Abstract
BackgroundLow-biomass microbiome studies (such as those of the lungs, placenta, and skin) are vulnerable to contamination and sequencing stochasticity, which obscure legitimate microbial signal. While human lung microbiome studies have rigorously identified sampling strategies that reliably capture microbial signal from these low-biomass microbial communities, the optimal sampling strategy for characterizing murine lung microbiota has not been empirically determined. Performing accurate, reliable characterization of murine lung microbiota and distinguishing true microbial signal from noise in these samples will be critical for further mechanistic microbiome studies in mice.ResultsUsing an analytic approach grounded in microbial ecology, 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. By 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.ConclusionsAn ecology-based analytical approach discriminates signal from noise in this low-biomass microbiome study 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, are crucial for biological interpretation of low-biomass microbiome studies, independent of specimen type.Aaejar9WP4PeeefSRNqdytVideo abstract
Highlights
Low-biomass microbiome studies are vulnerable to contamination and sequencing stochasticity, which obscure legitimate microbial signal
Murine whole lung tissue contains more bacterial Deoxyribonucleic acid (DNA) than bronchoalveolar lavage (BAL) fluid and negative controls Obtaining quality sequencing data depends on the presence of sufficient bacterial DNA in the samples to be analyzed
We first compared the quantity of bacterial DNA in whole lung tissue and BAL fluid obtained from healthy C57BL/6 mice (Fig. 1, step 3)
Summary
Low-biomass microbiome studies (such as those of the lungs, placenta, and skin) are vulnerable to contamination and sequencing stochasticity, which obscure legitimate microbial signal. Low-biomass samples—samples with low densities of bacterial cells and low quantities of bacterial DNA—are susceptible to contamination with background-derived signal, which affects the taxonomic composition of low-biomass samples [1, 2] This challenge of background DNA, contamination, and sequencing stochasticity (here collectively referred to as “noise”) intermingled with legitimate bacterial signal originating from a biological specimen (here referred to as “signal”) makes it challenging to decipher biological meaning from sequencing data [3]. These methodological challenges exist in all fields that study lowbiomass microbial communities across environmental, industrial, and biomedical contexts. Empirically validated sampling approaches such as bronchoalveolar lavage (BAL) fluid, which (in humans) samples a large surface area and yields high sample volumes, have been successfully implemented in lung microbiome studies [31]
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