Biology subjects

Wallin, J.

Publications and source records attributed to Wallin, J..

5 recordsLinked to original sources

bioRxiv2024

A climate and population dependent diffusion model forecasts the spread of Aedes Albopictus mosquitoes in Europe

Vectors of Dengue, Chikungunya, Zika, and Yellow Fever are emerging in new areas, posing increasing public health risks. Aedes albopictus, a key vector for these diseases, is expanding its range beyond its tropical and subtropical origins, driven by suitable climate, population mobility, trade, and urbanization. Since its introduction to Europe, Ae. albopictus has rapidly spread and triggered recurrent outbreaks. Past model attempts have handled vector suitability and vector introduction as independent drivers. Here we develop a novel, highly predictive spatio-temporal vector diffusion model based on minimum temperature, median temperature, relative humidity and human population as predictors. The model predicts areas of presence or absence with an accuracy of 99% and 79% for new established vector populations. The model explains how short- and long-range spread of Ae. albopictus interacts with vector suitability. These results show that the expansion of Ae. albopictus in Europe is predictable and closely linked to climate suitability, and human population. The new model integrates in one simultaneous model framework the climate and mobility drivers, providing a better basis for anticipating future outbreaks in situations of dependent interacting co-drivers. Significance statementThe Tiger mosquito, Aedes albopictus, which spreads diseases like Dengue, Chikungunya, Zika and Yellow fever, has accelerated its presence in Europe over the past decades. This poses a public health risk as Europe face an upsurge of autochthonous arbovirus transmission events. The change is partly due to conducive environments, climate change and human mobility and trade. We develop a novel model explaining the spread of the mosquito over the years 2010-2023, observing a change in recorded mosquito presence areas from 138 regions in 2010 to 537 regions in 2023. The model incorporates patterns in both space and time, capturing with high accuracy how the mosquito spreads from region to region based on climate suitability, geographical diffusion and human population density.

molecular biology↗

bioRxiv2024

Disclosing temperature sensitivity of West Nile virus transmission: novel computational approaches to mosquito-pathogen trait responses

Temperature influences the transmission of mosquito-borne pathogens with significant implications for disease risk in the context of climate change. Mathematical models of mosquito-borne infections rely on functions that capture mosquito-pathogen interactions in response to temperature to better estimate transmission dynamics. To derive these functions, experimental studies provide valuable data on the temperature sensitivity of mosquito life-history traits and pathogen transmission. However, the scarcity of experimental data and inconsistencies in methodologies for analysing and comparing temperature responses across mosquito species and pathogens present challenges to accurately modelling mosquito-borne infections. In this study, we investigated the thermal biology of West Nile virus (WNV), a major mosquito-borne infection. We critically reviewed existing experimental studies, obtaining temperature responses for eight mosquito-pathogen traits across 15 mosquito species. Using this data, we employed Bayesian hierarchical models to estimate temperature response functions for each trait and estimate their variation between species and experiments. We incorporate the resulting functions into mathematical models to estimate the temperature sensitivity of WNV transmission, focusing on six competent mosquito species of the genus Culex. Our study finds similarities in the temperature response among Culex species, with a general optimal transmission temperature around 24{degrees}C. We demonstrate that differing mechanistic assumptions in published models can result in a temperature optimum variation exceeding 3{degrees}C, underscoring the need for model scrutiny. Additionally, we identify substantial variability between trait temperature responses across experiments on the same mosquito species, indicating significant intra-species variation in trait performance. We provide recommendations for future experimental studies, emphasizing the critical need for additional data on all mosquito-pathogen traits, except for mosquito larva-to-adult development rate and survival, which are relatively well-documented. Incorporating additional data into our multi-species approach enhances the accuracy of temperature trait response estimates. These improvements are critical for forecasting future shifts in mosquito-borne disease risk due to climate change.

ecology↗

bioRxiv2021

RTK-dependent inducible degradation of mutant PI3K alpha drives GDC-0077 (Inavolisib) efficacy

PIK3CA is one of the most frequently mutated oncogenes; the p110 protein it encodes plays a central role in tumor cell proliferation and survival. Small molecule inhibitors targeting the PI3K p110 catalytic subunit have entered clinical trials, with early-phase GDC-0077 (Inavolisib) studies showing anti-tumor activity and a manageable safety profile in patients with PIK3CA-mutant, hormone receptor-positive breast cancer as a single agent or in combination therapy. Despite this, preclinical studies have shown that PI3K pathway inhibition releases negative feedback and activates receptor tyrosine kinase signaling, reengaging the pathway and attenuating drug activity. Here we discover that GDC-0077 and taselisib more potently inhibit mutant PI3K pathway signaling and cell viability through unique HER2-dependent degradation. Both are more effective than other PI3K inhibitors at maintaining prolonged pathway suppression, resulting in enhanced apoptosis and greater efficacy. This unique mechanism against mutant p110 reveals a new strategy for creating inhibitors that specifically target mutant tumors with selective degradation of the mutant oncoprotein and also provide a strong rationale for pursuing PI3K degraders in patients with HER2-positive breast cancer.

cancer biology↗

bioRxiv2021

Absolute quantification and single-cell dose-response of cytosolic siRNA delivery

Endosomal escape and subsequent cytosolic delivery of small inhibitory RNA (siRNA) therapeutics is believed to be highly inefficient. Since, it has not been possible to quantify cytosolic amounts of delivered siRNA at therapeutic doses, determination of delivery bottlenecks and total efficiency has been difficult. Here, we present a confocal microscopy-based method to detect cytosolic delivery of fluorescently labelled siRNA during lipid-mediated delivery. This method enables detection and quantification of sub-nanomolar cytosolic siRNA release amounts from individual release events with measures of quantitation confidence for each event. Single-cell kinetics of siRNA-mediated knockdown in cells expressing destabilized eGFP unveiled a dose-response relationship with respect to knockdown induction, depth and duration in the range from several hundred to thousands of cytosolic siRNA molecules. Accurate quantification of cytosolic siRNA, and the establishment of the intracellular dose-response relationships, will aid the development and characterization of novel delivery strategies for nucleic acid therapeutics.

cell biology↗

bioRxiv2019

Ghost QTL and hotspots in experimental crosses - novel solution by mixed model with nonzero mean

\"Ghost-QTL\" are the false discoveries in QTL mapping, that arise due to the \"accumulation\" of the polygenic effects, uniformly distributed over the genome. The locations on the chromosome which are strongly correlated with the summary polygenic effect depend on a specific sample correlation structure determined by the genotype at all loci. During the analysis of e-QTL data or recombinant inbred lines this correlation structure is preserved for all traits under consideration, and may lead to the so called \"hot-spots\" via the detection of the summary polygenic effect at exactly the same positions for most of the considered traits. We illustrate that the problem can be solved by the application of the extended mixed effect model, where the random effects are allowed to have a nonzero mean. We provide formulas for estimating the thresholds for the corresponding t-test statistics and use them in the stepwise selection strategy, which allows for a simultaneous detection of several QTL. Extensive simulation studies illustrate that our approach allows to eliminate ghost-QTL/false hot spot effects, while preserving a high power of detection of true QTL effects.

genetics↗