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Next generation sequencing techniques produce enormous data but its analysis and visualization remains a big challenge. To address this, we have developed Genome Annotator Light(GAL), a Docker based package for genome analysis and data visualization. GAL integrated several existing tools and in-house programs inside a Docker Container for systematic analysis and visualization of genomes through web browser. GAL takes varieties of input types ranging from raw Fasta files to fully annotated files, processes them through a standard annotation pipeline and visualizes on a web browser. Comparative genomic analysis is performed automatically within a given taxonomic class. GAL creates interactive genome browser with clickable genomic feature tracks; local BLAST-able database; query page, on-fly downstream data analysis using EMBOSS etc. Overall, GAL is an extremely convenient, portable and platform independent. Fully integrated web-resources can be easily created and deployed, e.g. www.eumicrobedb.org/cglab, for our in-house genomes. GAL is freely available at https://hub.docker.com/u/cglabiicb/.
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Genómica/métodos , Programas Informáticos , Gráficos por ComputadorRESUMEN
BACKGROUND: The community composition of the human microbiome is known to vary at distinct anatomical niches. But little is known about the nature of variations, if any, at the genome/sub-genome levels of a specific microbial community across different niches. The present report aims to explore, as a case study, the variations in gene repertoire of 28 Prevotella reference genomes derived from different body-sites of human, as reported earlier by the Human Microbiome Consortium. RESULTS: The pan-genome for Prevotella remains "open". On an average, 17% of predicted protein-coding genes of any particular Prevotella genome represent the conserved core genes, while the remaining 83% contribute to the flexible and singletons. The study reveals exclusive presence of 11798, 3673, 3348 and 934 gene families and exclusive absence of 17, 221, 115 and 645 gene families in Prevotella genomes derived from human oral cavity, gastro-intestinal tracts (GIT), urogenital tract (UGT) and skin, respectively. Distribution of various functional COG categories differs significantly among the habitat-specific genes. No niche-specific variations could be observed in distribution of KEGG pathways. CONCLUSIONS: Prevotella genomes derived from different body sites differ appreciably in gene repertoire, suggesting that these microbiome components might have developed distinct genetic strategies for niche adaptation within the host. Each individual microbe might also have a component of its own genetic machinery for host adaptation, as appeared from the huge number of singletons.
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Genoma Bacteriano , Microbiota/genética , Filogenia , Prevotella/genética , Tracto Gastrointestinal/microbiología , Humanos , Metagenoma , Boca/microbiología , Piel/microbiología , Distribución Tisular , Sistema Urogenital/microbiologíaRESUMEN
BACKGROUND: To better understand the influence of habitat on the genetic content of bacteria, with a focus on members of Candidate Phyla Radiation (CPR) bacteria, we studied the effects of transitioning from soil via seepage waters to groundwater on genomic composition of ultra-small Parcubacteria, the dominating CPR class in seepage waters, using genome resolved metagenomics. RESULTS: Bacterial metagenome-assembled genomes (MAGs), (318 total, 32 of Parcubacteria) were generated from seepage waters and compared directly to groundwater counterparts. The estimated average genome sizes of members of major phyla Proteobacteria, Bacteroidota and Cand. Patescibacteria (Candidate Phyla Radiation - CPR bacteria) were significantly higher in soil-seepage water as compared to their groundwater counterparts. Seepage water Parcubacteria (Paceibacteria) exhibited 1.18-fold greater mean genome size and 2-fold lower mean proportion of pseudogenes than those in groundwater. Bacteroidota and Proteobacteria also showed a similar trend of reduced genomes in groundwater compared to seepage. While exploring gene loss and adaptive gains in closely related CPR lineages in groundwater, we identified a membrane protein, and a lipoglycopeptide resistance gene unique to a seepage Parcubacterium genome. A nitrite reductase gene was also identified and was unique to the groundwater Parcubacteria genomes, likely acquired from other planktonic microbes via horizontal gene transfer. CONCLUSIONS: Overall, our data suggest that bacteria in seepage waters, including ultra-small Parcubacteria, have significantly larger genomes and higher metabolic enrichment than their groundwater counterparts, highlighting possible genome streamlining of the latter in response to habitat selection in an oligotrophic environment.
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The measurement of uncharacterized pools of biological molecules through techniques such as metabarcoding, metagenomics, metatranscriptomics, metabolomics, and metaproteomics produces large, multivariate datasets. Analyses of these datasets have successfully been borrowed from community ecology to characterize the molecular diversity of samples (É-diversity) and to assess how these profiles change in response to experimental treatments or across gradients (ß-diversity). However, sample preparation and data collection methods generate biases and noise which confound molecular diversity estimates and require special attention. Here, we examine how technical biases and noise that are introduced into multivariate molecular data affect the estimation of the components of diversity (i.e., total number of different molecular species, or entities; total number of molecules; and the abundance distribution of molecular entities). We then explore under which conditions these biases affect the measurement of É- and ß-diversity and highlight how novel methods commonly used in community ecology can be adopted to improve the interpretation and integration of multivariate molecular data. Video Abstract.
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Ecología , Metagenómica , Ecología/métodos , Metagenómica/métodos , Metabolómica/métodosRESUMEN
Sulfolobaceae family, comprising diverse thermoacidophilic and aerobic sulfur-metabolizing Archaea from various geographical locations, offers an ideal opportunity to infer the evolutionary dynamics across the members of this family. Comparative pan-genomics coupled with evolutionary analyses has revealed asymmetric genome evolution within the Sulfolobaceae family. The trend of genome streamlining followed by periods of differential gene gains resulted in an overall genome expansion in some species of this family, whereas there was reduction in others. Among the core genes, both Sulfolobus islandicus and Saccharolobus solfataricus showed a considerable fraction of positively selected genes and also higher frequencies of gene acquisition. In contrast, Sulfolobus acidocaldarius genomes experienced substantial amount of gene loss and strong purifying selection as manifested by relatively lower genome size and higher genome conservation. Central carbohydrate metabolism and sulfur metabolism coevolved with the genome diversification pattern of this archaeal family. The autotrophic CO2 fixation with three significant positively selected enzymes from S. islandicus and S. solfataricus was found to be more imperative than heterotrophic CO2 fixation for Sulfolobaceae. Overall, our analysis provides an insight into the interplay of various genomic adaptation strategies including gene gain-loss, mutation, and selection influencing genome diversification of Sulfolobaceae at various taxonomic levels and geographical locations.
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BACKGROUND: The highly diverse Cand. Patescibacteria are predicted to have minimal biosynthetic and metabolic pathways, which hinders understanding of how their populations differentiate in response to environmental drivers or host organisms. Their mechanisms employed to cope with oxidative stress are largely unknown. Here, we utilized genome-resolved metagenomics to investigate the adaptive genome repertoire of Patescibacteria in oxic and anoxic groundwaters, and to infer putative host ranges. RESULTS: Within six groundwater wells, Cand. Patescibacteria was the most dominant (up to 79%) super-phylum across 32 metagenomes sequenced from DNA retained on 0.2 and 0.1 µm filters after sequential filtration. Of the reconstructed 1275 metagenome-assembled genomes (MAGs), 291 high-quality MAGs were classified as Cand. Patescibacteria. Cand. Paceibacteria and Cand. Microgenomates were enriched exclusively in the 0.1 µm fractions, whereas candidate division ABY1 and Cand. Gracilibacteria were enriched in the 0.2 µm fractions. On average, Patescibacteria enriched in the smaller 0.1 µm filter fractions had 22% smaller genomes, 13.4% lower replication measures, higher proportion of rod-shape determining proteins, and of genomic features suggesting type IV pili mediated cell-cell attachments. Near-surface wells harbored Patescibacteria with higher replication rates than anoxic downstream wells characterized by longer water residence time. Except prevalence of superoxide dismutase genes in Patescibacteria MAGs enriched in oxic groundwaters (83%), no major metabolic or phylogenetic differences were observed. The most abundant Patescibacteria MAG in oxic groundwater encoded a nitrate transporter, nitrite reductase, and F-type ATPase, suggesting an alternative energy conservation mechanism. Patescibacteria consistently co-occurred with one another or with members of phyla Nanoarchaeota, Bacteroidota, Nitrospirota, and Omnitrophota. Among the MAGs enriched in 0.2 µm fractions,, only 8% Patescibacteria showed highly significant one-to-one correlation, mostly with Omnitrophota. Motility and transport related genes in certain Patescibacteria were highly similar to genes from other phyla (Omnitrophota, Proteobacteria and Nanoarchaeota). CONCLUSION: Other than genes to cope with oxidative stress, we found little genomic evidence for niche adaptation of Patescibacteria to oxic or anoxic groundwaters. Given that we could detect specific host preference only for a few MAGs, we speculate that the majority of Patescibacteria is able to attach multiple hosts just long enough to loot or exchange supplies.
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Genome and transcriptome sequencing data are extremely useful resources for researchers in carrying out biological experiments that involves cloning and characterizing genes. We are presenting here genome sequence data from different clades of life including photosynthetic prokaryotes; oomycetes pathogens; probiotic bacteria; endophytic yeasts and filamentous fungus and pathogenic protozoa Leishmania donovani. In addition, we are also presenting paired control and treated stress response transcriptomes of Cyanobacteria growing in extreme conditions. The Cyanobacterial species that are included in this dataset were isolated from extreme conditions including desiccated monuments, hot springs and saline archipelagos. The probiotic Lactobacillus paracasei was isolated from Indian sub-continent. The Kala azar causing protozoan Leishmania donovani, whose early infectious stage is also included in this dataset. The endophyte Arthrinium malaysianum was isolated as a contaminant has significant bio-remediation property. Our collaborators have isolated endophyte Rhodotorula mucilaginosa JGTA1 from Jaduguda mines, West Bengal, India infested with Uranium. Our collaborators have isolated a heterozygous diploid oomycetes pathogen, Phytophthora ramorum causing sudden oak death in CA, USA coast is also part of the data. These dataset presents a unique heterogeneous collection from various sources that are analyzed using "Genome Annotator Light (GAL): A Docker-based package for genome analysis and visualization" (Panda et al., 2019) and are presented in a web site automatically created by GAL at http://www.eumicrobedb.org/cglab.
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The conglomerate of microorganisms inhabiting various body-sites of human, known as the human microbiome, is one of the key determinants of human health and disease. Comprehensive pan-genomic and functional analysis approach for human microbiome components can enrich our understanding about impact of microbiome on human health. By utilizing this approach we developed PanGFR-HM (http://www.bioinfo.iicb.res.in/pangfr-hm/) - a novel dynamic web-resource that integrates genomic and functional characteristics of 1293 complete microbial genomes available from Human Microbiome Project. The resource allows users to explore genomic/functional diversity and genome-based phylogenetic relationships between human associated microbial genomes, not provided by any other resource. The key features implemented here include pan-genome and functional analysis of organisms based on taxonomy or body-site, and comparative analysis between groups of organisms. The first feature can also identify probable gene-loss events and significantly over/under represented KEGG/COG categories within pan-genome. The unique second feature can perform comparative genomic, functional and pathways analysis between 4 groups of microbes. The dynamic nature of this resource enables users to define parameters for orthologous clustering and to select any set of organisms for analysis. As an application for comparative feature of PanGFR-HM, we performed a comparative analysis with 67 Lactobacillus genomes isolated from human gut, oral cavity and urogenital tract, and therefore characterized the body-site specific genes, enzymes and pathways. Altogether, PanGFR-HM, being unique in its content and functionality, is expected to provide a platform for microbiome-based comparative functional and evolutionary genomics.
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Recent advances in ultra-high-throughput sequencing technology and metagenomics have led to a paradigm shift in microbial genomics from few genome comparisons to large-scale pan-genome studies at different scales of phylogenetic resolution. Pan-genome studies provide a framework for estimating the genomic diversity of the dataset, determining core (conserved), accessory (dispensable) and unique (strain-specific) gene pool of a species, tracing horizontal gene-flux across strains and providing insight into species evolution. The existing pan genome software tools suffer from various limitations like limited datasets, difficult installation/requirements, inadequate functional features etc. Here we present an ultra-fast computational pipeline BPGA (Bacterial Pan Genome Analysis tool) with seven functional modules. In addition to the routine pan genome analyses, BPGA introduces a number of novel features for downstream analyses like core/pan/MLST (Multi Locus Sequence Typing) phylogeny, exclusive presence/absence of genes in specific strains, subset analysis, atypical G + C content analysis and KEGG &COG mapping of core, accessory and unique genes. Other notable features include minimum running prerequisites, freedom to select the gene clustering method, ultra-fast execution, user friendly command line interface and high-quality graphics outputs. The performance of BPGA has been evaluated using a dataset of complete genome sequences of 28 Streptococcus pyogenes strains.