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PRI: Re-analysis of a public mass cytometry dataset reveals patterns of effective tumor treatments
(2022)
Recently, mass cytometry has enabled quantification of up to 50 parameters for millions of cells per sample. It remains a challenge to analyze such high-dimensional data to exploit the richness of the inherent information, even though many valuable new analysis tools have already been developed. We propose a novel algorithm "pattern recognition of immune cells (PRI)" to tackle these high-dimensional protein combinations in the data. PRI is a tool for the analysis and visualization of cytometry data based on a three or more-parametric binning approach, feature engineering of bin properties of multivariate cell data, and a pseudo-multiparametric visualization. Using a publicly available mass cytometry dataset, we proved that reproducible feature engineering and intuitive understanding of the generated bin plots are helpful hallmarks for re-analysis with PRI. In the CD4(+)T cell population analyzed, PRI revealed two bin-plot patterns (CD90/CD44/CD86 and CD90/CD44/CD27) and 20 bin plot features for threshold-independent classification of mice concerning ineffective and effective tumor treatment. In addition, PRI mapped cell subsets regarding co-expression of the proliferation marker Ki67 with two major transcription factors and further delineated a specific Th1 cell subset. All these results demonstrate the added insights that can be obtained using the non-cluster-based tool PRI for re-analyses of high-dimensional cytometric data.
Endothelial cells (ECs) are involved in a variety of cellular responses. As multifunctional components of vascular structures, endothelial (progenitor) cells have been utilized in cellular therapies and are required as an important cellular component of engineered tissue constructs and in vitro disease models. Although primary ECs from different sources are readily isolated and expanded, cell quantity and quality in terms of functionality and karyotype stability is limited. ECs derived from human induced pluripotent stem cells (hiPSCs) represent an alternative and potentially superior cell source, but traditional culture approaches and 2D differentiation protocols hardly allow for production of large cell numbers. Aiming at the production of ECs, we have developed a robust approach for efficient endothelial differentiation of hiPSCs in scalable suspension culture. The established protocol results in relevant numbers of ECs for regenerative approaches and industrial applications that show in vitro proliferation capacity and a high degree of chromosomal stability.
Endothelial cells (ECs) are involved in a variety of cellular responses. As multifunctional components of vascular structures, endothelial (progenitor) cells have been utilized in cellular therapies and are required as an important cellular component of engineered tissue constructs and in vitro disease models. Although primary ECs from different sources are readily isolated and expanded, cell quantity and quality in terms of functionality and karyotype stability is limited. ECs derived from human induced pluripotent stem cells (hiPSCs) represent an alternative and potentially superior cell source, but traditional culture approaches and 2D differentiation protocols hardly allow for production of large cell numbers. Aiming at the production of ECs, we have developed a robust approach for efficient endothelial differentiation of hiPSCs in scalable suspension culture. The established protocol results in relevant numbers of ECs for regenerative approaches and industrial applications that show in vitro proliferation capacity and a high degree of chromosomal stability.
Cells and organelles are not homogeneous but include microcompartments that alter the spatiotemporal characteristics of cellular processes. The effects of microcompartmentation on metabolic pathways are however difficult to study experimentally. The pyrenoid is a microcompartment that is essential for a carbon concentrating mechanism (CCM) that improves the photosynthetic performance of eukaryotic algae. Using Chlamydomonas reinhardtii, we obtained experimental data on photosynthesis, metabolites, and proteins in CCM-induced and CCM-suppressed cells. We then employed a computational strategy to estimate how fluxes through the Calvin-Benson cycle are compartmented between the pyrenoid and the stroma. Our model predicts that ribulose-1,5-bisphosphate (RuBP), the substrate of Rubisco, and 3-phosphoglycerate (3PGA), its product, diffuse in and out of the pyrenoid, respectively, with higher fluxes in CCM-induced cells. It also indicates that there is no major diffusional barrier to metabolic flux between the pyrenoid and stroma. Our computational approach represents a stepping stone to understanding microcompartmentalized CCM in other organisms.
Nitrogen (N) is an essential macronutrient for optimal plant growth and ultimately for crop productivity Nitrate serves as the main N source for most plants. Although it seems a well-established fact that nitrate concentration affects flowering, its molecular mode of action in flowering time regulation was poorly understood. We recently found how nitrate, present at the shoot apical meristem (SAM), controls flowering time In this short communication, we present data on the tissue-specific expression patterns of NITRATE REDUCTASE 1 (NIA1) and NIA2 in planta. We show that transcripts of both genes are present throughout the life cycle of Arabidopsis thaliana plants with NIA1 being predominantly active in leaves and NIA2 in meristematic tissues.