Biology subjects

Rasmussen, D.

Publications and source records attributed to Rasmussen, D..

9 recordsLinked to original sources

bioRxiv2026

Evolutionary reconstruction of bat influenza A viruses reveals segment-specific histories and host-associated selection

Influenza A (IAV) is a major zoonotic pathogen infecting a broad range of vertebrate hosts. In this study, we focus on inferring the evolutionary history of a subset of novel IAV, isolated from New World bats, which use a non-canonical host receptor and infer their relationship to sialic-acid-binding IAV. Little is known about when these novel subtypes emerged and how selection has acted upon them compared to sialic-acid-binding circulating strains. The current state of the field is split on whether bats are natural reservoirs for a distinct yet low abundance IAV lineage, or if influenza underwent rapid evolution after a recent spillover from a species within its standard host range. By analyzing segment-specific phylogenies, we hope to clarify the evolutionary history of bat IAV. Our objectives are to infer the date of divergence of non-canonical bat IAV from sialic-acid binding IAV, identify patterns of selection acting on bat IAV compared to representative samples of sialic-acid-binding IAV to identify potential signatures of genome-wide adaptation, and finally to reconstruct ancestral state transitions to infer which host taxa preceded spillover into bats. To accomplish this, we analyzed each IAV genome segment independently using least-squares molecular dating, Bayesian discrete-trait ancestral host reconstruction, and branch-site selection tests. Our results suggest that non-canonical bat IAV diverged from major IAV lineages 100-200 years ago, supporting a deeper evolutionary history rather than a very recent spillover event. However, discordance among genome segments in inferred divergence times, selective pressures, and ancestral hosts indicates that bat IAV experienced segment-specific evolutionary histories. Together, these findings suggest that non-canonical bat IAV represents a deeply divergent lineage with a complex evolutionary history involving segment-specific selection and host-transition dynamics.

microbiology↗

bioRxiv2026

Megalin deficiency perturbs retinal homeostasis and impairs cathepsin D processing and phagosome-lysosome maturation in the retinal pigment epithelium

The multiligand endocytic receptor, megalin (LRP2), is expressed in the retinal pigment epithelium (RPE) and patients lacking the receptor develop high myopia. Despite its established role in retinal development, the contribution of megalin to retinal homeostasis in the normally developed/mature eye remains poorly understood. Here, we investigated megalin function using an inducible knockout mouse (KO) model and human iPSC-derived RPE with megalin knockdown (KD) to distinguish post-developmental homeostatic functions from developmental effects. In vivo, megalin ablation caused progressive retinal degeneration and visual impairment, with morphological abnormalities in the RPE but no changes in myopia-associated ocular phenotypes including axial length and intraocular pressure. Proteomic profiling of megalin-KO RPE revealed reduction of autophagy-related proteins. In line with this, megalin deficiency was associated with accumulation of pro-cathepsin D, and perturbed rhodopsin turnover. This was supported in vitro, where trafficking of photoreceptor outer segment (POS) containing phagosomes to lysosomes was reduced, suggesting disturbed phagosome maturation. Megalin KD did not measurably impair initial uptake of POS discs, but delayed rhodopsin degradation, indicating defective post-ingestion processing. Together, these findings establish megalin as a key regulator of retinal homeostasis in the mature eye by controlling phagosome-lysosome fusion in the RPE and suggest that megalin dysfunction contributes to slowly progressive retinal degeneration. This positions megalin as a potential therapeutic target in lysosomal degenerative diseases in the retina.

Cell Biology↗

bioRxiv2024

Phylodynamics beyond neutrality: The impact ofincomplete purifying selection on viral phylogeniesand inference

Viral phylodynamics focuses on using sequence data to make inferences about the population dynamics of viral infectious diseases. These inferences commonly include estimation of the viral growth rate, the reproduction number, and the time of most recent common ancestor. With few exceptions, existing phylodynamic inference approaches assume that all observed and ancestral viral genetic variation is fitness-neutral. This assumption is violated more often than not, with a large body of analyses indicating that fitness varies substantially among genotypes circulating viral populations. Here, we focus specifically on fitness variation arising from deleterious mutations, asking whether incomplete purifying selection of deleterious mutations has the potential to bias phylodynamic inference. We use simulations of an exponentially growing population to explore how incomplete purifying selection distorts tree shape as well as how it shifts the distribution of non-neutral mutations over trees. Consistent with previous results, we find that incomplete purifying selection strongly shapes the distribution of mutations while only weakly impacting tree shape. Despite incomplete purifying selection shifting the distribution of mutations, we find little discernible bias in estimates of the viral growth rate and times of the most recent common ancestor. Our results reassuringly indicate that existing phylodynamic inference approaches may not yield biased epidemiological parameter estimates in the face of incomplete purifying selection, although more work is needed to assess the generalizability of these findings.

evolutionary biology↗

bioRxiv2023

Evolutionarily diverse origins of honey bee deformed wing viruses

Novel transmission routes can allow infectious diseases to spread, often with devastating consequences. Ectoparasitic varroa mites vector a diversity of RNA viruses and, having switched hosts from the eastern to western honey bees (Apis cerana to Apis mellifera). They provide an opportunity to explore how novel transmission routes shape disease epidemiology. As the principal driver of the spread of Deformed Wing Viruses (mainly DWV-A and DWV-B), varroa infestation has also driven global honey bee health declines. The more virulent DWV-B strain has been replacing the original DWV-A strain in many regions over the past two decades. Yet, how these viruses originated and spread remains poorly understood. Here we use a phylogeographic analysis based on whole genome data to reconstruct the origins and demography of DWV spread. We found that, rather than reemerging in western honey bees after varroa switched hosts, as suggested by previous work, DWV-A most likely originated in Asia and spread in the mid-20th century. It also showed a massive population size expansion following the varroa host switch. By contrast, DWV-B was most likely acquired more recently from a source outside Asia, and appears absent from eastern honey bees, the original varroa host. These results highlight the dynamic nature of viral adaptation, whereby a vectors host switch can give rise to competing and increasingly virulent disease pandemics. The evolutionary novelty and rapid global spread of these host-virus interactions, together with observed spillover into other species, illustrate how increasing globalisation poses urgent threats to biodiversity and food security.

evolutionary biology↗

bioRxiv2022

Development of allosteric, selective cyclin-dependent kinase 2 (CDK2) inhibitors that are negatively cooperative with cyclin binding and show potential as contraceptive agents

Compared to most ATP-site kinase inhibitors, small molecules that target an allosteric pocket have the potential for improved selectivity due to the often observed lower structural similarity at these distal sites. Despite their promise, relatively few examples of structurally confirmed, high-affinity allosteric kinase inhibitors exist. Cyclin-dependent kinase 2 (CDK2) is a target for many therapeutic indications, including non-hormonal contraception.1 However, an inhibitor against this kinase with exquisite selectivity has not reached the market because of the structural similarity between CDKs.1-2 In this paper, we describe the development and mechanism of action of new type III inhibitors that bind CDK2 with nanomolar affinity, making them the highest affinity, structurally confirmed allosteric CDK inhibitors reported. Notably, these anthranilic acid inhibitors exhibit a strong negative cooperative relationship with cyclin binding, which remains an underexplored mechanism for CDK2 inhibition. Furthermore, the binding profile of these compounds in both biophysical and cellular assays demonstrate the promise of this series for further development into a therapeutic selective for CDK2 over highly similar kinases like CDK1. The potential of these inhibitors as efficacious contraceptive agents is seen by incubation with mouse testicular explants, where they recapitulate Cdk2-/- and Spdya-/- phenotypes.

pharmacology and toxicology↗

bioRxiv2022

Recombination-aware Phylogeographic Inference Using the Structured Coalescent with Ancestral Recombination

Movement of individuals between populations or demes is often restricted, especially between geographically isolated populations. The structured coalescent provides an elegant theoretical framework for describing how movement between populations shapes the genealogical history of sampled individuals and thereby structures genetic variation within and between populations. However, in the presence of recombination an individual may inherit different regions of their genome from different parents, resulting in a mosaic of genealogical histories across the genome, which can be represented by an Ancestral Recombination Graph (ARG). In this case, different genomic regions may have different ancestral histories and so different histories of movement between populations. Recombination therefore poses an additional challenge to phylogeographic methods that aim to reconstruct the movement of individuals from genealogies, although also a potential benefit in that different loci may contain additional information about movement. Here, we introduce the Structured Coalescent with Ancestral Recombination (SCAR) model, which builds on recent approximations to the structured coalescent by incorporating recombination into the ancestry of sampled individuals. The SCAR model allows us to infer how the migration history of sampled individuals varies across the genome from ARGs, and improves estimation of key population genetic parameters such as population sizes, recombination rates and migration rates. Using the SCAR model, we explore the potential and limitations of phylogeographic inference using full ARGs. We then apply the SCAR to lineages of the recombining fungus Aspergillus flavus sampled across the United States to explore patterns of recombination and migration across the genome.

bioinformatics↗

bioRxiv2020

On reproductive and respiratory syndrome virus dissemination across pig production systems in the United States

Porcine reproductive and respiratory syndrome virus (PRRSV) remains widespread in the North American pig population. Despite improvements in virus characterization, it is unclear whether PRRSV infections are a product of viral circulation within a farm, within production systems (local) or across production systems (external). Here we examined the dissemination dynamics of PRRSV and the processes facilitating its spread within and among pig farms in three production systems. Overall, PRRSV genetic diversity declined since 2018, while phylodynamic results support frequent transmission across-production systems. We found that PRRSV dissemination occurred mostly through transmission between farms of different production companies, which were predominant for several months, especially from November until May when PRRSV tends to peak in the studied region. Within production systems, dissemination occurred mainly through regular pig flow (from sow to nursery and then to finisher farms); nevertheless, an important flux of PRRSV dissemination from finisher to sow and nursery farms highlighted the importance of downstream farms as sources of the virus. Farms at areas with pig density from 500 to 1000 pig/km2 and farms located at a range within 0.5 km and 0.7 km from major roads were more likely to infect by PRRSV, whereas farms at elevation between 41 and 61 meters and denser vegetation acted as dissemination barriers. Although remains a challenge, there is a need to disentangle the route of PRRSV transmission, results evidenced that dissemination among commercially unrelated pig production systems was intense, reinforcing the importance of farm proximity on PRRSV spread. Thus, consideration of farm location and their geographic characteristics may help to forecast dissemination. The understanding of PRRSV transmission routes has the potential to inform targeted strategies for its prevention and control. Further studies are needed to quantify the relative contribution of PRRSV transmission routes.

evolutionary biology↗

bioRxiv2018

BEAST 2.5: An Advanced Software Platform for Bayesian Evolutionary Analysis

Elaboration of Bayesian phylogenetic inference methods has continued at pace in recent years with major new advances in nearly all aspects of the joint modelling of evolutionary data. It is increasingly appreciated that some evolutionary questions can only be adequately answered by combining evidence from multiple independent sources of data, including genome sequences, sampling dates, phenotypic data, radiocarbon dates, fossil occurrences, and biogeographic range information among others. Including all relevant data into a single joint model is very challenging both conceptually and computationally. Advanced computational software packages that allow robust development of compatible (sub-)models which can be composed into a full model hierarchy have played a key role in these developments.\n\nDeveloping such software frameworks is increasingly a major scientific activity in its own right, and comes with specific challenges, from practical software design, development and engineering challenges to statistical and conceptual modelling challenges. BEAST 2 is one such computational software platform, and was first announced over 4 years ago. Here we describe a series of major new developments in the BEAST 2 core platform and model hierarchy that have occurred since the first release of the software, culminating in the recent 2.5 release.\n\nAuthor summaryBayesian phylogenetic inference methods have undergone considerable development in recent years, and joint modelling of rich evolutionary data, including genomes, phenotypes and fossil occurrences is increasingly common. Advanced computational software packages that allow robust development of compatible (sub-)models which can be composed into a full model hierarchy have played a key role in these developments. Developing scientific software is increasingly crucial to advancement in many fields of biology. The challenges range from practical software development and engineering, distributed team coordination, conceptual development and statistical modelling, to validation and testing. BEAST 2 is one such computational software platform for phylogenetics, population genetics and phylodynamics, and was first announced over 4 years ago. Here we describe the full range of new tools and models available on the BEAST 2.5 platform, which expand joint evolutionary inference in many new directions, especially for joint inference over multiple data types, non-tree models and complex phylodynamics.

evolutionary biology↗

bioRxiv2017

External introductions helped drive and sustain the high incidence of HIV-1 in rural KwaZulu-Natal, South Africa

Despite increasing access to antiretroviral therapy, HIV incidence in rural KwaZulu-Natal communities remains among the highest ever reported in Africa. While many epidemiological factors have been invoked to explain this high incidence, widespread human mobility and movement of viral lineages between geographic locations have implicated high rates of transmission across communities. High rates of crosscommunity transmission call into question how effective increasing local coverage of antiretroviral therapy will be at preventing new infections, especially if many new cases arise from external introductions. To help address this question, we use a new phylodynamic modeling approach to estimate both changes in epidemic dynamics through time and the relative contribution of local transmission versus external introductions to overall incidence from HIV-1 subtype C phylogenies. Our phylodynamic estimates of HIV prevalence and incidence are remarkably consistent with population-based surveillance data. Our analysis also reveals that early epidemic dynamics in this population were largely driven by a wave of external introductions. More recently, we estimate that anywhere between 20-60% of all new infections arise from external introductions from outside the local community. These results highlight the power of using phylodynamic methods to study generalized HIV epidemics and the growing need to consider larger-scale regional transmission dynamics above the level of local communities when designing and testing prevention strategies.

epidemiology↗