Within the rapidly evolving field of microbiome sequencing, a primary need exists for experimentally capturing microbiota in a manner as close as possible to their in vivo composition. During microbiome profiling, the first step necessarily involves lysis of the cell wall, releasing nucleic acids for next-generation sequencing. Microbial cell wall thicknesses can vary between 5nm to 80nm; while some species are quite easy to lyse, others are particularly resistant to lysis. Despite this, current chemical/mechanical lysis protocols ignore the possibility that species with different cell wall thicknesses are lysed at differential rates. This creates noise in species compositions and possibly skews current microbiome results in ways that are not currently understood. To develop a cell wall thickness-agnostic lysis protocol, we used Adaptive Focused Acoustics (AFA), a tunable acoustic methodology for processing of biological samples. Using identical aliquots of mouse stool homogenate as the lysis substrate, we compared AFA with chemical/mechanical lysis methodology routinely used in microbiome studies and found that AFA-mediated lysis substantially increases both microbial DNA yield as well as alpha and beta diversity. By starting with lower AFA energy levels, sequentially removing aliquots at each step, and subjecting the remainder to progressively stronger AFA treatment, we developed a sequential lysis method that accounts for differences in cell wall thickness. This method revealed even greater levels of diversity than single-timepoint AFA treatment. 16S sequencing results from the above experiments were verified by shotgun metagenome sequencing of a subset of the AFA samples. We found that lysis-induced noise affects not just species compositions, but also functional characterization of shotgun metagenome data. AFA samples also showed a higher detection of eukaryotic and fungal DNA. We suggest that AFA-mediated lysis produces a truer representation of the native microbiota, and that this method deserves consideration as a potential addition to microbiome lysis protocols. ### Competing Interest Statement Hamid Khoja and James Laugharn are employees of Covaris, Inc., which is the registered trademark owner for AFA technology.
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