Pathogen Population Dynamics Research Articles

P-1302. Alterations in the population structure and antimicrobial resistance of Salmonella enterica before and during the COVID-19 pandemic (2018 and 2020) in New York State

Abstract Background The COVID-19 pandemic impacted many core activities to combat antimicrobial resistance (AMR). Concurrently, there has been increased AMR, particularly in hospital-acquired infections. However, there is little data on AMR surveillance of community-acquired infections, such as foodborne infections, during this period. An estimated 212,500 resistant Salmonella enterica infections occur yearly. Here, we aim to elucidate the impact of the COVID-19 pandemic on the population dynamics of S. enterica lineages and the genetic determinants of AMR.Figure 1:Phylogenetic relationships, pan-genomic, lineage and antimicrobial resistance characteristics of [i]S. enterica[i] genomes before (2018, n=1,212) and during the COVID-19 pandemic (2020, n=975)A. A midpoint-rooted maximum likelihood phylogenetic tree based on 608,598 core-gene single nucleotide polymorphisms. Branch lengths are not displayed. Outer rings show Serotype, Sequence Type, and Region. Branches are colored by sampling year. A map displays the region associated with the source county of the isolate within New York State. B. Displays the Sequence Types as the proportion of the total population. Chi-squared p-values are displayed. C. Serotype as proportions of the yearly population. D. Resistance mechanism as a proportion of the yearly population Benjamini-Hochberg corrected p-values are displayed. Methods We leveraged 2,187 publicly available sequences derived from S. enterica isolates from human clinical samples across 56 counties in New York, USA, before the pandemic (2018, n=1,212 genomes) and during the pandemic (2020, n=975 genomes). Results A midpoint-rooted maximum likelihood phylogeny generated from 608,598 single-nucleotide polymorphisms from 3,482 core genes revealed the intermingling of isolates regardless of year and county of isolation. We did not find significant differences in the diversity (measured using the Simpson diversity index) of sequence types (ST) and serotypes between the two time periods. However, some STs and serotypes exhibited significant changes in the proportion of the annual population. We observed an increase in ST33 and a reduction in ST19, ST34, and low-frequency STs. There was a marked increase in serotypes Hadar, Newport, and Thompson and a decrease in serotypes Saintpaul and the low-frequency serotypes. We also measured the number of genomes carrying specific AMR genes as a proportion of the annual population per year. We found a significant change in the number of genomes carrying in aph(3”)-Ib and aph(6”)-Id (aminoglycoside resistance), tetC (tetracycline), and the fluoroquinolone resistance point mutation (gyrA_D87Y). Conclusion Our findings revealed the bacterial features, such as locally circulating lineages, mutations, and mobile antimicrobial resistance genes, that were altered before and during the COVID-19 pandemic. Together, our data show that major public health emergencies such as the COVID-19 pandemic can inadvertently alter the dynamics of other pathogen populations, including foodborne bacteria, which may have consequences for public health and treatment efforts. Disclosures All Authors: No reported disclosures

Temporal Dynamics of Two Genetically Diverse Downy Mildew Mitochondrial Clades on Cucumber Cultivars in South Carolina and Florida

Downy mildew (DM, Pseudoperonospora cubensis) is an important disease that can significantly reduce yield of field-grown cucumbers in the US. Cucumber cultivars with resistance to DM were widely grown for >30 years. However, resistance broke down in 2004 resulting in severe DM epidemics. Large plot trials were conducted to characterize pathogen virulence and population dynamics on DM tolerant cultivars Peacemaker and Expedition and susceptible SMR-58 in Charleston, SC and Fort Pierce, FL in 2016 and 2017. Rapid DM development on SMR-58 was observed at both locations in 2016 and 2017. Disease progress on Expedition and Peacemaker were slow as compared to SMR-58 in Fort Pierce, FL in 2016. Very low to no DM was observed on Peacemaker or Expedition in Charleston in 2016. In 2017, all cultivars were affected in Charleston, but only SMR-58 had severe DM (95-100%) in Fort Pierce. Pathogen population analysis using DM specific mitochondrial clade (MC1 and MC2) markers showed differences between the P. cubensis populations across location and years on the cucumber cultivars. Both MC1 and MC2 were detected in cucumber plots in SC and FL. The most prevalent DM mitochondrial clade in SC during June 2016 was MC1 primarily on SMR-58 (95-100%). However, in July 2016 that population shifted towards MC2 (45-77%). This suggested that the DM populations can change relatively quickly when suitable environment favors. Mixed populations of MC1 and MC2 continued to be observed in following year in Charleston, SC in 2017. In Fort Pierce, FL a complete shift was observed from MC2 in 2016 to MC1 in 2017. Since both MCs are present in the southeastern United States either at the same time or possibly different times during the production year, cultivars with combined resistance to P. cubensis populations will be needed to reduce reliance on fungicides to manage DM.

Turning the needle into the haystack: Culture-independent amplification of complex microbial genomes directly from their native environment.

High-throughput sequencing (HTS) has revolutionized microbiology, but many microbes exist at low abundance in their natural environment and/or are difficult, if not impossible, to culture in the laboratory. This makes it challenging to use HTS to study the genomes of many important microbes and pathogens. In this review, we discuss the development and application of selective whole genome amplification (SWGA) to allow whole or partial genomes to be sequenced for low abundance microbes directly from complex biological samples. We highlight ways in which genomic data generated by SWGA have been used to elucidate the population dynamics of important human pathogens and monitor development of antimicrobial resistance and the emergence of potential outbreaks. We also describe the limitations of this method and propose some potential innovations that could be used to improve the quality of SWGA and lower the barriers to using this method across a wider range of infectious pathogens.

Understanding the transmission of bacterial agents of sapronotic diseases using an ecosystem-based approach: A first spatially realistic metacommunity model.

Pathogens such as bacteria, fungi and viruses are important components of soil and aquatic communities, where they can benefit from decaying and living organic matter, and may opportunistically infect human and animal hosts. One-third of human infectious diseases is constituted by sapronotic disease agents that are natural inhabitants of soil or aquatic ecosystems. They are capable of existing and reproducing in the environment outside of the host for extended periods of time. However, as ecological research on sapronosis is infrequent and epidemiological models are even rarer, very little information is currently available. Their importance is overlooked in medical and veterinary research, as well as the relationships between free environmental forms and those that are pathogenic. Here, using dynamical models in realistic aquatic metacommunity systems, we analyze sapronosis transmission, using the human pathogen Mycobacterium ulcerans that is responsible for Buruli ulcer. We show that the persistence of bacilli in aquatic ecosystems is driven by a seasonal upstream supply, and that the attachment and development of cells to aquatic living forms is essential for such pathogen persistence and population dynamics. Our work constitutes the first set of metacommunity models of sapronotic disease transmission, and is highly flexible for adaptation to other types of sapronosis. The importance of sapronotic agents on animal and human disease burden needs better understanding and new models of sapronosis disease ecology to guide the management and prevention of this important group of pathogens.

Neutral genetic structuring of pathogen populations during rapid adaptation.

Pathogen species are experiencing strong joint demographic and selective events, especially when they adapt to a new host, for example through overcoming plant resistance. Stochasticity in the founding event and the associated demographic variations hinder our understanding of the expected evolutionary trajectories and the genetic structure emerging at both neutral and selected loci. What would be the typical genetic signatures of such a rapid adaptation event is not elucidated. Here, we build a demogenetic model to monitor pathogen population dynamics and genetic evolution on two host compartments (susceptible and resistant). We design our model to fit two plant pathogen life cycles, 'with' and 'without' host alternation. Our aim is to draw a typology of eco-evolutionary dynamics. Using time-series clustering, we identify three main scenarios: 1) small variations in the pathogen population size and small changes in genetic structure, 2) a strong founder event on the resistant host that in turn leads to the emergence of genetic structure on the susceptible host, and 3) evolutionary rescue that results in a strong founder event on the resistant host, preceded by a bot- tleneck on the susceptible host. We pinpoint differences between life cycles with notably more evolutionary rescue 'with' host alternation. Beyond the selective event itself, the demographic trajectory imposes specific changes in the genetic structure of the pathogen population. Most of these genetic changes are transient, with a signature of resistance overcoming that vanishes within a few years only. Considering time-series is therefore of utmost importance to accurately decipher pathogen evolution.

Population dynamics of the Lyme disease bacterium, Borrelia burgdorferi, during rapid range expansion in New York State.

Recent changes in climate and human land-use have resulted in alterations of the geographic range of many species, including human pathogens. Geographic range expansion and population growth of human pathogens increase human disease risk. Relatively little empirical work has investigated the impact of range changes on within-population variability, a contributor to both colonization success and adaptive potential, during the precise time in which populations are colonized. This is likely due to the difficulties of collecting appropriate natural samples during the dynamic phase of migration and colonization. We systematically collected blacklegged ticks (Ixodes scapularis) across New York State (NY), USA, between 2006 and 2019, a time period coinciding with a rapid range expansion of ticks and their associated pathogens including Borrelia burgdorferi, the etiological agent of Lyme disease. These samples provide a unique opportunity to investigate the population dynamics of human pathogens as they expand into novel territory. We observed that founder effects were short-lived, as gene flow from long-established populations brought almost all B. burgdorferi lineages to newly colonized populations within just a few years of colonization. By 7 years post-colonization, B. burgdorferi lineage frequency distributions were indistinguishable from long-established sites, indicating that local B. burgdorferi populations experience similar selective pressures despite geographic separation. The B. burgdorferi lineage dynamics elucidate the processes underlying the range expansion and demonstrate that migration into, and selection within, newly colonized sites operate on different time scales.

Acclimation to warmer temperatures can protect host populations from both further heat stress and the potential invasion of pathogens.

Thermal acclimation can provide an essential buffer against heat stress for host populations, while acting simultaneously on various life-history traits that determine population growth. In turn, the ability of a pathogen to invade a host population is intimately linked to these changes via the supply of new susceptible hosts, as well as the impact of warming on its immediate infection dynamics. Acclimation therefore has consequences for hosts and pathogens that extend beyond simply coping with heat stress-governing both population growth trajectories and, as a result, an inherent propensity for a disease outbreak to occur. The impact of thermal acclimation on heat tolerances, however, is rarely considered simultaneously with metrics of both host and pathogen population growth, and ultimately fitness. Using the host Daphnia magna and its bacterial pathogen, we investigated how thermal acclimation impacts host and pathogen performance at both the individual and population scales. We first tested the effect of maternal and direct thermal acclimation on the life-history traits of infected and uninfected individuals, such as heat tolerance, fecundity, and lifespan, as well as pathogen infection success and spore production. We then predicted the effects of each acclimation treatment on rates of host and pathogen population increase by deriving a host's intrinsic growth rate (rm) and a pathogen's basic reproductive number (R0). We found that direct acclimation to warming enhanced a host's heat tolerance and rate of population growth, despite a decline in life-history traits such as lifetime fecundity and lifespan. In contrast, pathogen performance was consistently worse under warming, with within-host pathogen success, and ultimately the potential for disease spread, severely hampered at higher temperatures. Our results suggest that hosts could benefit more from warming than their pathogens, but only by linking multiple individual traits to population processes can the full impact of higher temperatures on host and pathogen population dynamics be realised.

Aminoethoxyvinylglycine and low oxygen controlled atmosphere storage shift functional microbiomes of ‘Gala’ apples

The complexity and interconnected dynamics of postharvest microbial communities require whole-microbiome characterization to fully understand relationships among pathogens, biocontrol, and fruit quality. This study investigated the effects of the preharvest plant growth regulator aminoethoxyvinylglycine (AVG, 0.25 g L−1), which inhibits ethylene production, and low O2 (0.5 % and 2 %) controlled atmosphere (CA) storage compared with air storage, on the surface microbiome of ‘Gala’ apples stored at 0.5 °C. AVG and low O2 concentrations affected bacterial but not fungal communities. Bacterial but not fungal diversity decreased after 9 months of CA storage. Microbial genera with potential biocontrol functions such as Pseudomonas and Aureobasidium were found across all time points and treatments. The microbiomes detected in CA stored fruit were the most different from those in air stored fruit late in storage. At this time, metagenome prediction methods found that low O2 fruit may harbor bacteria with fewer gene pathways using O2 as a reactant compared to fruit in air storage. The results indicate that storage conditions influence the composition, diversity, and function of microbiomes inhabiting fruit surfaces, which provide a greater basis for understanding biocontrol and pathogen population dynamics in a more holistic manner.

Fusarium oxysporum f. sp. lycopersici biomass variations under disease control regimes using Trichoderma and compost

A comprehensive understanding of population dynamics of pathogens and bioagents in plant rhizospheres is important for improving organic farming. Fusarium oxysporum f. sp. lycopersici (FOL30) causes Fusarium wilt of tomato. In this study, we compared biomass variations of FOL30 under different disease control regimes, using Trichoderma asperellum TA23 strain, compost, or their combination. Biomass variations of FOL30 and TA23 were observed for 13 weeks using quantitative real-time PCR. Separate applications of TA23, compost, and their combination all reduced FOL biomass when compared to experimental controls. Regression analyses of the qPCR data showed that FOL populations fitted curvilinear polynomial order 3 regression models (R2 = 0.87 to 0.95). Areas under the population dynamic curves (AUPDCs; log10 ng DNA week-1 g-1 soil) were: 43.8 from FOL30 alone, 36.6 from FOL30 plus TA23, 25.4 from FOL30 plus compost, and 25.5 from FOL30 plus TA23 plus compost. These results indicate that the individual applications of TA23 or compost, or their combination, decreased the FOL biomass. The negative correlation between TA23 and FOL30 populations showed that the compost and biocontrol agent reduced FOL pathogen populations. This study demonstrates that compost fortified with T. asperellum TA23 decreased FOL populations and reduced disease, and that their use is a promising strategy for managing Fusarium wilt of tomato in organic farming.

Cambio climático y enfermedades transmitidas por vectores. Convertir el conocimiento en acción

Andalusia is particularly sensitive to climate change, not only because of extreme weather events, but also because of the impact on the population dynamics of vectors, pathogens, reservoirs and hosts, which has led to a change in the epidemiological patterns of vector-borne diseases. In order to achieve an integrated vector management for disease control, public action is necessary. This study describes the design of the initial phase of a strategy for knowledge translation about climate change and vector-borne diseases to the public, using transdisciplinary co-creation and the World Café participatory method with three discussion rounds to address strategies for three age groups (adults, adolescents and schoolchildren). The aim is to drive knowledge into action and for this purpose the underlying messages for action (strategic and instrumental) have been identified, as well as the formats of the knowledge products and the potential implementers of the strategies.

Game dynamics as a driver for pathogen spillover pulses

Understanding the underlying mechanisms for pathogen spillover is a main quest in epidemiology. Given the complexity of multi-host systems, several factors may play a relative role in spillover dynamics. A relatively less studied factor is the internal dynamics of pathogens that result from inter-strain competition. The competitive interactions among strains can cause deterministic changes in the population dynamics of pathogens. Such changes may affect the potential host-range of pathogens, influencing the probability of pathogen spillover. Here, our main goal is to show how an evolutionary game played by coexisting strains may induce pulses of pathogen spillover. To this end, we build a multi-host-multi-strain mean field model in which strains residing in a reservoir host have different capacities to explore an incidental host. We modelled inter-strain competition as a superinfection network and apply a game-theoretical analysis to it. The results indicate that game outcome depends on how reservoir hosts deal with the superinfection process (if superinfection is lethal, results in competitive exclusion or in coinfection). Our analysis suggests that game outcome can produce cycles in the strain composition that are cryptic in relation to the epidemiological dynamics of reservoirs (cycles in strain frequency composition cause small or no effect in the reservoir population). This suggests that relying solely on reservoir distribution and prevalence may subestimate the chance of pathogen spillover. Moreover, pulses of spillover can rely on the standing variation of pathogens, with no need for the emergence of novel mutations that increases pathogen host-range.

Ecology and distribution of Leptospira spp., reservoir hosts and environmental interaction in Sri Lanka, with identification of a new strain.

Leptospirosis is a neglected zoonotic disease and one of the leading causes of zoonotic morbidity and mortality, particularly in resource-poor settings. Sri Lanka has one of the highest disease burdens worldwide, with occasional endemic leptospirosis outbreaks (2008, 2011). Rodents are considered the main wildlife reservoir, but due to a scarcity of studies it is unclear which particular species contributes to bacterial transmission and reservoir maintenance in this multi-host multi-parasite system. Several rodent species act as agricultural pests both in rice fields and in food storage facilities. To unravel the interactions among the small mammal communities, pathogenic Leptospira spp. and human transmission pathways, we collected animals from smallholder food storage facilities, where contact between humans and small mammals is most likely, and screened kidney tissue samples for Leptospira spp. using PCR. Samples were collected in three climatic zones along a rainfall gradient. Pathogenic Leptospira spp. were detected in small mammal communities in 37 (74%) out of 50 sampled farms and 61 (12%) out of 500 collected individuals were infected. The small mammal community was comprised of Rattus rattus (87.6%), Suncus shrews (8.8%), Bandicota spp. (2.8%) and Mus booduga (0.8%). Three pathogenic Leptospira spp. were identified, L. borgpetersenii (n = 34), L. interrogans (n = 15), and L. kirschneri (n = 1). Suncus shrews were commonly infected (32%), followed by B. indica (23%) and R. rattus (10%). L. borgpetersenii strains similar to strains previously extracted from human clinal samples in Sri Lanka were detected in R. rattus and Suncus shrews. L. interrogans was observed in R. rattus only. A single L. kirschneri infection was found in M. booduga. The presence of human pathogenic Leptospira species in an agricultural pest rodent (R. rattus) and in commensal shrews (Suncus) calls for management of these species in commensal settings. Further investigation of the interplay between pathogen and reservoir population dynamics, overlap in geographic range and the extent of spill-over to humans in and around rural settlements is required to identify optimal management approaches.

Current Status and Future Perspectives of Genomics Research in the Rust Fungi.

Rust fungi in Pucciniales have caused destructive plant epidemics, have become more aggressive with new virulence, rapidly adapt to new environments, and continually threaten global agriculture. With the rapid advancement of genome sequencing technologies and data analysis tools, genomics research on many of the devastating rust fungi has generated unprecedented insights into various aspects of rust biology. In this review, we first present a summary of the main findings in the genomics of rust fungi related to variations in genome size and gene composition between and within species. Then we show how the genomics of rust fungi has promoted our understanding of the pathogen virulence and population dynamics. Even with great progress, many questions still need to be answered. Therefore, we introduce important perspectives with emphasis on the genome evolution and host adaptation of rust fungi. We believe that the comparative genomics and population genomics of rust fungi will provide a further understanding of the rapid evolution of virulence and will contribute to monitoring the population dynamics for disease management.

Improving sustainable crop protection using population genetics concepts.

Growing genetically resistant plants allows pathogen populations to be controlled and reduces the use of pesticides. However, pathogens can quickly overcome such resistance. In this context, how can we achieve sustainable crop protection? This crucial question has remained largely unanswered despite decades of intense debate and research effort. In this study, we used a bibliographic analysis to show that the research field of resistance durability has evolved into three subfields: (1) "plant breeding" (generating new genetic material), (2) "molecular interactions" (exploring the molecular dialogue governing plant-pathogen interactions) and (3) "epidemiology and evolution" (explaining and forecasting of pathogen population dynamics resulting from selection pressure[s] exerted by resistant plants). We argue that this triple split of the field impedes integrated research progress and ultimately compromises the sustainable management of genetic resistance. After identifying a gap among the three subfields, we argue that the theoretical framework of population genetics could bridge this gap. Indeed, population genetics formally explains the evolution of all heritable traits, and allows genetic changes to be tracked along with variation in population dynamics. This provides an integrated view of pathogen adaptation, in particular via evolutionary-epidemiological feedbacks. In this Opinion Note, we detail examples illustrating how such a framework can better inform best practices for developing and managing genetically resistant cultivars.

Climate change impact on the population dynamics of exotic pathogens: The case of the worldwide pathogen Phytophthora cinnamomi

Worldwide, Mediterranean-climate type forests are seriously threatened by climate change and Phytophthora cinnamomi, an extremely aggressive soilborne pathogen listed among the 100 worst invasive alien species. This study examines for first time the effects of annual and seasonal changes in temperature and rainfall under different climatic scenarios on P. cinnamomi dynamics in a Mediterranean forest naturally infested. We followed seasonally and during four years (2016–2020) P. cinnamomi abundance in the soil taking advantage of a climate change infrastructure that simulates a 30% rainfall reduction using rainout shelters and an increase in soil temperature using open top chambers. Seasonal abundance of P. cinnamomi was strongly linked to spring precipitation: the large inoculum density during this season suffered a strong decrease during the dry summer that was maintained until the next spring, despite of fall rains. Thus, inoculum density in spring may be considered the best indicator of the potential of P. cinnamomi infection in natural ecosystems. The two climatic treatments had significant effects on P. cinnamomi abundance, but only in some combinations of seasons and years. Rainfall exclusion had a negative effect on the spring abundance of P. cinnamomi mostly in wet years, causing a reduction as large as 30% in comparison with the control treatment. Meanwhile, warming effect varied from slightly negative in winter to positive in spring and early summer, causing increases as large as 31% in comparison with the control treatment. Overall, we provide novel experimental evidence suggesting that a drier climate might limit the abundance and activity of P. cinnamomi in water-limited forests, but that this negative effect might be at least partly counteracted by the positive effects of warming. These results also imply that P. cinnamomi represents an increasing threat under climate change for the conservation of forest ecosystems where water is not a limiting factor.

Transmissible cancer influences immune gene expression in an endangered marsupial, the Tasmanian devil (Sarcophilus harrisii).

Understanding the effects of wildlife diseases on populations requires insight into local environmental conditions, host defence mechanisms, host life‐history trade‐offs, pathogen population dynamics, and their interactions. The survival of Tasmanian devils (Sarcophilus harrisii) is challenged by a novel, fitness limiting pathogen, Tasmanian devil facial tumour disease (DFTD), a clonally transmissible, contagious cancer. In order to understand the devils’ capacity to respond to DFTD, it is crucial to gain information on factors influencing the devils’ immune system. By using RT‐qPCR, we investigated how DFTD infection in association with intrinsic (sex and age) and environmental (season) factors influences the expression of 10 immune genes in Tasmanian devil blood. Our study showed that the expression of immune genes (both innate and adaptive) differed across seasons, a pattern that was altered when infected with DFTD. The expression of immunogbulins IgE and IgM:IgG showed downregulation in colder months in DFTD infected animals. We also observed strong positive association between the expression of an innate immune gene, CD16, and DFTD infection. Our results demonstrate that sampling across seasons, age groups and environmental conditions are beneficial when deciphering the complex ecoevolutionary interactions of not only conventional host‐parasite systems, but also of host and diseases with high mortality rates, such as transmissible cancers.

Phaseolus vulgaris-Colletotrichum lindemuthianum Pathosystem in the Post-Genomic Era: An Update.

Phaseolus vulgaris-Colletotrichum lindemuthianum is one among the oldest host and pathogen interface. Researchers have taken painstaking efforts across the world for understanding the dialogue during early and late phases of interaction. Collectively, these efforts resulted in the deluge of information that helped the researchers to underpin the interface. The latest molecular biology techniques furnished novel detection methods for the anthracnose pathogen, refined the understanding of pathogen population dynamics, and provided the insights on co-evolutionary common bean resistance and C. lindemuthianum virulence dynamics. One of the important breakthroughs came when the Phaseolus vulgaris and its corresponding anthracnose pathogen (C. lindemuthianum) genomes were decoded in 2014 and 2017, respectively. Availability of both the genomes yielded a significant genomic information that helped bean communities to fine map the economically important traits and to identify the pathogenicity determinants and effector molecules. The interface is in a continuous development as knowledge of the anthracnose resistance genes, their precise physical locations, and the identification of effector proteins; the fungus arsenals are being routinely updated. Hence, we revisited the interface and tried to provide an overview of host pathogen dialogue in the genomic era. Additionally, we compiled the sporadic information on this pathosystem from India and provided its futuristic road map to shape its research in the world and northern India, the major dry bean area in the country.

Disease influences host population growth rates in a natural wild plant–pathogen association over a 30‐year period

Abstract The epidemiological and demographic dynamics of plant–pathogen interactions in natural environments are strongly affected by spatial and temporal influences. Here we assess the interaction between Filipendula ulmaria and its rust pathogen Triphragmium ulmariae by analysing a 30‐year long dataset that has followed pathogen and plant population dynamics in a metapopulation of ~230 host patches growing on islands of the Skeppsvik archipelago in northern Sweden. Over this period, the host metapopulation initially expanded in both number and size of individual patches before plateauing. In contrast, the pathogen metapopulation showed greater change. Disease incidence showed a convex pattern rising for the first decade before showing a marked decline in the last decade. At the same time, the prevalence of disease in infected populations showed a constant 30‐year long decline. At the individual host population level, each population was annually classified into one of four inter‐year states: healthy, recolonization, extinction and diseased. Host populations that were healthy from 1 year to the next were significantly smaller than all other host population categories, while host populations in which disease was constantly present were significantly larger. Host populations in which the pathogen underwent either an extinction or a recolonization event were of similar size and represented a measure of the host threshold size for long‐term pathogen survival. Host population growth rates declined as disease levels increased. The growth rate of host populations in which disease was continuously present was 75% lower than in populations that were free disease. The sensitivity of the association to climate change as demonstrated through a decline in disease incidence and prevalence and an increase in drought damage to plant populations as temperatures rise has only become apparent through analysis of an extensive long‐term dataset. Synthesis. To date wild plant–pathogen studies have focused on the epidemiology of the pathogen and its effect on individual plant fitness. Here we have established a link to the impact of the pathogen on the long‐term dynamics of host populations. This has the potential to trigger a cascade of changes in the species composition and diversity of communities.

Relationship of Colletotrichum lindemuthianum races and resistance loci in the Phaseolus vulgaris L. genome

AbstractAnthracnose caused by Colletotrichum lindemuthianum is one of the most critical diseases in the common bean (Phaseolus vulgaris L.). The characterization and localization of pathogenic fungal races are essential for understanding pathogen population dynamics and developing resistant cultivars. Here, we discussed the relationship between the diversity of C. lindemuthianum and common bean resistance genes against anthracnose disease. Indeed, several studies using a system of 12 differential bean cultivars have been carried out since 1991 to monitor anthracnose, reporting the constant appearance of new races. Colletotrichum lindemuthianum shows high virulence diversity, with 298 races distributed across 29 countries. In Brazil, we identified 89 races, with races 73, 65, and 81 as the most frequent. Moreover, we highlighted the common bean gene clusters, their unique location on chromosomes, and their relationship with races and resistance genes. The genetic mapping studies, molecular markers linked to anthracnose resistance alleles, and the specific races were integrated on the seven‐chromosome map using the reference genome of common bean. Recently, the ease of use of genome sequences and the development of molecular technologies have allowed molecular markers for marker‐assisted selection applied to anthracnose‐resistant cultivars. As a result, it is feasible that Mesoamerican genes Co‐5, Co‐42, Co‐6, Co‐16, and Co‐17, and the Andean genes Co‐12, Co‐14, Co‐Bf, Co‐15, Co‐AC, and CoPv01CDRK are well known to confer resistance to most races reported in Brazil and around the world. Thus, pyramiding these genes through molecular markers can help reduce the time and cost of introducing resistance genes in commercial common bean cultivars.

Occurrence of anthracnose pathogen races and resistance genes in common bean across 30 years in Brazil

Anthracnose caused by Colletotrichum lindemuthianum is one of the most critical diseases in the common bean (Phaseolus vulgaris L.). The characterization and localization of pathogenic fungal races are essential for understanding pathogen population dynamics and recommending strategies to develop resistant cultivars. As resistant genotypes are the most economical and ecologically safe means of controlling plant diseases, there have been efforts to characterize resistance genes in common bean. Several studies using a system of 12 differential bean cultivars have been carried out to monitor anthracnose since 1991, reporting the constant appearance of new fungal races. C. lindemuthianum shows high virulence diversity. The objective of the present study was to review the relationship between C. lindemuthianum races and the common bean pathogenic processes involved in the risk of developing anthracnose disease. As a result, 89 races occurred in Brazil, wherein 73, 65, and 81 of C. lindemuthianum are the most frequent. Furthermore, we built a map with the anthracnose resistance loci, molecular markers, and their respective physical position. The accessibility to the genomes and sequencing technologies permits molecular markers for marker-assisted selection applied to anthracnose-resistant cultivars. This study could be used as a reference for future resistance mapping studies and as a guide for selecting resistance loci in breeding programs aiming to develop common bean cultivars with durable anthracnose resistance.