Yet, no matter how tricky viruses are, human beings are trickier; they have come up with ingenious solutions to protect the human race from deadly viruses. First, let us find out how a virus sneaks into the body of a human being. Viruses are simple in their structure; however, their danger lies in their ability to trick the body. They can easily get into the cells, because they are disguised as nutrients that the cells desperately need; once it enters, it transfers its genome into the cell.
This is the method through which an infected cell follows the instructions of a virus. A virus does not have the mechanism to duplicate itself; yet, through transferring its data to the cell, it reproduces itself.
Despite sneaking into human cells, the cells do not stand helpless in the face of viruses. The immune system is designed to recognize our own cells from other invaders; once an invader is detected, our white blood cells rise to defend the body. T-lymphocytes and B-lymphocytes white cells play an important role in attacking the virus and in stopping it from replicating. Those white cells unite to defend the body against viruses; either by raising the alarm, stopping the virus from making copies of itself, or simply by creating antibodies.
Antibodies mark the virus so that other cells know that these are infected cells that they must attack. As has been the case for other viruses during earlier pandemics, SARS-CoV-2 will mutate and may naturally attenuate over time ii.
What makes the current pandemic unique is that, thanks to state-of-the-art nucleic acid sequencing technologies, we can follow in detail how SARS-CoV-2 evolves while it spreads. We argue that knowledge of naturally emerging attenuated SARS-CoV-2 variants across the globe should be of key interest in our fight against the pandemic.
Innate immunity is temporary and decays to zero soon after the virus is cleared. Virus V is shown in red, innate immunity Z in black and adaptive immunity X in blue. The scale for virus and adaptive immunity is fold change over the initial value V 0 and X 0 are set to 1. Parameters are chosen for a biologically relevant regime as described earlier [ 36 ] and are shown in Table 1. The original approach for attenuating a virus was to grow it in unnatural conditions e.
Adaptation to the unnatural conditions often—but unpredictably—reduced growth rate in the primary host humans , with consequent loss of pathogenesis.
Newer methods of engineered attenuation also lower viral growth rate but do so far more predictably [ 4 , 10 ]. With a viral growth rate less than wild-type, the attenuated virus attains a smaller peak density before clearance and thus elicits less adaptive immunity. To wit, a single infection with wild-type measles, mumps or rubella viruses typically induces lifelong immunity [ 41 , 42 ], while vaccine-induced immunity frequently requires boosting, as indicated by the CDC immunization schedule [ 17 ].
This basic trade-off provides a baseline that should be reproduced by any reasonable model of viral-immune dynamics: reduced viral growth rate should result in reduced viral density before clearance reduced pathogenesis. There should be a consequent reduced stimulation of adaptive immunity and a lower final level of adaptive immunity. Our model indeed generates the expected patterns Fig 2. This pattern highlights the fundamental question of our study: is it possible to engineer an attenuation that is better than achieved by merely reducing viral growth rate—can we arrange pathogenesis to go down but immunity go up?
Our approach to this question involves varying virus-affected parameters and observing changes in pathogenesis and in immunity, as done next. Solid lines indicate wild-type; dashed and dotted indicate attenuated. Reducing virus growth rate results in lower viral load as well as a reduction in the final level of adaptive immunity.
B Impact of the degree of attenuation reduction in r on both the final level of adaptive immunity blue and the pathology maximum virus load, red. C The tradeoff between pathology and peak adaptive immunity from changing growth rate r : reducing the growth rate results in lower pathology but also lower immunity.
Parameters values are given in Table 1. Viruses have pathways that interfere with the innate or adaptive immune responses [ 43 — 47 ]. As these reduce the magnitude or effect of immunity, they are candidate pathways, that if targeted, could lead to an increase in immunity.
We model the suppression of these viral pathways as changes in the parameters that correspond to attenuation strategies—reducing pathogenesis Table 2. Note that suppression of a viral pathway may result in an increase of the parameter value—which can occur when the wild-type virus depresses a host anti-viral response.
Viruses can also limit killing by the innate and adaptive immunity with low values of the rate constants k Z and k X respectively. Attenuation thus involves changing those parameters in the opposite directions, reducing pathology. But our interest also lies in which of these changes will have the additional effect of increasing the final level of adaptive immunity, or at least not lowering it.
Blocking reducing any viral immune-evasion pathway leads to attenuation of the virus Fig 3. All are thus potential routes for generation of a live attenuated virus vaccine.
But how might those changes affect the level of immunity? Blocking pathways that make the virus more sensitive to clearance by either innate k Z or adaptive k X immunity results in more rapid control of the virus but a lower final level of immunity.
Finally, suppressing the viral pathway accelerating innate immune decay d Z prolongs the stimulation of adaptive immunity and increases its final level.
Red curves give the pathology, with scale on the right vertical axis; blue lines give the final level of adaptive immunity, with scale on the left vertical axis. A vaccine strain would be designed to lower pathology, and the arrow immediately above the horizontal axis gives the direction of change in the parameter value that would reduce pathology.
The goal of directed attenuation is to achieve a decline in the red curve and an increase or no change in the blue curve relative to wild-type; several attenuation designs achieve this outcome. Baseline parameters are as in Fig 1 except for the parameter whose value is changed in the panel. A more detailed consideration of the effect of each parameter on the dynamics of infection and immunity is considered in S1 Text.
The effects of different attenuation pathways may be directly compared by plotting them together in a grid of pathology and immunity Fig 4. The ideal live attenuated virus vaccine would generate lower pathology but higher immunity than infection with the wild-type virus, corresponding to the upper left quadrant where wild-type is taken as the center. A summary of the effect of different directed attenuation strategies by single parameter changes is included in Table 2 above. Wild-type values are given at the intersection of the curves, so viable attenuation strategies would lie to the left.
As the goal is to attenuate and to increase the immune response, the desirable attenuation strategies lie in the upper left quadrant.
The tradeoff for the classic mode of attenuation—lowering growth rate r black line —has the undesirable effect of lowering immunity, a pattern mimicked by changes in several other parameters. Two potential problems with directed attenuation of a single viral anti-immune pathway are i reversion of attenuation during growth in the patient, and ii potential harm when vaccinating immunocompromised individuals.
Given modern methods for engineering attenuation, the first of these reversion may not be a significant problem; we thus focus on inadvertent vaccination of immunocompromised individuals. The problem is especially apparent if a virus is attenuated by deletion of an antiviral strategy that targets a defense pathway lacking in the patient, in which case there is no difference between infection by the wild-type virus and infection by the vaccine.
The conventional method of attenuation—which results in a reduction of the growth rate, r —avoids this problem, or at least makes the infection less severe than that with wild-type virus. Overcoming this problem with directed attenuation may require a combination strategy. One type of combination is to block immune evasion while separately reducing growth rate. Another type of combination is to block both evasion of adaptive immunity and evasion of innate immunity.
A worry with combination strategies is that the reduced immunity might be too severe: can wild-type immunity be attained in a virus with classic growth rate reduction when an anti-immunity defense is also disabled?
The answer appears to be affirmative for some combinations Fig 5. The top four panels show the combined effect of reducing viral growth rate going from right to left on the horizontal axis together with changing one immune parameter on the vertical axis. The effect of changing a single parameter alone is seen by moving parallel to the respective axis.
The goal of attenuation is to reduce pathology from wild-type values increase the level of blue, top row and to increase immunity increase redness, bottom row. Values of wild-type virus are given in upper right of each panel, values of the prospective vaccine in lower left. The goal is to have pathology become increasingly blue and immunity become increasingly red in traversing from wild-type to vaccine. The conventional attenuation strategy arising from reductions in the parameter r is seen to reduce both pathology and immunity moving left along the horizontal axis in any of the left four panels.
However, combining reductions in r with increasing the sensitivity of the adaptive immune response i. The right column shows attenuation achieved by changes in a pair of parameters that does not include r. Combinations are possible without altering growth rate r , and some combinations may likewise result in reduced pathology with enhanced immunity Fig 5. One of the striking observations from Fig 5 is that the effect of varying parameters is substantially different for the 3 cases.
In the plots in the first column, immunity changes in response to both parameters, but pathology changes largely in response to the growth rate r. The middle column shows both pathology and immunity being affected by the combination of parameter values. These results reinforce the unintuitive nature of directed attenuation, and illustrate how models can be useful tools to understand the consequences of the non-linearities and feedbacks for different vaccination strategies.
The presentation above used a single model of immunity and viral dynamics. To address the possibility that directed attenuation is an outcome specific to that model, two other models were studied see S1 Text. Directed attenuation was found to be attainable in those as well. The two models differed from the model above as follows. In one model, the stimulation of the adaptive immune response was dependent only on the amount of virus antigen. In a second model, the stimulation of adaptive immunity depended on both the activation of innate immunity and the amount of virus antigen.
Although the details of how to achieve directed attenuation differed somewhat across these models, directed attenuation was possible for some parameter changes, commonly those involved in viral suppression of immunity. The fact that directed attenuation can be attained across different models suggests that it may be a general principle. Attenuated vaccines have been the mainstay of viral vaccines for close to a century [ 2 — 4 ].
Attenuation is typically achieved by evolving the virus for example by growth in a new environment or genetically modifying it so as to reduce its growth rate following infection of the host [ 5 — 10 ]. Here we suggest an alternative approach to attenuation, one that directs the virus toward reduced viral defenses against host immunity.
This approach to attenuation is suggested by the fact that many viruses directly interfere with the immune response [ 43 — 49 ], and those interference genes are obvious targets for genetic engineering. Using a simple computational model of the immune response to viral infection, we found that disruptions of viral anti-immune pathways invariably led to reduced pathology, whereas disruption of some, not all, of these pathways did so without compromising immunity, even increasing the level of adaptive immunity in some cases.
Our model helps identify which virus immune evasion pathways might be disabled to achieve the desired outcome of increasing the level of immunity generated.
We can intuit the consequences of deleting some of the immune evasion pathways. Deleting pathways that make the virus resistant to clearance by innate and adaptive immunity is modeled by increasing the rate of virus clearance by innate or adaptive immunity k Z and k X. This results in more rapid virus clearance and more rapid waning of innate immunity, and consequently a shorter duration of stimulation of adaptive immunity, and thus a lower final level of adaptive immunity. It is hard to intuit the consequences of changes in these parameters because changes in these parameters affect the final level of adaptive immunity in multiple ways.
The second effect arises as a consequence of the faster generation of adaptive immunity. The faster generation of adaptive immunity leads to faster virus clearance which leads to earlier waning of innate immunity, and this curtails the duration of stimulation of adaptive immunity.
These two effects work in opposite directions, the former resulting in an increase in the rate of generation of adaptive immunity and the latter in a decrease in the duration of expansion of adaptive immunity. Intuition is not enough and we thus require mathematical models to determine the consequences of combining these two effects.
Finally, deleting virus pathways that increase the rate of inactivation of innate immunity modeled by lowering d Z tend to have a beneficial effect, because it prolongs the duration of stimulation of the adaptive immune response.
In the S1 Text we discuss the effects of changes in these parameters on the dynamics of virus and immunity in more detail. Recent studies have discovered many pathways used by viruses to evade the innate and adaptive immune responses [ 43 — 47 , 49 ].
Poxviruses are large DNA viruses with much of their genome encoding immune-evasion pathways [ 45 , 46 , 50 ]. These pathways target host type 1 interferon, tumor necrosis factors and the complement pathway of innate immunity. They also evade adaptive immunity by downregulating antigen presentation and by blocking costimulatory pathways and the apoptotic response.
Adenoviruses are medium-sized, non-enveloped viruses containing a double stranded DNA genome. They encode immune-evasion pathways that inhibit tumor necrosis factor activity, and also evade adaptive immunity by downregulating antigen presentation [ 51 — 53 ]. One of the best studied immune-evasion genes encodes the NS1 protein of the influenza virus, which interferes with multiple stages of the type 1 interferon signaling cascade [ 54 — 58 ].
Mutant influenza viruses lacking the NS1 gene are highly attenuated in wild-type interferon-competent mice, but not in IFN-incompetant systems such as STAT 1 knockout mice [ 59 ]. Viruses with a truncation or deletion of their NS1 gene have been shown to be promising candidates for a live attenuated vaccine in chicken [ 60 , 61 ]. Type 1 interferon plays a role in reducing virus replication, corresponding to a decrease in the growth rate of the virus r in our models, so we expect this to result in less pathology and a smaller immune response.
This is consistent with the outcome of experimental infections of chicken with influenza virus vaccines that have deletions in the NS1 protein [ 61 ]. We suggest that it might be worth exploring the possibility of targeting other virus immune-evasion pathways so that the immune response is increased. An instructive example of virus engineering is that described by Jackson et al [ 62 ] who inserted a mouse IL-4 gene into ectromelia virus mousepox. The engineered virus caused fatal infections of mice and even killed mice that were immune to the wild-type virus.
This shows that: engineering virus immune evasion pathways is possible, that the result might have been predicted by relatively simple understanding of immunity IL-4 activates the Th2 immune response and thereby suppresses the Th1 responses required for defense against viruses [ 63 ] , and that the outcome of engineering virus immune evasion pathways can result in viruses with increased virulence indicating caution is needed. A combination of experiments and modeling approaches would facilitate achieving the desired goal of engineering a virus vaccine with reduced pathology but that generates enhanced immunity.
We certainly do not have sufficiently accurate quantitative models of the dynamics of infections and immunity to rely principally on the models. And a purely empirical approach has the problem of choosing between the large number of possible genes and gene combinations that could be the target of genetic manipulation.
Intuiting the consequences of different mutations is challenging because of the non-linear feedbacks between control of virus and generation of host immunity. Consequently, models that incorporate the relevant details of specific virus immune-evasion pathways may help suggest combinations of pathways to be targeted, limiting the experimental effort needed, and analysis of the results will in turn allow refinement of the models. At a basic engineering level, we suggest that in addition to compromising virus immune-evasion genes e.
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