Pooled CRISPR screens with imaging on microraft arrays reveals stress granule-regulatory factors.

Genetic screens using pooled CRISPR-based approaches are scalable and inexpensive, but restricted to standard readouts, including survival, proliferation and sortable markers. However, many biologically relevant cell states involve cellular and subcellular changes that are only accessible by microscopic visualization, and are currently impossible to screen with pooled methods. Here we combine pooled CRISPR-Cas9 screening with microraft array technology and high-content imaging to screen image-based phenotypes (CRaft-ID; CRISPR-based microRaft followed by guide RNA identification). By isolating microrafts that contain genetic clones harboring individual guide RNAs (gRNA), we identify RNA-binding proteins (RBPs) that influence the formation of stress granules, the punctate protein-RNA assemblies that form during stress. To automate hit identification, we developed a machine-learning model trained on nuclear morphology to remove unhealthy cells or imaging artifacts. In doing so, we identified and validated previously uncharacterized RBPs that modulate stress granule abundance, highlighting the applicability of our approach to facilitate image-based pooled CRISPR screens.

Microraft array-based platform for sorting of viable microcolonies based on cell-lethal immunoassay of intracellular proteins in microcolony biopsies.

The majority of bioassays are cell-lethal and thus cannot be used for cell assay and selection prior to live-cell sorting. A quad microraft array-based platform was developed to perform semi-automated cell sampling, bioassay, and banking on ultra-small sample sizes. The system biopsies and collects colony fragments, quantifies intracellular protein levels via immunostaining, and then retrieves the living mother colonies based on the fragments' immunoassay outcome. To accomplish this, a magnetic, microwell-based plate was developed to mate directly above the microraft array and capture colony fragments with a one-to-one spatial correspondence to their mother colonies. Using the Signal Transducer and Activator of Transcription 3 (STAT3) model pathway in basophilic leukemia cells, the system was used to sort cells based on the amount of intracellular STAT3 protein phosphorylation (pSTAT3). Colonies were detected on quad arrays using bright field microscopy with 96 ± 20% accuracy (true-positive rate), 49 ± 3% of the colonies were identified as originating from a single cell, and the majority (95 ± 3%) of biopsied clonal fragments were successfully collected into the microwell plate for immunostaining. After assay, biopsied fragments were matched back to their mother colonies and mother colonies with fragments possessing the greatest and least pSTAT3/STAT3 were resampled for expansion and downstream biological assays for pSTAT3/STAT3 and immune granule exocytosis. This approach has the potential to enable colony screening and sorting based on assays not compatible with cell viability, greatly expanding the cell selection criteria available to identify cells with unique phenotypes for subsequent biomedical research.

Characterization of Tensioned PDMS Membranes for Imaging Cytometry on Microraft Arrays.

Polydimethylsiloxane (PDMS) membranes can act as sensing elements, barriers, and substrates, yet the low rigidity of the elastomeric membranes can limit their practical use in devices. Microraft arrays rely on a freestanding PDMS membrane as a substrate for cell arrays used in imaging cytometry and cellular isolation. However, the underlying PDMS membrane deforms under the weight of the cell media, making automated analytical microscopy (and thus cytometry and cell isolation) challenging. Here we report the development of microfabrication strategies and physically motivated mathematical modeling of membrane deformation of PDMS microarrays. Microraft arrays were fabricated with mechanical tension stored within the PDMS substrate. These membranes deformed 20× less than that of arrays fabricated using prior methods. Modeling of the deformation of pretensioned arrays using linear membrane theory yielded ≤15% error in predicting the array deflection and predicted the impact of cure temperatures up to 120 °C. A mathematical approach was developed to fit models of microraft shape to sparse real-world shape measurements. Automated imaging of cells on pretensioned microarrays using the focal planes predicted by the model produced high quality fluorescence images of cells, enabling accurate cell area quantification (<4% error) at increased speed (13×) relative to conventional methods. Our microfabrication method and simplified, linear modeling approach is readily applicable to control the deformation of similar membranes in MEMs devices, sensors, and microfluidics.

Development of Arrayed Colonic Organoids for Screening of Secretagogues Associated with Enterotoxins.

Enterotoxins increase intestinal fluid secretion through modulation of ion channels as well as activation of the enteric nervous and immune systems. Colonic organoids, also known as colonoids, are functionally and phenotypically similar to in vivo colonic epithelium and have been used to study intestinal ion transport and subsequent water flux in physiology and disease models. In conventional cultures, organoids exist as spheroids embedded within a hydrogel patty of extracellular matrix, and they form at multiple depths, impairing efficient imaging necessary to capture data from statistically relevant sample sizes. To overcome these limitations, an analytical platform with colonic organoids localized to the planar surface of a hydrogel layer was developed. The arrays of densely packed colonoids (140 µm average diameter, 4 colonoids/mm2) were generated in a 96-well plate, enabling assay of the response of hundreds of organoids so that organoid subpopulations with distinct behaviors were identifiable. Organoid cell types, monolayer polarity, and growth were similar to those embedded in hydrogel. An automated imaging and analysis platform efficiently tracked over time swelling due to forskolin and fluid movement across the cell monolayer stimulated by cholera toxin. The platform was used to screen compounds associated with the enteric nervous and immune systems for their effect on fluid movement across epithelial cells. Prostaglandin E2 promoted increased water flux in a subset of organoids that resulted in organoid swelling, confirming a role for this inflammatory mediator in diarrheal conditions but also illustrating organoid differences in response to an identical stimulus. By allowing sampling of a large number of organoids, the arrayed organoid platform permits identification of organoid subpopulations intermixed within a larger group of nonresponding organoids. This technique will enable automated, large-scale screening of the impact of drugs, toxins, and other compounds on colonic physiology.

Selective single cell isolation for genomics using microraft arrays.

Genomic methods are used increasingly to interrogate the individual cells that compose specific tissues. However, current methods for single cell isolation struggle to phenotypically differentiate specific cells in a heterogeneous population and rely primarily on the use of fluorescent markers. Many cellular phenotypes of interest are too complex to be measured by this approach, making it difficult to connect genotype and phenotype at the level of individual cells. Here we demonstrate that microraft arrays, which are arrays containing thousands of individual cell culture sites, can be used to select single cells based on a variety of phenotypes, such as cell surface markers, cell proliferation and drug response. We then show that a common genomic procedure, RNA-seq, can be readily adapted to the single cells isolated from these rafts. We show that data generated using microrafts and our modified RNA-seq protocol compared favorably with the Fluidigm C1. We then used microraft arrays to select pancreatic cancer cells that proliferate in spite of cytotoxic drug treatment. Our single cell RNA-seq data identified several expected and novel gene expression changes associated with early drug resistance.

Single-cell functional analysis of parathyroid adenomas reveals distinct classes of calcium sensing behaviour in primary hyperparathyroidism.

Primary hyperparathyroidism (PHPT) is a common endocrine neoplastic disorder caused by a failure of calcium sensing secondary to tumour development in one or more of the parathyroid glands. Parathyroid adenomas are comprised of distinct cellular subpopulations of variable clonal status that exhibit differing degrees of calcium responsiveness. To gain a clearer understanding of the relationship among cellular identity, tumour composition and clinical biochemistry in PHPT, we developed a novel single cell platform for quantitative evaluation of calcium sensing behaviour in freshly resected human parathyroid tumour cells. Live-cell intracellular calcium flux was visualized through Fluo-4-AM epifluorescence, followed by in situ immunofluorescence detection of the calcium sensing receptor (CASR), a central component in the extracellular calcium signalling pathway. The reactivity of individual parathyroid tumour cells to extracellular calcium stimulus was highly variable, with discrete kinetic response patterns observed both between and among parathyroid tumour samples. CASR abundance was not an obligate determinant of calcium responsiveness. Calcium EC50 values from a series of parathyroid adenomas revealed that the tumours segregated into two distinct categories. One group manifested a mean EC50 of 2.40 mM (95% CI: 2.37-2.41), closely aligned to the established normal range. The second group was less responsive to calcium stimulus, with a mean EC50 of 3.61 mM (95% CI: 3.45-3.95). This binary distribution indicates the existence of a previously unappreciated biochemical sub-classification of PHPT tumours, possibly reflecting distinct etiological mechanisms. Recognition of quantitative differences in calcium sensing could have important implications for the clinical management of PHPT.

The need for speed - Does the force-velocity property significantly alter strain distributions within skeletal muscle?

Skeletal muscles are complex structures with nonlinear constitutive properties. This complexity often requires finite element (FE) modeling to better understand muscle behavior and response to activation, especially the fiber strain distributions that can be difficult to measure in vivo. However, many FE muscle models designed to study fiber strain do not include force-velocity behavior. To investigate force-velocity property impact on strain distributions within skeletal muscle, we modified a muscle constitutive model with active and passive force-length properties to include force-velocity properties. We implemented the new constitutive model as a plugin for the FE software FEBio and applied it to four geometries: 1) a single element, 2) a multiple-element model representing a single fiber, 3) a model of tapering fibers, and 4) a model representing the bicep femoris long head (BFLH) morphology. Maximum fiber velocity and boundary conditions of the finite element models were varied to test their influence on fiber strain distribution. We found that force-velocity properties in the constitutive model behaved as expected for the single element and multi-element conditions. In the tapered fiber models, fiber strain distributions were impacted by changes in maximum fiber velocity; the range of strains increased with maximum fiber velocity, which was most noted in isometric contraction simulations. In the BFLH model, maximum fiber velocity had minimal impact on strain distributions, even in the context of sprinting. Taken together, the combination of muscle model geometry, activation, and displacement parameters play a critical part in determining the magnitude of impact of force-velocity on strain distribution.

Reproducibility in cytometry: Signals analysis and its connection to uncertainty quantification.

Signals analysis for cytometry remains a challenging task that has a significant impact on uncertainty. Conventional cytometers assume that individual measurements are well characterized by simple properties such as the signal area, width, and height. However, these approaches have difficulty distinguishing inherent biological variability from instrument artifacts and operating conditions. As a result, it is challenging to quantify uncertainty in the properties of individual cells and perform tasks such as doublet deconvolution. We address these problems via signals analysis techniques that use scale transformations to: (I) separate variation in biomarker expression from effects due to flow conditions and particle size; (II) quantify reproducibility associated with a given laser interrogation region; (III) estimate uncertainty in measurement values on a per-event basis; and (IV) extract the singlets that make up a multiplet. The key idea behind this approach is to model how variable operating conditions deform the signal shape and then use constrained optimization to "undo" these deformations for measured signals; residuals to this process characterize reproducibility. Using a recently developed microfluidic cytometer, we demonstrate that these techniques can account for instrument and measurand induced variability with a residual uncertainty of less than 2.5% in the signal shape and less than 1% in integrated area.

Serial flow cytometry in an inertial focusing optofluidic microchip for direct assessment of measurement variations.

Flow cytometry is an invaluable technology in biomedical research, but confidence in single-cell measurements remains limited due to a lack of appropriate techniques for uncertainty quantification (UQ). It is particularly challenging to evaluate the potential for different instrumentation designs or operating parameters to influence the measurement physics in ways that change measurement repeatability. Here, we report a direct experimental approach to UQ using a serial flow cytometer that measured each particle more than once along a flow path. The instrument was automated for real-time characterization of measurement precision and operated with particle velocities exceeding 1 m s-1, throughputs above 100 s-1, and analysis yields better than 99.9%. These achievements were enabled by a novel hybrid inertial and hydrodynamic particle focuser to tightly control particle positions and velocities. The cytometer identified ideal flow conditions with fluorescence area measurement precision on the order of 1% and characterized tradeoffs between precision, throughput, and analysis yield. The serial cytometer is anticipated to improve single-cell measurements through estimation (and subsequent control) of uncertainty contributions from various other instrument parameters leading to overall improvements in the ability to better classify sample composition and to find rare events.

Scalable Additive Construction of Arrayed Microstructures with Encoded Properties for Bioimaging.

Microarrays are essential components of analytical instruments. The elements of microarrays may be imbued with additional functionalities and encodings using composite materials and structures, but traditional microfabrication methods present substantial barriers to fabrication, design, and scalability. In this work, a tool-free technique was reported to additively batch-construct micromolded, composite, and arrayed microstructures. The method required only a compatible carrier fluid to deposit a material onto a substrate with some topography. Permutations of this basic fabrication approach were leveraged to gain control over the volumes and positions of deposited materials within the microstructures. As a proof of concept, cell micro-carrier arrays were constructed to demonstrate a range of designs, compositions, functionalities, and applications for composite microstructures. This approach is envisioned to enable the fabrication of complex composite biological and synthetic microelements for biosensing, cellular analysis, and biochemical screening.