The genomic landscape of the verrucomicrobial methanotroph Methylacidiphilum fumariolicum SolV
© Anvar et al.; licensee BioMed Central Ltd. 2014
Received: 4 March 2014
Accepted: 6 October 2014
Published: 20 October 2014
Aerobic methanotrophs can grow in hostile volcanic environments and use methane as their sole source of energy. The discovery of three verrucomicrobial Methylacidiphilum strains has revealed diverse metabolic pathways used by these methanotrophs, including mechanisms through which methane is oxidized. The basis of a complete understanding of these processes and of how these bacteria evolved and are able to thrive in such extreme environments partially resides in the complete characterization of their genome and its architecture.
In this study, we present the complete genome sequence of Methylacidiphilum fumariolicum SolV, obtained using Pacific Biosciences single-molecule real-time (SMRT) sequencing technology. The genome assembles to a single 2.5 Mbp chromosome with an average GC content of 41.5%. The genome contains 2,741 annotated genes and 314 functional subsystems including all key metabolic pathways that are associated with Methylacidiphilum strains, including the CBB pathway for CO2 fixation. However, it does not encode the serine cycle and ribulose monophosphate pathways for carbon fixation. Phylogenetic analysis of the particulate methane mono-oxygenase operon separates the Methylacidiphilum strains from other verrucomicrobial methanotrophs. RNA-Seq analysis of cell cultures growing in three different conditions revealed the deregulation of two out of three pmoCAB operons. In addition, genes involved in nitrogen fixation were upregulated in cell cultures growing in nitrogen fixing conditions, indicating the presence of active nitrogenase. Characterization of the global methylation state of M. fumariolicum SolV revealed methylation of adenines and cytosines mainly in the coding regions of the genome. Methylation of adenines was predominantly associated with 5′- m6 ACN4GT-3′ and 5′-CC m6 AN5CTC-3′ methyltransferase recognition motifs whereas methylated cytosines were not associated with any specific motif.
Our findings provide novel insights into the global methylation state of verrucomicrobial methanotroph M. fumariolicum SolV. However, partial conservation of methyltransferases between M. fumariolicum SolV and M. infernorum V4 indicates potential differences in the global methylation state of Methylacidiphilum strains. Unravelling the M. fumariolicum SolV genome and its epigenetic regulation allow for robust characterization of biological processes that are involved in oxidizing methane. In turn, they offer a better understanding of the evolution, the underlying physiological and ecological properties of SolV and other Methylacidiphilum strains.
KeywordsMethylacidiphilum fumariolicum SolV Genome assembly Single molecule sequencing Pacific biosciences Methylation Gene expression Verrucomicrobial methanotrophs
The discovery of three verrucomicrobial methanotrophs that constitute the Methylacidiphilum genus [1–4] and characterization of their ecological, physiological, and phylogenetic properties have shed light on the diversity of processes through which aerobic methanotrophs use methane as their sole source of carbon and energy . A remarkable characteristic of these bacteria is their ability to oxidize methane in extreme and hostile conditions of volcanic and geothermal areas. Three Methylacidiphilum strains (M. fumariolicum SolV, M. kamchatkense Kam1, M. infernorum V4) were isolated from acidic volcanic areas in Italy, Russia, and New Zealand, respectively [1–3]. The draft genome assembly of M. fumariolicum SolV and the complete genome sequence of M. infernorum V4 have previously been published [6, 7], showing over 98% sequence identity for their 16S rRNA genes . Likewise, phylogenetic analysis of the pmoA genes, encoding the 24 kDa β-subunit of particulate methane mono-oxygenase (pMMO), revealed a strong similarity of these strains and their separation from other methanotrophs . In addition, major differences in C1 utilization pathways were found between these strains and other proteobacterial and NC10 methanotrophs . A comprehensive understanding of how these bacteria have evolved and thrive in such hostile environmental conditions partially relies on deciphering their genetic diversity and architecture.
The draft genome of M. fumariolicum SolV was previously constructed using Illumina GAII and Roche 454 reads . Despite the high coverage of Illumina GAII and Roche 454 sequencing reads as well as improvement of the assembly by manual curation of the assembly graph, the genome of M. fumariolicum SolV remained fragmented (109 contigs and a N50 value of 50,138 bp). The short lengths of Illumina GAII and Roche 454 sequencing reads can prevent the assembler from resolving repeats, which leaves the assembly incomplete. Furthermore, regions with high or low GC content are difficult to PCR and thus to sequence using second-generation sequencing platforms. Here, we report the complete genome sequence of the M. fumariolicum SolV that was determined by Pacific Biosciences single-molecule real-time (SMRT) sequencing technology. Using SMRT sequencing, long and highly accurate single-molecule sequencing reads were generated to resolve long repeats that remained in the unfinished and fragmented draft genome. These reads can resolve regions with extreme GC content, palindromic sequences, and other sequence contexts that challenge other sequencing platforms. Following the completion of the genome and the annotation of genes and functional subsystems, we characterize the phylogenetic relationship between the genome of M. fumariolicum SolV and that of other methanotrophs, particularly the M. infernorum V4. In order to assess the accuracy of the single chromosome assembly, two independent SMRT sequencing runs were generated and aligned to determine the consensus accuracy. Next, we performed genome-wide expression analysis to understand how major pathways are regulated in M. fumariolicum SolV cell cultures grown under different conditions. Bacterial DNA methylation is believed to play a role in maintaining genome integrity, gene regulation, and as a defence mechanism to identify and destroy foreign DNA that is differentially methylated [9–12]. So far, the global methylation state of bacterial kingdom is poorly understood , owing to the complexity and laborious nature of experiments that are needed for such studies. In the advent of SMRT sequencing technology, polymerase kinetics during sequencing can be used to identify N6-methladenine (6mA), 4-methylcytosine (4mC), and 5-methylcytosine (5mC) at a base-pair resolution . Since M. fumariolicum SolV genome contains copies of methyltransferases, we extend the analysis to epigenetic characterization of M. fumariolicum SolV by providing a global methylation state of the genome and the associated motifs. Finally, we explore the occurrence of methylation within the coding sequences that can affect the regulation of genes.
Genome assembly and annotation
Read statistics of 8 SMRT sequencing runs pre and post correction
PacBio RS (raw)
PacBio RS (corrected)*
Number of reads
Median read length
SMRT de novo genome assembly statistics
SMRT de novo2
Number of reads
Number of contigs
Bases in scaffolds
The accuracy of the final assembly was assessed after aligning single-molecule sequencing reads that were generated from two independent SMRT sequencing runs. We observed a consensus accuracy of 99.9998% between reads and the reference sequence, with no significant coverage fluctuation over the entire genome. Moreover, 99.9% of Illumina GAII and Roche 454 reads (Additional file 1: Table S1, Figures S4 and S5) that were used to assemble the draft genome  mapped to the complete genome sequence (Figure 1B). However, we observed significant fluctuations in Illumina GAII coverage that often coincides with gaps in the draft genome and the presence of repeats. We found 409 repeats across the genome, including 54 short tandem repeats (STRs). We observed a high GC content (55.5%) across larger repeats (median length of 1,826 bp), whereas tandem repeats had a low GC content of 27.9% (Additional file 1: Figure S6). This is not the case for the genome of M. infernorum V4 as only a few short tandem and larger repeats were found (Additional file 1: Figures S7 and S8). The co-occurrence of repeats and low depth of coverage can significantly hamper the assembly and may explain the fragmentation of the draft genome.
After annotating the complete genome sequence using RAST , we identified 2,741 protein-encoding genes and 49 RNAs, from which 932 (33.4%) were allocated to 314 annotated subsystems, biological processes or structural complexes that are realised by a set of functional roles . The origin of replication was identified by GC Skew analysis  and mapped to approximately 6,597 nucleotides upstream of the dnaA gene that is located at 326002–327357 genomic coordinates. The terminus of DNA replication is approximately located at 1,450,937 genomic position. The complete genome annotation contains 458 newly discovered genes, from which 178 were found in gaps in the draft genome. Only 11.2% of genes that are fully or partially located in gaps had known function whereas the remaining genes were annotated as hypothetical proteins (Additional file 1: Table S2). We also identified two newly annotated genes (PEG.1144 and PEG.1150) that belong to the C-subunit of pMMO that were absent in the draft assembly. Furthermore, the annotations of genes that belong to key metabolic pathways were manually curated based on comparison to public databases (Figure 1B).
Phylogenetic and comparative genome analysis
Except for the facultative methanotroph Methylocella tundrae and the obligate methanotroph Methyloferula stellata, all aerobic methanotrophs known so far contain a membrane-bound particulate methane mono-oxygenase (pMMO). Therefore, the pmoA gene (encoding the ~24 kDa β-subunit of pMMO) has been widely used as a marker to determine the phylogeny of methanotrophic bacteria, which is largely comparable to that of the 16S rRNA-based phylogeny [23–26]. The phylogenetic relationship between annotated PmoA proteins indicates a strong separation of the genus Methylacidiphilum (consisting of M. fumariolicum SolV, M. infernorum V4 , and M. kamchatkense Kam1 ) from other methanotrophs (Additional file 1: Figure S9). The pmoA3 gene shows a very distinctive branch in the phylogenetic tree whereas pmoA1 and pmoA2 genes are clustered together as a separate Methylacidiphilum branch deep in the main cluster. These observations are in concordance with phylogenetic relationships that were previously reported for PmoA proteins [3, 4, 6].
Since M. infernorum V4 is the closest relative for which the complete genome sequence is known , we compared the genome of M. fumariolicum SolV to this strain. The analysis highlights a number of inversions and transpositions between two genomes (Additional file 1: Figure S10). Amino acid comparison of protein-encoding genes (PEGs) revealed that 24.4% of PEGs are present in the genome of M. infernorum V4 with more than 80% identity, whereas 32.6% were exclusive to M. fumariolicum SolV (Additional file 1: Figure S11). Notably, 64.3% of PEGs have at least 50% identity to the genome of M. infernorum V4 (Additional file 1: Table S3). Shared PEGs are distributed across the entire genome. In addition, we did not find a significant enrichment of PEGs that are exclusive to either genome in a specific metabolic pathway (Additional file 1: Figure S12).
The majority of differentially expressed genes showed a relatively lower level of expression in N2fix and O2lim cell cultures compared to μmax (85.1% and 93.5%, respectively). The expression levels (count-per-million; CPM) and associated statistics are provided for the curated list of genes that are present in nine key pathways (Additional file 1: Tables S4–S12). Despite a substantial down-regulation of genes in N2fix cell cultures, 71.9% of genes that are involved in nitrogen fixation were significantly upregulated (Figure 2D and Additional file 1: Figure S13). This observation is in agreement with our previous physiological studies that indicate the presence of active nitrogenase in these cultures . We did not observe a significant up-regulation of this pathway in O2lim cell cultures (Additional file 1: Figures S14 and S15). Moreover, genes involved in two out of three pmoCAB operons that encode for three subunits of pMMO were differentially expressed in N2fix and O2lim cell cultures (Additional file 1: Figure S15). In both cultures, genes in pmoCAB1 operon showed a significantly higher expression levels whereas those involved in pmoCAB2 showed a strong decline in their expression as compared to μmax cell cultures (Additional file 1: Tables S5 and S10). The expression of genes involved in tricarboxylic acid (TCA) cycle, carbon energy storage, carbon fixation, glycogen metabolism, and Calvin Benson Bassham (CBB) cycle pathways were either unchanged or showed a significant decline in N2fix and O2lim cell cultures as compared to μmax cell cultures (Additional file 1: Tables S4, S6, S7, S10-S12).
Base modifications and associated motifs
Adenine motif statistics
# motifs in genome
# motifs detected
% motifs detected
It is essential to decipher a complete genetic makeup of Methylacidiphilum fumariolicum SolV to fully understand the underlying mechanisms used to oxidize methane in the hostile environmental conditions of volcanic and geothermal areas [4, 29]. Although the high-quality draft genome of M. fumariolicum SolV was previously published , efforts in finishing the genome remained unsuccessful due to the inherent limitations of second-generation sequencing technologies in resolving repeats and regions with extreme GC content. Here, we present the complete reference sequence of the M. fumariolicum SolV genome obtained using the single-molecule real-time (SMRT) sequencing strategy. SMRT sequencing of two large-insert template libraries followed by correction of sequencing errors resulted in high-quality de novo assembly of a single chromosome that is 2.48 Mbp in size, with a GC content of 41.5%. Due to the presence of long repeats and extremely low sequencing depth of Illumina GAII in GC-rich regions, this could not be achieved by combining short second-generation sequencing reads and long reads generated by SMRT sequencing [15, 30]. The de novo assembled complete genome of M. fumariolicum SolV has a very high quality as it holds a consensus accuracy of 99.9998% with single-molecule reads that were generated in two independent SMRT sequencing runs. We identified a number of misassemblies in the draft genome that were mainly the result of repeats and large fluctuation in Illumina GAII coverage. Despite recent advancements in chemistry and library preparation protocols of second-generation sequencing platforms, achieving a sufficient and uniform coverage on genomic regions with extreme GC content is challenging .
Genome annotation revealed the presence of 2,741 protein-encoding genes, 49 RNAs, and 314 functional subsystems. Moreover, the annotation of the complete genome sequence enabled the discovery of 458 genes that were previously missed in the draft genome. Closer analysis of newly annotated genes revealed the presence of two genes that belong to the C-subunit of pMMO. These genes were missed in the draft assembly. For new genes that fall in gaps or misassembled regions of the draft genome, only a minor fraction (11.2%) could be associated with functional subsystems. Other major pathways that could be associated with multiple genes were Ton and Tol transport systems and ribonucleotide reduction. After manually curating key metabolic pathways, a full Calvin-Benson-Bassham cycle was identified for carbon fixation whereas both the ribulose monophosphate and serine cycle pathways were absent. This is in concordance with our previous physiological studies . The phylogenetic analysis of pmoA genes confirmed the separation of three species within the genus of Methylacidiphilum from other known methanotrophs. Moreover, 24.4% of annotated genes were highly conserved (>80% homology) between M. fumariolicum SolV and M. infernorum V4, whereas almost a third remained exclusive to the genome of M. fumariolicum SolV. The genome-wide analysis of expression profiles revealed a substantial down-regulation of genes in cell cultures with nitrogen fixation (N2fix) or oxygen limitation (O2lim) growth conditions. Except for genes that were originally missed or misassembled in the draft genome, our results are in full concordance to our previous transcriptome analysis  that was performed on the draft genome. The expression of genes involved in TCA cycle, carbon energy storage, carbon fixation, glycogen metabolism, and CBB cycle pathways were either unchanged or declined. The prominent down-regulation of genes is expected as less energy production is needed for these cell cultures given that they have been cultured at (4 times) reduced growth rates compared to μmax cells. Furthermore, oxygen concentration may play a role in regulating pmoCAB operons as the expression of the pmoCAB1 and pmoCAB2 genes were significantly different in N2fix and O2lim cell cultures. It has also been shown that pMMO is differentially expressed under different growth conditions in M. kamchatkense. The genome of species in the Methylacidiphilum genus includes all necessary genes to fix nitrogen [4, 7]. In the absence of ammonium and nitrate, genes that are involved in nitrogen fixation were significantly upregulated, which is in concordance with physiological studies that indicate the presence of active nitrogenase in N2fix cell cultures . These observations are in agreement with the result of our previous transcriptome analysis that was performed on the draft genome .
DNA methylation is involved in a variety of biological processes and can have a profound physiological and functional consequence . Despite its importance, the global DNA methylation state for most of the bacterial kingdom is poorly understood. The genome of M. fumariolicum SolV consist of several methyltransferases, including three polypeptides of Type I restriction-modification (RM) system. The absence of these genes in the genome of M. infernorum V4 suggests that methylation process can be regulated differently between species in the Methylacidiphilum genus. Comparative analysis of methylation patterns between these bacteria can be performed to elucidate the underlying mechanisms through which the genome integrity, gene regulation and defence processes are maintained given that such data is available in the future. Here, we characterize the methylation state of the M. fumariolicum SolV genome at a base-pair resolution by performing two SMRT sequencing runs on a single, Tet1 treated library. The result indicates a genome-wide adenine methylation that is associated with 5′- m6 ACN4GT-3′, 5′-CC m6 AN5CTC-3′, and 5′-G m6 AGN5TGG-3′ motifs. Of 8,566 motif sites in the genome, only 103 sites were considered unmethylated under our growth condition. Although we were able to identify 220 4mCs and 29 5mCs, cytosine methylations were not associated with any specific motifs. To our knowledge, both 6mA motifs are potentially novel. It is possible that M. fumariolicum SolV contains genomic regions that are actively evolved against any occurrence of the 5′-CC m6 AN5CTC-3′ system as there are several regions without any methylation of this kind. Mobile elements can, in principle, contribute to avoiding the RM systems. However, our analysis rules out their involvement since none were identified in the M. fumariolicum SolV genome (data not shown). Further studies are needed to reveal the underlying mechanisms for the negative selection of this methylation motif in this bacterium. In addition, it is essential to investigate the global influence of identified methylation motifs on gene expression that can be differentially regulated throughout the cell cycle and their affect on the physiology and function of this bacterium. This study provides a comprehensive atlas of M. fumariolicum SolV genome that allows for further transcriptome and epigenetic analysis of cell cultures under different growth conditions and stage of cell cycle to unravel the mechanisms through which methane oxidation is regulated in harsh fumarolic conditions.
In this study, we reveal the complete genome sequence of Methylacidiphilum fumariolicum strain SolV and performed a thorough analysis of its genetic makeup, using a single-molecule real-time sequencing strategy. The finished sequence of a single chromosome enabled us to provide insights on genes that were missed due to gaps in the draft genome that were mainly caused by the limitations of second-generation sequencing technologies, owing to repetitiveness and high GC content of these regions. In addition, the complete genome sequence allowed us to expose misassemblies and perform a comparative analysis between genomes of the M. fumariolicum SolV and M. infernorum V4. For the first time, we provide a high-resolution and global methylation state of a Methylacidiphilum bacterium and the associated motifs at a base-pair resolution. Unravelling the M. fumariolicum SolV genome and its epigenetic regulation allow for robust characterization of biological processes that are involved in oxidizing methane. In turn, they offer a better understanding of the evolution, the underlying physiological and ecological properties of SolV and other Methylacidiphilum strains.
Bacterial growth conditions
Methylacidiphilum fumariolicum SolV used in this study was originally isolated from the volcanic re-gion Campi Flegrei, in Italy near Naples . The cells were grown in medium containing g l-1: MgCl2.6H2O, 0.08; CaHPO4.2H2O, 0.44; Na2SO4, 0.14; K2SO4, 0.35; (NH4)2SO4, 0.26; 1 ml l-1 trace element solution  and 2% (v/v) autoclaved fangaia soil extract (liquid obtained from the Fangai mud pool at Pozzuoli in Italy). The pH and temperature for growth were 2 and 55°C, respectively. To obtain DNA for de novo assembly and modification analysis, cells were grown with methane at μmax conditions as described in .
Genomic DNA preparation
Genomic DNA of Methylacidiphilum fumariolicum SolV was isolated from cultures using the cetyltrimethylammonium bromide (CTAB) method described before  but without the use of lytic enzymes.
SMRTbell DNA template libraries were prepared according to the manufacturer’s specification after the fragmentation with G-tubes (Covaris). Two different SMRTbell template library sizes were used, which had an average insert size of ~5 Kb and ~20 Kb. Subsequently, fragmented DNA was end-repaired and ligated to hairpin adapters. SMRT sequencing was carried out on the Pacific Biosciences RS according to standard protocols, 4 SMRT cells with the C1 chemistry (diffusion loading, 1 × 90 min, 5 Kb fragment size) and 6 SMRT cells with the XL binding kit used in conjunction with the C2 sequencing kit (Magbead loading, 1 × 120 min, 20 Kb fragment size). To enhance the 5mC kinetics analysis, 5mC residues were converted to 5caC using the 5mC Tet1 Oxidation kit (WiseGene), according to the manufacturer’s specification. Subsequently, for the purpose of base modification analysis, SMRTbell template libraries (insert size of ~2 Kb) were prepared and sequenced on two additional SMRT cells as described above. All runs were processed using the standard primary data analysis.
De novo genome assembly
All continuous long reads from the first eight SMRT sequencing runs that were longer than 300 bp and passed the quality threshold of 0.75 were merged. Subsequently, the hierarchical genome-assembly process (HGAP) pipeline  was used to correct the sequencing errors by setting the seed length to 1500 bp for constructing preassemblies. The resulting corrected and preassembled reads were fed into the revised version of the Celera Assembler [15, 35] that is most suited for long corrected PacBio reads, owing to the use of the overlap-layout-consensus (OLC) strategy. Since SMRT sequencing shows very little variations of the quality throughout the reads , no quality values were used during the assembly. In addition, the BOGART unitigger and the default parameters (except the mersize of 14) were used. To validate the quality of the assembly and determine the final genome sequence, Quiver consensus algorithm  and reads from two additional SMRT sequencing runs were used. Quiver takes advantage of the full information from the raw pulse and base-calls that are generated during the SMRT sequencing to infer the best consensus sequence . To further evaluate the quality of the final genome assembly, the consensus sequence were circularised and compared to the high quality draft genome  that was previously generated using Illumina and Roche 454 reads. Sequence gaps in the draft genome were further characterized using BLAST  and a custom Python script. Additional data analyses were carried out in R and Matlab. Gepard  and Circos  were used for visualization.
The origin and terminus of DNA replication were determined after GC Skew and cumulative GC Skew analysis performed by GenSkew (http://genskew.csb.univie.ac.at). Annotation of the assembled genome was performed using RAST prokaryotic genome annotation service . The previously annotated draft genome of M. fumariolicum SolV [3, 6] and the complete genome of M. infernorum V4  were used to aid the identification of coding and functional noncoding sequences. Genomic repeats and other structural variations were identified using Nucmer  and filtered according to length threshold of 500 bp and 95% copy identity. Tandem repeats were separately identified using Tandem Repeat Finder online service .
For the phylogenetic analysis of M. fumariolicum SolV, we used the pmoA gene that is commonly used as a phylogenetic marker for methanotrophic bacteria. The complete sequence of the pmoA and amoA genes were analysed as previously described [3, 4, 41]. Phylogeny.fr analysis pipeline  was used to construct the phylogeny. DNA and protein sequences were aligned using ProbCons  and were subsequently curated using Gblocks . MEGA 5  and PhyML  were used to determine the best fitting model and to construct the phylogenetic tree based on the maximum likelihood strategy. For validation purposes, the trees were bootstrapped for 100 times.
Comparative genome analysis
The final genome sequence of M. fumariolicum SolV was compared to the genome sequence of a closely related bacterial strain, M. infernorum V4. BLAST  and Nucmer  were used to highlight sequence similarities between the two strains. In addition, we used RAST  to compare the conservation of annotated genes and pathways.
The Illumina RNA-Seq data from cell cultures at maximum growth rate (μmax; GSM995700), cell cultures in a Nitrogen fixing environment (N2fix; GSM995701), and cell cultures in an Oxygen deprived environment (O2lim; GSM995702) were separately aligned to the complete genome sequence and analysed using Generic Transcriptome Analysis Pipeline (GENTRAP; https://git.lumc.nl/rig-framework/gentrap/tree/master). edgeR  was used to identify genes that show significantly variable expression profiles under different conditions. Additional analysis was carried out in R and Matlab.
Base modification analysis
After aligning sequencing reads to the assembled genome, kinetic signals acquired during Pacific Biosciences SMRT sequencing were processed for all genomic positions using a previously described protocol [14, 48]. To identify modified bases, Pacific Biosciences SMRT Portal analysis platform 2.0 was used. SMRT Portal uses an in silico kinetic model and a t-test based scoring system to detect modified bases. In order to accurately identify methylated bases, a threshold of 50 for log-transformed P value was used. The threshold was optimized according to the distribution of P values for different bases, minimizing the false positive rate. The identification of sequence motifs was performed using the SMRT Portal. Additional data analysis was carried out in R using Pacific Biosciences R-Kinetics package, available at https://github.com/PacificBiosciences/R-kinetics.
The aligned whole-genome shotgun sequencing reads, RNA-Seq data, and complete genome sequence of Methylacidiphilum fumariolicum SolV are deposited at the European Nucleotide Archive under the study accession number PRJEB6910 (http://www.ebi.ac.uk/ena/data/view/PRJEB6910).
This project was partially funded by the Leiden Genome Technology Center Innovation grant. The authors would like to thank the Pacific Biosciences for their help and support on this project.
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