VALENCIA: a nearest centroid classification method for vaginal microbial communities based on composition

Abstract

Background: Taxonomic profiles of vaginal microbial communities can be sorted into a discrete number of categories termed community state types (CSTs). This approach is advantageous because collapsing a hyper-dimensional taxonomic profile into a single categorical variable enables efforts such as data exploration, epidemiological studies, and statistical modeling. Vaginal communities are typically assigned to CSTs based on the results of hierarchical clustering of the pairwise distances between samples. However, this approach is problematic because it complicates between-study comparisons and because the results are entirely dependent on the particular set of samples that were analyzed. We sought to standardize and advance the assignment of samples to CSTs.

Results: We developed VALENCIA (VAginaL community state typE Nearest CentroId clAssifier), a nearest centroid-based tool which classifies samples based on their similarity to a set of reference centroids. The references were defined using a comprehensive set of 13,160 taxonomic profiles from 1975 women in the USA. This large dataset allowed us to comprehensively identify, define, and characterize vaginal CSTs common to reproductive age women and expand upon the CSTs that had been defined in previous studies. We validated the broad applicability of VALENCIA for the classification of vaginal microbial communities by using it to classify three test datasets which included reproductive age eastern and southern African women, adolescent girls, and a racially/ethnically and geographically diverse sample of postmenopausal women. VALENCIA performed well on all three datasets despite the substantial variations in sequencing strategies and bioinformatics pipelines, indicating its broad application to vaginal microbiota. We further describe the relationships between community characteristics (vaginal pH, Nugent score) and participant demographics (race, age) and the CSTs defined by VALENCIA.

Conclusion: VALENCIA provides a much-needed solution for the robust and reproducible assignment of vaginal community state types. This will allow unbiased analysis of both small and large vaginal microbiota datasets, comparisons between datasets and meta-analyses that combine multiple datasets. Video abstract.

Fig. 1

Heatmap displaying the taxonomic composition of 13,160 vaginal microbial communities using the 25 most abundant phylotypes across all samples. Hierarchical clustering was performed using Bray-Curtis dissimilarity with Ward linkage. Seven community state types were defined, four of which were dominated by a single species of Lactobacillus and three which were not. This dataset was used to train VALENCIA

Fig. 2

Average relative abundance of twelve key taxa across all of the samples used to define each of the thirteen sub-CSTs. Error bars represent the standard error of the mean as defined using 100 bootstraps of ten percent of the training dataset. These “average” communities define the reference centroids used by VALENCIA to assign new samples to sub-CSTs. Sub-CST IV-C0 is not dominated by any one species. CST V has 20% relative abundance of L. iners in addition to L. jensenii, indicating these two species can co-occur. This relationship is maintained over extended periods of time in some longitudinal profiles

Fig. 3

Taxonomic composition of all samples (n = 13,160) in the training data set categorized by sub-CST assignment according to VALENCIA (a). Distribution of Shannon diversity index values by sub-CST assignment (b). Shannon diversity was calculated using the log base 2

Fig. 4

Validation of VALENCIA using three test datasets of vaginal taxonomic profiles derived from sequencing of the 16S rRNA gene. For each dataset, the similarity of each sample to its assigned sub-CST is plotted as a normalized histogram (left, a red, b blue, c green) versus that for the training dataset (dark grey). The taxonomic composition of each sample in the dataset is also provided (right). Test dataset 1 (a) was published by Hickey et al., contained 245 samples, was derived from sequencing of the V1V3 region, and contained samples from adolescent girls. Test dataset 2 (b) contained 1380 samples from menopausal women and was derived from sequencing of the V3V4 region. Test dataset 3 (c) was published by McClelland et al., contained 110 samples from eastern and southern African women, and was derived from sequencing of the V4 region

Fig. 5

The relationship between each VALENCIA-assigned sub-CST and Nugent score (a) and vaginal pH (b). Nugent score was separated into high (score 8–10), intermediate (score 4–7), and low (score 0–3) categories. Vaginal pH was split into four categories: less than or equal to 4.5, between 4.5 and 5.0, between 5.0 and 5.5, and greater than or equal to 5.5

Fig. 6

The relationship between the prevalence of each VALENCIA-assigned sub-CST and a woman’s self-identified race (a). Each bar represents the proportion of samples assigned to each CST in women whose race is Asian (n = 95), Black (n = 1,343), Hispanic (n = 110), White (n = 403), or Other (n = 17). For subjects who contributed multiple samples, the within subject relative prevalence of each CST was used in the calculation instead of their individual CST counts. We also examined relationships between the prevalence of each CST and a woman’s age (b). Only the prevalence of CST III was found to have a relationship with age among reproductive-age women. Bars represent the age distribution of subjects whose samples were (orange) or were not (grey) assigned to CST III. Older reproductive age women were less likely to have communities assigned to CST III than younger reproductive age women