Biology subjects

Dasmeh, P.

Publications and source records attributed to Dasmeh, P..

16 recordsLinked to original sources

bioRxiv2026

AlphaVaR: an R framework for the statistical interpretation of AlphaGenome variant-effect predictions

SummaryAlphaGenome (Google DeepMind) scores a DNA variant across thousands of functional tracks at single-base resolution, reporting both the magnitude of each predicted effect and its rarity against a genome-wide background. That volume is itself the obstacle to biological interpretation. Here we present AlphaVaR, an R package that gives AlphaGenomes output a typed structure together with the statistical methods and visualizations needed to interpret it. The output schema is identical for every variant, so the same tests apply throughout it. AlphaVaR provides localization tests with multiple-testing correction and effect sizes, a specificity index measuring how far an effect concentrates on a few elements of a chosen variable, and a transparent prioritization that ranks candidates across interpretable criteria and maps each to a target gene. Results feed a plot library, reproducible reports and a code-free Shiny application. Applied to rs1427407, the lead common variant for fetal-haemoglobin level, AlphaVaR recovers the established biology of the BCL11A erythroid enhancer. Availability and implementationhttps://github.com/KarimMarhaba/AlphaVaR, released under the MIT licence, R [≥] 4.2, with documentation at https://karimmarhaba.github.io/AlphaVaR/. The released version is archived at Zenodo (doi:10.5281/zenodo.21939265); the AlphaGenome scores analysed here are archived as a separate dataset (doi:10.5281/zenodo.21920988), and the scripts that regenerate every figure and reported number are in the repository (Supplementary Section S5). Contactpouria.dasmeh@uni-marburg.de Supplementary informationSupplementary data are available online.

genomics↗

bioRxiv2026

Negative Autoregulation Promotes the Evolution of Strong Environmental Switching

Living systems rely on gene regulatory circuits to respond to environmental change. Such circuits often act as molecular switches: OFF in the absence of a cue, and ON in its presence. We do not know how a circuits regulatory architecture affect its ability to evolve such responsiveness. In nature, a very frequent and simple regulatory architecture involves a transcriptional regulator that negatively regulates its own expression. To study how such autoregulation affects adaptive evolution, we engineered E. coli circuits in which a target gene is regulated by the repressor TetR with (A-) or without (A0) negative autoregulation of TetR. We evolved TetR in both architectures toward responsiveness to a novel environment, embodied by a novel inducer of TetR. Early during their evolution, TetR circuits with negative autoregulation evolved stronger environmental switching. A combination of high throughput DNA sequencing, protein engineering, and biophysical modeling showed why. Only A-circuits favored TetR alleles that interact strongly with both the inducer and DNA. Such alleles combine strong repression caused by strong DNA binding with strong derepression caused by strong inducer binding, the defining property of a strong environmental response. Our biophysical model shows that negative autoregulation helps to create this regulatory regime. As a result, only A- circuits favor alleles that create strong molecular switches. Altogether, our work shows that even the simplest form of gene regulation can change the topography of a fitness landscape, and enable new modes of evolutionary change.

evolutionary biology↗

bioRxiv2025

Gene Interaction Network Architecture of Human Polygenic Traits Reveals Domain-Specific Connectivity and Evolutionary Pressures

Human polygenic phenotypes arise from complex interactions among genes within regulatory networks. To gain insights into the structural and evolutionary characteristics of these networks, we analyzed gene interaction networks across 4756 human polygenic phenotypes, contrasting the network properties of genes associated with polygenic phenotypes against those of non-associated genes. Our results indicate that genes associated with polygenic phenotypes exhibit a significantly higher connectivity in their corresponding gene-interaction networks, with connectivity varying markedly across different trait domains. Notably, genes within highly connected networks are enriched for immune-related biological processes, whereas genes in less connected networks are more involved in neurogenesis. Furthermore, we found that genes embedded in highly connected networks are, on average, under weaker selective constraints than those in lowly connected networks. Overall, our findings provide a systematic analysis of gene interaction networks underlying human polygenic traits and reveal how selective constraints vary with network connectivity. These insights offer a framework for prioritizing genes based on their connectivity within trait-associated networks. To support this effort, we developed the online portal http://netpolygen.com enabling researchers to generate and explore hypotheses by identifying genes that are both highly associated and highly connected across thousands of polygenic phenotypes.

evolutionary biology↗

bioRxiv2024

Single cell analysis of Barrett's esophagus and carcinoma reveals cell types conferring risk via genetic predisposition

Inherited genetic variants contribute to Barretts esophagus (BE) and esophageal adenocarcinoma (EAC) but it is unknown which cell types are involved in this process. We performed single cell RNA-sequencing of BE, EAC and paired normal tissues and integrated data of a genome-wide association study to determine cell type-specific genetic risk and cellular processes that contribute to BE and EAC. The analysis revealed that EAC development is driven to a greater extent by local cellular processes than BE development. One cell type of BE origin (BE-EAC) and cellular processes that control the differentiation of columnar cells are of particular relevance for EAC development. Further, specific subtypes of fibroblasts and endothelial cells contribute to BE and EAC development, while dendritic cells and CD4+ memory T cells contribute exclusively to BE development. The diagnostic use of markers characterizing the identified cell types and cellular processes should be explored in future for EAC prediction.

cancer biology↗

bioRxiv2023

Neutral Drift and Threshold Selection Promote Phenotypic Variation

Phenotypic variations within a population exist on different scales of biological organization and play a central role in evolution by providing adaptive capacity at the population-level. Thus, the question of how evolution generates phenotypic variation within an evolving population is fundamental in evolutionary biology. Here we address this question by performing experimental evolution of an antibiotic resistance gene, VIM-2 {beta}-lactamase, combined with diverse biochemical assays and population genetics. We found that neutral drift, i.e., evolution under a static environment, with a low antibiotic concentration can promote and maintain significant phenotypic variation within the population with >100-fold differences in resistance strength. We developed a model based on the phenotype-environment-fitness landscape generated with >5,000 VIM-2 variants, and demonstrated that the combination of "mutation-selection balance" and "threshold-like fitness-phenotype relationship" is sufficient to explain the generation of large phenotypic variation within the evolving population. Importantly, high-resistance conferring variants can emerge during neutral drift, without being a product of adaptation. Our findings provide a novel and simple mechanistic explanation for why most genes in nature, and by extension, systems and organisms, inherently exhibit phenotypic variation, and thus, population-level evolvability.

evolutionary biology↗

bioRxiv2022

Phosphorylation sites are evolutionary checkpoints against liquid-solid transition in protein condensates

Assemblies of multivalent RNA-binding protein FUS can exist in the functional liquid-like state as well as less dynamic and potentially toxic amyloid- and hydrogel-like states. How could then cells form liquid-like condensates while avoiding their transformation to amyloids? Here we show how post-translational phosphorylation can provide a "handle" that prevents liquid-solid transition of intracellular condensates containing FUS. Using residue-specific coarse-grained simulations, for 85 different mammalian FUS sequences, we show how the number of phosphorylation sites and their spatial arrangement affect intracluster dynamics preventing conversion to amyloids. All atom simulations further confirm that phosphorylation can effectively reduce the {beta}-sheet propensity in amyloid-prone fragments of FUS. A detailed evolutionary analysis shows that mammalian FUS PLDs are enriched in amyloid-prone stretches compared to control neutrally evolved sequences suggesting that mammalian FUS proteins evolved to self-assemble. However, in stark contrast to proteins that do not phase-separate for their function, mammalian sequences have phosphosites in close proximity to these amyloid-prone regions. These results suggest that evolution uses amyloid-prone sequences in prion-like domains to enhance phase-separation of condensate proteins while enriching phosphorylation sites in close proximity to safe-guard against liquid-solid transitions. Significance StatementIntrinsically disordered regions and prion-like domains are widely observed in proteins that get enriched in membrane-less organelles (MLOs). Mammalian Fused in Sarcoma (FUS) sequences are significantly enriched in amyloid-prone sequences suggesting that they have evolved to self-assemble. While the amyloid-prone stretches promote self-assembly of these proteins at lower threshold concentrations, these assemblies are vulnerable to aberrant liquid-solid phase transitions. Molecular simulations and bioinformatics analyses show that evolution overcomes this challenge by placing phosphosites specifically close to amyloid-prone stretches. Introduction of negatively charged residues at phosphosite locations results in fewer amyloid-prone contacts and thereby lower beta-sheet propensity. Phosphorylation can thus allow cells to utilize amyloid-prone stretches to promote biogenesis of MLOs while protecting against liquid-solid transitions.

biophysics↗

bioRxiv2022

Rapid evolutionary change in trait correlations of a single protein

Many organismal traits are genetically determined and covary in evolving populations. The resulting trait correlations can either help or hinder evolvability - the ability to bring forth new and adaptive phenotypes. The evolution of evolvability requires that trait correlations themselves must be able to evolve, but we know little about this ability. To learn more about it, we here study one of the simplest evolvable systems, a gene encoding a single protein, and two traits of this protein, namely the ability to emit yellow and green light. We show that correlations between these two traits can evolve rapidly through both mutation and selection on short evolutionary time scales. In addition, we show that these correlations are driven by a proteins ability to fold, because single mutations that alter foldability can dramatically change trait correlations. Since foldability is important for most proteins and their traits, mutations affecting protein folding may alter trait correlations mediated by many other proteins. Thus, mutations that affect protein foldability may also help shape the correlations of complex traits that are affected by hundreds of proteins.

evolutionary biology↗

bioRxiv2021

The length scale of multivalent interactions is evolutionarily conserved in fungal and vertebrate phase-separating proteins

One key feature of proteins that form liquid droplets by phase separation inside a cell is the presence of multiple sites - multivalency - that mediate interactions with other proteins. We know little about the variation of multivalency on evolutionary time scales. Here, we investigated the long-term evolution ([~]600 million years) of multivalency in fungal mRNA decapping subunit 2 protein (Dcp2), and in the FET protein family. We found that multivalency varies substantially among the orthologs of these proteins. However, evolution has maintained the length scale at which sequence motifs that enable protein-protein interactions occur. That is, the total number of such motifs per hundred amino acids is higher and less variable than expected by neutral evolution. To help explain this evolutionary conservation, we developed a conformation classifier using machine-learning algorithms. This classifier demonstrates that disordered segments in Dcp2 and FET proteins tend to adopt compact conformations, which is necessary for phase separation. Thus, the evolutionary conservation we detected may help proteins preserve the ability to undergo phase separation. Altogether, our study reveals that the length scale of multivalent interactions is an evolutionarily conserved feature of two classes of phase-separating proteins in fungi and vertebrates.

evolutionary biology↗

bioRxiv2021

Yeast proteins reversibly aggregate like amphiphilic molecules

More than a hundred proteins in yeast reversibly aggregate and phase-separate in response to various stressors, such as nutrient depletion and heat shock. We know little about the sequence and structural features behind this ability, which has not been characterized on a proteome-wide level. To identify the distinctive features of aggregation-prone regions, we apply machine learning algorithms to genome-scale limited proteolysis-mass spectrometry data from 96 yeast proteins that phase-separate upon heat shock. We find that the aggregation-prone regions (APRs) of our study proteins are significantly enriched in aliphatic residues and depleted in positively charged amino acids. Aggregator proteins with longer APRs show a greater propensity to aggregate, a relationship that can be explained by equilibrium statistical thermodynamics. Altogether, our observations suggest that proteome-wide reversible protein aggregation is mediated by sequence-encoded properties. Aggregating proteins resemble supra-molecular amphiphiles, where APRs are the hydrophobic parts, and non-APRs are the hydrophilic parts.

molecular biology↗

bioRxiv2020

Natural selection has preserved and enhanced the phase-separation properties of FUS during 160 million years of mammalian evolution

Protein phase separation is essential for the self-assembly of non-membraneous organelles. However, we know little about its ability to change in evolution. Here we studied the evolution of the mammalian RNA binding protein FUS, a protein whose prion-like domain (PLD) is essential for the formation of stress granules through liquid-liquid phase separation. Although the prion-like domain evolves three times as rapidly as the remainder of FUS, it harbors absolutely conserved tyrosine residues that are crucial for phase separation. Ancestral reconstruction shows that the phosphorylation sites within the PLD are subject to stabilizing selection. They toggle among a small number of amino acid states. One exception to this pattern are primates, where the number of such phosphosites has increased through positive selection. In addition, we find frequent glutamine to proline changes that help maintain the unstructured state of FUS that is necessary for phase separation. In summary, natural selection has stabilized the liquid-forming potential of FUS and minimized the propensity of cytotoxic liquid-to-solid phase transitions during 160 million years of mammalian evolution.

evolutionary biology↗

bioRxiv2019

Positive selection in the Ebola virus proteome

To gain insight into the recent evolution of EBOLA virus (EBOV) proteins and identify evolutionary hotspots, I investigated patterns of amino acid substitutions in the proteomes of 49 members of EBOV genus including EBOV, Bundibugyo virus (BDBV), Reston virus (RESTV), Sudan virus (SUDV) and Tai Forest virus (TAFV) spanning outbreaks from 1974 to 2014 in Democratic Republic of Congo (DRC), Uganda, Gabon, Sudan, Ivory Coast, Philippines, and Guinea among humans, non-human primates, and pigs. Of the seven genes of the Ebola genome, I found significant variations in evolutionary rates of Glycoprotein (GP), RNA/dependent RNA polymerase (L), and Nucleoprotein (NP) across different lineages. GP and NP were found to evolve at 5- and 3-fold higher rate than other EBOV genes. Several residues in GP and NP show significant dN/dS >1 along the internal branches of the phylogenetic tree leading to Philippines and Sudan outbreaks. Most of these residues are located in solvent exposed areas shown previously to be antigenic. We further identified significant changes in specific amino acid properties of GP, NP and L during the recent evolutionary history of EBOV outbreaks and in particular during the 2014 outbreak. The positively selected residues and chemical properties are consistent with changes in epitope interaction and could thus be important in detecting adaptation of EBOV to the host immune defense system.

genomics↗

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↗