Zhu Yan, Zhao Jinxin, Maifiah Mohd Hafidz Mahamad, Velkov Tony, Schreiber Falk, Li Jian
Infection & Immunity Program, Monash Biomedicine Discovery Institute and Department of Microbiology, Monash University, Melbourne, Australia.
Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Melbourne, Australia.
mSystems. 2019 Feb 5;4(1). doi: 10.1128/mSystems.00157-18. eCollection 2019 Jan-Feb.
Multidrug-resistant (MDR) Acinetobacter baumannii has emerged as a very problematic pathogen over the past decades, with a high incidence in nosocomial infections. Discovered in the late 1940s but abandoned in the 1970s, polymyxins (i.e., polymyxin B and colistin) have been revived as the last-line therapy against Gram-negative "superbugs," including MDR A. baumannii. Worryingly, resistance to polymyxins in A. baumannii has been increasingly reported, urging the development of novel antimicrobial therapies to rescue this last-line class of antibiotics. In the present study, we integrated genome-scale metabolic modeling with multiomics data to elucidate the mechanisms of cellular responses to colistin treatment in A. baumannii. A genome-scale metabolic model, ATCC19606, was constructed for strain ATCC 19606 based on the literature and genome annotation, containing 897 genes, 1,270 reactions, and 1,180 metabolites. After extensive curation, prediction of growth on 190 carbon sources using ATCC19606 achieved an overall accuracy of 84.3% compared to Biolog experimental results. Prediction of gene essentiality reached a high accuracy of 86.1% and 82.7% compared to two transposon mutant libraries of AB5075 and ATCC 17978, respectively. Further integrative modeling with our correlative transcriptomics and metabolomics data deciphered the complex regulation on metabolic responses to colistin treatment, including (i) upregulated fluxes through gluconeogenesis, the pentose phosphate pathway, and amino acid and nucleotide biosynthesis; (ii) downregulated TCA cycle and peptidoglycan and lipopolysaccharide biogenesis; and (iii) altered fluxes over respiratory chain. Our results elucidated the interplay of multiple metabolic pathways under colistin treatment in A. baumannii and provide key mechanistic insights into optimizing polymyxin combination therapy. Combating antimicrobial resistance has been highlighted as a critical global health priority. Due to the drying drug discovery pipeline, polymyxins have been employed as the last-line therapy against Gram-negative "superbugs"; however, the detailed mechanisms of antibacterial killing remain largely unclear, hampering the improvement of polymyxin therapy. Our integrative modeling using the constructed genome-scale metabolic model ATCC19606 and the correlative multiomics data provide the fundamental understanding of the complex metabolic responses to polymyxin treatment in A. baumannii at the systems level. The model ATCC19606 may have a significant potential in antimicrobial systems pharmacology research in A. baumannii.
在过去几十年中，多重耐药鲍曼不动杆菌已成为一种极具问题的病原体，在医院感染中发病率很高。多粘菌素（即多粘菌素B和黏菌素）于20世纪40年代末被发现，但在20世纪70年代被弃用，现在已重新成为对抗革兰氏阴性“超级细菌”（包括多重耐药鲍曼不动杆菌）的一线治疗药物。令人担忧的是，越来越多的报道称鲍曼不动杆菌对多粘菌素产生了耐药性，这促使人们开发新的抗菌疗法来挽救这一类最后的抗生素。在本研究中，我们将基因组规模的代谢建模与多组学数据相结合，以阐明鲍曼不动杆菌对黏菌素治疗的细胞反应机制。基于文献和基因组注释，为菌株ATCC 19606构建了一个基因组规模的代谢模型ATCC19606，该模型包含897个基因、1270个反应和1180个代谢物。经过广泛的整理，使用ATCC19606预测190种碳源上的生长情况，与Biolog实验结果相比，总体准确率达到84.3%。与AB5075和ATCC 17978的两个转座子突变体文库相比，基因必需性预测的准确率分别达到86.1%和82.7%。进一步将我们的相关转录组学和代谢组学数据进行整合建模，解读了对黏菌素治疗代谢反应的复杂调控，包括：（i）通过糖异生、磷酸戊糖途径以及氨基酸和核苷酸生物合成的通量上调；（ii）三羧酸循环以及肽聚糖和脂多糖生物合成的通量下调；（iii）呼吸链上通量的改变。我们的结果阐明了鲍曼不动杆菌在黏菌素治疗下多种代谢途径的相互作用，并为优化多粘菌素联合治疗提供了关键的机制见解。对抗抗菌药物耐药性已被视为全球关键的卫生优先事项。由于药物研发渠道逐渐枯竭，多粘菌素已被用作对抗革兰氏阴性“超级细菌”的一线治疗药物；然而，抗菌杀灭的详细机制在很大程度上仍不清楚，这阻碍了多粘菌素治疗的改进。我们使用构建的基因组规模代谢模型ATCC19606和相关多组学数据进行的整合建模，在系统层面上提供了对鲍曼不动杆菌对多粘菌素治疗复杂代谢反应的基本理解。模型ATCC19606在鲍曼不动杆菌的抗菌系统药理学研究中可能具有巨大潜力。
