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.

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

PERONI, DIEGO
2017-01-01

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.
2017
Drago, L.; Toscano, M.; De Grandi, R.; Grossi, E.; Padovani, E. M.; Peroni, Diego
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/835209
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