A proteomic determination of cold adaptation in the Antarctic archaeon, Methanococcoides burtonii



A global view of the biology of the cold-adapted archaeon Methanococcoides burtonii was achieved using proteomics. Proteins specific to growth at 4°C versus Topt (23°C) were identified by mass spectrometry using the draft genome sequence of M. burtonii. mRNA levels were determined for all genes identified by proteomics, and specific enzyme assays confirmed the protein expression results. Key aspects of cold adaptation related to transcription, protein folding and metabolism, including specific roles for RNA polymerase subunit E, a response regulator and peptidyl prolyl cis/trans isomerase. Heat shock protein DnaK was expressed during growth at Topt, indicating that growth at ‘optimal’ temperatures was stressful for this cold-adapted organism. Expression of trimethylamine methyltransferase involves contiguous translation of two open reading frames, which is likely to result from incorporation of pyrrolysine at an amber stop codon. Thermal regulation in M. burtonii is achieved through complex gene expression events involving gene clusters and operons, through to protein modifications.


Temperature is a critical environmental factor controlling the evolution and biodiversity of life on earth (Feller and Gerday, 2003). The majority of the earth's biosphere is permanently below 5°C, dominated by ocean depths, glacier, alpine and polar regions (Feller and Gerday, 2003). The capacity of organisms to thrive in cold environments has led, in recent years, to an aggressive pursuit of cold adaptation ecology, biology and biotechnology (Karl et al., 1999; Cavicchioli et al., 2002; Thomas and Dieckman, 2002; Feller and Gerday, 2003) and fuelled interest in astrobiology linked to the discoveries of frozen water on Mars and Europa (Chyba and Phillips, 2001; Cavicchioli, 2002; Mitrofanov et al., 2003).

Archaea contribute significantly to biomass in cold environments (Karner et al., 2001), although few have been isolated. Recent genomic studies on cold-adapted archaea have facilitated a comparison of archaeal genomes from organisms capable of growth at 0°C and 110°C (Saunders et al., 2003). Distinguishing features of psychrophiles that emerged from the study included structural and compositional features of proteins and tRNA and the identification of novel, putative nucleic acid-binding proteins.

Advances in understanding the biology of cold-adapted archaea have occurred primarily through genomic and functional studies of the Antarctic methanogen Methanococcoides burtonii (Cavicchioli et al., 2000; Saunders et al., 2003). M. burtonii is a flagellated, motile methanogen isolated from permanently cold (1–2°C), methane-saturated waters from the bottom of Ace Lake, Antarctica (Franzmann et al., 1992).

Although M. burtonii has evolved in a permanently cold environment, it grows most rapidly at 23°C (Topt) and will tolerate temperatures up to 29°C (Franzmann et al., 1992). The tendency to be able to grow faster at temperatures exceeding that of the natural environment has been observed for the majority of psychrophiles (Feller and Gerday, 2003) and has generated a view that psychrophiles are not well adapted to their environmental temperatures. This, however, is a misconception, as faster growth rates arise from the kinetic effect of temperature on rates of reactions (Feller and Gerday, 2003). In essence, a microorganism will continue to grow faster until the most thermally sensitive cellular processes or structures become thermally compromised and therefore rate limiting. Consistent with this, physiological indicators including viability, enzyme secretion, protein synthesis and membrane permeability indicate that cold-adapted microorganisms are stressed when growing at Topt (Feller and Gerday, 2003).

Methanococcoides burtonii is an obligately methylotrophic methanogen able to use methylamines and methanol, but not formate, H2:CO2 or acetate for growth (Franzmann et al., 1992). Methanogens play a critical role not only in the global carbon cycle, but in global warming through the production of methane as a greenhouse gas (Galagan et al., 2002). Methylotrophic methanogens contribute an important and unusual role in global methane production. While hydrogen- and acetate-using methanogens compete with sulphate-reducing bacteria for substrate, methylotrophic methanogens are able to acquire and use trimethylamine without competition from other microorganisms (Summons et al., 1998; Deppenmeier, 2002a). Trimethylamine is consumed by methylotrophs in sediment and open-marine systems where it is abundant and derives from the osmoregulant, glycine betaine, which is present in a wide range of marine microorganisms and metazoans (Summons et al., 1998). Whereas there is a developing understanding of gene networks and regulation in acetoclastic and hydrogen-using methanogens (Deppenmeier et al., 2002; Galagan et al., 2002), there is a relatively limited understanding of obligate methylotrophs.

The principal aim of the present study was to examine the state of the M. burtonii cell by comparing protein and mRNA levels during growth at low temperature (4°C) and at Topt (23°C). Previous studies addressing cold adaptation in bacteria and eukaryotes have tended to focus on cold shock rather than cold growth. Moreover, few studies have described the molecular responses of cold-adapted microorganisms (Rabus et al., 2002), and no proteomic or microarray studies have reported the identification of genes involved in cold adaptation. This study therefore provides the first view of global gene expression in cold-adapted microorganisms and is a benchmark for comparative studies in other organisms. The study also identifies genes involved in methanogenesis in M. burtonii that are thermally regulated, thus highlighting the role that energy generation and biosynthesis pathways play in cold adaptation.


Two-dimensional gel analysis

Proteins important for cold adaptation were examined by comparing two-dimensional electrophoresis profiles for cells in late logarithmic phase, growing at low temperature (4°C) and Topt (23°C), using an approach that we have used previously for identifying starvation- and growth rate-regulated proteins from a marine bacterium (Ostrowski et al., 2004). A pH gradient of 4–7 was chosen for the first dimension, as a large proportion of the putative proteins from the draft genome sequence of M. burtonii have a predicted pI of 4–7 (Fig. 1). Second-dimension electrophoresis was performed on 11.5% and 15% reducing SDS polyacrylamide gels to optimize separation of proteins with a molecular weight of 20–150 kDa and 5–30 kDa respectively. Approximately 20% of the proteome is predicted to be 20 kDa or less, although it is noteworthy that M. burtonii does not encode any small Csp proteins, which are typical features of cold shock in bacteria (Saunders et al., 2003). The total number of spots analysed quantitatively was restricted to those spots that appeared on all three replicates of the same growth condition (Fig. 2). A total of 209 spots were analysed from the 11.5% gels and 28 spots from the 15% gels. This represented ≈ 50% of the maximum number of spots (400) detected on a typical 11.5% gel.

Figure 1.

Predicted proteome of M. burtonii. Relative abundance of predicted proteins in the proteome relative to isoelectric point.

Figure 2.

Comparison of two-dimensional protein profiles for M. burtonii. Growth temperature, 4°C (A and C) and 23°C (B and D). Acrylamide, 11.5% (A and B) and 15% (C and D). Arrows and numbers identify spots with increased intensity quantified in Table 1.

On comparing the spots present on the three replicate gels from the two growth temperatures, 54 spots had differential spot intensities of more than twofold. The intensity of 21 protein spots (10% of total) was elevated at 4°C, and the intensity of 33 spots (16% of total) was reduced at 4°C (Fig. 2). The relative change in intensity for spots observed at only one growth temperature (unique spots) was calculated using the detection limit of the least intense spot (350 p.p.m.). The range of spot intensities varied from 350 to 45 323 p.p.m. (120-fold).

Protein identification

Collision-induced dissociation (CID) spectra generated by µLC/ESI-MS/MS were obtained for all 54 spots with differential spot intensities. Nineteen of the 21 protein spots that were more intense at 4°C and 24 of the 33 protein spots that were less intense at 4°C were identified (Table 1). All identifications were made using the M. burtonii genome sequence database with sequest software. In contrast, only 10 identifications could be made using the NCBI nr database, producing equivalent matches. The number of peptide matches for the 43 spots that were identified varied from one to 15. The only instance in which more than one protein was detected from a single spot was for spot 3. For most proteins, the observed pI closely matched theoretical values. The largest difference was for spot 28, which had an observed/theoretical pI of 6.3/5.1. As the observed molecular weight of this spot (46 kDa) was similar to the predicted molecular weight for the protein (45 kDa), it is possible that the discrepancy in pI results from post-translational modification. The observed molecular weight of proteins was generally similar to predicted molecular weight, with spots 23, 40, 46 and 47 being the main exceptions. A number of proteins (spots 9, 12, 20, 23, 36, 40, 46, 47 and 51) had an observed weight more than 30% greater or less than their predicted molecular weight. The differences in observed molecular weights may reflect a changed second-dimension separation caused by anomalies due to protein sequence affecting the amount of SDS bound to the protein, post-translational modifications, spliced variants or SDS-resistant multimeric forms of the proteins. The identity of proteins from 11 spots (14, 17, 22, 30,32, 37, 38, 44, 52, 53 and 54) was not obtained. This resulted from a combination of low abundance, a lack of peptides following trypsin digestion and/or CID spectra of insufficient quality.

Table 1. . Properties of proteins identified by proteomics from M. burtonii.
No. of
Functional category and gene functionContig_b
Differential abundanced
  • a

    . Average intensity of spot at growth temperature in which it was most abundant.

  • b

    . Contig_gene numbers are from the 11 Dec 2003 release of the M. burtonii genome sequence annotation.

  • c

    . Numbers denote genes in different clusters.

  • d

    . Values in bold highlight protein and/or mRNA abundance elevated at 4

  • °


  • e

    . Un, unique; (), fold difference calculated relative to detection limit (350 p.p.m.); standard deviation (as a percentage of the maximum spot intensity) ranged from 5% to 30%.

  • f

    . mRNA levels that changed by less than 2 are shown, but tended to be not statistically significant (t-test, 95%).

  • g

    . (/), peptides matching contig_genes 61_917/918.

  • *Proteins also identified by searching the NCBI nr database using Mascot.

 1* 15895 65.1/4.875/62Methyl coenzyme M reductase, α subunit65_13251 2.3 3.1
 7 8223 55.5/5.152/45Methyl coenzyme M reductase, β subunit65_13211 2.0 3.5
 24 2272 95.0/5.152/45Methyl coenzyme M reductase, β subunit65_132110.2 
 25 5670155.1/5.152/45Methyl coenzyme M reductase, β subunit65_132110.5 
 28 1147 46.3/5.146/45Methyl coenzyme M reductase, β subunit65_132110.45 
 15* 1411 55.7/5.633/28Methyl coenzyme M reductase, γ subunit65_13241 2.0 3.4
 23* 1538 24.9/5.651/28Methyl coenzyme M reductase, γ subunit65_13241Un (<0.2) 
 34 2147 15.3/5.630/28Methyl coenzyme M reductase, γ subunit65_13241Un (<0.2) 
 40  825 24.6/4.524/59Methylamine methyltransferase61_916 0.24 3.3
 2 115910 (7/3)g4.8/5.262/49Trimethylamine methyltransferase61_917/9182 Un (>3.3) 1.1
 322836 6 (4/2)g4.6/5.263/49Trimethylamine methyltransferase61_917/9182 4.2  
 41 3911 24.5/4.028/23Trimethylamine corrinoid protein61_91920.42 1.6
 42 5630 34.4/4.028/23Trimethylamine corrinoid protein61_91920.27 
 43 5228 34.3/4.028/23Trimethylamine corrinoid protein61_9192Un (<0.07) 
 45 6640 14.1/4.029/23Trimethylamine corrinoid protein61_9192Un (<0.05) 
 51 6727 14.9/4.114/23Trimethylamine corrinoid protein69_194430.320.6
 48* 7745 54.5/4.623/18Dimethylamine corrinoid protein69_192140.42 2.4
 11* 2059 15.0/5.044/38F420H2 dehydrogenase 40 kDa subunit48_1745 3.6 4.2
 1015554 94.7/4.848/37Methylcobalamin:CoM methyltransferase60_801  2.0 1.3
 21 3012 14.9/4.759/51ATP synthase β chain66_14786Un (<0.1)1.0
 12* 1861 34.9/4.842/32Pyridoxine biosynthesis protein70_2449  2.6 1.1
 49 1259 25.0/5.215/15Riboflavin biosynthesis protein70_2551  2.5  
 16 2774 44.6/4.531/30Dihydroorotate dehydrogenase55_4837 3.7 1.1
 4  725 94.9/4.758/503-Isopropylmalate dehydratase67_16118 Un (>2.1) 9.9
 5* 2358135.1/4.956/45Adenosylhomocysteinase66_13819 Un (>6.7) 1.5
 8 6226 45.5/5.649/54Glutamate dehydrogenase69_2111  5.9 2.1
 6 1147 15.5/5.159/48Isopropylmalate synthase68_1677  2.1 2.9
 9  2137 35.3/4.849/37Glyceraldehyde 3-phosphate  dehydrogenase68_177210 2.4 1.0
 35* 2212 45.4/5.026/23Precorrin-2 C20 methyltransferase48_179110.43 2.7
 26 6791 45.5/5.555/46Thiamine biosynthesis protein70_2399 0.290.4
 33 5630 55.4/5.130/30F420-methylenetetrahydrosarcinapterin  dehydrogenase54_434 0.110.6
 36* 2132 24.9/4.626/19Pyruvate synthase, γ subunit70_2325120.241.1
 27 2236 25.8/5.646/39Putative cell wall biosynthesis regulatory70_2654130.50.11
Information processing
 19  632 25.5/5.023/21RNA polymerase subunit E69_191614 Un (>1.8) 1.2
 18*  958 34.4/4.424/19Response regulator70_250015 Un (>2.7) 2.5
 31 3588 76.7/6.027/24Ribosomal protein L1p69_2093160.20.5
 29* 2444 87.0/7.158/46Translation elongation factor 1A66_1393 Un (<0.1) 1.7
 50 3901 15.6/5.214/14SSU ribosomal protein70_221517 2.0 4.1
 20  858124.6/4.484/66DnaK (HSP70) chaperone protein55_49618Un (<0.4)0.4
 1316598 44.8/4.435/27Peptidyl prolyl cis/trans isomerase70_2255  3.1 2.0
 39 1472 24.6/4.528/25Hypothetical protein63_1104 0.43 1.1
 46 3097 34.3/4.227/41Hypothetical protein51_294 0.080.6
 47 1134 24.5/4.221/41Hypothetical protein51_294 Un (<0.3) 

Characteristics of the proteins with differential spot intensities

The identified proteins fall into a number of functional categories, and a large number of gene clusters were identified (Table 1). Gene clusters included putative operons that were defined by a common gene orientation and a maximum of 50 bp between genes. Clusters 17 and 18 included genes with 90 and 75 bp separation respectively; however, they included functionally related genes.

Twenty spots, representing 11 proteins are involved in methanogenesis and energy generation. Proteins with increased spot intensities at 4°C included a trimethylamine methyltransferase (TMA-MT) and the 40 kDa subunit of F420H2 dehydrogenase (F420H2-DH), and proteins with reduced spot intensities included two trimethylamine corrinoid proteins (TMA-CPs), one dimethylamine corrinoid proteins (DMA-CP) and the β chain of ATP synthase. The α, β and γ subunits of methyl coenzyme M reductase (CH3-CoM-R) each produced a series of spots consistent with protein modification (Fig. 3A–C). The intensity of one spot for each of the α, β and γ subunits of CH3-CoM-R increased at 4°C, whereas other spots for the β and γ subunits had reduced intensities at 4°C (Fig. 3A–C). This indicates that the distribution of subunit isoforms (resulting from post-translational modification) is altered by growth temperature. The spots were reproducibly present (size, shape and intensity) in all gels and unlikely to be experimental artifacts (Ostrowski et al., 2004).

Figure 3.

Spot clusters indicative of protein modification.
A. CH3-CoM-R, α subunit.
B. CH3-CoM-R, β subunit.
C. CH3-CoM-R, γ subunit.
F. Hypothetical protein (51-294). Boxed spots more (box) or less (circle) intense at 4°C.

The TMA-MT is particularly interesting as it is likely to result from the expression of a single gene product originating from gene 61-917 and terminating at the end of gene 61-918. The incorporation of pyrrolysine at an amber codon has been reported recently for a monomethylamine methyltransferase (MMA-MT) from Methanosarcina barkeri (Hao et al., 2002). Spots 2 and 3 had seven and four peptide matches to gene 61-917, and three and two matches to gene 61-918 respectively. This is strong evidence that the full-length TMA-MT is being expressed in M. burtonii and indicates that the amber codon in gene 61-917 probably encodes pyrrolysine. The predicted size for the TMA-MT resulting from contiguous translation of genes 61-917/918 and the intervening sequence is 339 amino acids (49 kDa). Closer inspection of the ion chromatogram did not reveal a peptide containing pyrrolysine. Pyrrolysine in the MMA-MT from M. barkeri was also not detected by mass spectrometry (James et al., 2001; Hao et al., 2002). The higher molecular weights of spots 2 and 3 (62 and 63 kDa respectively) and their presence in protein clusters (Fig. 3E) are indicative that the two spots represent isoforms of the full-length product as a result of protein modification. Cold adaptation in M. burtonii appears to involve cold-regulated synthesis of TMA-MT, with regulation involving protein modification.

Thirteen of the proteins with differential spot intensities are likely to play a role primarily in biosynthesis, includ-ing coenzyme metabolism, amino acid metabolism, nucleotide metabolism and glycolysis/gluconeogenesis (Table 1). Eight proteins involved in biosynthesis had higher spot intensities at 4°C, and five had lower abundance. Spot 27, which had lower intensity at 4°C, had peptide matches to 70-2654. The best match (e−92) to this protein was a predicted pyridoxal phosphate-dependent enzyme from the bacterium Thermoanaerobacter tengcongensis, and it also formed a protein homology model (e−56) with Salmonella typhimurium ArnB aminotransferase (1mdoA.pdb). These matches suggest that 70-2654 may be involved in lipid or S-layer modification important for growth at 23°C.

To examine the correlation between spot intensity and enzyme activity, the specific activity of glutamate dehydrogenase (GDH) and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) was measured in M. burtonii cell extracts. The activity of GDH forward and reverse reactions was 1.8- to twofold higher, and GAPDH forward activity was 1.8-fold higher from cells grown at 4°C compared with cells grown at 23°C (Fig. 4A and B). This pattern of activity paralleled that observed for protein spot intensities (Fig. 4A and B). For both growth temperatures, the reductive (biosynthetic) activity of GDH was approximately fourfold higher than the oxidative (catabolic) activity (Fig. 4A). The enzyme was specific for NADP+, which is a common feature of GDH enzymes (EC with an anabolic function (Ertan, 1992). To confirm that the observed enzyme activity resulted from a single GDH enzyme, activity staining of 4°C and 23°C cell extracts was performed on native gels. The presence of a single band indicated that the measured activity was likely to result solely from GDH expressed from gene 69-2111 (data not shown). Overall, these experiments demonstrated a strong correlation between protein spot intensities and enzyme activities and provided evidence that two biosynthetic enzymes involved in nitrogen and carbon utilization are involved in cold adaptation.

Figure 4.

Specific activity of GDH and GAPDH. GDH (A) and GAPDH (B) specific activity for forward (hatched) and reverse (open) reactions, and spot intensity (solid) for protein extracts from cells grown at 4°C and 23°C.

Adenosylhomocysteinase (AdoHcyase) converts S-adenosylhomocysteine (SAH) to adenosine and homocysteine. SAH is a strong product inhibitor of a large variety of S-adenosylmethionine-dependent methyltransferases, which produce it as an end-product. AdoHcyase is the only enzyme that can remove the inhibitory presence of SAH and is therefore a key enzyme in the regulation of methylation-dependent reactions involved in methanogenesis and the biosynthesis of proteins and nucleic acids (Ueland, 1982). Spot 5 is unique to growth at 4°C at a level at least 6.7-fold above the detection limit, demonstrating that there is a high level of regulation governing the activity of this enzyme and indicating that reactions involving methyl transfer are elevated at 4°C.

Seven proteins involved in information processing were regulated by growth at low temperature (Table 1). The intensity of spot 19 (632 p.p.m.) for RNA polymerase subunit E was close to the detection limit (350 p.p.m.); however, it was unique to growth at 4°C. A response regulator consisting of a CheY-like receiver domain and a winged-helix DNA-binding domain was also unique to growth at 4°C, at a level at least 2.7-fold above the detection limit. This protein had its best match (e−33) to COG0745 in M. barkeri, with the top 50 matches to proteins from mesophilic methanogens and a broad range of bacteria. The gene is orientated upstream, and in the same orientation, as a gene for a putative histidine kinase. Its top blast hit (e−42) was to Geobacter metallireducens, with the top 50 matches to sequences only present in bacteria. The arrangement of these two genes in M. burtonii is consistent with cognate response regulator and sensor transmitter proteins of a two-component regulatory system.

Ribosomal protein L1p and translation elongation factor 1A had lower abundance at 4°C, whereas SSU ribosomal protein had higher levels. Peptidyl-prolyl cis/trans isomerase (PPIase) was one of the most abundant proteins (16 598 p.p.m.), with higher spot intensity (3.1-fold) at 4°C. A DnaK (Hsp70) chaperone protein was not detected at 4°C and had at least 2.5-fold higher levels during growth at 23°C.

Two proteins with no known function were present at reduced levels in cells growing at 4°C. Genes 63-1104 and 51-294 encode conserved hypothetical proteins with best hits in M. barkeri and Methanosarcina mazei. psi-blast and hmmer were used to attempt to identify remote homologues. psi-blast with gene 51-294 showed that the protein was related to serine proteases. Neither gene was found in an operon or cluster that might indicate function in any of the other genomes. An N-terminal hydrophobic region was predicted for 51-294. The abundance of this protein appeared to be highly regulated as spot 46 was 12.5-fold lower at 4°C, and spot 47 was unique to growth at 23°C (Table 1). The proteins in spots 46 and 47 were approximately half the molecular weight of the full-length protein (Table 1, Fig. 3F). The peptides observed in spot 46 were located towards the C-terminus, and the peptides from spot 47 were located towards the N-terminus, indicating that the spots may have been derived from cleavage of the full-length protein.

Transcript levels of genes encoding proteins with differential spot intensities

Semi-quantitative reverse transcription polymerase chain reaction (RT-PCR) was used to determine the cellular levels of the transcripts from the 33 genes encoding proteins with differential spot intensities (Table 1). Protein and mRNA levels were compared by plotting the ratio of protein spot intensity at 4°C versus 23°C against mRNA levels for the same gene at 4°C versus 23°C (Fig. 5). Many of the genes with high protein levels at 4°C had high mRNA levels at 4°C (top right quadrant, Fig. 5), and approximately half the genes with reduced protein levels at 4°C also had reduced mRNA levels (lower left quadrant, Fig. 5). The measured abundance of mRNA and protein is a product not only of gene expression, but also of the stability, turnover and modification of the gene products.

Figure 5.

Scatterplot of the ratio of protein and mRNA present in cells grown at 4°C and 23°C. Genes represented by more than one protein spot are not included. Gene numbers, but not contig numbers, are shown.

Particular genes had higher levels of control at the mRNA or protein level. The abundance of adenosylhomocysteinase (66-1381) had > 6.7-fold higher levels of protein compared with 1.5-fold higher levels of mRNA at 4°C, whereas the putative cell wall regulatory protein (gene 70-2654) had twofold lower levels of protein with 9.1-fold lower levels of mRNA at 4°C (Fig. 5).

The abundance of the mRNA for the RNA polymerase subunit E gene had only a small increase at 4°C. In contrast, there was a 2.5-fold increase in the transcript level for the response regulator. It will be interesting to determine whether expression of the response regulator involves autoregulation.

The mRNA abundance for GDH and GAPDH genes was compared with the protein abundance and enzyme activities. At 4°C, GDH had 5.9-, 2.0- and 2.1-fold higher levels of protein, enzyme activity and mRNA respectively (Table 1, Figs 4 and 5). The overall effect of cold growth on GAPDH was less than on GDH, with 2.4- and 1.8-fold higher levels of protein and enzyme activity, respectively, and no change in mRNA levels. Cold regulation of GDH activity therefore appeared to involve protein and mRNA levels, whereas control of GAPDH activity appeared to be exclusively at the protein level.

Further insight into the thermal regulation of proteins identified from multiple spots (Fig. 3) was obtained by examining the mRNA levels of their respective genes. The mRNA levels were 1.7-fold lower for the hypothetical protein (gene 51-294) during growth at 4°C, which was consistent with the decreased intensities of spots 46 and 47. In contrast, the mRNA level for DMA-CP (gene 69-1921) was 2.4-fold higher at 4°C, while the protein level was 2.4-fold lower (Table 1). These data indicate a complexity of thermal regulation that requires further experimentation to unravel.

Putative operon structure, gene and protein regulation

Combining the bioinformatics with proteomics and mRNA analysis gives evidence of operon structure and multiple levels of gene regulation. The CH3-CoM-R α, β and γ subunits (genes 65-1325, 65-1321 and gene 65-1324 respectively) were identified as part of a putative five gene operon because of their arrangement and spacing in the genome (Table 1). The increase in mRNA abundance for these genes at 4°C was 3.1-, 3.5- and 3.4-fold higher, respectively, which is a good indication that they are translated from a single mRNA species. The increase in mRNA at 4°C also indicates that the activity of CH3-CoM-R is likely to be higher in the cell during growth at 4°C. On the two-dimensional gels, each subunit is part of a row or cluster of spots, some of which change as a function of growth temperature (Fig. 3A–C). The β and γ subunits have spots with both increased and decreased intensities at 4°C, while the α subunit has a spot that increases at 4°C (Fig. 3A–C). This indicates that, apart from control at the transcription level, the post-translational modifica-tions of the subunits are also regulated in a growth temperature-dependent manner.

The TMA-CP and TMA-MT genes also appear to form an operon (Table 1). The mRNA levels for TMA-CP (gene 61-919) and TMA-MT (gene 61-917/918) were 1.6- and 1.1-fold higher at 4°C (Table 1). The spot intensities decreased for TMA-CP and increased for TMA-MT, and for both enzymes involved modification (Table 1, Fig. 3D and E). These examples illustrate that thermal regulation in M. burtonii involves co-ordinated gene expression at the level of gene clusters and operons, through to the modification of individual proteins.


The application of proteomics using two-dimensional and µLC/MS-MS has proved to be very successful for identifying proteins involved in cold adaptation in M. burtonii. Forty-three of the 54 protein spots (80%) with differential spot intensities were identified. The high success rate was facilitated by the availability of high-coverage (≈ 12×) draft genome sequence, with only 10 matches being obtained by cross-species methods. The proteomics provided the platform for examining gene regulation at the mRNA level and for enzyme activity studies of the specific candidates, GDH and GAPDH. While the study has in principle illustrated the means of examining global gene expression in M. burtonii, it has specifically provided the first survey of gene expression controlled by cold growth in archaea and enabled a view of cold adaptation biology to be developed.

Transcriptional regulation

The basal transcription machinery of archaea consists of 12 subunits, which assemble in a complex similar to eukaryotic RNA polymerase II (Bell and Jackson, 2001). Subunits E and F form a heterodimer (Todone et al., 2001), analagous to RPB4/RPB7 and A14/A43 heterodimers in Saccharomyces cerevisiae (Meka et al., 2003). RPB4/RPB7 associate loosely with the 10-subunit core of the S. cerevisiae RNAP II. In Methanobacterium thermoautotrophicum, subunit E has been purified as part of the RNAP complex (Darcy et al., 1999). In reconstitution experiments with recombinant E/F proteins of Methanocaldococcus jannaschii, heterodimers were found to incorporate into the RNAP; however, they had no effect in transcription assays (Werner and Weinzierl, 2002). In a separate study, a recombinant archaeal E/F heterodimer from M. jannaschii was shown to bind RNA, probably mediated by the S1 nucleic acid-binding motif in subunit E (Meka et al., 2003). From these studies, it appears unclear what the nature of the association is between the E/F heterodimer and the core RNAP and how this may be affected by the physiology of the cell. Our proteomics results demonstrate that cellular levels of subunit E are higher during growth at low temperature. This would be consistent with subunit E fulfilling a specific role in regulating the transcription of genes involved in low-temperature growth or in facilitating transcription at low temperature in general. This could involve subunit E interacting with the nascent RNA during transcription and/or directing promoter-specific transcription initiation (Meka et al., 2003).

While the basal transcription machinery in archaea resembles that in eukaryotes, bacterial-like regulatory proteins have been shown to be involved in controlling gene expression (Bell and Jackson, 2001). This includes the RNA helicase gene from M. burtonii, which has regulatory mechanisms resembling those found in cold shock-induced RNA helicase genes from Escherichia coli and Anabaena and csp genes from E. coli (Lim et al., 2000). In the present study, the identification of a histidine kinase gene immediately downstream from the regulator raises the possibility of the two genes forming a temperature-responsive two-component regulatory system (2CRS). In bacteria, 2CRSs have been shown to have specific roles in the cold regulation of fatty acid desaturase activity in Bacillus subtilis (Aguilar et al., 2001), expression of virulence factors in Pseudomonas syringae (Smirnova et al., 2002) and genes involved in osmotic stress and cold stress in Synechocystis (Mikami et al., 2002). The increased abundance of the response regulator in the present study reinforces the finding that cold adaptation involves transcriptional regulation, and that it may involve mechanisms similar to those found in bacteria (Lim et al., 2000). Archaeal 2CRSs and, in particular, the response regulators contain structural features distinct from bacteria (Galperin et al., 2001). Little experimental work has been reported for archaeal 2CRSs, and this cold-regulated system in M. burtonii represents a good functional model.

Protein folding

Proteins involved in protein folding are often upregulated during heat shock and other stressful conditions, and serve to ensure that new proteins are folded correctly and denatured proteins are refolded. In bacteria, DnaK binds the nascent peptide emerging from the ribosome and either delivers it in an unfolded form to the chaperonin complex for proper folding or else releases it to continue folding spontaneously. Heat shock has been shown to induce the expression of DnaK in a cold-adapted bacterium (Michel et al., 1996) and Hsp70 (DnaK homologue) in the Antarctic yeast, Candida psychrophila (Deegenaars and Watson, 1997). Hsp70 has also been shown to be induced in BALB/c murine skin after both heat or cold shock (Huang et al., 2003). The increased levels of DnaK in M. burtonii during growth at 23°C are consistent with the view that growth of cold-adapted organisms at Topt (and not just heat shock) can be stressful (Feller and Gerday, 2003). Methanogenium frigidum was isolated from the same Antarctic Lake as M. burtonii, has a Topt of 15°C and is restricted to growth below 18°C (Franzmann et al., 1997). As DnaK is predicted from the draft coverage of the M. frigidum genome sequence (data not shown), it will be valuable to determine whether abundance of the protein correlates with growth temperature.

PPIases increase the rate at which proteins can fold by catalysing the otherwise rate-limiting cis/trans isomerization of proline imide bonds in polypeptides. Some PPIases also have the capacity to refold unfolded proteins (described by Ideno et al., 2001). The human PPIase, FKBP, is induced by heat shock (Sanchez, 1990). In contrast, TcFKBP18 from the hyperthermophilic archaeon, Thermococcus sp. KS-1, is induced by cold shock (Ideno et al., 2001). The increased abundance of the PPIase in M. burtonii at 4°C indicates that it is preferentially required for growth at low temperature. This prominence at low temperature may relate to an increased capacity for spontaneous isomerization at higher temperatures (Ideno et al., 2001).

In addition to thermal regulation of the PPIase (Ideno et al., 2001), the α and β subunit composition of the chaperonin complex has been shown to change with growth temperature in Thermococcus (Yoshida et al., 2001) and Sulfolobus (Kagawa et al., 2003). It was also shown recently that chaperonins from E. coli may be critical determinants for growth at low temperature (Ferrer et al., 2003). Clearly, protein folding is important for adaptation to both upper and lower growth temperature limits. Our data for DnaK and PPIase support this view by indicating that protein folding is a thermally sensitive process in M. burtonii and may contribute to its adaptation to the cold and capacity to grow at mesophilic temperatures.

Methanogenesis, ATP production and biosynthesis

Methanococcoides burtonii is an obligately methylotrophic methanogen able to use methylamines and methanol, but not formate, H2:CO2 or acetate for growth (Franzmann et al., 1992). In growth studies with M. burtonii and other methylotrophic methanogens, the production of methane, ATP, CO2 and biomass has been shown to occur at different rates and times throughout the growth phase (Summons et al., 1998; Maitra et al., 2001). Growth with TMA therefore proceeds via a series of disproportionation reactions leading to energy generation and biosynthesis, with obligatory methylotrophs needing to regulate a fine balance of genes involved in methanogenesis (Deppenmeier, 2002a). Our study revealed that a number of genes involved in methanogenesis are thermally regulated, and regulation involves the expression of genes in operons (e.g. CH3-CoM-R), protein modification (Fig. 3) and the synthesis of pyrrolysine containing TMA-MT (see below).

At 4°C, higher levels of protein and/or mRNA were observed for genes involved in methanogenesis leading to the generation of a proton motive force (PMF). These included  TMA-MT,  TMA-CP,  DMA-CP,  CH3-CoM-MT, CH3-CoM-R and F420H2-DH (Table 1). The F420H2-DH is a membrane-bound proton pump, which generates a proton gradient that drives most cellular processes, including ATP synthesis (Deppenmeier, 2002b). In methylotrophic methanogens, ATP can also be produced by a sodium motive force (SMF) (Deppenmeier, 2002a). At low temperature, a PMF has been shown to be easier to maintain than a SMF (Konings et al., 2002). The increased levels of gene products involved in methanogenesis indicate that a PMF is preferred in M. burtonii during low-temperature growth. The only ATP synthase subunit that was detected (spot 21) had lower protein levels at 4°C and unchanged mRNA levels. If the change in spot 21 is indicative of ATP synthase activity, this may indicate that ATP generation is reduced at low temperature. In this regard, it is noteworthy that CoM methylation can occur independently of ATP using free cobalamin rather than corrinoid proteins (Wassenaar et al., 1998; Sauer and Thauer, 1999).

The reduced F420 (F420H2) required for F420H2-DH is produced in CO2 oxidation. At 4°C, the F420-dependent methylenetetrahydrosarcinapterin dehydrogenase (54-434) is downregulated. This results in the F420H2 being directed to the F420H2-DH to support the generation of the PMF. A consequence of this may also be a reduced efflux of CO2 and more efficient utilization of carbon.

Pyruvate synthase converts acetyl-CoA to pyruvate and is dependent on thiamine pyrophosphate. Pyruvate synthase γ subunit and thiamine biosynthesis protein are less abundant at 4°C, indicating that acetyl-CoA will be directed towards the TCA cycle. A consequence of this would be the increased availability of oxoglutarate for anabolic functions of GDH. This is consistent with the increased levels of GDH at 4°C, in addition to pyridoxine biosynthesis protein and riboflavin biosynthesis protein, which are involved in amino acid metabolism. To examine further the bioconversion of acetyl-CoA in carbon metabolism at 4°C, we examined the expression of the carbon monoxide dehydrogenase D subunit gene (42-46), which is responsible for the conversion of CO2 to acetyl-CoA. mRNA levels were 2.1-fold higher in cells growing at 4°C (data not shown).

In combination, these results indicate that TMA methanogenesis leading to the generation of a PMF and pathways from acetyl-CoA leading to amino acid metabolism are favoured during growth at 4°C. This indicates that there is an effective regulation of fundamental processes of carbon and nitrogen metabolism, consistent with the evolution of the organism for growth in the cold. This is particularly well illustrated by the increased levels of GDH and GAPDH at 4°C, which are key enzymes in nitrogen and carbon metabolism.

TMA-MT: a pyrrolysine-containing enzyme

Pyrrolysine is a lysine amino acid with its epsilon nitrogen in amide linkage with (4R,5R)-4-substituted pyrroline-5-carboxylate that was identified in a monomethylamine methyltransferase (MMA-MT) from M. barkeri (Hao et al., 2002). Although its presence has been verified experimentally in the M. barkeri MMA-MT, its presence in other Methanosarcina species has only been invoked through bioinformatic searches for the presence of in frame amber codons (Deppenmeier et al., 2002; Galagan et al., 2002). This has led to the suggestion that it might be widespread in Methanosarcinacea (Ibba and Soll, 2002). The contiguous translation of genes 61-917/918 confirms that the amber codon in this putative TMA-MT is translated in M. burtonii and therefore likely to encode pyrrolysine. This is the first indication that a Methanococcoides species synthesizes pyrrolysine in a TMA-MT, and that synthesis of the protein is thermally regulated.

Pyrrolysine has been reported to be incorporated into the MMA-MT through a translational process involving a UAG codon in the MMA-MT gene, a specific tRNA (pylT) with a CUA anticodon and cognate tRNA synthetase (pylS) (Srinivasan et al., 2002). Recently, however, it was reported that the canonical lysyl-tRNA synthetases from M. barkeri, LysRS1 and LysRS2, are capable of charging the tRNA from pylT (Polycarpo et al., 2003). In M. burtonii, pylT is located in the genome sequence immediately upstream of a gene cluster encoding putative pylS, pylB and pylC (contig 60-797/798/799) homologues of M. barkeri. In view of our findings and the controversy surrounding the mechanism of pyrrolysine incorporation in the M. barkeri MMA-MT, it will be valuable to assess the thermal regulation of the M. burtonii genes and examine the functional role of pyrrolysine in the M. burtonii TMA-MT.

Experimental procedures

Organisms and culture conditions

Methanococcoides burtonii was grown in liquid-modified methanogen growth media (MFM) under anaerobic conditions in a gas phase of 80:20 N2:CO2 (Franzmann et al., 1992). Culture inocula were taken from actively growing batches of cells at their respective temperatures, and cells were passaged at least once before harvesting for biomass. Cultures grew with a doubling time of ≈ 80 h at 4°C and 20 h at 23°C. For all analytical procedures, 4°C and 23°C grown cultures were harvested at late logarithmic phase (absorbance 0.25 at 600 nm) by centrifugation at 2800 g for 25 min at 4°C.

Two-dimensional and image analysis

Procedures for two-dimensional and image analysis were performed as described previously (Fegatella et al., 1999; Ostrowski et al., 2004) with minor modifications. Cell pellets from 50 ml cultures were resuspended in 1.0 ml of TES buffer (10 mM Tris-HCl, pH 8.8, 1 mM EDTA, 100 mM NaCl) with 0.5 ml of protease inhibitor cocktail (Sigma) and disrupted on ice by sonication with a Branson sonifier for four cycles of 30 s on a 30% duty cycle and a power setting of 3. Cell debris was removed by centrifugation at 10 000 g for 25 min at 4°C, and the supernatant was transferred to a 1.0 ml dialysis unit (Sigma). Before electrophoresis, protein samples were dialysed against 50 mM NaH2PO4, pH 7.0 for 16 h at 4°C. An aliquot containing 50 µg of protein was added to rehydration buffer containing 9 M urea, 0.1 M dithiothreitol (DTT), 40 mM Tris-HCl, pH 8.8, 10 µl of IPG buffer and 4% (w/v) CHAPS. Nuclease buffer (10 µl) was added, and the mixture was incubated at room temperature for 20 min. The sample was centrifuged at 10 000 g for 20 min, and the supernatant was loaded on to an 18 cm Immobiline DryStrip pH 4–7 (Amersham) and rehydrated at room temperature for 18 h. Isoelectric focusing was performed using a flatbed Multiphor II (Amersham) at 15°C programmed for 2 h at 100 V, followed by 0.5 h at 500 V, 1500 V and 2500 V and 18 h at 3500 V. Strips were equilibrated, and SDS-PAGE was performed in 11.5% and 15% acrylamide gels using the Protean II system (Bio-Rad) at 50 V for 1 h, followed by 64 mA for 5 h. Gels were fixed individually in 0.2 l of fixing solution (50% v/v methanol, 10% v/v acetic acid) for a minimum of 1 h and stained using a sensitive ammoniacal silver method. Silver-stained gels were imaged using a Bio-Rad GS700 densitometer. For comparative image analysis, statistical data were acquired and analysed using z3 software (Compugen). Statistical analyses (Student's t-test, 95% confidence interval) were performed on three gels from each growth condition to determine spots showing reproducible changes of twofold or more.

Mass spectrometry identification of proteins

Procedures for two-dimensional and image analysis were performed as described previously (Ostrowski et al., 2004) with minor modifications. Stained gels were washed twice in 50% (v/v) acetonitrile and once in deionized water before spot excision. Before digestion, spots were reduced with 10 mM DTT at 56°C for 1 h, alkylated in 55 mM iodoacetamide for 45 min, washed with 0.2 ml of 100 mM NH4HCO3 for 10 min, rehydrated with 50 mM NH4HCO3, dehydrated in acetonitrile, dried in vacuo and rehydrated in buffer containing 10.5 ng µl−1 trypsin (Promega). After digestion, peptides were extracted, and samples were dried in vacuo at 4°C. Digests were separated by nano-LC using an Ultimate/Famos/Switchos system (LC Packings). Samples (5 µl) were loaded on to a C18 precolumn (500 µm × 2 mm; Micron) with H2O:CH3CN (98:2, 0.1% formic acid, buffer A) at 25 µl min−1. After a 4 min wash, the flow was switched into line with a C18 RP analytical column (PEPMAP, 75 µm × 15 cm) and eluted using buffer A to H2O:CH3CN (40:60, 0.1% formic acid) at 200 nl min−1 over 30 min. The nano electrospray needle was positioned ≈ 1 cm from the orifice of an API QStar Pulsar i tandem MS (ABI). The QStar was operated in information-dependent acquisition mode. A time-of-flight mass spectrometry (TOF MS) survey scan was acquired (m/z 350–1700, 0.5 s), and the two largest precursors (counts > 10) were selected sequentially by Q1 for tandem MS analysis (m/z 50–2000, 2.5 s). A processing script generated data suitable for submission to the database search programs. CID spectra were analysed using sequest software as described previously (Ostrowski et al., 2004) with the following parameters: peptide mass tolerance of 1.5 Da, strict trypsin enzyme digestion with the modifications +16 methionine and +57 cysteine. Searches were performed on a local database of M. burtonii translated sequences obtained from http://www.jgi.doe.gov/JGI_microbial/html/. All sequest scores were verified manually, and proteins were considered to be identified that matched the following criteria: fragments were tryptic, the Xcorr score was > 2 for [M + 2H]2+ and a distinct ladder sequence was visible. The CID spectra were also analysed using the Mascot MS/MS ion search (Matrix Science) with the following parameters: trypsin digestion allowing up to one missed cleavage, oxidation of methionine, peptide tolerance of 1.0 Da and MS/MS tolerance of 0.8 Da. Searches were performed on the NCBI nr database.

Enzyme activity assays

GDH and GAPDH activities were determined by spectrophotometric assays at room temperature using cell extracts (Ertan, 1992; Brunner et al., 2001).

Semi-quantitative RT-PCR

Total RNA was extracted from cell pellets with a Promega Total SV RNA isolation kit using the manufacturer's instructions and stored in 10 µl aliquots at −80°C. The concentration of RNA was determined using a Unicam UV2-100 UV/visible spectrophotometer version 3.50. Samples were diluted 1:20, and the absorbance was measured at 260 nm. RNA integrity was analysed by electrophoresis on formaldehyde–agarose gels for 4 h at room temperature. cDNA was synthesized from 2 µg of RNA using 100 ng of random hexamer primers (Promega), Superscript II and 40 U of RNaseOUT (Invitrogen) in a 20 µl volume. Reactions were processed in a Hybaid thermal cycler at 25°C for 10 min, 42°C for 50 min and 70°C for 15 min, and the cDNA was stored at −20°C. Gene-specific primer sets were designed for each  gene using the software primer3 (http://www-genome.wi.mit.edu/genome_software/other/primer3.html). PCR amplification was performed in a Hybaid thermal cycler with 0.4 µl of cDNA, 10 mM dNTPs, 0.1 µM or 0.2 µM target-specific primers (see Supplementary material, Table S1), 0.1 µM or 0.2 µM 16S rRNA primers and 0.2 U of Taq DNA polymerase (Sigma) in a total volume of 10 µl. Denaturation was performed at 96°C for 2 min, followed by 24 cycles of 95°C for 20 s, 55–58°C for 45 s, 68–72°C for 90–120 s. The multiplex PCR conditions were optimized to ensure that amplification remained exponential and that the two sets of primers (one set for the target gene and one set for the 16S rRNA) used in each reaction did not compete with each other. The level of 16S rRNA served as a control to allow normalization and comparison of RNA levels between genes. The cold-regulated RNA helicase gene, deaD (Lim et al., 2000), was also used as a control. Optimal annealing temperatures, extension temperatures and duration and ratios of gene-specific primers to 16S rRNA primers were defined (see Supplementary material, Table S2). Each set of reactions included a control to confirm the absence of genomic DNA and contained RNA instead of DNA with Superscript II omitted. Amplification products were electrophoresed on 2.5% agarose gels, stained with SYBR green I, visualized at 473 nm on a FLA-5000 (FujiFilm) and quantified using imagegauge 4.0 (FujiFilm). The ratio between target RNA and 16S rRNA was calculated to normalize for initial variations in sample concentration and as a control for reaction efficiency. Statistical analyses (two-sample, equal variance t-test, 95% confidence interval) were performed on three RNA replicates for each growth condition.

Computational methods

Gene models were generated from the draft genome assembly by the ORNL Computational Biology Division using the programs generation, glimmer and critica. To visualize gene clusters, contigs were converted to GenBank sequence format, annotated and viewed using artemis. The bioperl modules were used for sequence manipulation and analysis. Protein sequences were annotated using blast. psi-blast and hmmer were used in cases where a sequence had no significant blast hit. Protein molecular weights and isoelectric points were predicted using emboss. Transmembrane helices were predicted by taking the consensus results from several TM helix prediction servers at the ExPASy server. Homology modelling of protein structures was performed using the swiss-model automated server.


Thanks to Frank Larimer, Miriam Land and Paul Richardson for ensuring availability and up-to-date annotation of M. burtonii sequence data, and Tassia Kolesnikow for critical appraisal of the manuscript. This work was supported by the Australian Research Council.

Supplementary material

The following material is available from http://www.blackwellpublishing.com/products/journals/suppmat/mmi/mmi4130/mmi4130sm.htm

Table S1. Primers used in PCR amplification.

Table S2. Specific PCR conditions for cDNA amplification.