Dissertation committee:
Νικόλαος Θωμαΐδης, Καθηγητής, Τμήμα Χημείας, ΕΚΠΑ
Αναστάσιος Οικονόμου, Καθηγητής, Τμήμα Χημείας, ΕΚΠΑ
Ευάγγελος Γκίκας, Επίκουρος Καθηγητής, Τμήμα Φαρμακευτικής, ΕΚΠΑ
Ιωάννης Ντότσικας, Καθηγητής, Τμήμα Φαρμακευτικής, ΕΚΠΑ
Θωμάς Μαυρομούστακος, Καθηγητής, Τμήμα Χημείας, ΕΚΠΑ
Ειρήνη Παντερή, Καθηγητής, Τμήμα Φαρμακευτικής, ΕΚΠΑ
Χρήστος Κόκκινος, Επίκουρος Καθηγητής, Τμήμα Χημείας, ΕΚΠΑ
Summary:
Over the last decade, a high number of emerging contaminants were detected and identified in surface and waste waters that could threaten the aquatic environment due to their pseudo-persistence. As it is described in chapters 1 and 2, liquid chromatography high resolution mass spectroscopy (LC-HRMS) can be used as an efficient tool for their screening. Simultaneously screening of these samples by hydrophilic interaction liquid chromatography (HILIC) and reversed phase (RP) would help with full identification of suspects and unknown compounds. However, to confirm the identity of the most relevant suspect or unknown compounds, their chemical properties such as retention time behavior, MSn fragmentation and ionization modes should be investigated.
Chapter 3 of this thesis discusses the development of a comprehensive workflow to study the retention time behavior of large groups of compounds belonging to emerging contaminants. A dataset consisted of more than 2500 compounds was used for RP/HILIC-LC-HRMS, and their retention times were derived in both Electrospray Ionization mode (+/-ESI). These in silico approaches were then applied on the identification of 10 new transformation products of tramadol, furosemide and niflumic acid (under ozonation treatment).
Chapter 4 discusses about the development of a first retention time index system for LC-HRMS. Some practical applications of this RTI system in suspect and non-target screening in collaborative trials have been presented as well.
Chapter 5 describes the development of in silico based toxicity models to estimate the acute toxicity of emerging pollutants in the aquatic environment. This would help link the suspect/non-target screening results to the tentative environmental risk by predicting the toxicity of newly tentatively identified compounds.
Chapter 6 introduces an automatic and systematic way to perform suspect and non-target screening in LC-HRMS data. This would save time and the data analysis loads and enable the routine application of non-target screening for regulatory or monitoring purpose.
Keywords:
Chemometrics, Suspect Screening, Non-target Screening, High Resolution Mass Spectrometry
