Cruz, M. A. | bioRxiv Science

bioRxiv2020

Creating outbred and inbred populations of haplodiploid mites to measure adaptive responses in the lab

Laboratory studies are often criticized for not being representative of processes occurring in natural populations. This can be partially mitigated by using lab populations that capture large amounts of variation. Additionally, many studies addressing adaptation of organisms to their environment are done with laboratory populations, using quantitative genetics or experimental evolution methodologies. Such studies rely on populations that are either highly outbred or inbred. However, the methodology underlying the generation of such biological resources are usually not explicitly documented. Given their small size, short generation time, amenability to laboratory experimentation and knowledge of their ecological interactions, haplodiploid spider mites are becoming a widely used model organism. Here, we describe the creation of outbred populations of two species of spider mites, Tetranychus urticae and T. evansi, obtained by performing controlled crosses between individuals from field-collected populations. Subsequently, from the outbred population of T. evansi, we derived inbred lines, by performing several generations of sib-mating. These can be used to measure broad-sense heritability as well as correlations among traits. Finally, we outline an experimental evolution protocol that can be widely used in other systems. Sharing these biological resources with other laboratories and combining them with the available powerful genetic tools for T. urticae (and other species) will allow consistent and comparable studies that greatly contribute to our understanding of ecological and evolutionary processes.

evolutionary biology↗

bioRxiv2020

Discovery of a cryptic allosteric site in Ebola's 'undruggable' VP35 protein using simulations and experiments

Protein-protein and protein-nucleic acid interactions are often considered difficult drug targets because the surfaces involved lack obvious druggable pockets. Cryptic pockets could present opportunities for targeting these interactions, but identifying and exploiting these pockets remains challenging. Here, we apply a general pipeline for identifying cryptic pockets to the interferon inhibitory domain (IID) of Ebola viral protein 35 (VP35). VP35 plays multiple essential roles in Ebolas replication cycle but lacks pockets that present obvious utility for drug design. Using adaptive sampling simulations and machine learning algorithms, we predict VP35 harbors a cryptic pocket that is allosterically coupled to a key dsRNA-binding interface. Thiol labeling experiments corroborate the predicted pocket and mutating the predicted allosteric network supports our model of allostery. Finally, covalent modifications that mimic drug binding allosterically disrupt dsRNA binding that is essential for immune evasion. Based on these successes, we expect our pipeline is equally applicable to other proteins.

biochemistry↗