Pregled bibliografske jedinice broj: 936148
Tools for the identification of unknown compounds after gas chromatographic-mass spectrometric (GC-MS) analysis of urinary volatile organic metabolites (VOMs)
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 (CTDC 10) ; 12th Serbian Congress of Toxicology / Matović, Vesna (ur.).
Beograd: Serbian Society of Toxicology, 2018. str. 94-94 (poster, međunarodna recenzija, sažetak, znanstveni)
CROSBI ID: 936148 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
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 (CTDC 10) ; 12th Serbian Congress of Toxicology
Mjesto i datum
Beograd, Srbija, 18.04.2018. - 21.04.2018
Vrsta sudjelovanja
Poster
Vrsta recenzije
Međunarodna recenzija
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
POVEZANOST RADA
Ustanove:
Institut za medicinska istraživanja i medicinu rada, Zagreb
Profili:
Nataša Brajenović
(autor)
Blanka Tariba
(autor)
Andreja Jurič
(autor)
Irena Brčić Karačonji
(autor)
Alica Pizent
(autor)
Tanja Živković Semren
(autor)