Literature DB >> 26568784

Complete genome sequence of the thermophilic Acidobacteria, Pyrinomonas methylaliphatogenes type strain K22(T).

Kevin C Y Lee1, Xochitl C Morgan2, Jean F Power1, Peter F Dunfield3, Curtis Huttenhower2, Matthew B Stott1.   

Abstract

Strain K22(T) is the type species of the recently- described genus Pyrinomonas, in subdivision 4 of the phylum Acidobacteria (Int J Syst Evol Micr. 2014; 64(1):220-7). It was isolated from geothermally-heated soil from Mt. Ngauruhoe, New Zealand, using low-nutrient medium. P. methylaliphatogenes K22(T) has a chemoheterotrophic metabolism; it can hydrolyze a limited range of simple carbohydrates and polypeptides. Its cell membrane is dominated by iso-branching fatty acids, and up to 40 % of its lipid content is membrane-spanning and ether lipids. It is obligately aerobic, thermophilic, moderately acidophilic, and non-spore-forming. The 3,788,560 bp genome of P. methylaliphatogenes K22(T) has a G + C content of 59.36 % and contains 3,189 protein-encoding and 55 non-coding RNA genes. Genomic analysis was consistent with nutritional requirements; in particular, the identified transporter classes reflect the oligotrophic nature of this strain.

Entities:  

Keywords:  Acidobacteria; Geothermal; New Zealand; Pyrinomonas; Soil; Thermophile

Year:  2015        PMID: 26568784      PMCID: PMC4644332          DOI: 10.1186/s40793-015-0099-5

Source DB:  PubMed          Journal:  Stand Genomic Sci        ISSN: 1944-3277


Introduction

Phylotypes from the phylum 1 are commonly detected across a range of ecosystems, including marine and freshwater bodies, sediments, geothermal systems, and soils. Despite the apparent ubiquitous distribution acidobacterial phyotypes, particularly in soil environments, only 17 acidobacterial genera (represented by formal description and publication of respective type strains, in accordance with the International Code of Nomenclature of Prokaryotes [1]) have been validly published [2, 3]. Here we present a description of the complete genome sequence and annotation of strain K22T (= DSM 25857 = ICMP 18710), the type species of the genus within subdivision 4 of . K22T was isolated from a fumarole on the outer crater rim of the stratovolcano Mt. Ngauruhoe [4]. It exhibits a Gram-negative cell wall, is non-spore-forming, and is catalase- and oxidase-positive (Table 1). It is a thermophilic and moderately acidophilic obligately aerobic chemoorganotroph. Of particular note is its unusual lipid composition that is dominated by odd-numbered saturated iso-branching fatty acids (iso-C15:0, iso-C17:0, iso-C19:0 and iso-C21:0 that total >88.5 % of the total fatty acid extract) [4]. In addition, >40 % of the total membrane lipid content is made up by iso-branching glycerol ether analogues of the cellular fatty acids and membrane-spanning iso-diabolic acids [5]. Membrane-spanning and ether lipids occur ubiquitously in Archaea, but in recent studies have also been commonly detected in cultivated representatives in subdivision groups 1, 3 and 4 of [5, 6].
Table 1

Classification and general features of P. methylaliphatogenes K22T

MIGS IDPropertyTermEvidence codea
Current classificationDomain Bacteria TAS [35]
Phylum Acidobacteria TAS [36]
Class ‘Insertae sedis 99’
Order ‘Insertae sedis 100’
Family ‘Insertae sedis 101’
Genus Pyrinomonas TAS [4]
Species Pyrinomonas methylaliphatogenes TAS [4]
Type strain K22T (=DSM 25857T =ICMP 18710T).TAS [4]
Gram stainnegativeTAS [4]
Cell shaperodTAS [4]
Motilitynon-motileTAS [4]
Sporulationnon-sporulatingTAS [4]
Temperature rangethermophilic (50–69 °C)TAS [4]
Optimum temperature65 °CTAS [4]
pH rangemoderately acidophilic (4.1–7.8)
Optimum pH6.5
Carbon sourcepeptides, proteins, carbohydratesTAS [4]
Terminal electron receptoroxygenTAS [4]
Energy metabolismchemoorganotrophTAS [4]
MIGS-6Habitatgeothermal soilTAS [37]
MIGS-6.3Salinitynon-halophile (no growth > 1 % (w/v) NaCl)TAS [4]
MIGS-22Oxygen requirementobligate aerobeTAS [4]
MIGS-15Biotic relationshipfree-livingTAS [4]
MIGS-14Pathogenicitynot reportedNAS
MIGS-4Geographic locationMt Ngauruhoe, New ZealandTAS [37]
MIGS-5Sample collection2006NAS
MIGS-4.1 MIGS-4.2Latitude – Longitude39° 9’25.31”S - 175° 38’6.74”EIDA
MIGS-4.3Depthnot reportedIDA
MIGS-4.4Altitude2,270 mIDA

aEvidence 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 [38]

Classification and general features of P. methylaliphatogenes K22T aEvidence 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 [38] Subdivision 4 of the has five validly-named species: K22T,[4] [7, 8], [9], , and [3]. The latter three species are phylogenetically distant from K22T, are mesophilic and have differing pH ranges and substrate utilization profiles from that of K22T. is a moderately thermophilic facultatively anoxygenic photoheterotroph isolated from a hotspring microbial mat at Yellowstone National Park [7, 8]. An additional strain, Ellin6075 was isolated from an Australian pasture soil, and is a mesophilic heterotroph that derives its energy from complex carbohydrate sources, but has little information available regarding its phenotypic traits [10]. Common features shared by subdivision 4 strains include an aerobic and heterotrophic phenotype [3, 4], and membrane lipid iso-diabolic acids [5].

Organism information

Classification and features

Phylogenetic distances of closest-related phylotypes and cultivated subdivision 4 acidobacterial strains were determined by aligning the representative near full length 16S rRNA gene sequences (all sequences were > 1,400 nucleotides in length) and calculating sequence similarity via a pair-wise alignment within the ARB software environment [11]. Analysis showed that the 16S rRNA gene sequence of K22T (AM749787) is 85 % similar to strain A2-16T (JQ309130), and is 84 % similar to both strain A22_HD_4HT (KF245634), and Ac_23_E3T (KF245633) [3, 4, 9]. In addition, K22T shares 85 % 16S rRNA gene sequence similarity with both Ellin6075 (AY234727) [7] and BT (EF531339) [8]. The most closely-related phylotypes to K22T are two sequences from clonal libraries of environmental 16S rRNA genes (EU490264, EU490279) retrieved from geothermal soils on Mt. Erebus, Antarctica [12]; both of these shared 95 % 16S rRNA gene sequence similarity with K22T. Phylogenetic comparison (Fig. 1) showed that K22T is a taxonomically-distinct genus and species of subdivision 4 in the phylum .
Fig. 1

Phylogenetic tree based on 16S rRNA gene sequences of Pyrinomonas methylaliphatogenes K22T (highlighted) and other cultivated strains and clonal phylotypes within the phylum Acidobacteria. Four of the acidobacterial subdivisions are included. The tree was constructed via a Bayesian inference model (MrBayes), using Markov Chain Monte Carlo (MCMC - 2,000,000 resamples, four chains, temperature = 0.5) sampling methods to calculate posterior distributions of trees in the ARB software environment. Posterior probability values ≥ 90 % are indicated by open circles, ≥80 % by filled circles, and ≥70 % by open diamonds. The scale bar represents a 0.1 change per nucleotide position. Strains whose genomes have been sequenced, are marked with an asterisk; G. fermentans H5T (NZ_AUAU00000000), H. foetida TMBS4T (AGSB00000000), C. thermophilum BT (CP002414), P. methylaliphatogenes K22T (CBXV000000000), Candidatus ‘S. usitatus’ Ellin6076 (CP000473), Candidatus ‘K. versatilis’ Ellin345 (CP000360), Acidobacterium capsulatum ATCC 51196T (CP001472), Edaphobacter aggregans Wbg-1T (JQKI00000000), Granulicella mallensis MP5ACTX9T (CP003130), Granulicella tundricola MP5ACTX9T (CP002480), Terriglobus roseus KBS63T (CP003379), and Terriglobus saanensis SP1PR4T (CP002467). The phylotypes strains used as an outgroup included Thermoanaerobaculum aquaticum MP-01T (JX4200244), Dictyoglomus thermophilum H-6-12T (X69194), Caldisericum exile AZM16c01T (AB428365), Hydrogenobacter hydrogenophilus Z-829T (Z30424), Thermodesulfobacterium thermophilum DSM 1276T (AF334601), Deinococcus roseus TDMA-uv51 (AB264136), Truepera radiovicrix RQ-24T (DQ022076), Thermus aquaticus YT-1 (L09663), and Thermus scotoductus SE-1T (AF032127)

Phylogenetic tree based on 16S rRNA gene sequences of Pyrinomonas methylaliphatogenes K22T (highlighted) and other cultivated strains and clonal phylotypes within the phylum Acidobacteria. Four of the acidobacterial subdivisions are included. The tree was constructed via a Bayesian inference model (MrBayes), using Markov Chain Monte Carlo (MCMC - 2,000,000 resamples, four chains, temperature = 0.5) sampling methods to calculate posterior distributions of trees in the ARB software environment. Posterior probability values ≥ 90 % are indicated by open circles, ≥80 % by filled circles, and ≥70 % by open diamonds. The scale bar represents a 0.1 change per nucleotide position. Strains whose genomes have been sequenced, are marked with an asterisk; G. fermentans H5T (NZ_AUAU00000000), H. foetida TMBS4T (AGSB00000000), C. thermophilum BT (CP002414), P. methylaliphatogenes K22T (CBXV000000000), Candidatus ‘S. usitatus’ Ellin6076 (CP000473), Candidatus ‘K. versatilis’ Ellin345 (CP000360), Acidobacterium capsulatum ATCC 51196T (CP001472), Edaphobacter aggregans Wbg-1T (JQKI00000000), Granulicella mallensis MP5ACTX9T (CP003130), Granulicella tundricola MP5ACTX9T (CP002480), Terriglobus roseus KBS63T (CP003379), and Terriglobus saanensis SP1PR4T (CP002467). The phylotypes strains used as an outgroup included Thermoanaerobaculum aquaticum MP-01T (JX4200244), Dictyoglomus thermophilum H-6-12T (X69194), Caldisericum exile AZM16c01T (AB428365), Hydrogenobacter hydrogenophilus Z-829T (Z30424), Thermodesulfobacterium thermophilum DSM 1276T (AF334601), Deinococcus roseus TDMA-uv51 (AB264136), Truepera radiovicrix RQ-24T (DQ022076), Thermus aquaticus YT-1 (L09663), and Thermus scotoductus SE-1T (AF032127) K22T is non-motile and exhibits straight or bent rod cell morphology (0.3 – 0.6 μm in diameter and 1–4 μm in length) (Fig. 2). It has a temperature range (optimum) for growth of 50–69 °C (65 °C) and a pH range (optimum) of 4.1–7.8 (6.5). The bacterium has an obligately aerobic metabolism and can utilize a small selection of simple carbohydrates including glucose, lactate, alginate, mannose, xanthan, xylan, xylose, arabinose, and sucrose, as well as a limited variety of proteinaceous substrates including casamino acids, peptone, tryptone, yeast extract and nutrient broth (Table 1). It obtains nitrogen via the uptake of NO3−, NH4+, urea, yeast extract and casamino acids but cannot fix dinitrogen gas. The strain is not able to grow via photosynthesis, nor is it able grow autotrophically using CO2 as the sole source of carbon. However, optical density of culture is improved via the provision of additional CO2 in the headspace during heterotrophic growth, suggesting an assistive anapleurotic mechanism [4].
Fig. 2

Transmission electron micrograph of P. methylaliphatogenes K22T cultured in R2A liquid medium (60 °C), using a Zeiss LEO 912 Energy-Filtering TEM [34]. The scale bar represents 500 nm

Transmission electron micrograph of P. methylaliphatogenes K22T cultured in R2A liquid medium (60 °C), using a Zeiss LEO 912 Energy-Filtering TEM [34]. The scale bar represents 500 nm

Chemotaxonomic data

The primary cellular fatty acids are iso-C15:0 (40.8 %), iso-C17:0 (30.8 %), iso-C19:0 (12.1 %) and iso-C21:0 (4.8 %). K22T also possesses membrane-spanning dicarboxylic acid 13,16-dimethyl octacosanedioic (iso-diabolic) acid and glyceryl ethers of alkyl analogues of iso-C15:0 and iso-C17:0 and iso-diabolic acid. Its primary cellular quinone is MK-8 and its primary cellular lipids are phosphatidylethanolamine and phosphatidylcholine [4].

Genome sequencing information

Genome project history

The genome of K22T was selected for sequencing on the basis of its phylogenetic position and phenotypic dissimilarity to other cultured strains. The quality draft (QD) assembly and annotation was completed in December 2013. The genome project is deposited in the Genomes OnLine Database Gp0050834. A summary of the project information is shown in Table 2. The EMBL-Bank project accession number is CBXV000000000 and consists of 16 scaffolds. Table 2 presents the project information and its association with MIGS version 2.0 compliance [13].
Table 2

Project information

MIGS IDPropertyTerm
MIGS-31Finishing qualityHigh quality draft
MIGS-28Libraries usedTwo libraries used: One 454 library, one Illumina PE library
MIGS-29Sequencing platforms454 GS Junior Titanium, Illumina MiSeq
MIGS-31.2Fold coverage75.0 ×
MIGS-30AssemblersMIRA 4.0rc2
MIGS-32Gene calling methodProdigal
Locus tagPYK22
EMBL IDCBXV000000000
EMBL Date of Release12 January 2015
GOLD IDGp0050834
BIOPROJECTPRJEB4906
MIGS-13Source Material IdentifierDSMZ DSM 25857, ICMP ICMP 18710
Project relevanceMicrobial diversity of the Taupō Volcanic Zone, Tree of Life
Project information

Growth conditions and genomic DNA preparation

K22T was grown in 2 × 500 ml volumes of R2A liquid medium [14] at 60 °C in an air headspace (1 : 1 ratio of headspace to medium). The medium was sterilized at 121 °C (15 min, 15 psi) prior to inoculation. After three days of incubation, cells were collected via centrifugation. Culture purity was confirmed using an RFLP digestion (EcoR1) of the 16S rRNA gene PCR amplification product (amplification used the 9f/1492r primer set) [4]. The restriction digest pattern was identical to known axenic cultures of K22T. Genomic DNA was extracted from the wet biomass (200 mg) using the Nucleospin for Tissue extraction kit as per the manufacturer’s instructions (Macherey Nagel). The gDNA extract was purified via electrophoresis on a 0.8 % (w/v) agarose gel. The gel extracts were cleaned using a Gel Purification kit as per the manufacturer’s instructions (Macherey Nagel), giving a final concentration of 595 ng 100 μl−1. The purified gDNA was then frozen at −20 °C until sequenced.

Genome sequencing and assembly

Genomic sequencing was conducted using a combination of the Illumina MiSeq and 454 GS Junior platforms. A single-end 454 library was constructed according to the protocols of 454 GS FLX Titanium Rapid Library kits and GS Junior Titanium emPCR kits (Additional file 1). The sequencing of the 454 library yielded 75,215 reads with an average length of 492 bps. The paired-end Illumina library was constructed using the Nextera XT DNA Sample Preparation kit (Illumina), according to the manufacturer's protocol (Additional file 1), and sequenced on a MiSeq (2 × 150 bp paired-end reads), yielding 1,196,578 reads. The combined 454 (28.9 Mbp) and Illumina (301 Mbp) sequencing data were assembled together using the hybrid assembly capability of MIRA 4.0 rc4 [15] (parameter and methodologies provided in Additional file 1). The resulting contigs were manually curated via the Staden package [16], generating scaffolds with an average 75 × coverage. Scaffolds with average coverage two standard deviations below the aforementioned overall genome average were discarded (i.e. 32.5 × coverage threshold). The resulting 16 scaffolds contained 2,302,690 assembled reads and 3188 protein coding genes. The abundance of clustered regularly interspaced short palindromic repeats (CRISPRs) and other repeating elements (e.g. transposons and RHS repeat-encoded genes) may have contributed to the scaffolds junctions, such as those observed in scaffold CBXV010000001, CBXV010000004, CBXV010000005, and CBXV010000006.

Genome annotation

Genome annotation was processed via the DOE-JGI Integrated Microbial Genome – Expert Review (IMG-ER) annotation pipeline [17] using the following steps/components: Coding sequences (CDSs) were predicted using Prodigal [18]. The predicted CDSs were translated and used to search the National Center for Biotechnology Information (NCBI) non-redundant database, UniProt, TIGRFam, Pfam, PRIAM, KEGG, COG, and InterPro databases. These data sources were combined to ascribe descriptions of the protein tRNAScan-SE tool [19] was used to find tRNA genes, whereas ribosomal RNAs were found by searching against models of the ribosomal RNA genes built from SILVA. Other non-coding RNA such as the RNA components of the protein secretion complex and the RNaseP were identified by searching the genome for the corresponding Rfam profiles using INFERNAL [20]. Transmembrane helices and signal peptide cleavage sites within the putative proteins were predicted via TMHMM [21], and SignalP [22] respectively. Additional annotation and gene function prediction as well as data visualization was conducted within the IMG-ER system [23].

Genome properties

The QD assembly of the genome consists of 16 scaffolds totaling 3,788,560 bp in length (59.36 % GC content). Of the 3,244 genes predicted, 3,189 were protein-coding genes, and 55 were non-coding RNA genes. A majority (79.0 %) of genes were assigned putative functions, and the remainder were annotated as hypothetical proteins. The properties and the statistics of the K22T genome and the distribution of genes into COG functional categories are presented in Table 3, Table 4, and Fig. 3.
Table 3

Genome statistics

AttributeGenome (total)
Value% of totala
Size (bp)3,788,560100.0
DNA coding (bp)3,353,29888.5
G + C content (bp)2,249,19859.36
DNA Scaffolds16
Total genesb 3,244100.00
Protein-coding genes3,18998.3
RNA genes551.7
Pseudo genes00.0
Genes in paralog clusters253578.4
Protein coding genes with function prediction2,56479.0
Genes assigned to COGs2,02362.3
Genes assigned Pfam domain2,60580.3
Genes with signal peptides2939.0
Genes with transmembrane helices76623.7
CRISPR repeats15

aThe percentage 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

Table 4

Number of genes associated with the general COG functional categories

CodeValue% of totala Description
J1375.01Translation, ribosomal structure and biogenesis
A10.03RNA processing and modification
K1033.23Transcription
L772.41Replication, recombination and repair
B20.06Chromatin structure and dynamics
D270.85Cell cycle control, cell division, chromosome partitioning
V652.04Defense mechanisms
T1013.17Signal transduction mechanisms
M1915.99Cell wall/membrane/envelope biogenesis
N672.10Cell motility
U321.00Intracellular trafficking and secretion
O1233.85Posttranslational modification, protein turnover, chaperones
C1273.98Energy production and conversion
G1715.36Carbohydrate transport and metabolism
E2026.33Amino acid transport and metabolism
F652.04Nucleotide transport and metabolism
H1263.95Coenzyme transport and metabolism
I1053.29Lipid transport and metabolism
P1053.29Inorganic ion transport and metabolism
Q642.01Secondary metabolites biosynthesis, transport and catabolism
R2186.83General function prediction only
S852.66Function unknown
-1,22338.33Not in COGs

aThe total is based on the total number of protein coding genes (3180) in the annotated genome

Fig. 3

Graphical map of the genome of P. methylaliphatogenes K22T showing the eight largest scaffolds. From bottom to the top of each scaffold: Genes on forward strand (color by COG categories as denoted by the IMG platform), genes on the reverse strand (color by COG categories), RNA genes (tRNAs – green, sRNAs – red, other RNAs – black), GC content, and GC skew

Genome statistics aThe percentage 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 Number of genes associated with the general COG functional categories aThe total is based on the total number of protein coding genes (3180) in the annotated genome Graphical map of the genome of P. methylaliphatogenes K22T showing the eight largest scaffolds. From bottom to the top of each scaffold: Genes on forward strand (color by COG categories as denoted by the IMG platform), genes on the reverse strand (color by COG categories), RNA genes (tRNAs – green, sRNAs – red, other RNAs – black), GC content, and GC skew

Insights from the genome sequence

The K22T genome assembly has a size of 3.79 Mb with a %G + C content of 59.3, both of which are comparable with the genomes of other sequenced [24]. It possesses complete citric acid and pentose phosphate cycles. A complete electron transport pathway with an F-type ATPase, NADH dehydrogenase and cytochrome C complex, and the presence of genes encoding superoxide dismutase (PYK22_00483-00484) and catalase (PYK22_02691) are consistent with the observed aerobic phenotype. Genes encoding outer membrane secretion (for example, a type II secretion system, PYK22_02507-02511) and protein assembly (Bam complex, PYK22_02371 & 01777) are present, confirming the observed Gram-negative cell wall structure [4]. Interestingly, K22T possesses a near-complete complement of flagella encoding-genes (possibly missing the proximal rod flgF gene) despite having no observed motility. Key genes for all autotrophic carbon fixation pathways were absent. However, it was previously noted that while K22T was unable to fix carbon, additional CO2 to the headspace while growing heterotrophically improved growth [4]. The presence of phosphoenolpyruvate carboxylase and isocitrate dehydrogenase confirmed the ability of K22T to supplement carbon anapleurotically. No genes encoding the ability to fix dinitrogen gas were found, again confirming previous phenotypic observations. Interestingly, the genome contains a gene cluster encoding a group 5-type [NiFe] hydrogenase (PYK22_03058-03084) similar to that found in [25]; this may confer an ability to oxidize tropospheric concentrations of hydrogen for cell maintenance. Previous phenotypic characterization of K22T indicated that it possessed a heterotrophic phenotype with the ability to grow on a range of simple carbohydrates. The K22T genome encodes for a large number of beta-glucosidase and exoglucanase-acting glycosyl hydrolases, reflecting its ability to grow on primarily simple oligosaccharides such as cellobiose, sucrose, and maltose. A single C6 endoglucanase-acting glycosyl hydrolase (PYK22_03181) was identified in the genome despite having no reported growth on complex or crystalline cellulose as energy sources [4]. Two endo-1,4-beta-xylanases genes confer an ability to grow on xylan and xanthan gum. Transporters encoded in the K22T genome mainly belong to the ABC-type transporter superfamily and the major facilitator superfamily. This is consistent with previous study of acidobacterial genomes, which suggest these transporters types were adapted for low-nutrient conditions [26]. ABC transporters in K22T appear to be involved in the transport of carbohydrates (and derivatives) such as ribose, D-xylose, lipopolysaccharide (rfbAB, e.g. PYK22_01076-77, PYK22_01839-40, PYK22_02287-88), and lipo-oligosaccharide (nodJI, PYK22_00778 and PYK22_00785). These reflect the carbohydrate and polypeptide utilizing phenotype of the bacterium. K22T also possesses putative ABC transporters targeting amino acid cysteine, oligopeptides (oppABCDF, e.g. the PYK22_01277-281 cluster), and lipoproteins (lolCDE, PYK22_02373-4). Nitrogen assimilation is facilitated via an ammonia permease (PYK22_02853), the importation of oligopeptides by an oppABCDF ABC transporter system (similar to the system in [27]), and major facilitator superfamily nitrate/nitrite permeases (PYK22_00018 & PYK22_00946). Additionally, the K22T genome contained a cluster of genes tonB-exbB-exbD-exbD (PYK22_00991-94) associated with siderophore transport in some other acidobacterial species [26]. However, genes involved in siderophore synthesis, polyketide synthase, and nonribosomal peptide synthetase were not found, suggesting that it scavenges siderophores produced by other bacteria. Based upon 16S rRNA gene sequence similarity, the most closely related and cultivated strain to K22T is BT [28] (Fig. 1). The sequence similarity (~86 %) indicates that the two strains may belong to the same subdivision based on taxonomic sequence identity thresholds calculated for other prokaryotic taxa [29]. This phylogenetic dissimilarity between the two strains is also reflected in a comparison of the genomic content and the different metabolic modes of existence (chemoheterotrophic K22T vs. photoheterotrophic BT) of the two strains. For example, the BT genome encodes for genes for chlorosomes, bacteriochlorophyll pigments a and c and a pigment protein complex for phototrophic growth, whereas no genes encoding for phototrophy were found in K22T. The BT genome also contained significantly more COGs (15 vs 50) related to signal transduction kinases (COG0515 and COG0642) than were encoded in K22T. Conversely, K22T contained more genes related to amino acid utilization, such as amino acid transporters (COG0531) and amidohydrolases (COG1228), reflecting its ability to grow using proteinaceous media as the carbon and energy source. While both species possess carbohydrate-related metabolisms, the K22T genome encodes a much larger number of glycosyltransferases (COG0438 and COG0463) and beta-glucosidase-related glycosidases (COG1472) than that of B.

Conclusions

is one of the most widely-distributed bacterial phyla, particularly in soils [30-32]. Despite the wide distribution, the number of cultivated and sequenced representatives within most subdivisions within remains low [33]. The sequencing and annotation of the K22T genome presented here links the phenotypic traits of K22T [4] with its genetic characteristics, and represents a step that will assist future studies describing the ecological and metabolic capabilities of this widespread phylum.
  36 in total

1.  Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes.

Authors:  A Krogh; B Larsson; G von Heijne; E L Sonnhammer
Journal:  J Mol Biol       Date:  2001-01-19       Impact factor: 5.469

2.  Cultivation of globally distributed soil bacteria from phylogenetic lineages previously only detected in cultivation-independent surveys.

Authors:  Michelle Sait; Philip Hugenholtz; Peter H Janssen
Journal:  Environ Microbiol       Date:  2002-11       Impact factor: 5.491

3.  ARB: a software environment for sequence data.

Authors:  Wolfgang Ludwig; Oliver Strunk; Ralf Westram; Lothar Richter; Harald Meier; Arno Buchner; Tina Lai; Susanne Steppi; Gangolf Jobb; Wolfram Förster; Igor Brettske; Stefan Gerber; Anton W Ginhart; Oliver Gross; Silke Grumann; Stefan Hermann; Ralf Jost; Andreas König; Thomas Liss; Ralph Lüssmann; Michael May; Björn Nonhoff; Boris Reichel; Robert Strehlow; Alexandros Stamatakis; Norbert Stuckmann; Alexander Vilbig; Michael Lenke; Thomas Ludwig; Arndt Bode; Karl-Heinz Schleifer
Journal:  Nucleic Acids Res       Date:  2004-02-25       Impact factor: 16.971

4.  Chloracidobacterium thermophilum gen. nov., sp. nov.: an anoxygenic microaerophilic chlorophotoheterotrophic acidobacterium.

Authors:  Marcus Tank; Donald A Bryant
Journal:  Int J Syst Evol Microbiol       Date:  2015-02-09       Impact factor: 2.747

5.  Three genomes from the phylum Acidobacteria provide insight into the lifestyles of these microorganisms in soils.

Authors:  Naomi L Ward; Jean F Challacombe; Peter H Janssen; Bernard Henrissat; Pedro M Coutinho; Martin Wu; Gary Xie; Daniel H Haft; Michelle Sait; Jonathan Badger; Ravi D Barabote; Brent Bradley; Thomas S Brettin; Lauren M Brinkac; David Bruce; Todd Creasy; Sean C Daugherty; Tanja M Davidsen; Robert T DeBoy; J Chris Detter; Robert J Dodson; A Scott Durkin; Anuradha Ganapathy; Michelle Gwinn-Giglio; Cliff S Han; Hoda Khouri; Hajnalka Kiss; Sagar P Kothari; Ramana Madupu; Karen E Nelson; William C Nelson; Ian Paulsen; Kevin Penn; Qinghu Ren; M J Rosovitz; Jeremy D Selengut; Susmita Shrivastava; Steven A Sullivan; Roxanne Tapia; L Sue Thompson; Kisha L Watkins; Qi Yang; Chunhui Yu; Nikhat Zafar; Liwei Zhou; Cheryl R Kuske
Journal:  Appl Environ Microbiol       Date:  2009-02-05       Impact factor: 4.792

Review 6.  Impact of culture-independent studies on the emerging phylogenetic view of bacterial diversity.

Authors:  P Hugenholtz; B M Goebel; N R Pace
Journal:  J Bacteriol       Date:  1998-09       Impact factor: 3.490

7.  The Genomes OnLine Database (GOLD) v.5: a metadata management system based on a four level (meta)genome project classification.

Authors:  T B K Reddy; Alex D Thomas; Dimitri Stamatis; Jon Bertsch; Michelle Isbandi; Jakob Jansson; Jyothi Mallajosyula; Ioanna Pagani; Elizabeth A Lobos; Nikos C Kyrpides
Journal:  Nucleic Acids Res       Date:  2014-10-27       Impact factor: 16.971

Review 8.  Uniting the classification of cultured and uncultured bacteria and archaea using 16S rRNA gene sequences.

Authors:  Pablo Yarza; Pelin Yilmaz; Elmar Pruesse; Frank Oliver Glöckner; Wolfgang Ludwig; Karl-Heinz Schleifer; William B Whitman; Jean Euzéby; Rudolf Amann; Ramon Rosselló-Móra
Journal:  Nat Rev Microbiol       Date:  2014-09       Impact factor: 60.633

9.  Aridibacter famidurans gen. nov., sp. nov. and Aridibacter kavangonensis sp. nov., two novel members of subdivision 4 of the Acidobacteria isolated from semiarid savannah soil.

Authors:  Katharina J Huber; Pia K Wüst; Manfred Rohde; Jörg Overmann; Bärbel U Foesel
Journal:  Int J Syst Evol Microbiol       Date:  2014-02-26       Impact factor: 2.747

10.  Microbial biodiversity of thermophilic communities in hot mineral soils of Tramway Ridge, Mount Erebus, Antarctica.

Authors:  Rochelle M Soo; Susanna A Wood; Joseph J Grzymski; Ian R McDonald; S Craig Cary
Journal:  Environ Microbiol       Date:  2009-03       Impact factor: 5.491

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  7 in total

Review 1.  The Ecology of Acidobacteria: Moving beyond Genes and Genomes.

Authors:  Anna M Kielak; Cristine C Barreto; George A Kowalchuk; Johannes A van Veen; Eiko E Kuramae
Journal:  Front Microbiol       Date:  2016-05-31       Impact factor: 5.640

2.  The rhizospheric microbial community structure and diversity of deciduous and evergreen forests in Taihu Lake area, China.

Authors:  Zhiwen Wei; Xiaolong Hu; Xunhang Li; Yanzhou Zhang; Leichun Jiang; Jing Li; Zhengbing Guan; Yujie Cai; Xiangru Liao
Journal:  PLoS One       Date:  2017-04-05       Impact factor: 3.240

3.  Genomic insights into the Acidobacteria reveal strategies for their success in terrestrial environments.

Authors:  Stephanie A Eichorst; Daniela Trojan; Simon Roux; Craig Herbold; Thomas Rattei; Dagmar Woebken
Journal:  Environ Microbiol       Date:  2018-03-12       Impact factor: 5.491

4.  Acidobacteria Subgroups and Their Metabolic Potential for Carbon Degradation in Sugarcane Soil Amended With Vinasse and Nitrogen Fertilizers.

Authors:  Miriam Gonçalves de Chaves; Genivaldo Gueiros Z Silva; Raffaella Rossetto; Robert Alan Edwards; Siu Mui Tsai; Acacio Aparecido Navarrete
Journal:  Front Microbiol       Date:  2019-07-30       Impact factor: 5.640

Review 5.  Recent Understanding of Soil Acidobacteria and Their Ecological Significance: A Critical Review.

Authors:  Sadaf Kalam; Anirban Basu; Iqbal Ahmad; R Z Sayyed; Hesham Ali El-Enshasy; Daniel Joe Dailin; Ni Luh Suriani
Journal:  Front Microbiol       Date:  2020-10-30       Impact factor: 5.640

6.  GAL08, an Uncultivated Group of Acidobacteria, Is a Dominant Bacterial Clade in a Neutral Hot Spring.

Authors:  Ilona A Ruhl; Andriy Sheremet; Chantel C Furgason; Susanne Krause; Robert M Bowers; Jessica K Jarett; Triet M Tran; Stephen E Grasby; Tanja Woyke; Peter F Dunfield
Journal:  Front Microbiol       Date:  2022-01-11       Impact factor: 5.640

7.  Plants Rather than Mineral Fertilization Shape Microbial Community Structure and Functional Potential in Legacy Contaminated Soil.

Authors:  Jakub Ridl; Michal Kolar; Michal Strejcek; Hynek Strnad; Petr Stursa; Jan Paces; Tomas Macek; Ondrej Uhlik
Journal:  Front Microbiol       Date:  2016-06-24       Impact factor: 5.640

  7 in total

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