Interdisciplinary Computing and Complex BioSystems (ICOS) Research Group, School of Computing, Newcastle University, Newcastle Upon Tyne, UK.
Published: October 2022
AI Article Synopsis
Article Abstract
Genetic circuits are subject to variability due to cellular and compositional contexts. Cells face changing internal states and environments, the cellular context, to which they sense and respond by changing their gene expression and growth rates. Furthermore, each gene in a genetic circuit operates in a compositional context of genes which may interact with each other and the host cell in complex ways. The context of genetic circuits can, therefore, change gene expression and growth rates, and measuring their dynamics is essential to understanding natural and synthetic regulatory networks that give rise to functional phenotypes. However, reconstruction of microbial gene expression and growth rate profiles from typical noisy measurements of cell populations is difficult due to the effects of noise at low cell densities among other factors. We present here a method for the estimation of dynamic microbial gene expression rates and growth rates from noisy measurement data. Compared to the current state-of-the-art, our method significantly reduced the mean squared error of reconstructions from simulated data of growth and gene expression rates, improving the estimation of timing and magnitude of relevant shapes of profiles. We applied our method to characterize a triple-reporter plasmid library combining multiple transcription units in different compositional and cellular contexts in . Our analysis reveals cellular and compositional context effects on microbial growth and gene expression rate dynamics and suggests a method for the dynamic ratiometric characterization of constitutive promoters relative to an reference.
Background: Previous research has demonstrated correlations between the complex types and functions of brain cells and the etiology of glioma. However, the causal relationship between gene expression regulation in specific brain cell types and glioma risk, along with its therapeutic implications, remains underexplored.
Methods: Utilizing brain cell type-specific cis-expression quantitative trait loci (cis-eQTLs) and glioma genome-wide association study (GWAS) datasets in conjunction with Mendelian randomization (MR) and colocalization analyses, we conducted a systematic investigation to determine whether an association exists between the gene expression of specific brain cell types and the susceptibility to glioma, including its subtypes.
Non-small cell lung cancer (NSCLC) is the most pervasive sort of lung cancer with deadly outcome. According to recent studies, a number of neoplastic disorders and ferroptosis are intimately connected. This study aims to identify the role of key ferroptosis-related gene (protein kinase AMP-activated catalytic subunit alpha 2, PRKAA2) and explore new directions for the diagnosis and treatment of NSCLC.
Background: Tumor recurrence or metastasis after surgery is a significant factor influencing bladder cancer (BC) prognosis. Novel molecular biomarkers are necessary to determine each patient's specific outcome because current biomarkers have limited power for predicting prognosis. The proto-oncogene MET encodes c-MET, a tyrosine kinase receptor.
Introduction: Low back pain (LBP) is a significant global health burden, with variable treatment outcomes and an unclear underlying molecular mechanism. Effective prediction of treatment responses remains a challenge. In this study, we aimed to develop gene signature-based machine learning models using transcriptomic data from peripheral immune cells to predict treatment outcomes in patients with LBP.
Department of Hematology, The Affiliated Hospital of Qingdao University, Qingdao University, No. 16 Jiangsu Road, Qingdao, 266000, Shandong Province, China.
A poorer prognosis is thought to be associated with "double expressor lymphomas," which are a subtype of diffuse large B cell lymphomas (DLBCL) that co-express MYC and BCL2. While the role of ubiquitin-specific peptidase 37 (USP37) in lung cancer, where it mediates the deubiquitination and stabilization of c-myc, has been well-documented, its involvement in DLBCL remains unexplored. The use of RT-PCR, immunohistochemistry, or WB test allowed for the detection of elevated USP37 in DLBCL tissues and cells.
