Marini Simone, Oliva Marco, Slizovskiy Ilya B, Noyes Noelle Robertson, Boucher Christina, Prosperi Mattia
Department of Epidemiology, University of Florida, Gainesville, FL, United States.
Emerging Pathogens Institute, University of Florida, Gainesville, FL, United States.
Front Genet. 2021 Jan 22;12:564186. doi: 10.3389/fgene.2021.564186. eCollection 2021.
Antimicrobial resistance (AMR) is a significant and growing public health threat. Sequencing of bacterial isolates is becoming more common, and therefore automatic identification of resistant bacterial strains is of pivotal importance for efficient, wide-spread AMR detection. To support this approach, several AMR databases and gene identification algorithms have been recently developed. A key problem in AMR detection, however, is the need for computational approaches detecting potential novel AMR genes or variants, which are not included in the reference databases. Toward this direction, here we study the relation between AMR and relative solvent accessibility (RSA) of protein variants from an perspective. We show how known AMR protein variants tend to correspond to exposed residues, while on the contrary their susceptible counterparts tend to be buried. Based on these findings, we develop RSA-AMR, a novel relative solvent accessibility-based AMR scoring system. This scoring system can be applied to any protein variant to estimate its propensity of altering the relative solvent accessibility, and potentially conferring (or hindering) AMR. We show how RSA-AMR score can be integrated with existing AMR detection algorithms to expand their range of applicability into detecting potential novel AMR variants, and provide a ten-fold increase in Specificity. The two main limitations of RSA-AMR score is that it is designed on single point changes, and a limited number of variants was available for model learning.
抗菌药物耐药性（AMR）是一个重大且日益严重的公共卫生威胁。细菌分离株的测序越来越普遍，因此自动识别耐药菌株对于高效、广泛的AMR检测至关重要。为了支持这种方法，最近已经开发了几个AMR数据库和基因识别算法。然而，AMR检测中的一个关键问题是需要计算方法来检测参考数据库中未包含的潜在新型AMR基因或变体。朝着这个方向，我们从一个角度研究了AMR与蛋白质变体的相对溶剂可及性（RSA）之间的关系。我们展示了已知的AMR蛋白质变体如何倾向于对应于暴露的残基，而相反，它们的敏感对应物倾向于被埋藏。基于这些发现，我们开发了RSA-AMR，一种基于相对溶剂可及性的新型AMR评分系统。该评分系统可以应用于任何蛋白质变体，以估计其改变相对溶剂可及性的倾向，并潜在地赋予（或阻碍）AMR。我们展示了如何将RSA-AMR评分与现有的AMR检测算法相结合，以扩大其适用性范围，用于检测潜在的新型AMR变体，并将特异性提高十倍。RSA-AMR评分的两个主要局限性在于它是基于单点变化设计的，并且用于模型学习的变体数量有限。
