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Manohar SM. Shedding Light on Intracellular Proteins using Flow Cytometry. Cell Biochem Biophys 2024:10.1007/s12013-024-01338-1. [PMID: 38831173 DOI: 10.1007/s12013-024-01338-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/24/2024] [Indexed: 06/05/2024]
Abstract
Intracellular protein abundance is routinely measured in mammalian cells using population-based techniques such as western blotting which fail to capture single cell protein levels or using fluorescence microscopy which is although suitable for single cell protein detection but not for rapid analysis of large no. of cells. Flow cytometry offers rapid, high-throughput, multiparameter-based analysis of intracellular protein expression in statistically significant no. of cells at single cell resolution. In past few decades, customized assays have been developed for flow cytometric detection of specific intracellular proteins. This review discusses the scope of flow cytometry for intracellular protein detection in mammalian cells along with specific applications. Technological advancements to overcome the limitations of traditional flow cytometry for the same are also discussed.
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Affiliation(s)
- Sonal M Manohar
- Department of Biological Sciences, Sunandan Divatia School of Science, SVKM's NMIMS (Deemed-to-be) University, Vile Parle (West), Mumbai, 400056, India.
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Vir P, Arrigucci R, Lakehal K, Davidow AL, Pine R, Tyagi S, Bushkin Y, Lardizabal A, Gennaro ML. Single-Cell Cytokine Gene Expression in Peripheral Blood Cells Correlates with Latent Tuberculosis Status. PLoS One 2015; 10:e0144904. [PMID: 26658491 PMCID: PMC4681842 DOI: 10.1371/journal.pone.0144904] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2015] [Accepted: 11/25/2015] [Indexed: 12/29/2022] Open
Abstract
RNA flow cytometry (FISH-Flow) achieves high-throughput measurement of single-cell gene expression by combining in-situ nucleic acid hybridization with flow cytometry. We tested whether antigen-specific T-cell responses detected by FISH-Flow correlated with latent tuberculosis infection (LTBI), a condition affecting one-third of the world population. Peripheral-blood mononuclear cells from donors, identified as positive or negative for LTBI by current medical practice, were stimulated ex vivo with mycobacterial antigen. IFNG and IL2 mRNA production was assayed by FISH-Flow. Concurrently, immunophenotypes of the cytokine mRNA-positive cells were characterized by conventional, antibody-based staining of cell-surface markers. An association was found between donor LTBI status and antigen-specific induction of IFNG and IL2 transcripts. Induction of these cytokine genes, which was detected by FISH-Flow in a quarter the time required to see release of the corresponding proteins by ELISA, occurred primarily in activated CD4+ T cells via T-cell receptor engagement. Moreover, NK cells contributed to IFNG gene induction. These results show that antigen-driven induction of T-cell cytokine mRNA is a measurable single-cell parameter of the host responses associated with latent tuberculosis. FISH-Flow read-outs contribute a multi-scale dimension to the immunophenotyping afforded by antibody-based flow cytometry. Multi-scale, single-cell analyses may satisfy the need to determine disease stage and therapy response for tuberculosis and other infectious pathologies.
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Affiliation(s)
- Pooja Vir
- Public Health Research Institute, New Jersey Medical School, Rutgers, The State University of New Jersey, Newark, New Jersey, United States of America
| | - Riccardo Arrigucci
- Public Health Research Institute, New Jersey Medical School, Rutgers, The State University of New Jersey, Newark, New Jersey, United States of America
| | - Karim Lakehal
- Public Health Research Institute, New Jersey Medical School, Rutgers, The State University of New Jersey, Newark, New Jersey, United States of America
| | - Amy L. Davidow
- Department of Biostatistics, School of Public Health, New Jersey Medical School, Rutgers, The State University of New Jersey, Newark, New Jersey, United States of America
| | - Richard Pine
- Public Health Research Institute, New Jersey Medical School, Rutgers, The State University of New Jersey, Newark, New Jersey, United States of America
| | - Sanjay Tyagi
- Public Health Research Institute, New Jersey Medical School, Rutgers, The State University of New Jersey, Newark, New Jersey, United States of America
| | - Yuri Bushkin
- Public Health Research Institute, New Jersey Medical School, Rutgers, The State University of New Jersey, Newark, New Jersey, United States of America
| | - Alfred Lardizabal
- Global Tuberculosis Institute, New Jersey Medical School, Rutgers, The State University of New Jersey, Newark, New Jersey, United States of America
| | - Maria Laura Gennaro
- Public Health Research Institute, New Jersey Medical School, Rutgers, The State University of New Jersey, Newark, New Jersey, United States of America
- * E-mail:
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