Dataset Information

The pan-microbiome profiling system Taxa4Meta identifies clinical dysbiotic features and classifies diarrheal disease.

ABSTRACT: Targeted metagenomic sequencing is an emerging strategy to survey disease-specific microbiome biomarkers for clinical diagnosis and prognosis. However, this approach often yields inconsistent or conflicting results owing to inadequate study power and sequencing bias. We introduce Taxa4Meta, a bioinformatics pipeline explicitly designed to compensate for technical and demographic bias. We designed and validated Taxa4Meta for accurate taxonomic profiling of 16S rRNA amplicon data acquired from different sequencing strategies. Taxa4Meta offers significant potential in identifying clinical dysbiotic features that can reliably predict human disease, validated comprehensively via reanalysis of individual patient 16S data sets. We leveraged the power of Taxa4Meta's pan-microbiome profiling to generate 16S-based classifiers that exhibited excellent utility for stratification of diarrheal patients with Clostridioides difficile infection, irritable bowel syndrome, or inflammatory bowel diseases, which represent common misdiagnoses and pose significant challenges for clinical management. We believe that Taxa4Meta represents a new "best practices" approach to individual microbiome surveys that can be used to define gut dysbiosis at a population-scale level.

SUBMITTER: Wu Q

PROVIDER: S-EPMC10786686 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The pan-microbiome profiling system Taxa4Meta identifies clinical dysbiotic features and classifies diarrheal disease.

Wu Qinglong Q Badu Shyam S So Sik Yu SY Treangen Todd J TJ Savidge Tor C TC

The Journal of clinical investigation 20240116 2

Targeted metagenomic sequencing is an emerging strategy to survey disease-specific microbiome biomarkers for clinical diagnosis and prognosis. However, this approach often yields inconsistent or conflicting results owing to inadequate study power and sequencing bias. We introduce Taxa4Meta, a bioinformatics pipeline explicitly designed to compensate for technical and demographic bias. We designed and validated Taxa4Meta for accurate taxonomic profiling of 16S rRNA amplicon data acquired from dif ...[more]

PMID: 37962956

Similar Datasets

Project description:IntroductionDigestive system pan-cancer is one of the lethal malignant tumors, which have the propensity for poor prognosis and difficult treatment. Endoplasmic reticulum (ER) stress has served as a pivotal role in the progression of the tumor, while the implication of ER stress on digestive system pan-cancers still needs elucidation, especially from the perspective of clinical outcome and that of genomic features.MethodsFirst, Among the ER STRESS factors from the REACTOME_UNFOLDED_PROTEIN_RESPONSE_UPR (113 genes) and HALLMARK_UNFOLDED_PROTEIN_RESPONSE (92 genes) terms, 153 ER STRESS regulators were identified after removing replicates. The somatic mutation data and copy number variation data of gastrointestinal pan-cancer were downloaded from The Cancer Genome Atlas (TCGA) database. Then, we explored the clinical outcome and genetic mutation of ER stress-related differentially expressed genes (DEGs) by multiple bioinformatics analysis. Subsequently, we analyzed the Spearman correlation between the drug sensitivity of 179 gastrointestinal anticancer drugs and the transcriptional expression of 153 ER stress factors in 769 cancer cell lines of the GDSC2 cohort. Next, ssGSEA method was used to quantify the immune cell infiltration scores in the tumor microenvironment, and Spearman correlation was used to calculate the correlation between ER stress scores and immune cell infiltration. Finally, we analyzed the cellular origin of ER stress factor dysregulation.ResultsWe analyzed the genomic changes and clinical outcomes of ER stress factors in different tumors of gastrointestinal pan-cancer. Endoplasmic reticulum stress factor (ER) in digestive tract tumors showed high SNV mutation frequency, less methylation dysregulation and was associated with multiple oncogenic pathways. Endoplasmic reticulum stress factor (ER) is a risk factor for many cancers, but the effect on overall survival in rectal adenocarcinoma is opposite to that in other gastrointestinal tumors. And ER stress factors are highly correlated with drugs that target important pathways.DiscussionBased on the clinical prognosis and genomic analysis of ER stress-related factors in patients with gastrointestinal pan-cancer, this study provides a new direction for further research on gastrointestinal pan-cancer.

Project description:The vaginal microbiome plays a critical role in determining the progression of female genital tract infections; however, little is known about the vaginal microbiota of Indian women. We aimed to investigate the vaginal microbial architecture of women with asymptomatic bacterial vaginosis (BV) (n=20) and normal microbiota (n=19). Microbial diversity was analyzed in vaginal swabs from regularly menstruating women (18-45yrs) by 16S rRNA V3-V4 amplicon (MiSeq Illumina) sequencing. Rarefaction analysis showed a higher number of species in normal flora compared to BV. Alpha diversity as measured by Pielou's evenness revealed microbial diversity was significantly greater in BV samples than normal microbiota (p= 0.0165). Beta diversity comparison using UniFrac metrics indicated distinct microbial communities clustering between normal and BV flora. Firmicutes were the major phyla observed in vaginal specimens of normal microbiota whereas Actinobacteria, Fusobacteria, Bacteroidetes were significantly abundant in BV samples. Notably, the relative abundance of Lactobacillus was significantly high in normal microbiota. Conversely Gardnerella, Sneathia, Prevotella, Atopobium, Ureaplasma, Dialister significantly dominated dysbiotic microbiota. Relative frequency of Lactobacillus decreased significantly in BV (6%) as compared to normal microbiota (35.2%). L. fermentum, L. gasseri, L. iners, L. jensenii, L. mucosae, L. ruminis, L. salivarius, L. coleohominis was more exclusively present in normal microbiota. L. iners was detected from both the groups with a relative frequency of 50.4% and 17.2% in normal and BV microbiota respectively. Lefse analysis indicated Atopobium vaginae, Sneathia amnii, Mycoplasma hominis Prevotella disiens in the vaginal microbiota as a biomarker for dysbiosis and L. jensenii as a biomarker of a healthy microbiota. Firmicutes were negatively correlated to Tenericutes, Actinobacteria, Bacteroidetes, and Fusobacteria. Proteobacteria positively correlated to Tenericutes, and Bacteroidetes were shown to be positively correlated to Fusobacteria. Predicted functional analysis indicated differences in the functional profiles between BV and normal microbiota. Normal microbiota utilized pathways essential for phosphatidylglycerol biosynthesis I & II, peptidoglycan biosynthesis, geranylgeranyl diphosphate biosynthesis I, mevalonate pathway, CoA biosynthesis pathway I and pyrimidine nucleotide salvage; whereas BV bacteria had characteristic aromatic amino acid biosynthesis, pentose phosphate pathway, carbohydrate degradation. In conclusion, women with asymptomatic BV have vaginal microbiota significantly different than women with normal microbiota. Furthermore, the study provides insights into the vaginal microbial structure of Indian women that will enable us to explore the prospective candidates for restoring the vaginal microbiota.

Dataset Information

The pan-microbiome profiling system Taxa4Meta identifies clinical dysbiotic features and classifies diarrheal disease.

Publications

The pan-microbiome profiling system Taxa4Meta identifies clinical dysbiotic features and classifies diarrheal disease.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets