Metabolic response of Escherichia coli to subinhibitory concentration of ofloxacin

Abstract

Antibiotic resistance is one of the most important problems worldwide. In order to overcome antibiotic resistance, pathogen-antibiotic interactions should be investigated at molecular level. In our present study, we focused on metabolic differences in Escherichia coli (E. coli) under ofloxacin stress to understand adaptation and resistance mechanisms. We used GC/MS based metabolomics approach for metabolite identification and quantification. Experimental results showed that 17 metabolites were altered under subinhibitory concentration of ofloxacin. Pathway analysis indicated that TCA cycle, glyoxylate and dicarboxylate metabolism, biosynthesis of fatty acids, glutathione metabolism were induced by ofloxacin. Moreover, we evaluated metabolites individually and we found that spermine and L-ascorbic acid increased in ofloxacin treated groups. These metabolites are important in resistance and detoxifying processes in cells. In conclusion, altered metabolome profile gave information on adaptation and resistance processes in E. coli against ofloxacin. These metabolic changes will help to enlighten resistance mechanisms and discover novel treatment strategies against the pathogens.

Keywords

• Metabolomics
• antibiotic resistance
• GC/MS
• MS-DIAL
• TCA cycle

References

1. [1] Alos JI. Antibiotic resistance: A global crisis]. Enferm Infecc Microbiol Clin. 2015; 33(10): 692-699. [CrossRef].
2. [2] Ventola CL. The antibiotic resistance crisis: part 2: management strategies and new agents. P T.2015; 40(5): 344-352
3. [3] Caudle WM, Bammler TK, Lin Y, Pan S, Zhang J. Using 'omics' to define pathogenesis and biomarkers of Parkinson's disease. Expert Rev Neurother. 2010; 10(6): 925-942. [CrossRef]
4. [4] Hasin Y, Seldin M, Lusis A. Multi-omics approaches to disease. Genome Biol. 2017; 18(1): 83-92. [CrossRef]
5. [5] Sacco F, Silvestri A, Posca D, Pirro S, Gherardini PF, Castagnoli L, Mann M, Cesareni G. Deep Proteomics of Breast Cancer Cells Reveals that Metformin Rewires Signaling Networks Away from a Pro-growth State. Cell Syst. 2016; 2(3): 159-171. [CrossRef]
6. [6] Li W, Zhang S, Wang X, Yu J, Li Z, Lin W, Lin X. Systematically integrated metabonomic-proteomic studies of Escherichia coli under ciprofloxacin stress. J Proteomics. 2018; 179(1): 61-70. [CrossRef]
7. [7] Patkari M, Kumbhar C, Nag A, Mehra S. Distinct transcriptomic response of S. coelicolor to ciprofloxacin in a nutrient-rich environment. Appl Microbiol Biotechnol. 2018; 102(24): 10623-10643. [CrossRef]
8. [8] Wright MS, Suzuki Y, Jones MB, Marshall SH, Rudin SD, van Duin D, Kaye K, Jacobs MR, Bonomo RA, Adams MD. Genomic and transcriptomic analyses of colistin-resistant clinical isolates of Klebsiella pneumoniae reveal multiple pathways of resistance. Antimicrob Agents Chemother. 2015; 59(1): 536-543. [CrossRef]

9. [9] Li H, Zhang DF, Lin XM, Peng XX. Outer membrane proteomics of kanamycin-resistant Escherichia coli identified MipA as a novel antibiotic resistance-related protein. FEMS Microbiol Lett. 2015; 362(11): 1-8. [CrossRef]
10. [10] Griffin JL, Atherton H, Shockcor J, Atzori L. Metabolomics as a tool for cardiac research. Nature Reviews Cardiology 2011; 8(11): 630-643. [CrossRef]
11. [11] Fukusaki E. Application of Metabolomics for High Resolution Phenotype Analysis. Mass Spectrom. 2014; 3(3): 1-8. [CrossRef]
12. [12] Vincent IM, Ehmann DE, Mills SD, Perros M, Barrett MP. Untargeted Metabolomics To Ascertain Antibiotic Modes of Action. Antimicrob Agents Chemother. 2016; 60(4): 2281-2291. [CrossRef]
13. [13] Zampieri M, Zimmermann M, Claassen M, Sauer U. Nontargeted Metabolomics Reveals the Multilevel Response to Antibiotic Perturbations. Cell Reports. 2017; 19(6): 1214-1228. [CrossRef]
14. [14] Xiong XY, Sheng XQ, Liu D, Zeng T, Peng Y, Wang YC. A GC/MS-based metabolomic approach for reliable diagnosis of phenylketonuria. Anal Bioanal Chem. 2015; 407(29): 8825-8833. [CrossRef]
15. [15] Blondeau JM. Fluoroquinolones: Mechanism of action, classification, and development of resistance. Surv Ophthalmol. 2004; 49(1): 73-78. [CrossRef]
16. [16] Hooper DC. Mechanisms of action of antimicrobials: Focus on fluoroquinolones. Clinical Infectious Diseases.2001; 32(1): 9-15. [CrossRef]
17. [17] CLSI. Methods for Dilution Antimicrobial Susceptibility Tests for Bacteria That Grow Aerobically; Approved Standard -Tenth Edition.CLSI document M07-A10. Wayne, PA: Clinical and Laboratory Standards Institute. 2005
18. [18] Nemutlu E, Zhang S, Xu YZ, Terzic A, Zhong L, Dzeja PD, Cha YM. Cardiac Resynchronization Therapy Induces Adaptive Metabolic Transitions in the Metabolomic Profile of Heart Failure. J Card Fail. 2015; 21(6): 460-469. [CrossRef]
19. [19] Rosato RR, Fernandez R, Paz LI, Singh CR, Rosato AE. TCA Cycle-Mediated Generation of ROS Is a Key Mediator for HeR-MRSA Survival under beta-Lactam Antibiotic Exposure. Plos One. 2014; 9(6): 1-10. [CrossRef]
20. [20] Lorenz MC, Fink GR. The glyoxylate cycle is required for fungal virulence. Nature. 2001; 412(6842): 83-86. [CrossRef]
21. [21] Jung J, Park W. Comparative genomic and transcriptomic analyses reveal habitat differentiation and different transcriptional responses during pectin metabolism in Alishewanella species. Appl Environ Microbiol. 2013; 79(20): 6351-6361. [CrossRef]
22. [22] Kohanski MA, Dwyer DJ, Hayete B, Lawrence CA, Collins JJ. A common mechanism of cellular death induced by bactericidal antibiotics. Cell. 2007; 130(5): 797-810. [CrossRef]
23. [23] Nandakumar M, Nathan C, Rhee KY. Isocitrate lyase mediates broad antibiotic tolerance in Mycobacterium tuberculosis. Nat Commun. 2014; 5(1): 4306-4316. [CrossRef]
24. [24] Ahn S, Jung J, Jang IA, Madsen EL, Park W. Role of Glyoxylate Shunt in Oxidative Stress Response. J Biol Chem. 2016; 291(22): 11928-11938. [CrossRef] [25] Cameron JC, Pakrasi HB. Glutathione facilitates antibiotic resistance and photosystem I stability during exposure to gentamicin in cyanobacteria. Appl Environ Microbiol.2011; 77(10): 3547-3550. [CrossRef]