“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.

BackgroundEven though the genomics technologies have grown to a large extent, Sub Saharan Africa countries have not entirely reaped the benefits due to the lack of enough capacity to use these technologies. The lack of documentation on existing bioinformatics capacity in these countries hinders the guidance on leveraging the resources and in the identification of areas for improvement. The main objective of this study was to map out the interest and capacity for conducting bioinformatics and related research in Tanzania. Our findings identify critical areas for skills and infrastructure development for bioinformatics research. The study is a cross-sectional, explorative, descriptive study, among Tanzanian researchers in public and private academic and research institutionsResultsOut of 84 respondents, 50 (59.5%) were males. More than half of these 44 (52.4%) were in the age between 26-32 years. The majority 41 (48.8%) were master's degree holders with at least one publication related to bioinformatics. Eighty (95.2%) were willing to join the bioinformatics network and initiative in Tanzania. The major challenge faced by 22 (26.2%) of respondents was the lack of training and skills. The most used resources for bioinformatics analyses were the BLAST, PubMed and GenBank. Most performed analyses include sequence alignment and phylogenetic, which was reported by 57 (67.9%) and 42 (50%) of respondents, respectively. The most frequently used statistical software packages were SPSS and R. A quarter of the respondents were conversant with computer programming.ConclusionEarly career and young scientists were the largest group of responders engaged in bioinformatics research and activities across surveyed institutions in Tanzania. The use of bioinformatics tools for analysis is still low, including basic analysis tools such as BLAST, GenBank, sequence alignment software, Swiss-prot and TrEMBL. There is also poor access to resources and tools for bioinformatics analyses. As a way to address the skills and resources gaps, we recommend various modes of training and capacity building of relevant bioinformatics skills and provision of infrastructure so as to improve bioinformatics capacity in Tanzania.