Dataset Information

Salivary Microbiome in Adenoid Cystic Carcinoma Detected by 16S rRNA Sequencing and Shotgun Metagenomics.

ABSTRACT: Microorganisms are confirmed to be closely related to the occurrence and development of cancers in human beings. However, there has been no published report detailing relationships between the oral microbiota and salivary adenoid cystic carcinoma (SACC). In this study, unstimulated saliva was collected from 13 SACC patients and 10 healthy controls. The microbial diversities, compositions and functions were comprehensively analyzed after 16S rRNA sequencing and whole-genome shotgun metagenomic sequencing. The alpha diversity showed no significant difference between SACC patients and healthy controls, while beta diversity showed a separation trend. The SACC patients showed higher abundances of Streptococcus and Rothia, while Prevotella and Alloprevotella were more abundant in healthy controls. The prevalent KEGG pathways, carbohydrate-active enzymes, antibiotic resistances and virulence factors as well as the biomarkers in SACC were determined by functional gene analysis. Our study preliminarily investigated the salivary microbiome of SACC patients compared with healthy controls and might be the basis for further studies on novel diagnostic and treatment strategies.

SUBMITTER: Jiang Q

PROVIDER: S-EPMC8712576 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Salivary Microbiome in Adenoid Cystic Carcinoma Detected by 16S rRNA Sequencing and Shotgun Metagenomics.

Jiang Qian Q Liu Xing X Yang Qifen Q Chen Liang L Yang Deqin D

Frontiers in cellular and infection microbiology 20211214

Microorganisms are confirmed to be closely related to the occurrence and development of cancers in human beings. However, there has been no published report detailing relationships between the oral microbiota and salivary adenoid cystic carcinoma (SACC). In this study, unstimulated saliva was collected from 13 SACC patients and 10 healthy controls. The microbial diversities, compositions and functions were comprehensively analyzed after 16S rRNA sequencing and whole-genome shotgun metagenomic se ...[more]

PMID: 34970508

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Project description:As a diverse and complex food matrix, the animal food microbiota and repertoire of antimicrobial resistance (AMR) genes remain to be better understood. In this study, 16S rRNA gene amplicon sequencing and shotgun metagenomics were applied to three types of animal food samples (cattle feed, dry dog food, and poultry feed). ZymoBIOMICS mock microbial community was used for workflow optimization including DNA extraction kits and bead-beating conditions. The four DNA extraction kits (AllPrep PowerViral DNA/RNA Kit, DNeasy Blood & Tissue Kit, DNeasy PowerSoil Kit, and ZymoBIOMICS DNA Miniprep Kit) were compared in animal food as well as the use of peptide nucleic acid blockers for 16S rRNA gene amplicon sequencing. Distinct microbial community profiles were generated, which varied by animal food type and DNA extraction kit. Employing peptide nucleic acid blockers prior to 16S rRNA gene amplicon sequencing was comparable with post-sequencing in silico filtering at removing chloroplast and mitochondrial sequences. There was a good agreement between 16S rRNA gene amplicon sequencing and shotgun metagenomics on community profiles in animal feed data sets; however, they differed in taxonomic resolution, with the latter superior at resolving at the species level. Although the overall prevalence of AMR genes was low, resistome analysis of animal feed data sets by shotgun metagenomics revealed 10 AMR gene/protein families, including beta-lactamases, erythromycin/lincomycin/pristinamycin/tylosin, fosfomycin, phenicol, and quinolone. Future expansion of microbiome and resistome profiling in animal food will help better understand the bacterial and AMR gene diversity in these commodities and help guide pathogen control and AMR prevention efforts.IMPORTANCEWith the growing interest and application of metagenomics in understanding the structure/composition and function of diverse microbial communities along the One Health continuum, this study represents one of the first attempts to employ these advanced sequencing technologies to characterize the microbiota and AMR genes in animal food. We unraveled the effects of DNA extraction kits on sample analysis by 16S rRNA gene amplicon sequencing and showed similar efficacies of two strategies at removing chloroplast and mitochondrial reads. The in-depth analysis using shotgun metagenomics shed light on the community compositions and the presence of an array of AMR genes in animal food. This exploration of microbiomes and resistomes in representative animal food samples by both sequencing approaches laid important groundwork for future metagenomic investigations to gain a better understanding of the baseline/core microbiomes and associated AMR functions in these diverse commodities and help guide pathogen control and AMR prevention efforts.

Project description:Dysbiosis of human gut microbiota has been reported in association with ulcerative colitis (UC) in both children and adults using either 16S rRNA gene or shotgun sequencing data. However, these studies used either 16S rRNA or metagenomic shotgun sequencing but not both. We sequenced feces samples from 19 pediatric UC and 23 healthy children ages between 7 to 21 years using both 16S rRNA and metagenomic shotgun sequencing. The samples were analyzed using three different types of data: 16S rRNA genus level abundance, microbial species and pathway abundance profiles. We demonstrated that (a) the alpha diversity of pediatric UC cases is lower than that of healthy controls; (b) the beta diversity within children with UC is more variable than within the healthy children; (c) several microbial families including Akkermansiaceae, Clostridiaceae, Eggerthellaceae, Lachnospiraceae, and Oscillospiraceae, contain species that are depleted in pediatric UC compared to controls; (d) a few associated species unique to pediatric UC, but not adult UC, were also identified, e.g. some species in the Christensenellaceae family were found to be depleted and some species in the Enterobacteriaceae family were found to be enriched in pediatric UC; and (e) both 16S rRNA and shotgun sequencing data can predict pediatric UC status with area under the receiver operating characteristic curve (AUROC) of close to 0.90 based on cross validation. We showed that 16S rRNA data yielded similar results as shotgun data in terms of alpha diversity, beta diversity, and prediction accuracy. Our study demonstrated that pediatric UC subjects harbor a dysbiotic and less diverse gut microbial population with distinct differences from healthy children. We also showed that 16S rRNA data yielded accurate disease prediction results in comparison to shotgun data, which can be more expensive and laborious. These conclusions were confirmed in an independent data set of 7 pediatric UC cases and 8 controls.

Dataset Information

Salivary Microbiome in Adenoid Cystic Carcinoma Detected by 16S rRNA Sequencing and Shotgun Metagenomics.

Publications

Salivary Microbiome in Adenoid Cystic Carcinoma Detected by 16S rRNA Sequencing and Shotgun Metagenomics.

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