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.

Draft genome sequences of hydrocarbon degrading Haloferax sp. AB510, Haladaptatus sp. AB618 and Haladaptatus sp. AB643 isolated from the estuarine sediments of Sundarban mangrove forests, India.

The present study reports the draft genomes of three hydrocarbon-degrading haloarchaeal strains Haloferax sp. AB510, Haladaptatus sp. AB618 and Haladaptatus sp. AB643 that were isolated from the estuarine sediments of Sundarban mangrove forests, India. All three genomes had a high GC content of around 60%, characteristic of the haloarchaea. The Haloferax sp. AB510 genome was around 3.9 Mb in size and consisted of 4567 coding sequences and 54 RNAs. The Haladaptatus sp. AB618 and Haladaptatus sp. AB643 genomes were comparatively larger and around 4.8 Mb each. The AB618 and AB643 genomes comprised 5279 and 5304 coding sequences and 60 and 59 RNAs, respectively. All three of the genomes encoded several genes that attributed to their survival in the presence of hydrocarbons in their native habitats. Functional annotation and curation of the sequenced genomes suggested that the Haloferax sp. AB510 strain utilized the gentisate pathway of aromatic compound degradation. While the Haladaptatus sp. AB618 and Haladaptatus sp. AB643 strains possessed the freedom of utilizing both the gentisate and the catechol pathways for degrading aromatic hydrocarbons. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-022-03273-5.

Gut microbial determinants of clinically important improvement in patients with rheumatoid arthritis.

BACKGROUND: Rapid advances in the past decade have shown that dysbiosis of the gut microbiome is a key hallmark of rheumatoid arthritis (RA). Yet, the relationship between the gut microbiome and clinical improvement in RA disease activity remains unclear. In this study, we explored the gut microbiome of patients with RA to identify features that are associated with, as well as predictive of, minimum clinically important improvement (MCII) in disease activity. METHODS: We conducted a retrospective, observational cohort study on patients diagnosed with RA between 1988 and 2014. Whole metagenome shotgun sequencing was performed on 64 stool samples, which were collected from 32 patients with RA at two separate time-points approximately 6-12 months apart. The Clinical Disease Activity Index (CDAI) of each patient was measured at both time-points to assess achievement of MCII; depending on this clinical status, patients were distinguished into two groups: MCII+ (who achieved MCII; n = 12) and MCII- (who did not achieve MCII; n = 20). Multiple linear regression models were used to identify microbial taxa and biochemical pathways associated with MCII while controlling for potentially confounding factors. Lastly, a deep-learning neural network was trained upon gut microbiome, clinical, and demographic data at baseline to classify patients according to MCII status, thereby enabling the prediction of whether a patient will achieve MCII at follow-up. RESULTS: We found age to be the largest determinant of the overall compositional variance in the gut microbiome (R2 = 7.7%, P = 0.001, PERMANOVA). Interestingly, the next factor identified to explain the most variance in the gut microbiome was MCII status (R2 = 3.8%, P = 0.005). Additionally, by looking at patients' baseline gut microbiome profiles, we observed significantly different microbiome traits between patients who eventually showed MCII and those who did not. Taxonomic features include alpha- and beta-diversity measures, as well as several microbial taxa, such as Coprococcus, Bilophila sp. 4_1_30, and Eubacterium sp. 3_1_31. Notably, patients who achieved clinical improvement had higher alpha-diversity in their gut microbiomes at both baseline and follow-up visits. Functional profiling identified fifteen biochemical pathways, most of which were involved in the biosynthesis of L-arginine, L-methionine, and tetrahydrofolate, to be differentially abundant between the MCII patient groups. Moreover, MCII+ and MCII- groups showed significantly different fold-changes (from baseline to follow-up) in eight microbial taxa and in seven biochemical pathways. These results could suggest that, depending on the clinical course, gut microbiomes not only start at different ecological states, but also are on separate trajectories. Finally, the neural network proved to be highly effective in predicting which patients will achieve MCII (balanced accuracy = 90.0%, leave-one-out cross-validation), demonstrating potential clinical utility of gut microbiome profiles. CONCLUSIONS: Our findings confirm the presence of taxonomic and functional signatures of the gut microbiome associated with MCII in RA patients. Ultimately, modifying the gut microbiome to enhance clinical outcome may hold promise as a future treatment for RA.

A predictive index for health status using species-level gut microbiome profiling.

Providing insight into one's health status from a gut microbiome sample is an important clinical goal in current human microbiome research. Herein, we introduce the Gut Microbiome Health Index (GMHI), a biologically-interpretable mathematical formula for predicting the likelihood of disease independent of the clinical diagnosis. GMHI is formulated upon 50 microbial species associated with healthy gut ecosystems. These species are identified through a multi-study, integrative analysis on 4347 human stool metagenomes from 34 published studies across healthy and 12 different nonhealthy conditions, i.e., disease or abnormal bodyweight. When demonstrated on our population-scale meta-dataset, GMHI is the most robust and consistent predictor of disease presence (or absence) compared to α-diversity indices. Validation on 679 samples from 9 additional studies results in a balanced accuracy of 73.7% in distinguishing healthy from non-healthy groups. Our findings suggest that gut taxonomic signatures can predict health status, and highlight how data sharing efforts can provide broadly applicable discoveries.

Microbiome and ecology of a hot spring-microbialite system on the Trans-Himalayan Plateau.

Little is known about life in the boron-rich hot springs of Trans-Himalayas. Here, we explore the geomicrobiology of a 4438-m-high spring which emanates ~70 °C-water from a boratic microbialite called Shivlinga. Due to low atmospheric pressure, the vent-water is close to boiling point so can entropically destabilize biomacromolecular systems. Starting from the vent, Shivlinga's geomicrobiology was revealed along the thermal gradients of an outflow-channel and a progressively-drying mineral matrix that has no running water; ecosystem constraints were then considered in relation to those of entropically comparable environments. The spring-water chemistry and sinter mineralogy were dominated by borates, sodium, thiosulfate, sulfate, sulfite, sulfide, bicarbonate, and other macromolecule-stabilizing (kosmotropic) substances. Microbial diversity was high along both of the hydrothermal gradients. Bacteria, Eukarya and Archaea constituted >98%, ~1% and <1% of Shivlinga's microbiome, respectively. Temperature constrained the biodiversity at ~50 °C and ~60 °C, but not below 46 °C. Along each thermal gradient, in the vent-to-apron trajectory, communities were dominated by Aquificae/Deinococcus-Thermus, then Chlorobi/Chloroflexi/Cyanobacteria, and finally Bacteroidetes/Proteobacteria/Firmicutes. Interestingly, sites of >45 °C were inhabited by phylogenetic relatives of taxa for which laboratory growth is not known at >45 °C. Shivlinga's geomicrobiology highlights the possibility that the system's kosmotrope-dominated chemistry mitigates against the biomacromolecule-disordering effects of its thermal water.

Phylogenomics of an uncultivated, aerobic and thermophilic, photoheterotrophic member of Chlorobia sheds light into the evolution of the phylum Chlorobi.

All cultivated members of the phylum Chlorobi are classified under the two classes Chlorobia and Ignavibacteria. The recently-reported, uncultivated genome-species of Chlorobi have not suggested any alteration in the dichotomy of the two classes, but have hypothesized the existence of a distinct, aerobic and photoheterotrophic, order/family level lineage within Chlorobia, which otherwise was considered to be a monophyletic group of anaerobic sulfur-photolithoautotrophs. Here we report the discovery of a novel population genome bin (named Chlorobi-445) from the combined metagenomes of three spatially-contiguous but visually-distinct microbial mats growing along the 65-41 °C hydrothermal gradient of a boron-rich microbialite spring located in the Puga geothermal area of Eastern Ladakh, India. 1.3, 8.2 and 3.8% metagenomic reads from the mat communities located at 65 °C, 52 °C and 41 °C sample-sites respectively, were found to map-back to the 2,809,852 bp genome of Chlorobi-445. Phylogenomically, and therefore in terms of potential metabolic attributes, Chlorobi-445 showed close relationship with Ca. Thermochlorobacter aerophilum. Gene content suggested Chlorobi-445 to be an aerobic photoorganoheterotroph. Although this new lineage encodes all the proteins necessary for the biosynthesis of bacteriochlorophylls and the photosynthetic reaction centre, it is potentially devoid of genes concerned with lithotrophic sulfur oxidation and carbon-fixation. Individual Chlorobi phylogenies based on the sequence similarities of 16S rRNA genes, 22 ribosomal proteins, and 56 conserved marker-proteins that are encoded from single-copy genes, unanimously suggested that the class Chlorobia encompasses two major branches/clades. Whereas the Clade-I is a homogeneous cluster of culturable, anaerobic sulfur-/iron-oxidizing photolithoautotrophs, Clade-II harbors (i) Chloroherpeton species, and (ii) uncultivated aerobic photoheterotrophs such as Chlorobi-445, Chlorobium sp. GBChlB &Ca. T. aerophilum, in its two sub-clades. Distribution of bioenergetic attributes over the different branches of Chlorobi, together with the aerobic chemoorganoheterotrophic nature of the deepest-branching genome-species NICIL-2, indicated that the early Chlorobi were aerobic chemoorganoheterotrophs, while anaerobicity, phototrophy, lithotrophy, and autotrophy were all potentially added in the course of evolution.

Genome-Guided Insights into the Plant Growth Promotion Capabilities of the Physiologically Versatile Bacillus aryabhattai Strain AB211.

Bacillus aryabhattai AB211 is a plant growth promoting, Gram-positive firmicute, isolated from the rhizosphere of tea (Camellia sinensis), one of the oldest perennial crops and a major non-alcoholic beverage widely consumed all over the world. The whole genome of B. aryabhattai AB211 was sequenced, annotated and evaluated with special focus on genomic elements related to plant microbe interaction. It's genome sequence reveals the presence of a 5,403,026 bp chromosome. A total of 5226 putative protein-coding sequences, 16 rRNA, 120 tRNA, 8 ncRNAs, 58 non-protein coding genes, and 11 prophage regions were identified. Genome sequence comparisons between strain AB211 and other related environmental strains of B. aryabhattai, identified about 3558 genes conserved among all B. aryabhattai genomes analyzed. Most of the common genes involved in plant growth promotion activities were found to be present within core genes of all the genomes used for comparison, illustrating possible common plant growth promoting traits shared among all the strains of B. aryabhattai. Besides the core genes, some genes were exclusively identified in the genome of strain AB211. Functional annotation of the genes predicted in the strain AB211 revealed the presence of genes responsible for mineral phosphate solubilization, siderophores, acetoin, butanediol, exopolysaccharides, flagella biosynthesis, surface attachment/biofilm formation, and indole acetic acid production, most of which were experimentally verified in the present study. Genome analysis and experimental evidence suggested that AB211 has robust central carbohydrate metabolism implying that this bacterium can efficiently utilize the root exudates and other organic materials as an energy source. Genes for the production of peroxidases, catalases, and superoxide dismutases, that confer resistance to oxidative stresses in plants were identified in AB211 genome. Besides these, genes for heat shock tolerance, cold shock tolerance, glycine-betaine production, and antibiotic/heavy metal resistance that enable bacteria to survive biotic/abiotic stress were also identified. Based on the genome sequence information and experimental evidence as presented in this study, strain AB211 appears to be metabolically diverse and exhibits tremendous potential as a plant growth promoting bacterium.

Assessment of virulence potential of uncharacterized Enterococcus faecalis strains using pan genomic approach - Identification of pathogen-specific and habitat-specific genes.

Enterococcus faecalis, a leading nosocomial pathogen and yet a prominent member of gut microbiome, lacks clear demarcation between pathogenic and non-pathogenic strains at genome level. Here we present the comparative genome analysis of 36 E. faecalis strains with different pathogenic features and from different body-habitats. This study begins by addressing the genome dynamics, which shows that the pan-genome of E. faecalis is still open, though the core genome is nearly saturated. We identified eight uncharacterized strains as potential pathogens on the basis of their co-segregation with reported pathogens in gene presence-absence matrix and Pathogenicity Island (PAI) distribution. A ~7.4 kb genomic-cassette, which is itself a part of PAI, is found to exist in all reported and potential pathogens, but not in commensals and other uncharacterized strains. This region encodes four genes and among them, products of two hypothetical genes are predicted to be intrinsically disordered that may serve as novel targets for therapeutic measures. Exclusive existence of 215, 129, 4 and 1 genes in the blood, gastrointestinal tract, urogenital tract, oral cavity and lymph node derived E. faecalis genomes respectively suggests possible employment of distinct habitat-specific genetic strategies in the adaptation of E. faecalis in human host.