Quantitative Proteomics/Mass Spectrometry/Proteogenomics

Boris Macek

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  • Diploma in Molecular Biology 1999, University of Zagreb
  • PhD work 1999-2003 at the Institute for Medical Physics and Biophysics, University of Münster
  • Postdoctoral training at the University of Southern Denmark (Odense) and Max Planck Institute for Biochemistry (Martinsried)
  • Professor at the University of Tübingen since 2008

Research Interest

Current experimental workflows in proteomics, based on biochemical proteome pre-fractionation, high accuracy MS and downstream bioinformatics are capable of reliably identifying and quantifying expression levels of several thousand proteins in a single experiment, approaching the depth of message-based assays (transcriptome) and reaching the analytical capacity to completely map and quantify the smaller proteomes, such as that of bacteria and yeasts. We have developed several approaches based on stable isotope labeling to perform comprehensive studies of proteome, phosphoproteome and acetylome dynamics in model microorganisms such as B. subtilis, E. coli and S. pombe (1-3). We are currently applying these approaches to study bacterial persistence, one of the major mechanisms of multidrug tolerance (4). In course of this project, we have for the first time applied “dynamic stable isotope labeling by amino acids in cell culture (SILAC)” for measurements of protein turnover in bacterial persister cells, an approach that can be easily adapted for similar studies in senescent cancer cells.

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Workflow in a typical proteomics experiment. Proteins are extracted from a tissue or cell line and digested by a protease into peptides. The resulting peptide mixtures are separated and analyzed by mass spectrometry; peptide masses are recorded in a "full scan" or "MS" spectrum; peptide ions are fragmented and the fragment ions are recorded in an "MS/MS" spectrum. Both levels of information are used in protein database search and peptide identification.

Available PhD Projects

Project Title: Proteogenomics and phosphoproteomics of bacterial pathogens

Objectives: To perform in-depth proteome and phosphoproteome analysis of several prominent bacterial pathogens and develop adapted analytical procedures. To use genomic sequences of project-relevant pathogens to call variants and create six-frame-translation (SFT) protein databases. To use pathogen-specific six-frame translation databases to detect novel peptides and map them onto corresponding genome regions to detect novel ORFs and validate them using RT-PCR.

Approach and Expected Results: Shotgun proteomics based on high resolution and high accuracy Orbitrap mass spectrometry will be used for large-scale analysis of protein expression and post-translational modifications (PTMs). We will develop and apply protocols to provide a comprehensive resource of the proteome and phosphoproteome pathogen strains under various growth conditions. We will use the obtained datasets to reconstruct networks of protein kinases, protein phosphatases and their substrates (with DTU) and to correlate evolutionary age of proteins with their expression and PTMs using genomic phylostratigraphy (with IRB). Finally, we will use genomics data provided by Sahlgrenska University Hospital to re-annotate ORFs. Our results will provide the most extensive overview of the proteome and PTM dynamics for the analysed pathogens to date, with insights into functional and evolutionary aspects of their genomes and signal transduction networks. Our data will inform biological follow-up experiments of other consortium partners (DTU, CNRS) working on molecular characterization of regulatory pathways, as well as antibiotic development

Selected Reading

1) Macek B, Forchhammer K, Hardouin J, Weber-Ban E, Grangeasse C, Mijakovic I. (2019) Protein post-translational modifications in bacteria. Nat Rev Microbiol. 17(11):651–664

2) Ravikumar V, Nalpas NC, Anselm V, Krug K, Lenuzzi M, Šestak MS, Domazet-Lošo T, Mijakovic I, Macek B. (2018) In-depth analysis of Bacillus subtilis proteome identifies new ORFs and traces the evolutionary history of modified proteins. Sci Reports 8(1):17246

3) Carpy A, Krug K, Graf S, Koch A, Popic S, Hauf S, Macek B. (2014) Absolute proteome and phosphoproteome dynamics during the cell cycle of fission yeast. Mol Cell Proteomics 13(8):1925-36

4) Semanjski M, Germain E, Bratl K, Kiessling A, Gerdes K, Macek B. (2018) The kinases HipA and HipA7 phosphorylate different substrate pools in Escherichia coli to promote multidrug tolerance. Science Signaling 11, eaat5750