Civil and Environmental Engineering, South Dakota Mines, 501 E. St. Joseph Street, Rapid City, SD, 57701, USA.
2D-Materials for Biofilm Engineering, Science and Technology (2D BEST) Center, South Dakota Mines, 501 E. St. Joseph Street, Rapid City, SD, 57701, USA.
Sci Rep. 2023 Sep 27;13(1):16181. doi: 10.1038/s41598-023-43089-8.
Sulfate-reducing bacteria (SRB) are terminal members of any anaerobic food chain. For example, they critically influence the biogeochemical cycling of carbon, nitrogen, sulfur, and metals (natural environment) as well as the corrosion of civil infrastructure (built environment). The United States alone spends nearly $4 billion to address the biocorrosion challenges of SRB. It is important to analyze the genetic mechanisms of these organisms under environmental stresses. The current study uses complementary methodologies, viz., transcriptome-wide marker gene panel mapping and gene clustering analysis to decipher the stress mechanisms in four SRB. Here, the accessible RNA-sequencing data from the public domains were mined to identify the key transcriptional signatures. Crucial transcriptional candidate genes of Desulfovibrio spp. were accomplished and validated the gene cluster prediction. In addition, the unique transcriptional signatures of Oleidesulfovibrio alaskensis (OA-G20) at graphene and copper interfaces were discussed using in-house RNA-sequencing data. Furthermore, the comparative genomic analysis revealed 12,821 genes with translation, among which 10,178 genes were in homolog families and 2643 genes were in singleton families were observed among the 4 genomes studied. The current study paves a path for developing predictive deep learning tools for interpretable and mechanistic learning analysis of the SRB gene regulation.
硫酸盐还原菌（SRB）是任何厌氧食物链的末端成员。例如，它们对碳、氮、硫和金属的生物地球化学循环（自然环境）以及民用基础设施的腐蚀（建筑环境）具有重要影响。仅美国就花费近 40 亿美元来解决 SRB 的生物腐蚀挑战。分析这些生物体在环境压力下的遗传机制非常重要。本研究采用互补的方法，即转录组范围标记基因面板图谱和基因聚类分析，来破译 4 种硫酸盐还原菌的应激机制。在这里，从公共领域挖掘了可访问的 RNA-seq 数据，以鉴定关键的转录特征。完成了脱硫弧菌属的关键转录候选基因，并验证了基因簇预测。此外，使用内部 RNA-seq 数据讨论了 Oleidesulfovibrio alaskensis（OA-G20）在石墨烯和铜界面的独特转录特征。此外，比较基因组分析显示了具有翻译功能的 12821 个基因，其中 4 个研究基因组中存在 10178 个同源家族基因和 2643 个单基因家族基因。本研究为开发可解释和基于机制的 SRB 基因调控学习分析的预测性深度学习工具铺平了道路。
