Epidemiology is the science of how disease develops in populations, with applications in human, animal and plant diseases. For plant diseases, epidemiology has developed as a quantitative science with the aims of describing, understanding and predicting epidemics, and intervening to mitigate their consequences in plant populations. Although the central focus of epidemiology is at the population level, it is often necessary to recognise the system hierarchies present by scaling down to the individual plant/cellular level and scaling up to the community/landscape level. This is particularly important for diseases caused by plant viruses, which in most cases are transmitted by arthropod vectors. This leads to range of virus-plant, virus-vector and vector-plant interactions giving a distinctive character to plant virus epidemiology . These interactions have epidemiological, ecological and evolutionary consequences with implications for agronomic practices, pest and disease management, host resistance deployment, and the health of wild plant communities. Over the last two decades, there have been attempts to bring together these differing standpoints into a new synthesis, although this is more apparent for evolutionary and ecological approaches, perhaps reflecting the greater emphasis on shorter often annual time scales in epidemiological studies. It is argued here that incorporating an epidemiological perspective, specifically quantitative, into this developing synthesis will lead to new directions in plant virus research and disease management. This synthesis can serve to further consolidate and transform epidemiology as a key element in plant virus research. Epidemiology is the study of how disease develops in populations , in the This sequence raises questions concerning the epidemic as a hierarchical system with nested levels of integration. For example, if the aim is to understand the rate of change in disease at the population level, it would be necessary to describe processes at the individual plant level (and in some cases down to the cellular level); equally, if an understanding of disease at a higher level, such as in natural plant communities or over landscapes, then at the very least a description of processes at the population levels is required. This leads naturally to thinking in terms of systems epidemiology  and the A concept with a long history in plant pathology is the disease triangle, stressing the combination of a susceptible host, a virulent pathogen and a conducive abiotic environment as being essential for disease. Such a concept has it pedagogical uses but is often used in such a static way that it is questionable whether it provides any real insight into the processes underlying plant disease. As has been pointed out , there nThere have been many overviews of the place of plant virus epidemiology in plant virology research over the last two decades with its distinctive character brought together in an integrated way. It should be borne in mind that most are selective and not representative of the full range of plant viruses, which currently covers some 1516 species across 26 families ). In this review, for example, some 40 species only are covered in the research publications cited. A conventional view of plant virus disease epidemiology would emphasise how disease spreads in time and space, the role of vectors and the wider ecosystem, the interactions between viruses, vectors, host plants and the environment, and how knowledge of these interacting factors can improve disease control in different cropping systems [b.v1). InTechnological developments in support of research in plant virus epidemiology take many forms Many examples of recent developments and their application for a range of case studies have been reviewed , includiThere has long been recognition that a closer integration of plant disease epidemiology and evolutionary biology would add substantially to both our understanding of epidemic dynamics and the prospects for disease management. This certainly applies across all pathogen taxa, including plant viruses, in terms of the synthesis of epidemiology and population genetics . For plaTracing the origin and evolutionary pathways of plant viruses during crop domestication has proved difficult . To put Arabidopsis thaliana, it has been shown that cucumber mosaic virus (CMV) is a highly virulent pathogen, but with resistance and tolerance to the virus having evolved from other adaptive traits [The evolution of plant viruses with beneficial rather than harmful effects in crop plants ,27 raisee traits . The evoe traits  and showe traits , as woulEven in the shorter-term, the deployment of plant varieties with high levels of qualitative resistance to plant pathogens may lead to the development of pathogen genotypes which render the resistance ineffective. A model was developed in which epidemiological and evolutionary processes influence emergence of plant virus genotypes that infect previously resistant host genotypes . A globaAdditionally, ss well as the need to include an evolutionary perspective in plant virus epidemiology, there is a need and indeed a trend to bring in an ecological perspective on the role of plant viruses in both managed and unmanaged ecosystems . This adRecently, the various ways in which virus life history traits and ecology affect population dynamics and evolutionary potential have been reviewed , consideA full picture of the relationship between virus origin and evolution and host range must include ecological and epidemiological factors and these present new challenges for plant virus research. This can be seen from three perspectives: ecosystem ecology, viral community ecology, and epidemiology the host-virus-vector interaction ; a view Chenopodium spp. and if lucky a couple of commercially important crops, i.e., neither the experimental host range nor is ‘real world’ knowledge of virus distribution available. This point was taken up in relation to the “burden of proof” [In the synthesis of epidemiology, evolution and ecology, there should be a greater recognition that domesticated crop plants, even in extensive monocultures and other restricted cropping systems with less biodiversity also have an ecology, not just the wild or relatively unmanaged plant communities which are often used as exemplars for an ecological approach ,27,38. Ff proof” .Finally, there is much to be gained by comparing the evolution, ecology and epidemiology of plant viruses  with theEpidemiological analysis and mathematical models have long been used in support of forecasting and control of pathogens of human, animal and plants. However, despite some similarities in the modelling techniques, approaches to forecasting and control have developed independently and diverged , which iThe previous section highlighted some of the key overviews that provide some synthesis of evolutionary, ecological and epidemiological approaches in understanding plant virus epidemics. It is not clear how much this synthesis has contributed to an improved management of virus diseases, especially those of economic crops. Hence it is first necessary to show how epidemiological analysis has contributed to describing, understanding and predicting plant virus epidemics, and how the insights gained have contributed to disease management, whether in terms of cropping practices, host resistance deployment or forecasting based on weather or other environmental factors. The examples given are intended to be informative but not necessarily representative of all studies.Xylella fastidiosa [The first point to be made is that complete knowledge of a pathogenic agent is not necessarily a pre-requisite for disease control. For example, Bahia bark scaling of citrus is a disease of unknown aetiology, although analysis of its distribution suggests local dispersal by an insect vector. Even though of unknown aetiology, cost-effective methods of control can be devised based on this analysis . Conversstidiosa —a “paradSecondly, there are many examples of plant viruses which are well-characterised and have been long studied, such as plum pox disease, where epidemiological analysis has proved fruitful. Plum pox virus (strain D) was first discovered in Ontario, Canada, in 2000. An eradication programme was put in place based upon constant surveillance combined with stringent removal of infected plants and block plantings. Despite these protocols, eradication had not been achieved at the time of the programme’s termination in 2011 . The reaBursaphelenchus xylophilus, and vector abundance of Monochamus spp. beetles, in the northern Japanese mainland, was analysed [Long-term (1980–2011) spatial data on pine wilt disease (PWD), caused by the pathogenic nematode analysed . The datThe MCMV approach was applied recently to data on the spread of banana bunchy top virus disease (2014–2018) in a banana plantation in New South Wales, Australia . ParametR0 and its extensions [R0 value gives the number of infected ‘entities’ that would arise from the introduction of a single infectious entity into a susceptible host population during that entity’s period of infectiousness and provides a means of guiding control strategies, as has been shown in many studies in animal and human health, including the current COVID-19 pandemic. Besides its conceptual value, methods have been developed for estimating R0 during the early stages of a disease outbreak when information on the initial growth rate of an epidemic is available [R0 > 1, the epidemic will increase, and when R0 < 1, the epidemic will decrease.The basic reproduction number tensions  have becvailable . When R0R0 for plant diseases, including virus diseases have been given [R0 from theoretical models or from empirical data raises the question of how important it is to include vector-related parameters in models, or data of vector population dynamics and behaviour derived from field observations. Problems can also arise with theoretical models when host demography is included. There are no general methods for calculating R0 where there are time-dependent coefficients describing seasonality and environmental effects on host demography. However, when population demographics can be described by periodic functions the time averaged R0 may serve as a threshold for disease extinction [R0 is still defined purely in terms of the epidemiological parameters, the sensitivity of the final level of infection to changes in R0 depends on the epidemiological parameter being affected by a control measure [Applications of both the theory and practice of using en given ,53,54,55tinction . Where h measure .R0 depended on acquisition and inoculation coefficients, vector mortality and birth/immigration rates, natural and disease induced plant mortality, plant recovery rate from infection, and the total number of plants in the population. The point here is that depending on the assumptions made and the parameters defined in developing the model, a different R0 may result which makes direct comparisons of the numerical values obtained problematic. Including a latent period in the model formulation adds some complexity to both the analysis and interpretation of results. In the case where new plants are introduced into the system, a proportion of these may be infected but not showing symptoms [R0. If all new plants are considered healthy, then R0 effectively sets a threshold which determines the global dynamics . However, if a proportion of plants are latently infected then it can be shown that a stable endemic equilibrium for healthy, latently infected and infected plants also exists.A theoretical model for the dynamics of a vector-borne plant disease led to the derivation of a basic reproduction number using the next generation matrix . The valsymptoms . This chR0 for plant virus diseases have ignored not only the vector, but also the virus load within the plant. By making the transmission rates a function of virus titre within individual plants an expression was obtained which included within-plant multiplication in the formulation of R0. The derived expression proved valuable in determining the outcome of within-plant competition between virus strains where co-infection occurs [Finally, most derivations of n occurs , a topicn occurs ,62,63, an occurs ,65.An element that is receiving increasing attention is spatial aspects of plant virus epidemics, whether in terms of disease spread, spatial structure such as aggregation of host plants or disease, and the contribution of vector population dynamics, life history and behaviour to the spatial patterns of disease observed, e.g., the relative importance of seed-borne and vector transmission. Modern computational and modelling techniques make the inclusion of an explicit spatial dimension more feasible, although more demanding in terms of field observations. Three species of thrips and the incidence of tomato chlorotic spot virus infected plants were monitored regularly over three years in commercial tomato fields in south Florida . The disSpissistilus festinus at vineyards in California and New York [Having an explicit spatial basis for disease and vector surveys leads naturally to the generation of maps which illustrate the spatiotemporal progress of disease. Such maps were generated in a study of grapevine red blotch virus disease and the vector New York . AlthougThe spatial-temporal spread of wheat streak mosaic virus in winter wheat around a central mite-infested source of infested volunteer wheat was monitored over three successive cropping seasons . SpatialAfrican cassava mosaic virus disease in Uganda during the period when there was major expansion both in the diversity of the virus species and strains, and its spread and damage [Surveys are often made for the prevalence of specific virus diseases in a crop population. From an epidemiological perspective the key aspects are to place the survey design and implementation within a spatial and temporal frame. This was done for d damage . Two norSpatial aggregation in landscape characteristics can influence epidemic dynamics but has rarely been considered in mathematical models . A spatiSpatial structure in plant populations can also affect host community dynamics through competition and other seasonal effects as well as vector movement and virus transmission. Using barley and cereal yellow dwarf viruses as an example, the effects of host community structure  on vector movement and disease dynamics were modelled . A key fAlthough mathematical models have been proposed to describe the temporal dynamics of plant virus diseases by means of linked systems of ordinary differential equations, the spatial dimension has mostly been ignored. The spatiotemporal aspects of disease caused by begomoviruses have been modelled  within aMyzus persicae as the vector [A spatially explicit individual-based model was developed to simulate the spread of persistent and nonpersistent viruses, using parameter values appropriate for potato leafroll virus and potato virus Y respectively, with e vector . ResultsWhere virus disease has caused the widespread destruction, deterioration or abandonment of plantings, whole areas may be cleared to enable the planting of healthy, possibly more resistant material. Such a situation occurred in Ghana with cacao, where because of the widespread damage caused by cocoa swollen shoot disease, new block plantings of more resistant cacao genotypes were made. Virus spread within the crop can take place by radial movement from the periphery of the block plantings adjacent to previously infected, possibly relic, populations of cacao; or by wind-blown ‘jump spread’ into the interior by the relatively immobile mealybug vector. Given these two scenarios of spread, the effectiveness of imposing a cordon-sanitaire around the plantings was modelled using a spatiotemporal model ,74. AlthMany reviews have dealt with the effects of climate change on plant pests and pathogens, particularly in relation to global warming, but to some extent plant viruses have been poorly represented . For exa2 concentration, drought and flooding may be expected to have effects on host responses and emphasises the need to consider both biotic and abiotic constraints, and their interaction on plant virus epidemiology. As well as having effects on virus transmission, environmental factors can also affect tripartite and by implication tritrophic interactions [The impact of abiotic stresses on plant virus transmission and virus spread was recently reviewed . Elevateractions . Environractions . When viractions .Arabidopsis thaliana challenged with either turnip mosaic virus (TuMV) or CMV. The hypothesis was supported with TuMV; but with CMV, higher light intensity reduced CMV multiplication and had no effect on seed transmission.A further abiotic stress, which by comparison with water or temperature stresses has been little studied is that imposed by light intensity and quality. This aspect was studied in a recent study which looked at the effect of light intensity on seed transmission of viruses . The hypTomato spotted wilt virus (TSWV) in the south-eastern USA is Frankliniella fusca. Recently, the influence of meteorological factors on thrips flight and dispersal was incorporated as an add-on to Peanut Rx [A key issue in determining the effects of the environment, is noting the difference between weather  and climate  and how the associated meteorological variables can be used in forecasting and prediction of plant virus epidemics. Weather, or current meteorological conditions, can be used as part of a decision support system to help identify risk factors that can inform disease management decisions. One of the most developed for plant virus diseases is Peanut Rx, in which an assessment of relative risk of tomato spotted wilt disease is made available to peanut growers. The principal vector of eanut Rx . When heeanut Rx . CombiniInadequate nutrition can also lead to abiotic stress. Although accounting for nutrient supply is an essential feature of crop modelling, particularly for nitrogen and phosphorus, there have been few accounts in relation to modelling plant virus disease dynamics. A plant-growth model based on physiological processes was combined with a pest population-dynamic model and applied to the green peach aphid system in terms of direct herbivory effects but also indirectly for virus transmission . The aimAvena sativa [Two models differing in the way nutrient supply affects disease dynamics were developed and tested against data on virus accumulation of cereal yellow dwarf virus and number of infected phloem cells from stems of a sativa . UniquelMany important food crops are propagated vegetatively, e.g., sweet potato from vines and cassava from stem cuttings. In these production cycles, the planting material is often taken from farmers’ fields or through informal exchange with other farmers. In such systems, viruses can multiply and intensify leading to progressive degeneration in the varieties grown. However, a phenomenon known as reversion has been reported in which plants propagated from previously virus infected plants are free from virus , althougSolanaceae community.Farmers’ fields are generally part of a wider environment which includes wild plants such as agricultural weeds within the crop or natural flora in field margins, abandoned fields or in land at urban margins. Many studies have recognised the interface between crops and the wider environment as important in the interaction between plants, vectors and viruses, often influencing virus transmission and disease spread at a local level. A fewer number of studies have attempted to extend the analysis globally. An example is given for the Solanaceae family, which has species in all the settings above, is present globally, and is affected by a wide range of viruses . The autBemisia tabaci into tomato crops by insect screens, with or without insecticide-treated strips [The use of insect screening to prevent the entry of virus vectors is practiced in plant nurseries and in field cultivation for some horticultural crops. Experiments were designed to reduce the entry of d strips . A matheIn annual production cycles, the time gap between harvest and planting the succeeding crop may be short, with obvious implications for the carry-over of virus and vectors. A model for this scenario looked at repeating production cycles . ParametRogueing of diseased plants has long been practiced as a means of disease control, sometimes with the aim of eradication but more frequently either to contain an outbreak, or to maintain disease levels below economically damaging levels. Rogueing of diseased plants is often practised in combination with their replacement by healthy stock, especially for perennial tree fruit crops. An early model for plant virus disease dynamics was developed primarily to determine the effectiveness of rogueing of diseased with their replacement by healthy plants  in orderR0, its value could be calculated numerically from parameter values. Some important findings were found: (a), when the infection rate is high it may be impossible to eradicate disease by rogueing only infectious plants and so identifying latently infected plants would be key; (b), increasing replanting rates is counterproductive for disease control; and (c), the model of Chan & Jeger [R0 > 1) compared with pulse rogueing (R0 < 1).This model was further developed with a more realistic representation of rogueing and replanting as periodic pulses rather than continuously . Althoug & Jeger  with conThe effectiveness of rogueing was modelled for banana bunchy top virus and predicted to be achievable . Two keyCassava is a crop in which both rogueing of plants infected with cassava mosaic disease and subsequently replanting with new stem cuttings taken at harvest are practiced. In some circumstances, farmers are faced with the choice of stem cuttings taken from healthy or infected plants, based on the availability of planting material and the phenomenon known as reversion in which some cuttings taken from infected plants can lead to healthy plants. Such a choice may depend on farmer preferences, and the consequences of such preferences have been modelled ,93. In tThere are examples of other vegetatively-propagated crops where there is a lack of separation between the plantation crop and the production of planting material, especially in less developed informal systems of production. Material may be recycled from the plantation or mother trees to produce the next generation of planting material, thus perpetuating the presence of viruses even where there is a level of reversion to the healthy state. The outcomes in a model describing rogueing and replanting in such a combined system  could beRogueing with annual food crops gives less promising results. Data from 2-years of field trials at the International Rice Research Institute in the Philippines were used as a comparison with simulated results from a model for rice tungro disease (RTD) . The modBreeding for disease resistance plays a major role in developing strategies for disease management. This is especially the case for plant virus disease, but as with other pathogen groups less attention has been given to how host resistance should be used in the field. A large body of work has been directed at the development of plants with resistance to plant viruses, combining the screening of molecular markers for genotype selection through to phenotype selection in field trials. However, by comparison little has been done on the transmission and spread of plant viruses in resistant varieties under field conditions. From an epidemiological perspective, this is a major gap that is holding back progress in disease management and will be emphasised in this section.Potato virus Y (PVY), although long-known as a major potato pathogen, has emerged recently as a range of strains that challenge potato production globally . Taken tVector feeding resistance might be expected to reduce incidence and the spatial distribution of virus disease in crops. The spread of bean pod mottle virus (BPMV) was monitored in resistant compared with susceptible soybean . AlthougArabidopsis thaliana genotypes challenged with either CMV or TuMV [Tolerance as a disease management strategy has been claimed to be as widespread as host resistance although problems remain in the strict definition of tolerance and how it can be assessed. For some workers, especially those concerned with crops, it refers to limited symptom development or reduction in plant vigour or yield in a cultivar despite a normal virus accumulation that would be expected in a susceptible cultivar. For other workers, more concerned with the ecological and evolutionary aspects of plant-virus interactions, tolerance would be measured as the limited reduction in plant fitness . In a resistant (not immune) variety, there would be limited virus accumulation and symptom development, although there may be a penalty in terms of reduced vigour and yield in the absence of disease compared with a susceptible variety. Whether there are trade-offs in tolerances to different viruses was studied recently in  or TuMV . It was Penicillium simplicissimum, Fusarium equiseti, and Penicillium asperellum induced resistance in faba bean mechanically inoculated with bean yellow mosaic virus [Novel ways of improving the resistance characteristics of crops by exploiting microbial interactions can also assist in disease management, but these have not received the same attention or funding given to plant breeding. Pre-treatment of grain with the plant growth promoting fungi ic virus . Diseaseic virus .Arabidopsis thaliana with serial passaging of TuMV, the evolving isolates were more pathogenic in heterogeneous populations than in a metapopulation composed of distinct subpopulations [The impact of biodiversity on plant pests and diseases continues to evoke considerable interest both from its intrinsic value and from the contribution it can make to pest and disease control. The mechanisms of such control have been much researched with a consensus reached that biodiversity among potential plant hosts, within or between species, provides a dilution effect that limits the impact of pests and pathogens. A major meta-analysis has estimated the size of the dilution effect, as represented by species richness metrics, for both fungal and viral pathogens . They foulations .The use of varietal mixtures where the individual varieties differ in their resistances to pathogens has long been studied as a strategy to exploit crop heterogeneity. Such an approach has also been proposed for insect pests, such as aphids, where genetic isolation and adaptation during the parthenogenetic stage are well known. A modelling approach  was takeMuch of the work on varietal mixtures has been done within a cropping season. The longer-term dynamics of disease in a dynamic cropping system, with deployment of virus-resistant and susceptible varieties and other transitory crops has not been looked at in the same detail. In rice cropping systems, there can be a range of crops of different growth stages grown in the same locality. RTD can persist in a locality with the movement of virus from crops. Using a mathematical model of RTD, the effect of planting resistant varieties as a component of the cropping system over time was investigated . ProvideB. tabaci [Intercropping with a range of geometric arrangements of unrelated host plants is a more general form of crop biodiversity than the use of intraspecific varietal mixtures. There have been many studies on intercropping and insect pests but fewer on virus vectors and virus disease. A model was developed that monitored aphid and virus spread in an intercropped field, the spatial arrangements of intercropped plants, and the use of trap plants within the intercrops . Contrar. tabaci , althougF. occidentalis [African cassava mosaic virus with natural escape mechanisms, “reversion” and cutting selection was modelled to determine the effects on disease incidence and yield losses [Integrated pest management has become the gold standard in control for many insect pests but has not always been accepted by plant pathologists . Howeverdentalis , As suchdentalis . Single d losses . The resd losses , particuDegeneration of vegetative planting material can occur rapidly in circumstances where virus-free planting material is unavailable or too expensive in resource poor counties with limited farmer support and logistical services. A risk assessment framework was developed to model how best to develop an integrated strategy involving on-farm selection, assessing the extent of external sources of virus and the risks posed, reducing the rate of within-field transmission, and combining different control options by making use of host resistance to reduce the need for vector control . Such inIn the main plant viruses are transmitted horizontally by arthropod vectors, or vertically through true seed and vegetatively-propagated planting material. These cases and their interaction are the main emphasis in this review, but it should also be recognised that nematodes and fungi also transmit viruses. There are also relatively unexplored pathways of plant virus transmission in relation to disease epidemiology, including direct contact, root grafting, parasitic plants, and contamination of soil and water , but the(i)horizontal transmission by arthropods;(ii)vertical transmission;(iii)interactions between horizontal and vertical transmission;(iv)transmissibility, virus accumulation and virulenceTransmission will be reviewed in four main areas in this section:(v)the effects of vector population dynamics, behaviour and feeding, and how these are affected by natural enemies;(vi)the conditional vector preferences for infected or healthy plants;(vii)the common occurrence of coinfection of plants by multiple virus species, strains or genomic segments.In subsequent sections, three key areas relating to vector transmission will be discussed:Transmission is a continuum of processes starting with acquisition of virions when a vector probes/feeds on an infected plant, passaging and retention of the virions at specific sites in the vector, and subsequent inoculation of a recipient plant . Each ofAn understanding of transmission has claimed as necessary for determining disease control strategies ,127. A cHomalodisca vitripennis is a vector of the xylem-limited bacterium X. fastidiosa, but virus sequences have been found in this species that are closely related to the plant reovirus rice dwarf virus, a virus that is not limited to the phloem [Circulifer tenellus, although a phloem feeder, does not achieve the high rate of ingestion typical of other phloem feeders [Plant viruses in the main are acquired by vectors feeding on the phloem, although acquisition of nonpersistent viruses occurs during probing without feeding. Some insects, including cicadellid leafhoppers also feed from the xylem. The glassy-winged sharpshooter e phloem . Althouge phloem . Insectse phloem . Finally feeders , althougThe persistent transmission of viruses and the implications for insect-virus interactions has been reviewed comprehensively  and specThe form of transmission by vectors is arguably the key epidemiological characteristic of plant virus epidemics, as it defines the temporal scales of acquisition, retention, inoculation, and vector life history and behaviour that determine the rate of disease increase. A theoretical SEIR model was developed which described epidemic processes for the main classes of transmission: nonpersistent, semipersistent, persistent-circulative, and persistent-propagative . The basM. persicae transmitted many fewer virus particles (<5) per inoculation (following acquisition) than the census virus population would suggest. These results indicated that genetic drift may have a major effect on plant virus populations during vector transmission.Transmission of plant viruses can affect plant virus epidemiology in many ways other than disease dynamics. Within-host and between-host population bottlenecks in transmission have been documented but estimates of their size are rare . The emeMany models of plant virus epidemics assume that vector transmission takes place without regard to spatial heterogeneity of vectors within crops or on plants. A model of the effect of spatial aggregation of vectors on disease dynamics  was deveVertical transmission of plant viruses through seed has been less studied than horizontal transmission through vectors. As well as the better-known transmission through seed or pollen, another form of vertical transmission can occur by integration of viral genomes into the host genome . The epiArabidopsis thaliana and TuMV and CMV.The various stages of seed transmission that are relevant epidemiologically are the movement of virus from mother plant tissues to seed, from the embryo to the progeny seedling, and the contribution of seed transmission to local and long-range dispersal of viruses. More specifically , the effThe epidemiological significance of seed transmission is that even at low levels of seed transmission, this can be amplified by subsequent vector transmission, and hence can be responsible for the introduction of virus into new areas and trigger epidemic development ,150. SeePolymyxa [Seed transmission can also accompany transmission with vectors, including the plasmodiophorid Polymyxa  and mealPolymyxa . A similPolymyxa . The relPolymyxa . Grow-ouPolymyxa . In somePolymyxa .In the context of whether transmission is horizontal or vertical, or a combination of both, the effects on pathogenicity and virulence can be compared. This was explored in a theoretical model  raising Blanc  suggesteVirulence is defined as “the degree of damage caused to a host by parasite infection assumed to be negatively correlated with host fitness” whereas “pathogenicity is the qualitative capacity of a parasite to infect and cause disease on host” . These dArabidopsis thaliana was studied by serial passaging of different CMV strains under either horizontal or vertical transmission and then alternating the mode of transmission [The reduction in host fitness caused by a pathogen or parasite, has long been a concern of evolutionary biologists, especially as to whether there is a trade-off between virulence and transmissibility. For plant viruses, although most are horizontally transmitted by vectors, there are also routes for vertical transmission through seed as discussed above. Despite much theoretical modelling, there have been few experimental attempts to disentangle the relative effects of horizontal and vertical transmission on the evolution of virulence. The evolution of CMV on smission . PassagiThe relationship between virulence and transmissibility remains a topic of much interest. From a theoretical perspective, increased virus transmission should be correlated with increased pathogen-induced mortality (and reduced period of being infected), because both variables are functions of within-plant virus accumulation. However, it has been pointed out  that theInformation on the general biology and ecology of arthropod pests is essential for effective pest management. This applies in terms of their direct effects on crops , indireF. occidentalis on tomato spotted wilt infected plants promotes multiplication and spread of the virus in a crop [The most efficient vector is not necessarily the most relevant epidemiologically. This depends on vector abundance and seasonality at times when host plants are most susceptible, as found for plum pox virus and its aphid vectors on peach . Incorpon a crop . Howevern a crop . Insect n a crop .Vector life history and behavioural parameters play a key role in virus transmission and disease spread. Although not always considered explicitly, there is increasing interest incorporating them into models of disease dynamics. In many models the assumption is made that birth and death rates are the same for viruliferous and non-viruliferous vectors. This assumption was modified by allowing the per capita death rate of inoculative vectors to be increased relative to non-viruliferous vectors, and similarly for birth rates, and comparing the outcomes to the standard model . It was Dispersal, both active and passive, is a key element in the life cycle of most arthropod pests, including those that vector plant diseases . It has Landing behaviour of virus vectors in crops is influenced by both visual and olfactory plant cues. Management of nonpersistent viruses has largely stressed the visual cues but knowledge of how a virus manipulates a plant to enhance its own dispersal could be used to develop traps based on olfactory cues, including border or trap crops and ‘push-pull’ systems .The incidence of virus disease in a crop can depend as much on the presence of the virus and vector in alternative crops, wild plant populations and weeds, as on epidemic processes within the crop. This is particularly relevant where these alternate hosts act as a reservoir for both virus and vector and infection results from often transitory immigration and feeding of vectors into and within the crop. An epidemiological model was proposed  to repreAphis gossypii, whereas watermelon mosaic virus was mainly transmitted by non-colonising species such as M. persicae [A. gossypii and M. persicae are considered colonising species and were responsible for much of the epidemic spread of zucchini yellow mosaic virus compared with non-colonising species [A useful behavioural distinction can be made between colonising vs non-colonising vectors on a given crop. Based on transmission studies and spatiotemporal patterns of virus spread in melon crops, it was concluded that CMV was mainly transmitted by colonising species such as persicae . On zucc species .B. tabaci in a semi-persistent manner. Acquisition of the virus changed feeding behaviour in a biotype and sex dependent manner, but, overall, the results suggested an increased ability of the vector to transmit the virus [F. occidentalis carrying TSWV was some three-fold higher and caused less plant cell damage than with non-viruliferous thripsSap-sucking insects such as aphids, whiteflies and leafhoppers while feeding on plants cause little physical tissue damage, but in feeding can acquire and transmit plant viruses. The plant’s defence response to feeding can now be studied in much greater molecular detail in real-time  and may he virus . Vector he virus ,118, a tR0 threshold does not hold. Drought stress intensity and duration can also affect vector behaviour, feeding and reproduction. [Insect vectors of plant viruses are also plant herbivores. Few models have taken the dual nature of herbivory and the epidemiological consequences of infection into account. A hybrid model was developed  in whichduction. . FecundiFor persistently transmitted viruses, the duration of the feeding period is critical in determining then probabilities of acquisition and inoculation. As pointed out , the varMany virus vectors such as aphids have associations with endosymbiotic bacteria. Endosymbionts may influence aphid physiology and fitness in various ways. They may also affect feeding behaviour by increasing the number of punctures and reducing the duration of each puncture . The netSitona lineatus affected the behaviour of Acrythosiphon pisum the vector of pea enation mosaic virus [S. lineatus stimulated vector movement and virus spread to more susceptible parts of the plant. A key role of insects is to provide an ecosystem service through pollination of crops and native flora, a provision directly related to their feeding behaviour and life cycle. An intriguing suggestion made recently is that plant viruses may help to manipulate plant-insect interactions by making plants more attractive to pollinators [Tripartite interactions occur between organisms at the same trophic level. Interactions between herbivore vectors and herbivore non-vectors have been little studied in transmission and other epidemiological studies. Experiments were conducted to determine whether defoliation by ic virus . It was linators .Aphidius ervi reduced population numbers of the aphid A. pisum but increased nine-fold the incidence of bean yellow mosaic virus disease [Parasitoids and natural enemies have been shown to have a major effect on insect vector populations and behaviour. Such effects may be expected to affect virus transmission and disease spread. In a range of experimental test arenas, introduction of the parasitoid  disease . These e disease . Based o disease  was propA. gossypii were studied in the presence or absence of the parasitoid Aphidius colemani [The consequences of tritrophic interactions for the longer-term dynamics of a plant virus disease have been less studied. The short and long-term spatiotemporal dynamics of CMV (nonpersistent) and cucurbit aphid-borne yellows virus , both transmitted by colemani . In the A relatively unexplored area of research concerns competition between multiple vectors in transmission of a given virus, a scenario which has been modelled in terms of the basic reproduction number . In thisVector preference for host plants can take many forms.(i)A vector might show a preference for a given plant species or genotype, even though many related species/genotypes may harbour populations of the vector. This then becomes an important consideration when this range of plant species/genotypes can be shown to be susceptible  to the virus being vectored.(ii)Preference can also be shown for infected or healthy phenotypes of a given plant species through visual or olfactory cues.(iii)In an elaboration of this, vectors may switch preference from infected phenotypes when nonviruliferous, to healthy phenotypes when viruliferous. This form of vector preference has been termed conditional preference and is the subject of much current research based on the premise that it represents virus manipulation of the plant and vector.In each of these areas there have been extensive studies published—only a selected number are discussed here. Earlier papers up to about 2016 are summarised in B. tabaci [2 respectively. It seems that host preference among genotypes or cultivars of a crop may not be affected by whether a vector is viruliferous or non-viruliferous, i.e., there is no host genotype x vector status interaction. This was found for soybean and soybean vein necrosis virus where viruliferous and non-viruliferous adult female thrips were used to infest 18 soybean genotypes with the numbers of immature thrips subsequently counted [In studies on the host range of tomato chlorosis virus, several solanaceous and unrelated plant species were found to be susceptible and which supported oviposition by . tabaci . In tran counted . There wRhopalosiphum padi and potato/potato leafroll virus/M. persicae [During the last decade a major development in plant virus epidemiology has been the recognition that vectors may show preferences for landing and feeding that are dependent on the host’s status as infected or healthy. The responsiveness of insect vectors to healthy or infected plants was described for two systems: wheat/barley yellow dwarf virus/ persicae . Virus ipersicae . Complexpersicae .For non-persistent transmission, it has been argued that inhibition of settling while allowing probing will encourage transmission, whereas prolonged settling will retard transmission . HoweverAs well as the responses of insect vectors to virus infections, effects may also be found with non-vector insect herbivores and interactions with predators, as discussed in the section on tripartite and tritrophic interactions. CMV-infected plants may well have a reduced overall herbivore pressure through effects on palatability and apparency, however predators were found to locate herbivorous prey on infected plants as efficiently as those on healthy plants .Just as plant viruses can affect insect vector behaviour and population dynamics as described in the previous section , these aThere is now increasing acceptance that plant viruses have adaptations that facilitate transmission through acquisition, retention and inoculation. There appears to be a remarkable degree of convergence among unrelated viruses that share similar transmission characteristics, although the specific details of the virus-vector-plant interaction can clearly differ . ImportaMathematical modelling has also contributed to analysis of the epidemiological consequences of vector preferences. The landing and feeding preference of insect vectors on infected or healthy host plants has been shown to depend on whether the vector is inoculative. Including conditional preference depending on vector status into models, showed that a switch in preference once vector acquire virus from infected plants can enhance spread throughout an epidemic in cases where non-inoculative vectors prefer infected plants and inoculative vectors prefer healthy plants . This imEncarsia formosa between Q- and B-biotypes of B. tabaci: on infected but not healthy plants the Q-biotype was more attractive to the parasitoid than the B-biotype, due to quantitative differences in volatile profiles. Thrips species have long been reported to have feeding preferences for tospovirus infected plants. Virus acquisition occurs during the developmental period from early instars to adults and this period was shortened when Thrips palmi had acquired virus from groundnut bud necrosis virus infected plants without any effect on pre-adult mortality [B. tabaci whiteflies landed and settled on infected than non-infected squash, but the opposite was found with watermelon [Since the published studies listed in ortality . Squash termelon . In addiB. tabaci preferentially feeds on different hosts infected with TSWV, body size, longevity and fecundity were all reduced [Camelina sativa was infected with the cauliflower mosaic virus  or turnip yellows virus  with the aphid vectors M. persicae  and Brevicoryne brassicae , differing in transmission efficiency. Results showed that negative host-mediated effects of the nonpersistent CaMV on feeding behaviour and performance of both aphid species enhanced virus fitness. Transmission efficiency also played a role as only the response of the specialist vector to host-mediated effects of TuYV played a role in increased dispersal.It should also be noted that vector life history trait preferences are not always consistent across different hosts, even when virus-infected plants are generally higher quality hosts . The eff reduced  indicati reduced . Pea aph reduced . Aphid c reduced . The braA key question in future research is does a link between vector preference, transmission type, and natural enemies lead to increased virus fitness and can this be represented in the basic reproduction number? It is difficult to see how hypotheses on epidemic dynamics given different forms of vector preference could be tested in the field, which returns to the point made in the introduction about the balance that needs to be struck between explanation and prediction. This is one reason why modelling can assist in creating and analysing different scenarios. Modelling, for example, can help to differentiate the consequences of non-conditional and conditional preferences, even though these are unlikely to be tested in the field.Co-infection by multiple virus species or strains is known to be common, but presents major problems in etiological and epidemiological studies, not least where detection and identification are required for the causal agents. Improved diagnostic procedures, such as high throughput sequencing, introduce new problems in determining pathogenicity, assigning causality to a single agent in the mixture or to interactions among the co-infecting entities, and identifying novel or cryptic viruses .The literature on co-infection by plant viruses is extensive. In September 2017, a literature search yielded some 180 papers a mixture of reviews, perspectives and original research. Most papers were concerned with interactions between viruses at different levels dealing with cellular (even nuclear) interactions, cell-to-cell movement, vector transmission, virulence, symptom development, and yield losses. Cellular interactions were the most prevalent, mostly replication rates and virus titre (not necessarily correlated), but some studies showed clear interactions with vectors over short  and long-term (evolutionary) time scales. Some of the publications reflect some aspect of co-infection in relation to vector transmission, but often the vector contribution to coinfection is not discussed. Coinfections can also arise from vertical transmission . Even whThere are key questions over what is meant by “simultaneous” and “synergy/antagonism” in relation to virus co-infection which modelling and statistical analysis could bring some clarity and rigour.Syller  reviewedIn a subsequent review, Syller and Grupa  differenEm = E1 + E2 − E1E2, where the E’s represent proportionate effects). An outcome less than the expectation Em would represent antagonism, an outcome greater than the outcome would represent synergy, even though it may be less than additive. The Abbott formula has been proposed as one way to study the outcome of interactions with co-infecting viruses [Phaseolus vulgaris and Vicia fabae. Hence, Abbott’s formula would give a threshold to determine whether there is synergy (or antagonism) between two coinfecting viruses and could be modified for effects such as on virus titre in planta. The claim of synergy or antagonism among co-infecting viruses or virus strains is now so pervasive that rigorous statistical standards need to be developed to validate these claims.Outcomes of interactions among co-infecting entities can be neutral, antagonistic or synergistic and present statistical challenges in distinguishing these outcomes. In other areas, such as interactions between pesticides or microbial biocontrol agents in mixtures , rigorou viruses , where tIn this section, co-infection will be dealt with in stages from two viruses—with a common vector to many viruses—with many vectors, but with some nuances. Many of the papers acknowledge that there are several or many (in the case of aphids) vectors of a given plant virus but the experiments reported in general only involve one vector. Similarly, the same virus and vector can infect more than one crop (CMV is an extreme example) and hence cause more than one disease. These are perennial problems in the plant virology literature. Questions whether the helper strategy, in which a helper virus  can be transmitted by the vector but the dependent virus  can only be transmitted in the presence of the helper , falls wNTN) has increased in the US (and elsewhere) while the wild-type strain PVYO has been decreasing [M. persicae) or by separate aphids and then inoculated to the same plant. The necrotic strain was transmitted more efficiently than the wild type irrespective of the order of acquisition or inoculation. Rarely was it found that aphids sequentially acquiring both strains co-inoculated a recipient plant. An aphid does not to acquire both strains from one co-infected plant in order to transmit both strains. Co-infected plants would more likely result from inoculation by multiple aphids feeding on plants infected with the different strains rather than by single aphids feeding on multiple plants infected with the different strains.A recombinant necrotic strain of PVY  and cereal yellow dwarf virus (CYDV-RPV) with the aphid R. padi . The co-A. gossypii. ZYMV accumulated at similar rates in single and mixed infections, whereas WMV was much reduced in the presence of ZYMV. ZYMV also induced host changes that gave strong vector preference for infected plants, whereas WMV did not, although it was still readily acquired from mixed infections.Single and mixed infections were studied for two potyviruses, watermelon mosaic virus (WMV) and zucchini yellow mosaic virus (ZYMV), commonly infecting cucurbitaceous crops . The stuEpilachna varivestis; SMV by aphids including the recently introduced Aphis glycines. Penaflor et al. [A. glycines, whereas SMV infection reduced aphid population growth but conversely increased the preference for infected plants. Coinfection reversed the effects on population growth and aphids showed a preference for co-infected plants.BPMV and soybean mosaic virus (SMV) both cause substantial yield losses in soybean, losses which are worsened by co-infection with little or no harvestable yield. BPMV is transmitted by beetles including the coccinelid r et al.  studied Trialeurodes vaporariorom and B. tabaci. The group is of interest because it does not fall neatly into the transmissions categories of stylet-borne or semi-persistent (foregut). At least three whitefly species have been shown to transmit four torradovirus species [Torradoviruses are spherical viruses transmitted by the whitefly vectors  species  but the Brevipalpus yothersi and B. californicus, collected in citrus orchards. The rounded incidences were 17, 10 and 3% for singly and co-infected vectors respectively in B. yothersi and 12%, 21% and 4% in B. californicum. Clearly the incidences of coinfection in the two mite species were greater than the product of the two single incidences [Complications in analysing co-infection data can arise when two distinct viruses are transmitted by two distinct species of vector. Such as situation arises with data on Citrus leprosis virus C and orchis fleck dichorhaviris citrus strain  incidenccidences .Nephottetix virescens. Infection by each virus alone results in less pronounced symptoms especially for RTSV. RTBV is retained in the vector for a longer period, 4 rather than two days. When a vector carries both viruses, co-inoculation seems to be common. When the vector is inoculative with RSTV alone the infection probability seems to be higher. A simulation model with assumptions based on these and other details was developed by Holt and Chancellor [Two viruses are responsible for RTD: rice tungro spherical virus (RTSV) and rice tungro bacilliform virus (RTBV). They are both transmitted by leafhoppers in a semi-persistent manner with the most efficient vector being ancellor  to examiGrapevine leafroll disease is caused by a range of monopartite closteroviruses designated as Grapevine leafroll-associated viruses (GLRaVs), although their exact role in disease etiology remains unclear . The traSPVD results from co-infection with sweet potato chlorotic stunt virus and sweet potato feathery mottle virus. At least six other viruses from the same or different virus families were found to interact synergistically with SPVD . The claIn field studies of barley and cereal yellow dwarf viruses in US west coast grasslands, the effect of shared vectors, environmental conditions and spatial variation in hosts affected the spatial variation of single viruses, paired viruses and the whole virus community in grass hosts . It was At a high level, the ecological networks formed by multiple co-infecting viruses, hosts and vectors were analysed by McLeish et al. . Co-infeAmphorophora agathonica) preferred to land on raspberry leaf mottle infected plants rather than healthy plants, but on healthy rather than raspberry latent virus infected plants [The previous section examined how vector preference can affect the transmission and disease spread of plant viruses. In this section the epidemiology of co-infecting plant viruses is being examined. An important consideration in this context is the extent to which co-infected plants affect vector preference compared with plants infected with a single virus. Aphids  and rice ragged stunt virus (RRSV) . Both viCucumber mosaic is a tripartite RNA virus with the genomic RNA packaged into separate particles . MultiplThe area of co-infection and how this relates to recent work on vector behaviour and preference and at a higher scale the agroecological consequences is ripe for further attention by mathematical modellers ,261,262.There has been considerable progress over the last decade in achieving a greater synthesis of ecological and evolutionary insights with plant virus diseases and how these affect crops and wild plant communities. The role and function of plant viruses in nature have received a greater appreciation, for example the evolutionary trajectories that are possible from pathogenicity to mutualism, and vice-versa . HoweverMethods of epidemiological analysis have also matured over the last decade from the simple description of disease progress curves and disease gradients. Modern computational and data mining techniques have transformed the ways in which theoretical epidemiological models can be evaluated and parameters estimated when extensive empirical data on disease progress and associated biotic and abiotic factors are available, e.g., the linking of Markov chain Monte Carlo (MCMC) methods to estimate the parameters of compartmental models of disease progress ,50. TherConsiderably more work has been done on characterising spatial aggregation/structure in landscapes as a basis for describing and in some cases predicting the consequences of a plant virus epidemic ,71,72. CPerhaps the most promising development over the last decade has been the greater recognition of, and prominence given to, the vector in all aspects of virus epidemiology, and indeed this is a common thread from the ecological and evolutionary perspectives as well. How best to deploy host resistance and tolerance in the field can only be determined if the dynamic interplay between the virus, vector and host is characterised. The consequences of releasing varieties with different mechanisms of resistance can differ and affect the effective use of a variety ,266,267.Co-infection with plant viruses is now recognised as the norm for many crops. However, to what extent is such co-infection significant or simply a consequence of recent developments in high throughput sequencing . There a


We designed small‐scale virus filtration models to investigate the impact of the extended process times and dynamic product streams present in continuous manufacturing. Our data show that the Planova 20N and BioEX virus filters are capable of effectively removing bacteriophage PP7 (>4 log) when run continuously for up to 4 days. Additionally, both Planova 20N and BioEX filters were able to successfully process a mock elution peak of increased protein, salt, and bacteriophage concentrations with only an increase in filtration pressure observed during the higher protein concentration peak. These experiments demonstrated that small‐scale viral clearance studies can be designed to model a continuous virus filtration step with specific process parameters. For an integrated continuous purification process, there are no traditional hold tanks and the fluid flow is constant from one unit operation to another, creating a dynamic product stream with fluctuations in protein concentration, pH, and conductivity due to the inherent periodic elution peaks from one or more bind and elute steps. While these fluctuations may be dampened with the use of surge tanks, in instances where no surge tank is implemented, the fluctuating fluid streams have the potential to negatively impact virus filter performance. Previous studies have shown that some virus filters are susceptible to virus particle passage or reduced throughput with high protein concentrations or high ionic strength buffers.To develop a small‐scale model for continuous virus filtration, it is necessary to consider two key differences between the batch unit operation and the integrated continuous unit operation. The first key difference is the concept of a discrete input and output versus dynamic input and output. In traditional batch mode purification, the downstream process flow path typically has hold tanks between each process step which allows for (a) load homogeneity, (b) discrete input volumes/concentrations for the subsequent unit operation, (c) control of optimized flow rate and pressure for each unit operation and for the virus filtrations step in particular, and (d) accommodation for filter replacement based on total throughput limits per filter  and a newer model parvovirus filter (Planova BioEX) in our filter studies. Our goal was to determine the impact of a continuous process on the filtration operating parameters typically used in biotechnology processes and viral clearance capabilities of virus filters. The flow rates chosen for the studies presented in this work were dictated by the desire to maintain the pressures on the filters within the recommended limits established by the filters manufacturer when applicable (Planova BioEX) or from historical or published data (Planova 20N).22.12 effective surface area) from Asahi Kasei Medical  were used for the extended processing and peak mimicking studies. Nalgene Rapid‐Flow PES bottles (0.2 μm) from Thermo Fisher Scientific  were used as prefilters.Planova 20N and BioEX filters  was purchased from SeraCare Life Sciences . Sodium acetate, sodium chloride, and sodium hydroxide were purchased from Fisher Scientific .2.2.26 PFU/ml at the start of each day, prefiltered using 0.2 μm Nalgene Rapid Flow PES bottles, and applied to the virus filters daily for 4 days. Aliquots of spiked feed and 12 ml samples of the filtrate collected daily were stored at −80°C until plaque assays were conducted. Proportions of the filtrates from each day were pooled together to create a simulated pool at the end of each filtration. Large volume testing was performed on simulated pool samples. Log10 reduction values (LRV) were calculated by subtracting the log10 of the total virus in the filtrate from the log10 of the virus load applied to the filter.Crude bacteriophage PP7 was prepared and plaque assays were performed according to PDA TR‐41: Virus Filtration.2.2.3In order to conduct continuous filtration experiments for up to 4 days, the filtration setup was configured to have two load reservoirs connected to the feed line with a three‐way valve that can be switched between the reservoirs daily to allow uninterrupted virus filtration while supplying freshly spiked load material daily Figure . The flo2.2.4Virus filtration runs were conducted at constant flow starting at around 7 and 28.4 psi for Planova 20N and BioEX filters, respectively. Filtrations were ended if the pressure reached the manufacturer recommended pressure limits of 14.2 or 49.7 psi, respectively. Prior to filtration, the filter was primed with 10–15 ml of deionized water. For each filter type, commercially available h‐IgG was diluted at a relatively low concentration due to low purity of the material in 50 mM acetate and 20 mM sodium chloride buffer at pH 6.0. The diluted h‐IgG solution was prepared for each filtration and stored at 4°C for the duration of the run. Aliquots were obtained daily, spiked with PP7, pre‐filtered, then loaded into the virus filter at a specific flow rate  adjusted to create a buffer peak across the filters using two different load materials, A and B. The diluted h‐IgG concentrations and buffer concentrations can be seen in Table 2.3.27 PFU/ml for both load materials A and B. For high phage and the triple spike runs, load material A had a PP7 spike target of 106 PFU/ml, while load material B had a PP7 spike target of 108 PFU/ml to provide a 100‐fold increase in virus particles without overloading the filter membrane.Load materials A and B were freshly spiked with PP7 to the target shown in Table 2.3.310 ml of inlet line A1 20 ml of inlet line A2 (Load A)10 ml Step Gradient: 100% line B1 (Load B)20 ml of inlet line A2 (Load A)In order to mimic the properties of an elution peak, the virus filters were connected to the column selection valve of an AKTA Avant 25 , a baseline load was applied using pump A, and a step gradient of the simulated elution peak was applied using buffer pump B  were performed at constant flow rate of 0.5 and 1.0 ml/min (30 and 60 LMH), respectively. Flow rates were set to avoid exceeding manufacturer recommended pressure limits. Pressure was monitored by the AKTA “Pre‐Column” pressure sensor and/or using in‐line pressure sensors with external pressure monitor (SciLog PureTec) connected between the column selection valve and the filter. Each filter was primed with at least 20 ml of deionized water, all AKTA inlet lines and flow paths were sanitized with 0.5 M NaOH, and all buffer inlet lines were primed with respective buffers . Load samples from each day (Days 0–3), filtrate samples from each day (Filtrates 1–4), and a simulated filtrate pool sample were collected. PP7 titers were obtained using plaque assay. Large volume testing was performed on the filtrate pool samples. Titer results and calculated PP7 LRV are presented in Table 2, well above what can be expected from a batch process.The goal of these studies was to use Planova 20N filters in a continuous virus filtration setup. Planova 20N filtrations with PP7‐spiked h‐IgG solutions were carried out for 4 days. A starting pressure of 7 psi was chosen due to previously determined low‐pressure limit.y Days 0–, filtratWhile both Planova 20N filtrations were completed within the recommended pressure limits, a difference in the pressure profile of the two runs is observed, specifically after the first day of filtration. This indicates a permeability decay as filtration time increases beyond 8 hr. These results demonstrate the complexity of running a virus filter in a continuous setup as well as the need for better controls for the process. Additional controls may include installation of a bubble trap in‐line before the filters in order to prevent any microscopic bubbles in the load solution from affecting filter performance. Temperature control is also one of the parameters to consider for future studies. Finally, prefilter optimization or the inclusion of the prefilter inline could improve fouling contaminants.3.2Planova BioEX filtrations were performed using the conditions previously described and shown in Table 2 filter over 4 days, resulting in a total virus load of 9.8 log PFU (12.8 log PFU/m2). For Run 2, a total of 5.2 L of material was filtered over 3 days, resulting in a total virus load of 8.0 log PFU (10.5 log PFU/m2). Samples were collected as described for Planova 20N filtrations. Large volume testing was performed on the filtrate pool samples. Titer results and calculated PP7 LRV are presented in Table For Planova BioEX Run 1, a total of 6.9 L of material was loaded on the 0.001 m2, still achieving a greater throughput than a traditional batch process.In a traditional batch mode virus filtration step, the expectation is that two runs with similar load materials would result in similar pressure profiles. The same cannot be said of long‐duration virus filtrations. The performance of the Planova BioEX filters over two runs appears identical over 2 days (48 hr of filtration), but in this case a small load variation resulted in a greater difference in the pressure profile. Future control measures were discussed in the previous section for Planova 20N filters and can also be implemented for Planova BioEX filtrations in the future. Overall, the results show that Planova BioEX filters can be used in a continuous processing setup and achieve effective virus removal. The observed throughout from these runs was between 5,200 and 6,900 L/m3.32 with the first 20 L/m2 consisting of a baseline load of PP7‐spiked h‐IgG followed by 10 L/m2 mock peak and finally 20 L/m2 of baseline load, as mentioned previously. Because of the potential for the Load B spike to cause a pressure increase, experimental flow rates were selected that allowed for a significant increase in pressure without exceeding the filter limit. For the Planova 20N experiments, a flow rate of 0.5 ml/min (flux of 30 LMH) provided a baseline pressure of approximately 7 psi. For Planova BioEX experiments, a flow rate of 1.0 ml/min (flux of 60 LMH) provided a baseline pressure of approximately 20 psi. For both Planova 20N and BioEX filters, the Avant pump programming was able to successfully recreate elution peaks as seen by the conductivity and UV traces obtained when the filters were connected so the permeate flowed through the Avant sensors , suggesting that proper design of small‐scale studies is required based on the virus being tested as parvoviruses, PPV and MMV, are smaller than PP7 and may report passage at a lower load threshold.Planova 20N filter studies were run at a constant flow rate of 0.5 ml/min for a total run time of 120 min post flushing. For the Planova 20N filters, PP7 was detected in at least one duplicate run for each test condition with sample PP7 LRV ranging from 3.1 to >7.61 Table . PP7 pasns Table . These fPlanova BioEX filter studies were run at a constant flow rate of 1.0 ml/min to provide sufficient pressure, resulting in a total run time of 60 min post flushing. Due to the short run times, a single load was made for each study condition with distinct filter runs performed on the same day in series. The data from the Planova BioEX filters demonstrated robustness with respect to virus removal capabilities. There was no PP7 detected in any sample for any of the test conditions, with PP7 LRV ranging from >5.30 to >8.14 for peak fraction samples. This includes high protein and triple spike runs where the filter pressure increased during the mock spike and conditions where the total PP7 PFU loaded exceeded 10 log PFU (Table 4For a truly continuous manufacturing process, all upstream and downstream manufacturing steps are integrated with a continuous flow of product, which is in contrast to numerous hold tanks in traditional batch mode. For process steps that remain similar to traditional batch manufacturing, such as virus filtration, the impact of both a dynamic fluid stream and extended processing times must be understood. While there has been recent published research on continuous chromatography and continuous viral inactivation, there has been little published data on the impact of continuous manufacturing on virus filtration. This study provides both novel ideas when considering small‐scale design for mimicking continuous virus filtration conditions, including extended filtration process times and dynamic loading conditions, and experimental data to support the implementation into a continuous manufacturing setting. The extended processing small‐scale investigational studies overcame the concern of virus spike stability by allowing for a daily refresh of virus spike with minimal impact on the filtration process. The small‐scale investigational dynamic load studies using an AKTA Avant system successfully mimicked an elution peak spike being processed through a virus filter. The data show that both Planova 20N and Planova BioEX filtration pressure is only impacted by high protein concentrations present in an elution peak. While the pressure is reduced after passage of the elution peak, baseline pressure is not always achieved post spike. Further experiments mimicking multiple elution peaks in series would be needed to test if pressure limits would be exceeded, limiting the lifetime of the virus filters, and to see if periodic pressure fluctuations can impact virus passage. In terms of virus removal capabilities, the results of the small‐scale studies demonstrate that the Planova 20N and BioEX filters are both robust with respect to extended processing times and mock elution peaks. The only factor of the mock elution peak affecting virus removal was total virus loaded onto the Planova 20N filter, a known concernThis manuscript reflects the views of the authors and should not be construed to represent FDA's views or policies.This manuscript is not an FDA endorsement of one specific virus filter.


Plant traits and aphid biological parameters were examined under two climate and atmospheric scenarios, current (ambient CO2 and temperature = 400 ppm and 20 °C), and future predicted (elevated CO2 and temperature = 800 ppm and 22 °C), on non-infected and BYDV-PAV-infected plants. Our results show that combined elevated CO2 and temperature increased plant growth, biomass, and carbon to nitrogen (C:N) ratio, which in turn significantly decreased aphid fecundity and development time. However, virus infection reduced chlorophyll content, biomass, wheat growth and C:N ratio, significantly increased R. padi fecundity and development time. Regardless of virus infection, aphid growth rates remained unchanged under simulated future conditions. Therefore, as R. padi is currently a principal pest in temperate cereal crops worldwide, mainly due to its role as a plant virus vector, it will likely continue to have significant economic importance. Furthermore, an earlier and more distinct virus symptomatology was highlighted under the future predicted scenario, with consequences on virus transmission, disease epidemiology and, thus, wheat yield and quality. These research findings emphasize the complexity of plant–vector–virus interactions expected under future climate and their implications for plant disease and pest incidence in food crops.Climate change impacts crop production, pest and disease pressure, yield stability, and, therefore, food security. In order to understand how climate and atmospheric change factors affect trophic interactions in agriculture, we evaluated the combined effect of elevated carbon dioxide (CO Remarkably, 70% of the increase occurred in the last 60 years, with current CO2 concentrations surpassing 400 ppm. By the end of the century, equivalent CO2 concentration will reach 720–1000 ppm, which is estimated to increase global surface temperature by 2.2 °C , did not differ significantly due to CO2&T conditions nor virus infection   . Significant effects of climate and atmospheric conditions and BYDV-PAV infection on wheat traits and aphid biological parameters are summarized in 2 concentration and global temperature on Earth will increase [2 [2 and eT.By the end of this century, atmospheric COincrease , directlincrease . To daterease [2 ,47,48,66rease [2 ,27,45. T2&eT directly affects wheat growth depending on virus infection, and that eCO2&eT and virus infection directly influences the rest of wheat plants parameters, similar to when evaluating the effect of eCO2 solely for the same wheat cultivar [R. padi growth rate under eCO2&eT is similar to when grown under ambient conditions, so the combination of the two climatic factors could have a neutral effect on R. padi fitness when reared on non-infected or BYDV-PAV-infected plants, contrarily to the reduction in the growth rate for R. padi developed on non-infected wheat under the sole effect of eCO2 [We have found that eCOcultivar . However of eCO2 .2&eT differed depending on the plant variable. Typical virus symptoms, such as leaf discoloration (chlorophyll content reduction), developed earlier and were more distinct under eCO2&eT than under aCO2&aT conditions, which is consistent with other findings under higher temperature [2 [2&eT compared to those under aCO2&aT but a decrease in the number of tillers due to virus infection under eCO2&eT, as has been similarly described when BYDV-wheat plants were grown under eCO2 [All plant parameters analyzed in our study (except number of tillers) were influenced by BYDV-PAV infection, but the effect of eCOperature  or eCO2 ature [2 ,15. Our der eCO2 ,67 or under eCO2 . Hence, 2 that increases biomass and yield is commonly recognised in wheat [2 [2 but not as a result of eT nor of the interaction [2&eT, and there was a significant reduction in biomass due to virus infection under eCO2&eT and under aCO2&aT. In other studies, the positive effect of CO2 fertilization has been offset by increasing temperatures, therefore wheat grain yield and biomass could be reduced in the future [2 is only achieved when plants develop within the interval of optimal temperature for their growth [The fertilising effect of eCOin wheat , oat [15in wheat ,18,22,69wheat [2  but alsowheat [2  in wheateraction . In our e future ,71. Thusr growth . The frer growth ,74. 2 increases plant growth rate [2 combined with higher temperature also increased the growth rate of non-infected and BYDV-PAV-infected wheat. Nevertheless, BYDV infection prolonged wheat development time and virus symptomatology were more distinct under eCO2&eT. This could have additional implications on disease epidemiology, wheat yield and quality in the future. Elevated COwth rate ,69. In o2 [2&eT combined [R. padi fecundity under eCO2&eT could be attributed to the changes in the quantity and quality of plant N [2&eT than aCO2&aT; however, R. padi growth rate was not significantly different under eCO2&eT when compared to aCO2&aT. Decreased fecundity can indicate lower aphid population levels, but if it is offset by a shorter development time, as shown here, we are inclined to conclude that aphid numbers will likely remain unchanged in the future. Growth rates (mr or RGR) refer to the rate at which a population grows and balances the relationship between fecundity and development time; therefore, no differences in our R. padi growth rates indicate that there will be no change in the speed of growth of the aphid population under the future climate and atmospheric conditions that we established. Rhopalosiphum padi is currently a major aphid pest in temperate cereal crops worldwide [2 on herbivores could be offset by eT, and that the responses of cereal aphid populations to the two interrelated factors will be more similar to current ambient conditions than the expected future conditions when examining the factors separately. It further showed that the divergence in cereal aphid performance could be based on N limitation. Large N availability under eCO2, due to high soil N fertility and low aphid N requirements, could probably increase aphid populations; however, eT would reduce this effect [2 singly showed a decline in abundance of R. padi under eCO2 in a pasture grass [R. padi fecundity and in growth rates reared on non-infected wheat under eCO2, which could indicate lower aphid pest pressure. Conversely, other research showed a different trend in R. padi population on wheat, with an increase in fecundity therefore population under eCO2 [2 and eT combined [2, R. maidis (Fitch) increased its performance and produced higher number of winged aphids, which could increase the spread of plant viruses and exacerbate aphid damage on barley crops [2 concentration and temperature increases, etc. could explain the contrasting results and highlight potential aphid/host plant specificity. Reduction in N content has been observed in multiple plant species under eCO2 ,25,27,69combined , as-in ocombined ,75 there plant N ,44. In oorldwide . If the orldwide  reporteds effect ,37. Othere grass . Moreoveder eCO2  or an incombined . Furtherey crops . OverallR. padi increases alate production particularly when reared on virus-infected plants [2 affects symptomatology of plant viruses, enhancing earlier or greater differences (leaf discoloration) in infected plants, making them more attractive to insect vectors [2 can alter the epidemiology of BYDV by increasing the virus persistence of infected oat plants [2 also affects R. padi feeding behavior and therefore the potential for virus acquisition and transmission efficiency [2 on virus infection can be pathosystem- or even genotype-specific [R. padi to transmit BYDV-PAV usually increases as temperature rises inside the optimal thermal thresholds [2 and eT. Under eCO2, virus infection also increased N content in BYDV-infected plants, which can explain greater host suitability for R. padi [R. padi growth rate remained unchanged when aphids were grown on BYDV-PAV-infected plants under eCO2&eT compared to aCO2&aT. The earlier virus symptomatology found under eCO2&eT could make virus-infected plants more attractive to aphids. Within the same pathosystem that we analyzed, BYDV-PAV titer in wheat plants increased under eCO2 [A virus can modify host plants and vector behavior to enhance its spread under ambient conditions ,78,79,80d plants . Therefod plants . Elevate vectors ,38. Elevt plants  and the t plants . Furtherficiency . The effspecific ,85. In aspecific . The effresholds ,86. In o R. padi . Howeverder eCO2  when assR. padi growth rate as shown in our study is attributed to the combined effects of temperature and CO2, as an increase in temperature usually shortens insect development time while eCO2 indirectly affects aphid fecundity due to the lower nutrition quality of the host plant. Further research is needed to elucidate the impact of the combination of eT and eCO2 on the pathosystem considered by studying the attractiveness of R. padi to non-infected and virus-infected plants and by examining the virus titer in order to understand the potential virus dispersion and transmission under future climate and atmospheric conditions. Moreover, other abiotic factors, such as water stress or ozone, should be considered, to allow a more realistic prediction of the impact on food security due to the variations on pests and diseases under changing climate. We hypothesize that the neutral effect on Plant, insect herbivore, and pathogen responses to climate change can be specific to each level of the multitrophic system  and to t2 and temperature as predicted by 2100 will impact a particular plant–vector–virus system differently depending on virus infection. Under eCO2&eT, virus symptomatology in wheat developed earlier, which could increase visual attraction of R. padi to BYDV-infected plants and lead to an increase in virus spread prompting additional implications on disease epidemiology, therefore affecting wheat yield and quality in the future. Our study shows that simultaneous increase in COR. padi fecundity under eCO2&eT could be attributed to the reduction in plant N content. BYDV-PAV infection compensated partially this N dilution and increased R. padi fecundity and development time. However, independently of virus infection, aphid growth rates did not differ due to climate conditions. As R. padi is currently a major aphid pest in temperate cereal crops worldwide, if its population levels remain unchanged in the future, this aphid species will continue to have a significant economic importance, mainly due to its role as a virus vector. Nitrogen is essential for aphid biological functions thus, the decrease in This type of forecast studies highlights the importance of the effects of climate change on virus vectors and provides important information which can aid in the development of effective crop protection strategies to ensure the global food security.


Methanosarcina virus MV (MetMV), the second Methanosarcina sp. virus with a completely determined genome, is characteristic of hydrocarbon pollution in environmental (soil and water) samples. It was highly abundant in Hungarian hydrocarbon polluted samples and its genome was also present in the NCBI SRA database containing reads from hydrocarbon polluted samples collected in Canada, indicating the stability of its niche and the marker feature of this virus. MetMV, as the only currently identified marker virus for pollution in environmental samples, could contribute to the understanding of the complicated network of prokaryotes and their viruses driving the decomposition of environmental pollutants.Metagenomics is a helpful tool for the analysis of unculturable organisms and viruses. Viruses that target bacteria and archaea play important roles in the microbial diversity of various ecosystems. Here we show that  There is a recent trend in identifying viruses from metagenomic sequences , 2.The metagenomic analysis is a useful tool to analyze uncultured prokaryotic abundance and monitor prokaryotic processes and interactions during bioremediation  and to oIt is important to know the dynamic changes of viral environments. Characterizing the virome of a metagenomic sample is frequently hindered by the phenomenon called viral dark matter, i.e. the fact that a high proportion (40–90%) of sequences from a metagenome cannot be aligned to any known organism . KrishnaMetagenomics analyses of bacterial and archaea viruses are carried out without culturing them. Therefore, their host, usually determined using a culture-based method, remains unknown. Several computational approaches exist to predict bacteriophage and archaea virus hosts, including the comparison of host and virus abundance profile, genetic homology, CRISPR analysis, exact matches of sequences between host and virus, and comparison of oligonucleotide profiles . Each ofPhages and archaeal viruses play a crucial role in the dynamics of microbial diversity in various ecosystems –11, althSampling was based on the order (number 4184-20/2015) of the Government Office of Baranya County. The GPS coordinates of the sampling sites were: B1: 46°22'37.1"N 17°53'52.1"E, B2: 46°22'36.6"N 17°53'48.4"E, B3: 46°22'35.5"N 17°53'49.3"E and B4: 46°22'36.5"N 17°53'51.4"E. The sampled location was used as a military base and airport of the Hungarian army between 1936–1995 and by the US forces between 1995–2004. B1 was located directly at a damaged underground gas oil tank, B2 approximately 10 m from B1, B4 at a damaged gas oil pipeline, and B3 was drilled outside of the military base fence as a control. Samplings were carried out with a Borro driller, diameter 65 mm, and samples were taken from each hole at three depths: 0.8–1.0m, 5.0–5.5m and 7.0–7.5 m. Samples were stored in sealed glass bottles at +4 °C until analysis.DNA isolation occurred in three parallels from each sample using the PowerSoil Max kit  following the protocol provided by the producer. DNA library was prepared with Nextera XT DNA Library Prep kit  and the library sequenced paired-end on an Illumina MiSeq next-generation sequencer  using a V3 600 cycles kit , according to the protocol of the kit producers.TPH concentration was analyzed with a CVH InfraCal TOG/PTPH Analyzer which, was calibrated in the 125–2000 ppm range.Next-generation reads were analyzed for quality using the FastQC program (version 0.11.5) with default parameters. Low-quality bases and reads were trimmed and/or removed using the Trim galore (version 0.4.4 with paired mode) and Trimmomatic (version 0.36 with paired mode and using the CROP:150 MINLEN:150 parameters) programs . The quaDuring the downstream analysis, an assembled unknown 67,826 nucleotide long sequence, a potential archaeal virus genome, was used as a reference. The quality trimmed reads were aligned to this reference sequence with the bwa mem program (version 0.7.12-r1039) with default settings and paired mode . RedundaCRISPR spacer sequences were downloaded from CRISPRdb  (Last upftp://ftp.ccb.jhu.edu/pub/infphilo/centrifuge/data/p_compressed+h+v.tar.gz (Last updated 12/06/2016).The abundance profiles of bacteria in the analyzed samples were calculated by the Centrifuge program version 1.0.3-beta  using paMethanosarcina barkeri str. Fusaro reference sequence was downloaded from NCBI (Accession ID: NC_007355.1) and used for the calculation. The parameters were–m 4 searching for tetramers and using hash size–s 4560M. The same parameters were used for the MetMV virus sequence. The shuffleseq program from the EMBOSS software suite [Methanosarcina genome sequence.Tetramer nucleotide abundance values were calculated using the Jellyfish program . The Metre suite  was usedAnalyzing the samples, the quality-trimmed reads were mapped back to the de novo assembled MetMV virus contig and the mapped reads were counted by the samtools idxstats tool. The number of mapped reads were normalized for the fastqc library size. The average was calculated from the normalized results of the three DNA samples originating from the same soil sample.Additionally, in the analysis of the SRA samples, the percentage of the covered bases of the sequence was counted. It was previously shown that this could be used to indicate the viral presence in metagenomic samples , 27. A 7de novo assembler methods from DNA samples originating from deep (7.5–8.5 m) soil samples and contaminated with hydrocarbon pollutant.Next generation reads were generated from the samples using the Illumina Miseq platform. During the sequencing process, we obtained from 64,268 to 2,739,140 raw and from 50,323 to 2,395,890 high quality trimmed paired-end reads indicating the loss of a small fraction during the quality filtering process. From this data, different complement analyses were carried out to find specific viruses from the hydrocarbon contaminated soil. In this habitat, microorganisms whose viruses have not been well characterized can be found, especially anaerobic archaeal lifeforms. These viruses could potentially be used as indicators for those archaea which often difficult to detect with classical biological methods. Initially, the next generation reads were assembled with Further analysis was carried out on contigs longer than 60 kbp. A 67,826 bp long contig was selected from a sample obtained at a depth of 7.5 m at the B1 location. It was searched against the NCBI viral and full nucleotide collection, but no similarity was found with the database sequences. The genome of the newly discovered virus (named MetMV) was circular and 8,697 bp direct terminal repeats were detected .de novo sequence. Abundances from the number of mapped reads were counted by normalizing for the sequencing library size. The presence of this virus was detected in four samples, where the percentage of viral mapped reads was between 0.1 and 8.4  in the samples, the trimmed reads were mapped back to the generated  and 8.4 .Additionally, in the Prokka annotation, only hypothetical proteins from the predicted 39 open reading frames (ORFs) were found. A function was assigned to 14 ORFs with manual curation .in vitro system. On the other hand, when non-cultivation-based methods are used, various in silico tools are available for estimation of the host for isolated archaeal virus [The relationship between archaeal viruses and their unknown hosts is often difficult to determine using laboratory methods as these microorganisms are typically hard to grow in an artificial al virus .Methanosarcina mazei S-6 and Methanocaldococcus vulcanius M7 which were anaerobe methanogen archaea. The MetMV virus abundance was calculated from the aligned reads and compared to Methanosarcina sp. homologue reads, which were identified using the Centrifuge classification engine [Methanosarcina sp. raw read abundance and library size normalized abundance  were calculated and compared to the MetMV raw read and library size normalized abundance values. Strong correlations  were detected in case of Methanosarcina sp. Additionally, a third method was applied for host prediction analysis, the k-mer frequency of genome sequences. The Jellyfish program [Methanosarcina barkeri str. Fusaro and three further frequency datasets were generated using shuffleseq [Methanosarcina sp. genome but nucleotide order of the sequence was randomly shuffled. This negative control provided the same length and 1-nucleotide frequency (content) as the investigated genome. However, tetramer frequencies were altered (in a random manner). In the case of real data and the average value of three randomly shuffled sequences (negative control), correlations between data for Methanosarcina sp. and MetMV virus were 0.66 and 0.5 respectively.Initially, a specific CRISPR spacer sequence which could be found in the virus was identified from the CRISPR database . These sn engine . Both th program  and tetruffleseq  for negaMethanosarcina genus and the MetMV virus genome. These results (Methanosarcina genus. It should be noted that MetMV’s G+C content (42.7 mol%) was slightly above that of Methanosarcina barkeri str. Fusaro’s (39.3 mol%). However, these data were close enough to indicate that a Methanosarcina sp. could be the host of MetMV [All three independent methods showed a strong correlation between the  results  strengthof MetMV .The occurrence of the MetMV virus was investigated in metagenomes originating from all the samples. No significant correlation could be detected between the TPH concentration of the samples and the proportion of reads which could be mapped to the MetMV. However, if samples were marked with 1 when polluted with TPH  or with 0 when non-polluted, and marked with 1 when the MetMV virus could be detected  or with 0 when absent , a signiMethanosarcina-infecting virus (MetSV), providing its 11 kb long complete genome sequence [A recent study characterized a sequence . Here, win silico approach was chosen to predict its host. We used different bioinformatics prediction methods to achieve the best possible result to connect the host and its virus. Because the CRISPR system binds host and virus together, it was a good method to search for historical events connected to viruses in the host genome. This prediction may be more reliable than those derived from other methods as it showed co-occurrence and was based on the hypothesis of co-evolution of bacteria/archaea and virus. To strengthen the result of this method, the other co-occurrence methods and tetranucleotide frequency were used in parallel, as each of these methods investigated different features of the metagenome, archaea and virus genome.A 67,826 bp long circular complete genome of a virus (named MetMV) was assembled from reads occurring with high frequency in a metagenome sequenced from a hydrocarbon polluted soil sample. The small proportion of annotated ORFs could be due to the viral dark matter, i.e. the fact that reads originating from a metagenome sequencing could not be assigned to any known organism , indicatMethanosarcina sp. archaea was predicted as host of MetMV using in silico tools. It should be highlighted that Methanosarcina sp. plays an important role in the bioremediation of hydrocarbon polluted soil [A ted soil .Prokaryotic viruses are essential in driving processes in microbial ecosystems and maintaining fluctuating selection . Host-vi2, acetate, methylamine, formate etc.) to methane [Methanogenesis is the process when anaerobic archaea convert small organic molecules (CO methane . Members methane .Bacillus sp., which produces a peptide under lytic conditions and releases it into the environment [Because prokaryotic viruses can act also at the sub-species level, influencing the metabolic properties of the clades, thus driving the formation of new ecotypes, as it was proven in coevolution experiments , we can ironment , or indiironment . Based oMethanosarcina sp. was predicted as host of MetMV and MetMV is the second Methanosarcina sp. virus whose complete genome has been determined until now. Occurrence of MetMV strongly correlates with the presence of hydrocarbon pollution in environmental samples.Complete genome of the virus MetMV was assembled from reads originating from metagenome of a hydrocarbon polluted soil sample. A Recently, it was found that crAssphage’s genome structure remained conserved in the stable environment of the human gut, possibly indicating the stability of this niche . crAssph