Cytometry Part A最新文献

This 27-color flow cytometry antibody panel allows broad immune-profiling of major leukocyte subsets in human whole blood (WB). It includes lineage markers to identify myeloid and lymphoid cell populations including granulocytes, monocytes, myeloid dendritic cells (mDCs), natural killer (NK) cells, NKT-like cells, B cells, conventional CD4 and CD8 T cells, γδ T cells, mucosa-associated invariant T (MAIT) cells and innate lymphoid cells (ILC). To further characterize each of these populations, markers defining stages of cell differentiation (CCR7, CD27, CD45RA, CD127, CD57), cytotoxic potential (perforin, granzyme B) and cell activation/proliferation (HLA-DR, CD38, Ki-67) were included. This panel was developed for quantifying absolute counts and phenotyping major leukocyte populations in cryopreserved, fixed WB collected from participants enrolled in large multi-site tuberculosis (TB) vaccine clinical trials. This antibody panel can be applied to profile major leukocyte subsets in other sample types such as fresh WB or peripheral blood mononuclear cells (PBMCs) with only minor additional optimization.

Chimeric antigen receptor (CAR) T-cell therapy is a breakthrough in hematologic malignancies, such as acute B lymphoblastic leukemia (B-ALL). Monitoring this treatment is recommended, although standardized protocols have not been developed yet. This work compares two flow cytometry monitoring strategies and correlates this technique with qPCR method. CAR-T cells were detected by two different flow-cytometry protocols (A and B) in nine blood samples from one healthy donor and five B-ALL patients treated with Tisagenlecleucel (Kymriah®, USA). HIV-1 viral load allowed CAR detection by qPCR, using samples from seven healthy donors and nine B-ALL patients. CAR detection by protocol A and B did not yield statistically significant differences (1.9% vs. 11.8% CD3 + CAR+, p = 0.07). However, protocol B showed a better discrimination of the CD3 + CAR+ population. A strong correlation was observed between protocol B and qPCR (r = 0.7, p < 0.0001). CD3 + CAR+ cells were detected by flow cytometry only when HIV-1 viral load was above 10⁴ copies/mL. In conclusion, protocol B was the most specific flow-cytometry procedure for the identification of CAR-T cells and showed a high correlation with qPCR. Further efforts are needed to achieve a standardized monitoring approach.

The objective of titrating fluorochrome-labeled antibodies is to identify the optimal concentration for a given marker-fluorochrome pair that results in the best possible separation between the positive and negative cell populations, while minimizing the background within the negative population. Best practices in flow cytometry dictate that each new lot of antibody should be titrated on the sample of interest. However, many researchers routinely use large (30+) color panels due to recent technical advancements in fluorescence-based cytometry instrumentation which quickly leads to an unmanageable number of individual titrations. In this technical note, we provide evidence that antibodies can be effectively titrated in groups rather than individually, resulting in considerable time and cost savings. This approach streamlines the process, without compromising data quality, thereby enhancing the efficiency of setting up high-parameter cytometry experiments.

This 14-color, 13-antibody optimized multicolor immunofluorescence panel (OMIP) was designed for deep profiling of neutrophil subsets in various types of human samples to contextualize neutrophil plasticity in a range of healthy and diseased states. Markers present in the OMIP allow the profiling of neutrophil subsets associated with ontogeny, migration, phagocytosis capacity, granule release, and immune modulation. For panel design, we ensured that the commonly available fluorophores FITC/AF488, PE, and APC were assigned to the intracellular subset marker Olfactomedin 4, the maturity and activation marker CD10, and whole blood subset marker CD177, respectively. These markers can be easily replaced without affecting the core identification of neutrophils, enabling antibodies to new neutrophil antigens of interest or for fluorescent substrates to assess different neutrophil functions to be easily explored. Panel optimization was performed on whole blood and purified neutrophils. We demonstrate applications on clinical samples (whole blood and saliva) and experimental endpoints (purified neutrophils stimulated through an in vitro transmigration assay). We hope that providing a uniform platform to analyze neutrophil plasticity in various sample types will facilitate the future understanding of neutrophil subsets in health and disease.

Techniques currently used for the study of antigen-specific T-cell responses are either poorly informative or require a heavy workload. Consequently, many perspectives associated with the broader study of such approaches remain mostly unexplored in translational research. However, these could benefit many fields including but not limited to infectious diseases, oncology, and vaccination. Herein, the main objective of this work was to develop a standardized flow cytometry-based approach that would combine ease of use together with a relevant study of antigen-specific T-cell responses so that they could be more often included in clinical research. To this extent, a streamlined approach relying on 1/ the use of whole blood instead of peripheral blood mononuclear cells and 2/ solely based on the expression of extracellular activation-induced markers (AIMs), called whole blood AIM (WAIM), was developed and further compared to more conventional techniques such as enzyme-linked immunospot (ELISpot) and flow cytometry-based intracellular cytokine staining (ICS). Based on a cohort of 20 individuals receiving the COVID-19 mRNA vaccine and focusing on SARS-CoV-2 and cytomegalovirus (CMV)-derived antigen T-cell-specific responses, a significant level of correlation between the three techniques was found. Based on the use of whole blood and on the expression of extracellular activation-induced markers (CD154, CD137, and CD107a), the WAIM technique appears to be very simple to implement and yet allows interesting patient stratification capabilities as the chosen combination of extracellular markers exhibited higher orthogonality than cytokines that are commonly considered in ICS (IFN-γ, TNF-α, and IL-2).

High dimensional flow cytometry relies on multiple laser sources to excite the wide variety of fluorochromes now available for immunophenotyping. Ultraviolet lasers (usually solid state 355 nm) are a critical part of this as they excite the BD Horizon™ Brilliant Ultraviolet (BUV) series of polymer fluorochromes. The BUV dyes have increased the number of simultaneous fluorochromes available for practical high-dimensional analysis to greater than 40 for spectral cytometry. Immunologists are now seeking to increase this number, requiring both novel fluorochromes and additional laser wavelengths. A laser in the deep ultraviolet (DUV) range (from ca. 260 to 320 nm) has been proposed as an additional excitation source, driven by the on-going development of additional polymer dyes with DUV excitation. DUV lasers emitting at 280 and 320 nm have been previously validated for flow cytometry but have encountered practical difficulties both in probe excitation behavior and in availability. In this article, we validate an even shorter DUV 266 nm laser source for flow cytometry. This DUV laser provided minimal excitation of the BUV dyes (a desirable characteristic for high-dimensional analysis) while demonstrating excellent excitation of quantum nanoparticles (Qdots) serving as surrogate fluorochromes for as yet undeveloped DUV excited dyes. DUV 266 nm excitation may therefore be a viable candidate for expanding high-dimensional flow cytometry into the DUV range and providing an additional incidental excitation wavelength for spectral cytometry. Excitation in a spectral region with strong absorption by nucleic acids and proteins (260–280 nm) did result in strong autofluorescence requiring care in fluorochrome selection. DUV excitation of endogenous molecules may nevertheless have additional utility for label-free analysis applications.

The differential of leukocytes functions as the first indicator in clinical examinations. However, microscopic examinations suffered from key limitations of low throughputs in classifying leukocytes while commercially available hematology analyzers failed to provide quantitative accuracies in leukocyte differentials. A home-developed imaging and impedance flow cytometry of microfluidics was used to capture fluorescent images and impedance variations of single cells traveling through constrictional microchannels. Convolutional and recurrent neural networks were adopted for data processing and feature extractions, which were then fused by a support vector machine to realize the four-part differential of leukocytes. The classification accuracies of the four-part leukocyte differential were quantified as 95.4% based on fluorescent images plus the convolutional neural network, 90.3% based on impedance variations plus the recurrent neural network, and 99.3% on the basis of fluorescent images, impedance variations, and deep neural networks. Based on single-cell fluorescent imaging and impedance variations coupled with deep neural networks, the four-part leukocyte differential can be realized with almost 100% accuracy.

In biomedicine, the automatic processing of medical microscope images plays a key role in the subsequent analysis and diagnosis. Cell or nucleus segmentation is one of the most challenging tasks for microscope image processing. Due to the frequently occurred overlapping, few segmentation methods can achieve satisfactory segmentation accuracy yet. In this paper, we propose an approach to separate the overlapped cells or nuclei based on the outer Canny edges and morphological erosion. The threshold selection is first used to segment the foreground and background of cell or nucleus images. For each binary connected domain in the segmentation image, an intersection based edge selection method is proposed to choose the outer Canny edges of the overlapped cells or nuclei. The outer Canny edges are used to generate a binary cell or nucleus image that is then used to compute the cell or nucleus seeds by the proposed morphological erosion method. The nuclei of the Human U2OS cells, the mouse NIH3T3 cells and the synthetic cells are used for evaluating our proposed approach. The quantitative quantification accuracy is computed by the Dice score and 95.53% is achieved by the proposed approach. Both the quantitative and the qualitative comparisons show that the accuracy of the proposed approach is better than those of the area constrained morphological erosion (ACME) method, the iterative erosion (IE) method, the morphology and watershed (MW) method, the Generalized Laplacian of Gaussian filters (GLGF) method and ellipse fitting (EF) method in separating the cells or nuclei in three publicly available datasets.