What is proteomics?
Proteomics is a general name for protein research aiming to study as many proteins as possible simultaneously. In proteomics research several techniques are used to detect, visualize and measure hundreds or even thousands of proteins. These techniques include gel electrophoresis (such as two dimensional gel electrophoresis) and mass spectrometry methods. At present there is no single technology capable of detecting all proteins or protein concentration levels in complex biological mixtures such as cell lysate or plasma samples. However, there are several powerful complementary technologies which enable high resolution analysis of complex protein mixtures. Proteomics research is currently dominated by several different technical approaches:
2DE : Gel electrophoresis based proteomics, such as two dimensional electrophoresis (2DE).
MS/MS proteomics : Chromatographic or other protein separation methods coupled to mass spectrometry detection, such as liquid chromatography coupled with mass spectrometry (LC-MS/MS).
Chip based proteomics : Chip based proteomics such as SELDI-TOF-MS protein chip arrays (Surface Enhanced Laser Desorption/Ionization Time of Flight Mass Spectrometry) or antibody arrays.
Affinity proteomics: Large scale proteome studies using affinity specific reagents such as antibodies (tissue micro array or HTP-immuno capture studies).
Selecting a suitable proteomics method for a project depends on the research question at issue, available starting material, cost etc. A short summary of the proteomics technologies used at KBC can be seen in the table below:
| Proteomics method | Resolution | Troughput | Sensativity | Intact protein/ peptides | Comments |
| 2DE 2-dimensional gel electrophoresis | +++ | + | ++ | Intact proteins | - Sensitivity limited by labeling for visualization |
| MS/MS proteomics (isotopic labeling or label free quantification | ++++ | + | +++ | Peptides | + detects all types of proteins (mambrane proteins etc.) - Extensive fractionation and low throughput |
| SELDI-TOF-MS Protein chip based proteomics | ++ | +++ | ++ | Intact proteins | + intact protein profiling with minimal sample treatment - Laborious protein ID workflow |
| Tissue micro array (TMA) HTP imunolohistochemistry | Validation method not discovery proteomics | +++ | + | Tissue | - Need for antibodies, semi quantitive at best |
When utilizing proteomics techniques on clinical material (serum, plasma, tissue lysates etc.), one of the key aspects is to find disease related changes in the proteome. Hence, the ability to detect protein concentration changes in complex biological samples is crucial. Also, the ability to work on a relatively small amount of samples is important since the availability of patient material is limited.
Other important aspects in proteomics research are data handling and interpretation: bioinformatics and biostatistics. Adequate handling and analysis of complex and information rich data generated by gel and mass spectrometry analyses, as well as long lists of potentially important detected proteins, is a big challenge in this field of research. Further, the development of high through put validation methods is important to asses the clinical relevance of found proteome changes.
Why the samples for proteomics should be handled with extra care?
In proteomics we do not know which or what type of proteins will be found and therefore the aim is to keep all proteins intact and treat the samples with presumption that some proteins are very labile. Cells and extra cellular fluids like plasma and serum contain lots of proteases (enzymes that break down proteins rapidly). Handling proteomics samples therefore requires a fast workflow so that time from blood collection or tissue removal to freezing of the samples is as short as possible. Another important point to consider is the reproducibility of sample handling. In proteomics, hundreds of different proteins are measured simultaneously and the results are evaluated statistically. If the sample preparation introduces a large experimental variation, the risk of false discoveries increases as well as the risk of missing clinically potential biomarkers. This is the reason why the sample collection and handling methods has to be as standardized as possible when collecting samples for proteomics studies.
