ARISA data from the human gut microbiome can detect individual differences observed by 454 sequencing regardless of binning strategy

TL;DR

This study evaluates ARISA, a low-cost microbial profiling technique, and finds that with proper clustering, it can distinguish individual human gut microbiomes similarly to high-throughput sequencing, despite some limitations.

Contribution

It demonstrates that clustering method choice significantly impacts ARISA data analysis, while binning strategies have minimal effect, guiding better use of ARISA for microbiome studies.

Findings

Ward's clustering yields ARISA profiles similar to 454 sequencing.

Bin size and presence/absence calls have negligible effects.

ARISA closely approximates sequencing results at lower cost.

Abstract

ARISA (Automated Ribosomal Intergenic Spacer Analysis) is a low-cost technique that allows for the rapid comparison of different microbial environments. In this study, we asked if a set of ARISA profiles can distinguish human microbial environments from one another with the same accuracy as results generated from 454 high throughput DNA sequencing. Using a set of human microbial communities where the sequencing results cluster by subject, we tested how choices made during ARISA data processing influence clustering. We found that choice of clustering methods had a profound effect with Ward's clustering generating profiles the most similar to 454 sequencing. Factors such as bin size, using presence or absence calls and technical replicate manipulation had a negligible effect on clustering. In fact, no established bin sizing method reported in the literature performed significantly different results than simply picking bin intervals at random. We conclude that in an analysis of ARISA data from an ecosystem of sufficient complexity to saturate bins, a careful choice of clustering algorithm is essential whereas differing strategies for choosing bins are likely to have a much less pronounced effect on the outcome of the analysis. As a tool for distinguishing complex microbial communities, ARISA closely approximates the results obtained from DNA sequencing at a fraction of the cost; however ARISA fails to reproduce the sequencing results perfectly.