Oomycete Metabolism Is Highly Dynamic and Reflects Lifestyle Adaptations.

The selective pressure of pathogen-host symbiosis drives adaptations. How these interactions shape the metabolism of pathogens is largely unknown. Here, we use comparative genomics to systematically analyze the metabolic networks of oomycetes, a diverse group of eukaryotes that includes saprotrophs as well as animal and plant pathogens, with the latter causing devastating diseases with significant economic and/or ecological impacts.

Uncovering the Role of Metabolism in Oomycete-Host Interactions Using Genome-Scale Metabolic Models.

Metabolism is the set of biochemical reactions of an organism that enables it to assimilate nutrients from its environment and to generate building blocks for growth and proliferation. It forms a complex network that is intertwined with the many molecular and cellular processes that take place within cells. Systems biology aims to capture the complexity of cells, organisms, or communities by reconstructing models based on information gathered by high-throughput analyses (omics data) and prior knowledge.

Mining oomycete proteomes for metalloproteases leads to identification of candidate virulence factors in Phytophthora infestans.

Pathogens deploy a wide range of pathogenicity factors, including a plethora of proteases, to modify host tissue or manipulate host defences. Metalloproteases (MPs) have been implicated in virulence in several animal and plant pathogens. Here we investigated the repertoire of MPs in 46 stramenopile species including 37 oomycetes, 5 diatoms, and 4 brown algae.

Misannotated Multi-Nucleotide Variants in Public Cancer Genomics Datasets Lead to Inaccurate Mutation Calls with Significant Implications.

Although next-generation sequencing is widely used in cancer to profile tumors and detect variants, most somatic variant callers used in these pipelines identify variants at the lowest possible granularity, single-nucleotide variants (SNV). As a result, multiple adjacent SNVs are called individually instead of as a multi-nucleotide variants (MNV). With this approach, the amino acid change from the individual SNV within a codon could be different from the amino acid change based on the MNV that results from combining SNV, leading to incorrect conclusions about the downstream effects of the variants.

The Genome of Reveals High Heterozygosity, a Low Number of Canonical Effectors, and TC-Rich Promoters.

Along with , has arguably been the economically most important newly emerging downy mildew pathogen of the past two decades. Originating from Africa, it has started devastating basil production throughout the world, most likely due to the distribution of infested seed material. Here, we present the genome of this pathogen and results from comparisons of its genomic features to other oomycetes.

Metabolic Model of the -Tomato Interaction Reveals Metabolic Switches during Host Colonization.

The oomycete pathogen causes potato and tomato late blight, a disease that is a serious threat to agriculture. is a hemibiotrophic pathogen, and during infection, it scavenges nutrients from living host cells for its own proliferation. To date, the nutrient flux from host to pathogen during infection has hardly been studied, and the interlinked metabolisms of the pathogen and host remain poorly understood.

Functional Analysis of Mating Type Genes and Transcriptome Analysis during Fruiting Body Development of .

is a plant-pathogenic fungus producing apothecia as sexual fruiting bodies. To study the function of mating type () genes, single-gene deletion mutants were generated in both genes of the locus and both genes of the locus. Deletion mutants in two genes were entirely sterile, while mutants in the other two genes were able to develop stipes but never formed an apothecial disk.

Genome-wide characterization of Phytophthora infestans metabolism: a systems biology approach.

Genome-scale metabolic models (GEMs) provide a functional view of the complex network of biochemical reactions in the living cell. Initially mainly applied to reconstruct the metabolism of model organisms, the availability of increasingly sophisticated reconstruction methods and more extensive biochemical databases now make it possible to reconstruct GEMs for less well-characterized organisms, and have the potential to unravel the metabolism in pathogen-host systems. Here, we present a GEM for the oomycete plant pathogen Phytophthora infestans as a first step towards an integrative model with its host.