Open-Top Patterned Hydrogel-Laden 3D Glioma Cell Cultures for Creation of Dynamic Chemotactic Gradients to Direct Cell Migration.

The laminar flow profiles in microfluidic systems coupled to rapid diffusion at flow streamlines have been widely utilized to create well-controlled chemical gradients in cell cultures for spatially directing cell migration. However, within hydrogel-based closed microfluidic systems of limited depth (≤0.1 mm), the biomechanical cues for the cell culture are dominated by cell interactions with channel surfaces rather than with the hydrogel microenvironment. Also, leaching of poly(dimethylsiloxane) (PDMS) constituents in closed systems and the adsorption of small molecules to PDMS alter chemotactic profiles. To address these limitations, we present the patterning and integration of a PDMS-free open fluidic system, wherein the cell-laden hydrogel directly adjoins longitudinal channels that are designed to create chemotactic gradients across the 3D culture width, while maintaining uniformity across its ∼1 mm depth to enhance cell-biomaterial interactions. This hydrogel-based open fluidic system is assessed for its ability to direct migration of U87 glioma cells using a hybrid hydrogel that includes hyaluronic acid (HA) to mimic the brain tumor microenvironment and gelatin methacrylate (GelMA) to offer the adhesion motifs for promoting cell migration. Chemotactic gradients to induce cell migration across the hydrogel width are assessed using the chemokine CXCL12, and its inhibition by AMD3100 is validated. This open-top hydrogel-based fluidic system to deliver chemoattractant cues over square-centimeter-scale areas and millimeter-scale depths can potentially serve as a robust screening platform to assess emerging glioma models and chemotherapeutic agents to eradicate them.

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.

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

The integration of on-chip biophysical cytometry downstream of microfluidic enrichment for inline monitoring of phenotypic and separation metrics at single-cell sensitivity can allow for active control of separation and its application to versatile sample sets. We present integration of impedance cytometry downstream of cell separation by deterministic lateral displacement (DLD) for enrichment of activated macrophages from a heterogeneous sample, without the problems of biased sample loss and sample dilution caused by off-chip analysis. This required designs to match cell/particle flow rates from DLD separation into the confined single-cell impedance cytometry stage, the balancing of flow resistances across the separation array width to maintain unidirectionality, and the utilization of co-flowing beads as calibrated internal standards for inline assessment of DLD separation and for impedance data normalization. Using a heterogeneous sample with un-activated and activated macrophages, wherein macrophage polarization during activation causes cell size enlargement, on-chip impedance cytometry is used to validate DLD enrichment of the activated subpopulation at the displaced outlet, based on the multiparametric characteristics of cell size distribution and impedance phase metrics. This hybrid platform can monitor separation of specific subpopulations from cellular samples with wide size distributions, for active operational control and enhanced sample versatility.

Correlating Antibiotic-Induced Dysbiosis to Clostridioides difficile Spore Germination and Host Susceptibility to Infection Using an Ex Vivo Assay.

Antibiotic-induced microbiota disruption and its persistence create conditions for dysbiosis and colonization by opportunistic pathogens, such as those causing Clostridioides difficile (C. difficile) infection (CDI), which is the most severe hospital-acquired intestinal infection. Given the wide differences in microbiota across hosts and in their recovery after antibiotic treatments, there is a need for assays to assess the influence of dysbiosis and its recovery dynamics on the susceptibility of the host to CDI. Germination of C. difficile spores is a key virulence trait for the onset of CDI, which is influenced by the level of primary vs secondary bile acids in the intestinal milieu that is regulated by the microbiota composition. Herein, the germination of C. difficile spores in fecal supernatant from mice that are subject to varying degrees of antibiotic treatment is utilized as an ex vivo assay to predict intestinal dysbiosis in the host based on their susceptibility to CDI, as determined by in vivo CDI metrics in the same mouse model. Quantification of spore germination down to lower detection limits than the colony-forming assay is achieved by using impedance cytometry to count single vegetative bacteria that are identified based on their characteristic electrical physiology for distinction vs aggregated spores and cell debris in the media. As a result, germination can be quantified at earlier time points and with fewer spores for correlation to CDI outcomes. This sets the groundwork for a point-of-care tool to gauge the susceptibility of human microbiota to CDI after antibiotic treatments.

Supervised learning on impedance cytometry data for label-free biophysical distinction of pancreatic cancer cells versus their associated fibroblasts under gemcitabine treatment.

Chemotherapy failure in pancreatic cancer patients is widely attributed to cancer cell reprogramming towards drug resistance by cancer associated fibroblasts (CAFs), which are the abundant cell type in the tumor microenvironment. Association of drug resistance to specific cancer cell phenotypes within multicellular tumors can advance isolation protocols for enabling cell-type specific gene expression markers to identify drug resistance. This requires the distinction of drug resistant cancer cells versus CAFs, which is challenging since permeabilization of CAF cells during drug treatment can cause non-specific uptake of cancer cell-specific stains. Cellular biophysical metrics, on the other hand, can provide multiparametric information to assess the gradual alteration of target cancer cells towards drug resistance, but these phenotypes need to be distinguished versus CAFs. Using pancreatic cancer cells and CAFs from a metastatic patient-derived tumor that exhibits cancer cell drug resistance under CAF co-culture, the biophysical metrics from multifrequency single-cell impedance cytometry are utilized for distinction of the subpopulation of viable cancer cells versus CAFs, before and after gemcitabine treatment. This is accomplished through supervised machine learning after training the model using key impedance metrics for cancer cells and CAFs from transwell co-cultures, so that an optimized classifier model can recognize each cell type and predict their respective proportions in multicellular tumor samples, before and after gemcitabine treatment, as validated by their confusion matrix and flow cytometry assays. In this manner, an aggregate of the distinguishing biophysical metrics of viable cancer cells after gemcitabine treatment in co-cultures with CAFs can be used in longitudinal studies, to classify and isolate the drug resistant subpopulation for identifying markers.

Sensor technologies for quality control in engineered tissue manufacturing.

The use of engineered cells, tissues, and organs has the opportunity to change the way injuries and diseases are treated. Commercialization of these groundbreaking technologies has been limited in part by the complex and costly nature of their manufacture. Process-related variability and even small changes in the manufacturing process of a living product will impact its quality. Without real-time integrated detection, the magnitude and mechanism of that impact are largely unknown. Real-time and non-destructive sensor technologies are key for in-process insight and ensuring a consistent product throughout commercial scale-up and/or scale-out. The application of a measurement technology into a manufacturing process requires cell and tissue developers to understand the best way to apply a sensor to their process, and for sensor manufacturers to understand the design requirements and end-user needs. Furthermore, sensors to monitor component cells' health and phenotype need to be compatible with novel integrated and automated manufacturing equipment. This review summarizes commercially relevant sensor technologies that can detect meaningful quality attributes during the manufacturing of regenerative medicine products, the gaps within each technology, and sensor considerations for manufacturing.

Automated biophysical classification of apoptotic pancreatic cancer cell subpopulations by using machine learning approaches with impedance cytometry.

Unrestricted cell death can lead to an immunosuppressive tumor microenvironment, with dysregulated apoptotic signaling that causes resistance of pancreatic cancer cells to cytotoxic therapies. Hence, modulating cell death by distinguishing the progression of subpopulations under drug treatment from viable towards early apoptotic, late apoptotic, and necrotic states is of interest. While flow cytometry after fluorescent staining can monitor apoptosis with single-cell sensitivity, the background of non-viable cells within non-immortalized pancreatic tumors from xenografts can confound distinction of the intensity of each apoptotic state. Based on single-cell impedance cytometry of drug-treated pancreatic cancer cells that are obtained from tumor xenografts with differing levels of gemcitabine sensitivity, we identify the biophysical metrics that can distinguish and quantify cellular subpopulations at the early apoptotic versus late apoptotic and necrotic states, by using machine learning methods to train for the recognition of each phenotype. While supervised learning has previously been used for classification of datasets with known classes, our advancement is the utilization of optimal positive controls for each class, so that clustering by unsupervised learning and classification by supervised learning can occur on unknown datasets, without human interference or manual gating. In this manner, automated biophysical classification can be used to follow the progression of apoptotic states in each heterogeneous drug-treated sample, for developing drug treatments to modulate cancer cell death and advance longitudinal analysis to discern the emergence of drug resistant phenotypes.

Biophysical quantification of reorganization dynamics of human pancreatic islets during co-culture with adipose-derived stem cells.

Islet transplantation is a potential therapy for type 1 diabetes, but it is expensive due to limited pancreas donor numbers and the variability in islet quality. The latter is often addressed by co-culture of harvested islets with stem cells to promote in vitro remodeling of their basement membrane and enable expression of angiogenic factors for enhancing vascularization. However, given the heterogeneity in islet size, shape and function, there is a need for metrics to assess the reorganization dynamics of single islets over the co-culture period. Based on shape-evolution of individual multi-cell aggregates formed during co-culture of human islets with adipose derived stem cells and the pressures required for their bypass through microfluidic constrictions, we present size-normalized biomechanical metrics for monitoring the reorganization. Aggregates below a threshold size exhibit faster reorganization, as evident from rise in their biomechanical opacity and tightening of their size distribution, but this size threshold increases over culture time to include a greater proportion of the aggregates. Such biomechanical metrics can quantify the subpopulation of reorganized aggregates by distinguishing them versus those with incomplete reorganization, over various timepoints during the co-culture.

Single-cell assessment of the modulation of macrophage activation by ex vivo intervertebral discs using impedance cytometry.

Measurement of macrophage activation and its modulation for immune regulation is of great interest to arrest inflammatory responses associated with degeneration of intervertebral discs that cause chronic back pain, and with transplants that face immune rejection. Due to the phenotypic plasticity of macrophages that serve multiple immune functions, the net disease outcome is determined by a balance of subpopulations with competing functions, highlighting the need for single-cell methods to quantify heterogeneity in their activation phenotypes. However, since macrophage activation can follow several signaling pathways, cytometry after fluorescent staining of markers with antibodies does not often provide dose-dependent information on activation dynamics. We present high throughput single-cell impedance cytometry for multiparametric measurement of biophysical changes to individual macrophages for quantifying activation in a dose and duration dependent manner, without relying on a particular signaling pathway. Impedance phase metrics measured at two frequencies and the electrical diameter from impedance magnitude at lower frequencies are used in tandem to benchmark macrophage activation by degenerated discs against that from lipopolysaccharide stimulation at varying dose and duration levels, so that reversal of the activation state by curcumin can be ascertained. This label-free single-cell measurement method can form the basis for platforms to screen therapies for inflammation, thereby addressing the chronic problem of back pain.

On-chip microfluidic buffer swap of biological samples in-line with downstream dielectrophoresis.

Microfluidic cell enrichment by dielectrophoresis, based on biophysical and electrophysiology phenotypes, requires that cells be resuspended from their physiological media into a lower conductivity buffer for enhancing force fields and enabling the dielectric contrast needed for separation. To ensure that sensitive cells are not subject to centrifugation for resuspension and spend minimal time outside of their culture media, we present an on-chip microfluidic strategy for swapping cells into media tailored for dielectrophoresis. This strategy transfers cells from physiological media into a 100-fold lower conductivity media by using tangential flows of low media conductivity at 200-fold higher flow rate versus sample flow to promote ion diffusion over the length of a straight channel architecture that maintains laminarity of the flow-focused sample and minimizes cell dispersion across streamlines. Serpentine channels are used downstream from the flow-focusing region to modulate hydrodynamic resistance of the central sample outlet versus flanking outlets that remove excess buffer, so that cell streamlines are collected in the exchanged buffer with minimal dilution in cell numbers and at flow rates that support dielectrophoresis. We envision integration of this on-chip sample preparation platform prior to or post-dielectrophoresis, in-line with on-chip monitoring of the outlet sample for metrics of media conductivity, cell velocity, cell viability, cell position, and collected cell numbers, so that the cell flow rate and streamlines can be tailored for enabling dielectrophoretic separations from heterogeneous samples.

Modified Red Blood Cells as Multimodal Standards for Benchmarking Single-Cell Cytometry and Separation Based on Electrical Physiology.

Biophysical cellular information at single-cell sensitivity is becoming increasingly important within analytical and separation platforms that associate the cell phenotype with markers of disease, infection, and immunity. Frequency-modulated electrically driven microfluidic measurement and separation systems offer the ability to sensitively identify single cells based on biophysical information, such as their size and shape, as well as their subcellular membrane morphology and cytoplasmic organization. However, there is a lack of reliable and reproducible model particles with well-tuned subcellular electrical phenotypes that can be used as standards to benchmark the electrical physiology of unknown cell types or to benchmark dielectrophoretic separation metrics of novel device strategies. Herein, the application of red blood cells (RBCs) as multimodal standard particles with systematically modulated subcellular electrophysiology and associated fluorescence level is presented. Using glutaraldehyde fixation to vary membrane capacitance and by membrane resealing after electrolyte penetration to vary interior cytoplasmic conductivity and fluorescence in a correlated manner, each modified RBC type can be identified at single-cell sensitivity based on phenomenological impedance metrics and fitted to dielectric models to compute biophysical information. In this manner, single-cell impedance data from unknown RBC types can be mapped versus these model RBC types for facile determination of subcellular biophysical information and their dielectrophoretic separation conditions, without the need for time-consuming algorithms that often require unknown fitting parameters. Such internal standards for biophysical cytometry can advance in-line phenotypic recognition strategies.

Perfusable cell-laden micropatterned hydrogels for delivery of spatiotemporal vascular-like cues to tissues.

The integration of vasculature at physiological scales within 3D cultures of cell-laden hydrogels for the delivery of spatiotemporal mass transport, chemical and mechanical cues, is a stepping-stone towards building in vitro tissue models that recapitulate in vivo cues. To address this challenge, we present a versatile method to micropattern adjoining hydrogel shells with a perfusable channel or lumen core, for enabling facile integration with fluidic control systems, on one hand, and to cell-laden biomaterial interfaces, on the other hand. This microfluidic imprint lithography methodology utilizes the high tolerance and reversible nature of the bond alignment process to lithographically position multiple layers of imprints within a microfluidic device for sequential filling and patterning of hydrogel lumen structures with single or multiple shells. Through fluidic interfacing of the structures, the ability to deliver physiologically relevant mechanical cues for recapitulating cyclical stretch on the hydrogel shell and shear stress on endothelial cells in the lumen are validated. We envision application of this platform for recapitulation of the bio-functionality and topology of micro-vasculatures, alongside the ability to deliver transport and mechanical cues, as needed for 3D culture to construct in vitro tissue models.

Multiplexed assessment of engineered bacterial constructs for intracellular ß-galactosidase expression by redox amplification on catechol-chitosan modified nanoporous gold.

Synthetic biology approaches for rewiring of bacterial constructs to express particular intracellular factors upon induction with the target analyte are emerging as sensing paradigms for applications in environmental and in vivo monitoring. To aid in the design and optimization of bacterial constructs for sensing analytes, there is a need for lysis-free intracellular detection modalities that monitor the signal level and kinetics of expressed factors within different modified bacteria in a multiplexed manner, without requiring cumbersome surface immobilization. Herein, an electrochemical detection system on nanoporous gold that is electrofabricated with a biomaterial redox capacitor is presented for quantifying ß-galactosidase expressed inside modified Escherichia coli constructs upon induction with dopamine. This nanostructure-mediated redox amplification approach on a microfluidic platform allows for multiplexed assessment of the expressed intracellular factors from different bacterial constructs suspended in distinct microchannels, with no need for cell lysis or immobilization. Since redox mediators present over the entire depth of the microchannel can interact with the electrode and with the E. coli construct in each channel, the platform exhibits high sensitivity and enables multiplexing. We envision its application in assessing synthetic biology-based approaches for comparing specificity, sensitivity, and signal response time upon induction with target analytes of interest.

Real-Time Detection and Control of Microchannel Resonance Frequency in Acoustic Trapping Systems by Monitoring Amplifier Supply Currents.

The utilization of bulk acoustic waves from a piezoelectric transducer for selective particle trapping under flow in a microchannel is limited by the high sensitivity of the resonance frequency to tolerances in device geometry, drift during trapping, and variations in the local flow or sample conditions in each channel. This is addressed by detecting the resonance condition based on the impedance minimum obtained by monitoring the amplitude of the stimulation voltage across the piezo transducer and utilizing real-time feedback to control the stimulation frequency. However, this requires an overlap in the frequency bandwidth of the detection and the stimulation system and is also limited by the decline in the acoustic trapping power when the stimulation and resonance frequency measurement are conducted simultaneously. Instead, we present a novel circuit implementation for on-chip real-time resonance frequency measurement and feedback control based on monitoring the current drawn from the amplifier used to stimulate the piezo transducer, since the need for high measurement sensitivity in this mode does not lower the power available for stimulation of the transducer. The enhanced level of control of acoustic trapping utilizing this current mode is validated for various localized channel perturbations, including drift, wash steps, and buffer swaps, as well as for selective sperm cell trapping from a heterogeneous sample that includes lysed epithelial cells.

Apoptotic Bodies in the Pancreatic Tumor Cell Culture Media Enable Label-Free Drug Sensitivity Assessment by Impedance Cytometry.

The ability to rapidly and sensitively predict drug response and toxicity using in vitro models of patient-derived tumors is essential for assessing chemotherapy efficacy. Currently, drug sensitivity assessment for solid tumors relies on imaging adherent cells or by flow cytometry of cells lifted from drug-treated cultures after fluorescent staining for apoptotic markers. Subcellular apoptotic bodies (ABs), including microvesicles that are secreted into the culture media under drug treatment can potentially serve as markers for drug sensitivity, without the need to lift cells under culture. However, their stratification to quantify cell disassembly is challenging due to their compositional diversity, with tailored labeling strategies currently needed for the recognition and cytometry of each AB type. It is shown that the high frequency impedance phase versus size distribution of ABs determined by high-throughput single-particle impedance cytometry of supernatants in the media of gemcitabine-treated pancreatic tumor cultures exhibits phenotypic resemblance to lifted apoptotic cells and enables shape-based stratification within distinct size ranges, which is not possible by flow cytometry. It is envisioned that this tool can be applied in conjunction with the appropriate pancreatic tumor microenvironment model to assess drug sensitivity and toxicity of patient-derived tumors, without the need to lift cells from cultures.

A novel ultralow conductivity electromanipulation buffer improves cell viability and enhances dielectrophoretic consistency.

Cell separation has become a critical diagnostic, research, and treatment tool for personalized medicine. Despite significant advances in cell separation, most widely used applications require the use of multiple, expensive antibodies to known markers in order to identify subpopulations of cells for separation. Dielectrophoresis (DEP) provides a biophysical separation technique that can target cell subpopulations based on phenotype without labels and return native cells for downstream analysis. One challenge in employing any DEP device is the sample being separated must be transferred into an ultralow conductivity medium, which can be detrimental in retaining cells' native phenotypes for separation. Here, we measured properties of traditional DEP reagents and determined that after just 1-2 h of exposure and subsequent culture, cells' viability was significantly reduced below 50%. We developed and tested a novel buffer (Cyto Buffer) that achieved 6 weeks of stable shelf-life and demonstrated significantly improved viability and physiological properties. We then determined the impact of Cyto Buffer on cells' dielectric properties and morphology and found that cells retained properties more similar to that of their native media. Finally, we vetted Cyto Buffer's usability on a cell separation platform (Cyto R1) to determine combined efficacy for cell separations. Here, more than 80% of cells from different cell lines were recovered and were determined to be >70% viable following exposure to Cyto Buffer, flow stimulation, electromanipulation, and downstream collection and growth. The developed buffer demonstrated improved opportunities for electrical cell manipulation, enrichment, and recovery for next generation cell separations.

Self-aligned sequential lateral field non-uniformities over channel depth for high throughput dielectrophoretic cell deflection.

Dielectrophoresis (DEP) enables the separation of cells based on subtle subcellular phenotypic differences by controlling the frequency of the applied field. However, current electrode-based geometries extend over a limited depth of the sample channel, thereby reducing the throughput of the manipulated sample (sub-µL min-1 flow rates and <105 cells per mL). We present a flow through device with self-aligned sequential field non-uniformities extending laterally across the sample channel width (100 µm) that are created by metal patterned over the entire depth (50 µm) of the sample channel sidewall using a single lithography step. This enables single-cell streamlines to undergo progressive DEP deflection with minimal dependence on the cell starting position, its orientation versus the field and intercellular interactions. Phenotype-specific cell separation is validated (>µL min-1 flow and >106 cells per mL) using heterogeneous samples of healthy and glutaraldehyde-fixed red blood cells, with single-cell impedance cytometry showing that the DEP collected fractions are intact and exhibit electrical opacity differences consistent with their capacitance-based DEP crossover frequency. This geometry can address the vision of an "all electric" selective cell isolation and cytometry system for quantifying phenotypic heterogeneity of cellular systems.

Single-cell microfluidic impedance cytometry: from raw signals to cell phenotypes using data analytics.

The biophysical analysis of single-cells by microfluidic impedance cytometry is emerging as a label-free and high-throughput means to stratify the heterogeneity of cellular systems based on their electrophysiology. Emerging applications range from fundamental life-science and drug assessment research to point-of-care diagnostics and precision medicine. Recently, novel chip designs and data analytic strategies are laying the foundation for multiparametric cell characterization and subpopulation distinction, which are essential to understand biological function, follow disease progression and monitor cell behaviour in microsystems. In this tutorial review, we present a comparative survey of the approaches to elucidate cellular and subcellular features from impedance cytometry data, covering the related subjects of device design, data analytics (i.e., signal processing, dielectric modelling, population clustering), and phenotyping applications. We give special emphasis to the exciting recent developments of the technique (timeframe 2017-2020) and provide our perspective on future challenges and directions. Its synergistic application with microfluidic separation, sensor science and machine learning can form an essential toolkit for label-free quantification and isolation of subpopulations to stratify heterogeneous biosystems.

Label-Free Quantification of Cell Cycle Synchronicity of Human Neural Progenitor Cells Based on Electrophysiology Phenotypes.

The ability to coax human-induced pluripotent stem cells (hiPSCs) into human neural progenitor cells (hNPCs) can lead to novel drug discovery and transplant therapy platforms for neurological diseases. Since hNPCs can form organoids that mimic brain development, there is emerging interest in their label-free characterization for controlling cell composition to optimize organoid formation in three-dimensional (3D) cultures. However, this requires the ability to quantify hNPCs in heterogeneous samples with subpopulations of similar phenotype. Using high-throughput (>6000 cells per condition), single-cell impedance cytometry, we present the utilization of electrophysiology for quantification of hNPC subpopulations that are altered in cell cycle synchronicity by camptothecin (CPT) exposure. Electrophysiology phenotypes are determined from impedance magnitude and phase metrics for distinguishing each cell cycle phase, as validated by flow cytometry, for a wide range of subpopulation proportions. Using multishell dielectric models for each cell cycle phase, electrophysiology alterations with CPT dose could be predicted. This label-free detection strategy can prevent loss of cell viability to speed the optimization of cellular compositions for organoid development.

Quantifying bacterial spore germination by single-cell impedance cytometry for assessment of host microbiota susceptibility to Clostridioides difficile infection.

The germination of ingested spores is often a necessary first step required for enabling bacterial outgrowth and host colonization, as in the case of Clostridioides difficile (C. difficile) infection. Spore germination rate in the colon depends on microbiota composition and its level of disruption by antibiotic treatment since secretions by commensal bacteria modulate primary to secondary bile salt levels to control germination. Assessment of C. difficile spore germination typically requires measurement of colony-forming units, which is labor intensive and takes at least 24 h to perform but is regularly required due to the high recurrence rates of nosocomial antibiotic-associated diarrhea. We present a rapid method to assess spore germination by using high throughput single-cell impedance cytometry (>300 events/s) to quantify live bacterial cells, by gating for their characteristic electrophysiology versus spores, so that germination can be assessed after just 4 h of culture at a detection limit of ~100 live cells per 50 µL sample. To detect the phenotype of germinated C. difficile bacteria, we utilize its characteristically higher net conductivity versus that of spore aggregates and non-viable C. difficile forms, which causes a distinctive high-frequency (10 MHz) impedance phase dispersion within moderately conductive media (0.8 S/m). In this manner, we can detect significant differences in spore germination rates within just 4 h, with increasing primary bile salt levels in vitro and using ex vivo microbiota samples from an antibiotic-treated mouse model to assess susceptibility to C. difficile infection. We envision a rapid diagnostic tool for assessing host microbiota susceptibility to bacterial colonization after key antibiotic treatments.