Large-Scale Metagenome Assembly Reveals Novel Animal-Associated Microbial Genomes, Biosynthetic Gene Clusters, and Other Genetic Diversity

Gut microbiome diversity within Clostridia is negatively associated with human obesity

Clostridia are abundant in the human gut and comprise families associated with host health such as Oscillospiraceae, which has been correlated with leanness. However, culturing bacteria within this family is challenging, leading to their detection primarily through 16S rRNA amplicon sequencing, which has a limited ability to unravel diversity at low taxonomic levels, or by shotgun metagenomics, which is hindered by its high costs and complexity. In this cross-sectional study involving 114 Colombian adults, we used an amplicon-based sequencing strategy with alternative markers-gyrase subunit B (gyrB) and DNA K chaperone heat protein 70 (dnaK)-that evolve faster than the 16S rRNA gene. Comparing the diversity and abundance observed with the three markers in our cohort, we found a reduction in the diversity of Clostridia, particularly within Lachnospiraceae and Oscillospiraceae among obese individuals [as measured by the body mass index (BMI)]. Within Lachnospiraceae, the diversity of Ruminococcus_A negatively correlated with BMI. Within Oscillospiraceae, the genera CAG-170 and Vescimonas also exhibited this negative correlation. In addition, the abundance of Vescimonas was negatively correlated with BMI. Leveraging shotgun metagenomic data, we conducted a phylogenetic and genomic characterization of 120 metagenome-assembled genomes from Vescimonas obtained from a larger sample of the same cohort. We identified 17 of the 72 reported species. The functional annotation of these genomes showed the presence of multiple carbohydrate-active enzymes, particularly glycosyl transferases and glycoside hydrolases, suggesting potential beneficial roles in fiber degradation, carbohydrate metabolism, and butyrate production.

IMPORTANCE

The gut microbiota is diverse across various taxonomic levels. At the intra-species level, it comprises multiple strains, some of which may be host-specific. However, our understanding of fine-grained diversity has been hindered by the use of the conserved 16S rRNA gene. While shotgun metagenomics offers higher resolution, it remains costly, may fail to identify specific microbes in complex samples, and requires extensive computational resources and expertise. To address this, we employed a simple and cost-effective analysis of alternative genetic markers to explore diversity within Clostridia, a crucial group within the human gut microbiota whose diversity may be underestimated. We found high intra-species diversity for certain groups and associations with obesity. Notably, we identified Vescimonas, an understudied group. Making use of metagenomic data, we inferred functionality, uncovering potential beneficial roles in dietary fiber and carbohydrate degradation, as well as in short-chain fatty acid production.

Sequencing-based analysis of microbiomes

Microbiomes occupy a range of niches and, in addition to having diverse compositions, they have varied functional roles that have an impact on agriculture, environmental sciences, and human health and disease. The study of microbiomes has been facilitated by recent technological and analytical advances, such as cheaper and higher-throughput DNA and RNA sequencing, improved long-read sequencing and innovative computational analysis methods. These advances are providing a deeper understanding of microbiomes at the genomic, transcriptional and translational level, generating insights into their function and composition at resolutions beyond the species level.

Strain tracking in complex microbiomes using synteny analysis reveals per-species modes of evolution

Microbial species diversify into strains through single-nucleotide mutations and structural changes, such as recombination, insertions and deletions. Most strain-comparison methods quantify differences in single-nucleotide polymorphisms (SNPs) and are insensitive to structural changes. However, recombination is an important driver of phenotypic diversification in many species, including human pathogens. We introduce SynTracker, a tool that compares microbial strains using genome synteny-the order of sequence blocks in homologous genomic regions-in pairs of metagenomic assemblies or genomes. Genome synteny is a rich source of genomic information untapped by current strain-comparison tools. SynTracker has low sensitivity to SNPs, has no database requirement and is robust to sequencing errors. It outperforms existing tools when tracking strains in metagenomic data and is particularly suited for phages, plasmids and other low-data contexts. Applied to single-species datasets and human gut metagenomes, SynTracker, combined with an SNP-based tool, detects strains enriched in either point mutations or structural changes, providing insights into microbial evolution in situ.

Challenges in computational discovery of bioactive peptides in 'omics data

Peptides have a plethora of activities in biological systems that can potentially be exploited biotechnologically. Several peptides are used clinically, as well as in industry and agriculture. The increase in available 'omics data has recently provided a large opportunity for mining novel enzymes, biosynthetic gene clusters, and molecules. While these data primarily consist of DNA sequences, other types of data provide important complementary information. Due to their size, the approaches proven successful at discovering novel proteins of canonical size cannot be naïvely applied to the discovery of peptides. Peptides can be encoded directly in the genome as short open reading frames (smORFs), or they can be derived from larger proteins by proteolysis. Both of these peptide classes pose challenges as simple methods for their prediction result in large numbers of false positives. Similarly, functional annotation of larger proteins, traditionally based on sequence similarity to infer orthology and then transferring functions between characterized proteins and uncharacterized ones, cannot be applied for short sequences. The use of these techniques is much more limited and alternative approaches based on machine learning are used instead. Here, we review the limitations of traditional methods as well as the alternative methods that have recently been developed for discovering novel bioactive peptides with a focus on prokaryotic genomes and metagenomes.

Bridge RNAs direct programmable recombination of target and donor DNA

Genomic rearrangements, encompassing mutational changes in the genome such as insertions, deletions or inversions, are essential for genetic diversity. These rearrangements are typically orchestrated by enzymes that are involved in fundamental DNA repair processes, such as homologous recombination, or in the transposition of foreign genetic material by viruses and mobile genetic elements1,2. Here we report that IS110 insertion sequences, a family of minimal and autonomous mobile genetic elements, express a structured non-coding RNA that binds specifically to their encoded recombinase. This bridge RNA contains two internal loops encoding nucleotide stretches that base-pair with the target DNA and the donor DNA, which is the IS110 element itself. We demonstrate that the target-binding and donor-binding loops can be independently reprogrammed to direct sequence-specific recombination between two DNA molecules. This modularity enables the insertion of DNA into genomic target sites, as well as programmable DNA excision and inversion. The IS110 bridge recombination system expands the diversity of nucleic-acid-guided systems beyond CRISPR and RNA interference, offering a unified mechanism for the three fundamental DNA rearrangements-insertion, excision and inversion-that are required for genome design.

Interpretable metric learning in comparative metagenomics: The adaptive Haar-like distance

Random forests have emerged as a promising tool in comparative metagenomics because they can predict environmental characteristics based on microbial composition in datasets where β-diversity metrics fall short of revealing meaningful relationships between samples. Nevertheless, despite this efficacy, they lack biological insight in tandem with their predictions, potentially hindering scientific advancement. To overcome this limitation, we leverage a geometric characterization of random forests to introduce a data-driven phylogenetic β-diversity metric, the adaptive Haar-like distance. This new metric assigns a weight to each internal node (i.e., split or bifurcation) of a reference phylogeny, indicating the relative importance of that node in discerning environmental samples based on their microbial composition. Alongside this, a weighted nearest-neighbors classifier, constructed using the adaptive metric, can be used as a proxy for the random forest while maintaining accuracy on par with that of the original forest and another state-of-the-art classifier, CoDaCoRe. As shown in datasets from diverse microbial environments, however, the new metric and classifier significantly enhance the biological interpretability and visualization of high-dimensional metagenomic samples.

Isolation of potentially novel species expands the genomic and functional diversity of Lachnospiraceae

The Lachnospiraceae family holds promise as a source of next-generation probiotics, yet a comprehensive delineation of its diversity is lacking, hampering the identification of suitable strains for future applications. To address this knowledge gap, we conducted an in-depth genomic and functional analysis of 1868 high-quality genomes, combining data from public databases with our new isolates. This data set represented 387 colonization-selective species-level clusters, of which eight genera represented multilineage clusters. Pan-genome analysis, single-nucleotide polymorphism (SNP) identification, and probiotic functional predictions revealed that species taxonomy, habitats, and geography together shape the functional diversity of Lachnospiraceae. Moreover, analyses of associations with atherosclerotic cardiovascular disease (ACVD) and inflammatory bowel disease (IBD) indicated that several strains of potentially novel Lachnospiraceae species possess the capacity to reduce the abundance of opportunistic pathogens, thereby imparting potential health benefits. Our findings shed light on the untapped potential of novel species enabling knowledge-based selection of strains for the development of next-generation probiotics holding promise for improving human health and disease management.

Sequence-structure-function characterization of the emerging tetracycline destructase family of antibiotic resistance enzymes

Tetracycline destructases (TDases) are flavin monooxygenases which can confer resistance to all generations of tetracycline antibiotics. The recent increase in the number and diversity of reported TDase sequences enables a deep investigation of the TDase sequence-structure-function landscape. Here, we evaluate the sequence determinants of TDase function through two complementary approaches: (1) constructing profile hidden Markov models to predict new TDases, and (2) using multiple sequence alignments to identify conserved positions important to protein function. Using the HMM-based approach we screened 50 high-scoring candidate sequences in Escherichia coli, leading to the discovery of 13 new TDases. The X-ray crystal structures of two new enzymes from Legionella species were determined, and the ability of anhydrotetracycline to inhibit their tetracycline-inactivating activity was confirmed. Using the MSA-based approach we identified 31 amino acid positions 100% conserved across all known TDase sequences. The roles of these positions were analyzed by alanine-scanning mutagenesis in two TDases, to study the impact on cell and in vitro activity, structure, and stability. These results expand the diversity of TDase sequences and provide valuable insights into the roles of important residues in TDases, and flavin monooxygenases more broadly.

Unbiased organism-agnostic and highly sensitive signal peptide predictor with deep protein language model

Signal peptides (SPs) are essential to target and transfer transmembrane and secreted proteins to the correct positions. Many existing computational tools for predicting SPs disregard the extreme data imbalance problem and rely on additional group information of proteins. Here we introduce Unbiased Organism-agnostic Signal Peptide Network (USPNet), an SP classification and cleavage-site prediction deep learning method. Extensive experimental results show that USPNet substantially outperforms previous methods on classification performance by 10%. An SP-discovering pipeline with USPNet is designed to explore unprecedented SPs from metagenomic data. It reveals 347 SP candidates, with the lowest sequence identity between our candidates and the closest SP in the training dataset at only 13%. In addition, the template modeling scores between candidates and SPs in the training set are mostly above 0.8. The results showcase that USPNet has learnt the SP structure with raw amino acid sequences and the large protein language model, thereby enabling the discovery of unknown SPs.

Deep learning and CRISPR-Cas13d ortholog discovery for optimized RNA targeting

Effective and precise mammalian transcriptome engineering technologies are needed to accelerate biological discovery and RNA therapeutics. Despite the promise of programmable CRISPR-Cas13 ribonucleases, their utility has been hampered by an incomplete understanding of guide RNA design rules and cellular toxicity resulting from off-target or collateral RNA cleavage. Here, we quantified the performance of over 127,000 RfxCas13d (CasRx) guide RNAs and systematically evaluated seven machine learning models to build a guide efficiency prediction algorithm orthogonally validated across multiple human cell types. Deep learning model interpretation revealed preferred sequence motifs and secondary features for highly efficient guides. We next identified and screened 46 novel Cas13d orthologs, finding that DjCas13d achieves low cellular toxicity and high specificity-even when targeting abundant transcripts in sensitive cell types, including stem cells and neurons. Our Cas13d guide efficiency model was successfully generalized to DjCas13d, illustrating the power of combining machine learning with ortholog discovery to advance RNA targeting in human cells.

Evolving understanding of rumen methanogen ecophysiology

Production of methane by methanogenic archaea, or methanogens, in the rumen of ruminants is a thermodynamic necessity for microbial conversion of feed to volatile fatty acids, which are essential nutrients for the animals. On the other hand, methane is a greenhouse gas and its production causes energy loss for the animal. Accordingly, there are ongoing efforts toward developing effective strategies for mitigating methane emissions from ruminant livestock that require a detailed understanding of the diversity and ecophysiology of rumen methanogens. Rumen methanogens evolved from free-living autotrophic ancestors through genome streamlining involving gene loss and acquisition. The process yielded an oligotrophic lifestyle, and metabolically efficient and ecologically adapted descendants. This specialization poses serious challenges to the efforts of obtaining axenic cultures of rumen methanogens, and consequently, the information on their physiological properties remains in most part inferred from those of their non-rumen representatives. This review presents the current knowledge of rumen methanogens and their metabolic contributions to enteric methane production. It also identifies the respective critical gaps that need to be filled for aiding the efforts to mitigate methane emission from livestock operations and at the same time increasing the productivity in this critical agriculture sector.

APOLLO: A genome-scale metabolic reconstruction resource of 247,092 diverse human microbes spanning multiple continents, age groups, and body sites

Computational modelling of microbiome metabolism has proved instrumental to catalyse our understanding of diet-host-microbiome-disease interactions through the interrogation of mechanistic, strain- and molecule-resolved metabolic models. We present APOLLO, a resource of 247,092 human microbial genome-scale metabolic reconstructions spanning 19 phyla and accounting for microbial genomes from 34 countries, all age groups, and five body sites. We explored the metabolic potential of the reconstructed strains and developed a machine learning classifier able to predict with high accuracy the taxonomic strain assignments. We also built 14,451 sample-specific microbial community models, which could be stratified by body site, age, and disease states. Finally, we predicted faecal metabolites enriched or depleted in gut microbiomes of people with Crohn's disease, Parkinson disease, and undernourished children. APOLLO is compatible with the human whole-body models, and thus, provide unprecedented opportunities for systems-level modelling of personalised host-microbiome co-metabolism. APOLLO will be freely available under https://www.vmh.life/.

Insights into early evolutionary adaptations of the Akkermansia genus to the vertebrate gut

Akkermansia, a relevant mucin degrader from the vertebrate gut microbiota, is a member of the deeply branched Verrucomicrobiota, as well as the only known member of this phylum to be described as inhabitants of the gut. Only a few Akkermansia species have been officially described so far, although there is genomic evidence addressing the existence of more species-level variants for this genus. This niche specialization makes Akkermansia an interesting model for studying the evolution of microorganisms to their adaptation to the gastrointestinal tract environment, including which kind of functions were gained when the Akkermansia genus originated or how the evolutionary pressure functions over those genes. In order to gain more insight into Akkermansia adaptations to the gastrointestinal tract niche, we performed a phylogenomic analysis of 367 high-quality Akkermansia isolates and metagenome-assembled genomes, in addition to other members of Verrucomicrobiota. This work was focused on three aspects: the definition of Akkermansia genomic species clusters and the calculation and functional characterization of the pangenome for the most represented species; the evolutionary relationship between Akkermansia and their closest relatives from Verrucomicrobiota, defining the gene families which were gained or lost during the emergence of the last Akkermansia common ancestor (LAkkCA) and; the evaluation of the evolutionary pressure metrics for each relevant gene family of main Akkermansia species. This analysis found 25 Akkermansia genomic species clusters distributed in two main clades, divergent from their non-Akkermansia relatives. Pangenome analyses suggest that Akkermansia species have open pangenomes, and the gene gain/loss model indicates that genes associated with mucin degradation (both glycoside hydrolases and peptidases), (micro)aerobic metabolism, surface interaction, and adhesion were part of LAkkCA. Specifically, mucin degradation is a very ancestral innovation involved in the origin of Akkermansia. Horizontal gene transfer detection suggests that Akkermansia could receive genes mostly from unknown sources or from other Gram-negative gut bacteria. Evolutionary metrics suggest that Akkemansia species evolved differently, and even some conserved genes suffered different evolutionary pressures among clades. These results suggest a complex evolutionary landscape of the genus and indicate that mucin degradation could be an essential feature in Akkermansia evolution as a symbiotic species.

ResMiCo: Increasing the quality of metagenome-assembled genomes with deep learning

The number of published metagenome assemblies is rapidly growing due to advances in sequencing technologies. However, sequencing errors, variable coverage, repetitive genomic regions, and other factors can produce misassemblies, which are challenging to detect for taxonomically novel genomic data. Assembly errors can affect all downstream analyses of the assemblies. Accuracy for the state of the art in reference-free misassembly prediction does not exceed an AUPRC of 0.57, and it is not clear how well these models generalize to real-world data. Here, we present the Residual neural network for Misassembled Contig identification (ResMiCo), a deep learning approach for reference-free identification of misassembled contigs. To develop ResMiCo, we first generated a training dataset of unprecedented size and complexity that can be used for further benchmarking and developments in the field. Through rigorous validation, we show that ResMiCo is substantially more accurate than the state of the art, and the model is robust to novel taxonomic diversity and varying assembly methods. ResMiCo estimated 7% misassembled contigs per metagenome across multiple real-world datasets. We demonstrate how ResMiCo can be used to optimize metagenome assembly hyperparameters to improve accuracy, instead of optimizing solely for contiguity. The accuracy, robustness, and ease-of-use of ResMiCo make the tool suitable for general quality control of metagenome assemblies and assembly methodology optimization.

Taxonomic, Genomic, and Functional Variation in the Gut Microbiomes of Wild Spotted Hyenas Across 2 Decades of Study

The gut microbiome provides vital functions for mammalian hosts, yet research on its variability and function across adult life spans and multiple generations is limited in large mammalian carnivores. Here, we used 16S rRNA gene and metagenomic high-throughput sequencing to profile the bacterial taxonomic composition, genomic diversity, and metabolic function of fecal samples collected from 12 wild spotted hyenas (Crocuta crocuta) residing in the Masai Mara National Reserve, Kenya, over a 23-year period spanning three generations. The metagenomic data came from four of these hyenas and spanned two 2-year periods. With these data, we determined the extent to which host factors predicted variation in the gut microbiome and identified the core microbes present in the guts of hyenas. We also investigated novel genomic diversity in the mammalian gut by reporting the first metagenome-assembled genomes (MAGs) for hyenas. We found that gut microbiome taxonomic composition varied temporally, but despite this, a core set of 14 bacterial genera were identified. The strongest predictors of the microbiome were host identity and age, suggesting that hyenas possess individualized microbiomes and that these may change with age during adulthood. The gut microbiome functional profiles of the four adult hyenas were also individual specific and were associated with prey abundance, indicating that the functions of the gut microbiome vary with host diet. We recovered 149 high-quality MAGs from the hyenas' guts; some MAGs were classified as taxa previously reported for other carnivores, but many were novel and lacked species-level matches to genomes in existing reference databases. IMPORTANCE There is a gap in knowledge regarding the genomic diversity and variation of the gut microbiome across a host's life span and across multiple generations of hosts in wild mammals. Using two types of sequencing approaches, we found that although gut microbiomes were individualized and temporally variable among hyenas, they correlated similarly to large-scale changes in the ecological conditions experienced by their hosts. We also recovered 149 high-quality MAGs from the hyena gut, greatly expanding the microbial genome repertoire known for hyenas, carnivores, and wild mammals in general. Some MAGs came from genera abundant in the gastrointestinal tracts of canid species and other carnivores, but over 80% of MAGs were novel and from species not previously represented in genome databases. Collectively, our novel body of work illustrates the importance of surveying the gut microbiome of nonmodel wild hosts, using multiple sequencing methods and computational approaches and at distinct scales of analysis.

Carbon fixation pathways across the bacterial and archaeal tree of life

Carbon fixation is a critical process for our planet; however, its distribution across the bacterial and archaeal domains of life has not been comprehensively studied. Here, we performed an analysis of 52,515 metagenome-assembled genomes and discover carbon fixation pathways in 1,007 bacteria and archaea. We reveal the genomic potential for carbon fixation through the reverse tricarboxylic acid cycle in previously unrecognized archaeal and bacterial phyla (i.e. Thermoplasmatota and Elusimicrobiota) and show that the 3-hydroxypropionate bi-cycle is not, as previously thought, restricted to the phylum Chloroflexota. The data also substantially expand the phylogenetic breadth for autotrophy through the dicarboxylate/4-hydroxybutyrate cycle and the Calvin-Benson-Bassham cycle. Finally, the genomic potential for carbon fixation through the 3-hydroxypropionate/4-hydroxybutyrate cycle, previously exclusively found in Archaea, was also detected in the Bacteria. Carbon fixation thus appears to be much more widespread than previously known, and this study lays the foundation to better understand the role of archaea and bacteria in global primary production and how they contribute to microbial carbon sinks.

Mining the equine gut metagenome: poorly-characterized taxa associated with cardiovascular fitness in endurance athletes

Emerging evidence indicates that the gut microbiome contributes to endurance exercise performance. Still, the extent of its functional and metabolic potential remains unknown. Using elite endurance horses as a model system for exercise responsiveness, we built an integrated horse gut gene catalog comprising ~25 million unique genes and 372 metagenome-assembled genomes. This catalog represents 4179 genera spanning 95 phyla and functional capacities primed to exploit energy from dietary, microbial, and host resources. The holo-omics approach shows that gut microbiomes enriched in Lachnospiraceae taxa are negatively associated with cardiovascular capacity. Conversely, more complex and functionally diverse microbiomes are associated with higher glucose concentrations and reduced accumulation of long-chain acylcarnitines and non-esterified fatty acids in plasma, suggesting increased ß-oxidation capacity in the mitochondria. In line with this hypothesis, more fit athletes show upregulation of mitochondrial-related genes involved in energy metabolism, biogenesis, and Ca²⁺ cytosolic transport, all of which are necessary to improve aerobic work power, spare glycogen usage, and enhance cardiovascular capacity. The results identify an associative link between endurance performance and gut microbiome composition and gene function, laying the basis for nutritional interventions that could benefit horse athletes.

An integrated gene catalog of the gut microbiome in elite endurance horses is build. The holo-omics analyses identify an associative link between endurance performance and gut microbiome composition and gene function.

Codiversification of gut microbiota with humans

The gut microbiomes of human populations worldwide have many core microbial species in common. However, within a species, some strains can show remarkable population specificity. The question is whether such specificity arises from a shared evolutionary history (codiversification) between humans and their microbes. To test for codiversification of host and microbiota, we analyzed paired gut metagenomes and human genomes for 1225 individuals in Europe, Asia, and Africa, including mothers and their children. Between and within countries, a parallel evolutionary history was evident for humans and their gut microbes. Moreover, species displaying the strongest codiversification independently evolved traits characteristic of host dependency, including reduced genomes and oxygen and temperature sensitivity. These findings all point to the importance of understanding the potential role of population-specific microbial strains in microbiome-mediated disease phenotypes.

Functional characterization of prokaryotic dark matter: the road so far and what lies ahead

Eight-hundred thousand to one trillion prokaryotic species may inhabit our planet. Yet, fewer than two-hundred thousand prokaryotic species have been described. This uncharted fraction of microbial diversity, and its undisclosed coding potential, is known as the "microbial dark matter" (MDM). Next-generation sequencing has allowed to collect a massive amount of genome sequence data, leading to unprecedented advances in the field of genomics. Still, harnessing new functional information from the genomes of uncultured prokaryotes is often limited by standard classification methods. These methods often rely on sequence similarity searches against reference genomes from cultured species. This hinders the discovery of unique genetic elements that are missing from the cultivated realm. It also contributes to the accumulation of prokaryotic gene products of unknown function among public sequence data repositories, highlighting the need for new approaches for sequencing data analysis and classification. Increasing evidence indicates that these proteins of unknown function might be a treasure trove of biotechnological potential. Here, we outline the challenges, opportunities, and the potential hidden within the functional dark matter (FDM) of prokaryotes. We also discuss the pitfalls surrounding molecular and computational approaches currently used to probe these uncharted waters, and discuss future opportunities for research and applications.

Substrate degradation pathways, conserved functions and community composition of the hindgut microbiota in the herbivorous marine fish Kyphosus sydneyanus

Symbiotic gut microbiota in the herbivorous marine fish Kyphosus sydneyanus play an important role in digestion by converting refractory algal carbohydrate into short-chain fatty acids. Here we characterised community composition using both 16S rRNA gene amplicon sequencing and shotgun-metagenome sequencing. Sequencing was carried out on lumen and mucosa samples (radial sections) from three axial sections taken from the hindgut of wild-caught fish. Both lumen and mucosa communities displayed distinct distributions along the hindgut, likely an effect of the differing selection pressures within these hindgut locations, as well as considerable variation among individual fish. In contrast, metagenomic sequences displayed a high level of functional similarity between individual fish and gut sections in the relative abundance of genes (based on sequencing depth) that encoded enzymes involved in algal-derived substrate degradation. These results suggest that the host gut environment selects for functional capacity in symbionts rather than taxonomic identity. Functional annotation of the enzymes encoded by the gut microbiota was carried out to infer the metabolic pathways used by the gut microbiota for the degradation of important dietary substrates: mannitol, alginate, laminarin, fucoidan and galactan (e.g. agar and carrageenan). This work provides the first evidence of the genomic potential of K. sydneyanus hindgut microbiota to convert highly refractory algal carbohydrates into metabolically useful short-chain fatty acids.

A secondary metabolite drives intraspecies antagonism in a gut symbiont that is inhibited by cell-wall acetylation

The mammalian microbiome encodes numerous secondary metabolite biosynthetic gene clusters; yet, their role in microbe-microbe interactions is unclear. Here, we characterized two polyketide synthase gene clusters (fun and pks) in the gut symbiont Limosilactobacillus reuteri. The pks, but not the fun, cluster encodes antimicrobial activity. Forty-one of 51 L. reuteri strains tested are sensitive to Pks products; this finding was independent of strains' host origin. Sensitivity to Pks was also established in intraspecies competition experiments in gnotobiotic mice. Comparative genome analyses between Pks-resistant and -sensitive strains identified an acyltransferase gene (act) unique to Pks-resistant strains. Subsequent cell-wall analysis of wild-type and act mutant strains showed that Act acetylates cell-wall components, providing resistance to Pks-mediated killing. Additionally, pks mutants lost their competitive advantage, while act mutants lost their Pks resistance in in vivo competition assays. These findings provide insight into how closely related gut symbionts can compete and co-exist in the gastrointestinal tract.

Generation and application of pseudo-long reads for metagenome assembly

BACKGROUND

Metagenomic assembly using high-throughput sequencing data is a powerful method to construct microbial genomes in environmental samples without cultivation. However, metagenomic assembly, especially when only short reads are available, is a complex and challenging task because mixed genomes of multiple microorganisms constitute the metagenome. Although long read sequencing technologies have been developed and have begun to be used for metagenomic assembly, many metagenomic studies have been performed based on short reads because the generation of long reads requires higher sequencing cost than short reads.

RESULTS

In this study, we present a new method called PLR-GEN. It creates pseudo-long reads from metagenomic short reads based on given reference genome sequences by considering small sequence variations existing in individual genomes of the same or different species. When applied to a mock community data set in the Human Microbiome Project, PLR-GEN dramatically extended short reads in length of 101 bp to pseudo-long reads with N50 of 33 Kbp and 0.4% error rate. The use of these pseudo-long reads generated by PLR-GEN resulted in an obvious improvement of metagenomic assembly in terms of the number of sequences, assembly contiguity, and prediction of species and genes.

CONCLUSIONS

PLR-GEN can be used to generate artificial long read sequences without spending extra sequencing cost, thus aiding various studies using metagenomes.

MIntO: A Modular and Scalable Pipeline For Microbiome Metagenomic and Metatranscriptomic Data Integration

Omics technologies have revolutionized microbiome research allowing the characterization of complex microbial communities in different biomes without requiring their cultivation. As a consequence, there has been a great increase in the generation of omics data from metagenomes and metatranscriptomes. However, pre-processing and analysis of these data have been limited by the availability of computational resources, bioinformatics expertise and standardized computational workflows to obtain consistent results that are comparable across different studies. Here, we introduce MIntO (Microbiome Integrated meta-Omics), a highly versatile pipeline that integrates metagenomic and metatranscriptomic data in a scalable way. The distinctive feature of this pipeline is the computation of gene expression profile through integrating metagenomic and metatranscriptomic data taking into account the community turnover and gene expression variations to disentangle the mechanisms that shape the metatranscriptome across time and between conditions. The modular design of MIntO enables users to run the pipeline using three available modes based on the input data and the experimental design, including de novo assembly leading to metagenome-assembled genomes. The integrated pipeline will be relevant to provide unique biochemical insights into microbial ecology by linking functions to retrieved genomes and to examine gene expression variation. Functional characterization of community members will be crucial to increase our knowledge of the microbiome’s contribution to human health and environment. MIntO v1.0.1 is available at https://github.com/arumugamlab/MIntO.

Comparative Metagenomic Study of Rhizospheric and Bulk Mercury-Contaminated Soils in the Mining District of Almadén

Soil contamination by heavy metals, particularly mercury (Hg), is a problem that can seriously affect the environment, animals, and human health. Hg has the capacity to biomagnify in the food chain. That fact can lead to pathologies, of those which affect the central nervous system being the most severe. It is convenient to know the biological environmental indicators that alert of the effects of Hg contamination as well as the biological mechanisms that can help in its remediation. To contribute to this knowledge, this study conducted comparative analysis by the use of Shotgun metagenomics of the microbial communities in rhizospheric soils and bulk soil of the mining region of Almadén (Ciudad Real, Spain), one of the most affected areas by Hg in the world The sequences obtained was analyzed with MetaPhlAn2 tool and SUPER-FOCUS. The most abundant taxa in the taxonomic analysis in bulk soil were those of Actinobateria and Alphaproteobacteria. On the contrary, in the rhizospheric soil microorganisms belonging to the phylum Proteobacteria were abundant, evidencing that roots have a selective effect on the rhizospheric communities. In order to analyze possible indicators of biological contamination, a functional potential analysis was performed. The results point to a co-selection of the mechanisms of resistance to Hg and the mechanisms of resistance to antibiotics or other toxic compounds in environments contaminated by Hg. Likewise, the finding of antibiotic resistance mechanisms typical of the human clinic, such as resistance to beta-lactams and glycopeptics (vancomycin), suggests that these environments can behave as reservoirs. The sequences involved in Hg resistance (operon mer and efflux pumps) have a similar abundance in both soil types. However, the response to abiotic stress (salinity, desiccation, and contaminants) is more prevalent in rhizospheric soil. Finally, sequences involved in nitrogen fixation and metabolism and plant growth promotion (PGP genes) were identified, with higher relative abundances in rhizospheric soils. These findings can be the starting point for the targeted search for microorganisms suitable for further use in bioremediation processes in Hg-contaminated environments.

Novel canine high-quality metagenome-assembled genomes, prophages and host-associated plasmids provided by long-read metagenomics together with Hi-C proximity ligation

The human gut microbiome has been extensively studied, yet the canine gut microbiome is still largely unknown. The availability of high-quality genomes is essential in the fields of veterinary medicine and nutrition to unravel the biological role of key microbial members in the canine gut environment. Our aim was to evaluate nanopore long-read metagenomics and Hi-C (high-throughput chromosome conformation capture) proximity ligation to provide high-quality metagenome-assembled genomes (HQ MAGs) of the canine gut environment. By combining nanopore long-read metagenomics and Hi-C proximity ligation, we retrieved 27 HQ MAGs and 7 medium-quality MAGs of a faecal sample of a healthy dog. Canine MAGs (CanMAGs) improved genome contiguity of representatives from the animal and human MAG catalogues – short-read MAGs from public datasets – for the species they represented: they were more contiguous with complete ribosomal operons and at least 18 canonical tRNAs. Both canine-specific bacterial species and gut generalists inhabit the dog’s gastrointestinal environment. Most of them belonged to Firmicutes, followed by Bacteroidota and Proteobacteria. We also assembled one Actinobacteriota and one Fusobacteriota MAG. CanMAGs harboured antimicrobial-resistance genes (ARGs) and prophages and were linked to plasmids. ARGs conferring resistance to tetracycline were most predominant within CanMAGs, followed by lincosamide and macrolide ones. At the functional level, carbohydrate transport and metabolism was the most variable within the CanMAGs, and mobilome function was abundant in some MAGs. Specifically, we assigned the mobilome functions and the associated mobile genetic elements to the bacterial host. The CanMAGs harboured 50 bacteriophages, providing novel bacterial-host information for eight viral clusters, and Hi-C proximity ligation data linked the six potential plasmids to their bacterial host. Long-read metagenomics and Hi-C proximity ligation are likely to become a comprehensive approach to HQ MAG discovery and assignment of extra-chromosomal elements to their bacterial host. This will provide essential information for studying the canine gut microbiome in veterinary medicine and animal nutrition.

Host Genetic Determinants of the Microbiome Across Animals: From Caenorhabditis elegans to Cattle

Animals harbor diverse communities of microbes within their gastrointestinal tracts. Phylogenetic relationship, diet, gut morphology, host physiology, and ecology all influence microbiome composition within and between animal clades. Emerging evidence points to host genetics as also playing a role in determining gut microbial composition within species. Here, we discuss recent advances in the study of microbiome heritability across a variety of animal species. Candidate gene and discovery-based studies in humans, mice, Drosophila, Caenorhabditis elegans, cattle, swine, poultry, and baboons reveal trends in the types of microbes that are heritable and the host genes and pathways involved in shaping the microbiome. Heritable gut microbes within a host species tend to be phylogenetically restricted. Host genetic variation in immune- and growth-related genes drives the abundances of these heritable bacteria within the gut. With only a small slice of the metazoan branch of the tree of life explored to date, this is an area rife with opportunities to shed light into the mechanisms governing host-microbe relationships.

A multi-omics approach unravels metagenomic and metabolic alterations of a probiotic and synbiotic additive in rainbow trout (Oncorhynchus mykiss)

BACKGROUND

Animal protein production is increasingly looking towards microbiome-associated services such as the design of new and better probiotic solutions to further improve gut health and production sustainability. Here, we investigate the functional effects of bacteria-based pro- and synbiotic feed additives on microbiome-associated functions in relation to growth performance in the commercially important rainbow trout (Oncorhynchus mykiss). We combine complementary insights from multiple omics datasets from gut content samples, including 16S bacterial profiling, whole metagenomes, and untargeted metabolomics, to investigate bacterial metagenome-assembled genomes (MAGs) and their molecular interactions with host metabolism.

RESULTS

Our findings reveal that (I) feed additives changed the microbiome and that rainbow trout reared with feed additives had a significantly reduced relative abundance of the salmonid related Candidatus Mycoplasma salmoninae in both the mid and distal gut content, (II) genome resolved metagenomics revealed that alterations of microbial arginine biosynthesis and terpenoid backbone synthesis pathways were directly associated with the presence of Candidatus Mycoplasma salmoninae, and (III) differences in the composition of intestinal microbiota among feed types were directly associated with significant changes of the metabolomic landscape, including lipids and lipid-like metabolites, amino acids, bile acids, and steroid-related metabolites.

CONCLUSION

Our results demonstrate how the use of multi-omics to investigate complex host-microbiome interactions enable us to better evaluate the functional potential of probiotics compared to studies that only measure overall growth performance or that only characterise the microbial composition in intestinal environments. Video Abstract.

Nanopore adaptive sampling: a tool for enrichment of low abundance species in metagenomic samples

Adaptive sampling is a method of software-controlled enrichment unique to nanopore sequencing platforms. To test its potential for enrichment of rarer species within metagenomic samples, we create a synthetic mock community and construct sequencing libraries with a range of mean read lengths. Enrichment is up to 13.87-fold for the least abundant species in the longest read length library; factoring in reduced yields from rejecting molecules the calculated efficiency raises this to 4.93-fold. Finally, we introduce a mathematical model of enrichment based on molecule length and relative abundance, whose predictions correlate strongly with mock and complex real-world microbial communities.

Incorporating genome-based phylogeny and functional similarity into diversity assessments helps to resolve a global collection of human gut metagenomes

Tree-based diversity measures incorporate phylogenetic or functional relatedness into comparisons of microbial communities. This can improve the identification of explanatory factors compared to tree-agnostic diversity measures. However, applying tree-based diversity measures to metagenome data is more challenging than for single-locus sequencing (e.g., 16S rRNA gene). Utilizing the Genome Taxonomy Database (GTDB) for species-level metagenome profiling allows for functional diversity measures based on genomic content or traits inferred from it. Still, it is unclear how metagenome-based assessments of microbiome diversity benefit from incorporating phylogeny or function into measures of diversity. We assessed this by measuring phylogeny-based, function-based, and tree-agnostic diversity measures from a large, global collection of human gut metagenomes composed of 30 studies and 2943 samples. We found tree-based measures to explain phenotypic variation (e.g., westernization, disease status, and gender) better or equivalent to tree-agnostic measures. Ecophylogenetic and functional diversity measures provided unique insight into how microbiome diversity was partitioned by phenotype. Tree-based measures greatly improved machine learning model performance for predicting westernization, disease status, and gender, relative to models trained solely on tree-agnostic measures. Our findings illustrate the usefulness of tree- and function-based measures for metagenomic assessments of microbial diversity, which is a fundamental component of microbiome science. This article is protected by copyright. All rights reserved.

A catalogue of 1,167 genomes from the human gut archaeome

The human gut microbiome plays an important role in health, but its archaeal diversity remains largely unexplored. In the present study, we report the analysis of 1,167 nonredundant archaeal genomes (608 high-quality genomes) recovered from human gastrointestinal tract, sampled across 24 countries and rural and urban populations. We identified previously undescribed taxa including 3 genera, 15 species and 52 strains. Based on distinct genomic features, we justify the split of the Methanobrevibacter smithii clade into two separate species, with one represented by the previously undescribed 'Candidatus Methanobrevibacter intestini'. Patterns derived from 28,581 protein clusters showed significant associations with sociodemographic characteristics such as age groups and lifestyle. We additionally show that archaea are characterized by specific genomic and functional adaptations to the host and carry a complex virome. Our work expands our current understanding of the human archaeome and provides a large genome catalogue for future analyses to decipher its impact on human physiology.

Biogeography of Bacterial Communities and Specialized Metabolism in Human Aerodigestive Tract Microbiomes

The aerodigestive tract (ADT) is the primary portal through which pathogens and other invading microbes enter the body. As the direct interface with the environment, we hypothesize that the ADT microbiota possess biosynthetic gene clusters (BGCs) for antibiotics and other specialized metabolites to compete with both endogenous and exogenous microbes. From 1,214 bacterial genomes, representing 136 genera and 387 species that colonize the ADT, we identified 3,895 BGCs. To determine the distribution of BGCs and bacteria in different ADT sites, we aligned 1,424 metagenomes, from nine different ADT sites, onto the predicted BGCs. We show that alpha diversity varies across the ADT and that each site is associated with distinct bacterial communities and BGCs. We identify specific BGC families enriched in the buccal mucosa, external naris, gingiva, and tongue dorsum despite these sites harboring closely related bacteria. We reveal BGC enrichment patterns indicative of the ecology at each site. For instance, aryl polyene and resorcinol BGCs are enriched in the gingiva and tongue, which are colonized by many anaerobes. In addition, we find that streptococci colonizing the tongue and cheek possess different ribosomally synthesized and posttranslationally modified peptide BGCs. Finally, we highlight bacterial genera with BGCs but are underexplored for specialized metabolism and demonstrate the bioactivity of Actinomyces against other bacteria, including human pathogens. Together, our results demonstrate that specialized metabolism in the ADT is extensive and that by exploring these microbiomes further, we will better understand the ecology and biogeography of this system and identify new bioactive natural products.

IMPORTANCE Bacteria produce specialized metabolites to compete with other microbes. Though the biological activities of many specialized metabolites have been determined, our understanding of their ecology is limited, particularly within the human microbiome. As the aerodigestive tract (ADT) faces the external environment, bacteria colonizing this tract must compete both among themselves and with invading microbes, including human pathogens. We analyzed the genomes of ADT bacteria to identify biosynthetic gene clusters (BGCs) for specialized metabolites. We found that the majority of ADT BGCs are uncharacterized and the metabolites they encode are unknown. We mapped the distribution of BGCs across the ADT and determined that each site is associated with its own distinct bacterial community and BGCs. By further characterizing these BGCs, we will inform our understanding of ecology and biogeography across the ADT, and we may uncover new specialized metabolites, including antibiotics.

Vertebrate host phylogeny influences gut archaeal diversity

Commonly used 16S rRNA gene primers do not detect the full range of archaeal diversity present in the vertebrate gut. As a result, several questions regarding the archaeal component of the gut microbiota remain, including which Archaea are host-associated, the specificities of such associations and the major factors influencing archaeal diversity. Using 16S rRNA gene amplicon sequencing with primers that specifically target Archaea, we obtained sufficient sequence data from 185 gastrointestinal samples collected from 110 vertebrate species that span five taxonomic classes (Mammalia, Aves, Reptilia, Amphibia and Actinopterygii), of which the majority were wild. We provide evidence for previously undescribed Archaea-host associations, including Bathyarchaeia and Methanothermobacter, the latter of which was prevalent among Aves and relatively abundant in species with higher body temperatures, although this association could not be decoupled from host phylogeny. Host phylogeny explained archaeal diversity more strongly than diet, while specific taxa were associated with both factors, and cophylogeny was significant and strongest for mammalian herbivores. Methanobacteria was the only class predicted to be present in the last common ancestors of mammals and all host species. Further analysis indicated that Archaea-Bacteria interactions have a limited effect on archaeal diversity. These findings expand our current understanding of Archaea-vertebrate associations.

Functional Diversity within Gut Microbiomes: Implications for Conserving Biodiversity

Conservation research has historically been conducted at the macro level, focusing on animals and plants and their role in the wider ecosystem. However, there is a growing appreciation of the importance of microbial communities in conservation. Most microbiome research in conservation thus far has used amplicon sequencing methods to assess the taxonomic composition of microbial communities and inferred functional capabilities from these data. However, as manipulation of the microbiome as a conservation tool becomes more and more feasible, there is a growing need to understand the direct functional consequences of shifts in microbiome composition. This review outlines the latest advances in microbiome research from a functional perspective and how these data can be used to inform conservation strategies. This review will also consider some of the challenges faced when studying the microbiomes of wild animals and how they can be overcome by careful study design and sampling methods. Environmental changes brought about by climate change or direct human actions have the potential to alter the taxonomic composition of microbiomes in wild populations. Understanding how taxonomic shifts affect the function of microbial communities is important for identifying species most threatened by potential disruption to their microbiome. Preservation or even restoration of these functions has the potential to be a powerful tool in conservation biology and a shift towards functional characterisation of gut microbiome diversity will be an important first step.

Struo2: efficient metagenome profiling database construction for ever-expanding microbial genome datasets

Mapping metagenome reads to reference databases is the standard approach for assessing microbial taxonomic and functional diversity from metagenomic data. However, public reference databases often lack recently generated genomic data such as metagenome-assembled genomes (MAGs), which can limit the sensitivity of read-mapping approaches. We previously developed the Struo pipeline in order to provide a straight-forward method for constructing custom databases; however, the pipeline does not scale well enough to cope with the ever-increasing number of publicly available microbial genomes. Moreover, the pipeline does not allow for efficient database updating as new data are generated. To address these issues, we developed Struo2, which is >3.5 fold faster than Struo at database generation and can also efficiently update existing databases. We also provide custom Kraken2, Bracken, and HUMAnN3 databases that can be easily updated with new genomes and/or individual gene sequences. Efficient database updating, coupled with our pre-generated databases, enables “assembly-enhanced” profiling, which increases database comprehensiveness via inclusion of native genomic content. Inclusion of newly generated genomic content can greatly increase database comprehensiveness, especially for understudied biomes, which will enable more accurate assessments of microbiome diversity.

Improving Fungal Cultivability for Natural Products Discovery

The pool of fungal secondary metabolites can be extended by activating silent gene clusters of cultured strains or by using sensitive biological assays that detect metabolites missed by analytical methods. Alternatively, or in parallel with the first approach, one can increase the diversity of existing culture collections to improve the access to new natural products. This review focuses on the latter approach of screening previously uncultured fungi for chemodiversity. Both strategies have been practiced since the early days of fungal biodiscovery, yet relatively little has been done to overcome the challenge of cultivability of as-yet-uncultivated fungi. Whereas earlier cultivability studies using media formulations and biological assays to scrutinize fungal growth and associated factors were actively conducted, the application of modern omics methods remains limited to test how to culture the fungal dark matter and recalcitrant groups of described fungi. This review discusses the development of techniques to increase the cultivability of filamentous fungi that include culture media formulations and the utilization of known chemical growth factors, in situ culturing and current synthetic biology approaches that build upon knowledge from sequenced genomes. We list more than 100 growth factors, i.e., molecules, biological or physical factors that have been demonstrated to induce spore germination as well as tens of inducers of mycelial growth. We review culturing conditions that can be successfully manipulated for growth of fungi and visit recent information from omics methods to discuss the metabolic basis of cultivability. Earlier work has demonstrated the power of co-culturing fungi with their host, other microorganisms or their exudates to increase their cultivability. Co-culturing of two or more organisms is also a strategy used today for increasing cultivability. However, fungi possess an increased risk for cross-contaminations between isolates in existing in situ or microfluidics culturing devices. Technological improvements for culturing fungi are discussed in the review. We emphasize that improving the cultivability of fungi remains a relevant strategy in drug discovery and underline the importance of ecological and taxonomic knowledge in culture-dependent drug discovery. Combining traditional and omics techniques such as single cell or metagenome sequencing opens up a new era in the study of growth factors of hundreds of thousands of fungal species with high drug discovery potential.

Covariation of the Fecal Microbiome with Diet in Nonpasserine Birds

Opportunistic feeding and multiple other environment factors can modulate the gut microbiome, and bias conclusions, when wild animals are used for studying the influence of phylogeny and diet on their gut microbiomes. Here, we controlled for these other confounding factors in our investigation of the magnitude of the effect of diet on the gut microbiome assemblies of nonpasserine birds. We collected fecal samples, at one point in time, from 35 species of birds in a single zoo as well as 6 species of domestic poultry from farms in Guangzhou city to minimize the influences from interfering factors. Specifically, we describe 16S rRNA amplicon data from 129 fecal samples obtained from 41 species of birds, with additional shotgun metagenomic sequencing data generated from 16 of these individuals. Our data show that diets containing native starch increase the abundance of Lactobacillus in the gut microbiome, while those containing plant-derived fiber mainly enrich the level of Clostridium Greater numbers of Fusobacteria and Proteobacteria are detected in carnivorous birds, while in birds fed a commercial corn-soybean basal diet, a stronger inner-connected microbial community containing Clostridia and Bacteroidia was enriched. Furthermore, the metagenome functions of the microbes (such as lipid metabolism and amino acid synthesis) were adapted to the different food types to achieve a beneficial state for the host. In conclusion, the covariation of diet and gut microbiome identified in our study demonstrates a modulation of the gut microbiome by dietary diversity and helps us better understand how birds live based on diet-microbiome-host interactions.IMPORTANCE Our study identified food source, rather than host phylogeny, as the main factor modulating the gut microbiome diversity of nonpasserine birds, after minimizing the effects of other complex interfering factors such as weather, season, and geography. Adaptive evolution of microbes to food types formed a dietary-microbiome-host interaction reciprocal state. The covariation of diet and gut microbiome, including the response of microbiota assembly to diet in structure and function, is important for health and nutrition in animals. Our findings help resolve the major modulators of gut microbiome diversity in nonpasserine birds, which had not previously been well studied. The diet-microbe interactions and cooccurrence patterns identified in our study may be of special interest for future health assessment and conservation in birds.

Long-read metagenomics retrieves complete single-contig bacterial genomes from canine feces

Background

Long-read sequencing in metagenomics facilitates the assembly of complete genomes out of complex microbial communities. These genomes include essential biologic information such as the ribosomal genes or the mobile genetic elements, which are usually missed with short-reads. We applied long-read metagenomics with Nanopore sequencing to retrieve high-quality metagenome-assembled genomes (HQ MAGs) from a dog fecal sample.

Results

We used nanopore long-read metagenomics and frameshift aware correction on a canine fecal sample and retrieved eight single-contig HQ MAGs, which were > 90% complete with < 5% contamination, and contained most ribosomal genes and tRNAs. At the technical level, we demonstrated that a high-molecular-weight DNA extraction improved the metagenomics assembly contiguity, the recovery of the rRNA operons, and the retrieval of longer and circular contigs that are potential HQ MAGs. These HQ MAGs corresponded to Succinivibrio, Sutterella, Prevotellamassilia, Phascolarctobacterium, Catenibacterium, Blautia, and Enterococcus genera. Linking our results to previous gastrointestinal microbiome reports (metagenome or 16S rRNA-based), we found that some bacterial species on the gastrointestinal tract seem to be more canid-specific –Succinivibrio, Prevotellamassilia, Phascolarctobacterium, Blautia_A sp900541345–, whereas others are more broadly distributed among animal and human microbiomes –Sutterella, Catenibacterium, Enterococcus, and Blautia sp003287895. Sutterella HQ MAG is potentially the first reported genome assembly for Sutterella stercoricanis, as assigned by 16S rRNA gene similarity. Moreover, we show that long reads are essential to detect mobilome functions, usually missed in short-read MAGs.

Conclusions

We recovered eight single-contig HQ MAGs from canine feces of a healthy dog with nanopore long-reads. We also retrieved relevant biological insights from these specific bacterial species previously missed in public databases, such as complete ribosomal operons and mobilome functions. The high-molecular-weight DNA extraction improved the assembly’s contiguity, whereas the high-accuracy basecalling, the raw read error correction, the assembly polishing, and the frameshift correction reduced the insertion and deletion errors. Both experimental and analytical steps ensured the retrieval of complete bacterial genomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07607-0.

Free-Living, Psychrotrophic Bacteria of the Genus Psychrobacter Are Descendants of Pathobionts

Host-adapted microorganisms are generally assumed to have evolved from free-living, environmental microorganisms, as examples of the reverse process are rare. In the phylum Gammaproteobacteria, family Moraxellaceae, the genus Psychrobacter includes strains from a broad ecological distribution including animal bodies as well as sea ice and other nonhost environments. To elucidate the relationship between these ecological niches and Psychrobacter's evolutionary history, we performed tandem genomic analyses with phenotyping of 85 Psychrobacter accessions. Phylogenomic analysis of the family Moraxellaceae reveals that basal members of the Psychrobacter clade are Moraxella spp., a group of often-pathogenic organisms. Psychrobacter exhibited two broad growth patterns in our phenotypic screen: one group that we called the "flexible ecotype" (FE) had the ability to grow between 4 and 37°C, and the other, which we called the "restricted ecotype" (RE), could grow between 4 and 25°C. The FE group includes phylogenetically basal strains, and FE strains exhibit increased transposon copy numbers, smaller genomes, and a higher likelihood to be bile salt resistant. The RE group contains only phylogenetically derived strains and has increased proportions of lipid metabolism and biofilm formation genes, functions that are adaptive to cold stress. In a 16S rRNA gene survey of polar bear fecal samples, we detect both FE and RE strains, but in in vivo colonizations of gnotobiotic mice, only FE strains persist. Our results indicate the ability to grow at 37°C, seemingly necessary for mammalian gut colonization, is an ancestral trait for Psychrobacter, which likely evolved from a pathobiont.IMPORTANCE Host-associated microbes are generally assumed to have evolved from free-living ones. The evolutionary transition of microbes in the opposite direction, from host associated toward free living, has been predicted based on phylogenetic data but not studied in depth. Here, we provide evidence that the genus Psychrobacter, particularly well known for inhabiting low-temperature, high-salt environments such as sea ice, permafrost soils, and frozen foodstuffs, has evolved from a mammalian-associated ancestor. We show that some Psychrobacter strains retain seemingly ancestral genomic and phenotypic traits that correspond with host association while others have diverged to psychrotrophic or psychrophilic lifestyles.

Current State and Future Directions of Genetics and Genomics of Endophytic Fungi for Bioprospecting Efforts

The bioprospecting of secondary metabolites from endophytic fungi received great attention in the 1990s and 2000s, when the controversy around taxol production from Taxus spp. endophytes was at its height. Since then, hundreds of reports have described the isolation and characterization of putative secondary metabolites from endophytic fungi. However, only very few studies also report the genetic basis for these phenotypic observations. With low sequencing cost and fast sample turnaround, genetics- and genomics-based approaches have risen to become comprehensive approaches to study natural products from a wide-range of organisms, especially to elucidate underlying biosynthetic pathways. However, in the field of fungal endophyte biology, elucidation of biosynthetic pathways is still a major challenge. As a relatively poorly investigated group of microorganisms, even in the light of recent efforts to sequence more fungal genomes, such as the 1000 Fungal Genomes Project at the Joint Genome Institute (JGI), the basis for bioprospecting of enzymes and pathways from endophytic fungi is still rather slim. In this review we want to discuss the current approaches and tools used to associate phenotype and genotype to elucidate biosynthetic pathways of secondary metabolites in endophytic fungi through the lens of bioprospecting. This review will point out the reported successes and shortcomings, and discuss future directions in sampling, and genetics and genomics of endophytic fungi. Identifying responsible biosynthetic genes for the numerous secondary metabolites isolated from endophytic fungi opens the opportunity to explore the genetic potential of producer strains to discover novel secondary metabolites and enhance secondary metabolite production by metabolic engineering resulting in novel and more affordable medicines and food additives.

BiG-SLiCE: A highly scalable tool maps the diversity of 1.2 million biosynthetic gene clusters

BACKGROUND

Genome mining for biosynthetic gene clusters (BGCs) has become an integral part of natural product discovery. The >200,000 microbial genomes now publicly available hold information on abundant novel chemistry. One way to navigate this vast genomic diversity is through comparative analysis of homologous BGCs, which allows identification of cross-species patterns that can be matched to the presence of metabolites or biological activities. However, current tools are hindered by a bottleneck caused by the expensive network-based approach used to group these BGCs into gene cluster families (GCFs).

RESULTS

Here, we introduce BiG-SLiCE, a tool designed to cluster massive numbers of BGCs. By representing them in Euclidean space, BiG-SLiCE can group BGCs into GCFs in a non-pairwise, near-linear fashion. We used BiG-SLiCE to analyze 1,225,071 BGCs collected from 209,206 publicly available microbial genomes and metagenome-assembled genomes within 10 days on a typical 36-core CPU server. We demonstrate the utility of such analyses by reconstructing a global map of secondary metabolic diversity across taxonomy to identify uncharted biosynthetic potential. BiG-SLiCE also provides a "query mode" that can efficiently place newly sequenced BGCs into previously computed GCFs, plus a powerful output visualization engine that facilitates user-friendly data exploration.

CONCLUSIONS

BiG-SLiCE opens up new possibilities to accelerate natural product discovery and offers a first step towards constructing a global and searchable interconnected network of BGCs. As more genomes are sequenced from understudied taxa, more information can be mined to highlight their potentially novel chemistry. BiG-SLiCE is available via https://github.com/medema-group/bigslice.

MicrobeAnnotator: a user-friendly, comprehensive functional annotation pipeline for microbial genomes

BACKGROUND

High-throughput sequencing has increased the number of available microbial genomes recovered from isolates, single cells, and metagenomes. Accordingly, fast and comprehensive functional gene annotation pipelines are needed to analyze and compare these genomes. Although several approaches exist for genome annotation, these are typically not designed for easy incorporation into analysis pipelines, do not combine results from different annotation databases or offer easy-to-use summaries of metabolic reconstructions, and typically require large amounts of computing power for high-throughput analysis not available to the average user.

RESULTS

Here, we introduce MicrobeAnnotator, a fully automated, easy-to-use pipeline for the comprehensive functional annotation of microbial genomes that combines results from several reference protein databases and returns the matching annotations together with key metadata such as the interlinked identifiers of matching reference proteins from multiple databases [KEGG Orthology (KO), Enzyme Commission (E.C.), Gene Ontology (GO), Pfam, and InterPro]. Further, the functional annotations are summarized into Kyoto Encyclopedia of Genes and Genomes (KEGG) modules as part of a graphical output (heatmap) that allows the user to quickly detect differences among (multiple) query genomes and cluster the genomes based on their metabolic similarity. MicrobeAnnotator is implemented in Python 3 and is freely available under an open-source Artistic License 2.0 from https://github.com/cruizperez/MicrobeAnnotator .

CONCLUSIONS

We demonstrated the capabilities of MicrobeAnnotator by annotating 100 Escherichia coli and 78 environmental Candidate Phyla Radiation (CPR) bacterial genomes and comparing the results to those of other popular tools. We showed that the use of multiple annotation databases allows MicrobeAnnotator to recover more annotations per genome compared to faster tools that use reduced databases and is computationally efficient for use in personal computers. The output of MicrobeAnnotator can be easily incorporated into other analysis pipelines while the results of other annotation tools can be seemingly incorporated into MicrobeAnnotator to generate summary plots.

Large-Scale Metagenome Assembly Reveals Novel Animal-Associated Microbial Genomes, Biosynthetic Gene Clusters, and Other Genetic Diversity

Large-scale metagenome assemblies of human microbiomes have produced a vast catalogue of previously unseen microbial genomes; however, comparatively few microbial genomes derive from other vertebrates. Here, we generated 5,596 metagenome-assembled genomes (MAGs) from the gut metagenomes of 180 predominantly wild animal species representing 5 classes, in addition to 14 existing animal gut metagenome data sets. The MAGs comprised 1,522 species-level genome bins (SGBs), most of which were novel at the species, genus, or family level, and the majority were enriched in host versus environment metagenomes. Many traits distinguished SGBs enriched in host or environmental biomes, including the number of antimicrobial resistance genes. We identified 1,986 diverse biosynthetic gene clusters; only 23 clustered with any MIBiG database references. Gene-based assembly revealed tremendous gene diversity, much of it host or environment specific. Our MAG and gene data sets greatly expand the microbial genome repertoire and provide a broad view of microbial adaptations to the vertebrate gut.IMPORTANCE Microbiome studies on a select few mammalian species (e.g., humans, mice, and cattle) have revealed a great deal of novel genomic diversity in the gut microbiome. However, little is known of the microbial diversity in the gut of other vertebrates. We studied the gut microbiomes of a large set of mostly wild animal species consisting of mammals, birds, reptiles, amphibians, and fish. Unfortunately, we found that existing reference databases commonly used for metagenomic analyses failed to capture the microbiome diversity among vertebrates. To increase database representation, we applied advanced metagenome assembly methods to our animal gut data and to many public gut metagenome data sets that had not been used to obtain microbial genomes. Our resulting genome and gene cluster collections comprised a great deal of novel taxonomic and genomic diversity, which we extensively characterized. Our findings substantially expand what is known of microbial genomic diversity in the vertebrate gut.