Bhatt Vineet, Mohapatra Anwesha, Anand Swadha, Kuntal Bhusan K, Mande Sharmila S
Bio-Sciences R&D Division, TCS Research, Tata Consultancy Services Ltd., Pune, India.
Chemical Engineering and Process Development Division, CSIR-National Chemical Laboratory (NCL), Pune, India
Front Microbiol. 2018 Sep 18;9:2183. doi: 10.3389/fmicb.2018.02183. eCollection 2018.
Prediction of functional potential of bacteria can only be ascertained by the accurate annotation of its metabolic pathways. Homology based methods decipher metabolic gene content but ignore the fact that homologs of same protein can function in different pathways. Therefore, mere presence of all constituent genes in an organism is not sufficient to indicate a pathway. Contextual occurrence of genes belonging to a pathway on the bacterial genome can hence be exploited for an accurate estimation of functional potential of a bacterium. In this communication, we present a novel annotation resource to accurately identify pathway presence by using gene context. Our tool FLIM-MAP (Functionally Important Modules in bacterial Metabolic Pathways) predicts biologically relevant functional units called 'GCMs' (Gene Context based Modules) from a given metabolic reaction network. We benchmark the accuracy of our tool on amino acids and carbohydrate metabolism pathways.
细菌功能潜力的预测只能通过对其代谢途径的准确注释来确定。基于同源性的方法可以解读代谢基因的内容,但忽略了同一蛋白质的同源物可能在不同途径中发挥作用这一事实。因此,仅仅在生物体中存在所有组成基因并不足以表明存在某一途径。因此,可以利用细菌基因组上属于某一途径的基因的上下文出现情况来准确估计细菌的功能潜力。在本通讯中,我们提出了一种新颖的注释资源,通过使用基因上下文来准确识别途径的存在。我们的工具FLIM-MAP(细菌代谢途径中功能重要模块)从给定的代谢反应网络中预测称为“GCMs”(基于基因上下文的模块)的生物学相关功能单元。我们在氨基酸和碳水化合物代谢途径上对我们工具的准确性进行了基准测试。