Microbiota network and mathematic microbe mutualism in colostrum and mature milk collected in two different geographic areas: Italy versus Burundi

Abstract

Human milk is essential for the initial development of newborns, as it provides all nutrients and vitamins, such as vitamin D, and represents a great source of commensal bacteria. Here we explore the microbiota network of colostrum and mature milk of Italian and Burundian mothers using the auto contractive map (AutoCM), a new methodology based on artificial neural network (ANN) architecture. We were able to demonstrate the microbiota of human milk to be a dynamic, and complex, ecosystem with different bacterial networks among different populations containing diverse microbial hubs and central nodes, which change during the transition from colostrum to mature milk. Furthermore, a greater abundance of anaerobic intestinal bacteria in mature milk compared with colostrum samples has been observed. The association of complex mathematic systems such as ANN and AutoCM adopted to metagenomics analysis represents an innovative approach to investigate in detail specific bacterial interactions in biological samples.

Mycobiome Profiles in Breast Milk from Healthy Women Depend on Mode of Delivery, Geographic Location, and Interaction with Bacteria

“…In a recent work, bacterial interactions in the colostrum and mature milk of Italian and Burundian mothers were analyzed and showed different bacterial networks among the two populations. The identified networks were complex and dynamic, changing from colostrum to mature milk (60). In the present study, we have analyzed cooccurrence relationships between bacteria and fungi in breast milk, observing a complex network of interactions between fungi and bacteria and within the same domain.…”

Examining the relationship between maternal body size, gestational glucose tolerance status, mode of delivery and ethnicity on mother’s milk microbiota at three months post-partum

“…Ethnicity and geographic location typically come with an overlay of dietary variation, making the impact of each variable challenging to separate. Only a few studies to date have assessed associations between ethnicity and the milk microbiota; however, the ethnic/geographic groups differed from our study as they generally examined Europe, Africa and the United States, making it challenging to compare findings (Tables 3, 5; Supplementary Tables 5, 6) (12,21,36,37).…”

Artificial neural network analysis of bone quality DXA parameters response to teriparatide in fractured osteoporotic patients

“…This method of data mining is a new analytical process able to create a semantic connectivity map in which non-linear associations are preserved, connections schemes are explicated and the complex dynamics of adaptive interactions is captured. The AutoCM approach has been applied in recent years to the analysis of a growing number of different clinical diseases, demonstrating its value in identifying significant associations between clinical, serological and novel "omics" biomarkers [21,[36][37][38]. Therefore, ANNs could be a useful way to better understand the relationships between the numerous different variables that play a role in osteoporosis.…”