Multiplex Assay Selection and Optimization

Multiplex assays allow researchers to extract more information from less sample, often saving time and money in the process. This editorial looks at factors to consider for platform selection and shares tips for optimization.

Why multiplex?

“A main reason for multiplexing is to cast a broad net and investigate co-expression of readouts of interest,” says Damien Montamat-Sicotte, Scientific Business Director at CellCarta. “For example, when the objective is to have a complete overview that lets you identify a biomarker signature for a particular disease, multiplexing gives clarity on polyfunctionality and complex cellular responses or mechanisms.”

Multiplexing can also provide improved sensitivity. “This is particularly the case when multiplexing is applied in a syndromic setting, where it allows for identifying multiple conditions at once,” reports Dr. John Shon, CTO at Serimmune. “In addition, multiplex assays are useful for scenarios where there is significant risk of co-infections, such as tick-borne diseases. They can also improve specificity for one condition, with multiple positive antigens ensuring the response is specific to the organism of interest.”

Factors to consider for platform selection

A key factor to consider for platform selection is the research question being asked. For example, when selecting a multiplex imaging platform, there is often a tradeoff between plex size and sample number, which makes some platforms better suited for certain applications than others.

“Some multiplex imaging platforms allow for detecting 20 or more proteins in a single tissue section,” explains Sarah Klein, Ph.D., Associate Director of Multiplex Assays at Cell Signaling Technology. “This plex size supports discovery research, enabling scientists to obtain a vast amount of data with only a few tissue samples. Other platforms allow for staining and imaging of 2–8 proteins on a larger cohort of samples. This plex size is often large enough for targeted, translational studies of specific cell types or pathways. Typically, the number of samples is limited in high plex discovery platforms due to higher costs and longer time requirements for optimization, staining, imaging, and analysis.”

Another consideration is target abundance. If the target of interest is likely to be variably expressed, with some samples having very low expression levels, signal amplification may be required for accurate detection. Yet not all multiplex assays incorporate signal amplification.

“Clinical context is also important, as tests pick up pathogens differently during a disease’s natural history,” says Shon. “DNA or RNA nucleotide tests may be positive initially but become less sensitive as the infection is controlled by an immune response. Conversely, serology may be negative in the first few weeks after exposure, but then becomes positive, first with IgM, followed by IgG, and may be present for several months.”

Validating the assay

Important validation tests include precision, stability, and limit of quantification/detection. The International Organization for Standardization (ISO) defines precision as “the closeness of agreement between independent test results obtained under stipulated conditions”. Stability encompasses factors such as samples, reference standards, and assay reagents, as well as how consistent results are on different days. “For the limit of quantification, we describe this as the lowest measurement that still meets precision criteria,” explains Montamat-Sicotte. “The limit of detection is the lowest concentration of a substance (or, for flow cytometry, the lowest number of events) that can be measured as a positive signal but without meeting precision criteria.”

Shon comments that scale can present challenges for multiplex assay validation. “Serimmune produces exceptionally broad tests and one of the issues we have tackled is finding true differential signals in cohorts,” he says. “When you are looking at a million different things at once, particularly in small cohorts, it is likely you will find something different between the two. You need to understand what those findings mean, if anything. That is why a baseline population cohort is so critically important, especially in the discovery phase, to prevent overfitting and spurious findings.”

General tips for optimization

Each type of multiplex assay may require different optimization and validation. “Regardless, the quality and success of an antibody-based multiplex assay is directly correlated to the quality of the antibodies used,” cautions Klein. “Researchers should confirm that each antibody is working as expected before placing it into the multiplex setting. When possible, researchers should use orthogonal approaches to validate the multiplex data, such as western blot, flow cytometry, or RNA sequencing. Once antibody specificity is confirmed, the multiplex assay of choice may require additional optimization, such as antibody titration, antibody order, reagent and buffer titration, and incubation time optimization.”

Montamat-Sicotte advises prioritizing readouts throughout the optimization process. “Some readouts will have better performance than others, and having a certain focus will ensure that important readouts do not suffer from the multiplexing approach,” he says. Another general recommendation is to establish quality control metrics for ensuring that results are consistent over time. “By implementing these metrics from the outset, you can have confidence later on that results are similar to those that came before,” says Shon.

Types of multiplex assay

Each of the companies featured here provides different multiplex assay options. “CellCarta offers spectral flow cytometry, which can investigate up to 40 markers with great specificity and can combine phenotypic and functional readouts in the same assay,” says Montamat-Sicotte. “We also offer Olink, a proximity extension assay technology that enables researchers to investigate 96 biomarkers with high sensitivity from just a few microliters of sample.”

“Cell Signaling Technology’s SignalStar™ Multiplex IHC is a new technology for spatial biology research that uses high-throughput, mid-plex IHC assays to label up to eight targets in FFPE tissues simultaneously with flexible, highly validated antibody panels,” reports Klein. “An important advantage of SignalStar is that it does not utilize antibody cycling, which can result in the loss of epitopes required for antibody binding. SignalStar also allows for the detection of targets with low expression levels by using a combination of oligonucleotides and fluorophores to amplify the antibody signal, and can provide spatial biology data up to 70% faster than traditional multiplex IHC methods.”

The SignalStar Multiplex IHC workflow. Image provided by Cell Signaling Technology.

“Our Serum Epitope Repertoire Analysis (SERA) platform is a 10 billion bacterial display peptide array that functions as a universal serology assay,” explains Shon. “Because the assay is so broad, it takes ascertainment bias out of the equation and lets researchers look at the whole gamut of immune signals to whatever an individual has responded to. Using advanced computational methods, we have developed over fifty research panels to identify antibody specificities against a variety of infections and human antigens in cancer and autoimmune disease—all in one assay. In addition, this entire database can be queried against any arbitrary protein or proteome, including natural infections, new biotherapeutics, and gene vectors. Finally, the resolution allows researchers to identify the amino acid residues that are important for binding, which can be especially important when designing vaccines, biotherapeutics, and gene and cell therapies.”

The SERA workflow. Image provided by Serimmune.