Microbial gene expression analysis of healthy and cancerous esophagus uncovers bacterial biomarkers of clinical outcomes.
Journal
ISME communications
ISSN: 2730-6151
Titre abrégé: ISME Commun
Pays: England
ID NLM: 9918205372406676
Informations de publication
Date de publication:
05 Dec 2023
05 Dec 2023
Historique:
received:
20
07
2023
accepted:
21
11
2023
revised:
16
11
2023
medline:
5
12
2023
pubmed:
5
12
2023
entrez:
4
12
2023
Statut:
epublish
Résumé
Local microbiome shifts are implicated in the development and progression of gastrointestinal cancers, and in particular, esophageal carcinoma (ESCA), which is among the most aggressive malignancies. Short-read RNA sequencing (RNAseq) is currently the leading technology to study gene expression changes in cancer. However, using RNAseq to study microbial gene expression is challenging. Here, we establish a new tool to efficiently detect viral and bacterial expression in human tissues through RNAseq. This approach employs a neural network to predict reads of likely microbial origin, which are targeted for assembly into longer contigs, improving identification of microbial species and genes. This approach is applied to perform a systematic comparison of bacterial expression in ESCA and healthy esophagi. We uncover bacterial genera that are over or underabundant in ESCA vs healthy esophagi both before and after correction for possible covariates, including patient metadata. However, we find that bacterial taxonomies are not significantly associated with clinical outcomes. Strikingly, in contrast, dozens of microbial proteins were significantly associated with poor patient outcomes and in particular, proteins that perform mitochondrial functions and iron-sulfur coordination. We further demonstrate associations between these microbial proteins and dysregulated host pathways in ESCA patients. Overall, these results suggest possible influences of bacteria on the development of ESCA and uncover new prognostic biomarkers based on microbial genes. In addition, this study provides a framework for the analysis of other human malignancies whose development may be driven by pathogens.
Identifiants
pubmed: 38049632
doi: 10.1038/s43705-023-00338-1
pii: 10.1038/s43705-023-00338-1
pmc: PMC10696091
doi:
Types de publication
Journal Article
Langues
eng
Pagination
128Subventions
Organisme : NIA NIH HHS
ID : RF1 AG063481
Pays : United States
Informations de copyright
© 2023. The Author(s).
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