Open Access

Complete genome sequence of the plant-associated Serratia plymuthica strain AS13

  • Saraswoti Neupane
  • , Roger D. Finlay
  • , Nikos C. Kyrpides
  • , Lynne Goodwin,
  • , Sadhna Alström
  • , Susan Lucas
  • , Miriam Land,
  • , James Han
  • , Alla Lapidus
  • , Jan-Fang Cheng
  • , David Bruce,
  • , Sam Pitluck
  • , Lin Peters
  • , Galina Ovchinnikova
  • , Brittany Held,
  • , Cliff Han,
  • , John C. Detter,
  • , Roxanne Tapia,
  • , Loren Hauser,
  • , Natalia Ivanova
  • , Ioanna Pagani
  • , Tanja Woyke
  • , Hans-Peter Klenk
  • and Nils Högberg

DOI: 10.4056/sigs.2966299

Received: 26 September 2012

Published: 10 October 2012


Serratia plymuthica AS13 is a plant-associated Gammaproteobacteria, isolated from rapeseed roots. It is of special interest because of its ability to inhibit fungal pathogens of rapeseed and to promote plant growth. The complete genome of S. plymuthica AS13 consists of a 5,442,549 bp circular chromosome. The chromosome contains 4,951 protein-coding genes, 87 tRNA genes and 7 rRNA operons. This genome was sequenced as part of the project entitled “Genomics of four rapeseed plant growth promoting bacteria with antagonistic effect on plant pathogens” within the 2010 DOE-JGI Community Sequencing Program (CSP2010).




The members of the genus Serratia are widely distributed in nature. They are commonly found in soil, water, plants, insects, and other animals including humans [1]. The genus includes biologically and ecologically diverse species – from those beneficial to economically important plants, to pathogenic species that are harmful to humans. The plant-associated species comprise both endophytes and free living taxa, such as S. proteamaculans, S. plymuthica, S. liquefaciens and S. grimesii. Most of them are of interest because of their ability to promote plant growth and inhibit plant pathogenic fungi [2-6].

There are currently 16 validly named Serratia species. However, there are several unidentified plant-associated Serratia strains that have an impact on agriculture by stimulating plant growth and/or inhibiting soil borne plant pathogens [3]. S. plymuthica AS13 was isolated from rapeseed roots from Uppsala, Sweden. Our interest in S. plymuthica AS13 is due to its ability to stimulate rapeseed plant growth and to inhibit soil borne fungal pathogens such as Verticillium dahlia and Rhizoctonia solani [6]. Here we present a description of the complete genome of S. plymuthica AS13 and its annotation.

Classification and features

A representative sequence of the 16S rRNA gene of S. plymuthica AS13 was compared with the most recently released GenBank databases using NCBI BLAST [7] under default settings. It showed that the strain AS13 shares 99-100% similarity with the genus Serratia. When considering high-scoring segment pairs (HSPs) from the best 250 hits, the most frequent matches were several unspecified Serratia strains (17.2%) with maximum identity of 97-100%, while S. plymuthica (5.2%) had maximum identity of 97-100%, S. proteamaculans (4.8%) maximum identity of 97-99%, S. marcescens (4.8%) maximum identity of 96-97% and also different Rahnella strains (7%) maximum identity of 97-98%.

The phylogenetic relationship of S. plymuthica AS13 is shown in Figure 1 in a 16S rRNA based tree. All Serratia lineages clustered together and were distinct from other enterobacteria (except Obesumbacterium proteus). The tree also shows its very close relation with S. plymuthica strains AS9 and AS12, which was confirmed by digital DNA-DNA hybridization values [12] above 70% when compared with the (unpublished) draft genome sequence of the S. plymuthica type strain Breed K-7T from a culture of DSM 4540, and when compared with the complete genome sequences of S. plymuthica AS9 [13] and S. plymuthica AS12 [14] using the GGDC web server [15].

Figure 1

Phylogenetic tree highlighting the position of S. plymuthica AS13 in relation to other genera within the family Enterobacteriaceae, based on 1,472 characters of the 16S rRNA gene sequence aligned in ClustalW2 [8]. The tree was constructed under the maximum likelihood criterion using MEGA5 software [9] and rooted with Xanthomonas cucurbitae (a member of the Xanthomonadaceae family). The branches are scaled based on the expected number of substitutions per site. The numbers above branches are support values from 1,000 bootstrap replicates if larger than 60% [10]. The lineages shown in blue color are the genome sequences of bacterial strains that are registered in GOLD [11].

Strain AS13 is a rod shaped bacterium, 1-2 µm long, 0.5-0.7 µm wide (Figure 2 and Table 1), is Gram-negative, motile, and a member of the family Enterobacteriaceae. The bacterium is a facultative anaerobe and grows within the temperature range 4 °C - 40 °C and within a pH range of 4 - 10. It has chitinolytic, cellulolytic, proteolytic, and phospholytic activity [6] and can easily grow on different carbon sources such as glucose, cellobiose, succinate, mannitol, arabinose and inositol. It forms red to pink colored colonies that are 1-2 mm in diameter on potato dextrose agar at low temperature. The color of the bacterium depends on the growth substrate, temperature and pH of the culture medium [30]. The bacterium is deposited in the Culture Collection, University of Göteborg, Sweden (CCUG) as S. plymuthica AS13 (= CCUG 61398).

Figure 2

Scanning electron micrograph of S. plymuthica AS13

Table 1

Classification and general features of S. plymuthica AS13 according to the MIGS recommendations [16]




     Evidence codea

    Domain Bacteria

     TAS [17]

    Phylum Proteobacteria

     TAS [18]

    Class Gammaproteobacteria

     TAS [19,20]

    Current classification

    Order “Enterobacteriales

     TAS [21]

    Family Enterobacteriaceae

     TAS [22-24]

    Genus Serratia

     TAS [22,25,26]

    Species Serratia plymuthica

     TAS [22,27]

    Strain AS13


    Gram stain



    Cell shape









    Temperature range



    Optimum temperature



    Carbon source

    Glucose, inositol, arabinose, succinate, sucrose, fructose


    Energy metabolism





    Rapeseed roots











    Biotic relationship

    Plant associated

     TAS [6]





    Biosafety level


     TAS [28]


    Geographic location

    Uppsala, Sweden



    Sample collection time

    Summer 1998












    0.1 m




    24-25 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 [29]. If the evidence code is IDA, then the property should have been directly observed, for the purpose of this specific publication, for a live isolate by one of the authors, or an expert or reputable institution mentioned in the acknowledgements.


Little is known about the chemotaxonomy of S. plymuthica AS13. Fatty acid methyl ester (FAME) analysis showed the main fatty acid in strain AS13 comprises C16:0 (25.27%), C16:1ω7c (15.41%), C18:1ω7c (18.17%), C14:0 (5.21%), C17:0 cyclo (18.53%), along with other minor fatty acid components. Previously it has been shown that Serratia spp. contain a mixture of C14:0, C16:0, C16:1 and C18:1+2 fatty acids in which 50-80% of the total fatty acid in the cell is C14:0 and other fatty acids are less than 3% each [31]. This is consistent with the fact that C14:0 fatty acid is characteristic of the family Enterobacteriaceae.

Genome sequencing information

S. plymuthica AS13, a bacterial strain isolated from rapeseed roots was selected for sequencing on the basis of its biocontrol activity against fungal pathogens of rapeseed and its plant growth promoting ability. The genome project is deposited in the Genomes On Line Database [11] (GOLD ID = Gc01776) and the complete genome sequence is deposited in GenBank (INSDC ID = CP002775). Sequencing, finishing and annotation were performed by the DOE Joint Genome Institute (JGI). A summary of the project information is shown in Table 2 and its association with MIGS identifiers.

Table 2

Genome sequencing project information





    Finishing quality



    Libraries used

      Three libraries: one 454 standard library,      one paired end 454 library (9.0 kb insert size) and one Illumina library)


    Sequencing platforms

      Illumina GAii, 454 GS FLX Titanium


    Fold coverage

      262.2 × Illumina, 8.7 × pyrosequencing



      Newbler version 2.3, Velvet 1.0.13, phrap version SPS - 4.24


    Gene calling method

      Prodigal 1.4, GenePRIMP

    NCBI project ID




    Genbank Date of Release

      October 12, 2011



    Project relevance

      Biocontrol, Agriculture

Growth conditions and DNA isolation

S. plymuthica AS13 was grown in Luria Broth (LB) medium at 28 °C until early stationary phase. The DNA was extracted from the cells by using a standard CTAB protocol for bacterial genomic DNA isolation that is available at JGI [32].

Genome sequencing and assembly

The genome of S. plymuthica AS13 was sequenced using a combination of Illumina and 454 sequencing platforms. The details of library construction and sequencing can be found at the JGI [32]. The sequence data from Illumina GAii (1,457.3 Mb) were assembled with Velvet [33] and the consensus sequence was computationally shredded into 1.5 kb overlapping fake reads. The sequencing data from 454 pyrosequencing (79.5 Mb) were assembled with Newbler and consensus sequences were computationally shredded into 2 kb overlapping fake reads. The initial draft assembly contained 86 contigs in 1 scaffold. The 454 Newbler consensus reads, the Illumina Velvet consensus reads and the read pairs in the 454 paired end library were assembled and quality assessment performed in the subsequent finishing process by using software phrap package [34-37]. Possible mis-assemblies were corrected with gapResolution [32], Dupfinisher [38], or by sequencing cloned bridging PCR fragments with subcloning. The gaps between contigs were closed by editing in the software Consed [37], by PCR and by Bubble PCR primer walks (J.-F. Chang, unpublished). Fifty one additional reactions were necessary to close gaps and to raise the quality of the finished sequence. The sequence reads from Illumina were used to correct potential base errors and increase consensus quality using the software Polisher developed at JGI [39]. The final assembly is based on 46.8 Mb of 454 draft data which provides an average 8.7 × coverage of the genome and 1,415.6 Mb of Illumina draft data which provides an average 262.2 × coverage of the genome.

Genome annotation

The S. plymuthica AS13 genes were identified using Prodigal [40] as part of the genome annotation pipeline at Oak Ridge National Laboratory (ORNL), Oak Ridge, TN, USA, followed by a round of manual curation using the JGI GenePRIMP pipeline [41]. The predicted CDS were translated and used to search the National Center for Biotechnology Information (NCBI) nonredundant database, Uniport, TIGR-Fam, Pfam, PRIAM, KEGG, COG and InterPro databases. Non-coding genes and miscellaneous features were predicted using tRNAscan-SE [42], RNAmmer [43], Rfam [44], TMHMM [45], and signalP [46]. Additional gene prediction analysis and functional annotation was performed within the Integrated Microbial Genomes – Expert Review (IMG-ER) platform developed by the Joint Genome Institute, Walnut Creek, CA, USA [47].

Genome properties

The genome of S. plymuthica AS13 has a single circular chromosome of 5,442,549 bp with 55.96% GC content (Table 3 and Figure 3). It has 5,139 predicted genes, of which 4,951 were assigned as protein-coding genes. Among them, most of the protein coding genes (84.41%) were functionally assigned while the remaining ones were annotated as hypothetical proteins. 112 genes were assigned as RNA genes and 76 as pseudogenes. The distribution of genes into COG functional categories is presented in Table 4.

Table 3

Genome statistics



   % of totala

Genome size (bp)



DNA Coding region (bp)



DNA G+C content (bp)



Total genes



RNA genes



rRNA operons



Protein-coding genes






Genes in paralog clusters



Genes assigned to COGs



Genes assigned in Pfam domains



Genes with signal peptides



Genes with transmembrane helices



CRISPR repeats


   % of totala

a) The total is based on either the size of the genome in base pairs or the total number of protein coding genes in the annotated genome.

Figure 3

Graphical circular map of the chromosome. From outside to the center: Genes on forward strand (color by COG categories), Genes on reverse strand (color by COG categories), RNA genes (tRNAs blue, rRNAs red, other RNAs black), GC content, GC skew.

Table 4

Number of genes associated with the 25 general COG functional categories



    % age





      Translation, ribosomal structure and biogenesis




      RNA processing and modification








      Replication, recombination and repair




      Chromatin structure and dynamics




      Cell division and chromosome partitioning




      Nuclear structure




      Defense mechanisms




      Signal transduction mechanisms




      Cell envelope biogenesis, outer membrane




      Cell motility and secretion








      Extracellular structure




      Intracellular trafficking and secretion




      Posttranslational modification, protein turnover, chaperones




      Energy production and conversion




      Carbohydrate transport and metabolism




      Amino acid transport and metabolism




      Nucleotide transport and metabolism




      Coenzyme metabolism




      Lipid metabolism




      Inorganic ion transport and metabolism




      Secondary metabolite biosynthesis, transport and catabolism




      General function prediction only




      Function unknown




      Not in COG



We gratefully acknowledge the help of Elke Lang for providing cell cultures of the reference bacterial strain, Evelyne-Marie Brambilla for extraction of DNA and Anne Fiebig for assembly of the reference genome required for digital DNA-DNA hybridizations (all at DSMZ). The work conducted by the US Department of Energy Joint Genome Institute is supported by the Office of Science of the US Department of Energy under Contract No. DE-AC02-05CH11231.

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


  1. Grimont F, Grimont PAD. (1992). The genus Serratia. In: Balows A, Trüper HG, Dworkin M, Harder W, Schleifer KH (eds) The Prokaryotes, pp 2822-2848. Springer, New York.
  2. Kalbe C, Marten P and Berg G. Strains of genus Serratia as beneficial rhizobacteria of oilseed rape with antifungal properties. Microbiol Res. 1996; 151:433-439 View ArticlePubMed
  3. Müller H and Berg G. Impact of formulation procedures on the effect of the biocontrol agent Serratia plymuthica HRO-C48 on Verticillium wilt in oilseed rape. BioControl. 2008; 53:905-916 View Article
  4. Kurze S, Bahl H, Dahl R and Berg G. Biological control of fungal strawberry diseases by Serratia plymuthica HRO-C48. Plant Dis. 2001; 85:529-534 View Article
  5. Taghavi S, Garafola C, Monchy S, Newman L, Hoffman A, Weyens N, Barac T, Vangronsveld J and van der Lelie D. Genome survey and characterization of endophytic bacteria exhibiting a beneficial effect on growth and development of poplar trees. Appl Environ Microbiol. 2009; 75:748-757 View ArticlePubMed
  6. Alström S. Characteristics of bacteria from oilseed rape in relation to their biocontrol activity against Verticillium dahliae. J Phytopathol. 2001; 149:57-64 View Article
  7. Altschul SF, Thomas LS, Alejandro AS, Jingui Z, Webb M and David JL. Gapped BLAST and PSI-BLAST: A new generation of protein database search programs. Nucleic Acids Res. 1997; 25:3389-3402 View ArticlePubMed
  8. Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, Valentin F, Wallace IM, Wilm A and Lopez R. Clustal W and Clustal X version 2.0. Bioinformatics. 2007; 23:2947-2948 View ArticlePubMed
  9. Tamura K, Peterson D, Peterson N, Stecher G, Nei M and Kumar S. MEGA5: Molecular Evolutionary Genetics Analysis using Maximum Likelihood, Evolutionary Distance, and Maximum Parsimony Methods. Mol Biol Evol. 2011; 28:2731-2739 View ArticlePubMed
  10. Pattengale ND, Alipour M, Bininda-Emonds ORP, Moret BME and Stamatakis A. How many bootstrap replicates are necessary? Lect Notes Comput Sci. 2009; 5541:184-200 View Article
  11. Liolios K, Chen IM, Mavromatis K, Tavernarakis N, Hugenholtz P, Markowitz VM and Kyrpides NC. The Genomes On Line Database (GOLD) in 2009: status of genomic and metagenomic projects and their associated metadata. Nucleic Acids Res. 2009; 38:D346-D354 View ArticlePubMed
  12. Auch AF, von Jan M, Klenk HP and Göker M. Digital DNA-DNA hybridization for microbial species delineation by means of genome-to-genome sequence comparison. Stand Genomic Sci. 2010; 2:117-134 View ArticlePubMed
  13. Neupane S, Högberg N, Alström S, Lucas S, Han J, Lapidus A, Cheng JF, Bruce D, Goodwin L and Pitluck S. Complete genome sequence of the rapeseed plant-growth promoting Serratia plymuthica strain AS9. Stand Genomic Sci. 2012; 6:54-62 View ArticlePubMed
  14. Neupane S, Finlay RD, Alström S, Goodwin L, Kyrpides NC, Lucas S, Lapidus A, Bruce D, Pitluck S and Peters L. Complete genome sequence of Serratia plymuthica strain AS12. Stand Genomic Sci. 2012; 6:165-173 View ArticlePubMed
  15. Auch AF, Klenk HP and Göker M. Standard operating procedure for calculating genome-to-genome distances based on high-scoring segment pairs. Stand Genomic Sci. 2010; 2:142-148 View ArticlePubMed
  16. Field D, Garrity G, Gray T, Morrison N, Selengut J, Sterk P, Tatusova T, Thomson N, Allen MJ and Angiuoli SV. The minimum information about a genome sequence (MIGS) specification. Nat Biotechnol. 2008; 26:541-547 View ArticlePubMed
  17. Woese CR, Kandler O and Wheelis ML. Towards a natural system of organisms: proposal for the domains Archaea, Bacteria and Eucarya. Proc Natl Acad Sci USA. 1990; 87:4576-4579 View ArticlePubMed
  18. Garrity GM, Bell JA, Lilburn T. Phylum XIV. Proteobacteria phyl. nov. In: Garrity GM, Brenner DJ, Krieg NR, Staley JT (eds), Bergey's Manual of Systematic Bacteriology, Second Edition, Volume 2, Part B, Springer, New York, 2005, p. 1.
  19. . Validation of publication of new names and new combinations previously effectively published outside the IJSEM. List no. 106. Int J Syst Evol Microbiol. 2005; 55:2235-2238 View Article
  20. Garrity GM, Bell JA, Lilburn T. Class III. Gammaproteobacteria class. nov. In: Garrity GM, Brenner DJ, Krieg NR, Staley JT (eds), Bergey's Manual of Systematic Bacteriology, Second Edition, Volume 2, Part B, Springer, New York, 2005, p. 1.
  21. Garrity GM, Holt JG. Taxonomic Outline of the Archaea and Bacteria. In: Garrity GM, Boone DR, Castenholz RW (eds), Bergey's Manual of Systematic Bacteriology, Second Edition, Volume 1, Springer, New York, 2001, p. 155-166.
  22. Skerman VBD, McGowan V and Sneath PHA. Approved Lists of Bacterial Names. Int J Syst Bacteriol. 1980; 30:225-420 View Article
  23. Rahn O. New principles for the classification of bacteria. Zentralbl Bakteriol Parasitenkd Infektionskr Hyg. 1937; 96:273-286
  24. . Conservation of the family name Enterobacteriaceae, of the name of the type genus, and designation of the type species OPINION NO. 15. Int Bull Bacteriol Nomencl Taxon. 1958; 8:73-74
  25. Sakazaki R. Genus IX. Serratia Bizio 1823, 288. In: Buchanan RE, Gibbons NE (eds), Bergey's Manual of Determinative Bacteriology, Eighth Edition, The Williams and Wilkins Co., Baltimore, 1974, p. 326.
  26. Bizio B. Lettera di Bartolomeo Bizio al chiarissimo canonico Angelo Bellani sopra il fenomeno della polenta porporina. Biblioteca Italiana o sia Giornale di Letteratura. [Anno VIII]. Scienze e Arti. 1823; 30:275-295
  27. Breed RS, Murray EGD, Hitchens AP. In: Breed RS, Murray EGD, Hitchens AP (eds), Bergey's Manual of Determinative Bacteriology, Sixth Edition, The Williams and Wilkins Co., Baltimore, 1948, p. 481-482.
  28. BAuA. 2010, Classification of bacteria and archaea in risk groups. TRBA 466, p. 200.Web Site
  29. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS and Eppig JT. Gene Ontology: tool for the unification of biology. Nat Genet. 2000; 25:25-29 View ArticlePubMed
  30. Alström S and Gerhardson B. Characteirtics of a Serratia plymuthica isolate from plant rhizospheres. Plant Soil. 1987; 103:185-189 View Article
  31. Bergan T, Grimont AD and Grimont F. Fatty acids of Serratia determined by gas chromatography. Curr Microbiol. 1983; 8:7-11 View Article
  32. . Web Site
  33. Zerbino DR and Birney E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res. 2008; 18:821-829 View ArticlePubMed
  34. Phrap and Phred for Windows. MacOS, Linux, and Unix. Web Site
  35. Ewing B and Green P. Base-Calling of automated sequencer traces using Phred. II. error probabilities. Genome Res. 1998; 8:186-194PubMed
  36. Ewing B, Hillier L, Wendl MC and Green P. Base-Calling of automated sequencer traces using Phred. I. accuracy assessment. Genome Res. 1998; 8:175-185PubMed
  37. Gordon D, Abajian C and Green P. Consed: a graphical tool for sequence finishing. Genome Res. 1998; 8:195-202PubMed
  38. Han C, Chain P. Finishing repeat regions automatically with Dupfinisher. In: Proceeding of the 2006 international conference on bioinformatics & computational biology. Arabina HR, Valafar H (eds), CSREA Press. June 26-29, 2006: 141-146.
  39. Lapidus A, LaButti K, Foster B, Lowry S, Trong S, Goltsman E. POLISHER: An effective tool for using ultra short reads in microbial genome assembly and finishing. AGBT, Marco Island, FL, 2008.
  40. Hyatt D, Chen GL, LoCascio PF, Land ML, Larimer FW and Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics. 2010; 11:119 View ArticlePubMed
  41. Pati A, Ivanova NN, Mikhailova N, Ovchinnikova G, Hooper SD, Lykidis A and Kyrpides NC. GenePRIMP: a gene prediction improvement pipeline for prokaryotic genomes. Nat Methods. 2010; 7:455-457 View ArticlePubMed
  42. Lowe TM and Eddy SR. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res. 1997; 25:955-964PubMed
  43. Lagesen K, Hallin P, Rødland EA, Stærfeldt HH, Rognes T and Ussery DW. RNAmmer: consistent annotation of rRNA genes in genomic sequences. Nucleic Acids Res. 2007; 35:3100-3108 View ArticlePubMed
  44. Griffiths-Jones S, Bateman A, Marshall M, Khanna A and Eddy SR. Rfam: an RNA family database. Nucleic Acids Res. 2003; 31:439-441 View ArticlePubMed
  45. Krogh A, Larsson B, von Heijne G and Sonnhammer ELL. Predicting transmembrane protein topology with a hidden Markov model: Application to complete genomes. J Mol Biol. 2001; 305:567-580 View ArticlePubMed
  46. Bendtsen JD, Nielsen H, von Heijne G and Brunak S. Improved prediction of signal peptides: SignalP 3.0. J Mol Biol. 2004; 340:783-795 View ArticlePubMed
  47. Markowitz VM, Mavromatis K, Ivanova NN, Chen IMA, Chu K and Kyrpides NC. IMG ER: a system for microbial genome annotation expert review and curation. Bioinformatics. 2009; 25:2271-2278 View ArticlePubMed