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Spatio-temporal patterns of the spread of infectious diseases are commonly driven by environmental and ecological factors. This is particularly true for vector-borne diseases because vector populations can be strongly affected by host distribution as well as by climatic and landscape variables. Here, we aim to identify environmental drivers for bluetongue virus (BTV), the causative agent of a major vector-borne disease of ruminants that has emerged multiple times in Europe in recent decades. In order to determine the importance of climatic, landscape and host-related factors affecting BTV diffusion across Europe, we fitted different phylogeographic models to a dataset of 113 time-stamped and geo-referenced BTV genomes, representing multiple strains and serotypes. Diffusion models using continuous space revealed that terrestrial habitat below 300 m altitude, wind direction and higher livestock densities were associated with faster BTV movement. Results of discrete phylogeographic analysis involving generalized linear models broadly supported these findings, but varied considerably with the level of spatial partitioning. Contrary to common perception, we found no evidence for average temperature having a positive effect on BTV diffusion, though both methodological and biological reasons could be responsible for this result. Our study provides important insights into the drivers of BTV transmission at the landscape scale that could inform predictive models of viral spread and have implications for designing control strategies.

During wounding, tissues are disrupted so that bacteria can easily enter the host and trigger a host response. Both the host response and bacterial communication can occur through quorum sensing (QS) and quorum sensing inhibition (QSI). Here, we characterize the effect of wounding on the host-associated bacterial community of the bed bug. This is a model system where the male is wounding the female during every mating. Whereas several aspects of the microbial involvement during wounding have been previously examined, it is not clear to what extent QS and QSI play a role. We find that the microbiome differs depending on mating and feeding status of female bedbugs and is specific to the location of isolation. Most organs of bedbugs harbor bacteria, which are capable of both QS and QSI signaling. By focusing on the prokaryotic quorum communication system, we provide a baseline for future research in this unique system. We advocate the bedbug system as suitable for studying the effects of bacteria on reproduction and for addressing prokaryote and eukaryote communication during wounding.

The marine silicon cycle is intrinsically linked with carbon cycling in the oceans via biological production of silica by a wide range of organisms. The stable silicon isotopic composition (denoted by δ30Si) of siliceous microfossils extracted from sediment cores can be used as an archive of past oceanic silicon cycling. However, the silicon isotopic composition of biogenic silica has only been measured in diatoms, sponges and radiolarians, and isotopic fractionation relative to seawater is entirely unknown for many other silicifiers. Furthermore, the biochemical pathways and mechanisms that determine isotopic fractionation during biosilicification remain poorly understood. Here, we present the first measurements of the silicon isotopic fractionation during biosilicification by loricate choanoflagellates, a group of protists closely related to animals. We cultured two species of choanoflagellates, Diaphanoeca grandis and Stephanoeca diplocostata, which showed consistently greater isotopic fractionation (approximately −5 ‰ to −7 ‰) than cultured diatoms (−0.5 ‰ to −2.1 ‰). Instead, choanoflagellate silicon isotopic fractionation appears to be more similar to sponges grown under similar dissolved silica concentrations. Our results highlight that there is a taxonomic component to silicon isotope fractionation during biosilicification, possibly via a shared or related biochemical transport pathway. These findings have implications for the use of biogenic silica δ30Si produced by different silicifiers as proxies for past oceanic change.