Probing T-cell activation in nanoliter tumor co-cultures using membrane displacement trap arrays.

Immune responses against cancer are inherently stochastic, with small numbers of individual T cells within a larger ensemble of lymphocytes initiating the molecular cascades that lead to tumor cytotoxicity. A potential source of this intra-tumor variability is the differential ability of immune cells to respond to tumor cells. Classical microwell co-cultures of T cells and tumor cells are inadequate for reliably culturing and analyzing low cell numbers needed to probe this variability, and have failed in recapitulating the heterogeneous small domains observed in tumors. Here we leverage a membrane displacement trap array technology that overcomes limitations of conventional microwell plates for immunodynamic studies. The microfluidic platform supports on-demand formation of dense nanowell cultures under continuous perfusion reflecting the tumor microenvironment, with real-time monitoring of T cell proliferation and activation within each nanowell. The system enables selective ejection of cells for profiling by fluorescence activated cell sorting, allowing observed on-chip variability in immune response to be correlated with off-chip quantification of T cell activation. The technology offers new potential for probing the molecular origins of T cell heterogeneity and identifying specific cell phenotypes responsible for initiating and propagating immune cascades within tumors. Insight Box Variability in T cell activation plays a critical role in the immune response against cancer. New tools are needed to unravel the mechanisms that drive successful anti-tumor immune response, and to support the development of novel immunotherapies utilizing rare T cell phenotypes that promote effective immune surveillance. To this end, we present a microfluidic cell culture platform capable of probing differential T cell activation in an array of nanoliter-scale wells coupled with off-chip cell analysis, enabling a high resolution view of variable immune response within tumor / T cell co-cultures containing cell ensembles orders of magnitude smaller than conventional well plate studies.

Engineering time-controlled immunotherapy.

Designer lymphocytes expand the dynamic range of possibilities for treating disease.

An Optimized Single-Molecule Pull-Down Assay for Quantification of Protein Phosphorylation.

Phosphorylation is a necessary posttranslational modification that regulates protein function and directs cell signaling outcomes. Current methods to measure protein phosphorylation cannot preserve the heterogeneity in phosphorylation across individual proteins. The single-molecule pull-down (SiMPull) assay was developed to investigate the composition of macromolecular complexes via immunoprecipitation of proteins on a glass coverslip followed by single-molecule imaging. The current technique is an adaptation of SiMPull that provides robust quantification of the phosphorylation state of full-length membrane receptors at the single-molecule level. Imaging thousands of individual receptors in this way allows for quantifying protein phosphorylation patterns. The present protocol details the optimized SiMPull procedure, from sample preparation to imaging. Optimization of glass preparation and antibody fixation protocols further enhances data quality. The current protocol provides code for the single-molecule data analysis that calculates the fraction of receptors phosphorylated within a sample. While this work focuses on phosphorylation of the epidermal growth factor receptor (EGFR), the protocol can be generalized to other membrane receptors and cytosolic signaling molecules.

Universal antigen encoding of T cell activation from high-dimensional cytokine dynamics.

Systems immunology lacks a framework with which to derive theoretical understanding from high-dimensional datasets. We combined a robotic platform with machine learning to experimentally measure and theoretically model CD8+ T cell activation. High-dimensional cytokine dynamics could be compressed onto a low-dimensional latent space in an antigen-specific manner (so-called "antigen encoding"). We used antigen encoding to model and reconstruct patterns of T cell immune activation. The model delineated six classes of antigens eliciting distinct T cell responses. We generalized antigen encoding to multiple immune settings, including drug perturbations and activation of chimeric antigen receptor T cells. Such universal antigen encoding for T cell activation may enable further modeling of immune responses and their rational manipulation to optimize immunotherapies.

Multisite EGFR phosphorylation is regulated by adaptor protein abundances and dimer lifetimes.

Differential epidermal growth factor receptor (EGFR) phosphorylation is thought to couple receptor activation to distinct signaling pathways. However, the molecular mechanisms responsible for biased signaling are unresolved due to a lack of insight into the phosphorylation patterns of full-length EGFR. We extended a single-molecule pull-down technique previously used to study protein-protein interactions to allow for robust measurement of receptor phosphorylation. We found that EGFR is predominantly phosphorylated at multiple sites, yet phosphorylation at specific tyrosines is variable and only a subset of receptors share phosphorylation at the same site, even with saturating ligand concentrations. We found distinct populations of receptors as soon as 1 min after ligand stimulation, indicating early diversification of function. To understand this heterogeneity, we developed a mathematical model. The model predicted that variations in phosphorylation are dependent on the abundances of signaling partners, while phosphorylation levels are dependent on dimer lifetimes. The predictions were confirmed in studies of cell lines with different expression levels of signaling partners, and in experiments comparing low- and high-affinity ligands and oncogenic EGFR mutants. These results reveal how ligand-regulated receptor dimerization dynamics and adaptor protein concentrations play critical roles in EGFR signaling.

EGFR Ligands Differentially Stabilize Receptor Dimers to Specify Signaling Kinetics.

Epidermal growth factor receptor (EGFR) regulates many crucial cellular programs, with seven different activating ligands shaping cell signaling in distinct ways. Using crystallography and other approaches, we show how the EGFR ligands epiregulin (EREG) and epigen (EPGN) stabilize different dimeric conformations of the EGFR extracellular region. As a consequence, EREG or EPGN induce less stable EGFR dimers than EGF-making them partial agonists of EGFR dimerization. Unexpectedly, this weakened dimerization elicits more sustained EGFR signaling than seen with EGF, provoking responses in breast cancer cells associated with differentiation rather than proliferation. Our results reveal how responses to different EGFR ligands are defined by receptor dimerization strength and signaling dynamics. These findings have broad implications for understanding receptor tyrosine kinase (RTK) signaling specificity. Our results also suggest parallels between partial and/or biased agonism in RTKs and G-protein-coupled receptors, as well as new therapeutic opportunities for correcting RTK signaling output.

Optimal performance of the tryptophan operon of E. coli: a stochastic, dynamical, mathematical-modeling approach.

In this work, we develop a detailed, stochastic, dynamical model for the tryptophan operon of E. coli, and estimate all of the model parameters from reported experimental data. We further employ the model to study the system performance, considering the amount of biochemical noise in the trp level, the system rise time after a nutritional shift, and the amount of repressor molecules necessary to maintain an adequate level of repression, as indicators of the system performance regime. We demonstrate that the level of cooperativity between repressor molecules bound to the first two operators in the trp promoter affects all of the above enlisted performance characteristics. Moreover, the cooperativity level found in the wild-type bacterial strain optimizes a cost-benefit function involving low biochemical noise in the tryptophan level, short rise time after a nutritional shift, and low number of regulatory molecules.