Dataset Information

Monitoring Taiwanese bovine arboviruses and non-arboviruses using a vector-based approach.

ABSTRACT: In current sampling approaches, there exists a divergence between the surveillance of arthropod-borne and that of non-arthropod-borne viruses. It is commonly held that the collection of vector specimens applies only to arbovirus surveillance and that the surveillance of non-arboviruses must rely on traditional methods that involve the sampling of blood, faeces or saliva, or other examinations. The vector-based approach is a sampling method that has the ability to survey both arboviruses and non-arboviruses by distinguishing engorged vector specimens from entire vector samples. Accordingly, five arboviruses and three non-arboviruses were detected in a study using a vector-based approach conducted during 2012-2015. Hence, this report provides the first description of the Taiwanese vector species for the bovine arboviruses detected. The present investigations demonstrate that the vector-based approach applies not only to the surveillance of arboviruses, but also has potential as a possible tool for monitoring non-arboviruses on livestock farms in the future.

SUBMITTER: Tzeng HY

PROVIDER: S-EPMC7168380 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Monitoring Taiwanese bovine arboviruses and non-arboviruses using a vector-based approach.

Tzeng H-Y HY Wu H-H HH Ting L-J LJ Chang N-T NT Chou Y-C YC Tu W-C WC

Medical and veterinary entomology 20181128 2

In current sampling approaches, there exists a divergence between the surveillance of arthropod-borne and that of non-arthropod-borne viruses. It is commonly held that the collection of vector specimens applies only to arbovirus surveillance and that the surveillance of non-arboviruses must rely on traditional methods that involve the sampling of blood, faeces or saliva, or other examinations. The vector-based approach is a sampling method that has the ability to survey both arboviruses and non- ...[more]

PMID: 30488454

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Project description:BackgroundIn Japan, epizootic arboviral infections have severely impacted the livestock industry for a long period. Akabane, Aino, Chuzan, bovine ephemeral fever and Ibaraki viruses have repeatedly caused epizootic abnormal births and febrile illness in the cattle population. In addition, Peaton, Sathuperi, Shamonda and D'Aguilar viruses and epizootic hemorrhagic virus serotype 7 have recently emerged in Japan and are also considered to be involved in abnormal births in cattle. The above-mentioned viruses are hypothesized to circulate in tropical and subtropical Asia year round and to be introduced to temperate East Asia by long-distance aerial dispersal of infected vectors. To watch for arbovirus incursion and assess the possibility of its early warning, monitoring for arboviruses was conducted in the Yaeyama Islands, located at the most southwestern area of Japan, between 1994 and 2014.ResultsBlood sampling was conducted once a year, in the autumn, in 40 to 60 healthy cattle from the Yaeyama Islands. Blood samples were tested for arboviruses. A total of 33 arboviruses including Akabane, Peaton, Chuzan, D' Aguilar, Bunyip Creek, Batai and epizootic hemorrhagic viruses were isolated from bovine blood samples. Serological surveillance for the bovine arboviruses associated with cattle diseases in young cattle (ages 6-12 months: had only been alive for one summer) clearly showed their frequent incursion into the Yaeyama Islands. In some cases, the arbovirus incursions could be detected in the Yaeyama Islands prior to their spread to mainland Japan.ConclusionsWe showed that long-term surveillance in the Yaeyama Islands could estimate the activity of bovine arboviruses in neighboring regions and may provide a useful early warning for likely arbovirus infections in Japan. The findings in this study could contribute to the planning of prevention and control for bovine arbovirus infections in Japan and cooperative efforts among neighboring countries in East Asia.

Project description:Cell-to-cell fusion can be quantified by endowing acceptor and donor cells with latent reporter genes/proteins and activators of these genes/proteins, respectively. One way to accomplish this goal is by using a bipartite lentivirus vector (LV)-based cell fusion assay system in which the cellular fusion partners are transduced with a flippase-activatable Photinus pyralis luciferase (PpLuc) expression unit (acceptor cells) or with a recombinant gene encoding FLPeNLS+, a nuclear-targeted and molecularly evolved version of flippase (donor cells). Fusion of both cell populations will lead to the FLPe-dependent generation of a functional PpLuc gene. PpLuc activity is typically measured in cell lysates, precluding consecutive analysis of one cell culture. Therefore, in this study the PpLuc-coding sequence was replaced by that of Gaussia princeps luciferase (GpLuc), a secretory protein allowing repeated analysis of the same cell culture. In myotubes the spread of FLPeNLS+ may be limited due to its nuclear localization signal (NLS) causing low signal outputs. To test this hypothesis, myoblasts were transduced with LVs encoding either FLPeNLS+ or an NLS-less version of FLPe (FLPeNLS-) and subsequently co-cultured in different ratios with myoblasts containing the FLPe-activatable GpLuc expression cassette. At different times after induction of cell-to-cell fusion the GpLuc activity in the culture medium was determined. FLPeNLS+ and FLPeNLS- both activated the latent GpLuc gene but when the percentage of FLPe-expressing myoblasts was limiting, FLPeNLS+ generally yielded slightly higher signals than FLPeNLS- while at low acceptor-to-donor cell ratios FLPeNLS- was usually superior. The ability of FLPeNLS+ to spread through myofibers and to induce reporter gene expression is thus not limited by its NLS. However, at high FLPe concentrations the presence of the NLS negatively affected reporter gene expression. In summary, a rapid and simple chemiluminescence assay for quantifying cell-to-cell fusion progression based on GpLuc has been developed.

Project description:Monitoring the presence and movements of individuals or crowds in a given area can provide valuable insight into actual behavior patterns and hidden trends. Therefore, it is crucial in areas such as public safety, transportation, urban planning, disaster and crisis management, and mass events organization, both for the adoption of appropriate policies and measures and for the development of advanced services and applications. In this paper, we propose a non-intrusive privacy-preserving detection of people's presence and movement patterns by tracking their carried WiFi-enabled personal devices, using the network management messages transmitted by these devices for their association with the available networks. However, due to privacy regulations, various randomization schemes have been implemented in network management messages to prevent easy discrimination between devices based on their addresses, sequence numbers of messages, data fields, and the amount of data contained in the messages. To this end, we proposed a novel de-randomization method that detects individual devices by grouping similar network management messages and corresponding radio channel characteristics using a novel clustering and matching procedure. The proposed method was first calibrated using a labeled publicly available dataset, which was validated by measurements in a controlled rural and a semi-controlled indoor environment, and finally tested in terms of scalability and accuracy in an uncontrolled crowded urban environment. The results show that the proposed de-randomization method is able to correctly detect more than 96% of the devices from the rural and indoor datasets when validated separately for each device. When the devices are grouped, the accuracy of the method decreases but is still above 70% for rural environments and 80% for indoor environments. The final verification of the non-intrusive, low-cost solution for analyzing the presence and movement patterns of people, which also provides information on clustered data that can be used to analyze the movements of individuals, in an urban environment confirmed the accuracy, scalability and robustness of the method. However, it also revealed some drawbacks in terms of exponential computational complexity and determination and fine-tuning of method parameters, which require further optimization and automation.

Dataset Information

Monitoring Taiwanese bovine arboviruses and non-arboviruses using a vector-based approach.

Publications

Monitoring Taiwanese bovine arboviruses and non-arboviruses using a vector-based approach.

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