Integrated omics reveals actionable drivers of bioactive variation in US milk
Abstract
Despite milk being a global dietary staple, the molecular basis of its health-relevant bioactivity and the factors governing fine-scale compositional variation remain poorly understood. Here, we present an integrated seven-layer omics characterization of 60 US retail milk samples from ten geographic regions, combining genomics, transcriptomics, peptidomics, proteomics, lipidomics, metabolomics, and glycomics on the same samples. We also organized the identified and quantified compounds into the Dairy Molecule Database (DMD), a web-accessible resource for linking milk compound concentrations with SNPs, miRNAs, and product-level factors to support future milk quality optimization. In total, we identified 6,714 compounds and quantified 5,288 with absolute concentrations, including 5,220 compounds not previously available with absolute concentration estimates in existing milk compound databases. These profiles enabled bioactivity efficacy estimation and association analyses of factors linked to milk compound variation. We tested 54 computationally predicted antimicrobial candidate peptides; 35 showed activity and 6 had IC50 values below 256 μg/mL against A. baumannii, an ESKAPE pathogen. We further identified associations between downstream bioactive compound concentrations or estimated bioactivity efficacy and product-level factors, including purchase region, purchase ambient temperature, and packaging opacity, as well as SNPs, estimated Jersey breed proportion, and miRNA abundance. Overall, bioactivity efficacy profiles were associated with purchase region, selected SNPs, Jersey breed proportion, and selected miRNAs. These findings suggest that selective breeding and supply-chain optimization could help improve the bioactive quality of commercial milk.
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BibTeX
@misc{tan2026integrated,
title = {{Integrated omics reveals actionable drivers of bioactive variation in US milk}},
author = {Cheng-En Tan and Mariana Barboza and Pagkratios Tagkopoulos and Shanghyeon Kim and Lukas Maximilian Masopust and Ivor Prado and Muhammad Adil Salim and Fangzhou Li and George Berdovskiy and Ilias Apostolakos and Brandon Invergo and Karen M. Kalanetra and Danielle G. Lemay and David A. Mills and Armin Oloumi and Cheng-Yu Weng and Carlito B. Lebrilla and Xuan He and Carolyn Slupsky and Oliver Fiehn and Ibuki Kusumoto and Ameer Y. Taha and Yu Wang and Daniela Barile and Alexis Davis and David E. Olson and Justin B. Siegel and Ilias Tagkopoulos},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.04970},
eprint = {2610.04970},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.04970},
}
RIS
TY - UNPB
TI - Integrated omics reveals actionable drivers of bioactive variation in US milk
AU - Cheng-En Tan
AU - Mariana Barboza
AU - Pagkratios Tagkopoulos
AU - Shanghyeon Kim
AU - Lukas Maximilian Masopust
AU - Ivor Prado
AU - Muhammad Adil Salim
AU - Fangzhou Li
AU - George Berdovskiy
AU - Ilias Apostolakos
AU - Brandon Invergo
AU - Karen M. Kalanetra
AU - Danielle G. Lemay
AU - David A. Mills
AU - Armin Oloumi
AU - Cheng-Yu Weng
AU - Carlito B. Lebrilla
AU - Xuan He
AU - Carolyn Slupsky
AU - Oliver Fiehn
AU - Ibuki Kusumoto
AU - Ameer Y. Taha
AU - Yu Wang
AU - Daniela Barile
AU - Alexis Davis
AU - David E. Olson
AU - Justin B. Siegel
AU - Ilias Tagkopoulos
PY - 2026
DA - 2026/10/04
PB - arXiv
DO - 10.48550/arxiv.2610.04970
UR - https://arxiv.org/abs/2610.04970
AB - Despite milk being a global dietary staple, the molecular basis of its health-relevant bioactivity and the factors governing fine-scale compositional variation remain poorly understood. Here, we present an integrated seven-layer omics characterization of 60 US retail milk samples from ten geographic regions, combining genomics, transcriptomics, peptidomics, proteomics, lipidomics, metabolomics, and glycomics on the same samples. We also organized the identified and quantified compounds into the Dairy Molecule Database (DMD), a web-accessible resource for linking milk compound concentrations with SNPs, miRNAs, and product-level factors to support future milk quality optimization. In total, we identified 6,714 compounds and quantified 5,288 with absolute concentrations, including 5,220 compounds not previously available with absolute concentration estimates in existing milk compound databases. These profiles enabled bioactivity efficacy estimation and association analyses of factors linked to milk compound variation. We tested 54 computationally predicted antimicrobial candidate peptides; 35 showed activity and 6 had IC50 values below 256 μg/mL against A. baumannii, an ESKAPE pathogen. We further identified associations between downstream bioactive compound concentrations or estimated bioactivity efficacy and product-level factors, including purchase region, purchase ambient temperature, and packaging opacity, as well as SNPs, estimated Jersey breed proportion, and miRNA abundance. Overall, bioactivity efficacy profiles were associated with purchase region, selected SNPs, Jersey breed proportion, and selected miRNAs. These findings suggest that selective breeding and supply-chain optimization could help improve the bioactive quality of commercial milk.
ER -