Project description:This study aims to identify combination treatments capable of inducing improved IO responses in lung tumours and thus, help guide decisions on the next combination arms for the HUDSON trial (post-IO). For that purpose, a lung tumour GEMM model was treated with either vehicle, PD-L1, ATR, ATR/PD-L1; Cisplatin/PD-L1/Ctla4 or VEGFR/PD-L1 and tumours collected for transcriptional profiling.
Project description:Characterization of RNA processing events dependent on U2AF-related proteins PUF60 and RBM39. PUF60 (poly-U-binding factor 60 kDa, also known as FIR, Hfp or Ro-bp1) is a splicing factor homologous to the 65 kD subunit of the auxiliary factor of U2 small nuclear ribonucleoprotein (U2AF65). PUF60 has two central RNA recognition motifs and a C-terminal U2AF homology motif (UHM), but lacks the N terminal arginine/serine-rich (RS) and UHM ligand motif (ULM) domains present in U2AF65. PUF60 activity, in conjunction with U2AF, facilitates the association of U2 snRNP with the pre-mRNA. PUF60 and U2AF65 can bind SF3b155 ULMs simultaneously and noncompetitively. RBM39 (also known as CAPERα, HCC1, FSAP59 or RNPC2) is an RNA processing factor and a hormone-dependent transcriptional coactivator. RBM39 domain structure is similar to PUF60, except for the extra N-terminal RS domain with unknown function. To understand function of the two proteins on a genome-wide scale, each protein was individually depleted from human embryonic kidney cell line 293 using RNAi to systematically characterize the PUF60- and RBM39-dependent exon usage.
Project description:RNA-seq analysis was performed to understand the role of type I IFN response during SARS CoV-2 infection using transgenic mice. Each sample was collected from an individual C57BL/6J mouse. The total RNA was extracted from uninfected and SARS-CoV-2 infected mice lung tissue using RNeasy mini kit (QIAGEN #74104). The quantity of RNA was determined using Qubit RNA assay kit with Qubit 4.0 and the quality of RNA was tested using agarose gel electrophoresis and High Sensitivity Tape station Kit (Agilent 2200, #5067-5576, #5067-5577 and #5067-5578). After assessing the quality of RNA, ~900 ng of total RNA was taken for library preparation using NEBNext®Ultra™ II Directional RNA Library kit for Illumina (# E7760L) and NEBNext Poly (A) mRNA Magnetic Isolation Module (# E7490L) as per manufacturer's protocol. The prepared library was quantified using Qubit dsDNA assay kit (Invitrogen, Q32851) followed by quality check (QC) and fragment size distribution using a High Sensitivity Tape station Kit (Agilent 2200, #5067-5584 and #5067-5585). The library was sequenced using the HiSeq 4000 Illumina platform. The paired-end (PE) reads quality checks for each sample were carried out using FastQC v.0.11.5 (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). The adapter sequence was trimmed using the BBDuk version 37.58 version 37.58 and the alignment was performed using STAR v.2.5.3a with default parameters with human hg38 genome build, gencode v21 gtf 9GRCh38) from the gencode. The duplicates were discarded using Picard-2.9.4 (https://broadinstitute.github.io/picard/) from the aligned bam files and read counts were generated using featureCount v.1.5.3 from subread-1.5.3 package (https://bioinf.wehi.edu.au/) with Q = 10 for mapping quality. The count files were used as input for downstream differential gene expression analysis with DESeq2 version 1.14.1 9. The genes with read counts of ≤ 10 in any comparison were discarded followed by count transformation and statistical analysis using DESeq “R”. The “P” value were adjusted using the Benjamini and Hochberg multiple testing correction and the differentially expressed genes were identified (fold change of ≥1.5, P-value < 0.05). A unified non-redundant gene list was made for different comparisons and subjected to gene ontology (GO) analysis using the reactome database (https://reactome.org/). The top pathways (p < 0.05) were used for generating heat maps using Complexheatmap (Version 2.0.0) through unsupervised hierarchical clustering. The expression clusters were annotated based on enriched GO terms. Normalized gene expression was used to generate the boxplots with a median depicting the trends in the expression across the different conditions using ggplot2 [version 3.3.5]. The pathways analysis was performed using Metascape database (https://metascape.org/gp/index.html#/main/step1). The top pathways (p < 0.05) were taken for constructing bubble plots using ggplot2 [version 3.3.5].
Project description:Understanding MoA of ceralasertib (AZD6738) in driving efficacy through immune regulation via T-cells and tumour intrinsic pathways (STING/IFN) for AZD6738 driven efficacy.
Project description:We generated human induced pluripotent cells from intellectual disability patients carrying the c.2T>C mutation in KDM5C (Called “Mutant”). We generated a paired, isogenic human iPS cell line (called “Corrected”) using CRISPR/Cas9 and PiggyBac gene-editing technologies and conducted neuronal differentiation based on “Yichen Shi et al. Nat. Protoc. 7, 1836–1846 (2012)” to define differences in gene expression between the Mutant and Corrected during neurodevelopment.
Project description:CRISPR-Cas9 delivery by AAV holds promise for gene therapy but faces critical barriers due to its potential immunogenicity and limited payload capacity. Here, we demonstrate genome engineering in postnatal mice using AAV-split-Cas9, a multi-functional platform customizable for genome-editing, transcriptional regulation, and other previously impracticable AAV-CRISPR-Cas9 applications. We identify crucial parameters that impact efficacy and clinical translation of our platform, including viral biodistribution, editing efficiencies in various organs, antigenicity, immunological reactions, and physiological outcomes. These results reveal that AAV-CRISPR-Cas9 evokes host responses with distinct cellular and molecular signatures, but unlike alternative delivery methods, does not induce detectable cellular damage in vivo. Our study provides a foundation for developing effective genome therapeutics mRNA-Seq from muscles (9 samples; 3 mice x 3 conditions) and lymph nodes (9 samples; 3 mice x 3 conditions).
Project description:Investigate whole genome gene expression level changes in an S. flexneri ntrBC and nac mutants compared to wild type strain. NtrBC is a two component regulatory system, nac is a transcriptional activator Mutations in ntrBC and nac result in small plaque formation in Henle cell monolayers compared to wild type bacteria. Gene expression studies were pursued to identify the genes regulated by these transcriptional regulators.
Project description:Investigation of whole genome gene expression to identify overlooked sRNAs and sORFs. Background The completion of numerous genome sequences has introduced an era of whole-genome study. However, many real genes, including small RNAs (sRNAs) and small ORFs (sORFs), are missed in genome annotation. In order to improve genome annotation, we sought to identify novel sRNAs and sORFs in Shigella, the principal etiologic agents of bacillary dysentery or shigellosis. Results Firstly, we identified 64 sRNAs in Shigella which is experimentally validated in other bacteria based on sequence conservation. Secondly, among possible approaches to search for sRNAs, we employed computer-based and tiling array based methods, followed by RT-PCR and northern blots. This allowed us to identify 12 sRNAs in Shigella flexneri strain 301. We also find 29 candidate sORFs. Conclusions This investigation provides an updated and comprehensive annotation of the Shigella genome, increases the expected numbers of sORFs and sRNAs with the corresponding impact on future functional genomics and proteomics studies. Our method can be used for the large scale reannotation of sRNAs and sORFs in any microbe whose genome sequence is available.