ABSTRACT: Urine culture and microscopy techniques are used to profile the bacterial species present in urinary tract infections. To gain insight into the urinary flora, we analyzed clinical laboratory features and the microbial metagenome of 121 clean-catch urine samples. 16S rDNA gene signatures were successfully obtained for 116 participants, while metagenome sequencing data was successfully generated for samples from 49 participants. Although 16S rDNA sequencing was more sensitive, metagenome sequencing allowed for a more comprehensive and unbiased representation of the microbial flora, including eukarya and viral pathogens, and of bacterial virulence factors. Urine samples positive by metagenome sequencing contained a plethora of bacterial (median 41 genera/sample), eukarya (median 2 species/sample) and viral sequences (median 3 viruses/sample). Genomic analyses suggested cases of infection with potential pathogens that are often missed during routine urine culture due to species specific growth requirements. While conventional microbiological methods are inadequate to identify a large diversity of microbial species that are present in urine, genomic approaches appear to more comprehensively and quantitatively describe the urinary microbiome.
Project description:Recent studies have established that a complex community of microbes colonize the human urinary tract; however, their role in kidney transplant patients treated with prophylactic antibiotics remains poorly investigated. Our aim was to investigate the urinary microbiome of kidney transplant recipients. Urine samples from 21 patients after kidney transplantation and 8 healthy controls were collected. All patients received prophylactic treatment with the antibiotic combination trimethoprim-sulfamethoxazole. Metagenomic DNA was isolated from urine samples, sequenced using shotgun sequencing approach on Illumina HiSeq 2000 platform, and analyzed for microbial taxonomic and functional annotations. Our results demonstrate that the urine microbiome of kidney transplants was markedly different at all taxonomic levels from phyla to species, had decreased microbial diversity, and increased abundance of potentially pathogenic species compared with healthy controls. Specifically, at the phylum level, we detected a significant decrease in Actinobacteria and increase in Firmicutes due to increases in Enterococcus faecalis. In addition, there was an increase in the Proteobacteria due to increases in Escherichia coli. Analysis of predicted functions of the urinary metagenome revealed increased abundance of enzymes in the folate pathway including dihydrofolate synthase that are not inhibited by trimethoprim-sulfamethoxazole, but can augment folate metabolism. This report characterizes the urinary microbiome of kidney transplants using shotgun metagenomics approach. Our results indicate that the urinary microbiota may be modified in the context of prophylactic antibiotics, indicating that a therapeutic intervention may shift the urinary microbiota to select bacterial species with increased resistance to antibiotics. The evaluation and development of optimal prophylactic regimens that do not promote antibiotic resistance is an important future goal.
Project description:BACKGROUND: Urine within the urinary tract is commonly regarded as "sterile" in cultivation terms. Here, we present a comprehensive in-depth study of bacterial 16S rDNA sequences associated with urine from healthy females by means of culture-independent high-throughput sequencing techniques. RESULTS: Sequencing of the V1V2 and V6 regions of the 16S ribosomal RNA gene using the 454 GS FLX system was performed to characterize the possible bacterial composition in 8 culture-negative (<100,000 CFU/ml) healthy female urine specimens. Sequences were compared to 16S rRNA databases and showed significant diversity, with the predominant genera detected being Lactobacillus, Prevotella and Gardnerella. The bacterial profiles in the female urine samples studied were complex; considerable variation between individuals was observed and a common microbial signature was not evident. Notably, a significant amount of sequences belonging to bacteria with a known pathogenic potential was observed. The number of operational taxonomic units (OTUs) for individual samples varied substantially and was in the range of 20-500. CONCLUSIONS: Normal female urine displays a noticeable and variable bacterial 16S rDNA sequence richness, which includes fastidious and anaerobic bacteria previously shown to be associated with female urogenital pathology.
Project description:PURPOSE:Studies demonstrating bacterial DNA and cultivable bacteria in urine samples have challenged the clinical dogma that urine is sterile. Furthermore, studies now indicate that dysbiosis of the urinary microbiome is associated with pathological conditions. We propose that the urinary microbiome may influence chronic inflammation observed in the prostate, leading to prostate cancer development and progression. Therefore, we profiled the urinary microbiome in men with positive vs negative biopsies for prostate cancer. MATERIALS AND METHODS:Urine was collected from men prior to biopsy for prostate cancer. DNA was extracted from urine pellet samples and subjected to bacterial 16S rDNA Illumina® sequencing and 16S rDNA quantitative polymerase chain reaction. We determined the association between bacterial species and the presence or absence of cancer, cancer grade, and type and degree of prostate inflammation. RESULTS:Urine samples revealed diverse bacterial populations. There were no significant differences in ? or ? diversity and no clear hierarchical clustering of benign or cancer samples. We identified a cluster of pro-inflammatory bacteria previously implicated in urogenital infections in a subset of samples. Many species, including known uropathogens, were significantly and differentially abundant among cancer and benign samples, in low vs higher grade cancers and in relation to prostate inflammation type and degree. CONCLUSIONS:To our knowledge we report the most comprehensive study to date of the male urinary microbiome and its relationship to prostate cancer. Our results suggest a prevalence of pro-inflammatory bacteria and uropathogens in the urinary tract of men with prostate cancer.
Project description:Ever-increasing affordability of next-generation sequencing makes whole-metagenome sequencing an attractive alternative to traditional 16S rDNA, RFLP, or culturing approaches for the analysis of microbiome samples. The advantage of whole-metagenome sequencing is that it allows direct inference of the metabolic capacity and physiological features of the studied metagenome without reliance on the knowledge of genotypes and phenotypes of the members of the bacterial community. It also makes it possible to overcome problems of 16S rDNA sequencing, such as unknown copy number of the 16S gene and lack of sufficient sequence similarity of the "universal" 16S primers to some of the target 16S genes. On the other hand, next-generation sequencing suffers from biases resulting in non-uniform coverage of the sequenced genomes. To overcome this difficulty, we present a model of GC-bias in sequencing metagenomic samples as well as filtration and normalization techniques necessary for accurate quantification of microbial organisms. While there has been substantial research in normalization and filtration of read-count data in such techniques as RNA-seq or Chip-seq, to our knowledge, this has not been the case for the field of whole-metagenome shotgun sequencing. The presented methods assume that complete genome references are available for most microorganisms of interest present in metagenomic samples. This is often a valid assumption in such fields as medical diagnostics of patient microbiota. Testing the model on two validation datasets showed four-fold reduction in root-mean-square error compared to non-normalized data in both cases. The presented methods can be applied to any pipeline for whole metagenome sequencing analysis relying on complete microbial genome references. We demonstrate that such pre-processing reduces the number of false positive hits and increases accuracy of abundance estimates.
Project description:A decade ago, when the Human Microbiome Project was starting, urinary tract (UT) was not included because the bladder and urine were considered to be sterile. Today, we are presented with evidence that healthy UT possesses native microbiota and any major event disrupting its "equilibrium" can impact the host also. This dysbiosis often leads to cystitis symptoms, which is the most frequent lower UT complaint, especially among women. Cystitis is one of the most common causes of antimicrobial drugs prescriptions in primary and secondary care and an important contributor to the problem of antimicrobial resistance. Despite this fact, we still have trouble distinguishing whether the primary cause of majority of cystitis cases is a single pathogen overgrowth, or a systemic disorder affecting entire UT microbiota. There are relatively few studies monitoring changes and dynamics of UT microbiota in cystitis patients, making this field of research still an unknown. In this study variations to the UT microbiota of cystitis patients were identified and microbial dynamics has been modeled. The microbial genetic profile of urine samples from 28 patients was analyzed by 16S rDNA Illumina sequencing and bioinformatics analysis. One patient with bacterial cystitis symptoms was prescribed therapy based on national guideline recommendations on antibacterial treatment of urinary tract infections (UTI) and UT microbiota change was monitored by 16S rDNA sequencing on 24 h basis during the entire therapy duration. The results of sequencing implied that a particular class of bacteria is associated with majority of cystitis cases in this study. The contributing role of this class of bacteria - <i>Gammaproteobacteria</i>, was further predicted by generalized Lotka-Volterra modeling (gLVM). Longitudinal microbiota insight obtained from a single patient under prescribed antimicrobial therapy revealed rapid and extensive changes in microbial composition and emphasized the need for current guidelines revision in regards to therapy duration. Models based on gLVM indicated protective role of two taxonomic classes of bacteria, <i>Actinobacteria</i> and <i>Bacteroidia</i> class, which appear to actively suppress pathogen overgrowth.
Project description:<h4>Purpose</h4>The etiology of postmenopausal recurrent urinary tract infection (UTI) is not completely known, but the urinary microbiome is thought to be implicated. We compared the urinary microbiome in menopausal women with recurrent UTIs to age-matched controls, both in the absence of acute infection.<h4>Materials and methods</h4>This is a cross-sectional analysis of baseline data from 64 women enrolled in a longitudinal cohort study. All women were using topically applied vaginal estrogen. Women >55 years of age from the following groups were enrolled: 1) recurrent UTIs on daily antibiotic prophylaxis, 2) recurrent UTIs not on antibiotic prophylaxis and 3) age-matched controls without recurrent UTIs. Catheterized urine samples were collected at least 4 weeks after last treatment for UTI and at least 6 weeks after initiation of vaginal estrogen. Samples were evaluated using expanded quantitative urine culture (EQUC) and 16S rRNA gene sequencing.<h4>Results</h4>With EQUC, there were no significant differences in median numbers of microbial species isolated among groups (p=0.96), even when considering Lactobacilli (p=0.72). However, there were trends toward different <i>Lactobacillus</i> species between groups. With 16S rRNA sequencing, the majority of urine samples contained Lactobacillaceae<i>,</i> with nonsignificant trends in relative abundance among groups. Using a Bayesian analysis, we identified significant differences in anaerobic taxa associated with phenotypic groups. Most of these differences centered on Bacteroidales and the family Prevotellaceae, although differences were also noted in Actinobacteria and certain genera of Clostridiales.<h4>Conclusions</h4>Associations between anaerobes within the urinary microbiome and postmenopausal recurrent UTI warrants further investigation.
Project description:Prostate cancer is the second leading cause of cancer death in men in the developed world. A more sensitive and specific detection strategy for lethal prostate cancer beyond serum prostate specific antigen (PSA) population screening is urgently needed. Diagnosis by canine olfaction, using dogs trained to detect cancer by smell, has been shown to be both specific and sensitive. While dogs themselves are impractical as scalable diagnostic sensors, machine olfaction for cancer detection is testable. However, studies bridging the divide between clinical diagnostic techniques, artificial intelligence, and molecular analysis remains difficult due to the significant divide between these disciplines. We tested the clinical feasibility of a cross-disciplinary, integrative approach to early prostate cancer biosensing in urine using trained canine olfaction, volatile organic compound (VOC) analysis by gas chromatography-mass spectroscopy (GC-MS) artificial neural network (ANN)-assisted examination, and microbial profiling in a double-blinded pilot study. Two dogs were trained to detect Gleason 9 prostate cancer in urine collected from biopsy-confirmed patients. Biopsy-negative controls were used to assess canine specificity as prostate cancer biodetectors. Urine samples were simultaneously analyzed for their VOC content in headspace via GC-MS and urinary microbiota content via 16S rDNA Illumina sequencing. In addition, the dogs' diagnoses were used to train an ANN to detect significant peaks in the GC-MS data. The canine olfaction system was 71% sensitive and between 70-76% specific at detecting Gleason 9 prostate cancer. We have also confirmed VOC differences by GC-MS and microbiota differences by 16S rDNA sequencing between cancer positive and biopsy-negative controls. Furthermore, the trained ANN identified regions of interest in the GC-MS data, informed by the canine diagnoses. Methodology and feasibility are established to inform larger-scale studies using canine olfaction, urinary VOCs, and urinary microbiota profiling to develop machine olfaction diagnostic tools. Scalable multi-disciplinary tools may then be compared to PSA screening for earlier, non-invasive, more specific and sensitive detection of clinically aggressive prostate cancers in urine samples.
Project description:<h4>Background</h4>Clinical dogma is that healthy urine is sterile and the presence of bacteria with an inflammatory response is indicative of urinary tract infection (UTI). Asymptomatic bacteriuria (ABU) represents the state in which bacteria are present but the inflammatory response is negligible. Differentiating ABU from UTI is diagnostically challenging, but critical because overtreatment of ABU can perpetuate antimicrobial resistance while undertreatment of UTI can result in increased morbidity and mortality. In this study, we describe key characteristics of the healthy and ABU urine microbiomes utilizing 16S rRNA gene (16S rDNA) sequencing and metaproteomics, with the future goal of utilizing this information to personalize the treatment of UTI based on key individual characteristics.<h4>Methods</h4>A cross-sectional study of 26 healthy controls and 27 healthy subjects at risk for ABU due to spinal cord injury-related neuropathic bladder (NB) was conducted. Of the 27 subjects with NB, 8 voided normally, 8 utilized intermittent catheterization, and 11 utilized indwelling Foley urethral catheterization for bladder drainage. Urine was obtained by clean catch in voiders, or directly from the catheter in subjects utilizing catheters. Urinalysis, urine culture and 16S rDNA sequencing were performed on all samples, with metaproteomic analysis performed on a subsample.<h4>Results</h4>A total of 589454 quality-filtered 16S rDNA sequence reads were processed through a NextGen 16S rDNA analysis pipeline. Urine microbiomes differ by normal bladder function vs. NB, gender, type of bladder catheter utilized, and duration of NB. The top ten bacterial taxa showing the most relative abundance and change among samples were Lactobacillales, Enterobacteriales, Actinomycetales, Bacillales, Clostridiales, Bacteroidales, Burkholderiales, Pseudomonadales, Bifidobacteriales and Coriobacteriales. Metaproteomics confirmed the 16S rDNA results, and functional human protein-pathogen interactions were noted in subjects where host defenses were initiated.<h4>Conclusions</h4>Counter to clinical belief, healthy urine is not sterile. The healthy urine microbiome is characterized by a preponderance of Lactobacillales in women and Corynebacterium in men. The presence and duration of NB and method of urinary catheterization alter the healthy urine microbiome. An integrated approach of 16S rDNA sequencing with metaproteomics improves our understanding of healthy urine and facilitates a more personalized approach to prevention and treatment of infection.
Project description:Synbiotics, the combination of probiotics and prebiotics, are known to confer health benefits via intestinal microbiota modulation. However, significant intestinal microbiota alterations can be difficult to determine in intervention studies based on solely bacterial stool metagenomic analysis. Intestinal microbiota constituents secrete 20-200-nm-sized extracellular vesicles (EVs) containing microbial DNA, proteins, and lipids that are distributed throughout the body, providing an alternative target for microbiota metagenomic analysis. Here, we determined the impact of a synbiotic beverage enriched with the kimchi-derived bacterium Leuconostoc holzapfelii (L. holzapfelii) on the intestinal microbiota and local and circulatory microbiota-derived EV composition of healthy Korean adults. We isolated microbial DNA from stool bacteria, stool EVs, and urinary EVs and conducted next-generation sequencing of the 16S rDNA V3-V4 regions before and after synbiotic consumption. The species diversity of circulating urinary EVs was significantly increased after synbiotic consumption, while stool bacterial and EV diversity remained unchanged. Furthermore, we found that while a single genus was decreased among the stool bacteria constituents, stool EVs and urinary EVs showed significant alterations in four and eight genera, respectively. Blood chemistry assays revealed that synbiotic consumption significantly lowered aspartate aminotransferase (AST) serum levels, particularly in subjects with starting levels above the normal range (>40?UI/L). In conclusion, the L. holzapfelii-enriched synbiotic beverage greatly altered serum AST levels and microbial EV composition in urine and stool, while only minor changes were observed in the gut microbiota composition. Based on these findings, we suggest the potential use of microbiota-derived EVs as surrogate markers in future predictive diagnosis studies.
Project description:Bacterial DNA and live bacteria have been detected in human urine in the absence of clinical infection, challenging the prevailing dogma that urine is normally sterile. Urgency urinary incontinence (UUI) is a poorly understood urinary condition characterized by symptoms that overlap urinary infection, including urinary urgency and increased frequency with urinary incontinence. The recent discovery of the urinary microbiome warrants investigation into whether bacteria contribute to UUI. In this study, we used 16S rRNA gene sequencing to classify bacterial DNA and expanded quantitative urine culture (EQUC) techniques to isolate live bacteria in urine collected by using a transurethral catheter from women with UUI and, in comparison, a cohort without UUI. For these cohorts, we demonstrated that the UUI and non-UUI urinary microbiomes differ by group based on both sequence and culture evidences. Compared to the non-UUI microbiome, sequencing experiments revealed that the UUI microbiome was composed of increased Gardnerella and decreased Lactobacillus. Nine genera (Actinobaculum, Actinomyces, Aerococcus, Arthrobacter, Corynebacterium, Gardnerella, Oligella, Staphylococcus, and Streptococcus) were more frequently cultured from the UUI cohort. Although Lactobacillus was isolated from both cohorts, distinctions existed at the species level, with Lactobacillus gasseri detected more frequently in the UUI cohort and Lactobacillus crispatus most frequently detected in controls. Combined, these data suggest that potentially important differences exist in the urinary microbiomes of women with and without UUI, which have strong implications in prevention, diagnosis, or treatment of UUI. Importance: New evidence indicates that the human urinary tract contains microbial communities; however, the role of these communities in urinary health remains to be elucidated. Urgency urinary incontinence (UUI) is a highly prevalent yet poorly understood urinary condition characterized by urgency, frequency, and urinary incontinence. Given the significant overlap of UUI symptoms with those of urinary tract infections, it is possible that UUI may have a microbial component. We compared the urinary microbiomes of women affected by UUI to those of a comparison group without UUI, using both high-throughput sequencing and extended culture techniques. We identified statistically significant differences in the frequency and abundance of bacteria present. These differences suggest a potential role for the urinary microbiome in female urinary health.