bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

1 Longitudinal profiling of the macaque vaginal microbiome reveals similarities to

2 diverse human vaginal communities: implications for use as a pre-clinical model

3 for bacterial vaginosis.

4

5 Nicholas S. Rhoades1#, Sara M. Hendrickson2#, Danielle R. Gerken1, Kassandra

6 Martinez1, Ov D. Slayden3, Mark K. Slifka2*, Ilhem Messaoudi1*

7

8 1Department of Molecular biology and Biochemistry, University of California Irvine, Irvine,

9 CA, USA

10 2 Division of Neuroscience, Oregon National Primate Research Center, Beaverton OR,

11 USA

12 3Division of Reproductive & Developmental Sciences, Oregon National Primate

13 Research Center, Beaverton, OR, USA

14 USA

15 # These authors contributed equally to this work

16

17 * To whom correspondence should be addressed

18 Ilhem Messaoudi, PhD

19 Molecular Biology and Biochemistry

20 University of California Irvine

21 2400 Biological Sciences III

22 Irvine, CA 92697

23 Phone: 949-824-3078

24 Email: [email protected]

25 Or bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

26 Mark Slifka, PhD

27 Division of Neuroscience

28 Oregon National Primate Research Center

29 Oregon Health & Science University

30 505 NW 185th Avenue

31 Beaverton, OR 97006

32 Phone: (503) 346-5483

33 Email: [email protected]

34

35 This PDF file includes:

36 Main Text

37 Table 1

38 Figures 1 to 5

39 Supplemental figures 1 to 4

40 Supplemental tables 1 to 2

41 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

42 ABSTRACT

43 The vaginal microbiota plays an important role in women’s reproductive and

44 urogenital health. Disturbances in this microbial community can lead to several adverse

45 outcomes including pelvic inflammatory disease, bacterial vaginosis (BV) as well as

46 increased susceptibility to sexually transmitted infections, miscarriage, and pre-term

47 births. It is now well accepted that while the microbiome of healthy women in the

48 developed world is dominated by Lactobacillus , vaginal communities in

49 asymptomatic women, especially those in the developing world, can be comprised of a

50 diverse set of micro-organisms. The presence of a diverse vaginal microbiome has been

51 associated with increased susceptibility to HIV infection but their implications for

52 women’s health remain poorly understood. Rhesus macaques are an excellent

53 translational animal model due to significant physiological and genetic homology with

54 humans. In this study, we performed a longitudinal analysis of clinical and microbiome

55 data from 16 reproductive age female rhesus macaques. Many animals showed

56 hallmarks of BV, including Nugent scores above 7 and high vaginal pH. At both the

57 taxonomic and functional level, the rhesus macaque vaginal microbiome was most

58 similar to that of women who harbor a diverse vaginal community associated with

59 asymptomatic/symptomatic bacterial vaginosis. Specifically, rhesus macaque vaginal

60 microbiomes harbored a diverse set of anaerobic gram-negative , including;

61 Snethia, Prevotella, Porphyromonas, and Mobilluncus. Interestingly, some animals were

62 transiently colonized by Lactobacillus and some with Gardnerella. Our in-depth and

63 comprehensive analysis highlights the importance of the model to test interventions for

64 manipulating the vaginal microbiome.

65 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

66 IMPORTANCE

67 It is widely accepted that the “healthy” vaginal microbiome of the majority

68 of women in the developed world is dominated by Lactobacillus species.

69 However, in the developing world, a majority of women are colonized by diverse

70 microbial communities, typically associated with bacterial vaginosis, but remain

71 asymptomatic. Many questions remain about the drivers of this disparity and

72 potential interventions to alter the vaginal microbiome. Rhesus macaques

73 provide an excellent translational model due to significant physiological and

74 genetic homology with humans. In this study, we performed a longitudinal

75 analysis of clinical and microbiome data from a large cohort of reproductive age

76 rhesus macaques. At the taxonomic, genomic, and functional level, the rhesus

77 macaque vaginal microbiome was most similar to that of humans who harbor a

78 diverse vaginal community associated with asymptomatic/symptomatic bacterial

79 vaginosis. Our in-depth and comprehensive analysis highlights the utility of

80 macaques to test interventions for manipulating the vaginal microbiome.

81

82

83

84 85 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

86 INTRODUCTION

87 The vaginal microbial community modulates several critical physiological

88 functions and protect the host from infection with pathogenic organisms. The “healthy”

89 vaginal microbiome (VM) in women in the developed world is typically dominated by

90 Lactobacillus species, with L. crispatis, L. iners, L. johnsonii, and L. gasseri. These

91 microbes are considered keystone microbes that rarely co-occur in individuals (1, 2).

92 Lactobacilli inhibit the growth of other vaginal microbes via the production of lactic acid

93 through fermentation which decreases the pH of the vaginal environment (pH 3.5-5.5)

94 inhibiting the growth of other microbes (3). Lactobacillus species also competitively

95 exclude genitourinary pathogens thereby preventing infection. Disruptions of this

96 community have significant implications for women’s health (4-6). However,

97 approximately ~20% of women in the developed world and ~50% in the developing

98 world harbor a diverse VM with reduced abundance or absence of Lactobacilli and a

99 high abundance of taxa such as Gardnerella, Prevotella, Snethia, and Mobiluncus (1, 4).

100 This diverse community is often associated with a heightened inflammatory state,

101 increased susceptibility to sexually transmitted diseases notably HIV, and the

102 development of bacterial vaginosis (BV) (7).

103 BV is an inflammatory disorder and the most common vaginal infection in the US

104 affecting ~ 30% of women ages 15-44 (8). However, the prevalence of BV can vary

105 widely based on geographic location and racial background (8). BV is caused by

106 bacterial overgrowth, disruption of the commensal microbial community, and a pro-

107 inflammatory environment (9). While typically asymptomatic, BV can result in discomfort

108 and more importantly increased susceptibility to sexually transmitted diseases, preterm

109 birth, and pelvic inflammatory disease (6, 10, 11). The antibiotics Metronidazole and/or bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

110 Clindamycin are the current standard treatment for BV. However, BV recurs in ~50% of

111 women within 12 months of antibiotic treatment (12). Additionally, the production of

112 biofilms and the development of other antimicrobial resistance mechanisms will most

113 likely reduce the effectiveness of antibiotics treatments over time (13, 14). Recently, VM

114 transplants have been shown to be effective in the treatment of intractable BV (15).

115 However, microbiome transfer procedures have recently come under scrutiny due to

116 safety concerns (16, 17).

117 Another potential intervention is the use of pre-biotics to shift a microbial

118 community to a more “beneficial” state. Pre-biotics are molecules and/or nutrients that

119 are metabolically accessible to microbes with the goal of enriching for beneficial

120 microbes and/or depleting undesired microbes. An example of such an intervention is

121 the consumption or supplementation of dietary fiber to enrich the gut microbiome in

122 beneficial short-chain fatty acid-producing microbes (18, 19). The use of pre-biotics has

123 also been proposed as a cheap and easily accessible alternative to antibiotic treatment

124 for BV (20, 21). Of interest is the intravaginal application of di- or polysaccharides that

125 are preferentially metabolized and fermented by Lactobacillus to produce lactic acid and

126 hydrogen peroxide, thereby generating a low pH vaginal environment and inhibiting the

127 growth of BV-associated bacteria. Clinical trials are currently underway to test the use of

128 intravaginal Lactose (NTC03878511), Glucose (NCT03357666), and Glycogen

129 (NCT02042287) to treat BV symptoms. Sucrose in particular has shown potential for

130 improving clinical markers of BV in humans (22) and shifting the VM of rhesus

131 macaques (23). However, the clinical study only examined changes in clinical symptoms

132 and Amsel criteria at one-time point after 14 days of treatment and did not interrogate

133 changes in microbial communities (22). The preclinical study in macaques utilized

134 animals with a vaginal microbial community that had >1% Lactobacillus; did not identify bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

135 the Lactobacillus species present; nor did it report individual animal data (23). Therefore,

136 it is still unclear whether a sucrose intervention could improve clinical outcomes when

137 the frequency of Lactobacillus species is extremely low, which Lactobacillus strains can

138 respond to sucrose treatment, and how effective is this intervention.

139 To address these questions, we utilize a combination of clinical tests, 16S rRNA

140 amplicon sequencing, and shotgun metagenomics to characterize the taxonomic and

141 functional landscape of the rhesus macaque VM before and after intra-vaginal sucrose

142 treatment. Additionally, we determined the relatedness of rhesus macaque and human

143 vaginal microbes with whole-genome resolution. Previous studies have defined the

144 taxonomic landscape of pigtail (24), cynomologus (25), and rhesus (26) macaques VM.

145 Together these studies have shown that macaques harbor a diverse vaginal community

146 (24-26) that shares taxa with the diverse community state type associated with BV in

147 humans (25). These patterns include a low abundance of Lactobacillus spp. and a high

148 abundance of Snethia, Prevotella, and Mobiluncus among others. However, these

149 previous studies have been limited to amplicon sequencing techniques that are limited in

150 resolution and did not address the functional potential of the macaque vaginal

151 community or examine this similarity at a whole-genome level. The data presented

152 herein further strengthen the case for using macaques to test interventions for altering

153 the VM.

154 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

155 METHODS

156 Sample collection and cohort information

157 All macaque studies were reviewed and approved by the OHSU/ONPRC

158 Institutional Animal Care and Use Committees (IACUC). The animals were socially

159 housed indoors at the Oregon National Primate Research Center (ONPRC) following

160 standards established by the US Federal Animal Welfare Act and The National

161 Research Council Guide for the Care and Use of Laboratory Animals. All animals were

162 tested annually for simian viruses (Simian Immunodeficiency Virus, Simian Retrovirus 2,

163 Macacae herpesvirus 1, and Simian T lymphotropic virus) and received a mammalian

164 old tuberculin test semi-annually. The monkeys underwent pre-assignment evaluations

165 prior to initiation of the study. Qualifications of assignment to the study included normal

166 menstrual cycle, age 5-8 years, and a healthy weight of 4-8kgs, and all had to be void of

167 gastrointestinal issues and antibiotic use for greater than three months. At the pre-

168 assignment screening, Nugent score and microbiome samples were collected.

169 Samples were collected for 16S rRNA amplicon sequencing, metagenomics, and

170 Nugent scoring. Samples used for Nugent scoring, including pH analysis and whiff test,

171 were collected using polyester swabs (Fisher Scientific; item 23-400-122). Samples used

172 for microbiome analysis were collected with Copan Swabs (Fisher Scientific; 23-600-

173 957) and stored in 20% glycerol (shotgun metagenomics) or immediately snap-frozen

174 upon collection and stored at -80C until DNA extraction (16S rRNA amplicon

175 sequencing). To collect the vaginal and rectal swab samples, animals were sedated and

176 placed in a ventral recumbency with their pelvis slightly elevated. A sterile nasal

177 speculum was inserted vaginally to ensure a mid-vaginal sample collection without rectal

178 or vaginal introitus contamination. Preliminary screening identified 3/20 (15%) of adult

179 rhesus macaque females with vaginal pH = 4, absence of Clue cells, and negative Whiff bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

180 test. These animals were not included in the longitudinal study. The animals chosen for

181 further study had high pH (pH >5) and other characteristics of vaginal microbiome

182 dysbiosis.

183 To minimize the natural variability that may occur over the menstrual cycle,

184 animals received 21 days of combination oral contraceptives (Portia; Teva

185 Pharmaceuticals USA, Inc.) to synchronize the group. One day after the last dose of

186 oral contraceptives, samples were collected (Nugent scores, Clue cells, Whiff test,

187 microbiome, and metagenomics), and animals menstruated approximately 24-48 hours

188 later. Next, animals underwent post-menstruation sample collection (Nugent scores,

189 Clue cells, Whiff test microbiome, metagenomics), and then began five days of gel

190 treatment administration.

191 Animals were randomly designated to one of two treatment groups, Control

192 (vehicle only; n=8) or Sucrose (10% sucrose; n=8). The sucrose treatment consisted of

193 1.6% xanthan gum (Xantural 180; CP Kelco) added to a 10% sucrose solution (Sigma

194 Aldrich) to create a gel property and brought to a pH of 5.0 using lactic acid (Fisher

195 Scientific). The control treatment did not contain sucrose. Vaginal administration of the

196 gel occurred daily using a 5ml slip-tip syringe, with control animals received the xanthan

197 gum gel only.

198

199 Hormone quantification

200 Serum concentrations of estradiol (E2) and progesterone (P4) were assayed by

201 the ONPRC Endocrine Technologies Core. Hormone concentrations were determined

202 using a chemiluminescence-based automated clinical platform (Roche Diagnostics

203 Cobas e411, Indianapolis, IN). Serum E2 and P4 assay ranges were between 5-3000 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

204 pg/ml and 0.05-60 ng/ml, respectively. E2 and P4 intra-assay CVs were 8.3 and 4.2%,

205 whereas inter-assay CVs were 5.9 and 6.3%, respectively.

206

207 Clinical data generation

208 Nugent’s scoring was carried out by a trained microbiologist with 4 years of experience

209 performing Nugent scores in a CLIA-approved clinical laboratory using established

210 criteria for clinical studies (27). To complement Nugent scoring, three of four Amsel

211 criteria (28) were also assessed including vaginal pH, presence of Clue cells, and Whiff

212 test. Vaginal discharge, the fourth Amsel criteria, was not measured. The presence of

213 Clue cells (i.e., vaginal epithelial cells coated with bacteria, resembling a “sandy”

214 appearance) was determined and samples with 20% Clue cells were considered

215 positive for this test. Whiff tests were performed by adding 10% KOH to a sample of

216 vaginal fluid and the presence of fishy odor was interpreted as a positive test while its

217 absence was determined as a negative test result. A full breakdown of clinical

218 measurements can be found in supplemental table 1 (Supp. Table 1).

219

220 16S rRNA gene library construction and sequencing

221 Total DNA was extracted from vaginal swabs using the Blood and Tissue DNA

222 Isolation KIT (MO BIO Laboratories, Carlsbad, CA, USA). Rectal swabs were extracted

223 using the PowerSoil DNA Isolation KIT (MO BIO Laboratories, Carlsbad, CA, USA). This

224 DNA was used as the template to amplify the hypervariable V4 region of the 16S rRNA

225 gene using PCR primers (515F/926R with the forward primer containing a 12-bp

226 barcode) in duplicate reactions containing: 12.5 ul GoTaq master mix, 9.5 ul nuclease-

227 free H20, 1 ul template DNA, and 1 ul 10uM primer mix. Thermal cycling parameters

228 were 94C for 3 minutes; 35 cycles of 94C for 45 seconds, 50C for 1 minute, and 72C bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

229 for 1 minute and 30 seconds; followed by 72C for 10 minutes. PCR products were

230 purified using a MinElute 96 UF PCR Purification Kit (Qiagen, Valencia, CA, USA).

231 Libraries were sequenced (1 x 300 bases) using Illumina MiSeq.

232

233 16S rRNA gene sequence processing

234 Raw FASTQ 16S rRNA gene amplicon sequences were uploaded and processed

235 using the QIIME2 version 2019.10 (29) analysis pipeline as we have previously

236 described (30). Briefly, sequences were demultiplexed and quality filtered using DADA2

237 (31), which filters chimeric sequences and generated sequence variants were then

238 aligned using the MAFFT (32) and a phylogenetic tree was constructed using FastTree2

239 (33). was assigned to sequence variants using q2-feature-classifier against

240 the SILVA database (release 119) (34). To prevent sequencing depth bias, samples

241 were rarified to 10,000 sequences per sample before alpha and beta diversity analysis.

242 QIIME 2 was also used to generate the following alpha diversity metrics: richness (as

243 observed taxonomic units), Shannon evenness, and phylogenetic diversity. Beta

244 diversity was estimated in QIIME 2 using weighted and unweighted UniFrac distances

245 (35).

246 Analysis of the unweighted Unifrac distance (based on the presence/absence of

247 microbes) revealed that 9 vaginal samples were very similar to the fecal microbiome

248 (Supp. Figure 1A). These 9 samples had a significantly higher number of observed

249 Amplicon sequence Variants (ASVs) than the group average of all other vaginal samples

250 (Supp. Figure 1B) and a high relative abundance of taxa typically found in the fecal

251 microbiome (Supp. Figure 1C). Therefore, these nine VM samples were removed from

252 future analysis along with eight additional samples that did not meet our minimum

253 sequencing depth threshold of 10,000 reads (Supp. Figure 1D). bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

254 16S rRNA gene amplicon sequencing data obtained from vaginal swabs from

255 236 women from Umlazi, South Africa aged 18 to 23 was obtained from Gossman et al.

256 (4). These samples were imported into QIIME 2 and rarified to 13,000 reads per sample.

257 Taxonomy was assigned using the full-length SILVA database (release 119) at the 99%

258 OTU cutoff. Genus-level (L6) taxonomy tables were merged, and Bray-Curtis

259 dissimilarity matrices were generated using QIIME 2.

260

261 Shotgun metagenomics

262 Shotgun metagenomic libraries were prepared for vaginal samples obtained from

263 all animals at the initiation of oral contraceptives using the Illumina Nextera Flex library

264 prep kit, per the manufacturer's recommended protocol, and sequenced on an Illumina

265 HiSeq 4000 2 × 100. Raw demultiplexed reads were quality filtered using Trimmomatic

266 (36), and potential host reads were removed by aligning trimmed reads to the Macaca

267 mulatta genome (Mmul 8.0.1) using BowTie2 (37). After quality filtering and

268 decontamination, an average of 6.08 million reads (min 0.517, max 30 million reads) per

269 sample were used for downstream analysis. Samples with less than 1 million reads after

270 quality filtering were excluded from downstream analysis. Trimmed and decontaminated

271 reads were then annotated using the HUMAnN2 pipeline using the default setting with

272 the UniRef50 database and assigned to GO terms (38). Functional annotations were

273 normalized using copies per million (CPM) reads before statistical analysis (39-41).

274 Trimmed and decontaminated reads were assembled into contigs using meta-

275 SPAdes with default parameters (42). Assembled contigs <1kb were also binned into

276 putative metagenomically assembled genomes (MAGs) using MetaBat (43). Genome

277 completeness/contamination was tested using CheckM (44), and all bins with a bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

278 completeness > 80% and contamination < 2% were annotated using PATRIC (45). The

279 taxonomy of draft genomes was determined using PATRICs' similar genome finder.

280 Shotgun metagenomic sequencing data was obtained from Lev-Sagie et.al (15)

281 and Oliver et. al (46). Human samples were classified as " Lactobacillus dominated”

282 samples if the relative abundance of Lactobacillus >90%. Samples classified as “Diverse

283 human (BV symptomatic)” were the pre-transplant samples from Lev-Sagie et.al (15).

284 Samples classified as “Diverse human (asymptomatic)” were obtained from Oliver et. al

285 (46) with a Lactobacillus relative abundance < 90%. To avoid pseudoreplication only

286 samples from the earliest time-point were used. Sequences were annotated using the

287 HUMAnN2 pipeline as described above for rhesus vaginal samples.

288

289 Statistical analysis

290 All statistical analyses were conducted used PRISM (V8). QIIME 2 was used to

291 calculate alpha-diversity metrics; observed OTUs, Shannon evenness, and beta

292 diversity; and weighted and unweighted UniFrac distances. Bray-Curtis dissimilarity

293 matrices were constructed for species-level relative abundance. Unpaired t-tests and

294 one-way ANOVAs with post hoc correction were implemented using PRISM (V8) to

295 generate p values. The LEfSe algorithm was used to identify differentially abundant taxa

296 and pathways between groups with logarithmic linear discriminant analysis (LDA) score

297 cutoff of 2.

298 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

299 RESULTS

300 Rhesus macaques display the clinical hallmarks of BV and are colonized by a

301 diverse vaginal microbiome.

302 To determine if Rhesus macaques can serve as a model of BV, we screened 9

303 reproductive age female rhesus macaques. Of these animals, six (66%) had a Nugent

304 score >7 and the presence of Clue cells (Table 1). Additionally, 5 of these 6 animals had

305 a vaginal pH of 6.0 (Table 1). These data suggest that the majority of rhesus macaque

306 females display the clinical hallmarks of BV. Profiling of the vaginal microbial (VM)

307 communities using 16S rRNA gene amplicon sequencing showed a high relative

308 abundance of bacterial taxa associated with BV, including; Snethia, Mobiliuncus,

309 Prevotella, and Gardnerella (Table 1). Interestingly, 3 animals (33%) included in this

310 screen had a high relative abundance of Lactobacillus (43-84%). These data suggest

311 that a subset of RM can naturally harbor a Lactobacillus dominated vaginal community.

312

313 Intra-Vaginal Sucrose treatment does not alter the vaginal microbiome of rhesus

314 macaques

315 We screened an additional 20 animals for inclusion in a longitudinal study to

316 determine the efficacy of vaginal sucrose gel to improve BV clinical indicators and

317 increase the abundance of Lactobacillus in the VM. Initial screening of these 20 animals

318 indicated that 4 animals did not display the clinical indicators of BV (pH <5 and/or

319 Nugent score <4) and were excluded from the longitudinal study. The remaining 16

320 animals were split evenly into two groups. Animals in group 1 received seven daily

321 applications of a sucrose gel vaginally, while animals in group 2 received seven daily

322 applications of the gel alone. Since hormonal levels can influence VM composition (25,

323 47, 48), animals were administered an oral contraceptive for 21 days (1-month prior to bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

324 sucrose treatment) to synchronize the menstrual cycles of the animals (Figure 1A).

325 Contraceptive treatment resulted in a significant decrease in the levels of progesterone

326 and estradiol (Figure 1 B, C). Seven days after cessation of the contraceptive treatment,

327 the animals were then treated with either sucrose or placebo gel intravaginally for 7

328 days. These animals were sampled at 5 time-points across 35 days, to collect clinical

329 (Vaginal pH, Nugent scores, whiff test, and Clue cells), circulating hormone levels

330 (Progesterone and Oestrodiol), and microbiome (16S amplicon sequencing) data

331 (Figure 1A).

332 Sucrose treatment did not alter clinical measurements (pH, Nugent score, Whiff

333 test, or presence of Clue cells) or levels of progesterone or estradiol up to 28 days after

334 treatment (Supp. Figure 2 A-F). Additionally, we observed no differences in VM

335 diversity, overall community composition (Supp. Figure 3 A-C). Sucrose treatment also

336 did not increase the relative abundance of Lactobacillus (Supp. Figure 3D). Since

337 sucrose treatment did not lead to measurable changes in clinical or microbiome

338 measurements, we combined the two groups to generate a longitudinal dataset to further

339 our understanding of rhesus macaque VM community dynamics.

340 Analysis of the clinical markers of BV in all 16 animals showed association with

341 menstrual cycle. Specifically, menses were associated with reduced Nugent scores and

342 a smaller proportion of animals that meet all three measured Amsel criteria while pH

343 levels increased (Figure 1D-F). The association between menstrual cycle and these

344 clinical markers is more evident when comparing Nugent scores and vaginal pH in

345 animals with or without menses (Figure 1 G, H).

346

347 The taxonomic landscape of the rhesus macaque vaginal microbiome. bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

348 Using 16S rRNA gene amplicon sequencing, we characterized the taxonomic

349 landscape of the rhesus VM across eight time-points (Figure 2A). The rhesus VM is a

350 low diversity community with an average of ~50 ASVs per sample across all time-points

351 (Figure 2B). Interestingly, the overall community composition remained stable across

352 time-points in 7 animals (Figure 2C). These “Stable” communities were dominated by

353 either Prevotella, Prophymonas, or Snethia and were associated with a higher vaginal

354 pH (Figure 2 A, C). The VM of the remaining 9 animals was more variable, transitioning

355 between states and communities dominated by less common microbes such as

356 Gardnerella, and Lactobacillus (Figure 2C). Finally, we found that individual

357 (PERMANOVA: p=0.009) rather than time point (PERMANOVA: p=0.42) was the best

358 predictor of community composition.

359 We next explored the most abundant taxa within rhesus macaques VM. A small

360 number of samples (13/120) were dominated (>50% relative abundance) by a single

361 microbe (Figure 2A), including 9 samples dominated by Snethia, 2 by Gardnerella, and

362 4 by Lactobacillus. The remaining samples contained communities composed of multiple

363 anaerobic bacteria including Snethia, Porphyromonas, Prevotella, Fastidiosipila,

364 Cantonella, Mobiluncus, and Atopobium (Figure 2A). Additional taxa found in lower

365 abundance across all samples include Parvimonas, Dialister, Fusobacterium,

366 Treponema, Peptoniphilus, and Campylobacter (Figure 2A). The relative abundance of

367 the most abundant 25 taxa did not cluster by time of sample collection or menstruation

368 status; however, samples from some animals with a “Stable” VM did cluster together

369 (Figure 2E). Interestingly Lactobacillus was detectable in 51 samples and found in a

370 relative abundance above 30% in 5 samples. These five samples came from two

371 monkeys across 4 time-points. bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

372 We next explored the relationship between clinical measures, hormone levels,

373 and the relative abundance of vaginal microbes using Spearman rank correlations

374 (Figure 2F). As expected, Nugent score and vaginal pH were positively correlated, while

375 the relative abundance of Lactobacillus was negatively correlated with both vaginal pH

376 and Nugent score (Figure 2F). Nugent score was positively correlated with systemic

377 Progesterone levels. The relative abundance of Porphyomonas, Mobiluncus mulieris,

378 and Campylobacter sputorum were also positively correlated with Nugent scores (Figure

379 2F). Levels of estradiol did not correlate with clinical markers or relative abundance of

380 specific microbes. Surprisingly Gardnerella was also negatively correlated with vaginal

381 pH (Figure 2F). However, the vaginal pH of those animals was in the 5-7 range, and

382 those animals harbored a low abundance of Lactobacillus.

383

384 The rhesus macaque vaginal microbiome is comparable to human non-

385 Lactobacillus dominated vaginal communities.

386 Next, we compared our longitudinal 16S rRNA gene amplicon data to those

387 reported in humans by Gosmann et. al (4). This study was selected for the large number

388 of vaginal samples examined and the presence of both Lactobacillus dominated (N =83)

389 and diverse communities (N =117). Rhesus macaque samples were divided into

390 “Diverse” (N=105) and “High Lactobacillus” (N=5). Due to differences in differences in

391 the methodology, a comparison could only be made qualitatively at the genus level. A

392 principal coordinates analysis shows that the “Diverse” rhesus VM was more similar to

393 “Diverse” than “Lactobacillus dominated” human vaginal communities (Figure 3A, B).

394 Six bacterial genera were shared between at least one human and one macaque group

395 with 1% relative abundance: Lactobacillus, Prevotella, Gardnerella, Snethia, Atopbium,

396 and Mobiluncus (Figure 3C). Megasphera, Veillonella, and Bacteroidales were only bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

397 found in the diverse human vaginal microbiome (Figure 3B). On the other hand,

398 Porphytomonas, Fastidiosipila, Parvimonas, Dialister, Campylobacter, and Catonella

399 were only found in the “Diverse” macaque VM (Figure 2B).

400

401 Metagenomic genome assembly reveals taxa in the rhesus macaque vaginal

402 microbiome similar to human urogenital bacteria

403 Shotgun metagenomics provides higher resolution taxonomic information and

404 functional potential of microbial communities not attainable using 16S rRNA amplicon

405 sequencing. Shotgun metagenomic libraries were prepared from vaginal samples

406 collected before and 7 days after sucrose/placebo treatment (Figure 1A). We eliminated

407 any samples with less than 1 million reads after host decontamination resulting in the

408 loss of 8 samples at the pre-sucrose and 3 samples from the post-sucrose time points

409 (Supp. Figure 4A). As noted for 16s rRNA amplicon sequencing, sucrose treatment did

410 not exert a significant impact on the functional potential of the VM (Supp. Figure 4C).

411 Although we were unable to identify the Lactobacillus colonizing the rhesus VM at the

412 species level using 16S amplicon sequencing or genome assembly, annotation of

413 shotgun metagenomic reads using MetaPhlan revealed the presence of Lactobacillus

414 johnsonii, L. amylovarus, and L. acidophilus (Supp, Figure 4B).

415 We employed metagenomic genome assembly to generate a higher resolution

416 picture of which bacterial taxa were present in the rhesus macaque VM, and how they

417 relate to the genomes of bacterial strains isolated from the human VM. We constructed a

418 total of 78 metagenomically assembled genomes (MAGs) with >80% genome

419 completeness and <2% contamination as measured by CheckM (Table 2, Supp. Figure

420 4D). The MAGs were largely representative of dominant taxa identified in our 16S rRNA

421 amplicon sequencing data, including 9 Gardnerella, 6 Mobiluncus, 8 Prevotella, 2 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

422 Campylobacter and 3 Snethia genomes (Table 2, Supp. Figure 4D). We next

423 determined the relationship between our MAGs and human isolates. Macaques

424 Mobiluncus and Snethia genomes were most closely related to the common human

425 bacteria Mobiluncus mulieris, and Snethia sanguinegens respectively (Figure 4 A, B).

426 Macaque Gardnerella genomes were most closely related to Gardnerella vaginalis,

427 commonly detected in non-lactobacillus dominated communities and often associated

428 with BV in humans (Figure 4C). Additionally, assembled vaginal Prevotella and

429 Campylobacter genomes were distinct from those we previously assembled from rhesus

430 macaque fecal samples (Figure 4D, E). Our assembled Prevotella genomes were most

431 closely related to Prevotella timonensis and Prevotella bucallis previously isolated from

432 human vaginal samples (Figure 4D). The assembled Campylobacter were most similar

433 to Campylobacter sputorum which is most commonly associated with livestock

434 urogenital samples (Figure 4E).

435

436 The rhesus macaque vaginal microbiome is functionally more similar to women

437 with a diverse vaginal microbiome.

438 To determine the functional potential of the rhesus VM compared to that of

439 human VM, we compared our shotgun metagenomic data to those obtained from clinical

440 studies by Oliver et. al (46) and Lev-Sagie et. al (15). These studies analyzed samples

441 from human vaginal communities that were classified as “Lactobacillus dominated”

442 (>90% Lactobacillus), “Diverse asymptomatic” (<90% Lactobacillus), and “Recurrent

443 BV”. We used supervised random forest modeling to determine if the overall functional

444 capacity of the VM could be used to distinguish between samples collected from

445 asymptomatic women (either “Lactobacillus dominated” or “Diverse Asymptomatic”),

446 women with BV, and rhesus macaques. The overall random forest model was 83% bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

447 accurate at classifying samples into the four groups with overlap between the VMs from

448 women with BV and asymptomatic women with a diverse VM (Figure 5A). The VM of

449 rhesus macaques was more closely related to that of asymptomatic women with diverse

450 communities than to VM of women with BV (Figure 5B).

451 We then extracted the functional GO terms that distinguished between the four

452 groups (Supp. Figure 4E). We found that ‘D-gluconate metabolic process’,

453 ‘phosphoglycerate mutase activity’, and ‘lipopolysaccharide biosynthetic process’ were

454 among the most significant GO terms for classifying samples into the four groups (Supp.

455 Figure 4E). Several pathways were unique to each group. For example, “palmitoyl-[acyl-

456 carrier-protein] hydrolase activity” and “heme transport” pathways were common in

457 “Lactobacillus dominated” human VM communities but absent in vaginal communities

458 from rhesus macaques and from asymptomatic women with diverse communities or

459 those with recurrent BV (Figure 5C). Other terms such as ‘D-gluconate metabolic

460 process’ and ‘UDP-glucose metabolic process’ were found in human vaginal

461 communities regardless of health status, but absent in the rhesus VM (Figure 5C). We

462 also found GO-terms shared between Lactobacillus dominated humans and diverse

463 asymptomatic humans, but absent in women with BV and rhesus macaques such as

464 “protein-N(PI)-phosphohistidine-sugar phosphotransferase activity” and

465 “phosphoenolpyruvate-dependent sugar phosphotransferase system” that were absent

466 in vaginal communities from women with BV and rhesus macaque. We also found that

467 the "oxidation-reduction process” pathway was abundant in rhesus and human diverse

468 vaginal communities but not in Lactobacillus dominated human vaginal communities.

469 Finally, we also identified GO terms that were unique to the rhesus macaque vaginal

470 microbiome including “antioxidant activity”, “arginine catabolic process”, and “regulation

471 of pentose phosphate shunt” (Figure 5C). bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

472

473 DISCUSSION

474 Approximately 50% of women globally have a diverse vaginal microbiome

475 defined by the absence or low abundance of gram-positive Lactobacillus that typically

476 dominates the human vaginal microbiome in developed countries (1, 2, 4, 11). Instead,

477 this diverse community is composed of gram-negative anaerobic bacteria such as

478 Gardnerella, Prevotella, Snethia, and Mobiluncus (1). The prevalence of this diverse

479 community can vary widely by geographical location, with a prevalence between 20 and

480 30% in the developed world (1, 46) and between 50-80% in the developing world (4, 49).

481 Prevalence of this diverse community state has also been connected to multiple host

482 factors including ethnicity (50), genetics (51), and sexual habits (52). These diverse

483 vaginal communities are largely considered to be a dysbiotic state of the vaginal

484 microbiome, which can result in an inflammatory state such as BV, and increased

485 susceptibility to sexually transmitted diseases (4, 53). However, important questions

486 about the implications of this community remain unanswered since many women are

487 asymptomatically colonized by these diverse communities. These questions are

488 challenging to ask in the clinical setting and require the availability of a robust animal

489 model.

490 In this study, we carried out a comprehensive analysis of the rhesus macaque

491 VM using a combination of 16s rRNA amplicon as well as shotgun metagenomic

492 sequencing. We also measured key clinical parameters associated with BV. Our

493 analysis showed that most animals displayed clinical and microbial markers of BV

494 notably high vaginal pH and high Nugent scores. At the 16S rRNA gene amplicon level,

495 the rhesus VM harbors a diverse set of anaerobic microbes including Snethia,

496 Prevotella, Mobiliuncus, and Fusobacterium that are often associated with BV. Although bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

497 the rhesus macaque VM shares a core set of highly abundant genera with humans, it

498 also harbors a diverse set of anaerobic genera less commonly found in human vaginal

499 samples including; Porphyromonas, Fastidiosipila, Catonella, Peptostreptococcaceae,

500 Spriochaetaceae, and Campylobacter (54, 55).

501 Our observations are in line with previous studies that have reported a high

502 prevalence and abundance of these genera in other macaque species (24-26). However,

503 our study is the first to report the presence of Gardnerella, a key pathogen in human BV,

504 and an indicator of a dysbiotic community (24-26). Specifically, Gardnerella was present

505 in 62 of 120 samples and at 10 to 66% relative abundance in 15 samples analyzed in

506 this study. Additionally, using shotgun metagenomics, we assembled 9 Gardnerella

507 genomes from 9 different animals that were closely related to human Gardnerella

508 vaginalis. Moreover, we assembled genomes from a diverse set of vaginal microbes

509 including Mobiliuncus, Sneathia, and Prevotella that were closely related to genomes

510 assembled from the human urogenital tract.

511 As others have previously reported (26), we found that Lactobacillus spp. was

512 largely absent in the rhesus macaque vaginal microbiome. In our initial screen, a

513 Lactobacillus dominant microbiome was found in 3 of the 10 animals. However, in our

514 longitudinal study, a Lactobacillus dominant microbiome (33-87% relative abundance)

515 was only transiently observed in animal RM14 at one time-point and animal RM3 at four

516 time-points. Lactobacillus was also detected at between 1-15% relative abundance in 13

517 samples across 7 animals. In humans, Lactobacillus spp. are the major producers of

518 lactic acids that results in low vaginal pH (~3.5). In accordance with those observations,

519 the presence of Lactobacillus in these animals correlated with lower vaginal pH and

520 Nugent scores at these time points. Our shotgun metagenomics analysis revealed the

521 presence of L. amylovarus and L. acidophilus. Although these species have not been bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

522 identified in samples from women in the developed world, future studies should

523 investigate the presence of these Lactobacillus species in VM from women in developing

524 countries.

525 Previous studies reported that the macaque VM is highly variable over time and

526 that some of this variability was correlated to hormonal cycling (25). We observed a

527 similar trend with multiple taxa being correlated to Progesterone levels including

528 Mobiluncus mulleris and Peptoniphilus. In contrast to previous longitudinal studies, we

529 found that the vaginal microbiome of some animals remained relatively stable while that

530 of others was variable over time. While further studies are needed to determine the

531 causes and consequences of these two unique communities’ states, one potential

532 explanation for this pattern is fecal contamination. Indeed, some samples obtained from

533 6 of the 9 animals with “variable” communities had fecal contamination while samples

534 from only 1 of 7 animals with “stable” communities exhibited fecal contamination. This

535 may suggest that “variable” VM are responding to community perturbation caused by

536 infiltration of fecal material and microbes. It is also possible that we did not sample often

537 enough to capture the true variability of the rhesus VM. Daily variability has been

538 observed in human samples and was associated with diet, exercise, and natural

539 hormonal cycling (56).

540 We also compared the functional capacity of the rhesus vaginal microbiome of

541 three distinct human vaginal microbiome communities; “Lactobacillus-dominated”,

542 “Asymptomatic diverse” and “Recurrent BV”. This analysis revealed that the rhesus

543 macaque and human VM are functionally distinct. However, the rhesus VM is

544 functionally most similar to that of asymptomatic women with a diverse vaginal

545 community. We found differences in metabolic potential between the four groups with all

546 three human VM functionally enriched in a variety of carbohydrate metabolism GO terms bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

547 that were not found in the rhesus macaque vaginal microbiome. Host derived glycogens

548 are the major energy source in the vaginal microbiome and driver of Lactobacillus

549 dominance (57). Differences in host glycogen production between humans and other

550 mammals is hypothesized to contribute to the unique Lactobacillus dominated

551 communities found in humans (7, 58). Although a small percentage of animals can

552 transiently harbor a Lactobacillus dominated VM, microbial communities in rhesus

553 macaques have significantly less vaginal glycogen than humans which may contribute to

554 their inability to sustain a Lactobacillus dominated vaginal community (59).

555 We tested an intravaginal prebiotic sucrose intervention to drive the vaginal

556 microbiome to a lactobacillus dominated state and improve clinical markers of BV.

557 Despite previously reported positive results for this intervention (22, 23), we found no

558 clinical or microbial indications of improvement. In our hands, intravaginal sucrose gel

559 did not lower vaginal pH, Nugent scores, or Amsel criteria positivity. Additionally, we did

560 not observe an increase in the relative abundance of Lactobacillus or a shift in overall

561 community composition. This intervention could have failed because the relative

562 abundance of Lactobacillus in these particular animals was below detection at the start

563 of the intervention. Moreover, shotgun metagenomics indicated that the “protein-N(PI)-

564 phosphohistidine-sugar phosphotransferase activity” pathway, a key step in the bacterial

565 import of sucrose, was largely absent in VM of humans with BV and rhesus macaques.

566 A microbial community lacking genes within this pathway is less likely to import and

567 metabolize sucrose. It is also worth noting that since the original goal of this study was to

568 determine if intravaginal sucrose treatment could improve clinical markers and increase

569 the abundance of Lactobacillus, we excluded animals with low vaginal pH and high

570 Lactobacillus abundance. In future studies, these animals should be identified and bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

571 studied longitudinally to determine if this represents a stable or transient community

572 state.

573 It has been well established that humans in the developing world have a distinct

574 microbiome from those of the developed nations (60). This has been particularly well

575 characterized in the context of the gut microbiome. For example, individuals in the

576 developing world harbor a more diverse gut microbiome colonized by microbes that have

577 all but disappeared in the western microbiome (61). This is due to a combination of key

578 environmental factors such diet, and antibiotic use among other factors (62-64). In

579 humans, there is also a clear distinction between the vaginal microbiomes of individuals

580 of the developed and developing worlds. Specifically, women in the developing world

581 have a much higher prevalence of diverse non-Lactobacillus dominated communities (4,

582 49). Understanding the drivers of these distinct microbial community states is critical to

583 developing VM targeted therapies. As we have previously shown for the gut microbiome,

584 we found that the rhesus VM is also more reflective of women in the developing world

585 (30).

586 In summary, we show that macaques harbor a diverse vaginal microbial

587 community similar to that detected in women with a non-Lactobacillus dominated

588 community or symptomatic BV at the 16S rRNA gene amplicon level. Additionally, we

589 show genomes assembled from the rhesus macaque vaginal microbiome are closely

590 related to human pathobionts associated with BV. Future studies should focus on the

591 immunological landscape of the rhesus urogenital tract to determine if this diverse

592 community state results in local inflammation as seen in humans with BV and

593 asymptomatic women with diverse communities. There are many unanswered questions

594 about why this community is maintained in some women and populations. While this

595 community type has been shown to increase the risk for some sexually transmitted bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

596 diseases such as HIV and HPV, these communities may be important for defense

597 against pathogens that are more prevalent in the developing world. Rhesus macaques

598 offer a unique opportunity to explore the importance of a diverse vaginal community that

599 is highly prevalent in women on a global scale.

600 601 602 603 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

604 FIGURE LEGENDS 605 606 607 Figure 1: Longitudinal assessment of clinical markers associated with BV. (A) 608 Study design and timeline. (B-E) Scatter plot of measured systemic (B) Progesterone, 609 (C) Oestrodiol, (D) Nugent scores, and (E) pH. Each dot represents an individual sample 610 with solid lines connecting samples from the same individual across time. The bold black 611 line represents the mean value across time. Significance was measured by non- 612 parametric 1-way repeated measures ANOVA (Friedman test) with Dunn's posthoc 613 comparisons between time points. Overall p-value denoted on each graph and bars 614 denoting significance of post hoc tests, * p < 0.05, ** p < 0.01, *** p < 0.001. (F) Stacked 615 bar graph denoting the percentage of animals that meet Amsel criteria. Colors 616 correspond to those used in panels B-E. (G, H) Scatter plot of (G) Nugent scores and 617 (H) vaginal pH comparing samples collected in animals with and without menses. 618 Significance determined by unpaired t-test, ** p < 0.01. 619 620 621 Figure 2: Longitudinal changes in the rhesus macaque vaginal microbiome. (A) 622 Heatmap of the 25 most abundant taxa across all samples ordered from left to right by 623 average abundance. Samples clustered by average linkage of Bray-Curtis distance 624 between samples. Metadata associated with each sample including animal ID, time- 625 point, Nugent score, vaginal pH, whiff test positivity, and menstruation status is provided 626 as well as a heatmap of Spearman rank correlation rho values between vaginal pH, 627 Nugent scores and systemic progesterone levels against the abundance of top 25 628 microbes. (B) Scatter plot of absolute sequence variants (ASVs) at each time point. 629 Each dot represents an individual sample with solid lines connecting samples from the 630 same individual across time. The bold black line represents the mean value across time. 631 (C, D) Principal coordinate analysis of unweighted UniFrac distance colored by 632 individuals with lines connecting samples collected from the same individual over time, 633 with density plots of key microbial taxa along the PCoA1 and PCoA2 axis. 634 635 636 Figure 3: Comparison of human and rhesus macaque vaginal microbiomes. (A) 637 Principal coordinate analysis of Bray-Curtis distance between rhesus macaque vaginal 638 microbiome, Lactobacillus dominated human vaginal microbiome, and diverse non- 639 Lactobacillus dominated human vaginal microbiome samples. (B) Bar graph of the 640 average Bray-Curtis distance between the rhesus macaque vaginal microbiome and the 641 two representative human communities. Significance determined using 1-way ANOVA p 642 < 0.001, with Bonferroni posthoc comparisons, ** p < 0.01, *** p < 0.001. (C) Table of 643 shared and exclusive bacterial genera between the three microbial community types. To 644 be included in this analysis genera had to be present in 10% of samples within a group 645 at < 0.1% relative abundance. 646 647 Figure 4: Genomes assembled from the rhesus macaque vaginal microbiome. 648 Phylogenetic tree built using 500 randomly selected conserved Cross-genus gene 649 families (PGfams) for assembled genomes from (A) Mobiluncus, (B) Snethia, (C) 650 Gardnerella, (D) Prevotella and (E) Campylobacter. Genomes in bold were assembled in 651 this study. Genome ID’s colored by host source. 652 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

653 Figure 5: Comparison of the functional potential of the rhesus and human vaginal 654 microbiome. (a) NMDS plot colored by sample source, outer circles denote if a sample 655 was misclassified at any point during the random forest model generation. The color of 656 the outer circle represents which group that sample was misclassified as. (B) Heatmap 657 of 50 most important GO terms as predicted by random forest. (C) Bar graph of the 658 average random forest proximity between the rhesus macaque vaginal microbiome and 659 the three human communities. Significance determined using 1-way ANOVA p < 0.001, 660 with Bonferroni posthoc comparisons, * p < 0.05. 661 662 Supplemental Figure 1: Removal of vaginal samples with potential fecal 663 contamination. (A) Principal coordinate analysis of unweighted UniFrac distance 664 generated from vaginal and concurrently collected fecal samples colored by sample 665 source. Vaginal samples circled in black denote samples with suspected fecal 666 contamination. (B) Scatter plot of measured absolute sequence variants (ASVs) for each 667 sample type including vaginal samples with suspected sequence contamination. 668 Significance determined using 1-way ANOVA p < 0.001, with Bonferroni posthoc 669 comparisons, *** p < 0.001. (C) Stacked bar plot highlighting three taxa that were shared 670 between fecal samples and vaginal samples with fecal contamination but absent in all 671 other vaginal samples and the sequenced microbial community standard. (D) Table of all 672 vaginal samples used for 16S rRNA gene amplicon sequencing. Boxes highlighted in red 673 were samples eliminated due to suspected fecal contamination, boxes in white were 674 eliminated from alpha and beta-diversity analysis due to low sequencing depth. Boxes in 675 green denote samples that were retained for further analysis. 676 677 Supplemental Figure 2: Impact of intravaginal sucrose treatment on clinical 678 markers of BV in rhesus macaques. (A-F) Longitudinal measurements of (A) Nugent 679 scores, (B) vaginal pH, (C) Whiff positivity, (D) clue cell positivity, (E) levels of estradiol, 680 and (G) progesterone. 681 682 Supplemental Figure 3: Impact of intravaginal sucrose treatment on the vaginal 683 microbiome in rhesus macaques. (A) Principal coordinate analysis of weighted 684 UniFrac distance colored by treatment group at baseline (open circle) and 14-days post- 685 treatment (filled circle). (B, C) Longitudinal measurement of (B) ASVs and (C) Shannon 686 evenness divided by treatment group. (D) The relative abundance of Lactobacillus 687 separated by treatment group at baseline and 4 time-points post-treatment. 688 689 Supplemental Figure 4: Shotgun metagenomic analysis of rhesus macaque 690 vaginal microbiome. (A) Scatter plot of sequences remaining after removal of host 691 reads. Red indicates samples that were removed from downstream analysis due to low 692 sequencing depth. (B) Table of genomes assembled based on assigned genus. (C) 693 NMDS of shotgun metagenomic samples collected 7-days post sucrose treatment 694 colored by treatment group, outer circles denote if a sample was misclassified at any 695 point during the random forest model generation. The color of the outer circle indicates 696 which group that sample was misclassified. (D) Heat map of top 50 GO terms ordered by 697 the overall contribution to random forest prediction accuracy, colored by importance for 698 defining each group and their contribution to overall model accuracy. 699 700 701 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

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790 33. M. N. Price, P. S. Dehal, A. P. Arkin, FastTree 2--approximately maximum- 791 likelihood trees for large alignments. PLoS One 5, e9490 (2010). 792 34. C. Quast et al., The SILVA ribosomal RNA gene database project: improved 793 data processing and web-based tools. Nucleic Acids Res 41, D590-596 (2013). 794 35. C. Lozupone, M. E. Lladser, D. Knights, J. Stombaugh, R. Knight, UniFrac: an 795 effective distance metric for microbial community comparison. ISME J 5, 169- 796 172 (2011). 797 36. A. M. Bolger, M. Lohse, B. Usadel, Trimmomatic: a flexible trimmer for 798 Illumina sequence data. Bioinformatics 30, 2114-2120 (2014). 799 37. B. Langmead, S. L. Salzberg, Fast gapped-read alignment with Bowtie 2. Nat 800 Methods 9, 357-359 (2012). 801 38. S. Abubucker et al., Metabolic reconstruction for metagenomic data and its 802 application to the human microbiome. PLoS Comput Biol 8, e1002358 (2012). 803 39. B. E. Suzek, Y. Wang, H. Huang, P. B. McGarvey, C. H. Wu, UniRef clusters: a 804 comprehensive and scalable alternative for improving sequence similarity 805 searches. 31, 926-932 (2015). 806 40. P. D. Karp, M. Riley, S. M. Paley, A. Pellegrini-Toole, The MetaCyc Database. 807 Nucleic Acids Research 30, 59-61 (2002). 808 41. N. Segata et al., Metagenomic biomarker discovery and explanation. Genome 809 Biol 12, R60 (2011). 810 42. A. Bankevich et al., SPAdes: a new genome assembly algorithm and its 811 applications to single-cell sequencing. J Comput Biol 19, 455-477 (2012). 812 43. D. D. Kang, J. Froula, R. Egan, Z. Wang, MetaBAT, an efficient tool for 813 accurately reconstructing single genomes from complex microbial 814 communities. PeerJ 3, e1165 (2015). 815 44. D. H. Parks, M. Imelfort, C. T. Skennerton, P. Hugenholtz, G. W. Tyson, 816 CheckM: assessing the quality of microbial genomes recovered from isolates, 817 single cells, and metagenomes. Genome research 25, 1043-1055 (2015). 818 45. A. R. Wattam et al., Assembly, Annotation, and Comparative Genomics in 819 PATRIC, the All Bacterial Bioinformatics Resource Center. Methods Mol Biol 820 1704, 79-101 (2018). 821 46. A. Oliver et al., Cervicovaginal Microbiome Composition Is Associated with 822 Metabolic Profiles in Healthy Pregnancy. mBio 11, (2020). 823 47. C. Zhao et al., Characterization of the Vaginal Microbiome in Women with 824 Infertility and Its Potential Correlation with Hormone Stimulation during In 825 Vitro Fertilization Surgery. mSystems 5, (2020). 826 48. J. Xu et al., Fertility factors affect the vaginal microbiome in women of 827 reproductive age. Am J Reprod Immunol 83, e13220 (2020). 828 49. R. N. Lois Bayigga, Alfred Ssekagiri, David P. Kateete, Musa Sekikubo, 829 Deborah J. Anderson, Jiawu Xu, Douglas S. Kwon, Damalie Nakanjako, Diverse 830 vaginal microbiome was associated with pro-inflammatory vaginal milieu 831 among pregnant women in Uganda. Human Microbiome Journal 18, (2020). 832 50. R. L. Goldenberg et al., Bacterial colonization of the vagina during pregnancy 833 in four ethnic groups. Vaginal Infections and Prematurity Study Group. Am J 834 Obstet Gynecol 174, 1618-1621 (1996). bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

835 51. R. B. Ness et al., Can known risk factors explain racial differences in the 836 occurrence of bacterial vaginosis? J Natl Med Assoc 95, 201-212 (2003). 837 52. M. A. Klebanoff et al., Race of male sex partners and occurrence of bacterial 838 vaginosis. Sex Transm Dis 37, 184-190 (2010). 839 53. V. L. Edwards et al., The Cervicovaginal Microbiota-Host Interaction 840 Modulates Chlamydia trachomatis Infection. mBio 10, (2019). 841 54. K. Diop, J.-C. Dufour, A. Levasseur, F. Fenollar, Exhaustive repertoire of 842 human vaginal microbiota. Human microbiome journal 2019 v.11, (2019). 843 55. Y. Chen et al., Association between the vaginal microbiome and high-risk 844 human papillomavirus infection in pregnant Chinese women. BMC Infect Dis 845 19, 677 (2019). 846 56. S. D. Song et al., Daily Vaginal Microbiota Fluctuations Associated with 847 Natural Hormonal Cycle, Contraceptives, Diet, and Exercise. mSphere 5, 848 (2020). 849 57. S. S. Witkin, I. M. Linhares, Why do lactobacilli dominate the human vaginal 850 microbiota? BJOG 124, 606-611 (2017). 851 58. P. Mirmonsef et al., Free glycogen in vaginal fluids is associated with 852 Lactobacillus colonization and low vaginal pH. PLoS One 9, e102467 (2014). 853 59. P. Mirmonsef et al., A comparison of lower genital tract glycogen and lactic 854 acid levels in women and macaques: implications for HIV and SIV 855 susceptibility. AIDS Res Hum Retroviruses 28, 76-81 (2012). 856 60. T. Yatsunenko et al., Human gut microbiome viewed across age and 857 geography. Nature 486, 222-227 (2012). 858 61. E. Angelakis et al., Treponema species enrich the gut microbiota of traditional 859 rural populations but are absent from urban individuals. New Microbes New 860 Infect 27, 14-21 (2019). 861 62. C. De Filippo et al., Diet, Environments, and Gut Microbiota. A Preliminary 862 Investigation in Children Living in Rural and Urban Burkina Faso and Italy. 863 Front Microbiol 8, 1979 (2017). 864 63. C. De Filippo et al., Impact of diet in shaping gut microbiota revealed by a 865 comparative study in children from Europe and rural Africa. Proceedings of 866 the National Academy of Sciences of the United States of America 107, 14691- 867 14696 (2010). 868 64. L. C. Bailey et al., Association of antibiotics in infancy with early childhood 869 obesity. JAMA pediatrics 168, 1063-1069 (2014). 870 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

Table 1. Animal 1 2 3 4 5 6 7 8 9 10 Nuggent score 9 9 8 5 10 8 7 2 5 N.C. Clue cells >20% Yes Yes Yes No Yes Yes Yes No No N.C. Vagninal pH 7 7.5 5.5 7.5 7 7.5 5.5 6 4.5 8 16S amplicon relative abundance Leptotrichiacece (Snethia) 27.26 21.26 30.52 89.78 9.7 9.37 0.36 2.78 2.13 0.05 Lactobacillus 0.02 0 0 0.13 0.03 0.03 42.98 55.75 84.44 0.1 Prevotella 14.84 5.02 13.58 0 7.46 8.41 4.97 0.25 0.02 0.02 Mobiluncus 10.53 14.97 3.07 0 7.01 8.16 0.46 0.62 0.01 0 Gardnerella 0 0 0 0 1.17 0 0 6.01 8.29 0 Porphyromonas 6.66 10.78 11.08 0.29 2.95 5.18 0.32 0.36 0 8.7 Trichococcus 0.31 2.18 1.1 0.18 1.18 0.62 10.76 0.67 0.01 61.01 Campylobacter 3.74 3.79 7.1 0 5.74 15.94 0.07 0.27 0 0.02 Anaerococcus 0.43 0.07 1.75 0.35 0.27 0.37 15.77 0.75 0.11 15.1 Catonella 0 0 0 0 8.91 9.87 0 0.14 0 0 Fusobacterium 1.71 0.3 16.22 0.02 0 0 0.01 0.11 0.01 0 Peptoniphilus 4.14 3.81 1.62 0.24 1.56 3.91 0.27 0.58 0.01 1.7 N.C. = Not Collected

A 7-day Timepoint 1.1 1.2 2 3 4Sucrose 5 6 7 8 Oral Contraception Menses or Placebo Elapsed Time 24-days 4-days 21-days 7-days 10-days 4-days 7-days 14-days

Clinical Measurement Hormone Measurement Vaginal 16S Fecal 16S

VaginalbioRxiv shotgunpreprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint Animals with Menses(which was3/16 not certified by peer review)N.C. is the 4/16author/funder. All rights reserved.10/16 No 2/16 reuse allowed without 0/16 permission. 0/16 5/16 1/16

Animal ID RM1 RM5 RM9 RM13 RM2 RM6 RM10 RM14 RM3 RM7 RM11 RM15 RM4 RM8 RM12 RM16 B C 100 1000

10 100

1

10 0.1 Oestrodiol pg/ml Oestrodiol Progesterone pg/ml Progesterone 1-way RM ANOVA p < 0.0001 1-way RM ANOVA p = 0.0001 0.01 1 Timepoint 1.1 2 3 4 5 6 7 8 1.1 2 3 4 5 6 7 8

D E 10 9

8 8

6 7 pH 4 6 Nugent Score Nugent 2 5 1-way RM ANOVA p = 0.0002 1-way RM ANOVA p = 0.012 0 4 Timepoint 1.1 2 3 4 5 6 7 8 1.1 2 3 4 5 6 7 8

G H F 100 10 10

8

50 5

Vaginal pH Vaginal 6 Nugent Score Nugent % Animals Amsel + Amsel Animals %

0 0 4 Timepoint 1.1 2 3 4 5 6 7 8

Mense Mense Figure 1 Non-Mense Non-Mense B 125

A 100

75

50

AnimalTimepoint IDpH NugentWhiffMense Observed ASVs 25

Animal ID 0 RM1 Timepoint 1.2 2 3 4 5 6 7 8 RM2 C 0.4 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint RM3 Stable (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. RM4 0.3 RM5

RM6 0.2 RM7

RM8 0.1 RM9

RM10 15.91 Weighted2 -0.0 RM11 RM12 -0.1 RM13 RM14 -0.2

RM15 -0.5 -0.4 -0.3 -0.2 -0.1 -0.0 0.1 0.2 0.3 0.4 RM16 Weighted1 33.3 Timepoint Snethia 1 Prevotella timonesis 2 Porphyromonas 3 Shannon Evenness 4 Porphyromonas Porphyromonas bennonis Porphyromonas 5 D 0.4 Variable 6 7 0.3 8 0.2 Whiff/Menses

Yes/Positive 0.1 No/Negative

No data 15.91 Weighted2 -0.0 pH/Nugent -0.1 1 2 3 4 5 6 7 8 9 10 E Progesterone Nugent -0.2 pH Spearman Rho pH

GardnerellaLactobacillus -0.6 −0.3 0.0 0.3 0.6 Figure 2 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

A B

0.4 Lactobacillus dominated human Diverse human Diverse human 0.3 Diverse rhesus macaque High Lactobacillus High Lactobacillus rhesus macaque rhesus macaque Lactobacillus 0.2 dominated human

0.1 High Lactobacillus rhesus macaque -0.0

Bray2 22.2% Diverse Diverse human -0.1 rhesus macaque

-0.2 Lactobacillus dominated human

-0.3 Lactobacillus Diverse human dominated human -0.4

-0.5 0.00.20.4 0.5 0.6 0.7 0.8 0.9 1.0

-0.4 -0.3 -0.2 -0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 Bray-Curtis Distance Bray1 31.1%

C Lactobacillus High Lactobacillus Diverse Diverse dominated human rhesus macaque human rhesus macaque (N=83) (N=5) (N=117) (N=105) Lactobacillus 90.10 66.39 6.21 0.37 Gardnerella 6.19 15.36 35.11 2.96 Prevotella 0.69 1.17 17.66 11.01 Porphyromonas 2.38 0.18 14.97 Leptotrichiaceae (Snethia) 0.15 3.43 7.09 23.60 Megasphaera 0.84 6.42 Mobiluncus 0.01 0.19 2.34 4.11 Fastidiosipila 0.45 0.12 5.35 Dialister 0.03 0.87 0.76 4.34 Atopobium 0.28 4.29 Catonella 0.35 4.36 Parvimonas 0.01 0.66 0.21 3.27 Atopobium 2.22 3.16 Peptoniphilus 0.02 0.51 0.28 2.34 Spirochaetaceae 0.18 0.00 2.57 Veillonella 0.08 2.13 Peptostreptococcaceae 0.11 2.35 Fusobacterium 0.01 0.03 0.03 2.28 Bacteroidales 0.04 0.01 1.83 0.21 Campylobacter 0.14 1.73 Figure 3 Other 1.54 5.56 15.32 11.02 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

A Mobiluncus mulieris strain FDAARGOS_303 B Sneathia RM10_T4_B1 Mobiluncus mulieris ATCC 35243 Sneathia RM15_T6_B4 Mobiluncus mulieris 28-1 Mobiluncus mulieris strain NCTC11497 Sneathia RM4_T6_B9 Mobiluncus RM8_T4_B1 Sneathia sp. Sn35 Mobiluncus RM7_T4_B5 Sneathia sanguinegens strain CCUG41628 Mobiluncus RM3_T6_B2 Mobiluncus RM4_T6_B2 Streptobacillus moniliformis DSM 12112 Mobiluncus RM14_T6_B1 Fusobacterium nucleatum ATCC 25586 Mobiluncus RM2_T6_B2 0 . 0 8 Fusobacterium periodonticum ATCC 33693 Mobiluncus curtisii subsp. curtisii strain NCTC11656 Mobiluncus curtisii ATCC 43063 Fusobacterium perfoetens ATCC 29250 0 . 5 Actinomyces radicidentis strain CCUG 36733 Arcanobacterium phocae strain DSM 10002 Prevotella RM1_T6_B6 D Prevotella RM4_T4_B7 Prevotella RM11_T6_B2 Prevotella RM2_T6_B1 C Gardnerella RM5_T6_B1 Prevotella RM7_T4_B3 Gardnerella RM12_T6_B6 Prevotella RM12_T6_B2 Prevotella timonensis CRIS 5C-B1 Gardnerella RM11_T6_B3 Prevotella buccalis ATCC 35310 Gardnerella RM2_T4_B2 Prevotella RM4_T6_B1 Gardnerella RM6_T6_B1 Prevotella RM10_T6_B1 Gardnerella RM4_T6_B6 Prevotella oralis ATCC 33269 Gardnerella RM3_T6_B9 Prevotella amnii CRIS 21A-A Gardnerella RM13_T4_B8 Prevotella bivia JCVIHMP010 88 Gardnerella RM16_T6_B1 Prevotella melaninogenica ATCC 25845 Prevotella denticola F0289 Gardnerella vaginalis strain DSM 4944 Prevotella disiens FB035-09AN Gardnerella vaginalis ATCC 14018 Prevotella OR4B2M1 Gardnerella vaginalis HMP9231 Prevotella CA6B3M1 Gardnerella vaginalis strain N160 Prevotella stercorea DSM 18206 Bi dobacterium longum s ubsp. inf ant i s R0033 Prevotella OR10B2M1 Bi dobacterium breve strain NRBB52 Prevotella copri DSM 18205 0 . 2 Bi dobacterium bi dum BGN4 Bact eroides f ragilis YCH46 Bi dobacterium animalis subsp. lactis Bi-07 Bi dobacterium tsurumiense strain JCM 13495 0 . 2 Alloscardovia omnicolens DSM 21503 E Campylobacter sputorum INTA08/209 Campylobacter sputorum RM3237 Campylobacter RM14_T6_B2 Campylobacter RM10_T6_B6 Rhesus Vaginal (This Study) Rhesus Fecal Campylobacter ureolyticus RIGS 9880 Campylobacter OR3B6M8 Human Vaginal Animal Other Campylobacter CA6B5M8 Outgroup Campylobacter CA5B6M8 Human Fecal Campylobacter hyointestinalis LMG 9260 Human Oral Campylobacter fetus 82-40 Campylobacter coli 76339 Campylobacter jejuni F38011 Campylobacter lari LMG 11760 Figure 4 0.2 Helicobacter cinaedi ATCC BAA-847 Arcobacter butzleri RM4018 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.14.422805; this version posted December 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.

A B −4 0 2 4 Row Z−Score amino.acid.transmembrane.transporter.activity 0.6 83% correct protein.N.PI..phosphohistidine.sugar.phosphotransferase.activity dipeptidase.activity phosphoenolpyruvate.dependent.sugar.phosphotransferase.system amino.acid.transport RNA.secondary.structure.unwinding RNA.helicase.activity negative.regulation.of.G0.to.G1.transition 0.4 transcription.regulatory.region.sequence.speci c.DNA.binding oxidoreductase.activity..acting.on.paired.donors..with.incorporation.or.reduction.of.molecular.oxygen..reduced.pteridine.as.one.donor..and.incorporation.of.one.atom.of.oxygen lipopolysaccharide.biosynthetic.process voltage.gated.chloride.channel.activity ATPase.coupled.organic.phosphonate.transmembrane.transporter.activity FtsZ.dependent.cytokinesi 0.2 D.gluconate.metabolic.process tRNA.5..leader.removal aspartate.tRNA.Asn..ligase.activity

Dimension 2 chromosome.segregation protein.serine.threonine.kinase.activity UDP.glucose.metabolic.process UTP.glucose.1.phosphate.uridylyltransferase.activity 0.0 ribosomal.large.subunit.binding palmitoyl..acyl.carrier.protein..hydrolase.activity myristoyl..acyl.carrier.protein..hydrolase.activity heme.transport Lactobacillus dominated human N.acetyldiaminopimelate.deacetylase.activity N.acetyltransferase.activity −0.2 Diverse human (BV symptomatic) sporulation.resulting.in.formation.of.a.cellular.spore ATP.metabolic.process Diverse human (Asymptomatic) proton.transmembrane.transport Rhesus macaque antioxidant.activity arginine.catabolic.process transferase.activity..transferring.alkyl.or.aryl..other.than.methyl..groups −0.6 −0.4 −0.2 0.0 0.2 0.4 phosphoglycerate.mutase.activity oxidoreductase.activity..acting.on.the.CH.CH.group.of.donors Dimension 1 oxidoreductase.activity..acting.on.the.aldehyde.or.oxo.group.of.donors..NAD.or.NADP.as.acceptor aminoacyl.tRNA.ligase.activity tRNA.aminoacylation C oxidation.reduction.process alanine.tRNA.ligase.activity organic.substance.metabolic.process aspartate.tRNA.ligase.activity Diverse human response.to.cadmium.ion (BV symptomatic) nucleobase.containing.compound.kinase.activity intein.mediated.protein.splicing ATPase.coupled.polyamine.transmembrane.transporter.activity propionyl.CoA.carboxylase.activity Lactobacillus regulation.of.pentose.phosphate.shunt dominated human myelin.sheath hydroxymethyl...formyl..and.related.transferase.activity

Diverse human (Asymptomatic)

0.0 0.2 0.4 0.6 0.8 1.0 Average distance to rhesus macaque Figure 5