Metagenomic and metatranscriptomic analysis of human prostate microbiota from patients with prostate cancer.

Abstract

BACKGROUND:

Prostate cancer (PCa) is the most common malignant neoplasm among men in many countries. Since most precancerous and cancerous tissues show signs of inflammation, chronic bacterial prostatitis has been hypothesized to be a possible etiology. However, establishing a causal relationship between microbial inflammation and PCa requires a comprehensive analysis of the prostate microbiome. The aim of this study was to characterize the microbiome in prostate tissue of PCa patients and investigate its association with tumour clinical characteristics as well as host expression profiles.

RESULTS:

The metagenome and metatranscriptome of tumour and the adjacent benign tissues were assessed in 65 Chinese radical prostatectomy specimens. Escherichia, Propionibacterium, Acinetobacter and Pseudomonas were abundant in both metagenome and metatranscriptome, thus constituting the core of the prostate microbiome. The biodiversity of the microbiomes could not be differentiated between the matched tumour/benign specimens or between the tumour specimens of low and high Gleason Scores. The expression profile of ten Pseudomonas genes was strongly correlated with that of eight host small RNA genes; three of the RNA genes may negatively associate with metastasis. Few viruses could be identified from the prostate microbiomes.

CONCLUSIONS:

This is the first study of the human prostate microbiome employing an integrated metagenomics and metatranscriptomics approach. In this Chinese cohort, both metagenome and metatranscriptome analyses showed a non-sterile microenvironment in the prostate of PCa patients, but we did not find links between the microbiome and local progression of PCa. However, the correlated expression of Pseudomonas genes and human small RNA genes may provide tantalizing preliminary evidence that Pseudomonas infection may impede metastasis.

• Authors: Ye Feng, Varune Rohan Ramnarine, Robert Bell, Stanislav Volik, Elai Davicioni, Vanessa M Hayes, Shancheng Ren, Colin C Collins
• Journal: BMC genomics (BMC Genomics) Vol. 20 Issue 1 Pg. 146 (Feb 18 2019) ISSN: 1471-2164 [Electronic] England
• PMID: 30777011 (Publication Type: Journal Article)

Topics

• Aged
• Biodiversity
• Computational Biology (methods)
• Humans
• Kaplan-Meier Estimate
• Male
• Metagenome
• Metagenomics (methods)
• Microbiota
• Middle Aged
• Prostate (microbiology, pathology)
• Prostatic Neoplasms (etiology, metabolism, mortality, pathology)