Oh Jin Wook, Shin Min Kyoung, Park Hye-Ran, Kim Sejun, Lee Byungjo, Yoo Jung Sun, Chi Won-Jae, Sung Jung-Suk
Department of Life Science, Dongguk University-Seoul, Goyang 10326, Republic of Korea.
Research Institute, National Cancer Center, Goyang 10408, Republic of Korea.
Antibiotics (Basel). 2024 Nov 21;13(12):1113. doi: 10.3390/antibiotics13121113.
The emergence and prevalence of antibiotic-resistant bacteria (ARBs) have become a serious global threat, as the morbidity and mortality associated with ARB infections are continuously rising. The activation of quorum sensing (QS) genes can promote biofilm formation, which contributes to the acquisition of drug resistance and increases virulence. Therefore, there is an urgent need to develop new antimicrobial agents to control ARB and prevent further development. Antimicrobial peptides (AMPs) are naturally occurring defense molecules in organisms known to suppress pathogens through a broad range of antimicrobial mechanisms. In this study, we utilized a previously developed deep-learning model to identify AMP candidates from the venom gland transcriptome of the spider , followed by experimental validation. PA-Win2 was among the top-scoring predicted peptides and was selected based on physiochemical features. Subsequent experimental validation demonstrated that PA-Win2 inhibits the growth of , , , , , and multidrug-resistant . (MRPA) strain CCARM 2095. The peptide exhibited strong bactericidal activity against . , and MRPA CCARM 2095 through the depolarization of bacterial cytoplasmic membranes and alteration of gene expression associated with bacterial survival. In addition, PA-Win2 effectively inhibited biofilm formation and degraded pre-formed biofilms of . . The gene expression study showed that the peptide treatment led to the downregulation of QS genes in the Las, Pqs, and Rhl systems. These findings suggest PA-Win2 as a promising drug candidate against ARB and demonstrate the potential of in silico methods in discovering functional peptides from biological data.
抗生素耐药菌(ARBs)的出现和流行已成为严重的全球威胁,因为与ARB感染相关的发病率和死亡率不断上升。群体感应(QS)基因的激活可促进生物膜形成,这有助于获得耐药性并增加毒力。因此,迫切需要开发新的抗菌剂来控制ARB并防止其进一步发展。抗菌肽(AMPs)是生物体中天然存在的防御分子,已知可通过多种抗菌机制抑制病原体。在本研究中,我们利用先前开发的深度学习模型从蜘蛛毒腺转录组中鉴定AMP候选物,随后进行实验验证。PA-Win2是预测得分最高的肽之一,并根据理化特性进行选择。随后的实验验证表明,PA-Win2可抑制金黄色葡萄球菌、表皮葡萄球菌、溶血葡萄球菌、头状葡萄球菌、人葡萄球菌和多重耐药的耐甲氧西林金黄色葡萄球菌(MRPA)菌株CCARM 2095的生长。该肽通过使细菌细胞质膜去极化以及改变与细菌存活相关的基因表达,对金黄色葡萄球菌、表皮葡萄球菌和MRPA CCARM 2095表现出强大的杀菌活性。此外,PA-Win2有效抑制金黄色葡萄球菌和表皮葡萄球菌生物膜的形成并降解预先形成的生物膜。基因表达研究表明,该肽处理导致Las、Pqs和Rhl系统中QS基因的下调。这些发现表明PA-Win2是一种有前景的抗ARB药物候选物,并证明了计算机方法从生物数据中发现功能性肽的潜力。