Gut Microbiome 16S rRNA Gene Amplicon Taxonomic Profiling of Hospitalized Moroccan COVID-19 Patients.
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ABSTRACT:
SUBMITTER: Sehli S
PROVIDER: S-EPMC9302072 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Demands for faster and more accurate methods to analyze microbial communities from natural and clinical samples have been increasing in the medical and healthcare industry. Recent advances in next-generation sequencing technologies have facilitated the elucidation of the microbial community composition with higher accuracy and greater throughput than was previously achievable; however, the short sequencing reads often limit the microbial composition analysis at the species level due to the high similarity of 16S rRNA amplicon sequences. To overcome this limitation, we used the nanopore sequencing platform to sequence full-length 16S rRNA amplicon libraries prepared from the mouse gut microbiota. A comparison of the nanopore and short-read sequencing data showed that there were no significant differences in major taxonomic units (89%) except one phylotype and three taxonomic units. Moreover, both sequencing data were highly similar at all taxonomic resolutions except the species level. At the species level, nanopore sequencing allowed identification of more species than short-read sequencing, facilitating the accurate classification of the bacterial community composition. Therefore, this method of full-length 16S rRNA amplicon sequencing will be useful for rapid, accurate and efficient detection of microbial diversity in various biological and clinical samples.
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Project description:The 16S rRNA gene works as a rapid and effective marker for the identification of microorganisms in complex communities; hence, a huge number of microbiomes have been surveyed by 16S amplicon-based sequencing. The resolution of the 16S rRNA gene is always considered only at the genus level; however, it has not been verified on a wide range of microbes yet. To fully explore the ability and potential of the 16S rRNA gene in microbial profiling, here, we propose Qscore, a comprehensive method to evaluate the performance of amplicons by integrating the amplification rate, multitier taxonomic annotation, sequence type, and length. Our in silico assessment by a "global view" of 35,889 microbe species across multiple reference databases summarizes the optimal sequencing strategy for 16S short reads. On the other hand, since microbes are unevenly distributed according to their habitats, we also provide the recommended configuration for 16 typical ecosystems based on the Qscores of 157,390 microbiomes in the Microbiome Search Engine (MSE). Detailed data simulation further proves that the 16S amplicons produced with Qscore-suggested parameters exhibit high precision in microbiome profiling, which is close to that of shotgun metagenomes under CAMI metrics. Therefore, by reconsidering the precision of 16S-based microbiome profiling, our work not only enables the high-quality reusability of massive sequence legacy that has already been produced but is also significant for guiding microbiome studies in the future. We have implemented the Qscore as an online service at http://qscore.single-cell.cn to parse the recommended sequencing strategy for specific habitats or expected microbial structures. IMPORTANCE 16S rRNA has long been used as a biomarker to identify distinct microbes from complex communities. However, due to the influence of the amplification region, sequencing type, sequence processing, and reference database, the accuracy of 16S rRNA has not been fully verified on a global range. More importantly, the microbial composition of different habitats varies greatly, and it is necessary to adopt different strategies according to the corresponding target microbes to achieve optimal analytical performance. Here, we developed Qscore, which evaluates the comprehensive performance of 16S amplicons from multiple perspectives, thus providing the best sequencing strategies for common ecological environments by using big data.
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Project description:Next generation amplicon sequencing has created a plethora of data from human microbiomes. The accessibility to this scientific data and its corresponding metadata is important for its reuse, to allow for new discoveries, verification of published results, and serving as path for reproducibility. Dietary fiber consumption has been associated with a variety of health benefits that are thought to be mediated by gut microbiota. To enable direct comparisons of the response of the gut microbiome to fiber, we obtained 16S rRNA sequencing data and its corresponding metadata from 11 fiber intervention studies for a total of 2,368 samples. We provide curated and pre-processed genetic data and common metadata for comparison across the different studies.
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Project description:The "Landscape Of Gut Microbiome - Pan-India Exploration", or LogMPIE study, is the first large-scale, nationwide record of the Indian gut microbiome. The primary objective of the study was to identify and map the Indian gut microbiome baseline. This observational study was conducted across 14 geographical locations in India. Enrolled subjects were uniformly distributed across geographies (north, east, west and south) and body mass index (obese and non-obese). Furthermore, factors influencing the microbiome, such as age and physical activity, were also considered in the study design. The LogMPIE study recorded data from 1004 eligible subjects and reported 993 unique microorganisms across the Indian microbiome diaspora. The data not only map the Indian gut microbiome baseline but also function as a useful resource to study, analyse and identify signatures characterizing the physiological dispositions of the subjects. Furthermore, they provide insight into the unique features describing the Indian microbiome. The data are open and may be accessed from the European Nucleotide Archive (ENA) portal of the European Bioinformatics Institute (https://www.ebi.ac.uk/ena/data/view/PRJEB25642).
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Project description:Most experiments studying bacterial microbiomes rely on the PCR amplification of all or part of the gene for the 16S rRNA subunit, which serves as a biomarker for identifying and quantifying the various taxa present in a microbiome sample. Several computational methods exist for analyzing 16S amplicon sequencing. However, the most-used bioinformatics tools cannot produce high quality genus-level or species-level taxonomic calls and may underestimate the potential accuracy of these calls. We used 16S sequencing data from mock bacterial communities to evaluate the sensitivity and specificity of several bioinformatics pipelines and genomic reference libraries used for microbiome analyses, concentrating on measuring the accuracy of species-level taxonomic assignments of 16S amplicon reads. We evaluated the tools DADA2, QIIME 2, Mothur, PathoScope 2, and Kraken 2 in conjunction with reference libraries from Greengenes, SILVA, Kraken 2, and RefSeq. Profiling tools were compared using publicly available mock community data from several sources, comprising 136 samples with varied species richness and evenness, several different amplified regions within the 16S rRNA gene, and both DNA spike-ins and cDNA from collections of plated cells. PathoScope 2 and Kraken 2, both tools designed for whole-genome metagenomics, outperformed DADA2, QIIME 2 using the DADA2 plugin, and Mothur, which are theoretically specialized for 16S analyses. Evaluations of reference libraries identified the SILVA and RefSeq/Kraken 2 Standard libraries as superior in accuracy compared to Greengenes. These findings support PathoScope and Kraken 2 as fully capable, competitive options for genus- and species-level 16S amplicon sequencing data analysis, whole genome sequencing, and metagenomics data tools.
| S-EPMC10460424 | biostudies-literature
Project description:Fecal samples are frequently used to characterize bacterial populations of the gastrointestinal tract. A protocol is provided to profile gut bacterial populations using rodent fecal samples. We describe the optimal procedures for collecting rodent fecal samples, isolating genomic DNA, 16S rRNA gene V4 region sequencing, and bioinformatic analyses. This protocol includes detailed instructions and example outputs to ensure accurate, reproducible results and data visualization. Comprehensive troubleshooting and limitation sections address technical and statistical issues that may arise when profiling microbiota. For complete details on the use and execution of this protocol, please refer to Gubert et al. (2022).
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Project description:Iron metabolism is pivotal for cell fitness in the mammalian host. However, its role in group 3 innate lymphoid cells (ILC3s) is unknown. Here we show that transferrin receptor CD71-mediated iron metabolism cell-intrinsically controls ILC3 maintenance, cytokine production and host protection against Citrobacter rodentium infection, and metabolically affects mitochondrial respiration by switching of oxidative phosphorylation toward glycolysis. Iron deprivation or Tfrc deficiency reduces the expression and/or activity of the aryl hydrocarbon receptor (Ahr), a ligand-dependent transcription factor and a key ILC3 regulator. Furthermore, consistent with its role in generation of Ahr ligand, microbiome exerts a negative impact on CD71 expression in an Ahr-dependent manner. Genetic ablation or activation of Ahr in ILC3s leads to CD71 upregulation or downregulation, respectively, suggesting an active suppression of CD71 by Ahr. Iron overload partially restores defective ILC3 compartment in the small intestine of Ahr-deficient mice, representing compensatory action of CD71 upregulation during Ahr deficiency. Mechanistically, Ahr directly binds to the promoter region of the Tfrc locus to inhibit Tfrc transcription. These data collectively demonstrate an under-appreciated role of the Ahr-CD71-iron axis in regulation of ILC3 maintenance and function.
2023-07-10 | GSE222620 | GEO
Project description:ObjectiveThis study aimed to explore the correlation between microbiota dysbiosis and hypothyroidism in early pregnancy by 16S rRNA amplicon sequencing combined with metagenomic sequencing.MethodsSixty pregnant women (30 with hypothyroidism and 30 normal controls) were recruited for 16S rRNA amplicon sequencing, and 6 patients from each group were randomly selected for metagenomic sequencing to assess the gut microbiome profile.ResultsThe 16S rRNA results showed that beta-diversity in the hypothyroidism group was decreased. The relative abundances of the Prevotella and Paraprevotella genera increased in the hypothyroidism group, and Blautia predominated in the controls. The metagenomics results revealed that Prevotella_stercorea_CAG_629, Prevotella_hominis, Prevotella_sp_AM34_19LB, etc. were enriched in the hypothyroidism group at the species level. Functional analysis revealed that the pyridoxal 5'-phosphate synthase pdxT subunit module was decreased, and the short-chain fatty acid (SCFA) transporter and phospholipase/carboxylesterase modules were strongly enriched in the hypothyroidism group. Hypothyroidism patients had increased C-reactive protein (CRP), interleukin-2 (IL-2), IL-4, IL-10, and tumor necrosis factor (TNF)-α levels. The pyridoxal 5'-phosphate synthase pdxT subunit, the SCFA transporter, and the phospholipase/carboxylesterase module were associated with different Prevotella species.ConclusionIn early pregnancy, women with hypothyroidism exhibit microbiota dysbiosis, and Prevotella may affect the metabolism of glutamate, SCFA, and phospholipases, which could be involved in the development of hypothyroidism during pregnancy.
| S-EPMC11341541 | biostudies-literature