Caroline L. Monteil

Nonagricultural reservoirs contribute to emergence and evolution of Pseudomonas syringae crop pathogens

While the existence of environmental reservoirs of human pathogens is well established, less is known about the role of nonagricultural environments in emergence, evolution, and spread of crop pathogens. Here, we analyzed phylogeny, virulence genes, host range, and aggressiveness of Pseudomonas syringae strains closely related to the tomato pathogen P. syringae pv. tomato (Pto), including strains isolated from snowpack and streams. The population of Pto relatives in nonagricultural environments was estimated to be large and its diversity to be higher than that of the population of Pto and its relatives on crops. Ancestors of environmental strains, Pto, and other genetically monomorphic crop pathogens were inferred to have frequently recombined, suggesting an epidemic population structure for P. syringae. Some environmental strains have repertoires of type III-secreted effectors very similar to Pto, are almost as aggressive on tomato as Pto, but have a wider host range than typical Pto strains. We conclude that crop pathogens may have evolved through a small number of evolutionary events from a population of less aggressive ancestors with a wider host range present in nonagricultural environments.

Features of air masses associated with the deposition of Pseudomonas syringae and Botrytis cinerea by rain and snowfall

Clarifying the role of precipitation in microbial dissemination is essential for elucidating the processes involved in disease emergence and spread. The ecology of Pseudomonas syringae and its presence throughout the water cycle makes it an excellent model to address this issue. In this study, 90 samples of freshly fallen rain and snow collected from 2005–2011 in France were analyzed for microbiological composition. The conditions favorable for dissemination of P. syringae by this precipitation were investigated by (i) estimating the physical properties and backward trajectories of the air masses associated with each precipitation event and by (ii) characterizing precipitation chemistry, and genetic and phenotypic structures of populations. A parallel study with the fungus Botrytis cinerea was also performed for comparison. Results showed that (i) the relationship of P. syringae to precipitation as a dissemination vector is not the same for snowfall and rainfall, whereas it is the same for B. cinerea and (ii) the occurrence of P. syringae in precipitation can be linked to electrical conductivity and pH of water, the trajectory of the air mass associated with the precipitation and certain physical conditions of the air mass (i.e. temperature, solar radiation exposure, distance traveled), whereas these predictions are different for B. cinerea. These results are pertinent to understanding microbial survival, emission sources and atmospheric processes and how they influence microbial dissemination.

Harnessing Population Genomics to Understand How Bacterial Pathogens Emerge, Adapt to Crop Hosts, and Disseminate

Crop diseases emerge without warning. In many cases, diseases cross borders, or even oceans, before plant pathologists have time to identify and characterize the causative agents. Genome sequencing, in combination with intensive sampling of pathogen populations and application of population genetic tools, is now providing the means to unravel how bacterial crop pathogens emerge from environmental reservoirs, how they evolve and adapt to crops, and what international and intercontinental routes they follow during dissemination. Here, we introduce the field of population genomics and review the population genomics research of bacterial plant pathogens over the past 10 years. We highlight the potential of population genomics for investigating plant pathogens, using examples of population genomics studies of human pathogens. We also describe the complementary nature of the fields of population genomics and molecular plant-microbe interactions and propose how to translate new insights into improved disease prevention and control.

Pseudomonas syringae naturally lacking the canonical type III secretion system are ubiquitous in nonagricultural habitats, are phylogenetically diverse and can be pathogenic.

The type III secretion system (T3SS) is an important virulence factor of pathogenic bacteria, but the natural occurrence of variants of bacterial plant pathogens with deficiencies in their T3SS raises questions about the significance of the T3SS for fitness. Previous work on T3SS-deficient plant pathogenic bacteria has focused on strains from plants or plant debris. Here we have characterized T3SS-deficient strains of Pseudomonas syringae from plant and nonplant substrates in pristine nonagricultural contexts, many of which represent recently described clades not yet found associated with crop plants. Strains incapable of inducing a hypersensitive reaction (HR−) in tobacco were detected in 65% of 126 samples from headwaters of rivers (mountain creeks and lakes), snowpack, epilithic biofilms, wild plants and leaf litter and constituted 2 to 100% of the P. syringae population associated with each sample. All HR− strains lacked at least one gene in the canonical hrp/hrc locus or the associated conserved effector locus, but most lacked all six of the genes tested (hrcC, hrpL, hrpK1, avrE1 and hrpW1) and represented several disparate phylogenetic clades. Although most HR− strains were incapable of causing symptoms on cantaloupe seedlings as expected, strains in the recently described TA-002 clade caused severe symptoms in spite of the absence of any of the six conserved genes of the canonical T3SS according to PCR and Southern blot assays. The phylogenetic context of the T3SS variants we observed provides insight into the evolutionary history of P. syringae as a pathogen and as an environmental saprophyte.

A System to Automatically Classify and Name Any Individual Genome-Sequenced Organism Independently of Current Biological Classification and Nomenclature

A broadly accepted and stable biological classification system is a prerequisite for biological sciences. It provides the means to describe and communicate about life without ambiguity. Current biological classification and nomenclature use the species as the basic unit and require lengthy and laborious species descriptions before newly discovered organisms can be assigned to a species and be named. The current system is thus inadequate to classify and name the immense genetic diversity within species that is now being revealed by genome sequencing on a daily basis. To address this lack of a general intra-species classification and naming system adequate for today’s speed of discovery of new diversity, we propose a classification and naming system that is exclusively based on genome similarity and that is suitable for automatic assignment of codes to any genome-sequenced organism without requiring any phenotypic or phylogenetic analysis. We provide examples demonstrating that genome similarity-based codes largely align with current taxonomic groups at many different levels in bacteria, animals, humans, plants, and viruses. Importantly, the proposed approach is only slightly affected by the order of code assignment and can thus provide codes that reflect similarity between organisms and that do not need to be revised upon discovery of new diversity. We envision genome similarity-based codes to complement current biological nomenclature and to provide a universal means to communicate unambiguously about any genome-sequenced organism in fields as diverse as biodiversity research, infectious disease control, human and microbial forensics, animal breed and plant cultivar certification, and human ancestry research.

Population-genomic insights into emergence, crop adaptation and dissemination of Pseudomonas syringae pathogens.

Many bacterial pathogens are well characterized but, in some cases, little is known about the populations from which they emerged. This limits understanding of the molecular mechanisms underlying disease. The crop pathogen Pseudomonas syringae sensu lato has been widely isolated from the environment, including wild plants and components of the water cycle, and causes disease in several economically important crops. Here, we compared genome sequences of 45 P. syringae crop pathogen outbreak strains with 69 closely related environmental isolates. Phylogenetic reconstruction revealed that crop pathogens emerged many times independently from environmental populations. Unexpectedly, differences in gene content between environmental populations and outbreak strains were minimal with most virulence genes present in both. However, a genome-wide association study identified a small number of genes, including the type III effector genes hopQ1 and hopD1, to be associated with crop pathogens, but not with environmental populations, suggesting that this small group of genes may play an important role in crop disease emergence. Intriguingly, genome-wide analysis of homologous recombination revealed that the locus Psyr 0346, predicted to encode a protein that confers antibiotic resistance, has been frequently exchanged among lineages and thus may contribute to pathogen fitness. Finally, we found that isolates from diseased crops and from components of the water cycle, collected during the same crop disease epidemic, form a single population. This provides the strongest evidence yet that precipitation and irrigation water are an overlooked inoculum source for disease epidemics caused by P. syringae.

Ice nucleation active bacteria in precipitation are genetically diverse and nucleate ice by employing different mechanisms

A growing body of circumstantial evidence suggests that ice nucleation active (Ice+) bacteria contribute to the initiation of precipitation by heterologous freezing of super-cooled water in clouds. However, little is known about the concentration of Ice+ bacteria in precipitation, their genetic and phenotypic diversity, and their relationship to air mass trajectories and precipitation chemistry. In this study, 23 precipitation events were collected over 15 months in Virginia, USA. Air mass trajectories and water chemistry were determined and 33 134 isolates were screened for ice nucleation activity (INA) at −8 °C. Of 1144 isolates that tested positive during initial screening, 593 had confirmed INA at −8 °C in repeated tests. Concentrations of Ice+ strains in precipitation were found to range from 0 to 13 219 colony forming units per liter, with a mean of 384±147. Most Ice+ bacteria were identified as members of known and unknown Ice+ species in the Pseudomonadaceae, Enterobacteriaceae and Xanthomonadaceae families, which nucleate ice employing the well-characterized membrane-bound INA protein. Two Ice+ strains, however, were identified as Lysinibacillus, a Gram-positive genus not previously known to include Ice+ bacteria. INA of the Lysinibacillus strains is due to a nanometer-sized molecule that is heat resistant, lysozyme and proteinase resistant, and secreted. Ice+ bacteria and the INA mechanisms they employ are thus more diverse than expected. We discuss to what extent the concentration of culturable Ice+ bacteria in precipitation and the identification of a new heat-resistant biological INA mechanism support a role for Ice+ bacteria in the initiation of precipitation.

A Proposal for a Genome Similarity-Based Taxonomy for Plant-Pathogenic Bacteria that Is Sufficiently Precise to Reflect Phylogeny, Host Range, and Outbreak Affiliation Applied to Pseudomonas syringae sensu lato as a Proof of Concept

Taxonomy of plant pathogenic bacteria is challenging because pathogens of different crops often belong to the same named species but current taxonomy does not provide names for bacteria below the subspecies level. The introduction of the host range-based pathovar system in the 1980s provided a temporary solution to this problem but has many limitations. The affordability of genome sequencing now provides the opportunity for developing a new genome-based taxonomic framework. We already proposed to name individual bacterial isolates based on pairwise genome similarity. Here, we expand on this idea and propose to use genome similarity-based codes, which we now call life identification numbers (LINs), to describe and name bacterial taxa. Using 93 genomes of Pseudomonas syringae sensu lato, LINs were compared with a P. syringae genome tree whereby the assigned LINs were found to be informative of a majority of phylogenetic relationships. LINs also reflected host range and outbreak association for strains of P. syringae pathovar actinidiae, a pathovar for which many genome sequences are available. We conclude that LINs could provide the basis for a new taxonomic framework to address the shortcomings of the current pathovar system and to complement the current taxonomic system of bacteria in general.

Pseudomonas syringae Genomics: From Comparative Genomics of Individual Crop Pathogen Strains Toward Population Genomics

Whole-genome sequencing has become so affordable that we can now sequence genomes of dozens of individuals of a pathogen population instead of sequencing a single representative isolate. This change of framework enables us to answer questions impossible to address just a few years ago. Recent work on the complex has shown that such genomic approaches have practical implications for disease diagnostics, source attribution, and crop improvement. Most of this work is represented so far by studies on P. syringae pv. aesculi, pv. tomato, pv. actinidiae, and pv. phaseolicola and Pseudomonas cannabina pv. alisalensis. These studies performed comparative genomics and phylogenetic analyses using exclusively populations of P. syringae associated with crops. They thus excluded the vast majority of the P. syringae metapopulation, which is present outside of agricultural fields in habitats associated with the water cycle, leaf litter, and soil, which have been found to be significantly involved in the population dynamics of P. syringae and its evolutionary history. Bulk sequencing of P. syringae strains closely related to pathovar tomato from snowpack and surface water has started to reveal how the genomic diversity of P. syringae in non-agricultural environments relates to that of the epidemic population on crops. This chapter describes how population genomic analyses can take the study of evolution, ecology, disease, and molecular plant–microbe interactions of P. syringae to the next level by integrating all of its diversity and how such studies can be applied to help prevent and/or control future disease outbreaks.

Testing differences between pathogen compositions with small samples and sparse data

The structure of pathogen populations is an important driver of epidemics affecting crops and natural plant communities. Comparing the composition of two pathogen populations consisting of assemblages of genotypes or phenotypes is a crucial, recurrent question encountered in many studies in plant disease epidemiology. Determining whether there is a significant difference between two sets of proportions is also a generic question for numerous biological fields. When samples are small and data are sparse, it is not straightforward to provide an accurate answer to this simple question because routine statistical tests may not be exactly calibrated. To tackle this issue, we built a computationally intensive testing procedure, the generalized Monte Carlo plug-in test with calibration test, which is implemented in an R package available at https://doi.org/10.5281/zenodo.635791 . A simulation study was carried out to assess the performance of the proposed methodology and to make a comparison with standard statistical tests. This study allows us to give advice on how to apply the proposed method, depending on the sample sizes. The proposed methodology was then applied to real datasets and the results of the analyses were discussed from an epidemiological perspective. The applications to real data sets deal with three topics in plant pathology: the reproduction of Magnaporthe oryzae, the spatial structure of Pseudomonas syringae, and the temporal recurrence of Puccinia triticina.