Application of an ecology-based analytic approach to discriminate signal and noise in low-biomass microbiome studies: whole lung tissue is the preferred sampling method for amplicon-based characterization of murine lung microbiota

Abstract

AbstractBackgroundLow-biomass microbiome studies (such as those of the lungs, placenta, and skin) are vulnerable to contamination and sequencing stochasticity, which obscure legitimate microbial signal. Since low-biomass microbiome fields have had variable success in establishing the reality and clinical significance of identified microbiota, we sought to develop and apply an analytical approach to discriminate signal from noise in low-biomass microbiome studies. We used this approach to determine the optimal sampling strategy in murine lung microbiome studies, which will be essential for future mechanistic lung microbiome research.MethodsUsing a novel, ecology-based analytic approach, we compared bacterial DNA from the lungs of healthy adult mice collected via two common sampling approaches: homogenized whole lung tissue and bronchoalveolar lavage (BAL) fluid. We quantified bacterial DNA using droplet digital PCR, characterized bacterial communities using 16S rRNA gene sequencing, and systematically assessed the quantity and identity of bacterial DNA in both specimen types. We compared bacteria detected in lung specimens to each other and to potential source communities: negative (background) control specimens and paired oral samples.FindingsBy all measures, whole lung tissue in mice contained greater bacterial signal and less evidence of contamination than did BAL fluid. Relative to BAL fluid, whole lung tissue exhibited a greater quantity of bacterial DNA, distinct community composition, decreased sample-to-sample variation, and greater biological plausibility when compared to potential source communities. In contrast, bacteria detected in BAL fluid were minimally different from those of procedural, reagent, and sequencing controls.InterpretationAn ecology-based analytical approach discriminates signal from noise in low-biomass microbiome studies and identifies whole lung tissue as the preferred specimen type for murine lung microbiome studies. Sequencing, analysis, and reporting of potential source communities, including negative control specimens and contiguous biological sites, is crucial for biological interpretation of low-biomass microbiome studies, independent of specimen type.FundingNational Institutes of Health