Multichannel impedance cytometry downstream of cell separation by deterministic lateral displacement to quantify macrophage enrichment in heterogeneous samples

Neural Network-Enabled Multiparametric Impedance Signal Templating for High throughput Single-Cell Deformability Cytometry Under Viscoelastic Extensional Flows

Cellular biophysical metrics exhibit systematic alterations during processes, such as metastasis and immune cell activation, which can be used to identify and separate live cell subpopulations for targeting drug screening. Image-based biophysical cytometry under extensional flows can accurately quantify cell deformability based on cell shape alterations but needs extensive image reconstruction, which limits its inline utilization to activate cell sorting. Impedance cytometry can measure these cell shape alterations based on electric field screening, while its frequency response offers functional information on cell viability and interior structure, which are difficult to discern by imaging. Furthermore, 1-D temporal impedance signal trains exhibit characteristic shapes that can be rapidly templated in near real-time to extract single-cell biophysical metrics to activate sorting. We present a multilayer perceptron neural network signal templating approach that utilizes raw impedance signals from cells under extensional flow, alongside its training with image metrics from corresponding cells to derive net electrical anisotropy metrics that quantify cell deformability over wide anisotropy ranges and with minimal errors from cell size distributions. Deformability and electrical physiology metrics are applied in conjunction on the same cell for multiparametric classification of live pancreatic cancer cells versus cancer associated fibroblasts using the support vector machine model.

Performance optimization of a DLD microfluidic device for separating deformable CTCs

Deterministic lateral displacement (DLD) microfluidic devices work based on the streamlines created by an array of micro-posts. The configuration of pillars alters the isolation efficiency of these devices. The present paper optimizes the performance of a DLD device for isolating deformable circulating tumor cells. The input variables include cell diameter (d), Young's modulus (E s ${E}_s$ ), Reynolds number (Re), and tan θ, where θ is the tilted angle of micro-posts. The output, which is the response of the system, is DLD. The numerical simulation results are employed to optimize the device using the response surface method, leading to the proposition of a correlation to estimate DLD as a function of input variables. It is demonstrated that the maximum and minimum impacts on cell lateral displacement correspond toE s ${E}_s$ and Re, respectively.

A microfluidic impedance cytometry device for robust identification of H. pluvialis

H. pluvialis contains rich oleic acid and astaxanthin, which have important applications in the fields of biodiesel and biomedicine. Detection of live H. pluvialis is the prerequisite to obtaining oleic acid and astaxanthin. For this purpose, we successfully developed a reliable microfluidic impedance cytometry for the identification of live H. pluvialis. Firstly, we established a simulation model for detecting H. pluvialis based on their morphology and studied the effect of medium conductivity on the impedance of H. pluvialis at different frequencies. From the simulations, we determined that the optimal solution conductivity for the detection of H. pluvialis was 1500 μS cm-1 and studied the frequency responses of the impedance of H. pluvialis. Secondly, we fabricated the microchannels and stainless-steel detection electrodes and assembled them into microfluidic impedance cytometry. The frequency dependence of live and dead H. pluvialis was explored under different frequencies, and live and dead H. pluvialis were distinguished at a frequency of 1 MHz. The impedance of live H. pluvialis at the frequency of 1 MHz ranges from 33.73 to 52.23 Ω, while that of dead ones ranges from 13.05 to 19.59 Ω. Based on these findings, we accomplished the identification and counting of live H. pluvialis in the live and dead sample solutions. Furthermore, we accomplished the identification and counting of live H. pluvialis in the mixed samples containing Euglena and H. pluvialis. This approach possesses the promising capacity to serve as a robust tool in the identification of target microalgae, addressing a challenge in the fields of biodiesel and biomedicine.

Dielectrophoretic enrichment of live chemo-resistant circulating-like pancreatic cancer cells from media of drug-treated adherent cultures of solid tumors

Due to low numbers of circulating tumor cells (CTCs) in liquid biopsies, there is much interest in enrichment of alternative circulating-like mesenchymal cancer cell subpopulations from in vitro tumor cultures for utilization within molecular profiling and drug screening. Viable cancer cells that are released into the media of drug-treated adherent cancer cell cultures exhibit anoikis resistance or anchorage-independent survival away from their extracellular matrix with nutrient sources and waste sinks, which serves as a pre-requisite for metastasis. The enrichment of these cell subpopulations from tumor cultures can potentially serve as an in vitro source of circulating-like cancer cells with greater potential for scale-up in comparison with CTCs. However, these live circulating-like cancer cell subpopulations exhibit size overlaps with necrotic and apoptotic cells in the culture media, which makes it challenging to selectively enrich them, while maintaining them in their suspended state. We present optimization of a flowthrough high frequency (1 MHz) positive dielectrophoresis (pDEP) device with sequential 3D field non-uniformities that enables enrichment of the live chemo-resistant circulating cancer cell subpopulation from an in vitro culture of metastatic patient-derived pancreatic tumor cells. Central to this strategy is the utilization of single-cell impedance cytometry with gates set by supervised machine learning, to optimize the frequency for pDEP, so that live circulating cells are selected based on multiple biophysical metrics, including membrane physiology, cytoplasmic conductivity and cell size, which is not possible using deterministic lateral displacement that is solely based on cell size. Using typical drug-treated samples with low levels of live circulating cells (<3%), we present pDEP enrichment of the target subpopulation to ∼44% levels within 20 minutes, while rejecting >90% of dead cells. This strategy of utilizing single-cell impedance cytometry to guide the optimization of dielectrophoresis has implications for other complex biological samples.