Mohamed Hassan Mahmoud, Barzideh Zoha, Siddiqi Myra, LaPointe Gisèle
Dairy at Guelph, Department of Food Science, University of Guelph, Guelph, ON N1G 2W1, Canada.
Faculty of Computer and Artificial Intelligence, Benha University, Banha 13518, Egypt.
Microorganisms. 2023 Aug 10;11(8):2052. doi: 10.3390/microorganisms11082052.
Shotgun metagenomic sequencing was used to investigate the diversity of the microbial community of Cheddar cheese ripened over 32 months. The changes in taxa abundance were compared from assembly-based, non-assembly-based, and mOTUs2 sequencing pipelines to delineate the community profile for each age group. Metagenomic assembled genomes (MAGs) passing the quality threshold were obtained for 11 species from 58 samples. Although and were dominant across the shotgun samples, other species were identified using MG-RAST. NMDS analysis of the beta diversity of the microbial community revealed the similarity of the cheeses in older age groups (7 months to 32 months). As expected, the abundance of consistently decreased over ripening, while the proportion of permeable cells increased. Over the ripening period, the relative abundance of viable progressively increased, but at a variable rate among trials. Reads attributed to and remained below 1% relative abundance. The functional profiles of PMA-treated cheeses differed from those of non-PMA-treated cheeses. Starter rotation was reflected in the single nucleotide variant profiles of (SNVs of this species using mOTUs2), while the incoming milk was the leading factor in discriminating / SNV profiles. The relative abundance estimates from Kraken2, non-assembly-based (MG-RAST) and marker gene clusters (mOTUs2) were consistent across age groups for the two dominant taxa. Metagenomics enabled sequence variant analysis below the bacterial species level and functional profiling that may affect the metabolic interactions between subpopulations in cheese during ripening, which could help explain the overall flavour development of cheese. Future work will integrate microbial variants with volatile profiles to associate the development of compounds related to cheese flavour at each ripening stage.
采用鸟枪法宏基因组测序技术研究了成熟32个月的切达干酪微生物群落的多样性。比较了基于组装、非基于组装和mOTUs2测序流程的分类群丰度变化，以描绘每个年龄组的群落概况。从58个样本中获得了11个物种的宏基因组组装基因组（MAGs），这些基因组通过了质量阈值。虽然在鸟枪法样本中[具体物种1]和[具体物种2]占主导地位，但使用MG-RAST鉴定出了其他物种。对微生物群落的β多样性进行NMDS分析，结果显示老年组（7个月至32个月）的奶酪具有相似性。正如预期的那样，[具体物种3]的丰度在成熟过程中持续下降，而可渗透细胞的比例增加。在成熟期间，活的[具体物种4]的相对丰度逐渐增加，但不同试验中的增加速率不同。归因于[具体物种5]和[具体物种6]的读数相对丰度仍低于1%。经PMA处理的奶酪的功能谱与未经PMA处理的奶酪不同。起始菌株的轮换反映在[具体物种7]的单核苷酸变异谱中（使用mOTUs2对该物种的SNV），而原料奶是区分[具体物种8]/[具体物种9] SNV谱的主要因素。对于两个优势分类群，Kraken2、非基于组装（MG-RAST）和标记基因簇（mOTUs2）的相对丰度估计在各年龄组中是一致的。宏基因组学能够在细菌物种水平以下进行序列变异分析和功能谱分析这可能会影响奶酪成熟过程中不同亚群之间的代谢相互作用，这有助于解释奶酪的整体风味发展。未来的工作将把微生物变异与挥发性成分谱相结合，以关联每个成熟阶段与奶酪风味相关化合物的发展。
