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Draft genomes of “Pectobacterium peruviense” strains isolated from fresh water in France

  • Pierre Faye
  • Claire Bertrand
  • Jacques Pédron
  • Marie-Anne Barny
Open Access
Short genome report
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Abstract

Bacteria belonging to the genus Pectobacterium are responsible for soft rot disease on a wide range of cultivated crops. The “Pectobacterium peruviense” specie, recently proposed inside the Pectobacterium genus, gathers strains isolated from potato tubers cultivated in Peru at high altitude. Here we report the draft genome sequence of two strains belonging to “P. peruviense” isolated from river water in France indicating that the geographic distribution of this specie is likely to be larger than previously anticipated. We compared these genomes with the one published from the “P. peruviense” specie type strain isolated in Peru.

Keywords

Pectobacterium peruviense Soft rot Plant pathogen Water France 

Abbreviations

ANI

Average Nucleotide Identity

COG

Clusters of Orthologous Groups

CRISPR

Clustered Regularly Interspaced Short Palindromic Repeats

dDDH

digital DNA-DNA hybridization

gapA

glyceraldehyde-3-phosphate dehydrogenase A

MLSA

Multi Locus Sequence Analysis

NTU

Normalized Turbidity Unit

sp.

specie

subsp.

subspecie

Introduction

The Pectobacterium genus [1] gathers important plant pathogens that cause soft rot disease on a large variety of plant species [2]. Given their ability to cause disease on major crops, such as potato, Pectobacterium sp. have mainly been isolated from diseased plant during initial outbreak or sustained epidemic and their descriptions outside of agricultural context is scarce [3].

The classification of the Pectobacterium genus has been subject to extensive revision over the last decade. It is currently subdivided in 7 species; P. carotovorum [1], P. atrosepticum [4], P. betavasculorum [4], P. wasabiae [4], P. aroidearum [5] P. polaris [6], P. parmentieri [7] and the recently proposed “P. peruviense” [8]. The P. carotovorum specie is heterogeneous and is currently subdivided several recognized subspecies, P. carotovorum subsp. carotovorum [9, 10], P. carotovorum subsp. odoriferum [9, 10] and proposed subspecies “ P. carotovorum subsp. actinidiae” [11] and “ P. carotovorum subsp. brasiliense ” [12]. This heterogeneity led to assignation of many Pectobacterium isolates to P. carotovorum . One example is the strain UG32 (also named IFB5232, SCRI179, LMG30269 and PCM2893) that was initially described as P. carotovorum subsp. carotovorum and is now the proposed type strain of the “P. peruviense” specie [8, 13]. All the strains described so far in the “P. peruviense” specie have been isolated in Peru in the seventies during the twentieth century from potato plants cultivated at high altitude (2400–3800 m). Here we described the draft genome sequence of two strains A97-S13-F16 and A350-S18-N16 isolated in February and November 2016 at different altitudes in the Durance river stream in France.

Organism information

Classification and features

Strain A97-S13-F16 was isolated in february 2016 from fresh water sampled in the river Durance while strain A350-S18-N16 was isolated in november 2016 from fresh water sampled in river Bléone, close to the confluent with river Durance. The fresh water parameters measured at the sampling times respectively were the following respectively for A97-S13-F16 and A350-S18-N16 sampled water: temperature 6.4 °C and 10.4 °C; turbidity 2.69 NTU and 145 NTU, conductivity 629 μS and 629 μS. Following sampling, 500 ml of fresh water was filtered through 0.2 μm pore filters (Sartorius cellulose acetate filters), the bacteria present on the filters were suspended in 1 ml sterile distilled water and 100 μl of the suspension were poured onto semi selective modified single-layers CVPAG366 plates (same medium as described in [14] except that tryptone was not added to the medium, hereafter described as CVP). After 2 days of growth at 28 °C, two strains forming pits on CVP medium were further isolated, named A97-S13-F16 and A350-S18-N16 and stored in 40% /60% glycerol/ LB liquid medium (10 g tryptone, 5 g yeast extract, 10 g NaCl per one liter of medium) at − 80 °C.

Cells of both strains are rod shaped with length of approximately 2 μm in the exponential growth phase on LB medium (Fig. 1) and both strains are macerating potato tubers (Additional file 1: Figure S1). They are forming isolated colonies after 24 h at 28 °C on LB-15 g agar medium and after 48 h at 28 °C on TSA 10% medium (1,5 g tryptone, 0,5 g soy peptone, 0,5 g NaCl, 15 g agar per one liter of medium) and are inducing pits in CVP medium after 48 h at 28 °C.
Fig. 1

Photomicrographs of Gram stained exponentially growing “P. peruviense” cells. (a) strain A97-S13-F16, (b) A350-S18-N16. A light microscope with 100X magnification was used. These photomicrographs show the rod shaped forms of both strains. The bar scale represent 5 μm

Amplification and sequencing of the gapA house keeping gene was recently described to rapidly characterize the different Pectobacterium species [15]. The gapA sequences of strains A97-S13-F16 and A350-S18-N16 clustered with the one of proposed “P. peruviense” type strain (Fig. 2A) and the clusterization of both strains with “P. peruviense” was confirmed through MLSA analysis of full genomes (Fig. 2B).
Fig. 2

Phylogenetic trees of “P. peruviense” strains and strains of other Pectobacterium species and subspecies. a Phylogenetic tree constructed from the gapA nucleotide sequences. Sequences were aligned using the MUSCLE software [24] and the alignments were filtered by using the program GBLOCKS [25].Tree was computed using PHYML [26]. One hundred bootstrap replicates were performed to assess the statistical support of each node. Bootstrap support values (percentages) are indicated if superior to 95%. gapA sequences were retrieved from full genome of type strains (accession numbers are indicated in Fig. 1b) or obtained from the sequenced gapA amplicon for strains A97-S13-F16 and A350-S18-N16. b Phylogenetic tree constructed from concatenated sequences of 1266 homologous amino acid sequences. Before concatenation, the homologous sequences of each gene were aligned using the MUSCLE software [24] and the alignments were filtered by using the program GBLOCKS [25]. Tree was computed using PHYML [26]. One hundred bootstrap replicates were performed to assess the statistical support of each node. Bootstrap support values (percentages) are shown if less than 100%. The accession number for each genome is indicated inside brackets after the strain name. Dickeya solani RNS08.23.3.1.A was used as outgroup. Type strains are marked with T after the strain name

General feature of A97-S13-F16 and A350-S18-N16 are indicated in Table 1.
Table 1

Classification and general features of strains A97-S13-F16 and A350-S18-N16

MIGS ID

Property

Term

Evidence codea

 

Classification

Domain Bacteria

TAS [14]

  

Phylum Proteobacteria

TAS [15]

  

Class Gammaproteobacteria

TAS [16]

  

Order Enterobacterale

TAS [17]

  

Family Pectobacteriaceae

TAS [17]

  

Genus Pectobacterium

TAS [18]

  

Species Pectobacterium peruviense

NAS

  

strains: A97-S13-F16 and A350-S18-N16

 
 

Gram stain

Negative

NAS

 

Cell shape

Rod

IDA

 

Motility

Motile

IDA

 

Sporulation

Non sporulating

NAS

 

Temperature range

Able to grow at 25 °C–28 °C

IDA

 

Optimum temperature

Able to grow at 20 °C–30 °C

NAS

 

pH range; Optimum

Unknown

NAS

 

Carbon source

Ability to degrade polypectate

IDA

MIGS-6

Habitat

Isolated from water,

IDA

MIGS-6.3

Salinity

Able to grow in 1% NaCL

IDA

MIGS-22

Oxygen requirement

Facultative anaerobic

NAS [17]

MIGS-15

Biotic relationship

Free-living

IDA

MIGS-14

Pathogenicity

Ability to rot potato tubers

IDA

MIGS-4

Geographic location

A97-S13-F16, river Durance France

IDA

A359-S18-N18, river Bléone France

MIGS-5

Sample collection

A97-S13-F16, 1st February 2016

IDA

A359-S18-N18, 19th November 2016

MIGS-4.1

Latitude

A97-S13-F16, 44.701667

IDA

A359-S18-N18, 44.038631

MIGS-4.2

Longitude

A97-S13-F16, 6.599693

IDA

A359-S18-N18, 5.967728

MIGS-4.4

Altitude

A97-S13-F16, 907 m

IDA

A359-S18-N18, 438 m

a Evidence codes - IDA Inferred from Direct Assay, TAS Traceable Author Statement (i.e., a direct report exists in the literature), NAS Non-traceable Author Statement (i.e., not directly observed for the living, isolated sample, but based on a generally accepted property for the species, or anecdotal evidence). These evidence codes are from the Gene Ontology project [20]

Genome sequencing information

Genome project history

The aim of the project was to described Pectobacterium sp. isolated from environmental samples outside agricultural context. Fresh water sampling was performed in the river Durance and its tributaries in 2016. Amongst the isolated strains, the two strains A97-S13-F16 and A350-S18-N16, isolated in different locations and at different months in the river stream, were selected for sequencing following amplification and sequencing of their gapA house keeping gene because phylogenetic analysis of their gapA sequences positioned both gapA sequences close to the gapA sequence of the recently proposed “P. peruviense” type strain UGC32 [8, 13, 15].

Growth conditions and DNA isolation

After isolation from fresh water in 2016, strains A97-S13-F16 and A350-S18-N16 have been stored in 40%/60% glycerol /LB medium at − 80 °C. For preparation of genomic DNA, the strains were first grown overnight at 28 °C on solid LB medium. A single colony was then pick up and grown overnight in 2 ml of liquid LB medium at 28 °C with 120 rpm shaking. Bacterial cells were harvested by centrifugation (5 min at 12,000 rpm) and DNA was extracted with the wizard® genomic DNA extraction kit (Promega) following the supplier specification. DNA was suspended in 100 μl of sterile distilled water and the quantity and quality of DNA was assessed by nano-drop measurement, spectrophotometry analysis and gel analysis.

Genome sequencing and assembly

Genome sequencing was performed at the next generation sequencing core facilities of the Institute for Integrative Biology of the Cell, Bât. 21, Avenue de la Terrasse 91,190 Gif-sur-Yvette Cedex France. Nextera DNA libraries were prepared from 50 ng of high quality genomic DNA. Paired end 2 × 75 bp sequencing was performed on an Illumina NextSeq500 instrument, with a High Output 150 cycle kit.

CLC Genomics Workbench (Version 9.5.2, Qiagen Bioinformatics) was used to assemble 30,066,500 (mean length 53 bp) and 8,174,334 reads (mean length 52 bp) for strains A97-S13-F16 and A350-S18-N16 respectively. Final sequencing coverages were 331× and 86× with 61 and 73 scaffolds for strains A97-S13-F16 and A350-S18-N16 respectively (Table 2).
Table 2

Genome sequencing project information

MIGS ID

Property

P. Peruviense

P. Peruviense

A97-S13-F16

A350-S18-N16

 

Finishing quality

61 scaffolds

73 scaffolds

MIGS-28

Libraries used

Nextera DNA Library

Nextera DNA Library

MIGS 29

Sequencing platforms

Illumina NS500

Illumina NS500

MIGS 31.2

Fold coverage

331X

86X

MIGS 30

Assemblers

CLC Genomics

CLC Genomics

Workbench V 9.5.2

Workbench V 9.5.2

MIGS 32

Gene calling method

Glimmer 3

Glimmer 3

 

Locus Tag

A97-S13-F16

A350-S18-N16

 

Genbank ID

PYUO01000000

PYUO0100000

 

GenBank Date of Release

10th july 2018

10th july 2018

 

GOLD ID

  
 

BIOPROJECT

PRJNA445781

PRJNA445781

MIGS 13

Source Material Identifier

CFBP8625 a

CFBP8626 a

 

Project relevance

Environment

Environment

a Strains A97-S13-F16 and A350-S18-N16 are available at the CIRM-CFBP Collection under the indicated numbers

Genome annotation

Coding sequences were predicted using the RAST server [16] with the Glimmer 3 prediction tool [17]. COG assignments and Pfam domain predictions were done using the Web CD-Search Tool [18]. CRISPRFinder [19] was used to detect CRISPRs. Signal peptide and transmembrane domain were detected with the SignalP 4.1 Server [20] and transmembrane helices were predicted with TMHMM [21].

Genomes properties

The “P. peruviense” A97-S13-F16 draft genome contains 4,775,191 bp with a GC content of 51%. Total predicted genes are 4503 while predicted protein coding genes are 4459 and RNA genes 44. The final assembly comprised 61 scaffolds. Among the predicted genes, 72.21% have a predicted function, 79.91% were assigned to COG and 85.40% have a predicted Pfam domain. Among the predicted proteins, 392 have a predicted signal peptide while 1090 contain a predicted transmembrane helix. Three CRIPS repeats array were detected in this genome.

The “P. peruviense” A350-S18-N16 draft genome contains 4,871,019 bp with a GC content of 51,1%. Total predicted genes are 4635 while predicted protein coding genes are 4487 and RNA genes 48. The final assembly comprised 73 scaffolds. Among the predicted genes, 72.01% have a predicted function, 78.77% were assigned to GOG and 85.09% have a predicted Pfam domain. Among the predicted proteins, 395 have a predicted signal peptide while 1095 contain a predicted transmembrane helix. Two CRIPS repeats array were detected in this genome.

The properties and the statistics of the two draft genomes are summarized in Tables 3 and 4.
Table 3

Genome statistics

Attribute

P. peruviense A97-S13-F16

P. peruviense A350-S18-N16

Value

% of Total

Value

% of Total

Genome size (pb)

4,755,191

100.00

4,871,019

100.00

DNA coding (bp)

4,108,775

86.41

4,211,847

86.47

DNA G + C (pb)

2,425,147

51.00

2,489,091

51.10

DNA scaffolds

61

 

73

 

Total genes

4503

100.00

4635

100.00

Protein coding genes

4459

99.02

4587

98.96

RNA genes

44

0.97

48

1.03

Pseudo genes

NA

 

NA

 

Genes in internal clusters

NA

 

NA

 

Genes with function prediction

3252

72.21

3338

72.01

Genes assigned to COGs

3563

79.91

3613

78.77

Genes with Pfam domains

3808

85.40

3903

85.09

Genes with signal peptides

392

8.79

395

8.52

Genes with transmembrane helices

1090

24.44

1095

23.62

CRISPR repeats

3

 

2

 
Table 4

Number of genes associated with the 25 COG functional categories

Code

P. peruviense

P. peruviense

Description

A97-S13-F16

A350-S18-N16

Value

%age

Value

%age

E

366

8.21

367

8.00

Amino acid transport and metabolism

G

362

8.12

356

7.76

Carbohydrate transport and metabolism

D

41

0.92

43

0.94

Cell cycle control, cell division, chromosome partitioning

N

110

2.47

107

2.33

Cell motility

M

239

5.36

244

5.32

Cell wall/membrane/envelope biogenesis

H

167

3.75

167

3.64

Coenzyme transport and metabolism

Z

1

0.02

1

0.02

Cytoskeleton

V

85

1.91

90

1.96

Defense mechanisms

C

226

5.07

225

4.91

Energy production and conversion

W

4

0.09

4

0.09

Extracellular structures

S

202

4.53

209

4.56

Function unknown

G

204

4.58

206

4.49

General function prediction only

P

242

5.43

240

5.23

Inorganic ion transport and metabolism

U

82

1.84

91

1.98

Intracellular trafficking, secretion, and vesicular transport

I

103

2.31

102

2.20

Lipid transport and metabolism

X

23

0.52

57

1.24

Mobilome: prophages, transposons

F

90

2.02

91

1.98

Nucleotide transport and metabolism

O

152

3.41

152

3.31

Posttranslational modification, protein turnover, chaperones

L

127

2.85

127

2.77

Replication, recombination and repair

A

1

0.02

1

0.02

RNA processing and modification

Q

59

1.32

59

1.29

Secondary metabolites biosynthesis, transport and catabolism

T

146

3.27

148

3.23

Signal transduction mechanisms

K

291

6.53

287

6.26

Transcription

J

238

5.34

239

5.21

Translation, ribosomal structure and biogenesis

898

20.14

974

21.23

Not in COGs

The total %age is based on the total number of protein coding genes in the genome

Insight from genome sequences

Genome comparison between A97-S13-F16 and A350-S18-N16 and the genome of representative species of the Pectobacterium genus

A phylogenetic tree, constructed from concatenated sequences of 1266 homologs proteins, clustered the A97-S13-F16 and A350-S18-N16 strains together, close to UGC32 the proposed “P. peruviense” type strain (Fig. 1B). ANIb were further calculated between genomes of strains A97-S13-F16 and A350-S18-N16 and the genomes of described Pectobacterium species and subspecies (Additional file 2: Table S1). Pairwise ANIb values between the three “P. peruviense” genomes, A97-S13-F16 and A350-S18-N16 and UGC32, were above 97,5%. Pairewise ANIb values of these three “P. peruviense” genomes with genomes of other Pectobacterium species and subspecies were below 94%. dDDH is an in silico method to approach the wet-lab DDH method as closely as possible [22]. dDDH were calculated between the genomes of A97-S13-F16 and A350-S18-N16 and Pectobacterium genomes representative of known species and subspecies (Additional file 2: Table S1). dDDH values between A350-S18-N16, A97-S13-F16 genomes and the proposed “P. peruviense” UGC32 genomes were above 79%, well above the 70% species boundary. When pairwise calculations were performed between these three genomes with those of known Pectobacterium species and subspecies the estimated dDDH values dropped below 54%, well below the species boundary. This confirmed that A97-S13-F16 and A350-S18-N16 belong to the “P. peruviense” specie.

Genomes comparison between the “P. peruviense” strains

The phylogenetic trees (Fig. 2) indicate that strains A97-S13-F16 and A350-S18-N16 are more closely related to each other than they are from the “P. peruviense” type strain UGC32. To further gain insight into the distance between the three “P. peruviense” strains, we looked for shared and unique genes between genomes of strains A97-S13-F16, A350-S18-N16 and UGC32 type strain (Fig. 3). A97-S13-F16, A350-S18-N16 and UGC32 strains contain respectively a pool of specific genes of 292, 414 and 346. The slightly higher pool of specific genes observed in strain A350-S18-N16 could be partly related to its higher content of mobile genetic elements inserted in its genome as described in Table 4. Indeed, we observed 3 clusters of phage-related genes in strain A350-S18-N16, only one being also detected in strain A97-S13-F16. The Venn diagram indicated that 4129 genes are shared between strains A97-S13-F16 and A350-S18-N16 while only 3757 and 3765 genes are respectively shared between the type strain UGC32 and A97-S13-F16 / A350-S18-N16. This confirmed that A97-S13-F16 and A350-S18-N16 genomes are more closely related to each other than they are with the genome of the proposed type strain UGC32.
Fig. 3

Venn diagram. Shared and unique genes between the genomes of “P. peruviense” A97-S13-F16 and A350-S18-N16 and the proposed “P. peruviense” type strain UGC32. Orthology was assumed using a threshold of 80% identity on at least 80% of the protein length

Conclusions

In this study we presented the draft genome sequences of two strains of “P. peruviense” isolated from fresh water in river stream in France. The “P. peruviense” specie has recently been proposed and, until our study, the described strains belonging to the “P. peruviense” specie have all been isolated on potato tubers in the altiplano in Peru [8]. The presence of strains belonging to the “P. peruviense” specie in two independent environmental samples in France indicates that the geographic distribution of this specie is likely to be larger than previously anticipated. Both French strains are able to rot potato tubers like the proposed type strain UG32. The two French isolates are more closely related to each other than they are with the type strain UGC32. Whether this reflects the geographic provenance (France vs Peru) or the niche provenance (water vs diseased plants) is unknown.

Notes

Acknowledgements

This work has benefited from the expertise of the High-Throughput Sequencing Platform of I2BC, Gif sur Yvette, France. We thank our British colleague Emma Rochelle Newall for english editing of the manuscript. We thank Odile Berge and Frédérique Van Gijsegem for their help during river samplings and Ariane Toussaint and Antoine Pourbaix for hosting us during the field samplings.

Funding

This work is supported by Agence Nationale de la Recherche (COMBICONTROL, grant ANR-15-CE21–0003) and CNRS program (EC2CO- Biohefect/Ecodyn//Dril/MicrobiEenCARTOBACTER).

Availability of data and materials

This Whole Genome Shotgun project has been deposited at DDBJ/ENA/GenBank under the accessions PYUO00000000 and PYUP00000000. The versions described in this paper are versions PYUO01000000 and PYUP01000000. The strains are available at the CIRM CFBP.

Authors’ contributions

BMA initiated the study and provided and background information. BMA and CB isolated the strains. CB performed the gapA amplification and phylogenetic analysis, isolated the DNA for sequencing and performed the microscopy analysis. JP and FP assembled, analyzed the genomes and conducted the MLSA analysis. BMA and JP wrote the manuscript. All authors read and approved the final manuscript.

Ethics approval and consent to participate

not applicable.

Consent for publication

not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary material

40793_2018_332_MOESM1_ESM.docx (9.6 mb)
Additional file 1: FigureS1. Symptoms observed on potato tubers. Overnight cultures of bacterial strains A97-S13-F16 and A350-S18-N16 were suspended in 50 mM phosphate buffer pH 6.8 and adjusted to 1.0 at OD580nm. Tubers of S. tuberosum var. charlotte were inoculated with 10 μl of the cell suspension and placed at room temperature on wet paper towel in a plastic box. Six days post-infection, tubers were cut in half and representative symptoms are shown: A: A97-S13-F16, B: A350-S18-N16, C: 50 mM phosphate buffer pH 6.8. (DOCX 9779 kb)
40793_2018_332_MOESM2_ESM.docx (80 kb)
Additional file 2: Table S1. ANIb and dDDH pairwise values. dDDH and ANIb are respectively presented in the upper and lower part of the matrix triangle. Strains belonging to the same species are highlighted in red. Specific threshold value is 96% for ANIb and 70% for DDH. ANIb values were computed using the Blast algorithm of the Jspecies package [23]. dDDH were calculated according to [22]. (DOCX 79 kb)

References

  1. 1.
    Skerman VB, McGowan V, Sneath PH. Approved lists of bacterial names. Int J Syst Bacteriol. 1980;30:225–420.CrossRefGoogle Scholar
  2. 2.
    Ma B, Hibbing ME, Kim H-S, Reedy RM, Yedidia I, Breuer J, et al. Host range and molecular phylogenies of the soft rot Enterobacterial genera Pectobacterium and Dickeya. Phytopathology. 2007;97:1150–63.CrossRefGoogle Scholar
  3. 3.
    Pérombelon M, Kelman A. Ecology of the soft rot Erwinias. Annu Rev Phytopathol. 1980;18:361–87.CrossRefGoogle Scholar
  4. 4.
    Gardan L, Gouy C, Christen R, Samson R. Elevation of three subspecies of Pectobacterium carotovorum to species level: Pectobacterium atrosepticum sp. nov., Pectobacterium betavasculorum sp. nov. and Pectobacterium wasabiae sp. nov. Int J Syst Evol Microbiol. 2003;53:381–91.CrossRefGoogle Scholar
  5. 5.
    Nabhan S, De Boer SH, Maiss E, Wydra K. Pectobacterium aroidearum sp. nov., a soft rot pathogen with preference for monocotyledonous plants. Int J Syst Evol Microbiol. 2013;63:2520–5.CrossRefGoogle Scholar
  6. 6.
    Dees MW, Lysøe E, Rossmann S, Perminow J, Brurberg MB. Pectobacterium polaris sp. nov., isolated from potato (Solanum tuberosum). Int J Syst Evol Microbiol. 2017;67:5222–9.CrossRefGoogle Scholar
  7. 7.
    Khayi S, Cigna J, Chong T, Quêtu-Laurent A, Chan K, Helias V, et al. Transfer of the potato plant isolates of Pectobacterium wasabiae to Pectobacterium parmentieri sp. nov. Int J Syst Evol Microbiol. 2016;66:5379–83.CrossRefGoogle Scholar
  8. 8.
    Waleron M, Misztak A, Waleron M, Franczuk M, Wielgomas B, Waleron K. Transfer of Pectobacterium carotovorum subsp. carotovorum strains isolated from potatoes grown at high altitudes to Pectobacterium peruviense sp. nov. Syst Appl Microbiol. 2018;41:85–93.CrossRefGoogle Scholar
  9. 9.
    Hauben L, Moore ERB, Vauterin L, Steenackers M, Mergaert J, Verdonck L, et al. Phylogenetic position of Phytopathogens within the Enterobacteriaceae. Syst Appl Microbiol. 1998;21:384–97.CrossRefGoogle Scholar
  10. 10.
    List Editor: Validation List no. 68. Validation of publication of new names and new combinations previously effectively published outside the IJSB. Int J Syst Bacteriol. 1999;49:1–3.CrossRefGoogle Scholar
  11. 11.
    Koh Y, Kim G, Lee Y, Sohn S, Koh H, Kwon S, et al. Pectobacterium carotovorum subsp. actinidiae subsp. nov., a new bacterial pathogen causing canker-like symptoms in yellow kiwifruit, Actinidia chinensis. N Z J Crop Hortic Sci. 2012;40:269–79.CrossRefGoogle Scholar
  12. 12.
    Nabhan S, De Boer SH, Maiss E, Wydra K. Taxonomic relatedness between Pectobacterium carotovorum subsp. carotovorum, Pectobacterium carotovorum subsp. odoriferum and Pectobacterium carotovorum subsp. brasiliense subsp. nov. J Appl Microbiol. 2012;113:904–13.CrossRefGoogle Scholar
  13. 13.
    Panda P, Fiers MWEJ, Lu A, Armstrong KF, Pitman AR. Draft genome sequences of three Pectobacterium strains causing blackleg of potato: P. carotovorum subsp. brasiliensis ICMP 19477, P. atrosepticum ICMP 1526, and P. carotovorum subsp. carotovorum UGC32. Genome Announc. 2015;3:e00874–15.PubMedPubMedCentralGoogle Scholar
  14. 14.
    Hélias V, Hamon P, Huchet E, Wolf JVD, Andrivon D. Two new effective semiselective crystal violet pectate media for isolation of Pectobacterium and Dickeya: isolating pectolytic bacteria on CVP. Plant Pathol. 2012;61:339–45.CrossRefGoogle Scholar
  15. 15.
    Cigna J, Dewaegeneire P, Beury A, Gobert V, Faure D. A gapA PCR-sequencing assay for identifying the Dickeya and Pectobacterium potato pathogens. Plant Dis. 2017;101:1278–82.CrossRefGoogle Scholar
  16. 16.
    Aziz RK, Bartels D, Best AA, DeJongh M, Disz T, Edwards RA, et al. The RAST server: rapid annotations using subsystems technology. BMC Genomics. 2008;9:75.CrossRefGoogle Scholar
  17. 17.
    Delcher AL, Harmon D, Kasif S, White O, Salzberg SL. Improved microbial gene identification with GLIMMER. Nucleic Acids Res. 1999;27:4636–41.CrossRefGoogle Scholar
  18. 18.
    Marchler-Bauer A, Bryant SH. CD-search: protein domain annotations on the fly. Nucleic Acids Res. 2004;32:W327–31.CrossRefGoogle Scholar
  19. 19.
    Grissa I, Vergnaud G, Pourcel C. CRISPRFinder: a web tool to identify clustered regularly interspaced short palindromic repeats. Nucleic Acid Res. 35: W52–W57.CrossRefGoogle Scholar
  20. 20.
    Petersen TN, Brunak S, von HG, Nielsen H. SignalP 4.0: discriminating signal peptides from transmembrane regions. Nat Methods. 2011;8:785–6.CrossRefGoogle Scholar
  21. 21.
    Krogh A, Larsson B, von Heijne G, Sonnhammer EL. Predicting transmembrane protein topology with a hidden markov model: application to complete genomes11Edited by F. Cohen. J Mol Biol. 2001;305:567–80.CrossRefGoogle Scholar
  22. 22.
    Meier-Kolthoff JP, Auch AF, Klenk HP, Göker M. Genome sequence-based species delimitation with confidence intervals and improved distance functions. BMC Bioinformatics. 2013;14:60.CrossRefGoogle Scholar
  23. 23.
    Richter M, Rosselló-Móra R, Oliver Glöckner F, Peplies J. JSpeciesWS: a web server for prokaryotic species circumscription based on pairwise genome comparison. Bioinforma Oxf Engl. 2016;32:929–31.CrossRefGoogle Scholar
  24. 24.
    Edgar RC. MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics. 2004;5:113.CrossRefGoogle Scholar
  25. 25.
    Castresana J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol Biol Evol. 2000;17:540–52.CrossRefGoogle Scholar
  26. 26.
    Guindon S, Gascuel O. A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst Biol. 2003;52:696–704.CrossRefGoogle Scholar

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© The Author(s). 2018

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors and Affiliations

  1. 1.Institute of Ecology and Environmental sciences-ParisSorbonne Université, INRAParisFrance

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