anthomonas oryzae pv. oryzae (Xoo) is the etiological agent of bacterial blight disease in rice. The disease is most severe in southeast Asia but is increasingly damaging in west African countries, and results in substantial yield loss 1. TALes from Xoo are injected by a type III secretion system into plant cells and recognize effector-binding elements (EBEs) in cognate SWEET host gene promoters, which results in induction of SWEET genes and production of sugars that enable disease susceptibility in rice 2,3. An array of central repeats, which are 34-35 amino acids long, are present in each TALe and interact with EBEs via two repeat variable di-residues (RVDs) at the 12th and 13th position of each repeat 4,5. Aberrant repeats, longer than 35 amino acids, are hypothesized to allow looping out of the repeat to accommodate alternate sequence binding for a particular TALe 6. Bacterial blight depends on TALe-mediated induction of at least one member of a family of sugar-transporter genes. Although rice has more than 20 SWEET genes, only those of clade III are reported to be induced by Xoo 7-10. Although all five of the known clade III SWEET genes in rice can function as susceptibility genes for bacterial blight, only three are known to be targeted in nature 10. More specifically, SWEET11 expression is induced by strains encoding the TALe PthXo1, SWEET13 by PthXo2 and SWEET14 by any one of several TALes, namely AvrXa7, PthXo3, TalC and TalF (originally Tal5) 7,9-15 (Table 1). Effectors of Xoo that target clade III SWEET genes are referred to as major TALes owing to their strong virulence effect. Naturally occurring resistance has arisen as the result of nucleotide polymorphisms in EBEs of SWEET promoters. EBE alleles of SWEET11 that are not recognized by PthXo1 are collectively referred to as the recessive resistance gene xa13. Rice varieties containing xa13 are resistant to strains that solely depend on PthXo1 for SWEET induction. Most indica rice varieties carry a SWEET13 allele that contains four adenines in the EBE for PthXo2, and rice lines carrying this allele are susceptible to PthXo2-dependent strains 12. A rare exception is the recessive resistance allele xa25, which contains three adenines in the EBE for SWEET13 in the indica cultivar Minghui 63, conferring resistance to strains that depend solely on PthXo2 16. A similar recessive resistance allele in japonica rice varieties is equally effective against strains relying on PthXo2 (ref. 12). Additional naturally occurring recessive EBE polymorphisms that confer resistance to strains carrying PthXo2, and the overlapping EBEs for PthXo3, TalF and AvrXa7 have subsequently been identified in the promoters of SWEET13 and SWEET14, respectively, in germplasm collections 17,18. Rice susceptibility genes are good targets for genome editing for disease resistance. TALe-mediated susceptibility is particularly modifiable. For instance, transcription-activator-like effector nuclease (TALEN)-directed mutations in SWEET14 created lines resistant to strains carrying PthXo3/Avr...

Malassezia is a unique lipophilic genus in class Malasseziomycetes in Ustilaginomycotina, (Basidiomycota, fungi) that otherwise consists almost exclusively of plant pathogens. Malassezia are typically isolated from warm-blooded animals, are dominant members of the human skin mycobiome and are associated with common skin disorders. To characterize the genetic basis of the unique phenotypes of Malassezia spp., we sequenced the genomes of all 14 accepted species and used comparative genomics against a broad panel of fungal genomes to comprehensively identify distinct features that define the Malassezia gene repertoire: gene gain and loss; selection signatures; and lineage-specific gene family expansions. Our analysis revealed key gene gain events (64) with a single gene conserved across all Malassezia but absent in all other sequenced Basidiomycota. These likely horizontally transferred genes provide intriguing gain-of-function events and prime candidates to explain the emergence of Malassezia. A larger set of genes (741) were lost, with enrichment for glycosyl hydrolases and carbohydrate metabolism, concordant with adaptation to skin’s carbohydrate-deficient environment. Gene family analysis revealed extensive turnover and underlined the importance of secretory lipases, phospholipases, aspartyl proteases, and other peptidases. Combining genomic analysis with a re-evaluation of culture characteristics, we establish the likely lipid-dependence of all Malassezia. Our phylogenetic analysis sheds new light on the relationship between Malassezia and other members of Ustilaginomycotina, as well as phylogenetic lineages within the genus. Overall, our study provides a unique genomic resource for understanding Malassezia niche-specificity and potential virulence, as well as their abundance and distribution in the environment and on human skin.

Whole metagenome analysis has the potential to reveal functional triggers of skin diseases, but issues of cost, robustness and sampling efficacy have limited its application. Here, we have established an alternative, clinically practical and robust metagenomic analysis protocol and applied it to 80 skin microbiome samples epidemiologically stratified for atopic dermatitis (AD). We have identified distinct non-flare, baseline skin microbiome signatures enriched for Streptococcus and Gemella but depleted for Dermacoccus in AD-prone versus normal healthy skin. Bacterial challenge assays using keratinocytes and monocyte-derived dendritic cells established distinct IL-1-mediated, innate and Th1-mediated adaptive immune responses with Staphylococcus aureus and Staphylococcus epidermidis. Bacterial differences were complemented by perturbations in the eukaryotic community and functional shifts in the microbiome-wide gene repertoire, which could exacerbate a dry and alkaline phenotype primed for pathogen growth and inflammation in AD-susceptible skin. These findings provide insights into how the skin microbial community, skin surface microenvironment and immune system cross-modulate each other, escalating the destructive feedback cycle between them that leads to AD flare.

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