Abstract
Unique metabolic features allow fungi to colonize and persist within the human host. Investigations of unique metabolic fingerprints of a pathogenic fungus can provide a more complete understanding of the infection process and an interpretation of associations between genotype and phenotype. Gas chromatography–mass spectrometry (GC–MS) has proved to be one of the most powerful analytical techniques used for qualitative and quantitative detection of cellular metabolites. This technique has been used for comparative metabolomic analyses of both intracellular and secreted metabolites under variable conditions. This book chapter describes the use of GC–MS in the detection of both intracellular and secreted metabolites from Candida auris, a newly emerging fungal pathogen representing a serious global health threat due to its multidrug resistance profile. The identified fungal metabolites are compared using available software in order to assign a correlation between the pattern of accumulation of metabolites and behavior of the organism.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Wishart DS, Tzur D, Knox C, Eisner R, Guo AC, Young N, Cheng D, Jewell K, Arndt D, Sawhney S, Fung C, Nikolai L, Lewis M, Coutouly M-A, Forsythe I, Tang P, Shrivastava S, Jeroncic K, Stothard P, Amegbey G, Block D, Hau DD, Wagner J, Miniaci J, Clements M, Gebremedhin M, Guo N, Zhang Y, Duggan GE, MacInnis GD, Weljie AM, Dowlatabadi R, Bamforth F, Clive D, Greiner R, Li L, Marrie T, Sykes BD, Vogel HJ, Querengesser L (2007) HMDB: the human metabolome database. Nucleic Acids Res 35(suppl_1):D521–D526. https://doi.org/10.1093/nar/gkl923
Lee MS, Jung BH, Chung BC, Cho SH, Kim KY, Kwon OS, Nugraha B, Lee Y-J (2009) Metabolomics study with gas chromatography–mass spectrometry for predicting valproic acid–induced hepatotoxicity and discovery of novel biomarkers in rat urine. Int J Toxicol 28(5):392–404. https://doi.org/10.1177/1091581809340329
Tan B, Qiu Y, Zou X, Chen T, Xie G, Cheng Y, Dong T, Zhao L, Feng B, Hu X, Xu LX, Zhao A, Zhang M, Cai G, Cai S, Zhou Z, Zheng M, Zhang Y, Jia W (2013) Metabonomics identifies serum metabolite markers of colorectal cancer. J Proteome Res 12(6):3000–3009. https://doi.org/10.1021/pr400337b
Faber JH, Malmodin D, Toft H, Maher AD, Crockford D, Holmes E, Nicholson JK, Dumas ME, Baunsgaard D (2007) Metabonomics in diabetes research. J Diabetes Sci Technol 1(4):549–557
Ma Y, Kind T, Yang D, Leon C, Fiehn O (2014) MS2Analyzer: a software for small molecule substructure annotations from accurate tandem mass spectra. Anal Chem 86(21):10724–10731. https://doi.org/10.1021/ac502818e
Fiehn O, Kopka J, Trethewey RN, Willmitzer L (2000) Identification of uncommon plant metabolites based on calculation of elemental compositions using gas chromatography and quadrupole mass spectrometry. Anal Chem 72(15):3573–3580. https://doi.org/10.1021/ac991142i
Babushok VI, Linstrom PJ, Reed JJ, Zenkevich IG, Brown RL, Mallard WG, Stein SE (2007) Development of a database of gas chromatographic retention properties of organic compounds. J Chromatogr A 1157(1):414–421. https://doi.org/10.1016/j.chroma.2007.05.044
Horai H, Arita M, Kanaya S, Nihei Y, Ikeda T, Suwa K, Ojima Y, Tanaka K, Tanaka S, Aoshima K, Oda Y, Kakazu Y, Kusano M, Tohge T, Matsuda F, Sawada Y, Hirai MY, Nakanishi H, Ikeda K, Akimoto N, Maoka T, Takahashi H, Ara T, Sakurai N, Suzuki H, Shibata D, Neumann S, Iida T, Tanaka K, Funatsu K, Matsuura F, Soga T, Taguchi R, Saito K, Nishioka T (2010) MassBank: a public repository for sharing mass spectral data for life sciences. J Mass Spectrom 45(7):703–714. https://doi.org/10.1002/jms.1777
Kind T, Wohlgemuth G, Lee DY, Lu Y, Palazoglu M, Shahbaz S, Fiehn O (2009) FiehnLib: mass spectral and retention index libraries for metabolomics based on quadrupole and time-of-flight gas chromatography/mass spectrometry. Anal Chem 81(24):10038–10048. https://doi.org/10.1021/ac9019522
Semreen MH, Soliman SSM, Saeed BQ, Alqarihi A, Uppuluri P, Ibrahim AS (2019) Metabolic profiling of Candida auris, a newly-emerging multi-drug resistant Candida species, by GC-MS. Molecules 24(3):399
Alketbi EH, Hamdy R, El-Kabalawy A, Juric V, Pignitter M, Mosa KA, Almehdi AM, El-Keblawy AA, Soliman SSM (2021) Lipid-based therapies against SARS-CoV-2 infection. Rev Med Virol 31(5):1–13. https://doi.org/10.1002/rmv.2214
Ibarra-Trujillo C, Villar-Vidal M, Gaitán-Cepeda LA, Pozos-Guillen A, Mendoza-de Elias R, Sánchez-Vargas LO (2012) Ensayo de formación y cuantificación de biopelículas mixtas de Candida albicans y Staphylococcus aureus. Rev Iberoam Micol 29(4):214–222
DeJongh DC, Radford T, Hribar JD, Hanessian S, Bieber M, Dawson G, Sweeley CC (1969) Analysis of trimethylsilyl derivatives of carbohydrates by gas chromatography and mass spectrometry. J Am Chem Soc 91(7):1728–1740. https://doi.org/10.1021/ja01035a022
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature
About this protocol
Cite this protocol
Fayed, B., Kohder, G., Soliman, S.S.M. (2022). Gas Chromatography–Mass Spectrometry (GC–MS) Analysis of Candida auris Metabolites. In: Lorenz, A. (eds) Candida auris. Methods in Molecular Biology, vol 2517. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2417-3_12
Download citation
DOI: https://doi.org/10.1007/978-1-0716-2417-3_12
Published:
Publisher Name: Humana, New York, NY
Print ISBN: 978-1-0716-2416-6
Online ISBN: 978-1-0716-2417-3
eBook Packages: Springer Protocols