Dominant suppressor genes of p53-induced apoptosis in Drosophila melanogaster.

One of a major function of programmed cell death (apoptosis) is the removal of cells which suffered oncogenic mutations, thereby preventing cancerous transformation. By making use of a Double-Headed-EP (DEP) transposon, a P element derivative made in our laboratory, we made an insertional mutagenesis screen in Drosophila melanogaster to identify genes which, when overexpressed, suppress the p53-activated apoptosis. The DEP element has Gal4-activatable, outward-directed UAS-promoters at both ends which can be deleted separately in vivo. In the DEP insertion mutants, we used the GMR-Gal4 driver to induce transcription from both UAS-promoters and tested the suppression effect on the apoptotic rough eye phenotype generated by an activated UAS-p53 transgene. By DEP insertions, seven genes were identified which suppressed the p53-induced apoptosis. In four mutants, the suppression effect resulted from single genes activated by one UAS-promoter (Pka-R2, Rga, crol, Spt5). In the other three (Orct2, Polr2M, stg), deleting either UAS-promoter eliminated the suppression effect. In qPCR experiments we found that the genes in the vicinity of the DEP insertion also showed an elevated expression level. This suggested an additive effect of the nearby genes on suppressing apoptosis. In the eucaryotic genomes there are co-expressed gene clusters. Three of the DEP insertion mutants are included and two are in close vicinity of separate co-expressed gene clusters. This raises the possibility that the activity of some of the genes in these clusters may help the suppression of the apoptotic cell death.

Comparative single-cell multiplex immunophenotyping of therapy-naive patients with rheumatoid arthritis, systemic sclerosis, and systemic lupus erythematosus shed light on disease-specific composition of the peripheral immune system.

Introduction: Systemic autoimmune diseases (SADs) are a significant burden on the healthcare system. Understanding the complexity of the peripheral immunophenotype in SADs may facilitate the differential diagnosis and identification of potential therapeutic targets. Methods: Single-cell mass cytometric immunophenotyping was performed on peripheral blood mononuclear cells (PBMCs) from healthy controls (HCs) and therapy-naive patients with rheumatoid arthritis (RA), progressive systemic sclerosis (SSc), and systemic lupus erythematosus (SLE). Immunophenotyping was performed on 15,387,165 CD45+ live single cells from 52 participants (13 cases/group), using an antibody panel to detect 34 markers. Results: Using the t-SNE (t-distributed stochastic neighbor embedding) algorithm, the following 17 main immune cell types were determined: CD4+/CD57- T cells, CD4+/CD57+ T cells, CD8+/CD161- T cells, CD8+/CD161+/CD28+ T cells, CD8dim T cells, CD3+/CD4-/CD8- T cells, TCRγ/δ T cells, CD4+ NKT cells, CD8+ NKT cells, classic NK cells, CD56dim/CD98dim cells, B cells, plasmablasts, monocytes, CD11cdim/CD172dim cells, myeloid dendritic cells (mDCs), and plasmacytoid dendritic cells (pDCs). Seven of the 17 main cell types exhibited statistically significant frequencies in the investigated groups. The expression levels of the 34 markers in the main populations were compared between HCs and SADs. In summary, 59 scatter plots showed significant differences in the expression intensities between at least two groups. Next, each immune cell population was divided into subpopulations (metaclusters) using the FlowSOM (self-organizing map) algorithm. Finally, 121 metaclusters (MCs) of the 10 main immune cell populations were found to have significant differences to classify diseases. The single-cell T-cell heterogeneity represented 64MCs based on the expression of 34 markers, and the frequency of 23 MCs differed significantly between at least twoconditions. The CD3- non-T-cell compartment contained 57 MCs with 17 MCs differentiating at least two investigated groups. In summary, we are the first to demonstrate the complexity of the immunophenotype of 34 markers over 15 million single cells in HCs vs. therapy-naive patients with RA, SSc, and SLE. Disease specific population frequencies or expression patterns of peripheral immune cells provide a single-cell data resource to the scientific community.

Lectin-Based Immunophenotyping and Whole Proteomic Profiling of CT-26 Colon Carcinoma Murine Model.

A murine colorectal carcinoma (CRC) model was established. CT26 colon carcinoma cells were injected into BALB/c mice's spleen to study the primary tumor and the mechanisms of cell spread of colon cancer to the liver. The CRC was verified by the immunohistochemistry of Pan Cytokeratin and Vimentin expression. Immunophenotyping of leukocytes isolated from CRC-bearing BALB/c mice or healthy controls, such as CD19+ B cells, CD11+ myeloid cells, and CD3+ T cells, was carried out using fluorochrome-labeled lectins. The binding of six lectins to white blood cells, such as galectin-1 (Gal1), siglec-1 (Sig1), Sambucus nigra lectin (SNA), Aleuria aurantia lectin (AAL), Phytolacca americana lectin (PWM), and galectin-3 (Gal3), was assayed. Flow cytometric analysis of the splenocytes revealed the increased binding of SNA, and AAL to CD3 + T cells and CD11b myeloid cells; and increased siglec-1 and AAL binding to CD19 B cells of the tumor-bearing mice. The whole proteomic analysis of the established CRC-bearing liver and spleen versus healthy tissues identified differentially expressed proteins, characteristic of the primary or secondary CRC tissues. KEGG Gene Ontology bioinformatic analysis delineated the established murine CRC characteristic protein interaction networks, biological pathways, and cellular processes involved in CRC. Galectin-1 and S100A4 were identified as upregulated proteins in the primary and secondary CT26 tumor tissues, and these were previously reported to contribute to the poor prognosis of CRC patients. Modelling the development of liver colonization of CRC by the injection of CT26 cells into the spleen may facilitate the understanding of carcinogenesis in human CRC and contribute to the development of novel therapeutic strategies.

Pre-Pulse Inhibition of an escape response in adult fruit fly, Drosophila melanogaster.

Pre-Pulse Inhibition (PPI) is a neural process where suppression of a startle response is elicited by preceding the startling stimulus (Pulse) with a weak, non-startling one (Pre-Pulse). Defective PPI is widely employed as a behavioural endophenotype in humans and mammalian disorder-relevant models for neuropsychiatric disorders. We have developed a user-friendly, semi-automated, high-throughput-compatible Drosophila light-off jump response PPI paradigm, with which we demonstrate that PPI, with similar parameters measured in mammals, exists in adults of this model organism. We report that Drosophila PPI is affected by reduced expression of Dysbindin and both reduced and increased expression of Nmdar1 (N-methyl-D-aspartate receptor 1), perturbations associated with schizophrenia. Studying the biology of PPI in an organism that offers a plethora of genetic tools and a complex and well characterized connectome will greatly facilitate our efforts to gain deeper insight into the aetiology of human mental disorders, while reducing the need for mammalian models.

Single-cell immunophenotyping revealed the association of CD4+ central and CD4+ effector memory T cells linking exacerbating chronic obstructive pulmonary disease and NSCLC.

Introduction: Tobacco smoking generates airway inflammation in chronic obstructive pulmonary disease (COPD), and its involvement in the development of lung cancer is still among the leading causes of early death. Therefore, we aimed to have a better understanding of the disbalance in immunoregulation in chronic inflammatory conditions in smoker subjects with stable COPD (stCOPD), exacerbating COPD (exCOPD), or non-small cell lung cancer (NSCLC). Methods: Smoker controls without chronic illness were recruited as controls. Through extensive mapping of single cells, surface receptor quantification was achieved by single-cell mass cytometry (CyTOF) with 29 antibodies. The CyTOF characterized 14 main immune subsets such as CD4+, CD8+, CD4+/CD8+, CD4-/CD8-, and γ/δ T cells and other subsets such as CD4+ or CD8+ NKT cells, NK cells, B cells, plasmablasts, monocytes, CD11cdim, mDCs, and pDCs. The CD4+ central memory (CM) T cells (CD4+/CD45RA-/CD45RO+/CD197+) and CD4+ effector memory (EM) T cells (CD4+/CD45RA-/CD45RO+/CD197-) were FACS-sorted for RNA-Seq analysis. Plasma samples were assayed by Luminex MAGPIX® for the quantitative measurement of 17 soluble immuno-oncology mediators (BTLA, CD28, CD80, CD27, CD40, CD86, CTLA-4, GITR, GITRL, HVEM, ICOS, LAG-3, PD-1, PD-L1, PD-L2, TIM-3, TLR-2) in the four studied groups. Results: Our focus was on T-cell-dependent differences in COPD and NSCLC, where peripheral CD4+ central memory and CD4+ effector memory cells showed a significant reduction in exCOPD and CD4+ CM showed elevation in NSCLC. The transcriptome analysis delineated a perfect correlation of differentially expressed genes between exacerbating COPD and NSCLC-derived peripheral CD4+ CM or CD4+ EM cells. The measurement of 17 immuno-oncology soluble mediators revealed a disease-associated phenotype in the peripheral blood of stCOPD, exCOPD, and NSCLC patients. Discussion: The applied single-cell mass cytometry, the whole transcriptome profiling of peripheral CD4+ memory cells, and the quantification of 17 plasma mediators provided complex data that may contribute to the understanding of the disbalance in immune homeostasis generated or sustained by tobacco smoking in COPD and NSCLC.