MIMt - A curated 16S rRNA database for quick species identification
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ABSTRACT:
ORGANISM(S): Microorganisms
SUBMITTER:
PROVIDER: S-BSST1244 | biostudies-other |
REPOSITORIES: biostudies-other
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Project description:A bacterial strain Bz02 was isolated from a water sample collected from river Gomti at the Indian city of Lucknow. We characterized the strain using 16S rRNA sequence. Phylogenetic analysis showed that the strain formed a monophyletic clade with members of the genus Comamonas. The closest phylogenetic relative was Comamonas testosteroni with 95% 16S rRNA gene sequence similarity. It is proposed that the identified strain Bz02 be assigned as the type strain of a species of the genus Comamonas (Comamonas sp Bz02) based on 16S rRNA gene sequence search in Ribosomal Database Project, small subunit rRNA and large subunit rRNA databases together with the phylogenetic tree analysis. The sequence is deposted in GenBank with the accession number FJ211417.
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Project description:BackgroundReads assignment to taxonomic units is a key step in microbiome analysis pipelines. To date, accurate taxonomy annotation of 16S reads, particularly at species rank, is still challenging due to the short size of read sequences and differently curated classification databases. The close phylogenetic relationship between species encountered in dairy products, however, makes it crucial to annotate species accurately to achieve sufficient phylogenetic resolution for further downstream ecological studies or for food diagnostics. Curated databases dedicated to the environment of interest are expected to improve the accuracy and resolution of taxonomy annotation.ResultsWe provide a manually curated database composed of 10'290 full-length 16S rRNA gene sequences from prokaryotes tailored for dairy products analysis ( https://github.com/marcomeola/DAIRYdb ). The performance of the DAIRYdb was compared with the universal databases Silva, LTP, RDP and Greengenes. The DAIRYdb significantly outperformed all other databases independently of the classification algorithm by enabling higher accurate taxonomy annotation down to the species rank. The DAIRYdb accurately annotates over 90% of the sequences of either single or paired hypervariable regions automatically. The manually curated DAIRYdb strongly improves taxonomic annotation accuracy for microbiome studies in dairy environments. The DAIRYdb is a practical solution that enables automatization of this key step, thus facilitating the routine application of NGS microbiome analyses for microbial ecology studies and diagnostics in dairy products.
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Project description:Nanopore sequencing is rapidly becoming more popular for use in various microbiota-based applications. Major limitations of current approaches are that they do not enable de novo species identification and that they cannot be used to verify species assignments. This severely limits applicability of the nanopore sequencing technology in taxonomic applications. Here, we demonstrate the possibility of de novo species identification and verification using hexamer frequencies in combination with k-means clustering for nanopore sequencing data. The approach was tested on the human infant gut microbiota of 3-month-old infants. Using the hexamer k-means approach we identified two new low abundant species associated with vaginal delivery. In addition, we confirmed both the vaginal delivery association for two previously identified species and the overall high levels of bifidobacteria. Taxonomic assignments were further verified by mock community analyses. Therefore, we believe our de novo species identification approach will have widespread application in analyzing microbial communities in the future.
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Project description:The genus Leptospira is classified into 13 named species and 4 genomospecies based upon DNA-DNA reassociation studies. Phenotypic tests are unable to distinguish between species of Leptospira, and there is a need for a simplified molecular approach to the identification of leptospires. 16S rRNA gene sequences are potentially useful for species identification of Leptospira, but there are a large number of sequences of various lengths and quality in the public databases. 16S rRNA gene sequences of near full length and bidirectional high redundancy were determined for all type strains of the species of the Leptospiraceae. Three clades were identified within the genus Leptospira, composed of pathogenic species, nonpathogenic species, and another clade of undetermined pathogenicity with intermediate 16S rRNA gene sequence relatedness. All type strains could be identified by 16S rRNA gene sequences, but within both pathogenic and nonpathogenic clades as few as two or three base pairs separated some species. Sequences within the nonpathogenic clade were more similar, and in most cases < or =10 bp distinguished these species. These sequences provide a reference standard for identification of Leptospira species and confirm previously established relationships within the genus. 16S rRNA gene sequencing is a powerful method for identification in the clinical laboratory and offers a simplified approach to the identification of Leptospira species.
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Project description:Species-specific identification of campylobacters is problematic, primarily due to the absence of suitable biochemical assays and the existence of atypical strains. 16S rRNA gene (16S rDNA)-based identification of bacteria offers a possible alternative when phenotypic tests fail. Therefore, we evaluated the reliability of 16S rDNA sequencing for the species-specific identification of campylobacters. Sequence analyses were performed by using almost 94% of the complete 16S rRNA genes of 135 phenotypically characterized Campylobacter strains, including all known taxa of this genus. It was shown that 16S rDNA analysis enables specific identification of most Campylobacter species. The exception was a lack of discrimination among the taxa Campylobacter jejuni and C. coli and atypical C. lari strains, which shared identical or nearly identical 16S rDNA sequences. Subsequently, it was investigated whether partial 16S rDNA sequences are sufficient to determine species identity. Sequence alignments led to the identification of four 16S rDNA regions with high degrees of interspecies variation but with highly conserved sequence patterns within the respective species. A simple protocol based on the analysis of these sequence patterns was developed, which enabled the unambiguous identification of the majority of Campylobacter species. We recommend 16S rDNA sequence analysis as an effective, rapid procedure for the specific identification of campylobacters.
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Project description:Systematic computer alignment of mycoplasmal 16S rRNA sequences allowed the identification of variable regions with both genus- and species-specific sequences. Species-specific sequences of Mycoplasma collis were elucidated by asymmetric amplification and dideoxynucleotide sequencing of variable regions, using primers complementary to conserved regions of 16S rRNA. Primers selected for Mycoplasma pneumoniae, M. hominis, M. fermentans, Ureaplasma urealyticum, M. pulmonis, M. arthritidis, M. neurolyticum, M. muris, and M. collis proved to be species specific in the polymerase chain reaction. The genus-specific primers reacted with all mycoplasmal species investigated as well as with members of the genera Ureaplasma, Spiroplasma, and Acholeplasma. No cross-reaction was observed with members of the closely related genera Streptococcus, Lactobacillus, Bacillus, and Clostridium or with any other microorganism tested. On the basis of the high copy number of rRNA, a highly sensitive polymerase chain reaction assay was developed in which the nucleic acid content equivalent to a single organism could be detected.
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Project description:Although 16S rRNA gene sequence analysis is employed most often for the definitive identification of Nocardia species, alternate molecular methods and polymorphisms in other gene targets have also enabled species determinations. We evaluated a combined Nocardia PCR-based reverse line blot (RLB) hybridization assay based on 16S and 16S-23S rRNA gene spacer region polymorphisms to identify 12 American Type Culture Collection and 123 clinical Nocardia isolates representing 14 species; results were compared with results from 16S rRNA gene sequencing. Thirteen 16S rRNA gene-based (two group-specific and 11 species-specific) and five 16S-23S spacer-targeted (two taxon-specific and three species-specific) probes were utilized. 16S rRNA gene-based probes correctly identified 124 of 135 isolates (sensitivity, 92%) but were unable to identify Nocardia paucivorans strains (n = 10 strains) and a Nocardia asteroides isolate with a novel 16S rRNA gene sequence. Nocardia farcinica and Nocardia cyriacigeorgica strains were identified by the sequential use of an N. farcinica-"negative" probe and a combined N. farcinica/N. cyriacigeorgica probe. The assay specificity was high (99%) except for weak cross-reactivity between the Nocardia brasiliensis probe with the Nocardia thailandica DNA product; however, cross-hybridization with closely related nontarget species may occur. The incorporation of 16S-23S rRNA gene spacer-based probes enabled the identification of all N. paucivorans strains. The overall sensitivity using both probe sets was >99%. Both N. farcinica-specific 16S-23S rRNA gene spacer-directed probes were required to identify all N. farcinica stains by using this probe set. The study demonstrates the utility of a combined PCR/RLB assay for the identification of clinically relevant Nocardia species and its potential for studying subtypes of N. farcinica. Where species assignment is ambiguous or not possible, 16S rRNA gene sequencing is recommended.
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Project description:High-throughput sequencing 16S rRNA gene surveys have enabled new insights into the diversity of soil bacteria, and furthered understanding of the ecological drivers of abundances across landscapes. However, current analytical approaches are of limited use in formalizing syntheses of the ecological attributes of taxa discovered, because derived taxonomic units are typically unique to individual studies and sequence identification databases only characterize taxonomy. To address this, we used sequences obtained from a large nationwide soil survey (GB Countryside Survey, henceforth CS) to create a comprehensive soil specific 16S reference database, with coupled ecological information derived from survey metadata. Specifically, we modeled taxon responses to soil pH at the OTU level using hierarchical logistic regression (HOF) models, to provide information on both the shape of landscape scale pH-abundance responses, and pH optima (pH at which OTU abundance is maximal). We identify that most of the soil OTUs examined exhibited a non-flat relationship with soil pH. Further, the pH optima could not be generalized by broad taxonomy, highlighting the need for tools and databases synthesizing ecological traits at finer taxonomic resolution. We further demonstrate the utility of the database by testing against geographically dispersed query 16S datasets; evaluating efficacy by quantifying matches, and accuracy in predicting pH responses of query sequences from a separate large soil survey. We found that the CS database provided good coverage of dominant taxa; and that the taxa indicating soil pH in a query dataset corresponded with the pH classifications of top matches in the CS database. Furthermore we were able to predict query dataset community structure, using predicted abundances of dominant taxa based on query soil pH data and the HOF models of matched CS database taxa. The database with associated HOF model outputs is released as an online portal for querying single sequences of interest (https://shiny-apps.ceh.ac.uk/ID-TaxER/), and flat files are made available for use in bioinformatic pipelines. The further development of advanced informatics infrastructures incorporating modeled ecological attributes along with new functional genomic information will likely facilitate large scale exploration and prediction of soil microbial functional biodiversity under current and future environmental change scenarios.
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Project description:Comparing bacterial 16S rDNA sequences to GenBank and other large public databases via BLAST often provides results of little use for identification and taxonomic assignment of the organisms of interest. The human microbiome, and in particular the oral microbiome, includes many taxa, and accurate identification of sequence data is essential for studies of these communities. For this purpose, a phylogenetically curated 16S rDNA database of the core oral microbiome, CORE, was developed. The goal was to include a comprehensive and minimally redundant representation of the bacteria that regularly reside in the human oral cavity with computationally robust classification at the level of species and genus. Clades of cultivated and uncultivated taxa were formed based on sequence analyses using multiple criteria, including maximum-likelihood-based topology and bootstrap support, genetic distance, and previous naming. A number of classification inconsistencies for previously named species, especially at the level of genus, were resolved. The performance of the CORE database for identifying clinical sequences was compared to that of three publicly available databases, GenBank nr/nt, RDP and HOMD, using a set of sequencing reads that had not been used in creation of the database. CORE offered improved performance compared to other public databases for identification of human oral bacterial 16S sequences by a number of criteria. In addition, the CORE database and phylogenetic tree provide a framework for measures of community divergence, and the focused size of the database offers advantages of efficiency for BLAST searching of large datasets. The CORE database is available as a searchable interface and for download at http://microbiome.osu.edu.
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Project description:The availability of completely sequenced genomes allow the use of computational techniques to investigate cis-acting sequences controlling transcription regulation associated with groups of functionally related genes. Theoretical analysis was performed to assign functions to regulatory systems. The identification of such sites is relevant for locating a promoter at the 5' boundary of a gene. They also allow the prediction of specific gene-expression pattern and response to disturbances in a known signaling pathway. Here, we describe the identification of composite transcription factor (TF) binding sites over promoter regions in16s-rRNA gene for mycobacterium species strains ICC47, ICC67, ICC43 and CMVL700. It is established that the ribosomal gene comprises of sequences that are conserved during evolution and interspersed with divergent regions. Computational identification of known TF-binding sites was performed using TFSITESCAN tool and ooTFD database. The ICC67, ICC47, ICC43 and CMYL700 strains showed 12, 13, 9 and 15 known TF binding sites, respectively. Comparison between strains suggests 9 known TF predicted binding sites to be conserved among them. These data provide basis for the understanding of promoter regulation in 16s-rRNA.
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