|Year : 2022 | Volume
| Issue : 1 | Page : 51-58
Diversity in microbiota between Indian and Emiratis ethnicities is associated with benign prostatic hyperplasia
Zainab Al Shareef1, Naveed Ahmed Khan1, Mai Nidal Asad Ershaid2, Sameh Soliman3, Adel B Elmoselhi1
1 College of Medicine, University of Sharjah, Sharjah, United Arab Emirates; Research Institute for Medical and Health Sciences, University of Sharjah, Sharjah, United Arab Emirates
2 Research Institute for Medical and Health Sciences, University of Sharjah, Sharjah, United Arab Emirates
3 Research Institute for Medical and Health Sciences, University of Sharjah, Sharjah, United Arab Emirates; College of Pharmacy, University of Sharjah, Sharjah, United Arab Emirates
|Date of Submission||14-Oct-2021|
|Date of Decision||03-Jan-2022|
|Date of Acceptance||06-Jan-2022|
|Date of Web Publication||24-Jan-2022|
Adel B Elmoselhi
Department of Basic Biomedical Sciences, College of Medicine, University of Sharjah, Sharjah.
United Arab Emirates
Source of Support: None, Conflict of Interest: None
Background: Herein, we investigated the correlation between microbiota profile and benign prostatic hyperplasia (BPH) in patients from two different ethnicities, Indian and United Arab Emirates. Materials and Methods: Prostate samples were collected from patients in Al Baraha Hospital in Sharjah, United Arab Emirates. Next, metagenomic analysis of bacterial species was carried out by extracting DNA and 16S rRNA analysis. Results: Our results revealed that the gut bacterial communities of the Indian and Emirati populations were different. Principal coordinates analyses revealed differences in the bacterial community structure. Around 265 bacterial operational taxonomic units (OTUs) were specific to the Indian population vs. 968 bacterial OTUs observed in the Emirati population, whereas 586 bacterial OTUs were common to both groups. When the relative abundance of taxa was analyzed, Proteobacteria, Actinobacteriota, and Firmicutes represented the highest abundance, albeit the relative abundance was different between the two groups. At the genus level, the distribution of the genus Ralstonia was most abundant in the Emirati population followed by Pseudomonas, whereas Acinetobacter was the most abundant in the Indian population followed by Stenotrophomonas. Likewise, differences were observed between other genera in both groups. MetaStats analysis revealed that 21 bacterial species were considerably different between the two groups. Conclusion: Collectively, the data revealed that both groups showed differences in the structure of bacterial community. Further studies are warranted to determine the precise role of specific bacterial species in BPH and the underlying molecular mechanisms. The findings arising from these studies will be important in the rational development of therapeutic interventions.
Keywords: Benign prostatic hyperplasia, gut microbiome, metabolites
|How to cite this article:|
Al Shareef Z, Khan NA, Ershaid MN, Soliman S, Elmoselhi AB. Diversity in microbiota between Indian and Emiratis ethnicities is associated with benign prostatic hyperplasia. Adv Biomed Health Sci 2022;1:51-8
|How to cite this URL:|
Al Shareef Z, Khan NA, Ershaid MN, Soliman S, Elmoselhi AB. Diversity in microbiota between Indian and Emiratis ethnicities is associated with benign prostatic hyperplasia. Adv Biomed Health Sci [serial online] 2022 [cited 2022 Aug 11];1:51-8. Available from: http://www.abhsjournal.net/text.asp?2022/1/1/51/336460
| Background|| |
Benign prostatic hyperplasia (BPH) is the most common benign neoplasm afflicting aging men. The term refers to the abnormal increase in the size of the prostate leading to loss of control on the urinary bladder that results in either frequent urination or troubles including urination, urgency, straining, and incontinence  to complications including urinary tract infections (UTIs), bladder stones, and chronic kidney conditions . These symptoms are attributed to the histological changes occurring in the prostate, mainly hyperplasia of the glandular elements in the periurethral zone and the stromal elements in the transition zone. These changes are also dependent on the levels of testosterone and dihydrotestosterone (DHT) . The risk factors for BPH can include increasing age, age-related changes leading to metabolic disturbances, family history, changes in hormonal balance, obesity, heart diseases, diabetes, and chronic inflammation [1,2]. Progression of BPH can also be influenced by lack of exercise, smoking as well as patient’s diet . Prostate size does not correlate directly to the severity of lower urinary tract symptoms (LUTS), but studies have shown that larger prostate increases the risk for more severe LUTS and BPH progression, urinary retention, and the need for surgical intervention [5,6]. In contrast, small-sized prostates can also cause bladder outlet obstruction and LUTS . Men over the age of 60 are more susceptible to developing LUTS. However, epidemiological studies show that ethnicity contributes to the incidence of LUTS .
There is a growing interest in investigating the association between the microbiome and the onset or progression of BPH and prostatic cancer. The microbiome is defined as the collection of microorganisms including bacteria, fungi, and viruses along with their genetic information occupying a particular habitat. Although epidemiological studies show an association between the genito-urinary tract microbiota and prostatic diseases such as BPH and cancer, evidence suggests that the oral microbiome enhances the risk of BPH. Oral bacteria can stimulate the inflammatory response, and hence the diffusion of inflammatory cytokines is indirectly related to prostate inflammation, which promotes the development of BPH and prostatic cancer . Furthermore, a study conducted by Joshi et al.  showed that there is a correlation between prostate-specific antigen and periodontal disease in chronic prostatitis patients. In contrast, the urinary tract has been considered a sterile area and the presence of microbes is an indication of infection, albeit studies have shown that microbes can be present in the bladder of healthy individuals . The bacterial strains are detected in prostatic secretions, seminal fluid, and voided urine with variable profiles among different patients with BPH and PCA . In addition to the urinary tract microbiome, the gut microbiome is also linked to BPH and PCA. Bacterial metabolites secreted from the gut microbiota can, directly and indirectly, influence prostate health , and it is the subject of the present study. Microbiome has been strongly involved in the incidence and progression of prostate disease through the regulation of many mechanisms involved in inflammation, apoptosis, and cytokines and hormonal secretions . Furthermore, drug response and resistance reflect the microbiome composition in the treated tissue . IL-6 and IL-7 are the two key inflammatory cytokines detected in PCA pathogenesis [10,11]. Frequent tissue damage via inflammation can lead to the production of radioactive substances (ROS), tissue damage, and DNA modification ,,. However, the role of inflammation in developing solid tumors is not clarified yet. Many studies explained how frequent and persistent inflammation stimulates over-proliferation of stroma and glandular cells [15,16] and induces TNF and NF-κB because of ROS production . The proliferative prostate in response to ROS is called proliferative inflammatory atrophy (PIA) . Around 40% of PIA patients are predisposed to high-grade intraepithelial neoplasia, the step before PCA . Moreover, the considerable variation in the type of inflammatory cellular infiltration between prostatitis, BPH, and PCA, respectively, is another evidence for the potent role of inflammation in prostate disease . Hence, the overall aim of the present study was to determine the correlation between microbiota profile and BPH in patients from two different ethnicities, the Indian and United Arab Emirates.
| Materials and methods|| |
A retrospective cohort study recruited prostate tissue samples from a total of six BPH patients. In total, three Indian and three Emiratis were provided from the University of Sharjah (UOS) tissue biobank after approval from the Al Baraha hospital Committee and the Ministry of Health and Prevention (MOHAP), the United Arab Emirates, following approval from the local research Ethics Committee (approval reference number: REC-20-03-23-0, date 08/04/2020) and MOHAP (approval reference number: MOHAP/DXB-REC/ JJA/No. 75/2020, dated 30/08/2020).
Metagenomic DNA extraction and sequencing of the bacterial 16S rRNA
For the metagenomic studies, DNA was extracted from formalin-fixed, paraffin-embedded (FFPE) tissue samples. Indian samples (Group A) were 157768, 275191, and 286437 and Emiratis samples (Group B) were 117259, 126025, and 118976. DNA purity and concentration were elucidated using 1% agarose gels, and the DNA was then diluted to 1 ng/μL with sterile water as described previously . Gut metagenomic DNA was processed for 16S rRNA gene hypervariable region sequencing utilizing the following primers: 341F-CCTAYGGGRBGCASCAG; 806R-GGACTACNNGGGTATCTAAT ,,. To purify the PCR products, the Qiagen Gel Extraction Kit was utilized. NEBNext® UltraTM DNA Library Prep Kit was used to generate sequencing libraries on Illumina and then quantified with Q-PCR and Qubit, followed by analysis on Illumina platform. Finally, the library was sequenced on an Ion S5TM XL platform to generate 400 bp/600 bp single-end reads. The amplicon was sequenced on the Illumina paired-end platform, and 250 bp paired-end raw reads were generated. Quality filtering on raw tags was achieved with filtering to obtain clean tags. Operational taxonomic units (OTUs) clustering was carried out using effective data. In short, high-quality clean reads were obtained as per Cutadapt quality-controlled process (V1.9.1, http://cutadapt.readthedocs.io/en/stable/) . Next, the reads were related with the reference Silva database (https://www.arb-silva.de/)  using the UCHIME algorithm (http://www.drive5.com/usearch/manual/uchime_algo.html)  to detect chimera sequences, and subsequently, the chimera sequences were removed to achieve clean data . The analysis of sequences was accomplished via the Uparse software as described earlier . Sequences expressing ≥97% similarity were grouped in the same OTUs. Following this, representative sequences for each OTU were investigated and further annotated; in this regard, the Silva Database was utilized based on the Mothur algorithm. To determine the phylogenetics of differing OTUs, and the difference of the dominant species in differing samples (groups), multiple sequence alignment was completed utilizing the MUSCLE software as described previously . Based on clustering data of the OTUs, taxonomic annotation was accomplished for representative sequences of each OTU, to elucidate corresponding taxa information and taxa-based abundance distribution. Additionally, OTUs were analyzed for alpha diversity analysis to determine microbial diversity, beta diversity analysis to determine differences in the microbial composition, and Venn diagrams to determine the logical relationships between the two groups.
Statistical analysis using analysis of variance was used for the analysis of the OTUs abundance at different levels. Multiple variance analysis of the distance matrix was conducted with the Adonis comparative analysis between groups.
| Results|| |
Characteristics of study subjects
Our patients’ cohorts consist of six confirmed BPH patients with a median age of 59 years (range 58–66 years). Three patients were Indian (Group A) and three were Emirati.
Composition of microbial community between groups indicated a clear interspecific variation in the bacterial gut communities
Based on the high-quality sequences, two groups of OTUs with the largest abundance were obtained. Detection of chimeric sequences in the clean tags was performed and these were removed using Usearch software. Following this, 776750 valid tags were confirmed (370341 and 406409 tags for Group A and Group B, respectively). Next, OTUs classification was accomplished on all high-quality sequences with 97% similarity utilizing the Uparse software, and sequences with the largest abundance within OTUs were selected as representative sequences to be analyzed in the Silva-16S database. The data portrayed 4,202 OTUs that are 1,675 and 2,527 OTUs for Group A and Group B, respectively. The gut bacterial communities of different ethnicities were different as detailed in [Figure 1]. Approximately 265 bacterial OTUs were specific to Group A population (Indian population), whereas 968 bacterial OTUs were specific to the Group B population (Emirati population). Further, 586 bacterial OTUs were common to both groups. A complete list of all bacterial OTUs observed in both groups is shown in [Table 1].
|Figure 1: Venn diagram showing the distribution of bacterial OTUs between Indian (Group A) and Emirati populations (Group B) based on 16S rRNA gene sequence analysis|
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|Table 1: MetaStats analysis with significant differences between the two groups at the species-level|
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Metagenomics revealed a considerable difference in the relative abundance of taxa between the Indian and Emirati groups
To elucidate the top 10 taxa of each group at various taxonomic ranks (Phylum, Class, Order, Family, Genus), distribution histograms representing the relative abundance of taxa and taxa with higher relative proportion and abundance at various classification levels of each sample were visualized. [Figure 2] details the relative abundance of taxa in the phylum and genus. “Others” depict the total relative abundance of the rest of phyla besides the top 10. Interestingly, among the phyla, Proteobacteria represented the highest abundance in both groups, albeit the relative abundance was 96.6% in Group A (Indian population) and 71.4% in Group B populations (Emirati population) [Figure 2]A. In contrast, Actinobacteriota distribution varied among the two groups. Actinobacteriota was the second most abundant (16.4%) in Group B (Emirati population), but only 0.5% in Group A (Indian population). Similarly, the relative abundance of Firmicutes was different between the two groups. Firmicutes was the third most abundant (10.4%) in Group B (Emirati population) but only 1.7% in Group A (Indian population). Overall, the relative abundance of the top 10 phyla in Group A was in the order of Proteobacteria, Firmicutes, Actinobacteriota, Bacteroidota, Verrucomicrobiota, Desulfobacterota, Gemmatimonadota, Dependentiae, Acidobacteriota, and Chloroflexi. In contrast, the relative abundance of the top 10 phyla in the Emirati population was in the order of Proteobacteria, Actinobacteriota, Firmicutes, Bacteroidota, Desulfobacterota, Acidobacteriota, Gemmatimonadota, Chloroflexi, Verrucomicrobiota, and Dependentiae.
|Figure 2: Distribution of dominant phyla (A) and genus (B) in Indian (labeled as Group A) and Emirati populations (labeled as Group B), respectively|
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At the genus level, the distribution of the genus Ralstonia was the most abundant in the Emirati population (Group B) followed by Pseudomonas, whereas Acinetobacter was the most abundant in the Indian population (Group A) followed by Stenotrophomonas [Figure 2B]. Likewise, the differences were observed between other genera in both groups [Figure 2B]. Beta diversity analysis to determine differences in the microbial composition of both groups was performed. The data revealed that both groups showed some differences in the bacterial community structure, as shown in [Figure 3]. MetaStats analysis was performed to determine the differences between the two groups at the species level. The results showed that there are 21 species, which were considerably different between the two groups including Methylorubrum extorquens, Sphingomonas paucimobilis, Agrobacterium pusense, Comamonas aquatic, Bosea sp., Clostridium argentinense, Pelomonas puraquae, Blautia sp., Proteus mirabilis, Aeromonas veronii, Paracoccus sp., Marinobacter algicola, Anaerostipes hadrus, Rhodovulum sp., Corynebacterium propinquum, Prevotella melaninogenica, Bifidobacterium pseudolongum, Acinetobacter nosocomialis, Dialister sp., Paenibacillus popilliae, and Sandaracinus amylolyticus [Table 1]. The differences in the microbiological diversity were analyzed with the alpha diversity analysis and the diversity index Boxplot [Figure 4]A. According to the Chao diversity index of the sample distribution, our results showed that there were differences in the microbiological pattern [Figure 4]A. [Figure 4]B shows the rank abundance curve to visualize species richness and species evenness. A steep gradient indicated low evenness because the high-ranking species have much higher abundances than the low-ranking species [Figure 4]B.
|Figure 3: Tukey–Wilcon analysis for the differences in microbial communities between Group A (Indian population) and Group B (Emirati population), respectively|
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|Figure 4: (A) Boxplot for comparison of the diversity indices between Group A (Indian population) and Group B (Emirati population), respectively. (B) Rank abundance of groups|
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| Discussion|| |
Currently, many studies revealed the influence of human microbiomes on the progression of prostate disease and PCA [7, 31, 32]. To the best of our knowledge, this is the first study investigating the difference in microbiota associated with BPH between Emirati and Indian ethnicities. This study aimed to investigate the relative abundance of microbiota between the two groups and whether such difference is related to the development of BPH and prostatic cancer.
It is well known that Asian men are less susceptible to clinical BPH than white men  and the prevalence of BPH among Black Americans is higher than white Americans [34,35]. In contrast, a piece of evidence indicated that dysbiosis modifies the immune system and increases the systemic inflammatory response that can contribute to prostatitis/chronic pelvic pain syndrome, BPH, and PCA . Besides, microbiomes might regulate the systemic hormone levels particularly the estrogen and androgen in prostate-related diseases including PCA [36,37]. An in-vivo study demonstrated the fundamental role of the gut microbiome in the metabolism of the intestine and the de-glucuronidation of DHT and testosterone, which lead to an extreme elevation in the levels of free androgen and DHT in the colon . A similar observation was noticed on the patient’s serum and feces samples . The prostate is an androgen-targeted tissue and androgen is directly regulating the prostate epithelial growth and differentiation . Importantly, hypovitaminosis D is widely common across Emirati’s population, despite consuming many vitamin D products such as fish and seafood . Avoidance of sun exposure and sunscreen usage augmented the prevalence of vitamin D deficiency . The low level of 25-hydroxy vitamin D is also associated with the greater incidence of LUTS/PBH . Furthermore, host gut microbiota regulates the expression of vitamin D receptor in the intestine and vice versa . It is worth noting that vitamin D deficiency is less common in the Indian population. Additionally, we have noticed a lower prevalence of PBH and mild enlargement of the prostate in Indian patients when compared with the Middle East patients (unpublished data). This has led us to identify the microbiome distribution between both ethnicities.
Proteobacteria are one of the most abundant phyla in the intestine. It consists of well-recognized human pathogens. Proteobacteria exhibit a positive correlation with the inflammatory diseases in general . Interestingly, our results indicated that the most commonly identified phylum from PBH patients in both ethnicities (Indian and Emirati) is Proteobacteria [Figure 1A], followed by Actinibacteria and Firmicutes, whereas the phylum Bacteroidetes was detected in a higher percentage in the Emirati patients [Figure 1A]. A similar prevalence of the phyla was demonstrated by Jain et al.  in a study involving 36 Indian patients diagnosed with BPH to investigate the relationship between microbiota and the inflammation and DNA damage, particularly in the epithelial compartment of the prostate. Further evidence demonstrated the existence of Bacteroidetes and Firmicutes mostly in the urine of PCA patients . A similar pattern was observed in the bacterial distribution identified from tissues collected from the UAE population [Figure 1A], suggesting a possible risk of PCA. In contrast, the distribution of microbiota is different between Indian patients living in India and those living in the UAE . A possible explanation for these differences is the diet intake and geographic location and environmental factors . Consistently, a Chinese study on the prevalence of LUTS/BPH has demonstrated a higher prevalence of BPH in the north-west regions of China in comparison to south-west regions of China . The discrepancy of incidence was attributed to the diet intake as people in the north consume more milk products and red meats, whereas those in the south consume more vegetables and fruits .
The most abundant bacterial genera among the Indian samples were Stenotrophomonas [Figure 2A], followed by Acinetobacter and Pseudomonas. In contrast, the most abundant bacterial genera identified within the UAE samples were Ralstonia, followed by Stenotrophomonas and Acinetobacter, besides the presence of Staphylococcus only in the Emirati patients. Stenotrophomonas and Ralstonia are identified as opportunistic nosocomial infection-causing microorganisms. It is known that some species of Stenotrophomonas particularly S. maltophilia strains are pathogenic to humans and exhibit resistance toward multiple drugs due to their ability of biofilm formation. Studies have shown that this species causes opportunistic infections such as UTI, mucocutaneous, osteomyelitis, pneumonia, and meningitis, especially in immunocompromised patients [47,48]. Similarly, Ralstonia is also known to survive in low nutrition conditions and is an opportunistic nosocomial infection that causes meningitis and osteomyelitis . In contrast, Staphylococcus is another nosocomial infection-causing microorganism, whereas its pathogenicity is strongly associated with low human immunity and individual aging . In our study, the collected samples from both groups, Indian (Group A) and the UAE (Group B), were selected at the same ages, thus it cannot be a factor. Despite remarkable differences observed in this study in the microbial structure between the two groups, the number of samples is a limitation of this study. The findings observed in this study need to be further verified using a larger cohort, and it is the subject of future studies. Even though the presence of Staphylococcus particularly in the UAE samples can be explained in many ways such as high incidence of diabetes, non-invasive procedures such as a prostate stent or intraurethral catheter, or weakness of the immune system, however, its relation to BPH/PCA and the underlying molecular mechanisms need to be investigated.
| Conclusion|| |
Our current results revealed that Indian and United Arab Emirates BHP samples showed differences in their bacterial community structure. Further studies are warranted to determine the precise role of specific bacterial species in BHP and the underlying molecular mechanisms. The findings arising from these studies will be important in identifying specific targets for the development of therapeutic interventions.
The main limitation of this study is the small number of samples, which is coming from six patients (three Indian and three Emirati backgrounds). However, our hypothesis has been confirmed regarding the diversity of microbiota between Emirati and Indian ethnicities and thus a larger scale study is justified and has been warranted to confirm our results and further investigate the changes in metabolites.
Many thanks for Prof. Rifat Akram Hamoudi and Mr. Abdalla Al Eltayeb Mohamed from UOS tissue biobank for providing direct technical help.
Financial support and sponsorship
This study is partly funded from a grant by UOS Research Office to ABE.
Conflicts of interest
ABE and NAK envisioned the concept amid critical discussions with ZA. ME and ZA prepared samples and ABE conducted the experiments. NAK, SS, and ZA analyzed the results and prepared the first draft of the article. ABE, SS, ZA, and NAK finalized the manuscript.
Approval from the local research Ethics Committee (approval reference number: REC-20-03-23-0, date 08/04/2020) and MOHAP (approval reference number: MOHAP/DXB-REC/ JJA/No. 75/2020, dated 30/08/2020).
Data availability statement
Patients’ consent (if applicable)
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[Figure 1], [Figure 2], [Figure 3], [Figure 4]