Session 4

Koen Sandra, Liesa Verscheure, Gerd Vanhoenacker, Tom Merchiers, Shauni Detremmerie, Julie Storms, Isabel Vandenheede, Pat Sandra

RIC group, President Kennedypark 26, 8500, Kortrijk, Belgium
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Biotech drugs, once considered a risky and nearly impossible route to explore, are today dominating the pharma landscape. In the footsteps of the biotech pioneers walking this bumpy road, our chromatographic community rose to the challenge and sharpened the analytical toolbox.
Throughout the years we have seen products become increasingly complex and witnessed analytics becoming more and more performant.
This talk will reflect on the recent advances in the analysis of biologics; from the coupling of historical incompatible chromatographic methods with mass spectrometry, to the combination of ever more separation modes in multidimensional set-ups and the implementation of chemical and enzymatic reactors in the flow path for primary and higher order structural assessment.

Živoslav Tešić¹, Milica Nešović², Stevan Blagojević²

¹Faculty of Chemistry, University of Belgrade, Studentski trg 12 – 16, 11000 Belgrade, Serbia
²Institute of General and Physical Chemistry, Belgrade, Studentski trg 12 – 16, 11000 Belgrade, Serbia

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In recent years, the botanical and geographical origin of food has become an important topic in the context of food quality and safety, as well as consumer protection, in accordance with international standards. In the case of honeys, Melissopalynology analysis is used as the method of choice for assessing botanical origin. When collecting nectar, bees add a certain amount of pollen to it, which is used to assess the botanical origin. By counting pollen particles of appropriate plant species, botanical origin is attributed to such honey. The problem arises when honey contains a large number of pollen particles from nectarless plants. In such cases, it is necessary to apply some additional methods to assess the botanical origin. Polyphenols, secondary metabolites of plants, can provide important information about the origin.
In this study, we analyzed buckwheat honey with different pollen content, which varied from 5 to 40% of pollen, nectar as well as pollen using the UHPLC-DAD system connected to triple-quadrupole mass spectrometer. The 31 polyphenols were quantified. Dominant content is found for propolis-derived flavonoids such as chrysin and pinocembrin. The significant contribution was also attributed to p-hydroxybenzoic acid and p-coumaric acid as others discovered and suggested as markers for the botanical origin of buckwheat honey. An excellent correlation was found between nectar and honey polyphenols regardless of the content of pollen particles [1]. In the cases of buckwheat honey with low pollen content, comparing the polyphenolic profile of honey and nectar provides important additional data necessary for assessment of the botanical origin.

Reference
[1]  M. Nesovic, U. Gasic, T. Tosti, N. Horvacki, N. Nedic, M. Sredojevic, S. Blagojevic, Lj. Ignjatovic, Z. Tesic, RSC Adv. 11 (2021) 25816-25829.

Virginia Coman¹, Simion Beldean-Galea<sup>2

1</sup>Babeş-Bolyai University, Raluca Ripan Institute for Research in Chemistry, Fântânele 30, 400294 Cluj-Napoca, Romania
²Babeş-Bolyai University, Faculty of Environmental Science and Engineering, Fântânele 30, 400294 Cluj-Napoca, Romania

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The extraction stage of the compounds from a matrix is very important for the results of the final analysis because it can generate many errors, waste and health problems. Therefore, the principles of green chemistry in analytical chemistry aim to significantly reduce the waste generated by the analyses [1]. Due to the toxicity of solvents, various extraction methods have been developed in recent years to significantly reduce or completely remove the amount of solvents used to extract the compounds from the matrix [2]. The miniaturized extraction (microextraction) methods offer certain advantages: low amounts (microliters) of solvents, small amount of sample to be analysed, reduced extraction time, high enrichment factor (order of hundreds), and high selectivity and precision. Due to these benefits, these methods have developed rapidly and are applied to various classes of organic and inorganic compounds in different liquid or solid matrices [3].
This review is a state-of-the-art of the applications of the liquid-phase microextraction (LPME) in the analysis of pharmaceuticals (anti-inflammatories, antidepressants, antibiotics, hormones, anti-cancer drugs, etc.) in biological fluids (serum, urine, saliva, etc.) and environmental (waters, sediments) samples. Our work is focused on the theoretical aspects of LPME and the applications of dispersive liquid-liquid microextraction, dispersive liquid-liquid microextraction based on solidification of floating organic droplet and hollow fiber microextraction. Aspects related to the analysis techniques (gas chromatography, liquid chromatography, capillary electrophoresis) coupled with different detectors following the microextraction stage are also presented. A critical comparison is made between microextraction techniques and extraction techniques used for routine analysis to provide a viable and greener alternative.

References
[1]  A. Spietelun, Ł. Marcinkowski, M. de la Guardia, J. Namieśnik, Talanta 119 (2014) 34-45.
[2]  F.R. Mansour, N.D. Danielson, Anal. Chim. Acta 1016 (2018) 1-11.
[3]  N. Campillo, K. Gavazov, P. Viñas, I. Hagarova, V. Andruch, Appl. Spectrosc. Rev. 55 (2020) 307-326.

Antonia Garcia¹, María Bajo¹, Gabriel Montero¹, Laura Mayo¹, Vanesa Alonso-Herranz¹, Clarissa Caroli², Elisa Zubeldia-Varela³, Tomás Clive Barker-Tejeda³, Alma Villaseñor³, David Rojo¹, Coral Barbas¹, Maria Fernanda Rey-Stolle<sup>1

1</sup>Center for Metabolomics, CEMBIO, Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, 28660 Boadilla del Monte, Madrid, España
²Department of Life Sciences, University of Modena and Reggio Emilia, Modena, Italy
³CEMBIO, Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, 28660 Boadilla del Monte, Madrid, España &Departamento de Ciencias Médicas Básicas, Instituto de Medicina Molecular Aplicada

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GC-MS is a well-established technique. Just in one run in untargeted metabolomics, a large set of metabolites can be covered, such as amino acids, primary carbon metabolism, organic amines, free fatty acids, polyols, mono- and disaccharides, and sterols, among others. Typical advantages for metabolite annotations are retention time index (RI) and commercial spectrum libraries, with rich fragmentation [1]. Typical drawbacks are the required chemical derivatization, which converts the components of the samples into volatile and less polar molecules and the multiple derivatives. Methoxymation-silylation or alkylation are some of the most common in which acidic protons are converted into thermally stable derivatives. The former is more universal but reaction must take place after evaporation to dryness whereas the latter generates derivatives in milder-reaction conditions with higher stability [2] and allows the study of relevant microbiome metabolites, such as short-chain organic acids. After fifteen years of untargeted metabolomic studies based on low mass resolution GC-MS, we have concluded that at least 10% of the possible compounds remain unknown in the profile. The scenario is far worse with alkyl derivatives (after alkyl chloroformate [2]). Unfortunately, commercial libraries are unit mass resolution and besides, many of these derivatives are not included yet and that introduces a huge bias, especially for metabolites with multiple functional groups.
High-resolution and exact mass GC-MS can shed some light on the structural elucidation of metabolites and their multiple derivatives. This research aimed to take advantage of the new technology to open a new era for identification. Multiple derivatives covering all types of metabolites were investigated through standard solutions, samples, and spiked samples. Besides, a step-by-step approach for elucidation of unknowns will be presented here with examples from our ongoing CEMBIO studies in allergy, COPD, anorexia nervosa, Lynch cancer, and COVID-19, with plasma and stool samples.

References
[1]  F. Rey-Stolle et al., Anal. Chim. Acta (2021) 339043.
[2]           L. Zhao et al,. Anal. Chem. 89 (2017) 5565-5577.

Natasa P. Kalogiouri^1,2, Natalia Manousi^2,3, Antonio Ferracane^2,4, George A. Zachariadis³, Stephanos Koundouras⁵, Victoria F. Samanidou³, Peter Q. Tranchida⁴, Luigi Mondello^4,6,7, Erwin Rosenberg<sup>2

1</sup>Laboratory of Analytical Chemistry, Department of Chemistry, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
²Institute of Chemical Technology and Analytics, Vienna University of Technology, Getreidemarkt 9/164, 1060 Vienna, Austria
³Laboratory of Analytical Chemistry, Department of Chemistry, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
⁴Department of Chemical, Biological, Pharmaceutical and Environmental Sciences, University of Messina, Messina, Italy
⁵Laboratory of Viticulture, School of Agriculture, Aristotle University of Thessaloniki, Thessaloniki, 54124, Greece
⁶Chromaleont s.r.l., c/o Department of Chemical, Biological, Pharmaceutical and Environmental Sciences, University of Messina, Messina, Italy
⁷Department of Sciences and Technologies for Human and Environment, University Campus Bio-Medico of Rome, Rome, Italy

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Authentication is defined as the process that unquestionably verifies that food is genuine. In a global food market, Protected Designation of Origin (PDO) wines are highly appreciated for the period of aging that allows the evolution of unique organoleptic properties, and thus, the guarantee of the vintage age is a critical authenticity issue [1]. The coupling of SPME-Arrow to GCxGC/MS analysis in combination with chemometric techniques could establish advanced analytical methods for the investigation of the volatile fingerprint of wine and revolutionize the field of wine authenticity. In this work, an SPME-Arrow-GCxGC/MS method was optimized [2], and used for the determination of volatile markers in 24 monovarietal red wine samples belonging to the PDO Xinomavro Naoussa, produced during 4 different years (1998, 2005, 2008 and 2015), in Northern Greece. Overall, 258 volatile compounds were tentatively identified in all samples. The data matrix that constituted of 24 samples and 258 features was further processed with multivariate techniques to establish mathematical models and reveal volatile markers for each vintage age. A partial least square – discriminant analysis (PLS-DA) model was developed and successfully classified all the samples to the proper class according to the vintage age with an explained total variance of 85.1%. Variant Importance in Projection (VIP) algorithm was used to calculate the VIP scores of the determined volatiles and distinguish the most important features that affect the discrimination, revealing markers [3]. The developed prediction model was validated and the analyzed samples were classified with 100% accuracy according to the vintage age, on the basis of their volatile fingerprint. The established PLS-DA model provided satisfying clustering, revealing 15 markers as most important for the classification of the wine samples.

References
[1] N.P. Kalogiouri, V.F. Samanidou, Environ. Sci. Pollut. Res. Int. 28, 42 (2021) 59150-59164.
[2] I. Šikuten, P. Štambuk, J. Karoglan Kontic, E. Maletic, I. Tomaz, D. Preiner, Molecules 26, 23 (2021) 1-16.
[3] N.P. Kalogiouri, N. Manousi, E. Rosenberg, G.A. Zachariadis, A. Paraskevopoulou, V. Samanidou, Food Chem. 363 (2021) 130331.