417 research outputs found

    Brief aan de Nederlandse imkerij

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    Modular Nucleic Acid Assembled p/MHC Microarrays for Multiplexed Sorting of Antigen-Specific T Cells

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    The human immune system consists of a large number of T cells capable of recognizing and responding to antigens derived from various sources. The development of peptide-major histocompatibility (p/MHC) tetrameric complexes has enabled the direct detection of these antigen-specific T cells. With the goal of increasing throughput and multiplexing of T cell detection, protein microarrays spotted with defined p/MHC complexes have been reported, but studies have been limited due to the inherent instability and reproducibility of arrays produced via conventional spotted methods. Herein, we report on a platform for the detection of antigen-specific T cells on glass substrates that offers significant advantages over existing surface-bound schemes. In this approach, called “Nucleic Acid Cell Sorting (NACS)”, single-stranded DNA oligomers conjugated site-specifically to p/MHC tetramers are employed to immobilize p/MHC tetramers via hybridization to a complementary-printed substrate. Fully assembled p/MHC arrays are used to detect and enumerate T cells captured from cellular suspensions, including primary human T cells collected from cancer patients. NACS arrays outperform conventional spotted arrays assessed in key criteria such as repeatability and homogeneity. The versatility of employing DNA sequences for cell sorting is exploited to enable the programmed, selective release of target populations of immobilized T cells with restriction endonucleases for downstream analysis. Because of the performance, facile and modular assembly of p/MHC tetramer arrays, NACS holds promise as a versatile platform for multiplexed T cell detection

    Automated Analysis of Flow Cytometry Data to Reduce Inter-Lab Variation in the Detection of Major Histocompatibility Complex Multimer-Binding T Cells

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    Manual analysis of flow cytometry data and subjective gate-border decisions taken by individuals continue to be a source of variation in the assessment of antigen-specific T cells when comparing data across laboratories, and also over time in individual labs. Therefore, strategies to provide automated analysis of major histocompatibility complex (MHC) multimer-binding T cells represent an attractive solution to decrease subjectivity and technical variation. The challenge of using an automated analysis approach is that MHC multimer-binding T cell populations are often rare and therefore difficult to detect. We used a highly heterogeneous dataset from a recent MHC multimer proficiency panel to assess if MHC multimer-binding CD8+ T cells could be analyzed with computational solutions currently available, and if such analyses would reduce the technical variation across different laboratories. We used three different methods, FLOw Clustering without K (FLOCK), Scalable Weighted Iterative Flow-clustering Technique (SWIFT), and ReFlow to analyze flow cytometry data files from 28 laboratories. Each laboratory screened for antigen-responsive T cell populations with frequency ranging from 0.01 to 1.5% of lymphocytes within samples from two donors. Experience from this analysis shows that all three programs can be used for the identification of high to intermediate frequency of MHC multimer-binding T cell populations, with results very similar to that of manual gating. For the less frequent populations (<0.1% of live, single lymphocytes), SWIFT outperformed the other tools. As used in this study, none of the algorithms offered a completely automated pipeline for identification of MHC multimer populations, as varying degrees of human interventions were needed to complete the analysis. In this study, we demonstrate the feasibility of using automated analysis pipelines for assessing and identifying even rare populations of antigen-responsive T cells and discuss the main properties, differences, and advantages of the different methods tested
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