comparing bacterial isolates - t.seemann - imb winter school 2016 - fri 8 jul 2016
TRANSCRIPT
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Comparing bacterial isolates
A/Prof Torsten Seemann
Victorian Life Sciences Computation Initiative (VLSCI)Microbiological Diagnostic Unit Public Health Laboratory (MDU PHL)
Doherty Applied Microbial Genomics (DAMG)The University of Melbourne
IMB Winter School 2016 - Brisbane, AU - Fri 8 Jul 2016
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Introduction
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Doherty Applied Microbial Genomics
Public health & clinical microbial genomics
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The Doherty Institute
∷ Pathogen surveillance∷ Outbreak response
∷ Antimicrobial resistance∷ Virulence mechanisms
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Lots of genomics & transcriptomics
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Bacteria >> Viruses >> Fungi
Foodborne, human (clinical), animal and environmental samples
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Traditional public health and clinical microbiology
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Outbreak pathogen
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Focus on a small “informative” section
Use “marker genes” to genotype.
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Genotype shows isolates are related
Outbreak ?
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D’oh !
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Whole genome sequencing
∷ Use 100% of the genome
∷ Single SNP resolution: Infer source and transmission of infection
∷ Full complement of genes: Track mobile elements and antimicrobial resistance
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Isolating bacteria
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Swab sample onto “starter plate”
Some microbes will grow.Some will not.
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Pick a colony and streak it out
Colony is assumed to be dominated by one organism / species.
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“Pure” colonies grow
Each streak is a dilution
Single progenitor?
Final streaks assumed to be pure
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Sequence an isolate
Hundreds per week
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De novo assembly Align to reference
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The pan genome
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Five genomes
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Whole genome multiple alignment
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Find “common” segments
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The core genome
Core is common to all & has similar sequence.
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The accessory genome
Accessory = not core (but still similar within)
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The pan genome
Pan = Core + Accessory .
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Core
∷ Common DNA∷ Vertical evolution
∷ Critical genes∷ Genotyping∷ Phylogenetics
∷ Novel DNA∷ Lateral transfer
∷ Plasmids∷ Mobile elements∷ Phage
Accessory
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Determining the pan genome
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Whole genome alignment is difficult !
Rearrangements.Sequence divergence.
Duplications.
Does not scale computationally.
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Genome or Gene-ome ?
∷ The DNA sequence of all replicons: Chromosomes, plasmids
∷ The set of “genes” in an organism: “Protein-ome”- just protein coding genes e.g. CDS: “Gene-ome” - also include non-coding genes e.g. RNAs
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Bacteria are coding dense
∷ No introns∷ Overlapping genes∷ Very few intergenic regions
Genome ≈ Proteinome
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Genome vs Proteinome
5 Mbp genome ~5000 genes
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Reframing the problem
Align whole genomes (DNA)
⬇Cluster homologous genes
(DNA or AA)
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Homologs = common ancestor
OrthologSpeciation
Paralog Duplication
XenologLateral transfer
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Homolog clustering
∷ Group homologous proteins together: exploit sequence similarity + synteny + operons: all versus all sequence comparison (not scalable)
■ DNA or amino acid (fast heuristics): difficulty increases with taxa distance
∷ Depends on annotation quality■ Missing genes■ False genes
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∷ De novo assembly - SPAdes
∷ Annotation - Prokka
∷ Pan-genome - Roary
∷ Visualise - Phandango
Typical workflow
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Roary → matrix / spreadsheetCLUSTER STRAIN1 STRAIN2 STRAIN3
00001 DNO1000 EHEC1000 MRSA_1000
00002 DNO1001 EHEC1002 MRSA_1001
00003 DNO1002 EHEC1003 MRSA_1002
00004 DNO1003 EHEC1004 MRSA_1003
00005 DNO1004 EHEC1005 MRSA_1022
: : : :
02314 DNO1005 na MRSA_1023
02315 DNO1451 EHEC3215 na
02316 na EHEC3216 MRSA_1923
: : : :
04197 DNO1456 na na
04198 na EHEC3877 na
04199 na na MRSA_0533
Core
Dispensable
Isolate-specific
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Example pan genome
Rows are genomes, columns are genes.
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Core
Disp.
Disp.
Disp.
UniqueUnique
Unique
Three genomes (N=3)CoreIn all 3 strains (∈ N strains)
DispensableIn 2 strains(∈ [2,N-1] strains)
UniqueIn only 1 strain(∈ 1 strain)
Accessory
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Flowery Venn
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Venn will it end?
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Phylogenomics
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Trees show relationship
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Same tree!
Dendrogram
Spanning
Radial
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Every SNP is sacred
∷ Chocolate bar tree: branches were based on phenotypic attributes: size, colour, filling, texture, ingredients, flavour
∷ Genomic trees: want to use every part of the genome sequence: need to find all differences between isolates: show me the SNPs!
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Finding differences
AGTCTGATTAGCTTAGCTTGTAGCGCTATATTATAGTCTGATTAGCTTAGAT
ATTAGCTTAGATTGTAG
CTTAGATTGTAGC-C
TGATTAGCTTAGATTGTAGC-CTATAT
TAGCTTAGATTGTAGC-CTATATT
TAGATTGTAGC-CTATATTA
TAGATTGTAGC-CTATATTAT
SNP Deletion
Reference
Reads
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bug1 GATTACCAGCATTAAGG-TTCTCCAATCbug2 GAT---CTGCATTATGGATTCTCCATTCbug3 G-TTACCAGCACTAA-------CCAGTC
Collate reference alignments
The reference is a “middle man” to generate a “pseudo” whole genome alignment.
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bug1 GATTACCAGCATTAAGG-TTCTCCAATCbug2 GAT---CTGCATTATGGATTCTCCATTCbug3 G-TTACCAGCACTAA-------CCAGTCcore | | ||||||||| ||||||
Core sites are present in all genomes.
Core genome
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bug1 GATTACCAGCATTAAGG-TTCTCCAATCbug2 GAT---CTGCATTATGGATTCTCCATTCbug3 G-TTACCAGCACTAA-------CCAGTCcore | | ||||||||| ||||||SNPs | | | |
Core SNPS = polymorphic sites in core genome
Core SNPs
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bug1 ATAAbug2 TTTTbug3 ACAG
Infer phylogeny from aligned core SNPs
This is the primary information given to to tree building software.
Neighbour joiningMinimum evolutionMaximum likelihood
Bayesian models
bug2
bug1
bug3
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SNPs | | | |core | | ||||||||| ||||||bug1 GATTACCAGCATTAAGG-TTCTCCAATCbug2 GAT---CTGCATTATGGATTCTCCATTCbug3 G-TTACCAGCACTAA-------CCAGTCcore1 ||| ||||||||||| ||||||||||SNPs1 | | |
Remove taxon, different core (1)
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SNPs | | | |core | | ||||||||| ||||||bug1 GATTACCAGCATTAAGG-TTCTCCAATCbug2 GAT---CTGCATTATGGATTCTCCATTCbug3 G-TTACCAGCACTAA-------CCAGTCcore2 | | ||||||||| ||||||SNPs2 | | | |
Remove taxon, different core (2)
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SNPs | | | |core | | ||||||||| ||||||bug1 GATTACCAGCATTAAGG-TTCTCCAATCbug2 GAT---CTGCATTATGGATTCTCCATTCbug3 G-TTACCAGCACTAA-------CCAGTCcore3 | ||||||||||||| ||||||SNPs3 | |
Remove taxon, different core (3)
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Bringing it all together
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Diagonal-omics
∷ Phylogenetics: Based on core SNPs: Vertical transmission
∷ Pan-genome: Looks at accessory genome: Horizontal transmission
∷ Combine for best of both worlds
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http://jameshadfield.github.io/phandango/
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http://jameshadfield.github.io/phandango/
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Does WGS deliver?
Yes!Bioinformatics Epidemiology
Technology
Microbiology
This meansscientists
not just software
Domain expertise
Always changing...
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The End