From islands to infectomes: host-specific viral diversity among birds across remote islands.

BACKGROUND: Accelerating biodiversity loss necessitates monitoring the potential pathogens of vulnerable species. With a third of New Zealand's avifauna considered at risk of extinction, a greater understanding of the factors that influence microbial transmission in this island ecosystem is needed. We used metatranscriptomics to determine the viruses, as well as other microbial organisms (i.e. the infectomes), of seven bird species, including the once critically endangered black robin (Petroica traversi), on two islands in the remote Chatham Islands archipelago, New Zealand. RESULTS: We identified 19 likely novel avian viruses across nine viral families. Black robins harboured viruses from the Flaviviridae, Herpesviridae, and Picornaviridae, while introduced starlings (Sturnus vulgaris) and migratory seabirds (Procellariiformes) carried viruses from six additional viral families. Potential cross-species virus transmission of a novel passerivirus (family: Picornaviridae) between native (black robins and grey-backed storm petrels) and introduced (starlings) birds was also observed. Additionally, we identified bacterial genera, apicomplexan parasites, as well as a novel megrivirus linked to disease outbreaks in other native New Zealand birds. Notably, island effects were outweighed by host taxonomy as a significant driver of viral composition, even among sedentary birds. CONCLUSIONS: These findings underscore the value of surveillance of avian populations to identify and minimise escalating threats of disease emergence and spread in these island ecosystems. Importantly, they contribute to our understanding of the potential role of introduced and migratory birds in the transmission of microbes and associated diseases, which could impact vulnerable island-endemic species.

A novel gyrovirus is abundant in yellow-eyed penguin (Megadyptes antipodes) chicks with a fatal respiratory disease.

Yellow-eyed penguins (Megadyptes antipodes), or hoiho in te reo Maori, are predicted to become extinct on mainland Aotearoa New Zealand in the next few decades, with infectious disease a significant contributor to their decline. A recent disease phenomenon termed respiratory distress syndrome (RDS) causing lung pathology has been identified in very young chicks. To date, no causative pathogens for RDS have been identified. In 2020 and 2021, the number of chick deaths from suspected RDS increased four- and five-fold, respectively, causing mass mortality with an estimated mortality rate of >90%. We aimed to identify possible pathogens responsible for RDS disease impacting these critically endangered yellow-eyed penguins. Total RNA was extracted from tissue samples collected during post-mortem of 43 dead chicks and subject to metatranscriptomic sequencing and histological examination. From these data we identified a novel and highly abundant gyrovirus (Anelloviridae) in 80% of tissue samples. This virus was most closely related to Gyrovirus 8 discovered in a diseased seabird, while other members of the genus Gyrovirus include Chicken anaemia virus, which causes severe disease in juvenile chickens. No other exogenous viral transcripts were identified in these tissues. Due to the high relative abundance of viral reads and its high prevalence in diseased animals, it is likely that this novel gyrovirus is associated with RDS in yellow-eyed penguin chicks.

Effect of habitat degradation on hantavirus infection among introduced and endemic small mammals of Madagascar.

Hantaviruses are globally distributed zoonotic pathogens capable of causing fatal disease in humans. Rodents and other small mammals are the typical reservoirs of hantaviruses, though the particular host varies regionally. Addressing the risk of hantavirus spillover from animal reservoirs to humans requires identifying the local mammal reservoirs and the predictors of infection in those animals, such as their population density and habitat characteristics. We screened native and non-native small mammals and bats in northeastern Madagascar for hantavirus infection to investigate the influence of habitat, including effects of human land use on viral prevalence. We trapped 227 bats and 1663 small mammals over 5 successive years in and around Marojejy National Park across a range of habitat types including villages, agricultural fields, regrowth areas, and secondary and semi-intact forests. Animals sampled included endemic tenrecs (Tenrecidae), rodents (Nesomyidae) and bats (6 families), along with non-native rodents (Muridae) and shrews (Soricidae). A hantavirus closely related to the previously described Anjozorobe virus infected 9.5% of Rattus rattus sampled. We did not detect hantaviruses in any other species. Habitat degradation had a complex impact on hantavirus prevalence in our study system: more intensive land use increase the abundance of R. rattus. The average body size of individuals varied between agricultural and nonagricultural land-use types, which in turn affected infection prevalence. Smaller R.rattus had lower probability of infection and were captured more commonly in villages and forests. Thus, infection prevalence was highest in agricultural areas. These findings provide new insights to the gradients of hantavirus exposure risk for humans in areas undergoing rapid land use transformations associated with agricultural practices.

Multiple Instances QoS Routing in RPL: Application to Smart Grids.

The Smart Grid (SG) aims to transform the current electric grid into a "smarter" network where the integration of renewable energy resources, energy efficiency and fault tolerance are the main benefits. This is done by interconnecting every energy source, storage point or central control point with connected devices, where heterogeneous SG applications and signalling messages will have different requirements in terms of reliability, latency and priority. Hence, data routing and prioritization are the main challenges in such networks. So far, RPL (Routing Protocol for Low-Power and Lossy networks) protocol is widely used on Smart Grids for distributing commands over the grid. RPL assures traffic differentiation at the network layer in wireless sensor networks through the logical subdivision of the network in multiple instances, each one relying on a specific Objective Function. However, RPL is not optimized for Smart Grids, as its main objective functions and their associated metric does not allow Quality of Service differentiation. To overcome this, we propose OFQS an objective function with a multi-objective metric that considers the delay and the remaining energy in the battery nodes alongside with the dynamic quality of the communication links. Our function automatically adapts to the number of instances (traffic classes) providing a Quality of Service differentiation based on the different Smart Grid applications requirements. We tested our approach on a real sensor testbed. The experimental results show that our proposal provides a lower packet delivery latency and a higher packet delivery ratio while extending the lifetime of the network compared to solutions in the literature.