Programa de Genómica Computacional, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, México.
Department of Biomedical Engineering, Boston University, Boston, Mass, USA.
Bioinformatics. 2019 Mar 1;35(5):856-864. doi: 10.1093/bioinformatics/bty689.
A major component in increasing our understanding of the biology of an organism is the mapping of its genotypic potential into its phenotypic expression profiles. This mapping is executed by the machinery of gene regulation, which is essentially studied by changes in growth conditions. Although many efforts have been made to systematize the annotation of experimental conditions in microbiology, the available annotations are not based on a consistent and controlled vocabulary, making difficult the identification of biologically meaningful comparisons of knowledge derived from different experiments or laboratories.
We curated terms related to experimental conditions that affect gene expression in Escherichia coli K-12. Since this is the best-studied microorganism, the collected terms are the seed for the Microbial Conditions Ontology (MCO), a controlled and structured vocabulary that can be expanded to annotate microbial conditions in general. Moreover, we developed an annotation framework to describe experimental conditions, providing the foundation to identify regulatory networks that operate under particular conditions.
As far as we know, MCO is the first ontology for growth conditions of any bacterial organism, and it is available at http://regulondb.ccg.unam.mx and https://github.com/microbial-conditions-ontology. Furthermore, we will disseminate MCO throughout the Open Biological and Biomedical Ontology (OBO) Foundry in order to set a standard for the annotation of gene expression data. This will enable comparison of data from diverse data sources.
Supplementary data are available at Bioinformatics online.
增加我们对生物生物学理解的一个主要组成部分是将其基因型潜力映射到其表型表达谱中。这种映射是由基因调控机制执行的，而基因调控机制主要是通过改变生长条件来研究的。尽管已经做出了许多努力来系统化微生物学中实验条件的注释，但现有的注释不是基于一致和受控的词汇，使得难以识别来自不同实验或实验室的知识的生物学有意义的比较。
我们整理了与影响大肠杆菌 K-12 基因表达的实验条件相关的术语。由于这是研究得最好的微生物，因此收集的术语是微生物条件本体（MCO）的种子，这是一个受控和结构化的词汇，可以扩展到一般微生物条件的注释。此外，我们开发了一种描述实验条件的注释框架，为识别在特定条件下运行的调控网络提供了基础。
据我们所知，MCO 是任何细菌生物生长条件的第一个本体，可在 http://regulondb.ccg.unam.mx 和 https://github.com/microbial-conditions-ontology 上获得。此外，我们将在开放生物和生物医学本体（OBO）铸造厂中传播 MCO，以便为基因表达数据的注释设定标准。这将能够比较来自不同数据源的数据。
补充数据可在生物信息学在线获得。
