Nigiz Şeyma, Hazirolan Gülşen, Altinkanat Gelmez Gülşen, Özkul Ceren, Koçak Engin, Erdoğan Kablan Sevilay, Nemutlu Emirhan, Gündoğdu Aycan, Bayrakdar Fatma, Hasdemir Ufuk, Gür Deniz
Department of Pharmaceutical Microbiology, Faculty of Pharmacy, Hacettepe University, Ankara, Turkiye.
Department of Medical Microbiology, Faculty of Medicine, Hacettepe University, Ankara, Turkiye.
Turk J Med Sci. 2025 Jun 29;55(4):1024-1034. doi: 10.55730/1300-0144.6055. eCollection 2025.
BACKGROUND/AIM: which is a nosocomial pathogen, is naturally resistant to a wide spectrum of antibiotics, which makes the management of infections difficult. The aim of this study was to determine the susceptibilities of to ceftriaxone, ceftazidime, meropenem, amikacin, gentamicin, ciprofloxacin, and to compare the metabolic profiles of meropenem-resistant isolates under basal conditions and after exposure to sublethal concentrations of meropenem.
A total of 84 isolates were included from various samples. Genes for meropenem resistance were determined by polymerase chain reaction (PCR). Genetic similarities among isolates of were investigated by pulsed-field gel electrophoresis (PFGE). MIC changes of meropenem were investigated in the presence of the resistance-nodulation-cell division (RND) type pump inhibitor phenylalanyl-arginyl-β-naphthylamide (PAβN) and proton ionophore (uncoupler) carbonyl cyanide m-chlorophenylhydrazone (CCCP). A GC/MS-based metabolomics approach was implemented to determine the differentiation of metabolome structure. We examined the adaptive responses of isolates, characterized by resistance or susceptibility, under conditions of meropenem-induced stress.
The highest resistance rate was observed for ceftriaxone (27.6%). Amikacin was the most effective drug, with a resistance rate of 6.9%. Overall, 10 (11.9%) isolates were resistant to meropenem. Genotyping of β-lactamase genes revealed that was present in one isolate. In total, efflux pump activity was detected in four isolates. The GC/MS-based metabolomics analysis revealed alterations in nucleotide and pyrimidine metabolism, as well as in ATP-binding cassette (ABC) transporter pathways, between the meropenem-susceptible and meropenem-resistant groups.
Understanding the metabolic profiles of could facilitate the development of novel diagnostic approaches and antimicrobial strategies in the ongoing global effort to combat meropenem-resistant .
背景/目的:[病原体名称]作为一种医院病原菌,对多种抗生素天然耐药,这使得感染的管理变得困难。本研究的目的是确定[病原体名称]对头孢曲松、头孢他啶、美罗培南、阿米卡星、庆大霉素、环丙沙星的敏感性,并比较美罗培南耐药菌株在基础条件下和暴露于亚致死浓度美罗培南后的代谢谱。
从各种样本中纳入了总共84株[病原体名称]分离株。通过聚合酶链反应(PCR)确定美罗培南耐药基因。通过脉冲场凝胶电泳(PFGE)研究[病原体名称]分离株之间的遗传相似性。在存在耐药性-结瘤-细胞分裂(RND)型泵抑制剂苯丙氨酰-精氨酰-β-萘酰胺(PAβN)和质子离子载体(解偶联剂)羰基氰化物间氯苯腙(CCCP)的情况下,研究美罗培南的最低抑菌浓度(MIC)变化。采用基于气相色谱/质谱联用(GC/MS)的代谢组学方法来确定代谢组结构的差异。我们研究了在美罗培南诱导的应激条件下,以耐药或敏感为特征的分离株的适应性反应。
头孢曲松的耐药率最高(27.6%)。阿米卡星是最有效的药物,耐药率为6.9%。总体而言,10株(11.9%)分离株对美罗培南耐药。β-内酰胺酶基因分型显示,一株分离株中存在[具体β-内酰胺酶基因名称]。总共在4株分离株中检测到外排泵活性。基于GC/MS的代谢组学分析显示,美罗培南敏感组和耐药组之间在核苷酸和嘧啶代谢以及ATP结合盒(ABC)转运途径方面存在改变。
了解[病原体名称]的代谢谱有助于在全球对抗美罗培南耐药[病原体名称]的努力中开发新的诊断方法和抗菌策略。