Correcting for Antibody Waning in Cumulative Incidence Estimation From Sequential Serosurveys

Serosurveys are a widely used tool to estimate the cumulative incidence-the fraction of a population that has been infected by a given pathogen. These surveys rely on serological assays that measure the level of pathogen-specific antibodies. Because antibody levels are waning, the fraction of previously infected individuals that have seroreverted increases with time past infection. To avoid underestimating the true cumulative incidence, it is therefore essential to correct for waning antibody levels. We present an empirically supported approach for seroreversion correction in cumulative incidence estimation when sequential serosurveys are conducted in the context of a newly emerging infectious disease. The correction is based on the observed dynamics of antibody titers in seropositive cases and validated using several in silico test scenarios. Furthermore, through this approach we revise a previous cumulative incidence estimate relying on the assumption of an exponentially declining probability of seroreversion over time, of severe acute respiratory syndrome coronavirus 2, of 76% in Manaus, Brazil, by October 2020 to 47.6% (95% confidence region: 43.5-53.5). This estimate has implications, for example, for the proximity to herd immunity in Manaus in late 2020.

How infection-triggered pathobionts influence virulence evolution

Host-pathogen interactions can be influenced by the host microbiota, as the microbiota can facilitate or prevent pathogen infections. In addition, members of the microbiota can become virulent. Such pathobionts can cause co-infections when a pathogen infection alters the host immune system and triggers dysbiosis. Here we performed a theoretical investigation of how pathobiont co-infections affect the evolution of pathogen virulence. We explored the possibility that the likelihood of pathobiont co-infection depends on the evolving virulence of the pathogen. We found that, in contrast to the expectation from classical theory, increased virulence is not always selected for. For an increasing likelihood of co-infection with increasing pathogen virulence, we found scenario-specific selection for either increased or decreased virulence. Evolutionary changes, however, in pathogen virulence do not always translate into similar changes in combined virulence of the pathogen and the pathobiont. Only in one of the scenarios where pathobiont co-infection is triggered above a specific virulence level we found a reduction in combined virulence. This was not the case when the probability of pathobiont co-infection linearly increased with pathogen virulence. Taken together, our study draws attention to the possibility that host-microbiota interactions can be both the driver and the target of pathogen evolution. This article is part of the theme issue 'Sculpting the microbiome: how host factors determine and respond to microbial colonization'.

The pharmacokinetic-pharmacodynamic modelling framework as a tool to predict drug resistance evolution

Pharmacokinetic-pharmacodynamic (PKPD) models, which describe how drug concentrations change over time and how that affects pathogen growth, have proven highly valuable in designing optimal drug treatments aimed at bacterial eradication. However, the fast rise of antimicrobial resistance calls for increased focus on an additional treatment optimization criterion: avoidance of resistance evolution. We demonstrate here how coupling PKPD and population genetics models can be used to determine treatment regimens that minimize the potential for antimicrobial resistance evolution. Importantly, the resulting modelling framework enables the assessment of resistance evolution in response to dynamic selection pressures, including changes in antimicrobial concentration and the emergence of adaptive phenotypes. Using antibiotics and antimicrobial peptides as an example, we discuss the empirical evidence and intuition behind individual model parameters. We further suggest several extensions of this framework that allow a more comprehensive and realistic prediction of bacterial escape from antimicrobials through various phenotypic and genetic mechanisms.

Virulence decomposition for bifurcating infections

A fundamental goal in infection biology is to understand the emergence of variation in pathogen virulence-here defined as the decrease in host fitness caused by a pathogen. To uncover the sources of such variation, virulence can be decomposed into both host- and pathogen-associated components. However, decomposing virulence can be challenging owing to complex within-host pathogen dynamics such as bifurcating infections, which recently received increased empirical and theoretical attention. Bifurcating infections are characterized by the emergence of two distinct infection types: (i) terminal infections with high pathogen loads resulting in rapid host death, and (ii) persistent infections with lower loads and delayed host death. Here, we propose to use discrete mixture models to perform separate virulence decompositions for each infection type. Using this approach, we reanalysed a recently published experimental dataset on bacterial load and survival in Drosophila melanogaster. This analysis revealed several advantages of the new approach, most importantly the generation of a more comprehensive picture of the varying sources of virulence in different bacterial species. Beyond this application, our approach could provide valuable information for ground-truthing and improving theoretical models of within-host infection dynamics, which are developed to predict variation in infection outcome and pathogen virulence.

Per-pathogen virulence of HIV-1 subtypes A, C and D

HIV-1 subtypes differ in their clinical manifestations and the speed in which they spread. In particular, the frequency of subtype C is increasing relative to subtypes A and D. We investigate whether HIV-1 subtypes A, C and D differ in their per-pathogen virulence and to what extend this explains the difference in spread between these subtypes. We use data from the hormonal contraception and HIV-1 genital shedding and disease progression among women with primary HIV infection study. For each study participant, we determine the set-point viral load value, CD4⁺ T cell level after primary infection and CD4⁺ T cell decline. Based on both the CD4⁺ T cell count after primary infection and CD4⁺ T cell decline, we estimate the time until AIDS. We then obtain our newly introduced measure of virulence as the inverse of the estimated time until AIDS. After fitting a model to the measured virulence and set-point viral load values, we tested if this relation varies per subtype. We found that subtype C has a significantly higher per-pathogen virulence than subtype A. Based on an evolutionary model, we then hypothesize that differences in the primary length of infection period cause the observed variation in the speed of spread of the subtypes.

Assessing the relative importance of bacterial resistance, persistence and hyper-mutation for antibiotic treatment failure

To curb the rising threat of antimicrobial resistance, we need to understand the routes to antimicrobial treatment failure. Bacteria can survive treatment by using both genetic and phenotypic mechanisms to diminish the effect of antimicrobials. We assemble empirical data showing that, for example, Pseudomonas aeruginosa infections frequently contain persisters, transiently non-growing cells unaffected by antibiotics (AB) and hyper-mutators, mutants with elevated mutation rates, and thus higher probability of genetic resistance emergence. Resistance, persistence and hyper-mutation dynamics are difficult to disentangle experimentally. Hence, we use stochastic population modelling and deterministic fitness calculations to investigate the relative importance of genetic and phenotypic mechanisms for immediate treatment failure and establishment of prolonged, chronic infections. We find that persistence causes 'hidden' treatment failure with very low cell numbers if antimicrobial concentrations prevent growth of genetically resistant cells. Persister cells can regrow after treatment is discontinued and allow for resistance evolution in the absence of AB. This leads to different mutational routes during treatment and relapse of an infection. By contrast, hyper-mutation facilitates resistance evolution during treatment, but rarely contributes to treatment failure. Our findings highlight the time and concentration dependence of different bacterial mechanisms to escape AB killing, which should be considered when designing 'failure-proof' treatments.

Epidemiological and evolutionary consequences of different types of CRISPR-Cas systems

Bacteria have adaptive immunity against viruses (phages) in the form of CRISPR-Cas immune systems. Currently, 6 types of CRISPR-Cas systems are known and the molecular study of three of these has revealed important molecular differences. It is unknown if and how these molecular differences change the outcome of phage infection and the evolutionary pressure the CRISPR-Cas systems faces. To determine the importance of these molecular differences, we model a phage outbreak entering a population defending exclusively with a type I/II or a type III CRISPR-Cas system. We show that for type III CRISPR-Cas systems, rapid phage extinction is driven by the probability to acquire at least one resistance spacer. However, for type I/II CRISPR-Cas systems, rapid phage extinction is characterized by an a threshold-like behaviour: any acquisition probability below this threshold leads to phage survival whereas any acquisition probability above it, results in phage extinction. We also show that in the absence of autoimmunity, high acquisition rates evolve. However, when CRISPR-Cas systems are prone to autoimmunity, intermediate levels of acquisition are optimal during a phage outbreak. As we predict an optimal probability of spacer acquisition 2 factors of magnitude above the one that has been measured, we discuss the origin of such a discrepancy. Finally, we show that in a biologically relevant parameter range, a type III CRISPR-Cas system can outcompete a type I/II CRISPR-Cas system with a slightly higher probability of acquisition.

CRISPR-Cas systems are adaptive immune systems that use a complex 3-step molecular mechanism to defend prokaryotes against phages. Viral infections of populations defending themselves with CRISPR-Cas can result in rapid phage extinction or in medium-term phage maintenance. To investigate what controls the fate of the phage population, we use mathematical modeling of type I/II and type III CRISPR-Cas systems, and show that two parameters control the epidemiological short-term outcome: the type of CRISPR-Cas systems and CRISPR-Cas probability of resistance acquisition. Furthermore, the latter impacts host fitness. From this, we derive that 1) for both types, CRISPR-Cas acquisition probability is a key predictor of the efficiency and of the cost of a CRISPR-Cas system, 2) during an outbreak, there is an optimal probability of resistance acquisition balancing the cost of autoimmunity and immune efficiency and 3) type I/II CRISPR-Cas systems are likely to evolve higher acquisition probability than type III.

Modeling Polygenic Antibiotic Resistance Evolution in Biofilms

The recalcitrance of biofilms to antimicrobials is a multi-factorial phenomenon, including genetic, physical, and physiological changes. Individually, they often cannot account for biofilm recalcitrance. However, their combination can increase the minimal inhibitory concentration of antibiotics needed to kill bacterial cells by three orders of magnitude, explaining bacterial survival under otherwise lethal drug treatment. The relative contributions of these factors depend on the specific antibiotics, bacterial strain, as well as environmental and growth conditions. An emerging population genetic property—increased biofilm genetic diversity—further enhances biofilm recalcitrance. Here, we develop a polygenic model of biofilm recalcitrance accounting for multiple phenotypic mechanisms proposed to explain biofilm recalcitrance. The model can be used to generate predictions about the emergence of resistance—its timing and population genetic consequences. We use the model to simulate various treatments and experimental setups. Our simulations predict that the evolution of resistance is impaired in biofilms at low antimicrobial concentrations while it is facilitated at higher concentrations. In scenarios that allow bacteria exchange between planktonic and biofilm compartments, the evolution of resistance is further facilitated compared to scenarios without exchange. We compare these predictions to published experimental observations.

Applying mixture model methods to SARS-CoV-2 serosurvey data from Geneva

Serosurveys are an important tool to estimate the true extent of the current SARS-CoV-2 pandemic. So far, most serosurvey data have been analyzed with cutoff-based methods, which dichotomize individual measurements into sero-positives or negatives based on a predefined cutoff. However, mixture model methods can gain additional information from the same serosurvey data. Such methods refrain from dichotomizing individual values and instead use the full distribution of the serological measurements from pre-pandemic and COVID-19 controls to estimate the cumulative incidence. This study presents an application of mixture model methods to SARS-CoV-2 serosurvey data from the SEROCoV-POP study from April and May 2020 in Geneva (2766 individuals). Besides estimating the total cumulative incidence in these data (8.1% (95% CI: 6.8%–9.9%)), we applied extended mixture model methods to estimate an indirect indicator of disease severity, which is the fraction of cases with a distribution of antibody levels similar to hospitalized COVID-19 patients. This fraction is 51.2% (95% CI: 15.2%–79.5%) across the full serosurvey, but differs between three age classes: 21.4% (95% CI: 0%–59.6%) for individuals between 5 and 40 years old, 60.2% (95% CI: 21.5%–100%) for individuals between 41 and 65 years old and 100% (95% CI: 20.1%–100%) for individuals between 66 and 90 years old. Additionally, we find a mismatch between the inferred negative distribution of the serosurvey and the validation data of pre-pandemic controls. Overall, this study illustrates that mixture model methods can provide additional insights from serosurvey data.

Population genetics, biofilm recalcitrance, and antibiotic resistance evolution

Biofilms are communities of bacteria forming high-density sessile colonies. Such a lifestyle comes associated with costs and benefits: while the growth rate of biofilms is often lower than that of their free-living counterparts, this cost is readily repaid once the colony is subjected to antibiotics. Biofilms can grow in antibiotic concentrations a thousand times higher than planktonic bacteria. While numerous mechanisms have been proposed to explain biofilm recalcitrance towards antibiotics, little is yet known about their effect on the evolution of resistance. We synthesize the current understanding of biofilm recalcitrance from a pharmacodynamic and a population genetics perspective. Using the pharmacodynamic framework, we discuss the effects of various mechanisms and show that biofilms can either promote or impede resistance evolution.

Effector function does not contribute to protection from virus challenge by a highly potent HIV broadly neutralizing antibody in nonhuman primates

Protection from immunodeficiency virus challenge in nonhuman primates (NHPs) by a first-generation HIV broadly neutralizing antibody (bnAb) b12 has previously been shown to benefit from interaction between the bnAb and Fcγ receptors (FcγRs) on immune cells. To investigate the mechanism of protection for a more potent second-generation bnAb currently in clinical trials, PGT121, we carried out a series of NHP studies. These studies included treating with PGT121 at a concentration at which only half of the animals were protected to avoid potential masking of FcγR effector function benefits by dominant neutralization and using a new variant that more completely eliminated all rhesus FcγR binding than earlier variants. In contrast to b12, which required FcγR binding for optimal protection, we concluded that PGT121-mediated protection is not augmented by FcγR interaction. Thus, for HIV-passive antibody prophylaxis, these results, together with existing literature, emphasize the importance of neutralization potency for clinical antibodies, with effector function requiring evaluation for individual antibodies.

Bacteria primed by antimicrobial peptides develop tolerance and persist

Antimicrobial peptides (AMPs) are key components of innate immune defenses. Because of the antibiotic crisis, AMPs have also come into focus as new drugs. Here, we explore whether prior exposure to sub-lethal doses of AMPs increases bacterial survival and abets the evolution of resistance. We show that Escherichia coli primed by sub-lethal doses of AMPs develop tolerance and increase persistence by producing curli or colanic acid, responses linked to biofilm formation. We develop a population dynamic model that predicts that priming delays the clearance of infections and fuels the evolution of resistance. The effects we describe should apply to many AMPs and other drugs that target the cell surface. The optimal strategy to tackle tolerant or persistent cells requires high concentrations of AMPs and fast and long-lasting expression. Our findings also offer a new understanding of non-inherited drug resistance as an adaptive response and could lead to measures that slow the evolution of resistance.

Animals and plants defend themselves with ancient molecules called antimicrobial peptides (AMPs) against pathogens. As more and more bacterial diseases have become drug resistant, these AMPs are considered as promising alternatives. In natural situation such as on the skin, bacteria are often exposed to low concentrations of AMPs that do no kill. Here we show that the bacterium Escherichia coli when exposed to such low concentrations becomes recalcitrant to killing concentrations of the same AMPs. We report the ways in which the bacteria alter their surface to do so. We then use a mathematical model to show that these effects caused by low concentrations can drive the evolution of resistance. From the perspective of an organism using AMPs in self-defense, the best option is to deploy high concentrations of AMPs for long. Our findings also offer a new understanding of similar drug resistance mechanisms.

Estimating the cumulative incidence of SARS-CoV-2 with imperfect serological tests: Exploiting cutoff-free approaches

Large-scale serological testing in the population is essential to determine the true extent of the current SARS-CoV-2 pandemic. Serological tests measure antibody responses against pathogens and use predefined cutoff levels that dichotomize the quantitative test measures into sero-positives and negatives and use this as a proxy for past infection. With the imperfect assays that are currently available to test for past SARS-CoV-2 infection, the fraction of seropositive individuals in serosurveys is a biased estimator of the cumulative incidence and is usually corrected to account for the sensitivity and specificity. Here we use an inference method-referred to as mixture-model approach-for the estimation of the cumulative incidence that does not require to define cutoffs by integrating the quantitative test measures directly into the statistical inference procedure. We confirm that the mixture model outperforms the methods based on cutoffs, leading to less bias and error in estimates of the cumulative incidence. We illustrate how the mixture model can be used to optimize the design of serosurveys with imperfect serological tests. We also provide guidance on the number of control and case sera that are required to quantify the test's ambiguity sufficiently to enable the reliable estimation of the cumulative incidence. Lastly, we show how this approach can be used to estimate the cumulative incidence of classes of infections with an unknown distribution of quantitative test measures. This is a very promising application of the mixture-model approach that could identify the elusive fraction of asymptomatic SARS-CoV-2 infections. An R-package implementing the inference methods used in this paper is provided. Our study advocates using serological tests without cutoffs, especially if they are used to determine parameters characterizing populations rather than individuals. This approach circumvents some of the shortcomings of cutoff-based methods at exactly the low cumulative incidence levels and test accuracies that we are currently facing in SARS-CoV-2 serosurveys.

Long-term experimental evolution of HIV-1 reveals effects of environment and mutational history

An often-returning question for not only HIV-1, but also other organisms, is how predictable evolutionary paths are. The environment, mutational history, and random processes can all impact the exact evolutionary paths, but to which extent these factors contribute to the evolutionary dynamics of a particular system is an open question. Especially in a virus like HIV-1, with a large mutation rate and large population sizes, evolution is expected to be highly predictable if the impact of environment and history is low, and evolution is not neutral. We investigated the effect of environment and mutational history by analyzing sequences from a long-term evolution experiment, in which HIV-1 was passaged on 2 different cell types in 8 independent evolutionary lines and 8 derived lines, 4 of which involved a switch of the environment. The experiments lasted for 240–300 passages, corresponding to approximately 400–600 generations or almost 3 years. The sequences show signs of extensive parallel evolution—the majority of mutations that are shared between independent lines appear in both cell types, but we also find that both environment and mutational history significantly impact the evolutionary paths. We conclude that HIV-1 evolution is robust to small changes in the environment, similar to a transmission event in the absence of an immune response or drug pressure. We also find that the fitness landscape of HIV-1 is largely smooth, although we find some evidence for both positive and negative epistatic interactions between mutations.

Analysis of the longest evolutionary experiment with HIV-1 to-date reveals continuous viral adaptation over several years. The authors quantify the environment-specific mutations that arise and determine the fraction of mutations that co-occur with significantly different frequencies than expected by chance.

Number of HIV-1 founder variants is determined by the recency of the source partner infection

During sexual transmission, the high genetic diversity of HIV-1 within an individual is frequently reduced to one founder variant that initiates infection. Understanding the drivers of this bottleneck is crucial to developing effective infection control strategies. Little is known about the importance of the source partner during this bottleneck. To test the hypothesis that the source partner affects the number of HIV founder variants, we developed a phylodynamic model calibrated using genetic and epidemiological data on all existing transmission pairs for whom the direction of transmission and the infection stage of the source partner are known. Our results suggest that acquiring infection from someone in the acute (early) stage of infection increases the risk of multiple-founder variant transmission compared with acquiring infection from someone in the chronic (later) stage of infection. This study provides the first direct test of source partner characteristics to explain the low frequency of multiple-founder strain infections.

Disentangling non-specific and specific transgenerational immune priming components in host-parasite interactions

Exposure to a pathogen primes many organisms to respond faster or more efficiently to subsequent exposures. Such priming can be non-specific or specific, and has been found to extend across generations. Disentangling and quantifying specific and non-specific effects is essential for understanding the genetic epidemiology of a system. By combining a large infection experiment and mathematical modelling, we disentangle different transgenerational effects in the crustacean model Daphnia magna exposed to different strains of the bacterial parasite Pasteuria ramosa. In the experiment, we exposed hosts to a high dose of one of three parasite strains, and subsequently challenged their offspring with multiple doses of the same (homologous) or a different (heterologous) strain. We find that exposure of Daphnia to Pasteuria decreases the susceptibility of their offspring by approximately 50%. This transgenerational protection is not larger for homologous than for heterologous parasite challenges. Methodologically, our work represents an important contribution not only to the analysis of immune priming in ecological systems but also to the experimental assessment of vaccines. We present, for the first time, an inference framework to investigate specific and non-specific effects of immune priming on the susceptibility distribution of hosts—effects that are central to understanding immunity and the effect of vaccines.

Salmonella persisters promote the spread of antibiotic resistance plasmids in the gut

The emergence of antibiotic resistant bacteria by mutations or by acquisition of genetic material like resistance plasmids represents a major public health issue ^1,2 (Extended Data Fig. 1a). Persisters are bacterial subpopulations surviving antibiotics by reversibly adapting their physiology ^3–10. They promote the emergence of antibiotic resistant mutants ¹¹. We asked if persisters can also promote the spread of resistance plasmids. In contrast to mutations, resistance plasmid transfer requires the co-occurrence of two different bacterial strains: a donor and a recipient (Extended Data Fig. 1a). For our experiments, we chose the facultative intracellular entero-pathogen Salmonella enterica serovar Typhimurium (S.Tm) and E. coli, a common microbiota member ¹². S.Tm forms persisters surviving antibiotic therapy in several host tissues. We show that tissue-associated, S.Tm persisters account for long-lived reservoirs of plasmid donors or recipients. Persistent S.Tm reservoir formation requires Salmonella Pathogenicity Island (SPI) -1/2 in the gut-associated tissues or SPI-2 at systemic sites. Re-seeding of these bacteria into the gut lumen allows co-occurrence of donors with gut-resident recipients, thereby favouring plasmid transfer between various Enterobacteriaceae. We observe up to 99% transconjugants within 2-3 days after re-seeding. Mathematical modeling shows that rare re-seeding events may suffice for a high frequency of conjugation. Vaccination reduces tolerant reservoir formation after oral Salmonella infection and subsequent plasmid transfer. We conclude that even without selection for plasmid-encoded resistance genes, small persistent pathogen reservoirs can foster the spread of promiscuous resistance plasmids in the gut.

Virus dynamics and phyloanatomy: Merging population dynamic and phylogenetic approaches

In evolutionary biology and epidemiology, phylodynamic methods are widely used to infer population biological characteristics, such as the rates of replication, death, migration, or, in the epidemiological context, pathogen spread. More recently, these methods have been used to elucidate the dynamics of viruses within their hosts. Especially the application of phylogeographic approaches has the potential to shed light on anatomical colonization pathways and the exchange of viruses between distinct anatomical compartments. We and others have termed this phyloanatomy. Here, we review the promise and challenges of phyloanatomy, and compare them to more classical virus dynamics and population genetic approaches. We argue that the extremely strong selection pressures that exist within the host may represent the main obstacle to reliable phyloanatomic analysis.

Dissecting HIV Virulence: Heritability of Setpoint Viral Load, CD4+ T-Cell Decline, and Per-Parasite Pathogenicity

Pathogen strains may differ in virulence because they attain different loads in their hosts, or because they induce different disease-causing mechanisms independent of their load. In evolutionary ecology, the latter is referred to as “per-parasite pathogenicity”. Using viral load and CD4+ T-cell measures from 2014 HIV-1 subtype B-infected individuals enrolled in the Swiss HIV Cohort Study, we investigated if virulence—measured as the rate of decline of CD4+ T cells—and per-parasite pathogenicity are heritable from donor to recipient. We estimated heritability by donor–recipient regressions applied to 196 previously identified transmission pairs, and by phylogenetic mixed models applied to a phylogenetic tree inferred from HIV pol sequences. Regressing the CD4+ T-cell declines and per-parasite pathogenicities of the transmission pairs did not yield heritability estimates significantly different from zero. With the phylogenetic mixed model, however, our best estimate for the heritability of the CD4+ T-cell decline is 17% (5–30%), and that of the per-parasite pathogenicity is 17% (4–29%). Further, we confirm that the set-point viral load is heritable, and estimate a heritability of 29% (12–46%). Interestingly, the pattern of evolution of all these traits differs significantly from neutrality, and is most consistent with stabilizing selection for the set-point viral load, and with directional selection for the CD4+ T-cell decline and the per-parasite pathogenicity. Our analysis shows that the viral genotype affects virulence mainly by modulating the per-parasite pathogenicity, while the indirect effect via the set-point viral load is minor.

Predicting drug resistance evolution: insights from antimicrobial peptides and antibiotics

Antibiotic resistance constitutes one of the most pressing public health concerns. Antimicrobial peptides (AMPs) of multicellular organisms are considered part of a solution to this problem, and AMPs produced by bacteria such as colistin are last-resort drugs. Importantly, AMPs differ from many antibiotics in their pharmacodynamic characteristics. Here we implement these differences within a theoretical framework to predict the evolution of resistance against AMPs and compare it to antibiotic resistance. Our analysis of resistance evolution finds that pharmacodynamic differences all combine to produce a much lower probability that resistance will evolve against AMPs. The finding can be generalized to all drugs with pharmacodynamics similar to AMPs. Pharmacodynamic concepts are familiar to most practitioners of medical microbiology, and data can be easily obtained for any drug or drug combination. Our theoretical and conceptual framework is, therefore, widely applicable and can help avoid resistance evolution if implemented in antibiotic stewardship schemes or the rational choice of new drug candidates.

Estimating the mutational fitness effects distribution during early HIV infection

The evolution of HIV during acute infection is often considered a neutral process. Recent analysis of sequencing data from this stage of infection, however, showed high levels of shared mutations between independent viral populations. This suggests that selection might play a role in the early stages of HIV infection. We adapted an existing model for random evolution during acute HIV-infection to include selection. Simulations of this model were used to fit a global mutational fitness effects distribution to previously published sequencing data of the env gene of individuals with acute HIV infection. Measures of sharing between viral populations were used as summary statistics to compare the data to the simulations. We confirm that evolution during acute infection is significantly different from neutral. The distribution of mutational fitness effects is best fit by a distribution with a low, but significant fraction of beneficial mutations and a high fraction of deleterious mutations. While most mutations are neutral or deleterious in this model, about 5% of mutations are beneficial. These beneficial mutations will, on average, result in a small but significant increase in fitness. When assuming no epistasis, this indicates that, at the moment of transmission, HIV is near, but not on the fitness peak for early infection.

More or less-On the influence of labelling strategies to infer cell population dynamics

The adoptive transfer of labelled cell populations has been an essential tool to determine and quantify cellular dynamics. The experimental methods to label and track cells over time range from fluorescent dyes over congenic markers towards single-cell labelling techniques, such as genetic barcodes. While these methods have been widely used to quantify cell differentiation and division dynamics, the extent to which the applied labelling strategy actually affects the quantification of the dynamics has not been determined so far. This is especially important in situations where measurements can only be obtained at a single time point, as e.g. due to organ harvest. To this end, we studied the appropriateness of various labelling strategies as characterised by the number of different labels and the initial number of cells per label to quantify cellular dynamics. We simulated adoptive transfer experiments in systems of various complexity that assumed either homoeostatic cellular turnover or cell expansion dynamics involving various steps of cell differentiation and proliferation. Re-sampling cells at a single time point, we determined the ability of different labelling strategies to recover the underlying kinetics. Our results indicate that cell transition and expansion rates are differently affected by experimental shortcomings, such as loss of cells during transfer or sampling, dependent on the labelling strategy used. Furthermore, uniformly distributed labels in the transferred population generally lead to more robust and less biased results than non-equal label sizes. In addition, our analysis indicates that certain labelling approaches incorporate a systematic bias for the identification of complex cell expansion dynamics.

Antimicrobial combinations: Bliss independence and Loewe additivity derived from mechanistic multi-hit models

Antimicrobial peptides (AMPs) and antibiotics reduce the net growth rate of bacterial populations they target. It is relevant to understand if effects of multiple antimicrobials are synergistic or antagonistic, in particular for AMP responses, because naturally occurring responses involve multiple AMPs. There are several competing proposals describing how multiple types of antimicrobials add up when applied in combination, such as Loewe additivity or Bliss independence. These additivity terms are defined ad hoc from abstract principles explaining the supposed interaction between the antimicrobials. Here, we link these ad hoc combination terms to a mathematical model that represents the dynamics of antimicrobial molecules hitting targets on bacterial cells. In this multi-hit model, bacteria are killed when a certain number of targets are hit by antimicrobials. Using this bottom-up approach reveals that Bliss independence should be the model of choice if no interaction between antimicrobial molecules is expected. Loewe additivity, on the other hand, describes scenarios in which antimicrobials affect the same components of the cell, i.e. are not acting independently. While our approach idealizes the dynamics of antimicrobials, it provides a conceptual underpinning of the additivity terms. The choice of the additivity term is essential to determine synergy or antagonism of antimicrobials.This article is part of the themed issue 'Evolutionary ecology of arthropod antimicrobial peptides'.

Predicting HIV-1 transmission and antibody neutralization efficacy in vivo from stoichiometric parameters

The potential of broadly neutralizing antibodies targeting the HIV-1 envelope trimer to prevent HIV-1 transmission has opened new avenues for therapies and vaccines. However, their implementation remains challenging and would profit from a deepened mechanistic understanding of HIV-antibody interactions and the mucosal transmission process. In this study we experimentally determined stoichiometric parameters of the HIV-1 trimer-antibody interaction, confirming that binding of one antibody is sufficient for trimer neutralization. This defines numerical requirements for HIV-1 virion neutralization and thereby enables mathematical modelling of in vitro and in vivo antibody neutralization efficacy. The model we developed accurately predicts antibody efficacy in animal passive immunization studies and provides estimates for protective mucosal antibody concentrations. Furthermore, we derive estimates of the probability for a single virion to start host infection and the risks of male-to-female HIV-1 transmission per sexual intercourse. Our work thereby delivers comprehensive quantitative insights into both the molecular principles governing HIV-antibody interactions and the initial steps of mucosal HIV-1 transmission. These insights, alongside the underlying, adaptable modelling framework presented here, will be valuable for supporting in silico pre-trial planning and post-hoc evaluation of HIV-1 vaccination or antibody treatment trials.

Determinants of HIV-1 broadly neutralizing antibody induction

Broadly neutralizing antibodies (bnAbs) are a focal component of HIV-1 vaccine design, yet basic aspects of their induction remain poorly understood. Here we report on viral, host and disease factors that steer bnAb evolution using the results of a systematic survey in 4,484 HIV-1-infected individuals that identified 239 bnAb inducers. We show that three parameters that reflect the exposure to antigen-viral load, length of untreated infection and viral diversity-independently drive bnAb evolution. Notably, black participants showed significantly (P = 0.0086-0.038) higher rates of bnAb induction than white participants. Neutralization fingerprint analysis, which was used to delineate plasma specificity, identified strong virus subtype dependencies, with higher frequencies of CD4-binding-site bnAbs in infection with subtype B viruses (P = 0.02) and higher frequencies of V2-glycan-specific bnAbs in infection with non-subtype B viruses (P = 1 × 10^-5). Thus, key host, disease and viral determinants, including subtype-specific envelope features that determine bnAb specificity, remain to be unraveled and harnessed for bnAb-based vaccine design.

Insect antimicrobial peptides show potentiating functional interactions against Gram-negative bacteria

Antimicrobial peptides (AMPs) and proteins are important components of innate immunity against pathogens in insects. The production of AMPs is costly owing to resource-based trade-offs, and strategies maximizing the efficacy of AMPs at low concentrations are therefore likely to be advantageous. Here, we show the potentiating functional interaction of co-occurring insect AMPs (the bumblebee linear peptides hymenoptaecin and abaecin) resulting in more potent antimicrobial effects at low concentrations. Abaecin displayed no detectable activity against Escherichia coli when tested alone at concentrations of up to 200 μM, whereas hymenoptaecin affected bacterial cell growth and viability but only at concentrations greater than 2 μM. In combination, as little as 1.25 μM abaecin enhanced the bactericidal effects of hymenoptaecin. To understand these potentiating functional interactions, we investigated their mechanisms of action using atomic force microscopy and fluorescence resonance energy transfer-based quenching assays. Abaecin was found to reduce the minimal inhibitory concentration of hymenoptaecin and to interact with the bacterial chaperone DnaK (an evolutionarily conserved central organizer of the bacterial chaperone network) when the membrane was compromised by hymenoptaecin. These naturally occurring potentiating interactions suggest that combinations of AMPs could be used therapeutically against Gram-negative bacterial pathogens that have acquired resistance to common antibiotics.

Investigating the Consequences of Interference between Multiple CD8+ T Cell Escape Mutations in Early HIV Infection

During early human immunodeficiency virus (HIV) infection multiple CD8⁺ T cell responses are elicited almost simultaneously. These responses exert strong selective pressures on different parts of HIV’s genome, and select for mutations that escape recognition and are thus beneficial to the virus. Some studies reveal that the later these escape mutations emerge, the more slowly they go to fixation. This pattern of escape rate decrease(ERD) can arise by distinct mechanisms. In particular, in large populations with high beneficial mutation rates interference among different escape strains –an effect that can emerge in evolution with asexual reproduction and results in delayed fixation times of beneficial mutations compared to sexual reproduction– could significantly impact the escape rates of mutations. In this paper, we investigated how interference between these concurrent escape mutations affects their escape rates in systems with multiple epitopes, and whether it could be a source of the ERD pattern. To address these issues, we developed a multilocus Wright-Fisher model of HIV dynamics with selection, mutation and recombination, serving as a null-model for interference. We also derived an interference-free null model assuming initial neutral evolution before immune response elicitation. We found that interference between several equally selectively advantageous mutations can generate the observed ERD pattern. We also found that the number of loci, as well as recombination rates substantially affect ERD. These effects can be explained by the underexponential decline of escape rates over time. Lastly, we found that the observed ERD pattern in HIV infected individuals is consistent with both independent, interference-free mutations as well as interference effects. Our results confirm that interference effects should be considered when analyzing HIV escape mutations. The challenge in estimating escape rates and mutation-associated selective coefficients posed by interference effects cannot simply be overcome by improved sampling frequencies or sizes. This problem is a consequence of the fundamental shortcomings of current estimation techniques under interference regimes. Hence, accounting for the stochastic nature of competition between mutations demands novel estimation methodologies based on the analysis of HIV strains, rather than mutation frequencies.

Within-host evolution of human immunodeficiency virus (HIV) is shaped by strong immune responses mounted against the virus. Multiple CD8⁺ T cell populations, each recognizing a specific part of an HIV protein, simultaneously suppress HIV growth. Escape mutations that arise in HIV genome regions coding for these virion protein parts, impair CD8⁺ T cell recognition and are consequently strongly selected. The emergence and rise of these escape mutations exhibits an intriguing temporal pattern: the earlier an escape mutation arises, the faster it goes to fixation. This pattern is termed escape rate decrease (ERD). In this paper, we tested computationally whether interference, i.e. the coexistence of multiple genetically distinct HIV strains engaged in competitive interaction within the host, could be a possible source of ERD. As an alternative, we also mathematically derived the temporal pattern of escapes under interference-free conditions, and compared this with data. We found that interference between multiple beneficial mutations could generate ERD. However, ERD does not imply the presence of interference. Thus, more detailed data is required to unambiguously determine whether interference effects influence ERD generation. Nevertheless, interference should be considered when studying the within-host evolution of HIV. Ignoring its effects on population dynamics can severely underestimate the protective capacity of CD8⁺ T cells.

Population Dynamics Analysis of Ciprofloxacin-Persistent S. Typhimurium Cells in a Mouse Model for Salmonella Diarrhea

In vivo, antibiotics are often surprisingly inefficient at eliminating bacterial pathogens. In the case of ciprofloxacin therapy in a Salmonella enterica subspecies 1 serovar Typhimurium (S. Typhimurium, S. Tm) mouse infection model, this has been traced to tolerant bacterial cells surviving in lymph node monocytes (i.e., classical dendritic cells). To analyze the growth characteristics of these persisters, we have developed a population dynamics approach using mixtures of wild-type isogenic tagged strains (WITS) and a computational model. Here, we are providing a detailed description of the inoculum, the infection experiments, the computational analysis of the WITS data, and a computer simulation for assessing the quality of the growth parameters of the persistent S. Typhimurium cells. This approach is generic. It may be adapted to any organ infected and to any bacterial pathogen, provided that tools exist for generating, retrieving, and quantifying isogenic tagged strains.

The HIV-1 Entry Process: A Stoichiometric View

HIV-1 infection starts with fusion of the viral and the host cell membranes, a process mediated by the HIV-1 envelope glycoprotein trimer. The number of trimers required to complete membrane fusion, referred to as HIV-1 entry stoichiometry, remains under debate. A precise definition of HIV-1 entry stoichiometry is important as it reflects the efficacy of the viral entry process and steers the infectivity of HIV-1 virion populations. Initial estimates suggested a unanimous entry stoichiometry across HIV-1 strains while recent findings showed that HIV-1 strains can differ in entry stoichiometry. Here, we review current analyses of HIV-1 entry stoichiometry and point out future research directions to further define the interplay between entry stoichiometry, virus entry fitness, transmission, and susceptibility to antibody neutralization.

Estimating the In Vivo Killing Efficacy of Cytotoxic T Lymphocytes across Different Peptide-MHC Complex Densities

Cytotoxic T lymphocytes (CTLs) are important agents in the control of intracellular pathogens, which specifically recognize and kill infected cells. Recently developed experimental methods allow the estimation of the CTL's efficacy in detecting and clearing infected host cells. One method, the in vivo killing assay, utilizes the adoptive transfer of antigen displaying target cells into the bloodstream of mice. Surprisingly, killing efficacies measured by this method are often much higher than estimates obtained by other methods based on, for instance, the dynamics of escape mutations. In this study, we investigated what fraction of this variation can be explained by differences in peptide loads employed in in vivo killing assays. We addressed this question in mice immunized with lymphocytic choriomeningitis virus (LCMV). We conducted in vivo killing assays varying the loads of the immunodominant epitope GP33 on target cells. Using a mathematical model, we determined the efficacy of effector and memory CTL, as well as CTL in chronically infected mice. We found that the killing efficacy is substantially reduced at lower peptide loads. For physiological peptide loads, our analysis predicts more than a factor 10 lower CTL efficacies than at maximum peptide loads. Assuming that the efficacy scales linearly with the frequency of CTL, a clear hierarchy emerges among the groups across all peptide antigen concentrations. The group of mice with chronic LCMV infections shows a consistently higher killing efficacy per CTL than the acutely infected mouse group, which in turn has a consistently larger efficacy than the memory mouse group. We conclude that CTL killing efficacy dependence on surface epitope frequencies can only partially explain the variation in in vivo killing efficacy estimates across experimental methods and viral systems, which vary about four orders of magnitude. In contrast, peptide load differences can explain at most two orders of magnitude.

Protective efficacy of individual CD8+ T cell specificities in chronic viral infection

Specific CD8(+) T cells (CTLs) play an important role in resolving protracted infection with hepatitis B and C virus in humans and lymphocytic choriomeningitis virus (LCMV) in mice. The contribution of individual CTL specificities to chronic virus control, as well as epitope-specific patterns in timing and persistence of antiviral selection pressure, remain, however, incompletely defined. To monitor and characterize the antiviral efficacy of individual CTL specificities throughout the course of chronic infection, we coinoculated mice with a mixture of wild-type LCMV and genetically engineered CTL epitope-deficient mutant virus. A quantitative longitudinal assessment of viral competition revealed that mice continuously exerted CTL selection pressure on the persisting virus population. The timing of selection pressure characterized individual epitope specificities, and its magnitude varied considerably between individual mice. This longitudinal assessment of "antiviral efficacy" provides a novel parameter to characterize CTL responses in chronic viral infection. It demonstrates remarkable perseverance of all antiviral CTL specificities studied, thus raising hope for therapeutic vaccination in the treatment of persistent viral diseases.

The role of chance in primate lentiviral infectivity: from protomer to host organism

Infection is best described as a stochastic process. Whether a host becomes infected upon exposure has a strong random element. The same applies to cells exposed to virions. In this review, we show how the mathematical formalism for stochastic processes has been used to describe and understand the infection by the Human and Simian Immunodeficiency Virus on different levels. We survey quantitative studies on the establishment of infection in the host (the organismal level) and on the infection of target cells (the cellular and molecular level). We then discuss how a synthesis of the approaches across these levels could give rise to a predictive framework for assessing the efficacy of microbicides and vaccines.

Granulocytes impose a tight bottleneck upon the gut luminal pathogen population during Salmonella typhimurium colitis

Topological, chemical and immunological barriers are thought to limit infection by enteropathogenic bacteria. However, in many cases these barriers and their consequences for the infection process remain incompletely understood. Here, we employed a mouse model for Salmonella colitis and a mixed inoculum approach to identify barriers limiting the gut luminal pathogen population. Mice were infected via the oral route with wild type S. Typhimurium (S. Tm) and/or mixtures of phenotypically identical but differentially tagged S. Tm strains ("WITS", wild-type isogenic tagged strains), which can be individually tracked by quantitative real-time PCR. WITS dilution experiments identified a substantial loss in tag/genetic diversity within the gut luminal S. Tm population by days 2-4 post infection. The diversity-loss was not attributable to overgrowth by S. Tm mutants, but required inflammation, Gr-1+ cells (mainly neutrophilic granulocytes) and most likely NADPH-oxidase-mediated defense, but not iNOS. Mathematical modelling indicated that inflammation inflicts a bottleneck transiently restricting the gut luminal S. Tm population to approximately 6000 cells and plating experiments verified a transient, inflammation- and Gr-1+ cell-dependent dip in the gut luminal S. Tm population at day 2 post infection. We conclude that granulocytes, an important clinical hallmark of S. Tm-induced inflammation, impose a drastic bottleneck upon the pathogen population. This extends the current view of inflammation-fuelled gut-luminal Salmonella growth by establishing the host response in the intestinal lumen as a double-edged sword, fostering and diminishing colonization in a dynamic equilibrium. Our work identifies a potent immune defense against gut infection and reveals a potential Achilles' heel of the infection process which might be targeted for therapy.

Partial rescue of V1V2 mutant infectivity by HIV-1 cell-cell transmission supports the domain's exceptional capacity for sequence variation

BACKGROUND

Variable loops 1 and 2 (V1V2) of the HIV-1 envelope glycoprotein gp120 perform two key functions: ensuring envelope trimer entry competence and shielding against neutralizing antibodies. While preserving entry functionality would suggest a high need for V1V2 sequence optimization and conservation, shielding efficacy is known to depend on a high flexibility of V1V2 giving rise to its substantial sequence variability. How entry competence of the trimer is maintained despite the continuous emergence of antibody escape mutations within V1V2 has not been resolved. Since HIV cell-cell transmission is considered a highly effective means of virus dissemination, we investigated whether cell-cell transmission may serve to enhance infectivity of V1V2 variants with debilitated free virus entry.

RESULTS

In a detailed comparison of wt and V1V2 mutant envelopes, V1V2 proved to be a key factor in ascertaining free virus infectivity, with V1V2 mutants displaying significantly reduced trimer integrity. Despite these defects, cell-cell transmission was able to partially rescue infectivity of V1V2 mutant viruses. We identified two regions, encompassing amino acids 156 to 160 (targeted by broadly neutralizing antibodies) and 175 to 180 (encompassing the α4β7 binding site) which were particularly prone to free virus infectivity loss upon mutation but maintained infectivity in cell-cell transmission. Of note, V1V2 antibody shielding proved important during both free virus infection and cell-cell transmission.

CONCLUSIONS

Based on our data we propose a model for V1V2 evolution that centers on cell-cell transmission as a salvage pathway for virus replication. Escape from antibody neutralization may frequently result in V1V2 mutations that reduce free virus infectivity. Cell-cell transmission could provide these escape viruses with sufficiently high replication levels that enable selection of compensatory mutations, thereby restoring free virus infectivity while ensuring antibody escape. Thus, our study highlights the need to factor in cell-cell transmission when considering neutralization escape pathways of HIV-1.

Disentangling human tolerance and resistance against HIV

Title: Human tolerance against HIV An evolutionary ecology perspective on clinical data reveals that human traits can affect how well an individual tolerates HIV infection, and identifies host immunity factors associated with disease tolerance.

In ecology, “disease tolerance” is defined as an evolutionary strategy of hosts against pathogens, characterized by reduced or absent pathogenesis despite high pathogen load. To our knowledge, tolerance has to date not been quantified and disentangled from host resistance to disease in any clinically relevant human infection. Using data from the Swiss HIV Cohort Study, we investigated if there is variation in tolerance to HIV in humans and if this variation is associated with polymorphisms in the human genome. In particular, we tested for associations between tolerance and alleles of the Human Leukocyte Antigen (HLA) genes, the CC chemokine receptor 5 (CCR5), the age at which individuals were infected, and their sex. We found that HLA-B alleles associated with better HIV control do not confer tolerance. The slower disease progression associated with these alleles can be fully attributed to the extent of viral load reduction in carriers. However, we observed that tolerance significantly varies across HLA-B genotypes with a relative standard deviation of 34%. Furthermore, we found that HLA-B homozygotes are less tolerant than heterozygotes. Lastly, tolerance was observed to decrease with age, resulting in a 1.7-fold difference in disease progression between 20 and 60-y-old individuals with the same viral load. Thus, disease tolerance is a feature of infection with HIV, and the identification of the mechanisms involved may pave the way to a better understanding of pathogenesis.

When confronted with pathogens, hosts can either evolve to fight them or learn to live with them. The first of these two strategies is called “resistance” and the second “tolerance”. In the context of HIV, many genes conferring resistance have been identified, but no tolerance genes are known. Using statistical techniques originating from plant ecology, we analyzed data from an HIV cohort to look for differences in tolerance between HIV-infected individuals and tested whether they go hand in hand with genetic differences. We found that younger people are more tolerant to HIV infection. We also observed that individuals who carry two different alleles of HLA-B, an important immunity gene, are more tolerant. These findings add to our understanding of how hosts tolerate infections and could open new avenues for treating infections.

Cecum lymph node dendritic cells harbor slow-growing bacteria phenotypically tolerant to antibiotic treatment

Salmonella bacteria can tolerate antibiotics by adopting a slow-growing “persister” state that hides in host dendritic cells and can re-initiate infection after treatment ends. This can be avoided by supplementing antibiotic treatment with stimulants of innate immunity.

In vivo, antibiotics are often much less efficient than ex vivo and relapses can occur. The reasons for poor in vivo activity are still not completely understood. We have studied the fluoroquinolone antibiotic ciprofloxacin in an animal model for complicated Salmonellosis. High-dose ciprofloxacin treatment efficiently reduced pathogen loads in feces and most organs. However, the cecum draining lymph node (cLN), the gut tissue, and the spleen retained surviving bacteria. In cLN, approximately 10%–20% of the bacteria remained viable. These phenotypically tolerant bacteria lodged mostly within CD103⁺CX₃CR1⁻CD11c⁺ dendritic cells, remained genetically susceptible to ciprofloxacin, were sufficient to reinitiate infection after the end of the therapy, and displayed an extremely slow growth rate, as shown by mathematical analysis of infections with mixed inocula and segregative plasmid experiments. The slow growth was sufficient to explain recalcitrance to antibiotics treatment. Therefore, slow-growing antibiotic-tolerant bacteria lodged within dendritic cells can explain poor in vivo antibiotic activity and relapse. Administration of LPS or CpG, known elicitors of innate immune defense, reduced the loads of tolerant bacteria. Thus, manipulating innate immunity may augment the in vivo activity of antibiotics.

Antibiotics that are known to kill bacteria in vitro can be less efficacious in vivo. The reasons for this have remained poorly understood. Using a mouse model for Salmonella diarrhea, we found that bacterial persistence occurs in the presence of the antibiotic ciprofloxacin because Salmonella can exist in two different states: as a fast-growing population that spreads in the host's tissues and as a slow-growing “persister” subpopulation. The slow-growing bacteria infect and hide out inside dendritic cells of the host's immune system and cannot be attacked by the antibiotic—they are thereby rendered “tolerant,” despite their genetic susceptibility to the drug. These tolerant bacteria form a reservoir of viable cells that are able to reinitiate the infection on cessation of antibiotic therapy. Fortunately, however, these tolerant Salmonella cells are not invincible, and can be killed by adding agents that directly stimulate the host's immune defense. Combining innate immune stimulants with antibiotic treatment may offer new opportunities to improve antibacterial therapies.

Can non-lytic CD8+ T cells drive HIV-1 escape?

The CD8+ T cell effector mechanisms that mediate control of HIV-1 and SIV infections remain poorly understood. Recent work suggests that the mechanism may be primarily non-lytic. This is in apparent conflict with the observation that SIV and HIV-1 variants that escape CD8+ T cell surveillance are frequently selected. Whilst it is clear that a variant that has escaped a lytic response can have a fitness advantage compared to the wild-type, it is less obvious that this holds in the face of non-lytic control where both wild-type and variant infected cells would be affected by soluble factors. In particular, the high motility of T cells in lymphoid tissue would be expected to rapidly destroy local effects making selection of escape variants by non-lytic responses unlikely. The observation of frequent HIV-1 and SIV escape poses a number of questions. Most importantly, is the consistent observation of viral escape proof that HIV-1- and SIV-specific CD8+ T cells lyse infected cells or can this also be the result of non-lytic control? Additionally, the rate at which a variant strain escapes a lytic CD8+ T cell response is related to the strength of the response. Is the same relationship true for a non-lytic response? Finally, the potential anti-viral control mediated by non-lytic mechanisms compared to lytic mechanisms is unknown. These questions cannot be addressed with current experimental techniques nor with the standard mathematical models. Instead we have developed a 3D cellular automaton model of HIV-1 which captures spatial and temporal dynamics. The model reproduces in vivo HIV-1 dynamics at the cellular and population level. Using this model we demonstrate that non-lytic effector mechanisms can select for escape variants but that outgrowth of the variant is slower and less frequent than from a lytic response so that non-lytic responses can potentially offer more durable control.

The interplay between viruses and the immune system cannot always be studied with current experimental techniques or commonly used mathematical models. Consequently, many important questions remain unanswered. The questions we wished to address fall into this category. Recent evidence strongly suggests that CD8+ T cells control SIV, and potentially HIV-1, primarily by secreting anti-viral factors rather than by killing infected cells. However, this does not seem compatible with the common observation that HIV and SIV evolve to escape the immune response. Soluble anti-viral factors, like RANTES which protects uninfected cells from infection, would be expected to inhibit both wild-type and variant virus. Furthermore, the high speed and motility of T cells in lymphoid tissue will increase homogeneity and again decrease the likelihood that an escape variant can have a selective advantage in the face of non-lytic control. We wanted to understand whether viral escape is proof that HIV-1- and SIV-specific CD8+ T cells kill infected cells, determine the factors that facilitate viral escape, and investigate the comparative efficiency of lytic and non-lytic responses in controlling viral infections. Here we develop an elaborate but robust computational framework that captures T cell kinetics and spatial interactions in lymphoid tissue to addresses these important questions.

Lymph node colonization dynamics after oral Salmonella Typhimurium infection in mice

An understanding of how pathogens colonize their hosts is crucial for the rational design of vaccines or therapy. While the molecular factors facilitating the invasion and systemic infection by pathogens are a central focus of research in microbiology, the population biological aspects of colonization are still poorly understood. Here, we investigated the early colonization dynamics of Salmonella enterica subspecies 1 serovar Typhimurium (S. Tm) in the streptomycin mouse model for diarrhea. We focused on the first step on the way to systemic infection — the colonization of the cecal lymph node (cLN) from the gut — and studied roles of inflammation, dendritic cells and innate immune effectors in the colonization process. To this end, we inoculated mice with mixtures of seven wild type isogenic tagged strains (WITS) of S. Tm. The experimental data were analyzed with a newly developed mathematical model describing the stochastic immigration, replication and clearance of bacteria in the cLN. We estimated that in the beginning of infection only 300 bacterial cells arrive in the cLN per day. We further found that inflammation decreases the net replication rate in the cLN by 23%. In mice, in which dendritic cell movement is impaired, the bacterial migration rate was reduced 10-fold. In contrast, mice that cannot generate toxic reactive oxygen species displayed a 4-fold higher migration rate from gut to cLN than wild type mice. Thus, combining infections with mixed inocula of barcoded strains and mathematical analysis represents a powerful method for disentangling immigration into the cLN from replication in this compartment. The estimated parameters provide an important baseline to assess and predict the efficacy of interventions.

Like humans, pathogens have a demography. Within their hosts, they migrate, replicate, and die. Understanding these processes quantitatively can help designing vaccines and treatment by identifying vulnerabilities of the pathogen population. For most pathogens, however, quantitative information on how they replicate and spread in their hosts is lacking. Here, we investigate the early colonization of hosts by Salmonella bacteria after oral infection in a mouse model for complicated Salmonella diarrhea. To estimate migration and replication rates, we infected the mice with mixtures of identical, but distinguishable strains of the bacterium and analyzed the results with a mathematical model that describes the demography of the bacterial population. Random loss of some of these strains during colonization of the mice allows us to estimate migration rates between anatomical compartments. We find that approximately 300 bacteria migrate per day from the gut to the cecal lymph node – the first step towards systemic infection. We further investigate how bacterial migration and replication is affected by inflammation and various agents of the immune system. Our study provides unprecedented information on the colonization dynamics of this bacterial infection and introduces a framework for further improving therapy and vaccination.

Stabilization of cooperative virulence by the expression of an avirulent phenotype

Pathogens often infect hosts through collective actions: they secrete growth-promoting compounds or virulence factors, or evoke host reactions that fuel the colonization of the host. Such behaviours are vulnerable to the rise of mutants that benefit from the collective action without contributing to it; how these behaviours can be evolutionarily stable is not well understood. We address this question using the intestinal pathogen Salmonella enterica serovar Typhimurium (hereafter termed S. typhimurium), which manipulates its host to induce inflammation, and thereby outcompetes the commensal microbiota. Notably, the virulence factors needed for host manipulation are expressed in a bistable fashion, leading to a slow-growing subpopulation that expresses virulence genes, and a fast-growing subpopulation that is phenotypically avirulent. Here we show that the expression of the genetically identical but phenotypically avirulent subpopulation is essential for the evolutionary stability of virulence in this pathogen. Using a combination of mathematical modelling, experimental evolution and competition experiments we found that within-host evolution leads to the emergence of mutants that are genetically avirulent and fast-growing. These mutants are defectors that exploit inflammation without contributing to it. In infection experiments initiated with wild-type S. typhimurium, defectors increase only slowly in frequency. In a genetically modified S. typhimurium strain in which the phenotypically avirulent subpopulation is reduced in size, defectors rise more rapidly, inflammation ceases prematurely, and S. typhimurium is quickly cleared from the gut. Our results establish that host manipulation by S. typhimurium is a cooperative trait that is vulnerable to the rise of avirulent defectors; the expression of a phenotypically avirulent subpopulation that grows as fast as defectors slows down this process, and thereby promotes the evolutionary stability of virulence. This points to a key role of bistable virulence gene expression in stabilizing cooperative virulence and may lead the way to new approaches for controlling pathogens.

Viral mutation rates: modelling the roles of within-host viral dynamics and the trade-off between replication fidelity and speed

Many viruses, particularly RNA viruses, mutate at a very high rate per genome per replication. One possible explanation is that high mutation rates are selected to meet the challenge of fluctuating environments, including the host immune response. Alternatively, recent studies argue that viruses evolve under a trade-off between replication speed and fidelity such that fast replication is selected, and, along with it, high mutation rates. Here, in addition to these factors, we consider the role of viral life-history properties: namely, the within-host dynamics of viruses resulting from their interaction with the host. We develop mathematical models incorporating factors occurring within and between hosts, including deleterious and advantageous mutations, host death owing to virulence and clearance of viruses by the host. Beneficial mutations confer both a within-host and a transmission advantage. First, we find that advantageous mutations have only a weak effect on the optimal genomic mutation rate. Second, viral life-history properties have a large effect on the mutation rate. Third, when the speed-fidelity trade-off is included, there can be two locally optimal mutation rates. Our analysis provides a way to consider how life-history properties combine with biochemical trade-offs to shape mutation rates.

Influence of the fibroblastic reticular network on cell-cell interactions in lymphoid organs

Secondary lymphoid organs (SLO), such as lymph nodes and the spleen, display a complex micro-architecture. In the T cell zone the micro-architecture is provided by a network of fibroblastic reticular cells (FRC) and their filaments. The FRC network is thought to enhance the interaction between immune cells and their cognate antigen. However, the effect of the FRC network on cell interaction cannot be quantified to date because of limitations in immunological methodology. We use computational models to study the influence of different densities of FRC networks on the probability that two cells meet. We developed a 3D cellular automaton model to simulate cell movements and interactions along the FRC network inside lymphatic tissue. We show that the FRC network density has only a small effect on the probability of a cell to come into contact with a static or motile target. However, damage caused by a disruption of the FRC network is greatest at FRC densities corresponding to densities observed in the spleen of naïve mice. Our analysis suggests that the FRC network as a guiding structure for moving T cells has only a minor effect on the probability to find a corresponding dendritic cell. We propose alternative hypotheses by which the FRC network might influence the functionality of immune responses in a more significant way.

Restricted occupancy models for neutralization of HIV virions and populations

HIV virions infect cells by attaching to target cell receptors, fusing membranes with the cell and by finally releasing their genetic material into the target cells. Antibodies can hinder the infection by attaching to the HIV envelope glycoprotein trimers before or during attachment. The exact mechanisms and the quantitative requirements of antibody neutralization are still debated. Recently, the number of antibodies rendering one trimer non-functional, called stoichiometry of (trimer) neutralization, was studied with mathematical models. Here we extend this theoretical framework to calculate the stoichiometries of neutralizing a single virion and a whole virion population. We derive mathematical equations for antibody neutralization based on restricted occupancy theory. Additionally we simulate these processes when a direct calculation is not possible. We find that the number of trimers needed for cell entry and the number of antibodies neutralizing one trimer strongly influence the mean number of antibodies needed for virion and population neutralization. Further we show that the mean number of antibodies needed to neutralize a virion population exceeds the product of the number of virions in the population and the mean number of antibodies needed to neutralize one virion.

Interaction of the gp120 V1V2 loop with a neighboring gp120 unit shields the HIV envelope trimer against cross-neutralizing antibodies

Structure–function analysis and mathematical modeling reveal insight into the mechanisms through which conserved HIV-1 gp120 epitopes are masked in the HIV-1 envelope trimer.

The HIV-1 envelope trimer adopts a quaternary conformation that effectively shields neutralization-sensitive domains and thus represents a major obstacle for natural and vaccine-elicited antibody responses. By using a structure–function analysis based on a specifically devised mathematical model, we demonstrate in this study that protection from neutralization is enforced by intersubunit contact between the variable loops 1 and 2 (V1V2) and domains of neighboring gp120 subunits in the trimer encompassing the V3 loop. Our data are consistent with an interaction of the V1V2 and V3 loop at the spike apex as proposed by cryoelectron tomography experiments. By defining the orientation of the V1V2 loop within the trimer toward the neighboring gp120 subunit’s V3 loop, our data close an important gap in the understanding of the architecture of the trimeric spike. Knowledge on how the V1V2 barrier functions in the context of the trimer to mask conserved epitopes on gp120 may aid future vaccine design.

Population biological principles of drug-resistance evolution in infectious diseases

The emergence of resistant pathogens in response to selection pressure by drugs and their possible disappearance when drug use is discontinued are evolutionary processes common to many pathogens. Population biological models have been used to study the dynamics of resistance in viruses, bacteria, and eukaryotic microparasites both at the level of the individual treated host and of the treated host population. Despite the existence of generic features that underlie such evolutionary dynamics, different conclusions have been reached about the key factors affecting the rate of resistance evolution and how to best use drugs to minimise the risk of generating high levels of resistance. Improved understanding of generic versus specific population biological aspects will help to translate results between different studies, and allow development of a more rational basis for sustainable drug use than exists at present.

Comparison of cytotoxic T lymphocyte efficacy in acute and persistent lymphocytic choriomeningitis virus infection

Immune responses mediated by cytotoxic T lymphocytes (CTLs) have often been found to be functionally impaired in persistent infections. It is assumed that this impairment contributes to persistence of the infection. In this study, we compare the killing efficacy of CD8(+) T-cell responses in mice acutely and persistently infected with the lymphocytic choriomeningitis virus, using an in vivo CTL killing assay. To infer the killing efficacy of CTLs, we developed a new mathematical model describing the disappearance of peptide-pulsed cells from the blood of the mice over time. We estimate a lower half-life for peptide-pulsed cells in acute infection than in persistent infection, which indicates a higher killing efficacy of the CD8(+) T-cell response in acute infection. However, by controlling for the different levels of CTLs in acutely and persistently infected mice, we find that CTLs in persistent infection are only two times less efficacious than CTLs in acute infections. These results strongly suggest that the in vivo cytotoxicity of CD8(+) T-cell responses in persistent infection is modulated via the number of CTLs rather than their individual functionality.