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Laoharawee K, Kleinboehl EW, Jensen JD, Peterson JJ, Slipek NJ, Wick BJ, Johnson MJ, Webber BR, Moriarity BS. Engineering Memory T Cells as a platform for Long-Term Enzyme Replacement Therapy in Lysosomal Storage Disorders. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.23.590790. [PMID: 38712248 PMCID: PMC11071424 DOI: 10.1101/2024.04.23.590790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Enzymopathy disorders are the result of missing or defective enzymes. Amongst these enzymopathies, mucopolysaccharidosis type I, is a rare genetic lysosomal storage disorder caused by mutations in the gene encoding alpha-L-iduronidase (IDUA), ultimately causes toxic build-up of glycosaminoglycans (GAGs). There is currently no cure and standard treatments provide insufficient relief to the skeletal structure and central nervous system (CNS). Human memory T cells (Tm) migrate throughout the body's tissues and can persist for years, making them an attractive approach for cellular-based, systemic enzyme replacement therapy. Here, we tested genetically engineered, IDUA-expressing Tm as a cellular therapy in an immunodeficient mouse model of MPS I. Our results demonstrate that a single dose of engineered Tm leads to detectable IDUA enzyme levels in the blood for up to 22 weeks and reduced urinary GAG excretion. Furthermore, engineered Tm take up residence in nearly all tested tissues, producing IDUA and leading to metabolic correction of GAG levels in the heart, lung, liver, spleen, kidney, bone marrow, and the CNS. Our study indicates that genetically engineered Tm holds great promise as a platform for cellular-based enzyme replacement therapy for the treatment of mucopolysaccharidosis type I and potentially many other enzymopathies and protein deficiencies.
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This S, Costantino S, Melichar HJ. Machine learning predictions of T cell antigen specificity from intracellular calcium dynamics. SCIENCE ADVANCES 2024; 10:eadk2298. [PMID: 38446885 PMCID: PMC10917351 DOI: 10.1126/sciadv.adk2298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 01/29/2024] [Indexed: 03/08/2024]
Abstract
Adoptive T cell therapies rely on the production of T cells with an antigen receptor that directs their specificity toward tumor-specific antigens. Methods for identifying relevant T cell receptor (TCR) sequences, predominantly achieved through the enrichment of antigen-specific T cells, represent a major bottleneck in the production of TCR-engineered cell therapies. Fluctuation of intracellular calcium is a proximal readout of TCR signaling and candidate marker for antigen-specific T cell identification that does not require T cell expansion; however, calcium fluctuations downstream of TCR engagement are highly variable. We propose that machine learning algorithms may allow for T cell classification from complex datasets such as polyclonal T cell signaling events. Using deep learning tools, we demonstrate accurate prediction of TCR-transgenic CD8+ T cell activation based on calcium fluctuations and test the algorithm against T cells bearing a distinct TCR as well as polyclonal T cells. This provides the foundation for an antigen-specific TCR sequence identification pipeline for adoptive T cell therapies.
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Affiliation(s)
- Sébastien This
- Centre de recherche de l'Hôpital Maisonneuve-Rosemont, Montréal, Québec, Canada
- Département de Microbiologie, Infectiologie et Immunologie, Université de Montréal, Montréal, Québec, Canada
- Department of Microbiology and Immunology, Goodman Cancer Institute, McGill University, Montréal, Québec, Canada
| | - Santiago Costantino
- Centre de recherche de l'Hôpital Maisonneuve-Rosemont, Montréal, Québec, Canada
- Département d’Ophtalmologie, Université de Montréal, Montréal, Québec, Canada
| | - Heather J. Melichar
- Centre de recherche de l'Hôpital Maisonneuve-Rosemont, Montréal, Québec, Canada
- Department of Microbiology and Immunology, Goodman Cancer Institute, McGill University, Montréal, Québec, Canada
- Département de Médecine, Université de Montréal, Montréal, Québec, Canada
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LaBelle CA, Zhang RJ, Hunsucker SA, Armistead PM, Allbritton NL. Microraft arrays for serial-killer CD19 chimeric antigen receptor T cells and single cell isolation. Cytometry A 2023; 103:208-220. [PMID: 35899783 PMCID: PMC9883594 DOI: 10.1002/cyto.a.24678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2022] [Revised: 04/30/2022] [Accepted: 07/21/2022] [Indexed: 01/31/2023]
Abstract
Chimeric antigen receptor T (CAR-T) cell immunotherapies have seen success in treating hematological malignancies in recent years; however, the results can be highly variable. Single cell heterogeneity plays a key role in the variable efficacy of CAR-T cell treatments yet is largely unexplored. A major challenge is to understand the killing behavior and phenotype of individual CAR-T cells, which are able to serially kill targets. Thus, a platform capable of measuring time-dependent CAR-T cell mediated killing and then isolating single cells for downstream assays would be invaluable in characterizing CAR-T cells. An automated microraft array platform was designed to track CD19 CAR-T cell killing of CD19+ target cells and CAR-T cell motility over time followed by CAR-T cell collection based on killing behavior. The platform demonstrated automated CAR-T cell counting with up to 98% specificity and 96% sensitivity, and single cells were isolated with 89% efficiency. On average, 2.3% of single CAR-T cells were shown to participate in serial-killing of target cells, killing a maximum of three target cells in a 6 h period. The cytotoxicity and motility of >7000 individual CAR-T cells was tracked across four microraft arrays. The automated microraft array platform measured temporal cell-mediated cytotoxicity, CAR-T cell motility, CAR-T cell death, and CAR-T cell to target cell distances, followed by the capability to sort any desired CAR-T cell. The pipeline has the potential to further our understanding of T cell-based cancer immunotherapies and improve cell-therapy products for better patient outcomes.
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Affiliation(s)
- Cody A. LaBelle
- Joint Department of Biomedical Engineering, University of North Carolina, Chapel Hill, NC, and North Carolina State University, Raleigh, NC
- Department of Bioengineering, University of Washington, Seattle, WA
| | - Raymond J. Zhang
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC
| | - Sally A. Hunsucker
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC
| | - Paul M. Armistead
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC
- Department of Medicine, Division of Hematology, University of North Carolina, Chapel Hill, NC
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Molecular characterization of hypoxanthine guanine phosphoribosyltransferase mutant T cells in human blood: The concept of surrogate selection for immunologically relevant cells. MUTATION RESEARCH. REVIEWS IN MUTATION RESEARCH 2022; 789:108414. [PMID: 35690417 PMCID: PMC9188651 DOI: 10.1016/j.mrrev.2022.108414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 03/01/2022] [Accepted: 03/08/2022] [Indexed: 11/23/2022]
Abstract
Somatic cell gene mutations arise in vivo due to replication errors during DNA synthesis occurring spontaneously during normal DNA synthesis or as a result of replication on a DNA template damaged by endogenous or exogenous mutagens. In principle, changes in the frequencies of mutant cells in vivo in humans reflect changes in exposures to exogenous or endogenous DNA damaging insults, other factors being equal. It is becoming increasingly evident however, that somatic mutations in humans have a far greater range of interpretations. For example, mutations in lymphocytes provide invaluable probes for in vivo cellular and molecular processes, providing identification of clonal amplifications of these cells in autoimmune and infectious diseases, transplantation recipients, paroxysmal nocturnal hemoglobinuria (PNH), and cancer. The assay for mutations of the X-chromosomal hypoxanthine guanine phosphoribosyltransferase (HPRT) gene has gained popular acceptance for this purpose since viable mutant cells can be recovered for molecular and other analyses. Although the major application of the HPRT T cell assay remains human population monitoring, the enrichment of activated T cells in the mutant fraction in individuals with ongoing immunological processes has demonstrated the utility of surrogate selection, a method that uses somatic mutation as a surrogate marker for the in vivo T cell proliferation that underlies immunological processes to investigate clinical disorders with immunological features. Studies encompassing a wide range of clinical conditions are reviewed. Despite the historical importance of the HPRT mutation system in validating surrogate selection, there are now additional mutational and other methods for identifying immunologically active T cells. These methods are reviewed and provide insights for strategies to extend surrogate selection in future studies.
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Cortés-Llanos B, Wang Y, Sims CE, Allbritton NL. A technology of a different sort: microraft arrays. LAB ON A CHIP 2021; 21:3204-3218. [PMID: 34346456 PMCID: PMC8387436 DOI: 10.1039/d1lc00506e] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
A common procedure performed throughout biomedical research is the selection and isolation of biological entities such as organelles, cells and organoids from a mixed population. In this review, we describe the development and application of microraft arrays, an analysis and isolation platform which enables a vast range of criteria and strategies to be used when separating biological entities. The microraft arrays are comprised of elastomeric microwells with detachable polymer bases (microrafts) that act as capture and culture sites as well as supporting carriers during cell isolation. The technology is elegant in its simplicity and can be implemented for samples possessing tens to millions of objects yielding a flexible platform for applications such as single-cell RNA sequencing, subcellular organelle capture and assay, high-throughput screening and development of CRISPR gene-edited cell lines, and organoid manipulation and selection. The transparent arrays are compatible with a multitude of imaging modalities enabling selection based on 2D or 3D spatial phenotypes or temporal properties. Each microraft can be individually isolated on demand with retention of high viability due to the near zero hydrodynamic stress imposed upon the cells during microraft release, capture and deposition. The platform has been utilized as a simple manual add-on to a standard microscope or incorporated into fully automated instruments that implement state-of-the-art imaging algorithms and machine learning. The vast array of selection criteria enables separations not possible with conventional sorting methods, thus garnering widespread interest in the biological and pharmaceutical sciences.
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LaBelle CA, Massaro A, Cortés-Llanos B, Sims CE, Allbritton NL. Image-Based Live Cell Sorting. Trends Biotechnol 2020; 39:613-623. [PMID: 33190968 DOI: 10.1016/j.tibtech.2020.10.006] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 10/13/2020] [Accepted: 10/14/2020] [Indexed: 12/11/2022]
Abstract
Technologies capable of cell separation based on cell images provide powerful tools enabling cell selection criteria that rely on spatially or temporally varying properties. Image-based cell sorting (IBCS) systems utilize microfluidic or microarray platforms, each having unique characteristics and applications. The advent of IBCS marks a new paradigm in which cell phenotype and behavior can be explored with high resolution and tied to cellular physiological and omics data, providing a deeper understanding of single-cell physiology and the creation of cell lines with unique properties. Cell sorting guided by high-content image information has far-reaching implications in biomedical research, clinical medicine, and pharmaceutical development.
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Affiliation(s)
- Cody A LaBelle
- Joint Department of Biomedical Engineering, University of North Carolina, Chapel Hill, NC, and North Carolina State University, Raleigh, NC, USA; Department of Bioengineering, University of Washington, Seattle, WA, USA
| | - Angelo Massaro
- Department of Bioengineering, University of Washington, Seattle, WA, USA
| | | | - Christopher E Sims
- Department of Bioengineering, University of Washington, Seattle, WA, USA; Department of Medicine, University of Washington, Seattle, WA, USA
| | - Nancy L Allbritton
- Department of Bioengineering, University of Washington, Seattle, WA, USA.
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LaBelle CA, Zhang RJ, Armistead PM, Allbritton NL. Assay and Isolation of Single Proliferating CD4+ Lymphocytes Using an Automated Microraft Array Platform. IEEE Trans Biomed Eng 2019; 67:2166-2175. [PMID: 31794384 DOI: 10.1109/tbme.2019.2956081] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
OBJECTIVE 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.
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DiSalvo M, Smiddy NM, Allbritton NL. Automated sensing and splitting of stem cell colonies on microraft arrays. APL Bioeng 2019; 3:036106. [PMID: 31489396 PMCID: PMC6715441 DOI: 10.1063/1.5113719] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Accepted: 08/17/2019] [Indexed: 01/24/2023] Open
Abstract
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.
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Affiliation(s)
- Matthew DiSalvo
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill and North Carolina State University, Chapel Hill/Raleigh, North Carolina 27599/27607, USA
| | - Nicole M. Smiddy
- Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
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Chason KD, Jaspers I, Parker J, Sellers S, Brighton LE, Hunsucker SA, Armistead PM, Fischer WA. Age-Associated Changes in the Respiratory Epithelial Response to Influenza Infection. J Gerontol A Biol Sci Med Sci 2018; 73:1643-1650. [PMID: 29878083 PMCID: PMC6230210 DOI: 10.1093/gerona/gly126] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2018] [Indexed: 12/21/2022] Open
Abstract
Older adults suffer a disproportionate burden of influenza-related morbidity and mortality typically attributed to defects in the aging immune system collectively known as immunosenescence. While the age-related decline in the adaptive immune system has been well characterized, little is known about how aging affects the principal site of influenza infection-the nasal epithelium. In human nasal epithelial cell cultures (hNECs) from older adults, we found similar or increased levels of cytokines during influenza infection compared with hNECs from younger individuals. However, hNECs from older individuals demonstrated decreased mRNA expression for several key proteins that affect clearance of infected cells, including MHC-I and transporter associated with antigen presentation (TAP). These findings were confirmed at the level of protein expression. In vivo studies corroborated the in vitro differences in MHC-I and TAP gene expression and also revealed important decreases in the expression of key influenza-specific antiviral mediators MX1 and IFITM1. Furthermore, epithelial cell-cytotoxic T lymphocyte co-cultures demonstrate that CTL cytotoxic activity is dose-dependent on MHC-I antigen presentation. Taken together, these results indicate that aging is associated with important changes in the nasal epithelium, including antigen presentation and antiviral pathways, which may contribute to increased severity of disease in older adults through impaired clearance of infected cells.
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Affiliation(s)
- Kelly D Chason
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, The University of North Carolina at Chapel Hill School of Medicine
| | - Ilona Jaspers
- Department of Pediatrics, The University of North Carolina at Chapel Hill School of Medicine
- The Center for Environmental Medicine, Asthma and Lung Biology, The University of North Carolina at Chapel Hill School of Medicine
| | - Joel Parker
- Department of Genetics and Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill School of Medicine
| | - Subhashini Sellers
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, The University of North Carolina at Chapel Hill School of Medicine
| | - Louisa E Brighton
- Department of Pediatrics, The University of North Carolina at Chapel Hill School of Medicine
| | - Sally A Hunsucker
- Department of Genetics and Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill School of Medicine
| | - Paul M Armistead
- Department of Genetics and Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill School of Medicine
| | - William A Fischer
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, The University of North Carolina at Chapel Hill School of Medicine
- The Center for Environmental Medicine, Asthma and Lung Biology, The University of North Carolina at Chapel Hill School of Medicine
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Affiliation(s)
- Pieter E. Oomen
- University of Gothenburg, Department of Chemistry and Molecular Biology, Gothenburg 41296, Sweden
| | - Mohaddeseh A. Aref
- University of Gothenburg, Department of Chemistry and Molecular Biology, Gothenburg 41296, Sweden
| | - Ibrahim Kaya
- University of Gothenburg, Department of Chemistry and Molecular Biology, Gothenburg 41296, Sweden
- Department of Psychiatry and Neurochemistry, Sahlgrenska Academy at the University of Gothenburg, Mölndal Hospital, House V3, 43180 Mölndal, Sweden
- The Gothenburg Imaging Mass Spectrometry (Go:IMS) Laboratory, University of Gothenburg and Chalmers University of Technology, Gothenburg 41296, Sweden
| | - Nhu T. N. Phan
- University of Gothenburg, Department of Chemistry and Molecular Biology, Gothenburg 41296, Sweden
- The Gothenburg Imaging Mass Spectrometry (Go:IMS) Laboratory, University of Gothenburg and Chalmers University of Technology, Gothenburg 41296, Sweden
- University of Göttingen Medical Center, Institute of Neuro- and Sensory Physiology, Göttingen 37073, Germany
| | - Andrew G. Ewing
- University of Gothenburg, Department of Chemistry and Molecular Biology, Gothenburg 41296, Sweden
- The Gothenburg Imaging Mass Spectrometry (Go:IMS) Laboratory, University of Gothenburg and Chalmers University of Technology, Gothenburg 41296, Sweden
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Cai W, Chiu YJ, Ramakrishnan V, Tsai Y, Chen C, Lo YH. A single-cell translocation and secretion assay (TransSeA). LAB ON A CHIP 2018; 18:3154-3162. [PMID: 30179236 PMCID: PMC6177299 DOI: 10.1039/c8lc00821c] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
Understanding biological heterogeneity at the single cell level is required for advancing insights into the complexity of human physiology and diseases. While advances in technological and analytical methods have afforded unprecedented glimpses of this heterogeneity, the information captured to date largely represents one-time "snap" shots of single cell physiology. To address the limits of existing methods and to accelerate discoveries from single cell studies, we developed a single-cell translocation and secretion assay (TransSeA) that supports time lapse analysis, enables molecular cargo analysis of secretions such as extracellular vesicles (EVs) from single cells, allows massively parallel single cell transfer according to user-defined cell selection criteria, and supports tracking of phenotypes between parental and progeny cells derived from single cells. To demonstrate the unique capabilities and efficiencies of the assay, we present unprecedented single cell studies related to cell secretions, EV cargos and cell intrinsic properties. Although used as examples to demonstrate the feasibility and versatility of the technology, the studies already provided insights into key unanswered questions such as the microRNAs carried by EVs, the relationships between EV secretion rates and gene expressions, and the spontaneous, trans-generational phenotypic changes in EV secretion between parental and progeny cells.
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Affiliation(s)
- Wei Cai
- Materials Science and Engineering Program, University of California at San Diego, La Jolla, California, USA.
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DiSalvo M, Harris DM, Kantesaria S, Peña AN, Allbritton-King JD, Cole JH, Allbritton NL. Characterization of Tensioned PDMS Membranes for Imaging Cytometry on Microraft Arrays. Anal Chem 2018; 90:4792-4800. [PMID: 29510027 DOI: 10.1021/acs.analchem.8b00176] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
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.
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Affiliation(s)
- Matthew DiSalvo
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States and North Carolina State University, Raleigh, North Carolina 27607, United States
| | | | - Saurin Kantesaria
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States and North Carolina State University, Raleigh, North Carolina 27607, United States
| | | | - Jules D Allbritton-King
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States and North Carolina State University, Raleigh, North Carolina 27607, United States
| | - Jacqueline H Cole
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States and North Carolina State University, Raleigh, North Carolina 27607, United States
| | - Nancy L Allbritton
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States and North Carolina State University, Raleigh, North Carolina 27607, United States
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Abstract
Single-cell analysis has become an established method to study cell heterogeneity and for rare cell characterization. Despite the high cost and technical constraints, applications are increasing every year in all fields of biology. Following the trend, there is a tremendous development of tools for single-cell analysis, especially in the RNA sequencing field. Every improvement increases sensitivity and throughput. Collecting a large amount of data also stimulates the development of new approaches for bioinformatic analysis and interpretation. However, the essential requirement for any analysis is the collection of single cells of high quality. The single-cell isolation must be fast, effective, and gentle to maintain the native expression profiles. Classical methods for single-cell isolation are micromanipulation, microdissection, and fluorescence-activated cell sorting (FACS). In the last decade several new and highly efficient approaches have been developed, which not just supplement but may fully replace the traditional ones. These new techniques are based on microfluidic chips, droplets, micro-well plates, and automatic collection of cells using capillaries, magnets, an electric field, or a punching probe. In this review we summarize the current methods and developments in this field. We discuss the advantages of the different commercially available platforms and their applicability, and also provide remarks on future developments.
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