Biology subjects

Ghafari, M.

Publications and source records attributed to Ghafari, M..

15 recordsLinked to original sources

bioRxiv2026

Natural selection driven by escape from shifting antibody classes shapes SARS-CoV-2 evolution

The phenotypic fitness landscape defines the action of natural selection on pathogens, linking changes in their phenotypes to transmission and evolution. The rapidly changing nature of epidemic spread and antigenic landscapes pushes viruses to evolve on fitness seascapes. As a result, evolution of viruses such as SARS-CoV-2 proceeds in a neverending series of waves, driven by epistatic interactions and by the arms race between viral adaptation and human immunity. Phenotypic characterisation of these rapidly changing fitness seascapes is an open challenge. Using a Phenotypic Selection Inference framework that links phylogenetic estimates of mutation fitness effects with deep mutational scanning data, we traced how selective pressures on viral phenotypes have shifted throughout the COVID-19 pandemic. Natural selection has favoured enhanced ACE2 binding since the emergence of SARS-COV-2, with relatively constant selective pressure even for the most recent variants. The strength of selection for antibody escape was comparable to ACE2 binding during early evolution, but as population immunity rose, escape from class 3 and then class 2 antibodies became dominant. For variants circulating in 2024, natural selection shifted toward class 3 antibody escape, while those circulating in 2025 have experienced dynamic, rapidly changing pressures for escape from all antibody classes. These transitions reflect an ongoing arms race between viral adaptation and human immunity. Our findings reveal that SARS-CoV-2 antigenic evolution is governed by dynamic, class-specific immune pressures, and that selection for replication capacity has been continuously present during the pandemic, presumably to compensate for the effects of antigenic escape on viral replication. Our approach for the inference of phenotypic selection provides a framework to understand and anticipate the evolution of future variants.

evolutionary biology↗

bioRxiv2025

Effects of a Cancer-Associated Mutation and Multiple SerinePhosphorylation on Poly(ADP-Ribose) Polymerase 2

Poly [ADP-ribose] polymerase 2 (PARP2) plays a crucial role in DNA repair. A common single-nucleotide polymorphism (SNP) in the PARP2 gene, rs3093921, has been associated with pancreatic cancer and marginal zone lymphoma (MZL). This SNP results in a missense mutation, D235G, in the PARP2 protein. PARP2 is also reported to undergo post-translational modifications (PTMs), particularly phosphorylation at serine residues 226, 232, and 353. The C-terminal region of PARP2 includes the Trp-Gly-Arg (WGR) and ADP-ribosyl transferase (ART) domains, and the helical subdomain (HD). The latter two, spanning residues 220 to 583, comprise the catalytic region of PARP2. The DNA-induced enzymatic activation of PARP2 is regulated by local destabilization of the HD domain. We used molecular dynamics (MD) simulations to investigate the impact of these three PTMs on both the wild-type (WT) and the mutant (D235G) forms of PARP2. Our simulations suggest that, while neither the cancer-associated mutation nor PTMs on their own significantly alter the overall flexibility of residues within the HD domain, they cause notably greater deviations in the backbone structure of the HD domain compared to the WT. In addition, PTMs in the context of the mutation show reduced interactions between the mutation site and other protein regions, likely due to structural stabilization induced by the PTMs. Importantly, PTMs mitigate the structural disruption caused by the mutation, helping the mutant protein retain a WT-like conformation. Additionally, the HD domain contributes to maintaining PARP2 in its inactive state through its connection with the ART domain. However, the D235G mutation weakens this connection. While PTMs alone do not have a significant impact on this connection, the simultaneous presence of both the mutation and PTMs partially alleviates the disruptive effect of the mutation and leads to partial restoration of the connection between the HD and ART domains.

biophysics↗

bioRxiv2024

Understanding evolutionary and functional relationships of RNA polymerases in plant and fungal viruses through structural modeling and divergence date estimations

RNA-dependent RNA polymerases (RdRps) are crucial for RNA virus replication and serve as key marker genes for defining deep taxonomic ranks and for understanding viral evolutionary history. Despite their conserved functions and motifs, the high genetic diversity of RdRps complicates precise sequence comparisons across viral families, hindering accurate taxonomic classification of new species. Three-dimensional (3D) RdRp structures can help overcome these challenges through structure-guided alignments. However, such data are rare for myco- and phytoviruses, limiting investigation of their ecological and evolutionary links. In this study, we focused on the highly divergent order Sobelivirales, which includes sobemoviruses infecting plants -- a taxon known for its ancient origin -- and barnaviruses infecting fungi, which remain relatively unknown. Using deep-learning structural modeling, we generated reliable 3D models for 44 sobemoviral and sobelivirad species. Structure-guided alignments, together with new barnaviral and relevant outgroup sequences, enabled robust phylogenetic reconstruction, allowing us to propose revisions of existing viral families and suggest new evolutionary scenarios. Divergence dates were estimated for the first time at this taxonomical rank using the Prisoner of War model, which revealed a divergence of plant and fungal sobelivirads 27.0 {+/-} 10 million years ago -- much more recent than the separation of their respective hosts. This result suggests that cross-kingdom host shifts have contributed more likely to the evolutionary history of Sobelivirales than strict virus-host codivergence. Based on an extended dataset of 127 species, structure and sequence conservation analyses identified molecular signatures of sobeliviral families. These conserved and extented RdRp motifs will facilitate future taxonomic assignments and the development of diagnostic tools. Our interdisciplinary approach, integrating structure modeling and divergence dating, offers new insights into the evolutionary divergence of plant and fungal viruses, with potential applications to other viral orders and families. Author summaryRNA-dependent RNA polymerases (RdRps) are essential for RNA virus replication and serve as important markers for classifying viruses and understanding their evolution. However, with metagenomic studies that rapidly expand the known diversity of RNA viruses, it is increasingly difficult to compare highly divergent RdRps and accurately classify new species. When available, 3D structures of RdRps can help overcome this challenge through structure-guided alignments. Here, we focused on the highly divergent order Sobelivirales, which groups phytoviruses and mycoviruses. Deep-learning models were used to generate reliable 3D structures for 44 representative viral species. Structure-guided alignments combined with the identification of new barnaviruses and outgroups allowed us to build a more accurate viral phylogeny. Based on this finding, we proposed updates to existing viral families and genera within the order Sobelivirales. We estimated divergence dates using a model that previously uncovered the ancient origins of sobemovirus. Notably, we provided the first estimate of when these plant and fungal viruses diverged [~]27.0 {+/-} 10 million years ago, suggesting cross-kingdom host shifts rather than strict virus-host codivergence. We also identified molecular signatures that are useful for future virus classification and diagnosis, with potential applications to other viral groups.

evolutionary biology↗

bioRxiv2024

Lineage-aware evolutionary analysis of hepatitis C virus within-host dynamics

Analysis of viral genetic data has previously revealed distinct within-host population structures in both untreated and interferon-treated chronic hepatitis C virus (HCV) infections. While multiple subpopulations persisted during the infection, each subpopulation was observed only intermittently. However, it was unknown whether similar patterns were also present after Direct Acting Antiviral (DAA) treatment, where viral populations were often assumed to go through narrow bottlenecks. Here we tested for the maintenance of population structure after DAA treatment failure. We analysed whole-genome next-generation sequencing data generated from a randomised study using DAAs (the BOSON study). We focused on samples collected from patients (N=84) who did not achieve sustained virological response (i.e. treatment failure) and had sequenced virus from multiple timepoints. For each individual, we tracked concordance in nucleotide variant frequencies through time. Using a sliding window approach, we applied sequenced-based and tree-based clustering algorithms across the entire HCV genome. Finally, we reconstructed viral haplotypes and estimated lineage specific within-host divergence rates from the haplotype phylogenies. Distinct viral subpopulations were maintained among a high proportion of individuals post DAA treatment failure. Using maximum likelihood modelling and model comparison, we found an overdispersion of viral evolutionary rates among individuals, and significant differences in evolutionary rates between lineages within individuals. These results suggest the virus is compartmentalised within individuals, with the varying evolutionary rates due to different viral replication rates or different selection pressures. We propose lineage awareness in future analyses of HCV evolution and infections to avoid conflating patterns from distinct lineages, and to recognise the likely existence of unsampled subpopulations.

evolutionary biology↗

bioRxiv2024

Biased estimates of phylogenetic branch lengths resulting from the discretised Gamma model of site rate heterogeneity

A standard method in phylogenetic reconstruction for representing variation in substitution rates between sites in the genome is the discrete Gamma model (DGM). Relative rates are assumed to be distributed according to a discretised Gamma distribution, where the probabilities that a site is included in each class are equal. Here, we identify a serious bias in the branch lengths of reconstructed phylogenies when the DGM is used, with the magnitude of the effect varying with the number of sequences in the alignment. We demonstrate the existence of the bias in both simulated dataset and using real HIV-1 sequences; in both cases branch lengths are overestimated. We show that the alternative "FreeRate" model, which assumes no parametric distribution and allows the class probabilities to vary, is not subject to the issue. We further establish that the reason for the behaviour is the equal class probabilities, not the discretisation itself. We explore the mathematics of for the phenomenon, showing how maximum likelihood branch lengths under the DGM may differ from the true ones used to generate the tree, and that branch lengths will be overestimated where there is a long-tail of fast-evolving sites in the true rate distribution, which is the usual situation in real datasets. We recommend that the DGM be retired from general use. While FreeRate is an immediately available replacement, it is known to be difficult to fit, and thus there is scope for innovation in rate heterogeneity models.

evolutionary biology↗

bioRxiv2023

Revisiting the origins of the Sobemovirus genus: a case for ancient origins of plant viruses

The discrepancy between short- and long-term rate estimates, known as the time-dependent rate phenomenon (TDRP), poses a challenge to extrapolating evolutionary rates over time and reconstructing evolutionary history of viruses. The TDRP reveals a decline in evolutionary rate estimates with the measurement timescale, explained empirically by a power-law rate decay, notably observed in animal and human viruses. A mechanistic evolutionary model, the Prisoner of War (PoW) model, has been proposed to address TDRP in viruses. Although TDRP has been studied in animal viruses, its impact on plant virus evolutionary history remains largely unexplored. Here, we investigated the consequences of TDRP in plant viruses by applying the PoW model to reconstruct the evolutionary history of sobemoviruses, plant pathogens with significant importance due to their impact on agriculture and plant health. Our analysis showed that the Sobemovirus genus dates back over four million years, indicating an ancient origin. We found evidence that supports deep host jumps to Poaceae, Fabaceae, and Solanaceae occurring between tens to hundreds of thousand years ago, followed by specialization. Remarkably, the TDRP-corrected evolutionary history of sobemoviruses was extended far beyond previous estimates that had suggested their emergence during the Neolithic period. By incorporating sequences collected through metagenomic analyses, the resulting phylogenetic tree showcases increased genetic diversity, reflecting a deep history of sobemovirus species with major radiation events taking place during the Neolithic period, suggesting rapid diversification in that period. Our findings make a case for the possibility of deep evolutionary origins of plant viruses.

evolutionary biology↗

bioRxiv2023

The recency and geographical origins of the bat viruses ancestral to SARS-CoV and SARS-CoV-2

The emergence of SARS-CoV in 2002 and SARS-CoV-2 in 2019 has led to increased sampling of related sarbecoviruses circulating primarily in horseshoe bats. These viruses undergo frequent recombination and exhibit spatial structuring across Asia. Employing recombination-aware phylogenetic inference on bat sarbecoviruses, we find that the closest-inferred bat virus ancestors of SARS-CoV and SARS-CoV-2 existed just [~]1-3 years prior to their emergence in humans. Phylogeographic analyses examining the movement of related sarbecoviruses demonstrate that they traveled at similar rates to their horseshoe bat hosts and have been circulating for thousands of years in Asia. The closest-inferred bat virus ancestor of SARS-CoV likely circulated in western China, and that of SARS-CoV-2 likely circulated in a region comprising southwest China and northern Laos, both a substantial distance from where they emerged. This distance and recency indicate that the direct ancestors of SARS-CoV and SARS-CoV-2 could not have reached their respective sites of emergence via the bat reservoir alone. Our recombination-aware dating and phylogeographic analyses reveal a more accurate inference of evolutionary history than performing only whole-genome or single gene analyses. These results can guide future sampling efforts and demonstrate that viral genomic fragments extremely closely related to SARS-CoV and SARS-CoV-2 were circulating in horseshoe bats, confirming their importance as the reservoir species for SARS viruses.

evolutionary biology↗

bioRxiv2023

The evolutionary history of hepaciviruses

In the search for natural reservoirs of hepatitis C virus (HCV), a broad diversity of non-human viruses within the Hepacivirus genus has been uncovered. However, the evolutionary dynamics that shaped the diversity and timescale of hepaciviruses evolution remain elusive. To gain further insights into the origins and evolution of this genus, we screened a large dataset of wild mammal samples (n = 1,672) from Africa and Asia, and generated 34 full-length hepacivirus genomes. Phylogenetic analysis of these data together with publicly available genomes emphasizes the importance of rodents as hepacivirus hosts and we identify 13 rodent species and 3 rodent genera (in Cricetidae and Muridae families) as novel hosts of hepaciviruses. Through co-phylogenetic analyses, we demonstrate that hepacivirus diversity has been affected by cross-species transmission events against the backdrop of detectable signal of virus-host co-divergence in the deep evolutionary history. Using a Bayesian phylogenetic multidimensional scaling approach, we explore the extent to which host relatedness and geographic distances have structured present-day hepacivirus diversity. Our results provide evidence for a substantial structuring of mammalian hepacivirus diversity by host as well as geography, with a somewhat more irregular diffusion process in geographic space. Finally, using a mechanistic model that accounts for substitution saturation, we provide the first formal estimates of the timescale of hepacivirus evolution and estimate the origin of the genus to be about 22 million years ago. Our results offer a comprehensive overview of the micro- and macroevolutionary processes that have shaped hepacivirus diversity and enhance our understanding of the long-term evolution of the Hepacivirus genus. SignificanceSince the discovery of Hepatitis C virus, the search for animal virus homologues has gained significant traction, opening up new opportunities to study their origins and long-term evolutionary dynamics. Capitalizing on a large-scale screening of wild mammals, and genomic sequencing, we expand the novel rodent host range of hepaciviruses and document further virus diversity. We infer a significant influence of frequent cross-species transmission as well as some signal for virus-host co-divergence, and find comparative host and geographic structure. We also provide the first formal estimates of the timescale of hepaciviruses indicating an origin of about 22 million years ago. Our study offers new insights in hepacivirus evolutionary dynamics with broadly applicable methods that can support future research in virus evolution.

microbiology↗

bioRxiv2023

Reconstructing the evolutionary history of human, simian, and prosimian immunodeficiency viruses

The evolutionary history of simian and prosimian immunodeficiency viruses (SIVs and pSIVs) remains difficult to resolve due to time-dependent rate variation in viral evolution. Standard molecular clock methods relying on contemporary sequences often underestimate viral ages, conflicting with paleovirological and biogeographical evidence. Here, we apply the Prisoner of War model, which accounts for time-dependent rate effects, to reconstruct the evolutionary history of primate lentiviruses. Using non-recombinant genomic regions from 436 HIV, SIV, and pSIV sequences, we estimate that the most recent common ancestor of extant SIVs dates to [~]1 million years ago. The lineages giving rise to HIV-1 and HIV-2 (SIVcpz and SIVsmm) have circulated in their respective hosts for tens to hundreds of thousands of years, suggesting prolonged pre-pandemic human exposure. The divergence of SIV and pSIV is dated to 17-51 million years ago, consistent with lentiviral transfer during the last mammalian colonisation of Madagascar. Our analysis integrates lentiviral data across recent (HIV), intermediate (Bioko Island SIVs), and ancient (pSIV) timescales, enabling inferences not possible from any single timescale alone, and recovers both shallow and deep divergence events without relying on fixed internal node calibrations. This unified framework provides new insights into virus-host coevolution and zoonotic risk.

evolutionary biology↗

bioRxiv2022

Investigating the evolutionary origins of the first three SARS-CoV-2 variants of concern

The emergence of Variants of Concern (VOCs) of SARS-CoV-2 with increased transmissibility, immune evasion properties, and virulence poses a great challenge to public health. Despite unprecedented efforts to increase genomic surveillance, fundamental facts about the evolutionary origins of VOCs remain largely unknown. One major uncertainty is whether the VOCs evolved during transmission chains of many acute infections or during long-term infections within single individuals. We test the consistency of these two possible paths with the observed dynamics, focusing on the clustered emergence of the first three VOCs, Alpha, Beta, and Gamma, in late 2020, following a period of relative evolutionary stasis. We consider a range of possible fitness landscapes, in which the VOC phenotypes could be the result of single mutations, multiple mutations that each contribute additively to increasing viral fitness, or epistatic interactions among multiple mutations that do not individually increase viral fitness--a "fitness plateau". Our results suggest that the timing and dynamics of the VOC emergence, together with the observed number of mutations in VOC lineages, are in best agreement with the VOC phenotype requiring multiple mutations and VOCs having evolved within single individuals with long-term infections.

evolutionary biology↗

bioRxiv2021

Computational analysis of transition temperatures (Tts) of proteins fused to elastin-like polypeptide (ELP): deep fake evaluation of proteins, linkers, and trailers features

The phase transition temperature (Tt) prediction of the Elastin-like polypeptides (ELPs) is not trivial because it is related to complex sets of variables such as composition, sequence length, hydrophobic characterization, hydrophilic characterization, the sequence order in the fused proteins, linkers and trailer constructs. In this paper, two unique quantitative models are presented for the prediction of the Tt of a family of ELPs that could be fused to different proteins, linkers, and trailers. The lack of need to use multiple software, peptide information, such as PDB file, as well as knowing the second and third structures of proteins are the advantages of this model besides its high accuracy and speed. One of our models could predict the Tt values of the fused ELPs by entering the protein, linker, and trailer features with R2=99%. Also, another model is able to predict the Tt value by entering the fused protein feature with R2=96%. For more reliability, our method is enriched by Artificial Intelligence (AI) to generate similar proteins. In this regard, Generative Adversarial Network (GAN) is our AI method to create fake proteins and similar values. The experimental results show that our strategy for prediction of Tt is reliable in large data. Author SummaryThe application of Elastin-like polypeptides (ELPs) as a protein tag is now developed in a variety of biotechnology aspects especially in proteins purification and drug delivery. ELPs application as a protein tag is owed to retain the phase transition behavior when ELPs fused to other proteins, linkers and tags. ELPs undergo the phase transition behavior by changing from soluble phase to insoluble phase above its inverse transition temperature (Tt) within a short time span. This biophysical behavior is usually reversible at the temperature below the Tt. There are few reports for evaluation of the Tt of ELPs types by using the dissimilar equations and algorithms. Our current predictions are the most accurate calculations presented so far by using the protein, linker and trailer effects and the results were evaluated in accordance with the available experimental data. Furthermore, our results also show that our strategy for prediction of Tt is reliable in large data.

bioinformatics↗

bioRxiv2021

Prisoner of War dynamics explains the time-dependent pattern of substitution rates in viruses

Molecular clock dating is widely used to estimate timescales of phylogenetic histories and to infer rates at which species evolve. One of the major challenges with inferring rates of molecular evolution is the observation of a strong correlation between estimated rates and the timeframe of their measurements. Recent empirical analysis of virus evolutionary rates suggest that a power-law rate decay best explains the time-dependent pattern of substitution rates and that the same pattern is observed regardless of virus type (e.g. groups I-VII in the Baltimore classification). However there exists no explanation for this trend based on molecular evolutionary mechanisms. We provide a simple predictive mechanistic model of the time-dependent rate phenomenon, incorporating saturation and host constraints on the evolution of some sites. Our model recapitulates the ubiquitous power-law rate decay with a slope of -0.65 (95% HPD: -0.72, -0.52) and can satisfactorily account for the variation in inferred molecular evolutionary rates over a wide range of timeframes. We show that once the saturation of sites starts - typically after hundreds of years in RNA viruses and thousands of years in DNA viruses - standard substitution models fail to correctly estimate divergence times among species, while our model successfully re-creates the observed pattern of rate decay. We apply our model to re-date the diversification of genotypes of hepatitis C virus (HCV) to 396,000 (95% HPD: 326,000 - 425,000) years before present, a time preceding the dispersal of modern humans out of Africa, and also showed that the most recent common ancestor of sarbecoviruses dates back to 23,500 (95% HPD: 21,100 - 25,300) years ago, nearly thirty times older than previous estimates. This not only creates a radical new perspective for our understanding the origins of HCV but also suggests a substantial revision of evolutionary timescales of other viruses can be similarly achieved.

evolutionary biology↗

bioRxiv2020

Inferring transmission bottleneck size from viral sequence data using a novel haplotype reconstruction method

The transmission bottleneck is defined as the number of viral particles transmitted from one host to another. Genome sequence data has been used to evaluate the size of the transmission bottleneck between humans infected with the influenza virus, however, the methods used to make these estimates have some limitations. Specifically, approaches using viral allele frequency data may not fully capture a process which involves the transmission of entire viral genomes. Here we set out a novel approach for inferring viral transmission bottlenecks; our method combines haplotype reconstruction, a method for inferring the composition of genomes in a viral population, with two maximum likelihood methods for bottleneck inference, tailored for small and large bottleneck sizes respectively. Our method allows for rapid calculation, and performs well when applied to data from simulated transmission events, being robust to errors in the haplotype reconstruction process. Applied to data from a previous household transmission study of influenza A infection we confirm the result that the majority of transmission events involve a small number of viruses, albeit with slightly looser bottlenecks being inferred, with between 1 and 13 particles transmitted in the majority of cases. While influenza A transmission involves a tight population bottleneck, the bottleneck is not so tight as to universally prevent the transmission of within-host viral diversity.

evolutionary biology↗

bioRxiv2019

Complementary Performances of Convolutional and Capsule Neural Networks on Classifying Microfluidic Images of Dividing Yeast Cells

Microfluidic-based assays have become effective high-throughput approaches to examining replicative aging of budding yeast cells. Deep learning may offer an efficient way to analyze a large number of images collected from microfluidic experiments. Here, we compare three deep learning architectures to classify microfluidic time-lapsed images of dividing yeast cells into categories that represent different stages in the yeast replicative aging process. We found that convolutional neural networks outperformed capsule networks in terms of accuracy, precision, and recall. The capsule networks had the most robust performance at detecting one specific category of cell images. An ensemble of three best-fitted single-architecture models achieves the highest overall accuracy, precision, and recall due to complementary performances. In addition, extending classification classes and augmentation of the training dataset can improve the predictions of the biological categories in our study. This work lays a useful framework for sophisticated deep-learning processing of microfluidics-based assays of yeast replicative aging.

bioinformatics↗

bioRxiv2018

The expected time to cross extended fitness plateaus

For a population to acquire a complex adaptation requiring multiple individually neutral mutations, it must cross a plateau in the fitness landscape. We consider plateaus involving three mutations, and show that large populations can cross them rapidly via lineages that acquire multiple mutations while remaining at low frequency. Plateau-crossing is fastest for very large populations. At intermediate population sizes, recombination can greatly accelerate adaptation by combining independent mutant lineages to form triple-mutants. For more frequent recombination, such that the population is kept near linkage equilibrium, we extend our analysis to find simple expressions for the expected time to cross plateaus of arbitrary width.

evolutionary biology↗