instruction:
In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.
question:
The baculovirus expression vector system (BEVS) is a versatile and powerful platform for protein expression in insect cells. With the ability to approach similar post-translational modifications as in mammalian cells, the BEVS offers a number of advantages including high levels of expression as well as an inherent safety during manufacture and of the final product. Many BEVS products include proteins and protein complexes that require expression from more than one gene. This review examines the expression strategies that have been used to this end and focuses on the distinguishing features between those that make use of single polycistronic baculovirus (co-expression) and those that use multiple monocistronic baculoviruses (co-infection). Three major areas in which researchers have been able to take advantage of co-expression/co-infection are addressed, including compound structure-function studies, insect cell functionality augmentation, and VLP production. The core of the review discusses the parameters of interest for co-infection and co-expression with time of infection (TOI) and multiplicity of infection (MOI) highlighted for the former and the choice of promoter for the latter. In addition, an overview of modeling approaches is presented, with a suggested trajectory for future exploration. The review concludes with an examination of the gaps that still remain in co-expression/co-infection knowledge and practice.
answer:
Co-expression vs. co-infection using baculovirus expression vectors in insect cell culture: Benefits and drawbacks


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We describe the first genome isolation of Middle East respiratory syndrome coronavirus (MERS-CoV) in Kenya. This fatal zoonotic pathogen was first described in the Kingdom of Saudi Arabia in 2012. Epidemiological and molecular evidence revealed zoonotic transmission from camels to humans and between humans. Currently, MERS-CoV is classified by the WHO as having high pandemic potential requiring greater surveillance. Previous studies of MERS-CoV in Kenya mainly focused on site-specific and archived camel and human serum samples for antibodies. We conducted active nationwide cross-sectional surveillance of camels and humans in Kenya, targeting both nasal swabs and plasma samples from 1,163 camels and 486 humans collected from January 2016 to June 2018. A total of 792 camel plasma samples were positive by ELISA. Seroprevalence increased with age, and the highest prevalence was observed in adult camels (82.37%, 95% confidence interval (CI) 79.50-84.91). More female camels were significantly seropositive (74.28%, 95% CI 71.14-77.19) than male camels (P \ 0.001) (53.74%, 95% CI 48.48-58.90). Only 11 camel nasal swabs were positive for MERS-CoV by reverse transcription-quantitative PCR. Phylogenetic analysis of whole genome sequences showed that Kenyan MERS-CoV clustered within sub-clade C2, which is associated with the African clade, but did not contain signature deletions of orf4b in African viruses. None of the human plasma screened contained neutralizing antibodies against MERS-CoV. This study confirms the geographically widespread occurrence of MERS-CoV in Kenyan camels. Further one-health surveillance approaches in camels, wildlife, and human populations are needed.
answer:
Genetic Evidence of Middle East Respiratory Syndrome Coronavirus (MERS-Cov) and Widespread Seroprevalence among Camels in Kenya


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As a key factor in endemic and epidemic dynamics, the geographical distribution of viruses has been frequently interpreted in the light of their genetic histories. Unfortunately, inference of historical dispersal or migration patterns of viruses has mainly been restricted to model-free heuristic approaches that provide little insight into the temporal setting of the spatial dynamics. The introduction of probabilistic models of evolution, however, offers unique opportunities to engage in this statistical endeavor. Here we introduce a Bayesian framework for inference, visualization and hypothesis testing of phylogeographic history. By implementing character mapping in a Bayesian software that samples time-scaled phylogenies, we enable the reconstruction of timed viral dispersal patterns while accommodating phylogenetic uncertainty. Standard Markov model inference is extended with a stochastic search variable selection procedure that identifies the parsimonious descriptions of the diffusion process. In addition, we propose priors that can incorporate geographical sampling distributions or characterize alternative hypotheses about the spatial dynamics. To visualize the spatial and temporal information, we summarize inferences using virtual globe software. We describe how Bayesian phylogeography compares with previous parsimony analysis in the investigation of the influenza A H5N1 origin and H5N1 epidemiological linkage among sampling localities. Analysis of rabies in West African dog populations reveals how virus diffusion may enable endemic maintenance through continuous epidemic cycles. From these analyses, we conclude that our phylogeographic framework will make an important asset in molecular epidemiology that can be easily generalized to infer biogeogeography from genetic data for many organisms.
answer:

Bayesian Phylogeography Finds Its Roots