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Dielectrophoresis (DEP) is a powerful tool for label-free sorting of cells, even those with subtle differences in morphological and dielectric properties. Nevertheless, a major limitation is that most existing DEP techniques can efficiently sort cells only at low throughputs (<1 mL h−1). Here, we demonstrate that the integration of a three-dimensional (3D) coupled hydrodynamic-DEP cell pre-focusing module upstream of the main DEP sorting region enables cell sorting with a 10-fold increase in throughput compared to conventional DEP approaches. To better understand the key principles and requirements for high-throughput cell separation, we present a comprehensive theoretical model to study the scaling of hydrodynamic and electrostatic forces on cells at high flow rate regimes. Based on the model, we show that the critical cell-to-electrode distance needs to be ≤10 µm for efficient cell sorting in our proposed microfluidic platform, especially at flow rates ≥ 1 mL h−1. Based on those findings, a computational fluid dynamics model and particle tracking analysis were developed to find optimum operation parameters (e.g., flow rate ratios and electric fields) of the coupled hydrodynamic-DEP 3D focusing module. Using these optimum parameters, we experimentally demonstrate live/dead K562 cell sorting at rates as high as 10 mL h−1 (>150,000 cells min−1) with 90% separation purity, 85% cell recovery, and no negative impact on cell viability.

 

We demonstrate a label free and high-throughput microbubble-based acoustic microstreaming technique to isolate rare circulating cells such as circulating cancer associated fibroblasts (cCAFs) in addition to circulating tumor cells (CTCs) and immune cells ( i.e. leukocytes) from clinically diagnosed patients with a capture efficiency of 94% while preserving cell functional integrity within 8 minutes. The microfluidic device is self-pumping and was optimized to increase flow rate and achieve near perfect capturing of rare cells enabled by having a trapping capacity above the acoustic vortex saturation concentration threshold. Our approach enables rapid isolation of CTCs, cCAFs and their associated clusters from blood samples of cancer patients at different stages. By examining the combined role of cCAFs and CTCs in early cancer onset and metastasis progression, the device accurately diagnoses both cancer and the metastatic propensity of breast cancer patients. This was confirmed by flow cytometry where we observed that metastatic breast cancer blood samples had significantly higher percentage of exhausted CD8 + T cells expressing programmed cell death protein 1 (PD1), higher number of CD4 + T regulatory cells and T helper cells. We show for the first time that our lateral cavity acoustic transducers (LCATs)-based approach can thus be developed into a metastatic propensity assay for clinical usage by elucidating cancer immunological responses and the complex relationships between CTCs and its companion tumor microenvironment. 

We present an integrated microfluidic chip capable of label-free isolation of three major subpopulations of white blood cells (WBCs) (lymphocytes, monocytes and granulocytes) from undiluted whole blood. The proposed system accomplishes 3-part differential sorting of WBCs by: (1) On-chip lysis of RBCs from the blood sample, and (2) Downstream isolation of lymphocytes, monocytes and granulocytes using dielectrophoresis (DEP) technology. 

A high‐throughput non‐viral intracellular delivery platform is introduced for the transfection of large cargos with dosage‐control. This platform, termed Acoustic‐Electric Shear Orbiting Poration (AESOP), optimizes the delivery of intended cargo sizes with poration of the cell membranes via mechanical shear followed by the modulated expansion of these nanopores via electric field. Furthermore, AESOP utilizes acoustic microstreaming vortices wherein up to millions of cells are trapped and mixed uniformly with exogenous cargos, enabling the delivery of cargos into cells with targeted dosages. Intracellular delivery of a wide range of molecule sizes (<1 kDa to 2 MDa) with high efficiency (>90%), cell viability (>80%), and uniform dosages (<60% coefficient of variation (CV)) simultaneously into 1 million cells min⁻¹per single chip is demonstrated. AESOP is successfully applied to two gene editing applications that require the delivery of large plasmids: i) enhanced green fluorescent protein (eGFP) plasmid (6.1 kbp) transfection, and ii) clustered regularly interspaced short palindromic repeats (CRISPR)‐Cas9‐mediated gene knockout using a 9.3 kbp plasmid DNA encoding Cas9 protein and single guide RNA (sgRNA). Compared to alternative platforms, this platform offers dosage‐controlled intracellular delivery of large plasmids simultaneously to large populations of cells while maintaining cell viability at comparable delivery efficiencies.

 

Characterization of single cell metabolism is imperative for understanding subcellular functional and biochemical changes associated with healthy tissue development and the progression of numerous diseases. However, single‐cell analysis often requires the use of fluorescent tags and cell lysis followed by genomic profiling to identify the cellular heterogeneity. Identifying individual cells in a noninvasive and label‐free manner is crucial for the detection of energy metabolism which will discriminate cell types and most importantly critical for maintaining cell viability for further analysis. Here, we have developed a robust assay using the droplet microfluidic technology together with the phasor approach to fluorescence lifetime imaging microscopy to study cell heterogeneity within and among the leukemia cell lines (K‐562 and Jurkat). We have extended these techniques to characterize metabolic differences between proliferating and quiescent cells—a critical step toward label‐free single cancer cell dormancy research. The result suggests a droplet‐based noninvasive and label‐free method to distinguish individual cells based on their metabolic states, which could be used as an upstream phenotypic platform to correlate with genomic statistics. © 2018 International Society for Advancement of Cytometry