Marina Hrouda

Sample Handling and Registration

• Retrieved patient samples (whole blood, serum, and urine) from the reception area and registered them into the system.
• Verified that all required samples were available for testing.

Sample Preparation and Analysis

• Used a TECAN pipetting robot to prepare patient serum samples for HPLC-MS analysis measuring concentrations of antidepressants, antipsychotics, and antiarrhythmics to ensure they were within the therapeutic range.
• For vitamins (B1 and B2 in whole blood; A/E and C in serum) and other parameters (catecholamines and metanephrines in urine), samples were manually prepared followed by analysis using HPLC with fluorescence, UV, and electrochemical detection.

Data Interpretation and Quality Control

• Ensured that the results were accurate and within the expected clinical reference ranges.
• Performed regular quality control checks and maintained laboratory equipment to ensure consistency and reliability of results.

HPLC Maintenance

• Responsible for the regular maintenance, calibration, and troubleshooting of HPLC systems to ensure optimal performance.

Proteomics and Lipidomics

• Performed bottom-up proteomics with a HeLa protein digest standard with the aim to increase the number of detected proteins by optimizing chromatographic parameters and selecting the best column for the analysis.
• Performed lipidomics with lung cancer cell extract starting with Folch extraction to isolate the lipids and tested different chromatographic conditions and columns to improve lipid detection.
• Evaluated and compared the performance of various chromatography columns (packed, monolithic, and µPAC) for both proteomics and lipidomics.
• Optimized HPLC parameters (flow rate, loading flow, loading volume and gradient) and mass spectrometer operating settings (e.g., dry gas flow) to enhance sensitivity and improve the detection of proteins and lipids.

Data Analysis

• Used PEAKS software for protein identification and quantification, and MetaboScape for lipid identification.

Activity-Based Proteomics and Mouse Tissue Analysis

• Conducted activity-based proteomics to study enzymes involved in the breakdown of triacylglycerols (TAGs) in various tissues, including brain, white and brown adipose tissue and heart.
• Analyzed tissue samples from mice under different feeding conditions (fed, fasted, refed) provided by the Medical University of Graz (SFB Lipid hydrolysis-FWF F73). Tissues were pre-treated with an activity-based probe by colleagues to target the enzyme class of serine hydrolases prior to analysis.
• Performed labor-intensive sample preparation and HPLC-MS analysis to identify and quantify proteins involved in lipid metabolism.
• Sample preparation included protein extraction followed by protein quantification using a Bradford assay, reduction of disulfide bonds, alkylation of cysteine residues, linker addition, affinity capture, proteolytic digestion with trypsin, and a final desalting step before performing HPLC-MS analysis.

Protein Identification and Quantification

• Used the softwares MaxQuant and Perseus for protein identification and quantification.
• Created protein tissue maps and analyzed enzyme activity to study lipid metabolism changes under different dietary conditions.