- analysis of human prostate microbiota from patients with prostate cancer. - Background: Prostate cancer (PCa) is the most common malignant neoplasm among men in many countries.. - However, establishing a causal relationship between microbial inflammation and PCa requires a comprehensive analysis of the prostate microbiome. - 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. - 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. - Prostate cancer (PCa) is the most common malignant neoplasm among men in Western industrialized countries and its incidence is rapidly increasing in China. - The aetiologies of the disease remain largely unknown.. - Most of the above findings were obtained by performing traditional nucleic acid amplification tests, such as quantita- tive real-time PCR and amplification of 16S rRNA in. - Full list of author information is available at the end of the article. - 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0. - The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.. - The advent of next generation sequencing has revolutionized the study of human microbiomes. - To date, only two studies have applied massively parallel 16S rRNA sequen- cing for investigating the prostate microbiome [12, 13].. - While these two studies confirmed that the prostate was a non-sterile environment and discovered numerous bacterial organisms that had not been reported in prostate tissue, their limited sample size (<. - Meanwhile, the innate flaws of the 16 s rRNA-based technologies, such as the amplification bias that may distort the bacterial composition, an inability to quantify the actual microbial load, as well as an inability to capture viruses that lack 16S rRNA, also preclude an accur- ate and complete characterization of prostate microbiome.. - The information of patients and specimens is summarized in Additional file 1 [14]. - Briefly, 65 PCa patients were re- cruited in this study, with an average age of years old. - Treatment-naive prostate tumour and matched benign tissues were collected from the radical prostatec- tomy series at Shanghai Changhai Hospital and Fudan University Shanghai Cancer Center. - In order to further avoid false identification of bacterial reads which is mostly manifested as a large number of mapped reads being re- stricted to a few short genomic regions, the coverage uniformity of the bacterial genomes was assessed as de- scribed previously [15].. - We hypothesize that each human cell in the specimens have. - equal amount of human DNA/RNA. - Accordingly, the purpose of normalization in this study was to minimize the bias caused by differences in sequencing coverage across samples and to make the human DNA/RNA com- parable between specimens. - In detail, for the metagen- ome analysis, a scaling normalization was done by multiplying the read counts by a constant so that each specimen has 1 × 10 9 reads that were mapped to the hu- man genome hg19. - For the metatranscriptome analysis, a scaling normalization was done by multiplying the read counts by a constant so that each specimen has 1 × 10 4 reads that were mapped to the housekeeping gene GAPDH (ENSG . - The numbers of raw and normalized reads are listed in Additional file 2.. - Paired comparisons of the read counts between tumour and benign specimens were conducted using Wilcoxon matched-pairs signed rank test. - Correlation analysis of bacterial and host expression Nonparametric Spearman correlation was calculated be- tween the bacterial genes, genera and the host genes as well as the clinical parameters, including Gleason Score and prostate-specific antigen (PSA) level, in terms of their values among the 130 specimens. - The sequences of the bacterial genes were obtained by de novo assembly using Trinity software (v2.4, https://. - Annotation of these transcripts was performed by BLAST search of the assembled nucleotide sequences against NCBI non-redundant protein library. - The patients in the cohorts were split into two sub- groups by the mean expression value of the three small RNA genes, respectively, and then the Kaplan-Meier sur- vival analysis was performed using R package “survival”. - The cohort in this study is comprised of 65 matched PCa tumours and adjacent benign tissue from Chinese patients who underwent radical prostatectomy. - Similarly, most reads derived from metatranscriptome were also of human origin (>. - A total of 47 and 116 bacterial genera were identified in the metagenome and metatranscriptome, respectively, with 43 genera being present in both (Additional file 3).. - 1 and Additional file 3).. - Four viruses were identified in the metagenome and metatranscriptome, all of which belong to dsDNA vi- ruses. - At both metagenomic and metatranscriptomic level, the tumour and benign specimens did not differ from each other in terms of the alpha-diversity of their microbiomes (paired t test, p >. - the NMDS analysis could not separate tumour and benign specimens (Fig. - Neither the total bacterial load nor any specific genus showed significant differential distribution between the tumour and benign specimens at the metagenomic level (Wilcoxon signed-rank test, p >. - 2g, i), and the NMDS analysis could not separate them (Fig. - Correlation of microbiome with host expression profile At either metagenomic or metatranscriptomic level, no significant correlation could be found between the bacterial load (either total or of any specific genus) and any clinical parameters such as Gleason Score and prostate-specific antigen (PSA) level (Spearman correl- ation test, r <. - and the associated expression of these small RNAs are negatively related with metastasis.. - Escherichia, Propionibac- terium, Acinetobacter, and Pseudomonas were found to be abundant in both the metagenome and metatran- scriptome and thus constitute the core of the prostate microbiome in this Chinese population. - Escherichia and Propionibacterium have previously been shown to stimu- late progression of PCa in in vitro experiments but the biological significance for the other bacteria identified in this study remains unclear. - As expected, many of the organisms identified in the prostate tissue have also been detected in urine, semen, and expressed prostatic secretions [18–21]. - This similar microbial com- position provides evidence for the theory of ascending transmitted infection in the male urogenital tract to the seminal vesicles and prostate.. - 1 Bacterial composition of prostate microbiome revealed by metagenomic (a) and metatranscripotomic sequencing (b). - The lines below connect the matched tumour/benign specimens. - Nevertheless, we did not detect sexually transmitted disease-related organisms in this study, such as Neisseria gonorrhoeae, Chlamydia trachomatis, Myco- plasma hominis or Ureaplasma urealyticum. - Thus untreated sexually transmitted infections or viral infec- tions are not expected to account for a significant pro- portion of PCa risk in the general male population, or at least in the investigated cohort.. - The most urgent question in this field is whether the microbiomes from the tumour and benign tissues differ from each other and whether this difference has a causal re- lationship with carcinogenesis. - In this study, we did not find any bacterial species that showed significantly differential distribution between tumours and their matched benign specimens at either DNA or RNA level. - Also we did not find a significant difference between the tumour specimens of low and high Gleason Scores. - These findings suggest that the identified microbiota may comprise the normal flora of the prostate. - Due to the close proximity of the regions. - Panel a-f show comparisons between tumour and benign specimens. - distance between the matched tumour/benign specimens from the same patients. - distance between benign specimens from different patients. - distance between tumour and benign specimens from different patients. - The availability of the host transcriptome allowed us to detect a correlation between expression of human small RNA genes and Pseudomonas genes. - Through pseudouridylation these small RNAs par- ticipate in the regulation of gene expression and therefore affect pre-mRNA splicing, translation fidelity and possibly mRNA stability and decay [28, 29]. - If this association is validated in larger cohorts then the expression profile of the bacterial and small RNA genes may be used as biomarker for active surveillance.. - In this study we employed an integrated metagenomic and metatranscriptomic approach to investigate the pros- tate microbiome of PCa patients. - Bacteria were detected in all specimens but the composition was not significantly different between the matched tumour and adjacent be- nign tissues or between different tumour grades. - Additional file 1: Clinical pathological information of study cohort.. - Additional file 2: The number of raw and normalized reads for each taxonomic unit for both metagenome and metatranscriptome.. - Additional file 3: Comparison of bacterial composition between metagenome and metatranscriptome. - (A) Venn diagram of bacterial genera identified by metagenome, metatranscriptome and the study by Yow et al. - The detailed annotation and nucleotide sequences of these bacterial genes are listed in Additional file 5. - The Kaplan-Meier (KM) plots in panel b categorize the patients into the low and high group based on a median split of expression of the three small RNA genes. - Additional file 4: Prostatic virome. - Additional file 5: Detailed annotation and nucleotide sequences of the 10 bacterial genes that have the correlated expression profile with the eight small RNA genes. - PCa: Prostate cancer. - Yinghao Sun for providing the cohort information used in this study.. - The study was funded by China Scholarship Council (CSC to YF), Terry Fox Foundation (201012TFF to CC), Prostate Cancer Canada Team Grant (T2013 – 01 to CC), National Natural Science Foundation of China (81472397 to SR).. - All data supporting the conclusions of this article are included in this article and its additional files. - The datasets (including whole genome and whole transcriptome sequencing data) generated and/or analysed during the current study are available in the European Genome-phenome Archive (EGAS . - Ye Feng is a member of the editorial board (Associate Editor) of BMC Genomics. - Prostate cancer. - Prostatic inflammation enhances basal-to-luminal differentiation and accelerates initiation of prostate cancer with a basal cell origin. - A mouse model of chronic prostatic inflammation using a human prostate cancer-derived isolate of Propionibacterium acnes. - A human prostatic bacterial isolate alters the prostatic microenvironment and accelerates prostate cancer progression. - Frequency and typing of Propionibacterium acnes in prostate tissue obtained from men with and without prostate cancer. - High prevalence of human cytomegalovirus in prostatic intraepithelial neoplasia and prostatic carcinoma. - The microbiome of the prostate tumor microenvironment. - Yow MA, Tabrizi SN, Severi G, Bolton DM, Pedersen J, Australian Prostate Cancer B, Giles GG, Southey MC. - Characterisation of microbial communities within aggressive prostate cancer tissues. - Whole-genome and Transcriptome Sequencing of Prostate Cancer Identify New Genetic Alterations Driving Disease Progression. - A genomic classifier improves prediction of metastatic disease within 5 years after surgery in node-negative high-risk prostate cancer patients managed by radical prostatectomy without adjuvant therapy. - The microbiome of the urinary tract--a role beyond infection. - Urinary microbiota in patients with prostate cancer and benign prostatic hyperplasia. - Sexual behaviour, STDs and risks for prostate cancer. - Prostate cancer and sexually transmitted diseases: a meta-analysis. - Detection and expression of human BK virus sequences in neoplastic prostate tissues. - Detection of human polyomaviruses and papillomaviruses in prostatic tissue reveals the prostate as a habitat for multiple viral infections. - Integrative genomic profiling of human prostate cancer
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