The streamlined genome of Phytomonas spp. relative to human pathogenic kinetoplastids reveals a parasite tailored for plants

Members of the family Trypanosomatidae infect many organisms, including animals, plants and humans. Plant-infecting trypanosomes are grouped under the single genus Phytomonas, failing to reflect the wide biological and pathological diversity of these protists. While some Phytomonas spp. multiply in the latex of plants, or in fruit or seeds without apparent pathogenicity, others colonize the phloem sap and afflict plants of substantial economic value, including the coffee tree, coconut and oil palms. Plant trypanosomes have not been studied extensively at the genome level, a major gap in understanding and controlling pathogenesis. We describe the genome sequences of two plant trypanosomatids, one pathogenic isolate from a Guianan coconut and one non-symptomatic isolate from Euphorbia collected in France. Although these parasites have extremely distinct pathogenic impacts, very few genes are unique to either, with the vast majority of genes shared by both isolates. Significantly, both Phytomonas spp. genomes consist essentially of single copy genes for the bulk of their metabolic enzymes, whereas other trypanosomatids e.g. Leishmania and Trypanosoma possess multiple paralogous genes or families. Indeed, comparison with other trypanosomatid genomes revealed a highly streamlined genome, encoding for a minimized metabolic system while conserving the major pathways, and with retention of a full complement of endomembrane organelles, but with no evidence for functional complexity. Identification of the metabolic genes of Phytomonas provides opportunities for establishing in vitro culturing of these fastidious parasites and new tools for the control of agricultural plant disease. © 2014 Porcel et al

Deciphering the Pathobiome: Intra- and Interkingdom Interactions Involving the Pathogen Erysiphe alphitoides

Plant-inhabiting microorganisms interact directly with each other, forming complex microbial interaction networks. These interactions can either prevent or facilitate the establishment of new microbial species, such as a pathogen infecting the plant. Here, our aim was to identify the most likely interactions between Erysiphe alphitoides, the causal agent of oak powdery mildew, and other foliar microorganisms of pedunculate oak (Quercus robur L.). We combined metabarcoding techniques and a Bayesian method of network inference to decipher these interactions. Our results indicate that infection with E. alphitoides is accompanied by significant changes in the composition of the foliar fungal and bacterial communities. They also highlight 13 fungal operational taxonomic units (OTUs) and 13 bacterial OTUs likely to interact directly with E. alphitoides. Half of these OTUs, including the fungal endophytes Mycosphaerella punctiformis and Monochaetia kansensis, could be antagonists of E. alphitoides according to the inferred microbial network. Further studies will be required to validate these potential interactions experimentally. Overall, we showed that a combination of metabarcoding and network inference, by highlighting potential antagonists of pathogen species, could potentially improve the biological control of plant diseases