Bécavin Christophe, Koutero Mikael, Tchitchek Nicolas, Cerutti Franck, Lechat Pierre, Maillet Nicolas, Hoede Claire, Chiapello Hélène, Gaspin Christine, Cossart Pascale
Département de Biologie Cellulaire et Infection, Institut Pasteur, Unité des Interactions Bactéries-Cellules, Paris, France; INSERM, U604, Paris, France; INRA, USC2020, Paris, France; Institut Pasteur-Bioinformatics and Biostatistics Hub, C3BI, USR 3756 IP CNRS, Paris, France.
Département de Biologie Cellulaire et Infection, Institut Pasteur, Unité des Interactions Bactéries-Cellules, Paris, France; INSERM, U604, Paris, France; INRA, USC2020, Paris, France.
mSystems. 2017 Mar 14;2(2). doi: 10.1128/mSystems.00186-16. eCollection 2017 Mar-Apr.
As for many model organisms, the amount of omics data produced has recently increased exponentially. There are now >80 published complete genomes, around 350 different transcriptomic data sets, and 25 proteomic data sets available. The analysis of these data sets through a systems biology approach and the generation of tools for biologists to browse these various data are a challenge for bioinformaticians. We have developed a web-based platform, named Listeriomics, that integrates different tools for omics data analyses, i.e., (i) an interactive genome viewer to display gene expression arrays, tiling arrays, and sequencing data sets along with proteomics and genomics data sets; (ii) an expression and protein atlas that connects every gene, small RNA, antisense RNA, or protein with the most relevant omics data; (iii) a specific tool for exploring protein conservation through the phylogenomic tree; and (iv) a coexpression network tool for the discovery of potential new regulations. Our platform integrates all the complete species genomes, transcriptomes, and proteomes published to date. This website allows navigation among all these data sets with enriched metadata in a user-friendly format and can be used as a central database for systems biology analysis. In the last decades, has become a key model organism for the study of host-pathogen interactions, noncoding RNA regulation, and bacterial adaptation to stress. To study these mechanisms, several genomics, transcriptomics, and proteomics data sets have been produced. We have developed Listeriomics, an interactive web platform to browse and correlate these heterogeneous sources of information. Our website will allow listeriologists and microbiologists to decipher key regulation mechanism by using a systems biology approach.
与许多模式生物一样,近年来产生的组学数据量呈指数级增长。目前已发表了80多个完整基因组、约350个不同的转录组数据集和25个蛋白质组数据集。通过系统生物学方法分析这些数据集并为生物学家生成浏览这些各种数据的工具,对生物信息学家来说是一项挑战。我们开发了一个名为Listeriomics的基于网络的平台,该平台集成了用于组学数据分析的不同工具,即:(i)一个交互式基因组浏览器,用于显示基因表达阵列、平铺阵列和测序数据集以及蛋白质组学和基因组学数据集;(ii)一个表达和蛋白质图谱,将每个基因、小RNA、反义RNA或蛋白质与最相关的组学数据联系起来;(iii)一个通过系统发育树探索蛋白质保守性的特定工具;以及(iv)一个用于发现潜在新调控的共表达网络工具。我们的平台整合了迄今为止发表的所有完整物种基因组、转录组和蛋白质组。该网站允许以用户友好的格式在所有这些带有丰富元数据的数据集之间进行导航,并可作为系统生物学分析的中央数据库。在过去几十年中,已成为研究宿主-病原体相互作用、非编码RNA调控和细菌应激适应的关键模式生物。为了研究这些机制,已经产生了几个基因组学、转录组学和蛋白质组学数据集。我们开发了Listeriomics,一个交互式网络平台,用于浏览和关联这些异质信息源。我们的网站将使李斯特菌学家和微生物学家能够通过使用系统生物学方法来破译关键调控机制。