Genetic variation is fodder for evolution, and microbial plant-pathogens have it in spades. The Pseudomonas syringae genome is characterized by many rare “accessory” genes that co-occur with “core” genes found in all individuals. In fact, accessory genes outnumber core genes 2:1, even though accessory genes are not essential for survival. Moreover, there is tremendous variation in the gene content of P. syringae; isolates from different crop species, for example, differ in gene content by ~32% (Karasov et al. 2017). Whether these strain-specific genes have adaptive potential remains unknown; they may simply be a consequence of high rates of mutation and lateral gene transfer, even if purifying selection to remove deleterious variants is strong. Another, not mutually exclusive possibility is that accessory genes are maintained by positive selection as pathogens adapt to alternative hosts. Indeed, local adaptation has been hypothesized to explain the presence of rare alleles in P. syringae, which causes major agricultural loss in multiple crop species each year. To address these hypotheses, I have paired a set of P. syringae isolates with their original hosts of isolation. I first test for local adaptation by comparing the in planta fitness of each isolate in its own, and in each other’s, native host. Next, I ask to what degree strain-specific genes influence adaptive patterns by using Tn-seq to track the in planta gene frequencies of each pathogen over the course of infection in each host. From this combination of experiments, we will learn to what extent host ecology influences genome evolution and virulence in P. syringae; this is important not only to inform our understanding of the selective process, but also to fields concerned with the emergence and spread of infectious disease.
During the last two decades, scientists achieved a better understanding of the molecular basis of host-parasite co-evolution. However, many studies focused on the interaction of the genetic plant model species Arabidopsis thaliana and the highly pathogenic but non-specific tomato pathogen Pseudomonas syringae pv. tomato DC3000.
The Bergelson lab studies the interaction of A. thaliana and one of its highly abundant bacterial resident, P. viridiflava . We previously identified broad-scale natural variation in resistance phenotypes towards two distinct clades of P. viridiflava . While some genotypes of A. thaliana show little signs of disease or low bacteria titer, others suffer from severe hydrolysis of leaf tissue.
In a collaboration with Fabrice Roux, Joy Bergelson and Madlen Vetter, we currently identify and confirm the genetic loci underlying strain-specific and general defense mechanisms of A. thaliana against its natural pathogen P. viridiflava.
The outcome of host-microbe interactions is influenced by host genetics and interactions among bacterial community members. Previous studies described the bacterial community associated with Arabidopsis thaliana in the field. Using controlled greenhouse experiments we now aim to characterize how endophytic species composition influences plant-pathogen interactions. We furthermore seek to identify host genetic loci underlying the putative control of bacterial community composition.
Plants recognize potential pathogens and induce a complex immune response by detecting pathogen-associated molecular patterns (PAMPs). While immune responses are beneficial for mitigating the detrimental effects of pathogens, PAMP perception comes at the cost of growth reduction in seedlings. The genetic basis of growth versus defense trade-offs is poorly understood. A genome-wide association study identified the genetic loci contributing to natural variation in expenses in innate immune responses. We experimentally validated several a priori and de novo candidate genes, which significantly contribute to de- or increase of biomass after PAMP-triggered seedling growth inhibition.
Knowledge of the ecological forces that structure microbial communities is pivotal to designing strategies that maintain diversity and promote greater host fitness. One major force is interspecific bacterial interactions such as cooperation, competition, and predation. These interactions clearly depend on the spatial configuration of community members, which is lost or confounded in most 16S rRNA gene amplicon and shotgun metagenomic surveys.
Here, using the endophytic leaf bacterial community of Arabidopsis thaliana as a model, we visualize the spatial structure of multi-species, in planta bacterial communities, and examine the role of space in the maintenance of diversity. For this study, we take advantage of cultivatable species isolated from A. thaliana. These isolates are among the most abundant species found within the leaves in nature.
We inoculate controlled assemblages of these species into gnotobiotic plants, fix leaves after communities stabilize, and subject sectioned leaf samples to fluorescence in situ hybridization (FISH). Standard bandpass filter imaging limits analysis to only a few fluorophores and becomes convoluted in the presence of strong plant autofluorescence. Therefore, we use spectral imaging to subtract the autofluorescence spectrum and to distinguish overlapping emission spectra. To first confirm the effectiveness of this technique, we imaged mono-colonized leaves to observe each species’ niche preferences in the endophytic environment.
We next include pairwise combinations of isolates and observe how each species modulates its spatial distribution in response to another species. We have preliminary evidence that the plant environment does indeed modulate interspecific bacterial interactions.
Two isolates (Pseudomonasfluorescens and P. poae) that exhibit competitive exclusion in a spatially homogenous liquid media environment, coexist to equal numbers when inoculated into gnotobiotic plants, as determined by spread plating plant homogenates and counting colony forming units. The spatial structure of this community is currently under investigation. By working up from mono-colonized leaves to more complex communities, we demonstrate that the host environment promotes greater diversity by providing for complex spatial distributions. Knowledge of how bacteria spatially distribute in this host environment will inform future strategies for maintaining diversity and host health.
Our current understanding of microbial community structures largely comes from snapshots, samples taken at single time points. Further, in regards to plants, little is known how communities change as plants age and transition from vegetative to reproductive growth.
In this project, we have planted surface sterilized seeds at sites located in Southwestern Michigan and sampled root and leaf tissues as the plants germinate, over winter, grow, and flower. To quantify community structures, we will amplify and sequence a portion of the 16S rRNA gene. From these data, we will be able to assess whether A. thaliana harbors “core” leaf and root microbiomes as well as how these communities change with environmental factors and plant growth stages.
The recent explosion of microbiome studies has uncovered important correlations of bacterial community structures with temporal and environmental gradients.; however, our ability to predict which species complexes can coexist under which environmental conditions remains poor. In this project, we focus on the predictability of bacterial communities across two axes of complexity, environment and species richness. We take advantage of cultivatable bacterial species isolated from Arabidopsis thaliana. These isolates are among the most abundant species found within the leaves of A. thaliana in nature.
We inoculate random subsets of twelve bacterial species into three increasingly complex environments, from liquid media to solid media to gnotobiotic plants, and follow replicated communities over time. To quantify species’ relative abundances, we amplify the V3-V4 region of 16S rRNA gene, sequence the amplicons via the Illumina MiSeq platform, and match reads to the known sequences. We assessed predictability in terms of dissimilarity of species relative abundances across replicates to observe whether replicates converge or diverge over time.
Preliminary results indicate that replicate dissimilarity increases with increasing species richness but not with increasing environmental complexity. Surprisingly, communities from homogenous liquid environments show increased dissimilarity than communities grown on solid media. By working up from the simplest communities in liquid culture to more complex communities in planta, we provide a framework to make predictions not just for bacterial communities but also for complex communities in nature.
Understanding how organisms adapt to their environment has been a long standing question in evolutionary biology. While demonstrating local adaptation with reciprocal transplants is an old idea (KAWECKI and EBERT 2004), the recent technological advances in genomics present us with an opportunity to better understand the genetics and the process of adaptive evolution.
This is particularly true for the model plant Arabidopsis thaliana. A. thaliana is a small, mostly selfing, winter-annual brassica that was introduced as a model species for its short life cycle and small genome size (THE ARABIDOPSIS GENOME INITIATIVE 2000). Naturally occurring inbred lines (accessions) also have the advantage that once they have been genotyped or sequenced, seeds generated through selfing can be used for multiple experiments with high levels of replication. In addition to being a convenient model, A. thaliana is also a wild plant, found across the world in a great diversity of natural environments and displays great phenotypic variation between and within populations (see for example STINCHCOMBE et al. 2004; KRONHOLM et al. 2012; ZÜST et al. 2012). The recent genomic resources developed for this plant opens an unprecedented opportunity to investigate the genetics underlying adaptive variation
(HORTON et al. 2012; LONG et al. 2013) while the great effort that went into understanding the function of many, if not most, of its genes provides us with a new window into the functions, traits and environmental factors driving in local adaptation.
In this project we investigate local adaptation in natural populations of this small winter annual plant in Sweden. Prior work showed strong population structure (NORDBORG et al. 2005) and isolation by distance (PLATT et al. 2010) throughout the species range, suggesting that populations are stable and have had the opportunity to adapt to local environments. Local adaptation to climate variation was also found to be ubiquitous across Europe (FOURNIER-LEVEL et al. 2011; HANCOCK et al. 2011).
In Sweden we focus on two regions: the High Coast, about 4h drive North of Stockholm, and Skåne, in the South (Figure 1).
These two regions display contrasting climates, with the Northern region of the High Coast displaying colder temperatures, longer snow cover, and a broader range of photoperiod. The High Coast is close to the Northern limit of the species range and in this region Arabidopsis populations are only found on South facing slopes where they can capture the low incidence sun’s rays. In Skåne, in the South, A. thaliana is found in agricultural meadows, fields and on beaches along the Baltic sea.
Building on the old idea of reciprocal transplants (KAWECKI and EBERT 2004), and combining it with cutting edge genomics, we set up experiments designed to test for local adaptation, identify important phenotypes and selective pressures, and detect the molecular bases of local adaptation among natural populations of A. thaliana.
We use a set of 200 accessions all re-sequenced (LONG et al. 2013) in a dual experimental strategy. The first part our experimental design consists of experimental natural selection experiments. In both the High Coast (North) and Skåne (South), we selected 5 locations where the environment seemed suitable for an Arabidopsis population to establish. In each location we set up five-1 m2 plots in which we dispersed a mixture of seeds from the 200 re-sequenced accessions (LONG et al. 2013). Populations were allowed to establish without further intervention and we collected samples three times a year for the last 2 years. After low depth sequencing of the samples, we will be able to track changes in the frequency of individual genotypes, but also changes in allele frequency across the genome.
The second experimental strategy builds more directly on the idea of reciprocal transplants and consists of 4 large common garden type experiments (two in each region). Experiments were installed to coincide with local germination flushes among local natural populations and consisted of three complete randomized blocks, each block included 8 replicates per accessions. These experiments were used to gather data on flowering time, herbivore damage, rosette size, shape and growth, pathogen infections and microbial community composition (see Microbial community paragraph). We also directly measured over-winter survival and estimated seed production, two major fitness components for any annual plant. These experiments will allow us to directly test for local adaptation, investigate the contribution of various significant traits, and to identify the underlying molecular bases of adaptive variation using Genome-Wide Association mapping (ATWELL et al. 2010). While estimating fitness component in the common garden experiment is likely biased because it doesn’t include all components of fitness, the results will help us understand and validate results from the selection experiments.
Preliminary results show evidence for local adaptation. In the Southern Sweden common garden experiments, Southern accessions grew bigger and produced more seeds than Northern accessions (Figure 2).
Interestingly, genome-wide association mapping clearly identifies a disease resistance gene explaining a significant fraction of seed production in one of the Southern experiments (Figure 3).
In the other Southern experiment, herbivore attacks in the fall are associated with SNP polymorphisms located near the known glucosinolate genes AOP2 and AOP3. The amount of herbivore damage also significantly decreases the probability of overwinter survival. Overall, preliminary results seem to indicate a large contribution of biotic interaction to fitness components. This prompted us to further investigate the leaf microbial community variation among accessions in our four common garden experiments.
Microbial community variation.
In a prior study from our lab, M. Horton and N. Bodenhausen performed a common garden experiment in Michigan in which they grew a set of 196 worldwide accessions in natural conditions (BODENHAUSEN et al. 2013, HORTON et al. In Press). They characterized the bacterial and fungal communities in leaves and roots for each accession by sequencing the taxonomically informative genes 16S rRNA in bacteria and ITS in fungi. One of the major results of these studies is the effect of the plant’s genotype on the composition and diversity of the plant microbiota. Using methods developed in these studies, we aim at better understanding adaptive variation in Sweden by characterizing the leaf microbial communities of the plants in the common garden installed in Sweden. The specific questions here are:
1) Are there differences in the bacterial community among the four study sites? Observing different communities of microbes among our study sites would suggest that plants experience a different biotic environment depending on the location and climate.
2) Can we see differences in the leaf bacterial community among accessions of Arabidopsis thaliana, and if so then what are the genetics driving those differences? Differences in leaf microbial community among accessions grown in the same location would suggest that plants shape the microbial community they host. Because all accessions used in this study have been genome sequenced, we will have the opportunity to study the genetics shaping the leaf microbial community with GWA mapping.
3) Are natural populations of Arabidopsis thaliana locally adapted to the pathogens they encounter in their natural habitat?
Fitness estimates based on seed production will be generated via high throughput analysis of mature plants images. We will investigate if polymorphisms at genes shaping the bacterial community in the different experiments have effects on plant fitness and determine their importance relative to genes underlying other adaptive traits.
Daniele Filiault (Gregor Mendel Institute, Vienna)
Svante Holms (Mid-Sweden University)
Envel Kerdaffrec (Gregor Mendel Institute, Austria)
Fernando Rabanal (Gregor Mendel Institute, Austria)
Polina Novikova (Gregor Mendel Institute, Austria)
Takashi Tsuchimatsu (Gregor Mendel Institute, Austria)
Susan Duncan (John Innes Centre, UK)
Timothy Morton (University of Chicago, USA)
Roderick Wooley (University of Chicago)
Matthew Box (John Innes Centre, UK)
Alison Anastasio (University of Chicago, USA)
Arthur Korte (Gregor Mendel Institute, Austria)
Pamela Korte (Gregor Mendel Institute, Austria)
Viktoria Nizhynska (Gregor Mendel Institute, Austria)
Stéphanie Arnoux (Gregor Mendel Institute, Austria)
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In agriculture, plant resistance to pathogens is typically short-lived, lasting on the order of a few years. In contrast, resistance in natural plant populations seems to persist for millions of years. Why is resistance ephemeral in agriculture, but seemingly indefinite in natural populations? We address this question by studying the coevolution of natural populations of A. thaliana with natural populations of their pathogens using molecular, genomic and ecological techniques.
Our results led us to a hypothesis about what maintains resistance polymorphisms in natural populations: A. thaliana, unlike plants in agriculture, is rarely challenged with one dominant pathogen. Instead, A. thaliana populations are exposed to thousands of microbes, all at low to intermediate abundances, each with different mechanisms of persistence and/or pathogenicity. A. thaliana seems to evolve resistance in response to this diverse microbial community, and not to one pathogen factor. In short, the heterogeneity of the microbial community selects for heterogeneity in resistance traits.
The high selective pressures involved in the “arms race” between plants and their pathogens drives rapid evolution of genes involved in immunity on the host side and virulence on the pathogen side (Alcázar et al., 2011). However, plants are not typically infected by individual pathogens: they interact with a community of inter- and intraspecifically diverse microbes that also experience competitive pressures from one another. How these interactions among microbes affect their ability to cause disease and how the host plant influences the microbial community it harbors remain open questions for investigation.
Researchers have observed that P. syringae is a common natural pathogen of A. thaliana and that resistance to P. syringae infection varies among different A. thaliana accessions (Jakob et al., 2002). Recent work has shown that P. syringae strains isolated from A. thaliana leaf tissue are not only genetically diverse but also differ in their degree of virulence: many isolates harbor a polymorphism in the type three secretion system (T3SS), losing the ability to cause disease (Barrett et al., 2011; Kniskern et al., 2011). Such strains show increased growth in plant tissue when co-inoculated with other P. syringae isolates harboring an intact T3SS. This result suggests a model where non-pathogenic strains engage in “cheating” through taking advantage of the nutrients released from host cells infected by pathogenic strains (Barrett et al., 2011).
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University of Chicago, Dept. of Ecology & Evolution