Abstract
Agromyces aureus AR33T is a Gram-positive, rod-shaped and motile bacterium belonging to the Microbacteriaceae family in the phylum Actinobacteria that was isolated from a former zinc/lead mining and processing site in Austria. In this study, the whole genome was sequenced and assembled combining sequences obtained from Illumina MiSeq and Sanger sequencing. The assembly resulted in the complete genome sequence which is 4,373,124 bp long and has a GC content of 70.1%. Furthermore, we performed a comparative genomic analysis with other related organisms: 6 Agromyces spp., 4 Microbacteriaceae spp. and 2 other members of the class Actinobacteria.
Introduction
Agromyces aureus AR33T is a type strain belonging to the Microbacteriaceae family, Actinobacteria phylum [1]. It is a heavy metal resistant bacteria that was isolated from the rhizosphere of a willow tree ( Salix caprea L.) grown in a heavy metal contaminated site (Arnoldstein, Austria). Among other bacteria isolated from the same source, AR33T was able to significantly increase the extractability of zinc and cadmium from a contaminated soil [2]. Moreover, the inoculation of AR33T in combination with the fungus Cadophora finlandica caused an increase of zinc and cadmium concentration in the shoots of Salix caprea L. plants growing in a heavy metal contaminated soil [3]. Based on these interesting features and the fact that the Agromyces genus is still a relatively unexplored genus, we decided to sequence the whole genome of A. aureus AR33T to gain insights in this genus and the heavy metal resistance and immobilization and mobilization mechanisms. At the time of writing (June 2016), 27 species of the Agromyces genus have been recognized and only nine draft genomes are available in the NCBI database. Here, we present the first complete genome sequence of an Agromyces species, A. aureus AR33T and a comparative analysis with other Agromyces spp. and related members of the class Actinobacteria .
Organism information
Classification and features
A. aureus AR33T is a Gram-positive bacterium having yellow-pigmented colonies (Fig. 1a). Cells are rod shaped and can form curved hyphae (Fig. 1b). Phylogenetic analysis based on 16S rRNA genes of other Agromyces strains and related members of the same family ( Microbacteriaceae ) and class ( Actinobacteria ) is shown in Fig. 2. The general features of the strain are summarized in Table 1. In order to investigate the potential of A. aureus AR33T as plant-associated microbe from a heavy metal contaminated environment, we performed the following additional assays: production of auxins and siderophores, phosphate solubilization, resistance to heavy metals and heavy metal mobilization. To maximize metabolite production necessary for these properties, assays were performed in Landy medium (20 g l−1 glucose, 5 g l−1 glutamate, 0.25 g l−1 MgSO4, 0.25 g l−1 KCl, 0.5 g l−1 KH2PO4, 150 μg l−1 FeSO4, 5 mg l−1 MnSO4, 160 μg l−1 CuSO4, 1 g l−1 yeast extract, pH 7.2) [4], often used for secondary metabolite analysis in gram positive bacteria [5]. The optimal growth temperature and pH values are 28 °C and 6.5–7.5, respectively. AR33T showed oxidase, catalase activity and produced auxins [4, 6]. No phosphate solubilization activity [7] was detected. AR33T is resistant up to 6 mM of zinc and lead and up to 1 mM of cadmium. The production of siderophores was observed using the chrome azurol S assay [8] with Landy (without iron) as growth medium, but not in MM9. The latter is in accordance with a previous study using MM9 [2]. The ability to change the solubility of metals in soil was tested in heavy metal mobilization assays performed as described in [2], but using Landy as growth medium. In Landy, AR33T increased manifold the extractability of lead and iron, whereas the extractability of zinc was slightly increased and the extractability of cadmium, copper and manganese slightly decreased (Fig. 3). Earlier results showed an increase in extractability of both Zn and Cd eased with AR33T in tryptic soy broth [2], suggesting that the production of secondary metabolites such as siderophores and other chelating compounds can be influenced by the growth medium, previously documented for a number of members of the class Actinobacteria [9].
Chemotaxonomic data
A. aureus AR33T has a peptidoglycan type B2γ (D-Glu-L-Dab). Galactose, rhamnose, ribose and fucose constitute the cell-wall sugars. The major cellular fatty acids are anteiso-C15:0, anteiso-C17:0 and iso-C16:0, while diphosphatidylglycerol, glycolipid and phosphatidylglycerol are the predominant polar lipids. The main menaquinones are MK-11, −10 and −12.
Genome sequencing information
Genome project history
The genome of A. aureus AR33T was sequenced by GATC Biotech AG, Konstanz, Germany and subsequently assembled at our institute. The complete genome sequence is available in the NCBI database under the following accession number CP013979. The genome sequencing project information is summarized in Table 2.
Growth conditions and genomic DNA preparation
A. aureus AR33T cells were grown in Landy medium for 48 h at 28 °C with continuous shaking at 200 rpm. DNA was isolated using a phenol-chloroform based protocol. Briefly, cells were collected by centrifugation, re-suspended in lysis buffer (0.1 M NaCl, 0.05 M EDTA pH8, lysozyme 100 mg mL−1) and incubated for 10 min at 37 °C. Subsequently, 5% sarkosyl (sodium lauroyl sarcosinate) was added to the solution that was further incubated on ice for 5 min. DNA was extracted using 1 volume of phenol-chloroform-isoamylalcohol (25:24:1) and treated with RNaseA (20 mg mL−1) to remove RNA. After an additional cleaning step with chloroform, the DNA was precipitated using 2.5 volumes of ice-cold absolute ethanol and 0.1 volumes of 3 M sodium acetate (pH 5.2) and incubated for 3 h at −20 °C. Genomic DNA was collected by centrifugation; the pellet was washed with 70% ethanol and re-suspended in water. The quality and quantity of DNA were assessed on 1% agarose gel and measured with the NanoDrop spectrophotometer.
Genome sequencing and assembly
The whole genome was sequenced using the Illumina MiSeq platform (300 bp paired-end reads). Raw reads were screened for PhiX contamination using Bowtie2 [10]. Adapter- and quality-trimming was performed in Trimmomatic-0.32 [11]. Overlapping reads were subsequently merged using FLASH [12] and long single reads and paired end reads assembled with SPAdes 3.1.0 [13]. The initial assembly consisted in 4 contigs, of which one represented the rRNA genes. The gaps between the contigs were closed by designing primers at each contig edge (Additional file 1: Table S1). The PCR products were cloned and sequenced (Sanger). The 4 contigs and the Sanger sequences were manually assembled resulting in a single contig that could be circularized with Circlator [14]. The assembly quality was estimated in QUAST 2.3 [15] and quality control of mapping data performed in Qualimap 1.0 [16]. Phylosift v1.0.1 [17] was used to identify 38 highly conserved, single-copy marker genes that can be used to assess the completeness of the genome [18, 19]. In A. aureus AR33T all marker genes could be identified and the phylogenetic analysis showed no contamination. The presence of tRNA genes for all essential amino acids was verified using ARAGORN [20].
Genome annotation
The A. aureus AR33T genome was annotated using the NCBI Prokaryotic Genome Annotation Pipeline as well as Prokka [21, 22]. BLASTClust [23] was used to detect genes in internal clusters with the following threshold parameters: 70% covered length and 30% sequence identity. The COG functional categories were assigned through the WebMGA server [24]. The predicted CDSs were used to search against the Pfam database [25] to assign them to the corresponding protein families. SignalP [26] and TMHMM [27] were used to identify genes containing signal peptides and transmembrane helices, respectively. The detailed information about these features is summarized in Tables 3 and 4.
Genome properties
The complete genome of A. aureus AR33T has a total length of 4373124 bp, a CG content of 70.1% and contains three copies of the rRNA operon, of which one has a different 16S rRNA gene sequence (KU141338, KU141339). It has a total of 4005 predicted genes of which 3928 (98.1%) are protein coding genes and 31 are pseudogenes (0.8%). Two thousand nine hundred seventy-nine genes (74.4%) have a functional prediction and 2771 genes (70.5%) could be assigned to a COG functional category (Table 4). Additional information about the genome statistics is shown in Table 3. The map of the genome is represented in Fig. 4.
Insights from the genome sequence
To gain more information about the genome of A. aureus AR33T and about the Agromyces genus in general, we performed comparative genomic analysis using other 6 available Agromyces genomes with high quality assembly (Table 5). All genomes were annotated in Prokka [22] and the predicted genes were used in Roary [28] to calculate the Agromyces pan-genome and core-genome. Since these organisms are members of the same genus but belong to different species, we decided to set the Roary minimum blastp percentage identity at 80%. The choice of this threshold value is supported by the bidirectional best hit analysis performed in RAST [29] (Additional file 1: Figure S1). The Agromyces pan-genome has a total of 14,320 genes: 979 represent the core-genome; 3733 and 9608 form the shell and cloud genome, respectively (Fig. 5a). In particular, 1916 genes of A. aureus AR33T have orthologues in the shell genome and 1014 genes seem to be unique (Fig. 5b). Subsequently, we focused our comparative analysis on the two closest related organisms with a publicly available genome: Agromyces sp. Leaf222 and A. italicus DSM 16388 (Fig. 2, Additional file 1: Figure S2). The genome of A. aureus AR33T and Agromyces sp. Leaf222 seem to be the most similar ones having almost half (1575) of their CDSs sharing at least 80% amino acid similarity. Moreover, these two organisms share 137 COG functional categories and 117 KEGG metabolic pathways (Fig. 5c). Despite being part of the same phylogenetic clade (Fig. 2), A. italicus DSM 16388 seems to have a different set of genes and functionalities compared to A. aureus AR33T and Agromyces sp. Leaf222 (Fig. 5c). Finally, a distinctive feature of the A. aureus AR33T genome is the presence of several genes related to metal resistance and homeostasis. For instance, whereas all three have transporters for iron, an essential element, only strain AR33T has transporters also for nickel and cobalt. This feature is probably due to its isolation source, a former zinc/lead mining and processing site, and is in agreement with the displayed ability to mobilize metals (Fig. 3) and to survive in the presence of zinc, lead and cadmium.
Extended insights
To obtain further insights into the A. aureus AR33T genome, we included related organisms in our comparative analysis: Microbacterium testaceum StLB037, Microbacterium sp. CGR1, Clavibacter michiganensis subsp. michiganensis NCPPB 382, Leifsonia xyli subsp. xyli CTCB07, Cellulomonas flavigena DSM 20109 and Streptomyces coelicolor A3(2). The selection criteria were the following: (i) they have a closed genome; (ii) they are member of the same family ( Microbacteriaceae ) or class ( Actinobacteria ) that have a similar secondary metabolite gene clusters; (iii) they were isolated from soil or are plant-associated bacteria. We performed an all versus all genome comparison in Gegenees [30] to establish the overall similarity of the considered genomes (Additional file 1: Figure S3). The heat map reflects the phylogenetic tree (Fig. 2) and confirms that the closest sequenced relative of A. aureus AR33T is Agromyces sp. Leaf222. Differences between the analyzed genomes are highlighted in the circular map designed in BRIG [31] (Fig. 6). Interestingly, the gaps indicating regions with low similarity to compared genomes correspond to drastic changes in the GC content of A. aureus AR33T and code for: siderophores transporters and biosynthetic clusters, genes related to metal resistance and homeostasis, phage sequences and several hypothetical proteins. A distinctive characteristic of the Actinobacteria class is the ability to produce a wide range of secondary metabolites. Therefore, we identified secondary metabolites gene clusters using antiSMASH 3.0 [32] (Table 6). In the A. aureus AR33T genome, we could identify a type III PKS gene and clusters for the production of terpenoids, siderophores and lantipeptides. The presence of a siderophore biosynthetic cluster is supported by the positive result in the in vitro CAS assay [8] and could explain the ability to change the mobility of metals like iron and lead demonstrated in the heavy metal mobilization assay. This cluster seems to be involved in the production of a desferrioxamine-like siderophore and is found in other members of the Microbacteriaceae family as well. For instance, the genes belonging to the siderophore cluster in Agromyces sp. Leaf222 share 79–98% amino acid similarity with the ones of AR33T. The terpenoid cluster seems to be widespread among these organisms and is often associated to a yellow pigmentation of the colonies. The type III PKS gene shows similarities to a naringenin-chalcone synthase and is conserved among other Agromyces spp. and Microbacteriaceae spp. with the exception of Leifsonia xyli subsp. xyli CTCB07, which has a longer sequence. Finally, the lantipeptide gene cluster is a rare feature and its structure resembles the one that has been characterized in Streptomyces venezuelae for the production of lanthionine-containing peptides [33].
Conclusions
Heavy metals are recognized as one of the main soil contaminants world-wide. Bacteria such as A. aureus AR33T could be used to improve eco-friendly decontamination techniques such as bio-augmentation or phytoremediation. Here, we presented the first complete genome of an Agromyces that was isolated from a heavy metal mining/processing site in Austria. It is able to survive in the presence of metals such as zinc, lead and cadmium and can influence the metals mobility of a contaminated soil. Genomic analysis revealed the presence of secondary metabolite gene clusters potentially involved in terpenoid and lantipeptide production, type III PKS and siderophore biosynthesis. In particular, the last two gene clusters could be directly involved in the heavy metal im-mobilization process. Moreover, the correlation between the genotype and phenotype of A. aureus AR33T is supported by the presence of several metal resistance and homeostasis genes. We could identify genomic regions displaying low similarity to compared genomes of related organisms, which are characterized by a different GC content and by the presence of genes coding for siderophore transporters and biosynthetic clusters, genes related to metal resistance and homeostasis, phage sequences and several hypothetical proteins. The genome based phylogenetic analysis including closely related and more distant organisms isolated from similar environments appeared to be in agreement with the 16S rRNA gene phylogeny. This brief comparative analysis could be the starting point for further studies in different directions. For instance, it could lead to a deeper understanding of the Agromyces genus and its relationship with other members of the class Actinobacteria and to a better knowledge about the im-mobilization mechanisms.
Abbreviations
- ABC:
-
ATP binding cassette
- CAS:
-
Chrome azurol S
- COG:
-
Clusters of orthologous group
- CRISPR:
-
Clustered regularly interspaced short palindromic repeats
- Dab:
-
2,4-diaminobutyric acid
- MM9:
-
Minimal medium 9
- PKS:
-
Polyketide synthase
References
Corretto E, Antonielli L, Sessitsch A, Compant S, Gorfer M, Kuffner M, et al. Agromyces aureus sp. nov., isolated from the rhizosphere of Salix caprea L. grown in a heavy metal contaminated soil. Int J Syst Evol Microbiol. 2016;66(9):3749–54.
Kuffner M, Puschenreiter M, Wieshammer G, Gorfer M, Sessitsch A. Rhizosphere bacteria affect growth and metal uptake of heavy metal accumulating willows. Plant Soil. 2008;304:35–44.
De Maria S, Rivelli AR, Kuffner M, Sessitsch A, Wenzel WW, Gorfer M, et al. Interactions between accumulation of trace elements and major nutrients in Salix caprea after inoculation with rhizosphere microorganisms. Chemosphere. 2011;84(9):1256–61.
Cappuccino JG, Sherman N. Microbiology: a laboratory manual. 6th ed. San Francisco: Benjamin Cummings; 2002.
Arguelles-Arias A, Ongena M, Halimi B, Lara Y, Brans A, Joris B, Fickers P. Bacillus amyloliquefaciens GA1 as a source of potent antibiotics and other secondary metabolites for biocontrol of plant pathogens. Microb Cell Factories. 2009;8:63.
Brick JM, Bostock RM, Silverstone SE. Rapid in situ assay for indole acetic acid production by bacteria immobilized on a nitrocellulose membrane. Appl Environ Microbiol. 1991;57(2):535–8.
Pikovskaya RI. Mobilization of phosphorus in soil in connection with the vital activity of some microbial species. Mikrobiologiya. 1948;17:362–70.
Milagres AMF, Napoleão D, Machuca A. Detection of siderophore production from several fungi and bacteria by a modification of chrome azurol S (CAS) agar plate assay. J Microbiol Methods. 1999;37:1–6.
Ruiz B, Chávez A, Forero A, García-Huante Y, Romero A, Sánchez M, et al. Production of microbial secondary metabolites: regulation by the carbon source. Crit Rev Microbiol. 2010;36(2):146–67.
Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Meth. 2012;9(4):357–9.
Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30(15):2114–20.
Magoč T, Salzberg SL. FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics. 2011;27(21):2957–63.
Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol. 2012;19(5):455–77.
Hunt M, De Silva N, Otto TD, Parkhill J, Keane JA, Harris SR. Circlator: automated circularization of genome assemblies using long sequencing reads. Genome Biol. 2015;16(1):294.
Gurevich A, Saveliev V, Vyahhi N, Tesler G. QUAST: quality assessment tool for genome assemblies. Bioinformatics. 2013;29(8):1072–5.
García-Alcalde F, Okonechnikov K, Carbonell J, Cruz LM, Götz S, Tarazona S, et al. Qualimap: evaluating next-generation sequencing alignment data. Bioinformatics. 2012;28(20):2678–9.
Darling AE, Jospin G, Lowe E, Matsen IV FA, Bik HM, Eisen JA. PhyloSift: phylogenetic analysis of genomes and metagenomes. PeerJ. 2014;2:e243.
Vater A, Agbonavbare V, Carlin DA, Carruthers GM, Chac A, Doroud L, et al. Draft genome sequences of Shewanella sp. strain UCD-FRSP16_17 and nine Vibrio strains isolated from Abalone feces. Genome Announc. 2016;doi:10.1128/genomeA.00977-16.
Wu D, Jospin G, Eisen JA. Systematic identification of gene families for use as “markers” for phylogenetic and phylogeny-driven ecological studies of Bacteria and Archaea and their major subgroups. PLoS ONE. 2013;8(10):e77033.
Laslett D, Canback B. ARAGORN, a program to detect tRNA genes and tmRNA genes in nucleotide sequences. Nucl Acids Res. 2004;32(1):11–6.
Prokaryotic Genome Annotation Pipeline. http://www.ncbi.nlm.nih.gov/genome/annotation_prok. Accessed 21 June 2016.
Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014;30(14):2068–9.
BLASTClust, Max-Planck Institute for Developmental Biology. http://toolkit.tuebingen.mpg.de/blastclust. Accessed June 2016.
Wu S, Zhu Z, Fu L, Niu B, Li W. WebMGA: a customizable web server for fast metagenomic sequence analysis. BMC Genomics. 2011;12:444.
Finn RD, Coggill P, Eberhardt RY, Eddy SR, Mistry J, Mitchell AL, et al. The Pfam protein families database: towards a more sustainable future. Nucl Acids Res. 2016;44(D1):D279–85.
Petersen TN, Brunak S, von Heijne G, Nielsen H. SignalP 4.0: discriminating signal peptides from transmembrane regions. Nat Methods. 2011;8:785–6.
Krogh A, Larsson B, von Heijne G, Sonnhammer ELL. Predicting transmembrane protein topology with a hidden Markov model: Application to complete genomes. J Mol Biol. 2001;305(3):567–80.
Page AJ, Cummins CA, Hunt M, Wong VK, Reuter S, Holden MTG, et al. Roary: Rapid large-scale prokaryote pan genome analysis. Bioinformatics. 2015;31(22):3691–3.
Overbeek R, Olson R, Pusch GD, Olsen GJ, Davis JJ, Disz T, et al. The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). Nucleic Acids Res. 2014;42(Database issue):D206–14.
Ågren J, Sundström A, Håfström T, Segerman B. Gegenees: fragmented alignment of multiple genomes for determining phylogenomic distances and genetic signatures unique for specified target groups. PLoS ONE. 2012;7(6):e39107.
Alikhan NF, Petty NK, Zakour NLB, Beatson SA. BLAST Ring Image Generator (BRIG): simple prokaryote genome comparisons. BMC Genomics. 2011;12(1):402.
Weber T, Blin K, Duddela S, Krug D, Kim HU, Bruccoleri R, et al. antiSMASH 3.0 — a comprehensive resource for the genome mining of biosynthetic gene clusters. Nucl Acids Res. 2015;43(W1):W237–43.
Goto Y, Li B, Claesen J, Shi Y, Bibb MJ, van der Donk WA. Discovery of unique lanthionine synthetases reveals new mechanistic and evolutionary insights. PLoS Biol. 2010;8(3):e1000339.
Tamura K, Stecher G, Peterson D, Filipski A, Kumar S. MEGA6: Molecular Evolutionary Genetics Analysis Version 6.0. Mol Biol Evol. 2013;30:2725–9.
Carver T, Thomson N, Bleasby A, Berriman M, Parkhill J. DNAPlotter: circular and linear interactive genome visualization. Bioinformatics. 2009;25(1):119–20.
Zhou Y, Liang Y, Lynch KH, Dennis JJ, Wishart DS. PHAST: A Fast Phage Search Tool. Nucl Acids Res. 2011. doi:10.1093/nar/gkr485.
Woese CR, Kandler O, Wheelis ML. Towards a natural system of organisms: proposal for the domains Archaea, Bacteria, and Eucarya. Proc Natl Acad Sci U S A. 1990;87(12):4576–9.
Garrity GM, Holt JG. The road map to the manual. In: Boone D, Castenholz R, Garrity G, editors. Bergey’s manual® of systematic bacteriology. New York: Springer; 2001. p. 119–66.
Stackebrandt E, Rainey FA, WardRainey NL. Proposal for a new hierarchic classification system, Actinobacteria classis nov. Int J Syst Bacteriol. 1997;47(2):479–91.
Zhi XY, Li WJ, Stackebrandt E. An update of the structure and 16S rRNA gene sequence-based definition of higher ranks of the class Actinobacteria, with the proposal of two new suborders and four new families and emended descriptions of the existing higher taxa. Int J Syst Evol Microbiol. 2009;59:589–608.
Zgurskaya HI, Evtushenko LI, Akimov VN, Voyevoda HV, Dobrovolskaya TG, Lysak LV, et al. Emended description of the genus Agromyces and description of Agromyces cerinus subsp. cerinus sp. nov., subsp. nov., Agromyces cerinus subsp. nitratus sp. nov., subsp. nov., Agromyces fucosus subsp. fucosus sp. nov., subsp. nov., and Agromyces fucosus subsp. hippuratus sp. nov., subsp. nov. Int J Syst Bacteriol. 1992;42:635–41.
Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet. 2000;25(1):25–9.
Acknowledgements
We want to thank Markus Gorfer for providing Agromyces aureus AR33. The following analyses were carried out by the Identification Service, Leibniz-Institut DSMZ Deutsche Sammlung von Mikroorganismen und Zellkulturen GMbH, Braunschweig, Germany: peptidoglycan structure, analysis of cell-wall sugars, polar lipids, menaquinones and fatty acids.
Funding
This work was supported by the Austrian Science Fund FWF, project P 24569-B25 and by the Niederösterreichische Forschungs- und Bildungsges.m.b.H NFB, project LS11-014.
Author’s contributions
EC, AS and GB designed the study. EC wrote the manuscript and characterized the strain. SC performed the microcopy analysis. EC, CH and MP performed the heavy metal mobilization assays. Sequencing, assembly and annotation were done by EC, LA and GB. Comparative genomics analysis was performed by EC. All authors read and approved the final manuscript.
Competing interests
The authors declare that they have no competing interests.
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Additional file
Additional file 1:
Table S1. Primers used for gap closing. Figure S1. Bidirectional best hit analysis performed in RAST. Figure S2. Blast Dot Plot of Agromyces aureus AR33 versus Agromyces sp. Leaf222 calculated in RAST. Figure S3. Heat map showing similarities between whole genomes of A. aureus AR33 , other Agromyces spp. and related members of the same family and phylum. (PDF 277 kb)
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Corretto, E., Antonielli, L., Sessitsch, A. et al. Complete genome sequence of the heavy metal resistant bacterium Agromyces aureus AR33T and comparison with related Actinobacteria . Stand in Genomic Sci 12, 2 (2017). https://doi.org/10.1186/s40793-016-0217-z
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DOI: https://doi.org/10.1186/s40793-016-0217-z