Variability in G-protein-coupled signaling studied with microfluidic devices

Mapping of structural arrangement of cells and collective calcium transients: an integrated framework combining live cell imaging using confocal microscopy and UMAP-assisted HDBSCAN-based approach

Live cell calcium (Ca2+) imaging is one of the important tools to record cellular activity during in vitro and in vivo preclinical studies. Specially, high-resolution microscopy can provide valuable dynamic information at the single cell level. One of the major challenges in the implementation of such imaging schemes is to extract quantitative information in the presence of significant heterogeneity in Ca2+ responses attained due to variation in structural arrangement and drug distribution. To fill this gap, we propose time-lapse imaging using spinning disk confocal microscopy and machine learning-enabled framework for automated grouping of Ca2+ spiking patterns. Time series analysis is performed to correlate the drug induced cellular responses to self-assembly pattern present in multicellular systems. The framework is designed to reduce the large-scale dynamic responses using uniform manifold approximation and projection (UMAP). In particular, we propose the suitability of hierarchical DBSCAN (HDBSCAN) in view of reduced number of hyperparameters. We find UMAP-assisted HDBSCAN outperforms existing approaches in terms of clustering accuracy in segregation of Ca2+ spiking patterns. One of the novelties includes the application of non-linear dimension reduction in segregation of the Ca2+ transients with statistical similarity. The proposed pipeline for automation was also proved to be a reproducible and fast method with minimal user input. The algorithm was used to quantify the effect of cellular arrangement and stimulus level on collective Ca2+ responses induced by GPCR targeting drug. The analysis revealed a significant increase in subpopulation containing sustained oscillation corresponding to higher packing density. In contrast to traditional measurement of rise time and decay ratio from Ca2+ transients, the proposed pipeline was used to classify the complex patterns with longer duration and cluster-wise model fitting. The two-step process has a potential implication in deciphering biophysical mechanisms underlying the Ca2+ oscillations in context of structural arrangement between cells.

Coordination of MAPK and p53 dynamics in the cellular responses to DNA damage and oxidative stress

In response to different cellular stresses, the transcription factor p53 undergoes different dynamics. p53 dynamics, in turn, control cell fate. However, distinct stresses can generate the same p53 dynamics but different cell fate outcomes, suggesting integration of dynamic information from other pathways is important for cell fate regulation. To determine how MAPK activities affect p53-mediated responses to DNA breaks and oxidative stress, we simultaneously tracked p53 and either ERK, JNK, or p38 activities in single cells. While p53 dynamics were comparable between the stresses, cell fate outcomes were distinct. Combining MAPK dynamics with p53 dynamics was important for distinguishing between the stresses and for generating temporal ordering of cell fate pathways. Furthermore, cross-talk between MAPKs and p53 controlled the balance between proliferation and cell death. These findings provide insight into how cells integrate signaling pathways with distinct temporal patterns of activity to encode stress specificity and drive different cell fate decisions.

High-Content Single-Cell Förster Resonance Energy Transfer Imaging of Cultured Striatal Neurons Reveals Novel Cross-Talk in the Regulation of Nuclear Signaling by Protein Kinase A and Extracellular Signal-Regulated Kinase 1/2

Genetically encoded biosensors can be used to track signaling events in living cells by measuring changes in fluorescence emitted by one or more fluorescent proteins. Here, we describe the use of genetically encoded biosensors based on Förster resonance energy transfer (FRET), combined with high-content microscopy, to image dynamic signaling events simultaneously in thousands of neurons in response to drug treatments. We first applied this approach to examine intercellular variation in signaling responses among cultured striatal neurons stimulated with multiple drugs. Using high-content FRET imaging and immunofluorescence, we identified neuronal subpopulations with unique responses to pharmacological manipulation and used nuclear morphology to identify medium spiny neurons within these heterogeneous striatal cultures. Focusing on protein kinase A (PKA) and extracellular signal-regulated kinase 1/2 (ERK1/2) signaling in the cytoplasm and nucleus, we noted pronounced intercellular differences among putative medium spiny neurons, in both the magnitude and kinetics of signaling responses to drug application. Importantly, a conventional "bulk" analysis that pooled all cells in culture yielded a different rank order of drug potency than that revealed by single-cell analysis. Using a single-cell analytical approach, we dissected the relative contributions of PKA and ERK1/2 signaling in striatal neurons and unexpectedly identified a novel role for ERK1/2 in promoting nuclear activation of PKA in striatal neurons. This finding adds a new dimension of signaling crosstalk between PKA and ERK1/2 with relevance to dopamine D1 receptor signaling in striatal neurons. In conclusion, high-content single-cell imaging can complement and extend traditional population-level analyses and provides a novel vantage point from which to study cellular signaling. SIGNIFICANCE STATEMENT: High-content imaging revealed substantial intercellular variation in the magnitude and pattern of intracellular signaling events driven by receptor stimulation. Since individual neurons within the same population can respond differently to a given agonist, interpreting measures of intracellular signaling derived from the averaged response of entire neuronal populations may not always reflect what happened at the single-cell level. This study uses this approach to identify a new form of cross-talk between PKA and ERK1/2 signaling in the nucleus of striatal neurons.

Integrating Immunology and Microfluidics for Single Immune Cell Analysis

The field of immunoengineering aims to develop novel therapies and modern vaccines to manipulate and modulate the immune system and applies innovative technologies toward improved understanding of the immune system in health and disease. Microfluidics has proven to be an excellent technology for analytics in biology and chemistry. From simple microsystem chips to complex microfluidic designs, these platforms have witnessed an immense growth over the last decades with frequent emergence of new designs. Microfluidics provides a highly robust and precise tool which led to its widespread application in single-cell analysis of immune cells. Single-cell analysis allows scientists to account for the heterogeneous behavior of immune cells which often gets overshadowed when conventional bulk study methods are used. Application of single-cell analysis using microfluidics has facilitated the identification of several novel functional immune cell subsets, quantification of signaling molecules, and understanding of cellular communication and signaling pathways. Single-cell analysis research in combination with microfluidics has paved the way for the development of novel therapies, point-of-care diagnostics, and even more complex microfluidic platforms that aid in creating in vitro cellular microenvironments for applications in drug and toxicity screening. In this review, we provide a comprehensive overview on the integration of microsystems and microfluidics with immunology and focus on different designs developed to decode single immune cell behavior and cellular communication. We have categorized the microfluidic designs in three specific categories: microfluidic chips with cell traps, valve-based microfluidics, and droplet microfluidics that have facilitated the ongoing research in the field of immunology at single-cell level.

High capacity in G protein-coupled receptor signaling

G protein-coupled receptors (GPCRs) constitute a large family of receptors that activate intracellular signaling pathways upon detecting specific extracellular ligands. While many aspects of GPCR signaling have been uncovered through decades of studies, some fundamental properties, like its channel capacity—a measure of how much information a given transmission system can reliably transduce—are still debated. Previous studies concluded that GPCRs in individual cells could transmit around one bit of information about the concentration of the ligands, allowing only for a reliable on or off response. Using muscarinic receptor-induced calcium response measured in individual cells upon repeated stimulation, we show that GPCR signaling systems possess a significantly higher capacity. We estimate the channel capacity of this system to be above two, implying that at least four concentration levels of the agonist can be distinguished reliably. These findings shed light on the basic principles of GPCR signaling.

G protein-coupled receptors (GPCRs) activate intracellular signalling pathways upon extracellular stimulation. Here authors record single cell responses of GPCR signalling which allows the direct estimation of its channel capacity for each cell along with the reproducibility of its response.

Fundamental trade-offs between information flow in single cells and cellular populations

Signal transduction networks allow eukaryotic cells to make decisions based on information about intracellular state and the environment. Biochemical noise significantly diminishes the fidelity of signaling: networks examined to date seem to transmit less than 1 bit of information. It is unclear how networks that control critical cell-fate decisions (e.g., cell division and apoptosis) can function with such low levels of information transfer. Here, we use theory, experiments, and numerical analysis to demonstrate an inherent trade-off between the information transferred in individual cells and the information available to control population-level responses. Noise in receptor-mediated apoptosis reduces information transfer to approximately 1 bit at the single-cell level but allows 3-4 bits of information to be transmitted at the population level. For processes such as eukaryotic chemotaxis, in which single cells are the functional unit, we find high levels of information transmission at a single-cell level. Thus, low levels of information transfer are unlikely to represent a physical limit. Instead, we propose that signaling networks exploit noise at the single-cell level to increase population-level information transfer, allowing extracellular ligands, whose levels are also subject to noise, to incrementally regulate phenotypic changes. This is particularly critical for discrete changes in fate (e.g., life vs. death) for which the key variable is the fraction of cells engaged. Our findings provide a framework for rationalizing the high levels of noise in metazoan signaling networks and have implications for the development of drugs that target these networks in the treatment of cancer and other diseases.

Distinct cellular states determine calcium signaling response

The heterogeneity in mammalian cells signaling response is largely a result of pre‐existing cell‐to‐cell variability. It is unknown whether cell‐to‐cell variability rises from biochemical stochastic fluctuations or distinct cellular states. Here, we utilize calcium response to adenosine trisphosphate as a model for investigating the structure of heterogeneity within a population of cells and analyze whether distinct cellular response states coexist. We use a functional definition of cellular state that is based on a mechanistic dynamical systems model of calcium signaling. Using Bayesian parameter inference, we obtain high confidence parameter value distributions for several hundred cells, each fitted individually. Clustering the inferred parameter distributions revealed three major distinct cellular states within the population. The existence of distinct cellular states raises the possibility that the observed variability in response is a result of structured heterogeneity between cells. The inferred parameter distribution predicts, and experiments confirm that variability in IP3R response explains the majority of calcium heterogeneity. Our work shows how mechanistic models and single‐cell parameter fitting can uncover hidden population structure and demonstrate the need for parameter inference at the single‐cell level.

High-Content Quantification of Single-Cell Immune Dynamics

Cells receive time-varying signals from the environment and generate functional responses by secreting their own signaling molecules. Characterizing dynamic input-output relationships in single cells is crucial for understanding and modeling cellular systems. We developed an automated microfluidic system that delivers precisely defined dynamical inputs to individual living cells and simultaneously measures key immune parameters dynamically. Our system combines nanoliter immunoassays, microfluidic input generation, and time-lapse microscopy, enabling study of previously untestable aspects of immunity by measuring time-dependent cytokine secretion and transcription factor activity from single cells stimulated with dynamic inflammatory inputs. Employing this system to analyze macrophage signal processing under pathogen inputs, we found that the dynamics of TNF secretion are highly heterogeneous and surprisingly uncorrelated with the dynamics of NF-κB, the transcription factor controlling TNF production. Computational modeling of the LPS/TLR4 pathway shows that post-transcriptional regulation by TRIF is a key determinant of noisy and uncorrelated TNF secretion dynamics in single macrophages.

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Dynamic stimulation of single immune cells with a versatile microfluidic device

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Coupled longitudinal measurements of NF-κB localization and TNF secretion on the same cell

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Single-cell harvesting, staining, and mRNA quantification on the same device

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High-content dataset, and modeling of TRIF-based noise in TNF secretion

Innovative Tools and Technology for Analysis of Single Cells and Cell-Cell Interaction

Heterogeneity in single-cell responses and intercellular interactions results from complex regulation of cell-intrinsic and environmental factors. Single-cell analysis allows not only detection of individual cellular characteristics but also correlation of genetic content with phenotypic traits in the same cell. Technological advances in micro- and nanofabrication have benefited single-cell analysis by allowing precise control of the localized microenvironment, cell manipulation, and sensitive detection capabilities. Additionally, microscale techniques permit rapid, high-throughput, multiparametric screening that has become essential for -omics research. This review highlights innovative applications of microscale platforms in genetic, proteomic, and metabolic detection in single cells; cell sorting strategies; and heterotypic cell-cell interaction. We discuss key design aspects of single-cell localization and isolation in microfluidic systems, dynamic and endpoint analyses, and approaches that integrate highly multiplexed detection of various intracellular species.

A G-protein subunit translocation embedded network motif underlies GPCR regulation of calcium oscillations

G-protein βγ subunits translocate reversibly from the plasma membrane to internal membranes on receptor activation. Translocation rates differ depending on the γ subunit type. There is limited understanding of the role of the differential rates of Gβγ translocation in modulating signaling dynamics in a cell. Bifurcation analysis of the calcium oscillatory network structure predicts that the translocation rate of a signaling protein can regulate the damping of system oscillation. Here, we examined whether the Gβγ translocation rate regulates calcium oscillations induced by G-protein-coupled receptor activation. Oscillations in HeLa cells expressing γ subunit types with different translocation rates were imaged and quantitated. The results show that differential Gβγ translocation rates can underlie the diversity in damping characteristics of calcium oscillations among cells. Mathematical modeling shows that a translocation embedded motif regulates damping of G-protein-mediated calcium oscillations consistent with experimental data. The current study indicates that such a motif may act as a tuning mechanism to design oscillations with varying damping patterns by using intracellular translocation of a signaling component.

Efficient entry of cell-penetrating peptide nona-arginine into adherent cells involves a transient increase in intracellular calcium

Mechanisms by which drug-delivery vehicles based on cationic peptides cross cell membranes remain unknown. We report that an increase in intracellular calcium triggered by temperature drop or high peptide concentrations transiently permeabilizes the plasma membrane for nona-arginine (R₉) and delivers it to the cytosol.

Understanding the mechanism of entry of cationic peptides such as nona-arginine (R₉) into cells remains an important challenge to their use as efficient drug-delivery vehicles. At nanomolar to low micromolar R₉ concentrations and at physiological temperature, peptide entry involves endocytosis. In contrast, at a concentration ≥10 μM, R₉ induces a very effective non-endocytic entry pathway specific for cationic peptides. We found that a similar entry pathway is induced at 1–2 μM concentrations of R₉ if peptide application is accompanied by a rapid temperature drop to 15°C. Both at physiological and at sub-physiological temperatures, this entry mechanism was inhibited by depletion of the intracellular ATP pool. Intriguingly, we found that R₉ at 10–20 μM and 37°C induces repetitive spikes in intracellular Ca²⁺ concentration. This Ca²⁺ signalling correlated with the efficiency of the peptide entry. Pre-loading cells with the Ca²⁺ chelator BAPTA (1,2-bis(o-aminophenoxy)ethane-N,N,N′,N′-tetraacetic acid) inhibited both Ca²⁺ spikes and peptide entry, suggesting that an increase in intracellular Ca²⁺ precedes and is required for peptide entry. One of the hallmarks of Ca²⁺ signalling is a transient cell-surface exposure of phosphatidylserine (PS), a lipid normally residing only in the inner leaflet of the plasma membrane. Blocking the accessible PS with the PS-binding domain of lactadherin strongly inhibited non-endocytic R₉ entry, suggesting the importance of PS externalization in this process. To conclude, we uncovered a novel mechanistic link between calcium signalling and entry of cationic peptides. This finding will enhance our understanding of the properties of plasma membrane and guide development of future drug-delivery vehicles.

The structure of dynamic GPCR signaling networks

G-protein-coupled receptors (GPCRs) stimulate signaling networks that control a variety of critical physiological processes. Static information on the map of interacting signaling molecules at the basis of many cellular processes exists, but little is known about the dynamic operation of these networks. Here we focus on two questions. First, Is the network architecture underlying GPCR-activated cellular processes unique in comparison with others such as transcriptional networks? We discuss how spatially localized GPCR signaling requires uniquely organized networks to execute polarized cell responses. Second, What approaches overcome challenges in deciphering spatiotemporally dynamic networks that govern cell behavior? We focus on recently developed microfluidic and optical approaches that allow GPCR signaling pathways to be triggered and perturbed with spatially and temporally variant input while simultaneously visualizing molecular and cellular responses. When integrated with mathematical modeling, these approaches can help identify design principles that govern cell responses to extracellular signals. We outline why optical approaches that allow the behavior of a selected cell to be orchestrated continually are particularly well suited for probing network organization in single cells.

Modulation of alpha-synuclein toxicity in yeast using a novel microfluidic-based gradient generator

Parkinson's disease (PD) is a common age-associated neurodegenerative disorder. The protein α-synuclein (aSyn) is a key factor in PD both due to its association with familial and sporadic cases and because it is the main component of the pathological protein aggregates known as Lewy bodies. However, the precise cellular effects of aSyn aggregation are still elusive. Here, we developed an elastomeric microfluidic device equipped with a chemical gradient generator and 9 chambers containing cell traps to study aSyn production and aggregation in Saccharomyces cerevisiae. This study involved capturing single cells, exposing them to specific chemical environments and imaging the expression of aSyn by means of a GFP fusion (aSyn-GFP). Using a galactose (GAL) gradient we modulated aSyn expression and, surprisingly, by tracking the behavior of single cells, we found that the response of individual cells in a population to a given stimulus can differ widely. To study the combined effect of environmental factors and aSyn expression levels, we exposed cells to a gradient of FeCl3. We found a dramatic increase in the percentage of cells displaying aSyn inclusions from 27% to 96%. Finally, we studied the effects of ascorbic acid, an antioxidant, on aSyn aggregation and found a significant reduction in the percentage of cells bearing aSyn inclusions from 87% to 37%. In summary, the device developed here offers a powerful way of studying aSyn biology with single-cell resolution and high throughput using genetically modified yeast cells.

Engineering of synthetic cellular microenvironments: implications for immunity

In this article, we discuss novel synthetic approaches for studying the interactions of cells with their microenvironment. Notably, critical cellular processes such as growth, differentiation, migration, and fate determination, are tightly regulated by interactions with neighboring cells, and the surrounding extracellular matrix. Given the huge complexity of natural cellular environments, and their rich molecular and physical diversity, the mission of understanding "environmental signaling" at a molecular-mechanistic level appears to be extremely challenging. To meet these challenges, attempts have been made in recent years to design synthetic matrices with defined chemical and physical properties, which, artificial though they may be, could reveal basic "design principles" underlying the physiological processes. Here, we summarize recent developments in the characterization of the chemical and physical properties of cell sensing and adhesion, as well as the design and use of engineered, micro- to nanoscale patterned and confined environments, for systematic, comprehensive modulation of the cells' environment. The power of these biomimetic surfaces to highlight environmental signaling events in cells, and in immune cells in particular, will be discussed.

Microfluidic single-cell analysis for systems immunology

The immune system constantly battles infection and tissue damage, but exaggerated immune responses lead to allergies, autoimmunity and cancer. Discrimination of self from foreign and the fine-tuning of immunity are achieved by information processing pathways, whose regulatory mechanisms are little understood. Cell-to-cell variability and stochastic molecular interactions result in diverse cellular responses to identical signaling inputs, casting doubt on the reliability of traditional population-averaged analyses. Furthermore, dynamic molecular and cellular interactions create emergent properties that change over multiple time scales. Understanding immunity in the face of complexity and noisy dynamics requires time-dependent analysis of single-cells in a proper context. Microfluidic systems create precisely defined microenvironments by controlling fluidic and surface chemistries, feature sizes, geometries and signal input timing, and thus enable quantitative multi-parameter analysis of single cells. Such qualities allow observable dynamic environments approaching in vivo levels of biological complexity. Seamless parallelization of functional units in microfluidic devices allows high-throughput measurements, an essential feature for statistically meaningful analysis of naturally variable biological systems. These abilities recapitulate diverse scenarios such as cell-cell signaling, migration, differentiation, antibody and cytokine production, clonal selection, and cell lysis, thereby enabling accurate and meaningful study of immune behaviors in vitro.

On-chip nanohole array based sensing: a review

The integration of nanohole array based plasmonic sensors into microfluidic systems has enabled the emergence of platforms with unique capabilities and a diversified palette of applications. Recent advances in fabrication techniques together with novel implementation schemes have influenced the progress of these optofluidic platforms. Here, we review the advances that nanohole array based sensors have experienced since they were first merged with microfluidics. We examine established and new fabrication methodologies that have enabled both the fabrication of nanohole arrays with improved optical attributes and a reduction in manufacturing costs. The achievements of several platforms developed to date and the significant benefits obtained from operating the nanoholes as nanochannels are also reviewed herein. Finally, we discuss future opportunities for on-chip nanohole array sensors by outlining potential applications and the use of the abilities of the nanostructures beyond the optical context.

Microfluidic interrogation and mathematical modeling of multi-regime calcium signaling dynamics

Through microfluidic interrogation we analyzed real-time calcium responses of HEK293 cells stimulated with short pulses of the M3 muscarinic receptor ligand carbachol in two different concentration regimes. Lower ligand concentrations elicit oscillatory calcium signals while higher concentrations trigger a rapid rise that eventually settles down at a steady-state slightly above pre-stimulus levels, referred to as an acute signal. Cells were periodically pulsed with carbachol at these two concentration regimes using a custom-made microfluidic platform, and the resulting calcium signals were measured with a single fluorescent readout. Pulsed stimulations at these two concentration regimes resulted in multiple types of response patterns that each delivered complementary information about the M3 muscarinic receptor signaling pathway. These multiple types of calcium response patterns enabled development of a comprehensive mathematical model of multi-regime calcium signaling. The resulting model suggests that dephosphorylation of deactivated receptors is rate limiting for recovery of calcium signals in the acute regime (high ligand concentration), while calcium replenishment and IP3 production determine signal recovery in the oscillatory regime (low ligand concentration). This study not only provides mechanistic insight into multi-regime signaling of the M3 muscarinic receptor pathway, but also provides a general strategy for analyzing multi-regime pathways using only one fluorescent readout.

Towards the miniaturization of GPCR-based live-cell screening assays

G protein-coupled receptors (GPCRs) play a key role in many physiological or disease-related processes and for this reason are favorite targets of the pharmaceutical industry. Although ~30% of marketed drugs target GPCRs, their potential remains largely untapped. The discovery of new leads calls for the screening of thousands of compounds with high-throughput cell-based assays. Although microtiter plate-based high-throughput screening platforms are well established, microarray and microfluidic technologies hold potential for miniaturization, automation, and biosensor integration that may well redefine the format of GPCR screening assays. This paper reviews the latest research efforts directed to bringing microarray and microfluidic technologies into the realm of GPCR-based, live-cell screening assays.

Recent advances in single-cell studies of gene regulation

A mechanistic understanding of gene regulatory network dynamics requires quantitative single-cell data of multiple network components in response to well-defined perturbations. Recent advances in the development of fluorescent biomarkers for proteins, detection of RNA and interactions, microfluidic technology, and high-resolution imaging have set the stage for a host of new studies that elucidate the important roles of stochasticity and cell-cell variability in response to external perturbations. In this review, we briefly describe methods for high-resolution visualization and the control of gene expression, along with application of these novel methods to recent studies involving gene networks.

Microfluidics for single cell analysis

Substantial evidence shows that the heterogeneity of individual cells within a genetically identical population can be critical to their chance of survival. Methods that use average responses from a population often mask the difference from individual cells. To fully understand cell-to-cell variability, a complete analysis of an individual cell, from its live state to cell lysates, is essential. Highly sensitive detection of multiple components and high throughput analysis of a large number of individual cells remain the key challenges to realise this aim. In this context, microfluidics and lab-on-a-chip technology have emerged as the most promising avenue to address these challenges. In this review, we will focus on the recent development in microfluidics that are aimed at total single cell analysis on chip, that is, from an individual live cell to its gene and proteins. We also discuss the opportunities that microfluidic based single cell analysis can bring into the drug discovery process.

Information transduction capacity of noisy biochemical signaling networks

Molecular noise restricts the ability of an individual cell to resolve input signals of different strengths and gather information about the external environment. Transmitting information through complex signaling networks with redundancies can overcome this limitation. We developed an integrative theoretical and experimental framework, based on the formalism of information theory, to quantitatively predict and measure the amount of information transduced by molecular and cellular networks. Analyzing tumor necrosis factor (TNF) signaling revealed that individual TNF signaling pathways transduce information sufficient for accurate binary decisions, and an upstream bottleneck limits the information gained via multiple integrated pathways. Negative feedback to this bottleneck could both alleviate and enhance its limiting effect, despite decreasing noise. Bottlenecks likewise constrain information attained by networks signaling through multiple genes or cells.

Microfluidic array cytometer based on refractive optical tweezers for parallel trapping, imaging and sorting of individual cells

Analysis of genetic and functional variability in populations of living cells requires experimental techniques capable of monitoring cellular processes such as cell signaling of many single cells in parallel while offering the possibility to sort interesting cell phenotypes for further investigations. Although flow cytometry is able to sequentially probe and sort thousands of cells per second, dynamic processes cannot be experimentally accessed on single cells due to the sub-second sampling time. Cellular dynamics can be measured by image cytometry of surface-immobilized cells, however, cell sorting is complicated under these conditions due to cell attachment. We here developed a cytometric tool based on refractive multiple optical tweezers combined with microfluidics and optical microscopy. We demonstrate contact-free immobilization of more than 200 yeast cells into a high-density array of optical traps in a microfluidic chip. The cell array could be moved to specific locations of the chip enabling us to expose in a controlled manner the cells to reagents and to analyze the responses of individual cells in a highly parallel format using fluorescence microscopy. We further established a method to sort single cells within the microfluidic device using an additional steerable optical trap. Ratiometric fluorescence imaging of intracellular pH of trapped yeast cells allowed us on the one hand to measure the effect of the trapping laser on the cells' viability and on the other hand to probe the dynamic response of the cells upon glucose sensing.