Biology subjects

Dasmeh, P.

Publications and source records attributed to Dasmeh, P..

5 recordsLinked to original sources

bioRxiv2018

RNASeq analysis identifies non-canonical role of STAT2 and IRF9 in the regulation of a STAT1-independent antiviral and immunoregulatory transcriptional program induced by IFNβ and TNFα

IFN{beta} typically induces an antiviral and immunoregulatory transcriptional program through the activation of ISGF3 (STAT1, STAT2 and IRF9) transcriptional complexes. The response to IFN{beta} is context-dependent and is prone to crosstalk with other cytokines, such as TNF IFN{beta} and TNF synergize to drive a specific delayed transcriptional program. Previous observation led to the hypothesis that an alternative STAT1-independent pathway involving STAT2 and IRF9 might be involved in gene induction by the combination of IFN{beta} and TNF. Using genome wide transcriptional profiling by RNASeq, we found that the costimulation with IFN{beta} and TNF induces a broad antiviral and immunoregulatory transcriptional program independently of STAT1. Additionally, STAT2 and IRF9 are involved in the regulation of only a subset of these STAT1-independent genes. Consistent with the growing literature, STAT2 and IRF9 act in concert to regulate a subgroup of these genes. Unexpectedly, STAT2 and IRF9 were also engaged in specific independent pathways to regulate distinct sets of IFN{beta} and TNF-induced genes. Altogether these observations highlight the existence of distinct previously unrecognized non-canonical STAT1-independent, but STAT2 and/or IRF9-dependent pathways in the establishment of a delayed antiviral and immunoregulatory transcriptional program in conditions where elevated levels of both IFN{beta} and TNF are present.

immunology↗

bioRxiv2017

Multi-step regulation of transcription kinetics explains the non-linear relation between RNA polymerase II density and mRNA expression in Dosage Compensation

In heterogametic organisms, expression of unequal number of X chromosomes in males and females is balanced by a process called dosage compensation. In Drosophila and mammals, dosage compensation involves nearly two-fold up-regulation of the X chromosome mediated by dosage compensation complex (DCC). Experimental studies on the role of DCC on RNA polymerase II (Pol II) transcription in mammals disclosed a non-linear relationship between Pol II densities at different transcription steps and mRNA expression. An ~20-30% increase in Pol II densities corresponds to a rough 200% increase in mRNA expression and two-fold up-regulation. Here, using a simple kinetic model of Pol II transcription calibrated by in vivo measured rate constants of different transcription steps in mammalian cells, we demonstrate how this non-linearity can be explained by multi-step transcriptional regulation. Moreover, we show how multi-step enhancement of Pol II transcription can increase mRNA production while leaving Pol II densities unaffected. Our theoretical analysis not only recapitulates experimentally observed Pol II densities upon two-fold up-regulation but also points to a limitation of inferences based on Pol II profiles from chromatin immunoprecipitation sequencing (ChIP-seq) or global run-on assays.

biophysics↗

bioRxiv2017

Inferring the selection window in antimicrobial resistance using deep mutational scanning data and biophysics-based fitness models

Mutant-selection window (MSW) hypothesis in antimicrobial resistance implies a range for antimicrobial concentration that promotes selection of single-step resistant mutants. Since the inception and experimental verification, MSW has been at the forefront of strategies to minimize development of antimicrobial resistance (AR). Setting the upper and lower limits of MSW requires an understanding of the dependence of selection coefficient of arising mutations to antimicrobial concentration. In this work, we employed a biophysics-based and experimentally calibrated fitness model to estimate MSW in the case of Ampicillin and Cefotaxime resistance in E.coli TEM-1 beta lactamase. In line with experimental observations, we show that selection is active at very low levels of antimicrobials. Furthermore, we elucidate the dependence of MSW to catalytic efficiency of mutants, fraction of mutants in the population and discuss the role of population genetic parameters such as population size and mutation rate. Altogether, our analysis and formalism provide a predictive model of MSW with direct implications in the design of dosage strategies.

evolutionary biology↗

bioRxiv2017

Highly expressed genes evolve under strong epistasis from a proteome-wide scan in E. coli

Epistasis or the non-additivity of mutational effects is a major force in protein evolution, but it has not been systematically quantified at the level of a proteome. Here, we estimated the extent of epistasis for 2,382 genes in E. coli using several hundreds of orthologs for each gene within the class Gammaproteobacteria. We found that the average epistasis is ~41% across genes in the proteome and that epistasis is stronger among highly expressed genes. This trend is quantitatively explained by the prevailing model of sequence evolution based on minimizing the fitness cost of protein unfolding and aggregation. Our results highlight the coupling between selection and epistasis in the long-term evolution of a proteome.

evolutionary biology↗

bioRxiv2017

Estimating The Contribution Of Folding Stability To Non-Specific Epistasis In Protein Evolution

The extent of non-additive interaction among mutations or epistasis reflects the ruggedness of the fitness landscape, the mapping of genotype to reproductive fitness. In protein evolution, there is strong support for the importance and prevalence of epistasis, but whether there is a universal mechanism behind epistasis remains unknown. It is also unclear which of the biophysical properties of proteins--folding stability, activity, binding affinity, and dynamics--have the strongest contribution to epistasis. Here, we determine the contribution of selection for folding stability to epistasis in protein evolution. By combining theoretical estimates of the rates of molecular evolution and protein folding thermodynamics, we show that simple selection for folding stability implies that at least ~30% to ~60% of among amino acid substitutions would have experienced epistasis. Additionally, our model predicts substantial epistasis at marginal stabilities therefore linking epistasis to the strength of selection. Estimating the contribution of governing factors in molecular evolution such as protein folding stability to epistasis will provide a better understanding of epistasis that could improve methods in molecular evolution.

genetics↗