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  • Extended genome report
  • Open Access

First draft genome sequence of a strain belonging to the Zoogloea genus and its gene expression in situ

  • 1, 3,
  • 1,
  • 1,
  • 1, 4,
  • 1,
  • 1,
  • 2,
  • 2,
  • 2,
  • 2 and
  • 1Email author
Contributed equally
Standards in Genomic Sciences201712:64

  • Received: 11 April 2017
  • Accepted: 21 September 2017
  • Published:


The Gram-negative beta-proteobacterium Zoogloea sp. LCSB751 (LMG 29444) was newly isolated from foaming activated sludge of a municipal wastewater treatment plant. Here, we describe its draft genome sequence and annotation together with a general physiological and genomic analysis, as the first sequenced representative of the Zoogloea genus. Moreover, Zoogloea sp. gene expression in its environment is described using metatranscriptomic data obtained from the same treatment plant. The presented genomic and transcriptomic information demonstrate a pronounced capacity of this genus to synthesize poly-β-hydroxyalkanoate within wastewater.


  • Genome assembly
  • Genomic features
  • Lipid metabolism
  • Metatranscriptomics
  • Poly-hydroxyalkanoate
  • Wastewater treatement plant


Zoogloea spp. are chemoorganotrophic bacteria often found in organically enriched aquatic environments and are known to be able to accumulate intracellular granules of poly-β-hydroxyalkanoate [1]. The combination of these two characteristics renders this genus particulary interesting from the perspective of high-value resource production from wastewater [2, 3]. In particular, PHA may be used to synthesize biodegradable bioplastics or chemically transformed into the biofuel hydroxybutyrate methyl ester [2].

The genus name Zoogloea is derived from the Greek term; meaning ‘animal glue’, which refers to a phenotypic trait that was previously used to differentiate between Zoogloea species and other metabolically similar bacteria [1]. The polysaccharides making up this “zoogloeal matrix” have been proposed to act as a matrix for the adsorption of heavy metals [4].

To date, no genome sequence exists for any of the representative strains of the five presently recognised Zoogloea species and thus, limited information is available with regards to the genomic potential of the genus. Here we report the genome of a newly isolated Zoogloea sp. strain as a representative of the genus, with a focus on its biotechnological potential in particular for the production of biodiesel or bioplastics. Accordingly, we studied the Zoogloea core metabolism of the genus, particularly on the lipid accumulating properties of Zoogloea sp. LCSB751. Moreover, we integrate metatranscriptomic sequencing data to resolve gene expression of this genus in situ [5, 6]. Finally, we also analyze the clustered regularly interspaced palindromic repeats mediated defence mechanisms of Zoogloea sp. LCSB751 to infer putatively associated bacteriophages [7].

Organism information

Classification and features

Zoogloea sp. LCSB751 was isolated from an activated sludge sample collected from the surface of the first anoxic tank of the Schifflange communal wastewater treatment plant, Schifflange, Luxembourg (49°30′48.29′′N; 6°1′4.53′′E) on 12 October 2011. The activated sludge sample was processed by serial dilution with sterile physiological water to a factor of 104 and the biomass was then cultivated on solid MSV peptone medium [8] at 20 °C and under anoxic conditions (less than 100 ppm oxygen). Single colonies were iteratively re-plated until a pure culture was obtained. The newly isolated Zoogloea sp. LCSB751 was cryopreserved in 10% glycerol at −80 °C.

Zoogloea sp. LCSB751 is a facultative anaerobe as it was found to also grow aerobically at 20 °C - 25 °C with agitation in the following liquid media: R2A [9], MSV A + B [8] or Slijkhuis A [10]. Cell clumps were observed in all tested culture conditions. When grown on R2A agar or on MSV peptone agar at 25 °C under aerobic conditions, Zoogloea sp. LCSB751 colonies were initially punctiform and after three days, they were white, circular and raised with entire edges. The morphology of cells derived from these growth conditions indicates that these are short rod-shaped bacteria (Fig. 1a). The Gram-staining was negative which is in accordance with previously described isolates of Zoogloea spp. [11, 12] (Table 1).
Fig. 1
Fig. 1

Photomicrograph of Zoogloea sp. strain LCSB751. a: bright field of anaerobically grown colonies, Nile Red stained after heat fixation; b: same field observed with epifluorescence using an excitation light from a Xenon arc lamp. The beam was passed through an Optoscan monochromator (Cairn Research, Kent, UK) with 550/20 nm selected band pass. Emitted light was reflected through a 620/60 nm bandpass filter with a 565 dichroic connected to a cooled CCD camera (QImaging, Exi Blue). The images were taken using an inverted microscope (Nikon Ti) equipped with a 60× oil immersion Nikon Apo-Plan lambda objective (1.4 N.A) and an intermediate magnification of 1.5×. The scale represents 10 μm. All imaging data were collected and analysed using the OptoMorph (Cairn Research, Kent, UK) and ImageJ

Table 1

Classification and general features of Zoogloea sp. strain LCSB751 according to the MIGS recommendation [18]




Evidence codea



Domain Bacteria

TAS [34]


Phylum Proteobacterium

TAS [35]


Class Betaproteobacterium

TAS [36]


Order Rhodocyclales

TAS [13]


Family Rhodocyclaceae

TAS [13]


Genus Zoogloea



Species Unknown



Strain: LCSB751


Gram stain


TAS [1]


Cell shape


TAS [1]




TAS [1]



Not reported



Temperature range

5–40 °C

TAS [11, 13, 14]


Optimum temperature

25–30 °C

TAS [11, 13]


pH range; Optimum

6.0–9.0; 6.5–7.5

TAS [11, 13]



Activated sludge




Inhibited at 0.5% NaCl (w/v)

TAS [14]


Oxygen requirement

facultative anaerobe



Biotic relationship








Geographic location




Sample collection













275 m


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 [37]

Phylogenetic analysis based on 16S rRNA gene sequences confirmed that strain LCSB751 belongs to the Zoogloea genus of the beta-proteobacterial class (Table 1). However, this strain formed a distinct phyletic linage from the five recognized species of Zoogloea , that are represented by the type strains Z. caeni EMB43T [13], Z. oleivorans BucT [11], Z. oryzea A-7T [14], Z. ramigera Itzigsohn 1868 ATCC 19544 T [15] and Z. resiniphila DhA-35T [16, 17] (Fig. 2).
Fig. 2
Fig. 2

Phylogenetic tree based on 16S rRNA gene sequences. The type species strains of every species of the Rhodocyclaceae family were used (in bold) as well as all the type strains of the genus Zoogloea , according to the List of Prokaryotic names with Standing in Nomenclature (LPSN; Whole genome GenBank IDs are provided in brackets. The 16S rRNA sequences were aligned using ClustalW, the alignment was curated using Gblocks conserving 81% of the initial positions and the phylogeny was computed with BioNJ using 100 bootstraps and the default (K2P) substitution model, using the pipeline [38]

Extended feature descriptions

The capacity of Zoogloea sp. LCSB751 to accumulate intracellular granules of lipids was tested using the dye Nile Red as described by Roume, Heintz-Buschart et al. [5]. Figure 1b shows the Nile Red positive phenotype of the described strain.

Additionally, the growth characteristics of the strain Zoogloea sp. LCSB751 were determined aerobically and at 25 °C with agitation in 3 different liquid media. Its generation time was the longest in Slijkhuis A medium with the highest biomass production. MSV A + B allowed a generation time of 4 h 30 min but lead to a poor biomass production as demonstrated by the low maximal optical density at 600 nm (OD600) of 0.21. The tested liquid medium which allowed the fastest growth for Zoogloea sp. LCSB751 was R2A while the biomass production was close to those observed for Slijkhuis A (Table 2).
Table 2

Generation time, growth rate and maximum growth of Zoogloea sp. LCSB751 under different aerobic culture conditions


Generation time

± standard deviationa

Growth rate


Maximum OD600 b


1 h 54 min ± 3 min




4 h 30 min ± 53 min



Slijkhuis A

10 h 42 min ± 1 h 51min



aValues are an average of independent triplicate experiments

bOD600 stands for optical density measured at 600 nm with the spectrometer “Biochrom WPA CO 8000 Cell Density Meter” using BRAND disposable semi-micro UV cuvettes of 12.5 × 12.5 × 45 mm

Genome sequencing information

Genome project history

Overall, 140 pure bacterial isolates were obtained from a single activated sludge sample, and screened for lipid inclusions using the Nile Red fluorescent dye. The genomes of 85 Nile Red-positive isolates were sequenced, of which isolate LCSB065 has already been published [5]. In particular, the genome of Zoogloea sp. LCSB751 was analyzed to obtain information about the functional potential of this genus, which has no publically available representative genome sequence, but also based on its particular phylogenetic position and to acquire knowledge on the genes related to lipid accumulation. The permanent draft genome sequence of this strain is available on NCBI with the GenBank accession number MWUM00000000 (BioSample: SAMN06480675). Table 3 summarizes the project information according to the MIGS compliance [18].
Table 3

Project information





Finishing quality



Libraries used

Illumina paired-end reads (insert size 30 bp)


Sequencing platforms

Illumina HiSeq

MIGS 31.2

Fold coverage




SPAdes (version 3.1.1)


Gene calling method

RAST servera and Prokkab


Locus Tag



Genbank ID



GenBank Date of Release

15 March 2017








Source Material Identifier

LMG 29444


Project relevance

Environmental, biodiversity, biotechnological

aGene calling using GLIMMER [27, 39]

bGene calling using Prodigal [26, 40]

Growth conditions and genomic DNA preparation

Zoogloea sp. LCSB751 was grown on MSV peptone agar medium [8] at 20 °C under anoxic conditions. Half of the biomass was scrapped in order to cryopreserve the strain, while the second half was used for DNA extraction using the Power Soil DNA isolation kit (MO BIO, Carlsbad, CA, USA). This cryostock was used to distribute the strain to the Belgian Coordinated Collection of Microorganisms collection center and deposited under number LMG 29444.

Genome sequencing and assembly

The purified DNA was sequenced on an Illumina Genome Analyzer IIx as previously described by Roume, Heintz-Buschart and colleagues [5]. Briefly, a paired-end sequencing library with a theoretical insert size of 300 bp was prepared with the AMPure XP/Size Select Buffer Protocol as previously described by Kozarewa & Turner [19], modified to allow for size-selection of fragments using the double solid phase reversible immobilization procedure [20] and sequenced on an Illumina HiSeq with a read length of 100 bp at TGen North (AZ, USA). The resulting 2,638,115 paired-end reads were trimmed of N bases (i.e. minimum phred quality score of 3 and filtered for Illumina TruSeq3 adapters), retaining 2,508,729 (~95%) of paired reads, 129,378 and eight forward- and reverse-singleton reads (i.e. mate pair discarded), respectively. All reads retained (paired-end and singleton reads) after the pre-processing were de novo assembled using SPAdes ver. 3.1.1, using the default kmer range and parameters [21].

The total number of contigs (776), the mean contig length (7497 bp) and the N50 value (180,423 bp) of the draft assembly of Zoogloea sp. LCSB751 (Table 3) indicate a fragmented assembly despite an estimated sequencing depth of ~150× fold coverage, ~100× based on 21-mer frequencies (using KMC2 [22]) and a ~ 120× average depth of coverage based on mapping reads back onto the de novo assembled contigs [2325]. Assembled contigs above 1 kb are represented in Fig. 3.
Fig. 3
Fig. 3

Circular graphical map of the Zoogloea sp. LCSB751 draft genome assembly, annotation and in situ expression. Data shown on the map explained from the outer to inner circles (i-x): i) contigs above 1 kb. Accordingly, all subsequent information contained within inner circles are based on these contigs, including ii) forward strand coding sequences in red (CDS), iii) reverse strand CDS in blue, iv) CDS that are related to lipid accumulation in yellow (forward and reverse strands), v-viii) gene expression in situ based on metatranscriptomic data from four sampling dates (25 January 2011, 11 January 2012, 5 October 2011, and 12 October 2011 [6]) ix) GC-deviation (from overall G + C %) and x) GC-skew, respectively. Graphics were generated using Circos [41]. CDS were predicted and annotated using the RAST server [27]. Metatranscriptomic data from four sampling dates were aligned against the draft genome using BWA [42] and depth of coverage, computed using BEDtools [25] was used as a proxy for expression. Depth of coverage <0.3 were set to zero

Genome annotation

Gene (i.e. open reading frame) prediction and annotation was carried out on the assembled contigs using Prokka ver. 1.11 [26] and the RAST server [27], both executed using default parameters and databases. Briefly, Prokka predicted a total of 5200 features including 5118 CDS, 3 rRNA, 76 tRNA genes and one tmRNA genes as well as two repeat regions. Similarly, the RAST server predicted a total of 5202 features, of which 5125 represent coding sequences (CDS), 6 rRNA and 71 tRNA genes. The annotation derived from the RAST server was used for most of the genome descriptions and downstream analyses, unless explicitly mentioned. CDS on the forward and reverse strands within contigs above 1 kb are represented in Fig. 3. In addition, the proteins predicted by the RAST server were submitted to i) the WebMGA server [28], ii) the SignalP server v.4.1 [29] and iii) the TMHMM server v.2.0 [30], for COG functional annotation, signal peptides prediction and transmembrane helices prediction, respectively. 5202 of the predicted amino acid sequences were annotated with 13,030 Pfam IDs. Finally, metaCRT [31] was used to predict CRISPR loci and the resulting CRISPR-spacers were submitted to the CRISPRtarget server [32] for the identification of putatively associated bacteriophage sequences.

Genome properties

The draft genome assembly of Zoogloea sp. LCSB751 consists of 5,817,831 bp with a G + C content of 64.2%, distributed over 776 contigs (773 scaffolds) with an N50 value of 180,423 bp (Table 4), GC-skew and –deviation of contigs above 1 kb are represented in Fig. 3. The raw reads are available via the GenBank nucleotide database under the accession number MWUM00000000, while the assembly and the annotation (IDs 6666666.102999) can be accessed through the RAST server guest account.
Table 4

Genome statistics of Zoogloea sp. LCSB751



% of Totala

Genome size (bp)



DNA coding (bp)b



DNA G + C (bp)



DNA scaffolds



Total genes

5,202c / 5,200d

100.00c / 100.00d

Protein coding genes

5,125c / 5,118d

98.52c / 98.42d

RNA genes

77c / 80d

1.48c / 1.54d

Pseudo genes



Genes in internal clusters



Genes with function prediction c



Genes assigned to COGs



Genes with Pfam domains



Genes with signal peptides



Genes with transmembrane helices



CRISPR repeats

2d / 3e


aTotal is based on either the size of the genome in base pairs, total number of scaffolds or the total number of genes in the annotated genome

bCumulative length of genes, without considering overlaps

cAs predicted by RAST server [27]

dAs predicted by Pokka [26]

eAs predicted by MetaCRT [31]

The rRNA operon region is assumed to be occurring in multiple copies, because all reads from this region were assembled into a single contig with a higher depth of coverage (~1200×, for RAST server features: fig|6666666.102999.rna.57, fig|6666666.102999.rna.60 and fig|6666666.102999.rna.61) compared to the rest of the genome. All 20 regular amino-acids were covered by tRNA-anticodons. The RAST server and Prokka annotated approximately 22% (1139) and 26% (1329) of the CDS as hypothetical proteins or proteins of unknown function, respectively. The distribution of COG functional categories are reported in Table 5, while subsystem-based functional classification are available via RAST server.
Table 5

Number of genes associated with general COG functional categories








Translation, ribosomal structure and biogenesis




RNA processing and modification








Replication, recombination and repair




Chromatin structure and dynamics




Cell cycle control, Cell division, chromosome partitioning




Defense mechanisms




Signal transduction mechanisms




Cell wall/membrane biogenesis




Cell motility




Intracellular trafficking and secretion




Posttranslational modification, protein turnover, chaperones




Energy production and conversion




Carbohydrate transport and metabolism




Amino acid transport and metabolism




Nucleotide transport and metabolism




Coenzyme transport and metabolism




Lipid transport and metabolism




Inorganic ion transport and metabolism




Secondary metabolites biosynthesis, transport and catabolism




General function prediction only




Function unknown



Not in COGs

Percentage (%) is based on the total number of protein coding genes in the genome

Insights from the genome sequence

Genome-based inference of the central metabolism

The genome of Zoogloea sp. LCSB751 is predicted to encode for all the genes required for a complete TCA cycle, but is missing some or the complete set of genes for the EMP pathway, the pentose phosphate pathway and the Entner-Doudoroff pathway.

A periplasmic nitrate reductase as well as a nitrite reductase were identified, suggesting complete reduction of nitrate to ammonia by Zoogloea sp. LCSB751. Furthermore, a complete set of nif genes involved in nitrogen fixation were also encoded in the genome.

Genes for a complete electron transport chain were predicted as well as an alternative RNF complex [33].

The genome of Zoogloea sp. LCSB751 also encodes numerous genes for flagella synthesis and assembly, suggesting a motile lifestyle. Furthermore, the strain is predicted to be prototroph for all amino acids, nucleotides and vitamins B2, B6, B9, H, and is missing a single gene for the synthesis of B12.

Additionally, the catechol 2,3-dioxygenase that has been studied in Z. oleivorans , was found to be encoded by the genome of Zoogloea sp. LCSB751 [11].

Lipid metabolism

The genome of Zoogloea sp. LCSB751 was further analysed with a focus on genes related to lipid metabolism, to better understand the lipid accumulation properties of Zoogloea spp. With 202 genes annotated with COG functional category I “Lipid transport and metabolism”, more than 3.8% of the genome of Zoogloea sp. LCSB751 is potentially dedicated to lipid metabolism (Table 5 and Fig. 3). Using the SEED subsystem feature, similar results were obtained with 194 genes (3.8%) classified in the “Fatty acids, lipids and Isoprenoids” subsystem (Table 6).
Table 6

Gene abundance and frequency related to the lipid metabolism of Zoogloea sp. LCSB751


Subsystem feature count

Subsystem feature (%)

Fatty acids, lipids and isoprenoids






  Cardiolipin synthesis



  Glycerolipid and glycerophospholipid metabolism in bacteria






  Triacylglycerol metabolism



Fatty acids



  Fatty acid biosynthesis FASII



  Fatty acid metabolism cluster



Fatty acids, lipids and isoprenoids - no subcategory



  Polyhydroxybutyrate metabolism






  Isoprenoids for quinones



  Isoprenoid biosynthesis



  Polyprenyl diphosphate biosynthesis



  Nonmevalonate branch of isoprenoid Biosynthesis



The different categories (in bold) and subcategories of the subsystem “Fatty acids, lipids and isoprenoid” are represented

Specifically, a complete set of predicted genes necessary for the synthesis, polymerisation and depolymerisation of PHA [2] was found as well as the genes of the MEP/DOXP pathway for terpenoid synthesis. However, the gene necessary to convert diacylglycerol in triacylglycerol or fatty alcohol in wax ester was not predicted, suggesting that PHA granules are the only lipid bodies accumulated in Zoogloea sp. LCSB751.

In situ gene expression

While genomic data provides information about the genetic potential of Zoogloea sp. LCSB751, it is possible to study expressed functions of the Zoogloea population in situ by using metatranscriptomic data derived from the biological wastewater treatment plant this strain originated from. Metatranscriptomic data derived from samples collected at four distinct time points (25 January 2011, 11 January 2012, 5 October 2011, and 12 October 2011), as studied by Muller and collaborators [6] was used herein. Genes with an average depth of coverage equal or higher than 0.3 were considered as expressed by mapping the rRNA-depleted transcripts on the genome of Zoogloea sp. LCSB751. 259, 312, 269 and 330 genes, respectively, were expressed, with 160 of them being expressed at all four time points (Fig. 3 and Additional file 1: Table S1). For the vast majority, (4732 genes), no transcripts were detected, which can be explained by the low population size of Zoogloea sp. in situ. This was estimated by phylogenetic marker gene (16S rRNA) amplicon sequencing on the sample collected on 25 January 2011 (data from [6]), for which the Zoogloea sp. population size was estimated at 0.1%. Similarly, metagenomic data from all the samples further support the low abundance of this strain in situ (Additional file 1: Table S2).

Nitrate reductase encoding genes (specifically the periplasmic nitrate reductase; NapA) were found to be expressed in all the four time points, while nitrite reductase or nitrogen fixation genes were sporadically expressed in those four time points. Interestingly, at least one copy of the acetoacetyl-CoA reductase and of the polyhydroxyalkanoic acid synthase were found to be expressed at each time point, possibly suggesting PHA accumulation by the population of Zoogloea sp. in this environment. Additionally, the third most expressed gene of Zoogloea sp. in this environment is a “granule associated protein (phasin)” typically known to be associated with PHA granules.

CRISPR-Cas system and putative bacteriophages

A total of three CRISPR loci were detected with metaCRT, accompanied by six CRISPR-associated (cas) genes. Five of the predicted cas genes occur consecutively, within the same contig and all of the predicted cas genes occur adjacent to a CRISPR locus [7]. Two of CRISPR repeats types were 37 bp in length (sequence: GTTTCAATCCACGTCCGTTATTGCTAACGGACGAATC; GTGGCACTCGCTCCGAAGGGAGCGACTTCGTTGAAGC) while one of them is 32 bp (sequence: CACTCGCTCCGGAGGGAGCGACTTCGTTGAAG). These CRISPRs contain 175, 51 and 11 spacers, respectively, ranging from lengths of 33 to 46 bp. A total of 77 matches were found when searching the spacers against the ACLAME phage/viral/plasmid gene database, NCBI phage and NCBI virus databases using the CRISPRtarget tool [32]. 51 of the spacers match to bacteriophages, 6 to viruses, 11 to genes within plasmids and six to genes within prophages (Additional file 1: Table S3). Based on the available metatranscriptomic data, minute to no expression of the cas genes was observed, while the detected CRISPR regions were not covered by the metatranscriptomic data (Additional file 1: Table S1). This is likely due to the overall low abundance of this species in situ (Additional file 1: Table S2).


We describe the first draft genome of a strain potentially belonging to a novel species within the genus Zoogloea . The genetic inventory of Zoogloea sp. LCSB751 makes it of particular interest for future wastewater treatment strategies based around the comprehensive reclamation of nutrients and chemical energy-rich biomolecules around the concept of a “wastewater biorefinery column” [3] as well as for industrial biotechnological applications. Future comparative genomics studies would allow the scientific community to further confirm if the reported genomic repertoire is indeed typical of this genus. Using metatranscriptomic data, we further show that Zoogloea sp. populations are active in the studied wastewater treatment plant despite being low in abundance and likely accumulate PHA in situ.



Clusters of Orthologous Groups


Clustered regularly interspaced palindromic repeats







The authors thank Mr. Bissen and Mr. Di Pentima from the Syndicat Intercommunal à Vocation Ecologique (SIVEC) for their permission to collect samples and gain access to the monitoring platform of the Schifflange wastewater treatment plant; Dr. Nicolás Pinel for assisting with the large data transfers and initial analysis of the isolates. Dr. Aidos Baumuratov for his support for microscopic analyses of the isolates; and the high performance computing facilities of the University of Luxembourg. This work was supported by an ATTRACT program grant (ATTRACT/A09/03) and a European Union Joint Programming in Neurodegenerative Diseases grant (INTER/JPND/12/01) both to PW, and Aide à la Formation Recherche (AFR) grants to both EELM (PRD-2011-1/SR) and SN (PHD-2014-1/7934898) as well as a CORE Junior grant to EELM (C15/SR/10404839), all funded by the Luxembourg National Research Fund (FNR).

Authors’ contributions

EELM and LAL isolated the strain, LAL prepared the DNA, NDH prepared the library and sequenced it, SN, MZ, CCL and EELM performed the bioinformatics analyses. MZ performed growth experiments. MH and EELM visualized data. EELM and PW designed and coordinated the project. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

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Authors’ Affiliations

Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 7 Avenue des Hauts-Fourneaux, L-4362 Esch-sur-Alzette, Luxembourg
TGen North, 3051 West Shamrell Boulevard, Flagstaff, AZ 86001, USA
Present address: Department of Microbiology, Genomics and the Environment, UMR 7156 UNISTRA – CNRS, Université de Strasbourg, Strasbourg, France
Present address: Saarland University, Building E2 1, 66123 Saarbrücken, Germany


  1. Dugan PR, Stoner DL, Pickrum HM: The Genus Zoogloea. In The Prokaryotes: Vol. 7: Proteobacteria: Delta and Epsilon Subclasses. Deeply Rooting Bacteria. New York: Springer Science & Business Media; 2006:1105.Google Scholar
  2. Muller EEL, Sheik AR, Wilmes P. Lipid-based biofuel production from wastewater. Curr Opin Biotechnol. 2014;30C:9–16.View ArticleGoogle Scholar
  3. Sheik AR, Muller EEL, Wilmes P. A hundred years of activated sludge: time for a rethink. Front Microbiol. 2014;5(March):47.PubMedPubMed CentralGoogle Scholar
  4. Sag̃ Y, Kutsal T. Biosorption of heavy metals by Zoogloea ramigera: use of adsorption isotherms and a comparison of biosorption characteristics. Chem Eng J Biochem Eng J. 1995;60:181–8.View ArticleGoogle Scholar
  5. Roume H, Heintz-Buschart A, Muller EEL, May P, Satagopam VP, Laczny CC, Narayanasamy S, Lebrun LA, Hoopmann MR, Schupp JM, Gillece JD, Hicks ND, Engelthaler DM, Sauter T, Keim PS, Moritz RL, Wilmes P. Comparative integrated omics: identification of key functionalities in microbial community-wide metabolic networks. NPJ Biofilms Microbiomes. 2015;1:15007.Google Scholar
  6. Muller EEL, Pinel N, Laczny CC, Hoopman MR, Narayanasamy S, Lebrun LA, Roume H, Lin J, May P, Hicks ND, Heintz-Buschart A, Wampach L, Liu CM, Price LB, Gillece JD, Guignard C, Schupp JM, Vlassis N, Baliga NS, Moritz RL, Keim PS, Wilmes P. Community integrated omics links the dominance of a microbial generalist to fine-tuned resource usage. Nat Commun. 2014;5:5603.View ArticlePubMedPubMed CentralGoogle Scholar
  7. Amitai G, Sorek R. CRISPR-Cas adaptation: insights into the mechanism of action. Nat Rev Microbiol. 2016;14:67–76.View ArticlePubMedGoogle Scholar
  8. Levantesi C, Rossetti S, Thelen K, Kragelund C, Krooneman J, Eikelboom D, Nielsen PH, Tandoi V. Phylogeny, physiology and distribution of “Candidatus Microthrix calida”, a new Microthrix species isolated from industrial activated sludge wastewater treatment plants. Environ Microbiol. 2006;8:1552–63.View ArticlePubMedGoogle Scholar
  9. Reasoner DJ, Geldreich EE. A new medium for the enumeration and subculture of bacteria from potable water. Appl Environ Microbiol. 1985;49:1–7.PubMedPubMed CentralGoogle Scholar
  10. Slijkhuis H. Microthrix parvicella, a filamentous bacterium isolated from activated sludge: cultivation in a chemically defined medium. Appl Environ Microbiol. 1983;46:832–9.PubMedPubMed CentralGoogle Scholar
  11. Farkas M, Táncsics A, Kriszt B, Benedek T, Tóth EM, Kéki Z, Veres PG, Szoboszlay S. Zoogloea oleivorans sp. nov., a floc-forming, petroleum hydrocarbon-degrading bacterium isolated from biofilm. Int J Syst Evol Microbiol. 2015;65:274–9.View ArticlePubMedGoogle Scholar
  12. Huang T-L, Zhou S-L, Zhang H-H, Bai S-Y, He X-X, Yang X. Nitrogen removal characteristics of a newly isolated indigenous aerobic denitrifier from oligotrophic drinking water reservoir, Zoogloea sp. N299. Int J Mol Sci. 2015;16:10038–60.View ArticlePubMedPubMed CentralGoogle Scholar
  13. Shao Y, Chung BS, Lee SS, Park W, Lee S-S, Jeon CO. Zoogloea caeni sp. nov., a floc-forming bacterium isolated from activated sludge. Int J Syst Evol Microbiol. 2009;59(Pt 3):526–30.View ArticlePubMedGoogle Scholar
  14. Xie C-H, Yokota A. Zoogloea oryzae sp. nov., a nitrogen-fixing bacterium isolated from rice paddy soil, and reclassification of the strain ATCC 19623 as Crabtreella saccharophila gen. nov., sp. nov. Int J Syst Evol Microbiol. 2006;56(Pt 3):619–24.View ArticlePubMedGoogle Scholar
  15. Unz R. Neotype strain of Zoogloea ramigera Itzigsohn. Int J Syst Bacteriol. 1971;21:91–9.View ArticleGoogle Scholar
  16. Mohn WW, Wilson AE, Bicho P, Moore ER. Physiological and phylogenetic diversity of bacteria growing on resin acids. Syst Appl Microbiol. 1999;22:68–78.View ArticlePubMedGoogle Scholar
  17. International Journal of Systematic Bacteriology. Validation of the publication of new names and new combinations previously effectively published outside the IJSB. List No. 70. Int J Syst Bacteriol 1999, 49:935–936.Google Scholar
  18. Field D, Garrity G, Gray T, Morrison N, Selengut J, Sterk P, Tatusova T, Thomson N, Allen MJ, Angiuoli SV, Ashburner M, Axelrod N, Baldauf S, Ballard S, Boore J, Cochrane G, Cole J, Dawyndt P, De Vos P, DePamphilis C, Edwards R, Faruque N, Feldman R, Gilbert J, Gilna P, Glöckner FO, Goldstein P, Guralnick R, Haft D, Hancock D, et al. The minimum information about a genome sequence (MIGS) specification. Nat Biotechnol. 2008;26:541–7.View ArticlePubMedPubMed CentralGoogle Scholar
  19. Kozarewa I, Turner DJ. 96-plex molecular barcoding for the Illumina Genome Analyzer. Methods Mol Biol. 2011;733:279–98.View ArticlePubMedGoogle Scholar
  20. Rodrigue S, Materna AC, Timberlake SC, Blackburn MC, Malmstrom RR, Alm EJ, Chisholm SW. Unlocking short read sequencing for metagenomics. PLoS One. 2010;5:e11840.View ArticlePubMedPubMed CentralGoogle Scholar
  21. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, Lesin VM, Nikolenko SI, Pham S, Prjibelski AD, Pyshkin AV, Sirotkin AV, Vyahhi N, Tesler G, Alekseyev MA, Pevzner PA. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol A J Comput Mol Cell Biol. 2012;19:455–77.View ArticleGoogle Scholar
  22. Deorowicz S, Kokot M, Grabowski S, Debudaj-Grabysz A. KMC 2: fast and resource-frugal k-mer counting. Bioinformatics. 2015;31:1569–76.View ArticlePubMedGoogle Scholar
  23. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R. The sequence alignment/map format and SAMtools. Bioinformatics. 2009;25:2078–9.View ArticlePubMedPubMed CentralGoogle Scholar
  24. Li H, Durbin R. Fast and accurate long-read alignment with Burrows–Wheeler transform. Bioinformatics. 2010;26:589–95.View ArticlePubMedPubMed CentralGoogle Scholar
  25. Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 2010;26:841–2.View ArticlePubMedPubMed CentralGoogle Scholar
  26. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014;30:2068–9.View ArticlePubMedGoogle Scholar
  27. Aziz RKK, Bartels D, Best AAA, DeJongh M, Disz T, Edwards RAA, Formsma K, Gerdes S, Glass EMM, Kubal M, Meyer F, Olsen GJJ, Olson R, Osterman ALL, Overbeek RAA, McNeil LKK, Paarmann D, Paczian T, Parrello B, Pusch GDD, Reich C, Stevens R, Vassieva O, Vonstein V, Wilke A, Zagnitko O. The RAST Server: rapid annotations using subsystems technology. BMC Genomics. 2008;9:75.View ArticlePubMedPubMed CentralGoogle Scholar
  28. 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.View ArticlePubMedPubMed CentralGoogle Scholar
  29. Petersen TN, Brunak S, von Heijne G, Nielsen H. SignalP 4.0: discriminating signal peptides from transmembrane regions. Nat Methods. 2011;8:785–6.View ArticlePubMedGoogle Scholar
  30. 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;305:567–80.View ArticlePubMedGoogle Scholar
  31. Bland C, Ramsey TL, Sabree F, Lowe M, Brown K, Kyrpides NC, Hugenholtz P. CRISPR recognition tool (CRT): a tool for automatic detection of clustered regularly interspaced palindromic repeats. BMC Bioinformatics. 2007;8:209.View ArticlePubMedPubMed CentralGoogle Scholar
  32. Biswas A, Gagnon JN, Brouns SJJ, Fineran PC, Brown CM. CRISPRTarget. RNA Biol. 2013;10:817–27.View ArticlePubMedPubMed CentralGoogle Scholar
  33. Biegel E, Schmidt S, González JM, Müller V. Biochemistry, evolution and physiological function of the Rnf complex, a novel ion-motive electron transport complex in prokaryotes. Cell Mol Life Sci C. 2011;68:613–34.Google Scholar
  34. 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;87:4576–9.View ArticlePubMedPubMed CentralGoogle Scholar
  35. Garrity GM, Bell JA, Lilburn T. Phylum XIV. phyl. nov. In: DJ Brenner, NR Krieg, JT Staley, GM Garrity (eds), Bergey’s Manual of Systematic Bacteriology. Second Edition, Volume 2, Part B. New York: Springer; 2005, p. 1.Google Scholar
  36. Garrity GM, Bell JA, Lilburn T. Class II. class. nov. In: DJ Brenner, NR Krieg, JT Staley, GM Garrity (eds), Bergey’s Manual of Systematic Bacteriology. Second Edition, Volume 2, Part C. New York: Springer; 2005, p. 575.Google Scholar
  37. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, Harris MA, Hill DP, Issel-Tarver L, Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, Sherlock G. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet. 2000;25:25–9.View ArticlePubMedPubMed CentralGoogle Scholar
  38. Dereeper A, Guignon V, Blanc G, Audic S, Buffet S, Chevenet F, Dufayard J-F, Guindon S, Lefort V, Lescot M, Claverie J-M, Gascuel O. robust phylogenetic analysis for the non-specialist. Nucleic Acids Res. 2008;36(Web Server issue):W465–9.View ArticlePubMedPubMed CentralGoogle Scholar
  39. Delcher AL, Harmon D, Kasif S, White O, Salzberg SL. Improved microbial gene identification with GLIMMER. Nucleic Acids Res. 1999;27:4636–41.View ArticlePubMedPubMed CentralGoogle Scholar
  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;11:119.View ArticlePubMedPubMed CentralGoogle Scholar
  41. Krzywinski M, Schein J, Birol I, Connors J, Gascoyne R, Horsman D, Jones SJ, Marra MA. Circos: an information aesthetic for comparative genomics. Genome Res. 2009;19:1639–45.View ArticlePubMedPubMed CentralGoogle Scholar
  42. Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009;25:589–95.Google Scholar


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