On the Use of Diversity Measures in Longitudinal Sequencing Studies of Microbial Communities

Abstract

Identification of the majority of organisms present in human-associated microbial communities is feasible with the advent of high throughput sequencing technology. As substantial variability in microbiota communities is seen across subjects, the use of longitudinal study designs is important to better understand variation of the microbiome within individual subjects. Complex study designs with longitudinal sample collection require analytic approaches to account for this additional source of variability. A common approach to assessing community changes is to evaluate the change in alpha diversity (the variety and abundance of organisms in a community) over time. However, there are several commonly used alpha diversity measures and the use of different measures can result in different estimates of magnitude of change and different inferences. It has recently been proposed that diversity profile curves are useful for clarifying these differences, and may provide a more complete picture of the community structure. However, it is unclear how to utilize these curves when interest is in evaluating changes in community structure over time. We propose the use of a bi-exponential function in a longitudinal model that accounts for repeated measures on each subject to compare diversity profiles over time. Furthermore, it is possible that no change in alpha diversity (single community/sample) may be observed despite the presence of a highly divergent community composition. Thus, it is also important to use a beta diversity measure (similarity between multiple communities/samples) that captures changes in community composition. Ecological methods developed to evaluate temporal turnover have currently only been applied to investigate changes of a single community over time. We illustrate the extension of this approach to multiple communities of interest (i.e., subjects) by modeling the beta diversity measure over time. With this approach, a rate of change in community composition is estimated. There is a need for the extension and development of analytic methods for longitudinal microbiota studies. In this paper, we discuss different approaches to model alpha and beta diversity indices in longitudinal microbiota studies and provide both a review of current approaches and a proposal for new methods.

Endometriosis and the microbiome: a systematic review

“…Microbial communities can be characterised through the use of diversity indices . α ‐Diversity is used to describe the diversity of a microbial community within a single sample or site whereas β ‐diversity is an index used to compare the diversity of microbial communities across different samples or sites . Five of eighteen studies assessed α ‐diversity .…”

Changes in microbiome diversity following beta-lactam antibiotic treatment are associated with therapeutic versus subtherapeutic antibiotic exposure in cystic fibrosis

“…genus, Ace, and Chao give more weight to richness. Shannon weights richness and evenness equally, while Simpson provides more weight to evenness 49 . Beta diversity between samples was measured using Morisita-Horn 49 .…”

“…Shannon weights richness and evenness equally, while Simpson provides more weight to evenness 49 . Beta diversity between samples was measured using Morisita-Horn 49 . The OTU and taxonomy tables were also imported into Rstudio for subsequent analyses using phyloseq and DESeq2 to determine differential abundance and create principle coordinates analysis (PCoA) plots 50,51 .…”

Sexually Dimorphic Influence of Neonatal Antibiotics on Bone

“…B). In contrast, the Bray–Curtis measure of β‐diversity, used to identify similarities between the microbiota communities of the experimental groups, showed distinct clustering of samples based on both exposures to Abx and sex (Fig. C).…”

“…Neonatal Abx administration resulted in long-lasting intestinal dysbiosis in adult mice as revealed by 16S Illumina sequencing analysis. Phylogenetic diversity, intended as the measure of the richness or diversity of the microbiota community of each experimental group, 25 was significantly lower in neonatal Abx-treated mice, with no differences within sex, as assessed by the Shannon index (Fig. 1B).…”