Maria Fedorova

Maria studied Biochemistry at Saint-Petersburg State University, Russia and obtained her PhD at the Faculty of Chemistry and Mineralogy, Leipzig University, Germany. Already within the Master project, which she did under the supervision of Prof. Nadezda Kuleva, Maria was interested in understanding redox regulation and stress responses in biological systems. When she joined the  laboratory of Prof. Ralf Hoffmann at the Institute of Bioanalytical Chemistry in Leipzig for her PhD project, she got the opportunity to combine her knowledge in biochemistry and interests in redox biology with advanced bioanalytical methods such as proteomics. Her PhD thesis entitled “Analysis of protein modifications formed by oxidative stress in vivo”, described application of proteomics, both gel- (yes, even 2D PAGE and DIGE, if someone remember what it is😊) and MS-based, to identify redox sensitive post-translational modifications (oxPTMs), including Cys ( DOI: 10.1021/pr901099e), Trp oxidation ( DOI: 10.1002/pmic.201000147) and protein carbonylation ( DOI: 10.1021/pr901182r;  DOI: 10.1016/j.jprot.2011.07.002;  DOI: 10.1039/c3an00724c;  DOI: 10.1002/mas.21381).

Being fascinated with mass spectrometry as a technique which allows to measure hundreds of molecular species, characterize their structure (at least to certain extent) and (relatively) quantify the response, Maria moved on from proteins to lipids. Why? The choice was governed by the same redox biology questions. One type of oxPTMs are adducts between nucleophilic amino acid residues in proteins and electrophilic products of lipid peroxidation ( DOI: 10.1021/ac302356z; DOI: 10.1016/j.redox.2014.12.009; DOI: 10.1016/j.redox.2016.12.028). And if one wish to characterize those, it is not enough to know the protein and the modification site but also the structure of lipid peroxidation product (LPP) itself. And this challenge became the topic of Maria’s Junior Research Group at the Centre for Biotechnology and Biomedicine (BBZ) in Leipzig. Joint by the group of extraordinary Master and PhD students, over the years we dug deeper and deeper into fascinating diversity of LPPs, and develop multiple methods for their analysis, mostly based on the application of liquid chromatography and high-resolution MS. If interested, have a look at our retrospective paper ( DOI: 10.1126/sciadv.adf6710) which reviews the main steps along this way!

Overall, studying the diversity of lipid modifications, both in vitro (cell culture) and in vivo (animal and human tissues) allowed us to conceptualized the term “epilipidome” as a subset of natural lipidome, formed via enzymatic and non-enzymatic lipid modifications including oxidation, nitration, sulfation and halogenation, and compose a new level of lipidome complexity required to regulate complex biological functions, similar to epigenetic modifications of DNA and protein PTMs ( DOI: 10.1016/j.freeradbiomed.2019.04.027). The concept of epilipidome was readily picked up by the community, and it is one of the basis for numerous collaborations within COST Action EpiLipidNET, a network of over 390 researchers interested in lipid biology, lipidomics and lipid modifications!

However, it is difficult to study lipid modifications without knowing what happens to lipids themselves. So, we had to extend our research even further to lipidomics! Over last year’s Maria’s group established several high-throughput LC-MS workflows based on the application of different LC types (RP and HILIC) coupled on-line to MS detection for identification and quantification of lipids. Last few years we focused especially on setting up a robust and high-throughput methods for in-depth identification and (semi)absolute quantification of lipids in animal and human tissues (e.g. white adipose tissue – see our AdipoAtlas ( DOI: 10.1016/j.xcrm.2021.100407) and Human Aortic Valve Atlas is coming up!), and blood plasma samples ( DOI: 10.1007/s00216-020-02576-x; DOI: 10.1016/j.chemphyslip.2019.03.006).

High-throughput LC-MS/MS generates a lot of data! When we started to work with lipids, there were almost no computational tools out there to deal with lipidomics LC-MS/MS datasets. After a year of manually identifying lipids from tandem spectra, Zhixu Ni got finally tired and decided to change the focus of his research from wet lab experiments to designing computational solutions for high-throughput processing of lipidomics and epilipidomics datasets. That resulted in creation of LipidHunter, LPPtiger, LipidLynxX and even LipidJaguar (coming soon!) – our pride of Big Cats to hunts in the dark forest of lipidomics data 😊( read more).

Having in our hands all the technologies and tools, developed over last 10 years in Maria’s lab by talented and motivated PostDocs, PhD, Master and Bachelor students, we are confident that LMAI team can tackle the most complicated questions on the role of lipids in stress responses in biological systems!