In-depth proteomics




Proteomics is a field aiming for systems level analysis of proteins and by this generate new knowledge in biology. As a field, proteomics is in an exciting rapid development propelled by technology developments leading to new methods and improved instrumentation. In order to obtain good proteome coverage in our quantitative proteomics experiments on human samples, we develop and use High Resolution Isoelectric Focusing (HiRIEF) as pre-fractionation method before the LC-MS/MS analysis (Branca R., et al., Nature Methods, 2014). This method fractionates peptides based on their isoelectric point (pI) before LC-MS/MS analysis. There are several benefits of employing peptide pI-based fractionation in proteomics. First, it provides outstanding peptide resolving power, thereby increasing the number of identified proteins and peptides, which is beneficial when aiming for improved quantitative accuracy or for example aiming to find protein variants by mass spectrometry (Zhu Y, Mol. Cell. Prot.  2013). Secondly, the peptide pI can be predicted, which allows for a rational pI-based fractionation of databases used for peptide spectral matching (Branca R., et al., Nature Methods, 2014) or predictable pre-fractionation for targeted proteomics.

Using the HiRIEF LC-MS/MS method, we can also increase the overlapping identification and quantification between samples in larger clinical proteomics profiling experiments. Today, we routinely identify and quantify between 8000 to 14 000 proteins in human samples; the number depends on the sample type.

Selected publications using HiRIEF LC-MS(MS method:

  1. Roberts TC, Johansson HJ, McClorey G, Godfrey C, Blomberg KE, Coursindel T, Gait MJ, Smith CI, Lehtiö J, El Andaloussi S, Wood MJ. Multi-level omics analysis in a murine model of dystrophin loss and therapeutic restoration. Hum Mol Genet. 2015 Dec 1;24(23):6756-68.
  2. Zhu Y., Hultin-Rosenberg L., Forshed J., Branca R.M., Orre L.M., Lehtiö J., SpliceVista, a tool for splice variant identification and visualization in shotgun proteomics data. Mol Cell. Prot. 2014 Jun;13(6):1552-62.
  3. Mundt F, Johansson H, Forshed J, Arslan S, Metintas M, Dobra K, Lehtiö J, Hjerpe A. Proteome screening of pleural effusions identifies galectin 1 as a diagnostic biomarker and highlights several prognostic biomarkers for malignant mesothelioma. Mol Cell Proteomics. 2014 Mar;13(3):701-15
  4. Kjellin H, Johansson H, Höög A, Lehtiö J, Jakobsson PJ, Kjellman M. Differentially expressed proteins in malignant and benign adrenocortical tumors. PLoS One 2014 Feb 3;9(2):e87951
  5. Branca R.M., Orre L-M., Johansson H.J., Granholm V., Huss M., Pérez-Bercoff Å., Forshed J., Käll L.,  Lehtiö J. HiRIEF LC-MS enables deep proteome coverage and unbiased proteogenomics. Nature Methods, 2014 Jan;11(1):59-62. Epub 2013 Nov 17.
  6. Zirath H.,Frenzel A., Oliynyk G., Segerström L., Westermark U.K., Larsson K., Munksgaard Persson M.,Hultenby K., Lehtiö J., Einvik C.,Påhlman S.,Kogner P., Jakobsson P.J., Arsenian Henriksson M., MYC-Inhibition Induces Metabolic Changes Leading to Accumulation of Lipid Droplets in Tumor Cells. Proc Natl Acad Sci U S A., 2013 Jun 18;110(25):10258-63.