Molecular Evidence for the Association of Tomato leaf curl Gujarat virus with a Leaf Curl Disease of Phaseolus vulgaris L.

A leaf curl disease with symptoms typical of begomoviruses was observed in bean (Phaseolus vulgaris) at the Main Research Farm of the Indian Institute of Pulses Research, Kanpur, India. Infected plants had severe distortion of leaves and the plants were unproductive. PCR indicated the involvement of French bean leaf curl virus (JQ866297), a recently described Begomovirus, and Tomato leaf curl Gujarat virus (ToLCGV). The full‐length genome of ToLCGV associated with leaf curl disease of bean was 2757 nucleotides long and had maximum identity (97–98%) with seven isolates of ToLCGV (AY234383, AF449999, EU573714, GQ994098, AY190290, FR819708, AF413671) and is designated as Tomato leaf curl Gujarat virus‐(IN:Knp:Bean:2013) (KF440686). To the best of our knowledge, this is the first record of ToLCGV infecting a leguminous host, P. vulgaris.     

Molecular and Biological Analysis of Potato virus M (PVM) Isolates from the Czech Republic

The sequences of the 3′‐terminal region of four Czech Potato virus M isolates VIRUBRA 4/007, VIRUBRA 4/009, VIRUBRA 4/016 and VIRUBRA 4/035 were determined and compared with sequences of PVM isolates available in GenBank. Among the Czech isolates, VIRUBRA 4/007 and 4/016 as well as VIRUBRA 4/016 and 4/035 showed the highest nucleotide identity (93%). Isolates VIRUBRA 4/007, 4/016 and 4/035 were most similar to the PV0273 isolate from Germany and to the wild isolate from Russia. Interestingly, isolate VIRUBRA 4/009 significantly differed from the other three Czech isolates and was the only European isolate that showed the highest nucleotide identity with American isolates. Moreover, the PVM isolates from the Czech Republic and Germany differed in their host range. Phylogenetic analysis based on ORF5 coding for coat protein showed that the Czech isolates could be classified in two of the three groupings of the phylogenetic tree obtained. This is the first report on molecular and biological analysis of the genome sequences of PVM isolates from the Czech Republic.     

Molecular Detection and Characterization of Chinese Yam Mild Mosaic Virus Isolates

An improved RT‐PCR was developed and validated for the detection of Yam mild mosaic virus (YMMV). Sequences of the coat protein core region of 19 Chinese isolates were obtained, and analysis indicated the presence of different genetic variants. Phylogenetic analyses showed that the Chinese isolates were divided into two distinct clusters. Complete genomic sequences of two distinct Chinese variants were determined to be 9527 and 9529 nucleotides long, excluding the 3′ poly (A) tail. Their genomic structure and organization were virtually identical to that of a Brazilian isolate. The two variants shared identity of 87.3% to one another and 83.9–84.6% to the Brazilian variant at the genomic sequence level. Phylogenetic analyses supported that they represented two distinct YMMV lineages.     

Comparative Epidemiology of Three Virus Diseases on Zucchini Squash

Zucchini yellow mosaic virus (ZYMV), Papaya ringspot virus – type W (PRSV‐W) and Zucchini lethal chlorosis virus (ZLCV) cause important diseases on zucchini squash crops in Brazil. ZYMV and PRSV‐W belong to the genus Potyvirus and are transmitted by aphids, whereas ZLCV belongs to Tospovirus and is transmitted by the thrips Frankliniella zucchini. These three viruses may occur simultaneously in the field, and the epidemiology of the corresponding diseases may be determined by interactions among viruses, hosts and vectors. In this work, the progress of the diseases caused by these viruses was studied over a temporal and geographic range for three planting seasons (PS). For the lethal chlorosis (ZLCV), a monomolecular model was found to be the best fit for the data, though only during the third PS. For data collected during the first two PS, the Gompertz model was found to fit the data best. The spatial distribution of disease indicated disease aggregation at the end of the crop cycle. For the yellow mosaic (ZYMV), the model that best fit in the 1st PS was the logistic and in the 2nd and 3rd PS was monomolecular. The spatial pattern of the disease was random when the disease incidence was low but aggregated when the disease incidence was high. The common mosaic (PRSV‐W) showed the lowest incidence in all three PS. An exponential model was the best fit for data collected during all PS, and the spatial pattern of the disease was random. Interactions among the three viruses apparently did not result in changes in the epidemiology of the diseases. Removal of sources of inoculum and planting at an unfavourable time for reproduction of virus vectors are the two main measures recommended for the control of these diseases. The use of insecticide is indicated only for the control of the F. zucchini.     

Avoidable errors in the modelling of outbreaks of emerging pathogens, with special reference to Ebola

As an emergent infectious disease outbreak unfolds, public health response is reliant on information on key epidemiological quantities, such as transmission potential and serial interval. Increasingly, transmission models fit to incidence data are used to estimate these parameters and guide policy. Some widely used modelling practices lead to potentially large errors in parameter estimates and, consequently, errors in model-based forecasts. Even more worryingly, in such situations, confidence in parameter estimates and forecasts can itself be far overestimated, leading to the potential for large errors that mask their own presence. Fortunately, straightforward and computationally inexpensive alternatives exist that avoid these problems. Here, we first use a simulation study to demonstrate potential pitfalls of the standard practice of fitting deterministic models to cumulative incidence data. Next, we demonstrate an alternative based on stochastic models fit to raw data from an early phase of 2014 West Africa Ebola virus disease outbreak. We show not only that bias is thereby reduced, but that uncertainty in estimates and forecasts is better quantified and that, critically, lack of model fit is more readily diagnosed. We conclude with a short list of principles to guide the modelling response to future infectious disease outbreaks.     

Virus evolution and transmission in an ever more connected world

The frequency and global impact of infectious disease outbreaks, particularly those caused by emerging viruses, demonstrate the need for a better understanding of how spatial ecology and pathogen evolution jointly shape epidemic dynamics. Advances in computational techniques and the increasing availability of genetic and geospatial data are helping to address this problem, particularly when both information sources are combined. Here, we review research at the intersection of evolutionary biology, human geography and epidemiology that is working towards an integrated view of spatial incidence, host mobility and viral genetic diversity. We first discuss how empirical studies have combined viral spatial and genetic data, focusing particularly on the contribution of evolutionary analyses to epidemiology and disease control. Second, we explore the interplay between virus evolution and global dispersal in more depth for two pathogens: human influenza A virus and chikungunya virus. We discuss the opportunities for future research arising from new analyses of human transportation and trade networks, as well as the associated challenges in accessing and sharing relevant spatial and genetic data.     

Rate of novel host invasion affects adaptability of evolving RNA virus lineages

Although differing rates of environmental turnover should be consequential for the dynamics of adaptive change, this idea has been rarely examined outside of theory. In particular, the importance of RNA viruses in disease emergence warrants experiments testing how differing rates of novel host invasion may impact the ability of viruses to adaptively shift onto a novel host. To test whether the rate of environmental turnover influences adaptation, we experimentally evolved 144 Sindbis virus lineages in replicated tissue-culture environments, which transitioned from being dominated by a permissive host cell type to a novel host cell type. The rate at which the novel host ‘invaded’ the environment varied by treatment. The fitness (growth rate) of evolved virus populations was measured on each host type, and molecular substitutions were mapped via whole genome consensus sequencing. Results showed that virus populations more consistently reached high fitness levels on the novel host when the novel host ‘invaded’ the environment more gradually, and gradual invasion resulted in less variable genomic outcomes. Moreover, virus populations that experienced a rapid shift onto the novel host converged upon different genotypes than populations that experienced a gradual shift onto the novel host, suggesting a strong effect of historical contingency.     

Ecological dynamics of emerging bat virus spillover

Viruses that originate in bats may be the most notorious emerging zoonoses that spill over from wildlife into domestic animals and humans. Understanding how these infections filter through ecological systems to cause disease in humans is of profound importance to public health. Transmission of viruses from bats to humans requires a hierarchy of enabling conditions that connect the distribution of reservoir hosts, viral infection within these hosts, and exposure and susceptibility of recipient hosts. For many emerging bat viruses, spillover also requires viral shedding from bats, and survival of the virus in the environment. Focusing on Hendra virus, but also addressing Nipah virus, Ebola virus, Marburg virus and coronaviruses, we delineate this cross-species spillover dynamic from the within-host processes that drive virus excretion to land-use changes that increase interaction among species. We describe how land-use changes may affect co-occurrence and contact between bats and recipient hosts. Two hypotheses may explain temporal and spatial pulses of virus shedding in bat populations: episodic shedding from persistently infected bats or transient epidemics that occur as virus is transmitted among bat populations. Management of livestock also may affect the probability of exposure and disease. Interventions to decrease the probability of virus spillover can be implemented at multiple levels from targeting the reservoir host to managing recipient host exposure and susceptibility.     

Ecological connectivity shapes quasispecies structure of RNA viruses in an Antarctic lake

RNA viruses exist as complex mixtures of genotypes, known as quasispecies, where the evolution potential resides in the whole community of related genotypes. Quasispecies structure and dynamics have been studied in detail for virus infecting animals and plants but remain unexplored for those infecting micro‐organisms in environmental samples. We report the first metagenomic study of RNA viruses in an Antarctic lake (Lake Limnopolar, Livingston Island). Similar to low‐latitude aquatic environments, this lake harbours an RNA virome dominated by positive single‐strand RNA viruses from the order Picornavirales probably infecting micro‐organisms. Antarctic picorna‐like virus 1 (APLV1), one of the most abundant viruses in the lake, does not incorporate any mutation in the consensus sequence from 2006 to 2010 and shows stable quasispecies with low‐complexity indexes. By contrast, APLV2‐APLV3 are detected in the lake water exclusively in summer samples and are major constituents of surrounding cyanobacterial mats. Their quasispecies exhibit low complexity in cyanobacterial mat, but their run‐off‐mediated transfer to the lake results in a remarkable increase of complexity that may reflect the convergence of different viral quasispecies from the catchment area or replication in a more diverse host community. This is the first example of viral quasispecies from natural aquatic ecosystems and points to ecological connectivity as a modulating factor of quasispecies complexity.