Project description:While dogs are increasingly being utilized as large-animal models of disease, important features of age-related immunosenescence in the dog have yet to be evaluated due to the lack of defined naïve vs. memory T lymphocyte phenotypes. We therefore performed multi-color flow cytometry on peripheral blood mononuclear cells from young and aged beagles, and determined the differential cytokine production by proposed memory subsets. CD4+ and CD8+ T lymphocytes in aged dogs displayed increased cytokine production, and decreased proliferative capacity. Antibodies targeting CD45RA and CD62L, but less so CD28 or CD44, defined canine cells that consistently exhibited properties of naïve-, central memory-, effector memory-, and terminal effector-like CD4+ and CD8+ T lymphocyte subsets. Older dogs demonstrated decreased frequencies of naïve-like CD4+ and CD8+ T lymphocytes, and an increased frequency of terminal effector-like CD8+ T lymphocytes. Overall findings revealed that aged dogs displayed features of immunosenescence similar to those reported in other species.
Project description:Primary immunodeficiency diseases (PID) is a heterogeneous group of disorders caused by genetic defects of the immune system, which manifests clinically as recurrent infections, autoimmune diseases, or malignancies. Early detection of other PID remains a challenge, particularly in older children due to milder and less specific symptoms, a low level of clinician PID awareness and poor provision of hospital laboratories with appropriate devices. T-cell recombination excision circles (TREC) and kappa-deleting element recombination circle (KREC) in a dried blood spot and in peripheral blood using real-time polymerase chain reaction (PCR) are used as a tool for severe combined immune deficiency but not in PID. They represent an attractive and cheap target for a more extensive use in clinical practice. This study aimed to assess TREC/KREC correspondence with lymphocyte subpopulations, measured by flow cytometry and evaluate correlations between TREC/KREC, lymphocyte subpopulations and immunoglobulins. We carried out analysis of data from children assessed by clinical immunologists at Speransky Children's Hospital, Moscow, Russia with suspected immunodeficiencies between May 2013 and August 2016. Peripheral blood samples were sent for TREC/KREC, flow cytometry (CD3, CD4, CD8, and CD19), IgA, IgM, and IgG analysis. A total of 839 samples were analyzed for using TREC assay and flow cytometry and 931 KREC/flow cytometry. TREC demonstrated an AUC of 0.73 (95% CI 0.70-0.76) for CD3, 0.74 (95% CI 0.71-0.77) for CD4 and 0.67 (95% CI 0.63-0.70) for CD8, respectively, while KREC demonstrated an AUC of 0.72 (95% CI 0.69-0.76) for CD19. Moderate correlation was found between the levels of TREC and CD4 (r = 0.55, p < 0.01) and KREC with CD19 (r = 0.56, p < 0.01). In this study, promising prediction models were tested. We found that TREC and KREC are able to moderately detect abnormal levels of individual lymphocyte subpopulations. Future research should assess associations between TREC/KREC and other lymphocyte subpopulations and approach TREC/KREC use in PID diagnosis.
Project description:To investigate a non-invasive strategy for immune monitoring the peripheral blood by flow cytometry, to address the critical need to itdentify predictive immunological biomarkers that correlate with treatment response Peripheral blood mononuclear cells (PBMCs) from 19 non–small-cell lung cancer (NSCLC) patients before and after ICI treatment and four healthy human donors were evaluated, utilizing spectral flow to monitor 24 immune cell markers simultaneously over the course of treatment. We performed immune cell profiling analysis using data obtained from RNA-seq of 19 different patients before and after immunotherapy, to validate the multi-color flow based immune profiling
Project description:Flow Cytometry is an analytical technology to simultaneously measure multiple markers per single cell. Ten thousands to millions of single cells can be measured per sample and each sample may contain a different number of cells. All samples may be bundled together, leading to a 'multi-set' structure. Many multivariate methods have been developed for Flow Cytometry data but none of them considers this structure in their quantitative handling of the data. The standard pre-processing used by existing multivariate methods provides models mainly influenced by the samples with more cells, while such a model should provide a balanced view of the biomedical information within all measurements. We propose an alternative 'multi-set' preprocessing that corrects for the difference in number of cells measured, balancing the relative importance of each multi-cell sample in the data while using all data collected from these expensive analyses. Moreover, one case example shows how multi-set pre-processing may benefit removal of undesired measurement-to-measurement variability and another where class-based multi-set pre-processing enhances the studied response upon comparison to the control reference samples. Our results show that adjusting data analysis algorithms to consider this multi-set structure may greatly benefit immunological insight and classification performance of Flow Cytometry data.
Project description:As checkpoint inhibitor immunotherapies gain traction among cancer researchers and clinicians, the need grows for assays that can definitively phenotype patient immune cells. Herein, we present an 8-color flow cytometry panel for lineage and immune checkpoint markers and validate it using healthy human donor peripheral blood mononuclear cells (PBMCs). Flow cytometry data was generated on a BD LSR Fortessa and supported by Luminex multiplex soluble immunoassay. Our data showed significant variation between donors at both baseline and different stages of activation, as well as a trend in increasing expression of checkpoint markers on stimulated CD4+ and CD8+ T-cells with time. Soluble immune checkpoint quantification assays revealed that LAG-3, TIM-3, CTLA-4, and PD-1 soluble isoforms are upregulated after stimulation. This 8-color flow cytometry panel, supported here by soluble immunoassay, can be used to identify and evaluate immune checkpoints on T-lymphocytes in cryopreserved human PBMC samples. This panel is ideal for characterizing checkpoint expression in clinical samples for which cryopreservation is necessary.
Project description:Immunophenotyping of vesicles, such as extracellular vesicles (EVs), is essential to understanding their origin and biological role. We previously described a custom-built flow analyzer that utilizes a gravity-driven flow, high numerical aperture objective, and micrometer-sized flow channels to reach the sensitivity needed for fast multidimensional analysis of the surface proteins of EVs, even down to the smallest EVs (e.g., ∼30-40 nm). It is difficult to flow focus small EVs, and thus, the transiting EVs exhibit a distribution in particle velocities due to the laminar flow. This distribution of vesicle velocities leads to potentially incorrect results when immunophenotyping nanometer-sized vesicles using cross-correlation analysis (Xcorr), as the order of appearance of the vesicles might not be the same at different spatially offset laser excitation regions. Here, we describe an alternative cross-correlation analysis strategy (Scorr), which uses information on particle transit time across the laser excitation beam width to improve multicolor colocalization in single-vesicle immunoprofiling. We tested the performance of the algorithm for colocalization analysis of multicolor nanobeads and EVs experimentally and via simulations and found that Scorr improved both the efficiency and accuracy of colocalization versus Xcorr. As shown from Monte Carlo simulations, Scorr provided an ∼1.2-4.7-fold increase in the number of colocalized peaks and ensured negligible colocalization of peaks. In silico results were in good agreement with experimental data, which showed an increase in colocalized peaks of ∼1.3-2.5-fold and ∼1.2-2-fold for multicolor beads and EVs, respectively.
Project description:Plasma cells are rare cells that have been notoriously difficult to detect by flow cytometry. New advances have described B220+ CD138+ plasma cells in the bone marrow that are particularly difficult to distinguish between CD138 intermediate B220+ developing B cells. Herein we describe a novel method for detecting plasma cells in the bone marrow using a combination of CD138 and Sca-1 staining.
Project description:Introduction:Current processing of renal biopsy samples provides limited information about immune mechanisms causing kidney injury and disease activity. We used flow cytometry with transplanted kidney biopsy samples to provide more information on the immune status of the kidney. Methods:To enhance the information available from a biopsy, we developed a technique for reducing a fraction of a renal biopsy sample to single cells for multicolor flow cytometry and quantitation of secreted cytokines present within the biopsy sample. As proof of concept, we used our technique with transplant kidney biopsy samples to provide examples of clinically relevant immune information obtainable with cytometry. Results:A ratio of CD8+ to CD4+ lymphocytes greater than or equal to 1.2 in transplanted allografts is associated with rejection, even before it is apparent by microscopy. Elevated numbers of CD45 leukocytes and higher levels of interleukin (IL)-6, IL-8, and IL-10 indicate more severe injury. Antibody binding to renal microvascular endothelial cells can be measured and corresponds to antibody-mediated forms of allograft rejection. Eculizumab binding to endothelial cells suggests complement activation, which may be independent of bound antibody. We compared intrarenal leukocyte subsets and activation states to those of peripheral blood from the same donor at the time of biopsy and found significant differences; thus the need for new techniques to evaluate immune responses within the kidney. Conclusion:Assessment of leukocyte subsets, renal microvascular endothelial properties, and measurement of cytokines within a renal biopsy by flow cytometry enhance understanding of pathogenesis, indicate disease activity, and identify potential targets for therapy.
Project description:Combining the strength of flow cytometry with fluorescence imaging and digital image analysis, imaging flow cytometry is a powerful tool in diverse fields including cancer biology, immunology, drug discovery, microbiology, and metabolic engineering. It enables measurements and statistical analyses of chemical, structural, and morphological phenotypes of numerous living cells to provide systematic insights into biological processes. However, its utility is constrained by its requirement of fluorescent labeling for phenotyping. Here we present label-free chemical imaging flow cytometry to overcome the issue. It builds on a pulse pair-resolved wavelength-switchable Stokes laser for the fastest-to-date multicolor stimulated Raman scattering (SRS) microscopy of fast-flowing cells on a 3D acoustic focusing microfluidic chip, enabling an unprecedented throughput of up to ∼140 cells/s. To show its broad utility, we use the SRS imaging flow cytometry with the aid of deep learning to study the metabolic heterogeneity of microalgal cells and perform marker-free cancer detection in blood.
Project description:Extracellular Vesicles (EVs), membrane vesicles released by all cells, are emerging mediators of cell-cell communication. By carrying biomolecules from tissues to biofluids, EVs have attracted attention as non-invasive sources of clinical biomarkers in liquid biopsies. EVs-based liquid biopsies usually require EVs isolation before content analysis, which frequently increases sample volume requirements. We here present a Flow Cytometry (FC) strategy that does not require isolation or concentration of EVs prior to staining. By doing so, it enables population analysis of EVs in samples characterized by challenging small volumes, while reducing overall sample processing time. To illustrate its application, we performed longitudinal non-lethal population analysis of EVs in mouse plasma and in single-animal collections of murine vitreous humor. By quantifying the proportion of vesicular particles in purified and non-purified biological samples, this method also serves as a precious tool to quality control isolates of EVs purified by different protocols. Our FC strategy has an unexplored clinical potential to analyze EVs in biofluids with intrinsically limited volumes and to multiply the number of different analytes in EVs that can be studied from a single collection of biofluid.