Chetta Massimiliano, Tarsitano Marina, Vicari Laura, Saracino Annalisa, Bukvic Nenad
U.O.C. Genetica Medica e di Laboratorio, Ospedale Antonio Cardarelli, 80131 Napoli, Italy.
Clinica di Malattie Infettive, Dipartimento di Scienze Biomediche ed Oncologia Umana, Università degli Studi "Aldo Moro" di Bari, 70124 Bari, Italy.
Pathogens. 2021 Jan 14;10(1):69. doi: 10.3390/pathogens10010069.
In silico analysis is a promising approach for understanding biological events in complex diseases. Herein we report on the innovative computational workflow allowed to highlight new direct interactions between human transcription factors (TFs) and an entire genome of virus ZikaSPH2015 strain in order to identify the occurrence of specific motifs on a genomic Zika Virus sequence that is able to bind and, therefore, sequester host's TFs. The analysis pipeline was performed using different bioinformatics tools available online (free of charge). According to obtained results of this in silico analysis, it is possible to hypothesize that these TFs binding motifs might be able to explain the complex and heterogeneous phenotype presentation in Zika-virus-affected fetuses/newborns, as well as the less severe condition in adults. Moreover, the proposed in silico protocol identified thirty-three different TFs identical to the distribution of TFBSs (Transcription Factor Binding Sites) on ZikaSPH2015 strain, potentially able to influence genes and pathways with biological functions confirming that this approach could find potential answers on disease pathogenesis.
计算机模拟分析是理解复杂疾病中生物事件的一种有前景的方法。在此，我们报告了一种创新的计算工作流程，该流程能够突出人类转录因子（TFs）与寨卡病毒SPH2015株的整个基因组之间新的直接相互作用，以便在寨卡病毒基因组序列上识别能够结合并因此隔离宿主TFs的特定基序的出现。分析流程使用了在线可用的不同生物信息学工具（免费）。根据此次计算机模拟分析获得的结果，可以推测这些TF结合基序可能能够解释寨卡病毒感染胎儿/新生儿中复杂且异质的表型表现，以及成人中较轻的病情。此外，所提出的计算机模拟方案在寨卡病毒SPH2015株上鉴定出了33种与转录因子结合位点（TFBSs）分布相同的不同TFs，它们可能能够影响具有生物学功能的基因和通路，证实了这种方法可以找到有关疾病发病机制的潜在答案。
