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The mosquito midgut functions as a key interface between pathogen and vector. However, studies of midgut physiology and virus infection dynamics are scarce, and inCulex tarsalis—an extremely efficient vector of West Nile virus (WNV)—nonexistent. We performed single-cell RNA sequencing onCx. tarsalismidguts, defined multiple cell types, and determined whether specific cell types are more permissive to WNV infection. We identified 20 cell states comprising 8 distinct cell types, consistent with existing descriptions ofDrosophilaandAedes aegyptimidgut physiology. Most midgut cell populations were permissive to WNV infection. However, there were higher levels of WNV RNA (vRNA) in enteroendocrine cells (EE), suggesting enhanced replication in this population. In contrast, proliferating intestinal stem cells (ISC) had the lowest levels of vRNA, a finding consistent with studies suggesting ISC proliferation in the midgut is involved in infection control. ISCs were also found to have a strong transcriptional response to WNV infection; genes involved in ribosome structure and biogenesis, and translation were significantly downregulated in WNV-infected ISC populations. Notably, we did not detect significant WNV-infection induced upregulation of canonical mosquito antiviral immune genes (e.g.,AGO2,R2D2, etc.) at the whole-midgut level. Rather, we observed a significant positive correlation between immune gene expression levels and vRNA load in individual cells, suggesting that within midgut cells, high levels of vRNA may trigger antiviral responses. Our findings establish aCx. tarsalismidgut cell atlas, and provide insight into midgut infection dynamics of WNV by characterizing cell-type specific enhancement/restriction of, and immune response to, infection at the single-cell level. 

Abstract Climate change has the potential to disrupt species interactions across global ecosystems. Ectotherm–endotherm interactions may be especially prone to this risk due to the possible mismatch between the species in physiological response and performance. However, few studies have examined how changing temperatures might differentially impact species' niches or available suitable habitat when they have very different modes of thermoregulation. An ideal system for studying this interaction is the predator–prey system. In this study, we used ecological niche modeling to characterize the niche overlap and examine biogeography in past and future climate conditions of prairie rattlesnakes (Crotalus viridis) and Ord's kangaroo rats (Dipodomys ordii), an endotherm–ectotherm pair typifying a predator–prey species interaction. Our models show a high niche overlap between these two species (D = 0.863 andI = 0.979) and further affirm similar paleoecological distributions during the last glacial maximum (LGM) and mid‐Holocene (MH). Under future climate change scenarios, we found that prairie rattlesnakes may experience a reduction in overall suitable habitat (RCP 2.6 = −1.82%, 4.5 = −4.62%, 8.5 = −7.34%), whereas Ord's kangaroo rats may experience an increase (RCP 2.6 = 9.8%, 4.5 = 11.71%, 8.5 = 8.37%). We found a shared trend of stable suitable habitat at northern latitudes but reduced suitability in southern portions of the range, and we propose future monitoring and conservation be focused on those areas. Overall, we demonstrate a biogeographic example of how interacting ectotherm–endotherm species may have mismatched responses under climate change scenarios and the models presented here can serve as a starting point for further investigation into the biogeography of these systems. 

Abstract Background Many snakes are low-energy predators that use crypsis to ambush their prey. Most of these species feed very infrequently, are sensitive to the presence of larger vertebrates, such as humans, and spend large portions of their lifetime hidden. This makes direct observation of feeding behaviour challenging, and previous methodologies developed for documenting predation behaviours of free-ranging snakes have critical limitations. Animal-borne accelerometers have been increasingly used by ecologists to quantify activity and moment-to-moment behaviour of free ranging animals, but their application in snakes has been limited to documenting basic behavioural states (e.g., active vs. non-active). High-frequency accelerometry can provide new insight into the behaviour of this important group of predators, and here we propose a new method to quantify key aspects of the feeding behaviour of three species of viperid snakes ( Crotalus spp.) and assess the transferability of classification models across those species. Results We used open-source software to create species-specific models that classified locomotion, stillness, predatory striking, and prey swallowing with high precision, accuracy, and recall. In addition, we identified a low cost, reliable, non-invasive attachment method for accelerometry devices to be placed anteriorly on snakes, as is likely necessary for accurately classifying distinct behaviours in these species. However, species-specific models had low transferability in our cross-species comparison. Conclusions Overall, our study demonstrates the strong potential for using accelerometry to document critical feeding behaviours in snakes that are difficult to observe directly. Furthermore, we provide an ‘end-to-end’ template for identifying important behaviours involved in the foraging ecology of viperids using high-frequency accelerometry. We highlight a method of attachment of accelerometers, a technique to simulate feeding events in captivity, and a model selection procedure using biologically relevant window sizes in an open-access software for analyzing acceleration data (AcceleRater). Although we were unable to obtain a generalized model across species, if more data are incorporated from snakes across different body sizes and different contexts (i.e., moving through natural habitat), general models could potentially be developed that have higher transferability. 

This work contributes to just and pro-social treatment of digital pieceworkers ("crowd collaborators") by reforming the handling of crowd-sourced labor in academic venues. With the rise in automation, crowd collaborators' treatment requires special consideration, as the system often dehumanizes crowd collaborators as components of the “crowd” [41]. Building off efforts to (proxy-)unionize crowd workers and facilitate employment protections on digital piecework platforms, we focus on employers: academic requesters sourcing machine learning (ML) training data. We propose a cover sheet to accompany submission of work that engages crowd collaborators for sourcing (or labeling) ML training data. The guidelines are based on existing calls from worker organizations (e.g., Dynamo [28]); professional data workers in an alternative digital piecework organization; and lived experience as requesters and workers on digital piecework platforms. We seek feedback on the cover sheet from the ACM community