BiG-MAP: an Automated Pipeline To Profile Metabolic Gene Cluster Abundance and Expression in Microbiomes

Decoding the diagnostic and therapeutic potential of microbiota using pan-body pan-disease microbiomics

The human microbiome emerges as a promising reservoir for diagnostic markers and therapeutics. Since host-associated microbiomes at various body sites differ and diseases do not occur in isolation, a comprehensive analysis strategy highlighting the full potential of microbiomes should include diverse specimen types and various diseases. To ensure robust data quality and comparability across specimen types and diseases, we employ standardized protocols to generate sequencing data from 1931 prospectively collected specimens, including from saliva, plaque, skin, throat, eye, and stool, with an average sequencing depth of 5.3 gigabases. Collected from 515 patients, these samples yield an average of 3.7 metagenomes per patient. Our results suggest significant microbial variations across diseases and specimen types, including unexpected anatomical sites. We identify 583 unexplored species-level genome bins (SGBs) of which 189 are significantly disease-associated. Of note, the existence of microbial resistance genes in one specimen was indicative of the same resistance genes in other specimens of the same patient. Annotated and previously undescribed SGBs collectively harbor 28,315 potential biosynthetic gene clusters (BGCs), with 1050 significant correlations to diseases. Our combinatorial approach identifies distinct SGBs and BGCs, emphasizing the value of pan-body pan-disease microbiomics as a source for diagnostic and therapeutic strategies.

Unlocking the biosynthetic potential and taxonomy of the Antarctic microbiome along temporal and spatial gradients

Extreme environments, such as Antarctica, select microbial communities that display a range of evolutionary strategies to survive and thrive under harsh environmental conditions. These include a diversity of specialized metabolites, which have the potential to be a source for new natural product discovery. Efforts using (meta)genome mining approaches to identify and understand biosynthetic gene clusters in Antarctica are still scarce, and the extent of their diversity and distribution patterns in the environment have yet to be discovered. Herein, we investigated the biosynthetic gene diversity of the biofilm microbial community of Whalers Bay, Deception Island, in the Antarctic Peninsula and revealed its distribution patterns along spatial and temporal gradients by applying metagenome mining approaches and multivariable analysis. The results showed that the Whalers Bay microbial community harbors a great diversity of biosynthetic gene clusters distributed into seven classes, with terpene being the most abundant. The phyla Proteobacteria and Bacteroidota were the most abundant in the microbial community and contributed significantly to the biosynthetic gene abundances in Whalers Bay. Furthermore, the results highlighted a significant correlation between the distribution of biosynthetic genes and taxonomic diversity, emphasizing the intricate interplay between microbial taxonomy and their potential for specialized metabolite production.IMPORTANCEThis research on antarctic microbial biosynthetic diversity in Whalers Bay, Deception Island, unveils the hidden potential of extreme environments for natural product discovery. By employing metagenomic techniques, the research highlights the extensive diversity of biosynthetic gene clusters and identifies key microbial phyla, Proteobacteria and Bacteroidota, as significant contributors. The correlation between taxonomic diversity and biosynthetic gene distribution underscores the intricate interplay governing specialized metabolite production. These findings are crucial for understanding microbial adaptation in extreme environments and hold significant implications for bioprospecting initiatives. The study opens avenues for discovering novel bioactive compounds with potential applications in medicine and industry, emphasizing the importance of preserving and exploring these polyextreme ecosystems to advance biotechnological and pharmaceutical research.

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.

Identification of peptides from honeybee gut symbionts as potential antimicrobial agents against Melissococcus plutonius

Eusocial pollinators are crucial elements in global agriculture. The honeybees and bumblebees are associated with a simple yet host-restricted gut community, which protect the hosts against pathogen infections. Recent genome mining has led to the discovery of biosynthesis pathways of bioactive natural products mediating microbe-microbe interactions from the gut microbiota. Here, we investigate the diversity of biosynthetic gene clusters in the bee gut microbiota by analyzing 477 genomes from cultivated bacteria and metagenome-assembled genomes. We identify 744 biosynthetic gene clusters (BGCs) covering multiple chemical classes. While gene clusters for the post-translationally modified peptides are widely distributed in the bee guts, the distribution of the BGC classes varies significantly in different bee species among geographic locations, which is attributed to the strain-level variation of bee gut members in the chemical repertoire. Interestingly, we find that Gilliamella strains possessing a thiopeptide-like BGC show potent activity against the pathogenic Melissococcus plutonius. The spectrometry-guided genome mining reveals a RiPP-encoding BGC from Gilliamella with a 10 amino acid-long core peptide exhibiting antibacterial potentials. This study illustrates the widespread small-molecule-encoding BGCs in the bee gut symbionts and provides insights into the bacteria-derived natural products as potential antimicrobial agents against pathogenic infections.

gutSMASH predicts specialized primary metabolic pathways from the human gut microbiota

The gut microbiota produce hundreds of small molecules, many of which modulate host physiology. Although efforts have been made to identify biosynthetic genes for secondary metabolites, the chemical output of the gut microbiome consists predominantly of primary metabolites. Here we introduce the gutSMASH algorithm for identification of primary metabolic gene clusters, and we used it to systematically profile gut microbiome metabolism, identifying 19,890 gene clusters in 4,240 high-quality microbial genomes. We found marked differences in pathway distribution among phyla, reflecting distinct strategies for energy capture. These data explain taxonomic differences in short-chain fatty acid production and suggest a characteristic metabolic niche for each taxon. Analysis of 1,135 individuals from a Dutch population-based cohort shows that the level of microbiome-derived metabolites in plasma and feces is almost completely uncorrelated with the metagenomic abundance of corresponding metabolic genes, indicating a crucial role for pathway-specific gene regulation and metabolite flux. This work is a starting point for understanding differences in how bacterial taxa contribute to the chemistry of the microbiome.

A widely distributed gene cluster compensates for uricase loss in hominids

Approximately 15% of US adults have circulating levels of uric acid above its solubility limit, which is causally linked to the disease gout. In most mammals, uric acid elimination is facilitated by the enzyme uricase. However, human uricase is a pseudogene, having been inactivated early in hominid evolution. Though it has long been known that uric acid is eliminated in the gut, the role of the gut microbiota in hyperuricemia has not been studied. Here, we identify a widely distributed bacterial gene cluster that encodes a pathway for uric acid degradation. Stable isotope tracing demonstrates that gut bacteria metabolize uric acid to xanthine or short chain fatty acids. Ablation of the microbiota in uricase-deficient mice causes severe hyperuricemia, and anaerobe-targeted antibiotics increase the risk of gout in humans. These data reveal a role for the gut microbiota in uric acid excretion and highlight the potential for microbiome-targeted therapeutics in hyperuricemia.

Metabolome-guided genome mining of RiPP natural products

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a chemically diverse class of metabolites. Many RiPPs show potent biological activities that make them attractive starting points for drug development. A promising approach for the discovery of new classes of RiPPs is genome mining. However, the accuracy of genome mining is hampered by the lack of signature genes shared across different RiPP classes. One way to reduce false-positive predictions is by complementing genomic information with metabolomics data. In recent years, several new approaches addressing such integrative genomics and metabolomics analyses have been developed. In this review, we provide a detailed discussion of RiPP-compatible software tools that integrate paired genomics and metabolomics data. We highlight current challenges in data integration and identify opportunities for further developments targeting new classes of bioactive RiPPs.

Bioinformatic mining for RiPP biosynthetic gene clusters in Bacteroidales reveals possible new subfamily architectures and novel natural products

The Bacteroidales order, widely distributed among diverse human populations, constitutes a key component of the human microbiota. Members of this Gram-negative order have been shown to modulate the host immune system, play a fundamental role in the gut's microbial food webs, or be involved in pathogenesis. Bacteria inhabiting such a complex environment as the human microbiome are expected to display social behaviors and, hence, possess factors that mediate cooperative and competitive interactions. Different types of molecules can mediate interference competition, including non-ribosomal peptides (NRPs), polyketides, and bacteriocins. The present study investigates the potential of Bacteroidales bacteria to biosynthesize class I bacteriocins, which are ribosomally synthesized and post-translationally modified peptides (RiPPs). For this purpose, 1,136 genome-sequenced strains from this order were mined using BAGEL4. A total of 1,340 areas of interest (AOIs) were detected. The most commonly identified enzymes involved in RiPP biosynthesis were radical S-adenosylmethionine (rSAM), either alone or in combination with other biosynthetic enzymes such as YcaO. A more comprehensive analysis of a subset of 9 biosynthetic gene clusters (BGCs) revealed a consistent association in Bacteroidales BGCs between peptidase-containing ATP-binding transporters (PCATs) and precursor peptides with GG-motifs. This finding suggests a possibly shared mechanism for leader peptide cleavage and transport of mature products. Notably, human metagenomic studies showed a high prevalence and abundance of the RiPP BGCs from Phocaeicola vulgatus and Porphyromonas gulae. The mature product of P. gulae BGC is hypothesized to display γ-thioether linkages and a C-terminal backbone amidine, a potential new combination of post-translational modifications (PTM). All these findings highlight the RiPP biosynthetic potential of Bacteroidales bacteria, as a rich source of novel peptide structures of possible relevance in the human microbiome context.

[Latest Findings on Polyketides/Non-ribosomal Peptides That Are Secondary Metabolites of Streptococcus mutans]

Dental caries is a chronic infectious disease that occurs in the hard tissue of teeth under the influence of multiple factors, among which bacteria being a key factor. Streptococcus mutans ( S. mutans) is considered a major pathogen that causes caries. Secondary metabolites, including bacteriocins and polyketides/non-ribosomal peptides, are a class of small-molecule compounds synthesized by S. mutans. To date, polyketides/non-ribosomal peptides identified in S. mutans include mutanobactin, mutanocyclin, and mutanofactin, which are synthesized by the mub, muc, and muf biosynthetic gene clusters, respectively. These polyketides/non-ribosomal peptides play important roles in bacterial inter-species competition, oxidative stress, and biofilm formation. In this review, we provided an overview of the synthesis, function and regulation of three polyketides/non-ribosomal peptides of S. mutans, including mutanobactin, mutanocyclin, and mutanofactin, aiming to provide new insights into the cariogenic mechanism of S. mutans and to promote the better management of dental caries.

A systematically biosynthetic investigation of lactic acid bacteria reveals diverse antagonistic bacteriocins that potentially shape the human microbiome

BACKGROUND

Lactic acid bacteria (LAB) produce various bioactive secondary metabolites (SMs), which endow LAB with a protective role for the host. However, the biosynthetic potentials of LAB-derived SMs remain elusive, particularly in their diversity, abundance, and distribution in the human microbiome. Thus, it is still unknown to what extent LAB-derived SMs are involved in microbiome homeostasis.

RESULTS

Here, we systematically investigate the biosynthetic potential of LAB from 31,977 LAB genomes, identifying 130,051 secondary metabolite biosynthetic gene clusters (BGCs) of 2,849 gene cluster families (GCFs). Most of these GCFs are species-specific or even strain-specific and uncharacterized yet. Analyzing 748 human-associated metagenomes, we gain an insight into the profile of LAB BGCs, which are highly diverse and niche-specific in the human microbiome. We discover that most LAB BGCs may encode bacteriocins with pervasive antagonistic activities predicted by machine learning models, potentially playing protective roles in the human microbiome. Class II bacteriocins, one of the most abundant and diverse LAB SMs, are particularly enriched and predominant in the vaginal microbiome. We utilized metagenomic and metatranscriptomic analyses to guide our discovery of functional class II bacteriocins. Our findings suggest that these antibacterial bacteriocins have the potential to regulate microbial communities in the vagina, thereby contributing to the maintenance of microbiome homeostasis.

CONCLUSIONS

Our study systematically investigates LAB biosynthetic potential and their profiles in the human microbiome, linking them to the antagonistic contributions to microbiome homeostasis via omics analysis. These discoveries of the diverse and prevalent antagonistic SMs are expected to stimulate the mechanism study of LAB's protective roles for the microbiome and host, highlighting the potential of LAB and their bacteriocins as therapeutic alternatives. Video Abstract.

Soil conditions and the plant microbiome boost the accumulation of monoterpenes in the fruit of Citrus reticulata 'Chachi'

BACKGROUND

The medicinal material quality of Citrus reticulata 'Chachi' differs depending on the bioactive components influenced by the planting area. Environmental factors, such as soil nutrients, the plant-associated microbiome and climatic conditions, play important roles in the accumulation of bioactive components in citrus. However, how these environmental factors mediate the production of bioactive components of medicinal plants remains understudied.

RESULTS

Here, a multi-omics approach was used to clarify the role of environmental factors such as soil nutrients and the root-associated microbiome on the accumulation of monoterpenes in the peel of C. reticulata 'Chachi' procured from core (geo-authentic product region) and non-core (non-geo-authentic product region) geographical regions. The soil environment (high salinity, Mg, Mn and K) enhanced the monoterpene content by promoting the expression of salt stress-responsive genes and terpene backbone synthase in the host plants from the core region. The microbial effects on the monoterpene accumulation of citrus from the core region were further verified by synthetic community (SynCom) experiments. Rhizosphere microorganisms activated terpene synthesis and promoted monoterpene accumulation through interactions with the host immune system. Endophyte microorganisms derived from soil with the potential for terpene synthesis might enhance monoterpene accumulation in citrus by providing precursors of monoterpenes.

CONCLUSIONS

Overall, this study demonstrated that both soil properties and the soil microbiome impacted monoterpene production in citrus peel, thus providing an essential basis for increasing fruit quality via reasonable fertilization and precision microbiota management. Video Abstract.

Advances in mining and expressing microbial biosynthetic gene clusters

Natural products (NPs) especially the secondary metabolites originated from microbes exhibit great importance in biomedical, industrial and agricultural applications. However, mining biosynthetic gene clusters (BGCs) to produce novel NPs has been hindered owing that a large population of environmental microbes are unculturable. In the past decade, strategies to explore BGCs directly from (meta)genomes have been established along with the fast development of high-throughput sequencing technologies and the powerful bioinformatics data-processing tools, which greatly expedited the exploitations of novel BGCs from unculturable microbes including the extremophilic microbes. In this review, we firstly summarized the popular bioinformatics tools and databases available to mine novel BGCs from (meta)genomes based on either pure cultures or pristine environmental samples. Noticeably, approaches rooted from machine learning and deep learning with focuses on the prediction of ribosomally synthesized and post-translationally modified peptides (RiPPs) were dramatically increased in recent years. Moreover, synthetic biology techniques to express the novel BGCs in culturable native microbes or heterologous hosts were introduced. This working pipeline including the discovery and biosynthesis of novel NPs will greatly advance the exploitations of the abundant but unexplored microbial BGCs.

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.

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.