Project description:The Thioacetamide-treated rat was first identified as a model of hepatotoxicity by Gupta in 1956 and is now well-established, not least because the histopathogical output closely mimics that seen in humans with chronic liver disease. Acute treatment of rats with Thioacetamide causes pronounced necrosis and inflammation. Animals received intraperitoneal (ip) doses of vehicle-only (0.9% (v/v) saline) (n=3), or 100 mg/kg Thioacetamide (n=3) and were sacrificed after 24 hours. Blood was withdrawn via the descending vena cava and immediately transferred into potassium/EDTA tubes. Following centrifugation (16,100g, 4M-BM-0C, 5 min) the plasma was collected and stored at -80M-BM-0C. miRNA microarray profiling of RNA extracted from the plasma of rats treated with Thioacetamide revealed that a subset of miRNAs were differentially expressed following treatment. These miRNAs appeared to mediate pathways involved in hepatic fibrosis and stellate cell activation, suggesting that they might function as predictive biomarkers following compound-induced hepatotoxicity. The changes correlated well with increases in ALT levels, which are the current gold standard method for determining the extent of liver injury. Furthermore, it is hypothesised that particular aetiologies of liver damage might cause differing expression profiles of miRNAs, thus certain miRNAs could be implemented in a panel-type expression study to distinguish between different types of hepatic injury. Single channel miRNA microarrays were performed on n= 3 samples, 2 treatment groups; control and test. Control animals received vehicle-only (0.9% (v/v) saline) via the ip route. Test animals received 100 mg/kg Thioacetamide dissolved in 0.9% (v/v) saline, via the ip route. 24 h after dosing animals were sacrificed using decapitation under terminal anaesthesia.
Project description:The Thioacetamide-treated rat was first identified as a model of hepatotoxicity by Gupta in 1956 and is now well-established, not least because the histopathogical output closely mimics that seen in humans with chronic liver disease. Acute treatment of rats with Thioacetamide causes pronounced necrosis and inflammation. Animals received intraperitoneal (ip) doses of vehicle-only (0.9% (v/v) saline) (n=3), or 100 mg/kg Thioacetamide (n=3) and were sacrificed after 24 hours. Blood was withdrawn via the descending vena cava and immediately transferred into potassium/EDTA tubes. Following centrifugation (16,100g, 4°C, 5 min) the plasma was collected and stored at -80°C. miRNA microarray profiling of RNA extracted from the plasma of rats treated with Thioacetamide revealed that a subset of miRNAs were differentially expressed following treatment. These miRNAs appeared to mediate pathways involved in hepatic fibrosis and stellate cell activation, suggesting that they might function as predictive biomarkers following compound-induced hepatotoxicity. The changes correlated well with increases in ALT levels, which are the current gold standard method for determining the extent of liver injury. Furthermore, it is hypothesised that particular aetiologies of liver damage might cause differing expression profiles of miRNAs, thus certain miRNAs could be implemented in a panel-type expression study to distinguish between different types of hepatic injury.
Project description:The effect of vitamin D supplementation on tumorigenesis in a thioacetamide (TAA)-induced rat intrahepatic cholangiocarcinoma model
Project description:Analysis of LBNF1 rat testes from controls, containing both somatic and all germ cell types and from irradiated rats in which all cells germ cells except type A spermatgogonia are eliminated. Results provide insight into distinguishing germ and somatic cell genes and identification of somatic cell genes that are upregulated after irradiation.
Project description:Living organisms are intricate systems with dynamic internal processes. Their RNA, protein, and metabolite levels fluctuate in response to variations in health and environmental conditions. Among these, RNA expression is particularly accessible for comprehensive analysis, thanks to the evolution of high throughput sequencing technologies in recent years. This progress has enabled researchers to identify unique RNA patterns associated with various diseases, as well as to develop predictive and prognostic biomarkers for therapy response. Such cross-sectional studies allow for the identification of differentially expressed genes (DEGs) between groups, but they have limitations. Specifically, they often fail to capture the temporal changes in gene expression following individual perturbations and may lead to significant false discoveries due to inherent noise in RNA sequencing sample preparation and data collection. To address these challenges, our study hypothesized that frequent, longitudinal RNA sequencing (RNAseq) analysis of blood samples could offer a more profound understanding of the temporal dynamics of gene expression in response to drug interventions, while also enhancing the accuracy of identifying genes influenced by these drugs. In this research, we conducted RNAseq on 829 blood samples collected from 84 Sprague-Dawley lab rats. Excluding the control group, each rat was administered one of four different compounds known for liver toxicity: tetracycline, isoniazid, valproate, and carbon tetrachloride. We developed specialized bioinformatics tools to pinpoint genes that exhibit temporal variation in response to these treatments.
Project description:Cervical cancer is a global public health subject as it affects women in the reproductive ages, and accounts for the second largest burden among cancer patients worldwide with an unforgiving 50% mortality rate. Poor awareness and access to effective diagnosis have led to this enormous disease burden, calling for point-of-care, minimally invasive diagnosis methods. Here, an end-to-end quantitative approach for a new kind of diagnosis has been developed, comprising identification of optimal biomarkers, design of the sensor, and simulation of the diagnostic circuit. Using miRNA expression data in the public domain, we identified circulating miRNA biomarkers specific to cervical cancer using multi-tier screening. Synthetic riboregulators called toehold switches specific for the biomarker panel were then designed. To predict the dynamic range of toehold switches for use in genetic circuits as biosensors, we developed a generic grammar of these switches, and built a multivariate linear regression model using thermodynamic features derived from RNA secondary structure and interaction. The model yielded predictions of toehold efficacy with an adjusted R2 = 0.59. Reaction kinetics modelling was performed to predict the sensitivity of the second-generation toehold switches to the miRNA biomarkers. Simulations showed a linear response between 10nM and 100nM before saturation. Our study demonstrates an end-to-end workflow for the efficient design of genetic circuits geared towards the effective detection of unique genomic signatures that would be increasingly important in today’s world. The approach has the potential to direct experimental efforts and minimise costs. All resources are provided open-source (https://github.com/igem2019) under GNU GPLv3 licence.