Tag Archives: bacteria

Local adaptation and the accessory genome in an endemic plant-pathogen

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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. 

Visualization of microbial communities within single leaves

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 (Pseudomonas fluorescens 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.

Biogeographical and temporal patterns of the microbial communities of Arabidopsis thaliana located in the Midwestern United States

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.

Predictability of bacterial communities across environmental and species complexities

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.