Rhodopsin protein

Exploring the Microarray Revolution: A New Era in Proteomic Analysis

Proteins have extensive functions to ensure that the body remains healthy. Proteins are involved in nearly all aspects of cellular behavior, from maintaining cell structure to immune function. They are also associated with DNA-related processes, including mitosis and replication. Studying protein behavior and interactions can help us understand the ramifications DNA mutations and how these contribute to disease. Further, proteomic analysis can help us to learn more about complex diseases, like Alzheimer’s, where misfolded proteins cause pathologies.

Each disease has its own unique criteria for diagnosis, often starting with symptoms, however, protein analysis is a critical component to verifying diagnosis. In fact, proteomic analysis of disease holds the potential to identify valuable biomarkers that can be used to detect disease early, track treatment effectiveness, discover disease subgroups, and identify new therapeutic targets. Altogether, this means more precise and effective medicine. Innovative technologies are required to help scientists identify protein biomarkers that can meet all these expectations. Enter protein microarrays.

There are three basic types of protein microarrays distinguished by the material printed on the slide: antibody (analytical), reverse-phase, and functional. Antibody arrays use antibodies, reverse-phase arrays (RPMA) use cells or lysates, and functional arrays use protein. 

In an antibody microarray, antibodies are spotted onto a slide surface to capture other molecules, cells, or proteins.  Advantages of this technique include cell separation, comparison of different cells from tissue homogenates (disease versus normal), cell classification, protein profiling, protein quantification and binding affinity. 

RPMAs spot-print cell or tissue lysates onto slides.  The lysates are labeled and identified using target specific antibodies that are quantified via immunofluorescence or chemiluminescence.  RPMA is often used to detect specific disease-related proteins or post-translational modifications (PTMs) of proteins from patient cell or tissue lysates. Some advantages of RPMA assays include good sensitivity and specificity of disease detection, small sample requirement (picograms per spot), throughput, and quantifiability.

Functional protein microarrays utilize full-length proteins printed onto a coated slide surface. As the name implies, functional protein arrays must utilize proteins with intact functional domains that are crucial for protein interactions and analysis. Importantly, many arrays that use full-length proteins may not be functional and may simply qualify as a protein array. (Learn more about Sengenics’s functional protein arrays.)

Functional protein arrays excel at immunoprofiling, or mapping the antibody repertoire to the proteins on the array. These arrays are high throughput, providing a quick and accurate approach to identify biomarkers for disease detection, predict patient outcomes, and determine potential adverse events prior to treatment. 

Microarrays have the potential to push the boundaries of our knowledge on proteins. Here, we explore functional microarrays in more detail.

Broad Applications for Discovery and Quantitative Analysis

In recent years, functional protein microarrays have significantly broadened the scope for discovery and quantitative analysis in proteomics. With new advanced AI data processing algorithms, stronger bioinformatics assets and better array fabrication, these arrays offer a deep and comprehensive understanding of biological processes and disease mechanisms.¹

Functional protein microarrays are particularly valuable for acquiring detailed information on immune system surveillance, marking proteins and pathways that have become potentially harmful due to disease.  This includes PTMs that are not detected by other methods.  For example, citrullination is a low abundance PTM involved in inflammation that is easily missed by other assays but produces new binding regions called neoepitopes that are easily identified in a functional protein array.

These capabilities facilitate a comprehensive analysis of the myriad protein interactions in health and disease. This depth of analysis is vital for uncovering the molecular mechanisms underlying various physiological and pathological processes.³

Facilitating Clinical Research and Diagnostics

Functional protein microarrays have shown promise in clinical research and diagnostics, but their widespread adoption in clinical settings is still somewhat limited. Up to now, these arrays have greatly facilitated identification of biomarkers, and analysis of protein functions in various areas of clinical research, including cancer biomarker discovery, autoimmune disease diagnosis, infectious disease detection, and drug target identification.

Due to the high throughput, sensitivity and specificity, functional protein arrays are well suited for future use in precision medicine where a patient’s immunoprofile can help direct treatment and care while avoiding adverse events. For example, Lewis et. al. utilized the Sengenics i-Ome® functional protein array with rheumatoid arthritis patients and identified four different classifications of the disease, each with different prognoses4.

The application of microarray technology in clinical research exemplifies its potential to transform the future of patient care, where personalized medicine and targeted therapies become the standard of care. 5


  1. Duarte, J. S., J; Mulder, N; Blackburn, J. (2013). Protein Functional Microarrays: Design, Use and Bioinformatic Analysis in Cancer Biomarker Discovery and Quantitation. In X. Wang (Ed.), Bioinformatics of Human Proteomics (pp. 39-74). Springer Science+Business Media Dordrecht.
  2. Borrebaeck, C., Wingren C. (2007). High-throughput proteomics using antibody microarrays: an update. Expert Review of Molecular Diagnostics, 7(5):673-686. doi:10.1586/14747159.7.5.673.
  3. Joos, T., et. al. (2002). Protein microarray Technology. Trends in Biotechnology, 20(4):160-166. doi:10.1016/S0167-7799(01)01910-2.
  4. Lewis, M. J., et. al. (2018). Autoantibodies targeting TLR and SMAD pathways define new subgroups in systemic lupus erythematosus. J Autoimmun, 91, 1-12. https://doi.org/10.1016/j.jaut.2018.02.009
  5. Calvert, V, et. al. (2003). Protein microarrays: Molecular profiling technologies for clinical specimens. Proteomics, 3(11):2091-2100. doi:10.1002/pmic.200300592.