Project description:In patient-derived xenograft (PDX) mouse, ANKL cells actively proliferate in liver, compared with spleen. We use single cell RNA sequencing (scRNA-seq) to analyze the diversity of ANKL cells in liver and spleen
Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to evaluate the effects of liver-specific E4BP4 overexpression under mouse albumin promoter on the liver glucose and lipid metabolism.
Project description:Thymus and spleen, in contrast to liver, are radiosensitive tissues in which p53-dependent apoptosis is triggered after whole body radiation in vivo. Combined RNA-seq and ChIP-seq analyses of radiation-treated mouse organs identifies both shared and tissue-specific p53 transcriptional responses. As expected, the p53 targets shared amongst thymus and spleen are enriched in apoptotic targets. Surprisingly, the inability to upregulate these genes in the liver is not due to reduced gene occupancy. Use of an engineered mouse model shows that deletion of the C-terminus of p53 can confer radiation-induced expression of p53 apoptotic targets in the liver with concomitant increased cell death. Global RNA-seq analysis reveals an additional role of the C-terminus being also needed for transcriptional activation of liver-specific p53 targets. It is hypothesized that both suppression of apoptotic gene expression combined with enhanced activation of liver-specific targets confers tissue-specific radio-resistance.
Project description:Small RNAs were deep sequenced from the liver and spleen of adult mice in an effort to identify somatic piRNAs. Following sequencing of all small RNAs, known non-coding RNAs were computationally removed from the dataset. The remaining RNAs were then mapped to the genome and analyzed for sequence characteristics (5' base, length) typical of known piRNAs. To determine if any of the identified small RNAs were MIWI2 dependent, we deep sequenced small RNAs from liver and spleen of MIWI2 KO mice and analyzed them as above. We deep sequenced small RNAs from the liver and spleen of one WT mouse and one MIWI2 knock-out mouse. We then trimmed sequencing adapters and removed known ncRNAs (rRNA, tRNA, snoRNA, snRNA, miRNA) from the dataset before aligning reads to the mm9 assembly of the mouse genome.
Project description:Iron Mouse PV3
"A computational model to understand mouse iron physiology and diseases"
By Jignesh Parmar and Pedro Mendes
Base model
This is a dynamic model of iron distribution in mice, covering seven compartments: plasma, bone marrow, red blood cells (RBC), spleen, duodenum, liver, and the rest of the body . This is mostly a physiological model with regulation by hepcidin and erythropoietin, including only a minimal amount of molecular details.
This version of the model does not include the radioactive-labelled tracer iron species that were used for parameter estimation (that is included in a separate file). This model has all parameter values already set to the best estimates obtained with the model with radioactive tracer. This model is useful to study the steady state properties of the system and as a basis for various types of simulation.
Model validation was carried out with other model files that were derived from this one and where certain parameters were altered or new interventions added.
Project description:We report the transcriptomic profiles of liver-tropic and spleen-tropic ANKL cells obtained from patient-derived xenograft (PDX) mouse. We also report the transcriptomic profiles of liver niche collected from healthy mice or PDX mice.
Project description:Background: Antigen-specific T cells are particularly important for eliminating bacterial infection, and the dynamics in this process help uncover the mechanisms by which bacteria are eliminated.Results: In this study, we sorted the antigen-specific CD8+ T cell in the mouse liver and spleen at 5, 7, and 14 days after infection of Listeria monocytogenes expressing the OVA protein, finding that antigen-specific CD8+ T cell expansion after infection peaked on Day 7. Through the RNAseq analysis, we identified 355 genes whose expression peaked on 7 days post-infection shared in both of spleen and liver. For these shared genes, the KEGG pathway analysis showed a notable enrichment in the metabolic pathway. We also discovered 1621 proteins shared in the mouse liver and spleen that peaked seven days after infection by the LC-MS/MS analysis. The KEGG pathway analysis for these proteins revealed a significant enrichment in Splicesome, RNA transport, Ubiquitin mediated proteolysis, and Huntington disease. Transcriptomics coupled proteomics reveals 45 genes/proteins that were elevated on day 7 post listeria infection both in the spleen and liver. These 45 molecules were enriched in Human T-cell leukemia virus 1 infection and T cell activation, which played an important role in the activation of T cells and the anti-infection process.Conclusion: Transcriptomics coupled proteomics reveals the key signaling pathways to regulate antigen-specific CD8+ T cells by infection of Listeria monocytogenes expressing the OVA protein in mouse spleen and liver.