Functional modules in prokaryotic genomes

基因组和元基因组学项目继续向数据库注入其产物具有未知功能的基因。计算方法对于提供有关这类基因产品功能的线索至关重要，因为基因数据库的增长速度远远快于那些实验功能表征的数据库。这项研究计划的主要目的是(A)检测功能模块，即其产物共同工作的基因组，以及(B)有助于了解它们的进化。为了做到这一点，我将开发和改进计算方法来预测基因产品的功能关系。检测到的功能相互作用的基团和网络应该补充目前已知的模块，并揭示新的模块。原核生物(细菌和古生菌)中功能模块的例子包括：操纵子，一起转录的基因的延伸；调节子，其表达由相同的调节蛋白协调的基因；刺激子，对特定信号或刺激作出反应的基因；以及致病岛，其产物提供致病特性的基因组。由于每个基因组中功能模块的特定成员各不相同，另一个目标是确定每个模块中的主要角色或核心基因，以及可能负责特定适应的外围角色。另一个结果是，这些模块及其基因将被分类，从功能上最可靠的，在整个进化过程中保持某种功能的，到非常可塑性的，功能差异很大的那些。这项工作将利用来自各种微生物基因组项目、来自元基因组学(环境和社区基因组学)以及通过分子生物学历史积累的知识的丰富信息来源。

Genome and metagenomics projects continue to flood databases with genes whose products have unknown functions. Computational methods are essential to provide clues about the functions of such gene products because the genetic databases grow at a much faster rate than those of experimental functional characterizations. The main aims of this research program are (a) to detect functional modules, groups of genes whose products work together, and (b) to contribute to the understanding of their evolution. To do so, I will develop and refine computational methods to predict functional relationships of gene products. Detected groups and networks of functional interactions should complement currently known modules as well as reveal new ones. Examples of functional modules in Prokaryotes (Bacteria and Archaea) include: operons, stretches of genes transcribed together; regulons, genes whose expression is coordinated by the same regulatory protein; stimulons, genes responding to a particular signal or stimulus; and pathogenicity islands, groups of genes whose products confer pathogenic characteristics. Because the specific members of a functional module within each genome vary, another aim is to identify the main players or core genes within each module, and the peripheral players, which might be responsible for particular adaptations. Another result will be the classification of the modules, and their genes, into groups ranging from most functionally committed, those that keep a function throughout evolution, to very plastic, those whose functions widely diverge. This work will exploit the rich source of information coming from the various microbial genome projects, from metagenomics (environmental and community genomics), as well as from knowledge accumulated through the history of molecular biology.