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. 2019 Aug 27;79(15):1731–1738. doi: 10.1002/pros.23897

Metagenomic analysis reveals a rich bacterial content in high‐risk prostate tumors from African men

Ye Feng 1,2,[Link], Weerachai Jaratlerdsiri 3,[Link], Sean M Patrick 4, Ruth J Lyons 3, Anne‐Maree Haynes 3, Colin C Collins 5,6, Phillip D Stricker 7, MS Riana Bornman 4, Vanessa M Hayes 3,4,8,9,
PMCID: PMC6790596  PMID: 31454437

Abstract

Background

Inflammation is a hallmark of prostate cancer (PCa), yet no pathogenic agent has been identified. Men from Africa are at increased risk for both aggressive prostate disease and infection. We hypothesize that pathogenic microbes may be contributing, at least in part, to high‐risk PCa presentation within Africa and in turn the observed ethnic disparity.

Methods

Here we reveal through metagenomic analysis of host‐derived whole‐genome sequencing data, the microbial content within prostate tumor tissue from 22 men. What is unique about this study is that patients were separated by ethnicity, African vs European, and environments, Africa vs Australia.

Results

We identified 23 common bacterial genera between the African, Australian, and Chinese prostate tumor samples, while nonbacterial microbes were notably absent. While the most abundant genera across all samples included: Escherichia, Propionibacterium, and Pseudomonas, the core prostate tumor microbiota was enriched for Proteobacteria. We observed a significant increase in the richness of the bacterial communities within the African vs Australian samples (t = 4.6‐5.5; P = .0004‐.001), largely driven by eight predominant genera. Considering core human gut microbiota, African prostate tissue samples appear enriched for Escherichia and Acidovorax, with an abundance of Eubacterium associated with host tumor hypermutation.

Conclusions

Our study provides suggestive evidence for the presence of a core, bacteria‐rich, prostate microbiome. While unable to exclude for fecal contamination, the observed increased bacterial content and richness within the African vs non‐African samples, together with elevated tumor mutational burden, suggests the possibility that bacterially‐driven oncogenic transformation within the prostate microenvironment may be contributing to aggressive disease presentation in Africa.

Keywords: Africa, bacterial burden, ethnic disparity, microbiome, prostate cancer, prostate microenvironment, tumor mutational burden

1. INTRODUCTION

Prostate cancer (PCa) is the most common male malignancy and the third cause of cancer‐related death in men in the United States, with disproportionate incidence and mortality in African Americans.1 In the Southern African Prostate Cancer Study (SAPCS), we showed black South African men to present with the significantly increased high‐risk disease compared with age‐matched African Americans.2 Besides genetic and socioeconomic contributions, a protective association with increased sexual activity and an inverse association with erectile dysfunction, have suggested a possible role for pathogen shedding in reducing PCa risk.3 Additional epidemiological evidence for a pathogenic link to PCa risk, as reviewed, includes: prostatitis (inflammation of the prostate), sexually transmitted infections, and history of acne.4 With the highest rate of infectious diseases and infection‐related cancers,5 our hypothesis is that the elevated high‐risk PCa presentation observed within men from Africa, at least in part, be contributed by a microbial pathogenic agent(s).

Next‐generation sequencing (NGS) has allowed for an unbiased assessment of the human microbiome, particularly shifts in microbial content (dysbiosis) associated with the disease. While the microbial content of the human gut, skin, oral cavity, vagina, and, more recently, the urinary tract have received much attention, the prostate has largely been overlooked.6 Before the application of NGS approaches, the most promising candidate to emerge from culture‐based and amplification studies included Propionibacterium, which was further shown to enhance cell proliferation both in vivo and in vitro.7 Two studies using ultradeep massively parallel 16S ribosomal RNA sequencing provided evidence for an abundance of bacteria within the human prostate.8, 9 Focusing on Australian men of European ancestry, core tissue was formalin‐fixed and paraffin‐embedded or snap‐frozen after surgery, with a range of pathologies and tissue types (tumor, peritumor, or nontumor; 16 patients), and some were of aggressive disease (Gleason score ≥8; 10 patients). Key observations included significant enrichment for Actinobacteria and the possible correlation between microbial dysbiosis and pathophysiology,8 and an abundance of Enterobacteriaceae with additional low levels of endogenous retroviruses detected using additional total RNA massively parallel sequencing.9 More recently, we used unbiased shotgun sequencing of fresh prostate tumor and matched adjacent benign tissue from 65 Chinese men having undergone prostate surgery, identifying 47 bacterial genera, and confirming previous reports of enrichment for Propionibacterium and Actinobacteria.10 No microbial differentiation between patient‐matched tumor‐benign tissue was observed—most likely a consequence of field effect. Together with a recent review that includes genitourinary microbiota detected in urine, seminal fluid and expressed prostatic secretions, and associated prostatic disease,11 these studies provide tantalizing evidence for the role of bacterial infection in PCa pathogenesis.

2. PATIENTS AND METHODS

2.1. Patients and ethics

African patients were recruited at the time of diagnosis from the University of Pretoria's Steve Biko Academic Hospital in South Africa (n = 6), while Australian patients (all European descent) were recruited at the time of surgery from St Vincent's Hospital in New South Wales (n = 16). Histopathological Gleason score was used to classify tumors as high risk (Gleason score ≥8; all African and nine Australian patients) or low risk (Gleason score = 6; seven Australian patients) (see Table 1 for clinical characteristics). African patients consented as part of the previously described SAPCS.2

Table 1.

Sequencing statistics and bacterial content for 22 African and Australian patients

UP2003 UP2039 UP2099 UP2113 UP2116 UP2133 5545 13104 13179 10651 15917 5684 16599 12543 5287 5958 10738 6359 5656 11452 5060 5902
Ethnicity/Country African African African African African African Eur/Aus Eur/Aus Eur/Aus Eur/Aus Eur/Aus Eur/Aus Eur/Aus Eur/Aus Eur/Aus Eur/Aus Eur/Aus Eur/Aus Eur/Aus Eur/Aus Eur/Aus Eur/Aus
HR/LRPCa HRPCa HRPCa HRPCa HRPCa HRPCa HRPCa HRPCa HRPCa HRPCa HRPCa HRPCa HRPCa HRPCa HRPCa HRPCa LRPCa LRPCa LRPCa LRPCa LRPCa LRPCa LRPCa
Clinical characteristics and sequencing statistics
Gleason score 9 8 8 8 10 9 8 9 9 9 9 9 9 9 9 6 6 6 6 6 6 6
Tumor purity 42% 68% 78% 41% 44% 43% 79% 41% 52% 75% 42% 75% 68% 52% 55% 56% 84% 52% 33% 56% 53% 70%
hg38 coverage 86× 75× 82× 86× 87× 81× 67× 76× 85× 91× 86× 71× 89× 77× 80× 68× 80× 79× 86× 68× 74× 74×
TMB (Mut/Mb) 4.6 3.3 3.4 55 3 4.7 a 2.2 1.9 2.2 2.6 2.1 1.9 2.8 1.7 1.8 1.7 1.6 1.8 3 1.1 1.7 1.3
Unmapped reads b 1.16% 0.73% 1.07% 1.04% 0.74% 1.08% 0.92% 1.26% 1.17% 0.78% 1.31% 0.97% 0.82% 0.80% 0.90% 0.90% 0.71% 0.96% 0.64% 1.57% 1% 0.65%
Bacterial content and load (no reads c )
Total no of genera 23 39 18 55 24 47 10 17 7 5 21 13 7 16 10 9 18 17 10 22 18 7
Bacteroides 32.9 5267.7 91 4339.7 221.2 8085.8 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
Escherichia 481.9 310.6 314.6 982.8 458 2236.9 281.6 433.8 391.1 167.3 310.1 244.5 199.8 148.3 200.7 298.8 259 297.7 120.5 530.8 338 107.6
Eubacterium 8.8 16.9 10.4 3862.6 5.9 892.1 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
Acidovorax 329.3 279.3 110.7 1569 193.7 183.8 NA 5.5 NA NA NA 9.1 NA NA NA NA 18.3 13.2 NA 8.9 NA 1.3
Propionibacterium 35.7 57.7 88.1 84.4 25.4 65.5 38 158.5 120.8 145.1 441.9 87.4 57.8 80.2 31.4 62.9 51.9 376.3 90.4 194 63.8 50
Acinetobacter 172.9 94.1 33.6 60.7 17.8 7 NA 6.1 5 NA 7.1 NA NA NA 5.8 6.9 10 8.4 NA 1099.9 33.5 NA
Pseudomonas 66.4 45.8 40 53.5 49.1 58 44.4 79.9 41.4 25.3 31.2 26.1 16.8 29.8 26.2 71.2 187 171.7 134.2 225.4 24.6 24
Total burden 1419.2 6841 889.4 13 605.7 1294.6 13 404.8 487.9 948 653.7 390.4 1232.2 539.3 347.5 590 418.2 595.5 827.8 1465 494.1 2366.4 717.1 281

Abbreviations: Aus, Australian; Eur, European; HRPCa, high‐risk prostate cancer; LRPCa, low‐risk prostate cancer; NA, not applicable; TMB, tumor mutational burden.

a

Hyperduplicated tumor genome.

b

Percentage of reads not mapping to the human reference genome (hg38).

c

Normalized number of reads.

South African patients consented understudy approval granted by the University of Pretoria Human Research Ethics Committee (HREC #43/2010) including US Federal‐wide assurance (FWA00002567 and IRB00002235 IORG0001762). Biospecimens were shipped under the Republic of South Africa Department of Health Export Permit, in accordance with the National Health Act 2003 (J1/2/4/2 #1/12) and interinstitutional Material Transfer Agreement to the Garvan Institute of Medical Research in Australia. Australian patients consented under the St Vincent's Hospital HREC approval (#SVH/12/231). Data generation and analysis were performed in accordance with site‐specific approval granted by St Vincent's Hospital HREC (#SVH 15/227), with Garvan Governance approval (#GHRP 1522).

2.2. Sample processing

Fresh prostate tissue was obtained either at routine diagnostic sampling, via a condom sheathed needle transrectal core biopsy (African) or immediately post radical prostatectomy, via core biopsy needle sampling under sterile conditions (Australian). It should be noted that all patients would have received antibiotics, specifically Ciproxin before biopsy (African) or Ceftriaxone during surgery (Australian). All samples were immediately placed in a droplet of optimal cutting temperature cryopreservation medium on sterilized foil, the foil folded and placed in a histology cassette before being snap‐frozen. All samples were stored at −80°C. African samples were shipped on dry ice to Australia. Total DNA was extracted for all samples within a single laboratory using Qiagen columns (Qiagen Pty Ltd, Doncaster, VIC). DNA was stored at 4°C in elution buffer (AE: 10 mM Tris‐Cl, 0.5 mM EDTA, at pH 9.0) before sequencing.

2.3. Whole‐genome sequencing

All samples underwent whole‐genome 2 × 150 cycle paired‐end sequencing on an Illumina HiSeq X Ten instrument (Kinghorn Center for Clinical Genomics [KCCG], Garvan Institute) and were sequenced at the same time to eliminate potential for batch effects. On average, over 80X coverage per prostate tissue specimen was generated, as previously described.12 Reads were adapter‐trimmed and filtered to remove low‐quality bases (<Q15), short reads (<70 bp), and missing read pairs, before aligned to the hg38 reference using bwa‐mem v0.7.12.13 While mapped reads were used to establish the host genomic landscape of the African vs Australian‐derived tumors,12 unmapped data was used for further microbiome analyses.

2.4. Host tumor mutational burden

Tumor mutational burden (TMB), that is, the total number per megabase (Mb) of single‐nucleotide variants and small insertions and deletions (indels) acquired during tumorigenesis, was calculated against matched blood, as previously described by Jaratlerdsiri12 (see genomic data summarized in Table 1). We report a 1.2‐fold increase in TMB between the low‐ and high‐risk Australian‐derived tumors and a 1.8‐fold increase in TMB between the African‐ and Australian‐derived high‐risk tumors, excluding for the single hypermutated African tumor UP2113 (55 somatic mutations/Mb). A second African‐derived tumor (UP2133) was uniquely hyperduplicated with 234 tandem duplications.

2.5. Microbial and statistical analysis

Reads unmapped to the human reference, were mapped by BWA to National Center for Biotechnology Information (NCBI) full set of microbial reference genomes, using a minimum cut‐off of five mapped reads per sample. RepeatMasker was used to identify repeat and low complexity reads. The coverage uniformity of the bacterial genomes was assessed as described previously.14 The relative abundance of the identified microorganisms was measured based on their normalized read counts.

The indices of alpha‐ and beta‐diversity were calculated using the QIIME package. Comparison of these indices between groups was conducted using the Student t test. The nonmetric multidimensional scaling (NMDS) analysis was performed using the vegan package in R software.15

3. RESULTS

3.1. Prostate tissue and tumor microbiome

Unmapped human sequences derived from cancerous prostate tissue were retrieved and mapped against microbial reference genomes. While read counts for viruses were negligible and unlikely significant, we observed 281 to 49 809 bacterial reads per 109 human genome‐mapped reads (Table 1). No other nonbacterial/nonviral reads were identified. Using a minimum cut‐off of five mapped reads per sample, we identified a total of 75 bacterial genera within the African (Table S1) and 48 in the Australian prostate tumor tissue (Table S2), with an overlap of 28 genera, the vast majority (20 of 28) Proteobacteria (Table 2). The most abundant genera across the study included: Escherichia, Propionibacterium, and Pseudomonas (Figure 1A), in agreement with the complimentary study out of China.10 While Escherichia has been shown to stimulate PCa progression in vitro,17 Propionibacterium acne has reported being significantly more common in prostate tissue from men with, compared with men without PCa.18 Comparing our African and Australian data with the 47 bacterial genera from the Chinese study,10 we identified 23 commonly represented genera (Table 2).

Table 2.

Bacterial genera shared between African and Australian prostate tumor samples (n=28)

Genus Phylum Chinese prostate tissue study10 Fecal‐derived core gut microbiome (34 genera)16
Achromobacter Proteobacteria Absent Absent
Propionibacterium Actinobacteria Present Absent
Sphingomonas Proteobacteria Present Absent
Ralstonia Proteobacteria Present Absent
Acidovorax Proteobacteria Present Absent
Micrococcus Actinobacteria Absent Absent
Kluyvera Proteobacteria Absent Absent
Moraxella Proteobacteria Present Absent
Rhodococcus Actinobacteria Present Absent
Dechlorosoma Proteobacteria Present Absent
Delftia Proteobacteria Present Absent
Klebsiella Proteobacteria Present Present (rank 28)
Escherichia‐Shigella Proteobacteria Present Present (rank 19)
Pantoea Proteobacteria Present Absent
Cupriavidus Proteobacteria Present Absent
Enterobacter Proteobacteria Present Absent
Corynebacterium Actinobacteria Present Absent
Citrobacter Proteobacteria Present Absent
Thermus Deinococcus‐Thermus Absent Absent
Acinetobacter Proteobacteria Present Absent
Streptococcus Firmicutes Present Present (rank 14)
Stenotrophomonas Proteobacteria Present Absent
Salmonella Proteobacteria Present Absent
Pseudomonas Proteobacteria Present Absent
Ochrobactrum Proteobacteria Present Absent
Comamonas Proteobacteria Absent Absent
Staphylococcus Firmicutes Present Absent
Lactobacillus Firmicutes Present Absent

Figure 1.

Figure 1

Prostate microbiomes shown in this study. A, Heatmap showing the read count of the top 15 abundant bacterial genera identified in the patients in this study, with the UPGMA tree constructed based on the weighted_UniFrac distance between specimens. B, The NMDS plots in which the African and European samples are distinguishable but the high‐ and low‐risk European samples are not distinguishable. C, Comparison of the alpha‐diversity indices, ACE and chao1, between the prostate microbiomes of the African and European patients. D, Bacterial genera that are differentially abundant between the African and the European patients. NMDS, nonmetric multidimensional scaling [Color figure can be viewed at wileyonlinelibrary.com]

3.2. Microbial biodiversity and abundance associated with clinical presentation and ethnicity

Neither clustering nor NMDS based on beta‐diversity measures (differences in species composition) could distinguish the high‐risk and low‐risk Australian‐European tumors (Figure 1A and 1B). Complimentary to the Chinese study,10 we showed a lack of association between bacterial abundance and clinical presentation. In contrast, we observed a significant increase in the community richness (alpha‐diversity) in the African over the European‐derived tumors (ACE and chao1, t = 5.5 and 4.6, P = .0004 and .001, two‐tailed t test) (Figure 1C). Four genera, Streptococcus, Alicycliphilus, Acidovorax, and Escherichia, were elevated and four, Bacteroides, Eubacterium, Parabacteroides, and Odoribacter, were exclusive to our African‐derived prostate tumor tissue (Figure 1D). These anaerobic genera accounted for 62% to 89% of the total African‐derived bacterial burden. Streptococcus was reported as one of 11 predominant bacterial genera (>1% threshold) in European Italian prostate and cancer tissue.8 Irrespective of country of origin, we observed a predominance of Gram‐negative over Gram‐positive bacteria (all P < 7.1e−5), while anaerobic to aerobic ratio was significantly associated with African‐derived tumors (P = .0002).

4. DISCUSSION

Taking advantage of discarded unmapped human genomic data generated in whole‐genome sequencing efforts, we were ideally positioned in this study to perform metagenomic analysis for experimentally controlled data generated from cancerous prostate tissue derived from patients from geographically distinct continents, Africa and Australia,12 while allowing for further correlation with recently published data from China.10 Avoiding for sequencing‐derived batch effects, it should be noted that as a host genome‐profiling study, negative sequencing controls were not included. Synergies observed across the cohorts include: (a) a lack of nonbacterial microbes and (b) a 1.6‐fold increase in the total number of bacterial genera represented within the African vs Australian and African vs Chinese tissues. The most abundant bacterial genera across the cohorts include Escherichia, Propionibacterium, and Pseudomonas. Overall, we observed an overrepresentation of Proteobacteria across the study samples (71%, 20 of 28 genera) and between the continents (74%, 17 of 23 genera), including well‐known human pathogens, such as Escherichia, Salmonella, and Acinetobacter.19 Although we found no correlation between the presence of these bacteria and clinical presentation (high‐ vs low‐risk PCa), larger studies are required to make further clinical correlations. Conversely, the possibility exists that the 23 bacterial genera common across the three ethnic groups from three continents, may constitute the core prostate human microbiome, irrespectively of disease status.

A major limitation of metagenomic studies is controlling for contaminants. While we were unable to control for differences in sampling procedures, transrectal biopsy sampling in Africans vs postsurgical sampling in Australians, ensuring samples were fresh reduced contaminants commonly introduced during tissue fixation, and centralizing the sequencing to a single laboratory, workflow and time point, further minimized for potential downstream confounders. It is therefore essential that we consider the potential for fecal contamination of the African samples. The healthy human fecal‐derived gut microbiome is characterized by an abundance of Bacteroidetes and Firmicutes,6 specifically Bacteroides and Eubacterium.16 Notably, Bacteroidetes: Bacteroides, Parabacteroides, and Odoribacter, and the Firmicutes: Eubacterium, were found to be uniquely represented within our African tissues. Although absent from our Australian tissues, both Bacteroides and Eubacterium were present within the postsurgically derived Chinese tissue. It is also well‐established that the gut microbiome will differ considerably between ethnic groups and continents, with most studies focused on non‐Africans. A study comparing the healthy fecal bacterial content in children from Africa (rural village in Burkina Faso) and Europe (urban area in Florence, Italy) for example, confirmed an abundance of Firmicutes (51%) and Bacteroides (23%) in the Europeans, while Prevotella (53%) and Xylanibacter (20%) were predominant in the African‐derived stools.20 While Xylanibacter was absent in our African prostate samples, Prevotella was present, as reported also for the Chinese samples.

In the absence of patient‐specific rectal swabs, to further assess the source of abundance for the African‐derived prostate microbiota, we performed an extensive comparative analysis with 34 published core gut bacterial genera identified from the stools of 364 healthy volunteers from Denmark, Spain, China, or the United States.16 Of the 15 most abundant African‐derived prostate bacterial genera identified in our study (Figure 1A), 8 were notably absent within the core gut microbiome and include (in order of abundance): Acidovorax, Propionibacterium, Acinetobacter, Pseudomonas, Ochrobactrum, Porphyromonas, Cupriavidus, and Finegoldia, of which only Porphyromonas and Finegoldia were absent in our Australian samples, although Finegoldia was present in the Chinese samples. Conversely, 27 of the 34 core gut genera were not rated abundant in our African prostate samples, with 17 notably absent and including (in order of fecal core abundance): Faecalibacterium, Coprococcus, Dorea, Blautia, Colinsella, Capnocytophaga, Bilophila, Sutterella, Dialister, Paraprevotella, Haemophilus, Methanobrevibacter, Desulfovibrio, Megasphaera, Butyrivibrio, Mitsuokella, and Phascolarctobacterium. Of the prostate‐derived genera common across the African, Australian, and Chinese tissues, only three were ranked as core fecal microbiota (Table 2), with a notable absence of Bacteroidetes and underrepresentation of Firmicutes (3 of 23 genera).

A recent study using 16S sequencing from rectal swabs from men undergoing transrectal biopsy reported enrichment for core gut genera Bacteroides and Streptococcus in cancerous over noncancerous patients.21 In our African‐derived tumor tissue, these genera were ranked first and eighth, respectively. While Bacteroides was absent within our Australian tumors and present in the Chinese, Streptococcus was present across all studies. Two additional studies have reported Streptococcus to be enriched in rectal swabs and/or voided urine from men with PCa.22, 23 Taken together, we cannot exclude for a possible contribution of these core gut microbiota in promoting advanced PCa presentation within Africa. Associations to consider include, Bacteroides abundance within vaginal communities of women with bacterial vaginosis (BV), a common condition impacting southern African women,24 and Bacteroides abundance within the gut mucosa of patients with colorectal cancer.25

Irrespective of Bacteroides abundance, eight genera were common across all the African samples of which Escherichia and Acidovorax appear to be the most significant to all tumors (Figure 2). While Escherichia is a well‐known human infectious pathogen,19 Acidovorax, although a common phytopathogen found in the environment, has been associated with rare cases of human infection.26, 27 Besides total bacterial burden, Eubacterium abundance was significantly associated with host tumor genomic instability, including the most hypermutated prostate tumor identified to date, 55 mutations/Mb (t = −1650, P = 4.9e−10) and a uniquely hyperduplicated tumor with 33.4‐fold increase in acquired tandem duplications (t = −378, P = 4.1e−08). Increased TMB is a hallmark of carcinogenic induced cancers, namely ultraviolet exposure in melanoma (TMB 13.5 mutations/Mb) and tobacco smoke in lung cancer (TMB 7.2 mutations/Mb), leading to associated genomic instability and/or DNA damage.28 PCa with no known mutagenic agent, has a TMB of <1 mutations/Mb across pathologies.29 Having observed a 1.8‐fold increase in TMB between our African‐ vs European‐derived high‐risk tumors (t = 4.4544, P = .007; two‐tailed t test), this is roughly fourfold greater than reported overall for PCa.12 As is the case of Helicobacter pylori and Salmonella enterica, bacteria can induce DNA damage influencing oncogenic transformation.30 As with Bacteroides, Eubacterium abundance has been observed in South African women with BV.31

Figure 2.

Figure 2

Distribution of common bacterial genera within six African high‐risk prostate tumors, with Bacteroides, included (inner panel) and excluded (outer panel). Number in a chart indicates the percentage of bacterial abundance [Color figure can be viewed at wileyonlinelibrary.com]

5. SUMMARY

In conclusion, we have observed 23 common bacterial genera within prostate tissue derived from patients from three continents, with a predominance for Proteobacteria. Including known pathogens, such as Escherichia, Salmonella, and Acinetobacter, we found no link with clinical presentation. Compared with Australian and Chinese data, our African‐derived high‐risk PCa tissue showed a 1.6‐fold increased bacterial burden, with an abundance of anaerobic bacteria. While unable to exclude for fecal contamination within our African samples, notable observations included: half of the core human gut bacterial genera were absent, Escherichia and Acidovorax were significantly abundant, while total bacterial burden and Eubacterium abundance correlated with host tumor hypermutation. Further studies controlling for possible contaminants are required to elucidate if microbes are contributing to adverse disease presentation within Africa.

CONFLICT OF INTERESTS

The authors declare that there are no conflict of interests.

AUTHOR CONTRIBUTIONS

VMH designed and initiated the study with support from MSRB. SMP, RJL, A‐MH, PDS, and MSRB were responsible for patient recruitment, consenting, sampling, and processing. YF, WJ, and VMH analyzed the data and wrote the manuscript. CCC edited the manuscript and provided a critical review. All authors read and approved the final manuscript.

DATA ACCESSIBILITY

Sequencing data have been deposited at the NCBI Sequence Read Archive (SRA accession SRP119289) with BioProject number PRJNA412953. All data supporting the conclusions of this article are included in Tables S1 and S2 (tabulated list of bacteria identified).

Supporting information

Table S1. Bacterial genera observed in six African‐derived prostate tissues

Table S2. Bacterial genera observed in 16 European‐derived prostate cancer tissue

ACKNOWLEDGMENTS

The authors thank the patients and all urological staff associated with the Southern African Prostate Cancer Study (SAPCS) and the St Vincent's Prostate Cancer BioBank (housed at the Garvan Institute). This work was supported in part by the Cancer Association of South Africa (CANSA) and National Research Foundation (NRF) of South Africa, as well as the Australian Prostate Cancer Research Center NSW (APCRC‐NSW) and St Vincent's Prostate Cancer Center. VMH is supported by the University of Sydney Foundation and Petre Foundation, Australia and YF by the China Scholarship Council (#CSC201606325044). We acknowledge the University of Sydney Informatics Hub for providing access to the High‐Performance Computing infrastructure used in this study.

Feng Y, Jaratlerdsiri W, Patrick SM, et al. Metagenomic analysis reveals a rich bacterial content in high‐risk prostate tumors from African men. The Prostate. 2019;79:1731–1738. 10.1002/pros.23897

References

REFERENCES

  • 1. Siegel RL, Miller KD, Jemal A. Cancer statistics. CA Cancer J Clin. 2017;67:7‐30. [DOI] [PubMed] [Google Scholar]
  • 2. Tindall EA, Monare LR, Petersen DC, et al. Clinical presentation of prostate cancer in black South Africans. Prostate. 2014;74:880‐891. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3. Tindall EA, Bornman MR, van‐Zyl S, et al. Addressing the contribution of previously described genetic and epidemiological risk factors associated with increased prostate cancer risk and aggressive disease within men from South Africa. BMC Urol. 2013;13:74. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4. Sfanos KS, De Marzo AM. Prostate cancer and inflammation: the evidence. Histopathology. 2012;60:199‐215. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5. Plummer M, de Martel C, Vignat J, Ferlay J, Bray F, Franceschi S. Global burden of cancers attributable to infections in 2012: a synthetic analysis. Lancet Glob Health. 2016;4:e609‐e616. [DOI] [PubMed] [Google Scholar]
  • 6. Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome. Nature. 2012;486:207‐214. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7. Goodman B, Gardner H. The microbiome and cancer. J Pathol. 2018;244:667‐676. [DOI] [PubMed] [Google Scholar]
  • 8. Cavarretta I, Ferrarese R, Cazzaniga W, et al. The microbiome of the prostate tumor microenvironment. Eur Urol. 2017;72:625‐631. [DOI] [PubMed] [Google Scholar]
  • 9. Yow MA, Tabrizi SN, Severi G, et al. Characterisation of microbial communities within aggressive prostate cancer tissues. Infect Agent Cancer. 2017;12:4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10. Feng Y, Ramnarine VR, Bell R, et al. Metagenomic and metatranscriptomic analysis of human prostate microbiota from patients with prostate cancer. BMC Genomics. 2019;20:146. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11. Bajic P, Dornbier RA, Doshi CP, Wolfe AJ, Farooq AV, Bresler L. Implications of the genitourinary microbiota in prostatic disease. Curr Urol Rep. 2019;20:34. [DOI] [PubMed] [Google Scholar]
  • 12. Jaratlerdsiri W, Chan EKF, Gong T, et al. Whole‐genome sequencing reveals elevated tumor mutational burden and initiating driver mutations in African men with treatment‐naive, high‐risk prostate cancer. Cancer Res. 2018;78:6736‐6746. [DOI] [PubMed] [Google Scholar]
  • 13. Li H, Durbin R. Fast and accurate short read alignment with Burrows‐Wheeler transform. Bioinformatics. 2009;25:1754‐1760. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14. Zhang C, Cleveland K, Schnoll‐Sussman F, et al. Identification of low abundance microbiome in clinical samples using whole genome sequencing. Genome Biol. 2015;16:265. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.R Core Team. R: a language and environment for statistical computing Vienna, Austria: R Foundation for Statistical Computing; 2016.
  • 16. Tramontano M, Andrejev S, Pruteanu M, et al. Nutritional preferences of human gut bacteria reveal their metabolic idiosyncrasies. Nat Microbiol. 2018;3:514‐522. [DOI] [PubMed] [Google Scholar]
  • 17. Simons BW, Durham NM, Bruno TC, et al. A human prostatic bacterial isolate alters the prostatic microenvironment and accelerates prostate cancer progression. J Pathol. 2015;235:478‐489. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18. Davidsson S, Mölling P, Rider JR, et al. Frequency and typing of Propionibacterium acnes in prostate tissue obtained from men with and without prostate cancer. Infect Agent Cancer. 2016;11:26. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19. Rizzatti G, Lopetuso LR, Gibiino G, Binda C, Gasbarrini A. Proteobacteria: a common factor in human diseases. Biomed Res Int. 2017;2017:9351507. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20. De‐Filippo C, Cavalieri D, Di‐Paola M, et al. Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa. Proc Natl Acad Sci USA. 2010;107:14691‐14696. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21. Liss MA, White JR, Goros M, et al. Metabolic biosynthesis pathways identified from fecal microbiome associated with prostate cancer. Eur Urol. 2018;74:575‐582. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22. Shrestha E, White JR, Yu SH, et al. Profiling the urinary microbiome in men with positive versus negative biopsies for prostate cancer. J Urol. 2018;199:161‐171. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23. Alanee S, el‐Zawahry A, Dynda D, et al. A prospective study to examine the association of the urinary and fecal microbiota with prostate cancer diagnosis after transrectal biopsy of the prostate using 16sRNA gene analysis. Prostate. 2019;79:81‐87. [DOI] [PubMed] [Google Scholar]
  • 24. Campisciano G, Zanotta N, Licastro D, De‐Seta F, Comar M. In vivo microbiome and associated immune markers: new insights into the pathogenesis of vaginal dysbiosis. Sci Rep. 2018;8:2307. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25. Flemer B, Lynch DB, Brown JMR, et al. Tumour‐associated and non‐tumour‐associated microbiota in colorectal cancer. Gut. 2017;66:633‐643. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26. Malkan AD, Strollo W, Scholand SJ, Dudrick SJ. Implanted‐port‐catheter‐related sepsis caused by Acidovorax avenae and methicillin‐sensitive Staphylococcus aureus . J Clin Microbiol. 2009;47:3358‐3361. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27. Orsborne C, Hardy A, Isalska B, Williams SG, Muldoon EG. Acidovorax oryzae catheter‐associated bloodstream infection. J Clin Microbiol. 2014;52:4421‐4424. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28. Chalmers ZR, Connelly CF, Fabrizio D, et al. Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden. Genome Med. 2017;9:34. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29. Abeshouse A, Ahn J, Akbani R, et al. The molecular taxonomy of primary prostate cancer. Cell. 2015;163:1011‐1025. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30. Gagnaire A, Nadel B, Raoult D, Neefjes J, Gorvel JP. Collateral damage: insights into bacterial mechanisms that predispose host cells to cancer. Nat Rev Microbiol. 2017;15:109‐128. [DOI] [PubMed] [Google Scholar]
  • 31. Africa C, Nel J, Stemmet M. Anaerobes and bacterial vaginosis in pregnancy: virulence factors contributing to vaginal colonisation. Int J Environ Res Public Health. 2014;11:6979‐7000. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Table S1. Bacterial genera observed in six African‐derived prostate tissues

Table S2. Bacterial genera observed in 16 European‐derived prostate cancer tissue

Data Availability Statement

Sequencing data have been deposited at the NCBI Sequence Read Archive (SRA accession SRP119289) with BioProject number PRJNA412953. All data supporting the conclusions of this article are included in Tables S1 and S2 (tabulated list of bacteria identified).


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