University of Amsterdam
Science Park 904
Dr. Gertjan Kramer
As our name implies we apply mass spectrometry in a biological context. We are a research group and the Mass Spectrometry Research Core Facility of the Swammerdam Institute for Life Sciences of the University of Amsterdam. We apply mass spectrometry to a variety of biological questions from within the institute and our main focus areas are proteomics (bottum-up) and metabolomics (untargeted, LC-MS based).
We cover the large part of bottom up proteomics applications and also some limited intact protein analysis.
- Quantitative Proteomics (Label-Free, SILAC/15N metabolic, Isobaric chemical labelling).
- Proteome Wide Translation and Degradation rates (Pulsed SILAC/TMT, Pulsed SILAC-AHA).
- Deep Phosphoproteome analysis.
- Protein Analytics: sequence confirmation, ptm-mapping, holo-mass determination.
- Protein interactions: CO-IP, CHIP-SICAP, IP-MS, Thermal Proteome Profiling.
- Low sample input proteomics for rare cells or small tissue sections.
As mass spectrometrists we routinely measure small molecules, our metabolomics focus is untargeted quantitative metabolomics.
- Untargeted metabolomic profiling of Polar and Apolar metabolites.
- Targeted metabolomic profiling of large metabolite sets.
- Low sample input metabolomics.
- Biodiversity & ecology
- Biomedical & health
- Agri & Food
- Industrial biotech
- Untargeted LCMS based Metabolomics Analysis.
- Proteomics and Metabolomics Data Processing.
- Advanced protocols for low input sample preparation (TMT, MBR).
- Chemical Biology Expertise in Proteomics (Click Chemistry, AHA-Pulse labelling).
- Microbiology (focus on spore proteomics)
- Green Life Sciences
- Cell and Systems Biology
Expertise and Track Record
43500985050 Unraveling on- and off-targets of the PPAR-delta ligands in microglial cells by thermal shift proteomics with C. Yi (Amsterdam UMC, locatie AMC).
We are experienced mass spectrometrists operating state of the art equipment, as such we cover an important part of proteomics and metabolomics sample analysis as do others. What sets us apart, are some unique applications we have developed over the years.
1) Chemical Biology: AHA-pulse labelling to quantify proteome wide protein synthesis rates.
2) Bacterial spore proteomics for a variety of food spoiling and medically relevant organisms.
3) High sensitivity measurements of low input samples: i.e. from rare cells or small tissue sections.
4) Protein-Protein and Protein-Metabolite/Compound interaction studies.
- PH2: a kinase controlling vacuolar acidification in plant cells. (NWO-ALW, F Quattrocchio 2017-2020) Here we deliver phosphoproteomics and subcellular proteomics to unravel vacuolar acidification in Petunia.
- The molecular basis for Endospore Heterogeneity. (NWO-ALW S. Brul 2017-2020) We provide our signature spore proteomics approaches to unravel bacterial spore heterogeneity.
We have participated in a large number of cross technology projects over the years. Most often this involves integrating a variety of ‘omics’ data to answer a research question or combining with other techniques as follow up from a proteomics/metabolomics screen.
A number of publications of integrative projects are listed in the references below, we always provided either protein/proteomics or metabolite/metabolomics data to a study.
- 1. Cooke A, Schwarzl T, Huppertz I, Kramer G, Mantas P, Alleaume AM, Huber W, Krijgsveld J, Hentze MW. The RNA-Binding Protein YBX3 Controls Amino Acid Levels by Regulating SLC mRNA Abundance. 2019 Cell Rep.
- 2. Pannekoek Y, Huis in ‘t Veld RA, Schipper K, Bovenkerk S, Kramer G, Brouwer MC, van de Beek D, Speijer D, van der Ende A. Neisseria meningitidis Uses Sibling Small Regulatory RNAs To Switch from Cataplerotic to Anaplerotic Metabolism. 2017 MBio
- 3. Kramer G, Wegdam W, Donker-Koopman W, Ottenhof R, Gaspar P, Verhoek M, Nelson J, Gabriel T, Kallemeijn W, Boot RG, Laman JD, Vissers PC, Cox T, Pavlova E, Moran MT, Aerts JMFG, van Eijk M. Elevation of glycoprotein nonmetastatic melanoma protein B (gpNMB) in type 1 Gaucher disease patients and mouse models. 2016 FEBS open bio
- 4. S. Andreas Angermayr, Pascal van Alphen, Dicle Hasdemir, Kramer G, Muzamal Iqbal, Wilmar van Grondelle, Huub C. Hoefsloot, Young Hae Choi and Klaas J. Hellingwerf Culturing of Synechocystis sp. PCC6803 with N2/CO2 in a diel regime shows multi-phase glycogen dynamics and low maintenance costs. 2016 Appl Environ. Micr.
- 5. Jiang L, Brackeva B, Ling Z, Kramer G, Aerts JM, Schuit F, Keymeulen B, Pipeleers D, Gorus F, Martens GA. Potential of Protein Phosphatase Inhibitor 1 as Biomarker of pancreatic beta cell injury in vitro and in vivo. Diabetes. 2013 Apr 4
- 6. McLoughlin F, Arisz SA, Dekker HL, Kramer G, de Koster CG, Haring MA, Munnik T, Testerink C. Identification of novel candidate phosphatidic acid-binding proteins involved in the salt-stress response of Arabidopsis thaliana roots. Biochem J. 2013 Mar 15;450(3):573-8
- 7. Witte MD, Kallemeijn WW, Aten J, Li KY, Strijland A, Donker-Koopman WE, van den Nieuwendijk AM, Bleijlevens B, Kramer G, Florea BI, Hooibrink B, Hollak CE, Ottenhoff R, Boot RG, van der Marel GA, Overkleeft HS and Aerts JM: Ultrasensitive in situ visualization of active glucocerebrosidase molecules. Nat Chem Biol 6: 907-13, 2010.
- 8. Plug T, Kramer G, Meijers JC. A role for arginine-12 in thrombin-thrombomodulin-mediated activation of thrombin-activatable fibrinolysis inhibitor. 2014 J Thromb Haemost.
- 9. Bekker M, Kramer G, Hartog AF, Wagner MJ, de Koster CG, Hellingwerf KJ and de Mattos MJ: Changes in the redox state and composition of the quinone pool of Escherichia coli during aerobic batch-culture growth. Microbiology 153: 1974-80, 2007.
- 10. Mirzaian M, Wisse P, Ferraz MJ, Gold H, Donker-Koopman WE, Verhoek M, Overkleeft HS, Boot RG, Kramer G, Dekker N, Aerts JM. Mass spectrometric quantification of glucosylsphingosine in plasma and urine of type 1 Gaucher patients using an isotope standard. 2015 Blood Cells Mol. Dis.
- Dedicated Postdocs: 1
- Dedicated technicians: 2
- Labmanager: 0.5
- Biostatistician: 0.5
- PhD students: 3
- 1x LCMS: timsTOF-pro Bruker
- 1x LCMS: Amazon speed with ETD Bruker
- 1x LCMS: LTQ-Orbitrap Thermo
- 1x LCMS: ApexQ FTICR Bruker
- 2x Fractionation LC Ultimate3000
- 2x Fractionation LC Ultimate
- 4x server (36 cores, 128GB RAM, running: Maxquant, MASCOTserver+distiller, PEAKSX, Metaboscape, R)
- 40 TB of fully mirrored active data storage, with long term archiving to Tape.
ProteomeXchange, Metabolights, Massive