Dibbisa Duguma, Daba Tadesse, Mohammed Seid
Department of Applied Biology, School of Applied Natural Science, Adama Science and Technology University, Adama, Ethiopia.
School of Biological Sciences and Biotechnology, CNCS, Haramaya University, Dire Dawa, Ethiopia.
Bioinform Biol Insights. 2024 Nov 24;18:11779322241299905. doi: 10.1177/11779322241299905. eCollection 2024.
Environmental pollution has become a worldwide concern that requires rigorous efforts from all sectors of society to monitor, control, and remediate it. In environmental pollution control, CR3 has become a model organism to study resistance to heavy metals as a means of bacterial bioremediation. This research aimed to single out regulatory element analysis and conduct a comparative genome study of the heavy metal resistance genes in the complete genome of CR3 using bioinformatics and omics tools. Comparative genome analysis, promoter prediction, common motif identification, transcriptional start site identification, gene annotation, and transcription factor identification search are the major steps to understanding gene expression and regulation. MEME Suit, TOMTOM, Prokka, Rapid Annotation utilizing Subsystem Technology (RAST), Orthologous Average Nucleotide Identity Software Tool (OAT), and EziBio databases or programs were the major tools used in this study. Fourteen transcriptional factors were identified and predicted from the most credible and lowest candidate motifs with an e-value of 3.0e-009, which was statistically the utmost remarkable candidate motif. A detailed evaluation was further performed, and 14 transcriptional factors were identified as in activation, repression, and dual functions. The data revealed that most transcriptional factors identified were used for activation rather than repression. The CR3 genome contains many genes responsible for resisting heavy metals such as mercury, cadmium, zinc, copper, and arsenate. As a result, regulatory elements will lay a solid basis for understanding genes responsible for heavy metal bioremediation. It was concluded that further studies with wet lab support could be conducted for confirmation. Moreover, other advanced bioinformatics and omics technologies are needed to strengthen the results.
环境污染已成为一个全球关注的问题，需要社会各界做出严格努力来监测、控制和治理。在环境污染控制中，CR3已成为一种模式生物，用于研究细菌生物修复中对重金属的抗性。本研究旨在通过生物信息学和组学工具，筛选出调控元件分析，并对CR3全基因组中的重金属抗性基因进行比较基因组研究。比较基因组分析、启动子预测、共有基序识别、转录起始位点识别、基因注释和转录因子识别搜索是理解基因表达和调控的主要步骤。MEME Suit、TOMTOM、Prokka、利用子系统技术的快速注释（RAST）、直系同源平均核苷酸同一性软件工具（OAT）以及EziBio数据库或程序是本研究中使用的主要工具。从最可靠且最低的候选基序中识别并预测出14个转录因子，其e值为3.0e - 009，这在统计学上是最显著的候选基序。进一步进行了详细评估，确定了14个具有激活、抑制和双重功能的转录因子。数据显示，所识别的大多数转录因子用于激活而非抑制。CR3基因组包含许多负责抵抗汞、镉、锌、铜和砷酸盐等重金属的基因。因此，调控元件将为理解负责重金属生物修复的基因奠定坚实基础。得出的结论是，可以在湿实验室支持下进行进一步研究以进行确认。此外，还需要其他先进的生物信息学和组学技术来强化研究结果。
