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Single cell analysis methods are increasingly being utilized to investigate how individual cells process information and respond to diverse stimuli. Soluble proteins play a critical role in controlling cell populations and tissues, but directly monitoring secretion is technically challenging. Microfabricated well arrays have been developed to assess secretion at the single cell level, but these systems are limited by low detection sensitivity. Semiconductor quantum dots (QD) exhibit remarkably bright and photostable luminescence signal, but to date they have not been evaluated in single cell secretion studies using microfabricated well arrays. Here, we used QDs in a sandwich immunoassay to detect secretion of the soluble cytokine tumor necrosis factor-α (TNF-α) from single cells. To enhance detection sensitivity, we employed two different strategies. First, we used a unique single QD imaging approach, which provided a detection threshold (180 attomolar) that was >100-fold lower than previously reported results using QDs. We also amplified QD binding to each captured TNF-α molecule using the bioorthogonal cycloaddition reaction between trans-cyclooctene and tetrazine, which further lowered detection threshold to 60 attomolar. This is 6 orders of magnitude more sensitive than organic fluorophores that have been used for single cell secretion studies, and far surpasses single molecule resolution within sub-picoliter microwells that are used to assess single cell secretion. Finally, single cell secretion studies were performed using phorbol 12-myristate 13-acetate (PMA) differentiated and lipopolysaccharide (LPS) activated U-937 cells. TNF-α secretion was detected from 3-fold more single cells using the QD-based method in comparison to rhodamine, which was accomplished by extending sensitivity into the range of ∼2 to 10 000 molecules captured per microwell. In future work, we will apply this technique to assess immune cell secretion dynamics under diverse stimuli and disease settings. We will also incorporate multiplexing capabilities to evaluate the secretome at the resolution of single molecules.

The targeted delivery of nanoparticle carriers holds tremendous potential to transform the detection and treatment of diseases. A major attribute of nanoparticles is the ability to form multiple bonds with target cells, which greatly improves the adhesion strength. However, the multivalent binding of nanoparticles is still poorly understood, particularly from a dynamic perspective. In previous experimental work, we studied the kinetics of nanoparticle adhesion and found that the rate of detachment decreased over time. Here, we have applied the adhesive dynamics simulation framework to investigate binding dynamics between an antibody-conjugated, 200-nm-diameter sphere and an ICAM-1-coated surface on the scale of individual bonds. We found that nano adhesive dynamics (NAD) simulations could replicate the time-varying nanoparticle detachment behavior that we observed in experiments. As expected, this behavior correlated with a steady increase in mean bond number with time, but this was attributed to bond accumulation only during the first second that nanoparticles were bound. Longer-term increases in bond number instead were manifested from nanoparticle detachment serving as a selection mechanism to eliminate nanoparticles that had randomly been confined to lower bond valencies. Thus, time-dependent nanoparticle detachment reflects an evolution of the remaining nanoparticle population toward higher overall bond valency. We also found that NAD simulations precisely matched experiments whenever mechanical force loads on bonds were high enough to directly induce rupture. These mechanical forces were in excess of 300 pN and primarily arose from the Brownian motion of the nanoparticle, but we also identified a valency-dependent contribution from bonds pulling on each other. In summary, we have achieved excellent kinetic consistency between NAD simulations and experiments, which has revealed new insights into the dynamics and biophysics of multivalent nanoparticle adhesion. In future work, we will leverage the simulation as a design tool for optimizing targeted nanoparticle agents.