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The growth and survival of an organism in a particular environment is highly depends on the certain indispensable genes, termed as essential genes. Sulfate-reducing bacteria (SRB) are obligate anaerobes which thrives on sulfate reduction for its energy requirements. The present study usedOleidesulfovibrio alaskensisG20 (OA G20) as a model SRB to categorize the essential genes based on their key metabolic pathways. Herein, we reported a feedback loop framework for gene of interest discovery, from bio-problem to gene set of interest, leveraging expert annotation with computational prediction. Defined bio-problem was applied to retrieve the genes of SRB from literature databases (PubMed, and PubMed Central) and annotated them to the genome of OA G20. Retrieved gene list was further used to enrich protein–protein interaction and was corroborated to the pangenome analysis, to categorize the enriched gene sets and the respective pathways under essential and non-essential. Interestingly, thesatgene (dde_2265) from the sulfur metabolism was the bridging gene between all the enriched pathways. Gene clusters involved in essential pathways were linked with the genes from seleno-compound metabolism, amino acid metabolism, secondary metabolite synthesis, and cofactor biosynthesis. Furthermore, pangenome analysis demonstrated the gene distribution, where 69.83% of the 116 enriched genes were mapped under “persistent,” inferring the essentiality of these genes. Likewise, 21.55% of the enriched genes, which involves specially the formate dehydrogenases and metallic hydrogenases, appeared under “shell.” Our methodology suggested that semi-automated text mining and network analysis may play a crucial role in deciphering the previously unexplored genes and key mechanisms which can help to generate a baseline prior to perform any experimental studies.
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Genome-Wide Computational Prediction and Analysis of Noncoding RNAs in Oleidesulfovibrio alaskensis G20
Noncoding RNAs (ncRNAs) play key roles in the regulation of important pathways, including cellular growth, stress management, signaling, and biofilm formation. Sulfate-reducing bacteria (SRB) contribute to huge economic losses causing microbial-induced corrosion through biofilms on metal surfaces. To effectively combat the challenges posed by SRB, it is essential to understand their molecular mechanisms of biofilm formation. This study aimed to identify ncRNAs in the genome of a model SRB, Oleidesulfovibrio alaskensis G20 (OA G20). Three in silico approaches revealed genome-wide distribution of 37 ncRNAs excluding tRNAs in the OA G20. These ncRNAs belonged to 18 different Rfam families. This study identified riboswitches, sRNAs, RNP, and SRP. The analysis revealed that these ncRNAs could play key roles in the regulation of several pathways of biosynthesis and transport involved in biofilm formation by OA G20. Three sRNAs, Pseudomonas P10, Hammerhead type II, and sX4, which were found in OA G20, are rare and their roles have not been determined in SRB. These results suggest that applying various computational methods could enrich the results and lead to the discovery of additional novel ncRNAs, which could lead to understanding the “rules of life of OA G20” during biofilm formation.
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- Award ID(s):
- 1920954
- PAR ID:
- 10537359
- Publisher / Repository:
- Microorganisms
- Date Published:
- Journal Name:
- Microorganisms
- Volume:
- 12
- Issue:
- 5
- ISSN:
- 2076-2607
- Page Range / eLocation ID:
- 960
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/microorganisms12050960
