Laimonas Kelbauskas, Shashanka Ashili, Jeff Houkal, Dean Smith, Aida Mohammadreza, Kristen Lee, Jessica Forrester, Ashok Kumar, Cody Youngbull, Yanqing Tian, Mark Holl, Roger Johnson, Deirdre Meldrum, Yasser Anis, Thomas Paulson
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 system's 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.
Shashanka Ashili, Laimonas Kelbauskas, Jeff Houkal, Dean Smith, Yanqing Tian, Cody Youngbull, Haixin Zhu, Yasser Anis, Michael Hupp, Kristen Lee, Ashok Kumar, Juan Vela, Andrew Shabilla, Roger Johnson, Mark Holl, Deirdre Meldrum
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.
Laimonas Kelbauskas, Shashanka Ashili, Jeff Houkal, Dean Smith, Aida Mohammadreza, Kristen Lee, Ashok Kumar, Yasser Anis, Tom Paulson, Cody Youngbull, Yanqing Tian, Roger Johnson, Mark Holl, Deirdre Meldrum
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.
This paper introduces a visual-servoing system used in the automation of microelectromechanical system microassembly. In the proposed system, small microparts, 20 µm wide and 2 µm thick, are automatically grasped using a passive compliant microgripper in a first step toward achieving complete automation of the microassembly process. A fuzzy logic controller uses vision-based position and force feedback to correct the microgripper and micropart alignment and to guide the system toward achievement of a successful grasp. A depth-from-defocus depth estimation technique is used to properly align the micropart in the same horizontal plane as the microgripper. The performance of the system is investigated experimentally, and experimental results are presented.
In this paper, a new visual force sensor is proposed to measure the microforces acting upon the jaws of passive, compliant microgrippers, used to construct out-of-plane 3-D microstructures. The vision-based force measurement technique is reduced to determining the deflections of the microgripper jaws during the microassembly process. A computer vision system is used to measure the deflections in the gripper's jaws during the joining and grasping processes. A mathematical model of the microgripper system was developed where a relation between the force and the jaw displacement was deduced. Image processing methods, such as Zero-crossing Laplacian of Gaussian edge detection and region-filling, are used. The relative positions of the microgripper jaws, with respect to the gripper's pad, are determined by means of object recognition. Performed experiments confirm the success of the proposed sensor and verify that the measured deflections comply with the profile variations of the microgripper.
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