Ramaiah Arunachalam, Arumugaswami Vaithilingaraja
Centre for Infectious Disease Research, Indian Institute of Science, Bangalore, 560 012 India.
Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048 USA ; Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048 USA ; Department of Surgery, University of California at Los Angeles, Los Angeles, CA 90095 USA.
Virusdisease. 2016 Jun;27(2):136-44. doi: 10.1007/s13337-016-0305-0. Epub 2016 Feb 22.
The current outbreak of Zaire ebolavirus (EBOV) lasted longer than the previous outbreaks and there is as yet no proven treatment or vaccine available. Understanding host immune pressure and associated EBOV immune evasion that drive the evolution of EBOV is vital for diagnosis as well as designing a highly effective vaccine. The aim of this study was to deduce adaptive selection pressure acting on each amino acid sites of EBOV responsible for the recent 2014 outbreak. Multiple statistical methods employed in the study include SLAC, FEL, REL, IFEL, FUBAR and MEME. Results show that a total of 11 amino acid sites from sGP and ssGP, and 14 sites from NP, VP40, VP24 and L proteins were inferred as positively and negatively selected, respectively. Overall, the function of 11 out of 25 amino acid sites under selection pressure exactly found to be involved in T cell and B-cell epitopes. We identified that the EBOV had evolved through purifying selection pressure, which is a predictor that is known to aid the virus to adapt better to the human host and subsequently reduce the efficiency of existing immunity. Furthermore, computational RNA structure prediction showed that the three synonymous nucleotide mutations in NP gene altered the RNA secondary structure and optimal base-pairing energy, implicating a possible effect on genome replication. Here, we have provided evidence that the EBOV strains involved in the recent 2014 outbreak have evolved to minimize the detection by T and B cells by accumulating adaptive mutations to increase the survival fitness.
当前扎伊尔埃博拉病毒(EBOV)疫情的持续时间比以往疫情更长,且目前尚无经证实有效的治疗方法或疫苗。了解驱动EBOV进化的宿主免疫压力及相关的EBOV免疫逃逸机制,对于诊断以及设计高效疫苗至关重要。本研究的目的是推断作用于导致2014年近期疫情的EBOV各氨基酸位点的适应性选择压力。该研究采用的多种统计方法包括SLAC、FEL、REL、IFEL、FUBAR和MEME。结果显示,来自sGP和ssGP的总共11个氨基酸位点,以及来自NP、VP40、VP24和L蛋白的14个位点分别被推断为受到正选择和负选择。总体而言,在选择压力下的25个氨基酸位点中,有11个位点的功能被确切发现与T细胞和B细胞表位有关。我们发现EBOV是通过纯化选择压力进化而来的,这是一种已知有助于病毒更好地适应人类宿主并进而降低现有免疫效率的预测指标。此外,计算RNA结构预测表明,NP基因中的三个同义核苷酸突变改变了RNA二级结构和最佳碱基配对能量,这可能对基因组复制产生影响。在此,我们提供了证据表明,参与2014年近期疫情的EBOV毒株已经通过积累适应性突变来减少T细胞和B细胞的检测,从而提高生存适应性。