School of Medicine

Proteomics Core


Simple Protein Identification

We use a Bottom-Up Proteomics approach to identify protein molecules. Samples can be derived from 1D SDS gels, 2D SDS gels, or Immuniprecipitation (IP) experiments. The protein(s) is then subjected to proteolytic digestion, and then mass spectrometry. When submitting samples for protein identification, it is helpful to know what organism is comes from and which post-translational modification (PTMs) might be present.

Discovery-Based Proteomics

Discovery-based, or Bottom-Up Proteomics is a Liquid Chromatography Mass Spectrometry (LCMS) approach to identifying as many protein components of a biological sample as possible. First proteins are harvested from cells, tissues or other biological material. This protein fraction is then subjected to proteolytic digestion, typically using trypsin. Peptides are then separated using one or more dimensions of liquid chromatography and the LC eluent is directly injected into a mass spectrometer using an electrospray ionization. MS1 or survey scans readily identify the tryptic peptide parent ions, and then MS2 scans utilize Collision Induced Dissociation (CID) to gather amino acid composition and sequence information about the parent ions. This information can be used to determine the original protein composition of the biological sample.

With advances to LCMS instrumentation and analysis techniques, Discovery-Based workflows can identify more proteins in more complex samples than ever before. Moreover, the techniques are generally foundational for more complex experiments. In addition, these techniques can be refined to garner additional information such as Post-Translational Modification (PTMs) which are important clues as to the involvement of protein and protein complexes in the biology of the cell. Ubiquitinoylation and phosphorylation are of particular interest because they are critical to pathways for signaling, activation, and often give insight into disease.

Quantitative Discovery-Based Proteomics

While Discovery-Based Proteomics is useful for assembling a thorough inventory of the protein components of a biological sample, Quantitative Discovery-Based Proteomics folds in the ability to determine the relative quantitation between biological samples among treatment groups. This furthers the understanding of the functions of individual proteins and their place in the complex biological system. There are generally three main approaches to achieving relative quantitation in Discovery-Based Proteomics:

  1. Label-Free Workflows

Label-free relative quantitation involves comparing the abundances of proteins in multiple samples without the use of isotopic labels.  Samples are run individually, then common chromatographic features are used to align the various runs with software. Signals corresponding to individual peptide ions are integrated over the LC time scale and compared between runs. Label-free analysis is a powerful and widely used technique for identifying and quantifying relative changes in complex protein samples. It can be applied to complex biomarker discovery and systems biology studies as well as to isolated proteins and protein complexes. Key benefits of label-free precursor-based quantitation include the fact that unlimited numbers of samples can be compared and that samples can be of any origin. However, this approach suffers from run-to-run variability as each sample is run independently form each other.

  1. SILAC Workflows

Stable isotope labeling with amino acids in cell culture (SILAC)-based quantitation is a powerful and widely used technique for identifying and quantifying relative changes in complex protein samples. It can be applied to complex biomarker discovery and systems biology studies as well as to isolated proteins and protein complexes. As its name implies, SILAC involves labeling protein samples in vivo with a heavy-isotope-labeled form of an amino acid. Inclusion of the labeled amino acid in cell or tissue culture media results in replacement of the natural light amino acid with the heavy form in newly synthesized proteins. Cells grown under differing experimental conditions (and in heavy or light media) can be mixed and all subsequent processing steps can be performed on the combined sample. This serves to greatly reduce sample handling variability, resulting in more accurate quantitation. Currently the number of samples that can be multiplexed is limited as there are a small number of heavy- and light-amino acid combinations.

  1. TMT Workflows

Isobaric chemical tags are a more universal alternative to SILAC. In a single analysis, they can be used to identify and quantify relative changes in complex protein samples across multiple experimental conditions. They can be used with a wide variety of samples including cells, tissues, and biological fluids. Isobaric chemical tags facilitate the simultaneous analysis of a large number of samples. Thermo Scientific Tandem Mass Tag (TMT) reagents are isobaric chemical tags consisting of an MS/MS reporter group, a spacer arm and a reactive group. Amine-reactive groups covalently bind to peptide N-termini or to lysine residues. Each tag fragments during MS/MS, producing unique reporter ions. Protein quantitation is accomplished by comparing the intensities of the reporter ions. At present, up to 16 samples can be analyzed at the same time.

Quantitative Targeted-Based Proteomics

Targeted Proteomics usually follows Discovery Proteomics, in that one is no longer asking the question “Which proteins are changing?”, but instead asking “How much are specific proteins changing?” While these measurements have traditionally been performed using Western Blotting, modern proteomic techniques have evolved to offer complementary quantitative performance. In fact, often many different targets can be monitored for quantitative differences at the same time, and over many samples. These experiments are called Parallel Reaction Monitoring (PRM). With the incorporation of standard, or heavy-labelled peptides, these experiments can achieve absolute quantitation.

Example References:

Label-Free: “The One Hour Yeast Proteome.” Molecular & Cellular Proteomics. Vol. 13, Issue 1. 1 Jan 2014.

SILAC: “Super-SILAC Allows Classification of Diffuse Large B-cell Lymphoma Subtypes by Their Protein Expression Profiles.” Molecular & Cellular Proteomics. Vol. 11, Issue 5. 1 May 2012.

TMT: “A comprehensive Xist interactome reveals cohesin repulsion and an RNA-directed chromosome conformation.” Science. Vol 349, Issue 6245. 17 July 2015.

Targeted: “What is targeted proteomics? A concise revision of targeted acquisition and targeted data analysis in mass spectrometry.” Proteomics 17, 17-18, 2017.

The Proteomics Core Facility is located in the Clinical Science Research Building room 331. For further information please contact Jiri Adamec, (