A group of investigators under Dr. Matthias Mann at Max Planck Institute of Biochemistry in Martinsried, Germany is working on an interesting quantitative proteomics technology that might offer a new way to analyze cell proteins in a range of disorders, such as cancer and autoimmune diseases. Called super-SILAC (stable-isotope labeling by amino acids in cell culture), the method generates thousands of isotopically labeled peptides in unique amounts to serve as “internal standards for mass spectrometry-based analysis.”
The Max Planck researchers break down proteins into smaller pieces called peptides and use a so-called mass spectrometer to ionise them and sort them according to their masses in an electrical field. Based on the distribution and strength of the peptide signals and their fragments in the measuring instruments, the researchers can reconstruct the proteins and even their quantities.
To be able to do this, however, the scientists must first know what they are looking for. To date, only relatively few proteins are known that are indicative of various cancer types. This is where Tami Geiger comes in: over the past three years, the young Israeli scientist has been setting up a protein database of key cancer cell lines. She uses this library as a reference in comparing human tissue samples from patients. To compare the samples of a healthy person with those of a cancer patient, for example, she labels proteins with specific carbon or nitrogen isotopes which are heavier than naturally occurring atoms. On the basis of the signal strength of the marked and unmarked peptides in the mass spectrometer, Tami Geiger can recognise whether a protein is formed more strongly or more weakly within cancer cells.