Spatiotemporal analysis of mycolactone distribution in vivo reveals partial diffusion in the central nervous system

Mycobacterium ulcerans, the causative agent of Buruli ulcer (BU) disease, is unique amongst human pathogens in its capacity to produce a lipid toxin called mycolactone. While previous studies have demonstrated that bacterially-released mycolactone diffuses beyond infection foci, the spatiotemporal distribution of mycolactone remained largely unknown. Here, we used the zebrafish model to provide the first global kinetic analysis of mycolactone’s diffusion in vivo, and multicellular co-culture systems to address the critical question of the toxin’s access to the brain.Zebrafish larvae were injected with a fluorescent-derivative of mycolactone to visualize the in vivo diffusion of the toxin from the peripheral circulation. A rapid, body-wide distribution of mycolactone was observed, with selective accumulation in tissues near the injection site and brain, together with an important excretion through the gastro-intestinal tract. Our conclusion that mycolactone reached the central nervous system was reinforced by an in cellulo model of human blood brain barrier and a mouse model of M. ulcerans-infection.Here we show that mycolactone has a broad but heterogenous profile of distribution in vivo. Our investigations in vitro and in vivo support the view that a fraction of bacterially-produced mycolactone gains access to the central nervous system. The relative persistence of mycolactone in the bloodstream suggests that assays of circulating mycolactone are relevant for BU disease monitoring and treatment optimization.     

Disentangling the assembly mechanisms of ant cuticular bacterial communities of two Amazonian ant species sharing a common arboreal nest

Bacteria living on the cuticle of ants are generally studied for their protective role against pathogens, especially in the clade of fungus‐growing ants. However, little is known regarding the diversity of cuticular bacteria in other ant host species, as well as the mechanisms leading to the composition of these communities. Here, we used 16S rRNA gene amplicon sequencing to study the influence of host species, species interactions and the pool of bacteria from the environment on the assembly of cuticular bacterial communities on two phylogenetically distant Amazonian ant species that frequently nest together inside the roots system of epiphytic plants, Camponotus femoratus and Crematogaster levior. Our results show that (a) the vast majority of the bacterial community on the cuticle is shared with the nest, suggesting that most bacteria on the cuticle are acquired through environmental acquisition, (b) 5.2% and 2.0% of operational taxonomic units (OTUs) are respectively specific to Ca. femoratus and Cr. levior, probably representing their respective core cuticular bacterial community, and (c) 3.6% of OTUs are shared between the two ant species. Additionally, mass spectrometry metabolomics analysis of metabolites on the cuticle of ants, which excludes the detection of cuticular hydrocarbons produced by the host, were conducted to evaluate correlations among bacterial OTUs and m/z ion mass. Although some positive and negative correlations are found, the cuticular chemical composition was weakly species‐specific, suggesting that cuticular bacterial communities are prominently environmentally acquired. Overall, our results suggest the environment is the dominant source of bacteria found on the cuticle of ants.     

The phylogenetic range of bacterial and viral pathogens of vertebrates

Many major human pathogens are multihost pathogens, able to infect other vertebrate species. Describing the general patterns of host–pathogen associations across pathogen taxa is therefore important to understand risk factors for human disease emergence. However, there is a lack of comprehensive curated databases for this purpose, with most previous efforts focusing on viruses. Here, we report the largest manually compiled host–pathogen association database, covering 2,595 bacteria and viruses infecting 2,656 vertebrate hosts. We also build a tree for host species using nine mitochondrial genes, giving a quantitative measure of the phylogenetic similarity of hosts. We find that the majority of bacteria and viruses are specialists infecting only a single host species, with bacteria having a significantly higher proportion of specialists compared to viruses. Conversely, multihost viruses have a more restricted host range than multihost bacteria. We perform multiple analyses of factors associated with pathogen richness per host species and the pathogen traits associated with greater host range and zoonotic potential. We show that factors previously identified as important for zoonotic potential in viruses—such as phylogenetic range, research effort, and being vector‐borne—are also predictive in bacteria. We find that the fraction of pathogens shared between two hosts decreases with the phylogenetic distance between them. Our results suggest that host phylogenetic similarity is the primary factor for host‐switching in pathogens.     

Reproductives and eggs trigger worker vibration in a subterranean termite

In insect societies, the presence of reproductives or eggs has been shown to shape several biological traits in the colony members. Social interactions are one of these traits that involve modification of the communication system of the entire colony. Many studies described the role of chemical compounds and dominance behaviors in the presence of reproductive but vibratory behaviors received very few investigations. Yet, vibratory behaviors are ideal candidates, particularly for subterranean species like termites, as they could be quickly transmitted through the substrate and could be very diversified (origin, modulation). Here, we investigated whether the presence of reproductives/eggs affects the vibratory behavior (body‐shaking) of workers in the subterranean termite Reticulitermes flavipes. Our results reveal that the presence of reproductives or eggs triggers an increase of workers' body‐shaking, independent of their colony of origin after 24 hr. We hypothesize that vibratory communication could be used to transfer information about the presence of reproductives and eggs to the entire colony, suggesting that vibratory behaviors could serve as an important yet neglected mediator of social regulation.     

Contrasting Gene Decay in Subterranean Vertebrates: Insights from Cavefishes and Fossorial Mammals

Evolution sometimes proceeds by loss, especially when structures and genes become dispensable after an environmental shift relaxes functional constraints. Subterranean vertebrates are outstanding models to analyze this process, and gene decay can serve as a readout. We sought to understand some general principles on the extent and tempo of the decay of genes involved in vision, circadian clock, and pigmentation in cavefishes. The analysis of the genomes of two Cuban species belonging to the genus Lucifuga provided evidence for the largest loss of eye-specific genes and nonvisual opsin genes reported so far in cavefishes. Comparisons with a recently evolved cave population of Astyanax mexicanus and three species belonging to the Chinese tetraploid genus Sinocyclocheilus revealed the combined effects of the level of eye regression, time, and genome ploidy on eye-specific gene pseudogenization. The limited extent of gene decay in all these cavefishes and the very small number of loss-of-function mutations per pseudogene suggest that their eye degeneration may not be very ancient, ranging from early to late Pleistocene. This is in sharp contrast with the identification of several vision genes carrying many loss-of-function mutations in ancient fossorial mammals, further suggesting that blind fishes cannot thrive more than a few million years in cave ecosystems.     

Convolutional neural networks improve species distribution modelling by capturing the spatial structure of the environment

Convolutional Neural Networks (CNNs) are statistical models suited for learning complex visual patterns. In the context of Species Distribution Models (SDM) and in line with predictions of landscape ecology and island biogeography, CNN could grasp how local landscape structure affects prediction of species occurrence in SDMs. The prediction can thus reflect the signatures of entangled ecological processes. Although previous machine-learning based SDMs can learn complex influences of environmental predictors, they cannot acknowledge the influence of environmental structure in local landscapes (hence denoted “punctual models”). In this study, we applied CNNs to a large dataset of plant occurrences in France (GBIF), on a large taxonomical scale, to predict ranked relative probability of species (by joint learning) to any geographical position. We examined the way local environmental landscapes improve prediction by performing alternative CNN models deprived of information on landscape heterogeneity and structure (“ablation experiments”). We found that the landscape structure around location crucially contributed to improve predictive performance of CNN-SDMs. CNN models can classify the predicted distributions of many species, as other joint modelling approaches, but they further prove efficient in identifying the influence of local environmental landscapes. CNN can then represent signatures of spatially structured environmental drivers. The prediction gain is noticeable for rare species, which open promising perspectives for biodiversity monitoring and conservation strategies. Therefore, the approach is of both theoretical and practical interest. We discuss the way to test hypotheses on the patterns learnt by CNN, which should be essential for further interpretation of the ecological processes at play.