SREB, a GATA Transcription Factor That Directs Disparate Fates in Blastomyces dermatitidis Including Morphogenesis and Siderophore Biosynthesis

Blastomyces dermatitidis belongs to a group of human pathogenic fungi that exhibit thermal dimorphism. At 22°C, these fungi grow as mold that produce conidia or infectious particles, whereas at 37°C they convert to budding yeast. The ability to switch between these forms is essential for virulence in mammals and may enable these organisms to survive in the soil. To identify genes that regulate this phase transition, we used Agrobacterium tumefaciens to mutagenize B. dermatitidis conidia and screened transformants for defects in morphogenesis. We found that the GATA transcription factor SREB governs multiple fates in B. dermatitidis: phase transition from yeast to mold, cell growth at 22°C, and biosynthesis of siderophores under iron-replete conditions. Insertional and null mutants fail to convert to mold, do not accumulate significant biomass at 22°C, and are unable to suppress siderophore biosynthesis under iron-replete conditions. The defect in morphogenesis in the SREB mutant was independent of exogenous iron concentration, suggesting that SREB promotes the phase transition by altering the expression of genes that are unrelated to siderophore biosynthesis. Using bioinformatic and gene expression analyses, we identified candidate genes with upstream GATA sites whose expression is altered in the null mutant that may be direct or indirect targets of SREB and promote the phase transition. We conclude that SREB functions as a transcription factor that promotes morphogenesis and regulates siderophore biosynthesis. To our knowledge, this is the first gene identified that promotes the conversion from yeast to mold in the dimorphic fungi, and may shed light on environmental persistence of these pathogens

An Insect Herbivore Microbiome with High Plant Biomass-Degrading Capacity

Herbivores can gain indirect access to recalcitrant carbon present in plant cell walls through symbiotic associations with lignocellulolytic microbes. A paradigmatic example is the leaf-cutter ant (Tribe: Attini), which uses fresh leaves to cultivate a fungus for food in specialized gardens. Using a combination of sugar composition analyses, metagenomics, and whole-genome sequencing, we reveal that the fungus garden microbiome of leaf-cutter ants is composed of a diverse community of bacteria with high plant biomass-degrading capacity. Comparison of this microbiome's predicted carbohydrate-degrading enzyme profile with other metagenomes shows closest similarity to the bovine rumen, indicating evolutionary convergence of plant biomass degrading potential between two important herbivorous animals. Genomic and physiological characterization of two dominant bacteria in the fungus garden microbiome provides evidence of their capacity to degrade cellulose. Given the recent interest in cellulosic biofuels, understanding how large-scale and rapid plant biomass degradation occurs in a highly evolved insect herbivore is of particular relevance for bioenergy

Understanding multicellular function and disease with human tissue-specific networks

Tissue and cell-type identity lie at the core of human physiology and disease. Understanding the genetic underpinnings of complex tissues and individual cell lineages is crucial for developing improved diagnostics and therapeutics. We present genome-wide functional interaction networks for 144 human tissues and cell types developed using a data-driven Bayesian methodology that integrates thousands of diverse experiments spanning tissue and disease states. Tissue-specific networks predict lineage-specific responses to perturbation, reveal genes’ changing functional roles across tissues, and illuminate disease-disease relationships. We introduce NetWAS, which combines genes with nominally significant GWAS p-values and tissue-specific networks to identify disease-gene associations more accurately than GWAS alone. Our webserver, GIANT, provides an interface to human tissue networks through multi-gene queries, network visualization, analysis tools including NetWAS, and downloadable networks. GIANT enables systematic exploration of the landscape of interacting genes that shape specialized cellular functions across more than one hundred human tissues and cell types