Open Access

First high quality draft genome sequence of a plant growth promoting and cold active enzyme producing psychrotrophic Arthrobacter agilis strain L77

  • Ram N. Singh1,
  • Sonam Gaba1,
  • Ajar N. Yadav1,
  • Prakhar Gaur1,
  • Sneha Gulati1,
  • Rajeev Kaushik1 and
  • Anil K. Saxena1, 2Email author
Standards in Genomic Sciences201611:54

https://doi.org/10.1186/s40793-016-0176-4

Received: 23 December 2015

Accepted: 15 August 2016

Published: 26 August 2016

Abstract

Arthrobacter agilis strain L77, is a plant growth promoting and cold active hydrolytic enzymes producing psychrotrophic bacterium, isolated from Pangong Lake, a subglacial lake in north western Himalayas, India. Genome analysis revealed metabolic versatility with genes involved in metabolism and cold shock adaptation, utilization and biosynthesis of diverse structural and storage polysaccharides such as plant based carbon polymers. The genome of Arthrobacter agilis strain L77 consists of 3,608,439 bp (3.60 Mb) of a circular chromosome. The genome comprises of 3316 protein coding genes and 74 RNA genes, 725 hypothetical proteins, 25 pseudo-genes and 1404 unique genes.

Keywords

Arthrobacter PsychrotrophicPGPBCold-active enzymesPangong LakeHimalayas

Introduction

The microorganisms from extreme environments are of particular importance in global ecology since the majority of terrestrial and aquatic ecosystems of our planet are permanently or seasonally submitted to cold temperatures. Microorganisms capable of coping with low temperatures are widespread in these natural environments where they often represent the dominant flora and they should therefore be regarded as the most successful colonizers of our planet. Members of the genus Arthrobacter [1, 2] are Gram-positive, show rods in exponential growth and cocci in their stationary phase, able to grow under aerobic as well as anaerobic conditions and belong to the phylum Actinobacteria [3]. Different species of Arthrobacter [1, 2] have been implicated in plant growth promotion [4], production of industrially important enzymes [5, 6] and as xeroprotectant [7, 8]. These reports suggest that species from Arthrobacter [1, 2] harbor genes for coding enzymes that can be useful in the industry, agriculture and biotechnology. Arthrobacter agilis [9] strain L77 was isolated from Pangong Lake, a subglacial lake in north western Himalayas, India and exhibit plant growth promoting attributes as well as production of hydrolytic enzymes. The culture was further characterized for production of EPS and anti-freeze compounds (AFCs). Here, we present the draft genome sequence of Arthrobacter agilis [9] strain L77 along with the description of genome properties and annotation.

Organism information

Classification and features

Arthrobacter agilis [9] strain L77 was isolated from frozen sub-glacial Pangong Lake (33°82′55.59″N and 78°59′26.69″E) in north western Himalaya, India (Table 1). This psychrotrophic bacterium was isolated using standard serial dilution method on Trypticase soya agar [10] plate and has been reported to possess plant growth promoting attributes and could produce cold active enzymes and AFCs. It could solubilize phosphorus, zinc and could produce indole acetic acid and ammonia. It could produce cold active enzymes such as lipase, amylase, protease, chitinase and β-galactosidase.
Table 1

Classification and general features of Arthrobacter agilis strain L77

MIGS ID

Property

Term

Evidence codea

 

Classification

Domain Bacteria

TAS [12]

  

Phylum Actinobacteria

TAS [3]

  

Class Actinobacteria

TAS [13]

  

Order Actinomycetales

TAS [2, 14]

  

Family Micrococcaceae

TAS [2, 15]

  

Genus Arthrobacter

TAS [1, 2]

  

Species Arthrobacter agilis

TAS [9]

  

Strain L77

NAS

 

Gram stain

Positive

IDA

 

Cell shape

Polymorphic: Coccus to rod shaped

IDA

 

Motility

Non-motile

TAS [9]

 

Sporulation

Non-sporulating

TAS [9]

 

Temperature range

−10 °C −30 °C

IDA

 

Optimum temperature

15 °C

IDA

 

pH range; Optimum

6–9, 7

IDA

 

Carbon source

Yeast extract, glucose, lactose, mannose

TAS [9]

MIGS-6

Habitat

Sub-glacial Lake

IDA

MIGS-6.3

Salinity

Grown on 5 % > NaCl (w/v)

IDA

MIGS-22

Oxygen requirement

Aerobic

TAS [9]

MIGS-15

Biotic relationship

Free living

TAS [9]

MIGS-14

Pathogenicity

Non-pathogeneic

NAS

MIGS-4

Geographic location

India, Leh Ladakh, Jammu & Kashmir

TAS [10]

MIGS-5

Sample collection

March 28, 2010

IDA

MIGS-4.1

Latitude

33°82′55.59″N

NAS

MIGS-4.2

Longitude

78°59′26.69″E

NAS

MIGS-4.4

Altitude

3215 m

NAS

aEvidence codes - 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 [49]

Strain L77 is a bright yellow colored (Fig. 1) Gram-positive, aerobic, non-motile bacterium exhibiting a rod-coccus cycle. The initial validation of bacterium was done by 16S rRNA gene sequencing using the universal eubacterial primers pA (5′-AGAGTTTGATCCTGGCTCAG-3′) and pH (5′-AAGGAGGTGATCCAGCCGCA-3′) [11]. The 16S rRNA gene sequence places Arthrobacter agilis strain L77 in the domain Bacteria [12] (Table 1), phylum Actinobacteria [3] and Class Actinobacteria [13], order Actinomycetales [2, 14] and family Micrococcaceae [2, 15] during homology search by BLAST [16]. Only few of the closely related species after reclassification [17] of genus Arthrobacter [1, 2,] with validly published names: A. agilis DSM 20550 T [9], A. woluwensis 1551 T DSM 10495 [18], A. methylotrophus DSM 14008 T [19], A. tecti LMG 22282 T [20], A. parietis LMG 22281 T [20], A. subterraneus CH7 T DSM 17585 [21], A. tumbae LMG 19501 T [20], Arthrobacter oryzae KV-651 T DSM 25586 [22], Arthrobacter alkaliphilus LC6 T DSM 23368 [23], Arthrobacter flavus JCM 11496 T [24], A. cupressi D48 T DSM 24664 [25], A. globiformis DSM 20124 T [1, 2] were selected for drawing the phylogenetic position of strain L77.
Fig. 1

Full grown yellow colored bacterial culture on Tripticase Soy Agar (TSA) medium

A phylogenetic tree was constructed (Fig. 2) from the 16S rRNA gene sequence together with other Arthrobacter [1, 2] homologs using MEGA 6.0 software suite [26]. The evolutionary history was inferred by using the Maximum Likelihood method based on the Tamura-Nei model [27]. The tree with the highest log likelihood (0.14495825) is shown. The percentage of trees in which the associated taxa clustered together is shown next to the branches. Initial tree(s) for the heuristic search were obtained automatically by applying Neighbor-Join and BioNJ algorithms to a matrix of pairwise distances estimated using the Maximum Composite Likelihood (MCL) approach, and then selecting the topology with superior log likelihood value. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. The analysis involved 13 nucleotide sequences. All positions containing gaps and missing data were eliminated. There were a total of 1553 positions in the final dataset. Evolutionary analyses were conducted in MEGA6.0 [26]. According to the 16S rRNA gene similarity, the nearest phylogenetic neighbors of Arthrobacter agilis strain L77 are Arthrobacter flavus JCM 11496 T [24] (AB537168) with 97.8 %, A. tecti LMG 22282 T [20] (AJ639829) with 97.13 %, A. parietis LMG 22281 T [20] (AJ639830) with 97.41 %, A. subtrerraneus CH7 T DSM 17585 [21] (DQ097525) with 97.66 % and A. tumbae LMG 19501 T [20] (AJ315069) with 97.68 % similarity. The 16S rRNA gene sequence also submitted to NCBI GenBank with the accession number KT804924.
Fig. 2

Phylogenetic placements of Arthrobacter agilis strain L77 between known species of Arthrobacter genus

Extended feature descriptions

Arthrobacter agilis strain L77, a psychrotrophic bacterium, forms bright yellow color colonies (Fig. 1) on TSA medium and could grow in a pH range of 6–9 and tolerate 5 % NaCl. Growth studies showed that the isolate when incubated at 15 and 30 °C was in the exponential phase until 36 h, while at 4 °C, the exponential phase started after 24 h (Fig. 3). Freezing survival studies of Arthrobacter agilis strain L77 revealed that when the culture was initially grown at 4 °C prior to freezing at −10 and −20 °C, it showed significantly higher freezing survival rather than culture initially grown at 15 and 30 °C prior to freezing (Fig. 3).
Fig. 3

Growth curves of Arthrobacter agilis strain L77 at three different temperatures 4, 15 and 30 °C

Exopolysaccharide production was found to be higher at lower incubation temperatures (4 or 15 °C) in comparison to the optimal growth temperature (30 °C) for Arthrobacter agilis (L77) (Fig. 4). EPS production by psychrophilic bacteria is one of the adaptations at low temperatures. The high polyhydroxyl content of EPS lowers the freezing point and ice nucleation temperature of water. In addition, EPS can trap water, nutrients and metal-ions and facilitate surface adhesion, cellular aggregation and biofilm formation and may also play a role in protecting extracellular enzymes against cold denaturation and autolysis [28, 29].
Fig. 4

The survival of Arthrobacter agilis strain L77 subjected to freezing temperature (−10 and −20 °C) shifted from three different temperatures 4, 15 and 30 °C

Remarkable variations in terms of accumulation of various organic acids, sugars, polyols and amino acids were detected through HPLC at three different incubation temperatures (4, 15 and 30 °C) (Additional file 1: Table S1, Additional file 2: Table S2 and Fig. 5). Among the sugars, accumulation of mannitol and sorbitol was observed only at 4 °C. The amino acids expression pattern revealed that the most prominent increase was observed in the concentrations of glycine, cysteine and arginine at 4 °C (Additional file 2: Table S2). It has been reported that the cold active enzymes and efficient growth rates are used to facilitate and maintain the adequate metabolic fluxes at near freezing temperature for cold-adaptation [30]. The development of freezing tolerance by producing cryoprotectant compounds or adaptation of cytoplasmic enzymes to cold conditions for protecting cytoplasmic components is one of the strategy used by microbial cells to survive in freezing conditions as these molecules depress freezing point for the protection of cells [31].
Fig. 5

EPS accumulation by Arthrobacter agilis strain L77 at three different temperatures 4, 15 and 30 °C

Enhanced EPS production by the psychrophilic bacteria at low temperature suggests that EPS plays an important role in desiccation protection or prevention of drying of bacterial cells from freezing temperature. It can be assumed that the strain L77 follows a cold evading strategy to thrive in freezing conditions by synthesizing various cryoprotectants (sugars, polyols and amino acids). These cryoprotectants are known to depress freezing point to evade crystallization [32].

Genome sequencing information

Genome project history

This organism was selected for sequencing on the basis of its environmental and agricultural relevance to help in plant growth and ability to provide inorganic phosphate to crops at very low temperature. It also has biogeochemical importance of producing AFCs, so helpful for soil aeration. The genome project is deposited in the online genome database (NCBI-Genome). Sequencing, assembly and annotations were performed at Division of Microbiology, Indian Agricultural Research Institute (ICAR-IARI), New Delhi, India. A summary of the project information is shown in the Table 2.
Table 2

Genome sequencing project information for Arthrobacter agilis strain L77

MIGS ID

Property

Term

MIGS-31

Finishing quality

Unfinished, improved high quality draft

MIGS-28

Libraries used

Paired End (insert size 250 bp)

MIGS-29

Sequencing platforms

Illumina MiSeq

MIGS-31.2

Fold coverage

180×

MIGS-30

Assemblers

A5 pipeline v jan-2014

MIGS-32

Gene calling method

Prodigal

 

Locus Tag

RY94

 

Genbank ID

JWSU00000000.1-10.1

 

Genbank Date of Release

08-Jan-2015

 

GOLD ID

Gp0117366

 

BIOPROJECT

PRJNA270909

MIGS 13

Source Material Identifier

L77

 

Project relevance

Bioprospecting

Growth conditions and genomic DNA preparation

A culture of L77 was grown in Trypticase soya broth, until they reached an OD(600 nm) > 1.0. The cells were pelleted from 5 ml culture, washed thrice with TE buffer (10 mM Tris and 1 mM EDTA, pH 8.0) and the pellet was resuspended in 750 μl TE buffer. Genomic DNA was extracted from the suspended pellet using Zymo Research Fungal/Bacterial DNA MicroPrep™ following the standard protocol prescribed by the manufacturer.

Genome sequencing and assembly

The draft genome of Arthrobacter agilis strain L77 (PRJNA270909) was generated at the Division of Microbiology, ICAR-Indian Agricultural Research Institute (ICAR-IARI), New Delhi, India using Illumina [33] technology (Table 2). For this genome, we constructed and sequenced an Illumina MiSeq shotgun library which generated 1,568,654 reads totaling 321.8 Mb data. The raw fastq data was checked for quality using Fast QC [34]. Trimmomatic 0.32 [35] with Nextra adapter sequences was used to hard clip reads. Assembly of trimmed reads was carried out using a5 pipeline version 2014 [36] (Table 2). In terms of N50 and total number of scaffolds, the a5 pipeline [36] was found to be better than other genome assemblers. CONTIGuator [37] was used to improve the assembly draft. The final draft was identified as Arthrobacter agilis L77, using megablast with RDP 16S database, release 11–1 [38]. This whole-genome project (Bioproject ID: PRJNA270909) has been registered and assembled sequence data submitted at NCBI GenBank under the accession no. JWSU00000000.1-10.1. The version described in this paper is the first version.

Genome annotation

Genes were identified using Prokka 1.8 [39] based on Prodigal [40] (Table 2) as part of the Oak Ridge National Laboratory genome annotation pipeline. The predicted CDSs were further annotated on Pfam [41], and (COGs) [42]. These data sources were combined to assert a product description for each predicted protein. Non-coding genes and miscellaneous features were predicted using tRNAscan-SE [43], RNAMMer [44], Rfam [45], TMHMM [46], and signalP v4.1 [47] (Table 3).
Table 3

Genome Statistics for Arthrobacter agilis strain L77

Attribute

Value

% of total

Genome size (bp)

3,608,439

100.00

DNA coding (bp)

3,224,998

89.37

DNA G + C (bp)

2,518,329

69.79

DNA scaffolds

10

100.00

Total genes

3390

100.00

Protein coding genes

3316

97.81

RNA genes

84

2.18

Pseudo genes

25

0.73

Genes in internal clusters

N/A

N/A

Genes with function prediction

2591

78.10

Genes assigned to COGs

2122

63.64

Genes assigned to Pfam domains

2855

85.11

Genes with signal peptides

126

5.51

Genes with transmembrane helices

852

25.6

CRISPR repeats

N/A

N/A

Genome properties

The genome is 3,608,439 bp in size, which has GC content of 69.79 mol % (Table 3). There are 47 tRNA, 1 tmRNA, 6 rRNA and 20 ncRNA genes. Of the 3390 predicted genes, 3316 are protein-coding genes (CDSs). Of the total CDSs, 63.64 % represent COG functional categories and 5.51 % consist of signal peptides (Table 3). The distribution of genes into COG functional categories are presented in Table 4. The genome map (Fig. 6) was visualized by CG view server [48].
Table 4

Number of protein coding genes of Arthrobacter agilis strain L77 associated with general COG functional categories

Code

Value

% agea

COG category

J

184

5.54

Translation, ribosomal structure and biogenesis

A

1

0.03

RNA processing and modification

K

208

6.27

Transcription

L

109

3.28

Replication recombination and repair

B

1

0.03

Chromatin structure and dynamics

D

22

0.66

Cell cycle control, Cell division, chromosome partitioning

V

49

1.47

Defense mechanisms

T

113

3.40

Signal transduction mechanisms

M

124

3.73

Cell wall/membrane biogenesis

N

30

0.90

Cell motility

U

19

0.57

Intracellular trafficking and secretion

O

104

3.13

Posttranslational modification, protein turnover, chaperones

C

110

3.31

Energy production and conversion

G

213

6.42

Carbohydrate transport and metabolism

E

200

6.03

Amino acid transport and metabolism

F

71

2.14

Nucleotide transport and metabolism

H

114

3.43

Coenzyme transport and metabolism

I

88

2.65

Lipid transport and metabolism

P

118

3.55

Inorganic ion transport and metabolism

Q

38

1.14

Secondary metabolites biosynthesis, transport and catabolism

R

204

6.15

General function prediction only

S

166

5.00

Function unknown

1030

31.06

Not in COGs

aThe total is based on the number of protein coding genes in the annotated genome

Fig. 6

Graphical map of genome of Arthrobacter agilis strain L77. From outside to centre: RNA genes (Brown, tRNA and light purple, rRNA) and other genes are colored according to COG categories. Inner circle shows the GC skew with positive (+) as dark green and negative (−) as dark purple. GC content is indicated in black

Insights from the genome sequence

The isolate was successfully screened for lipase, amylase, protease, chitinase and β-galactosidase. Genome analysis showed two important genes pstA and pstC which are required for the translocation of phosphate across the membranes. Another important gene, PstB (an ADP binding protein), of the phosphate transport system is responsible for giving energy to the phosphate transport system of the organism. PhoR and PhoP were also found which are important for regulation of phosphate operon. PhoH like protein has a probable ATPase which is induced when phosphate level decreases. Genome annotation also predicted a putative cold shock protein which is supposed to play an important role in low temperature conditions. There are other proteins which shares evolutionary relationship with bacterial cold shock proteins such as Rhodanase and S1 RNA binding protein suggesting their role in low temperature conditions. In-depth analysis of the genome could give us better insight into mechanism of tolerance of this strain to low temperature. Other temperature responsive proteins were found such as molecular chaperone Hsp31 and glyoxalase 3 that influence the exposure of hydrophobic domains of proteins and stabilize the early unfolding under high temperature stress conditions to provide stability to the isolate in temperature stress.

Genes of heavy metal resistance were also found in the annotation. Mercuric resistance operon regulatory protein activates the mercury resistance operon in the presence of mercury thus protecting the bacteria from harmful side-effects of mercury. Mercuric reductase is also present which is responsible for conversion of Hg2+ to Hg0. copZ is a copper chaperone that replaces zinc with copper and releases copY from the DNA which is a negative regulator of copYZAB under excess copper. Gene of nitrogen regulation, nitrogen regulatory protein P-II was found that regulates the level of nitrogen by regulating glutamine. When the ratio of glutamine to 2-ketoglutarate decreases, uridine is added on a tyrosine of P-II to form P-II-UMP which in turn deadenylates glutamine synthase resulting in its activation. Putative genes coding for these activities were identified in the genome based on annotation (Table 5).
Table 5

Candidate genes coding for putative lipase, amylase, chitinase, protease, β-galactosidase, phosphate transport regulation, cold shock proteins, chaperons and heavy metal resistance activities identified in Arthrobacter agilis strain L77 draft genome

Putative Gene

Annotation

Size (aa)

 

Lipase

 

 ABAGL_00531

GDSL-like Lipase/Acylhydrolase

262

 ABAGL_00732

Lipase 1 precursor

288

 ABAGL_00875

GDSL-like Lipase/Acylhydrolase

267

 ABAGL_01161

Lipase 1 precursor

350

 ABAGL_03217

GDSL-like Lipase/Acylhydrolase

272

 

Amylase

 

 ABAGL_00299

Glucose-resistance amylase regulator

338

 ABAGL_01452

Glucose-resistance amylase regulator

336

 ABAGL_01652

Trehalose synthase/amylase TreS

588

 ABAGL_01737

Alpha-amylase precursor

905

 ABAGL_01923

Alpha-amylase/pullulanase

257

 ABAGL_01950

Glucose-resistance amylase regulator

327

 

Chitinase

 

 ABAGL_01394

putative bifunctional chitinase/lysozyme precursor

520

 ABAGL_01777

Chitinase

400

 

Protease

 

 ABAGL_00100

Putative cysteine protease YraA

188

 ABAGL_00190

Flp pilus assembly protein, protease CpaA

207

 ABAGL_00447

Lon protease

364

 ABAGL_00456

Putative serine protease HtrA

496

 ABAGL_00667

Serine proteasec

401

 ABAGL_00940

CAAX amino terminal protease self- immunity

268

 ABAGL_00971

CAAX amino terminal protease self- immunity

247

 ABAGL_01091

Serine protease Do-like HtrA

366

 ABAGL_01213

Rhomboid protease GluP

291

 ABAGL_01289

ATP-dependent zinc metalloprotease FtsH

689

 ABAGL_01302

Putative ATP-dependent Clp protease ATP-binding subunit

835

 ABAGL_01392

CAAX amino terminal protease self- immunity

266

 ABAGL_01505

Minor extracellular protease vpr precursor

1059

 ABAGL_01669

Flp pilus assembly protein, protease CpaA

168

 ABAGL_01755

CAAX amino terminal protease self- immunity

326

 ABAGL_02020

Putative serine protease HtrA

310

 ABAGL_02206

Putative metalloprotease

303

 ABAGL_02449

Putative zinc metalloproteasec/MT2700

388

 ABAGL_02467

Modulator of FtsH protease HflK

310

 ABAGL_02638

ATP-dependent Clp protease ATP-binding subunit ClpX

430

 ABAGL_02639

ATP-dependent Clp protease proteolytic subunit 1

224

 ABAGL_02640

ATP-dependent Clp protease proteolytic subunit 2

208

 ABAGL_02862

ATP-dependent Clp protease adaptor protein ClpS

105

 ABAGL_02923

ATP-dependent zinc metalloprotease FtsH

438

 ABAGL_03163

Serine protease inhibitor-like protein

389

 ABAGL_03211

CAAX amino terminal protease self- immunity

267

 ABAGL_03271

Metalloprotease MmpA

447

 ABAGL_00551

Protease PrtS precursor

355

 ABAGL_00739

Protease 2

734

 ABAGL_01958

Protease synthase and sporulation negative regulatory protein

215

 ABAGL_02571

Protease PrsW

425

 ABAGL_03295

Protease 3 precursor

455

 

β-galactosidase

 

 ABAGL_00260

β-galactosidase bgaB

667

 ABAGL_00292

β-galactosidase

687

 ABAGL_01083

β-galactosidase precursor

708

 

Phosphate Transport Regulation

 

 ABAGL_01317

Phosphate transport system permease protein PstA

310

 ABAGL_01318

Phosphate import ATP-binding protein PstB

367

 ABAGL_01316

Phosphate transport system permease protein PstC

259

 ABAGL_00191

Alkaline phosphatase synthesis sensor protein PhoR

544

 ABAGL_03137

Alkaline phosphatase synthesis sensor protein PhoR

555

 ABAGL_01671

PhoH-like protein

443

 ABAGL_02530

PhoH-like protein

344

 

Cold shock Proteins

 

 ABAGL_01978

putative cold shock protein A

67

 

Chaperons

 

 ABAGL_01554

Molecular chaperone Hsp31 and glyoxalase 3

255

 ABAGL_01067

Copper chaperone CopZ

74

 

Heavy Metal Resistance

 

 ABAGL_02628

Mercuric resistance operon regulatory protein

134

Conclusions

The 3.6 Mb draft genome of Arthrobacter agilis strain L77 was assembled and annotated. The isolate was successfully screened for production of EPS and AFCs with potential application in biotechnology. The candidate genes coding for hydrolytic enzymes and cold shock proteins were identified in the genome. Arthrobacter agilis strain L77 will serve as a source for antifreeze proteins, functional enzymes and other bioactive molecules in future bioprospecting projects.

Abbreviations

AFCs: 

Anti-freeze compounds

EPS: 

Exopolysaccharides

Declarations

Acknowledgments

The authors are grateful to the National Agricultural Innovation Project (NAIP), Indian Council of Agricultural Research, Govt. of India, New Delhi and Division of Microbiology, ICAR-Indian Agricultural Research Institute (IARI), Pusa, New Delhi and for providing the financial support facilities, to undertake the investigations.

Author’s contributions

RNS and SGa equally contributed to the work. RNS carried out the sample collection, participated in the strain identification, sequence alignment, assembly and annotation analysis and drafted the manuscript. SGa participated in the sequence assembly and annotation analysis. ANY and SGu carried out the bacterial isolation and performed the physiological assays. PG did the initial sequence assembly of the raw data. RK participated in sample collection and sequencing of 16S rRNA gene. AKS conceived of the study, and participated in its design, coordination and helped to finalize the manuscript. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

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’ Affiliations

(1)
Division of Microbiology, ICAR-Indian Agricultural Research Institute
(2)
Present Address: ICAR-National Bureau of Agriculturally Important Microorganisms

References

  1. Conn H, Dimmick I. Soil bacteria similar in morphology to Mycobacterium and Corynebacterium. J Bacteriol. 1947;54(3):291.PubMedPubMed CentralGoogle Scholar
  2. Skerman V, McGowan V, Sneath P, Moore W, Moore LV. Approved lists of bacterial names. Int J Syst Bacteriol. 1980;30:225–420.View ArticleGoogle Scholar
  3. Garrity GM, Holt JG. The road map to the manual. Bergey’s Manual® of Systematic Bacteriology. Springer New York; 2001. p. 119–66.Google Scholar
  4. Manzanera M, Narváez-Reinaldo JJ, García-Fontana C, Vílchez JI, González-López J. Genome sequence of Arthrobacter koreensis 5J12A, a plant growth-promoting and desiccation-tolerant strain. Genome Announc. 2015;3(3):e00648–15.PubMedPubMed CentralGoogle Scholar
  5. Kallimanis A, LaButti KM, Lapidus A, Clum A, Lykidis A, Mavromatis K, et al. Complete genome sequence of Arthrobacter phenanthrenivorans type strain (Sphe3). Stand Genomic Sci. 2011;4(2):123.View ArticlePubMedPubMed CentralGoogle Scholar
  6. Kiran S, Swarnkar MK, Pal M, Thakur R, Tewari R, Singh AK, et al. Complete genome sequencing of protease-producing novel Arthrobacter sp. strain IHBB 11108 using PacBio single-molecule real-time sequencing technology. Genome Announc. 2015;3(2):e00346–15.View ArticlePubMedPubMed CentralGoogle Scholar
  7. Manzanera M, Santa-Cruz-Calvo L, Vílchez J, García-Fontana C, Silva-Castro G, Calvo C, et al. Genome sequence of Arthrobacter siccitolerans 4 J27, a xeroprotectant-producing desiccation-tolerant microorganism. Genome Announc. 2014;2(3):e00526–14.View ArticlePubMedPubMed CentralGoogle Scholar
  8. SantaCruz-Calvo L, González-López J, Manzanera M. Arthrobacter siccitolerans sp. nov., a highly desiccation-tolerant, xeroprotectant-producing strain isolated from dry soil. Int J Syst Evol Microbiol. 2013;63(Pt 11):4174–80.View ArticlePubMedPubMed CentralGoogle Scholar
  9. Koch C, Schumann P, Stackebrandt E. Reclassification of Micrococcus agilis (Ali-Cohen 1889) to the genus Arthrobacter as Arthrobacter agilis comb. nov. and emendation of the genus Arthrobacter. Int J Syst Bacteriol. 1995;45(4):837–9.View ArticlePubMedGoogle Scholar
  10. Yadav AN, Sachan SG, Verma P, Tyagi SP, Kaushik R, Saxena AK. Culturable diversity and functional annotation of psychrotrophic bacteria from cold desert of Leh Ladakh (India). World J Microbiol Biotechnol. 2015;31(1):95–108.View ArticlePubMedGoogle Scholar
  11. Edwards U, Rogall T, Blöcker H, Emde M, Böttger EC. Isolation and direct complete nucleotide determination of entire genes. Characterization of a gene coding for 16S ribosomal RNA. Nucleic Acids Res. 1989;17(19):7843–53.View ArticlePubMedPubMed CentralGoogle Scholar
  12. 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.View ArticlePubMedPubMed CentralGoogle Scholar
  13. Stackebrandt E, Rainey FA, Ward-Rainey NL. Proposal for a new hierarchic classification system, Actinobacteria classis nov. Int J Syst Bacteriol. 1997;47(2):479–91.View ArticleGoogle Scholar
  14. Buchanan R. Studies in the nomenclature and classification of the bacteria: II. The primary subdivisions of the schizomycetes. J Bacteriol. 1917;2(2):155.PubMedPubMed CentralGoogle Scholar
  15. Pribram E. A contributionto the classification of microörganisms. J Bacteriol. 1929;18(6):361.PubMedPubMed CentralGoogle Scholar
  16. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990;215(3):403–10.View ArticlePubMedGoogle Scholar
  17. Busee HJ. Review of the taxonomy of the genus Arthrobacter, emendation of the genus Arthrobacter sensu lato, proposal to reclassify selected species of the genus Arthrobacter in the novel genera Glutamicibacter gen. nov., Paeniglutamicibacter gen. nov., Pseudoglutamicibacter gen. nov., Paenarthrobacter gen. nov. and Pseudoarthrobacter gen. nov, and emended description of Arthrobacter roseus. Int J Syst Evol Microbiol. 2016;66:9–37.View ArticleGoogle Scholar
  18. Funke G, Hutson RA, Bernard KA, Pfyffer GE, Wauters G, Collins MD. Isolation of Arthrobacter spp. from clinical specimens and description of Arthrobacter cumminsii sp. nov. and Arthrobacter woluwensis sp. nov. J Clin Microbiol. 1996;34(10):2356–63.PubMedPubMed CentralGoogle Scholar
  19. Borodina E, Kelly DP, Schumann P, Rainey FA, Ward-Rainey NL, Wood AP. Enzymes of dimethylsulfone metabolism and the phylogenetic characterization of the facultative methylotrophs Arthrobacter sulfonivorans sp. nov., Arthrobacter methylotrophus sp. nov., and Hyphomicrobium sulfonivorans sp. nov. Arch Microbiol. 2002;177(2):173–83.View ArticlePubMedGoogle Scholar
  20. Heyrman J, Verbeeren J, Schumann P, Swings J, De Vos P. Six novel Arthrobacter species isolated from deteriorated mural paintings. Int J Syst Evol Microbiol. 2005;55(4):1457–64.View ArticlePubMedGoogle Scholar
  21. Chang H, Bae J, Nam Y, Kwon H, Park JR, Shin K, et al. Arthrobacter subterraneus sp. nov., isolated from deep subsurface water of the South Coast of Korea. J Microbiol Biotechnol. 2007;17(11):1875.PubMedGoogle Scholar
  22. Kageyama A, Morisaki K, Ōmura S, Takahashi Y. Arthrobacter oryzae sp. nov. and Arthrobacter humicola sp. nov. Int J Syst Evol Microbiol. 2008;58(1):53–6.View ArticlePubMedGoogle Scholar
  23. Ding L, Hirose T, Yokota A. Four novel Arthrobacter species isolated from filtration substrate. Int J Syst Evol Microbiol. 2009;59(4):856–62.View ArticlePubMedGoogle Scholar
  24. Reddy G, Aggarwal R, Matsumoto G, Shivaji S. Arthrobacter flavus sp. nov., a psychrophilic bacterium isolated from a pond in McMurdo Dry Valley, Antarctica. Int J Syst Evol Microbiol. 2000;50(4):1553–61.View ArticlePubMedGoogle Scholar
  25. Zhang J, Ma Y, Yu H. Arthrobacter cupressi sp. nov., a novel actinomycete isolated from the rhizosphere soil of Cupressus sempervirens. Int J Syst Evol Microbiol. 2012. doi:10.1099/ijs.0.036889-0.
  26. Tamura K, Stecher G, Peterson D, Filipski A, Kumar S. MEGA6: molecular evolutionary genetics analysis version 6.0. Mol Biol Evol. 2013;30(12):2725–9.View ArticlePubMedPubMed CentralGoogle Scholar
  27. Tamura K, Nei M. Estimation of the number of nucleotide substitutions in the control region of mitochondrial DNA in humans and chimpanzees. Mol Biol Evol. 1993;10(3):512–26.PubMedGoogle Scholar
  28. Nichols CM, Guezennec J, Bowman J. Bacterial exopolysaccharides from extreme marine environments with special consideration of the southern ocean, sea ice, and deep-sea hydrothermal vents: a review. Mar Biotechnol. 2005;7(4):253–71.View ArticlePubMedGoogle Scholar
  29. Poli A, Anzelmo G, Nicolaus B. Bacterial exopolysaccharides from extreme marine habitats: production, characterization and biological activities. Marine Drugs. 2010;8(6):1779–802.View ArticlePubMedPubMed CentralGoogle Scholar
  30. Shivaji S, Prakash JS. How do bacteria sense and respond to low temperature? Arch Microbiol. 2010;192(2):85–95.View ArticlePubMedGoogle Scholar
  31. Yamashita Y, Nakamura N, Omiya K, Nishikawa J, Kawahara H, Obata H. Identification of an antifreeze lipoprotein from Moraxella sp. of Antarctic origin. Biosci Biotech Biochem. 2002;66(2):239–47.View ArticleGoogle Scholar
  32. Chattopadhyay M. Cold-adaptation of Antarctic microorganisms–possible involvement of viable but nonculturable state. Polar Biol. 2000;23(3):223–4.View ArticleGoogle Scholar
  33. Bennett EA, Massilani D, Lizzo G, Daligault J, Geigl E-M, Grange T. Library construction for ancient genomics: Single strand or double strand? BioTechn. 2014;56(6):289.View ArticleGoogle Scholar
  34. Andrews S. FastQC: a quality control tool for high throughput data. Reference Source. 2010.Google Scholar
  35. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014. doi:10.1093/bioinformatics/btu170.
  36. Coil D, Jospin G, Darling AE. A5-miseq: an updated pipeline to assemble microbial genomes from Illumina MiSeq data. Bioinformatics. 2014. doi:10.1093/bioinformatics/btu661.
  37. Galardini M, Biondi EG, Bazzicalupo M, Mengoni A. CONTIGuator: a bacterial genomes finishing tool for structural insights on draft genomes. Source Code Biol Med. 2011;6:11.View ArticlePubMedPubMed CentralGoogle Scholar
  38. Cole JR, Wang Q, Cardenas E, Fish J, Chai B, Farris RJ, et al. The Ribosomal Database Project: improved alignments and new tools for rRNA analysis. Nucleic Acids Res. 2009;37 suppl 1:D141–5.View ArticlePubMedGoogle Scholar
  39. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014. doi:10.1093/bioinformatics/btu153.
  40. Hyatt D, Chen G-L, LoCascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics. 2010;11(1):119.View ArticlePubMedPubMed CentralGoogle Scholar
  41. Bateman A, Coin L, Durbin R, Finn RD, Hollich V, Griffiths‐Jones S, et al. The Pfam protein families database. Nucleic Acids Res. 2004;32 suppl 1:D138–41.View ArticlePubMedPubMed CentralGoogle Scholar
  42. Tatusov RL, Koonin EV, Lipman DJ. A genomic perspective on protein families. Science. 1997;278(5338):631–7.View ArticlePubMedGoogle Scholar
  43. Lowe TM, Eddy SR. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res. 1997;25(5):0955–64.View ArticleGoogle Scholar
  44. Lagesen K, Hallin P, Rødland EA, Stærfeldt H-H, Rognes T, Ussery DW. RNAmmer: consistent and rapid annotation of ribosomal RNA genes. Nucleic Acids Res. 2007;35(9):3100–8.View ArticlePubMedPubMed CentralGoogle Scholar
  45. Griffiths-Jones S, Bateman A, Marshall M, Khanna A, Eddy SR. Rfam: an RNA family database. Nucleic Acids Res. 2003;31(1):439–41.View ArticlePubMedPubMed CentralGoogle Scholar
  46. Krogh A, Larsson B, Von Heijne G, Sonnhammer EL. Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. J Mol Biol. 2001;305(3):567–80.View ArticlePubMedGoogle Scholar
  47. Bendtsen JD, Nielsen H, von Heijne G, Brunak S. Improved prediction of signal peptides: SignalP 3.0. J Mol Biol. 2004;340(4):783–95.View ArticlePubMedGoogle Scholar
  48. Grant JR, Stothard P. The CGView server: a comparative genomics tool for circular genomes. Nucleic Acids Res. 2008;36 suppl 2:W181–4.View ArticlePubMedPubMed CentralGoogle Scholar
  49. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, Harris MA, Hill DP, Traver LIKasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, Sherlock G. Gene Ontology: tool for the unification of biology. Nat Genet. 2000; 25(1):25–29.Google Scholar

Copyright

© The Author(s). 2016