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Supplementary information
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SI Materials and Methods
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Subject’s selection
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BV status was assessed using the Amsel clinical criteria for all subjects [1] and confirmed
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using Gram-stain criteria (Nugent scores) [2]. The inclusion and exclusion criteria for these
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patients were as previously described. The participants who met three or more of the
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following criteria were clinically diagnosed as BV: a homogenous, milky vaginal discharge; >
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20% clue cells on wet mount; a vaginal discharge with an elevated pH (≥ 4.5); and release of
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a fishy amine odor upon addition of 10% potassium hydroxide (KOH) solution to the vaginal
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fluid (the so-called “whiff” test). The Nugent scoring system involves performing a Gram
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stain on a vaginal smear and enumerating lactobacilli versus Gram-negative rods and other
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bacterial morphotypes. Only participants with a Gram stain score ≥ 7 were confirmed to have
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BV. Participants without these changes were defined as the healthy control group. Any
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participant having any of the following exclusion criteria was excluded from participation: <
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18 years of age; pregnancy; diabetes mellitus; the use of probiotics, prebiotics, synbiotics,
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antibiotics, or other vaginal antimicrobials (orally or by topical application in the
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vulvar/vaginal area) in the previous month; menstruation; presence of an intrauterine device;
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vaginal intercourse within the latest 3 days; known active infection due to Chlamydia, yeast,
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Neisseria gonorrhoeae, or Trichomonas vaginalis; clinically apparent herpes simplex
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infection; or defined diagnosed HPV, HSV-2, or HIV-1 infection.
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Sample preparation
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When women underwent genital examinations before and after treatment, three swabs were
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taken near the mid-vagina using a sterile swab from each woman, packaged, and placed in ice
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packs. Two swabs were used to assess the BV status with the Amsel clinical criteria and
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Nugent scoring system; the third vaginal swab was used for bacterial genomic DNA
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extraction which were immediately transferred to the laboratory in an ice-box, and stored at
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-80°C after preparation within 15 min for further analysis.
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Total bacterial genomic DNA extraction
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The bacterial cells retrieved on swabs were submerged in 1 ml of sterile normal saline
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(prepared with RNase-free H2O [pH 7.0]) and vigorously agitated to dislodge cells, while
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vaginal swabs that were not used serves as negative controls, which were handled in the same
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way. The cells were pelleted by centrifugation (Thermo Electron Corporation, Boston, MA,
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USA) at full speed (≥ 10,000 g) for 10 min, washed by re-suspending the cells in sterile
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normal saline, and centrifuged at full speed for 5 min. Then, bacterial DNA was extracted
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from the vaginal swabs using QIAamp DNA Mini Kit (QIAGEN, Hilden, Germany)
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according to manufacturer’s instructions, with the following minor modification: samples
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were agitated with 100 mg zirconium beads (0.1 mm) in Mini-beadbeater (FastPrep, Thermo
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Electron Corporation, USA) for 2 min and incubated at 56°C for 1 hour in lysis solution
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containing proteinase K [3, 4]. The concentration of extracted DNA was determined using a
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NanoDrop ND-1000 spectrophotometer (Thermo Electron Corporation); the integrity and size
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were checked using 1.0% agarose gel electrophoresis containing 0.5 mg/ml ethidium bromide.
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All DNA was stored at -20°C before further analysis.
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PCR Amplification and Sample Pooling for 454 pyrosequencing
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PCR amplification of the 16S rRNA gene hypervariable V3-region was performed with
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universal bacterial primer which corresponded to positions 341 to 534 in Escherichia coli.
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Amplicon pyrosequencing was performed with standard 454/Roche GS-FLX Titanium
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protocols. To pool and sort multiple samples in a single 454 GS-FLX run, we designed unique
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barcode of 8 nucleotides to identify each sample (Table S5). We used a set of 8-bp barcodes
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designed according to Fierer et al. [5-7]. The main criterion of these barcodes is that the
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adjoining nucleotides must be different because the single nucleotide repeats are the main
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source of errors in pyrosequencing technology. The resulting forward primer was a fusion of
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the 454 life science adaptor A, the barcode, and 341F (5’-GCCTCCCTCGCGCCATCAG
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-NNNNNNNN-ATTACCGCGGC TGCTGG -3’). And the resulting reverse primer was a
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fusion of the 454 life science adaptor B, the same barcode with forward primer, and 534R (5’-
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GCCTTGCCAGCCCGCTCAG-NNNNNNNN-CCTACGGGAGGCAGCAG -3’). The PCR
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amplicon library was created for each individual DNA sample. The amplification mix
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contained 1.25 U of Hot Start Taq polymerase (Takara, Dalian, China), 1 x PCR buffer (2.5
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mM MgCl2 included), 3 pmol of each primer, 200 mM each deoxynucleoside triphosphate
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(dNTP) and 1 l of extracted bacterial DNA in a total volume of 50 l. Samples were initially
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denatured at 94 °C for 5 min, then amplified by using 30 cycles of 94 °C for 30 s, 55 °C for
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30 s, and 72 °C for 30 s. A final extension of 7 min at 72 °C was added at the end of the
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program to ensure complete amplification of the target region. Negative controls (both
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no-template and template from unused swabs) were included in all steps of the process to
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check for primer or sample DNA contamination. Before pooling these 100 samples, PCR
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products were purified by electrophoresis on a 1% agarose gel and eluted with QIAquick Gel
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Extraction Kit (QIAGEN). The concentration of each PCR product was measured by using a
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NanoDrop ND-1000 spectrophotometer (Thermo Electron Corporation) three times and then
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quantified by using on-chip gel electrophoresis with Agilent 2100 BioAnalyzer (Agilent
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Technologies, Santa Clara, CA, USA) and DNA LabChip Kit 7500. Individual amplicon
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libraries were pooled in equimolar amounts, and subjected to emulsion PCR, and generated
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amplicon libraries and sequenced unidirectionally in the reverse direction (B-adaptor) by
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means of the Genome Sequencer FLX (GS-FLX) system (Roche, Basel, Switzerland) at 454
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Life Sciences. Because samples were pooled by equal mass, variation in the number of
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sequences recovered from each sample likely reflects slight biases in PCR efficiency among
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primer barcodes.
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Sequence processing pipeline for 454 pyrosequencing reads
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Initially, all pyrosequencing reads were screened and filtered for quality and length of the
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sequences using customized Perl scripts. Raw sequences were processed and analyzed
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following the procedure described previously [7]. Sequences were included in the subsequent
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analysis, only if the sequences met all four of the following criteria: (1) the sequence carries
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the correct barcode and exact match to the primer in at least one end; (2) the sequence carries
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the correct primer sequence in the other end, even though the barcode absent; (3) the sequence
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has a length of longer than 160 nucleotides (excluding barcode and primer A sequences) [8];
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and (4) the sequence without any ambiguous bases (Ns). Because all of the samples are
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pooled into a single sequencing reaction, we incorporate the barcodes to allow reads from
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each individual sample to be identified. In this way, we could analyze the sequences from
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each sample separately. Sequencing reads were derived directly from FLX sequencing run
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output files. This resulting multi-FASTA file contained 498,814 total high-quality reads.
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Based upon the individual sample barcode sequence, those sequences specific for each sample
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were extracted from the multi-FASTA file into individual FASTA files. The sequences were
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then relabeled according to denote the original sample. In order to facilitate the subsequent
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pipeline pyrosequencing analysis, the script then trimmed off the forward primer sequence
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and barcode sequence after alignment and oriented the remaining sequence such that all
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sequences begin with the 5’ end according to standard sense strand conventions. We included
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only sequences with the forward primer motif to ensure that the highly informative V3 region
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was available for taxonomic assignment.
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Phylogenetic assignment, alignment and clustering of 16S rRNA gene fragments
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The qualified 16S rRNA gene fragments were phylogenetically assigned according to their
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best matches to sequences based upon BLASTn using WND-BLAST [9] and a curated 16S
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database derived from high quality 16S sequences obtained from RDPII database [10].
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Phylogenetic assignments were also evaluated using the Nearest Alignment Space
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Termination (NAST, http://greengenes.lbl.gov/NAST) database [11]. Multiple sequence
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alignment was done using a newly update version of DOTUR, called MOTHUR (version
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1.20.0; http://www.mothur.org/) [12], which are designed to be a platform that will enable to
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align their 16S rRNA gene sequences, calculate pairwise distances, and analyze the resulting
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distance matrices. With the MOTHUR filter.seqs command, we will remove any vertical gaps
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from the alignment. Based on the alignment, a distance matrix at a given % dissimilarity was
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constructed using with MOTHUR dist.seqs command. The proportion of OTUs shared among
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the communities was determined using MOTHUR, which uses the .list output files from
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MOTHUR as input and determines the fraction of OTUs shared by communities as a function
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of genetic distance. These pairwise distances served as input to MOTHUR for clustering the
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sequences into OTUs of defined sequence similarity that ranged from unique to 3%
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dissimilarity. A distance matrix was then generated using the MOTHUR tree.shared
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command. These clusters served as OTUs for generating predictive rarefaction models and for
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making calculations with the richness (diversity) indexes ACE and Chao1 [13] in MOTHUR.
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These programs were run on a SUSE Linux Enterprise 10 machine, 24 quad core 48
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processors at 3.0 Ghz with 128 GB of RAM.
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Statistical data analysis of OTU richness: rarefaction, Chao 1 and ACE
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To estimate species richness and diversity, taxonomy-independent methods were used.
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Clustering was done with a given % dissimilarity for inclusion into an OTU and was
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performed on alignments of sequences from individual participant. The matrices were used to
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define operational taxonomic units with 1% dissimilarity for determination of the coverage
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percentage by Good’s method. The species richness and relative abundance of species
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(Evenness) was estimated by further sampling-based (rarefaction) analyses of OTU data and
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of calculated Shannon and Simpson diversity indices. These clusters served as OTUs for
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generating rarefaction curves and for making calculations with the richness and diversity
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indexes, abundance based coverage estimator (ACE), bias-corrected Chao1 richness estimator,
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in MOTHUR at each dissimilarity level. Shannon index characterize diversity based on the
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number of species present (species richness). The Shannon index of evenness was calculated
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with the formula E = H/ln(S), where H is the Shannon diversity index and S is the total
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number of sequences in that group. This metric is insensitive to the taxa richness and ranges
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from 0 to 1, with 0 representing complete dominance and 1 representing an evenly structured
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community. Good’s coverage percentage was calculated as [1/ (n/N)]/100, where n represents
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the number of single-member phylotypes and N represents the number of sequences. The
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resulting tables of OTU clusters versus dataset and primer were the source data for the Venn
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diagrams. We plotted our Venn diagrams using the Venn Diagram Plotter program written by
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Littlefield and Monroe at the Department of Energy, PNNL, Richland, VA. Taxonomy-based
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analyses were performed by assigning taxonomic status to each sequence using the Naïve
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Bayesian CLASSIFIER program of the Michigan State University Center for Microbial
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Ecology Ribosomal Database Project (RDP) database (http://rdp.cme.msu.edu/) [14] with an
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50% bootstrap score. Sequences were aligned using INFERNAL Aligner both from individual
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participant and then as pooled sequences from all participants of a single group. Cluster
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analysis was performed using the complete linkage clustering algorithm available through the
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Pyrosequencing pipeline of the Ribosomal Database Project [15]. The neighbor-joining tree
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was constructed using the MEGA 4.0 program based on the Jukes-Cantor model and used for
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UniFrac analysis. Principal coordinates analysis (PCA) of vaginal bacterial communities
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among the 115 samples from 4 groups was obtained by pyrosequencing, and performed using
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the R program. Statistical analyses for Shannon and Simpson index were performed using
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SPSS Data Analysis Program version 16.0 (SPSS Inc, Chicago, IL) with One-Way ANOVA.
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All tests for significance were two-sided, and p values < 0.05 were considered statistically
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significant.
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Real-time qPCR for vaginal microbiota
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To estimate the accurate copy numbers of bacteria in vagina samples and validate the relative
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abundance of bacteria in genus determined by 454 pyrosequencing, 16S rRNA gene-targeted
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quantitative PCR (qPCR) was performed with a Power SYBR Green PCR Master Mix
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(Takara, Dalian, China) on an ABI 7900 Real-time PCR instrument according to the
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manufacturer’s instructions (Applied Biosystems, Foster city, CA). Species-specific primer
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sets were chosen to quantify total bacteria, Lactobacillus genus, L. iners, L. crispatus, L.
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jensenii, Gardnerella vaginalis, Atopobium vaginae, Eggerthella sp., Megasphaera typeⅠsp.,
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Leptotrichia/Sneathia sp. and Prevotella sp. (Table S6). For each primer set, a constructed
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plasmid was chosen to create a 10-log-fold standard curve for direct quantification of all
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samples. With the exception of total domain Bacteria and Lactobacillus genus, all standard
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curve genes were amplified from the vaginal samples, constructed plasmids, sequenced and
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confirmed the source of target organisms by BLAST in GenBank. For total domain Bacteria
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and Lactobacillus genus, Escherichia coli ATCC 25922 and Lactobacillus casei ATCC 27139
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was used to create the plasmid standards, respectively. For each, the product was cloned into
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pMD18-T vector using the Simple TA Cloning Kit (Takara, Dalian, China) following the
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manufacturer’s procedure. Purified insert-containing plasmids were quantified using a
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NanoDrop ND-1000 spectrophotometer (Thermo Electron Corporation), and taking into
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account the size of the product insert, the number of target gene copies was calculated from
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the mass of DNA. Tenfold serial dilutions ranging from 1 × 109 to 1 gene copies were
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included on each 96-well plate. Each subject’s extracted DNA was subjected to a human
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-Globin PCR to ensure that amplifiable DNA was successfully extracted from the sample
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and to monitor for PCR inhibitors with the same protocol listed for bacterial PCR [13]. Each
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qPCR contained 12.5 L of 2 × Takara Perfect Real Time master mix, 10.9 L of water, 0.3
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L of a 10 M F/R primer mix, and 1 L of extracted bacterial genomic DNA. Cycling
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conditions: 95 °C for 3 min; 40 repeats of the following steps: 94 °C for 30 s, 30 s annealing
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at different temperature, and 72°C for 30 s. At each cycle, accumulation of PCR products was
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detected by monitoring the increase in fluorescence of the reporter dye, dsDNA-binding
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SYBR Green. Following amplification, melting temperature analysis of PCR products was
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performed to determine the specificity of the PCR. Melting curves were obtained from 55 °C
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to 90 °C, with continuous fluorescence measurements taken at every 1 °C increase in
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temperature. Data analysis was conducted with Sequence Detection Software version 1.6.3,
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supplied by Applied Biosystems. All reactions were carried out in triplicate and a nontemplate
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control was performed in every analysis. In addition, the abundance of each group relative to
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total domain Bacteria gene copy number was calculated for each replicate, and the mean,
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standard deviation and statistical significance were determined. Comparisons between BV-M
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and BV-L women were calculated with unpaired t-tests (SPSS Data Analysis Program version
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16.0, SPSS Inc, Chicago, IL) and were considered statistically significant if p < 0.05.
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