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Here, we present a protocol to evaluate the killing capacity and functional profile of human HIV-specific CD8 T cells. We describe steps for culturing peripheral blood mononuclear cells (PBMCs) from patients with HIV on antiretroviral therapy (ART) with HIV peptides ex vivo and quantifying HIV-specific CD8 T cell killing using flow cytometry. We then detail procedures for integrating the established killing assay with intracellular cytokine staining (ICS) and assessing CD8 T cell function. This protocol can provide insights into CD8 T cell-mediated immunity against HIV. For complete details on the use and execution of this protocol, please refer to Mbitikon-Kobo et al.,1 Noto et al.,2 and Gubser et al.3.
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OBJECTIVE: This study assessed the cellular composition and effects of leukocyte-platelet-rich fibrin (L-PRF) exudate on whole blood platelets from healthy volunteers. Key objectives included evaluating leukocyte subpopulations, platelet activation markers, platelet-leukocyte interactions and quantifying inflammatory cytokines within the L-PRF exudate. MATERIALS AND METHODS: L-PRF was obtained from 20 healthy donors. Flow cytometry methodologies were used to assess intracellular calcium kinetics and activated GPIIbIIIa, and P-selectin expression. Leukocyte subpopulations and platelet-leukocyte interactions were characterized using monoclonal antibodies. Inflammatory cytokines (IL-8, IL-1ß, IL-6, IL-10, TNF, IL-12p70) within L-PRF exudate were quantified using a cytometric bead array. RESULTS: The expression of activated GPIIbIIIa, and P-selectin exhibited a significant increase (p < 0.001) when L-PRF exudate was added to platelets of whole blood. Regarding intracellular Ca2+ mobilization, the L-PRF exudate elicited significant responses (p < 0.001). L-PRF exudate contained different leukocytes populations, being TCD4 + the most representative of T cells. It was possible to stablish a profile of cytokines produced by the L-PRF exudate, with human IL-8 cytokine exhibiting the highest average (16.90 pg/mL). CONCLUSIONS: Despite the study limitations, the research yielded important insights: 1- L-PRF exudate can stimulate platelet activation, essential in healing, tissue inflammation and remodeling. 2-The presence of leukocyte subpopulations within L-PRF exudate reflexes its complexity and potential to enhance immune responses. 3-The analysis of inflammatory cytokines within L-PRF exudate revealed its immunomodulatory potential. These findings are valuable evidences for understanding the potential role of L-PRF exudate in regenerative dentistry and medicine, offering innovative therapeutic strategies. CLINICAL RELEVANCE: This research highlights crucial aspects that could significantly influence the clinical use of L-PRF exudate in the oral cavity. The findings support the application of L-PRF exudate in both surgical and regenerative dentistry, facilitating the development of innovative therapeutic strategies to enhance patient outcomes.
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Plaquetas , Citocinas , Exudados y Transudados , Citometría de Flujo , Fibrina Rica en Plaquetas , Humanos , Masculino , Citocinas/metabolismo , Femenino , Adulto , Voluntarios Sanos , Activación Plaquetaria , Leucocitos , Biomarcadores/sangreRESUMEN
Psoriasis is a chronic, inflammatory skin disease characterized by a dysregulated immune response and systemic inflammation. Up to one-third of patients with psoriasis have psoriatic arthritis (PsA). Targeted treatment with antibodies neutralizing tumor necrosis factor (TNF) can ameliorate both diseases. We here explored the impact of long-term infliximab treatment on the composition and activity status of circulating immune cells involved in chronic skin and joint inflammation. Immune cells were analyzed by multicolor flow cytometry. We measured markers of immune activation in peripheral blood mononuclear cell (PBMC) populations in 24 infliximab-treated patients with psoriasis/psoriatic arthritis compared to 32 healthy controls. We observed a significant decrease in the frequency of both peripheral natural killer (NK) cells and their subset CD56dimCD16+ NK cells in PsA compared to healthy controls and patients with psoriasis. The latter had a strong positive correlation with PASI in these patients, while CD56brightCD16- NK cells were negatively correlated with PASI. In addition, we observed an upregulation of CD69+ intermediate CD14+CD16+ and CD69+ classical CD14+CD16- monocytes in PsA and increased activity of CD38+ intermediate CD14+CD16+ monocytes in patients with psoriasis. Compared to healthy controls, psoriasis patients demonstrated shifts of the three B cell subsets with a decrease in transitional CD27-CD38high B cells. Our exploratory study indicates a preserved pathophysiological process including continuous systemic inflammation despite clinical stability of the patients treated with infliximab.
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Extracellular vesicles (EVs) are membranous nanoparticles classified based on their size and surface markers, which can be specific to various cell origins. Here, we present a protocol for the isolation of pulmonary-specific EVs in mice. We describe steps for differential centrifugation, density gradient centrifugation, and commercially available polyethylene glycol(PEG)-based precipitation, employing pulmonary-specific EV-bound chemicals and antibodies. We then detail procedures for the characterization of these EVs through nanoparticle tracking analysis, flow cytometry, scanning electron microscopy, and transmission electron microscopy. For complete details on the use and execution of this protocol, please refer to Lee et al.1,2,3,4.
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Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) infection can lead to life-threatening clinical manifestations. Patients with cardiovascular disease (CVD) are at higher risk for severe courses of COVID-19. So far, however, there are hardly any strategies for predicting the course of SARS-CoV-2 infection in CVD patients at hospital admission. Thus, we investigated whether this prediction is achievable by prospectively analysing the blood immunophenotype of 94 nonvaccinated participants, including uninfected and acutely SARS-CoV-2-infected CVD patients and healthy donors, using a 36-colour spectral flow cytometry panel. Unsupervised data analysis revealed little differences between healthy donors and CVD patients, whereas the distribution of the cell populations changed dramatically in SARS-CoV-2-infected CVD patients. The latter had more mature NK cells, activated monocyte subsets, central memory CD4+ T cells, and plasmablasts but fewer dendritic cells, CD16+ monocytes, innate lymphoid cells, and CD8+ T-cell subsets. Moreover, we identified an immune signature characterised by CD161+ T cells, intermediate effector CD8+ T cells, and natural killer T (NKT) cells that is predictive for CVD patients with a severe course of COVID-19. Thus, intensified immunophenotype analyses can help identify patients at risk of severe COVID-19 at hospital admission, improving clinical outcomes through specific treatment.
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BACKGROUND: The difference in the clinical course, response to therapy, and distribution of CNS inflammation in primary-progressive (PPMS) and relapsing-remitting multiple sclerosis (RRMS) suggests differences in the underlying immunological characteristics of the disease. We aimed to investigate differences in immunological profiles in relation to intrathecal inflammation in different MS forms. METHODS: The peripheral blood (PB) proportions of CD4 + and CD8 + T-cells and CD19 + B-cells were retrospectively compared with the markers of intrathecal immunoglobulin G (IgG) synthesis at diagnosis: IgG index, percentage of intrathecal IgG synthesis (IF IgG), the number of oligoclonal bands (OCB), depending on the blood-brain barrier (BBB) function, and antibody specific index to neurotrophic viruses (MRZH reaction). RESULTS: Thirty-six controls, 71 RRMS and 25 PPMS were enrolled. PPMS had higher percentage of CD4 + T-cells compared to RRMS (P = 0.043) and controls (P = 0.003). The percentage of CD8 + T-cells and CD19 + B-cells, and respective absolute cell counts did not differ according to the MS phenotype. In RRMS with the dysfunctional BBB, the IgG index (r = 0.642, P = 0.012) correlated significantly with the CD19 + B-cells while the CD4 + T-cells inversely correlated with IF IgG (r=-0.574, P = 0.039). Interestingly, in PPMS the number of OCB was positively associated with CD4+ (r = 0.603, P = 0.015) and negatively associated with CD8 + T-cells (r=-0.554, P = 0.033), while IF IgG negatively correlated with CD8 + T-cells (r=-0.689, P = 0.003), but only in the preserved BBB function. CONCLUSIONS: The PB CD4 + T-cells and B-cells were associated with the intrathecal inflammation in RRMS with BBB dysfunction while CD8 + T-cells were involved in PPMS with CNS-compartmentalized inflammation.
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This "Best Practices in User Consultation" article is the result of a 2022 International Society for the Advancement of Cytometry (ISAC) membership survey that collected valuable insights from the shared research laboratory (SRL) community and of a group discussion at the CYTO 2022 workshop of the same name. One key takeaway is the importance of initiating a consultation at the outset of a flow cytometry project, particularly for trainees. This approach enables the improvement and standardization of every step, from planning experiments to interpreting data. This proactive approach effectively mitigates experimental bias and avoids superfluous trial and error, thereby conserving valuable time and resources. In addition to guidelines, the optimal approaches for user consultation specify communication channels, methods, and critical information, thereby establishing a structure for productive correspondence between SRL and users. This framework functions as an exemplar for establishing robust and autonomous collaborative relationships. User consultation adds value by providing researchers with the necessary information to conduct reproducible flow cytometry experiments that adhere to scientific rigor. By following the steps, instructions, and strategies outlined in these best practices, an SRL can readily tailor them to its own setting, establishing a personalized workflow and formalizing user consultation services. This article provides a pragmatic guide for improving the caliber and efficacy of flow cytometry research and aggregates the flow cytometry SRL community's collective knowledge regarding user consultation.
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As the dimensionality, throughput and complexity of cytometry data increases, so does the demand for user-friendly, interactive analysis tools that leverage high-performance machine learning frameworks. Here we introduce FlowAtlas: an interactive web application that enables dimensionality reduction of cytometry data without down-sampling and that is compatible with datasets stained with non-identical panels. FlowAtlas bridges the user-friendly environment of FlowJo and computational tools in Julia developed by the scientific machine learning community, eliminating the need for coding and bioinformatics expertise. New population discovery and detection of rare populations in FlowAtlas is intuitive and rapid. We demonstrate the capabilities of FlowAtlas using a human multi-tissue, multi-donor immune cell dataset, highlighting key immunological findings. FlowAtlas is available at https://github.com/gszep/FlowAtlas.jl.git.
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Biología Computacional , Citometría de Flujo , Inmunofenotipificación , Programas Informáticos , Humanos , Inmunofenotipificación/métodos , Citometría de Flujo/métodos , Biología Computacional/métodos , Aprendizaje AutomáticoRESUMEN
Arginase1 (ARG1) is a metabolic enzyme that is highly expressed in tumor-associated myeloid-derived suppressor cells (MDSCs) and causes the dysfunction of tumor-reactive T cells. Here, we present a protocol for detecting ARG1 expression in tumor MDSCs from a murine model of colon cancer using flow cytometry. We describe steps for tumor tissue processing, antibody staining, and data acquisition. We then detail procedures for identifying MDSC subsets and detecting ARG1 expression using a precise gating strategy. For complete details on the use and execution of this protocol, please refer to Zhang et al.1.
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Fresh, unpasteurized carrot juice is a popular element of the everyday diet of many consumers, and as such the matter of the juice's microbial safety remains an important one. Imaging flow cytometry (FCM) allows a fast enumeration and determination of cells, as well as their further differentiation. However, carrot juice is a difficult food product to analyze with the use of FCM due to interference from autofluorescence and the presence of plant debris. In this research, we aimed to obtain an effective and repeatable protocol for the preparation of carrot juice samples for FCM analysis. Through experimental and software-based means we successfully determined a reliable protocol for the preparation of fresh, unpasteurized carrot juice, which consisted of a sequence of filtering, centrifugation, enzyme treatment, and finally the implementation of the Machine Learning protocol for the best result.
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Automation in clinical flow cytometry has the potential to revolutionize the field by improving processes and enhancing efficiency and accuracy. Integrating advanced robotics and artificial intelligence, these technologies can streamline sample preparation, data acquisition, and analysis. Automated sample handling reduces human error and increases throughput, allowing laboratories to handle larger volumes with consistent precision. Intelligent algorithms contribute to rapid data interpretation, aiding in the identification of cellular markers for disease diagnosis and monitoring. This automation not only accelerates turnaround times but also ensures reproducibility, making clinical flow cytometry a reliable tool in the realm of personalized medicine and diagnostics.
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Citometría de Flujo , Citometría de Flujo/métodos , Humanos , Automatización , Automatización de Laboratorios , Inteligencia ArtificialRESUMEN
Multiparameter flow cytometry (MPF) is an essential component of the diagnostic workup of hematologic malignancies. Recently developed tools have expanded the utility of MPF in detecting T-cell clonality and myelomonocytic dysplasia. Minimal/measurable residual disease analysis has long been established as critical in the management of B-lymphoblastic leukemia and is emerging as a useful tool in myeloid malignancies. With the continued increased complexity of MPF assays, emerging tools for data collection and analysis will allow users to take full advantage of MPF in the diagnosis of hematologic disease.
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Citometría de Flujo , Neoplasias Hematológicas , Humanos , Neoplasias Hematológicas/diagnóstico , Neoplasias Hematológicas/patología , Inmunofenotipificación , Neoplasia Residual/diagnósticoRESUMEN
The clinical analysis of urine has classically focused on conventional chemical-based urinalysis and urine microscopy. Contemporary advances in both analysis subsets have started to employ new technologies such as automated image analysis, flow cytometry, and mass spectrometry. In addition to new detection technologies, current analyzers have incorporated more advanced imaging, automated sample handing, and machine learning analyses into their workflow. The most advanced semiautomated analyzers can be interfaced with hospital medical record systems, and in the point-of-care setting, smartphones can be used for image analysis. This review will discuss current technological advancements in the field of urinalysis and urine microscopy.
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Urinálisis , Humanos , Urinálisis/instrumentación , Espectrometría de Masas , Citometría de Flujo , Microscopía/instrumentación , Automatización de Laboratorios , Aprendizaje AutomáticoRESUMEN
Clinical flow cytometry plays a vital role in the diagnosis and monitoring of various red blood cell disorders. The high throughput, precision, and automation potential of this technique allows for cost-effective and timely analysis compared to older and more manual test methods. Flow cytometric analysis serves as the gold standard diagnostic method for multiple hematological disorders, especially in clinical scenarios where an assay needs to have high sensitivity, high specificity, and a short turnaround time. In this review, we discuss the role of flow cytometric analysis in paroxysmal nocturnal hemoglobinuria, fetal-maternal hemorrhage, and hereditary spherocytosis.
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Citometría de Flujo , Esferocitosis Hereditaria , Humanos , Citometría de Flujo/métodos , Esferocitosis Hereditaria/diagnóstico , Esferocitosis Hereditaria/sangre , Eritrocitos/citología , Hemoglobinuria Paroxística/diagnóstico , Hemoglobinuria Paroxística/sangre , Enfermedades Hematológicas/diagnóstico , Enfermedades Hematológicas/sangre , Embarazo , Femenino , Transfusión Fetomaterna/diagnóstico , Transfusión Fetomaterna/sangreRESUMEN
There are approximately 500 congenital disorders that impair immune cell development and/or function. Patients with these disorders may present with a wide range of symptoms, including increased susceptibility to infection, autoimmunity, autoinflammation, lymphoproliferation, and/or atopy. Flow cytometry-based immune phenotyping of T and B lymphocytes plays an essential role in the evaluation of patients with these presentations. In this review, we describe the clinical utility of flow cytometry as part of a comprehensive evaluation of immune function and how this testing may be used as a diagnostic tool to identify underlying aberrant immune pathways, monitor disease activity, and assess infection risk.
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Linfocitos B , Citometría de Flujo , Inmunofenotipificación , Linfocitos T , Humanos , Linfocitos B/inmunología , Linfocitos T/inmunología , Síndromes de Inmunodeficiencia/diagnóstico , Síndromes de Inmunodeficiencia/inmunologíaRESUMEN
Clinical assessment of platelet activation by flow cytometry is useful in the characterization and diagnosis of platelet-specific disorders and as a measure of risk for thrombosis or bleeding. Platelets circulate in a resting, "unactivated" state, but when activated they undergo alterations in surface glycoprotein function and/or expression level, exposure of granule membrane proteins, and exposure of procoagulant phospholipids. Flow cytometry provides the means to detect these changes and, unlike other platelet tests, is appropriate for measuring platelet function in samples from patients with low platelet counts. The present review will focus on flow cytometric tests for platelet activation markers.
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Plaquetas , Citometría de Flujo , Activación Plaquetaria , Humanos , Pruebas de Función Plaquetaria , Trastornos de las Plaquetas Sanguíneas/diagnóstico , Trastornos de las Plaquetas Sanguíneas/sangre , Biomarcadores/sangreRESUMEN
Circulating cell-free nucleic acids are considered a promising source of biomarkers for diseases and cancer. Liquid biopsy biomarkers for brain tumours represent a major, still unmet, clinical need. In plasma, nucleic acids can be free or be associated with extracellular vesicles (EVs). Here we report an easy and reproducible method to analyse cell-free nucleic acids in plasma and EVs by conventional flow cytometry easy to translate into the clinics. Nucleic acids associated with the EVs or present in plasma samples are stained by Pyronin Y, which is a fluorescent dye that is preferably binding double-stranded nucleic acids. Fluorescent staining of EVs isolated from cell-conditioned media is suitable for DNA and RNA detection by flow cytometry. The nucleic acids are partially protected from degradation by the EVs' membrane. Additionally, DNA and RNA can be stained in plasma samples and plasma-derived EVs. Remarkably, analysis of plasma from patients and healthy individuals reveals a difference in their nucleic acid profiles. Taken together, our results indicate that the proposed methodology, which is based on conventional direct flow cytometry, is a promising easy tool for plasma nucleic acid analysis.
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Cellular phenotype and function are altered in different microenvironments. For targeted therapies it is important to understand site-specific cellular adaptations. Juvenile Idiopathic Arthritis (JIA) is characterised by autoimmune joint inflammation, with frequent inadequate treatment responses. To comprehensively assess the inflammatory immune landscape, we designed a 37-parameter spectral flow cytometry panel delineating mononuclear cells from JIA synovial fluid (SF) of autoimmune inflamed joints, compared to JIA and healthy control blood. Synovial monocytes and NK cells (CD56bright) lack Fc-receptor CD16, suggesting antibody-mediated targeting may be ineffective. B cells and DCs, both in small frequencies in SF, undergo maturation with high 4-1BB, CD71, CD39 expression, supporting T cell activation. SF effector and regulatory T cells were highly active with newly described co-receptor combinations that may alter function, and suggestion of metabolic reprogramming via CD71, TNFR2 and PD-1. Most SF effector phenotypes, as well as an identified CD4-Foxp3+ T cell population, were restricted to the inflamed joint, yet specific SF-predominant CD4+Foxp3+ Treg subpopulations were increased in blood of active but not inactive JIA, suggesting possible recirculation and loss of immunoregulation at distal sites. This first comprehensive dataset of the site-specific inflammatory landscape at protein level will inform functional studies and the development of targeted therapeutics to restore immunoregulatory balance and achieve remission in JIA.
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Imaging flow cytometry, which combines the advantages of flow cytometry and microscopy, has emerged as a powerful tool for cell analysis in various biomedical fields such as cancer detection. In this study, we develop multiplex imaging flow cytometry (mIFC) by employing a spatial wavelength division multiplexing technique. Our mIFC can simultaneously obtain brightfield and multi-color fluorescence images of individual cells in flow, which are excited by a metal halide lamp and measured by a single detector. Statistical analysis results of multiplex imaging experiments with resolution test lens, magnification test lens, and fluorescent microspheres validate the operation of the mIFC with good imaging channel consistency and micron-scale differentiation capabilities. A deep learning method is designed for multiplex image processing that consists of three deep learning networks (U-net, very deep super resolution, and visual geometry group 19). It is demonstrated that the cluster of differentiation 24 (CD24) imaging channel is more sensitive than the brightfield, nucleus, or cancer antigen 125 (CA125) imaging channel in classifying the three types of ovarian cell lines (IOSE80 normal cell, A2780, and OVCAR3 cancer cells). An average accuracy rate of 97.1% is achieved for the classification of these three types of cells by deep learning analysis when all four imaging channels are considered. Our single-detector mIFC is promising for the development of future imaging flow cytometers and for the automatic single-cell analysis with deep learning in various biomedical fields.