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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.
Pubmed ID: 34970508 RIS Download
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An Operational Taxonomic Unit (OTU) clustering software for 16S and other marker genes. Highly accurate OTU sequences and improved diversity measures.
View all literature mentionsA database which provides ribosome related data services to the scientific community, including online data analysis, rRNA derived phylogenetic trees, and aligned and annotated rRNA sequences. It specifically contains information on quality-controlled, aligned and annotated bacterial and archaean 16S rRNA sequences, fungal 28S rRNA sequences, and a suite of analysis tools for the scientific community. Most of the RDP tools are now available as open source packages for users to incorporate in their local workflow.
View all literature mentionsDatabase that describes the families of structurally-related catalytic and carbohydrate-binding modules (or functional domains) of enzymes that degrade, modify, or create glycosidic bonds. This specialist database is dedicated to the display and analysis of genomic, structural and biochemical information on Carbohydrate-Active Enzymes (CAZymes). CAZy data are accessible either by browsing sequence-based families or by browsing the content of genomes in carbohydrate-active enzymes. New genomes are added regularly shortly after they appear in the daily releases of GenBank. New families are created based on published evidence for the activity of at least one member of the family and all families are regularly updated, both in content and in description. An original aspect of the CAZy database is its attempt to cover all carbohydrate-active enzymes across organisms and across subfields of glycosciences. One can search for CAZY Family pages using the Protein Accession (Genpept Accession, Uniprot Accession or PDB ID), Cazy family name or EC number. In addition, genomes can be searched using the NCBI TaxID. This search can be complemented by Google-based searches on the CAZy site.
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