Orsi Renato H, Bergholz Teresa M, Wiedmann Martin, Boor Kathryn J
Department of Food Science, Cornell University, Ithaca, NY 14853, USA
Department of Food Science, Cornell University, Ithaca, NY 14853, USA.
Database (Oxford). 2015 Mar 28;2015. doi: 10.1093/database/bav027. Print 2015.
Listeria monocytogenes is a food-borne pathogen of humans and other animals. The striking ability to survive several stresses usually used for food preservation makes L. monocytogenes one of the biggest concerns to the food industry, while the high mortality of listeriosis in specific groups of humans makes it a great concern for public health. Previous studies have shown that a regulatory network involving alternative sigma (σ) factors and transcription factors is pivotal to stress survival. However, few studies have evaluated at the metabolic networks controlled by these regulatory mechanisms. The L. monocytogenes BioCyc database uses the strain 10403S as a model. Computer-generated initial annotation for all genes also allowed for identification, annotation and display of predicted reactions and pathways carried out by a single cell. Further ongoing manual curation based on published data as well as database mining for selected genes allowed the more refined annotation of functions, which, in turn, allowed for annotation of new pathways and fine-tuning of previously defined pathways to more L. monocytogenes-specific pathways. Using RNA-Seq data, several transcription start sites and promoter regions were mapped to the 10403S genome and annotated within the database. Additionally, the identification of promoter regions and a comprehensive review of available literature allowed the annotation of several regulatory interactions involving σ factors and transcription factors. The L. monocytogenes 10403S BioCyc database is a new resource for researchers studying Listeria and related organisms. It allows users to (i) have a comprehensive view of all reactions and pathways predicted to take place within the cell in the cellular overview, as well as to (ii) upload their own data, such as differential expression data, to visualize the data in the scope of predicted pathways and regulatory networks and to carry on enrichment analyses using several different annotations available within the database.
单核细胞增生李斯特菌是一种可通过食物传播给人类和其他动物的病原体。它具有在通常用于食品保鲜的多种应激条件下存活的显著能力，这使得单核细胞增生李斯特菌成为食品行业最担忧的问题之一，而特定人群中李斯特菌病的高死亡率也使其成为公共卫生领域的重大关注点。先前的研究表明，一个涉及替代σ因子和转录因子的调控网络对于应激生存至关重要。然而，很少有研究评估这些调控机制所控制的代谢网络。单核细胞增生李斯特菌BioCyc数据库以10403S菌株作为模型。对所有基因进行计算机生成的初始注释，也能够识别、注释和展示单个细胞所进行的预测反应和途径。基于已发表的数据进行进一步的人工整理以及对选定基因进行数据库挖掘，使得功能注释更加精确，进而能够注释新的途径，并将先前定义的途径微调为更具单核细胞增生李斯特菌特异性的途径。利用RNA测序数据，将几个转录起始位点和启动子区域定位到10403S基因组，并在数据库中进行注释。此外，启动子区域的识别以及对现有文献的全面综述，使得能够注释涉及σ因子和转录因子的几种调控相互作用。单核细胞增生李斯特菌10403S BioCyc数据库是研究李斯特菌及相关生物体的研究人员的新资源。它使用户能够：（i）在细胞概述中全面了解预测在细胞内发生的所有反应和途径，以及（ii）上传自己的数据，如差异表达数据，以便在预测途径和调控网络的范围内可视化数据，并使用数据库中可用的几种不同注释进行富集分析。
