Ahmed Shwan, Shams Sahand, Trivedi Dakshat, Lima Cassio, McGalliard Rachel, Parry Christopher M, Carrol Enitan D, Muhamadali Howbeer, Goodacre Royston
Centre for Metabolomics Research, Department of Biochemistry, Cell and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, United Kingdom.
Department of Environment and Quality Control, Kurdistan Institution for Strategic Studies and Scientific Research, Sulaymaniyah, Kurdistan Region, Iraq.
Metabolomics. 2024 Dec 15;21(1):8. doi: 10.1007/s11306-024-02206-y.
Rapid detection and identification of pathogens and antimicrobial susceptibility is essential for guiding appropriate antimicrobial therapy and reducing morbidity and mortality associated with sepsis.
The metabolic response of clinical isolates of Klebsiella oxytoca exposed to different concentrations of ciprofloxacin (the second generation of quinolones antibiotics) were studied in order to investigate underlying mechanisms associated with antimicrobial resistance (AMR).
Metabolomics investigations were performed using Fourier-transform infrared (FT-IR) spectroscopy as a metabolic fingerprinting approach combined with gas chromatography-mass spectrometry (GC-MS) for metabolic profiling.
Our findings demonstrated that metabolic fingerprints provided by FT-IR analysis allowed for the differentiation of susceptible and resistant isolates. GC-MS analysis validated these findings, while also providing a deeper understanding of the metabolic alterations caused by exposure to ciprofloxacin. GC-MS metabolic profiling detected 176 metabolic features in the cellular extracts cultivated on BHI broth, and of these, 137 could be identified to Metabolomics Standards Initiative Level 2. Data analysis showed that 40 metabolites (30 Level 2 and 10 unknown) were differentiated between susceptible and resistant isolates. The identified metabolites belonging to central carbon metabolism; arginine and proline metabolism; alanine, aspartate and glutamate metabolism; and pyruvate metabolism. Univariate receiver operating characteristic (ROC) curve analyses revealed that six of these metabolites (glycerol-3-phosphate, O-phosphoethanolamine, asparagine dehydrate, maleimide, tyrosine, and alanine) have a crucial role in distinguishing susceptible from resistant isolates (AUC > 0.84) and contributing to antimicrobial resistance in K. oxtytoca.
Our study provides invaluable new insights into the mechanisms underlying development of antimicrobial resistance in K. oxytoca suggests potential therapeutic targets for prevention and identification of AMR in K. oxytoca infections.
病原体的快速检测与鉴定以及抗菌药物敏感性对于指导恰当的抗菌治疗并降低脓毒症相关的发病率和死亡率至关重要。
研究产酸克雷伯菌临床分离株在暴露于不同浓度环丙沙星(第二代喹诺酮类抗生素)时的代谢反应,以探究与抗菌药物耐药性(AMR)相关的潜在机制。
采用傅里叶变换红外(FT-IR)光谱作为代谢指纹图谱方法,并结合气相色谱-质谱联用(GC-MS)进行代谢谱分析,开展代谢组学研究。
我们的研究结果表明,FT-IR分析提供的代谢指纹图谱能够区分敏感和耐药分离株。GC-MS分析验证了这些结果,同时还能更深入地了解环丙沙星暴露引起的代谢变化。GC-MS代谢谱分析在脑心浸液肉汤中培养的细胞提取物中检测到176个代谢特征,其中137个可鉴定到代谢组学标准倡议第2级。数据分析表明,敏感和耐药分离株之间有40种代谢物(30种第2级和10种未知代谢物)存在差异。鉴定出的代谢物属于中心碳代谢、精氨酸和脯氨酸代谢、丙氨酸、天冬氨酸和谷氨酸代谢以及丙酮酸代谢。单变量受试者工作特征(ROC)曲线分析显示,其中6种代谢物(3-磷酸甘油、O-磷酸乙醇胺、天冬酰胺脱水物、马来酰亚胺、酪氨酸和丙氨酸)在区分敏感和耐药分离株方面起关键作用(曲线下面积>0.84),并促成产酸克雷伯菌的抗菌药物耐药性。
我们的研究为产酸克雷伯菌抗菌药物耐药性发展的潜在机制提供了宝贵的新见解,提示了预防和鉴定产酸克雷伯菌感染中AMR的潜在治疗靶点。