This document discusses a presentation on plant-pathogenic bacteria by Leighton Pritchard from The James Hutton Institute. The presentation covers several topics: 1) An introduction to The James Hutton Institute and its work on plant-pathogen interactions like soft-rot enterobacteria. 2) Genomics research including the first sequenced genome of a soft-rot enterobacterium in 2003 and subsequent sequencing of 25 Dickeya genomes in 2013. 3) Classification and diagnostics challenges around legislating by bacterial taxonomy when taxonomy is uncertain and mapping taxonomy to phenotypes is complex. Problems with existing classification and consequences of misclassification are discussed.

1. Little Rotters
Adventures with Plant-Pathogenic Bacteria
Leighton Pritchard1,2,3
1
Information and Computational Sciences,
2
Centre for Human and Animal Pathogens in the Environment,
3
Dundee Effector Consortium,
The James Hutton Institute, Invergowrie, Dundee, Scotland, DD2 5DA

2. Acceptable Use Policy
Recording of this talk, taking photos, discussing the content using
email, Twitter, blogs, etc. is permitted (and encouraged),
providing distraction to others is minimised.
These slides will be made available at
http://www.slideshare.net/leightonp

3. Table of Contents
1 Introduction
Hey, Hey We’re The James Hutton Institute!
The Tangled Taxonomy of Soft-Rot Enterobacteria
The Insidious Dickeya Menace
2 Genomics
The £250k Genome
25 Dickeya Genomes
3 Classification and Diagnostics
Diagnosis: Plant Murder I
ANI Are You OK? Are You OK ANI?
Diagnosis: Plant Murder II
4 Systems Biology
Plant Pathology’s Next Top Model?
5 Synthetic Biology
From Food (Waste) To Fuel
6 Acknowledgements

4. The James Hutton Institute

5. The James Hutton Institute
Formed in 2011 by merger
Scottish Crop Research Institute (Dundee)
Macaulay Land Use Research Institute (Aberdeen)
Comprises Biomathematics and Statistics Scotland (BioSS)
Hosts University of Dundee Division of Plant Sciences
http://www.hutton.ac.uk/

6. The James Hutton Institute
Mission
To deliver the highest quality integrated and innovative science
that contributes knowledge, products and services to meet the
multiple demands on land and natural resources.
Food security
Societal and agricultural impact
Extensive burden/cost (P. infestans ≈e1bn in Europe)
Emerging pathogens (imports, climate change)
Environmental sustainability
Pesticide minimisation and withdrawal
Durable resistance via breeding (and/or GM)

7. Plant-Pathogen Interactions (potato)
Phytophthora
infestans/oomycetes & fungi
Myzus persicae/aphids
Erwinia, Dickeya,
Pectobacterium spp./Bacteria
PCN/nematodes

8. Table of Contents
1 Introduction
Hey, Hey We’re The James Hutton Institute!
The Tangled Taxonomy of Soft-Rot Enterobacteria
The Insidious Dickeya Menace
2 Genomics
The £250k Genome
25 Dickeya Genomes
3 Classification and Diagnostics
Diagnosis: Plant Murder I
ANI Are You OK? Are You OK ANI?
Diagnosis: Plant Murder II
4 Systems Biology
Plant Pathology’s Next Top Model?
5 Synthetic Biology
From Food (Waste) To Fuel
6 Acknowledgements

9. Soft-Rot Enterobacteria (SRE) a
a
Toth et al. (2006) Annu. Rev. Phytopath. doi:10.1146/annurev.phyto.44.070505.143444
Erwinia, Dickeya and Pectobacterium spp.
Plant Cell Wall Degrading Enzymes (PCWDEs)

10. Tangled Taxonomy of SRE a b
a
Pritchard et al. (2016) Anal. Methods doi:10.1039/c5ay02550h
b
Williams et al. (2010) J. Bact. doi:10.1128/JB.01480-09
Gammaproteobacteria, Enterobacteria taxonomy difficult to
resolve, in general
Historical classification mostly polyphasic/phenotypic
Soft rot enterobacteria (SRE) all originally Erwinia spp.
SRE now three distinct genera (Dickeya, Pectobacterium,
Erwinia)
Pectobacterium used to be E. chrysanthemi
Dickeya used to be P. chrysanthemi
Old names hold over in the literature, collections, etc.

11. Tangled Taxonomy of SREa
a
Czajkowski et al. (2015) Ann. Appl. Biol. doi:10.1111/aab.12166

12. Table of Contents
1 Introduction
Hey, Hey We’re The James Hutton Institute!
The Tangled Taxonomy of Soft-Rot Enterobacteria
The Insidious Dickeya Menace
2 Genomics
The £250k Genome
25 Dickeya Genomes
3 Classification and Diagnostics
Diagnosis: Plant Murder I
ANI Are You OK? Are You OK ANI?
Diagnosis: Plant Murder II
4 Systems Biology
Plant Pathology’s Next Top Model?
5 Synthetic Biology
From Food (Waste) To Fuel
6 Acknowledgements

13. Dickeya spp. moving across Europeab
a
Toth et al. (2011) Plant Path. doi:10.1111/j.1365-3059.2011.02427.x
b
Parkinson et al. (2015) Eur. J. Plant Path. doi:10.1007/s10658-014-0523-5
D. dianthicola is established across Europe
D. solani is an emerging, encroaching threat

14. Legislationa
a
Pritchard et al. (2016) Anal. Methods doi:10.1039/c5ay02550h
European and Mediterranean Plant Protection Organisation
(EPPO)
Member states should regulate D. dianthicola and E. amylovora as
quarantine pests (A2 list)
Seed Potatoes (Scotland) Amendment Regulations (2010)
Zero tolerance policy for all Dickeya spp. on potatoes in Scotland
to ensure production of ‘clean’ (disease-free) seed potato
production for export
: EUPHRESCO consortium: control and epidemiology

15. Scottish Government Controlsa
a
http://www.gov.scot/Topics/farmingrural/Agriculture/plant/18273/PotatoHealthControls/
PotatoQuarantineDiseases/Dickeya
No positive tests for D. solani since 2010

16. Table of Contents
1 Introduction
Hey, Hey We’re The James Hutton Institute!
The Tangled Taxonomy of Soft-Rot Enterobacteria
The Insidious Dickeya Menace
2 Genomics
The £250k Genome
25 Dickeya Genomes
3 Classification and Diagnostics
Diagnosis: Plant Murder I
ANI Are You OK? Are You OK ANI?
Diagnosis: Plant Murder II
4 Systems Biology
Plant Pathology’s Next Top Model?
5 Synthetic Biology
From Food (Waste) To Fuel
6 Acknowledgements

17. 2003: E. carotovora SCRI1043 a
a
Bell et al. (2004) Proc. Natl. Acad. Sci. USA doi:10.1073/pnas.0402424101
£250k collaboration between SCRI, University of
Cambridge, WT Sanger Institute
Single isolate: E. carotovora subsp. atroseptica SCRI1043
The first sequenced enterobacterial plant pathogen (32
authors!)
All repeats and gaps bridged and sequenced directly
Result: a single, complete, high-quality 5Mbp circular
chromosome at 10.2X coverage: 106,500 reads

18. 2003: E. carotovora subsp. atroseptica
Compared against all 142 available bacterial genomes

19. GenomeDiagram/SciArt a b c
a
Pritchard et al. (2006) Bioinformatics doi:10.1093/bioinformatics/btk021
b
Shemilt (2009) in“Digital Visual Culture: Theory and Practice” ISBN 978-1-84150-248-9
c
Shemilt (2010) in “Art Practice in a Digital Culture”, ISBN 978-0-7546-7623-2
Influence
Free open-source comparative
genomics visualisation library
Impact
Artwork (prints, audio-visual
installation) exhibited in UK and
internationally

20. Functional adaptation in Pbaa
a
Toth et al. (2006) Ann. Rev. Phytopath. doi:10.1146/annurev.phyto.44.070505.143444

21. Functional adaptation in Pbaa
a
Toth et al. (2006) Ann. Rev. Phytopath. doi:10.1146/annurev.phyto.44.070505.143444

22. Table of Contents
1 Introduction
Hey, Hey We’re The James Hutton Institute!
The Tangled Taxonomy of Soft-Rot Enterobacteria
The Insidious Dickeya Menace
2 Genomics
The £250k Genome
25 Dickeya Genomes
3 Classification and Diagnostics
Diagnosis: Plant Murder I
ANI Are You OK? Are You OK ANI?
Diagnosis: Plant Murder II
4 Systems Biology
Plant Pathology’s Next Top Model?
5 Synthetic Biology
From Food (Waste) To Fuel
6 Acknowledgements

23. 2013: Dickeya spp. a b
a
Pritchard et al. (2013) Genome Ann. 1 (4) doi:10.1128/genomeA.00087-12
b
Pritchard et al. (2013) Genome Ann. 1 (6) doi:10.1128/genomeA.00978-13
Sequenced and annotated 25 new isolates of Dickeya
25 Dickeya isolates, at least six species
Multiple sequencing methods: 454, Illumina (SE, PE)
Minor publications (6, 8 authors)
Results: 12-237 fragments containing 4.2-5.1Mbp, at 6-84X
coverage, 170k-4m reads
Automated annotation Initially RAST with manual
correction

24. 2013: Dickeya spp.
Within-genus comparisons: large-scale synteny and rearrangement
Within-species comparisons: e.g. indels, HGT

25. Pangenome
Species Weak prune Strong prune
Core 2201 2201
D. chrysanthemi 32 36
D. dadantii 11 14
D. dianthicola 102 127
D. paradisiaca 404 441
D. solani 120 157
D. zeae 33 40
Accessory: RBBH only with all other members
of same species
Weak: All RBBH < 80% ID, 40% coverage
Strong: Trim complete graph by Mahalanobis
distance until minimal cliques found

26. 2013: Dickeya spp. a
a
van der Wolf et al. (2014) Int. J. Syst. Evol. Micr. 64:768-774 doi:10.1099/ijs.0.052944-0
Within-genus comparisons: whole genome-based species
delineation

27. Table of Contents
1 Introduction
Hey, Hey We’re The James Hutton Institute!
The Tangled Taxonomy of Soft-Rot Enterobacteria
The Insidious Dickeya Menace
2 Genomics
The £250k Genome
25 Dickeya Genomes
3 Classification and Diagnostics
Diagnosis: Plant Murder I
ANI Are You OK? Are You OK ANI?
Diagnosis: Plant Murder II
4 Systems Biology
Plant Pathology’s Next Top Model?
5 Synthetic Biology
From Food (Waste) To Fuel
6 Acknowledgements

28. Introduction of D. dianthicola a
a
Parkinson et al. (2015) Eur. J. Plant Pathol. doi:10.1007/s10658-014-0523-5
VNTR identified from genomes used to trace D. dianthicola
introduction through historical isolates of ornamentals; potato

29. VNTR Minimum Spanning Tree a
a
Parkinson et al. (2015) Eur. J. Plant Pathol. doi:10.1007/s10658-014-0523-5
Central nodes associated with: older, ornamental accessions.
Distal nodes associated with: recent, potato accessions.

30. Ddi introduction through ornamentals
Earliest (1957) strains already show VNTR diversity
No recorded Dickeya potato infection until 1975
Greater VNTR diversity on ornamentals than potato
Ornamental to potato cross-infection supported by three
VNTR profiles in both host types
Ornamental plants likely provided a route for introduction of
the broad host range pathogen Dickeya to EU potato crops.
There is strict prohibition and regulation of potato import into
the EU; there is not equivalent regulation of ornamental
imports

31. Legislation by taxonomy a
a
Pritchard et al. (2016) Anal. Methods doi:10.1039/c5ay02550h
European and Mediterranean Plant Protection Organisation
(EPPO)
Member states should regulate D. dianthicola and E. amylovora as
quarantine pests (A2 list)
Why legislate by taxonomy?
“Easy” to incorporate into legislation: binary (yes/no)
classification
Assumption: taxonomy can be determined precisely
Assumption: taxonomy is a proxy for disease risk
Those assumptions do not necessarily hold

32. Problems a b c
a
Pritchard et al. (2016) Anal. Methods doi:10.1039/c5ay02550h
b
Toth et al. (2006) Ann. Rev. Phyto. doi:10.1146/annurev.phyto.44.070505.143444
c
Deans et al. (2015) PLoS Biol. doi:10.1371/journal.pbio.1002033
Is existing bacterial taxonomy/nomenclature correct?
Is a species concept even relevant for bacteria?
Taxonomy is ‘vertical’, but pathogenicity may be ‘laterally’
transferred (plasmid-borne, etc.)
Mapping from taxonomy to phenotype is not one-to-one
Testing for disease phenotypes not straightforward
Relationship between gene complement and disease not fully
understood

33. Brute Force Primer Design
1 Design large numbers of primers to (draft) genomes from the
target groups
2 Test cross-hybridisation of primer sets in silico against target
and 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-target
organisms

34. qPCR Primer Design: 1
1 If needed, convert drafts to (pseudo)chromosomes and
identify CDS
2 Define target and related off-target groups
3 Define classes within target groups
targets
off-targets
classification
V
IV
III
II
I
genomes

35. qPCR Primer Design: 2
1 Bulk predict primer sets on all chromosomes (Primer3)
2 Design only thermodynamically plausible primers
3 Over 1000 primer sets per chromosome
targets
off-targets
classification
V
IV
III
II
I
genomes

36. qPCR Primer Design: 3
1 Predict cross-amplification in silico (primersearch)
2 Classify primers by cross-amplification profile
3 Additional screen against off-target database (BLAST)
targets
off-targets
classification
V
IV
III
II
I
genomes
I
II
III
IV
V

37. qPCR Primer Design: 4
1 Select diagnostic primer sets
2 Evaluate in vitro against panel of previously “unseen” isolates
of known class
3 Report performance metrics
targets
off-targets
classification
V
IV
III
II
I
I
II
III
IV
V
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

38. Classification is a problem! a
a
Pritchard et al. (2013) Plant Path. doi:10.1111/j.1365-3059.2012.02678.x
qPCR design gave no diagnostic primers for several species.
Misassigned species in GenBank made ‘training’ impossible.
1
1
ML tree, recA

39. Consequences of misclassification a b
a
Pritchard et al. (2016) Anal. Methods doi:10.1039/c5ay02550h
b
Varghese et al. (2015) Nucl. Acids Res. doi:10.1093/nar/gkv657
Failed classification has real-world consequences:
False positives (type I errors):
clean samples rejected: economic cost
farms quarantined/close: economic/societal cost
False negatives (type II errors):
(irreversible) introduction of infectious material
potential for novel host jumps and spread
“Gold-standard”, correctly classified training and test sets essential
to estimate classifier error rates.
MiSI: 18% of NCBI genomes: bacterial species misclassified

40. Table of Contents
1 Introduction
Hey, Hey We’re The James Hutton Institute!
The Tangled Taxonomy of Soft-Rot Enterobacteria
The Insidious Dickeya Menace
2 Genomics
The £250k Genome
25 Dickeya Genomes
3 Classification and Diagnostics
Diagnosis: Plant Murder I
ANI Are You OK? Are You OK ANI?
Diagnosis: Plant Murder II
4 Systems Biology
Plant Pathology’s Next Top Model?
5 Synthetic Biology
From Food (Waste) To Fuel
6 Acknowledgements

41. DNA-DNA hybridisation a b
a
Morello-Mora and Amann (2001) FEMS Micro. Rev. doi:10.1016/S0168-6445(00)00040-1
b
Chan et al (2012) BMC Microbiol. doi:10.1186/1471-2180-12-302
“Gold Standard” for
prokaryotic taxonomy,
since 1960s. “70%
identity ≈ same species.”
Denature DNA from two
organisms.
Allow to anneal.
Reassociation ≈ similarity,
measured as ∆T of
denaturation curves.
Proxy for sequence similarity - replace with genome analysis?

42. Average Nucleotide Identity (ANIm) a
a
Richter and Rossello-Mora (2009) Proc. Natl. Acad. Sci. USA doi:10.1073/pnas.0906412106
1. Align genomes
(MUMmer)
2. ANIm: Mean
% identity of all
matches
DDH:ANIm
linear
70%ID ≈
95%ANIm

43. ANIm
Average identity of all ‘homologous’ regions
Approximates a limiting case of MLST/MLSA/multigene
comparisons
Straightforward principle
Classification not dependent on dataset composition (unlike
tree methods)

44. D. solani ANIm a
a
van der Wolf et al. (2014) Int. J. Syst. Evol. Micr. doi:10.1099/ijs.0.052944-0
Defining D. solani as a new species, with ANIm:

45. 34 Dickeya spp. ANIm a
a
Pritchard et al. (2016) Anal. Methods doi:10.1039/c5ay02550h
Nine
species-level
groups (two
novel)
Three species
misidentified
in GenBank
Dickeya_solani_GBBC2040
Dickeya_solani_IPO2222
Dickeya_solani_MK10
Dickeya_solani_MK16
Dickeya_solani_AMYI01
Dickeya_solani_AMWE01
Dickeya_dianthicola_NCPPB_3534
Dickeya_dianthicola_GBBC2039
Dickeya_dianthicola_NCPPB_453
Dickeya_dianthicola_IPO980
Dickeya_spp_NCPPB_3274
Dickeya_spp_MK7
Dickeya_dadantii_NCPPB_2976
Dickeya_dadantii_3937_uid52537
Dickeya_dadantii_NCPPB_3537
Dickeya_dadantii_NCPPB_898
Dickeya_zeae_APMV01
Dickeya_zeae_AJVN01
Dickeya_zeae_NCPPB_3531
Dickeya_zeae_CSL_RW192
Dickeya_dadantii_Ech586_uid42519
Dickeya_zeae_APWM01
Dickeya_zeae_MK19
Dickeya_zeae_NCPPB_3532
Dickeya_zeae_NCPPB_2538
Dickeya_spp_NCPPB_569
Dickeya_chrysanthami_NCPPB_402
Dickeya_chrysanthami_NCPPB_516
Dickeya_zeae_Ech1591_uid59297
Dickeya_chrysanthami_NCPPB_3533
Dickeya_aquatica_DW_0440
Dickeya_aquatica_CSL_RW240
Dickeya_dadantii_Ech703_uid59363
Dickeya_paradisiaca_NCPPB_2511
Dickeya_solani_GBBC2040
Dickeya_solani_IPO2222
Dickeya_solani_MK10
Dickeya_solani_MK16
Dickeya_solani_AMYI01
Dickeya_solani_AMWE01
Dickeya_dianthicola_NCPPB_3534
Dickeya_dianthicola_GBBC2039
Dickeya_dianthicola_NCPPB_453
Dickeya_dianthicola_IPO980
Dickeya_spp_NCPPB_3274
Dickeya_spp_MK7
Dickeya_dadantii_NCPPB_2976
Dickeya_dadantii_3937_uid52537
Dickeya_dadantii_NCPPB_3537
Dickeya_dadantii_NCPPB_898
Dickeya_zeae_APMV01
Dickeya_zeae_AJVN01
Dickeya_zeae_NCPPB_3531
Dickeya_zeae_CSL_RW192
Dickeya_dadantii_Ech586_uid42519
Dickeya_zeae_APWM01
Dickeya_zeae_MK19
Dickeya_zeae_NCPPB_3532
Dickeya_zeae_NCPPB_2538
Dickeya_spp_NCPPB_569
Dickeya_chrysanthami_NCPPB_402
Dickeya_chrysanthami_NCPPB_516
Dickeya_zeae_Ech1591_uid59297
Dickeya_chrysanthami_NCPPB_3533
Dickeya_aquatica_DW_0440
Dickeya_aquatica_CSL_RW240
Dickeya_dadantii_Ech703_uid59363
Dickeya_paradisiaca_NCPPB_2511
0.00
0.25
0.50
0.75
1.00
ANIm_percentage_identity

46. 55 Pectobacterium spp. ANIm a
a
Pritchard et al. (2016) Anal. Methods doi:10.1039/c5ay02550h
Ten
species-level
groups (four
novel)
P. carotovorum
split: several
species
P. wasabiae
split: two
species
P. atrosepticum SCRI1043
P. atrosepticum NCPPB 3404
P. atrosepticum JG10­08
P. atrosepticum 21A
P. atrosepticum CFBP 6276
P. atrosepticum NCPPB 549
P. atrosepticum ICMP 1526
P. carotovorum PC1
P. carotovorum UGC32
P. betavasculorum NCPPB 2793
P. betavasculorum NCPPB 2795
P. carotovorum M022
P. wasabiae CFBP 3304
P. wasabiae NCPPB 3701
P. wasabiae NCPPB3702
P. wasabiae CFIA1002
P. wasabiae WPP163
P. wasabiae RNS08.42.1A
P. sp. SCC3193 SCC3193
P. carotovorum BC D6
P. carotovorum YC D49
P. carotovorum BC S2
P. carotovorum YC D29
P. carotovorum YC D65
P. carotovorum CFIA1001
P. carotovorum PCC21
P. carotovorum YC D46
P. carotovorum YC T31
P. carotovorum YC D62
P. carotovorum YC T3
P. carotovorum CFIA1009
P. carotovorum YC D52
P. carotovorum YC D21
P. carotovorum YC D64
P. carotovorum YC D60
P. carotovorum CFIA1033
P. carotovorum PBR1692
P. carotovorum LMG 21371
P. carotovorum BD255
P. carotovorum ICMP 19477
P. carotovorum LMG 21372
P. carotovorum KKH3
P. carotovorum NCPPB3841
P. carotovorum NCPPB 3839
P. carotovorum BC S7
P. carotovorum YC T1
P. carotovorum NCPPB 3395
P. carotovorum YC D57
P. carotovorum BC T2
P. carotovorum ICMP 5702
P. carotovorum NCPPB 312
P. carotovorum YC D16
P. carotovorum YC T39
P. carotovorum WPP14
P. carotovorum BC T5
P. atrosepticum SCRI1043
P. atrosepticum NCPPB 3404
P. atrosepticum JG10­08
P. atrosepticum 21A
P. atrosepticum CFBP 6276
P. atrosepticum NCPPB 549
P. atrosepticum ICMP 1526
P. carotovorum PC1
P. carotovorum UGC32
P. betavasculorum NCPPB 2793
P. betavasculorum NCPPB 2795
P. carotovorum M022
P. wasabiae CFBP 3304
P. wasabiae NCPPB 3701
P. wasabiae NCPPB3702
P. wasabiae CFIA1002
P. wasabiae WPP163
P. wasabiae RNS08.42.1A
P. sp. SCC3193 SCC3193
P. carotovorum BC D6
P. carotovorum YC D49
P. carotovorum BC S2
P. carotovorum YC D29
P. carotovorum YC D65
P. carotovorum CFIA1001
P. carotovorum PCC21
P. carotovorum YC D46
P. carotovorum YC T31
P. carotovorum YC D62
P. carotovorum YC T3
P. carotovorum CFIA1009
P. carotovorum YC D52
P. carotovorum YC D21
P. carotovorum YC D64
P. carotovorum YC D60
P. carotovorum CFIA1033
P. carotovorum PBR1692
P. carotovorum LMG 21371
P. carotovorum BD255
P. carotovorum ICMP 19477
P. carotovorum LMG 21372
P. carotovorum KKH3
P. carotovorum NCPPB3841
P. carotovorum NCPPB 3839
P. carotovorum BC S7
P. carotovorum YC T1
P. carotovorum NCPPB 3395
P. carotovorum YC D57
P. carotovorum BC T2
P. carotovorum ICMP 5702
P. carotovorum NCPPB 312
P. carotovorum YC D16
P. carotovorum YC T39
P. carotovorum WPP14
P. carotovorum BC T5
0.00
0.25
0.50
0.75
1.00
ANIm_percentage_identity

47. Criticisms of ANIma
a
Pritchard et al. (2016) Anal. Methods doi:10.1039/c5ay02550h
95% threshold ‘arbitrary’
Taxonomic classification, not phylogenetic reconstruction
No functional (or gene-based) interpretation: still need
pangenome classification and analysis
Only considers ‘homologous’ regions:
Define ‘homologous’
misled by HGT/LGT?
misled by distant relationships/low extent of homology?
Coverage plots help interpretation: exclude HGT/LGT low
homology bias.

48. 55 Pectobacterium spp. ANIma
a
Pritchard et al. (2016) Anal. Methods doi:10.1039/c5ay02550h
All isolates
align over
>50% of
whole
genome
P. carotovorum YC T31
P. carotovorum YC D21
P. carotovorum YC T3
P. carotovorum CFIA1009
P. carotovorum YC D64
P. carotovorum YC D52
P. carotovorum YC D62
P. carotovorum YC D60
P. carotovorum YC D49
P. carotovorum BC D6
P. carotovorum YC D65
P. carotovorum YC D46
P. carotovorum BC S2
P. carotovorum YC D29
P. carotovorum PCC21
P. carotovorum CFIA1001
P. carotovorum YC T1
P. carotovorum NCPPB 3395
P. carotovorum UGC32
P. carotovorum KKH3
P. carotovorum BC S7
P. carotovorum ICMP 5702
P. carotovorum NCPPB 312
P. carotovorum BC T2
P. carotovorum YC D16
P. carotovorum YC T39
P. carotovorum YC D57
P. carotovorum WPP14
P. carotovorum BC T5
P. carotovorum CFIA1033
P. carotovorum PC1
P. carotovorum LMG 21371
P. carotovorum BD255
P. carotovorum PBR1692
P. carotovorum ICMP 19477
P. carotovorum LMG 21372
P. wasabiae CFBP 3304
P. wasabiae NCPPB 3701
P. wasabiae NCPPB3702
P. sp. SCC3193 SCC3193
P. wasabiae WPP163
P. wasabiae RNS08.42.1A
P. wasabiae CFIA1002
P. atrosepticum CFBP 6276
P. atrosepticum NCPPB 3404
P. atrosepticum NCPPB 549
P. atrosepticum ICMP 1526
P. atrosepticum SCRI1043
P. atrosepticum JG10­08
P. atrosepticum 21A
P. carotovorum NCPPB3841
P. carotovorum NCPPB 3839
P. carotovorum M022
P. betavasculorum NCPPB 2793
P. betavasculorum NCPPB 2795
P. carotovorum M022
P. carotovorum YC T1
P. carotovorum KKH3
P. carotovorum UGC32
P. carotovorum CFIA1033
P. carotovorum NCPPB3841
P. carotovorum NCPPB 3839
P. carotovorum BC S7
P. carotovorum ICMP 19477
P. carotovorum BD255
P. carotovorum LMG 21372
P. carotovorum PBR1692
P. carotovorum LMG 21371
P. carotovorum PC1
P. carotovorum ICMP 5702
P. carotovorum NCPPB 312
P. carotovorum YC D57
P. carotovorum BC T2
P. carotovorum YC D16
P. carotovorum WPP14
P. carotovorum BC T5
P. carotovorum YC D62
P. carotovorum YC T31
P. carotovorum YC D52
P. carotovorum YC T3
P. carotovorum YC D64
P. carotovorum YC D21
P. carotovorum YC D60
P. carotovorum YC T39
P. carotovorum CFIA1001
P. carotovorum YC D46
P. carotovorum YC D49
P. carotovorum BC D6
P. carotovorum YC D65
P. carotovorum BC S2
P. carotovorum YC D29
P. carotovorum PCC21
P. carotovorum CFIA1009
P. atrosepticum ICMP 1526
P. atrosepticum CFBP 6276
P. atrosepticum SCRI1043
P. atrosepticum NCPPB 3404
P. atrosepticum NCPPB 549
P. atrosepticum JG10­08
P. atrosepticum 21A
P. wasabiae WPP163
P. sp. SCC3193 SCC3193
P. wasabiae RNS08.42.1A
P. wasabiae CFIA1002
P. wasabiae CFBP 3304
P. wasabiae NCPPB 3701
P. wasabiae NCPPB3702
P. carotovorum NCPPB 3395
P. betavasculorum NCPPB 2793
P. betavasculorum NCPPB 2795
0.00
0.25
0.50
0.75
1.00
ANIm_alignment_coverage

49. 34 Dickeya spp. ANIma
a
Pritchard et al. (2016) Anal. Methods doi:10.1039/c5ay02550h
Most isolates
align over
>50% of
whole
genome
Community:
two outlier
species are
questionable
assignments
Dickeya_dadantii_Ech703_uid59363
Dickeya_paradisiaca_NCPPB_2511
Dickeya_aquatica_DW_0440
Dickeya_aquatica_CSL_RW240
Dickeya_solani_MK10
Dickeya_solani_AMYI01
Dickeya_solani_AMWE01
Dickeya_solani_MK16
Dickeya_solani_GBBC2040
Dickeya_solani_IPO2222
Dickeya_dianthicola_NCPPB_453
Dickeya_dianthicola_GBBC2039
Dickeya_dianthicola_IPO980
Dickeya_dianthicola_NCPPB_3534
Dickeya_dadantii_NCPPB_2976
Dickeya_dadantii_3937_uid52537
Dickeya_spp_NCPPB_3274
Dickeya_spp_MK7
Dickeya_dadantii_NCPPB_3537
Dickeya_dadantii_NCPPB_898
Dickeya_zeae_APMV01
Dickeya_zeae_AJVN01
Dickeya_zeae_APWM01
Dickeya_dadantii_Ech586_uid42519
Dickeya_zeae_CSL_RW192
Dickeya_zeae_NCPPB_3532
Dickeya_zeae_NCPPB_2538
Dickeya_zeae_NCPPB_3531
Dickeya_zeae_MK19
Dickeya_spp_NCPPB_569
Dickeya_chrysanthami_NCPPB_402
Dickeya_chrysanthami_NCPPB_516
Dickeya_zeae_Ech1591_uid59297
Dickeya_chrysanthami_NCPPB_3533
Dickeya_dadantii_Ech703_uid59363
Dickeya_paradisiaca_NCPPB_2511
Dickeya_aquatica_DW_0440
Dickeya_aquatica_CSL_RW240
Dickeya_dianthicola_GBBC2039
Dickeya_dianthicola_NCPPB_3534
Dickeya_dianthicola_NCPPB_453
Dickeya_dianthicola_IPO980
Dickeya_solani_GBBC2040
Dickeya_solani_IPO2222
Dickeya_solani_MK10
Dickeya_solani_MK16
Dickeya_solani_AMYI01
Dickeya_solani_AMWE01
Dickeya_dadantii_NCPPB_3537
Dickeya_dadantii_NCPPB_898
Dickeya_spp_NCPPB_3274
Dickeya_spp_MK7
Dickeya_dadantii_NCPPB_2976
Dickeya_dadantii_3937_uid52537
Dickeya_zeae_APMV01
Dickeya_zeae_AJVN01
Dickeya_dadantii_Ech586_uid42519
Dickeya_zeae_APWM01
Dickeya_zeae_MK19
Dickeya_zeae_NCPPB_3532
Dickeya_zeae_NCPPB_2538
Dickeya_zeae_NCPPB_3531
Dickeya_zeae_CSL_RW192
Dickeya_spp_NCPPB_569
Dickeya_zeae_Ech1591_uid59297
Dickeya_chrysanthami_NCPPB_3533
Dickeya_chrysanthami_NCPPB_402
Dickeya_chrysanthami_NCPPB_516
0.00
0.25
0.50
0.75
1.00
ANIm_alignment_coverage

50. 34 Dickeya spp. ANIma
a
Pritchard et al. (2016) Anal. Methods doi:10.1039/c5ay02550h
Combine
identity and
coverage in a
single
(Hadamard)
measure.
None
None
GCF_000365305.1_DDI453_v1.0_genomic
GCF_000975305.1_DdRNS04.9V1.0_genomic
GCF_000430955.1_DDIIPO980_1.0_genomic
GCF_000365405.1_DDI3534_1.0_genomic
GCF_000365405.2_DDI3534_1.0_genomic
GCF_000406085.1_DXXRW240_1.0_genomic
GCF_000365365.1_DDIGBBC2039_1.0_genomic
GCF_001401705.1_Dsl_1.0_genomic
GCF_000831935.1_ASM83193v1_genomic
GCF_000365285.1_DSOMK10_1.0_genomic
GCF_001644705.1_ASM164470v1_genomic
GCF_000474655.1_Dickeya1.0_genomic
GCF_000511285.1_SSPACE_genomic
GCF_001417915.1_Dsl_1.0_genomic
GCF_000365345.1_DSOMK16_1.0_genomic
GCF_001401695.1_Dsl_1.0_genomic
GCF_001506125.1_ASM150612v1_genomic
GCF_000400565.1_DSOGBBC2040_1.0_genomic
GCF_000400795.1_DSOIPO2222_1.0_genomic
GCF_000406265.1_DDA3537_1.0_genomic
GCF_000406145.1_DDA898_1.0_genomic
GCF_000147055.1_ASM14705v1_genomic
GCF_000406185.1_DDA2976_1.0_genomic
GCF_000784735.1_ASM78473v1_genomic
GCF_000406205.1_DXX3274_1.0_genomic
GCF_001187965.1_ASM118796v1_genomic
GCF_000406305.1_DXXMK7_1.0_genomic
GCF_001187975.1_ASM118797v1_genomic
GCF_000774065.1_ASM77406v1_genomic
GCF_000803195.1_ASM80319v1_genomic
GCF_000404105.1_DiZe_1.0_genomic
GCF_000264075.1_ASM26407v1_genomic
GCF_000816045.1_ASM81604v1_genomic
GCF_000406045.1_DZERW192_1.0_genomic
GCF_000406225.1_DZE3531_1.0_genomic
GCF_000025065.1_ASM2506v1_genomic
GCF_000400525.1_DZE3532_1.0_genomic
GCF_000406165.1_DZE2538_1.0_genomic
GCF_000406325.1_DZEMK19_1.0_genomic
GCF_000382585.1_DiZ_MS1_genomic
GCF_000406125.1_DXY569_1.0_genomic
GCF_000406105.1_DCH402_1.0_genomic
GCF_000406245.1_DCH3533_1.0_genomic
GCF_000023565.1_ASM2356v1_genomic
GCF_000784725.1_ASM78472v1_genomic
GCF_000406065.1_DCH516_1.0_genomic
GCF_000400505.1_DPA2511_1.0_genomic
GCF_000023545.1_ASM2354v1_genomic
GCA_000406085.2_ASM40608v2_genomic
GCF_000406285.1_DXXDW0440_1.0_genomic
GCF_000023545.1_ASM2354v1_genomic
GCF_000400505.1_DPA2511_1.0_genomic
GCF_000406285.1_DXXDW0440_1.0_genomic
GCA_000406085.2_ASM40608v2_genomic
GCF_000023565.1_ASM2356v1_genomic
GCF_000406245.1_DCH3533_1.0_genomic
GCF_000784725.1_ASM78472v1_genomic
GCF_000406065.1_DCH516_1.0_genomic
GCF_000406105.1_DCH402_1.0_genomic
GCF_000406125.1_DXY569_1.0_genomic
GCF_000406165.1_DZE2538_1.0_genomic
GCF_000400525.1_DZE3532_1.0_genomic
GCF_000406325.1_DZEMK19_1.0_genomic
GCF_000382585.1_DiZ_MS1_genomic
GCF_000025065.1_ASM2506v1_genomic
GCF_000406225.1_DZE3531_1.0_genomic
GCF_000406045.1_DZERW192_1.0_genomic
GCF_000816045.1_ASM81604v1_genomic
GCF_000264075.1_ASM26407v1_genomic
GCF_000404105.1_DiZe_1.0_genomic
GCF_000430955.1_DDIIPO980_1.0_genomic
GCF_000365305.1_DDI453_v1.0_genomic
GCF_000975305.1_DdRNS04.9V1.0_genomic
GCF_000365405.2_DDI3534_1.0_genomic
GCF_000365405.1_DDI3534_1.0_genomic
GCF_000365365.1_DDIGBBC2039_1.0_genomic
GCF_000406085.1_DXXRW240_1.0_genomic
GCF_000784735.1_ASM78473v1_genomic
GCF_000406185.1_DDA2976_1.0_genomic
GCF_000147055.1_ASM14705v1_genomic
GCF_000406145.1_DDA898_1.0_genomic
GCF_000406265.1_DDA3537_1.0_genomic
GCF_000803195.1_ASM80319v1_genomic
GCF_000774065.1_ASM77406v1_genomic
GCF_001187975.1_ASM118797v1_genomic
GCF_000406305.1_DXXMK7_1.0_genomic
GCF_001187965.1_ASM118796v1_genomic
GCF_000406205.1_DXX3274_1.0_genomic
GCF_001506125.1_ASM150612v1_genomic
GCF_001401695.1_Dsl_1.0_genomic
GCF_000365345.1_DSOMK16_1.0_genomic
GCF_001417915.1_Dsl_1.0_genomic
GCF_000400795.1_DSOIPO2222_1.0_genomic
GCF_000400565.1_DSOGBBC2040_1.0_genomic
GCF_000365285.1_DSOMK10_1.0_genomic
GCF_000511285.1_SSPACE_genomic
GCF_000474655.1_Dickeya1.0_genomic
GCF_001644705.1_ASM164470v1_genomic
GCF_001401705.1_Dsl_1.0_genomic
GCF_000831935.1_ASM83193v1_genomic
0.27 0.27 0.26 0.26 0.26 0.26 0.26 0.26 0.29 0.26 0.26 0.26 0.26 0.26 0.26 0.26 0.26 0.26 0.26 0.25 0.25 0.26 0.26 0.24 0.26 0.26 0.27 0.27 0.26 0.25 0.21 0.21 0.21 0.19 0.19 0.19 0.2 0.2 0.19 0.2 0.21 0.23 0.22 0.21 0.22 0.22 1 1 0.16 0.16
0.27 0.26 0.26 0.26 0.26 0.26 0.26 0.25 0.26 0.25 0.26 0.26 0.26 0.26 0.26 0.26 0.26 0.26 0.26 0.25 0.24 0.26 0.26 0.24 0.26 0.26 0.27 0.27 0.25 0.25 0.2 0.21 0.21 0.19 0.19 0.19 0.2 0.2 0.19 0.2 0.21 0.23 0.21 0.21 0.22 0.22 1 1 0.15 0.15
0.29 0.29 0.3 0.3 0.3 0.29 0.29 0.28 0.29 0.28 0.28 0.29 0.28 0.29 0.29 0.29 0.28 0.28 0.28 0.28 0.28 0.28 0.3 0.3 0.3 0.3 0.29 0.3 0.3 0.29 0.29 0.28 0.28 0.29 0.29 0.29 0.28 0.28 0.28 0.27 0.3 0.29 0.29 0.29 0.29 0.3 0.15 0.15 0.98 1
0.3 0.29 0.3 0.3 0.3 0.29 0.29 0.28 0.27 0.28 0.28 0.29 0.28 0.29 0.29 0.29 0.28 0.28 0.29 0.28 0.28 0.29 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.29 0.29 0.29 0.29 0.3 0.29 0.29 0.28 0.28 0.29 0.28 0.31 0.29 0.3 0.29 0.3 0.3 0.15 0.15 1 0.99
0.65 0.66 0.64 0.63 0.63 0.63 0.62 0.61 0.6 0.62 0.63 0.63 0.63 0.63 0.63 0.63 0.62 0.62 0.62 0.61 0.62 0.66 0.65 0.64 0.61 0.62 0.62 0.63 0.61 0.61 0.6 0.61 0.62 0.62 0.62 0.61 0.64 0.64 0.61 0.63 0.61 0.83 1 1 0.9 0.9 0.22 0.22 0.32 0.32
0.65 0.65 0.64 0.63 0.63 0.63 0.62 0.61 0.6 0.62 0.62 0.63 0.62 0.63 0.63 0.63 0.62 0.62 0.63 0.61 0.61 0.65 0.65 0.63 0.6 0.62 0.62 0.63 0.61 0.61 0.61 0.61 0.61 0.62 0.62 0.61 0.63 0.64 0.61 0.63 0.61 0.83 1 1 0.9 0.9 0.22 0.22 0.32 0.32
0.66 0.65 0.63 0.63 0.63 0.64 0.62 0.62 0.6 0.62 0.63 0.63 0.63 0.63 0.63 0.63 0.63 0.63 0.63 0.61 0.61 0.64 0.64 0.63 0.61 0.62 0.62 0.62 0.61 0.6 0.61 0.61 0.61 0.61 0.61 0.61 0.63 0.63 0.61 0.62 0.61 0.84 0.91 0.89 1 0.9 0.22 0.22 0.32 0.32
0.63 0.64 0.61 0.62 0.61 0.62 0.61 0.59 0.59 0.59 0.61 0.61 0.61 0.61 0.62 0.62 0.61 0.61 0.61 0.61 0.6 0.63 0.64 0.63 0.59 0.61 0.6 0.61 0.6 0.59 0.6 0.6 0.6 0.6 0.61 0.6 0.63 0.62 0.6 0.6 0.61 0.82 0.88 0.87 0.87 1 0.22 0.22 0.32 0.32
0.66 0.66 0.64 0.64 0.64 0.65 0.63 0.61 0.59 0.61 0.62 0.62 0.62 0.62 0.63 0.62 0.62 0.62 0.62 0.6 0.59 0.64 0.63 0.62 0.6 0.6 0.6 0.61 0.6 0.59 0.6 0.61 0.61 0.61 0.61 0.61 0.62 0.62 0.6 0.6 0.61 1 0.82 0.81 0.83 0.83 0.23 0.23 0.31 0.31
0.55 0.54 0.53 0.55 0.55 0.54 0.53 0.52 0.55 0.52 0.53 0.54 0.53 0.54 0.54 0.54 0.53 0.53 0.54 0.52 0.51 0.53 0.55 0.55 0.53 0.55 0.54 0.55 0.54 0.52 0.56 0.55 0.55 0.54 0.57 0.53 0.55 0.55 0.55 0.54 1 0.54 0.54 0.54 0.54 0.56 0.19 0.19 0.29 0.3
0.56 0.56 0.54 0.55 0.55 0.54 0.54 0.56 0.58 0.56 0.57 0.57 0.57 0.57 0.57 0.57 0.57 0.57 0.57 0.55 0.56 0.57 0.56 0.59 0.54 0.57 0.56 0.57 0.56 0.55 0.8 0.8 0.8 0.82 0.85 0.84 0.93 1 0.91 0.89 0.59 0.6 0.61 0.61 0.6 0.62 0.2 0.2 0.29 0.29
0.56 0.55 0.54 0.55 0.55 0.54 0.53 0.55 0.58 0.56 0.57 0.57 0.56 0.57 0.57 0.57 0.57 0.57 0.57 0.56 0.54 0.57 0.57 0.59 0.54 0.57 0.56 0.57 0.56 0.55 0.81 0.8 0.8 0.82 0.85 0.84 1 0.93 0.9 0.88 0.6 0.6 0.61 0.6 0.6 0.62 0.19 0.19 0.3 0.3
0.56 0.55 0.55 0.56 0.56 0.54 0.54 0.55 0.54 0.56 0.56 0.57 0.56 0.57 0.57 0.57 0.56 0.57 0.57 0.55 0.54 0.57 0.57 0.58 0.55 0.57 0.56 0.57 0.56 0.55 0.82 0.81 0.81 0.84 0.87 0.84 0.93 0.93 1 0.89 0.61 0.6 0.6 0.59 0.6 0.6 0.19 0.19 0.31 0.31
0.57 0.56 0.55 0.55 0.55 0.55 0.54 0.56 0.54 0.56 0.57 0.57 0.57 0.57 0.58 0.57 0.57 0.57 0.57 0.56 0.55 0.57 0.58 0.59 0.56 0.57 0.56 0.56 0.56 0.55 0.81 0.82 0.82 0.83 0.85 0.84 0.92 0.93 0.9 1 0.6 0.61 0.63 0.62 0.62 0.62 0.2 0.2 0.3 0.3
0.58 0.58 0.56 0.57 0.57 0.56 0.55 0.57 0.6 0.57 0.58 0.58 0.58 0.58 0.58 0.58 0.58 0.58 0.58 0.57 0.55 0.59 0.58 0.59 0.57 0.58 0.57 0.57 0.57 0.56 0.82 0.81 0.83 0.84 0.87 1 0.88 0.89 0.86 0.85 0.6 0.62 0.62 0.61 0.61 0.63 0.2 0.2 0.32 0.32
0.57 0.56 0.55 0.56 0.56 0.55 0.54 0.55 0.58 0.55 0.56 0.56 0.56 0.56 0.56 0.57 0.56 0.56 0.56 0.55 0.55 0.56 0.56 0.58 0.55 0.57 0.57 0.57 0.56 0.56 0.85 0.85 0.85 0.88 1 0.83 0.86 0.87 0.86 0.83 0.63 0.6 0.6 0.6 0.6 0.61 0.19 0.19 0.31 0.31
0.58 0.57 0.56 0.56 0.56 0.56 0.55 0.54 0.53 0.55 0.56 0.56 0.55 0.56 0.56 0.56 0.55 0.55 0.56 0.55 0.53 0.56 0.56 0.57 0.55 0.57 0.57 0.57 0.56 0.55 0.84 0.85 0.86 1 0.89 0.82 0.85 0.85 0.84 0.83 0.6 0.61 0.61 0.61 0.6 0.61 0.19 0.19 0.32 0.32
0.56 0.56 0.54 0.54 0.54 0.54 0.52 0.53 0.52 0.53 0.54 0.54 0.54 0.54 0.54 0.54 0.54 0.54 0.54 0.51 0.51 0.54 0.54 0.55 0.53 0.53 0.53 0.53 0.53 0.52 0.96 1 1 0.83 0.83 0.78 0.8 0.8 0.79 0.78 0.59 0.59 0.58 0.58 0.58 0.59 0.2 0.2 0.3 0.3
0.56 0.56 0.54 0.54 0.55 0.54 0.53 0.54 0.52 0.54 0.54 0.55 0.54 0.55 0.55 0.55 0.54 0.54 0.55 0.52 0.51 0.54 0.55 0.56 0.54 0.54 0.53 0.54 0.53 0.53 0.95 1 1 0.83 0.84 0.77 0.81 0.8 0.8 0.79 0.6 0.59 0.59 0.58 0.59 0.59 0.2 0.2 0.3 0.3
0.56 0.56 0.54 0.56 0.56 0.54 0.53 0.54 0.53 0.54 0.55 0.55 0.55 0.55 0.55 0.55 0.55 0.55 0.55 0.53 0.52 0.55 0.55 0.56 0.53 0.55 0.54 0.55 0.54 0.53 1 0.96 0.98 0.83 0.86 0.79 0.82 0.82 0.81 0.79 0.62 0.59 0.59 0.58 0.59 0.61 0.21 0.21 0.3 0.31
0.99 0.98 1 0.95 0.95 0.97 0.95 0.72 0.71 0.73 0.73 0.74 0.73 0.74 0.74 0.74 0.74 0.74 0.74 0.7 0.69 0.73 0.73 0.72 0.7 0.71 0.71 0.72 0.71 0.69 0.56 0.57 0.57 0.58 0.57 0.56 0.58 0.57 0.57 0.56 0.61 0.66 0.66 0.65 0.64 0.64 0.27 0.27 0.33 0.33
1 1 0.95 0.95 0.95 0.95 0.94 0.72 0.71 0.73 0.74 0.74 0.74 0.75 0.74 0.74 0.74 0.74 0.74 0.7 0.69 0.73 0.73 0.72 0.71 0.71 0.71 0.72 0.71 0.69 0.57 0.57 0.58 0.58 0.57 0.56 0.57 0.58 0.56 0.56 0.61 0.66 0.64 0.64 0.64 0.64 0.27 0.27 0.32 0.32
1 1 0.95 0.97 0.97 0.96 0.95 0.72 0.77 0.73 0.74 0.74 0.74 0.74 0.74 0.74 0.74 0.74 0.74 0.7 0.69 0.73 0.73 0.72 0.71 0.72 0.71 0.72 0.71 0.7 0.57 0.58 0.58 0.58 0.57 0.56 0.57 0.58 0.56 0.56 0.61 0.66 0.65 0.64 0.64 0.65 0.27 0.27 0.32 0.32
0.99 1 0.95 1 1 0.96 0.95 0.72 0.72 0.73 0.74 0.75 0.74 0.75 0.75 0.75 0.74 0.75 0.75 0.72 0.7 0.74 0.74 0.73 0.72 0.72 0.72 0.73 0.72 0.7 0.58 0.58 0.58 0.58 0.59 0.58 0.58 0.58 0.59 0.57 0.63 0.66 0.65 0.64 0.65 0.64 0.27 0.27 0.33 0.34
0.99 1 0.95 1 1 0.96 0.95 0.72 0.72 0.73 0.74 0.75 0.74 0.75 0.75 0.75 0.74 0.75 0.75 0.72 0.7 0.74 0.74 0.73 0.72 0.72 0.72 0.73 0.72 0.7 0.59 0.58 0.58 0.58 0.59 0.58 0.58 0.58 0.58 0.57 0.63 0.66 0.65 0.64 0.65 0.65 0.27 0.27 0.33 0.34
0.96 0.97 0.95 0.93 0.94 1 1 0.7 0.74 0.71 0.73 0.72 0.72 0.72 0.72 0.72 0.72 0.72 0.72 0.7 0.69 0.72 0.72 0.71 0.7 0.7 0.71 0.71 0.7 0.68 0.55 0.55 0.55 0.56 0.56 0.55 0.56 0.57 0.55 0.54 0.6 0.64 0.62 0.61 0.62 0.63 0.27 0.26 0.32 0.32
0.9 0.89 0.88 0.87 0.87 1 0.94 0.66 0.69 0.67 0.68 0.68 0.68 0.68 0.68 0.68 0.68 0.68 0.68 0.64 0.63 0.67 0.67 0.67 0.65 0.66 0.66 0.67 0.66 0.64 0.51 0.52 0.52 0.52 0.52 0.52 0.52 0.52 0.51 0.51 0.56 0.6 0.59 0.58 0.59 0.59 0.25 0.25 0.29 0.29
0.67 0.67 0.65 0.65 0.65 0.67 0.64 0.67 0.71 0.68 0.69 0.69 0.69 0.69 0.69 0.69 0.69 0.69 0.69 0.67 0.65 0.68 0.7 1 0.7 0.73 0.72 0.73 0.72 0.71 0.53 0.53 0.53 0.53 0.54 0.53 0.56 0.56 0.54 0.54 0.57 0.57 0.58 0.58 0.58 0.59 0.23 0.23 0.3 0.3
0.75 0.74 0.72 0.73 0.74 0.74 0.73 0.79 0.82 0.79 0.81 0.81 0.81 0.81 0.81 0.82 0.81 0.81 0.81 0.82 0.84 0.85 1 0.77 0.77 0.78 0.76 0.77 0.78 0.77 0.57 0.58 0.58 0.58 0.59 0.58 0.6 0.59 0.59 0.59 0.63 0.64 0.66 0.65 0.65 0.66 0.27 0.27 0.33 0.33
0.76 0.76 0.74 0.75 0.75 0.75 0.73 0.81 0.81 0.81 0.84 0.84 0.83 0.83 0.83 0.83 0.83 0.83 0.83 0.9 0.89 1 0.87 0.77 0.77 0.79 0.78 0.79 0.79 0.78 0.59 0.58 0.58 0.59 0.6 0.61 0.62 0.61 0.6 0.59 0.62 0.67 0.67 0.67 0.66 0.67 0.27 0.27 0.32 0.32
0.73 0.72 0.71 0.71 0.71 0.71 0.71 0.78 0.81 0.78 0.83 0.79 0.79 0.8 0.8 0.8 0.79 0.79 0.8 0.9 1 0.89 0.86 0.74 0.76 0.76 0.79 0.76 0.76 0.74 0.55 0.55 0.55 0.56 0.59 0.56 0.59 0.6 0.57 0.57 0.6 0.62 0.64 0.63 0.63 0.64 0.26 0.26 0.31 0.32
0.72 0.72 0.7 0.71 0.71 0.7 0.7 0.78 0.81 0.78 0.8 0.8 0.8 0.8 0.8 0.8 0.79 0.8 0.8 1 0.88 0.87 0.82 0.74 0.74 0.76 0.75 0.76 0.75 0.74 0.55 0.55 0.54 0.56 0.57 0.57 0.59 0.58 0.57 0.56 0.59 0.61 0.62 0.61 0.61 0.64 0.25 0.26 0.31 0.31
0.76 0.75 0.73 0.74 0.74 0.74 0.72 0.8 0.83 0.8 0.82 0.82 0.82 0.82 0.83 0.83 0.82 0.82 0.82 0.78 0.77 0.8 0.81 0.83 0.87 0.92 0.91 0.92 0.97 1 0.59 0.59 0.59 0.6 0.62 0.6 0.62 0.62 0.6 0.6 0.63 0.64 0.65 0.64 0.64 0.65 0.27 0.27 0.33 0.34
0.75 0.75 0.72 0.73 0.73 0.74 0.72 0.79 0.78 0.79 0.81 0.81 0.81 0.81 0.81 0.81 0.8 0.81 0.81 0.77 0.76 0.79 0.8 0.83 0.86 0.91 0.9 0.91 1 0.94 0.57 0.58 0.58 0.59 0.6 0.59 0.61 0.61 0.6 0.59 0.63 0.64 0.64 0.63 0.63 0.64 0.27 0.27 0.34 0.34
0.75 0.75 0.73 0.73 0.73 0.74 0.72 0.79 0.82 0.79 0.81 0.81 0.81 0.81 0.81 0.81 0.81 0.81 0.81 0.77 0.75 0.79 0.78 0.82 0.84 0.95 1 1 0.9 0.88 0.58 0.57 0.57 0.59 0.61 0.58 0.61 0.61 0.59 0.58 0.63 0.63 0.65 0.64 0.64 0.65 0.28 0.28 0.33 0.34
0.75 0.74 0.73 0.73 0.73 0.74 0.73 0.79 0.82 0.79 0.81 0.81 0.8 0.81 0.81 0.81 0.8 0.81 0.81 0.77 0.79 0.78 0.78 0.82 0.85 0.96 1 1 0.9 0.88 0.58 0.57 0.57 0.59 0.6 0.58 0.61 0.61 0.59 0.58 0.63 0.63 0.65 0.64 0.64 0.65 0.28 0.28 0.33 0.33
0.75 0.75 0.72 0.72 0.73 0.74 0.72 0.79 0.82 0.79 0.8 0.81 0.8 0.81 0.81 0.81 0.8 0.8 0.8 0.77 0.75 0.78 0.79 0.82 0.85 1 0.95 0.95 0.9 0.88 0.58 0.57 0.57 0.59 0.6 0.59 0.61 0.61 0.59 0.59 0.63 0.63 0.64 0.63 0.63 0.64 0.28 0.27 0.33 0.34
0.77 0.76 0.74 0.75 0.75 0.76 0.75 0.8 0.84 0.81 0.83 0.83 0.82 0.83 0.83 0.83 0.82 0.82 0.83 0.79 0.79 0.8 0.81 0.82 1 0.89 0.88 0.88 0.89 0.87 0.58 0.6 0.6 0.59 0.61 0.6 0.61 0.61 0.6 0.6 0.64 0.65 0.65 0.64 0.66 0.66 0.29 0.28 0.35 0.35
0.77 0.76 0.75 0.75 0.75 0.76 0.74 0.93 1 1 1 1 0.99 1 1 1 1 0.99 1 0.81 0.79 0.82 0.82 0.78 0.79 0.81 0.8 0.81 0.8 0.79 0.58 0.58 0.58 0.58 0.59 0.59 0.61 0.61 0.59 0.59 0.62 0.65 0.65 0.64 0.65 0.65 0.27 0.27 0.32 0.32
0.77 0.76 0.75 0.75 0.75 0.76 0.73 0.93 1 0.99 1 1 0.99 1 1 1 1 0.99 1 0.81 0.79 0.82 0.82 0.78 0.79 0.81 0.8 0.81 0.8 0.79 0.58 0.58 0.58 0.58 0.6 0.59 0.61 0.61 0.59 0.59 0.62 0.65 0.65 0.64 0.65 0.65 0.27 0.27 0.32 0.32
0.77 0.77 0.75 0.75 0.75 0.76 0.73 0.93 1 1 1 1 1 1 1 1 0.99 1 1 0.81 0.79 0.82 0.82 0.78 0.79 0.81 0.8 0.81 0.8 0.79 0.58 0.58 0.58 0.58 0.59 0.59 0.61 0.61 0.59 0.59 0.62 0.65 0.65 0.64 0.65 0.65 0.27 0.27 0.32 0.32
0.78 0.77 0.75 0.75 0.75 0.76 0.73 0.94 0.98 0.99 1 1 0.99 1 1 1 0.99 1 1 0.81 0.79 0.83 0.82 0.77 0.79 0.8 0.8 0.81 0.8 0.79 0.58 0.58 0.58 0.58 0.59 0.59 0.61 0.61 0.59 0.59 0.62 0.65 0.65 0.64 0.65 0.64 0.27 0.27 0.32 0.32
0.77 0.76 0.74 0.75 0.75 0.75 0.73 0.93 0.97 0.99 0.99 0.99 0.99 1 1 1 0.99 1 1 0.81 0.78 0.82 0.82 0.77 0.79 0.8 0.8 0.81 0.8 0.78 0.58 0.58 0.58 0.58 0.59 0.59 0.61 0.61 0.59 0.59 0.62 0.64 0.64 0.63 0.64 0.65 0.27 0.27 0.32 0.32
0.77 0.76 0.74 0.74 0.75 0.75 0.73 0.93 0.96 0.98 0.98 0.99 0.98 0.99 0.99 0.99 0.98 1 1 0.8 0.78 0.82 0.82 0.77 0.78 0.8 0.8 0.8 0.8 0.78 0.57 0.58 0.58 0.57 0.59 0.58 0.61 0.61 0.59 0.58 0.62 0.64 0.64 0.63 0.64 0.64 0.27 0.27 0.32 0.32
0.77 0.76 0.74 0.74 0.74 0.75 0.73 0.93 0.98 1 1 1 1 1 1 1 1 1 1 0.8 0.78 0.81 0.81 0.77 0.78 0.79 0.79 0.8 0.79 0.78 0.57 0.58 0.58 0.57 0.59 0.58 0.6 0.6 0.59 0.58 0.61 0.64 0.64 0.63 0.64 0.63 0.27 0.27 0.31 0.32
0.77 0.77 0.75 0.75 0.75 0.76 0.73 0.94 1 1 1 1 1 1 1 1 0.99 1 1 0.82 0.79 0.83 0.82 0.78 0.79 0.81 0.8 0.81 0.8 0.79 0.58 0.58 0.59 0.58 0.6 0.59 0.61 0.61 0.59 0.59 0.62 0.65 0.65 0.64 0.65 0.65 0.27 0.27 0.32 0.32
0.78 0.77 0.75 0.75 0.75 0.76 0.74 0.94 1 1 1 1 1 1 1 1 1 1 1 0.82 0.79 0.83 0.82 0.78 0.79 0.81 0.8 0.81 0.8 0.79 0.58 0.58 0.59 0.58 0.6 0.59 0.61 0.61 0.59 0.59 0.62 0.65 0.65 0.64 0.65 0.65 0.27 0.27 0.32 0.32
0.77 0.77 0.75 0.75 0.75 0.76 0.75 0.94 1 1 1 1 1 1 1 1 1 1 1 0.82 0.82 0.84 0.82 0.78 0.79 0.81 0.8 0.82 0.8 0.79 0.58 0.58 0.59 0.58 0.6 0.59 0.61 0.61 0.59 0.59 0.62 0.65 0.65 0.64 0.65 0.65 0.27 0.27 0.32 0.32
0.77 0.76 0.74 0.74 0.74 0.75 0.73 1 0.93 0.94 0.95 0.95 0.95 0.96 0.96 0.96 0.95 0.95 0.96 0.81 0.78 0.82 0.82 0.77 0.78 0.8 0.8 0.8 0.8 0.78 0.58 0.58 0.58 0.58 0.59 0.59 0.61 0.61 0.59 0.59 0.62 0.65 0.64 0.63 0.65 0.64 0.27 0.27 0.32 0.32
0.78 0.83 0.75 0.76 0.76 0.8 0.78 0.95 1 1 1.1 1.1 1.1 1 1 1 1 1 1 0.86 0.83 0.84 0.87 0.83 0.83 0.85 0.85 0.86 0.81 0.83 0.58 0.58 0.58 0.58 0.63 0.63 0.65 0.65 0.59 0.58 0.67 0.64 0.64 0.64 0.64 0.65 0.28 0.31 0.32 0.35
0.0
0.2
0.4
0.6
0.8
1.0
ANIm_hadamard

51. pyani software a
a
http://widdowquinn.github.io/pyani
Python ANI
module and
script
Active
development
Parallelises
on clusters
Preprint
coming soon
(simulated
genomes; lots
of bacterial
taxonomy!)

52. Table of Contents
1 Introduction
Hey, Hey We’re The James Hutton Institute!
The Tangled Taxonomy of Soft-Rot Enterobacteria
The Insidious Dickeya Menace
2 Genomics
The £250k Genome
25 Dickeya Genomes
3 Classification and Diagnostics
Diagnosis: Plant Murder I
ANI Are You OK? Are You OK ANI?
Diagnosis: Plant Murder II
4 Systems Biology
Plant Pathology’s Next Top Model?
5 Synthetic Biology
From Food (Waste) To Fuel
6 Acknowledgements

53. qPCR Primer Design
With ‘correct’ classifications, we can design accurate diagnostics
targets
off-targets
classification
V
IV
III
II
I
genomes
I
II
III
IV
V

54. Dickeya primer evaluation a
a
Pritchard et al. (2013) Plant Path. doi:10.1111/j.1365-3059.2012.02678.x
Primers designed to 29 sequenced Dickeya isolates
Evaluated against panel of 70 unseen isolates
100% sensitivity; 0-4% FDR

55. E. coli diagnostic primers a b
a
https://github.com/ehec-outbreak-crowdsourced/BGI-data-analysis/wiki
b
Kwan et al. (2011) http://precedings.nature.com/documents/6663/version/1
Summer 2011, E. coli EHEC O104:H4 outbreak, Germany
3950 affected, 53 deaths; rapid production of sequence data,
crowd-sourcing of analyses

56. E. coli primer evaluation a
a
Pritchard et al. (2012) PLoS One doi:10.1371/journal.pone.0034498
Primers designed to nine crowdsourced draft outbreak E. coli
O104: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

57. find differential primers a
a
http://widdowquinn.github.io/find differential primers/
Software freely available at GitHub
Parallises across cluster

58. Table of Contents
1 Introduction
Hey, Hey We’re The James Hutton Institute!
The Tangled Taxonomy of Soft-Rot Enterobacteria
The Insidious Dickeya Menace
2 Genomics
The £250k Genome
25 Dickeya Genomes
3 Classification and Diagnostics
Diagnosis: Plant Murder I
ANI Are You OK? Are You OK ANI?
Diagnosis: Plant Murder II
4 Systems Biology
Plant Pathology’s Next Top Model?
5 Synthetic Biology
From Food (Waste) To Fuel
6 Acknowledgements

59. Comparative metabolism a b
a
Biopython KGML/KEGG visualisation module
b
https://github.com/widdowquinn/Notebooks-Bioinformatics
Metabolic potential is a clue to community function & host range

60. Differential Metabolic Capacity
Annotated metabolic capacity
predicts host range
Growth curves confirm predicted
carbon use
Transposon mutant grids for 17
sequenced Dickeya

61. Dynamic Metabolic Modelling
Flux Balance Analysis models
for sequenced Dickeya
whole-organism metabolic flux
prediction of KO effects
substrate usage/production
flux optimisation (SynBio)
Potential Influence
Systems-level understanding of environmental interactions of
plant pathogens
Funding
RESAS 5-year programme

62. Table of Contents
1 Introduction
Hey, Hey We’re The James Hutton Institute!
The Tangled Taxonomy of Soft-Rot Enterobacteria
The Insidious Dickeya Menace
2 Genomics
The £250k Genome
25 Dickeya Genomes
3 Classification and Diagnostics
Diagnosis: Plant Murder I
ANI Are You OK? Are You OK ANI?
Diagnosis: Plant Murder II
4 Systems Biology
Plant Pathology’s Next Top Model?
5 Synthetic Biology
From Food (Waste) To Fuel
6 Acknowledgements

63. Food or Fuel? a
a
Mohr & Rahman et al. (2013) Energy Policy doi:10.1016/j.enpol.2013.08.033
Biofuels: ”Riches to Rags”
1st generation: fuel from food crops
2nd generation: fuel from cellulosic crops, e.g. miscanthus,
willow
Stealing food, or stealing land/water?

64. Food and Fuel? a
a
Mohr & Rahman et al. (2013) Energy Policy doi:10.1016/j.enpol.2013.08.033
Waste material = carbon-neutral feedstock
Agricultural waste as feedstock?
2nd generation fuel from food crops?
Maize stover, straw, sugarcane bagasse, etc.

65. Processing Waste a b c
a
Beall & Ingram (1993) J. Indust. Micro. 11:151-155
b
Zhou et al. (1999) Appl. Environ. Microbiol. 65:2439-2445
c
Edwards et al. (2011) Appl. Environ. Microbiol. doi:10.1128/AEM.05700-11
Soft rot pathogens
(PCWDEs): hydrolases and lyases
Engineer pathogens for ethanol production? a
Express PCWDEs in ethanologenic E. coli? b,c
PCWDE libraries for synthetic biology?
SynBio automated platforms for engineered microbial pathways
(e.g. Cellulect, UoEdinburgh)
understanding enzyme structure-function relationships

66. CAZy a
a
Lombard et al. (2014) Nucl. Acids Res. doi:10.1093/nar/gkt1178
CAZy: Carbohydrate-Active Enzymes database (http://www.cazy.org/)
5 Dickeya, 14 Erwinia, 9 Pectobacterium genomes
63 Dickeya, 66 Erwinia, 74 Pectobacterium families
Survey/mine natural diversity of CAZymes

67. Pathogen Diversity a
a
Pritchard et al. (2016) Anal. Methods doi:10.1039/C5AY02550H
48 Dickeya, 38 Erwinia, 57 Pectobacterium genomes
Survey/mine natural diversity of PCWDEs: ‘evolvability’
Pectobacterium_atrosepticum_SCRI1043_uid57957Pectobacterium_atrosepticum_NCPPB8549Pectobacterium_atrosepticum_NCPPB3404Pectobacterium_atrosepticum_21APectobacterium_atrosepticum_JG10-08Pectobacterium_carotovorum_PC1_uid59295Pectobacterium_carotovorum_subsp_carotovorum_NCPPB312Pectobacterium_carotovorum_subsp_oderiferum_NCPPB3841Pectobacterium_carotovorum_subsp_oderiferum_NCPPB3839Pectobacterium_carotovorum_subsp_carotovorum_NCPPB3395Pectobacterium_carotovorum_PCC21_uid174335Pectobacterium_carotovorum_subsp_brasiliensis_B5Pectobacterium_carotovorum_subsp_brasiliensis_B4Pectobacterium_betavasculorum_NCPPB2293Pectobacterium_betavasculorum_NCPPB2795Pectobacterium_wasabiae_NCPPB3702Pectobacterium_wasabiae_NCPPB3701Pectobacterium_wasabiae_WPP163_uid41297Pectobacterium_SCC3193_uid193707Dickeya_solani_AMYI01Dickeya_solani_AMWE01Dickeya_solani_GBBC2040Dickeya_solani_IPO2222Dickeya_solani_MK16Dickeya_solani_MK10Dickeya_dianthicola_NCPPB_3534Dickeya_dianthicola_GBBC2039Dickeya_dianthicola_NCPPB_453Dickeya_dianthicola_IPO980Dickeya_spp_NCPPB_3274Dickeya_spp_MK7Dickeya_dadantii_NCPPB_2976Dickeya_dadantii_NCPPB_898Dickeya_dadantii_NCPPB_3537Dickeya_dadantii_3937_uid52537Pantoea_ananatis_AJ13355_uid162073Pantoea_ananatis_LMG_20103_uid46807Pantoea_ananatis_PA13_uid162181Pantoea_ananatis_uid86861Erwinia_amylovora_CFBP1430_uid46839Erwinia_amylovora_ATCC_49946_uid46943Erwinia_Ejp617_uid159955Erwinia_pyrifoliae_Ep1_96_uid40659Erwinia_pyrifoliae_DSM_12163_uid159693Dickeya_dadantii_Ech703_uid59363Dickeya_paradisiaca_NCPPB_2511Dickeya_aquatica_DW_0440Dickeya_aquatica_CSL_RW240Erwinia_tasmaniensis_Et1_99_uid59029Pantoea_At_9b_uid55845Pantoea_vagans_C9_1_uid49871Erwinia_billingiae_Eb661_uid50547Dickeya_zeae_APMV01Dickeya_zeae_AJVN01Dickeya_zeae_CSL_RW192Dickeya_zeae_NCPPB_3531Dickeya_dadantii_Ech586_uid42519Dickeya_zeae_APWM01Dickeya_zeae_NCPPB_2538Dickeya_zeae_MK19Dickeya_zeae_NCPPB_3532Dickeya_spp_NCPPB_569Dickeya_chrysanthami_NCPPB_402Dickeya_chrysanthami_NCPPB_516Dickeya_zeae_Ech1591_uid59297Dickeya_chrysanthami_NCPPB_3533
Pectobacterium_atrosepticum_SCRI1043_uid57957Pectobacterium_atrosepticum_NCPPB8549Pectobacterium_atrosepticum_NCPPB3404Pectobacterium_atrosepticum_21APectobacterium_atrosepticum_JG10-08Pectobacterium_carotovorum_PC1_uid59295Pectobacterium_carotovorum_subsp_carotovorum_NCPPB312Pectobacterium_carotovorum_subsp_oderiferum_NCPPB3841Pectobacterium_carotovorum_subsp_oderiferum_NCPPB3839Pectobacterium_carotovorum_subsp_carotovorum_NCPPB3395Pectobacterium_carotovorum_PCC21_uid174335Pectobacterium_carotovorum_subsp_brasiliensis_B5Pectobacterium_carotovorum_subsp_brasiliensis_B4Pectobacterium_betavasculorum_NCPPB2293Pectobacterium_betavasculorum_NCPPB2795Pectobacterium_wasabiae_NCPPB3702Pectobacterium_wasabiae_NCPPB3701Pectobacterium_wasabiae_WPP163_uid41297Pectobacterium_SCC3193_uid193707Dickeya_solani_AMYI01Dickeya_solani_AMWE01Dickeya_solani_GBBC2040Dickeya_solani_IPO2222Dickeya_solani_MK16Dickeya_solani_MK10Dickeya_dianthicola_NCPPB_3534Dickeya_dianthicola_GBBC2039Dickeya_dianthicola_NCPPB_453Dickeya_dianthicola_IPO980Dickeya_spp_NCPPB_3274Dickeya_spp_MK7Dickeya_dadantii_NCPPB_2976Dickeya_dadantii_NCPPB_898Dickeya_dadantii_NCPPB_3537Dickeya_dadantii_3937_uid52537Pantoea_ananatis_AJ13355_uid162073Pantoea_ananatis_LMG_20103_uid46807Pantoea_ananatis_PA13_uid162181Pantoea_ananatis_uid86861Erwinia_amylovora_CFBP1430_uid46839Erwinia_amylovora_ATCC_49946_uid46943Erwinia_Ejp617_uid159955Erwinia_pyrifoliae_Ep1_96_uid40659Erwinia_pyrifoliae_DSM_12163_uid159693Dickeya_dadantii_Ech703_uid59363Dickeya_paradisiaca_NCPPB_2511Dickeya_aquatica_DW_0440Dickeya_aquatica_CSL_RW240Erwinia_tasmaniensis_Et1_99_uid59029Pantoea_At_9b_uid55845Pantoea_vagans_C9_1_uid49871Erwinia_billingiae_Eb661_uid50547Dickeya_zeae_APMV01Dickeya_zeae_AJVN01Dickeya_zeae_CSL_RW192Dickeya_zeae_NCPPB_3531Dickeya_dadantii_Ech586_uid42519Dickeya_zeae_APWM01Dickeya_zeae_NCPPB_2538Dickeya_zeae_MK19Dickeya_zeae_NCPPB_3532Dickeya_spp_NCPPB_569Dickeya_chrysanthami_NCPPB_402Dickeya_chrysanthami_NCPPB_516Dickeya_zeae_Ech1591_uid59297Dickeya_chrysanthami_NCPPB_3533
0.00
0.25
0.50
0.75
1.00
ANIm_percentage_identity

68. Protein Structures a b
a
Chapon et al. (2001) J. Mol. Biol. doi:10.1006/jmbi.2001.4787
b
Larson et al. (2003) Biochem. doi:10.1021/bi034144c
Several landmark enzyme structures from Dickeya
First GH5 xylanase structure (1NOF)
Cel5 (1EGZ)
Obtain novel structures for Dickeya CAZymes

69. Generate Diversity
Gene shuffling/directed evolution
Saturating site-directed mutagenesis
Functional space
theoretically available to enzyme family
structure/sequence
Functional
space explored
in nature

70. Gene Shuffling a
a
Crameri et al. (1998) Nature doi:10.1038/34663
Generate novel diversity and select for substrate specificity

71. Positional epistasis a
a
McLaughlin et al. (2012) Nature doi:10.1038/nature11500
Context-dependence of mutation and function: epistasis
“hotspots”/pathways for control of substrate specificity
Saturated single substitutions, with substrate assay screens

72. Protein Sectors a b
a
Pritchard & Dufton (2000) J. Theor. Biol. doi:10.1006/jtbi.1999.1043
b
Halabi et al. (2009) Cell doi:10.1016/j.cell.2009.07.038
Sequence diversity and protein structure enables:
Correlated mutation/conservation analysis
Decomposition of structure into ”sectors”
Sectors: subdomain structural/functional organisation of
proteins

73. Anticipated Outputs
Libraries of carbohydrate-processing enzymes for SynBio
Survey of natural PCWDE diversity
Novel specificity variants from gene shuffling
Saturated site-specific mutagenesis libraries for screening
against novel substrates
IP?
Structure-function insight
New PCWDE enzyme structures
Sector and epistasis maps for PCWDEs
Reverse-engineering of carbohydrate-processing enzymes
Empirically-improved enzymes
Gene-shuffling targeted to novel specificity
Forward-engineering of carbohydrate-processing enzymes
IP?

74. Acknowledgements
Dickeya/Erwinia/Pectobacterium
Steve Baeyen (ILVO)
Emma Campbell (JHI)
Sean Chapman (JHI)
John Elphinstone (Fera)
Tracey Gloster (St Andrews)
Rachel Glover (Fera)
Sonia Humphris (JHI)
Martine Maes (ILVO)
Katrin Mackenzie (BioSS)
Neil Parkinson (Fera)
Minna Pirhonen (Helsinki)
Gerry Saddler (SASA)
Elaine Shemilt (Duncan of
Jordanstone)
Ian Simpson (Edinburgh)
Ian Toth (JHI)
Jan van der Wolf (Wageningen)
Johan van Vaerenbergh (ILVO)
Frank Wright (BioSS)
Eirini Xemantilotou (St
Andrews/JHI)
Nematodes
Peter Cock (JHI)
John Jones (JHI/St Andrews)
Robbie Rae (John Moores)
Peter Thorpe (JHI)
Phytophthora
Miles Armstrong (Dundee)
Anna Avrova (JHI)
Jim Beynon (Warwick)
Paul Birch (Dundee)
David Cooke (JHI)
Kath Denby (York)
Eleanor Gilroy (JHI)
Sarah Green (Forest Research)
Edgar Huitema (Dundee)
Rory McLean (Dundee)
Hazel McLellan (Dundee)
Sophien Kamoun (TSL)
Gail Preston (Oxford)
Paul Sharp (Edinburgh)
Jens Steinbrenner (Warwick)
Pieter van West (Aberdeen)
Steve Whisson (JHI)
Computational and Systems
Biology
David Broadhurst (Edith
Cowan)
Peter Cock (JHI)
Mark Dufton (Strathclyde)
Roy Goodacre (Manchester)
Douglas Kell (Manchester)
David Martin (Dundee)
Iain Milne (JHI)
Pedro Mendes (Manchester)
E. coli/other bacteria
Florence Abram (Galway)
Martina Bielaszewska (Muenster)
Fiona Brennan (Galway)
Ken Forbes (Aberdeen)
Nicola Holden (JHI)
Ashleigh Holmes (JHI)
Paul Hoskisson (Strathclyde)
Helge Karch (Muenster)
Norval Strachan (Aberdeen)
David Studholme (Exeter)
Nick Waters (Galway)
Metagenomics/Communities
Natalie Ferry (Salford)
Thomas Freitag (JHI)
Ryan Joynson (Liverpool)
John Mitchell (St Andrews)
Les Noble (Aberdeen)
Jim Prosser (Aberdeen)
V Anne Smith (St Andrews)
Potato
Micha Bayer (JHI)
Glenn Bryan (JHI)
Graham Etherington (TSL)
Ingo Hein (JHI)
Florian Jupe (JHI)
Jonathan Jones (TSL)
Dan Maclean (TSL)
. . .and many others. . .

75. Licence: CC-BY-SA
By: Leighton Pritchard
This presentation is licensed under the Creative Commons
Attribution ShareAlike license
https://creativecommons.org/licenses/by-sa/4.0/