Improving our understanding of aspergillus fumigatus
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Improving our understanding of Aspergillus fumigatus. Project Overview. Aspergillus fumigatus. RNA- Seq. WGS. SNP calling. Statistical analysis. Network analysis. Why sequence Aspergillus fumigatus ? . Allergic aspergillosis – associated with asthma Invasive aspergillosis

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Improving our understanding of Aspergillus fumigatus

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Improving our understanding of aspergillus fumigatus

Improving our understanding of Aspergillusfumigatus


Project overview

Project Overview

Aspergillusfumigatus

  • RNA-Seq

  • WGS

  • SNP calling

  • Statistical analysis

  • Network analysis


Why sequence aspergillus fumigatus

Why sequence Aspergillus fumigatus?

  • Allergic aspergillosis – associated with asthma

  • Invasive aspergillosis

    • > 40% hospital acquired ?

    • Very high mortality rate (50–90%) in treated patients

    • No effective drugs, vaccines or diagnostics

    • Emerging drug resistance: 10%-50%

Bueid et al., 2010

Invasive aspergillosis


Two additional reference genomes

Two additional reference genomes

Mitochodrial genetic diversity

  • AF10 and AF210 – chosen because they are different from Af293 and Af1163

  • Unique MLST types

    • Af10: Clinical isolate from immunosuppressed patient in LA; fully susceptible to azoles and amphothericin B

    • Af210: Nosocomial infection in Manchester; MLST identical to ICU environmental strain and 5 other clinical samples

  • Sequencing completed; annotation pending

  • Mitochondria compared for 11 Aspergillusand Penicilliumgenomes

Joardar, submitted


Novel drug resistance mechanisms snp calling clustering and association

Novel drug resistance mechanisms:SNP calling, clustering, and association

*sequential resistant isolates TBS

SNP density along the 8 Afu293 chromosomes show a subtelomere bias

SNP/10Kb


50 loci show extreme allelic variability between strains

>50 loci show extreme allelic variability between strains

  • Greater than 15 SNPs/Kb

  • Several involved in vegetative incompatibility

HET locus AFUB_017990

GBrowse2


Significant variability is also present in drug resistance genes

Significant variability is also present in drug resistance genes

  • Cyp51A: 10-12 SNPs

  • Mdr1/AtrD ABC transporter: 2-8 SNPs

cyp51A asn2

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Annotation improvement with rnaseq

Annotation improvement with RNAseq

630 updates so far

  • Use sequence reads to validate and/or modify existing gene models

  • Update categories

    • Gene extension

    • Gene mergers

    • UTRs

    • Alternative Isoforms

    • Novel genes

    • Exon boundary adjustments

    • Validation of hypotheticals


Rna seq reveals alternative isoforms in a transcription factor linked to hypoxia

RNA-Seq reveals alternative isoforms in a transcription factor linked to hypoxia

AFUB_018340

GBrowse2


Rna seq identifies novel genes

RNA-Seq identifies novel genes

Novel genes


Rna seq expression profiling of host pathogen interactions

RNA-Seqexpression profiling of host-pathogen interactions

  • Fungusexposed vs. non-exposed to NK cells

    • 171 genes

    • 63 genes

  • Human NK cells exposed to fungus

    • 503 genes

    • 518 genes

  • => Pathway enrichment and network analysis

    • Key drivers of the transcriptional changes

    • Targets for immuno-modulation therapy


Outbreak investigation

Outbreak Investigation

  • Current methodology depends on analysis of short tandem repeats at 6 loci in the genome

  • However, there are no high-confidence global SNP markers for outbreak investigation

  • Sequenced “clonal” strains from two different outbreaks to understand variability

    • Identify novel SNPs to be used as markers

    • Technology is complementary to currently used typing schemes


Future directions

Future directions

  • Integration of omics data for drug resistant isolates

    • => Drug resistance and diagnostic arrays

  • Additional genotyping markers

    • Ribosomal monomers

    • Mitochondrial genomes

    • HET genes

    • => Geographic variation and disease phenotypes

  • RNA-Seqsoftware evaluation tool

  • Sequencing of a highly virulent species A. tanneri

  • Development of a system for genetic analysis of A. fumigatus

    • Sequencing of “supermaters”

    • Testing drug resistance SNPs


Acknowledgements

Acknowledgements

  • J. Craig Venter Institute

    • Informatics

      • Natalie FedorovaAbrams

      • Suman Pakala

      • Vinita Joardar

      • NikhatZafar

      • Suchitra Pakala

      • PratapVenepally

      • VenkiMoktali

      • Culture & sample prep

      • Stephanie Maunoud

      • Yan Yu

      • Tatiana Slepushkina

      • Ashlee Dravis

    • IFX, IT, Sequencing Core

  • GSCID directors at JCVI

    • Bill Nierman

    • Karen Nelson

  • Funding: NIAID/NIH

  • Outside collaborators

  • U. of Manchester: David Denning

  • NIAID/NIH: June Kwon-Chung

  • CDC: Arun Balajee

  • U. of Montana: Robb Cramer

  • U. of Georgia: Michelle Momany

  • U. of Tuebingen: JuergenLoeffler

  • U. of Wisconsin: Nancy Keller


Questions

Questions


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