Li Xinfu, Xiong Qiang, Zhou Hui, Xu Baocai, Sun Yun
College of Food Science and Light Industry, Nanjing Tech University, Nanjing, China.
School of Food Science and Biology Engineering, Hefei University of Technology, Hefei, China.
Front Microbiol. 2021 Sep 28;12:713513. doi: 10.3389/fmicb.2021.713513. eCollection 2021.
, , and were investigated for their roles in in the spoilage of sterilized smoked bacon. These five strains, individually and in combination, were applied as starters on sliced bacon at 4-5 log CFU/g using a hand-operated spraying bottle and stored for 45 days at 0-4°C. Dynamics, diversity, and succession of microbial community during storage of samples were studied by high-throughput sequencing (HTS) of the V3-V4 region of the 16S rRNA gene. A total of 367 bacterial genera belonging to 21 phyla were identified. Bacterial counts in all the inoculated specimens increased significantly within the first 15 days while the microbiota developed into more similar communities with increasing storage time. At the end of the storage time, the highest abundance of (96.46%) was found in samples inoculated with . Similarly, for samples inoculated with and , a sharp increase in and abundance was observed as they reached a maximum relative abundance of 97.95 and 81.6%, respectively. Hence, these species were not only the predominant ones but could also have been the more competitive ones, potentially inhibiting the growth of other microorganisms. By analyzing the bacterial load of meat products using the SSO model, the relationships between the microbial communities involved in spoilage can be understood to assist further research.
研究了[具体菌株1]、[具体菌株2]、[具体菌株3]、[具体菌株4]和[具体菌株5]在灭菌烟熏培根变质过程中的作用。使用手动喷雾瓶将这五种菌株单独或组合以4 - 5 log CFU/g的浓度接种在切片培根上，并在0 - 4°C下储存45天。通过对16S rRNA基因V3 - V4区域的高通量测序（HTS）研究样品储存期间微生物群落的动态、多样性和演替。共鉴定出属于21个门的367个细菌属。所有接种标本中的细菌数量在最初15天内显著增加，而随着储存时间的增加，微生物群发展成更相似的群落。在储存期结束时，接种[具体菌株1]的样品中[具体优势菌属1]的丰度最高（96.46%）。同样，对于接种[具体菌株2]和[具体菌株3]的样品，观察到[具体优势菌属2]和[具体优势菌属3]的丰度急剧增加，它们分别达到最大相对丰度97.95%和81.6%。因此，这些物种不仅是优势物种，而且可能是更具竞争力的物种，有可能抑制其他微生物的生长。通过使用SSO模型分析肉类产品的细菌负荷，可以了解参与变质的微生物群落之间的关系，以协助进一步的研究。
