Temporal dynamics of the bat wing transcriptome: Insight into gene-expression changes that enable protection against pathogen

Skin acts as a mechanical barrier between the body and its surrounding environment and plays an important role in resistance to pathogens. However, we still know little regarding skin responses to physiological changes, particularly with regard to responses against potential pathogens. We herein executed RNA-seq on the wing of the Rhinolophus ferrumequinum to assess gene-expression variations at four physiological stages: pre-hibernation, hibernation (early-hibernation and late-hibernation), and post-hibernation, as well as the gene-expression patterns of infected and uninfected bats with the Pseudogymnoascus destructans (Pd). Our results showed that a greater number of differentially expressed genes between the more disparate physiological stages. Functional enrichment analysis showed that the down-regulated response pathways in hibernating bats included phosphorus metabolism and immune response, indicating metabolic suppression and decreased whole immune function. We also found up-regulated genes in post-hibernating bats that included C-type lectin receptor signalling, Toll-like receptor signalling pathway, and cell adhesion, suggesting that the immune response and skin integrity of the wing were improved after bats emerged from their hibernation and that this facilitated clearing Pd from the integument. Additionally, we found that the genes involved in cytokine or chemokine activity were up-regulated in late-hibernation compared to early-hibernation and that FOSB regulation of immune cell activation was differentially expressed in bats infected with Pd during late-hibernation, implying that the host's innate immune function was enhanced during late-hibernation so as to resist pathogenic infection. Our findings highlight the concept that maintenance of intrinsic immunity provides protection against pathogenic infections in highly resistant bats.

Sarbecoviruses of British horseshoe bats; sequence variation and epidemiology

Horseshoe bats are the natural hosts of the Sarbecovirus subgenus that includes SARS-CoV and SARS-CoV- 2. Despite the devastating impact of the COVID-19 pandemic, there is still little known about the underlying epidemiology and virology of sarbecoviruses in their natural hosts, leaving large gaps in our pandemic preparedness. Here we describe the results of PCR testing for sarbecoviruses in the two horseshoe bat species (Rhinolophus hipposideros and R. ferrumequinum) present in Great Britain, collected in 2021-22 during the peak of COVID-19 pandemic. One hundred and ninety seven R. hipposideros samples from 33 roost sites and 277 R. ferrumequinum samples from 20 roost sites were tested. No coronaviruses were detected in any samples from R. ferrumequinum whereas 44 and 56 % of individual and pooled (respectively) faecal samples from R. hipposideros across multiple roost sites tested positive in a sarbecovirus-specific qPCR. Full genome sequences were generated from three of the positive samples (and partial genomes from two more) using Illumina RNAseq on unenriched samples. Phylogenetic analyses showed that the obtained sequences belong to the same monophyletic clade, with >95 % similarity to previously-reported European isolates from R. hipposideros. The sequences differed in the presence or absence of accessory genes ORF 7b, 9b and 10. All lacked the furin cleavage site of SARS-CoV-2 spike gene and are therefore unlikely to be infective for humans. These results demonstrate a lack, or at least low incidence, of SARS-CoV-2 spill over from humans to susceptible GB bats, and confirm that sarbecovirus infection is widespread in R. hipposideros. Despite frequently sharing roost sites with R. ferrumequinum, no evidence of cross-species transmission was found.

What drives bat activity at field boundaries?

Field boundaries are important habitat for bats in agricultural landscapes, serving as commuting and foraging areas for many species. The goal of our study was to better understand the drivers of bat activity in agricultural landscapes to inform conservation policy and make specific recommendations for habitat management. We placed sixty-four full spectrum bat detectors at random recording locations, weekly, along field boundaries in North Somerset between July and October 2020. We used an automated classifier to analyse recordings and performed error rate modelling to account for and remove the majority of error in automated classifications. We used generalised additive models to explore bat response to recording location metrics, controlling for spatial-autocorrelation and temporal differences in sampling. We validated our models with k-fold cross-validation and explored the utility of our models for predicting bat activity at new sites. We found that field boundary characteristics better describe bat activity than adjacent field characteristics or measures of local landscape for the majority of species studied. Bat activity was higher along tall, wide, vegetated field boundaries containing trees; there was lower activity at arable recording locations. Still, bat activity was highly variable and predictive error was high. We found a large spatial effect driving activity patterns, meaning models are not able to predict activity beyond the extent of the study area. We recommend management strategies that give incentives to farmers for replacing fences with hedgerows, planting hedgerow trees, and maintaining tall and outgrown field boundaries.

Habitat Associations of Bats in an Agricultural Landscape: Linear Features Versus Open Habitats

1. Bats are important components of agricultural ecosystems. However, little is known about the extent to which bats use linear features when foraging and commuting in agricultural settings, when compared to the interior of fields. 2. As part of a large-scale citizen science project, bat detectors were placed in the centre of agricultural fields (arable and pasture) and along linear features (intensively managed hedgerows, sympathetically managed hedgerows and treelines). 3. Our results show that all 10 of the bat species groups identified were found both along linear features and in the middle of agricultural fields. Of the five species groups analysed further, all had significantly more bat activity along linear features compared to the middle of fields, except for Nyctalus noctula. However, our results showed that 29% of calls from Rhinolophus ferrumequinum were recorded in the middle of agricultural fields, compared to only 10% for Pipistrellus pipistrellus. Bat activity was more likely to be associated with treelines compared to other linear feature types. 4. Our results highlight the importance of linear feature management to bat conservation, but also the need to consider field centres during survey design and Environmental Impact Assessments.

Traffic noise playback reduces the activity and feeding behaviour of free-living bats

Increasing levels of road noise are creating new anthropogenic soundscapes that may affect wildlife globally. Bats, which form about a third of all mammal species, are sensitive bioindicators, and may be particularly vulnerable because of their dependency on echolocation. Here we present the first controlled field experiment with free-living bats. Using a Before-After-Control-Impact phantom road experimental design, we examine the impacts of traffic noise on their activity and feeding behaviour. Disentangling the impacts of traffic noise from other co-varying exposures such as habitat quality, the experiment demonstrates a significant negative effect on the activity of each of the five, ecologically different, species (genus for Myotis spp.) examined. This suggests that the results are widely applicable. The negative effects are largely attributable to noise in the sonic spectrum, which elicited aversive responses in all bat species tested,whereas responses to ultrasoundwere restricted to a single species. Our findings demonstrate that traffic noise can affect bat activity at least 20m away from the noise source. For Pipistrellus pipistrellus and Pipistrellus pygmaeus, feeding behaviour, as well as overall activity, was negatively affected. Ecological Impact Assessments are therfore needed wherever there are significant increases in traffic flow, and not just when new roads are built. Further research is required to identify effective mitigation strategies, to delineate the zone of influence of road noise, and to assess whether there is any habituation over time.

Comparing context-dependent call sequences employing machine learning methods: an indication of syntactic structure of greater horseshoe bats

For analysis of vocal syntax, accurate classification of call sequence structures in different behavioural contexts is essential. However, an effective, intelligent program for classifying call sequences from numerous recorded sound files is still lacking. Here, we employed three machine learning algorithms (logistic regression, support vector machine and decision trees) to classify call sequences of social vocalizations of greater horseshoe bats (Rhinolophus ferrumequinum) in aggressive and distress contexts. The three machine learning algorithms obtained highly accurate classification rates (logistic regression 98%, support vector machine 97% and decision trees 96%). The algorithms also extracted three of the most important features for the classification: the transition between two adjacent syllables, the probability of occurrences of syllables in each position of a sequence, and the characteristics of a sequence. The results of statistical analysis also supported the classification of the algorithms. The study provides the first efficient method for data mining of call sequences and the possibility of linguistic parameters in animal communication. It suggests the presence of song-like syntax in the social vocalizations emitted within a non-breeding context in a bat species.

Seasonal Changes in Gut Microbiota Diversity and Composition in the Greater Horseshoe Bat

A large number of microorganisms colonize the intestines of animals. The gut microbiota plays an important role in nutrient metabolism and affects a number of physiological mechanisms in the host. Studies have shown that seasonal changes occur in the intestinal microbes of mammals that hibernate seasonally. However, these studies only focused on ground squirrels and bears. It remains unclear how hibernation might affect the intestinal microbes of bats. In this study, we measured microbial diversity and composition in the gut of Rhinolophus ferrumequinum in different periods (early spring, early summer, late summer, torpor, and interbout arousal) using 16S ribosomal RNA gene amplicon sequencing and PICRUSt to predict functional profiles. We found seasonal changes in the diversity and composition of the gut microbes in R. ferrumequinum. The diversity of gut microbiota was highest in the late summer and lowest in the early summer. The relative abundance of Proteobacteria was highest in the early summer and significantly lower in other periods. The relative abundance of Firmicutes was lowest in the early summer and significantly increased in the late summer, followed by a significant decrease in the early winter and early spring. The relative abundance of Tenericutes was significantly higher in the early spring compared with other periods. The results of functional prediction by PICRUSt showed seasonal variations in the relative abundance of metabolism-related pathways, including lipid metabolism, carbohydrate metabolism, and energy metabolism. Functional categories for carbohydrate metabolism had significantly lower relative abundance in early winter-torpor compared with late summer, while those associated with lipid metabolism had significantly higher relative abundance in the early winter compared with late summer. Overall, our results show that seasonal physiological changes associated with hibernation alter the gut microbial community of R. ferrumequinum. Hibernation may also alter the metabolic function of intestinal microbes, possibly by converting the gut microflora from carbohydrate-related to lipid-related functional categories. This study deepens our understanding of the symbiosis between hibernating mammals and gut microbes.

sequence divergence: comparative transcriptome sequencing among natural Rhinolophus ferrumequinum populations with different acoustic phenotypes

BACKGROUND

Although the sensory drive hypothesis can explain the geographic variation in echolocation frequencies of some bat species, the molecular mechanisms underlying this phenomenon are still unclear. The three lineages of greater horseshoe bat (Rhinolophus ferrumequinum) in China (northeast, central-east, and southwest) have significant geographic variation in resting frequencies (RF) of echolocation calls. Because their cochleae have an acoustic fovea that is highly sensitive to a narrow range of frequencies, we reported the transcriptomes of cochleae collected from three genetic lineages of R. ferrumequinum, which is an ideal organism for studying geographic variation in echolocation signals, and tried to understand the mechanisms behind this bat phenomenon by analyzing gene expression and sequence variation.

RESULTS

A total of 8190 differentially expressed genes (DEGs) were identified. We identified five modules from all DEGs that were significantly related to RF or forearm length (FL). DEGs in the RF-related modules were significantly enriched in the gene categories involved in neural activity, learning, and response to sound. DEGs in the FL-related modules were significantly enriched in the pathways related to muscle and actin functions. Using 21,945 single nucleotide polymorphisms, we identified 18 candidate unigenes associated with hearing, five of which were differentially expressed among the three populations. Additionally, the gene ERBB4, which regulates diverse cellular processes in the inner ear such as cell proliferation and differentiation, was in the largest module. We also found 49 unigenes that were under positive selection from 4105 one-to-one orthologous gene pairs between the three R. ferrumequinum lineages and three other Chiroptera species.

CONCLUSIONS

The variability of gene expression and sequence divergence at the molecular level might provide evidence that can help elucidate the genetic basis of geographic variation in echolocation signals of greater horseshoe bats.

Molecular identification of Betacoronavirus in bats from Sardinia (Italy): first detection and phylogeny

Bats may be natural reservoirs for a large variety of emerging viruses, including mammalian coronaviruses (CoV). The recent emergence of severe acute respiratory syndrome-associated coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) in humans, with evidence that these viruses may have their ancestry in bats, highlights the importance of virus surveillance in bat populations. Here, we report the identification and molecular characterization of a bat β-Coronavirus, detected during a viral survey carried out on different bat species in the island of Sardinia (Italy). Cutaneous, oral swabs, and faecal samples were collected from 46 bats, belonging to 15 different species, and tested for viral presence. Coronavirus RNA was detected in faecal samples from three different species: the greater horseshoe bat (Rhinolophus ferrumequinum), the brown long-eared bat (Plecotus auritus), and the European free-tailed bat (Tadarida teniotis). Phylogenetic analyses based on RNA-dependent RNA polymerase (RdRp) sequences assigned the detected CoV to clade 2b within betacoronaviruses, clustering with SARS-like bat CoVs previously reported. These findings point to the need for continued surveillance of bat CoV circulating in Sardinian bats, and extend the current knowledge on CoV ecology with novel sequences detected in bat species not previously described as β-Coronavirus hosts.