Genome Taxonomy Database Research Articles

Isolation and sequence-based characterization of a koala symbiont: Lonepinella koalarum.

Koalas (Phascolarctos cinereus) are highly specialized herbivorous marsupials that feed almost exclusively on Eucalyptus leaves, which are known to contain varying concentrations of many different toxic chemical compounds. The literature suggests that Lonepinella koalarum, a bacterium in the Pasteurellaceae family, can break down some of these toxic chemical compounds. Furthermore, in a previous study, we identified L. koalarum as the most predictive taxon of koala survival during antibiotic treatment. Therefore, we believe that this bacterium may be important for koala health. Here, we isolated a strain of L. koalarum from a healthy koala female and sequenced its genome using a combination of short-read and long-read sequencing. We placed the genome assembly into a phylogenetic tree based on 120 genome markers using the Genome Taxonomy Database (GTDB), which currently does not include any L. koalarum assemblies. Our genome assembly fell in the middle of a group of Haemophilus, Pasteurella and Basfia species. According to average nucleotide identity and a 16S rRNA gene tree, the closest relative of our isolate is L. koalarum strain Y17189. Then, we annotated the gene sequences and compared them to 55 closely related, publicly available genomes. Several genes that are known to be involved in carbohydrate metabolism could exclusively be found in L. koalarum relative to the other taxa in the pangenome, including glycoside hydrolase families GH2, GH31, GH32, GH43 and GH77. Among the predicted genes of L. koalarum were 79 candidates putatively involved in the degradation of plant secondary metabolites. Additionally, several genes coding for amino acid variants were found that had been shown to confer antibiotic resistance in other bacterial species against pulvomycin, beta-lactam antibiotics and the antibiotic efflux pump KpnH. In summary, this genetic characterization allows us to build hypotheses to explore the potentially beneficial role that L. koalarum might play in the koala intestinal microbiome. Characterizing and understanding beneficial symbionts at the whole genome level is important for the development of anti- and probiotic treatments for koalas, a highly threatened species due to habitat loss, wildfires, and high prevalence of Chlamydia infections.

Metagenomic analysis of gut microbiome and resistome of diarrheal fecal samples from Kolkata, India, reveals the core and variable microbiota including signatures of microbial dark matter

BackgroundMetagenomic analysis of the gut microbiome and resistome is instrumental for understanding the dynamics of diarrheal pathogenesis and antimicrobial resistance transmission (AMR). Metagenomic sequencing of 20 diarrheal fecal samples from Kolkata was conducted to understand the core and variable gut microbiota. Five of these samples were used for resistome analysis. The pilot study was conducted to determine a microbiota signature and the source of antimicrobial resistance genes (ARGs) in the diarrheal gut.Results16S rRNA amplicon sequencing was performed using Illumina MiSeq platform and analysed using the MGnify pipeline. The Genome Taxonomy Database (GTDB-Tk) was used for bacterial taxonomic identification. Diarrheal etiology was determined by culture method. Phylum Firmicutes, Bacteroidetes, Proteobacteria and Actinobacteria were consistently present in 20 samples. Firmicutes was the most abundant phylum in 11 samples. The Bacteroidetes/Firmicutes ratio was less than 1 in 18 samples. 584 genera were observed. 18 of these were present in all the 20 samples. Proteobacteria was the dominant phylum in 6 samples associated with Vibrio cholerae infection. Conservation of operational taxonomic units (OTUs) among all the samples indicated the existence of a core microbiome. Asymptomatic carriage of pathogens like Vibrio cholerae and Helicobacter pylori was found. Signature of Candidate phyla or “microbial dark matter” occurred. Significant correlation of relative abundance of bacterial families of commensals and pathogens were found. Whole-genome sequencing (WGS) on Illumina MiSeq system and assembly of raw reads using metaSPAdes v3.9.1 was performed to study the resistome of 5 samples. ABRicate was used to assign ARG function. 491 resistance determinants were identified. In 80% of the samples tetracycline resistance was the most abundant resistance determinant. High abundance of ARGs against β-lactams, aminoglycosides, quinolones and macrolides was found. Eschericia sp. was the major contributor of ARGs.ConclusionsThis is the first comparative study of the gut microbiome associated with different diarrheal pathogens. It presents the first catalogue of different bacterial taxa representing the core and variable microbiome in acute diarrheal patients. The study helped to define a trend in the gut microbiota signature associated with diarrhea and revealed which ARGs are abundantly present and the metagenome-assembled genomes (MAGs) contributing to AMR.

Single-Cell Genomics of Novel Actinobacteria With the Wood-Ljungdahl Pathway Discovered in a Serpentinizing System.

Serpentinite-hosted systems represent modern-day analogs of early Earth environments. In these systems, water-rock interactions generate highly alkaline and reducing fluids that can contain hydrogen, methane, and low-molecular-weight hydrocarbons-potent reductants capable of fueling microbial metabolism. In this study, we investigated the microbiota of Hakuba Happo hot springs (∼50°C; pH∼10.5–11), located in Nagano (Japan), which are impacted by the serpentinization process. Analysis of the 16S rRNA gene amplicon sequences revealed that the bacterial community comprises Nitrospirae (47%), “Parcubacteria” (19%), Deinococcus-Thermus (16%), and Actinobacteria (9%), among others. Notably, only 57 amplicon sequence variants (ASV) were detected, and fifteen of these accounted for 90% of the amplicons. Among the abundant ASVs, an early-branching, uncultivated actinobacterial clade identified as RBG-16-55-12 in the SILVA database was detected. Ten single-cell genomes (average pairwise nucleotide identity: 0.98–1.00; estimated completeness: 33–93%; estimated genome size: ∼2.3 Mb) that affiliated with this clade were obtained. Taxonomic classification using single copy genes indicates that the genomes belong to the actinobacterial class-level clade UBA1414 in the Genome Taxonomy Database. Based on metabolic pathway predictions, these actinobacteria are anaerobes, capable of glycolysis, dissimilatory nitrate reduction and CO2 fixation via the Wood–Ljungdahl (WL) pathway. Several other genomes within UBA1414 and two related class-level clades also encode the WL pathway, which has not yet been reported for the Actinobacteria phylum. For the Hakuba actinobacterium, the energy metabolism related to the WL pathway is likely supported by a combination of the Rnf complex, group 3b and 3d [NiFe]-hydrogenases, [FeFe]-hydrogenases, and V-type (H+/Na+ pump) ATPase. The genomes also harbor a form IV ribulose 1,5-bisphosphate carboxylase/oxygenase (RubisCO) complex, also known as a RubisCO-like protein, and contain signatures of interactions with viruses, including clustered regularly interspaced short palindromic repeat (CRISPR) regions and several phage integrases. This is the first report and detailed genome analysis of a bacterium within the Actinobacteria phylum capable of utilizing the WL pathway. The Hakuba actinobacterium is a member of the clade UBA1414/RBG-16-55-12, formerly within the group “OPB41.” We propose to name this bacterium ‘Candidatus Hakubanella thermoalkaliphilus.’

Taxonomy of Bacteria and Archaea.

Improvements to the Genome Taxonomy Database provide a complete bacterial and archaeal taxonomy.

A complete domain-to-species taxonomy for Bacteria and Archaea.

The Genome Taxonomy Database is a phylogenetically consistent, genome-based taxonomy that provides rank-normalized classifications for ~150,000 bacterial and archaeal genomes from domain to genus. However, almost 40% of the genomes in the Genome Taxonomy Database lack a species name. We address this limitation by using commonly accepted average nucleotide identity criteria to set bounds on species and propose species clusters that encompass all publicly available bacterial and archaeal genomes. Unlike previous average nucleotide identity studies, we chose a single representative genome to serve as the effective nomenclatural 'type' defining each species. Of the 24,706 proposed species clusters, 8,792 are based on published names. We assigned placeholder names to the remaining 15,914 species clusters to provide names to the growing number of genomes from uncultivated species. This resource provides a complete domain-to-species taxonomic framework for bacterial and archaeal genomes, which will facilitate research on uncultivated species and improve communication of scientific results.

An assessment of genome annotation coverage across the bacterial tree of life.

Although gene-finding in bacterial genomes is relatively straightforward, the automated assignment of gene function is still challenging, resulting in a vast quantity of hypothetical sequences of unknown function. But how prevalent are hypothetical sequences across bacteria, what proportion of genes in different bacterial genomes remain unannotated, and what factors affect annotation completeness? To address these questions, we surveyed over 27 000 bacterial genomes from the Genome Taxonomy Database, and measured genome annotation completeness as a function of annotation method, taxonomy, genome size, 'research bias' and publication date. Our analysis revealed that 52 and 79 % of the average bacterial proteome could be functionally annotated based on protein and domain-based homology searches, respectively. Annotation coverage using protein homology search varied significantly from as low as 14 % in some species to as high as 98 % in others. We found that taxonomy is a major factor influencing annotation completeness, with distinct trends observed across the microbial tree (e.g. the lowest level of completeness was found in the Patescibacteria lineage). Most lineages showed a significant association between genome size and annotation incompleteness, likely reflecting a greater degree of uncharacterized sequences in 'accessory' proteomes than in 'core' proteomes. Finally, research bias, as measured by publication volume, was also an important factor influencing genome annotation completeness, with early model organisms showing high completeness levels relative to other genomes in their own taxonomic lineages. Our work highlights the disparity in annotation coverage across the bacterial tree of life and emphasizes a need for more experimental characterization of accessory proteomes as well as understudied lineages.

Struo: a pipeline for building custom databases for common metagenome profilers.

Taxonomic and functional information from microbial communities can be efficiently obtained by metagenome profiling, which requires databases of genes and genomes to which sequence reads are mapped. However, the databases that accompany metagenome profilers are not updated at a pace that matches the increase in available microbial genomes, and unifying database content across metagenome profiling tools can be cumbersome. To address this, we developed Struo, a modular pipeline that automatizes the acquisition of genomes from public repositories and the construction of custom databases for multiple metagenome profilers. The use of custom databases that broadly represent the known microbial diversity by incorporating novel genomes results in a substantial increase in mappability of reads in synthetic and real metagenome datasets. Source code available for download at https://github.com/leylabmpi/Struo. Custom genome taxonomy database databases available at http://ftp.tue.mpg.de/ebio/projects/struo/. Supplementary data are available at Bioinformatics online.

GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database.

SummaryThe Genome Taxonomy Database Toolkit (GTDB-Tk) provides objective taxonomic assignments for bacterial and archaeal genomes based on the GTDB. GTDB-Tk is computationally efficient and able to classify thousands of draft genomes in parallel. Here we demonstrate the accuracy of the GTDB-Tk taxonomic assignments by evaluating its performance on a phylogenetically diverse set of 10 156 bacterial and archaeal metagenome-assembled genomes.Availability and implementationGTDB-Tk is implemented in Python and licenced under the GNU General Public Licence v3.0. Source code and documentation are available at: https://github.com/ecogenomics/gtdbtk.Supplementary information Supplementary data are available at Bioinformatics online.

Quantitatively Partitioning Microbial Genomic Traits among Taxonomic Ranks across the Microbial Tree of Life.

Widely used microbial taxonomies, such as the NCBI taxonomy, are based on a combination of sequence homology among conserved genes and historically accepted taxonomies, which were developed based on observable traits such as morphology and physiology. A recently proposed alternative taxonomy database, the Genome Taxonomy Database (GTDB), incorporates only sequence homology of conserved genes and attempts to partition taxonomic ranks such that each rank implies the same amount of evolutionary distance, regardless of its position on the phylogenetic tree. This provides the first opportunity to completely separate taxonomy from traits and therefore to quantify how taxonomic rank corresponds to traits across the microbial tree of life. We quantified the relative abundances of clusters of orthologous group functional categories (COG-FCs) as a proxy for traits within the lineages of 13,735 cultured and uncultured microbial lineages from a custom-curated genome database. On average, 41.4% of the variation in COG-FC relative abundance is explained by taxonomic rank, with domain, phylum, class, order, family, and genus explaining, on average, 3.2%, 14.6%, 4.1%, 9.2%, 4.8%, and 5.5% of the variance, respectively (P < 0.001 for all). To our knowledge, this is the first work to quantify the variance in metabolic potential contributed by individual taxonomic ranks. A qualitative comparison between the COG-FC relative abundances and genus-level phylogenies, generated from published concatenated protein sequence alignments, further supports the idea that metabolic potential is taxonomically coherent at higher taxonomic ranks. The quantitative analyses presented here characterize the integral relationship between diversification of microbial lineages and the metabolisms which they host.IMPORTANCE Recently, there has been great progress in defining a complete taxonomy of bacteria and archaea, which has been enabled by improvements in DNA sequencing technology and new bioinformatic techniques. A new, algorithmically defined microbial tree of life describes those linkages, relying solely on genetic data, which raises the issue of how microbial traits relate to taxonomy. Here, we adopted cluster of orthologous group functional categories as a scheme to describe the genomic contents of microbes, a method that can be applied to any microbial lineage for which genomes are available. This simple approach allows quantitative comparisons between microbial genomes with different gene compositions from across the microbial tree of life. Our observations demonstrate statistically significant patterns in cluster of orthologous group functional categories at taxonomic levels that span the range from domain to genus.

A New Genome-to-Genome Comparison Approach for Large-Scale Revisiting of Current Microbial Taxonomy

Microbial diversity has always presented taxonomic challenges. With the popularity of next-generation sequencing technology, more unculturable bacteria have been sequenced, facilitating the discovery of additional new species and complicated current microbial classification. The major challenge is to assign appropriate taxonomic names. Hence, assessing the consistency between taxonomy and genomic relatedness is critical. We proposed and applied a genome comparison approach to a large-scale survey to investigate the distribution of genomic differences among microorganisms. The approach applies a genome-wide criterion, homologous coverage ratio (HCR), for describing the homology between species. The survey included 7861 microbial genomes that excluded plasmids, and 1220 pairs of genera exhibited ambiguous classification. In this study, we also compared the performance of HCR and average nucleotide identity (ANI). The results indicated that HCR and ANI analyses yield comparable results, but a few examples suggested that HCR has a superior clustering effect. In addition, we used the Genome Taxonomy Database (GTDB), the gold standard for taxonomy, to validate our analysis. The GTDB offers 120 ubiquitous single-copy proteins as marker genes for species classification. We determined that the analysis of the GTDB still results in classification boundary blur between some genera and that the marker gene-based approach has limitations. Although the choice of marker genes has been quite rigorous, the bias of marker gene selection remains unavoidable. Therefore, methods based on genomic alignment should be considered for use for species classification in order to avoid the bias of marker gene selection. On the basis of our observations of microbial diversity, microbial classification should be re-examined using genome-wide comparisons.

A standardized bacterial taxonomy based on genome phylogeny substantially revises the tree of life.

Taxonomy is an organizing principle of biology and is ideally based on evolutionary relationships among organisms. Development of a robust bacterial taxonomy has been hindered by an inability to obtain most bacteria in pure culture and, to a lesser extent, by the historical use of phenotypes to guide classification. Culture-independent sequencing technologies have matured sufficiently that a comprehensive genome-based taxonomy is now possible. We used a concatenated protein phylogeny as the basis for a bacterial taxonomy that conservatively removes polyphyletic groups and normalizes taxonomic ranks on the basis of relative evolutionary divergence. Under this approach, 58% of the 94,759 genomes comprising the Genome Taxonomy Database had changes to their existing taxonomy. This result includes the description of 99 phyla, including six major monophyletic units from the subdivision of the Proteobacteria, and amalgamation of the Candidate Phyla Radiation into a single phylum. Our taxonomy should enable improved classification of uncultured bacteria and provide a sound basis for ecological and evolutionary studies.