Maghembe Reuben, Damian Donath, Makaranga Abdalah, Nyandoro Stephen Samwel, Lyantagaye Sylvester Leonard, Kusari Souvik, Hatti-Kaul Rajni
Department of Molecular Biology and Biotechnology, College of Natural and Applied Sciences, University of Dar es Salaam, P.O. Box 25179, Dar es Salaam, Tanzania.
Department of Biological and Marine Sciences, Marian University College, P.O. Box 47, Bagamoyo, Tanzania.
Antibiotics (Basel). 2020 May 4;9(5):229. doi: 10.3390/antibiotics9050229.
"Omics" represent a combinatorial approach to high-throughput analysis of biological entities for various purposes. It broadly encompasses genomics, transcriptomics, proteomics, lipidomics, and metabolomics. Bacteria and microalgae exhibit a wide range of genetic, biochemical and concomitantly, physiological variations owing to their exposure to biotic and abiotic dynamics in their ecosystem conditions. Consequently, optimal conditions for adequate growth and production of useful bacterial or microalgal metabolites are critically unpredictable. Traditional methods employ microbe isolation and 'blind'-culture optimization with numerous chemical analyses making the bioprospecting process laborious, strenuous, and costly. Advances in the next generation sequencing (NGS) technologies have offered a platform for the pan-genomic analysis of microbes from community and strain downstream to the gene level. Changing conditions in nature or laboratory accompany epigenetic modulation, variation in gene expression, and subsequent biochemical profiles defining an organism's inherent metabolic repertoire. Proteome and metabolome analysis could further our understanding of the molecular and biochemical attributes of the microbes under research. This review provides an overview of recent studies that have employed omics as a robust, broad-spectrum approach for screening bacteria and microalgae to exploit their potential as sources of drug leads by focusing on their genomes, secondary metabolite biosynthetic pathway genes, transcriptomes, and metabolomes. We also highlight how recent studies have combined molecular biology with analytical chemistry methods, which further underscore the need for advances in bioinformatics and chemoinformatics as vital instruments in the discovery of novel bacterial and microalgal strains as well as new drug leads.
“组学”代表了一种用于对生物实体进行高通量分析以实现各种目的的组合方法。它广泛涵盖基因组学、转录组学、蛋白质组学、脂质组学和代谢组学。由于细菌和微藻暴露于其生态系统条件下的生物和非生物动态变化,它们表现出广泛的遗传、生化以及随之而来的生理变异。因此,难以准确预测有利于细菌或微藻生长及产生有用代谢产物的最佳条件。传统方法采用微生物分离和大量化学分析进行“盲目”的培养优化,使得生物勘探过程既费力又成本高昂。下一代测序(NGS)技术的进步为从群落和菌株到基因水平的微生物泛基因组分析提供了一个平台。自然或实验室条件的变化伴随着表观遗传调控、基因表达的变化以及随后定义生物体固有代谢库的生化特征。蛋白质组和代谢组分析可以加深我们对所研究微生物的分子和生化特性的理解。本综述概述了最近的一些研究,这些研究采用组学作为一种强大的广谱方法来筛选细菌和微藻,通过关注它们的基因组、次生代谢物生物合成途径基因、转录组和代谢组来挖掘它们作为药物先导物来源的潜力。我们还强调了最近的研究如何将分子生物学与分析化学方法相结合,这进一步凸显了生物信息学和化学信息学作为发现新型细菌和微藻菌株以及新药物先导物的重要工具取得进展的必要性。