New resources for functional analysis of omics data for the genus Aspergillus

<p>Abstract</p> <p>Background</p> <p>Detailed and comprehensive genome annotation can be considered a prerequisite for effective analysis and interpretation of omics data. As such, Gene Ontology (GO) annotation has become a well accepted framework for functional annotation. The genus <it>Aspergillus </it>comprises fungal species that are important model organisms, plant and human pathogens as well as industrial workhorses. However, GO annotation based on both computational predictions and extended manual curation has so far only been available for one of its species, namely <it>A. nidulans</it>.</p> <p>Results</p> <p>Based on protein homology, we mapped 97% of the 3,498 GO annotated <it>A. nidulans </it>genes to at least one of seven other <it>Aspergillus </it>species: <it>A. niger</it>, <it>A. fumigatus</it>, <it>A. flavus</it>, <it>A. clavatus</it>, <it>A. terreus</it>, <it>A. oryzae </it>and <it>Neosartorya fischeri</it>. GO annotation files compatible with diverse publicly available tools have been generated and deposited online. To further improve their accessibility, we developed a web application for GO enrichment analysis named FetGOat and integrated GO annotations for all <it>Aspergillus </it>species with public genome sequences. Both the annotation files and the web application FetGOat are accessible via the Broad Institute's website (<url>http://www.broadinstitute.org/fetgoat/index.html</url>). To demonstrate the value of those new resources for functional analysis of omics data for the genus <it>Aspergillus</it>, we performed two case studies analyzing microarray data recently published for <it>A. nidulans</it>, <it>A. niger </it>and <it>A. oryzae</it>.</p> <p>Conclusions</p> <p>We mapped <it>A. nidulans </it>GO annotation to seven other <it>Aspergilli</it>. By depositing the newly mapped GO annotation online as well as integrating it into the web tool FetGOat, we provide new, valuable and easily accessible resources for omics data analysis and interpretation for the genus <it>Aspergillus</it>. Furthermore, we have given a general example of how a well annotated genome can help improving GO annotation of related species to subsequently facilitate the interpretation of omics data.</p

Standardized metadata for human pathogen/vector genomic sequences

High throughput sequencing has accelerated the determination of genome sequences for thousands of human infectious disease pathogens and dozens of their vectors. The scale and scope of these data are enabling genotype-phenotype association studies to identify genetic determinants of pathogen virulence and drug/insecticide resistance, and phylogenetic studies to track the origin and spread of disease outbreaks. To maximize the utility of genomic sequences for these purposes, it is essential that metadata about the pathogen/vector isolate characteristics be collected and made available in organized, clear, and consistent formats. Here we report the development of the GSCID/BRC Project and Sample Application Standard, developed by representatives of the Genome Sequencing Centers for Infectious Diseases (GSCIDs), the Bioinformatics Resource Centers (BRCs) for Infectious Diseases, and the U.S. National Institute of Allergy and Infectious Diseases (NIAID), part of the National Institutes of Health (NIH), informed by interactions with numerous collaborating scientists. It includes mapping to terms from other data standards initiatives, including the Genomic Standards Consortium's minimal information (MIxS) and NCBI's BioSample/BioProjects checklists and the Ontology for Biomedical Investigations (OBI). The standard includes data fields about characteristics of the organism or environmental source of the specimen, spatial-temporal information about the specimen isolation event, phenotypic characteristics of the pathogen/vector isolated, and project leadership and support. By modeling metadata fields into an ontology-based semantic framework and reusing existing ontologies and minimum information checklists, the application standard can be extended to support additional project-specific data fields and integrated with other data represented with comparable standards. The use of this metadata standard by all ongoing and future GSCID sequencing projects will provide a consistent representation of these data in the BRC resources and other repositories that leverage these data, allowing investigators to identify relevant genomic sequences and perform comparative genomics analyses that are both statistically meaningful and biologically relevant

Re-Annotation Is an Essential Step in Systems Biology Modeling of Functional Genomics Data

One motivation of systems biology research is to understand gene functions and interactions from functional genomics data such as that derived from microarrays. Up-to-date structural and functional annotations of genes are an essential foundation of systems biology modeling. We propose that the first essential step in any systems biology modeling of functional genomics data, especially for species with recently sequenced genomes, is gene structural and functional re-annotation. To demonstrate the impact of such re-annotation, we structurally and functionally re-annotated a microarray developed, and previously used, as a tool for disease research. We quantified the impact of this re-annotation on the array based on the total numbers of structural- and functional-annotations, the Gene Annotation Quality (GAQ) score, and canonical pathway coverage. We next quantified the impact of re-annotation on systems biology modeling using a previously published experiment that used this microarray. We show that re-annotation improves the quantity and quality of structural- and functional-annotations, allows a more comprehensive Gene Ontology based modeling, and improves pathway coverage for both the whole array and a differentially expressed mRNA subset. Our results also demonstrate that re-annotation can result in a different knowledge outcome derived from previous published research findings. We propose that, because of this, re-annotation should be considered to be an essential first step for deriving value from functional genomics data

Quantitative Trait Locus (QTL) Mapping Reveals a Role for Unstudied Genes in Aspergillus Virulence

Infections caused by the fungus Aspergillus are a major cause of morbidity and mortality in immunocompromised populations. To identify genes required for virulence that could be used as targets for novel treatments, we mapped quantitative trait loci (QTL) affecting virulence in the progeny of a cross between two strains of A. nidulans (FGSC strains A4 and A91). We genotyped 61 progeny at 739 single nucleotide polymorphisms (SNP) spread throughout the genome, and constructed a linkage map that was largely consistent with the genomic sequence, with the exception of one potential inversion of ∼527 kb on Chromosome V. The estimated genome size was 3705 cM and the average intermarker spacing was 5.0 cM. The average ratio of physical distance to genetic distance was 8.1 kb/cM, which is similar to previous estimates, and variation in recombination rate was significantly positively correlated with GC content, a pattern seen in other taxa. To map QTL affecting virulence, we measured the ability of each progeny strain to kill model hosts, larvae of the wax moth Galleria mellonella. We detected three QTL affecting in vivo virulence that were distinct from QTL affecting in vitro growth, and mapped the virulence QTL to regions containing 7–24 genes, excluding genes with no sequence variation between the parental strains and genes with only synonymous SNPs. None of the genes in our QTL target regions have been previously associated with virulence in Aspergillus, and almost half of these genes are currently annotated as “hypothetical”. This study is the first to map QTL affecting the virulence of a fungal pathogen in an animal host, and our results illustrate the power of this approach to identify a short list of unknown genes for further investigation

Effects of a defective ERAD pathway on growth and heterologous protein production in Aspergillus niger

Endoplasmic reticulum associated degradation (ERAD) is a conserved mechanism to remove misfolded proteins from the ER by targeting them to the proteasome for degradation. To assess the role of ERAD in filamentous fungi, we have examined the consequences of disrupting putative ERAD components in the filamentous fungus Aspergillus niger. Deletion of derA, doaA, hrdC, mifA, or mnsA in A. niger yields viable strains, and with the exception of doaA, no significant growth phenotype is observed when compared to the parental strain. The gene deletion mutants were also made in A. niger strains containing single- or multicopies of a glucoamylase–glucuronidase (GlaGus) gene fusion. The induction of the unfolded protein response (UPR) target genes (bipA and pdiA) was dependent on the copy number of the heterologous gene and the ERAD gene deleted. The highest induction of UPR target genes was observed in ERAD mutants containing multiple copies of the GlaGus gene. Western blot analysis revealed that deletion of the derA gene in the multicopy GlaGus overexpressing strain resulted in a 6-fold increase in the intracellular amount of GlaGus protein detected. Our results suggest that impairing some components of the ERAD pathway in combination with high expression levels of the heterologous protein results in higher intracellular protein levels, indicating a delay in protein degradation

Sensing the fuels: glucose and lipid signaling in the CNS controlling energy homeostasis

The central nervous system (CNS) is capable of gathering information on the body’s nutritional state and it implements appropriate behavioral and metabolic responses to changes in fuel availability. This feedback signaling of peripheral tissues ensures the maintenance of energy homeostasis. The hypothalamus is a primary site of convergence and integration for these nutrient-related feedback signals, which include central and peripheral neuronal inputs as well as hormonal signals. Increasing evidence indicates that glucose and lipids are detected by specialized fuel-sensing neurons that are integrated in these hypothalamic neuronal circuits. The purpose of this review is to outline the current understanding of fuel-sensing mechanisms in the hypothalamus, to integrate the recent findings in this field, and to address the potential role of dysregulation in these pathways in the development of obesity and type 2 diabetes mellitus

Defining family business: a closer look at definitional heterogeneity

Researchers have used a myriad of different definitions in seeking to explain the heterogeneity of family firms and their unique behavior; however, no widely-accepted definition exists today. Definitional clarity in any field is essential to provide (a) the basis for the analysis of performance both spatially and temporally and (b) the foundation upon which theories, frameworks and models are developed. We provide a comprehensive analysis of prior research and identify and classify 82 definitions of family business. We then review and evaluate five key theoretical perspectives in family business to identify how these have shaped and informed the definitions employed in the field and duly explain family firm heterogeneity. Finally, we provide a conceptual diagram to inform the choice of definition in different research settings

Occupancy and fractal dimension analyses of the spatial distribution of cytotoxic (CD8+) T cells infiltrating the tumor microenvironment in triple negative breast cancer

Favorable outcomes have been associated with high densities of tumor infiltrating lymphocytes (TILs) such as cytotoxic (CD8+) T cells. However, the clinical signifi- cance of the spatial distribution of TILs is less well understood. We have developed novel statistical techniques to characterize the spatial distribution of TILs at various length scales. These include a box counting method that we call “occupancy” and novel applications of fractal dimensions. We apply these techniques to the spatial distribution of CD8+ T cells in the tumor microenvironment of tissue resected from 35 triple negative breast cancer patients. We find that there is a distinct difference in the spatial distribution of CD8+ T cells between good clinical outcome (no recurrence within at least 5 years of diagnosis) and poor clinical outcome (recurrence within 3 years of diagnosis). The statistical significance of the difference between good and poor outcome in the occupancy, fractal dimension (FD), and FD difference of CD8+ T cells is comparable to that of the CD8+ T cell density. Even when we randomly exclude some of the cells so that the images have the same cell density, we still find that the fractal dimension at short length scales is correlated with cancer recurrence, implying that the actual spatial distribution of CD8+ cells, and not just the CD8+ cell density, is associated with clinical outcome. The occupancy and FD difference indicate that the CD8+ T cells are more spatially dispersed in good outcome and more aggregated in poor outcome. We discuss possible interpretations