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bioRxiv2021

Epidemiological and evolutionary consequences of CRISPR-Cas reactivity

Adaptive immune systems face a control challenge: they should react with enough strength to clear an infection while avoiding to harm their organism. CRISPR-Cas systems are adaptive immune systems of prokaryotes that defend against fast evolving viruses. Here, we explore the CRISPR-Cas control challenge and look how its reactivity, i.e. its probability to acquire a new resistance, impacts the epidemiological outcome of a phage outbreak and the prokaryotes fitness. We show that in the absence of phage evolution, phage extinction is driven by the probability to acquire at least one resistance. However, when phage evolution is fast, phage extinction is characterised by an epidemiological critical threshold: any reactivity below this critical threshold leads to phage survival whereas any reactivity above it leads to phage extinction. We also show that in the absence of autoimmunity, high levels of reactivity evolve. However, when CRISPR-Cas systems are prone to autoimmune reactions, intermediate levels of reactivity are evolutionarily optimal. These results help explaining why natural CRISPR-Cas systems do not show high levels of reactivity. Author summaryCRISPR-Cas systems are adaptive immune systems that use a complex 3-step molecular mechanism to defend prokaryotes against phages. Viral infections of populations defending with CRISPR-Cas can result in rapid phage extinction or in medium-term phage maintenance. What controls phage fate? Using mathematical modeling, we show that two parameters control this outcome: the phage escape rate and CRISPR-Cas reactivity (i.e. its probability of resistance acquisition upon infection). Furthermore, CRISPR-Cas reactivity impacts host fitness. From this, we derive that 1) CRISPR-Cas reactivity is a key predictor of the efficiency and of the cost of a CRISPR-Cas system, 2) there is an optimal reactivity balancing the cost of autoimmunity and immune efficiency and 3) high phage escape rate selects for higher CRISPR-Cas reactivities.

microbiology↗

bioRxiv2021

Dynamic molecular epidemiology reveals lineage-associated single-nucleotide variants that alter RNA structure in Chikungunya virus

Chikungunya virus (CHIKV) is an emerging Alphavirus which causes millions of human infections every year. Outbreaks have been reported in Africa and Asia since the early 1950s, from three CHIKV lineages: West African, East Central South African, and Asian Urban. As new outbreaks occurred in the Americas, individual strains from the known lineages have evolved, creating new monophyletic groups that generated novel geographic-based lineages. Building on a recently updated phylogeny of CHIKV, we report here the availability of an interactive CHIKV phylodynamics dataset, which is based on more than 900 publicly available CHIKV genomes. We provide an interactive view of CHIKV molecular epidemiology built on Nextstrain, a web-based visualization framework for real-time tracking of pathogen evolution. CHIKV molecular epidemiology reveals single nucleotide variants that change the stability and fold of locally stable RNA structures. We propose alternative RNA structure formation in different CHIKV lineages by predicting more than a dozen RNA elements that are subject to perturbation of the structure ensemble upon variation of a single nucleotide.

evolutionary biology↗

bioRxiv2021

Accessory genomic epidemiology of co-circulating Acinetobacter baumannii clones

A. baumannii has become one of the most important multidrug resistant nosocomial pathogens all over the world. Nonetheless, very little is known about the diversity of A. baumannii lineages co-existing in hospital settings. Here, using whole-genome sequencing, epidemiological data and antimicrobial susceptibility tests, we uncover the transmission dynamics of extensive and multidrug resistant A. baumannii in a tertiary hospital for a decade. Our core genome phylogeny of almost 300 genomes suggests that there were several introductions of lineages from international clone 2 into the hospital. The molecular dating analysis shows that these introductions happened between 2004 and 2015. Furthermore, using the accessory genome, we show that these lineages were extensively disseminated across many wards in the hospital. Our results demonstrate that accessory genome variation can be a very powerful tool for conducting genomic epidemiology. We anticipate future studies employing the accessory genome as a phylogenomic marker over very short microevolutionary scales.

microbiology↗

bioRxiv2021

Complexity of genomic epidemiology of carbapenem-resistant Klebsiella pneumoniae isolates in Colombia urges the reinforcement of whole genome sequencing based surveillance programs

BackgroundCarbapenem-resistant Klebsiella pneumoniae (CRKP) is an emerging public health problem. This study explores the specifics of CRKP epidemiology in Colombia based on whole genome sequencing (WGS) of the National Reference Laboratory at Instituto Nacional de Salud (INS)s 2013-2017 sample collection. MethodsA total of 425 CRKP isolates from 21 departments were analyzed by HiSeq-X10(R)Illumina high-throughput sequencing. Bioinformatic analysis was performed, primarily using the pipelines developed collaboratively by the National Institute for Health Research Global Health Research Unit (GHRU) on Genomic Surveillance of AMR, and AGROSAVIA. ResultsOf the 425 CRKP isolates, 91.5% were carbapenemase-producing strains. The data support a recent expansion and the endemicity of CRKP in Colombia with the circulation of 7 high-risk clones, the most frequent being CG258 (48.39% of isolates). We identified genes encoding carbapenemases blaKPC-3, blaKPC-2, blaNDM-1, blaNDM-9, blaVIM-2, blaVIM-4, and blaVIM-24, and various mobile genetic elements (MGE). The virulence of CRKP isolates was low, but colibactin (clb3) was present in 25.2% of isolates, and a hypervirulent CRKP clone (CG380) was reported for the first time in Colombia. ST258, ST512, and ST4851 were characterized by low levels of diversity in the core genome (ANI> 99.9%). ConclusionsThe study outlines complex CRKP epidemiology in Colombia. CG258 expanded clonally and carries specific carbapenemases in specific MGEs, while the other high-risk clones (CG147, CG307, and CG152) present a more diverse complement of carbapenemases. The specifics of the Colombian situation stress the importance of WGS-based surveillance to monitor evolutionary trends of STs, MGE, and resistance and virulence genes. summaryIn Colombia, the dissemination of carbapenemases in carbapenem-resistant Klebsiella pneumoniae is attributed to horizontal gene transfer and successful circulation of CG258, and, to a lesser extent, other clones such as ST307, ST147, and ST152.

genomics↗

bioRxiv2021

Combining biomarker and virus phylogenetic models improves epidemiological source identification

To identify and stop active HIV transmission chains new epidemiological techniques are needed. Here, we describe the development of a multi-biomarker augmentation to phylogenetic inference of the underlying transmission history in a local population. HIV biomarkers are measurable biological quantities that have some relationship to the amount of time someone has been infected with HIV. To train our model, we used five biomarkers based on real data from serological assays, HIV sequence data, and target cell counts in longitudinally followed, untreated patients with known infection times. The biomarkers were modeled with a mixed effects framework to allow for patient specific variation and general trends, and fit to patient data using Markov Chain Monte Carlo (MCMC) methods. Subsequently, the density of the unobserved infection time conditional on observed biomarkers were obtained by integrating out the random effects from the model fit. This probabilistic information about infection times was incorporated into the likelihood function for the transmission history and phylogenetic tree reconstruction, informed by the HIV sequence data. To critically test our methodology, we developed a coalescent-based simulation framework that generates phylogenies and biomarkers given a specific or general transmission history. Testing on many epidemiological scenarios showed that biomarker augmented phylogenetics can reach 90% accuracy under idealized situations. Under realistic within-host HIV evolution, involving substantial within-host diversification and frequent transmission of multiple lineages, the average accuracy was at about 50% in transmission clusters involving 5-50 hosts. Realistic biomarker data added on average 16 percentage points over using the phylogeny alone. Using more biomarkers improved the performance. Shorter temporal spacing between transmission events and increased transmission heterogeneity reduced reconstruction accuracy, but larger clusters were not harder to get right. More sequence data per infected host also improved accuracy. We show that the method is robust to incomplete sampling, and we evaluate real HIV-1 transmission clusters. The technology presented here could allow for better prevention programs by providing data for locally informed and tailored strategies. AUTHOR SUMMARYWhile phylogenetic methods have been successfully used to infer transmission patterns on many scales, substantial uncertainty about the corresponding transmission history has remained. Here, we introduce a formal inference framework for the simultaneous use of HIV biomarkers and HIV sequences derived from persons who may have infected each other. We created a flexible system that can use up to five biomarkers to estimate the time of infection of each person, with the appropriate uncertainty given by an empirical probability distribution. These time-of-infection distributions were jointly modelled with the HIV phylogenetic tree estimation to produce possible transmission histories. We show that adding biomarkers substantially limits the possible transmission histories. This makes it possible to identify transmission risks, to assess confidence in source attributions, and to make efficient resource allocations to prevent further transmissions in local epidemics.

evolutionary biology↗

bioRxiv2021

Molecular Epidemiology and Microbiological Characteristics of Cryptococcus gattii VGII isolates from China

Cryptococcus gattii (C. gattii) is a fungal pathogen that once caused an outbreak of cryptococcosis on Vancouver Island, and had spread worldwide, while few data were available in China. In this study, seven clinical isolates of C. gattii VGII were collected from 19 hospitals, Multi-locus Sequence Typing (MLST) analysis and whole-genome sequencing (WGS) was performed, and combined with published data for phylogenetic analysis. In addition, in vitro antifungal susceptibility testing, phenotypic analysis, and in vivo virulence studies were performed, subsequently, histopathological analysis of lung tissue was performed. C.gattii VGII infected patients were mainly immunocompetent male, and most of them had symptoms of central nervous system (CNS) involvement. MLST results showed that isolates from china exhibited high genetic diversity, and sequence type (ST) 7 was the major ST among the isolates. Some clinical isolates showed a close phylogenetic relationship with strains from Australia and South America. All clinical isolates did not show resistance to antifungal drugs. In addition, there was no correlation between virulence factors (temperature, melanin production, and capsule size) and virulence while in vivo experiments showed significant differences in virulence among strains. Lung fungal burden and damage to lung tissue correlated with virulence, and degree of damage to lung tissue in mice may highlight differences in virulence. Our work seeks to provide useful data for molecular epidemiology, antifungal susceptibility, and virulence differences of C. gattii VGII in China. Author SummaryCryptococcus gattii is one of the life-threatening fungal pathogens that can infect immunocompetent individuals. C.gattii can be invaded through the respiratory tract and can be spread to the brain, causing meningoencephalitis and even death. In 1999, an outbreak of C. gattii VGII occurred on Vancouver Island in Canada and spread in the Pacific Northwest region, which attracted more attention. Compared with other nations, the data of C gattii VGII in China was limited. To better understand the molecular epidemiology and microbiological characteristics of C.gattii VGII isolates from China, Bioinformatics analysis and in vivo and in vitro experiments were performed for clinical strains. Multi-locus Sequence Typing and whole-genome sequencing reveal the genetic diversity of the isolates and genetic relationships with isolates from other countries. We also investigated the antifungal drug susceptibility and virulence differences of the isolates. The authors expect that our work can provide useful data for the prevention and control of C. gattii VGII in China and to draw attention to C. gattii.

microbiology↗

bioRxiv2021

Passive epidemiological surveillance in wildlife in Costa Rica identifies pathogens of zoonotic and conservation importance

Epidemiological surveillance systems for pathogens in wild species have been proposed as a preventive measure for epidemic events. These systems can minimize the detrimental effects of an outbreak, but most importantly, passive surveillance systems are the best adapted to countries with limited resources. Therefore, the present study aims to evaluate the technical and infrastructural feasibility to establish this type of scheme in Costa Rica targeting thedetection of pathogens of zoonotic and conservation importance in wildlife. Between 2018 and 2020, 85 carcasses of free-ranging vertebrates were admitted for post mortem analysis and complementary laboratory analysis, representing a solid basis for the implementation of a passive surveillance system for wildlife diseases in the country. However, we encounter during this research significant constraints that affected the availability of carcasses for analysis, mainly related to the initial identification of cases, detection biases towards events in populated- or easily accessible-areas with nearby located wildlife management centers, further associated with financial disincentives, and limited local logistics capacity. Thus resulting in the exclusion of some geographic regions of the country. This epidemiological surveillance scheme allowed us to estimate the general state of health of the countrys wildlife, establishing the cause of death of the analyzed animals as follows: (i) 46 (54.1%) traumatic events, (ii) 23 (27.1%) infectious agents, (iii) two (2.4%) degenerative illness, (iv) three (3.5%) presumably poisoning, and (v) in 11 (12.9%)undetermined. It also allowed the detection of pathogens such as, canine distemper virus, Klebsiella pneumoniae, Toxoplasma gondii, Trypanosoma spp., Angiostrongylus spp., Dirofilaria spp., Baylisascaris spp., among others. As well as recognizing the circulation of these pathogens around national territory and also on those analyzed species. This strategy is crucial in geographical regions defined as critical for the appearance of diseases due to their great biodiversity and social conditions.

pathology↗

bioRxiv2022

Confirming Multiplex Q-PCR Use in COVID-19 with Next Generation Sequencing: Strategies for Epidemiological Advantage

Rapid classification and tracking of emerging SARS-CoV-2 variants are critical for understanding the transmission dynamics and developing strategies for interrupting the transmission chain. Next-Generation Sequencing (NGS) is an exceptional tool for whole-genome analysis and deciphering new mutations. The technique has been instrumental in identifying the Variants of Concern and tracking this pandemic. However, NGS remains expensive and time-consuming for large-scale monitoring of COVID-19. This study analyzed a total of 78 de-identified samples that screened positive for SARS-CoV-2 from two timeframes, August 2020 and July 2021. All 78 samples were classified into WHO lineages by whole genome sequencing then compared with two commercially available Q-PCR assays for spike protein mutation(s). The data showed good concordance with Q-PCR and NGS analysis for specific SARS-COV-2 lineages and characteristic mutations. Deployment of Q-PCR testing to detect known SARS-COV-2 variants may be extremely beneficial. These assays are quick and cost-effective, thus can be implemented as an alternative to sequencing for screening known mutations of SARS-COV-2 for clinical and epidemiological interest. The findings support the great potential for Q-PCR to be an effective strategy offering several COVID-19 epidemiological advantages.

genomics↗

bioRxiv2022

Evaluation of nanopore sequencing for epigenetic epidemiology: a comparison with DNA methylation microarrays

Most epigenetic epidemiology to date has utilized microarrays to identify positions in the genome where variation in DNA methylation is associated with environmental exposures or disease. However, these profile less than 3% of DNA methylation sites in the human genome, potentially missing affected loci and preventing the discovery of disrupted biological pathways. Third generation sequencing technologies, including Nanopore sequencing, have the potential to revolutionise the generation of epigenetic data, not only by providing genuine genome-wide coverage but profiling epigenetic modifications direct from native DNA. Here we assess the viability of using Nanopore sequencing for epidemiology by performing a comparison with DNA methylation quantified using the most comprehensive microarray available, the Illumina EPIC array. We implemented a CRISPR-Cas9 targeted sequencing approach in concert with Nanopore sequencing to profile DNA methylation in three genomic regions to attempt to rediscover genomic positions that existing technologies have shown are differentially methylated in tobacco smokers. Using Nanopore sequencing reads, DNA methylation was quantified at 1,779 CpGs across three regions, providing a finer resolution of DNA methylation patterns compared to the EPIC array. The correlation of estimated levels of DNA methylation between platforms was high. Furthermore, we identified 12 CpGs where hypomethylation was significantly associated with smoking status, including 10 within the AHRR gene. In summary, Nanopore sequencing is a valid option for identifying genomic loci where large differences in DNAm are associated with a phenotype and has the potential to advance our understanding of the role differential methylation plays in the aetiology of complex disease.

neuroscience↗

bioRxiv2022

Novel epidemiological model of gastrointestinal-nematode infection to assess grazing cattle resilience by integrating host growth, parasite, grass and environmental dynamics

Gastrointestinal nematode (GIN) infections are ubiquitous and often cause morbidity and reduced performance in livestock. Emerging anthelmintic resistance and increasing change in climate patterns require evaluation of alternatives to traditional treatment and management practices. Mathematical models of parasite transmission between hosts and the environment have contributed towards the design of appropriate control strategies in ruminants, but have yet to account for relationships between climate, infection pressure, immunity, resources, and growth. Here, we develop a new epidemiological model of GIN transmission in a herd of grazing cattle, including host tolerance (body weight and feed intake), parasite burden and acquisition of immunity, together with weather-dependent development of parasite free-living stages, and the influence of grass availability on parasite transmission. Dynamic host, parasite and environmental factors drive a variable rate of transmission. Using literature sources, the model was parametrised for Ostertagia ostertagi, the prevailing pathogenic GIN in grazing cattle populations in temperate climates. Model outputs were validated on published empirical studies from first season grazing cattle in Northern Europe. These results show satisfactory qualitative and quantitative performance of the model; they also indicate the model may approximate the dynamics of grazing systems under co-infection by O. ostertagi and Cooperia oncophora, a second GIN species common in cattle. In addition, model behaviour was explored under illustrative anthelmintic treatment strategies, considering impacts on parasitological and performance variables. The model has potential for extension to explore altered infection dynamics as a result of management and climate change, and to optimise treatment strategies accordingly. As the first mechanistic model to combine parasitic and free-living stages of GIN with host feed-intake and growth, it is well suited to predict complex system responses under non-stationary conditions. We discuss the implications, limitations and extensions of the model, and its potential to assist in the development of sustainable parasite control strategies. HIGHLIGHTSO_LINematode control in cattle is complicated by drug resistance and climate change C_LIO_LIA model was developed to predict GIN epidemiology under varying conditions C_LIO_LIThe model incorporates cattle growth, infection and immunity, grass availability, weather C_LIO_LIPredictions were validated against empirical studies of GIN in N Europe C_LIO_LIThe model applies to Ostertagia ostertagi, and possibly to co-infecting Cooperia C_LI O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY https://www.lmcni.com/ C_FIG_DISPLAY

ecology↗

bioRxiv2022

From components to communities: bringing network science to clustering for genomic epidemiology

Defining clusters of epidemiologically-related infections is a common problem in the surveillance of infectious disease. A popular method for generating clusters is pairwise distance clustering, which assigns pairs of sequences to the same cluster if their genetic distance falls below some threshold. The result is often represented as a network or graph of infections. A connected component is a set of interconnected nodes in a graph that are not connected to any other node. The current approach to pairwise clustering is to map clusters to the connected components of the graph. However, the distance thresholds typically used for viruses like HIV-1 tend to yield components that exclude large numbers of infections as unconnected nodes. This is problematic for public health applications of clustering, such as tracking the growth of clusters over time. We propose that this problem can be addressed with community detection, a class of clustering methods being developed in the field of network science. A community is a set of nodes that are more densely inter-connected relative to the number of connections to external nodes. Thus, a connected component may be partitioned into two or more communities. Here we describe community detection methods in the context of genetic clustering for epidemiology, demonstrate how a popular method (Markov clustering) enables us to resolve variation in transmission rates within a giant connected component of HIV-1 sequences, and identify current challenges and directions for further work.

bioinformatics↗

bioRxiv2022

Genomic epidemiology of the cholera outbreak in Yemen reveals the spread of a multi-drug resistance plasmid between diverse lineages of Vibrio cholerae

The humanitarian crisis in Yemen led in 2016 to the biggest cholera outbreak documented in modern history, with more than 2.5 million suspected cases to date. In late 2018, epidemiological surveillance showed that V. cholerae isolated from cholera patients had turned multi-drug resistant (MDR). We generated genomes from 260 isolates sampled in Yemen between 2018 and 2019 to identify a possible shift in circulating genotypes. 84% of V. cholerae isolates were serogroup O1 belonging to the seventh pandemic El Tor (7PET) lineage, sublineage T13 - same as in 2016 and 2017 - while the remaining 16% of strains were non-toxigenic and belonged to divergent V. cholerae lineages, likely reflecting sporadic gut colonisation by endemic strains. Phylogenomic analysis reveals a succession of T13 clones, with 2019 dominated by a clone that carried an IncC-type plasmid harbouring an MDR pseudo-compound transposon (PCT). Identical copies of these mobile elements were found independently in several unrelated lineages, suggesting exchange and recombination between endemic and epidemic strains. Treatment of severe cholera patients with macrolides in Yemen from 2016 to early 2019 coincides with the emergence of the plasmid-carrying T13 clone. The unprecedented success of this genotype where an SXT-family integrative and conjugative element (SXT/ICE) and an IncC plasmid coinhabit show the stability of this MDR plasmid in the 7PET background, which may durably reduce options for epidemic cholera case management. We advocate a heightened genomic epidemiology surveillance of cholera to help control the spread of this highly-transmissible, MDR clone.

microbiology↗

bioRxiv2022

Coinfection with chytrid genotypes drives divergent infection dynamics reflecting broad epidemiological patterns

By altering the abundance, diversity, and distribution of species -- and their pathogens -- globalization may inadvertently select for more virulent pathogens. In Brazils Atlantic Forest, a hotspot of amphibian biodiversity, the pet trade has facilitated the co-occurrence of previously isolated enzootic and panzootic lineages of the pathogenic amphibian-chytrid ( Bd) and generated new virulent recombinant genotypes ( hybrid). Epidemiological data indicate that amphibian declines are most severe in hybrid zones, suggesting that coinfections are causing more severe infections or selecting for higher virulence. We investigated how coinfections involving these genotypes shaped virulence and transmission. Overall, coinfection favored the more virulent and competitively superior panzootic genotype, despite dampening its virulence and transmission. However, for the least virulent and least competitive genotype, coinfection increased both pathogen virulence and transmission. Thus, by integrating experimental and epidemiological data, our results provide mechanistic insight into how globalization can select for, and propel, the emergence of introduced hypervirulent lineages, such as the globally distributed panzootic lineage of Bd.

ecology↗

bioRxiv2022

Exploring how ecological and epidemiological processes shape multi-host disease dynamics using global sensitivity analysis

We use global sensitivity analysis (specifically, Partial Rank Correlation Coefficients) to explore the roles of ecological and epidemiological processes in shaping the temporal dynamics of a parameterized SIR-type model of two host species and an environmentally transmitted pathogen. We compute the sensitivities of disease prevalence in each host species to model parameters. Sensitivity rankings and subsequent biological interpretations are calculated and contrasted for cases were the pathogen is introduced into a disease-free community and where a second host species is introduced into an endemic single-host community. In some cases the magnitudes and dynamics of the sensitivities can be predicted only by knowing the host species characteristics (i.e., their competitive abilities and disease competence) whereas in other cases they can be predicted by factors independent of the species characteristics (specifically, intraspecific versus interspecific processes or the species roles of invader versus resident). For example, when a pathogen is initially introduced into a disease-free community, disease prevalence in both hosts is more sensitive to the burst size of the first host than the second host. In comparison, disease prevalence in each host is more sensitive to its own infection rate than the infection rate of the other host species. In total, this study illustrates that global sensitivity analysis can provide useful insight into how ecological and epidemiological processes shape disease dynamics and how those effects vary across time and system conditions. Our results show that sensitivity analysis can provide quantification and direction when exploring biological hypotheses.

ecology↗

bioRxiv2023

Anchoring the mean generation time in the SEIR to mitigate biases in R0 estimates due to uncertainty in the distribution of the epidemiological delays

The basic reproduction number,[R] 0, is of paramount importance in the study of infectious disease dynamics. Primarily,[R] 0 serves as an indicator of the transmission potential of an emerging infectious disease and the effort required to control the invading pathogen. However, its estimates from compartmental models are strongly conditioned by assumptions in the model structure, such as the distributions of the latent and infectious periods (epidemiological delays). To further complicate matters, models with dissimilar delay structures produce equivalent incidence dynamics. Following a simulation study, we reveal that the nature of such equivalency stems from a linear relationship between[R] 0 and the mean generation time, along with adjustments to other parameters in the model. Leveraging this knowledge, we propose and successfully test an alternative parameterisation of the SEIR model that produces accurate[R] 0 estimates regardless of the distribution of the epidemiological delays, at the expense of biases in other quantities deemed of lesser importance. We further explore this approachs robustness by testing various transmissibility levels, generation times, and data fidelity (overdispersion). Finally, we apply the proposed approach to data from the 1918 influenza pandemic. We anticipate that this work will mitigate biases in estimating[R] 0.

ecology↗

bioRxiv2023

Effects of pathogen sexual reproduction on the evolutionary and epidemiological control provided by deployment strategies for two major resistance genes in agricultural landscapes.

O_LIResistant cultivars are of value for protecting crops from disease, but can be rapidly overcome by pathogens. Several strategies have been proposed to delay pathogen adaptation (evolutionary control), while maintaining effective protection (epidemiological control). Resistance genes can be i) combined in the same cultivar (pyramiding), ii) deployed in different cultivars sown in the same field (mixtures) or in different fields (mosaics), or iii) alternated over time (rotations). The outcomes of these strategies have been investigated principally in pathogens displaying pure clonal reproduction, but sexual reproduction may promote the emergence of superpathogens adapted to all the resistance genes deployed. C_LIO_LIWe improved the spatially explicit stochastic model landsepi to include pathogen sexual reproduction, and then investigate the effect of sexual reproduction on evolutionary and epidemiological outcomes across deployment strategies for two major resistance genes. C_LIO_LISexual reproduction only favours the establishment of a superpathogen when single mutant pathogens are present together at a sufficiently high frequency, as in mosaic and mixture strategies. C_LIO_LIWe concluded that, although sexual reproduction may promote the establishment of a superpathogen, it did not affect the optimal strategy recommendations for a wide range of mutation probabilities, associated fitness costs, and landscape organisations (notably the cropping ratio of resistant fields). C_LI

evolutionary biology↗

bioRxiv2023

The immune regulation and epidemiological consequences of immune priming in Drosophila

Invertebrates lack the immune machinery underlying vertebrate-like acquired immunity. However, in many insects past infection by the same pathogen can prime the immune response, resulting in improved survival upon reinfection. Here, we investigated the generality, specificity and mechanistic basis of innate immune priming in the fruit fly Drosophila melanogaster when infected with the gram-negative bacterial pathogen Providencia rettgeri. We find that priming in response to P. rettgeri infection is a long-lasting and pathogen-specific response. We further explore the epidemiological consequences of immune priming and find it has the potential to curtail pathogen transmission by reducing pathogen shedding and spread. The enhanced survival of individuals previously exposed to a non-lethal bacterial inoculum coincided with a transient decrease in bacterial loads, and we provide strong evidence that the effect of priming requires the IMD-responsive antimicrobial-peptide Diptericin-B in the fat body. Further, we show that while Diptericin B is the main effector of bacterial clearance, it is not sufficient for immune priming, which requires regulation of IMD by peptidoglycan recognition proteins. This work underscores the plasticity and complexity of invertebrate responses to infection, providing novel experimental evidence for the effects of innate immune priming on population-level epidemiological outcomes.

immunology↗

bioRxiv2023

Understanding the Divergent Evolution and Epidemiology of H3N8 Influenza Viruses in Dogs and Horses

Cross-species virus transmission events can lead to dire public health emergencies in the form of epidemics and pandemics. One example in animals is the emergence of the H3N8 equine influenza virus (EIV), first isolated in 1963 in Miami, Florida, USA, after emerging among horses in South America. In the early 21st century the American lineage of EIV diverged into two Florida clades that persist today, while an EIV transferred to dogs around 1999 and gave rise to the H3N8 canine influenza virus (CIV), first reported in 2004. Here, we compare CIV in dogs and EIV in horses to reveal their host-specific evolution, to determine the sources and connections between significant outbreaks, and to gain insight into the factors controlling their different evolutionary fates. H3N8 CIV only circulated in North America, was geographically restricted after the first few years, and went extinct in 2016. Of the two EIV Florida clades, clade 1 circulates widely and shows frequent transfers between the USA and South America, Europe and elsewhere, while clade 2 was globally distributed early after it emerged, but since about 2018 has only been detected in Central Asia. Any potential zoonotic threat of these viruses to humans can only be determined with an understanding of its natural history and evolution. Our comparative analysis of these three viral lineages reveals distinct patterns and rates of sequence variation yet with similar overall evolution between clades, suggesting epidemiological intervention strategies for possible eradication of H3N8 EIV. (242 words) IMPORTANCEThe emergence of viruses in new hosts is a threat to human and animal health. The H3N8 equine influenza virus (EIV) emerged in 1963 by transfer of an avian influenza virus, and the H3N8 canine influenza virus (CIV) subsequently emerged in 1999 when EIV transferred to dogs. H3N8 CIV persistently circulated in only a few locations in the USA, and has not been detected since 2016. In the same period H3N8 EIV has circulated as two separate clades, one in North America and other regions of the world, while the other currently appears to be found only in Central Asia. By comparing the hosts, epidemiology, and evolution of these influenza viruses we explain how these lineages had different evolutionary fates, and show why elucidating these evolutionary processes is key to understanding zoonotic disease and viral emergence. (137 words)

evolutionary biology↗