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Motivation Identifying rare subpopulations of cells is a critical step in order to extract knowledge from single-cell expression data, especially when the available data is limited and rare subpopulations only contain a few cells. In this paper, we present a data mining method to identify small subpopulations of cells that present highly specific expression profiles. This objective is formalized as a constrained optimization problem that jointly identifies a small group of cells and a corresponding subset of specific genes. The proposed method extends the max-sum submatrix problem to yield genes that are, for instance, highly expressed inside a small number of cells, but have a low expression in the remaining ones. Results We show through controlled experiments on scRNA-seq data that the MicroCellClust method achieves a high F 1 score to identify rare subpopulations of artificially planted human T cells. The effectiveness of MicroCellClust is confirmed as it reveals a subpopulation of CD4 T cells with a specific phenotype from breast cancer samples, and a subpopulation linked to a specific stage in the cell cycle from breast cancer samples as well. Finally, three rare subpopulations in mouse embryonic stem cells are also identified with MicroCellClust. These results illustrate the proposed method outperforms typical alternatives at identifying small subsets of cells with highly specific expression profiles. Availabilityand implementation The R and Scala implementation of MicroCellClust is freely available on GitHub, at https://github.com/agerniers/MicroCellClust/ The data underlying this article are available on Zenodo, at https://dx.doi.org/10.5281/zenodo.4580332. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Abstract: The thymus provides a unique cellular and hormonic microenvironment for the development of immunocompetent T cells. Thymic polypeptides have been widely used clinically for the treatment of tumors, infectious diseases and immune deficiency diseases. They have already shown the ability to stimulate the maturation of hematopoietic stem cells towards the CD3+CD4+ T cell lineage. However, their effects on the thymopoiesis of embryonic stem cells are still unexplored. In this paper, we compared the effects of three thymic polypeptides, thymopentin (TP5), thymosin alpha-1 (Tα-1) and thymopeptides on the in vitro thymopoiesis of mouse embryonic stem (ES) cells. Using the embryoid body induction system, we found that both Tα-1 and thymopeptides effectively induced ES cells to differentiate sequentially into the CD3+ and CD4+/CD8+ T cells. These T cells had T cell receptor (TCR) Vβ gene rearrangement and most were TCRαβ T cells. We also found that the expression of the Notch receptor and its ligands Delta-like-1 and Delta-like-4 gradually increased during the induction. However, TP5 failed to induce the T cell differentiation of the ES cells. In summary, this is the first report to demonstrate that Tα-1 can stimulate the T cell early stage differentiation from ES cells using the embryoid body protocol. These findings provide a powerful model for studying T cell development and may open new venues for the clinical application of Tα-1. [Copyright &y& Elsevier]

The article presents data related to biotechnology research papers in the U.S. The US remains the most productive country in terms of biotech-related papers. But numbers of papers from the European Union surpassed the US last year (with Germany and the UK ahead of most EU countries); elsewhere, Korea, China and Japan also publish frequently. Some of the top cited papers, published in different journals, by field are: RNAi--Systematic functional analysis of the Caenorhabditis elegans genome using RNAi; Gene therapy--LMO2-associated clonal T cell proliferation in two patients after gene therapy for SCID-X2 and Nuclear transfer--Derivation of oocytes from mouse embryonic stem cells.