AUTHOR=Moossavi Shirin , Atakora Faisal , Miliku Kozeta , Sepehri Shadi , Robertson Bianca , Duan Qing Ling , Becker Allan B. , Mandhane Piushkumar J. , Turvey Stuart E. , Moraes Theo J. , Lefebvre Diana L. , Sears Malcolm R. , Subbarao Padmaja , Field Catherine J. , Bode Lars , Khafipour Ehsan , Azad Meghan B.
TITLE=Integrated Analysis of Human Milk Microbiota With Oligosaccharides and Fatty Acids in the CHILD Cohort
JOURNAL=Frontiers in Nutrition
VOLUME=6
YEAR=2019
URL=https://www.frontiersin.org/journals/nutrition/articles/10.3389/fnut.2019.00058
DOI=10.3389/fnut.2019.00058
ISSN=2296-861X
ABSTRACT=Background: Human milk contains many bioactive components that are typically studied in isolation, including bacteria. We performed an integrated analysis of human milk oligosaccharides and fatty acids to explore their associations with milk microbiota.
Methods: We studied a sub-sample of 393 mothers in the CHILD birth cohort. Milk was collected at 3–4 months postpartum. Microbiota was analyzed by 16S rRNA gene V4 sequencing. Oligosaccharides and fatty acids were analyzed by rapid high-throughput high performance and gas liquid chromatography, respectively. Dimension reduction was performed with principal component analysis for oligosaccharides and fatty acids. Center log-ratio transformation was applied to all three components. Associations between components were assessed using Spearman rank correlation, network visualization, multivariable linear regression, redundancy analysis, and structural equation modeling. P-values were adjusted for multiple comparisons. Key covariates were considered, including fucosyltransferase-2 (FUT2) secretor status of mother and infant, method of feeding (direct breastfeeding or pumped breast milk), and maternal fish oil supplement use.
Results: Overall, correlations were strongest between milk components of the same type. For example, FUT2-dependent HMOs were positively correlated with each other, and Staphylococcus was negatively correlated with other core taxa. Some associations were also observed between components of different types. Using redundancy analysis and structural equation modeling, the overall milk fatty acid profile was significantly associated with milk microbiota composition. In addition, some individual fatty acids [22:6n3 (docosahexaenoic acid), 22:5n3, 20:5n3, 17:0, 18:0] and oligosaccharides (fucosyl-lacto-N-hexaose, lacto-N-hexaose, lacto-N-fucopentaose I) were associated with microbiota α diversity, while others (C18:0, 3′-sialyllactose, disialyl-lacto-N-tetraose) were associated with overall microbiota composition. Only a few significant associations between individual HMOs and microbiota were observed; notably, among mothers using breast pumps, Bifidobacterium prevalence was associated with lower abundances of disialyl-lacto-N-hexaose. Additionally, among non-secretor mothers, Staphylococcus was positively correlated with sialylated HMOs.
Conclusion: Using multiple approaches to integrate and analyse milk microbiota, oligosaccharides, and fatty acids, we observed several associations between different milk components and microbiota, some of which were modified by secretor status and/or breastfeeding practices. Additional research is needed to further validate and mechanistically characterize these associations and determine their relevance to infant gut and respiratory microbiota development and health.