Evolutionary emergence of infectious diseases in heterogeneous host populations

Building pyramids against the evolutionary emergence of pathogens

Mutations allowing pathogens to escape host immunity promote the spread of infectious diseases in heterogeneous host populations and can lead to major epidemics. Understanding the conditions that slow down this evolution is key for the development of durable control strategies against pathogens. Here, we use theory and experiments to compare the efficacy of three strategies for the deployment of resistance: (i) a mixing strategy where the host population contains two single-resistant genotypes, (ii) a pyramiding strategy where the host carries a double-resistant genotype, (iii) a combining strategy where the host population is a mix of a single-resistant genotype and a double-resistant genotype. First, we use evolutionary epidemiology theory to clarify the interplay between demographic stochasticity and evolutionary dynamics to show that the pyramiding strategy always yields lower probability of evolutionary emergence. Second, we test experimentally these predictions with the introduction of bacteriophages into bacterial populations where we manipulated the diversity and the depth of immunity using a Clustered Regularly Interspaced Short Palindromic Repeats-CRISPR associated (CRISPR-Cas) system. These biological assays confirm that pyramiding multiple defences into the same host genotype and avoiding combination with single-defence genotypes is a robust way to reduce pathogen evolutionary emergence. The experimental validation of these theoretical recommendations has practical implications in various areas, including for the optimal deployment of resistance varieties in agriculture and for the design of durable vaccination strategies.

My host's enemy is my enemy: plasmids carrying CRISPR-Cas as a defence against phages

Bacteria are infected by mobile genetic elements like plasmids and virulent phages, and those infections significantly impact bacterial ecology and evolution. Recent discoveries reveal that some plasmids carry anti-phage immune systems like CRISPR-Cas, suggesting that plasmids may participate in the coevolutionary arms race between virulent phages and bacteria. Intuitively, this seems reasonable as virulent phages kill the plasmid's obligate host. However, the efficiency of CRISPR-Cas systems carried by plasmids can be expected to be lower than those carried by the chromosome due to continuous segregation loss, creating susceptible cells for phage amplification. To evaluate the anti-phage protection efficiency of CRISPR-Cas on plasmids, we develop a stochastic model describing the dynamics of a virulent phage infection against which a conjugative plasmid defends using CRISPR-Cas. We show that CRISPR-Cas on plasmids provides robust protection, except in limited parameter sets. In these cases, high segregation loss favours phage outbreaks by generating a population of defenceless cells on which the phage can evolve and escape CRISPR-Cas immunity. We show that the phage's ability to exploit segregation loss depends strongly on the evolvability of both CRISPR-Cas and the phage itself.

CRISPR-Cas in Pseudomonas aeruginosa provides transient population-level immunity against high phage exposures

The prokaryotic adaptive immune system, CRISPR-Cas (clustered regularly interspaced short palindromic repeats; CRISPR-associated), requires the acquisition of spacer sequences that target invading mobile genetic elements such as phages. Previous work has identified ecological variables that drive the evolution of CRISPR-based immunity of the model organism Pseudomonas aeruginosa PA14 against its phage DMS3vir, resulting in rapid phage extinction. However, it is unclear if and how stable such acquired immunity is within bacterial populations, and how this depends on the environment. Here, we examine the dynamics of CRISPR spacer acquisition and loss over a 30-day evolution experiment and identify conditions that tip the balance between long-term maintenance of immunity versus invasion of alternative resistance strategies that support phage persistence. Specifically, we find that both the initial phage dose and reinfection frequencies determine whether or not acquired CRISPR immunity is maintained in the long term, and whether or not phage can coexist with the bacteria. At the population genetics level, emergence and loss of CRISPR immunity are associated with high levels of spacer diversity that subsequently decline due to invasion of bacteria carrying pilus-associated mutations. Together, these results provide high resolution of the dynamics of CRISPR immunity acquisition and loss and demonstrate that the cumulative phage burden determines the effectiveness of CRISPR over ecologically relevant timeframes.

Modeling spatial evolution of multi-drug resistance under drug environmental gradients

Multi-drug combinations to treat bacterial populations are at the forefront of approaches for infection control and prevention of antibiotic resistance. Although the evolution of antibiotic resistance has been theoretically studied with mathematical population dynamics models, extensions to spatial dynamics remain rare in the literature, including in particular spatial evolution of multi-drug resistance. In this study, we propose a reaction-diffusion system that describes the multi-drug evolution of bacteria, based on a rescaling approach (Gjini and Wood, 2021). We show how the resistance to drugs in space, and the consequent adaptation of growth rate is governed by a Price equation with diffusion. The covariance terms in this equation integrate features of drug interactions and collateral resistances or sensitivities to the drugs. We study spatial versions of the model where the distribution of drugs is homogeneous across space, and where the drugs vary environmentally in a piecewise-constant, linear and nonlinear manner. Applying concepts from perturbation theory and reaction-diffusion equations, we propose an analytical characterization of average mutant fitness in the spatial system based on the principal eigenvalue of our linear problem. This enables an accurate translation from drug spatial gradients and mutant antibiotic susceptibility traits, to the relative advantage of each mutant across the environment. Such a mathematical understanding allows to predict the precise outcomes of selection over space, ultimately from the fundamental balance between growth and movement traits, and their diversity in a population.

Transient eco-evolutionary dynamics early in a phage epidemic have strong and lasting impact on the long-term evolution of bacterial defences

Organisms have evolved a range of constitutive (always active) and inducible (elicited by parasites) defence mechanisms, but we have limited understanding of what drives the evolution of these orthogonal defence strategies. Bacteria and their phages offer a tractable system to study this: Bacteria can acquire constitutive resistance by mutation of the phage receptor (surface mutation, sm) or induced resistance through their CRISPR-Cas adaptive immune system. Using a combination of theory and experiments, we demonstrate that the mechanism that establishes first has a strong advantage because it weakens selection for the alternative resistance mechanism. As a consequence, ecological factors that alter the relative frequencies at which the different resistances are acquired have a strong and lasting impact: High growth conditions promote the evolution of sm resistance by increasing the influx of receptor mutation events during the early stages of the epidemic, whereas a high infection risk during this stage of the epidemic promotes the evolution of CRISPR immunity, since it fuels the (infection-dependent) acquisition of CRISPR immunity. This work highlights the strong and lasting impact of the transient evolutionary dynamics during the early stages of an epidemic on the long-term evolution of constitutive and induced defences, which may be leveraged to manipulate phage resistance evolution in clinical and applied settings.

The proportion of resistant hosts in mixtures should be biased towards the resistance with the lowest breaking cost

Current agricultural practices facilitate emergence and spread of plant diseases through the wide use of monocultures. Host mixtures are a promising alternative for sustainable plant disease control. Their effectiveness can be partly explained by priming-induced cross-protection among plants. Priming occurs when plants are challenged with non-infective pathogen genotypes, resulting in increased resistance to subsequent infections by infective pathogen genotypes. We developed an epidemiological model to explore how mixing two distinct resistant varieties can reduce disease prevalence. We considered a pathogen population composed of three genotypes infecting either one or both varieties. We found that host mixtures should not contain an equal proportion of resistant plants, but a biased ratio (e.g. 80 : 20) to minimize disease prevalence. Counter-intuitively, the optimal ratio of resistant varieties should contain a lower proportion of the costliest resistance for the pathogen to break. This benefit is amplified by priming. This strategy also prevents the invasion of pathogens breaking all resistances.

Ecology and evolution of phages encoding anti-CRISPR proteins

CRISPR-Cas are prokaryotic defence systems that provide protection against invasion by mobile genetic elements (MGE), including bacteriophages. MGE can overcome CRISPR-Cas defences by encoding anti-CRISPR (Acr) proteins. These proteins are produced in the early stages of the infection and inhibit the CRISPR-Cas machinery to allow phage replication. While research on Acr has mainly focused on their discovery, structure and mode of action, and their applications in biotechnology, the impact of Acr on the ecology of MGE as well as on the coevolution with their bacterial hosts only begins to be unravelled. In this review, we summarise our current understanding on the distribution of anti-CRISPR genes in MGE, the ecology of phages encoding Acr, and their coevolution with bacterial defence mechanisms. We highlight the need to use more diverse and complex experimental models to better understand the impact of anti-CRISPR in MGE-host interactions.

The impact of cross-reactive immunity on the emergence of SARS-CoV-2 variants

Introduction

A key feature of the COVID-19 pandemic has been the emergence of SARS-CoV-2 variants with different transmission characteristics. However, when a novel variant arrives in a host population, it will not necessarily lead to many cases. Instead, it may fade out, due to stochastic effects and the level of immunity in the population. Immunity against novel SARS-CoV-2 variants may be influenced by prior exposures to related viruses, such as other SARS-CoV-2 variants and seasonal coronaviruses, and the level of cross-reactive immunity conferred by those exposures.

Methods

Here, we investigate the impact of cross-reactive immunity on the emergence of SARS-CoV-2 variants in a simplified scenario in which a novel SARS-CoV-2 variant is introduced after an antigenically related virus has spread in the population. We use mathematical modelling to explore the risk that the novel variant invades the population and causes a large number of cases, as opposed to fading out with few cases.

Results

We find that, if cross-reactive immunity is complete (i.e. someone infected by the previously circulating virus is not susceptible to the novel variant), the novel variant must be more transmissible than the previous virus to invade the population. However, in a more realistic scenario in which cross-reactive immunity is partial, we show that it is possible for novel variants to invade, even if they are less transmissible than previously circulating viruses. This is because partial cross-reactive immunity effectively increases the pool of susceptible hosts that are available to the novel variant compared to complete cross-reactive immunity. Furthermore, if previous infection with the antigenically related virus assists the establishment of infection with the novel variant, as has been proposed following some experimental studies, then even variants with very limited transmissibility are able to invade the host population.

Discussion

Our results highlight that fast assessment of the level of cross-reactive immunity conferred by related viruses against novel SARS-CoV-2 variants is an essential component of novel variant risk assessments.

Can breeders prevent pathogen adaptation when selecting for increased resistance to infectious diseases?

Background

Recent research shows that genetic selection has high potential to reduce the prevalence of infectious diseases in livestock. However, like all interventions that target infectious diseases, genetic selection of livestock can exert selection pressure on pathogen populations. Such selection on the pathogen may lead to escape strategies and reduce the effect of selection of livestock for disease resistance. Thus, to successfully breed livestock for lower disease prevalence, it is essential to develop strategies that prevent the invasion of pathogen mutants that escape host resistance. Here we investigate the conditions under which such “escape mutants” can replace wild-type pathogens in a closed livestock population using a mathematical model of disease transmission.

Results

Assuming a single gene that confers sufficient resistance, results show that genetic selection for resistance in livestock typically leads to an “invasion window” within which an escape mutant of the pathogen can invade. The bounds of the invasion window are determined by the frequency of resistant hosts in the population. The lower bound occurs when the escape mutant has an advantage over the wild-type pathogen in the population. The upper bound occurs when local eradication of the pathogen is expected. The invasion window is smallest when host resistance is strong and when infection with the wild-type pathogen provides cross immunity to infection with the escape mutant.

Conclusions

To minimise opportunities for pathogens to adapt, under the assumptions of our model, the aim of disease control through genetic selection should be to achieve herd-level eradication of the infection faster than the rate of emergence of escape mutants of the pathogen. Especially for microparasitic infections, this could be achieved by placing animals into herds according to their genetic resistance, such that these herds stay completely out of the invasion window. In contrast to classical breeding theory, our model suggests that multi-trait selection with gradual improvement of each trait of the breeding goal might not be the best strategy when resistance to infectious disease is part of the breeding goal. Temporally, combining genetic selection with other interventions helps to make the invasion window smaller, and thereby reduces the risk of invasion of escape mutants.

Ecological and evolutionary dynamics of multi-strain RNA viruses

Potential interactions among co-circulating viral strains in host populations are often overlooked in the study of virus transmission. However, these interactions probably shape transmission dynamics by influencing host immune responses or altering the relative fitness among co-circulating strains. In this Review, we describe multi-strain dynamics from ecological and evolutionary perspectives, outline scales in which multi-strain dynamics occur and summarize important immunological, phylogenetic and mathematical modelling approaches used to quantify interactions among strains. We also discuss how host-pathogen interactions influence the co-circulation of pathogens. Finally, we highlight outstanding questions and knowledge gaps in the current theory and study of ecological and evolutionary dynamics of multi-strain viruses.

Competition and coevolution drive the evolution and the diversification of CRISPR immunity

The diversity of resistance challenges the ability of pathogens to spread and to exploit host populations. Yet, how this host diversity evolves over time remains unclear because it depends on the interplay between intraspecific competition among host genotypes and coevolution with pathogens. Here we study experimentally the effect of coevolving phage populations on the diversification of bacterial CRISPR immunity across space and time. We demonstrate that the negative-frequency-dependent selection generated by coevolution is a powerful force that maintains host resistance diversity and selects for new resistance mutations in the host. We also find that host evolution is driven by asymmetries in competitive abilities among different host genotypes. Even if the fittest host genotypes are targeted preferentially by the evolving phages, they often escape extinctions through the acquisition of new CRISPR immunity. Together, these fluctuating selective pressures maintain diversity, but not by preserving the pre-existing host composition. Instead, we repeatedly observe the introduction of new resistance genotypes stemming from the fittest hosts in each population. These results highlight the importance of competition on the transient dynamics of host-pathogen coevolution.

Developing an empirical model for spillover and emergence: Orsay virus host range in Caenorhabditis

A lack of tractable experimental systems in which to test hypotheses about the ecological and evolutionary drivers of disease spillover and emergence has limited our understanding of these processes. Here we introduce a promising system: Caenorhabditis hosts and Orsay virus, a positive-sense single-stranded RNA virus that naturally infects C. elegans. We assayed species across the Caenorhabditis tree and found Orsay virus susceptibility in 21 of 84 wild strains belonging to 14 of 44 species. Confirming patterns documented in other systems, we detected effects of host phylogeny on susceptibility. We then tested whether susceptible strains were capable of transmitting Orsay virus by transplanting exposed hosts and determining whether they transmitted infection to conspecifics during serial passage. We found no evidence of transmission in 10 strains (virus undetectable after passaging in all replicates), evidence of low-level transmission in 5 strains (virus lost between passage 1 and 5 in at least one replicate) and evidence of sustained transmission in 6 strains (including all three experimental C. elegans strains) in at least one replicate. Transmission was strongly associated with viral amplification in exposed populations. Variation in Orsay virus susceptibility and transmission among Caenorhabditis strains suggests that the system could be powerful for studying spillover and emergence.

Revisiting implementation of multiple natural enemies in pest management

A major goal of biological control is the reduction and/or eradication of pests using various natural enemies, in particular, via deliberate infection of the target species by parasites. To enhance the biological control, a promising strategy seems to implement a multi-enemy assemblage rather than a single control agent. Although a large body of theoretical studies exists on co-infections in epidemiology and ecology, there is still a big gap in modelling outcomes of multi-enemy biological control. Here we theoretically investigate how the efficiency of biological control of a pest depends on the number of natural enemies used. We implement a combination of eco-epidemiological modelling and the Adaptive Dynamics game theory framework. We found that a progressive addition of parasite species increases the evolutionarily stable virulence of each parasite, and thus enhances the mortality of the target pest. However, using multiple enemies may have only a marginal effect on the success of biological control, or can even be counter-productive when the number of enemies is excessive. We found the possibility of evolutionary suicide, where one or several parasite species go extinct over the course of evolution. Finally, we demonstrate an interesting scenario of coexistence of multiple parasites at the edge of extinction.

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.

Targeted Virome Sequencing Enhances Unbiased Detection and Genome Assembly of Known and Emerging Viruses-The Example of SARS-CoV-2

Targeted virome enrichment and sequencing (VirCapSeq-VERT) utilizes a pool of oligos (baits) to enrich all known—up to 2015—vertebrate-infecting viruses, increasing their detection sensitivity. The hybridisation of the baits to the target sequences can be partial, thus enabling the detection and genomic reconstruction of novel pathogens with <40% genetic diversity compared to the strains used for the baits’ design. In this study, we deploy this method in multiplexed mixes of viral extracts, and we assess its performance in the unbiased detection of DNA and RNA viruses after cDNA synthesis. We further assess its efficiency in depleting various background genomic material. Finally, as a proof-of-concept, we explore the potential usage of the method for the characterization of unknown, emerging human viruses, such as SARS-CoV-2, which may not be included in the baits’ panel. We mixed positive samples of equimolar DNA/RNA viral extracts from SARS-CoV-2, coronavirus OC43, cytomegalovirus, influenza A virus H3N2, parvovirus B19, respiratory syncytial virus, adenovirus C and coxsackievirus A16. Targeted virome enrichment was performed on a dsDNA mix, followed by sequencing on the NextSeq500 (Illumina) and the portable MinION sequencer, to evaluate its usability as a point-of-care (PoC) application. Genome mapping assembly was performed using viral reference sequences. The untargeted libraries contained less than 1% of total reads mapped on most viral genomes, while RNA viruses remained undetected. In the targeted libraries, the percentage of viral-mapped reads were substantially increased, allowing full genome assembly in most cases. Targeted virome sequencing can enrich a broad range of viruses, potentially enabling the discovery of emerging viruses.

Bacterial-Viral Interactions: A Factor That Facilitates Transmission Heterogeneities

The transmission of infectious diseases is characterized by heterogeneities that are shaped by the host, the pathogen, and the environment. Extreme forms of these heterogeneities are called super-spreading events. Transmission heterogeneities are usually identified retrospectively, but their contribution to the dynamics of outbreaks makes the ability to predict them valuable for science, medicine, and public health. Previous studies identified several factors that facilitate super-spreading; one of them is the interaction between bacteria and viruses within a host. The heightened dispersal of bacteria colonizing the nasal cavity during an upper respiratory viral infection, and the increased shedding of HIV-1 from the urogenital tract during a sexually transmitted bacterial infection, are among the most extensively studied examples of transmission heterogeneities that result from bacterial-viral interactions. Interrogating these transmission heterogeneities, and elucidating the underlying cellular and molecular mechanisms, are part of much-needed efforts to guide public health interventions, in areas that range from predicting or controlling the population transmission of respiratory pathogens, to limiting the spread of sexually transmitted infections, and tailoring vaccination initiatives with live attenuated vaccines.

Host mixtures for plant disease control: benefits from pathogen selection and immune priming

Multiline and cultivar mixtures are highly effective methods for agroecological plant disease control. Priming‐induced cross protection, occurring when plants are challenged by avirulent pathogen genotypes and resulting in increased resistance to subsequent infection by virulent ones, is one critical key to their lasting performance against polymorphic pathogen populations. Strikingly, this mechanism was until recently absent from mathematical models aiming at designing optimal host mixtures. We developed an epidemiological model to explore the effect of host mixtures composed of variable numbers of single‐resistance cultivars on the equilibrium prevalence of the disease caused by pathogen populations polymorphic for virulence complexity. This model shows that a relatively large amount of resistance genes must be deployed to achieve low disease prevalence, as pathogen competition in mixtures tends to select for intermediate virulence complexity. By contrast, priming significantly reduces the number of plant genotypes needed to drop disease prevalence below an acceptable threshold. Given the limited availability of resistance genes in cultivars, this mechanism of plant immunity should be assessed when designing host mixtures.

Genetic diversity and disease: The past, present, and future of an old idea

Why do infectious diseases erupt in some host populations and not others? This question has spawned independent fields of research in evolution, ecology, public health, agriculture, and conservation. In the search for environmental and genetic factors that predict variation in parasitism, one hypothesis stands out for its generality and longevity: genetically homogeneous host populations are more likely to experience severe parasitism than genetically diverse populations. In this perspective piece, I draw on overlapping ideas from evolutionary biology, agriculture, and conservation to capture the far-reaching implications of the link between genetic diversity and disease. I first summarize the development of this hypothesis and the results of experimental tests. Given the convincing support for the protective effect of genetic diversity, I then address the following questions: (1) Where has this idea been put to use, in a basic and applied sense, and how can we better use genetic diversity to limit disease spread? (2) What new hypotheses does the established disease-diversity relationship compel us to test? I conclude that monitoring, preserving, and augmenting genetic diversity is one of our most promising evolutionarily informed strategies for buffering wild, domesticated, and human populations against future outbreaks.

Microbial defenses against mobile genetic elements and viruses: Who defends whom from what?

Prokaryotes have numerous mobile genetic elements (MGEs) that mediate horizontal gene transfer (HGT) between cells. These elements can be costly, even deadly, and cells use numerous defense systems to filter, control, or inactivate them. Recent studies have shown that prophages, conjugative elements, their parasites (phage satellites and mobilizable elements), and other poorly described MGEs encode defense systems homologous to those of bacteria. These constitute a significant fraction of the repertoire of cellular defense genes. As components of MGEs, these defense systems have presumably evolved to provide them, not the cell, adaptive functions. While the interests of the host and MGEs are aligned when they face a common threat such as an infection by a virulent phage, defensive functions carried by MGEs might also play more selfish roles to fend off other antagonistic MGEs or to ensure their maintenance in the cell. MGEs are eventually lost from the surviving host genomes by mutational processes and their defense systems can be co-opted when they provide an advantage to the cell. The abundance of defense systems in MGEs thus sheds new light on the role, effect, and fate of the so-called "cellular defense systems," whereby they are not only merely microbial defensive weapons in a 2-partner arms race, but also tools of intragenomic conflict between multiple genetic elements with divergent interests that shape cell fate and gene flow at the population level.

Evolutionary dynamics in an SI epidemic model with phenotype-structured susceptible compartment

We present an SI epidemic model whereby a continuous structuring variable captures variability in proliferative potential and resistance to infection among susceptible individuals. The occurrence of heritable, spontaneous changes in these phenotypic characteristics and the presence of a fitness trade-off between resistance to infection and proliferative potential are explicitly incorporated into the model. The model comprises an ordinary differential equation for the number of infected individuals that is coupled with a partial integrodifferential equation for the population density function of susceptible individuals through an integral term. The expression for the basic reproduction number [Formula: see text] is derived, the disease-free equilibrium and endemic equilibrium of the model are characterised and a threshold theorem involving [Formula: see text] is proved. Analytical results are integrated with the results of numerical simulations of a calibrated version of the model based on the results of artificial selection experiments in a host-parasite system. The results of our mathematical study disentangle the impact of different evolutionary parameters on the spread of infectious diseases and the consequent phenotypic adaption of susceptible individuals. In particular, these results provide a theoretical basis for the observation that infectious diseases exerting stronger selective pressures on susceptible individuals and being characterised by higher infection rates are more likely to spread. Moreover, our results indicate that heritable, spontaneous phenotypic changes in proliferative potential and resistance to infection can either promote or prevent the spread of infectious diseases depending on the strength of selection acting on susceptible individuals prior to infection. Finally, we demonstrate that, when an endemic equilibrium is established, higher levels of resistance to infection and lower degrees of phenotypic heterogeneity among susceptible individuals are to be expected in the presence of infections which are characterised by lower rates of death and exert stronger selective pressures.

Estimating the risk of pandemic avian influenza

Outbreaks of highly pathogenic strains of avian influenza (HPAI) cause high mortality in avian populations worldwide. When spread from avian reservoirs to humans, HPAI infections cause mortality in about 50% of human infections. Cases of human-to-human transmission of HPAI are relatively rare, and have, to date, only been reported in situations of close contact. These transmissions have resulted in isolated clusters of human HPAI infections, but have not yet caused a pandemic. Given the large number of human H5N1 HPAI infections to date, none of which has resulted in a pandemic, we estimate an upper bound on the probability of H5N1 pandemic emergence. We use this estimate to provide the likelihood of observing such a pandemic over the next decade. We then develop a more accurate parameter-based estimate of the emergence probability and predict the likelihood that, through rare mutations, an H5N1 influenza pandemic will emerge over the same time span.

Ecological and evolutionary solutions to the plasmid paradox

The 'plasmid paradox' arises because, although plasmids are common features of bacterial genomes, theoretically they should not exist: rates of conjugation were believed insufficient to allow plasmids to persist by infectious transmission, whereas the costs of plasmid maintenance meant that plasmids should be purged by negative selection regardless of whether they encoded beneficial accessory traits because these traits should eventually be captured by the chromosome, enabling the loss of the redundant plasmid. In the decade since the plasmid paradox was described, new data and theory show that a range of ecological and evolutionary mechanisms operate in bacterial populations and communities to explain the widespread distribution and stable maintenance of plasmids. We conclude, therefore, that multiple solutions to the plasmid paradox are now well understood. The current challenge for the field, however, is to better understand how these solutions operate in natural bacterial communities to explain and predict the distribution of plasmids and the dynamics of the horizontal gene transfer that they mediate in bacterial (pan)genomes.

Ecological memory preserves phage resistance mechanisms in bacteria

Bacterial defenses against phage, which include CRISPR-mediated immunity and other mechanisms, can carry substantial growth rate costs and can be rapidly lost when pathogens are eliminated. How bacteria preserve their molecular defenses despite their costs, in the face of variable pathogen levels and inter-strain competition, remains a major unsolved problem in evolutionary biology. Here, we present a multilevel model that incorporates biophysics of molecular binding, host-pathogen population dynamics, and ecological dynamics across a large number of independent territories. Using techniques of game theory and non-linear dynamical systems, we show that by maintaining a non-zero failure rate of defenses, hosts sustain sufficient levels of pathogen within an ecology to select against loss of the defense. This resistance switching strategy is evolutionarily stable, and provides a powerful evolutionary mechanism that maintains host-pathogen interactions, selects against cheater strains that avoid the costs of immunity, and enables co-evolutionary dynamics in a wide range of systems.

Models of Plant Resistance Deployment

Owing to their evolutionary potential, plant pathogens are able to rapidly adapt to genetically controlled plant resistance, often resulting in resistance breakdown and major epidemics in agricultural crops. Various deployment strategies have been proposed to improve resistance management. Globally, these rely on careful selection of resistance sources and their combination at various spatiotemporal scales (e.g., via gene pyramiding, crop rotations and mixtures, landscape mosaics). However, testing and optimizing these strategies using controlled experiments at large spatiotemporal scales are logistically challenging. Mathematical models provide an alternative investigative tool, and many have been developed to explore resistance deployment strategies under various contexts. This review analyzes 69 modeling studies in light of specific model structures (e.g., demographic or demogenetic, spatial or not), underlying assumptions (e.g., whether preadapted pathogens are present before resistance deployment), and evaluation criteria (e.g., resistance durability, disease control, cost-effectiveness). It highlights major research findings and discusses challenges for future modeling efforts.

Managing health disasters and Civil-Military Cooperation: A case of COVID-19 in Pakistan

As an institution, the Pakistan Army has been playing a significant role in dealing with emergencies and disasters facing the nation. The novel coronavirus disease, Severe Acute Respiratory Syndrome (SARS) COVID-19, was wreaking havoc around the world. The pandemic is a threat to health and has caused severe damage across most aspects of the society. The situation forced the formation of a unique series of civil-military inter-agency relationships to be formed, in order to curb the spread of the pandemic. The Pakistan Army that was neither trained nor equipped to undertake any such health disaster management operation played a significant role in preventing disease and overcoming the disaster. Civil-military cooperation (CIMIC) was the key to the successful response of Pakistan towards COVID-19. The research was based on qualitative interviews that analysed the phenomenon of COVID-19 pandemic, that is, 'health disaster', to elucidate the disaster management practices performed through the framework of CIMIC in Pakistan. With regard to this, the article argued that formulating a comprehensive guideline or framework was necessary to maintain an effective and cooperative relationship between civil and military components. It further demonstrated the need to recognise the constitutive factors that influenced the functionalisation and institutionalisation of CIMIC to manage the highly complex health-related emergencies.

Functional immunogenetic variation, rather than local adaptation, predicts ectoparasite infection intensity in a model fish species

Natural host populations differ in their susceptibility to infection by parasites, and these intrapopulation differences are still an incompletely understood component of host‐parasite dynamics. In this study, we used controlled infection experiments with wild‐caught guppies (Poecilia reticulata) and their ectoparasite Gyrodactylus turnbulli to investigate the roles of local adaptation and host genetic composition (immunogenetic and neutral) in explaining differences in susceptibility to infection. We found differences between our four study host populations that were consistent between two parasite source populations, with no indication of local adaptation by either host or parasite at two tested spatial scales. Greater values of host population genetic variability metrics broadly aligned with lower population mean infection intensity, with the best alignments associated with major histocompatibility complex (MHC) “supertypes”. Controlling for intrapopulation differences and potential inbreeding variance, we found a significant negative relationship between individual‐level functional MHC variability and infection: fish carrying more MHC supertypes experienced infections of lower severity, with limited evidence for supertype‐specific effects. We conclude that population‐level differences in host infection susceptibility probably reflect variation in parasite selective pressure and/or host evolutionary potential, underpinned by functional immunogenetic variation.

Evolutionary Ecology and Interplay of Prokaryotic Innate and Adaptive Immune Systems

Like many organisms, bacteria and archaea have both innate and adaptive immune systems to defend against infection by viruses and other parasites. Innate immunity most commonly relies on the endonuclease-mediated cleavage of any incoming DNA that lacks a specific epigenetic modification, through a system known as restriction-modification. CRISPR-Cas-mediated adaptive immunity relies on the insertion of short DNA sequences from parasite genomes into CRISPR arrays on the host genome to provide sequence-specific protection. The discovery of each of these systems has revolutionised our ability to carry out genetic manipulations, and, as a consequence, the enzymes involved have been characterised in exquisite detail. In comparison, much less is known about the importance of these two arms of the defence for the ecology and evolution of prokaryotes and their parasites. Here, we review our current ecological and evolutionary understanding of these systems in isolation, and discuss the need to study how innate and adaptive immune responses are integrated when they coexist in the same cell.

Rates of SARS-CoV-2 transmission and vaccination impact the fate of vaccine-resistant strains

Vaccines are thought to be the best available solution for controlling the ongoing SARS-CoV-2 pandemic. However, the emergence of vaccine-resistant strains may come too rapidly for current vaccine developments to alleviate the health, economic and social consequences of the pandemic. To quantify and characterize the risk of such a scenario, we created a SIR-derived model with initial stochastic dynamics of the vaccine-resistant strain to study the probability of its emergence and establishment. Using parameters realistically resembling SARS-CoV-2 transmission, we model a wave-like pattern of the pandemic and consider the impact of the rate of vaccination and the strength of non-pharmaceutical intervention measures on the probability of emergence of a resistant strain. As expected, we found that a fast rate of vaccination decreases the probability of emergence of a resistant strain. Counterintuitively, when a relaxation of non-pharmaceutical interventions happened at a time when most individuals of the population have already been vaccinated the probability of emergence of a resistant strain was greatly increased. Consequently, we show that a period of transmission reduction close to the end of the vaccination campaign can substantially reduce the probability of resistant strain establishment. Our results suggest that policymakers and individuals should consider maintaining non-pharmaceutical interventions and transmission-reducing behaviours throughout the entire vaccination period.

Taking Advantage of Pathogen Diversity and Immune Priming to Minimize Disease Prevalence in Host Mixtures: A Model

Host mixtures are a promising method for agroecological plant disease control. Plant immunity is key to the success of host mixtures against polymorphic pathogen populations. This immunity results from priming-induced cross-protection, whereby plants able to resist infection by specific pathogen genotypes become more resistant to other pathogen genotypes. Strikingly, this phenomenon was absent from mathematical models aiming at designing host mixtures. We developed a model to specifically explore how priming affects the coexistence of two pathogen genotypes in host mixtures composed of two host genotypes and how it affects disease prevalence. The main effect of priming is to reduce the coexistence region in the parameter space (due to the cross-protection) and to generate a singular mixture of resistant and susceptible hosts corresponding to the maximal reduction disease prevalence (in absence of priming, a resistant pure stand is optimal). The epidemiological advantage of host mixtures over a resistant pure stand thus appears as a direct consequence of immune priming. We also showed that there is indirect cross-protection between host genotypes in a mixture. Moreover, the optimal mix prevents the emergence of a resistance-breaking pathogen genotype. Our results highlight the importance of considering immune priming to design optimal and sustainable host mixtures.

Vaccine escape in a heterogeneous population: insights for SARS-CoV-2 from a simple model

As a countermeasure to the SARS-CoV-2 pandemic, there has been swift development and clinical trial assessment of candidate vaccines, with subsequent deployment as part of mass vaccination campaigns. However, the SARS-CoV-2 virus has demonstrated the ability to mutate and develop variants, which can modify epidemiological properties and potentially also the effectiveness of vaccines. The widespread deployment of highly effective vaccines may rapidly exert selection pressure on the SARS-CoV-2 virus directed towards mutations that escape the vaccine-induced immune response. This is particularly concerning while infection is widespread. By developing and analysing a mathematical model of two population groupings with differing vulnerability and contact rates, we explore the impact of the deployment of vaccines among the population on the reproduction ratio, cases, disease abundance and vaccine escape pressure. The results from this model illustrate two insights: (i) vaccination aimed at reducing prevalence could be more effective at reducing disease than directly vaccinating the vulnerable; (ii) the highest risk for vaccine escape can occur at intermediate levels of vaccination. This work demonstrates a key principle: the careful targeting of vaccines towards particular population groups could reduce disease as much as possible while limiting the risk of vaccine escape.

Host genotype and genetic diversity shape the evolution of a novel bacterial infection

Pathogens continue to emerge from increased contact with novel host species. Whilst these hosts can represent distinct environments for pathogens, the impacts of host genetic background on how a pathogen evolves post-emergence are unclear. In a novel interaction, we experimentally evolved a pathogen (Staphylococcus aureus) in populations of wild nematodes (Caenorhabditis elegans) to test whether host genotype and genetic diversity affect pathogen evolution. After ten rounds of selection, we found that pathogen virulence evolved to vary across host genotypes, with differences in host metal ion acquisition detected as a possible driver of increased host exploitation. Diverse host populations selected for the highest levels of pathogen virulence, but infectivity was constrained, unlike in host monocultures. We hypothesise that population heterogeneity might pool together individuals that contribute disproportionately to the spread of infection or to enhanced virulence. The genomes of evolved populations were sequenced, and it was revealed that pathogens selected in distantly-related host genotypes diverged more than those in closely-related host genotypes. S. aureus nevertheless maintained a broad host range. Our study provides unique empirical insight into the evolutionary dynamics that could occur in other novel infections of wildlife and humans.

Matrix-Based Formulation of Heterogeneous Individual-Based Models of Infectious Diseases: Using SARS Epidemic as a Case Study

Heterogeneities of individual attributes and behaviors play an important role in the complex process of epidemic spreading. Compared to differential equation-based system dynamical models of infectious disease transmission, individual-based epidemic models exhibit the advantage of providing a more detailed description of realities to capture heterogeneities across a population. However, the higher granularity and resolution of individual-based epidemic models comes with the cost of increased computational complexities, which result in difficulty in formulating individual-based epidemic models with mathematics. Furthermore, it requires great effort to understand and reproduce existing individual-based epidemic models presented by previous researchers. We proposed a mathematical formulation of heterogeneous individual-based epidemic models using matrices. Matrices and vectors were applied to represent individual attributes and behaviors. We derived analytical results from the matrix-based formulations of individual epidemic models, and then designed algorithms to force the computation of matrix-based individual epidemic models. Finally, we used a SARS epidemic control as a case study to verify the matrix-based formulation of heterogeneous individual-based epidemic models.

Coevolution between bacterial CRISPR-Cas systems and their bacteriophages

CRISPR-Cas systems provide bacteria and archaea with adaptive, heritable immunity against their viruses (bacteriophages and phages) and other parasitic genetic elements. CRISPR-Cas systems are highly diverse, and we are only beginning to understand their relative importance in phage defense. In this review, we will discuss when and why CRISPR-Cas immunity against phages evolves, and how this, in turn, selects for the evolution of immune evasion by phages. Finally, we will discuss our current understanding of if, and when, we observe coevolution between CRISPR-Cas systems and phages, and how this may be influenced by the mechanism of CRISPR-Cas immunity.

Epidemiological and evolutionary consequences of periodicity in treatment coverage

Host heterogeneity is a key driver of host-pathogen dynamics. In particular, the use of treatments against infectious diseases creates variation in quality among hosts, which can have both epidemiological and evolutionary consequences. We present a general theoretical model to highlight the consequences of different imperfect treatments on pathogen prevalence and evolution. These treatments differ in their action on host and pathogen traits. In contrast with previous studies, we assume that treatment coverage can vary in time, as in seasonal or pulsed treatment strategies. We show that periodic treatment strategies can limit both disease spread and virulence evolution, depending on the type of treatment. We also introduce a new method to analytically calculate the selection gradient in periodic environments, which allows our predictions to be interpreted using the concept of reproductive value, and can be applied more generally to analyse eco-evolutionary dynamics in class-structured populations and fluctuating environments.

Long-run bacteria-phage coexistence dynamics under natural habitat conditions in an environmental biotechnology system

Bacterial viruses are widespread and abundant across natural and engineered habitats. They influence ecosystem functioning through interactions with their hosts. Laboratory studies of phage-host pairs have advanced our understanding of phenotypic and genetic diversification in bacteria and phages. However, the dynamics of phage-host interactions have been seldom recorded in complex natural environments. We conducted an observational metagenomic study of the dynamics of interaction between Gordonia and their phages using a three-year data series of samples collected from a full-scale wastewater treatment plant. The aim was to obtain a comprehensive picture of the coevolution dynamics in naturally evolving populations at relatively high time resolution. Coevolution was followed by monitoring changes over time in the CRISPR loci of Gordonia metagenome-assembled genome, and reciprocal changes in the viral genome. Genome-wide analysis indicated low strain variability of Gordonia, and almost clonal conservation of the trailer end of the CRISPR loci. Incorporation of newer spacers gave rise to multiple coexisting bacterial populations. The host population carrying a shorter CRISPR locus that contain only ancestral spacers, which has not acquired newer spacers against the coexisting phages, accounted for more than half of the total host abundance in the majority of samples. Phages genome co-evolved by introducing directional changes, with no preference for mutations within the protospacer and PAM regions. Metagenomic reconstruction of time-resolved variants of host and viral genomes revealed how the complexity at the population level has important consequences for bacteria-phage coexistence.

Host-shift as the cause of emerging infectious diseases: Experimental approaches using Drosophila-virus interactions

Host shifts, when a cross-species transmission of a pathogen can lead to successful infections, are the main cause of emerging infectious diseases, such as COVID-19. A complex challenge faced by the scientific community is to address the factors that determine whether the cross-species transmissions will result in spillover or sustained onwards infections. Here we review recent literature and present a perspective on current approaches we are using to understand the mechanisms underlying host shifts. We highlight the usefulness of the interactions between Drosophila species and viruses as an ideal study model. Additionally, we discuss how cross-infection experiments - when pathogens from a natural reservoir are intentionally injected in novel host species- can test the effect cross-species transmissions may have on the fitness of virus and host, and how the host phylogeny may influence this response. We also discuss experiments evaluating how cooccurrence with other viruses or the presence of the endosymbiont bacteria Wolbachia may affect the performance of new viruses in a novel host. Finally, we discuss the need of surveys of virus diversity in natural populations using next-generation sequencing technologies. In the long term, these approaches can contribute to a better understanding of the basic biology of host shifts.

It is unclear how important CRISPR-Cas systems are for protecting natural populations of bacteria against infections by mobile genetic elements

Articles on CRISPR commonly open with some variant of the phrase “these short palindromic repeats and their associated endonucleases (Cas) are an adaptive immune system that exists to protect bacteria and archaea from viruses and infections with other mobile genetic elements.” There is an abundance of genomic data consistent with the hypothesis that CRISPR plays this role in natural populations of bacteria and archaea, and experimental demonstrations with a few species of bacteria and their phage and plasmids show that CRISPR-Cas systems can play this role in vitro. Not at all clear are the ubiquity, magnitude, and nature of the contribution of CRISPR-Cas systems to the ecology and evolution of natural populations of microbes and the strength of selection mediated by different types of phage and plasmids to the evolution and maintenance of CRISPR-Cas systems. In this perspective, with the aid of heuristic mathematical–computer simulation models, we explore the a priori conditions under which exposure to lytic and temperate phage and conjugative plasmids will select for and maintain CRISPR-Cas systems in populations of bacteria and archaea. We review the existing literature addressing these ecological and evolutionary questions and highlight the experimental and other evidence needed to fully understand the conditions responsible for the evolution and maintenance of CRISPR-Cas systems and the contribution of these systems to the ecology and evolution of bacteria, archaea, and the mobile genetic elements that infect them.

The network structure and eco-evolutionary dynamics of CRISPR-induced immune diversification

As a heritable sequence-specific adaptive immune system, CRISPR-Cas is a powerful force shaping strain diversity in host-virus systems. While the diversity of CRISPR alleles has been explored, the associated structure and dynamics of host-virus interactions have not. We explore the role of CRISPR in mediating the interplay between host-virus interaction structure and eco-evolutionary dynamics in a computational model and compare the results with three empirical datasets from natural systems. We show that the structure of the networks describing who infects whom and the degree to which strains are immune, are respectively modular (containing groups of hosts and viruses that interact strongly) and weighted-nested (specialist hosts are more susceptible to subsets of viruses that in turn also infect the more generalist hosts with many spacers matching many viruses). The dynamic interplay between these networks influences transitions between dynamical regimes of virus diversification and host control. The three empirical systems exhibit weighted-nested immunity networks, a pattern our theory shows is indicative of hosts able to suppress virus diversification. Previously missing from studies of microbial host-pathogen systems, the immunity network plays a key role in the coevolutionary dynamics.

Comparative genetic diversity of Cryptosporidium species causing human infections

Parasites sometimes expand their host range and cause new disease aetiologies. Genetic changes can then occur due to host-specific adaptive alterations, particularly when parasites cross between evolutionarily distant hosts. Characterizing genetic variation in Cryptosporidium from humans and other animals may have important implications for understanding disease dynamics and transmission. We analyse sequences from four loci (gp60, HSP-70, COWP and actin) representing multiple Cryptosporidium species reported in humans. We predicted low genetic diversity in species that present unusual human infections due to founder events and bottlenecks. High genetic diversity was observed in isolates from humans of Cryptosporidium meleagridis, Cryptosporidium cuniculus, Cryptosporidium hominis and Cryptosporidium parvum. A deviation of expected values of neutrality using Tajima's D was observed in C. cuniculus and C. meleagridis. The high genetic diversity in C. meleagridis and C. cuniculus did not match our expectations but deviations from neutrality indicate a recent decrease in genetic variability through a population bottleneck after an expansion event. Cryptosporidium hominis was also found with a significant Tajima's D positive value likely caused by recent population expansion of unusual genotypes in humans. These insights indicate that changes in genetic diversity can help us to understand host-parasite adaptation and evolution.

Diversity in CRISPR-based immunity protects susceptible genotypes by restricting phage spread and evolution

Diversity in host resistance often associates with reduced pathogen spread. This may result from ecological and evolutionary processes, likely with feedback between them. Theory and experiments on bacteria-phage interactions have shown that genetic diversity of the bacterial adaptive immune system can limit phage evolution to overcome resistance. Using the CRISPR-Cas bacterial immune system and lytic phage, we engineered a host-pathogen system where each bacterial host genotype could be infected by only one phage genotype. With this model system, we explored how CRISPR diversity impacts the spread of phage when they can overcome a resistance allele, how immune diversity affects the evolution of the phage to increase its host range and if there was feedback between these processes. We show that increasing CRISPR diversity benefits susceptible bacteria via a dilution effect, which limits the spread of the phage. We suggest that this ecological effect impacts the evolution of novel phage genotypes, which then feeds back into phage population dynamics.

Skirmish or war: the emergence of agricultural plant pathogens

Understanding the ecological and evolutionary processes underlying the emergence of infectious disease is critically important in guiding prevention, management and breeding strategies. Novel pathogen lineages may arise within agricultural environments, wild hosts or from non-host associated disease reservoirs. Although the source of most disease outbreaks remains unknown, environmental and zoonotic origins are frequently identified in mammalian pathosystems and expanded sampling of plant pathosystems reveals important links with wild populations. This review describes key ecological and evolutionary processes underlying disease emergence, with particular emphasis on shifts from wild reservoirs to cultivated hosts and genetic mechanisms driving host adaption subsequent to emergence.

Winter is coming: Pathogen emergence in seasonal environments

Many infectious diseases exhibit seasonal dynamics driven by periodic fluctuations of the environment. Predicting the risk of pathogen emergence at different points in time is key for the development of effective public health strategies. Here we study the impact of seasonality on the probability of emergence of directly transmitted pathogens under different epidemiological scenarios. We show that when the period of the fluctuation is large relative to the duration of the infection, the probability of emergence varies dramatically with the time at which the pathogen is introduced in the host population. In particular, we identify a new effect of seasonality (the winter is coming effect) where the probability of emergence is vanishingly small even though pathogen transmission is high. We use this theoretical framework to compare the impact of different preventive control strategies on the average probability of emergence. We show that, when pathogen eradication is not attainable, the optimal strategy is to act intensively in a narrow time interval. Interestingly, the optimal control strategy is not always the strategy minimizing R₀, the basic reproduction ratio of the pathogen. This theoretical framework is extended to study the probability of emergence of vector borne diseases in seasonal environments and we show how it can be used to improve risk maps of Zika virus emergence.

Seasonality drives fluctuations in the probability of pathogen emergence, with dramatic consequences for public health and agriculture. We show that this probability of pathogen emergence can be vanishingly small before the low transmission season. We derive the conditions for the existence of this winter is coming effect and identify optimal control strategies that minimize the risk of pathogen emergence. We generalize this framework to account for different forms of environmental variations, different modes of control and complex pathogen life cycles. We illustrate how this framework can be used to improve predictions of Zika emergence at different points in space and time.

Disease control through removal of population using Z-control approach

Present study considers the situation where the removal of population is adopted as a prevention measure for isolating the susceptible population from an infected region to reduce the disease prevalence. To investigate the scenario, a dynamic error based method, Z-type control is applied in an SI type disease model with the aim of achieving a predetermined disease prevalence. The controlled system is designed by introducing a new compartment (the population in an infection-free region) in the uncontrolled system to capture the removal of susceptible population from the infected region to an infection free region. By performing numerical simulations, our study shows that using Z-control mechanism, the removal of susceptible to an infection free region can effectively achieve a predetermined disease prevalence. The removal rates required for achieving a specific reduction in infected population for different levels of disease endemicity are quantified. Furthermore, the global sensitivity analysis (PRCC) is also performed to have a more clear insights on the correlations of the control parameter with the model parameters.

Killer Archaea: Virus-Mediated Antagonism to CRISPR-Immune Populations Results in Emergent Virus-Host Mutualism

Theory, simulation, and experimental evolution demonstrate that diversified CRISPR-Cas immunity to lytic viruses can lead to stochastic virus extinction due to a limited number of susceptible hosts available to each potential new protospacer escape mutation. Under such conditions, theory predicts that to evade extinction, viruses evolve toward decreased virulence and promote vertical transmission and persistence in infected hosts. To better understand the evolution of host-virus interactions in microbial populations with active CRISPR-Cas immunity, we studied the interaction between CRISPR-immune Sulfolobus islandicus cells and immune-deficient strains that are infected by the chronic virus SSV9. We demonstrate that Sulfolobus islandicus cells infected with SSV9, and with other related SSVs, kill uninfected, immune strains through an antagonistic mechanism that is a protein and is independent of infectious virus. Cells that are infected with SSV9 are protected from killing and persist in the population. We hypothesize that this infection acts as a form of mutualism between the host and the virus by removing competitors in the population and ensuring continued vertical transmission of the virus within populations with diversified CRISPR-Cas immunity.IMPORTANCE Multiple studies, especially those focusing on the role of lytic viruses in key model systems, have shown the importance of viruses in shaping microbial populations. However, it has become increasingly clear that viruses with a long host-virus interaction, such as those with a chronic lifestyle, can be important drivers of evolution and have large impacts on host ecology. In this work, we describe one such interaction with the acidic crenarchaeon Sulfolobus islandicus and its chronic virus Sulfolobus spindle-shaped virus 9. Our work expands the view in which this symbiosis between host and virus evolved, describing a killing phenotype which we hypothesize has evolved in part due to the high prevalence and diversity of CRISPR-Cas immunity seen in natural populations. We explore the implications of this phenotype in population dynamics and host ecology, as well as the implications of mutualism between this virus-host pair.

Human immunodeficiency virus infection (HIV)-associated rheumatic manifestations in thepre- and post-HAART eras

Rheumatic manifestations remain an important clinical manifestation associated to HIV. To date after 4 decades of the onset of the HIV/AIDS pandemic, almost 37 million individuals are living with the infection, including close to 2 million of newly infected individuals. The status, however, of a considerable proportion of HIV/AIDS patients has changed from a near fatal disorder secondary to opportunistic infections to a chronic disease in which renal cardiovascular, diabetes, malignancy, and autoimmune co-morbid disorders have become prevalent and relevant. In addition, the spectrum of rheumatic disorders also has changed since the introduction of HAART and its diagnosis and treatment represents a challenge. The purpose of this review is to define and discuss the HIV-related rheumatic manifestations in the pre- and post-HAART eras.

Co-evolution within structured bacterial communities results in multiple expansion of CRISPR loci and enhanced immunity

Type II CRISPR-Cas systems provide immunity against phages and plasmids that infect bacteria through the insertion of a short sequence from the invader's genome, known as the 'spacer', into the CRISPR locus. Spacers are transcribed into guide RNAs that direct the Cas9 nuclease to its target on the invader. In liquid cultures, most bacteria acquire a single spacer. Multiple spacer integration is a rare event which significance for immunity is poorly understood. Here, we found that when phage infections occur on solid media, a high proportion of the surviving colonies display complex morphologies that contain cells with multiple spacers. This is the result of the viral-host co-evolution, in which the immunity provided by the initial acquired spacer is easily overcome by escaper phages. Our results reveal the versatility of CRISPR-Cas immunity, which can respond with both single or multiple spacer acquisition schemes to solve challenges presented by different environments.

Variability in the durability of CRISPR-Cas immunity

The durability of host resistance is challenged by the ability of pathogens to escape the defence of their hosts. Understanding the variability in the durability of host resistance is of paramount importance for designing more effective control strategies against infectious diseases. Here, we study the durability of various clustered regularly interspaced short palindromic repeats-Cas (CRISPR-Cas) alleles of the bacteria Streptococcus thermophilus against lytic phages. We found substantial variability in durability among different resistant bacteria. Since the escape of the phage is driven by a mutation in the phage sequence targeted by CRISPR-Cas, we explored the fitness costs associated with these escape mutations. We found that, on average, escape mutations decrease the fitness of the phage. Yet, the magnitude of this fitness cost does not predict the durability of CRISPR-Cas immunity. We contend that this variability in the durability of resistance may be because of variations in phage mutation rate or in the proportion of lethal mutations across the phage genome. These results have important implications on the coevolutionary dynamics between bacteria and phages and for the optimal deployment of resistance strategies against pathogens and pests. Understanding the durability of CRISPR-Cas immunity may also help develop more effective gene-drive strategies based on CRISPR-Cas9 technology. This article is part of a discussion meeting issue 'The ecology and evolution of prokaryotic CRISPR-Cas adaptive immune systems'.

CRISPR-Cas immunity leads to a coevolutionary arms race between Streptococcus thermophilus and lytic phage

CRISPR-Cas is an adaptive prokaryotic immune system that prevents phage infection. By incorporating phage-derived 'spacer' sequences into CRISPR loci on the host genome, future infections from the same phage genotype can be recognized and the phage genome cleaved. However, the phage can escape CRISPR degradation by mutating the sequence targeted by the spacer, allowing them to re-infect previously CRISPR-immune hosts, and theoretically leading to coevolution. Previous studies have shown that phage can persist over long periods in populations of Streptococcus thermophilus that can acquire CRISPR-Cas immunity, but it has remained less clear whether this coexistence was owing to coevolution, and if so, what type of coevolutionary dynamics were involved. In this study, we performed highly replicated serial transfer experiments over 30 days with S. thermophilus and a lytic phage. Using a combination of phenotypic and genotypic data, we show that CRISPR-mediated resistance and phage infectivity coevolved over time following an arms race dynamic, and that asymmetry between phage infectivity and host resistance within this system eventually causes phage extinction. This work provides further insight into the way CRISPR-Cas systems shape the population and coevolutionary dynamics of bacteria-phage interactions. This article is part of a discussion meeting issue 'The ecology and evolution of prokaryotic CRISPR-Cas adaptive immune systems'.