A workflow for bacterial metabolic fingerprinting and lipid profiling: application to Ciprofloxacin challenged Escherichia coli
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Abstract
The field of lipidomics focuses upon the non-targeted analysis of lipid composition, the process of which follows similar routines to those applied in conventional metabolic profiling, however lipidomics differs with respect to the sample preparation steps and chosen analytical platform applied to the sample analysis. Conventionally, lipidomics has applied analytical techniques such as direct infusion mass spectrometry and more recently reverse phase liquid chromatography–mass spectrometry, for the detection of mono-, di-, and tri-acyl glycerols, phospholipids, and other complex lipophilic species such as sterols. The field is rapidly expanding, especially with respect to the clinical sciences where it is known that changes of lipid composition, especially phospholipids, are commonly associated with many disease processes. As a proof of principle study, a small number of Escherichia coli isolates were selected on the basis of their sensitivity to a second generation fluoroquinolone antibiotic, known as Ciprofloxacin (E. coli isolates 161 and 171, non-ST131 isolates, which are resistant and sensitive respectively: E. coli isolates 160 and 173, ST131 sequence isolates which are resistant and susceptible respectively). It has been proposed that Ciprofloxacin may be a surface active drug that interacts at the surface-water interface of the phospholipid bi-layer where the head groups reside. Further, antibiotic resistance through intracellular exclusion is known to result in remodelling of the phospholipid membrane. Therefore, to study the effects of Ciprofloxacin on both susceptible and resistant bacterial strains, lipid profiling would present an informative approach. Control and antibiotic challenged cultures for each of the isolates were compared for changes in metabolite and lipid composition as detected by FT-IR spectroscopy and RP-UHPLC–MS, and appraised with a variety of chemometric data analysis approaches. The developed bacterial lipidomics workflow was deemed to be highly reproducible (with respect to the employed technical and analytical routines) and led to the detection of a large array of lipid classes as well as highlighting a range of significant lipid alterations that differed in regulation between susceptible and resistant E. coli isolates.
Keywords
Lipidomics Escherichia coli Ciprofloxacin hydrochloride Antibiotic-resistance Fourier transform infrared spectroscopy Liquid chromatography–mass spectrometryNotes
Acknowledgments
JWA, AV, YX, and RG would like to acknowledge CR-UK for current research funding. HR thanks The Saudi Ministry of higher education and King Saud University for funding. EC and RG are grateful to the EU Commonsense (http://www.fp7projectcommonsense.eu/) project (Grant 261809) financed by the European Commission under the 7th Framework Programme for Research and Technological Development.
Supplementary material
References
- Allwood, J. W., Clarke, A., Goodacre, R., & Mur, L. A. J. (2010). Dual metabolomics: A novel approach to understanding plant-pathogen interactions. Phytochem., 71, 590–597.CrossRefGoogle Scholar
- Allwood, J. W., Ellis, D. I., & Goodacre, R. (2008). Metabolomic technologies and their application to the study of plants and plant-host interactions. Physiologia Plantarum, 132, 117–135.PubMedGoogle Scholar
- Allwood, J. W., Ellis, D. I., Heald, J. K., Goodacre, R., & Mur, L. A. J. (2006). Metabolomic approaches reveal that phosphatidic and phosphatidyl glycerol phospholipids are major discriminatory metabolites in responses by Brachypodium distachyon to challenge by Magnaporthe grisea. Plant Journal, 46, 351–368.CrossRefPubMedGoogle Scholar
- Allwood, J. W., Erban, A., de Koning, S., Dunn, W. B., Luedemann, A., Lommen, A., et al. (2009). Inter-laboratory reproducibility of fast gas chromatography—electron impact—time of flight mass spectrometry (GC–EI–TOF/MS) based plant metabolomics. Metabolomics, 5, 479–496.CrossRefPubMedCentralPubMedGoogle Scholar
- AlRabiah, H., Correa, E., Upton, M., & Goodacre, R. (2013). High-throughput phenotyping of uropathogenic E. coli isolates with Fourier transform infrared spectroscopy. The Analyst, 138, 1363–1369.CrossRefPubMedGoogle Scholar
- AlRabiah, H., Xu, Y., Rattray, N. J. W., Vaughan, A. A., Gibreel, T., Sayqal, A., et al. (2014). Multiple metabolomics of uropathogenic E. coli reveal different information content in terms of metabolic potential compared to virulence factors. The Analyst. doi:10.1039/c4an00176a.PubMedGoogle Scholar
- Ames, G. F. (1968). Lipids of Salmonella typhimurium and Escherichia coli: Structure and metabolism. Journal of Bacteriology, 95, 833–843.PubMedCentralPubMedGoogle Scholar
- Bensikaddour, H., Snoussi, K., Lins, L., Van Bambeke, F., Tulkens, P. M., Brasseur, R., et al. (2008). Interactions of ciprofloxacin with DPPC and DPPG: Fluorescence anisotropy, ATR–FTIR and 31P NMR spectroscopies and conformational analysis. Biochimica et Biophysica Acta, 1778, 2535–2543.CrossRefPubMedGoogle Scholar
- Biais, B., Allwood, J. W., Deborde, C., Xu, Y., Maucort, M., Beauvoit, B., et al. (2009). 1H-NMR, GC–EI–TOF/MS, and dataset correlation for fruit metabolomics: application to spatial metabolite analysis in melon. Analytical Chemistry, 81, 2884–2894.CrossRefPubMedGoogle Scholar
- Bligh, E. G., & Dyer, W. J. (1959). A rapid method of total lipid extraction and purification. Canadian Journal of Biochemistry and Physiology, 37, 811–917.CrossRefGoogle Scholar
- Brown, M., Wedge, D., Goodacre, R., Kell, D. B., Baker, P. N., Kenny, L. C., et al. (2011). Automated workflows for accurate mass-based putative metabolite identification in LC/MS-derived metabolomic datasets. Bioinformatics, 27, 1108–1112.CrossRefPubMedCentralPubMedGoogle Scholar
- Castrillo, J. I., Zeef, L. A., Hoyle, D. C., Zhang, N., Hayes, A., Gardner, D. C. J., et al. (2007). Growth control of the eukaryote cell: A systems biology study in yeast. Journal of Biology, 6, 4.CrossRefPubMedCentralPubMedGoogle Scholar
- Crompton, M. J., Dunstan, R. H., Macdonald, M. M., Gottfries, J., von Eiff, C., & Roberts, T. K. (2014). Small changes in environmental paramaters lead to alterations in antiobiotic resistance, cell morphology, and membrane fatty acid composition in Staphylococcus lugdunensis. PLoS ONE, 9(4), e92296.CrossRefPubMedCentralPubMedGoogle Scholar
- De Vos, C. H. R., Moco, S., Lommen, A., Keurentjes, J. J. B., Bino, R. J., & Hall, R. D. (2007). Untargeted large-scale plant metabolomics using liquid chromatography coupled to mass spectrometry. Nature Protocols, 2, 778–791.CrossRefPubMedGoogle Scholar
- Diederen, B. M., & Kluytmans, J. A. (2006). The emergence of infections with community-associated methicillin resistant Staphylococcus aureus. The Journal of Infection, 52, 157–168.CrossRefPubMedGoogle Scholar
- Dunn, W. B., Broadhurst, D., Begley, P., Zelena, E., Francis-McIntyre, S., Anderson, N., et al. (2011). Procedures for large-scale metabolic profiling of serum and plasma using gas chromatography and liquid chromatography coupled to mass spectrometry. Nature Protocols, 6, 1060–1083.CrossRefPubMedGoogle Scholar
- Dunn, W. B., Broadhurst, D., Brown, M., Baker, P. N., Redman, C. W. G., Kenny, L. C., et al. (2008). Metabolic profiling of serum using ultra performance liquid chromatography and the LTQ-orbitrap mass spectrometry system. Journal of Chromatography B, 871(2), 288–298.CrossRefGoogle Scholar
- Dunn, W. B., Broadhurst, D. I., Deepak, S. M., Buch, M. H., McDowell, G., Spasic, I., et al. (2007). Serum metabolomics reveals many novel metabolic markers of heart failure, including pseudouridine and 2-oxoglutarate. Metabolomics, 3, 413–426.CrossRefGoogle Scholar
- Ellis, D. I., & Goodacre, R. (2006). Metabolic fingerprinting in disease diagnosis: biomedical applications of infrared and Raman spectroscopy. Analyst, 131, 875–885.CrossRefPubMedGoogle Scholar
- Fiehn, O. (2002). Metabolomics—The link between genotypes and phenotypes. Plant Molecular Biology, 48, 155–171.CrossRefPubMedGoogle Scholar
- Fiehn, O., Kopka, J., Dörmann, P., Altmann, T., Trethewey, R. N., & Willmitzer, L. (2000). Metabolite profiling for plant functional genomics. Nature Biotechnology, 18, 1157–1161.CrossRefPubMedGoogle Scholar
- Goodacre, R., Vaidyanathan, S., Bianchi, G., & Kell, D. B. (2002). Metabolic profiling using direct infusion electrospray ionisation mass spectrometry for the characterisation of olive oils. The Analyst, 11, 1457–1462.CrossRefGoogle Scholar
- Greenwood, D. (2000). Antimicrobial chemotherapy (4th ed.). Norfolk: Oxford University Press Inc.Google Scholar
- Griffin, J. L., & Kauppinen, R. A. (2007). Tumour metabolomics in animal models of human cancer. Journal of Proteome Research, 6, 498–505.CrossRefPubMedGoogle Scholar
- Han, X., & Gross, R. W. (2005). Shotgun lipidomics: Electrospray ionization mass spectrometric analysis and quantitation of cellular lipidomes directly from crude extracts of biological samples. Mass Spectrometry Reviews, 24, 367–412.CrossRefPubMedGoogle Scholar
- Herrgård, M. J., Swainston, N., Dobson, P., Dunn, W. B., Arga, K. Y., Arvas, M., et al. (2008). A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology. Nature Biotechnology, 26, 1155–1160.CrossRefPubMedCentralPubMedGoogle Scholar
- Kaper, J. B., Nataro, J. B., & Mobley, H. L. T. (2004). Pathogenic Escherichia coli. Nature Reviews Microbiology, 2, 123–140.CrossRefPubMedGoogle Scholar
- Kaplan, F., Kopka, J., Haskell, D. W., Zhao, W., Schiller, K. C., Gatzke, N., et al. (2004). Exploring the temperature-stress metabolome of Arabidopsis. Plant Physiology, 136, 4159–4168.CrossRefPubMedCentralPubMedGoogle Scholar
- Kenny, L. C., Broadhurst, D. I., Dunn, W., Brown, M., North, R. A., McCowan, L., et al. (2010). Robust early pregnancy prediction of later preeclampsia using metabolomic biomarkers. Hypertension, 56, 741–749.CrossRefPubMedGoogle Scholar
- Koek, M. M., Muilwijk, B., van der Werf, M. J., & Hankemeier, T. (2006). Microbial metabolomics with gas chromatography/mass spectrometry. Analytical Chemistry, 78, 1272–1281.CrossRefPubMedGoogle Scholar
- Kolak, M., Westerbacka, J., Velagapudi, V. R., Wagsater, D., Yetukuri, L., Makkonen, J., et al. (2007). Adipose tissue inflammation and increased ceramide content characterize subjects with high liver fat content independent of obesity. Diabetes, 56, 1960–1968.CrossRefPubMedGoogle Scholar
- Lau, S. H., Reddy, S., Cheesbrough, J., Bolton, F. J., Willshaw, G., Cheasty, T., et al. (2008). Major uropathogenic Escherichia coli strain isolated in the northwest of England identified by multilocus sequence typing. Journal of Clinical Microbiology, 46, 1076–1080.CrossRefPubMedCentralPubMedGoogle Scholar
- Leying, H., Suerbaum, S., Kroll, H.-P., Karch, H., & Opferkuch, W. (1986). Influence of ß-lactam antibiotics and ciprofloxacin on composition and immunogenicity of Escherichia coli outer membrane. Antimicrobial Agents and Chemotherapy, 30, 475–480.CrossRefPubMedCentralPubMedGoogle Scholar
- Lisec, J., Schauer, N., Kopka, J., Willmitzer, L., & Fernie, A. R. (2006). Gas chromatography mass spectrometry-based metabolite profiling in plants. Nature Protocols, 1, 387–396.CrossRefPubMedGoogle Scholar
- Lowe, R. G. T., Allwood, J. W., Galster, A. M., Urban, M., Daudi, A., Canning, G., et al. (2010). A combined 1H nuclear magnetic resonance and electrospray ionization-mass spectrometry analysis to understand the basal metabolism of plant-pathogenic Fusarium spp. Molecular Plant-Microbe Interactions, 23, 1605–1618.CrossRefPubMedGoogle Scholar
- MacKenzie, D. A., Defernez, M., Dunn, W. B., Brown, M., Fuller, L. J., Seco de Herrera, S. R. M., et al. (2008). Relatedness of medically important strains of Saccharomyces cerevisiae as revealed by phylogenetics and metabolomics. Yeast, 25, 501–512.CrossRefPubMedGoogle Scholar
- Mattila, I., Seppänen-Laakso, T., Suortti, T., & Orešič, M. (2008). Application of lipidomics and metabolomics to the study of adipose tissue. Methods in Molecular Biology, 456, 123–130.CrossRefPubMedGoogle Scholar
- Merino, S., Doménech, O., Diez, I., Sanz, F., Vinas, M., Montero, M. T., et al. (2003). Effects of ciprofloxacin on Escherichia coli lipid bilayers: An Atomic Force Microscopy Study. Langmuir, 19, 6922–6927.CrossRefGoogle Scholar
- Mori, H. (2004). From the Sequence to Cell Modelling: Comprehensive Functional Genomics in Escherichia coli. Journal of Biochemistry and Molecular Biology, 37, 83–92.CrossRefPubMedGoogle Scholar
- Okusu, H., Ma, D., & Nikaido, H. (1996). AcrAB efflux pump plays a major role in the antibiotic resistance phenotype of Escherichia coli multiple-antibiotic-resistance (Mar) mutants. Journal of Bacteriology, 178, 306–308.PubMedCentralPubMedGoogle Scholar
- Orešič, M., Simmel, S., Sysi-Aho, M., Näntö-Salonen, K., Seppänen-Laakso, T., Parikka, V., et al. (2008). Dysregulation of lipid and amino acid metabolism precedes islet autoimmunity in children who later progress to type 1 diabetes. The Journal of Experimental Medicine, 205, 2975–2984.CrossRefPubMedCentralPubMedGoogle Scholar
- Poole, K., Krebes, K., McNally, C., & Neshat, S. (1993). Multiple antibiotic resistance in Pseudomonas aeruginosa: evidence for involvement of an efflux operon. Journal of Bacteriology, 22, 7363–7372.Google Scholar
- Preisner, O., Almeida Lopes, A., Guiomar, R., Machado, J., & Menezes, J. C. (2007). Fourier transform infrared (FT-IR) spectroscopy in bacteriology: towards a reference method for bacteria discrimination. Analytical and Bioanalytical Chemistry, 387, 1739–1748.CrossRefPubMedGoogle Scholar
- RajBhandary, U. L., & Söll, D. (2008). Aminoacyl-tRNAs, the bacterial cell envelope, and antibiotics. Proceedings of the National Academy of Sciences, 105, 5285–5286.CrossRefGoogle Scholar
- Riley, M., Abe, T., Arnaud, M. B., Berlyn, M. K. B., Blattner, F. R., Chaudhuri, R. R., et al. (2006). Escherichia coli K-12: a cooperatively developed annotation snapshot—2005. Nucleic Acids Research, 34, 1–9.CrossRefPubMedCentralPubMedGoogle Scholar
- Roessner, U., Luedemann, A., Brust, D., Fiehn, O., Linke, T., Willmitzer, L., et al. (2001). Metabolic profiling allows comprehensive phenotyping of genetically or environmentally modified plant systems. Plant Cell, 13, 11–29.CrossRefPubMedCentralPubMedGoogle Scholar
- Rojas-Cherto, M., Peironcely, J. E., Kasper, P. T., van der Hooft, J. J. J., de Vos, R. C. H., Vreeken, R., et al. (2012). Metabolite identification using automated comparison of high-resolution multistage mass spectral trees. Analytical Chemistry, 84, 5524–5534.CrossRefPubMedGoogle Scholar
- Roux, A., Xu, Y., Heilier, J.-F., Olivier, M.-F., Ezan, E., Tabet, J.-C., et al. (2012). Annotation of the human adult urinary metabolome and metabolite identification using ultra high performance liquid chromatography coupled to a linear quadrupole ion trap-orbitrap mass spectrometer. Analytical Chemistry, 84, 6429–6437.CrossRefPubMedGoogle Scholar
- Roy, H., & Ibba, M. (2008). RNA-dependent lipid remodeling by bacterial multiple peptide resistance factors. Proceedings of the National Academy of Sciences, 105, 4667–4672.CrossRefGoogle Scholar
- Sáenz, Y., Briñas, L., Domínguez, E., Ruiz, J., Zarazaga, M., Vila, J., et al. (2004). Mechanisms of resistance in multiple-antibiotic-resistant Escherichia coli strains of human, animal, and food origins. Antimicrobial Agents and Chemotherapy, 48, 3996–4001.CrossRefPubMedCentralPubMedGoogle Scholar
- Saito, K., & Matsuda, F. (2010). Metabolomics for functional genomics, systems biology and biotechnology. Annual Review of Plant Biology, 61, 463–489.CrossRefPubMedGoogle Scholar
- Sreekumar, A., Poisson, L. M., Rajendiran, T. M., Khan, A. P., Cao, Q., Yu, J., et al. (2009). Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Nature, 457, 910–914.CrossRefPubMedCentralPubMedGoogle Scholar
- Sumner, L. W., Amberg, A., Barrett, D., Beale, M. H., Beger, R., Daykin, C. A., et al. (2007). Proposed minimum reporting standards for chemical analysis. Metabolomics, 3, 211–221.CrossRefPubMedCentralPubMedGoogle Scholar
- Tikunov, Y., De Vos, C. H. R., Gonzalez-Paramas, A. M., Hall, R. D., & Bovy, A. G. (2010). A role for differtential glycoconjugation in the emission of phenylpropanoid volatiles from tomato fruit discovered using a metabolic data fusion approach. Plant Physiology, 152, 55–70.CrossRefPubMedCentralPubMedGoogle Scholar
- Tomasz, A. (1994). Multiple-antibiotic-resistant bacteria—A report on the Rockefeller University Workshop. The New England Journal of Medicine, 330, 1247–1251.CrossRefPubMedGoogle Scholar
- van der Hooft, J. J. J., Vervoort, J., Bino, R. J., Beekwilder, J., & de Vos, R. C. H. (2011). Polyphenol identification based on systematic and robust high-resolution accurate mass spectrometry fragmentation. Analytical Chemistry, 83, 409–416.CrossRefPubMedGoogle Scholar
- van der Hooft, J. J. J., Vervoort, J., Bino, R. J., & de Vos, R. C. H. (2012). Spectral trees as a robust annotation tool in LC–MS based metabolomics. Metabolomics, 8, 691–703.CrossRefGoogle Scholar
- Van Der Werf, M. J., Overkamp, K. M., Mulwijk, B., Koek, M. M., Van Der Werff-Van Der Vat, B. J. C., Jellema, R. H., Coulier, L. & Hankemeier, T. (2008). Comprehensive analysis of the metabolome of Pseudomonas putida S12 grown on different carbon sources. Molecular Biosystems, 4, 315–327.Google Scholar
- Velagapudi, V. R., Hezaveh, R., Reigstad, C. S., Gopalacharyulu, P., Yetukuri, L., Islam, S., et al. (2010). The gut microbiota modulates host energy and lipid metabolism in mice. Journal of Lipid Research, 51, 1101–1112.CrossRefPubMedCentralPubMedGoogle Scholar
- Wedge, D. C., Allwood, J. W., Dunn, W. B., Vaughan, A. A., Simpson, K., Brown, M., et al. (2011). Is serum or plasma more appropriate for inter-subject comparisons in metabolomic studies? An assessment in patients with small-cell lung cancer. Analytical Chemistry, 83, 6689–6697.CrossRefPubMedGoogle Scholar
- Wehlri, P. M., Lindberg, E., Sparén, A., Josefson, M., Dunstan, R. H., Wold, A. E., et al. (2013). Exploring bacterial phenotypic diversity using factorial design and FTIR multivariate fingerprinting. Journal of Chemometrics. doi:10.1002/cem.2588.Google Scholar
- Wiener, J., Quinn, J. P., Bradford, P. A., Goering, R. V., Nathan, C., Bush, K., et al. (1999). Multiple antibiotic-resistant Klebsiella and Escherichia coli in nursing homes. The Journal of the American Medical Association, 281, 517–523.CrossRefGoogle Scholar
- Winder, C. L., Dunn, W. B., Schuler, S., Broadhurst, D., Jarvis, R. M., Stephens, G. M., et al. (2008). Global metabolic profiling of Escherichia coli cultures: an evaluation of methods for quenching and extraction of intracellular metabolites. Analytical Chemistry, 80, 2939–2948.CrossRefPubMedGoogle Scholar
- Winder, C. L., Gordon, S. V., Dale, J., Hewinson, R. G., & Goodacre, R. (2006). Metabolic fingerprints of Mycobacterium bovis cluster with molecular type: Implications for genotype-phenotype links. Microbiology, 152, 2757–2765.CrossRefPubMedGoogle Scholar