Biomolecules from complex samples can be separated by applying various chromatographic techniques like ion exchange, affinity or reverse phase (RP). To achieve a reversible interaction between an analyte and the stationary phase different properties like size, charge or hydrophobicity can be utilized. In proteomics RP-HPLC based separation procedures are used as a standard feature. Thereby, the peptides to be examined are pump together with the solvent through a column that contains the stationary phase. Fractionated peptides are subsequently analyzed with mass spectrometry. In order to obtain better proteome coverage and to facilitate detection of low abundant proteins enhancement of separation performance is an important issue for our studies.
Mass spectrometry is a technique to determine mass-to-charge ratios (m/z) of ions. All MS instruments have the same basic principle: ion generation, ion separation and ion detection. Ion generation is depending on the employed ion source. The most frequently used ionization methods in proteomics are Elektrospray-Ionisation (ESI) and Matrix-assisted Laser-Desorption/Ionisation (MALDI). Using ESI-MS proteins/peptides are atomized at the end of a capillary on which a voltage is applied. Resulting ions are move from the solvent into the gas phase (desolvatisation). Ion generation using MALDI is based on co-crystallization of the analyte with a matrix. The matrix molecules are irritated with a pulsed laser. Thereby, energy is transferred from the matrix to the analyte molecules within the crystal which are desorbed and ionized. Furthermore, protonation of the analyte takes place through matrix molecules. After generation of the ions they are focused by electric lenses and enter the analyzer. Several mass analyzer can be used like quadrupol, time-of-flight or ion traps. Often two similar or varying (hybrid system) analyzer are combined. Finally, the prior separated ions are recorded with the detector. In addition to the m/z determination sequence analysis of peptides are performed via MS in proteomics. Therefor so call MS/MS experiments are applied in which a peptide is defined/picked in a first MS scan. Subsequently, this peptide is fragmented in a collision cell leading to a break of the peptide bonds and fragment ions are generated which are detected with a second MS scan. Fragment ion information serves as basis for sequence determination of the precursor peptide, since the distances of consecutive fragment ions correlates to the mass of one amino acid.
In the field of proteomics mass spectrometry is employed for identification, characterization as well as for quantification of proteins and peptides from complex samples.
MALDI mass spectrometry imaging (MALDI-MSI)
Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is a fairly new and powerful technique within the field of proteomics and biomarker research combining mass spectrometry with microscopy. The method enables the analysis of different biological material such as proteins, lipids or small molecules. Preferred materials are thin tissue sections that are prepared on glass slides, if necessary pretreated, covered with matrix and subsequently measured. During measurement moves a laser beam over a predefined area of the sample producing an ordered array of mass spectra that are afterwards visualized as color coded ion images. Thus every single m/z value contains the spatial arrangement of a specific molecule in the measured sample. Main difference to other MS techniques is that the cellular and molecular integrity of the sample are maintained. After measurement, the matrix is removed and the tissue histologically stained and scanned. The high-resolution microscope image of the section can be co-localized with the measured MS image, thus combining spatially resolved histological information with the spatially resolved MS information. MSI has been successfully applied in studies to discover differences between tumor and healthy tissue.
One-dimensional polyacrylamide gel electrophoresis (1D-PAGE)
Simple pre-separation of complex protein mixtures before mass spectrometric or for western blot analysis is normally done with 1D-PAGE. 1D-PAGE according to Lämmli, with sodium dodecyl sulfate (SDS) as negative-charge detergent (7) is widely used for the separation of proteins according to their electrophoretic mobility. Due to SDS binding, the proteins are denaturized showing identical charge per unit protein mass, which after the application of an electric field results in separation by size. Afterwards, proteins can be visualized by staining methods with e.g. silver or Coomassie.
Two-Dimensional Protein Separation: Classical 2D-PAGE and 2D-DIGE
Two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) is based on the combination of two orthogonal separation techniques. In the first dimension, proteins are separated by their isoelectric point, a technique known as isoelectric focusing (IEF). There are two important variants of IEF, which are carrier-ampholine (CA)-based IEF and immobilized pH gradient (IPG)-based IEF. In the second dimension, proteins are further separated by their electrophoretic mobility using SDS-PAGE. Finally, proteins can be visualized with e.g. Coomassie or silver staining. Afterwards, gels can be compared by image analysis and protein spots relatively quantified.
Two-Dimensional Protein Separation: 2D-DIGE
The introduction of fluorescent reagents for protein labeling (difference-in-gel-electrophoresis or DIGE) has brought substantial improvement in the field of 2D-PAGE. It provides multiplexing of up to three samples in one gel, higher sensitivity compared to normal protein staining methods and a higher linear range for quantitation.
Laser Capture Microdissection
Laser capture microdissection (LCM) or laser microdissection (LMD), which enables the isolation of defined single cells or cell clusters . Under this approach, the tissue of interest is sectioned, placed onto a glass slide and visualized via microscopy. The cells or regions of interest are collected in a tube. Hence, DNA, RNA and proteins that are characteristic of these subpopulations of cells can be analyzed through PCR, western blot or mass spectrometry .
Protein microarrays and Peptide microarrays
Protein microarrays and peptide microarrays are one of the leading high-throughput tools for biomarker detection and drug development. They can contain up to 20,000 molecules (proteins e.g. antibodies, peptides etc.), therefore they allow processing of numerous samples in a short time. In principle, protein microarrays can be incubated with a sample solution of interest containing potential interacting proteins/peptides. Interacting proteins that have already been identified can be detected using labeled antibodies. If new interaction partners are found, it is necessary to apply additional analytic tools, e.g. mass spectrometry.
Antigen–antibody interactions are of special interest in several autoimmune and progressive diseases. To discover more about the binding circumstances, protein–protein and protein–peptide interactions can be examined which are a major focus in studies of disease progression and signal pathway identification. Furthermore, peptide arrays can also be used to identify the epitopes of a protein, which is highly beneficial for drug discovery and therapy development.
The Luminex® technology is a fluidic microarrays system, which allows the simultaneous analysis of up to 100 different molecules of interest in one well of a microtiter plate. Luminex® is of special interest for screening of a defined panel of candidates in a bigger cohort.
Amino Acid analysis
Amino acid analysis (AAA) allows the determination of the concentration of amio acids in a defined sample and therefore the determination of the protein or peptide concentration. AAA can be subdivided in three steps: In the first step, the samples are chemical hydrolyzed, in a second step the single amino acids are derivatized with a fluorophore in a third step the fluorophore coupled amino acids are separated with reversed-phase HPLC. The quantitative analysis is done with an internal amino acid standard.
Cell Culture Models
The term cell culture refers to the culturing of eukaryotic cells outside of their natural environment. In primary cell culture the cells are isolated from a tissue or an organ and subsequently cultured in growth media which contains essential nutrients. Dependent on the cultured cell types the isolation may require complicated protocols for successful isolation and culture time is generally limited by the life span of the isolated cells. In contrast, the culture of established immortal cell lines (cancer cell lines, immortalized cells, hybridoma cells) does not require such isolation steps and cells can principally be cultured without or with minor limitations regarding life span or cell numbers. Experiments using such cell lines can often be scaled according to the requirements of the researcher, reaching from multi well plates up to millions of cells.
Cell culture models have been used for decades to study the physiological and pathophysiological characteristics of cells (e.g. metabolism, cell signaling, differentiation, motility). In cell culture models the behavior of cells can be investigated under defined conditions. In the past, by usage of cell culture models enormous knowledge was achieved and could be successfully transferred to complex organisms. A wide range of cell culture assay has been established and can be used relatively easy. Another great advantage of cell culture is that cells can be genetically manipulated for example by knocking down expression of specific proteins or overexpressing proteins of interest. This allows investigation of the function of specific proteins and might allow the interpretation of their role in a respective disease. At the MPC we mainly focus on cell culture models of neural cells allowing the investigation of neurodegenerative diseases. Another focus is the analysis of liver cancer cell lines in order to reach conclusions on the corresponding malignant diseases.
In proteomics another big advantage of cell culture models is their usage of for method development. Many cell lines can be modulated using defined substances (e.g. activation using cytokines) and thereby proteome changes can be induced under controlled conditions. Analytical starting material is generally not limited which supports the establishment of new analytical workflows.
Molecular biological techniques belong to the highly important tools to study signal transduction pathways or protein-protein interactions. By the use of methods for classical cloning as well as PCR based methods like InFusion cloning we generate expression constructs, which are necessary for subsequent work like proteomic or protein-based assays. For example, we generate knockdown vectors, expression plasmids for constitutive or induced expression of wildtyp genes or deletion mutants. For microscopic methods we also clone vectors that combine expression of a gene of interest to a fluorescence marker like the green fluorescence protein. All of our generated constructs are subsequently validated by sequencing before they will be used for transfection or microinjection experiments in cell culture. Finally, we are also using quantitative methods like real-time PCR to determine the expression level of a certain gene in different model systems.
Bioinformatics / Biostatistics Analyses
As working group Bioinformatics / Biostatistics of the Medizinisches Proteom-Center we provide our own developed Proteomics software tools for users of different Bioinformatics and IT skills. Furthermore, we provide our expertise in cooperations regarding data standardization and conversion of data sets and result lists that are to be uploaded into public repositories or to be submitted to journals. We also provide our expertise and hardware in cooperations to allow researchers to perform computational and statistical analyses of Proteomics data using our tools or other tools developed in the Proteomics community.
Proteomics Software Tools:
• Proteomics Conversion Tool (ProCon): data format conversion for proteomics data
• Unique Peptide Finder (UPF): determination of unique peptides in protein databases
• Protein List Comparator (ProLiC): comparison of protein lists, considering protein sequence information or information about measured peptide sets
• Protein Array Analyzer (PAA): R package for biomarker discovery with protein microarrays
• FindPairs Module of the PeakQuant Software suite: automatic determination of protein abundance ratios and quality characteristics for 14N/15N labelling, SILAC, and iTRAQ data
• Statistical DIGE Analyzer (SDA): data processing and analysis for DIGE experiments
• Protein Inference Algorithms (PIA): protein inference (for protein ambiguities in bottom-up proteomics) supporting distinct search engines and protein inference algorithms
• CrossPlatformCommander (XPlatCom): data conversion, quality control, data comparison, text mining and statistical analyses for multi-OMICS workflows
Data Standardization and Conversion:
We offer our expertise regarding Proteomics XML-based data standards and ontologies:
• Data provision for manuscript publication and journal guidelines
• Data conversion
• Data upload
• CV maintenance as community service
Computational and Statistical Analysis of Proteomics Data:
• Bioinformatics Analysis of Proteomics data as cooperation
• Hardware sharing as cooperation (high-performance compute cluster, virtual servers, GPU array and Intel Xeon Phi)
• Statistical Analysis of high-throughput data as cooperation
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