highly discriminatory diagnostic primer design from whole genome data
TRANSCRIPT
Highly DiscriminatoryDiagnostic Primer DesignFrom Whole Genome Data
Leighton Pritchard1,3,4, Sonia Humphris2,3, Nicola Holden2,3,4 and Ian Toth2,3,4
1Information and Computational Sciences,2Cellular and Molecular Sciences,3Centre for Human and Animal Pathogens in the Environment,4Dundee Effector Consortium,The James Hutton Institute, Invergowrie, Dundee, Scotland, DD2 5DA
Table of Contents
IntroductionThe Insidious Dickeya Menace
Primer DesignStandard qPCR Primer DesignqPCR Primer Design From Whole Genomes
ResultsDickeya Diagnostic Primer PerformanceE. coli Diagnostic Primer PerformancePrimer Design Software
AcknowledgementsWithout Whom. . .
Dickeya spp.
• Dickeya spp.1 are virulent enterobacterial soft-rottingpathogens of ornamental and crop plants
• Eight species now assigned.
• Quarantine organism (zero tolerance in Scotland)
1formerly Erwinia chrysanthemi
Dickeya on crops and ornamentals
2 3
2Landesanst. f. Pflanzenbau und Pflanzenschutz, Mainz Archive
3Florida Division of Plant Industry Archive
Dickeya spp. are a threat in Europe
• D. dianthicola is established across Europe
• D. solani is an emerging, encroaching threat
Why Dickeya qPCR diagnostics?
• To legislate for, or quarantine contaminated materials, onehas to be able to identify the pathogen
• qPCR is still cheaper, quicker and easier than bacterialgenome sequencing (for now, anyway. . . )
• No qPCR primers existed to distinguish among Dickeya spp.
• Having sequenced 25 Dickeya isolates, we were approached todevelop diagnostic primers at the species/isolate level
Table of Contents
IntroductionThe Insidious Dickeya Menace
Primer DesignStandard qPCR Primer DesignqPCR Primer Design From Whole Genomes
ResultsDickeya Diagnostic Primer PerformanceE. coli Diagnostic Primer PerformancePrimer Design Software
AcknowledgementsWithout Whom. . .
qPCR In a Nutshell
Standard qPCR Primer Design
The goal is to identify a region to be amplified that is:
• sufficiently similar in all target organisms to be amplified byyour primer/oligo set
• sufficiently different (or absent) in all off-target organismsthat it is not amplified by your primer/oligo set
This is harder to do manually, the more similar the target andoff-target organismsFrequent choices:
• intergenic transcribed spacers (ITS)
• ribosomal DNA
• “housekeeping” or “virulence” genes
qPCR Primer Design Problems
• Which permutation ofprotocol choice?
• Is amplified regiondiagnostic?
• Are primers/oligos specificin a sample?
• Are primers/oligos efficientacross positives (SNPs)?
A Brute Force Approach
1. Design large numbers of primers to (draft) genomes from thetarget groups
2. Test cross-hybridisation of primer sets in silico against targetand off-target groups
3. Screen primers against broader set of off-target sequences
4. Classify primer sets according to in silico specificity
5. Evaluate specificity against unseen panel of target/off-targetorganisms
qPCR Primer Design: 1
1. If needed, convert drafts to (pseudo)chromosomes andidentify CDS
2. Define target and related off-target groups3. Define classes within target groups
targets
o�-targets
classi�cation
V
IV
III
II
I
genomes
qPCR Primer Design: 2
1. Bulk predict primer sets on all chromosomes (Primer3)2. Design only thermodynamically plausible primers3. Over 1000 primer sets per chromosome
targets
o�-targets
classi�cation
V
IV
III
II
I
genomes
qPCR Primer Design: 3
1. Predict cross-amplification in silico (primersearch)2. Classify primers by cross-amplification profile3. Additional screen against off-target database (BLAST)
targets
o�-targets
classi�cation
V
IV
III
II
I
genomes
IIIIIIIVV
qPCR Primer Design: 4
1. Select diagnostic primer sets2. Evaluate in vitro against panel of previously “unseen” isolates
of known class3. Report performance metrics
targets
o�-targets
classi�cation
V
IV
III
II
I
IIIIIIIVV
primer sets validation gels
III IV V +ve -ve
III IV V +ve -ve
III IV V +ve -ve
III IV V +ve -ve
II
V
I
III
Table of Contents
IntroductionThe Insidious Dickeya Menace
Primer DesignStandard qPCR Primer DesignqPCR Primer Design From Whole Genomes
ResultsDickeya Diagnostic Primer PerformanceE. coli Diagnostic Primer PerformancePrimer Design Software
AcknowledgementsWithout Whom. . .
Dickeya primer evaluation
Primers designed to 29 sequenced Dickeya isolatesEvaluated against panel of 70 unseen isolates100% sensitivity; 0-4% FDR 4
4Pritchard et al. (2013) Plant Path. 62: 587-596. doi:10.1111/j.1365-3059.2012.02678.x
E. coli diagnostic primers
• Summer 2011, E. coli EHEC O104:H4 outbreak• Unprecedented scale: 3950 affected, 53 deaths• Rapid production of sequence data, crowd-sourcing5
6
5https://github.com/ehec-outbreak-crowdsourced/BGI-data-analysis/wiki
6Kwan et al. (2011) http://precedings.nature.com/documents/6663/version/1
E. coli primer evaluation
• Primers designed to nine crowdsourced draft outbreak E. coliO104:H4 assemblies
• 21 clinical outbreak, 32 HUSEC/EPEC isolates• Combined primers specific at sub-serotype level
100% sensitivity, 9-22% FDR for individual primers; 100% specificity and sensitivity for paired primers 7
7Pritchard et al. (2012) PLoS One 7: e34498. doi:10.1371/journal.pone.0034498
find differential primers.py
• Software freely available at GitHub8
• Installs as Python script, takes config file, and runs fromcommand-line (or Makefile)
8https://github.com/widdowquinn/find_differential_primers
Table of Contents
IntroductionThe Insidious Dickeya Menace
Primer DesignStandard qPCR Primer DesignqPCR Primer Design From Whole Genomes
ResultsDickeya Diagnostic Primer PerformanceE. coli Diagnostic Primer PerformancePrimer Design Software
AcknowledgementsWithout Whom. . .
Acknowledgements
James Hutton InstituteNicola HoldenSonia HumphrisIan TothEmma CampbellGitHubBenjamin LeopoldMichael Robeson
FERAValerie BertrandJohn ElphinstoneNeil ParkinsonSASAGerry SaddlerUniversity of MunsterMartina BielaszewskaHelge Karch