September 1, 2007 (Vol. 27, No. 15)
LEAP Technology Selects for Low-abundance Proteins Making Biomarker Search Easier
Proteomics holds the promise of new diagnostic and therapeutic applications to improve patient care in various areas such as cancer, cardiovascular disease, autoimmune diseases, and neurological disorders. Currently over 50% of the biotech and pharmaceutical markets are generated from products that are either derived from ligands or through interaction with receptors. Ligands are also strong candidates for biomarkers due to their physiological importance and low abundance.
The discovery of new biomarkers is hampered by limitations in current technology to detect and quantify low-abundance proteins in the presence of high-abundance proteins in complex biological samples. For example, in serum low-abundance proteins such as growth factors and cytokines are present in one millionth (1/106) to one trillionth (1/1010) of the abundant proteins such as albumin.
Current proteomic techniques are limited to detecting proteins within a dynamic range of 104 fold and to around 3,000 distinct polypeptides. Therefore, low-abundance proteins cannot be detected for further analysis without removal of abundant proteins to decrease both dynamic concentration range and complexity (1/105–1/106 distinct polypeptides).
Standard methods to deplete a sample of major high-abundance proteins can improve the relative concentration of low- abundance proteins from 10- to 100-fold but this is still not adequate for detecting low abundance proteins. In addition, there is the risk of losing low-abundance proteins that remain bound to high-abundance proteins.
The ProSpectrum Library™-based method enriches low-abundance proteins by decreasing the concentrations of the high-abundance proteins. However the complexity within the compressed dynamic range is increased as the result of enrichment. It posts new challenges for detection and quantification of low-abundance proteins. The artificial nature of the library further challenges effectiveness of the method for enriching desired biomarkers.
Figure 1
Ligand Enrichment and Profiling
LEAP Biosciences (www.leapbio.com) developed a sample-preparation technology by which low-abundance and biologically important proteins such as ligands can be selectively enriched before being subjected to conventional proteomics analysis. LEAP technology utilizes cells, organelles, or other receptor-bearing biological surfaces as receptor carriers to capture ligands present in a biological sample such as serum and urine for ligand enrichment (Figure 1).
During the binding step, ligand molecules bind to the receptor carrier while unrelated molecules remain free in the sample. After washing to get rid of non-specific binding, the ligands bound to the receptor carriers are eluted off from the receptor carriers. The eluted ligands are then subjected to proteomic profiling such as 1-D or 2-D electrophoresis or liquid chromatography.
The ligand molecules can be labeled to facilitate detection and analysis either before or after enrichment. Labeling before enrichment allows specific detection of sample-derived ligands even with the presence of nonsample derived molecules that may be introduced during blocking of receptor carriers before interacting with sample or shedding from the receptor carrier.
Using EGF (ligand) and Hela cells (receptor carrier) as a model system, the degree of enrichment using this approach has been demonstrated to be 375-fold with 73% recovery rate from a human serum sample.
Selective enrichment and differential ligand profiling is demonstrated using fluorescence 2-D difference gel electrophoresis (DIGE; Figure 2A). In this experiment, ligand proteins were first enriched from plasma samples of two individuals (sample #1 and sample #2) separately by LEAP method using Hela cells as the receptor carrier.
Enriched ligand sample from Sample #1 was then labeled with the fluorescent dye Cy3 (green) and enriched ligand sample from Sample #2 was labeled with another dye Cy5 (red). The two labeled samples were combined in equal amount and then subject to 2-D gel electrophoresis.
While most proteins were expressed in a similar level between these two samples as shown in yellow spots in Figure 2A, a small number of proteins were differentially expressed shown in green and red spots within circles in the close-up image (Figure 2C). When compared to Figure 2B, the DIGE profile of raw serum and plasma confirms that the LEAP method has eliminated a large number of high-abundance proteins and selectively enriched the low molecular weight proteins that are characteristic of ligand molecules.
Figure 2
Differential Protein Profiling
LEAP technology was further explored for its application on differential protein profiling for biomarker discovery using patient samples. Serum proteins from four multiple myeloma patients and a normal control were first labeled with biotin before subjecting them to a LEAP ligand-enrichment method using NIH3T3 cells as the receptor carrier.
The enriched ligands were then run on 1-D SDS PAGE followed by a Western blot. The biotin-labeled ligand proteins were detected by HRP-conjugated streptavidin. The profiles of the multiple myeloma patients share an elevated level of a protein migrated at position X, suggesting protein X as a biomarker candidate for multiple myeloma (Figure 3).
Advantages of the LEAP technology include selective enrichment of biologically functional (based on binding) ligands specific to desired targets; simple elimination of unwanted proteins; enriched samples that can be subsequently analyzed using conventional methods—2-D DIGE, Western blotting, LC/MS, etc.; the ability to profile both known and unknown ligands; and applicability to any ligand/receptor association and interaction of any two interacting molecules that are polypeptides or nonpolypeptides.
LEAP technology has broad applications in the discovery of novel ligands for diagnostic and therapeutic purposes, assessment of therapeutic potential in nonclinical studies, and the monitoring of patient response to a specific treatment regimen.
Stem cell research is currently in need of accurate markers to distinguish stem cells of different origin such as embryonic stem cells and adult stem cells. LEAP technology can provide a solution for accurate typing of stem cells of different origins by generating a characteristic ligand profile for stem cells of each origin using a universal ligand mixture. Since each derived ligand profile reflects the receptor profile of the corresponding stem cells, the ligand profile should serve as a fingerprint for each type of stem cell.
Biomarkers for plaque rupture would be useful in predicting heart attack and stroke. Plaque rupture is initiated by the break of the fibrous cap, which is composed of smooth muscle cells (SMC). LEAP technology can be applied to discover biomarkers associated with plaque rupture by comparing ligand profiles of SMC from the sera of the same patient collected before and after heart attack.
LEAP technology can also be applied to identify satiety molecules through differential protein profiling of ligands enriched from sera of the same individual collected at hungry and full states using hypothalamus neurons as the receptor carrier.
To date, there are more than 100 forms of arthritis currently affecting one in five adults in the U.S. The characterization of ligand profiles of synovial fluid from patients with various types of arthritis may provide biologists information for designing new therapeutics for arthritis and also with biomarkers for accurate diagnosis.
LEAP technology can also be applied to discover unidentified ligands for orphan receptors through differential protein profiling of ligands enriched from a ligand-containing mixture using both orphan receptor null cells and orphan receptor expressing cells derived from the null cells.
The simplicity, efficiency, and biological relevance of the LEAP technology should improve the odds for biomarker discovery in diagnostic, therapeutic, and basic research areas. First-generation products are currently in beta testing and will soon be available to all researchers in the biomedical community.
Figure 3
