Evolution within a given virulence phenotype (pathotype) is driven by changes in aggressiveness: a case study of French wheat leaf rust populations

Plant pathogens are constantly evolving and adapting to their environment, including their host. Virulence alleles emerge, and then increase, and sometimes decrease in frequency within pathogen populations in response to the fluctuating selection pressures imposed by the deployment of resistance genes. In some cases, these strong selection pressures cannot fully explain the evolution observed in pathogen populations. A previous study on the French population of Puccinia triticina, the causal agent of wheat leaf rust, showed that two major pathotypes — groups of isolates with a particular combination of virulences — predominated but then declined over the 2005-2016 period. The relative dynamics and the domination of these two pathotypes — 166 317 0 and 106 314 0 —, relative to the other pathotypes present in the population at a low frequency although compatible, i.e. virulent on several varieties deployed, could not be explained solely by the frequency of Lr genes in the landscape. Within these two pathotypes, we identified two main genotypes that emerged in succession. We assessed three components of aggressiveness — infection efficiency, latency period and sporulation capacity — for 44 isolates representative of the four P. triticina pathotype-genotype combinations. We showed, for both pathotypes, that the more recent genotypes were more aggressive than the older ones. Our findings were highly consistent for the various components of aggressiveness for pathotype 166 317 0 grown on Michigan Amber — a ‘naive’ cultivar never grown in the landscape — or on Apache — a ‘neutral’ cultivar, which does not affect the pathotype frequency in the landscape and therefore was postulated to have no or minor selection effect on the population composition. For pathotype 106 314 0, the most recent genotype had a shorter latency period on several of the cultivars most frequently grown in the landscape, but not on ‘neutral’ and ‘naive’ cultivars. We conclude that the quantitative components of aggressiveness can be significant drivers of evolution in pathogen populations. A gain in aggressiveness stopped the decline in frequency of a pathotype, and subsequently allowed an increase in frequency of this pathotype in the pathogen population, providing evidence that adaptation to a changing varietal landscape not only affects virulence but can also lead to changes in aggressiveness

Carbon storage of headwater riparian zones in an agricultural landscape

<p>Abstract</p> <p>Background</p> <p>In agricultural regions, streamside forests have been reduced in age and extent, or removed entirely to maximize arable cropland. Restoring and reforesting such riparian zones to mature forest, particularly along headwater streams (which constitute 90% of stream network length) would both increase carbon storage and improve water quality. Age and management-related cover/condition classes of headwater stream networks can be used to rapidly inventory carbon storage and sequestration potential if carbon storage capacity of conditions classes and their relative distribution on the landscape are known.</p> <p>Results</p> <p>Based on the distribution of riparian zone cover/condition classes in sampled headwater reaches, current and potential carbon storage was extrapolated to the remainder of the North Carolina Coastal Plain stream network. Carbon stored in headwater riparian reaches is only about 40% of its potential capacity, based on 242 MgC/ha stored in sampled mature riparian forest (forest > 50 y old). The carbon deficit along 57,700 km headwater Coastal Plain streams is equivalent to about 25TgC in 30-m-wide riparian buffer zones and 50 TgC in 60-m-wide buffer zones.</p> <p>Conclusions</p> <p>Estimating carbon storage in recognizable age-and cover-related condition classes provides a rapid way to better inventory current carbon storage, estimate storage capacity, and calculate the potential for additional storage. In light of the particular importance of buffer zones in headwater reaches in agricultural landscapes in ameliorating nutrient and sediment input to streams, encouraging the restoration of riparian zones to mature forest along headwater reaches worldwide has the potential to not only improve water quality, but also simultaneously reduce atmospheric CO₂.</p

Major histocompatibility complex class I molecules protect motor neurons from astrocyte-induced toxicity in amyotrophic lateral sclerosis

Astrocytes isolated from individuals with amyotrophic lateral sclerosis (ALS) are toxic to motor neurons (MNs) and play a non–cell autonomous role in disease pathogenesis. The mechanisms underlying the susceptibility of MNs to cell death remain unclear. Here we report that astrocytes derived from either mice bearing mutations in genes associated with ALS or human subjects with ALS reduce the expression of major histocompatibility complex class I (MHCI) molecules on MNs; reduced MHCI expression makes these MNs susceptible to astrocyte-induced cell death. Increasing MHCI expression on MNs increases survival and motor performance in a mouse model of ALS and protects MNs against astrocyte toxicity. Overexpression of a single MHCI molecule, HLA-F, protects human MNs from ALS astrocyte–mediated toxicity, whereas knockdown of its receptor, the killer cell immunoglobulin-like receptor KIR3DL2, on human astrocytes results in enhanced MN death. Thus, our data indicate that, in ALS, loss of MHCI expression on MNs renders them more vulnerable to astrocyte-mediated toxicity

CloVR: A virtual machine for automated and portable sequence analysis from the desktop using cloud computing

Next-generation sequencing technologies have decentralized sequence acquisition, increasing the demand for new bioinformatics tools that are easy to use, portable across multiple platforms, and scalable for high-throughput applications. Cloud computing platforms provide on-demand access to computing infrastructure over the Internet and can be used in combination with custom built virtual machines to distribute pre-packaged with pre-configured software. We describe the Cloud Virtual Resource, CloVR, a new desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing. In a case study, we demonstrate the use of CloVR to automatically process next-generation sequencing data on multiple cloud computing platforms. The CloVR VM and associated architecture lowers the barrier of entry for utilizing complex analysis protocols on both local single- and multi-core computers and cloud systems for high throughput data processing.https://doi.org/10.1186/1471-2105-12-35