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Tools for the identification of unknown compounds after gas chromatographic-mass spectrometric (GC-MS) analysis of urinary volatile organic metabolites (VOMs)


Živković Semren, Tanja; Brčić Karačonji, Irena; Jurič, Andreja; Brajenović, Nataša; Tariba Lovaković, Blanka; Pizent Alica
Tools for the identification of unknown compounds after gas chromatographic-mass spectrometric (GC-MS) analysis of urinary volatile organic metabolites (VOMs) // 10th Congress of Toxicology in Developing Countries (CTDC10) & 12th Congress of the Serbian Society of Toxicology (12th SCT) / Matović, Vesna (ur.).
Beograd: Serbian Society of Toxicology, 2018. str. 94-94 (poster, podatak o recenziji nije dostupan, sažetak, znanstveni)


Naslov
Tools for the identification of unknown compounds after gas chromatographic-mass spectrometric (GC-MS) analysis of urinary volatile organic metabolites (VOMs)

Autori
Živković Semren, Tanja ; Brčić Karačonji, Irena ; Jurič, Andreja ; Brajenović, Nataša ; Tariba Lovaković, Blanka ; Pizent Alica

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni

ISBN
978-86-917867-1-7

Skup
10th Congress of Toxicology in Developing Countries (CTDC10) & 12th Congress of the Serbian Society of Toxicology (12th SCT)

Mjesto i datum
Beograd, Srbija, 18-21.04.2018

Vrsta sudjelovanja
Poster

Vrsta recenzije
Podatak o recenziji nije dostupan

Ključne riječi
Metabolomics, HS-SPME, AMDIS, Kovats retention index, NIST

Sažetak
Volatile organic metabolites (VOMs) in human urine can be used in non-targeted metabolomics research to identify specific metabolites that may be useful as new diagnostic, predictive, and prognostic disease biomarkers. Determination of urinary metabolite profile provides novel information on phenotypic characteristics of an organism that cannot be obtained from target measurement. The headspace-solid phase microextraction (HS-SPME) technique coupled with gas chromatography-mass spectrometry (GC-MS) proved to be the most successful in VOMs analysis. After data processing of raw GC-MS data crucial step is to identify compounds of interest. Due to the complexity of the matrix, wide chemical diversity of the metabolites and their wide concentration range, metabolite identification is intrinsically difficult. In our laboratory, we use automated mass spectral deconvolution and identification system (AMDIS) for identification of unknown VOMs. AMDIS first deconvolutes the raw GCMS data file to find all components, and then compare mass spectral data against a library of target compound (e.g. National Institute of Standards (NIST) mass spectral library). To reduce possible solutions of identification offered by NIST Kovats retention index (RI) is used. A Kovats retention index system uses a series of standards, homologous series of n-alkanes applied as reference peak. Despite some limitations, presented methods could be very useful in VOMs identification. To confirm identification of unknown VOMs unequivocally, analysis of available analytical standards using the same GC-MS conditions is recommended.

Izvorni jezik
Engleski

Znanstvena područja
Kemija, Javno zdravstvo i zdravstvena zaštita



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