How High-plex, Mid-plex & Single-target proteomic technologies can be merged together to empower your research

In the dynamic landscape of biomedical research, proteomics play a crucial role in providing invaluable insights into the role of proteins in biological systems. The diversity of proteomic technologies can be generally classified into high-plex, mid-plex, and single-target assays based on their level of throughput (samples per run) and depth of analysis (analytes per sample). Yet, many researchers still find themselves caught in the dilemma of choosing the ‘perfect’ method for their projects. The truth is, there’s no one-size-fits-all approach. Merging technologies can actually amplify the capabilities of your research, orthogonally validate your biomarker findings, and provide a comprehensive and solid understanding that wouldn’t be possible otherwise.

High-plex Proteomics: Broad Scope, Large number of Analytes 

High-plex proteomics provide a broad overview of the proteome. Mass spectrometry and targeted approaches (i.e. Olink and/or Somalogic) are often used to measure 100s or 1000s of proteins, thereby offering a wide snapshot of the proteome. Because of the very large number of analytes measured per run, technologies can become expensive on a per sample basis and may not be feasible to measure very large numbers of samples. These approaches can provide a broad overview of biomarkers and mechanisms but are limited in terms of fine-grained details for specific biomarkers.

Mid-plex Proteomics: The Balanced Approach

Mid-plex technologies like multiplexed ELISA (i.e. Luminex, MSD) offer a balance between scale and specificity. These methods can quantify dozens to one hundred of proteins with good sensitivity and specificity. Mid-plex assays are often more cost effective on a per sample basis than high-plex approaches, can be customized to focus on proteins of particular interest, and can be used for screening thousands of samples. 

Single-target Proteomics: Focused and Sensitive

Single-target proteomics techniques, such as single-target ELISAs, are ideal for validating specific biomarkers, studying individual pathways, providing strong quantitative data, or expanding to other single-target platforms using the antibodies of interests (i.e. from ELISA to  lateral flow assays). Single-target assays are usually quicker and less expensive. In addition, some single-target instrumentation is usually incorporated in clinical and research labs enabling an efficient commercialization strategy.

The Power of Integration

Each of these technologies comes with its own set of advantages and limitations, but what if you could combine them for a more comprehensive analysis? A strategic multi-platform integration can work wonders. Start with high-plex proteomics to identify potential biomarkers and altered pathways. This will give you a macroscopic view to direct your research hypothesis. Follow this up with mid-plex assays to narrow down your list of interesting proteins, validate findings or select biomarkers that give you the best clinical and analytical performance. Finally, select your single-target platform that maximizes the chances of clinical implementation using your most promising candidates. 

Merging these methods allows for resource optimization. High-plex techniques can be cost-prohibitive for large numbers of samples, but combining them with mid-plex and single-target assays will give you more solid answers for the same budget. On this front, combining methods allows for robust research outcomes. In several cases single techniques rely on the same antibodies and can lead to false results due to antibody cross reactivity. Merging techniques will orthogonally validate your biomarker findings creating robust knowledge for clinical applications. 

In conclusion, the key to empowering your research may lie in a skillful integration choosing between high-plex, mid-plex, and low/single-target proteomics in order to take advantage of each method’s unique strengths. By doing so, you’ll gain a richer, validated and more complete picture of the proteomic landscape that could be pivotal in advancing our understanding of complex biological systems.

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