Biology subjects

Wahl, L. M.

Publications and source records attributed to Wahl, L. M..

12 recordsLinked to original sources

bioRxiv2025

Un-LOK-ing a new approach for conformational selective targeting of STK10 (LOK)

STK10 (serine/threonine kinase 10, LOK), is an important regulator of diverse cellular processes, such as cell cycle progression or lymphocyte migration. STK10 has emerged as a potential therapeutic target for diseases associated with impaired cell migration and cell division. Here we present a late-stage optimization of a macrocyclic pyrazolo[1,5-a]pyrimidine scaffold that led to a urea-based lead series targeting the back-pocket of STK10. Co-crystal structure analysis of 23 revealed that the optimized macrocycles adopted a unique binding mode that protrudes deep into the back pocket of STK10. Compound 23 exhibited potent on-target activity in biophysical and activity assays and displayed nanomolar activity for STK10 in cells. In addition, 23 shows good selectivity against the kinome and remarkably also against the closely related kinase SLK (STE20-like kinase). Therefore, we propose that targeting the unique and largely extended pocket in STK10 represents an opportunity to develop highly selective STK10 inhibitors. TOC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=85 SRC="FIGDIR/small/666149v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@36f039org.highwire.dtl.DTLVardef@d55025org.highwire.dtl.DTLVardef@80c007org.highwire.dtl.DTLVardef@bf2471_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2025

Evolutionary Rescue Promotes Mutators

The role of mutation rate in evolutionary rescue has been extensively explored, but little work has investigated how evolutionary rescue can promote mutators, lineages with higher mutation rates. Under complete linkage, we investigate the likelihood of evolutionary rescue on a mutator background that either emerges de novo or pre-exists in the population prior to a severe environmental change. If such an evolutionary rescue event occurs, the mutator lineage sweeps into the population, and thus the environmental stress has promoted mutators. Our findings indicate that mutation rate evolution can substantially boost rescue probabilities, but stronger mutators are most effective when the wildtype has a low mutation rate, while their advantage diminishes for higher wildtype mutation rates. Interestingly, at intermediate wildtype mutation rates, emerging mutators can be almost equally likely to sweep no matter how slowly or quickly the environment changes. However, at low wildtype mutation rates, mutators are only likely to sweep for very slow environmental changes due to the sequential nature of necessary mutations for such sweeps to occur. Finally, we show that pre-existing mutators can be significantly more likely to rescue the population compared to the wildtype, provided the wildtypes mutation rate is relatively low. This research opens new avenues for investigating mutator dynamics in response to environmental stress.

evolutionary biology↗

bioRxiv2024

Dynamics of the distribution of fitness effects during adaptation

Mutations drive adaptive evolution due to their heritable effects on fitness. Empirical measures of the distribution of fitness effects of new mutations (the DFE) have been increasingly successful, and have recently highlighted the fact that the DFE changes during adaptation. Here, we analyze these dynamic changes to the DFE during a simplified adaptive process: an adaptive walk across additive and multiplicative fitness landscapes. First, we derive analytical approximations for the underlying fitness distributions of alleles present in the genotype and available through mutation and use these to derive expressions for the DFE at each step of the adaptive walk. We then confirm these predictions with independent simulations that relax several simplifying assumptions made in the analysis. As expected, our analysis predicts that as adaptation proceeds, the DFE is reshaped through an increase in deleterious mutations (a shift to the left). Surprisingly, this change occurs through different mechanisms depending on the number of alleles available per site: for a small number of available alleles, we observe a depletion of high-fitness alleles available through mutation as expected, however for a large number of alleles we observe that adaptation may be more limited by the availability of low-fitness alleles to be replaced, rather than by the availability of high-fitness alleles to replace them.

evolutionary biology↗

bioRxiv2024

Non-hypermutator cancers access driver mutations through reversals in germline mutational bias

Cancer is an evolutionary disease driven by mutations in asexually-reproducing somatic cells. In asexual microbes, bias reversals in the mutation spectrum can speed adaptation by increasing access to previously undersampled beneficial mutations. By analyzing tumors from 20 tissues, along with normal tissue and the germline, we demonstrate this effect in cancer. Non-hypermutated tumors reverse the germline mutation bias and have consistent spectra across tissues. These spectra changes carry the signature of hypoxia, and they facilitate positive selection in cancer genes. Hypermutated and non-hypermutated tumors thus acquire driver mutations differently: hypermutated tumors by higher mutation rates and non-hypermutated tumors by changing the mutation spectrum to reverse the germline mutation bias.

cancer biology↗

bioRxiv2023

Development of selective pyridopyrimidin-7(8H)-one-based Mammalian STE20-like (MST3/4) kinase inhibitors

Mammalian STE20-like (MST) kinases 1-4 play key roles in regulating the Hippo and autophagy pathways, and their dysregulation has been implicated in cancer development. In contrast to the well-studied MST1/2, the roles of MST3/4 are less clear, in part due to the lack of potent and selective MST3/4 inhibitors. Here, we re-evaluated literature compounds, and used structure-guided design to optimize the p21-activated kinase (PAK) inhibitor G-5555 (8) to selectively target MST3/4. These efforts resulted in the development of MR24 (24) and MR30 (27) with good kinome-wide selectivity, high potency for MST3/4, and selectivity towards the closely related MST1/2. In combination with the MST1/2 inhibitor PF-06447475 (2) the two MST3/4 inhibitors can be used to elucidate the multiple roles of MST kinases in cells. We found that MST3/4-selective inhibition caused a cell cycle arrest in the G1 phase, while MST1/2 inhibition resulted in accumulation of cells in the G2/M phase. These data point to distinct functions of these closely related kinases, which can now be addressed with subfamily-selective chemical tool compounds.

biochemistry↗

bioRxiv2023

Within-host evolution of SARS-CoV-2: how often are mutations transmitted?

Despite a relatively low mutation rate, the large number of SARS-CoV-2 infections has allowed for substantial genetic change, leading to a multitude of emerging variants. Using a recently determined mutation rate (per site replication), as well as parameter estimates for within-host SARS-CoV-2 infection, we apply a stochastic transmission-bottleneck model to describe the survival probability of de novo SARS-CoV-2 mutations. For narrow bottlenecks, we find mutations affecting pertarget-cell attachment rate (with phenotypes associated with fusogenicity and ACE2 binding), have similar transmission probabilities to mutations affecting viral load clearance (with phenotypes associated with humoral evasion). We further find that mutations affecting the eclipse rate (with phenotypes associated with reorganization of cellular metabolic processes and synthesis of viral budding precursor material) are highly favoured relative to all other traits examined. We find mutations leading to reduced removal rates of infected cells (with phenotypes associated with innate immune evasion) have limited transmission advantage relative to mutations leading to humoral evasion. Predicted transmission probabilities, however, for mutations affecting innate immune evasion are more consistent with the range of clinically-estimated household transmission probabilities for de novo mutations. This result suggests that although mutations affecting humoral evasion are more easily transmitted when they occur, mutations affecting innate immune evasion may occur more readily. We examine our predictions in the context of a number of previously characterized mutations in circulating strains of SARS-CoV-2. Our work offers both a null model for SARS-CoV-2 substitution rates and predicts which aspects of viral life history are most likely to successfully evolve, despite low mutation rates and repeated transmission bottlenecks.

genetics↗

bioRxiv2022

Shifts in mutation bias promote mutators by altering the distribution of fitness effects

Recent experimental evidence demonstrates that shifts in mutational biases, for example increases in transversion frequency, can change the distribution of fitness effects of mutations (DFE). In particular, reducing or reversing a prevailing bias can increase the probability that a de novo mutation is beneficial. It has also been shown that mutator bacteria are more likely to emerge if the beneficial mutations they generate have a larger effect size than observed in the wildtype. Here, we connect these two results, demonstrating that mutator strains that reduce or reverse a prevailing bias have a positively-shifted DFE, which in turn can dramatically increase their emergence probability. Since changes in mutation rate and bias are often coupled through the gain and loss of DNA repair enzymes, our results predict that the invasion of mutator strains will be facilitated by shifts in mutation bias that offer improved access to previously under-sampled beneficial mutations.

evolutionary biology↗

bioRxiv2021

Selection bias in mutation accumulation

Mutation accumulation (MA) experiments, in which de novo mutations are sampled and subsequently characterized, are an essential tool in understanding the processes underlying evolution. In microbial populations, MA protocols typically involve a period of population growth between severe bottlenecks, such that a single individual can form a visible colony. While it has long been appreciated that the action of positive selection during this growth phase cannot be eliminated, it is typically assumed to be negligible. Here, we quantify the effect of both positive and negative selection in MA studies, demonstrating that selective effects can substantially bias the distribution of fitness effects (DFE) and mutation rates estimated from typical MA protocols in microbes. We then present a simple correction for this bias which applies to both beneficial and deleterious mutations, and can be used to correct the observed DFE in multiple environments. Finally, we use simulated MA experiments to illustrate the extent to which the MA-inferred DFE differs from the underlying true DFE, and demonstrate that the proposed correction accurately reconstructs the true DFE over a wide range of scenarios. These results highlight that positive selection during microbial MA experiments is in fact not negligible, but can be corrected to gain a more accurate understanding of fundamental evolutionary parameters.

evolutionary biology↗

bioRxiv2020

Mosaic vaccination: how distributing different vaccines across a population could improve epidemic control

Although vaccination has been remarkably effective against some pathogens, for others, rapid antigenic evolution results in vaccination conferring only weak and/or short-lived protection. Consequently, considerable effort has been invested in developing more evolutionarily robust vaccines, either by targeting highly conserved components of the pathogen (universal vaccines) or by including multiple immunological targets within a single vaccine (multi-epitope vaccines). An unexplored third possibility is to vaccinate individuals with one of a number of qualitatively different vaccines, creating a mosaic of individual immunity in the population. Here we explore whether a mosaic vaccination strategy can deliver superior epidemiological outcomes to conventional vaccination, in which all individuals receive the same vaccine. We suppose vaccine doses can be distributed between distinct vaccine targets (e.g., different surface proteins against which an immune response can be generated) and/or immunologically-distinct variants at these targets (e.g., strains); the pathogen can undergo antigenic evolution at both targets. Using simple mathematical models, we show that mosaic vaccination often outperforms conventional vaccination, leading to fewer infected individuals, improved vaccine efficacy, and lower individual risks over the course of the epidemic.

evolutionary biology↗

bioRxiv2020

Shifts in mutation spectra enhance access to beneficial mutations

Biased mutation spectra are pervasive, with wide variation in the magnitude of mutational biases that influence genome evolution and adaptation. How do such diverse biases evolve? Our experiments show that changing the mutation spectrum allows populations to sample previously under-sampled mutational space, including beneficial mutations. The resulting shift in the distribution of fitness effects is advantageous: beneficial mutation supply and beneficial pleiotropy both increase, while deleterious load reduces. More broadly, simulations indicate that reducing or reversing the direction of a long-term bias is always selectively favoured. Such changes in mutation bias can occur easily via altered function of DNA repair genes. A phylogenetic analysis shows that these genes are repeatedly gained and lost in bacterial lineages, leading to frequent bias shifts in opposite directions. Thus, shifts in mutation spectra may evolve under selection, and can directly alter the outcome of adaptive evolution by facilitating access to beneficial mutations. SIGNIFICANCE STATEMENTMutations are important because they provide raw material for evolution. Some types of mutations occur more often than others, and the strength of such mutational bias varies across species. It is not clear how this variation arises. We experimentally measured the immediate effects of changing the mutation bias of E. coli, and used simulations to understand the long-term effects. Altering mutational bias is beneficial whenever the new bias increases sampling of mutational classes that were previously under-sampled. We also show that historically, bacteria have often experienced such beneficial bias switches. Our work thus demonstrates the importance of mutational biases in evolution. By allowing exploration of new mutational space, altered mutation biases could drive rapid adaptation.

evolutionary biology↗

bioRxiv2018

Transmission cycles generate diversity in pathogenic viruses

We investigate the fate of de novo mutations that occur during the in-host replication of a pathogenic virus, predicting the probability that such mutations are passed on during disease transmission to a new host. Using influenza A virus as a model organism, we develop a life-history model of the within-host dynamics of the infection, using a multitype branching process with a coupled deterministic model to capture the population of available target cells. We quantify the fate of neutral mutations and mutations affecting five life-history traits: clearance, attachment, budding, cell death, and eclipse phase timing. Despite the severity of disease transmission bottlenecks, our results suggest that in a single transmission event, several mutations that appeared de novo in the donor are likely to be transmitted to the recipient. Even in the absence of a selective advantage for these mutations, the sustained growth phase inherent in each disease transmission cycle generates genetic diversity that is not eliminated during the transmission bottleneck.

evolutionary biology↗

bioRxiv2018

Evolutionary emergence of infectious diseases in heterogeneous host populations

Emergence and re-emergence of pathogens are notoriously difficult to predict. The erratic nature of those events is reinforced by the stochastic nature of pathogen evolution during the early phase of an epidemic. For instance, mutations allowing pathogens to escape host resistance may boost pathogen spread and promote emergence. Yet, the ecological factors that govern such evolutionary emergence remain elusive both because of the lack of ecological realism of current theoretical frameworks and the difficulty of experimentally testing their predictions. Here we develop a theoretical model to explore the effects of the heterogeneity of the host population on the probability of pathogen emergence, with or without pathogen evolution. We show that evolutionary emergence and the spread of escape mutations in the pathogen population is more likely to occur when the host population contains an intermediate proportion of resistant hosts. We also show that lower pathogen inoculum size and higher diversity of host resistance decrease the probability of evolutionary emergence. Crucially, we present experimental confirmations of these predictions using lytic bacteriophages infecting their bacterial hosts containing diverse CRISPR-Cas immune defenses. We discuss the implications of these results for cross-species spillover and for the management of emerging infectious diseases.\n\nSignificance statementCan we predict the emergence of infectious diseases? The probability that an epidemic breaks out is highly dependent on the ability of the pathogen to acquire new adaptive mutations and to induce evolutionary emergence. Forecasting pathogen emergence thus requires a good understanding of the interplay between epidemiology and evolution taking place at the onset of an outbreak. Here, we provide a comprehensive theoretical framework to analyze the impact of host population heterogeneity on the probability of pathogen evolutionary emergence. We use this model to predict the impact of the fraction of susceptible hosts, the inoculum size of the pathogen and the diversity of host resistance on pathogen emergence. Our experiments using lytic bacteriophages and CRISPR-resistant bacteria support our theoretical predictions.

evolutionary biology↗