Untargeted Metabolomic Analysis of Lactation-Stage-Matched Human and Bovine Milk Samples at 2 Weeks Postnatal

Abstract

Epidemiological data demonstrate that bovine whole milk is often substituted for human milk during the first 12 months of life and may be associated with adverse infant outcomes. The objective of this study is to interrogate the human and bovine milk metabolome at 2 weeks of life to identify unique metabolites that may impact infant health outcomes. Human milk (n = 10) was collected at 2 weeks postpartum from normal-weight mothers (pre-pregnant BMI < 25 kg/m2) that vaginally delivered term infants and were exclusively breastfeeding their infant for at least 2 months. Similarly, bovine milk (n = 10) was collected 2 weeks postpartum from normal-weight primiparous Holstein dairy cows. Untargeted data were acquired on all milk samples using high-resolution liquid chromatography–high-resolution tandem mass spectrometry (HR LC-MS/MS). MS data pre-processing from feature calling to metabolite annotation was performed using MS-DIAL and MS-FLO. Our results revealed that more than 80% of the milk metabolome is shared between human and bovine milk samples during early lactation. Unbiased analysis of identified metabolites revealed that nearly 80% of milk metabolites may contribute to microbial metabolism and microbe–host interactions. Collectively, these results highlight untargeted metabolomics as a potential strategy to identify unique and shared metabolites in bovine and human milk that may relate to and impact infant health outcomes.

An Automated Workflow Composition System for Liquid Chromatography–Mass Spectrometry Metabolomics Data Processing

“…The code for reproducing the process of automated workflow composition in this study can be found at: . We used the data collected for our previous milk metabolomics study to illustrate a traditional workflow for the following three use cases . Example data acquisition and analysis results for use cases can be found in the Supporting Information.…”

Science and Faith to Understand Milk Bioactivity for Infants

“…In recent decades, omics technologies have been applied as ‘holistic’ add-on techniques to traditional (single-factor) milk bioactivity research in the natural sciences. Genomic analyses of milk and infant cells are used to identify the breast milk miRNA regulators that affect immune maturation [ 98 ], transcriptomics to assess the expressions of milk stem cells and host gene expressions [ 110 ], proteomics and peptidomics to characterize all milk proteins and host cell protein responses [ 111 ], epigenomics to explore the (longer-term) effects of milk on host gene expressions [ 112 ], metabolomics to assess interactions with milk or host metabolites [ 113 ], and microbiomics to assess the interactions between milk and host microbes [ 114 ]—just to mention a few examples. Such techniques, and the wealth of new data they contribute, provide a broader picture of milk components and their multiple effects on the human body.…”