The Vaginal Microbiome in Women Recently Experiencing BV and UTI

The Vaginal Microbiome in Women Recently Experiencing BV and UTI | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results The Vaginal Microbiome in Women Recently Experiencing BV and UTI Sonia N. Whang , Xinyue Wang , Krystal J. Thomas-White , Genevieve Olmschenk , John E. Garza , Pita Navarro , View ORCID Profile Nicole M. Gilbert doi: https://doi.org/10.1101/2025.11.27.690987 Sonia N. Whang 1 Department of Pediatrics, Washington University School of Medicine in St. Louis , MO 63110, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Xinyue Wang 1 Department of Pediatrics, Washington University School of Medicine in St. Louis , MO 63110, USA 2 Institute for Informatics, Data Science and Biostatistics, Washington University School of Medicine in St. Louis , MO 63110, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Krystal J. Thomas-White 3 Evvy , New York, NY 10001, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Genevieve Olmschenk 3 Evvy , New York, NY 10001, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site John E. Garza 4 McDonnell Genome Institute, Washington University School of Medicine in St. Louis , MO 63310, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Pita Navarro 3 Evvy , New York, NY 10001, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Nicole M. Gilbert 1 Department of Pediatrics, Washington University School of Medicine in St. Louis , MO 63110, USA 5 Department of Obstetrics and Gynecology, Washington University School of Medicine in St. Louis , MO 63110, USA 6 Department of Molecular Microbiology, Washington University School of Medicine in St. Louis , MO 63110, USA 7 Center for Women’s Infectious Disease Research, Washington University School of Medicine in St. Louis , MO 63110, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Nicole M. Gilbert For correspondence: gilbert{at}wustl.edu Abstract Full Text Info/History Metrics Supplementary material Preview PDF ABSTRACT The vaginal microbiome (VMB) influences susceptibility to urogenital infections, yet large-scale, species-level metagenomic studies in real-world populations are rare. We analyzed shotgun metagenomic profiles and linked clinical metadata from 10,003 women across the United States who self-reported recent bacterial vaginosis (BV), urinary tract infection (UTI), both, or neither. Women reporting recent BV or UTI displayed distinct community structures, including higher prevalence of VALENCIA CST IV subtypes and significantly elevated alpha diversity compared with women who reported no prior diagnosis. Species-level Gardnerella profiling revealed that multiple Gardnerella species were enriched in BV but did not differ significantly between UTI and non-UTI groups, refining prior mechanistic hypotheses. Uropathogens such as E. coli, E. faecalis , and S. saprophyticus were detectable at higher prevalence and relative abundance in women who experienced UTI, including among participants who reported recent antibiotic use, consistent with the possibility of residual or recurrent vaginal colonization. These findings demonstrate that microbial signatures associated with recent BV and UTI remain detectable at population scale, provide a high-resolution reference for real-world vaginal metagenomics, and offer new directions for prevention strategies that consider the vaginal reservoir in recurrent urogenital infections. INTRODUCTION The vaginal microbiome (VMB) is a dynamic and complex microbial ecosystem that plays a central role in maintaining mucosal homeostasis, pathogen defense, and reproductive health. The VMB is often classified into Community State Types (CSTs) based on dominant bacterial taxa 1 . CST I, II, III, and V are dominated by the Lactobacillus species L. crispatus , L. gasseri , L. iners , and L. jensenii . These taxa help maintain an acidic vaginal environment through lactic acid production and other antimicrobial mechanisms. In contrast, CST IV is characterized by a diverse, polymicrobial community depleted of Lactobacillus and enriched for anaerobes. Importantly, CST IV represents a broad microbiologic category rather than a diagnostic entity, and clinical symptoms do not always correspond directly to CST classifications. To increase resolution within dysbiotic communities, the VALENCIA framework further subdivides CST IV into profiles dominated by Gardnerella (IV-A, IV-B), Prevotella (IV-C0), or other anaerobic taxa (IV-C1/2/3/4), enabling finer discrimination of heterogenous non- Lactobacillus states. Clinically, a polymicrobial VMB is diagnosed as bacterial vaginosis (BV). BV is the most common cause of vaginal discharge among reproductive-aged women 2 . It is diagnosed by the presence of at least three of four Amsel criteria: (1) thin, homogeneous, grayish-white vaginal discharge; (2) elevated vaginal pH (>4.5); (3) positive whiff test (fishy odor upon addition of potassium hydroxide); and (4) clue cells (epithelial cells coated in bacteria) on microscopy 3 . Molecular PCR diagnostics like the BD MAX™ Vaginal Panel that detect BV-associated taxa such as Gardnerella, Atopobium vaginae , and Megasphaera are also available. BV has been associated with serious health risks, such as increased susceptibility to sexually transmitted infections (STIs), pelvic inflammatory disease, urinary tract infections (UTI) and adverse pregnancy outcomes including preterm birth 4 , 5 . Globally, the prevalence of BV is high, ranging from 23-29% 2 . BV is highly recurrent and notoriously difficult to cure; 50%-80% of women will experience a recurrence within 6-12 months 6 , 7 . Several intrinsic and sociodemographic factors, including age, race and ethnicity, menopause status, and body mass index (BMI) are associated with increased rates of BV. Black women are more than twice as likely to develop BV compared to white women of European ancestry (non-Hispanic) and show the highest prevalence overall, followed by Hispanic women 2 . International data consistently show the highest BV rates among younger women in their reproductive years (aged 20-40) and decreasing rates as women age through perimenopause and post-menopause 8 – 10 . A meta-analysis estimated an average BV prevalence of approximately 16.9% in postmenopausal women 11 . Interestingly, the VMB often shifts to lower levels of Lactobacillus during perimenopause and post-menopause, despite lower rates of BV diagnoses 8 , again showing that a polymicrobial VMB is not always definitive of BV or symptoms. A relationship between body mass index (BMI) and BV has been noted 12 , but this observation is not consistent in all studies 12 – 14 . In the Women’s Interagency HIV Study (WIHS), obesity (BMI >30 kg/m²) correlated with lower BV prevalence among postmenopausal women (adjusted OR 0.87, CI 0.79–0.97), but no such relationship was observed in premenopausal women 15 . Collectively, these findings highlight a complex, context-dependent relationship between the VMB and symptomatic BV, underscoring the need to better understand microbial and host factors that predispose to persistent or relapsing disease. Urinary tract infections (UTIs) are among the most common bacterial infections acquired in the community and in hospitals, affecting millions of patients annually and resulting in substantial healthcare burden. More than 400 million UTI cases occur each year and the global burden of UTIs is rising 16 . Annually, the cost of diagnosing and treating UTI reaches billions of dollars globally, with approximately $2 billion per year in the United States 17 . UTI diagnosis can be made based on a combination of symptoms and a positive urine dip-stick analysis or culture. The infection is commonly present with a constellation of lower urinary symptoms including dysuria (pain or burning during urination), urinary frequency, urgency, suprapubic or lower abdominal discomfort, and cloudy or foul-smelling urine that may occasionally contain hematuria (blood in the urine). Most infections in all populations are caused by the Gram-negative uropathogenic E. coli (UPEC). UPEC accounts for 70–90% of community-acquired UTIs and approximately 50% of nosocomial UTI cases 18 . Beyond E. coli , other frequently isolated uropathogens include Klebsiella pneumoniae, Streptococcus agalactiae, Pseudomonas aeruginosa, Enterococcus faecalis , and Staphylococcus saprophyticus, and Proteus mirabilis . Women experience higher rates of UTI and recurrent UTI (rUTI) than men, and the risk of rUTIs may escalate after menopause 19 , 20 . Like BV, UTI is highly recurrent. 30-40% of women will experience a recurrence within 6 months, despite successful antibiotic treatment 21 , 22 , 23 . The gut and the vagina have long been recognized as potential reservoirs for uropathogens that could seed recurrent infections. Multiple studies, encompassing over 1,100 women, have linked the VMB to UTI risk, finding that women with BV or a Lactobacillus -deplete VMB are 2 to 13 times more likely to develop UTIs compared to their BV-free counterparts, even after adjusting for age and pregnancy status 24 – 27 . Vaginal interventions that restore Lactobacillus dominance 28 , 29 , including topical estrogen and probiotic L. crispatus 30 have shown protective effects, significantly reducing the recurrence of UTIs. Furthermore, the vagina is increasingly recognized as a potential reservoir for uropathogens implicated in UTIs. Its anatomical proximity to the urethra, along with factors such as sexual activity, hormonal changes, and hygiene practices, could facilitate the transfer of vaginal bacteria into the lower urinary tract and vice versa. Common taxa such as Gardnerella, Prevotella, Ureaplasma , and Lactobacillus frequently co-occur in vaginal and bladder samples, suggesting anatomical migration 31 , 32 . A growing body of evidence supports a close microbial connection between the VMB and the urinary tract. Culture-based and 16S rRNA studies have shown that the microbiomes of vaginal and catheterized urine samples display greater microbial similarity with each other than with the gut 33 . The correlation is particularly strong in women with acute BV 34 . Thus, vaginal microbes other than recognized uropathogens may also impact UTI susceptibility and severity. For example, our group has demonstrated in an experimental mouse model that transient exposure to Gardnerella can induce urothelial exfoliation and exacerbate UTI severity by promoting UPEC persistence or by reactivating latent UPEC reservoirs to cause rUTI and pyelonephritis 35 , 36 . Specifically, when we exposed mice to Gardnerella in their bladders prior to UPEC inoculation, the mice were more susceptible to persistent high-titer UPEC UTI 35 , 37 . When Gardnerella was inoculated into mice whose bladders harbored quiescent intracellular reservoirs (QIRs) of UPEC from a previous (resolved) UTI, Gardnerella exposure triggered UPEC egress to cause rUTI 36 , 38 . Furthermore, Gardnerella strains exhibited clade-dependent differences in bladder pathogenicity in our mouse model 35 , 38 , underscoring the need to investigate their distinct relationships with UTI in women. These data establish a biologically plausible link between the vaginal microbiome and UTI susceptibility. However, whether these mechanistic observations translate to human populations—and whether specific Gardnerella species contribute differentially to BV versus UTI—remains unclear. Shotgun metagenomics offers species-level, and in some cases strain-level, resolution of vaginal communities, enabling more precise evaluation of microbial signatures linked to BV, UTI, and other urogenital conditions. Despite its advantages, shotgun metagenomics has predominantly been applied in small cohorts or controlled research studies, limiting population-level insights. Large-scale, real-world metagenomic datasets have the potential to address this gap by capturing a broader range of life-course, demographic, symptom, and treatment variables that influence microbial ecology and infection risk. Here we report on our academic-industry collaboration analyzing shotgun metagenomic profiles and linked metadata from 10,003 women across the United States who self-reported recent BV, UTI, both infections, or neither. To our knowledge, this study represents the largest shotgun metagenomic analysis of the vaginal microbiome in relation to BV and UTI in a real-world population. Participants answered a questionnaire which allowed us to evaluate associations between the VMB, demographic, lifestyle, life course, symptoms, diagnoses, and treatments. This dataset enabled us to (1) evaluate associations between recent BV and UTI history and VMB composition at population scale, including CST and VALENCIA community structure; (2) characterize species-level Gardnerella profiles in relation to both BV and UTI to refine mechanistic hypotheses generated from prior animal work; and (3) examine the prevalence and relative abundance of vaginal uropathogens, including among participants who reported recent antibiotic use, to explore whether microbial signatures remain detectable after treatment. Together, these analyses leverage real-world, high-resolution metagenomics to deepen understanding of vaginal–urinary microbial relationships and provide a critical reference framework for future mechanistic, clinical, and precision-medicine studies focused on recurrent urogenital infections. RESULTS Participant Characteristics and Group Designations This retrospective observational study included 10,003 participants that self-collected and submitted vaginal swabs for microbiome characterization via shotgun metagenomic sequencing between November 2022 and May 2024. The participants in the study were distributed across all major geographic regions of the United States, including the Northeast, South, Midwest, and West. Participants were classified into four groups ( Figure 1 ): recent BV only (BV; n = 4846), recent UTI only (UTI; n = 1185), both BV and UTI within the past 30 days (BV&UTI; n = 1053), and never diagnosed with either BV or UTI (ND; n = 2919). There were significant differences in self-reported race and ethnic background, menopause status, age, and body mass index (BMI) between groups ( Table 1 , Supplementary Table 1 ), which is consistent with prior research linking these characteristics to BV and UTI risk as well as VMB composition. Hence, our data analysis was adjusted for race/ethnicity, age, menopause, and BMI. Download figure Open in new tab Figure 1: Group designations and study design. Shotgun metagenomic sequencing was performed on self-collected vaginal swabs. The participants completed a health history questionnaire and were classified into study groups based on their answers to the indicated questions. View this table: View inline View popup Download powerpoint Table 1: Group Demographics. Categorical variables, two-sided Chi-squared tests. Continuous variables, adjusted LS-mean and post-hoc multiple comparison tests. Community structure differs markedly by recent BV and UTI history First, we examined the taxa present in the VMB of all the participants included in the study ( Figure 2A ). Each column of the heatmap represents the data from a different participant, while the rows listed the relative abundances of the top 50 bacterial taxa. Lactobacillus and Gardnerella were the most abundant genera ( Figure 2A ). L. crispatus was the most abundant Lactobacillus and coincided with lower Shannon diversity, as well as CST I and Valencia Type I-A /I-B classifications. VMB dominated by L. iners (CST III, Valencia IIIA/IIIB), L. gasseri (CST II, Valencia II), and L. jensenii (CST V, Valencia V) were also present. The top Gardnerella species included G. swidsinskii and G. vaginalis as the most abundant, followed by G. piotii , G. leopoldii , and G. spA . CST IV samples had higher Shannon diversity and included Gardnerella , Fannyhessea , Prevotella , Megasphaera , Sneathia , and other BV-associated bacteria. The distributions of all CST and Valencia Types were significantly different between groups ( Supplementary Table 2A-B ). Consistent with established literature 39 , CST I, III, and IV were the most abundant classifications among all participants ( Figure 2B , Supplementary Table 2A ). The ND and UTI groups had a higher proportion of CST I and lower CST IV compared to both the BV and BV&UTI groups ( Supplementary Table 2A ). Additionally, the BV group was less likely to have CST V and more likely to have CST III, while the UTI and BV&UTI groups were more likely to have a CST II compared to ND ( Supplementary Table 2A ). According to Valencia types ( Figure 2C ; Supplementary Table 2B ), the breakdown of CST between ND and UTI were very similar except that the CST IV Valencia Type stratification in the UTI group was more likely to have C0 or C2, which carry an abundance of Prevotella and Enterococcus , respectively. In addition, the BV&UTI group were more likely to classify as CST IV-B ( Gardnerella / Atopobium ) and IV-C0 ( Prevotella ), which is consistent with other studies of women with UPEC UTI and BV diagnosis 40 . In summary, the VMB composition recapitulated known relationships between the VMB and higher CST IV prevalence in BV, while providing new nuanced differences in the VMB of UTI women. Download figure Open in new tab Figure 2: Community structure differs markedly by recent BV and UTI history. (A) Heatmap of the relative abundance of the 50 most abundant VMB species, study group, CST, Valencia type, and Shannon diversity from all 10,003 participants. Comparative distribution of (B) CST and (C) Valencia Type in each study group. Full p -values and statistical analysis of the CST and Valencia types are listed in Supplementary Tables S2A-B , respectively. Vaginal microbiome alpha diversity was assessed using (D) Shannon Index and (E) Simpson Index and compared using Adjusted LS-mean. ***p <0.01 ***p <0.001, ****p <0.0001. (F) Principal component analysis (PCoA) of individual participants, represented by dots and colored based on the groups. Ellipses indicate 95% confidence intervals and bacterial species accounting for the largest differences are indicated. (G) PCoA of Bray-Curtis distance plot is depicted. Alpha and beta diversity comparisons between groups Consistent to the polymicrobial nature of the condition, both groups reporting BV had significantly higher Shannon & Simpson indexes (alpha-diversity) than ND ( Figure 2D-E ). There was no significant difference in Shannon index noted between BV and BV&UTI. Notably the UTI group women also exhibited an increase in alpha diversity (Shannon: *** p = 0.0002, Simpson: ** p = 0.0083) compared to ND. These data demonstrate that women reporting recent UTI have an intrinsically more diverse VMB compared to women in the ND group. We generated a principal coordinate analysis (PCoA) based on a Euclidean distance plot ( Figure 2F ) to compare dissimilarity measures and determine the microorganisms that could be attributed to the differences between groups. This analysis identified L. crispatus and L. iners as the greatest drivers of group variation (45%), followed by several Gardnerella species (22.6%). The ND group cluster was positioned towards L. crispatus , while both the BV and BV&UTI groups were shifted toward L. iners and Gardnerella species ( Figure 2F ). The UTI group had substantial overlap with ND, with only a slight shift toward the other two groups. A very similar pattern and shift was observed using a Bray-Curtis distance plot ( Figure 2G ). Bray-Curtis dissimilarity was significantly different between groups based on an unadjusted permutational multivariate analysis of variance (PERMANOVA) analysis, but was not significant after adjusting for race, age, BMI and menopause status. Symptoms and quality of life Women experiencing BV or UTI had a significantly higher (meaning worse) quality of life score compared to ND women ( Figure 3A ) and reported significant effects on their sleep, work/education, emotional health, intimate and sexual relationships, social life, finances, and ability to do physical activities ( Supplementary Table 3 ). Women in the BV, UTI, and BV&UTI groups were significantly more likely than ND to submit their sample because they’ve had persistent symptoms or because they were experiencing recurrent vaginal infections ( Supplementary Table 4 ). Likewise, the rates of reported symptoms were significantly different between the four groups and matched what would be expected for each infection ( Figure 3B , Supplementary Table 5 ). For example, the women in the BV groups were more likely than ND to report that they experienced excessive discharge , odorous discharge and vaginal swelling. Thin vaginal fluid and fishy odor are hallmark and diagnostic features of BV. Moreover, odorous discharge and several vaginal smells (fishy, rotten, musty) were significantly positively associated with BV-associated bacteria, including Gardnerella, Sneathia, and Prevotella, and were negatively associated with L. crispatus ( Figure 3C ). Women in the UTI groups more often experienced the hallmark UTI symptoms of burning sensation and pain while peeing and also had a higher rate of vulvar pain . There were fewer microbial associations with UTI symptoms than there were with BV symptoms, but E. coli , the leading cause of UTI, was positively associated with burning sensation ( Figure 3C ). Patterns of sexual activity were different between the four groups and were consistent with prior reported links between sexual behaviors, BV and UTI ( Supplementary Table 6) . Download figure Open in new tab Figure 3: Symptoms and quality of life. (A) Quality of life (QOL) score analyzed using LS-mean, adjusted for confounders. **p <0.01, ****p <0.0001. ( B ) Heatmap of odds ratios comparing self-reported symptoms, derived from Supplementary Table 5. ( C ) Heatmap of MaAsLin2 analysis indicate the magnitude and direction of significant associations between common urogenital symptoms and bacterial species. MI = mild, MO = moderate, SE = severe. FI= fishy, RO = rotten, SO = sour, ME = metallic, CL = bleach/ammonia, MU = musty, ON = onion or body odor-like, SW = sweet, VI = vinegar-like, OT = other, YE = yeasty (bead or starch-like). Species-level Gardnerella profiles distinguish BV from ND but not UTI from non-UTI Our previous mouse models demonstrated that urinary tract exposure to Gardnerella exacerbates UTI caused by uropathogenic E. coli both by promoting persistent infections 37 or by triggering recurrence from latent intracellular reservoirs 38 , 36 , 35 . We recently reported that only certain Gardnerella species can persist in the bladder or cause urothelial damage and inflammation 41 . We hypothesized that women experiencing UTI might harbor higher levels or distinct species of vaginal Gardnerella which could serve as a reservoir for UTI-promoting urinary tract exposures. Therefore, we compared the relative abundance levels of Gardnerella between each group. Approximately 20% of women in each of the BV groups had a VMB dominated by (>50% relative abundance) Gardnerella , which was a significantly higher frequency than in the ND and UTI groups ( Figure 4A ). Likewise, both groups reporting BV had significantly higher total Gardnerella relative abundance than the ND group ( Figure 4B ). Similar patterns were observed for the most abundant Gardnerella species, with significantly higher G. vaginalis, G. piotii, G. swidsinskii, G. leopoldii, and G. spA in both BV groups relative to the ND group ( Figure 4C-G ). Among the less abundant Gardnerella, G. spB, G. spE , and G. spG exhibited significantly higher levels in the BV compared to the ND group ( Figure 4H ; Supplementary Figure 1C and 1E ). G. spB was significantly higher in the BV compared to the BV&UTI group ( Figure 4H ), and G. spD was significantly higher in the BV&UTI compared to the ND group ( Supplementary Figure 1B ). Most samples had multiple Gardnerella species and only a small proportion of women in the study had a VMB dominated by a single ( Supplementary Fig 1G-J ). Prior studies have reported both positive and negative correlations between certain Gardnerella species 42 , 43 . In our study, pairwise correlation analyses found that the relative abundance levels of all Gardnerella species were significantly positively correlated with each other in all four groups ( Figure 4I-L ). The correlations were strongest between G. vaginalis, G. piotii, G. leopoldii , and G. swidsinskii, G. spA, G. spB, and G. spG. To summarize, our results were consistent with previous studies that have established Gardnerella as a BV-associated genera with varying relative abundances between distinct species. Contrary to our hypothesis, there was no apparent association between Gardnerella relative abundance or species distribution and recent UTI experience. Download figure Open in new tab Figure 4: Species-level Gardnerella profiles distinguish BV from ND but not UTI from non-UTI. (A) Prevalence of Gardnerella -dominant (>50% relative abundance) VMB. * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001, Pearson Chi-square test. Comparisons of species-level Gardnerella dominance data are in Supplementary Figure 1G-J . B-H Gardnerella relative abundance comparisons using adjusted LS-mean. * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001. Comparative analysis of Gardnerella spC-spH relative abundances are provided in Supplementary Figure 1A-F. ( I-L ) Correlation matrices of Gardnerella species from each group, using Spearman correlation. Vaginal uropathogens are more prevalent and abundant among participants with recent UTI Having not identified any Gardnerella species that were increased in women recently experiencing UTI, next we conducted pairwise linear discriminant analysis (LDA) effect size (LEfSe) analysis to identify which vaginal taxa were enriched in each group. As expected, we observed different patterns of Lactobacillus and BV-associated bacteria between groups. Interestingly, the UTI group was enriched for L. gasseri relative to the ND group, which was enriched for L. jensenii ( Figure 5A ). The ND group had enriched L. crispatus , consistent with the higher proportion of CST I, and L. jensenii relative to the BV ( Figure 5B ) and the BV&UTI ( Figure 5C ) groups. Women reporting BV were also enriched for L. iners ( Figure 5B ). The groups reporting BV were also enriched for several Gardnerella species and other BV-associated taxa including Prevotella , Sneathia , and Fannyhessea relative to the ND group ( Figure 5B-C ). We also utilized MaAsLin 2 to determine the taxa associated with each infection group relative to ND ( Figure 5E ). Again, L. crispatus was negatively (blue) associated, whereas bacteria like Prevotella, Fannyhessea, and Sneathia , were positively (red) associated with both BV and BV&UTI. Nine Gardnerella species were associated with both the BV and BV&UTI groups. Among these, G. vaginalis , G. piotii , G. spA , G. spB , and G. spE were additionally associated with the UTI group. Results from both the LEfSe and MaAsLin 2 analyses suggested that vaginal colonization by uropathogens is more common in women reporting UTI. MaAsLin identified that E. coli and S. agalactiae were positively associated with the UTI group relative to ND ( Figure 5E ). Both the UTI and BV&UTI groups had enrichment of known uropathogens, including E. coli , K. pneumoniae , E. faecalis , and S. agalactiae ( Figure 5A and 5C ) . The BV&UTI group was also enriched for P. mirabilis and Candida albicans ( Supplementary Figure 2C ) compared to ND. Similarly, the BV&UTI group could be distinguished from the BV group based on enrichment for E. coli, E. faecalis, P. mirabilis, K. pneumoniae, and C. albicans ( Figure 5D ). Download figure Open in new tab Figure 5: Microbial associations with recent BV or UTI include known BV-associated bacteria and uropathogens. ( A-D ) Pairwise linear discriminant analyses. LDA scores represent the effect size of each abundant species. Species enriched in each group with an LDA score >2.5 are shown for (A) ND vs UTI and (D) BV vs BV&UTI, and an LDA score > 3.0 is depicted for (C) ND vs BV and (D) ND vs BV&UTI. For a full list of abundant species with LDA scores > 2.0, see Supplementary Figure 2A-D. (E) Heatmap of results from MaAsLin2 analysis indicates the magnitude and direction of significant associations between the study groups and the bacterial species. Microbial signatures of BV and UTI remain detectable among participants reporting recent antibiotic use Given these observations, we evaluated the relative abundance of the potential uropathogens E. coli, K. pneumoniae, E. faecalis, P. mirabilis, S. agalactiae, S. saprophyticus, P. aeruginosa, and C. albicans in the VMB collectively and individually. Uropathogen relative abundances were generally low in comparison to the levels of Lactobacillus and Gardnerella species. Notwithstanding, collective uropathogen relative abundance was significantly higher in the UTI and BV&UTI groups compared to ND ( Figure 6A ). E. faecalis and K. pneumoniae relative abundances were significantly higher in the UTI group compared to ND ( Figure 6C and 6E ). The BV&UTI group had significantly higher levels of E. coli, E. faecalis, K. pneumoniae, and P. mirabilis compared to ND ( Figure 6B-E ). Furthermore, E. coli , K. pneumoniae and P. mirabilis were significantly more abundant in the BV&UTI group compared to BV ( Figure 6B and 6D-E ). The prevalence of uropathogens was significantly higher in women who reported recent UTI, even after adjusting for confounding factors ( Table 2 ; ND vs. UTI Adj OR 1.4; CI 1.2-1.6; ND vs BV&UTI Adj OR 1.4; CI 1.2-1.6). E. coli, E. faecalis, K. pneumoniae , S. saprophyticus and S. agalactiae were more prevalent in the VMB of women reporting UTI than their ND counterparts. Women who experienced BV&UTI exhibited a higher prevalence of E. coli, E. faecalis, K. pneumoniae , S. agalactiae and P. mirabilis compared to the ND group and a higher prevalence of E. coli, E. faecalis and P. mirabilis compared to the BV group. Finally, E. faecalis was more prevalent in the BV compared to the ND group ( Table 2 ). Download figure Open in new tab Figure 6: Vaginal uropathogens are higher among participants with recent UTI, even those taking antibiotics. (A-E) Relative abundances of uropathogens with significant differences between groups. ( F) Schematic of sub-analysis stratifying participants within each group based on reported antibiotic use within the last 30 days. Received antibiotic (+) vs no antibiotics (-) treatment. (G-L) Relative abundance of uropathogens with significant differences between the groups. (M) Heatmap summary of all the significant differences in uropathogen abundance between the AB treated groups (+) , non-treated group (-) , and both (ALL) compared to ND. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. View this table: View inline View popup Download powerpoint Table 2: Comparison of uropathogen prevalence. Odds ratio and 95% confidence intervals using the logistic regression model. Presence was defined by a relative abundance of >0.1% and <0.1% was considered as absence. As would be expected, women in the BV, UTI and BV&UTI groups were much more likely to report having taken antibiotics in the past 30 days. This was also true for other treatments such as probiotics, antifungals, hormones, boric acid suppositories, and feminine hygiene products ( Supplementary Table 7 ). We reasoned that the patterns of uropathogen colonization could be different between women who did or did not report taking antibiotics (AB). We anticipated that women taking AB might have lower levels of uropathogens and that the differences we observed in relative abundance levels could be contributed primarily by women who reported that they experienced UTI but did not seek antibiotic treatment. Therefore, we divided each infection group into participants that either reported using antibiotics (+/AB) or not (–/NO). Each subgroup was compared to the whole ND group because there was no difference in uropathogen colonization based on antibiotic use in the ND group ( Supplementary Table 8 ). Contrary to our expectations, uropathogen relative abundances were significantly higher in the BV and BV&UTI groups only in the women who took AB relative to the ND group ( Figure 6G ) . E. faecalis levels were significantly higher in all three AB subgroups ( Figure 6I ). The comparative analysis revealed a difference in E. faecalis , S. saprophyticus and S. agalactiae between women in the BV group who took AB (+) and the ND group ( Figure 6I and 6K-L ; Supplementary Table 8 ). Moreover, BV&UTI participants that took antibiotics had a higher abundance of E. coli , E. faecalis , and P. mirabilis , compared to ND participants ( Figure 6H-J ). E. faecalis, E. coli , and S. saprophyticus were highly abundant in UTI women that took antibiotics ( Figure 6H-I and 6K ). MaAsLin2 analysis revealed E. coli and S. agalactiae to have a high association with AB treatment. ( Supplementary Figure 3 ). Antifungals had a negative association with many BV-bacteria such as Gardnerella, Fannyhessea, Megasphaera , and Prevotella , but they had a strong positive association with boric acid treatment. We saw the opposite pattern when we examined Gardnerella abundances with respect to antibiotic use. Although total Gardnerella levels were significantly higher in the BV groups irrespective of antibiotics, the levels of G. leopoldii and 5 of the unnamed Gardnerella species were only significantly higher in the BV groups who did not take AB ( Supplementary Table 9 ). In summary, antibiotic use appears to correspond with shifts in BV-associated bacteria but not in a reduction of uropathogens in the VMB. Discussion The importance of the vaginal microbiome in women’s quality-of-life and risk of infection is receiving increased attention outside of academic and clinical settings. The success of recent citizen-science studies of the VMB demonstrates the enthusiasm of women to provide self-collected samples for studies aimed at understanding and improving their health 44 , 45 . Women are often looking for answers to urogenital discomfort and recurrent infections that current clinical methodologies and treatments do not resolve. In this large study of 10,003 women across the United States, we identified distinct vaginal microbial signatures associated with recent histories of BV, UTI, or both conditions. Using shotgun metagenomics, we found robust enrichment of multiple Gardnerella species and anaerobe-dominant VALENCIA CST IV subtypes among individuals reporting recent BV or BV&UTI, along with significantly elevated alpha diversity relative to participants without recent diagnoses and who had never been diagnosed with either condition. In contrast, individuals reporting recent UTI without BV displayed more heterogeneous community structures and increases in uropathogen prevalence, highlighting the complexity of vaginal–urinary microbial interactions in human populations. Relationships that are evident in the literature between the VMB, symptoms, demographics, and BV and UTI were largely recapitulated in this real-world study in which self-sampling and reporting of health and lifestyle parameters occurred in the privacy of the home. Species-level Gardnerella resolution clarified and extended prior observations. Multiple Gardnerella species were strongly enriched in women reporting recent BV, but none distinguished participants with and without recent UTI. These results refine hypotheses derived from animal models showing that Gardnerella exposure can promote UTI by uropathogenic E. coli . Our findings suggest that while Gardnerella abundance is a clear biomarker of BV, it may not differentiate UTI risk at the population level, or that such associations may be obscured by heterogeneous infection timing, antibiotic exposures, or low-level species or strain differences not captured in this dataset. Prior studies have implicated Gardnerella in BV treatment failure, linking persistence to recurrent BV (rBV) 46 . Here we observed a different pattern of Gardnerella species between women who did or did not report antibiotic use, but the total Gardnerella levels were not significantly different. These associations highlight the need for further study of specific Gardnerella clades to understand the clinical significance of species-level dynamics. For example, shotgun metagenomics facilitates the detection of mobile genetic elements, antimicrobial resistance genes, and metabolic pathways, offering deeper insights into the functional potential of vaginal microbial communities. Metagenome-assembled genomes could be generated to identify Gardnerella genes or pathways associated with BV or UTI history or specific symptoms that women report experiencing. We also observed that established uropathogens—including E. faecalis , E. coli , and S. saprophyticus —were detectable at higher prevalence and relative abundance in the VMB among participants reporting recent UTI. Although the levels were lower than more typical VMB members, the large sample size equipped us to detect significant associations that would likely be missed in smaller studies. Prior works suggests that the relative abundance levels of uropathogens need not be high to confer risk for UTI. Patients with uropathogenic E. coli in their GI tract had increased risk of UTI, even though it only accounted for <1% relative abundance of the GI microbiome 47 . Notably, uropathogens remained detectable in our study among individuals who reported recent antibiotic use. Because precise infection and antibiotic timing could not be determined, we cannot conclude that these taxa persist after treatment. However, their continued detection is consistent with the possibility of residual or recurrent colonization and supports the concept of the vagina as a reservoir for uropathogens in recurrent UTI. Current clinical practice does not routinely consider the VMB when diagnosing and treating UTIs. Together with prior work, our study underscores the need to consider treatments directed toward eradicating the uropathogen and potential UTI co-conspirators from the vaginal reservoir in future personalized medicine approaches to prevent recurrent UTI. Behavioral and symptom data provided additional context for understanding microbial states. Symptoms typical of BV (odor, discharge, irritation) tracked closely with CST IV and Gardnerella -enriched communities, while reports of sexual activity patterns, including new partners and intercourse frequency, aligned with increased microbiome diversity and reduced Lactobacillus representation. Although causality cannot be inferred, these associations support existing hypotheses that behavioral and mucosal factors modulate susceptibility to vaginal dysbiosis and may influence trajectories of recurrent urogenital infections. Here we focused on BV and UTI because of our basic science research expertise. We note that we also observed vulvar redness and internal itchiness , which are hallmark features of vulvovaginal Candidiasis (VVC), to be positively associated with Candida albicans ( Supplementary Figure 4 ). Therefore, our study provides a framework for real-world investigations of other urogenital infections such as VVC. We acknowledge that there are limitations inherent in this study, including the self-collection of vaginal specimens and the self-reporting of infections, symptoms, and treatments. Even though standardized collection kits were used, there could be variation in collection methods by different participants. The infection groups in this study included samples from women who reported that they experienced BV or UTI (including those who hadn’t been diagnosed, but believed they had it) sometime in the past 30 days. We do not have specific dates of when the infections occurred, and diagnoses were not confirmed by a clinician at the time of sample collection. Approximately 85% of the women who answered “I think so” also reported that they had been diagnosed with the same infection in their lifetime (BV 84.2% = 3424/4066; UTI 85.2% = 1030/1209) and were therefore equipped to recognize their symptoms associated with past clinical diagnoses. We note that it is common practice for clinicians treating patients with a history of rBV or rUTI to prescribe antibiotics based on symptom onset without a clinic visit. Antibiotic use was reported in the last 30 days and should not have occurred during the 7 days immediately prior to sample collection (based on the standard submission instructions), but we do not know the exact timing or type of antibiotics used. Finally, the ND group in this study included women who reported that they had never been diagnosed with BV or UTI in the past nor did they think they had it within the last 30 days. However, they were not precisely all healthy controls devoid of infections; nearly 80% (2333/2920) of the ND group reported no other infections in the last 30 days, leaving 20% that reported at least one other infection (i.e., aerobic vaginitis, yeast infections). Nearly all women in the study reported that they had been diagnosed with at least one urogenital infection in their lifetime. Despite these limitations, the VMB composition, symptoms, and demographic patterns in each group in this study matched strikingly well with what has been reported from clinical studies. Together, these findings advance understanding of vaginal microbial ecology at population scale and highlight several implications for clinical practice and future research. First, the strong enrichment of Gardnerella and other BV-associated species in women reporting recent BV despite recent antibiotic use supports the current idea that microbial persistence drives recurrent BV. Second, the detection of uropathogens despite recent antibiotic use underscores the need for improved therapeutic strategies that address vaginal reservoirs, promote sustainable Lactobacillus colonization, and disrupt microbial communities associated with recurrent UTI. Third, the overlapping symptoms and microbial signatures in women experiencing both BV and UTI in close succession supports integrated approaches to managing these infections, rather than treating them as isolated conditions. Fourth, this study demonstrates the feasibility and value of leveraging real-world metagenomic data, paired with detailed symptom, treatment, and behavioral metadata, for translational insights that complement traditional clinic-based studies. Methods Sample collection and questionnaire All study participants provided informed consent, and study procedures were conducted in accordance with protocols approved by a federally accredited Institutional Review Board (IRB# 20220118.evvy). Vaginal samples and metadata were collected between November 2022 and May 2024. Women filled out an online questionnaire reporting their demographic, lifestyle and sexual behavior information (see Supplementary Materials for more details). In Table 1 , women experiencing perimenopausal symptoms as well as women diagnosed perimenopausal by a doctor were both combined under ‘Perimenopause.’ ‘Early menopause’ included women who experienced hysterectomy, uterine ablation, primary ovarian insufficiency, chemotherapy, etc. Sequencing Sample inclusion required patients to have completed vaginal microbiome characterization via shotgun metagenomic sequencing through Evvy’s VMB telehealth service platform following previously established protocols 48 . A sample collection kit (Copan, Murrieta, CA, USA) was shipped directly to the participant who self-collects a vaginal swab and ships the sample at ambient temperature to a CLIA, CAP, and CLEP certified lab (CLIA 45D1086390, CAP 7214171, PFI 9433 Microgen DX, Lubbock, TX, USA). Samples were processed, which includes a chemical and mechanical lysis, host depletion, and DNA extraction using an automated extraction handling instrument. NGS libraries were prepared, multiplexed, quality checked, and sequenced on the Illumina NovaSeq 600 (Illumina, San Diego, CA, USA). Sequencing data were processed through Evvy’s pipeline, which is specifically designed to characterize the vaginal microbiome. Samples that passed detection thresholds were reported to the provider and patient 48 . Participant data collection on the platform included questionnaires documenting symptomatology, relevant clinical diagnoses, and demographic information. Survey questions analyzed in this study are listed in the Supplementary Materials document. Group Designations Participants were stratified based on their responses to an initial survey at the time of self-collected sample submission ( Figure 1 ). Participants were asked, “In the past 30 days, have you been diagnosed by a medical professional with any of the following infections?” They could answer “Yes” , “Not diagnosed, but think I’ve had this in the past 30 days” , or “No” to UTI and BV selections (in addition to other urogenital infections not analyzed in this study). Women who responded with “Yes” or “Not diagnosed, but think I’ve had this in the past 30 days” to either infection were included in the corresponding BV ( N = 4846) or UTI (N = 1185) groups. If they responded positively to the question for both infections, then they were included in the BV&UTI (N = 1053) group. Women who answered “No” to both infections and also answered “Never Diagnosed” to the question “How often have you been diagnosed with each of the following conditions?” were placed in the Never Diagnosed ( ND ; N = 2919) group. Participants were instructed to “avoid testing while menstruating, as well as if they have had sex, used an oral antifungal, vaginal suppositories, or vulvar topical cream in the last 24-48 hours, or taken antibiotics within the last 7 days.” Metagenomic analysis Metagenomic data analysis was conducted via a custom bioinformatics pipeline 48 . Evvy’s proprietary pipeline includes processing raw sequencing reads through quality filtering and host sequence depletion. Samples are required to have at least 20,000 non-human reads to continue through the bioinformatic pipeline. The reads are then aligned to a proprietary reference database generated from a curated collection of vaginal microbial genomes to generate taxonomic relative abundance profiles. Gardnerella species were determined as we previously described 49 . There are many unclassified Gardnerella sp. genomes, but we classified these genomes into subtaxa groups spA-spH. Statistical analysis Statistical analyses were conducted using SAS software (SAS Studio via SAS OnDemand for Academics), Prism software 10 (GraphPad Software Inc, San Diego, CA), Python (Python Software Foundation, Delaware, US), and R (version 4.5.0, R Foundation for Statistical Computing, Vienna, Austria). Our primary objectives were to examine whether vaginal microbiome composition differed between groups and whether the relative abundances of Gardnerella species and established uropathogen species differed between groups. Clinical subgroups included: Never diagnosed (ND; reference), UTI, BV, and BV&UTI. P -values < 0.05 were considered significant. Relative abundance values were derived from metagenomic sequencing data and log-transformed to improve normality where necessary. All models were checked for assumptions of normality, homoscedasticity, and multicollinearity. We used generalized linear models (GLM) to evaluate differences in mean relative abundance of Gardnerella and uropathogens across groups. The primary predictor was the clinical group, while age, body mass index (BMI), self-reported race/ethnicity, and menopausal status were included as covariates to control for potential confounding. Least-squares mean (LS-mean) were estimated and pairwise differences between groups were assessed using Bonferroni-adjusted p -values and 95% confidence intervals. This approach allowed us to identify statistically significant differences in Gardnerella and uropathogen abundance while accounting for demographic heterogeneity in the study population. To assess the association between Gardnerella and uropathogen abundance and odds of UTI and/or BV, we conducted multivariable logistic regression analyses. The outcomes were binary clinical variables, and the independent variable of interest was the relative abundance of Gardnerella and uropathogenic species. Models were adjusted for age, BMI, race, and menopausal status. Adjusted odds ratios with 95% confidence intervals were reported. In exploratory models, we also examined effect modification by menopausal status and race using interaction terms. To control for inflated type I error due to multiple comparisons, Bonferroni correction was applied to all pairwise comparisons within the GLM framework. For logistic regression models with multiple microbial predictors, we used false discovery rate correction when appropriate. To compare categorical microbial abundance classifications (Dominance vs Non-dominant; Presence vs. Absence) across study groups, we performed two-tailed Chi-square tests of independence. We determined dominance as 50% microbial relative abundance or higher, and presence as 0.1% relative abundance or above to ensure analytical robustness. These analyses evaluated whether the prevalence of Gardnerella species and uropathogens differed among the four clinical subgroups (ND, UTI, BV, and BV&UTI). Pairwise comparisons between study groups (UTI vs ND, BV vs ND, BV&UTI vs ND, UTI vs BV, BV&UTI vs UTI, BV&UTI vs BV) were conducted, and the resulting Chi-square p -values were summarized in tables to indicate statistically significant differences in species-level distributions. All categorical analyses were two-sided, and p < 0.05 was considered statistically significant. Microbiome features, diversity, and association analyses The metadata associations between microbiome features (microbial taxa) and symptoms/groups/diagnosis/treatments were determined using the MaAsLin2 package within R. MaAsLin2 creates generalized linear mixed effect models to analyze clinical metadata associations with microbial metagenomic features. A heatmap and hierarchical clustering based on Euclidean distance, depicting patterns of abundance from the metagenomic data of each participant was constructed using the ‘pheatmap’ package within R. The heatmap annotations display the VMB profiles classified based on established community state type (CST) and Valencia categories, the Shannon diversity index values, and the study group. Principle coordinate analysis (PCoA) was used to evaluate the similarities or differences in the composition of the sample communities based on Euclidian and Bray-Curtis distances by ‘factoextra’ and ‘adonis’ packages, respectively ( 79 ). Alpha diversity (Shannon and Simpson Indexes) and beta diversity (Bray-Curtis Index) were carried out using the packages ‘vegan’ and ‘ggplot’. Significance of PCoA of Bray-Curtis dissimilarity was analyzed using pairwise permutational multivariate analysis of variance (PERMANOVA) and performed with 999 permutations using the ‘vegan’ package and ‘adonis’ function. Differential analysis of taxa was performed using the Python package LEfSe v1.0. In addition, p 2 obtained by linear discriminant analysis were considered statistically significant. The correlation matrices of Gardnerella species were produced by GraphPad Prism analysis, using Spearman correlation and analyzed by a two-tailed test. Data visualization was performed with GraphPad Prism, Python, and R. Data availability This research study was co-sponsored by Evvy and Washington University School of Medicine, and the authors of the paper who have access to the data are employees or WashU scientific collaborators of Evvy who have signed contracts with Evvy to be bound by Evvy’s privacy policy and access restrictions. Additional data can be made available through a Data Transfer Agreement that protects the privacy of participants’ data; interested researchers may make requests by contacting kate{at}evvy.com . The information provided by interested researchers will be used to generate a Data Transfer Agreement (DTA). The DTA protects the privacy of the participants’ data and will need to be signed by both the institution and Evvy before data can be transferred. Additional specifications for laboratory protocols and metagenomics bioinformatic pipelines can be made available upon request. Code availability Analysis code is available at GitHub under project titled “Vaginal Microbiome in Women Recently Experiencing BV & UTI” https://github.com/GilbertLab778/Evvy-BV-UTI References Author contributions Sonia N. Whang – data preparation and analysis, concept, study design, biostatistical analysis, manuscript draft, figure preparation Xinyue Wang – biostatistical analysis, table preparation, manuscript draft Krystal J. Thomas-White – data preparation, concept and expertise, manuscript editing Genevieve Olmschenk – data preparation and analysis, manuscript editing John E. Garza – data processing through Python and data figure creation. Pita Navarro – concept, study design, manuscript editing Nicole M. Gilbert – concept and expertise, study design, manuscript draft and editing, resources, oversight All authors read and approved the manuscript. Competing interests Authors Gilbert, Whang, Wang and Garza declare no financial or non-financial competing interests. Olmschenk, Navarro, and Thomas-White are employees of Allora Health (dba Evvy). Additional information Supplementary information Correspondence and requests for materials should be addressed to Nicole M. Gilbert. Acknowledgements David Lyttle, Rob Markowitz for relative abundance participants’ data preparation. Ann Rosen, Dr. Drew Schwartz, Dr. Michael White, Dr. Tychele Turner, and Dr. Christopher Miller for computational and bioinformatics assistance and guidance in processing data and creating figures in R and Python. Dr. Fan Zhang for her biostatistical expertise and initial guidance in the analysis. Morgan Timm for proofreading and providing clinical insights and ideas. Funder Information Declared National Institute of Diabetes and Digestive and Kidney Diseases , R01DK137964 References ↵ Ravel , J. et al. Vaginal microbiome of reproductive-age women . Proc Natl Acad Sci U S A 108 Suppl 1 , 4680 – 4687 , doi: 10.1073/pnas.1002611107 ( 2011 ). OpenUrl Abstract / FREE Full Text ↵ Peebles , K. , Velloza , J. , Balkus , J. E. , McClelland , R. S. & Barnabas , R. V . High Global Burden and Costs of Bacterial Vaginosis: A Systematic Review and Meta-Analysis . Sex Transm Dis 46 , 304 – 311 , doi: 10.1097/OLQ.0000000000000972 ( 2019 ). OpenUrl CrossRef PubMed ↵ Amsel , R. et al. Nonspecific vaginitis. Diagnostic criteria and microbial and epidemiologic associations . Am J Med 74 , 14 – 22 , doi: 10.1016/0002-9343(83)91112-9 ( 1983 ). OpenUrl CrossRef PubMed Web of Science ↵ Gilbert , N. M. et al. Social, microbial, and immune factors linking bacterial vaginosis and infectious diseases . J Clin Invest 135 , doi: 10.1172/JCI184322 ( 2025 ). OpenUrl CrossRef ↵ Fettweis , J. M. et al. The vaginal microbiome and preterm birth . Nat Med 25 , 1012 – 1021 , doi: 10.1038/s41591-019-0450-2 ( 2019 ). OpenUrl CrossRef PubMed ↵ George , S. D. , Van Gerwen , O. T. & Muzny , C. A . Bacterial vaginosis: an overlooked STI? Expert Rev Anti Infect Ther , 1 – 7 , doi: 10.1080/14787210.2025.2583166 ( 2025 ). OpenUrl CrossRef ↵ Bradshaw , C. S. et al. High recurrence rates of bacterial vaginosis over the course of 12 months after oral metronidazole therapy and factors associated with recurrence . J Infect Dis 193 , 1478 – 1486 , doi: 10.1086/503780 ( 2006 ). OpenUrl CrossRef PubMed Web of Science ↵ Cauci , S. et al. Prevalence of bacterial vaginosis and vaginal flora changes in peri- and postmenopausal women . J Clin Microbiol 40 , 2147 – 2152 , doi: 10.1128/JCM.40.6.2147-2152.2002 ( 2002 ). OpenUrl Abstract / FREE Full Text Ranjit , E. , Raghubanshi , B. R. , Maskey , S. & Parajuli , P . Prevalence of Bacterial Vaginosis and Its Association with Risk Factors among Nonpregnant Women: A Hospital Based Study . Int J Microbiol 2018, 8349601 , doi: 10.1155/2018/8349601 ( 2018 ). OpenUrl CrossRef ↵ Bitew , A. , Mengist , A. , Belew , H. , Aschale , Y. & Reta , A. The Prevalence, Antibiotic Resistance Pattern, and Associated Factors of Bacterial Vaginosis Among Women of the Reproductive Age Group from Felege Hiwot Referral Hospital, Ethiopia . Infect Drug Resist 14 , 2685 – 2696 , doi: 10.2147/IDR.S305329 ( 2021 ). OpenUrl CrossRef PubMed ↵ Stewart , L. L. , Vodstrcil , L. A. , Coombe , J. , Bradshaw , C. S. & Hocking , J. S . Prevalence of bacterial vaginosis in postmenopausal women: a systematic review and meta-analysis . Sex Health 19 , 17 – 26 , doi: 10.1071/SH21083 ( 2022 ). OpenUrl CrossRef PubMed ↵ Qi , J. , Han , H. , Li , X. & Ren , Y . Association between body mass index and prevalence of bacterial vaginosis: Results from the NHANES 2001-2004 study . PLoS One 19 , e0296455 , doi: 10.1371/journal.pone.0296455 ( 2024 ). OpenUrl CrossRef Lokken , E. M. et al. A Prospective Cohort Study of the Association Between Body Mass Index and Incident Bacterial Vaginosis . Sex Transm Dis 46 , 31 – 36 , doi: 10.1097/OLQ.0000000000000905 ( 2019 ). OpenUrl CrossRef PubMed ↵ Brookheart , R. T. , Lewis , W. G. , Peipert , J. F. , Lewis , A. L. & Allsworth , J. E . Association between obesity and bacterial vaginosis as assessed by Nugent score . Am J Obstet Gynecol 220 , 476 e471 – 476 e411 , doi: 10.1016/j.ajog.2019.01.229 ( 2019 ). OpenUrl CrossRef ↵ Daubert , E. et al. Obesity is associated with lower bacterial vaginosis prevalence in menopausal but not pre-menopausal women in a retrospective analysis of the Women’s Interagency HIV Study . PLoS One 16 , e0248136 , doi: 10.1371/journal.pone.0248136 ( 2021 ). OpenUrl CrossRef PubMed ↵ He , Y. et al. Epidemiological trends and predictions of urinary tract infections in the global burden of disease study 2021 . Sci Rep 15 , 4702 , doi: 10.1038/s41598-025-89240-5 ( 2025 ). OpenUrl CrossRef PubMed ↵ Foxman , B . Epidemiology of urinary tract infections: incidence, morbidity, and economic costs . Am J Med 113 Suppl 1A , 5S – 13S , doi: 10.1016/s0002-9343(02)01054-9 ( 2002 ). OpenUrl CrossRef PubMed Web of Science ↵ Flores-Mireles , A. L. , Walker , J. N. , Caparon , M. & Hultgren , S. J . Urinary tract infections: epidemiology, mechanisms of infection and treatment options . Nat Rev Microbiol 13 , 269 – 284 , doi: 10.1038/nrmicro3432 ( 2015 ). OpenUrl CrossRef PubMed ↵ Deltourbe , L. , Lacerda Mariano , L. , Hreha , T. N. , Hunstad , D. A. & Ingersoll , M. A. The impact of biological sex on diseases of the urinary tract . Mucosal Immunol 15 , 857 – 866 , doi: 10.1038/s41385-022-00549-0 ( 2022 ). OpenUrl CrossRef PubMed ↵ Lenger , S. M. et al. d-Mannose for Recurrent Urinary Tract Infection Prevention in Postmenopausal Women Using Vaginal Estrogen: A Randomized Controlled Trial . Urogynecology (Phila) 29 , 367 – 377 , doi: 10.1097/SPV.0000000000001270 ( 2023 ). OpenUrl CrossRef PubMed ↵ Sze , C. , Attia , S. & Zimmern , P . Effective risk reduction strategies and pharmacological treatment for uncomplicated recurrent urinary tract infections . Expert Opin Pharmacother , 1 – 13 , doi: 10.1080/14656566.2025.2584405 ( 2025 ). OpenUrl CrossRef ↵ Medina , M. & Castillo-Pino , E . An introduction to the epidemiology and burden of urinary tract infections . Ther Adv Urol 11 , 1756287219832172 , doi: 10.1177/1756287219832172 ( 2019 ). OpenUrl CrossRef PubMed ↵ Franco , A. V . Recurrent urinary tract infections . Best Pract Res Clin Obstet Gynaecol 19 , 861 – 873 , doi: 10.1016/j.bpobgyn.2005.08.003 ( 2005 ). OpenUrl CrossRef PubMed ↵ Regassa , B. T. et al. Prevalence of bacterial vaginosis and its associated factors among pregnant women attending antenatal care clinics at public hospitals in West Shoa Zone, Oromia, Ethiopia . Sci Rep 14 , 21474 , doi: 10.1038/s41598-024-72644-0 ( 2024 ). OpenUrl CrossRef Koumans , E. H. , Kendrick , J. S. & Group , C. D. C. B. V. W . Preventing adverse sequelae of bacterial vaginosis: a public health program and research agenda . Sex Transm Dis 28 , 292 – 297 , doi: 10.1097/00007435-200105000-00011 ( 2001 ). OpenUrl CrossRef PubMed Web of Science Hillebrand , L. , Harmanli , O. H. , Whiteman , V. & Khandelwal , M . Urinary tract infections in pregnant women with bacterial vaginosis . Am J Obstet Gynecol 186 , 916 – 917 , doi: 10.1067/mob.2002.123987 ( 2002 ). OpenUrl CrossRef PubMed Web of Science ↵ Stapleton , A. E. The Vaginal Microbiota and Urinary Tract Infection . Microbiol Spectr 4 , doi: 10.1128/microbiolspec.UTI-0025-2016 ( 2016 ). OpenUrl CrossRef ↵ Hemmerling , A. et al. Effect of the vaginal live biotherapeutic LACTIN-V (Lactobacillus crispatus CTV-05) on vaginal microbiota and genital tract inflammation among women at high risk of HIV acquisition in South Africa: a phase 2, randomised, placebo-controlled trial . Lancet Microbe 6 , 101037 , doi: 10.1016/j.lanmic.2024.101037 ( 2025 ). OpenUrl CrossRef PubMed ↵ Ravel , J. et al. Impact of a multi-strain L. crispatus-based vaginal synbiotic on the vaginal microbiome: a randomized placebo-controlled trial . NPJ Biofilms Microbiomes 11 , 158 , doi: 10.1038/s41522-025-00788-6 ( 2025 ). OpenUrl CrossRef PubMed ↵ Amabebe , E. & Anumba , D. O. C . The Vaginal Microenvironment: The Physiologic Role of Lactobacilli . Front Med (Lausanne) 5 , 181 , doi: 10.3389/fmed.2018.00181 ( 2018 ). OpenUrl CrossRef PubMed ↵ Perez-Carrasco , V. , Soriano-Lerma , A. , Soriano , M. , Gutierrez-Fernandez , J. & Garcia-Salcedo , J. A . Urinary Microbiome: Yin and Yang of the Urinary Tract . Front Cell Infect Microbiol 11 , 617002 , doi: 10.3389/fcimb.2021.617002 ( 2021 ). OpenUrl CrossRef PubMed ↵ Komesu , Y. M. et al. Defining the relationship between vaginal and urinary microbiomes . Am J Obstet Gynecol 222 , 154 e151 – 154 e110 , doi: 10.1016/j.ajog.2019.08.011 ( 2020 ). OpenUrl CrossRef ↵ Thomas-White , K. et al. Culturing of female bladder bacteria reveals an interconnected urogenital microbiota . Nat Commun 9 , 1557 , doi: 10.1038/s41467-018-03968-5 ( 2018 ). OpenUrl CrossRef PubMed ↵ Gottschick , C. et al. The urinary microbiota of men and women and its changes in women during bacterial vaginosis and antibiotic treatment . Microbiome 5 , 99 , doi: 10.1186/s40168-017-0305-3 ( 2017 ). OpenUrl CrossRef PubMed ↵ O’Brien , V. P. , Lewis , A. L. & Gilbert , N. M . Bladder Exposure to Gardnerella Activates Host Pathways Necessary for Escherichia coli Recurrent UTI . Front Cell Infect Microbiol 11 , 788229 , doi: 10.3389/fcimb.2021.788229 ( 2021 ). OpenUrl CrossRef PubMed ↵ O’Brien , V. P. , Joens , M. S. , Lewis , A. L. & Gilbert , N. M . Recurrent Escherichia coli Urinary Tract Infection Triggered by Gardnerella vaginalis Bladder Exposure in Mice . J Vis Exp , doi: 10.3791/61967 ( 2020 ). OpenUrl CrossRef ↵ Gilbert , N. M. et al. Gardnerella Exposures Alter Bladder Gene Expression and Augment Uropathogenic Escherichia coli Urinary Tract Infection in Mice . Front Cell Infect Microbiol 12 , 909799 , doi: 10.3389/fcimb.2022.909799 ( 2022 ). OpenUrl CrossRef PubMed ↵ Gilbert , N. M. , O’Brien , V. P. & Lewis , A. L . Transient microbiota exposures activate dormant Escherichia coli infection in the bladder and drive severe outcomes of recurrent disease . PLoS Pathog 13 , e1006238 , doi: 10.1371/journal.ppat.1006238 ( 2017 ). OpenUrl CrossRef PubMed ↵ Dong , W. et al. Characteristics of Vaginal Microbiota of Women of Reproductive Age with Infections . Microorganisms 12 , doi: 10.3390/microorganisms12051030 ( 2024 ). OpenUrl CrossRef ↵ Mejia , M. E. et al. Vaginal microbial dynamics and pathogen colonization in a humanized microbiota mouse model . NPJ Biofilms Microbiomes 9 , 87 , doi: 10.1038/s41522-023-00454-9 ( 2023 ). OpenUrl CrossRef ↵ Kumar , L. , Whang , S. N. , Potter , R. F. & Gilbert , N. M . Strain-level differences in Gardnerella urinary tract persistence and pathogenesis are consistent with comparative phylogenomic analyses . bioRxiv , doi: 10.1101/2025.09.19.677092 ( 2025 ). OpenUrl Abstract / FREE Full Text ↵ Munch , M. M. et al. Gardnerella Species and Their Association With Bacterial Vaginosis . J Infect Dis 230 , e171 – e181 , doi: 10.1093/infdis/jiae026 ( 2024 ). OpenUrl CrossRef PubMed ↵ France , M. T. et al. VIRGO2: Unveiling the Functional and Ecological Complexity of the Vaginal Microbiome with an Enhanced Non-Redundant Gene Catalog . bioRxiv , doi: 10.1101/2025.03.04.641479 ( 2025 ). OpenUrl Abstract / FREE Full Text ↵ Lebeer , S. et al. A citizen-science-enabled catalogue of the vaginal microbiome and associated factors . Nat Microbiol 8 , 2183 – 2195 , doi: 10.1038/s41564-023-01500-0 ( 2023 ). OpenUrl CrossRef PubMed ↵ Ahannach , S. , Van Hoyweghen , I. , Verhoeven , V. & Lebeer , S . Citizen science as an instrument for women’s health research . Nat Med 30 , 3445 – 3454 , doi: 10.1038/s41591-024-03371-2 ( 2024 ). OpenUrl CrossRef PubMed ↵ Plummer , E. L. et al. Prevotella and Gardnerella Are Associated With Treatment Failure Following First-line Antibiotics for Bacterial Vaginosis . J Infect Dis 228 , 646 – 656 , doi: 10.1093/infdis/jiad261 ( 2023 ). OpenUrl CrossRef PubMed ↵ Young , M. G. et al. Distinct Escherichia coli transcriptional profiles in the guts of recurrent UTI sufferers revealed by pangenome hybrid selection . Nat Commun 15 , 9466 , doi: 10.1038/s41467-024-53829-7 ( 2024 ). OpenUrl CrossRef PubMed ↵ Thomas-White , K. et al. A Metagenomics Pipeline to Characterize Self-Collected Vaginal Microbiome Samples . Diagnostics (Basel) 14 , doi: 10.3390/diagnostics14182039 ( 2024 ). OpenUrl CrossRef ↵ Olmschenk G , T.-W. K. , Weaver F , Navarro P . Gardnerella Species Variations Show Pathogenic and Metabolic Differences . American Journal of Obstetrics and Gynecology ( 2024 ). View the discussion thread. Back to top Previous Next Posted November 28, 2025. Download PDF Supplementary Material Email Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following The Vaginal Microbiome in Women Recently Experiencing BV and UTI Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share The Vaginal Microbiome in Women Recently Experiencing BV and UTI Sonia N. Whang , Xinyue Wang , Krystal J. Thomas-White , Genevieve Olmschenk , John E. Garza , Pita Navarro , Nicole M. Gilbert bioRxiv 2025.11.27.690987; doi: https://doi.org/10.1101/2025.11.27.690987 Share This Article: Copy Citation Tools The Vaginal Microbiome in Women Recently Experiencing BV and UTI Sonia N. Whang , Xinyue Wang , Krystal J. Thomas-White , Genevieve Olmschenk , John E. Garza , Pita Navarro , Nicole M. Gilbert bioRxiv 2025.11.27.690987; doi: https://doi.org/10.1101/2025.11.27.690987 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Microbiology Subject Areas All Articles Animal Behavior and Cognition (7642) Biochemistry (17708) Bioengineering (13904) Bioinformatics (41992) Biophysics (21466) Cancer Biology (18618) Cell Biology (25531) Clinical Trials (138) Developmental Biology (13387) Ecology (19924) Epidemiology (2067) Evolutionary Biology (24337) Genetics (15615) Genomics (22521) Immunology (17749) Microbiology (40424) Molecular Biology (17194) Neuroscience (88673) Paleontology (667) Pathology (2839) Pharmacology and Toxicology (4827) Physiology (7650) Plant Biology (15160) Scientific Communication and Education (2046) Synthetic Biology (4302) Systems Biology (9826) Zoology (2271)