Drug screening at single-organoid resolution via bioprinting and interferometry.

High throughput drug screening is an established approach to investigate tumor biology and identify therapeutic leads. Traditional platforms use two-dimensional cultures which do not accurately reflect the biology of human tumors. More clinically relevant model systems such as three-dimensional tumor organoids can be difficult to scale and screen. Manually seeded organoids coupled to destructive endpoint assays allow for the characterization of treatment response, but do not capture transitory changes and intra-sample heterogeneity underlying clinically observed resistance to therapy. We present a pipeline to generate bioprinted tumor organoids linked to label-free, time-resolved imaging via high-speed live cell interferometry (HSLCI) and machine learning-based quantitation of individual organoids. Bioprinting cells gives rise to 3D structures with unaltered tumor histology and gene expression profiles. HSLCI imaging in tandem with machine learning-based segmentation and classification tools enables accurate, label-free parallel mass measurements for thousands of organoids. We demonstrate that this strategy identifies organoids transiently or persistently sensitive or resistant to specific therapies, information that could be used to guide rapid therapy selection.

Quantitative Phase Imaging: Recent Advances and Expanding Potential in Biomedicine.

Quantitative phase imaging (QPI) is a label-free, wide-field microscopy approach with significant opportunities for biomedical applications. QPI uses the natural phase shift of light as it passes through a transparent object, such as a mammalian cell, to quantify biomass distribution and spatial and temporal changes in biomass. Reported in cell studies more than 60 years ago, ongoing advances in QPI hardware and software are leading to numerous applications in biology, with a dramatic expansion in utility over the past two decades. Today, investigations of cell size, morphology, behavior, cellular viscoelasticity, drug efficacy, biomass accumulation and turnover, and transport mechanics are supporting studies of development, physiology, neural activity, cancer, and additional physiological processes and diseases. Here, we review the field of QPI in biology starting with underlying principles, followed by a discussion of technical approaches currently available or being developed, and end with an examination of the breadth of applications in use or under development. We comment on strengths and shortcomings for the deployment of QPI in key biomedical contexts and conclude with emerging challenges and opportunities based on combining QPI with other methodologies that expand the scope and utility of QPI even further.

Pressure-Driven Mitochondrial Transfer Pipeline Generates Mammalian Cells of Desired Genetic Combinations and Fates.

Generating mammalian cells with desired mitochondrial DNA (mtDNA) sequences is enabling for studies of mitochondria, disease modeling, and potential regenerative therapies. MitoPunch, a high-throughput mitochondrial transfer device, produces cells with specific mtDNA-nuclear DNA (nDNA) combinations by transferring isolated mitochondria from mouse or human cells into primary or immortal mtDNA-deficient (ρ0) cells. Stable isolated mitochondrial recipient (SIMR) cells isolated in restrictive media permanently retain donor mtDNA and reacquire respiration. However, SIMR fibroblasts maintain a ρ0-like cell metabolome and transcriptome despite growth in restrictive media. We reprogrammed non-immortal SIMR fibroblasts into induced pluripotent stem cells (iPSCs) with subsequent differentiation into diverse functional cell types, including mesenchymal stem cells (MSCs), adipocytes, osteoblasts, and chondrocytes. Remarkably, after reprogramming and differentiation, SIMR fibroblasts molecularly and phenotypically resemble unmanipulated control fibroblasts carried through the same protocol. Thus, our MitoPunch "pipeline" enables the production of SIMR cells with unique mtDNA-nDNA combinations for additional studies and applications in multiple cell types.

Cell viscoelasticity is linked to fluctuations in cell biomass distributions.

The viscoelastic properties of mammalian cells can vary with biological state, such as during the epithelial-to-mesenchymal (EMT) transition in cancer, and therefore may serve as a useful physical biomarker. To characterize stiffness, conventional techniques use cell contact or invasive probes and as a result are low throughput, labor intensive, and limited by probe placement. Here, we show that measurements of biomass fluctuations in cells using quantitative phase imaging (QPI) provides a probe-free, contact-free method for quantifying changes in cell viscoelasticity. In particular, QPI measurements reveal a characteristic underdamped response of changes in cell biomass distributions versus time. The effective stiffness and viscosity values extracted from these oscillations in cell biomass distributions correlate with effective cell stiffness and viscosity measured by atomic force microscopy (AFM). This result is consistent for multiple cell lines with varying degrees of cytoskeleton disruption and during the EMT. Overall, our study demonstrates that QPI can reproducibly quantify cell viscoelasticity.