a software tool for addressing these challenges that is compatible with large-scale screening platforms for natural product discovery. After searching millions of spectra in the Global Natural Products Social (GNPS) molecular networking infrastructure against just eight genomic and metagenomic datasets, MetaMiner discovered 31 known and seven unknown RiPPs from diverse microbial communities, including human microbiome and lichen microbiome, and microorganisms isolated from the International Space Station.

Microcins in Enterobacteriaceae: Peptide Antimicrobials in the Eco-Active Intestinal Chemosphere

Microcins are low-molecular-weight, ribosomally produced, highly stable, bacterial-inhibitory molecules involved in competitive, and amensalistic interactions between Enterobacteriaceae in the intestine. These interactions take place in a highly complex chemical landscape, the intestinal eco-active chemosphere, composed of chemical substances that positively or negatively influence bacterial growth, including those originated from nutrient uptake, and those produced by the action of the human or animal host and the intestinal microbiome. The contribution of bacteria results from their effect on the host generated molecules, on food and digested food, and organic substances from microbial origin, including from bacterial degradation. Here, we comprehensively review the main chemical substances present in the human intestinal chemosphere, particularly of those having inhibitory effects on microorganisms. With this background, and focusing on Enterobacteriaceae, the most relevant human pathogens from the intestinal microbiota, the microcin’s history and classification, mechanisms of action, and mechanisms involved in microcin’s immunity (in microcin producers) and resistance (non-producers) are reviewed. Products from the chemosphere likely modulate the ecological effects of microcin activity. Several cross-resistance mechanisms are shared by microcins, colicins, bacteriophages, and some conventional antibiotics, which are expected to produce cross-effects. Double-microcin-producing strains (such as microcins MccM and MccH47) have been successfully used for decades in the control of pathogenic gut organisms. Microcins are associated with successful gut colonization, facilitating translocation and invasion, leading to bacteremia, and urinary tract infections. In fact, Escherichia coli strains from the more invasive phylogroups (e.g., B2) are frequently microcinogenic. A publicly accessible APD3 database http://aps.unmc.edu/AP/ shows particular genes encoding microcins in 34.1% of E. coli strains (mostly MccV, MccM, MccH47, and MccI47), and much less in Shigella and Salmonella (<2%). Some 4.65% of Klebsiella pneumoniae are microcinogenic (mostly with MccE492), and even less in Enterobacter or Citrobacter (mostly MccS). The high frequency and variety of microcins in some Enterobacteriaceae indicate key ecological functions, a notion supported by their dominance in the intestinal microbiota of biosynthetic gene clusters involved in the synthesis of post-translationally modified peptide microcins.

A metagenomic strategy for harnessing the chemical repertoire of the human microbiome

Extensive progress has been made in determining the effects of the microbiome on human physiology and disease, but the underlying molecules and mechanisms governing these effects remain largely unexplored. Here, we combine a new computational algorithm with synthetic biology to access biologically active small molecules encoded directly in human microbiome–derived metagenomic sequencing data. We discover that members of a clinically used class of molecules are widely encoded in the human microbiome and that they exert potent antibacterial activities against neighboring microbes, implying a possible role in niche competition and host defense. Our approach paves the way toward a systematic unveiling of the chemical repertoire encoded by the human microbiome and provides a generalizable platform for discovering molecular mediators of microbiome-host and microbiome-microbiome interactions.

The Microbiota-Gut-Brain Axis

The importance of the gut-brain axis in maintaining homeostasis has long been appreciated. However, the past 15 yr have seen the emergence of the microbiota (the trillions of microorganisms within and on our bodies) as one of the key regulators of gut-brain function and has led to the appreciation of the importance of a distinct microbiota-gut-brain axis. This axis is gaining ever more traction in fields investigating the biological and physiological basis of psychiatric, neurodevelopmental, age-related, and neurodegenerative disorders. The microbiota and the brain communicate with each other via various routes including the immune system, tryptophan metabolism, the vagus nerve and the enteric nervous system, involving microbial metabolites such as short-chain fatty acids, branched chain amino acids, and peptidoglycans. Many factors can influence microbiota composition in early life, including infection, mode of birth delivery, use of antibiotic medications, the nature of nutritional provision, environmental stressors, and host genetics. At the other extreme of life, microbial diversity diminishes with aging. Stress, in particular, can significantly impact the microbiota-gut-brain axis at all stages of life. Much recent work has implicated the gut microbiota in many conditions including autism, anxiety, obesity, schizophrenia, Parkinson’s disease, and Alzheimer’s disease. Animal models have been paramount in linking the regulation of fundamental neural processes, such as neurogenesis and myelination, to microbiome activation of microglia. Moreover, translational human studies are ongoing and will greatly enhance the field. Future studies will focus on understanding the mechanisms underlying the microbiota-gut-brain axis and attempt to elucidate microbial-based intervention and therapeutic strategies for neuropsychiatric disorders.

Bioactive Synthetic-Bioinformatic Natural Product Cyclic Peptides Inspired by Nonribosomal Peptide Synthetase Gene Clusters from the Human Microbiome

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.

Host transcriptome and microbiome interaction modulates physiology of full-sibs broilers with divergent feed conversion ratio

Efficient livestock production relies on effective conversion of feed into body weight gain (BWG). High levels of feed conversion are especially important in production of broiler chickens, birds reared for meat, where economic margins are tight. Traits associated with improved broiler growth and feed efficiency have been subjected to intense genetic selection, but measures such as feed conversion ratio (FCR) remain variable, even between full siblings (sibs). Non-genetic factors such as the composition and function of microbial populations within different enteric compartments have been recognized to influence FCR, although the extent of interplay between hosts and their microbiomes is unclear. To examine host–microbiome interactions we investigated variation in the composition and functions of host intestinal-hepatic transcriptomes and the intestinal microbiota of full-sib broilers with divergent FCR. Progeny from 300 broiler families were assessed for divergent FCR set against shared genetic backgrounds and exposure to the same environmental factors. The seven most divergent full-sib pairs were chosen for analysis, exhibiting marked variation in transcription of genes as well as gut microbial diversity. Examination of enteric microbiota in low FCR sibs revealed variation in microbial community structure and function with no difference in feed intake compared to high FCR sibs. Gene transcription in low and high FCR sibs was significantly associated with the abundance of specific microbial taxa. Highly intertwined interactions between host transcriptomes and enteric microbiota are likely to modulate complex traits like FCR and may be amenable to selective modification with relevance to improving intestinal homeostasis and health.

Macrocyclic colibactin induces DNA double-strand breaks via copper-mediated oxidative cleavage

Colibactin is an assumed human gut bacterial genotoxin, whose biosynthesis is linked to clb genomic island that distributes widespread in pathogenic and commensal human enterobacteria. Colibactin-producing gut microbes promote colon tumor formation and enhance progression of colorectal cancer via DNA double-strand breaks-induced cellular senescence and death; however, the chemical basis contributing to the pathogenesis at the molecular level has not been fully characterized. Here we report the discovery of colibactin-645 a macrocyclic colibactin metabolite that recapitulates the previously assumed genotoxicity and cytotoxicity. Colibactin-645 shows strong DNA DSBs activity in vitro and in human cell cultures via a unique copper-mediated oxidative mechanism. We also delineate a complete biosynthetic model for colibactin-645, highlighting a unique fate of the aminomalonate building monomer in forming the C-terminal 5-hydroxy 4-oxazolecarboxylic acid moiety through the activities of both the polyketide synthase ClbO and the amidase ClbL. This work thus provides a molecular basis for colibactin’s DNA DSBs activity and facilitates further mechanistic study of colibactin-related CRC incidence and prevention.

Baseline human gut microbiota profile in healthy people and standard reporting template

A comprehensive knowledge of the types and ratios of microbes that inhabit the healthy human gut is necessary before any kind of pre-clinical or clinical study can be performed that attempts to alter the microbiome to treat a condition or improve therapy outcome. To address this need we present an innovative scalable comprehensive analysis workflow, a healthy human reference microbiome list and abundance profile (GutFeelingKB), and a novel Fecal Biome Population Report (FecalBiome) with clinical applicability. GutFeelingKB provides a list of 157 organisms (8 phyla, 18 classes, 23 orders, 38 families, 59 genera and 109 species) that forms the baseline biome and therefore can be used as healthy controls for studies related to dysbiosis. This list can be expanded to 863 organisms if closely related proteomes are considered. The incorporation of microbiome science into routine clinical practice necessitates a standard report for comparison of an individual’s microbiome to the growing knowledgebase of “normal” microbiome data. The FecalBiome and the underlying technology of GutFeelingKB address this need. The knowledgebase can be useful to regulatory agencies for the assessment of fecal transplant and other microbiome products, as it contains a list of organisms from healthy individuals. In addition to the list of organisms and their abundances, this study also generated a collection of assembled contiguous sequences (contigs) of metagenomics dark matter. In this study, metagenomic dark matter represents sequences that cannot be mapped to any known sequence but can be assembled into contigs of 10,000 nucleotides or higher. These sequences can be used to create primers to study potential novel organisms. All data is freely available from https://hive.biochemistry.gwu.edu/gfkb and NCBI’s Short Read Archive.

Novel antimicrobial peptide discovery using machine learning and biophysical selection of minimal bacteriocin domains

Bacteriocins, the ribosomally produced antimicrobial peptides of bacteria, represent an untapped source of promising antibiotic alternatives. However, bacteriocins display diverse mechanisms of action, a narrow spectrum of activity, and inherent challenges in natural product isolation making in vitro verification of putative bacteriocins difficult. A subset of bacteriocins exert their antimicrobial effects through favorable biophysical interactions with the bacterial membrane mediated by the charge, hydrophobicity, and conformation of the peptide. We have developed a pipeline for bacteriocin-derived compound design and testing that combines sequence-free prediction of bacteriocins using machine learning and a simple biophysical trait filter to generate 20 amino acid peptides that can be synthesized and evaluated for activity. We generated 28,895 total 20-mer candidate peptides and scored them for charge, α-helicity, and hydrophobic moment. Of those, we selected 16 sequences for synthesis and evaluated their antimicrobial, cytotoxicity, and hemolytic activities. Peptides with the overall highest scores for our biophysical parameters exhibited significant antimicrobial activity against Escherichia coli and Pseudomonas aeruginosa. Our combined method incorporates machine learning and biophysical-based minimal region determination to create an original approach to swiftly discover bacteriocin candidates amenable to rapid synthesis and evaluation for therapeutic use.

Genomic and Metagenomic Approaches for Predictive Surveillance of Emerging Pathogens and Antibiotic Resistance

Antibiotic-resistant organisms (AROs) are a major concern to public health worldwide. While antibiotics have been naturally produced by environmental bacteria for millions of years, modern widespread use of antibiotics has enriched resistance mechanisms in human-impacted bacterial environments. Antibiotic resistance genes (ARGs) continue to emerge and spread rapidly. To combat the global threat of antibiotic resistance, researchers must develop methods to rapidly characterize AROs and ARGs, monitor their spread across space and time, and identify novel ARGs and resistance pathways. We review how high-throughput sequencing-based methods can be combined with classic culture-based assays to characterize, monitor, and track AROs and ARGs. Then, we evaluate genomic and metagenomic methods for identifying ARGs and biosynthetic pathways for novel antibiotics from genomic data sets. Together, these genomic analyses can improve surveillance and prediction of emerging resistance threats and accelerate the development of new antibiotic therapies to combat resistance.

Novel bioactive natural products from bacteria via bioprospecting, genome mining and metabolic engineering

For over seven decades, bacteria served as a valuable source of bioactive natural products some of which were eventually developed into drugs to treat infections, cancer and immune system-related diseases. Traditionally, novel compounds produced by bacteria were discovered via conventional bioprospecting based on isolation of potential producers and screening their extracts in a variety of bioassays. Over time, most of the natural products identifiable by this approach were discovered, and the pipeline for new drugs based on bacterially produced metabolites started to run dry. This mini-review highlights recent developments in bacterial bioprospecting for novel compounds that are based on several out-of-the-box approaches, including the following: (i) targeting bacterial species previously unknown to produce any bioactive natural products, (ii) exploring non-traditional environmental niches and methods for isolation of bacteria and (iii) various types of 'genome mining' aimed at unravelling genetic potential of bacteria to produce secondary metabolites. All these approaches have already yielded a number of novel bioactive compounds and, if used wisely, will soon revitalize drug discovery pipeline based on bacterial natural products.

An anaerobic bacterium host system for heterologous expression of natural product biosynthetic gene clusters

Anaerobic bacteria represent an overlooked rich source of biological and chemical diversity. Due to the challenge of cultivation and genetic intractability, assessing the capability of their biosynthetic gene clusters (BGCs) for secondary metabolite production requires an efficient heterologous expression system. However, this kind of host system is still unavailable. Here, we use the facultative anaerobe Streptococcus mutans UA159 as a heterologous host for the expression of BGCs from anaerobic bacteria. A natural competence based large DNA fragment cloning (NabLC) technique was developed, which can move DNA fragments up to 40-kb directly and integrate a 73.7-kb BGC to the genome of S. mutans UA159 via three rounds of NabLC cloning. Using this system, we identify an anti-infiltration compound, mutanocyclin, from undefined BGCs from human oral bacteria. We anticipate this host system will be useful for heterologous expression of BGCs from anaerobic bacteria.

Anaerobic bacteria represent a rich source of biological and chemical diversity but are difficult to cultivate and there is a lack of heterologous expression systems. Here the authors develop an expression system based on S. mutans UA159 for biosynthetic gene clusters from anaerobic bacteria.

Large-Scale Analyses of Human Microbiomes Reveal Thousands of Small, Novel Genes

Small proteins are traditionally overlooked due to computational and experimental difficulties in detecting them. To systematically identify small proteins, we carried out a comparative genomics study on 1,773 human-associated metagenomes from four different body sites. We describe >4,000 conserved protein families, the majority of which are novel; ∼30% of these protein families are predicted to be secreted or transmembrane. Over 90% of the small protein families have no known domain and almost half are not represented in reference genomes. We identify putative housekeeping, mammalian-specific, defense-related, and protein families that are likely to be horizontally transferred. We provide evidence of transcription and translation for a subset of these families. Our study suggests that small proteins are highly abundant and those of the human microbiome, in particular, may perform diverse functions that have not been previously reported.

Automated structure prediction of trans-acyltransferase polyketide synthase products

Bacterial trans-acyltransferase polyketide synthases (trans-AT PKSs) are among the most complex known enzymes from secondary metabolism and are responsible for the biosynthesis of highly diverse bioactive polyketides. However, most of these metabolites remain uncharacterized, since trans-AT PKSs frequently occur in poorly studied microbes and feature a remarkable array of non-canonical biosynthetic components with poorly understood functions. As a consequence, genome-guided natural product identification has been challenging. To enable de novo structural predictions for trans-AT PKS-derived polyketides, we developed the trans-AT PKS polyketide predictor (TransATor). TransATor is a versatile bio- and chemoinformatics web application that suggests informative chemical structures for even highly aberrant trans-AT PKS biosynthetic gene clusters, thus permitting hypothesis-based, targeted biotechnological discovery and biosynthetic studies. We demonstrate the applicative scope in several examples, including the characterization of new variants of bioactive natural products as well as structurally new polyketides from unusual bacterial sources.

Role of antimicrobial peptides in controlling symbiotic bacterial populations

Covering: up to 2018 Antimicrobial peptides (AMPs) have been known for well over three decades as crucial mediators of the innate immune response in animals and plants, where they are involved in the killing of infecting microbes. However, AMPs have now also been found to be produced by eukaryotic hosts during symbiotic interactions with bacteria. These symbiotic AMPs target the symbionts and therefore have a more subtle biological role: not eliminating the microbial symbiont population but rather keeping it in check. The arsenal of AMPs and the symbionts' adaptations to resist them are in a careful balance, which contributes to the establishment of the host-microbe homeostasis. Although in many cases the biological roles of symbiotic AMPs remain elusive, for a number of symbiotic interactions, precise functions have been assigned or proposed to the AMPs, which are discussed here. The microbiota living on epithelia in animals, from the most primitive ones to the mammals, are challenged by a cocktail of AMPs that determine the specific composition of the bacterial community as well as its spatial organization. In the symbiosis of legume plants with nitrogen-fixing rhizobium bacteria, the host deploys an extremely large panel of AMPs - called nodule-specific cysteine-rich (NCR) peptides - that drive the bacteria into a terminally differentiated state and manipulate the symbiont physiology to maximize the benefit for the host. The NCR peptides are used as tools to enslave the bacterial symbionts, limiting their reproduction but keeping them metabolically active for nitrogen fixation. In the nutritional symbiotic interactions of insects and protists that have vertically transmitted bacterial symbionts with reduced genomes, symbiotic AMPs could facilitate the integration of the endosymbiont and host metabolism by favouring the flow of metabolites across the symbiont membrane through membrane permeabilization.

The human gut microbiome - a new and exciting avenue in cardiovascular drug discovery

Introduction: Over the past decade, numerous research efforts have identified the gut microbiota as a novel regulator of human metabolic syndrome and cardiovascular disease (CVD). With the elucidation of underlying molecular mechanisms of the gut microbiota and its metabolites, the drug-discovery process of CVD therapeutics might be expedited. Areas covered: The authors describe the evidence concerning the impact of gut microbiota on metabolic disorders and CVD and summarize the current knowledge of the gut microbial mechanisms that underlie CVD with a focus on microbial metabolites. In addition, they discuss the potential impact of the gut microbiota on the drug efficacy of available cardiometabolic therapeutic agents. Most importantly, the authors review the role of the gut microbiome as a promising source of potential drug targets and novel therapeutics for the development of new treatment modalities for CVD. This review also presents the various effective strategies to investigate the gut microbiome for CVD drug-discovery approaches. Expert opinion: With the elucidation of its causative role in cardiometabolic disease and atherosclerosis, the human gut microbiome holds promises as a reservoir of novel potential therapeutic targets as well as novel therapeutic agents, paving a new and exciting avenue in cardiovascular drug discovery.

RWHMDA: Random Walk on Hypergraph for Microbe-Disease Association Prediction

Based on advancements in deep sequencing technology and microbiology, increasing evidence indicates that microbes inhabiting humans modulate various host physiological phenomena, thus participating in various disease pathogeneses. Owing to increasing availability of biological data, further studies on the establishment of efficient computational models for predicting potential associations are required. In particular, computational approaches can also reduce the discovery cycle of novel microbe-disease associations and further facilitate disease treatment, drug design, and other scientific activities. This study aimed to develop a model based on the random walk on hypergraph for microbe-disease association prediction (RWHMDA). As a class of higher-order data representation, hypergraph could effectively recover information loss occurring in the normal graph methodology, thus exclusively illustrating multiple pair-wise associations. Integrating known microbe-disease associations in the Human Microbe-Disease Association Database (HMDAD) and the Gaussian interaction profile kernel similarity for microbes, random walk was then implemented for the constructed hypergraph. Consequently, RWHMDA performed optimally in predicting the underlying disease-associated microbes. More specifically, our model displayed AUC values of 0.8898 and 0.8524 in global and local leave-one-out cross-validation (LOOCV), respectively. Furthermore, three human diseases (asthma, Crohn's disease, and type 2 diabetes) were studied to further illustrate prediction performance. Moreover, 8, 10, and 8 of the 10 highest ranked microbes were confirmed through recent experimental or clinical studies. In conclusion, RWHMDA is expected to display promising potential to predict disease-microbe associations for follow-up experimental studies and facilitate the prevention, diagnosis, treatment, and prognosis of complex human diseases.

mSphere of Influence: Systematically Decoding Microbial Chemical Communication

Laura A. Mike works in the field of bacterial pathogenesis. In this mSphere of Influence article, she reflects on how “Insights into Secondary Metabolism from a Global Analysis of Prokaryotic Biosynthetic Gene Clusters” by P. Cimermancic et al. (Cell 158:412–421, 2014, https://doi.org/10.1016/j.cell.2014.06.034) and “A Systematic Analysis of Biosynthetic Gene Clusters in the Human Microbiome Reveals a Common Family of Antibiotics” by M. S. Donia et al. (Cell 158:1402–1414, 2014, https://doi.org/10.1016/j.cell.2014.08.032) made an impact on her by systematically identifying microbiome-associated biosynthetic gene clusters predicted to synthesize secondary metabolites, which may facilitate interspecies interactions.

Laura A. Mike works in the field of bacterial pathogenesis. In this mSphere of Influence article, she reflects on how “Insights into Secondary Metabolism from a Global Analysis of Prokaryotic Biosynthetic Gene Clusters” by P. Cimermancic et al. (Cell 158:412–421, 2014, https://doi.org/10.1016/j.cell.2014.06.034) and “A Systematic Analysis of Biosynthetic Gene Clusters in the Human Microbiome Reveals a Common Family of Antibiotics” by M. S. Donia et al. (Cell 158:1402–1414, 2014, https://doi.org/10.1016/j.cell.2014.08.032) made an impact on her by systematically identifying microbiome-associated biosynthetic gene clusters predicted to synthesize secondary metabolites, which may facilitate interspecies interactions.