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Cortés‐Llanos B, Jain V, Cooper‐Volkheimer A, Browne EP, Murdoch DM, Allbritton NL. Automated microarray platform for single-cell sorting and collection of lymphocytes following HIV reactivation. Bioeng Transl Med 2023; 8:e10551. [PMID: 37693052 PMCID: PMC10487311 DOI: 10.1002/btm2.10551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 04/29/2023] [Accepted: 05/04/2023] [Indexed: 09/12/2023] Open
Abstract
A promising strategy to cure HIV-infected individuals is to use latency reversing agents (LRAs) to reactivate latent viruses, followed by host clearance of infected reservoir cells. However, reactivation of latent proviruses within infected cells is heterogeneous and often incomplete. This fact limits strategies to cure HIV which may require complete elimination of viable virus from all cellular reservoirs. For this reason, understanding the mechanism(s) of reactivation of HIV within cellular reservoirs is critical to achieve therapeutic success. Methodologies enabling temporal tracking of single cells as they reactivate followed by sorting and molecular analysis of those cells are urgently needed. To this end, microraft arrays were adapted to image T-lymphocytes expressing mCherry under the control of the HIV long terminal repeat (LTR) promoter, in response to the application of LRAs (prostratin, iBET151, and SAHA). In response to prostratin, iBET151, and SAHA, 30.5%, 11.2%, and 12.1% percentage of cells, respectively. The arrays enabled large numbers of single cells (>25,000) to be imaged over time. mCherry fluorescence quantification identified cell subpopulations with differing reactivation kinetics. Significant heterogeneity was observed at the single-cell level between different LRAs in terms of time to reactivation, rate of mCherry fluorescence increase upon reactivation, and peak fluorescence attained. In response to prostratin, subpopulations of T lymphocytes with slow and fast reactivation kinetics were identified. Single T-lymphocytes that were either fast or slow reactivators were sorted, and single-cell RNA-sequencing was performed. Different genes associated with inflammation, immune activation, and cellular and viral transcription factors were found.
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Affiliation(s)
- Belén Cortés‐Llanos
- Department of BioengineeringUniversity of WashingtonWashingtonUSA
- Department of MedicineDuke UniversityNorth CarolinaUSA
| | - Vaibhav Jain
- Department of Molecular PhysiologyDuke UniversityNorth CarolinaUSA
| | | | - Edward P. Browne
- Department of MedicineUniversity of North CarolinaNorth CarolinaUSA
- Department of Microbiology and ImmunologyUniversity of North CarolinaNorth CarolinaUSA
- UNC HIV Cure CenterUniversity of North CarolinaNorth CarolinaUSA
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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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Cortés-Llanos B, Jain V, Volkheimer A, Browne EP, Murdoch DM, Allbritton NL. Automated microarray for single-cell sorting and collection of lymphocytes following HIV reactivation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.02.526757. [PMID: 36778314 PMCID: PMC9915582 DOI: 10.1101/2023.02.02.526757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
A promising strategy to cure HIV infected individuals is to use latency reversing agents (LRAs) to reactivate latent viruses, followed by host clearance of infected reservoir cells. However, reactivation of latent proviruses within infected cells is heterogeneous and often incomplete. This fact limits strategies to cure HIV which may require complete elimination of viable virus from all cellular reservoirs. For this reason, understanding the mechanism(s) of reactivation of HIV within cellular reservoirs is critical to achieve therapeutic success. Methodologies enabling temporal tracking of single cells as they reactivate followed by sorting and molecular analysis of those cells are urgently needed. To this end, microraft arrays were adapted to image T-lymphocytes expressing mCherry under the control of the HIV long terminal repeat (LTR) promoter, in response to the application of various LRAs (prostratin, iBET151, and SAHA). In response to prostratin, iBET151, and SAHA, 30.5 %, 11.2 %, and 12.1 % percentage of cells respectively, reactivated similar to that observed in other experimental systems. The arrays enabled large numbers of single cells (>25,000) to be imaged over time. mCherry fluorescence quantification identified cell subpopulations with differing reactivation kinetics. Significant heterogeneity was observed at the single cell level between different LRAs in terms of time to reactivation, rate of mCherry fluorescence increase upon reactivation, and peak fluorescence attained. In response to prostratin, subpopulations of T lymphocytes with slow and fast reactivation kinetics were identified. Single T-lymphocytes that were either fast or slow reactivators were sorted, and single-cell RNA-sequencing was performed. Different genes associated with inflammation, immune activation, and cellular and viral transcription factors were found. These results advance our conceptual understanding of HIV reactivation dynamics at the single-cell level toward a cure for HIV.
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DiSalvo M, Cortés-Llanos B, LaBelle CA, Murdoch DM, Allbritton NL. Scalable Additive Construction of Arrayed Microstructures with Encoded Properties for Bioimaging. MICROMACHINES 2022; 13:1392. [PMID: 36144015 PMCID: PMC9500771 DOI: 10.3390/mi13091392] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Revised: 08/20/2022] [Accepted: 08/23/2022] [Indexed: 06/16/2023]
Abstract
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.
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Affiliation(s)
- Matthew DiSalvo
- Microsystems and Nanotechnology Division, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA
| | - Belén Cortés-Llanos
- Department of Bioengineering, University of Washington, Seattle, WA 98105, USA
- Department of Medicine, Duke University Medical Center, Durham, NC 27705, USA
| | - Cody A. LaBelle
- Department of Bioengineering, University of Washington, Seattle, WA 98105, USA
| | - David M. Murdoch
- Department of Medicine, Duke University Medical Center, Durham, NC 27705, USA
| | - Nancy L. Allbritton
- Department of Bioengineering, University of Washington, Seattle, WA 98105, USA
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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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