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