High-throughput amplicon sequencing to assess the impact of processing factors on the development of microbial communities during spontaneous meat fermentation

During spontaneous meat fermentation, diverse microbial communities develop over time. These communities consist mainly of lactic acid bacteria (LAB) and coagulase-negative staphylococci (CNS), of which the species composition is influenced by the fermentation temperature and the level of acidification. Recent development and application of amplicon-based high-throughput sequencing (HTS) methods have allowed to gain deeper insights into the microbial communities of fermented meats. The aim of the present study was to investigate the effect of different fermentation temperatures and acidification profiles on the CNS communities during spontaneous fermentation, using a previously developed amplicon-based HTS method targeting both the 16S rRNA and tuf genes. Spontaneous fermentations were performed with five different lots of meat to assess inter-lot variability. The process influence was investigated by fermenting the meat batters for seven days at different fermentation temperatures (23 °C, 30 °C, and 37 °C) and in the absence or presence of added glucose to simulate different acidification levels. Additionally, the results were compared with a starter culture-initiated fermentation process. The data revealed that the fermentation temperature was the most influential processing condition in shaping the microbial communities during spontaneous meat fermentation processes, whereas differences in pH were only responsible for minor shifts in the microbial profiles. Furthermore, the CNS communities showed a great level of variability, which depended on the initial microbial communities present and their competitiveness. • The background microbiota and temperature were the key processing parameters during spontaneous meat fermentation • Great variability was found in the staphylococcal communities during different spontaneous fermentations • Community composition was set by by the processing parameters and adaptations of the background microbiota to the conditions