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bioRxiv · 10.64898/2026.07.13.738261

Data Independent Acquisition Pipeline for Microbiome Samples (Microbe-DIA)

Obermiller, S. A.·Lipton, M. S.·Piehowski, P. D.·Bilbao, A.·McCue, L. A.·Prozapas, V. N.·Attah, I. K.
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Abstract

The functional complexity inherent in microbiomes complicates analytical approaches aimed at defining phenotype. As proteins are the functional effectors of microbiome phenotypes, improving the performance of mass spectrometry-based metaproteomics is critical to achieving the functional characterization of these systems. Data-independent acquisition (DIA) improves protein coverage and reduces data missingness when compared to data-dependent acquisition (DDA) in metaproteomics. However, the application of DIA to complex microbial systems remains constrained by analytical throughput and computational scalability. Here, we optimized LC-MS/MS acquisition parameters for both DDA and DIA using a model microbiome, demonstrating how DIA enables increased sample throughput without compromising quantitative performance. In addition, we demonstrated a computationally efficient, library-free DIA workflow that overcomes reliance on empirical spectral libraries. Our analytical and computational innovations establish a scalable and cost-effective pipeline for metaproteomics of complex microbial communities.

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Obermiller, S. A., Lipton, M. S., Piehowski, P. D., Bilbao, A., McCue, L. A., Prozapas, V. N., Attah, I. K.. 2026-07-14. Data Independent Acquisition Pipeline for Microbiome Samples (Microbe-DIA). https://doi.org/10.64898/2026.07.13.738261

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