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Master Thesis Presentation

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Master Thesis Presentation

  1. 1. Whole Genome Sequencing analysis of an outbreak of Mycobacterium caprae in alpine region affecting both domestic and wildlife animals: molecular epidemiological perspective By Ashok Varadharajan Msc Epidemiology LMU Supervisor Dr. Helmut Blum Laboratory for Functional Genome Analysis Gene Center of the LMU Feodor-Lynen-Strasse 25 81377 Munich
  2. 2. BACKGROUND Tuberculosis An infectious bacterial disease characterized by the growth of nodules (tubercles) in the tissues, especially the lungs. Mycobaterium Tuberculosis Complex (MTC) Genetically related group of Mycobacterium species causing tuberculosis in humans or other organisms  Mycobacterium tuberculosis  Mycobacterium africanum  Mycobacterium bovis  Mycobacterium microti  Mycobacterium canettii  Mycobacterium caprae  Mycobacterium pinnipedii  Mycobacterium suricattae  Mycobacterium mungi tubercl es
  3. 3. BACKGROUND Mycobacterium caprae  Formerly known as M. Tuberculosis subsp. caprae and M. Bovis subsp. caprae  Designated as new species in the MTC in 2003  Predominantly found in Central and Western European countries  Pathogen can affect both animals and Humans  Differentiating Features in MTC  Special combination of polymorphisms in the genes of oxyR , pncA, katG, gyrA and gyrB  Region of Differentiation 4 (RD4)
  4. 4. BACKGROUND Phylogeny of MTC (Rodriguez-Campos et.al, 2014) Differences between M. caprae and M. bovis
  5. 5. PROBLEMS  Increased prevalance of tuberculosis by M. caprae around Alpine regions  Affected in various species such as Cattle, Red deer, Fox and Human  Lack of Knowledge about the transmission of infection between domestic and wildlife animals  Little knowledge about genomic features of M. Caprae concerning markers for genotyping  Lack of Complete genome sequence of M.caprae, complicating the differentiation of M. caprae and M. bovis
  6. 6. OBJECTIVES  Analysis of spatial spread of the disease by Whole Genome Sequencing analysis. 1. Identification of Variants 2. Clustering of isolates 3. Analysis of Infection chain 4. Analysis of RD4 region  Development of Web Integrated Environment 1. Automation of Variant Calling pipeline 2. A tailored database to store the identified variants 3. Real time generation of results such as phylogenetic tree, Minimum Spanning Tree , SNP plot Coverage plot etc
  7. 7. Distribution of sequenced M. caprae isolates Host Number of Isolates Red Deer 95 Cattle 180 Human 3 Schaf 1 Total 279 By host By Location Germany Region Number of Isolates GAP 9 Landshut 3 OA 122 OAL 21 Oldenburg 2 RO 1 TÖÄ 2 UA 7 UAL 4 WM 2 Unknown 15 Austria Region Number of Isolates BH Schwaz 7 Bludenz 18 Bregenz 2 Eranet 12 Kaisers 12 Reutte 15 Vorarlber 1 Zillertal 23 Total 279
  8. 8. WHOLE GENOME SEQUENCING (WGS) Sequencer - Illumina HiSeq 1500 Technique - Paired-End sequencing Coverage - 100x Read Length – 100 – 150 basepairs Principle of WGS Downstream Analysis M. Caprae Genome Library Preparation Sequenced Reads
  9. 9. METHODS - IDENTIFICATION OF VARIANTS Paired End Fastq files Quality Filter Alignment BWA - MEM Removing Duplicates Picard - MarkDuplicates Variant Calling •Samtools - Pileup •VarScan - mpileup2snp SNPs VCF Variant Calling Workflow
  10. 10. METHODS - IDENTIFICATION OF VARIANTS Paired End Fastq files Quality Filter Alignment Removing Duplicates Variant Calling SNPs @HISEQ:55:H80HWADXX:2:1101:1341:2054 1:N:0: GCTCAATTCGAGCCGATGCACCAGGTGTTCCTAGGTGTGCGGT + CCCFFFFFHHHHHJJJJJJJJJJJJHIJJJJJIJJHIIJJJJJ @HISEQ:55:H80HWADXX:2:1101:1259:2056 1:N:0: AGCCTGCTGGTTGCTGGGTCATTGCGCCATGCCTTCGAGAACA + CBCFFFFFHHHHHIJIIJIHIJJIJIJJJJJJJJJJJJIJJJJ @HISEQ:55:H80HWADXX:2:1101:1341:2054 3:N:0: GGGGGATCGACCGCTCCCGGAATTCGGTGGAAGCTGCTGCGGT + CCCFFFFFHHHHHJJJJJJJJJJJJJJJJJJJJJJJJJJJHHD @HISEQ:55:H80HWADXX:2:1101:1259:2056 3:N:0: GGCGAGGGCCGCGTCATTGCGGCGTAGCGTGGACGCGATGTTG + CCCFFFFFHHHHHIIJJJJJJJJJIGHFFFDDDDDDDDDDDDD Identifiers-> Sequence -> Comments -> Quality -> Identifiers-> Sequence -> Comments -> Quality ->
  11. 11. METHODS - IDENTIFICATION OF VARIANTS Paired End Fastq files Quality Filter Alignment Removing Duplicates Variant Calling SNPs
  12. 12. METHODS - IDENTIFICATION OF VARIANTS Paired End Fastq files Quality Filter Alignment Removing Duplicates Variant Calling SNPs Reference Genome Position Mapped Reads Coverage
  13. 13. METHODS - IDENTIFICATION OF VARIANTS Paired End Fastq files Quality Filter Alignment Removing Duplicates Variant Calling SNPs Duplica te Reads
  14. 14. METHODS - IDENTIFICATION OF VARIANTS Paired End Fastq files Quality Filter Alignment Removing Duplicates Variant Calling SNPs SNP Reference Base
  15. 15. METHODS - IDENTIFICATION OF VARIANTS Paired End Fastq files Quality Filter Alignment Removing Duplicates Variant Calling SNPs
  16. 16. METHODS – CLUSTERING OF ISOLATES - Phylogenetic tree can be drawn from custom generated Fasta sequence containing only the identified SNPs - FastTree tool can generate approximately- maximum-likelihood phylogenetic trees Phylogenetic Tree Magnified Version of Constructed tree
  17. 17. METHODS – ANALYSIS OF INFECTION CHAIN Minimum Spanning Tree Algorithm available:  Kruskal's algorithm  Prim's algorithm  reverse-delete algorithm Applications  Taxonomy  Cluster Analysis  Constructing trees for broadcasting in computer networks
  18. 18. METHODS – ANALYSIS OF RD4 REGION OA OA OA OA OA OAL RO GAP GAP GAP GAP OA OA OA OA OA OA
  19. 19. Compare Strains View SNPs SNP plot Phylogenetic Tree Coverage Plot Minimum Spanning Tree WEB INTEGRATED ENVIRONMENT Illumina HiSeq Sequencer Fastq Files Raw Reads Demultiplexi ng Databas e Web Serve r Variant Calling Pipeline Galax y MCDBA Mycobacterium caprae Database and Analysis (MCDBA)
  20. 20. QUESTIONS? ???
  21. 21. THANK YOU

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