Publications Using the CellRaft® Technology
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Three-dimensional (3D) culture systems have been developed that can re-capitulate organ level responses, simulate compound diffusion through complex structures, and assess cellular heterogeneity of tissues, making them attractive models for advanced in vitro research and discovery. Organoids are a unique subtype of 3D cell cul- ture that are grown from stem cells, are self-organizing, and closely replicate in vivo pathophysiology. Organoids have been used to understand tissue development, model diseases, test drug sensitivity and toxicity, and advance regenerative medicine. However, traditional organoid culture methods are inadequate because they are low throughput and ill-suited for single organoid imaging, phenotypic assessment, and isolation from heterogenous organoid populations. To address these bottlenecks, we have adapted our tissue culture consumable and instrumentation to enable automated imaging, identification, and isolation of individual organoids. Organoids grown on the 3D CellRaft Array can be reliably tracked, imaged, and phenotypically analyzed using brightfield and fluorescent microscopy as they grow over time, then released and transferred fully intact for use in downstream applications. Using mouse hepatic and pancreatic organoids, we have demonstrated the use of this technology for single-organoid imaging, clonal organoid generation, parent organoid subcloning, and single- organoid RNA extraction for downstream gene expression or transcriptomic analysis. The results validate the ability of the CellRaft AIR® System to facilitate efficient, user-friendly, and automated workflows broadly applicable to organoid research by overcoming several pain points: 1) single organoid time-course imaging and phenotypic assessment, 2) establishment of single cell-derived organoids, and 3) isolation and retrieval of single organoids for downstream applications.
While T lymphocytes have been employed as a cancer immunotherapy, the development of effective and specific T-cell-based therapeutics remains challenging. A key obstacle is the difficulty in identifying T cells reactive to cancer-associated antigens. The objective of this research was to develop a versatile platform for single cell analysis and isolation that can be applied in immunology research and clinical therapy development. Methods: An automated microscopy and cell sorting system was developed to track the proliferative behavior of single-cell human primary CD4+ lymphocytes in response to stimulation using allogeneic lymphoblastoid feeder cells. Results: The system identified single human T lymphocytes with a sensitivity of 98% and specificity of 99% and possessed a cell collection efficiency of 86%. Time-lapse imaging simultaneously tracked 4,534 alloreactive T cells on a single array; 19% of the arrayed cells formed colonies of ≥2 cells. From the array, 130 clonal colonies were isolated and 7 grew to colony sizes of >10,000 cells, consistent with the known proliferative capacity of T cells in vitro and their tendency to become exhausted with prolonged stimulation. The isolated colonies underwent ELISA assay to detect interferon-γ secretion and Sanger sequencing to determine T cell receptor β sequences with a 100% success rate. Conclusion: The platform is capable of both identification and isolation of proliferative T cells in an automated manner. Significance: This novel technology enables the identification of TCR sequences based on T cell proliferation which is expected to speed the development of future cancer immunotherapies.
Motility and invasion are key steps in the metastatic cascade, enabling cells to move through normal tissue borders into the surrounding stroma. Most available in vitro assays track cell motility or cell invasion but lack the ability to measure both simultaneously and then separate single cells with unique behaviors. In this work, we developed a cell-separation platform capable of tracking cell movement (chemokinesis) and invasion through an extracellular matrix in space and time. The platform utilized a collagen scaffold with embedded tumor cells overlaid onto a microraft array. Confocal microscopy enabled high resolution (0.4 × 0.4 × 3.5 µm voxel) monitoring of cell movement within the scaffolds. Two pancreatic cancer cell lines with known differing invasiveness were characterized on this platform, with median motilities of 14 ± 6 μm and 10 ± 4 μm over 48 h. Within the same cell line, cells demonstrated highly variable motility, with XYZ movement ranging from 144 μm to 2 μm over 24 h. The ten lowest and highest motility cells, with median movements of 33 ± 11 μm and 3 ± 1 μm, respectively, were separated and sub-cultured. After 6 weeks of culture, the cell populations were assayed on a Transwell invasion assay and 227 ± 56 cells were invasive in the high motility population while only 48 ± 10 cells were invasive in the low motility population, indicating that the resulting offspring possessed a motility phenotype reflective of the parental cells. This work demonstrates the feasibility of sorting single cells based on complex phenotypes along with the capability to further probe those cells and explore biological phenomena.
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.
Human induced pluripotent stem cells (hiPSCs) are widely used for disease modeling, tissue engineering, and clinical applications. Although the development of new disease-relevant or customized hiPSC lines is of high importance, current automated hiPSC isolation technologies rely largely on the fluorescent labeling of cells, thus limiting the cell line development from many applications. The objective of this research was to develop a platform for high-throughput hiPSC cytometry and splitting that utilized a label-free cell sensing approach. An image analysis pipeline utilizing background subtraction and standard deviation projections was implemented to detect hiPSC colonies from bright-field microscopy data. The pipeline was incorporated into an automated microscopy system coupling quad microraft cell-isolation arrays, computer-based vision, and algorithms for smart decision making and cell sorting. The pipeline exhibited a hiPSC detection specificity of 98% and a sensitivity of 88%, allowing for the successful tracking of growth for hundreds of microcolonies over 7 days. The automated platform split 170 mother colonies from a microarray within 80 min, and the harvested daughter biopsies were expanded into viable hiPSC colonies suitable for downstream assays, such as polymerase chain reaction (PCR) or continued culture. Transmitted light microscopy offers an alternative, label-free modality for isolating hiPSCs, yet its low contrast and specificity for adherent cells remain a challenge for automation. This novel approach to label-free sensing and microcolony subsampling with the preservation of the mother colony holds the potential for hiPSC colony screening based on a wide range of properties including those measurable only by a cell destructive assay.
In order to establish a causal relationship between somatic mutations and aging, mutational events must be directly identified in primary human tissues. Single cell sequencing holds promise for the detection of a full complement of mutations in somatic cells, overcoming the challenges that arise due to the random nature and very low abundance of most somatic mutations; however, the genome amplification procedures required for single cell genomics have a high error rate. To address this problem, Vijg, et al. developed a highly accurate single cell multiple displacement amplification (SCMDA) to comprehensively determine the full spectrum of base substitutions in a single somatic cell, and thereby assess mutation accumulation as a function of age in human B lymphocytes from healthy individuals. To aid in this analysis, bulk B lymphocytes were isolated from PBMCs and subsequently plated on gelatin coated CytoSort™ Arrays. Using the CellRaft® Technology, single B lymphocytes were isolated and collected in PCR tubes for SCMDA and downstream analysis of somatic mutations.
Neocortical neurons are among the most diverse and longest-lived mammalian cells, and human-specific brain phenotypes are attributed to neocortical expansion during evolution. McConnell and coworkers assembled a brain copy number variation (CNV) atlas to reveal the frequency of neocortical neurons with complex karyotypes and the associated variability among individuals. These CNVs represent rare variants with strong contributions to genetic risks for schizophrenia, autism, and other neurological disorders. The CellRaft® Technology was used to isolate, and verify the integrity of, single nuclei following flow sorting to assess the quality of the whole genome amplification (WGA) method utilized. The authors provide evidence that a functional consequence of CNV neurons may be selective vulnerability to aging-associated atrophy.
Generation of cell lines with specific mutations is integral to the in vitro study of many diseases and the associated pathogenesis, and the CRISPR-Cas9 gene editing system has revolutionized the ability to efficiently generate disease models. Limiting dilution and FACS have traditionally been used to obtain clonal cell lines with specific genomic modifications introduced by the CRISPR-Cas9 system; however, they require large sample sizes and often yield low cell viability. The authors used the CellRaft® Technology to sort cells based on the temporal evolution of fluorescent protein expression (EGFP) to generate a CRISPR gene-edited cell line with a leukemia-associated mutation (S34F) in the U2AF1 protein, allowing for the further study of the consequences of this mutation on mRNA splicing in AML.
It has long been known that genetic material is mutable at a rate subject to natural selection, but multicellular organisms have a somatic genome with a mutation rate that differs from the germline mutation rate. However, a lack of reliable methods to measure somatic mutation frequencies in DNA have precluded a direct comparison in mutation rates between somatic and germline cells. Vijg and colleagues present the first direct comparison of mutation rates in human and mouse single somatic cells, both of which are further compared to human and mouse de novo germline mutation rates. The CellRaft® Technology is utilized here to isolate single cells for downstream single cell whole genome sequencing after amplification. The results presented suggest that somatic mutation frequencies are significantly higher than germline mutation frequencies, which may point toward somatic mutations as a conserved mechanism of aging.
The authors present a novel methodology to address the artifacts associated with cell lysis and whole genome amplification during genome-wide DNA mutation analysis, termed Single-Cell Multiple Displacement Amplification (SCMDA). SCMDA and SCcaller were validated by direct comparison of SNVs from amplified single cells and unamplified clones derived from cells in the same population of early passage human primary fibroblasts. The CellRaft® Technology was utilized for multiple steps in the validation workflow, including isolation of single cells and generation of single cell clones. Single cells were plated on CytoSort™ Arrays, isolated, and subjected to downstream SCMDA, library preparation, and sequencing. Empty CellRafts® were also isolated to serve as negative controls in WGA. To generate single cell clones, cells were plated on CytoSort™ Arrays and isolated once the clones reached confluency on the CellRaft®, approximately 10-16 cells per raft, for further expansion in 96-well plates. Lastly, to generate kindred single cells and clones, small clones were transferred from 96-well and seeded on a fresh CellRaft Arrayto isolate single cells. This method, and the corresponding single-cell variant caller SCcaller, provide a foundation for standardizing somatic mutation analysis in single-cell genomics.