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

Author

Listed:
  • Benjamin P. Kellman

    (University of California, San Diego
    University of California, San Diego
    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
    University of California, San Diego)

  • Annalee Fürst

    (University of California, San Diego)

  • Bokan Bao

    (University of California, San Diego
    University of California, San Diego
    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
    University of California, San Diego)

  • Nathan E. Lewis

    (University of California, San Diego
    University of California, San Diego)

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.

Suggested Citation

  • 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 & A, 2022. "Elucidating Human Milk Oligosaccharide biosynthetic genes through network-based multi-omics integration," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-29867-4
    DOI: 10.1038/s41467-022-29867-4
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    References listed on IDEAS

    as
    1. Bokan Bao & Benjamin P. Kellman & Austin W. T. Chiang & Yujie Zhang & James T. Sorrentino & Austin K. York & Mahmoud A. Mohammad & Morey W. Haymond & Lars Bode & Nathan E. Lewis, 2021. "Correcting for sparsity and interdependence in glycomics by accounting for glycan biosynthesis," Nature Communications, Nature, vol. 12(1), pages 1-14, December.
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