During pregnancy, IgG, a certain isotype of antibody, is transported to the baby from the mother through the placenta, so even babies have high levels of antibodies with similar antigen specificities as the mother.
Passive immunity is short-lived, ranging from a couple days to a couple months. Because the passive memory comes from antibodies instead of B cells themselves, infants do not inherit long-term immunological memory from the mother.
Following an infection, long-term active memory is acquired by activation of B and T cells. Memory cells derive from their parent B and T cells, and undergo clonal selection following infection, which increases antigen-binding affinity.
Following reinfection, the secondary immune response typically eliminates the pathogen before symptoms of an infection can occur. During the secondary immune response, memory T cells rapidly proliferate into active helper and cytotoxic T cells specific to that antigen, while memory B cells rapidly produce antibodies to neutralize the pathogen.
Long-term active memory consists of rapid response and form permanent immunological memory so long as those memory cells survive. Vaccinations take advantage of memory lymphocyte development by artificially-generating active immunity, a process called immunization. During a vaccination, the antigen of a pathogen is introduced into the body and stimulates the immune system to develop a specific immunity against that pathogen. Vaccination is an extremely effective manipulation of the immune system that helps fight diseases.
In other words, even if a patient's antibody levels wane over time, the adaptive immune system has ways to pick up the slack. And in previous studies of other infectious diseases, researchers have shown that immune memory can last a long time. And they did. Similar studies have been conducted with survivors of the flu pandemic, and Crotty said scientists were able to show that the patients' immune memories could recognize that particular influenza virus. But immune memory varies from virus to virus, Crotty said, and it's not well understood why these differences exist.
It's not clear, for instance, why the immune system can recognize some viruses many decades later, while for others, the memory response is weak or unstable. It's also not known where memory responses to the coronavirus will fall on that spectrum. Scientists are researching all aspects of potential coronavirus immunity, but there have been some encouraging early results. In a study published in May in the journal Cell , Crotty and his colleagues studied cells from 10 patients who had recovered from mild cases of COVID The scientists exposed their immune cells to pieces of the virus.
They found that all of the patients had T helper cells that could detect the coronavirus's signature spike protein and that 70 percent of the patients had cytotoxic T cells that could sense and extinguish infected cells.
Sette said that although it was a small study, the findings offer a good baseline for research, because ideally a coronavirus vaccine would try to induce similar immune responses. More research is needed, but Cruickshank said research on adaptive immune responses is shedding light on the human body's intricate workings and how the complex biological systems can fight off viral interlopers like the coronavirus.
IE 11 is not supported. For an optimal experience visit our site on another browser. Politics Covid U. News World Opinion Business. Share this —. Nevertheless, an affinity-specificity tradeoff has been reported for a bNAb against the hemagglutinin epitope of influenza Wu et al. The width of this binding profile i. Upon primary infection i. This simplification becomes less accurate as the immune system ages and the supply of effective receptors become more scarce.
Following a naive response to a primary infection and the subsequent affinity maturation, the immune system stores memory cells with an enhanced affinity to use them against future infections Janeway et al.
As pathogens evolve globally to escape the immune challenge, drugs, or vaccination, they drift away from the primary antigen in antigenic space. A cross-reactive memory can mount a response to an evolved antigen, yet with a reduced affinity that decays with antigenic shift; see Figure 1. A memory response in an individual is triggered through the recognition of an antigen by a circulating memory receptor.
Therefore, the probability that an antigen is recognized through a novel naive response P recog. Here, we have assumed that the affinity of the memory receptor does not change over the response time, which is a simplification since memory receptor can undergo limited affinity maturation Shlomchik, ; McHeyzer-Williams et al.
The deliberation time prior to a novel response provides a window for memory to react with an antigen and mount an immune response by initiating an irreversible cascade of downstream events. Although initiation of this pathogenic recognition can be modeled as an equilibrium process, the resulting immune response is a non-equilibrium and an irreversible process, the details of which are not included in our model. The optimal solution for a rational yet constrained decision follows,. If information processing is highly efficient i.
On the other hand, if the prior is strong i. Moreover, if the prior distribution is uniform across actions i. In our analysis, we consider the case of unbiased maximum entropy solution for decision-making. As a result the probability to utilize memory Q mem. Importantly, in the regime that memory is efficient and being utilized to mount a response i. A longer deliberation, which on one hand leads to the accumulation of pathogens, would allow the immune system to exploit the utility of a usable memory i.
Interestingly, previous work has drawn a similar correspondence between the inverse temperature in thermodynamics and the effect of sample size on statistical inference LaMont and Wiggins, It should be noted that our decision-making formalism assumes that if memory is available, it can be utilized much more efficiently and robustly than a naive response. Therefore, we do not consider scenarios where memory and naive responses are equally involved in countering an infection—a possibility that could play a role in real immune responses.
This deviation arises because an energetically sub-optimal memory response can still be favorable when time is of an essence and the decision has to be made on the fly with short deliberation. The dissipation K diss measures the sub-optimality cost of the mounted response through non-equilibrium decision-making and quantifies deviation from an equilibrium immune response Grau-Moya et al.
To infer an optimal strategy, we introduce net utility U net that accounts for the tradeoff between the expected utility and dissipation at a given round of infection at time point t i ,. Net utility can be interpreted as the extracted information theoretical work of a rational decision-maker that acts in a limited time, and hence, is constantly kept out of equilibrium Grau-Moya et al.
While we do not model time limits to memory, we effectively model only one memory at a time. This effect is the consequence of modeling the memory as only being beneficial until a novel immune response is triggered resulting in the storage of an updated memory centered around a more recent antigen Figure 1.
After such an update, the old memory is no longer relevant as antigens have drifted away. In our model, the characteristic time for a novel response and memory update is set by the expected antigenic divergence Figure 2. Accordingly, cross-reactivity of memory is optimized so that the organism can mount effective responses against evolved forms of antigens in this window of time.
However, if the lifetime of memory were to be shorter than this characteristic time of memory update, we expect the organism to store more specific memory since this memory would be utilized to counter a more limited antigenic evolution before it is lost.
In other words, the shorter of either the memory lifetime or the characteristic time for memory updates determines the optimal cross-reactivity for immune memory. In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses. This paper lies out an interesting framework to think about the consequences of immune memory. The central tension is one between memory cells with high affinity for a narrow range of antigens and lower affinity but broader spectrum that can deal with evolving pathogens better.
The reviewers appreciated the combination of abstraction, involving thermodynamic and information theoretic frameworks and the grappling with specifics of immune memory. Thank you for submitting your article "Optimal evolutionary decision-making to store immune memory" for consideration by eLife.
Your article has been reviewed by 2 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Naama Barkai as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Kayla Sprenger Reviewer 2. The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission. As promised in the introduction, the authors could comment on how their approach could be applied to memory T cells in future work, even if the dynamics of such memory is different.
Reviewer 1. Improve Figure 1 so it defines the model more comprehensively without the reader having to consult the Methods section. Cross-reactive Abs are observed to take long to evolve. But the authors results seem to suggest that much cross-reactivity is evolved early in the affinity maturation. The authors should clarify. Reviewer 2. How would the assumed lifetime of memory B cells affect your results? It appears you have assumed that memory B cells persist through the lifespan of the organism.
A discussion of how your results would change if memory lasted for less time would be useful. In this article, Schnaack and Nourmohammad explore the dynamic constraints in triggering optimal immune responses to eradicate infections.
The key paradox being addressed here is that, depending on the speed of evolution of pathogens, the immune system can tune the specificity of the lymphocytes' receptor that are selected e. Given that the formalism is quite abstract e. The authors make a good attempt at discussing their main insight and it is certainly thought-provoking: they found that the number of exposures to a pathogen, as it relates to the age span of the organism under consideration, is a critical parameter to decide the amount of cross-reactivity stored in memory leukocytes.
This is the strongest insight as it relates to experimental results. There are theoretical surprises as well: the bimodality of receptor specificities that get selected when pathogens are very diverse at the antigen level is thought-provoking.
The authors do point out that this may relate to experimental observations for B cells mixed populations are selected with or without class switching. Overall, this is a very well written and insightful manuscript leveraging results from non-equilibrium statistical physics and accounting for varied strategies for the immune system.
This manuscript features a novel mathematical model for investigating how the immune system optimally stores memory of B cell receptor-pathogen interactions in order to maximize protection against future pathogens with diverse evolutionary rates. Results support recent experimental findings that B cell differentiation into memory cells is strongly regulated during the affinity maturation process and that the kinetics and energetics of an immune response are simultaneously optimized to ensure an effective response.
Unique insights are also provided into the immunological phenomenon of original antigenic sin, such as the effect on this phenomenon of organismal lifetime, which is also explored in the context of optimal memory storage strategies.
The presented mathematical framework is rigorously constructed such that meaningful insights can be gleaned into the workings of the adaptive immune response to evolving pathogens. The framework combines fundamental concepts from information processing and equilibrium and non-equilibrium thermodynamics with concepts from probability and statistics in a unique and thoughtful way.
The conclusions appear to be well-aligned with recent experimental findings, providing validity for the model and for the subsequent predictions that are made on optimal memory storage strategies for organisms with varying lifespans.
The results provide useful insights into longstanding questions in immunology, such as whether cell fate decisions on memory B cell differentiation are regulated during the process of affinity maturation, and into the origins of original antigenic sin from an immune response perspective and potential mitigation strategies. With regards to the former point, the model accurately reproduces recent experimental findings showing differentiation into memory B cells during affinity maturation is indeed highly regulated.
This thus sets a bar for future computational models of immunological memory processes and affinity maturation to incorporate this feature, rather than assuming differentiation into memory B cells is stochastic and carried out at a constant rate throughout affinity maturation, which is currently a common assumption. Broad parameter regimes are explored, rendering the findings potentially relevant for infection scenarios with diverse pathogens. Typically, cross-reactivity or equivalently breadth takes a long time to evolve, as evidenced by the fact that broadly neutralizing antibodies bnAbs arise only after many years of infection or re-infection by an evolving pathogen.
Arguments are made by the authors that memory B cells are preferentially produced early on in the affinity maturation process, and that memory B cells are also preferentially stored with intermediate cross-reactivity, which would seem to imply that a good deal of cross-reactivity can be evolved early on in the maturation process. These arguments would seem to be at odds with the concept of bnAb evolution and thus warrant some clarity.
The impact of the paper could potentially be heightened if some discussion of how the principles gleaned on optimal immune memory strategies could be translated to, e. Lines , It is stated that "as in most molecular interactions, immune pathogen recognization is cross-reactive". I am confused by this statement, as many molecular interactions are indeed not cross-reactive e. Immune-pathogen recognition would also not typically appear to be cross-reactive unless the pathogen is highly mutable or there have been multiple infections of an evolved pathogen, so this sentence further confuses me.
Please note that if the sentence is kept as is, I believe the authors meant to use "recognition" instead of "recognization". Besides the concept of original antigenic sin, could the concept of immune imprinting where immune memory is biased over the lifetime of an organism also be captured by or incorporated into this model somehow? As it appears to be defined, antigenic divergence characterizes two distinct infections by a given pathogen.
Line in what kinds of scenarios or against what types of pathogens , might prior preferences be important to consider? To clarify, all of the analyses carried out here assume no prior preferences? In regard to Equation 2, it would seem that the same maximum net utility value could be obtained with either a particularly high expected utility or a particularly low Kdiss. Would the optimal memory protocol look different in these two cases, despite them having the same net utility value?
Perhaps this is already addressed, but the answer is not immediately clear to me. Can the authors please clarify this? Line , it is not clear what is meant by the statement that "Physico-chemical constraints in protein structures can introduce a tradeoff between immune receptors' affinity and cross-reactivity". Is this tradeoff not determined by the antigenic divergence that an immune system encounters upon a new infection compared to a past infection?
Lines , the last sentence seems to imply that a moderate amount of cross-reactivity or equivalently breadth is achieved early on in the affinity maturation process.
Can the authors please comment on this? In addition, I was under the impression that broadly neutralizing antibodies are typically class-switched, i. Is their evidence that the cross-reactivity of IgM receptors produced early on in affinity maturation is really effective at 'countering evolving pathogens' lines ?
In the last Results section on the effect of infection frequency, and perhaps in general throughout the manuscript, is the assumption made that memory B cells persist for the entire lifetime of an organism? Some studies have placed the half-life of memory B cells to be only between 8 and 10 weeks, and others up to or possibly beyond 2 years, and still others for the lifetime of the host but requiring constant renewal through antigen-specific stimulation.
How might changes in the expected lifetime of memory B cells affect the optimal memory strategies that are presented? We have now included a paragraph in the Discussion section highlighting the parallels between T cell and B cell memory generation lines Of course, as the reviewers have pointed out the mechanisms are distinct but conceptually one may be able to give a similar evolutionary rationale for understanding memory differentiation in these B-cells and T-cells.
We have extended Figure 1 to indicate more details about the model in the schematic. It is true that BnAbs, which are known for their cross-reactivity, take long to evolve within individuals. In a sense, BnAbs achieve their breadth by specifically targeting conserved regions of a virus that are shared among a broad panel of strains. This is of course not true for all BnAbs and some are broad in a true sense. Still, we argue that BnAbs are more of an exception than a rule when thinking about cross-reactive interactions.
As we are now clarifying in the text, we consider cross-reactivity as a feature that makes naive or pre-class switched antibodies flexible to interact with different pathogenic targets. As the reviewer has pointed out, memory B-cells can persist for a very long time e.
However, long-term memory does not necessarily imply that individual cells have a long life span, but rather it can be due to the persistence of renewing clones specific to a given antigen.
Indeed, the mechanisms to maintain a long-lived immune memory are not well understood. While we do not model time limits to memory, we effectively model only one dominant memory at a time. This process is the consequence of modeling the memory as only being beneficial until a novel immune response is triggered resulting in the storage of an updated memory centered around a more recent antigen.
After such update, the old memory is no longer relevant as antigens have drifted away. In our current setup, the characteristic time for a novel response and memory update is set by the expected antigenic divergence.
We thank the reviewer for raising this interesting question. A series of experiments have investigated different aspects of this question Blanchard-Rohner et al. In brief:. Therefore, given the experimental evidence, if memory is available and is activated, it is unlikely that it would be outcompeted and overshadowed by the naive B cell response.
These arguments were previously only presented in the Methods section lines We have now included these arguments in the main text Lines to better justify our assumptions. Thanks for bringing up this question. We have added a discussion on this matter to the manuscript lines We expect the model to still hold for the intra-host evolution of pathogens like HIV. The reviewer is correct that we use no prior preferences in our analyses, and we are now explicitly stating this fact in the manuscript Lines The implications of this question are very interesting.
We expect in principle that extreme choices of priors impact the outcome of our model. One can however turn this question around and ask whether such priors can emerge as optimal strategies in light of immune-pathogen coevolution.
One possibility to imagine is whether there is an evolutionary advantage to optimize immune machinery over evolutionary time scales so that it generates repertoires that can respond more efficiently to commonly observed pathogens.
Mayer et al. It would be very interesting to study how such priors could naturally emerge in the context of immune-pathogen coevolution, but this topic is beyond the scope of this manuscript. The reviewer is correct that dissipation and the expected utility could in principle compensate each other and result in degenerate states with the same optimum net utility. However, as shown in Figure 2, for each value of antigenic divergence, we only obtain a single global optimum and do not see any degeneracy in the solutions.
This tradeoff is rooted in the biophysics of protein and specifically antibody structures. In contrast, naive or pre-class switched antibodies are more flexible and they can interact with different pathogenic targets i.
Taken together, these structural studies suggest that the physico-chemical constraints in protein structures of antibodies cause a tradeoff between affinity and cross-reactivity, at least for a broad class of such molecules.
Of course, there are always exceptions to this rule and further studies are necessary to better understand the biophysical constraints on antibody structures. These points were previously discussed in the Methods lines and we have now included these statement earlier in the text when the model is introduced Lines Blanchard-Rohner, A. Pulickal, C. Jol-van der Zijde, M. Snape, and A. Appearance of peripheral blood plasma cells and memory B cells in a primary and secondary immune response in humans.
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