Background
Immune phenotypes can be extremely diverse and complex, posing both a challenge to understand them and an opportunity to target them with advanced immune engineering approaches. Unfortunately, proteomics tools that capture the breadth of possible immune responses lack the throughput and affordability to rapidly profile the large sample numbers generated to identify and characterize optimally engineered therapeutic candidates. To overcome this issue, we developed the nELISA: a high-throughput miniaturized ELISA capable of quantifying >275 cytokines, proteases, immune receptors, and growth factors, at 10x-reduced cost compared to previous tools. Here, we applied the nELISA to model systems as a proof-of-concept for use in immune engineering.
Methods
We ran the largest PBMC secretome screen to date, in which ~10,000 PBMC samples were profiled in 1 week, at a throughput of 1536 samples/day. Cells were treated with various inflammatory stimuli, and were further perturbed with a selected library of 80 recombinant protein perturbagens.
Results
The broad nELISA content enabled us to capture disease phenotypes and donor variability, as well as distinguish between perturbations with similar effects on single markers but vastly different overall phenotypes. For example, IFN gamma was potently induced by >12 perturbagens with very different effects on other cytokines. Thus, IL-23 had almost no impact other than to induce IFN gamma; in contrast, IL-15 also induced IL-1 beta, TNF alpha, CXCL9, CXCL10, and CCL5, whereas IFN beta impacted the expression of >20 cytokines in addition to IFN gamma. Interestingly, we also identified cases perturbagens that could substitute for another, while avoiding deleterious effects. Thus, IL-1 Receptor antagonist shared all of the immunosuppressive effects of IFN beta, without inducing IFN gamma and CXCL10, supporting its use as a replacement for Type I interferons in certain indications such as multiple sclerosis.
Conclusions
These findings highlight the ability of the nELISA to capture a wide range of immune phenotypes at a throughput and cost amenable to immune engineering studies.