4.7 Article

Emerging frontiers in human milk microbiome research and suggested primers for 16S rRNA gene analysis

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ELSEVIER
DOI: 10.1016/j.csbj.2020.11.057

Keywords

Microbiome; Microbiota; 16S rRNA gene; Human Milk; Microbial barcoding; PCR primers

Funding

  1. McGill University
  2. Comtie Mexiquense de Ciencia y Tecnologia (COMECYT) of Mexico
  3. NSERC [RGPIN-2016-04961]

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Human milk is recognized as the ideal food for infants, providing unique nutritional and immune properties, as well as serving as an important source of bacteria for infants. Research into the human milk microbiome indicates that there is still much to learn about its origins, composition, and functions. Factors such as maternal influences, diet, lifestyle, and location are believed to impact the diversity and composition of the milk microbiome, with advancements in research methods shaping our understanding of this complex ecosystem.
Human milk is the ideal food for infants due to its unique nutritional and immune properties, and more recently human milk has also been recognized as an important source of bacteria for infants. However, a substantial amount of fundamental human milk microbiome information remains unclear, such as the origin, composition and function of the community and its members. There is emerging evidence to suggest that the diversity and composition of the milk microbiome might differ between lactation stages, due to maternal factors and diet, agrarian and urban lifestyles, and geographical location. The evolution of the methods used for studying milk microbiota, transitioning from culture dependent-approaches to include culture-independent approaches, has had an impact on findings and, in particular, primer selection within 16S rRNA gene barcoding studies have led to discrepancies in observed microbiota communities. Here, the current state-of-the-art is reviewed and emerging frontiers essential to improving our understanding of the human milk microbiome are considered. (C) 2020 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.

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