| Literature DB >> 30344890 |
Pierre Faye1, Claire Bertrand1, Jacques Pédron1, Marie-Anne Barny1.
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.Entities:
Keywords: France; Pectobacterium peruviense; Plant pathogen; Soft rot; Water
Year: 2018 PMID: 30344890 PMCID: PMC6186074 DOI: 10.1186/s40793-018-0332-0
Source DB: PubMed Journal: Stand Genomic Sci ISSN: 1944-3277
Fig. 1Photomicrographs 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
Fig. 2Phylogenetic 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
Classification and general features of strains A97-S13-F16 and A350-S18-N16
| MIGS ID | Property | Term | Evidence codea |
|---|---|---|---|
| Classification | Domain | TAS [ | |
| Phylum | TAS [ | ||
| Class | TAS [ | ||
| Order | TAS [ | ||
| Family | TAS [ | ||
| Genus | TAS [ | ||
| Species | NAS | ||
| strains: | |||
| Gram stain |
| NAS | |
| Cell shape |
| IDA | |
| Motility |
| IDA | |
| Sporulation |
| NAS | |
| Temperature range |
| IDA | |
| Optimum temperature |
| NAS | |
| pH range; Optimum |
| NAS | |
| Carbon source |
| IDA | |
| MIGS-6 | Habitat |
| IDA |
| MIGS-6.3 | Salinity |
| IDA |
| MIGS-22 | Oxygen requirement |
| NAS [ |
| MIGS-15 | Biotic relationship |
| IDA |
| MIGS-14 | Pathogenicity |
| IDA |
| MIGS-4 | Geographic location |
| IDA |
|
| |||
| MIGS-5 | Sample collection |
| IDA |
|
| |||
| MIGS-4.1 | Latitude |
| IDA |
|
| |||
| MIGS-4.2 | Longitude |
| IDA |
|
| |||
| MIGS-4.4 | Altitude |
| IDA |
|
|
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 project information
| MIGS ID | Property |
|
|
|---|---|---|---|
| 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 statistics
| Attribute | ||||
|---|---|---|---|---|
| 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 | ||
Number of genes associated with the 25 COG functional categories
| Code |
|
| 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
Fig. 3Venn 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