Investigation of the effects of ampicillin and ceftazidime antibiotics on Proteus mirabilis using metabolomics approaches and bioinformatics analyses

Antibiotic resistance is a generally natural process in which microorganisms develop resistance to antibiotics. This resistance can cause antibiotics to become ineffective or less effective against microorganisms, making infections more difficult to treat and leading to more serious complications. To combat antibiotic resistance, comprehensive analysis of changes in the metabolic activities of microorganisms can be helpful in understanding antibiotic resistance. Proteus mirabilis (P. mirabilis) is a critical pathogen that is a common cause of urinary tract infections, such as urinary tract infections (UTI), especially in women. An antibiotic-based approach is often used to treat P. mirabilis infections. However, when resistant strains are encountered, treatment options may become limited. Antibiotic resistance of P. mirabilis can make it difficult to fight infection and limit the clinical treatment process. Therefore, in this thesis study, it was aimed to examine the process of antibiotic resistance development of P. mirabilis due to ampicillin at sub-inhibitory concentration and whether passages resistant to ampicillin develop cross-resistance to other antibiotics using metabolic methods. For this purpose, resistant passages were obtained by gradually imparting resistance to ampicillin at sub-inhibitory concentration to the P. mirabilis strain using the disc diffusion method. It was aimed to compare the expression of the differences in the metabolomic profiles by applying ampicillin and ceftazidime antibiotics to the ampicillin-resistant passages and sensitive control strains obtained from each step. Metabolomic data obtained from the thesis study, supported by statistical and bioinformatic analyses, contribute to mapping metabolic pathways, understanding metabolic changes and determining interactions between metabolites. In antibiotic resistance studies, metabolomics provides valuable information in identifying metabolic changes in resistant microorganisms, understanding the response of microorganisms to antibiotic exposure, understanding how antibiotics affect metabolic pathways, and providing a comprehensive understanding of antibiotic resistance mechanisms.