Elucidating Human Milk Oligosaccharide biosynthetic genes through network-based multi-omics integration

Benjamin P. Kellman, Anne Richelle, Jeong-Yeh Yang, Digantkumar Chapla, Austin W. T. Chiang, Julia A. Najera, Chenguang Liang, Annalee Fürst, Bokan Bao, Natalia Koga, Mahmoud A. Mohammad, Anders Bech Bruntse, Morey W. Haymond, Kelley W. Moremen, Lars Bode and Nathan E. Lewis ()
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Benjamin P. Kellman: University of California, San Diego
Anne Richelle: University of California, San Diego
Jeong-Yeh Yang: University of Georgia
Digantkumar Chapla: University of Georgia
Austin W. T. Chiang: University of California, San Diego
Julia A. Najera: University of California, San Diego
Chenguang Liang: University of California, San Diego
Annalee Fürst: University of California, San Diego
Bokan Bao: University of California, San Diego
Natalia Koga: University of California, San Diego
Mahmoud A. Mohammad: Children’s Nutrition Research Center, US Department of Agriculture/Agricultural Research Service, Baylor College of Medicine
Anders Bech Bruntse: University of California, San Diego
Morey W. Haymond: Children’s Nutrition Research Center, US Department of Agriculture/Agricultural Research Service, Baylor College of Medicine
Kelley W. Moremen: University of Georgia
Lars Bode: University of California, San Diego
Nathan E. Lewis: University of California, San Diego

Nature Communications, 2022, vol. 13, issue 1, 1-15

Abstract: Abstract Human Milk Oligosaccharides (HMOs) are abundant carbohydrates fundamental to infant health and development. Although these oligosaccharides were discovered more than half a century ago, their biosynthesis in the mammary gland remains largely uncharacterized. Here, we use a systems biology framework that integrates glycan and RNA expression data to construct an HMO biosynthetic network and predict glycosyltransferases involved. To accomplish this, we construct models describing the most likely pathways for the synthesis of the oligosaccharides accounting for >95% of the HMO content in human milk. Through our models, we propose candidate genes for elongation, branching, fucosylation, and sialylation of HMOs. Our model aggregation approach recovers 2 of 2 previously known gene-enzyme relations and 2 of 3 empirically confirmed gene-enzyme relations. The top genes we propose for the remaining 5 linkage reactions are consistent with previously published literature. These results provide the molecular basis of HMO biosynthesis necessary to guide progress in HMO research and application with the goal of understanding and improving infant health and development.

Date: 2022
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DOI: 10.1038/s41467-022-29867-4

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