Suppr超能文献

PhREEPred:噬菌体抗性出现预测网络工具,用于预测封装细菌逃避噬菌体鸡尾酒治疗。

PhREEPred: Phage Resistance Emergence Prediction Web Tool to Foresee Encapsulated Bacterial Escape from Phage Cocktail Treatment.

机构信息

Malopolska Centre of Biotechnology, Jagiellonian University, Gronostajowa 7A, 30-387 Krakow, Poland.

Department of Pathogen Biology and Immunology, University of Wroclaw, Przybyszewskiego 63/77, 51-148 Wroclaw, Poland.

出版信息

J Mol Biol. 2022 Jul 30;434(14):167670. doi: 10.1016/j.jmb.2022.167670. Epub 2022 Jun 6.

Abstract

Phages, as well as phage-derived proteins, especially lysins and depolymerases, are intensively studied to become prospective alternatives or supportive antibacterials used alone or in combination. In the common phage therapy approach, the unwanted emergence of phage-resistant variants from the treated bacterial population can be postponed or reduced by the utilization of an effective phage cocktail. In this work, we present a publicly available web tool PhREEPred (Phage Resistance Emergence Prediction) (https://phartner.shinyapps.io/PhREEPred/), which will allow an informed choice of the composition of phage cocktails by predicting the outcome of phage cocktail or phage/depolymerase combination treatments against encapsulated bacterial pathogens given a mutating population that escapes single phage treatment. PhREEPred simulates solutions of our mathematical model calibrated and tested on the experimental Klebsiella pneumoniae setup and Klebsiella-specific lytic phages: K63 type-specific phage KP34 equipped with a capsule-degrading enzyme (KP34p57), capsule-independent myoviruses KP15 and KP27, and recombinant capsule depolymerase KP34p57. The model can calculate the phage-resistance emergence depending on the bacterial growth rate and initial density, the multiplicity of infection, phage latent period, its infectiveness and the cocktail composition, as well as initial depolymerase concentration and activity rate. This model reproduced the experimental results and showed that (i) the phage cocktail of parallelly infecting phages is less effective than the one composed of sequentially infecting phages; (ii) depolymerase can delay or prevent bacterial resistance by unveiling an alternative receptor for initially inactive phages. In our opinion, this customer-friendly web tool will allow for the primary design of the phage cocktail and phage-depolymerase combination effectiveness against encapsulated pathogens.

摘要

噬菌体及其衍生蛋白,特别是溶菌酶和解聚酶,正在被深入研究,以期成为有前途的替代品或辅助抗菌药物,单独或联合使用。在常用的噬菌体治疗方法中,通过使用有效的噬菌体鸡尾酒,可以推迟或减少治疗细菌种群中噬菌体耐药变体的不必要出现。在这项工作中,我们提出了一个公共可用的网络工具 PhREEPred(噬菌体耐药性出现预测)(https://phartner.shinyapps.io/PhREEPred/),该工具可以通过预测噬菌体鸡尾酒或噬菌体/解聚酶组合治疗针对被包裹的细菌病原体的结果,来帮助做出明智的选择噬菌体鸡尾酒的组成,前提是给定一个逃避单一噬菌体治疗的突变种群。PhREEPred 模拟了我们的数学模型的解决方案,该模型经过校准并在实验性肺炎克雷伯氏菌设置和特定于肺炎克雷伯氏菌的溶菌噬菌体上进行了测试:配备胶囊降解酶(KP34p57)的 K63 型特异性噬菌体 KP34、胶囊非依赖性肌病毒 KP15 和 KP27 以及重组胶囊解聚酶 KP34p57。该模型可以根据细菌的增长率和初始密度、感染复数、噬菌体潜伏期、感染力和鸡尾酒组成,以及初始解聚酶浓度和活性率来计算噬菌体耐药性的出现。该模型再现了实验结果,并表明:(i)平行感染噬菌体的噬菌体鸡尾酒不如由顺序感染噬菌体组成的鸡尾酒有效;(ii)解聚酶可以通过揭示最初不活跃噬菌体的替代受体来延迟或防止细菌耐药性。在我们看来,这个用户友好的网络工具将允许对包裹病原体的噬菌体鸡尾酒和噬菌体-解聚酶组合的有效性进行初步设计。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验