Jeff Houkal

Method for physiologic phenotype characterization at the single-cell level in non-interacting and interacting cells

Intercellular heterogeneity is a key factor in a variety of core cellular processes including proliferation, stimulus response, carcinogenesis, and drug resistance. However, cell-to-cell variability studies at the single-cell level have been hampered by the lack of enabling experimental techniques. We present a measurement platform that features the capability to quantify oxygen consumption rates of individual, non-interacting and interacting cells under normoxic and hypoxic conditions. It is based on real-time concentration measurements of metabolites of interest by means of extracellular optical sensors in cell-isolating microwells of subnanoliter volume. We present the results of a series of measurements of oxygen consumption rates (OCRs) of individual non-interacting and interacting human epithelial cells. We measured the effects of cell-to-cell interactions by using the systems capability to isolate two and three cells in a single well. The major advantages of the approach are: 1. ratiometric, intensity-based characterization of the metabolic phenotype at the single-cell level, 2. minimal invasiveness due to the distant positioning of sensors, and 3. ability to study the effects of cell-cell interactions on cellular respiration rates.

A platform for high-throughput bioenergy production phenotype characterization in single cells

Driven by an increasing number of studies demonstrating its relevance to a broad variety of disease states, the bioenergy production phenotype has been widely characterized at the bulk sample level. Its cell-to-cell variability, a key player associated with cancer cell survival and recurrence, however, remains poorly understood due to ensemble averaging of the current approaches. We present a technology platform for performing oxygen consumption and extracellular acidification measurements of several hundreds to 1,000 individual cells per assay, while offering simultaneous analysis of cellular communication effects on the energy production phenotype. The platform comprises two major components: a tandem optical sensor for combined oxygen and pH detection, and a microwell device for isolation and analysis of single and few cells in hermetically sealed sub-nanoliter chambers. Our approach revealed subpopulations of cells with aberrant energy production profiles and enables determination of cellular response variability to electron transfer chain inhibitors and ion uncouplers.

Automated platform for multiparameter stimulus response studies of metabolic activity at the single-cell level

We have developed a fully automated platform for multiparameter characterization of physiological response of individual and small numbers of interacting cells. The platform allows for minimally invasive monitoring of cell phenotypes while administering a variety of physiological insults and stimuli by means of precisely controlled microfluidic subsystems. It features the capability to integrate a variety of sensitive intra- and extra-cellular fluorescent probes for monitoring minute intra- and extra-cellular physiological changes. The platform allows for performance of other, post- measurement analyses of individual cells such as transcriptomics. Our method is based on the measurement of extracellular metabolite concentrations in hermetically sealed ~200-pL microchambers, each containing a single cell or a small number of cells. The major components of the system are a) a confocal laser scan head to excite and detect with single photon sensitivity the emitted photons from sensors; b) a microfluidic cassette to confine and incubate individual cells, providing for dynamic application of external stimuli, and c) an integration module consisting of software and hardware for automated cassette manipulation, environmental control and data collection. The custom-built confocal scan head allows for fluorescence intensity detection with high sensitivity and spatial confinement of the excitation light to individual pixels of the sensor area, thus minimizing any phototoxic effects. The platform is designed to permit incorporation of multiple optical sensors for simultaneous detection of various metabolites of interest. The modular detector structure allows for several imaging modalities, including high resolution intracellular probe imaging and extracellular sensor readout. The integrated system allows for simulation of physiologically relevant microenvironmental stimuli and simultaneous measurement of the elicited phenotypes. We present details of system design, system characterization and metabolic response analysis of individual eukaryotic cells.

A novel method for multiparameter physiological phenotype characterization at the single-cell level

Non-genetic intercellular heterogeneity has been increasingly recognized as one of the key factors in a variety of core cellular processes including proliferation, stimulus response, carcinogenesis and drug resistance. Many diseases, including cancer, originate in a single or a few cells. Early detection and characterization of these abnormal cells can provide new insights into the pathogenesis and serve as a tool for better disease diagnosis and treatment. We report on a novel technology for multiparameter physiological phenotype characterization at the single-cell level. It is based on real-time measurements of concentrations of several metabolites by means of extracellular optical sensors in microchambers of sub-nL volume containing single cells. In its current configuration, the measurement platform features the capability to detect oxygen consumption rate and pH changes under normoxic and hypoxic conditions at the single-cell level. We have conceived, designed and developed a semi-automated method for single-cell manipulation and loading into microwells utilizing custom, high-precision fluid handling at the nanoliter scale. We present the results of a series of measurements of oxygen consumption rates (OCRs) of single human metaplastic esophageal epithelial cells. In addition, to assess the effects of cell-to-cell interactions, we have measured OCRs of two and three cells placed in a single well. The major advantages of the approach are a) multiplexed characterization of cell phenotype at the single-cell level, b) minimal invasiveness due to the distant positioning of sensors, and c) flexibility in terms of accommodating measurements of other metabolites or biomolecules of interest.