A Virtual Look at Epstein–Barr Virus Infection: Biological Interpretations
Computer simulation and mathematical modeling are receiving increased attention as alternative approaches for providing insight into biological and other complex systems 1 ., An important potential area of application is microbial pathogenesis , particularly in cases of human diseases for which applicable animal models are lacking ., To date , most simulations of viral pathogenesis have tended to focus on HIV 2–7 , and employ mathematical models based on differential equations ., None have addressed the issue of acute infection by the pathogenic human herpes virus Epstein–Barr virus ( EBV ) and its resolution into lifetime persistence ., With the ever-increasing power of computers to simulate larger and more complex systems , the possibility arises of creating an in silico virtual environment in which to study infection ., We have used EBV to investigate the utility of this approach ., EBV is a human pathogen , associated with neoplastic disease , that is a paradigm for understanding persistent infection in vivo and for which a readily applicable animal model is lacking ( reviewed in 8 , 9 ) ., Equally important is that EBV infection occurs in the lymphoid system , which makes it relatively tractable for experimental analysis and has allowed the construction of a biological model of viral persistence that accounts for most of the unique and peculiar properties of the virus 10 , 11 ., We are therefore in a position to map this biological model onto a computer simulation and then ask how accurately it represents EBV infection ( i . e . , use our knowledge of EBV to test the validity of the simulation ) and whether the matching of biological observation and simulation output provides novel insights into the mechanism of EBV infection ., Specifically , we can ask if it is possible to identify critical switch points in the course of the disease where small changes in behavior have dramatic effects on the outcome ., Examples of this would be the switch from clinically silent to clinically apparent infection and from benign persistence to fatal infection ( as occurs in fatal acute EBV infection and the disease X-linked lymphoproliferative 12 , for example ) , or to clearance of the virus ., Indeed , is clearance ever possible , or do all infections lead inevitably to either persistence or death ?, Such an analysis would be invaluable ., Not only would it provide insight into the host–virus balance that allows persistent infection , but it would also reveal the feasibility and best approaches for developing therapeutic interventions to diminish the clinical symptoms of acute infection , prevent fatal infection , and/or clear the virus ., A diagrammatic version of the biological model is presented in Figure 1 ., EBV enters through the mucosal surface of the Waldeyer ring , which consists of the nasopharyngeal tonsil ( adenoids ) , the paired tubal tonsils , the paired palatine tonsils , and the lingual tonsil arranged in a circular orientation around the walls of the throat ., Here EBV infects and is amplified in epithelium ., It then infects naïve B cells in the underlying lymphoid tissue ., The components of the ring are all equally infected by the virus 13 ., EBV uses a series of distinct latent gene transcription programs , which mimic a normal B cell response to antigen , to drive the differentiation of the newly infected B cells ., During this stage , the infected cells are vulnerable to attack by cytotoxic T cells ( CTLs ) 14 ., Eventually , the latently infected B cells enter the peripheral circulation , the site of viral persistence , as resting memory cells that express no viral proteins 15 and so are invisible to the immune response ., The latently infected memory cells circulate between the periphery and the lymphoid tissue 13 ., When they return to the Waldeyer ring they are occasionally triggered to terminally differentiate into plasma cells ., This is the signal for the virus to begin replication 16 , making the cells vulnerable to CTL attack again 14 ., Newly released virions may infect new B cells or be shed into saliva to infect new hosts , but are also the target of neutralizing antibody ., Primary EBV infection in adults and adolescents is usually symptomatic and referred to as infectious mononucleosis ( AIM ) ., It is associated with an initial acute phase in which a large fraction ( up to 50% ) of circulating memory B cells may be latently infected 17 ., This induces the broad T lymphocyte immune response characteristic of acute EBV infection ., Curiously , primary infection early in life is usually asymptomatic ., In immunocompetent hosts , infection resolves over a period of months into a lifelong persistent phase in which ∼1 in 105 B cells carry the virus 18 ., Exactly how persistent infection is sustained is unclear ., For example , once persistence is established , it is unknown if the pool of latently infected memory B cells is self-perpetuating or if a low level of new infection is necessary to maintain it ., Indeed , we do not know for sure that the pool of latently infected B cells in the peripheral memory compartment is essential for lifetime persistence ., It is even unclear whether the virus actually establishes a steady state during persistence or continues to decay , albeit at an ever slower rate 17 ., In the current study we describe the creation and testing of a computer simulation ( PathSim ) that recapitulates essential features of EBV infection ., The simulation has predictive power and has utility for experiment design and understanding EBV infection ., One practical limitation of available simulation and modeling approaches has been their inaccessibility to the working biologist ., This is often due to the use of relatively unfamiliar computer interfaces and output formats ., To address these issues , we have presented the simulation via a user-friendly visual interface on a standard computer monitor ., This allows the simulation to be launched and output to be accessed and analyzed in a visual way that is simple and easily comprehensible to the non-specialist ., The computer model ( PathSim ) is a representation of the biological model described in the Introduction ., A schematic version of both is shown in Figure 1 ., To simulate EBV infection , we created a virtual environment consisting of a grid that describes a biologically meaningful topography , in this case the Waldeyer ring ( five tonsils and adenoids ) and the peripheral circulation , which are the main sites of EBV infection and persistence ., The tonsils and adenoids were composed of solid hexagonal base units representing surface epithelium , lymphoid tissue , and a single germinal center/follicle ( Figure 2A–2C; Video S1 ) ., Each hexagonal unit had one high endothelial venule ( HEV ) entry point from the peripheral blood and one exit point into the lymphatic system ( Figure 2A ) ., Discrete agents ( cells or viruses ) reside at the nodes ( red boxes ) of the 3-D grid ( white lines ) ., There they can interact with other agents and move to neighboring nodes ., Agents are assessed at regular , specified time intervals as they move and interact upon the grid ., Virtual cells were allowed to leave the Waldeyer ring via draining lymphatics and return via the peripheral blood and HEVs ( Figure 2A and 2B; Video S1 ) as in normal mucosal lymphoid tissue 19 ., A brief summary list of the agents employed in our simulation , and their properties and interactions , is given in Table 1 ., In this report we refer to actual B cells as , for example , “B cells” , “latently infected B cells” , or “lytically infected B cells” , and their virtual representations as “virtual B cells” , “BLats” , or “BLyts” ., Similarly , we refer to actual virus as virions and their virtual counterparts as virtual virus or Vir ., A full description of the simulation , including a complete list of agents , rules , the default parameters that produce the output described below , and a preliminary survey of the extended parameter space is presented in M . Shapiro , K . Duca , E . Delgado-Eckert , V . Hadinoto , A . Jarrah , et al . ( 2007 ) A virtual look at Epstein-Barr virus infection: simulation mechanism ( unpublished data ) ., Here , we will first present a description of how the virtual environment was visualized and then focus on a comparison of simulation output with the known biological behavior of the virus ., Simulation runs were accessed through an information-rich virtual environment ( IRVE ) ( Figures 2 and 3; Videos S1 and S2 ) , which was invoked through a Web interface ., This provided a visually familiar , straightforward context for immediate comprehension of the spatial behavior of the system 20 ., It also allowed specification of parameters , run management , and ready access to data output and analysis ., Figure 3 demonstrates how the time course of infection may be visualized ., Usually the simulation was initialized by a uniform distribution of Vir over the entire surface of the Waldeyer ring , thereby seeding infection uniformly ., However , in the simulation shown in Figure 3A , virtual EBV was uniformly deposited only on the lingual tonsil ., Figure 3B–3D shows the gradual spread of virtual infection ( intensity of red color indicating the level of free Vir ) to the adjacent tonsils ., It can be seen in this case that the infection spreads uniformly to all the tonsils at once , implying that it was spreading via BLats returning from the blood compartment and reactivating to become BLyts , rather than spreading within the ring ., Examples of infectious spread between and within the tonsils can also be seen in Video S2 ., In this paper we present a comprehensive model of EBV infection that effectively simulates the overall dynamics of acute and persistent infection ., The fact that this simulation can be tuned to produce the course of EBV infection suggests that it models the basic processes of this disease ., To achieve this , we have created a readily accessible , virtual environment that appears to capture most of the salient features of the lymphoid system necessary to model EBV infection ., Achieving infection dynamics that reflect an acute infection followed by recovery to long-term low-level persistent infection seems to require access of the virus to a blood compartment where it is shielded from immunosurveillance ., Because we cannot perform a comprehensive parameter search ( due to the very large parameter space involved ) , we cannot unequivocally state that the blood compartment is essential ., What is clear though , is that persistence is a very robust feature in the presence of a blood compartment , and that we could not achieve an infection process that even remotely resembles typical persistent EBV infection in its absence ., The areas in which the simulation most closely follows known biology are summarized in Table 2 and include the peak time of infection , 33–38 d , compared to the incubation time for AIM of 35–50 d 21 ., This predicts that patients become sick and enter the clinic at or shortly after peak infection in the peripheral blood , a prediction confirmed by our patient studies , where the numbers of infected B cells in the periphery always decline after the first visit 17 ., An important feature of a simulation is its predictive power ., Our analysis predicted that access to the peripheral memory compartment is essential for long-term persistence ., This is consistent with recent studies on patients with hyper-IgM syndrome 31 ., Although these individuals lack classical memory cells , they can be infected by EBV; however , they cannot sustain persistent infection and the virus becomes undetectable ., Unfortunately , those studies did not include a sufficiently detailed time course to see if time to virus loss coincided with the simulation prediction of 1–2 mo ., Another area where the simulation demonstrated its predictive power was in the dynamics of viral replication ., In the simulation it was unexpectedly observed that the level of Vir production plateaued long before BLats , predicting that the levels of virus shedding , unlike latently infected cells , will have leveled off by the time AIM patients arrive in the clinic ., This prediction , which contradicted the common wisdom that virus shedding should be high and decline rapidly in AIM patients , was subsequently confirmed experimentally ( V ., Hadinoto , M . Shapiro , T . Greenough , J . Sullivan , K . Luzuriaga , D . Thorley-Lawson ( 2007 ) On the dynamics of acute EBV infection and the pathogenesis of infectious mononucleosis ( unpublished data ) and see also 22 , 23 ) ., The simulation also quite accurately reproduces the relatively large variation in virus production over time , compared to the stability of B latent ., This difference is likely a consequence of stochasticity ( random variation ) having a relatively larger impact on virus production ., This is because the number of B cells replicating the virus at any given time is very small , both in reality and the simulation , compared to the number of infected B cells , but the number of virions they release when they do burst is very large ., This difference may reflect on the biological requirements for persistence of the virus since a transient loss in virus production due to stochasticity can readily be overcome through recruitment from the pool of B latents ., However , a transient loss of B latents would mean clearance of the virus ., Hence , close regulation of B latent but not virion levels is necessary to ensure persistent infection ., Although there is now a growing consensus that EBV infects normal epithelial cells in vivo 27–29 , the biological significance of this infection remains unclear ., The available evidence suggests that epithelial cell infection may not be required for long-term persistence 25 , 26 , and this is also seen in the simulation ., The alternate proposal is that epithelial infection might play an important role in amplifying the virus , during ingress and/or egress , as an intermediary step between B cells and saliva ., This is based on the observation that the virus can replicate aggressively in primary epithelial cells in vivo 30 ., In the simulation , epithelial amplification had no significant effect on the ability of Vir to establish persistence ., This predicts that epithelial amplification does not play a critical role in entry of the virus , but leaves open the possibility that it may be important for increasing the infectious dose present in saliva for more efficient infection of new hosts ., The simulation is less accurate in the precise quantitation of the dynamics ., Virtual acute infection resolves significantly more slowly and persistence is at a higher level than in a real infection ., In addition , virtual persistent infection demonstrates clear evidence of oscillations in the levels of infected cells that have not been detected in a real infection ., The most likely explanation for these discrepancies is that we have not yet implemented T cell memory ., Thus , as the levels of virtual infected cells drops , the immune response weakens , allowing Vir to rebound while a new supply of virtual CTLs is generated ., Immunological memory would allow a more sustained T cell response that would produce a more rapid decline of infected cells , lower levels of sustained persistence , and tend to flatten out oscillatory behavior , thus making the simulation more quantitatively accurate ., This is one of the features that will be incorporated into the next version of our simulation ., It remains to be determined what additional features need to be implemented to sharpen the model and also whether and to what extent the level of representation we have chosen is necessary for faithful representation of EBV infection ., Our simulation of the Waldeyer ring and the peripheral circulation was constructed with the intent of modeling EBV infection ., Conversely , our analysis can be thought of as the use of EBV to validate the accuracy of our Waldeyer ring/peripheral circulation simulation and to evaluate whether it can be applied to other pathogens ., Of particular interest is the mouse gamma herpesvirus MHV68 32 , 33 ., The applicability of MHV68 as a model for EBV is controversial ., Although it also persists in memory B cells 34 , it appears to lack the sophisticated and complicated latency states that EBV uses to access this compartment ., However , one of the simplifications in our simulation is that the details of these different latency states and their transitions are all encompassed within a single concept , the BLat ., We have also assumed a time line whereby a newly infected BLat becomes activated and CTL sensitive , migrates to the follicle , and exits into the circulation , where it is no longer seen by our virtual CTLs ., In essence , we have generalized the process by which the virus proceeds from free virion to the site of persistence in such a way that it may be applicable to both EBV and MHV68 ., Thus , we might expect that the overall dynamics of infection may be similar even though detailed biology may vary ., As a first step to test if this concept had value , we performed an analysis based on studies with MHV68 where it was observed that the levels of infected B cells at persistence were unaffected by the absolute amount of input virus at the time of infection 35 ., When this parameter was varied in the simulation , we saw the same outcome ., This preliminary attempt raises the possibility that the mouse virus may be useful for examining quantitative aspects of EBV infection dynamics ., The last area we wished to investigate was whether we could identify biologically meaningful “switch” points , i . e . , places in time and space where relatively small changes in critical parameters dramatically affect outcome , for example , switching from persistence to clearance to death ., We have observed one such switch point—reactivation of BLats upon return to the Waldeyer ring—that rapidly switches the infection process from persistence to death ., How this might relate to fatal EBV infection , X-linked lymphoproliferative disease , is uncertain ., However , viral production is a function both of how many B cells initiate reactivation and how efficiently they complete the process ., We believe that most such cells are killed by the immune response before they release virus 16 , so defects in the immune response could allow more cells to complete the viral replication process and give the same fatal outcome ., The ability to find such conditions for switch points could be very useful in the long term for identifying places in the infection process where the virus might be optimally vulnerable to drug intervention ., The easiest place to target EBV is during viral replication; however , it is currently unclear whether viral replication and infection are required for persistence ., It may be that simply turning off viral replication after persistence is established fails to eliminate the virus because the absence of new cells entering the pool through infection is counterbalanced by the failure of infected cells to disappear through reactivation of the virus ., If , however , a drug allowed abortive reactivation , then cells would die without producing infectious virus and new infection would be prevented ., This models the situation that would arise with a highly effective drug or viral mutant that blocked a critical stage in virion production ( e . g . , viral DNA synthesis or packaging ) , so that reactivation caused cell death without release of infectious virus ., A similar effect could be expected with a drug or vaccine that effectively blocked all new infection ., This is another case in which studies with the mouse virus , where non-replicative mutants can be produced and tested , may be informative as to whether and to what extent infection is required to sustain the pool of latently infected B cells and persistence ., The simulation could then be used to predict how effective an anti-viral that blocked replication , or a vaccine that induced neutralizing antibodies , would need to be at reducing new infection in order to cause EBV to be lost from the memory pool ( for a more detailed discussion of this issue see M . Shapiro , K . Duca , E . Delgado-Eckert , V . Hadinoto , A . Jarrah , et al . ( 2007 ) A virtual look at Epstein-Barr virus infection: simulation mechanism ( unpublished data ) ) ., Most modeling of virus infection to date has tended to focus on HIV and use differential equations 2–7 ., One such study involved EBV infection 36 , but to our knowledge none outside of our group has addressed the issue studied here of acute EBV infection and how it resolves into lifetime persistence ., In preliminary studies of our own , modeling EBV infection with differential equations that incorporate features common to the HIV models , with parameters physiologically reasonable for EBV did not produce credible dynamics of infection ( K . Duca , unpublished observations ) ., Although we do not exclude the possibility that such models may be useful for simulating EBV , we took an agent-based approach because it is intuitively more attractive to biologists ., Such models are increasingly being recognized as an effective alternative way to simulate biological processes 37–39 and have several advantages ., The main advantage is that the “agent” paradigm complies by definition with the discrete and finite character of biological structures and entities such as organs , cells , and pathogens ., This makes it more accurate , from the point of view of scientific modeling ., It is also less abstract since the simulated objects , processes , and interactions usually have a straightforward biological interpretation and the spatial structure of the anatomy can be modeled meticulously ., The stochasticity inherent to chemical and biological processes can be incorporated in a natural way ., Lastly , it is generally much easier to incorporate qualitative or semi-quantiative information into rule sets for discrete models than it is for such data to be converted to accurate rate equations ., The major drawback to agent-based models is that there is currently no mathematical theory that allows for rigorous analysis of their dynamics ., Currently , one simply runs such simulations many times and performs statistical analyses to assess their likely behaviors ., Developing such a mathematical theory remains an important goal in the field ., In summary , we have described a new computer simulation of EBV infection that captures many of the salient features of acute and persistent infection ., We believe that this approach , combined with mouse modeling ( MHV68 ) and EBV studies in patients and healthy carriers , will allow us to develop a more profound understanding of the mechanism of viral persistence and how such infections might be treated and ultimately cleared ., Details of the AIM patient populations tested have been published previously 17 ., Adolescents ( ages 17–24 ) presenting to the clinic at the University of Massachusetts at Amherst Student Health Service ( Amherst , Massachusetts , United States ) with clinical symptoms consistent with acute infectious mononucleosis were recruited for this study ., Following informed consent , blood and saliva samples were collected at presentation and periodically thereafter ., Diagnosis at the time of presentation to the clinic required a positive monospot test and the presence of atypical lymphocytes 21 ., Confirmation of primary Epstein–Barr infection required the detection of IgM antibodies to the EBV viral capsid antigen in patient sera 40 ., These studies were approved by the Human Studies Committee at the University of Massachusetts Medical School ( Worcester , Massachusetts , United States ) and by the Tufts New England Medical Center and Tufts University Health Sciences Institutional Review Board ., All blood samples were diluted 1:1 in 1x PBS ., The technique for estimating the absolute number of latently infected B cells in the peripheral blood of patients and healthy carriers of the virus is a real-time PCR–based variation of our previously published technique 17 , the details of which will be published elsewhere ( V ., Hadinoto , M . Shapiro , T . Greenough , J . Sullivan , K . Luzuriaga , et al . ( 2007 ) On the dynamics of acute EBV infection and the origins of infectious mononucleosis ( unpublished data ) ) ., To measure the absolute levels of virus shedding in saliva , individuals were asked to rinse and gargle for a few minutes with 5 ml of water and the resultant wash processed for EBV-specific DNA PCR using the same real-time–based PCR technique ., We have performed extensive studies to standardize this procedure that will be detailed elsewhere ( V ., Hadinoto , M . Shapiro , T . Greenough , J . Sullivan , K . Luzuriaga , et al . ( 2007 ) On the dynamics of acute EBV infection and the origins of infectious mononucleosis ( unpublished data ) ) ., In the simulation , B cells are either uninfected ( BNaïve ) , latently infected ( BLat ) , or replicating virtual virus ( BLyt ) ; we do not distinguish blast and memory B cells ., In the biological model , newly infected B cells in the lymphoepithelium of the Waldeyer ring pass through different latency states , which are vulnerable to attack by cytotoxic T cells ( CTL latent ) ., Subsequently , they become memory B cells that enter the peripheral circulation and become invisible to the immune response by turning off viral protein expression ., In the simulation , all these latency states are captured in the form of a single entity , the BLat ., In addition , the blood circulation and lymphatic system are both represented as abstract entities that only allow for transport of BNaïves and BLats around the body ., Virtual T cells are restricted to the Waldeyer ring ., This simplification is based on the assumption that , in the biological model , EBV-infected cells entering the peripheral circulation are normal and invisible to CTLs , because the virus is inactive , and therefore the peripheral circulation simply acts as an independent pool of and a conduit for B latent ., Operationally , therefore , BLats escape TLats in the simulation simply by entering the peripheral circulation ., Consequently , unlike the biological model , BLats are vulnerable to TLats whenever they reenter the lymph node ., Each agent ( e . g . , Vir or a BNaïve ) has a defined life span , instructions for movement , and functions that depend on which other agents they encounter ( for example , if a Vir encounters a BNaïve , it infects it with some defined probability ) ., The agents , rules , and parameters used are based on known biology wherever possible with simplifications ( see above ) where deemed appropriate ., A brief description and discussion of the agents and their rules is given in Table 1 ., A detailed listing is provided in M . Shapiro , K . Duca , E . Delgado-Eckert , V . Hadinoto , A . Jarrah , et al . ( 2007 ) A virtual look at Epstein-Barr virus infection: simulation mechanism ( unpublished data ) ., At each time point ( 6 min of real time ) , every agent is evaluated and appropriate actions are initiated ., The simulation is invoked through a Web interface ( IRVE; see movies linked to Figure 2 , and 20 ) that allows a straightforward visual , familiar , and scalable context for access to parameter specification , run management , data output , and analysis ., This has the additional advantage that it readily allows comprehension of the spatial behavior of the system ( e . g . , “how does the infection spread ? ” ) ., The simulation may also be invoked from the command line ., Through the Web , users can process simulation data for output and analysis by a number of common applications such as Microsofts Excel , University of Marylands TimeSearcher 41 , and MatLab ., We have developed display components that encapsulate multiple-view capabilities and improved multi-scale interface mappings ., The IRVE is realized in the international standard VRML97 language ., The simulation can be rerun and reanalyzed using a normal VCR-type control tool , which allows the operator , for example , to fast forward , pause , rewind , or drag to a different time point , and to play back runs or analyze simulation output dynamically ., In the IRVE , any spatial object ( including the global system ) can be annotated with absolute population numbers ( as a time plot and/or numeric table ) or proportional population numbers ( as a bar graph ) for any or all of the agents ., Spatial objects themselves can be animated by heat-map color scales ., The intensity of the color associated with each agent is a measure of the absolute level of the agent; so , for example , as the level of free Vir increases , so will the level of intensity of the associated color ( in this case red ) both within the single units and in the entire organ ., In our simulation we manage multiple views of the dynamic population values through a higher order annotation called a PopView ( population view ) ., A PopView is an interactive annotation that provides three complementary representations of the agent population ., The representations can be switched through in series by simple selection ., The default view is a color-coded bar graph where users can get a quick , qualitative understanding of the agent populations in a certain location at that time step ., The second is a field-value pair text panel , which provides numeric readouts of population levels at that time step ., The third is a line graph where the population values for that region are plotted over time ., Because of the large amount of time points and the large number of grid locations , the IRVE manages an integrated information environment across two orders of magnitude: “Macro” and “Micro” scales ., Through the standard VRML application the user has a number of options including free-navigational modes such as: fly , pan , turn , and examine ., This allows users to explore the system , zooming in and out of anatomical structures as desired ., In addition , the resulting visualization space is navigable by predefined viewpoints , which can be visited sequentially or randomly through menu activation ., This guarantees that all content can be accessible and users can recover from any disorientation ., The Visualizer manages Macro and Micro scale result visualizations using proximity-based filtering and scripting of scene logic ., As users approach a given anatomical structure , the micro-scale meshes and results are loaded and synchronized to the time on the users VCR controller .
The possibility of using computer simulation and mathematical modeling to gain insight into biological and other complex systems is receiving increased attention ., However , it is as yet unclear to what extent these techniques will provide useful biological insights or even what the best approach is ., Epstein–Barr virus ( EBV ) provides a good candidate to address these issues ., It persistently infects most humans and is associated with several important diseases ., In addition , a detailed biological model has been developed that provides an intricate understanding of EBV infection in the naturally infected human host and accounts for most of the virus diverse and peculiar properties ., We have developed an agent-based computer model/simulation ( PathSim , Pathogen Simulation ) of this biological model ., The simulation is performed on a virtual grid that represents the anatomy of the tonsils of the nasopharyngeal cavity ( Waldeyer ring ) and the peripheral circulation—the sites of EBV infection and persistence ., The simulation is presented via a user friendly visual interface and reproduces quantitative and qualitative aspects of acute and persistent EBV infection ., The simulation also had predictive power in validation experiments involving certain aspects of viral infection dynamics ., Moreover , it allows us to identify switch points in the infection process that direct the disease course towards the end points of persistence , clearance , or death ., Lastly , we were able to identify parameter sets that reproduced aspects of EBV-associated diseases ., These investigations indicate that such simulations , combined with laboratory and clinical studies and animal models , will provide a powerful approach to investigating and controlling EBV infection , including the design of targeted anti-viral therapies .
The possibility of using computer simulation and mathematical modeling to gain insight into biological systems is receiving increased attention ., However , it is as yet unclear to what extent these techniques will provide useful biological insights or even what the best approach is ., Epstein–Barr virus ( EBV ) provides a good candidate to address these issues ., It persistently infects most humans and is associated with several important diseases , including cancer ., We have developed an agent-based computer model/simulation ( PathSim , Pathogen Simulation ) of EBV infection ., The simulation is performed on a virtual grid that represents the anatomy where EBV infects and persists ., The simulation is presented on a computer screen in a form that resembles a computer game ., This makes it readily accessible to investigators who are not well versed in computer technology ., The simulation allows us to identify switch points in the infection process that direct the disease course towards the end points of persistence , clearance , or death , and identify conditions that reproduce aspects of EBV-associated diseases ., Such simulations , combined with laboratory and clinical studies and animal models , provide a powerful approach to investigating and controlling EBV infection , including the design of targeted anti-viral therapies .
agent based model, infectious diseases, epstein-barr virus, computer simulation, pathology, virology, immunology, dynamics of infection, computational biology