Fitness advantage of Bacteroides thetaiotaomicron capsular polysaccharide in the mouse gut depends on the resident microbiota.

Many microbiota-based therapeutics rely on our ability to introduce a microbe of choice into an already-colonized intestine. In this study, we used genetically barcoded Bacteroides thetaiotaomicron (B. theta) strains to quantify population bottlenecks experienced by a B. theta population during colonization of the mouse gut. As expected, this reveals an inverse relationship between microbiota complexity and the probability that an individual wildtype B. theta clone will colonize the gut. The polysaccharide capsule of B. theta is important for resistance against attacks from other bacteria, phage, and the host immune system, and correspondingly acapsular B. theta loses in competitive colonization against the wildtype strain. Surprisingly, the acapsular strain did not show a colonization defect in mice with a low-complexity microbiota, as we found that acapsular strains have an indistinguishable colonization probability to the wildtype strain on single-strain colonization. This discrepancy could be resolved by tracking in vivo growth dynamics of both strains: acapsular B.theta shows a longer lag phase in the gut lumen as well as a slightly slower net growth rate. Therefore, as long as there is no niche competitor for the acapsular strain, this has only a small influence on colonization probability. However, the presence of a strong niche competitor (i.e., wildtype B. theta, SPF microbiota) rapidly excludes the acapsular strain during competitive colonization. Correspondingly, the acapsular strain shows a similarly low colonization probability in the context of a co-colonization with the wildtype strain or a complete microbiota. In summary, neutral tagging and detailed analysis of bacterial growth kinetics can therefore quantify the mechanisms of colonization resistance in differently-colonized animals.

Hydrodynamic flow and concentration gradients in the gut enhance neutral bacterial diversity.

The gut microbiota features important genetic diversity, and the specific spatial features of the gut may shape evolution within this environment. We investigate the fixation probability of neutral bacterial mutants within a minimal model of the gut that includes hydrodynamic flow and resulting gradients of food and bacterial concentrations. We find that this fixation probability is substantially increased, compared with an equivalent well-mixed system, in the regime where the profiles of food and bacterial concentration are strongly spatially dependent. Fixation probability then becomes independent of total population size. We show that our results can be rationalized by introducing an active population, which consists of those bacteria that are actively consuming food and dividing. The active population size yields an effective population size for neutral mutant fixation probability in the gut.

A rationally designed oral vaccine induces immunoglobulin A in the murine gut that directs the evolution of attenuated Salmonella variants.

The ability of gut bacterial pathogens to escape immunity by antigenic variation-particularly via changes to surface-exposed antigens-is a major barrier to immune clearance1. However, not all variants are equally fit in all environments2,3. It should therefore be possible to exploit such immune escape mechanisms to direct an evolutionary trade-off. Here, we demonstrate this phenomenon using Salmonella enterica subspecies enterica serovar Typhimurium (S.Tm). A dominant surface antigen of S.Tm is its O-antigen: a long, repetitive glycan that can be rapidly varied by mutations in biosynthetic pathways or by phase variation4,5. We quantified the selective advantage of O-antigen variants in the presence and absence of O-antigen-specific immunoglobulin A and identified a set of evolutionary trajectories allowing immune escape without an associated fitness cost in naive mice. Through the use of rationally designed oral vaccines, we induced immunoglobulin A responses blocking all of these trajectories. This selected for Salmonella mutants carrying deletions of the O-antigen polymerase gene wzyB. Due to their short O-antigen, these evolved mutants were more susceptible to environmental stressors (detergents or complement) and predation (bacteriophages) and were impaired in gut colonization and virulence in mice. Therefore, a rationally induced cocktail of intestinal antibodies can direct an evolutionary trade-off in S.Tm. This lays the foundations for the exploration of mucosal vaccines capable of setting evolutionary traps as a prophylactic strategy.

Cross-scale dynamics and the evolutionary emergence of infectious diseases.

When emerging pathogens encounter new host species for which they are poorly adapted, they must evolve to escape extinction. Pathogens experience selection on traits at multiple scales, including replication rates within host individuals and transmissibility between hosts. We analyze a stochastic model linking pathogen growth and competition within individuals to transmission between individuals. Our analysis reveals a new factor, the cross-scale reproductive number of a mutant virion, that quantifies how quickly mutant strains increase in frequency when they initially appear in the infected host population. This cross-scale reproductive number combines with viral mutation rates, single-strain reproductive numbers, and transmission bottleneck width to determine the likelihood of evolutionary emergence, and whether evolution occurs swiftly or gradually within chains of transmission. We find that wider transmission bottlenecks facilitate emergence of pathogens with short-term infections, but hinder emergence of pathogens exhibiting cross-scale selective conflict and long-term infections. Our results provide a framework to advance the integration of laboratory, clinical, and field data in the context of evolutionary theory, laying the foundation for a new generation of evidence-based risk assessment of emergence threats.

Growing, evolving and sticking in a flowing environment: understanding IgA interactions with bacteria in the gut.

Immunology research in the last 50 years has made huge progress in understanding the mechanisms of anti-bacterial defense of deep, normally sterile, tissues such as blood, spleen and peripheral lymph nodes. In the intestine, with its dense commensal microbiota, it seems rare that this knowledge can be simply translated. Here we put forward the idea that perhaps it is not always the theory of immunology that is lacking to explain mucosal immunity, but rather that we have overlooked crucial parts of the mucosal immunological language required for its translation: namely intestinal and bacterial physiology. We will try to explain this in the context of intestinal secretory antibodies (mainly secretory IgA), which have been described to prevent, to alter, to not affect, or to promote colonization of the intestine and gut-draining lymphoid tissues, and where effector mechanisms have remained elusive. In fact, these apparently contradictory outcomes can be generated by combining the basic premises of bacterial agglutination with an understanding of bacterial growth (i.e. secretory IgA-driven enchained growth), fluid handling and bacterial competition in the gut lumen.

Enchained growth and cluster dislocation: A possible mechanism for microbiota homeostasis.

Immunoglobulin A is a class of antibodies produced by the adaptive immune system and secreted into the gut lumen to fight pathogenic bacteria. We recently demonstrated that the main physical effect of these antibodies is to enchain daughter bacteria, i.e. to cross-link bacteria into clusters as they divide, preventing them from interacting with epithelial cells, thus protecting the host. These links between bacteria may break over time. We study several models using analytical and numerical calculations. We obtain the resulting distribution of chain sizes, that we compare with experimental data. We study the rate of increase in the number of free bacteria as a function of the replication rate of bacteria. Our models show robustly that at higher replication rates, bacteria replicate before the link between daughter bacteria breaks, leading to growing cluster sizes. On the contrary at low growth rates two daughter bacteria have a high probability to break apart. Thus the gut could produce IgA against all the bacteria it has encountered, but the most affected bacteria would be the fast replicating ones, that are more likely to destabilize the microbiota. Linking the effect of the immune effectors (here the clustering) with a property directly relevant to the potential bacterial pathogeneicity (here the replication rate) could avoid to make complex decisions about which bacteria to produce effectors against.

Antibody-mediated crosslinking of gut bacteria hinders the spread of antibiotic resistance.

The body is home to a diverse microbiota, mainly in the gut. Resistant bacteria are selected by antibiotic treatments, and once resistance becomes widespread in a population of hosts, antibiotics become useless. Here, we develop a multiscale model of the interaction between antibiotic use and resistance spread in a host population, focusing on an important aspect of within-host immunity. Antibodies secreted in the gut enchain bacteria upon division, yielding clonal clusters of bacteria. We demonstrate that immunity-driven bacteria clustering can hinder the spread of a novel resistant bacterial strain in a host population. We quantify this effect both in the case where resistance preexists and in the case where acquiring a new resistance mutation is necessary for the bacteria to spread. We further show that the reduction of spread by clustering can be countered when immune hosts are silent carriers, and are less likely to get treated, and/or have more contacts. We demonstrate the robustness of our findings to including stochastic within-host bacterial growth, a fitness cost of resistance, and its compensation. Our results highlight the importance of interactions between immunity and the spread of antibiotic resistance, and argue in the favor of vaccine-based strategies to combat antibiotic resistance.

High-avidity IgA protects the intestine by enchaining growing bacteria.

Vaccine-induced high-avidity IgA can protect against bacterial enteropathogens by directly neutralizing virulence factors or by poorly defined mechanisms that physically impede bacterial interactions with the gut tissues ('immune exclusion'). IgA-mediated cross-linking clumps bacteria in the gut lumen and is critical for protection against infection by non-typhoidal Salmonella enterica subspecies enterica serovar Typhimurium (S. Typhimurium). However, classical agglutination, which was thought to drive this process, is efficient only at high pathogen densities (≥108 non-motile bacteria per gram). In typical infections, much lower densities (100-107 colony-forming units per gram) of rapidly dividing bacteria are present in the gut lumen. Here we show that a different physical process drives formation of clumps in vivo: IgA-mediated cross-linking enchains daughter cells, preventing their separation after division, and clumping is therefore dependent on growth. Enchained growth is effective at all realistic pathogen densities, and accelerates pathogen clearance from the gut lumen. Furthermore, IgA enchains plasmid-donor and -recipient clones into separate clumps, impeding conjugative plasmid transfer in vivo. Enchained growth is therefore a mechanism by which IgA can disarm and clear potentially invasive species from the intestinal lumen without requiring high pathogen densities, inflammation or bacterial killing. Furthermore, our results reveal an untapped potential for oral vaccines in combating the spread of antimicrobial resistance.

Inflammation boosts bacteriophage transfer between Salmonella spp.

Bacteriophage transfer (lysogenic conversion) promotes bacterial virulence evolution. There is limited understanding of the factors that determine lysogenic conversion dynamics within infected hosts. A murine Salmonella Typhimurium (STm) diarrhea model was used to study the transfer of SopEΦ, a prophage from STm SL1344, to STm ATCC14028S. Gut inflammation and enteric disease triggered >55% lysogenic conversion of ATCC14028S within 3 days. Without inflammation, SopEΦ transfer was reduced by up to 105-fold. This was because inflammation (e.g., reactive oxygen species, reactive nitrogen species, hypochlorite) triggers the bacterial SOS response, boosts expression of the phage antirepressor Tum, and thereby promotes free phage production and subsequent transfer. Mucosal vaccination prevented a dense intestinal STm population from inducing inflammation and consequently abolished SopEΦ transfer. Vaccination may be a general strategy for blocking pathogen evolution that requires disease-driven transfer of temperate bacteriophages.

Credibility, credulity, and redistribution.

After raising some doubts for cultural group selection as an explanation of prosocial religiosity, we propose an alternative that views it as a "greenbeard effect." We combine the dynamic constraints on the evolution of greenbeard effects with Iannaccone's (1994) account of strict sects. Our model shows that certain social conditions may foster credulity and prosociality.

Rational Design and Adaptive Management of Combination Therapies for Hepatitis C Virus Infection.

Recent discoveries of direct acting antivirals against Hepatitis C virus (HCV) have raised hopes of effective treatment via combination therapies. Yet rapid evolution and high diversity of HCV populations, combined with the reality of suboptimal treatment adherence, make drug resistance a clinical and public health concern. We develop a general model incorporating viral dynamics and pharmacokinetics/ pharmacodynamics to assess how suboptimal adherence affects resistance development and clinical outcomes. We derive design principles and adaptive treatment strategies, identifying a high-risk period when missing doses is particularly risky for de novo resistance, and quantifying the number of additional doses needed to compensate when doses are missed. Using data from large-scale resistance assays, we demonstrate that the risk of resistance can be reduced substantially by applying these principles to a combination therapy of daclatasvir and asunaprevir. By providing a mechanistic framework to link patient characteristics to the risk of resistance, these findings show the potential of rational treatment design.

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.

A quantitative high-resolution genetic profile rapidly identifies sequence determinants of hepatitis C viral fitness and drug sensitivity.

Widely used chemical genetic screens have greatly facilitated the identification of many antiviral agents. However, the regions of interaction and inhibitory mechanisms of many therapeutic candidates have yet to be elucidated. Previous chemical screens identified Daclatasvir (BMS-790052) as a potent nonstructural protein 5A (NS5A) inhibitor for Hepatitis C virus (HCV) infection with an unclear inhibitory mechanism. Here we have developed a quantitative high-resolution genetic (qHRG) approach to systematically map the drug-protein interactions between Daclatasvir and NS5A and profile genetic barriers to Daclatasvir resistance. We implemented saturation mutagenesis in combination with next-generation sequencing technology to systematically quantify the effect of every possible amino acid substitution in the drug-targeted region (domain IA of NS5A) on replication fitness and sensitivity to Daclatasvir. This enabled determination of the residues governing drug-protein interactions. The relative fitness and drug sensitivity profiles also provide a comprehensive reference of the genetic barriers for all possible single amino acid changes during viral evolution, which we utilized to predict clinical outcomes using mathematical models. We envision that this high-resolution profiling methodology will be useful for next-generation drug development to select drugs with higher fitness costs to resistance, and also for informing the rational use of drugs based on viral variant spectra from patients.

Modelling clinical data shows active tissue concentration of daclatasvir is 10-fold lower than its plasma concentration.

OBJECTIVES: Daclatasvir is a highly potent inhibitor of hepatitis C virus. We estimated the active tissue concentration of daclatasvir in vivo. METHODS: We developed a mathematical model incorporating pharmacokinetic/pharmacodynamic and viral dynamics. By fitting the model to clinical data reported previously, we estimated the ratio between plasma drug concentration and active tissue concentration in vivo. RESULTS: The modelling results show that the active tissue concentration of daclatasvir is ∼9% of the concentration measured in plasma (95% CI 1%-29%). CONCLUSIONS: Using plasma concentrations as surrogates for clinical recommendations may lead to substantial underestimation of the risk of resistance.

Evolutionary invasion and escape in the presence of deleterious mutations.

Replicators such as parasites invading a new host species, species invading a new ecological niche, or cancer cells invading a new tissue often must mutate to adapt to a new environment. It is often argued that a higher mutation rate will favor evolutionary invasion and escape from extinction. However, most mutations are deleterious, and even lethal. We study the probability that the lineage will survive and invade successfully as a function of the mutation rate when both the initial strain and an adaptive mutant strain are threatened by lethal mutations. We show that mutations are beneficial, i.e. a non-zero mutation rate increases survival compared to the limit of no mutations, if in the no-mutation limit the survival probability of the initial strain is smaller than the average survival probability of the strains which are one mutation away. The mutation rate that maximizes survival depends on the characteristics of both the initial strain and the adaptive mutant, but if one strain is closer to the threshold governing survival then its properties will have greater influence. These conclusions are robust for more realistic or mechanistic depictions of the fitness landscapes such as a more detailed viral life history, or non-lethal deleterious mutations.

Intergenerational phenotypic mixing in viral evolution.

Viral particles (virions) are made of genomic material packaged with proteins, drawn from the pool of proteins in the parent cell. It is well known that when virion concentrations are high, cells can be coinfected with multiple viral strains that can complement each other. Viral genomes can then interact with proteins derived from different strains, in a phenomenon known as phenotypic mixing. But phenotypic mixing is actually far more common: viruses mutate very often, and each time a mutation occurs, the parent cell contains different types of viral genomes. Due to phenotypic mixing, changes in viral phenotypes can be shifted by a generation from the mutations that cause them. In the regime of evolutionary invasion and escape, when mutations are crucial for the virus to survive, this timing can have a large influence on the probability of emergence of an adapted strain. Modeling the dynamics of viral evolution in these contexts thus requires attention to the mutational mechanism and the determinants of fitness.

Activation-dependent plasticity of polarized GPCR distribution on the neuronal surface.

Directionality of information flow through neuronal networks is sustained at cellular level by polarized neurons. However, specific targeting or anchoring motifs responsible for polarized distribution on the neuronal surface have only been identified for a few neuronal G-protein-coupled receptors (GPCRs). Here, through mutational and pharmacological modifications of the conformational state of two model GPCRs, the axonal CB1R cannabinoid and the somatodendritic SSTR2 somatostatin receptors, we show important conformation-dependent variations in polarized distribution. The underlying mechanisms include lower efficiency of conformation-dependent GPCR endocytosis in axons, compared with dendrites, particularly at moderate activation levels, as well as endocytosis-dependent transcytotic delivery of GPCRs from the somatodendritic domain to distal axonal portions, shown by using compartmentalized microfluidic devices. Kinetic modeling predicted that GPCR distribution polarity is highly regulated by steady-state endocytosis, which is conformation dependent and is able to regulate the relative amount of GPCRs targeted to axons and that axonally polarized distribution is an intermediary phenotype that appears at moderate basal activation levels. Indeed, we experimentally show that gradual changes in basal activation-dependent endocytosis lead to highly correlated shifts of polarized GPCR distribution on the neuronal surface, which can even result in a fully reversed polarized distribution of naturally somatodendritic or axonal GPCRs. In conclusion, polarized distribution of neuronal GPCRs may have a pharmacologically controllable component, which, in the absence of dominant targeting motifs, could even represent the principal regulator of sub-neuronal distribution. Consequently, chronic modifications of basal GPCR activation by therapeutic or abused drugs may lead to previously unanticipated changes in brain function through perturbation of polarized GPCR distribution on the neuronal surface.

Multiple scales of selection influence the evolutionary emergence of novel pathogens.

When pathogens encounter a novel environment, such as a new host species or treatment with an antimicrobial drug, their fitness may be reduced so that adaptation is necessary to avoid extinction. Evolutionary emergence is the process by which new pathogen strains arise in response to such selective pressures. Theoretical studies over the last decade have clarified some determinants of emergence risk, but have neglected the influence of fitness on evolutionary rates and have not accounted for the multiple scales at which pathogens must compete successfully. We present a cross-scale theory for evolutionary emergence, which embeds a mechanistic model of within-host selection into a stochastic model for emergence at the population scale. We explore how fitness landscapes at within-host and between-host scales can interact to influence the probability that a pathogen lineage will emerge successfully. Results show that positive correlations between fitnesses across scales can greatly facilitate emergence, while cross-scale conflicts in selection can lead to evolutionary dead ends. The local genotype space of the initial strain of a pathogen can have disproportionate influence on emergence probability. Our cross-scale model represents a step towards integrating laboratory experiments with field surveillance data to create a rational framework to assess emergence risk.

Influence of viral replication mechanisms on within-host evolutionary dynamics.

Viruses replicate their genomes using a variety of mechanisms, leading to different distributions of mutations among their progeny. Yet, models of viral evolution often only consider the mean mutation rate. To investigate when and how replication mechanisms impact viral evolution, we analyze the early dynamics of within-host infection for two idealized cases: when all offspring virions from an infected cell carry the same genotype, mutated or not; and when mutations occur independently across offspring virions. Other replication life histories fall between these extremes. Using branching process models, we study the probability that viral infection becomes established when mutations are lethal, and in the more general case of two strains of different fitness. For a given mean mutation rate, we show that a lineage of viruses with correlated mutations is less likely to survive than with independent mutations, but when it survives, the viral population grows faster. While this holds true for all parameter regimes, replication life history has a quantitatively significant influence on viral dynamics when stochastic effects are important and when mutations are crucial for survival-conditions typical of evolutionary escape situations.