An Open-Source Membrane Stretcher for Simultaneous Mechanical and Structural Characterizations of Soft Materials and Biological Tissues.

The ability to simultaneously measure material mechanics and structure is central for understanding their nonlinear relationship that underlies the mechanical properties of materials, such as hysteresis, strain-stiffening and -softening, and plasticity. This experimental capability is also critical in biomechanics and mechanobiology research, as it enables direct characterizations of the intricate interplay between cellular responses and tissue mechanics. Stretching devices developed over the past few decades, however, do not often allow simultaneous measurements of the structural and mechanical responses of the sample. In this work, we introduce an open-source stretching system that can apply uniaxial strain at a submicron resolution, report the tensile force response of the sample, and be mounted on an inverted microscope for real-time imaging. Our system consists of a pair of stepper-based linear motors that stretch the sample symmetrically, a force transducer that records the sample tensile force, and an optically clear sample holder that allows for high-magnification microscopy. Using polymer samples and cellular specimens, we characterized the motion control accuracy, force measurement robustness, and microscopy compatibility of our stretching system. We envision that this uniaxial stretching system will be a valuable tool for characterizing soft and living materials.

Regulation of Chromatin Modifications through Coordination of Nucleus Size and Epithelial Cell Morphology Heterogeneity.

Cell morphology heterogeneity within epithelial collectives is a pervasive phenomenon intertwined with tissue mechanical properties. Despite its widespread occurrence, the underlying mechanisms driving cell morphology heterogeneity and its consequential biological ramifications remain elusive. Here, we investigate the dynamic evolution of epithelial cell morphology and nucleus morphology during crowding, unveiling a consistent correlation between the two. Our investigation reveals a persistent log-normal probability distribution characterizing both cell and nucleus areas across diverse crowding stages and epithelial model systems. We showed that this morphological diversity arises from asymmetric partitioning during cell division and is perpetuated through actomyosin-mediated regulation of cell-nucleus size coordination. Moreover, we provide insights into the impact of nucleus morphology on chromatin dynamics, demonstrating that constraining nucleus area leads to downregulation of the euchromatic mark H3K9ac and upregulation of the heterochromatic mark H3K27me3 through modulation of histone demethylase UTX expression. These findings under-score the significance of cell morphology heterogeneity as a driver of chromatin state diversity, shaping functional variability within epithelial tissues.

Phenotyping senescent mesenchymal stromal cells using AI image translation.

Mesenchymal stromal cells (MSCs) offer promising potential in biomedical research, clinical therapeutics, and immunomodulatory therapies due to their ease of isolation and multipotent, immunoprivileged, and immunosuppersive properties. Extensive efforts have focused on optimizing the cell isolation and culture methods to generate scalable, therapeutically-relevant MSCs for clinical applications. However, MSC-based therapies are often hindered by cell heterogeneity and inconsistency of therapeutic function caused, in part, by MSC senescence. As such, noninvasive and molecular-based MSC characterizations play an essential role in assuring the consistency of MSC functions. Here, we demonstrated that AI image translation algorithms can effectively predict immunofluorescence images of MSC senescence markers from phase contrast images. We showed that the expression level of senescence markers including senescence-associated beta-galactosidase (SABG), p16, p21, and p38 are accurately predicted by deep-learning models for Doxorubicin-induced MSC senescence, irradiation-induced MSC senescence, and replicative MSC senescence. Our AI model distinguished the non-senescent and senescent MSC populations and simultaneously captured the cell-to-cell variability within a population. Our microscopy-based phenotyping platform can be integrated with cell culture routines making it an easily accessible tool for MSC engineering and manufacturing.

Prostate lineage-specific metabolism governs luminal differentiation and response to antiandrogen treatment.

Lineage transitions are a central feature of prostate development, tumourigenesis and treatment resistance. While epigenetic changes are well known to drive prostate lineage transitions, it remains unclear how upstream metabolic signalling contributes to the regulation of prostate epithelial identity. To fill this gap, we developed an approach to perform metabolomics on primary prostate epithelial cells. Using this approach, we discovered that the basal and luminal cells of the prostate exhibit distinct metabolomes and nutrient utilization patterns. Furthermore, basal-to-luminal differentiation is accompanied by increased pyruvate oxidation. We establish the mitochondrial pyruvate carrier and subsequent lactate accumulation as regulators of prostate luminal identity. Inhibition of the mitochondrial pyruvate carrier or supplementation with exogenous lactate results in large-scale chromatin remodelling, influencing both lineage-specific transcription factors and response to antiandrogen treatment. These results establish reciprocal regulation of metabolism and prostate epithelial lineage identity.

Trustworthy in silico cell labeling via ensemble-based image translation.

Artificial intelligence (AI) image translation has been a valuable tool for processing image data in biological and medical research. To apply such a tool in mission-critical applications, including drug screening, toxicity study, and clinical diagnostics, it is essential to ensure that the AI prediction is trustworthy. Here, we demonstrate that an ensemble learning method can quantify the uncertainty of AI image translation. We tested the uncertainty evaluation using experimentally acquired images of mesenchymal stromal cells. We find that the ensemble method reports a prediction standard deviation that correlates with the prediction error, estimating the prediction uncertainty. We show that this uncertainty is in agreement with the prediction error and Pearson correlation coefficient. We further show that the ensemble method can detect out-of-distribution input images by reporting increased uncertainty. Altogether, these results suggest that the ensemble-estimated uncertainty can be a useful indicator for identifying erroneous AI image translations.

Microwell-based flow culture increases viability and restores drug response in prostate cancer spheroids.

3D cancer spheroids represent a highly promising model for study of cancer progression and therapeutic development. Wide-scale adoption of cancer spheroids, however, remains a challenge due to the lack of control over hypoxic gradients that may cloud the assessment of cell morphology and drug response. Here, we present a Microwell Flow Device (MFD) that generates in-well laminar flow around 3D tissues via repetitive tissue sedimentation. Using a prostate cancer cell line, we demonstrate the spheroids in the MFD exhibit improved cell growth, reduced necrotic core formation, enhanced structural integrity, and downregulated expression of cell stress genes. The flow-cultured spheroids also exhibit an improved sensitivity to chemotherapy with greater transcriptional response. These results demonstrate how fluidic stimuli reveal the cellular phenotype previously masked by severe necrosis. Our platform advances 3D cellular models and enables study into hypoxia modulation, cancer metabolism, and drug screening within pathophysiological conditions.

Rapid prototyping of functional acoustic devices using laser manufacturing.

Acoustic patterning of micro-particles has many important biomedical applications. However, fabrication of such microdevices is costly and labor-intensive. Among conventional fabrication methods, photo-lithography provides high resolution but is expensive and time consuming, and not ideal for rapid prototyping and testing for academic applications. In this work, we demonstrate a highly efficient method for rapid prototyping of acoustic patterning devices using laser manufacturing. With this method we can fabricate a newly designed functional acoustic device in 4 hours. The acoustic devices fabricated using this method can achieve sub-wavelength, complex and non-periodic patterning of microparticles and biological objects with a spatial resolution of 60 µm across a large active manipulation area of 10 × 10 mm2.

Supracellular measurement of spatially varying mechanical heterogeneities in live monolayers.

The mechanical properties of tissues have profound impacts on a wide range of biological processes such as embryo development (1,2), wound healing (3-6), and disease progression (7). Specifically, the spatially varying moduli of cells largely influence the local tissue deformation and intercellular interaction. Despite the importance of characterizing such a heterogeneous mechanical property, it has remained difficult to measure the supracellular modulus field in live cell layers with a high-throughput and minimal perturbation. In this work, we developed a monolayer effective modulus measurement by integrating a custom cell stretcher, light microscopy, and AI-based inference. Our approach first quantifies the heterogeneous deformation of a slightly stretched cell layer and converts the measured strain fields into an effective modulus field using an AI inference. This method allowed us to directly visualize the effective modulus distribution of thousands of cells virtually instantly. We characterized the mean value, SD, and correlation length of the effective cell modulus for epithelial cells and fibroblasts, which are in agreement with previous results. We also observed a mild correlation between cell area and stiffness in jammed epithelia, suggesting the influence of cell modulus on packing. Overall, our reported experimental platform provides a valuable alternative cell mechanics measurement tool that can be integrated with microscopy-based characterizations.

Cell-cell adhesion impacts epithelia response to substrate stiffness: Morphology and gene expression.

Monolayer epithelial cells interact constantly with the substrate they reside on and their surrounding neighbors. As such, the properties of epithelial cells are profoundly governed by the mechanical and molecular cues that arise from both the substrate and contiguous cell neighbors. Although both cell-substrate and cell-cell interactions have been studied individually, these results are difficult to apply to native confluent epithelia, in which both jointly regulate the cell phenotype. Specifically, it remains poorly understood about the intertwined contributions from intercellular adhesion and substrate stiffness on cell morphology and gene expression, two essential microenvironment properties. Here, by adjusting the substrate modulus and altering the intercellular adhesion within confluent kidney epithelia, we found that cell-substrate and cell-cell interactions can mask each other's influence. For example, we found that epithelial cells exhibit an elongated morphological phenotype only when the substrate modulus and intercellular adhesions are both reduced, whereas their motility can be upregulated by either reduction. These results illustrate that combinatorial changes of the physical microenvironment are required to alter cell morphology and gene expression.

Investigating heterogeneities of live mesenchymal stromal cells using AI-based label-free imaging.

Mesenchymal stromal cells (MSCs) are multipotent cells that have great potential for regenerative medicine, tissue repair, and immunotherapy. Unfortunately, the outcomes of MSC-based research and therapies can be highly inconsistent and difficult to reproduce, largely due to the inherently significant heterogeneity in MSCs, which has not been well investigated. To quantify cell heterogeneity, a standard approach is to measure marker expression on the protein level via immunochemistry assays. Performing such measurements non-invasively and at scale has remained challenging as conventional methods such as flow cytometry and immunofluorescence microscopy typically require cell fixation and laborious sample preparation. Here, we developed an artificial intelligence (AI)-based method that converts transmitted light microscopy images of MSCs into quantitative measurements of protein expression levels. By training a U-Net+ conditional generative adversarial network (cGAN) model that accurately (mean [Formula: see text] = 0.77) predicts expression of 8 MSC-specific markers, we showed that expression of surface markers provides a heterogeneity characterization that is complementary to conventional cell-level morphological analyses. Using this label-free imaging method, we also observed a multi-marker temporal-spatial fluctuation of protein distributions in live MSCs. These demonstrations suggest that our AI-based microscopy can be utilized to perform quantitative, non-invasive, single-cell, and multi-marker characterizations of heterogeneous live MSC culture. Our method provides a foundational step toward the instant integrative assessment of MSC properties, which is critical for high-throughput screening and quality control in cellular therapies.

Effect of luminal flow on doming of mpkCCD cells in a 3D perfusable kidney cortical collecting duct model.

The cortical collecting duct (CCD) of the mammalian kidney plays a major role in the maintenance of total body electrolyte, acid/base, and fluid homeostasis by tubular reabsorption and excretion. The mammalian CCD is heterogeneous, composed of Na+-absorbing principal cells (PCs) and acid-base-transporting intercalated cells (ICs). Perturbations in luminal flow rate alter hydrodynamic forces to which these cells in the cylindrical tubules are exposed. However, most studies of tubular ion transport have been performed in cell monolayers grown on or epithelial sheets affixed to a flat support, since analysis of transepithelial transport in native tubules by in vitro microperfusion requires considerable expertise. Here, we report on the generation and characterization of an in vitro, perfusable three-dimensional kidney CCD model (3D CCD), in which immortalized mouse PC-like mpkCCD cells are seeded within a cylindrical channel embedded within an engineered extracellular matrix and subjected to luminal fluid flow. We find that a tight epithelial barrier composed of differentiated and polarized PCs forms within 1 wk. Immunofluorescence microscopy reveals the apical epithelial Na+ channel ENaC and basolateral Na+/K+-ATPase. On cessation of luminal flow, benzamil-inhibitable cell doming is observed within these 3D CCDs consistent with the presence of ENaC-mediated Na+ absorption. Our 3D CCD provides a geometrically and microphysiologically relevant platform for studying the development and physiology of renal tubule segments.

Renal reabsorption in 3D vascularized proximal tubule models.

Three-dimensional renal tissues that emulate the cellular composition, geometry, and function of native kidney tissue would enable fundamental studies of filtration and reabsorption. Here, we have created 3D vascularized proximal tubule models composed of adjacent conduits that are lined with confluent epithelium and endothelium, embedded in a permeable ECM, and independently addressed using a closed-loop perfusion system to investigate renal reabsorption. Our 3D kidney tissue allows for coculture of proximal tubule epithelium and vascular endothelium that exhibits active reabsorption via tubular-vascular exchange of solutes akin to native kidney tissue. Using this model, both albumin uptake and glucose reabsorption are quantified as a function of time. Epithelium-endothelium cross-talk is further studied by exposing proximal tubule cells to hyperglycemic conditions and monitoring endothelial cell dysfunction. This diseased state can be rescued by administering a glucose transport inhibitor. Our 3D kidney tissue provides a platform for in vitro studies of kidney function, disease modeling, and pharmacology.

Determining Quiescent Colloidal Suspension Viscosities Using the Green-Kubo Relation and Image-Based Stress Measurements.

By combining confocal microscopy and stress assessment from local structural anisotropy, we directly measure stresses in 3D quiescent colloidal liquids. Our noninvasive and nonperturbative method allows us to measure forces ≲50 fN with a small and tunable probing volume, enabling us to resolve the stress fluctuations arising from particle thermal motions. We use the Green-Kubo relation to relate these measured stress fluctuations to the bulk Brownian viscosity at different volume fractions, comparing against simulations and conventional rheometry measurements. We find that the Green-Kubo analysis gives excellent agreement with these prior results, suggesting that similar methods could be applied to investigations of local flow properties in many poorly understood far-from-equilibrium systems, including suspensions that are glassy, strongly sheared, or highly confined.

Relating microstructure and particle-level stress in colloidal crystals under increased confinement.

The mechanical properties of crystalline materials can be substantially modified under confinement. Such modified macroscopic properties are usually governed by the altered microstructures and internal stress fields. Here, we use a parallel plate geometry to apply a quasi-static squeeze flow crushing a colloidal polycrystal while simultaneously imaging it with confocal microscopy. The confocal images are used to quantify the local structure order and, in conjunction with Stress Assessment from Local Structural Anisotropy (SALSA), determine the stress at the single-particle scale. We find that during compression, the crystalline regions break into small domains with different geometric packing. These domains are characterized by a pressure and deviatoric stress that are highly localized with correlation lengths that are half those found in bulk. Furthermore, the mean deviatoric stress almost doubles, suggesting a higher brittleness in the highly-confined samples.

Tunable shear thickening in suspensions.

Shear thickening, an increase of viscosity with shear rate, is a ubiquitous phenomenon in suspended materials that has implications for broad technological applications. Controlling this thickening behavior remains a major challenge and has led to empirical strategies ranging from altering the particle surfaces and shape to modifying the solvent properties. However, none of these methods allows for tuning of flow properties during shear itself. Here, we demonstrate that by strategic imposition of a high-frequency and low-amplitude shear perturbation orthogonal to the primary shearing flow, we can largely eradicate shear thickening. The orthogonal shear effectively becomes a regulator for controlling thickening in the suspension, allowing the viscosity to be reduced by up to 2 decades on demand. In a separate setup, we show that such effects can be induced by simply agitating the sample transversely to the primary shear direction. Overall, the ability of in situ manipulation of shear thickening paves a route toward creating materials whose mechanical properties can be controlled.

Measuring nonlinear stresses generated by defects in 3D colloidal crystals.

The mechanical, structural and functional properties of crystals are determined by their defects, and the distribution of stresses surrounding these defects has broad implications for the understanding of transport phenomena. When the defect density rises to levels routinely found in real-world materials, transport is governed by local stresses that are predominantly nonlinear. Such stress fields however, cannot be measured using conventional bulk and local measurement techniques. Here, we report direct and spatially resolved experimental measurements of the nonlinear stresses surrounding colloidal crystalline defect cores, and show that the stresses at vacancy cores generate attractive interactions between them. We also directly visualize the softening of crystalline regions surrounding dislocation cores, and find that stress fluctuations in quiescent polycrystals are uniformly distributed rather than localized at grain boundaries, as is the case in strained atomic polycrystals. Nonlinear stress measurements have important implications for strain hardening, yield and fatigue.

Hydrodynamic and Contact Contributions to Continuous Shear Thickening in Colloidal Suspensions.

Shear thickening is a widespread phenomenon in suspension flow that, despite sustained study, is still the subject of much debate. The longstanding view that shear thickening is due to hydrodynamic clusters has been challenged by recent theory and simulations suggesting that contact forces dominate, not only in discontinuous, but also in continuous shear thickening. Here, we settle this dispute using shear reversal experiments on micron-sized silica and latex particles to measure directly the hydrodynamic and contact force contributions to shear thickening. We find that contact forces dominate even continuous shear thickening. Computer simulations show that these forces most likely arise from frictional interactions.

A multi-axis confocal rheoscope for studying shear flow of structured fluids.

We present a new design for a confocal rheoscope that enables uniform uniaxial or biaxial shear. The design consists of two precisely positioned parallel plates with a gap that can be adjusted down to 2 ±0.1 µm, allowing for the exploration of confinement effects. By using our shear cell in conjunction with a biaxial force measurement device and a high-speed confocal microscope, we are able to measure the real-time biaxial stress while simultaneously imaging the material three-dimensional structure. We illustrate the importance of the instrument capabilities by discussing the applications of this instrument in current and future research topics in colloidal suspensions.

Biaxial shear of confined colloidal hard spheres: the structure and rheology of the vorticity-aligned string phase.

Using a novel biaxial confocal rheoscope, we investigate the flow of the shear induced vorticity aligned string phase [X. Cheng et al., Proc. Natl. Acad. Sci. U. S. A., 2011, 109, 63], which has a highly anisotropic microstructure. Using biaxial shear protocols we show that we have excellent control of the string phase anisotropic morphology. We choose a shear protocol that drives the system into the string phase. Subsequently, a biaxial force measurement device is used to determine the suspension rheology along both the flow and vorticity directions. We find no measurable dependence of the suspension stress response along the shear and vorticity directions due to the hydrodynamically induced string morphology. In particular, we find that the suspension's high frequency stress response is nearly identical along the two orthogonal directions. While we do observe an anisotropic stress response at lower shear frequencies associated with shear thinning, we show that this anisotropy is independent of the shear induced string structure. These results suggest that for the range of flows explored, Brownian and hydrodynamic contributions to the stress arising from the anisotropic suspension microstructure are sufficiently weak that they do not significantly contribute to the rheology. Collectively, this study presents a general and powerful approach for using biaxial confocal rheometry to elucidate the relationship between microstructure and rheology in complex fluids driven far-from-equilibrium.

Far-from-equilibrium sheared colloidal liquids: disentangling relaxation, advection, and shear-induced diffusion.

Using high-speed confocal microscopy, we measure the particle positions in a colloidal suspension under large-amplitude oscillatory shear. Using the particle positions, we quantify the in situ anisotropy of the pair-correlation function, a measure of the Brownian stress. From these data we find two distinct types of responses as the system crosses over from equilibrium to far-from-equilibrium states. The first is a nonlinear amplitude saturation that arises from shear-induced advection, while the second is a linear frequency saturation due to competition between suspension relaxation and shear rate. In spite of their different underlying mechanisms, we show that all the data can be scaled onto a master curve that spans the equilibrium and far-from-equilibrium regimes, linking small-amplitude oscillatory to continuous shear. This observation illustrates a colloidal analog of the Cox-Merz rule and its microscopic underpinning. Brownian dynamics simulations show that interparticle interactions are sufficient for generating both experimentally observed saturations.