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Published on: September 10, 2016
Distribution characteristics and seasonal variation of microbial communities in powdered infant formula processing
Lihan Wang1, Jingqi Cheng1, Runze Li1
1Key Lab of Dairy Science, Ministry of Education, College of Food Science, Northeast Agricultural University, Harbin 150030, China.
Abstract:
The powdered infant formula (PIF) processing environment, as an industrial production site, provides a habitat conducive to microbial aggregation and colonization. However, the distribution and dynamics of microbial communities within this environment remain inadequately characterized. In this study, microbial community analysis was conducted using high-throughput sequencing on samples collected from the full production chain of 8 PIF factories. The sampling encompassed various types (raw milk, staff, air, equipment, wall and ground, and others) during two different seasons (summer and winter). The microbial diversity, composition, and dominant species varied across different groups. Potential source tracking analysis revealed close interactions between staff, air, and surface samples, indicating a potential risk of microbial transfer between staff and the processing environment. The β-nearest taxon index based null model showed that stochastic processes predominantly governed microbial community assembly across all groups. Positive interspecies interactions within the network structure, observed across different seasons and sample types, played a vital role in stabilizing and assembling microbial communities. Notably, the microbiota association networks of summer were more complex but demonstrated higher susceptibility to external disturbances. Conversely, the network structure of surface samples was more robust than that of other types of samples. These findings have improved our understanding of the microbial community distribution patterns in PIF processing environments, facilitating the prospective prediction and assessment of potential microbial sources and contamination risks in the processing chain, which in turn guides the implementation of refined control measures.
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