The development of high-throughput technology platforms for protein profiling and biomarker research has driven significant advances in the field of proteomics, allowing researchers to analyze several thousand proteins within a single study. Those wishing to undertake a proteomic study will be faced with a choice of which approach to consider. This article provides a brief overview of two popular tools available for proteomics research: antibody arrays and mass spectrometry (MS). Here we outline how the data outputs from the two methods can be quantitative, semi-quantitative, or qualitative, and further explain how they complement one another to enable increased proteome coverage. Ultimately, the approach you choose will be defined by the question you wish to answer.
Antibody arrays use antibodies immobilized on a solid substrate (e.g. a nitrocellulose membrane, glass slide, or beads) to capture defined protein targets from a sample. Binding is confirmed with labeled detection antibodies, generating a signal proportional to the amount of captured analyte. Protein identification is straightforward, using spot position in the case of antibody arrays or bead color for cytometric bead arrays (CBAs). A major advantage of these techniques is their ability to detect low abundance proteins by virtue of exquisite antibody sensitivity. Conversely, a protein can only be detected if a validated antibody is available and compatible with the array platform. The largest commercial antibody arrays contain as many as 2,000 antibodies in a single panel, yet combinations of smaller antibody arrays or CBAs can be used to maximize the number of analytes detected.
Liquid chromatography-mass spectrometry (LC-MS) is the most widely used MS format for proteomics studies. It requires that proteins are denatured, reduced, alkylated, and digested before the resulting peptides are separated and ionized; each charged peptide is then assigned to a protein based on its mass and fragmentation. Depending on the upstream sample preparation and matrix, more than 5,000 proteins can be identified in a single MS analysis. A limitation of MS is that highly abundant proteins can mask the detection of low abundance proteins by ion suppression, thus depletion of high abundance proteins or enrichment of specific low abundance proteins may be necessary to detect low abundance targets. However, MS is “hypothesis-free” because it does not rely on antibodies for detection and therefore makes no upfront assumptions regarding which proteins will be of interest.
Although antibody arrays and MS differ in terms of sensitivity, throughput, and breadth of content, using both techniques in parallel enables researchers to increase the proteome coverage within the same study. For instance, by providing reproducible detection of low abundance analytes such as cytokines and other secreted effectors, antibody arrays can deliver the global perspective necessary to tailor therapeutic regimes. In contrast, the discovery of truly novel biomarkers is possible with MS, such as unknown protein isoforms or post-translational modifications for which no purified antibodies currently exist.
Data outputs for proteomics research can be qualitative, semi-quantitative, or quantitative according to the method chosen. Techniques such as lateral flow (e.g., home pregnancy urine strip tests) are qualitative, providing a rapid yes/no answer through visual inspection. Typical semi-quantitative readouts include absorbance units, pixels, and fluorescence units, all of which can be expressed as ratios of signal change. Quantitative readouts are provided as concentrations (e.g. pg/mL) relative to a standard curve. An advantage of semi-quantitative methods is that they are typically less costly than quantitative approaches. While both antibody arrays and MS can be either semi-quantitative or quantitative, obtaining quantitative data from a commercially available array is less onerous for the researcher than generating quantitative MS data. The array manufacturer optimizes the standard curve for each target in the panel, whereas quantitative MS analysis requires the end user to calibrate the instrument for each isotopically labeled peptide representing the protein-of-interest. This makes using quantitative antibody arrays to verify semi-quantitative MS data an attractive approach for many researchers.
The objectives of a study may help determine whether antibody arrays and MS should be used separately or in tandem. When the research topic is focused on a specific disease or biological process, antibody arrays are an appropriate platform since they are composed of a pre-selected panel of antibodies targeting markers with known or suspected functions in homeostasis and disease. In situations where potential biomarkers are largely unknown, MS offers a bias-free method to discover novel targets. The proteome coverage when using both antibody arrays and MS will be larger than using either method alone; this is particularly useful in protein profiling or biomarker discovery efforts. Alternatively, antibody arrays can be used as an orthogonal method to validate MS data.
Further reading about arrays and MS can be found here.