Figures
Abstract
The SAR11 Alphaproteobacteria are the most abundant heterotrophs in the oceans and are believed to play a major role in mineralizing marine dissolved organic carbon. Their genomes are among the smallest known for free-living heterotrophic cells, raising questions about how they successfully utilize complex organic matter with a limited metabolic repertoire. Here we show that conserved genes in SAR11 subgroup Ia (Candidatus Pelagibacter ubique) genomes encode pathways for the oxidation of a variety of one-carbon compounds and methyl functional groups from methylated compounds. These pathways were predicted to produce energy by tetrahydrofolate (THF)-mediated oxidation, but not to support the net assimilation of biomass from C1 compounds. Measurements of cellular ATP content and the oxidation of 14C-labeled compounds to 14CO2 indicated that methanol, formaldehyde, methylamine, and methyl groups from glycine betaine (GBT), trimethylamine (TMA), trimethylamine N-oxide (TMAO), and dimethylsulfoniopropionate (DMSP) were oxidized by axenic cultures of the SAR11 strain Ca. P. ubique HTCC1062. Analyses of metagenomic data showed that genes for C1 metabolism occur at a high frequency in natural SAR11 populations. In short term incubations, natural communities of Sargasso Sea microbial plankton expressed a potential for the oxidation of 14C-labeled formate, formaldehyde, methanol and TMAO that was similar to cultured SAR11 cells and, like cultured SAR11 cells, incorporated a much larger percentage of pyruvate and glucose (27–35%) than of C1 compounds (2–6%) into biomass. Collectively, these genomic, cellular and environmental data show a surprising capacity for demethylation and C1 oxidation in SAR11 cultures and in natural microbial communities dominated by SAR11, and support the conclusion that C1 oxidation might be a significant conduit by which dissolved organic carbon is recycled to CO2 in the upper ocean.
Citation: Sun J, Steindler L, Thrash JC, Halsey KH, Smith DP, Carter AE, et al. (2011) One Carbon Metabolism in SAR11 Pelagic Marine Bacteria. PLoS ONE 6(8): e23973. https://doi.org/10.1371/journal.pone.0023973
Editor: Jack Anthony Gilbert, Argonne National Laboratory, United States of America
Received: July 19, 2011; Accepted: July 28, 2011; Published: August 23, 2011
Copyright: © 2011 Sun et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This research was funded by a grant from the Marine Microbiology Initiative of the Gordon and Betty Moore Foundation to SJG, National Science Foundation Microbial Observatory grant MCB-0237728 to SJG, and is based upon work supported by the National Science Foundation award no. DBI-1003269 to JCT. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
C1 metabolism takes place through a network of interrelated biochemical reactions that involves the transfer of one-carbon units from one compound to another. C1 units can be donated in the form of methyl (-CH3), methylene (-CH2-), methenyl (-CH = ), formyl (-CHO) and formimino (-CH = NH) groups [1], [2]. A few specialized bacteria oxidize methyl groups and C1 compounds, such as methanol, formaldehyde, formate and methylamine, to derive energy and cellular carbon. The most well known of these organisms are methylotrophs, which assimilate C1 carbon into biomass via the ribulose monophosphate (RuMP) or serine cycle pathways [3]–[7]. Less well known are organisms that have C1 oxidation pathways for energy production, but lack pathways for the net synthesis of biomass from C1 precursors [8].
Marine dissolved organic carbon (DOC) includes a diverse array of C1 and methylated compounds that are potential substrates for C1 oxidation. The most common methylated compounds in marine environments are osmolytes such as GBT, TMAO, and DMSP [9]–[11]. Methanol is a major component of oxygenated volatile organic chemicals in the oceans and atmosphere [12], [13]. Air measurements over the Pacific Ocean indicate that sea surface methanol concentrations are about 100 nM and that central ocean regions are net sinks for methanol deposited from the atmosphere [12]–[14]. Formaldehyde is ubiquitous in seawater. Likely sources of seawater formaldehyde are atmospheric deposition from industrial emissions and the photo-oxidation of atmospheric hydrocarbons [15], [16], and the photo-oxidation of dissolved organic carbon in the ocean surface [17]. The metabolism of methylated compounds in mammals also produces formaldehyde [18]. Formaldehyde is a key reactive intermediate in bacterial metabolism of C1 growth substrates like methane or methanol [19]-[21], and it is also a central intermediate of GBT methyl group oxidation [22]. Due to its nonspecific reactivity with proteins and DNA, formaldehyde is toxic to cells, and thus many studies have examined mechanisms by which organisms can remove this potentially lethal compound [23], [24].
Marine bacteria of the SAR11 clade are the most abundant aerobic, free-living, heterotrophic bacteria in ocean surface waters [25], [26]. SAR11 was first discovered in the Sargasso Sea in 1990 [27] and is now considered to be one of the most successful organisms on the planet. Candidatus Pelagibacter ubique strain HTCC1062, the first cultured SAR11 strain, has one of the most compact genomes known for a free-living organism (1,308,759 base pairs), and has dispensed with many functions that are common in other free-living bacteria, apparently in response to selective pressure for small genome size [28]. The SAR11 clade is divided into subclades that have distinct temporal and spatial distributions in the environment that are believed to represent ecotypes or species [29]. Most strains now being studied in laboratories belong to the Group Ia subclade, which is common in the ocean euphotic zone [29].
In this study, we observed a suite of genes for demethylation and C1 oxidation in three SAR11 Ia genomes (Ca. P. ubique strains HTCC1062, HTCC1002, and HTCC7211) for which no role in SAR11 had yet been identified. Genomic and metagenomic data were used to explore the potential for C1 metabolism in the three SAR11 isolates and natural SAR11 populations, and experiments with pure cultures of cells were used to confirm predictions. Together, our data demonstrate that SAR11 cells are capable of oxidizing a range of C1 compounds and methyl groups from methylated compounds to produce energy.
Results and Discussion
Comparative Genome Analyses and Proposed Metabolic Pathways
Genes in the HTCC1062 genome associated with C1 oxidation are shown in Figure 1. The proposed metabolic pathways for these genes are discussed in detail below (Fig. 2), although for clarity we include only the HTCC1062 gene identifiers (e.g, “SAR11_”) in the text. Table S1 lists C1 metabolism genes by gene identifier, COG number, organism, and function to reduce confusion caused by the common practice of assigning different gene names to homologous genes that have related functions. To evaluate the conservation and diversity of C1 oxidation pathways in SAR11 we examined the distribution of genes for C1 metabolism among three SAR11 genomes of the Group Ia subclade, and these genes were found in all three SAR11 Ia genomes (Table 1). A survey of the global ocean survey (GOS) metagenomic data for SAR11 genes involved in C1 metabolism also supported the conclusion that these genes occur frequently in SAR11 genomes. Averaged across ocean sampling locations worldwide, the ratio of SAR11 C1 genes, relative to SAR11 recA, ranged from 0.2 to 2.1 (Fig. S1 and Table S2).
(A) formate dehydrogenase; (B) methanol metabolism; (C) methylamine oxidation; (D) glycine betaine oxidation; (E) aminomethyltransferases (Asterisk). fdhF, formate dehydrogenase, alpha subunit; fdsB, NAD-dependent formate dehydrogenase, beta subunit; fdhD, formate dehydrogenase, chain D; mobA, molybdopterin-guanine dinucleotide biosynthesis protein A; moeA, molybdopterin biosynthesis protein; fhs, formate-THF ligase; SAR11_1286, putative glutamine amidotransferase; Fe-ADH, iron-containing alcohol dehydrogenase; ssdH, aldehyde dehydrogenase family; SAR11_1289, short chain dehydrogenase; soxB, sarcosine oxidase; soxD & soxD2, sarcosine oxidase delta chain; soxA & soxA2, sarcosine oxidase alpha chain; soxG & soxG2, sarcosine oxidase gamma subunit; soxB2, sarcosine oxidase beta subunit; glxBCD, glutamate synthase; glnT, Glutamine synthetase III (putative gamma-glutamylmethylamide synthetase); bhmT, betaine-homocysteine methyltransferase; sardh, sarcosine dehydrogenase; dmgdh, dimethylglycine dehydrogenase; gcvT, glycine system cleavage T-protein; gcvH, glycine cleavage H-protein; gcvP, glycine cleavage P-protein; dmdA, dimethylsulfoniopropionate-dependent demethylase; mhpC, hydrolase, alpha/beta hydrolase fold family; fadD, CoA activator for DMSP beta oxidation; mmgC, acyl-CoA dehydrogenase for DMSP beta oxidation; metF, methylene-THF reductase; opuAB, glycine betaine transport system permease protein; opuAA, glycine betaine transport ATP-binding protein; opuAC, substrate-binding region of ABC-type glycine betaine transport system; SAR11_1265 & SAR11_1303, gcvT-like aminomethyltransferase protein; SAR11_1304, monomeric sarcosine oxidase. Colors correspond to pathways in Figure 2.
(A) THF-linked oxidation pathway; (B) methanol oxidation pathway; (C) glycine betaine demethylation and oxidation; (D) methylamine oxidation pathways; (E) TMAO degradation pathway; (F) glycine cleavage pathway; (G) DMSP demethylation. Note: ? - unidentified metabolic processes/enzymes; * - spontaneous reaction; † - two paralogous operons.
Central to the process of C1 and methylated compound oxidation in SAR11 Ia is the tetrahydrofolate (THF)-linked oxidation pathway, which oxidizes C1 units to CO2, yielding energy in the form of reduced nucleotides and ATP (Fig. 2). The gene products of metF (SAR11_1264), folD (SAR11_0307) and fhs (SAR11_1285) are predicted to catalyze early steps in the methyl-THF linked oxidation pathway (Fig. 2A). The genes fdhF (SAR11_0679), fdsB (SAR11_0680) and fdhD (SAR11_0681; Fig. 1A) are predicted to encode subunits of formate dehydrogenase (FDH), which catalyzes the final step in the pathway, the oxidation of formate to CO2 [30], [31] (Fig. 2A). Gene mobA (SAR11_0684) and moeA (SAR11_0685) are predicted to encode proteins for the synthesis of a molybdenum cofactor, which is required for the activity of most bacterial molybdoenzymes, such as FDH [32]-[34].
Putative genes that encode C1 oxidation activities are found in many bacterial phyla, archaea and eukaryotes. We used the phylogenomic pipeline HAL [35] to study the distribution of C1 oxidation genes in the class Alphaproteobacteria and found evidence for many of these genes throughout the genomes investigated (Fig. S2). For example, homologs of fdhF and fdhD were observed in 77 and 58 of 127 genomes, respectively. However, outside of the methylotrophs, which can grow using C1 compounds as a sole carbon and energy source, C1 oxidation has received relatively little attention. FDH genes have been reported in Rhizobium japonicum and Agrobacterium tumefaciens [36]-[38]. Interestingly, several non-methylotrophs, including A. tumefaciens, are capable of utilizing methylamine as a nitrogen source, but not as a sole carbon source. As with SAR11 Ia, these bacteria contain the proposed THF-linked C1 oxidation pathway and lack specialized pathways for the assimilation of C1 compounds [8], [36]. These observations suggest that, as we report below for SAR11 Ia strains, R. japonicum and A. tumefaciens, and probably many other bacteria, may utilize C1 and methylated compounds for energy production.
All three SAR11 Ia genomes possess an alcohol dehydrogenase (ADH) gene (SAR11_1287; Fig. 1B) that was initially annotated as methanol dehydrogenase. We propose that this enzyme catalyzes the oxidation of short chain alcohols, including methanol, to the corresponding aldehydes (Fig. 2B). In the case of methanol, the oxidation product is formaldehyde, which can be converted to CO2 by the methyl-THF linked oxidation pathway described above. This gene encodes a member of the iron-containing alcohol dehydrogenase (Fe-ADH, PF00465) protein family found in many microorganisms. Oxidation of methanol rarely is observed in non-methylotrophic bacteria that lack the classical pyrroloquinoline-quinone (PQQ)-containing methanol dehydrogenase. Methanol dehydrogenase activity has been confirmed in ADH proteins from some Firmicutes and Archaea [39]-[41]. A phylogenetic tree of the Fe-ADH proteins from three SAR11 Ia strains (Fig. 3, light green) and closely related homologs from other organisms shows that the proteins with demonstrated methanol dehydrogenase activity (arrows) are more highly diverged than their close relatives, and that the SAR11 Fe-ADH proteins branch nearby (Fig. 3). As we report below (Tables 2 and 3), physiological evidence from ATP assays supports the conclusion that the SAR11 Fe-ADH is not specific for methanol oxidation, but can oxidize other short chain primary alcohols as well. Similar conclusions were reported previously for other bacterial ADH genes in the same family [42]-[44]. Only short-chained, primary alcohols (methanol, ethanol, and 1-propanol) stimulated ATP production in HTCC1062.
Coloration is according to 16S rRNA gene phylogeny, as shown in the boxed legend. Bootstrap values were omitted for clarity; nodes with less than 60% support were collapsed. Arrows indicate Fe-ADH proteins for which methanol dehydrogenase activity has been demonstrated experimentally. Scale bar = 0.4 changes per position.
A predicted GBT degradation pathway operon was identified in the SAR11 Ia genomes. In this pathway, the three N-methyl groups of GBT are removed in sequence by three enzymes: betaine-homocysteine methyltransferase (BHMT), dimethylglycine dehydrogenase, and sarcosine dehydrogenase (encoded separately by SAR11_1173, SAR11_1253, and SAR11_1221 in HTCC1062). These methyl groups have different predicted fates. The first methyl group is transferred to methionine by BHMT, an enzyme that is common and well studied in mammals, but is rarely found in prokaryotes [45], [46]. The second and third methyl groups are predicted to be transferred to THF in reactions that are coupled to partial oxidation and then further oxidized to CO2 by the THF-linked oxidation pathway described above (Fig. 2A, C). A previous study showed that the uptake and metabolism of GBT by bacteria-sized organisms in seawater was correlated with salinity [47]. Consistent with that study, metagenomic analysis showed relatively constant ratios of SAR11 GBT gene frequencies in ocean populations, and absence of these genes in metagenomes from fresh water (Table S2, ID GS20).
Genes for methylamine dehydrogenase are missing from SAR11 Ia genomes, but they contain genes necessary to encode an alternative, glutamate-mediated pathway for methylamine oxidation [48]. Latypova and colleagues showed that N-methylglutamate synthase (NMGS) and N-methylglutamate dehydrogenase (NMGD), encoded by mgsABC and mgdABCD in Methyloversatilis universalis, participate in methylamine oxidation [48]. When the M. universalis NMGS protein sequences were blasted against the predicted HTCC1062 proteome, it returned a glxBCD operon (SAR11_1313-1315) as the top hit. This operon is annotated as a glutamate synthase and shares gene order with the M. universalis NMGS operon. We hypothesize that this operon may encode a holoenzyme that has NMGS activity. NMGS catalyzes transfer of a methyl group from methylamine to glutamate to produce N-methyglutamate as a product.
We postulate that the next step in the pathway, oxidation of N-methyglutamate to glutamate and 5, 10-methylene-THF, with the reduction of FAD to FADH2, is catalyzed by the products of SAR11 genes that are annotated as heterotetrameric forms of sarcosine oxidase (Fig. 2D). Two paralogous operons of four sarcosine oxidase genes, soxBDAG (SAR11_1064-1067) and soxB2D2A2G2 (SAR11_1281-1284), are located in separate locations of HTCC1062 genomes with the same gene orders and conserved functional domains as those encoding NMGD in M. universalis (Fig. 1C). Metagenome surveys showed that these two sets of paralogs are highly represented in SAR11 populations globally (Fig. S1). We postulate that one of these sets of paralogs encodes the sarcosine oxidase holoenzyme, and the other encodes NMGD; however, which operon encodes which function is unclear. Heterotetrameric sarcosine oxidases (a.k.a sarcosine dehydrogenase) participate in the GBT degradation pathway by converting sarcosine to glycine. In HTCC1062, SAR11_1304 is predicted to encode the monomeric form of sarcosine oxidase, and is adjacent to two genes annotated as an aminomethyltransferase (AMT) and a GBT transporter (SAR11_1303 and SAR11_1302; Fig. 1E). The presence of two paralogous sarcosine oxidase operons and an individual gene encoding a monomeric sarcosine oxidase is noteworthy considering that paralogs are rare in highly compact SAR11 genomes [28]. We postulate that SAR11 Ia strains may use these genes for the reactions described above and possibly for the demethylation of unknown substrates in oxidation reactions that are likely to produce the intermediate 5, 10-methylene-THF [49].
A different pathway for methylamine demethylation that involves the intermediate gamma-glutamylmethylamide was also postulated by Latypova and colleagues [48]. We found the homolog of gamma-glutamylmethylamide synthetase (GMAS) from this pathway in HTCC1062, which was annotated as glnT, a glutamine synthetase III (SAR11_1316, Fig. 1C) and shares the conserved Gln-synt_C domain (Pfam PF00120.17) with GMAS. However, the complete pathway has not been identified and the enzyme was considered to be not essential for oxidation of methylamine in M. universalis [48].
The three SAR11 Ia genomes include a family of paralogous AMT genes (Fig. 1E). Phylogenetic analysis provided strong support for placing the four AMT genes from HTCC1062 into three functionally distinct subgroups (Fig. 4). SAR11_0666 encodes the glycine cleavage system T-protein (GcvT), part of the glycine cleavage multi-enzyme complex (GCV), which is present in most bacteria and mitochondria [50]. GCV catalyzes the degradation of glycine to form 5, 10-methylene-THF, CO2 and NH3 [51] (Fig. 2F). SAR11_0246 encodes DmdA, a member of the AMT protein family that catalyzes removal of the first methyl group from DMSP to produce methylmercaptopropionate (MMPA) in a pathway for DMSP catabolism [52], [53] (Fig. 2G). However, the enzyme that subsequently demethylates MMPA to mercaptopropionate (MPA) has not been identified.
Four paralogous AMTs in HTCC1062 were placed into three functional subgroups: DmdA-like, GcvT, and an AMT of unknown function. All four AMTs were also identified in HTCC1002 and HTCC7211 genomes. This phylogenetic tree was generated using the neighbor-joining method. Bootstrap values are based on 100 iterations.
SAR11_1265 and SAR11_1303 are annotated as probable AMTs with unknown substrates. Three genes (opuAB, opuAA, and opuAC) are located near SAR11_1303 and encode putative homologs of the GBT transport system permease protein, GBT transport ATP-binding protein and substrate-binding region of ABC-type GBT transport system (Fig. 1E). Therefore, we postulate that SAR11_1303 may encode an AMT involved in GBT metabolism. Notably, SAR11_1265 is adjacent to the putative metF (SAR11_1264), encoding a homolog of methylene-THF reductase. MetF in Methylobacterium chloromethanicum CM4 enables the oxidation of methyl-THF to methylene-THF [20]. SAR11_1265 is closely related to SAR11_0246 (dmdA) (Fig. 4), and was observed at similar abundances in GOS metagenomic analysis (Fig. S1), leading us to speculate that this gene might catalyze removal of the second methyl group in the DMSP degradation pathway. All of the four AMTs tended towards a 1∶1 ratio with single-copy gene recA (Fig. S1), suggesting that these genes may be part of the SAR11 Ia core genome.
Another gene, SAR11_0621, was initially annotated as an AMT, but later was identified as ygfZ, which encodes a folate-binding protein. Studies on YgfZ in Escherichia coli and Arthrobacter globiformis revealed THF-binding folds in the structure of this protein, but otherwise little similarity to the GcvT family of AMT proteins [54], [55]. Recent studies indicated that YgfZ in E. coli has methylase activity [56] or may be involved in the regulation of C1 metabolism [54]. There is currently no direct evidence for a role in C1 metabolism for YgfZ in SAR11.
Some of the three SAR11 Ia genomes had additional genes implicated in C1 metabolism (Table 1). Genes encoding glutathione-dependent formaldehyde activating enzyme (GFA), glutathione-dependent formaldehyde dehydrogenase (GD-FALDH) and S-formyl-glutathione hydrolase (FGH) are present in HTCC7211, but not in HTCC1062 or HTCC1002. In Paracoccus denitrificans, these proteins catalyze the well-studied glutathione (GSH) dependent pathway that converts formaldehyde to CO2 [7], [57]-[59]. We note that some of the predicted C1 oxidation functions of these genes are redundant with genes for the THF-linked oxidation pathway that are also present in the HTCC7211 genome; however, unlike strain HTCC1062, strain HTCC7211, an isolate from the oligotrophic Sargasso Sea, is predicted to be able to oxidize formaldehyde by using GFA to catalyze the first step in the pathway.
Methane monooxygenases, which catalyze the first reaction of methane oxidation pathways, were not present in any SAR11 genome, indicating that these cells are unlikely to be methane oxidizers. Karl and coworkers reported that methane is produced from methylphosphonate in seawater by the activity of the microbial C-P lyase pathway [60]. This pathway is present in the genome of HTCC7211, but there are no known metabolic pathways by which methyl groups from methylphosphonate can be diverted into THF-linked C1 oxidation.
Direct Experimental Evidence for C1 Oxidation in SAR11 Strain HTCC1062
Genome analysis suggested that C1 metabolism evolved in SAR11 Ia for energy production, rather than as a means to accumulate biomass. Testing this hypothesis was challenging because SAR11 Ia cells require a variety of unusual organic growth factors and cannot be cultured on “sole” carbon sources, a common paradigm in microbiology. Some required compounds, notably glycine, can be oxidized to produce energy as well as being needed for biomass production [61]. Thus, we were not surprised when the addition of various C1 and methylated compounds did not change growth rates or yields of cultures (data not shown). To test for C1 oxidation activities predicted by genome analysis, we turned to direct measurements of energy production and substrate oxidation.
Measurements of cellular ATP content supported the conclusion that HTCC1062 can produce energy from a wide variety of C1 and methylated compounds (Table 3). ATP levels were assayed in HTCC1062 cells that were first grown in the presence of C1 and methylated compounds to be certain that pathways involving C1 oxidation genes were induced. Concentrations of compounds used for ATP assays and 14C experiments (below) were determined in advance by growth assays, as described in the materials and methods. Pyruvate, which was shown previously to be actively metabolized as an energy and carbon source by HTCC1062 cells [62], was used as a positive control. ATP content increased in cells incubated with all of the methylated compounds tested with the exception of formate, relative to negative controls. Methanol and TMAO caused the greatest increases in ATP content (3- and 2.4-fold, respectively). We speculate that formate did not enhance ATP levels because it was not transported into cells.
Consistent with predictions from the genome sequence, radioisotope studies with 14C-[methyl]-GBT, 14C-TMA, 14C-methanol and 14C-formaldehyde demonstrated that HTCC1062 oxidized methyl groups from methylated compounds and C1 compounds to CO2, but incorporation of the compounds into biomass was negligible (Fig. 5). Among these compounds, the oxidation rate was fastest with 5 µM 14C-TMA (3.82 nmol×1010cells−1×h−1), while 100 nM 14C-formaldehyde was oxidized to 14CO2 at the lowest rate (0.01 nmol×1010 cells−1×h−1), likely reflecting the lack of formaldehyde activating enzyme in HTCC1062. The rate of 20 µM methanol oxidized to 14CO2 was 0.50 nmol×1010 cells−1×h−1.
HTCC1062 Cells from log phase were collected and resuspended in artificial seawater media (ASW). Radioisotope assays were conducted at room temperature (22°C) in ASW amended with (A) 1 µM 14C-[methyl]-GBT; (B) 5 µM 14C-TMA; (C) 20 µM 14C-methanol; or (D) 100 nM 14C-formaldehyde. Where not visible, error bars are smaller than the size of the symbols.
The ability of cultured Ca. P. ubique to oxidize C1 compounds, and the conservation of genes for C1 metabolism in streamlined SAR11 genomes, suggests that C1 oxidation pathways may contribute significantly to the energy budget of these cells in nature. To examine this hypothesis, we measured the potential rates at which 14C-labeled C1 and methylated compounds were oxidized and incorporated into biomass by cells concentrated from the Sargasso Sea upper euphotic zone during the period of summer stratification. Long-term time series measurements have shown that SAR11 cells range from 30-40% of cells at this ocean site, and that the distinctive microbial community that forms in the upper euphotic zone during the summer is dominated by the SAR11 Ia subclade [25], [29]. The data from bacterioplankton populations collected in the western Sargasso Sea revealed rates of carbon assimilation and oxidation of the same order observed with pure SAR11 cultures in the laboratory (Fig. 6 and [62]). Similar methanol oxidation rates (∼0.8 – 2.5 nmol×1010 cells−1×h−1) were measured in off-shelf northeast Atlantic seawaters [14], which are also dominated by SAR11 cells [25]. Notably, in the natural bacterioplankton community less than 6 % of the 14C-methanol, 2 % of 14C-formate, and 3 % of 14C-formaldehyde were assimilated into biomass, with the remainder oxidized to CO2 by the natural community. In contrast, 35 % of glucose and 27 % of pyruvate were assimilated into bacterioplankton biomass in the field experiments (Fig. 6), similar to the fraction of organic carbon assimilation into biomass observed previously with growing SAR11 cultures and typical of bacterial organic carbon assimilation in general [62]. One noteworthy difference between the results obtained with cultured strain HTCC1062 and measurements made in the field is the higher rate of formaldehyde oxidation in the field study. During comparative genome sequence analysis the protein GFA (formaldehyde activating enzyme) was noted in the HTCC7211 genome (Table 1), an isolate obtained from the Sargasso Sea. It may be that ecotypes of SAR11 found in the Sargasso Sea summer upper euphotic zone microbial community have a potential to oxidize formaldehyde that is not found in coastal isolates. Overall, these findings suggest that energy production by C1 oxidation, rather than methylotrophy, in which a large fraction (i.e., 62 %; [63]) of the C1 compound is incorporated into biomass, is the predominant mode of C1 oxidation in surface waters of temperate oligotrophic oceans.
The oxidation and incorporation rates were calculated from the initial linear part of each curve. Rate of 14C-compound oxidation to 14CO2 (▪); rate of 14C-compounds incorporation into biomass (□).
Conclusions
It is a paradox that the SAR11 clade evolved small genomes while becoming the most successful heterotrophs known, because DOC is a complex substrate that would appear to require complex metabolic pathways for oxidation. The most obvious solution to this conundrum is substrate specialization by SAR11 and other heterotrophic species in microbial communities, dividing the oxidative side of the carbon cycle into niches. In this report we show that a considerable part of the SAR11 Ia genomes is devoted to C1 metabolism that produces energy but not biomass. C1 and methylated compounds have not generally been regarded as a large fraction of the marine carbon cycle, but there have been a number of reports of C1 compounds and C1 oxidation activity in marine systems [14], [47]. We speculate that C1 metabolism evolved in SAR11 because it gave these cells the ability to catabolize a variety of compounds – ranging from low molecular weight photolysis products to osmolytes carrying multiple methyl groups, such as DMSP and GBT. DMSP catabolism in SAR11, and its use as a source of reduced sulfur for growth, has been the subjects of previous studies that did not examine the fate of methyl groups [53], [64].
The concept of cells producing energy but not biomass from C1 compounds has received little attention. The best analogy is the term “carboxidovory”, which was coined to describe the metabolism of cells that produce energy by oxidizing carbon monoxide, and to distinguish them from “carboxidotrophs” [65], [66], which can use carbon atoms from carbon monoxide for the net assimilation of biomass. Based on this precedent, we propose a new term, “methylovores”, to distinguish cells, such as SAR11 and likely many other bacteria, that can utilize C1 compounds as a source of energy, from methylotrophs, which are able to use C1 compounds as sole sources of energy and carbon.
Phylogenomic studies have placed the mitochondria deep within the Alphaproteobacteria, close to Rickettsiales and the SAR11 clade [67]. Although respiration is a central feature of mitochondria that is assumed to have driven the original endosymbiotic event, mitochondria make complex contributions to cellular metabolism, including vitamin biosynthesis [68], and the metabolism of C1 compounds [69], [70], which evidence supports as being present in the protomitochondrion [71]. In light of the data presented here it is not unreasonable to speculate that the C1 metabolism of mitochondria was contributed by free-living methylovorous ancestors of modern SAR11.
The findings we report show that SAR11 Group Ia strains can produce cellular energy from a broad range of C1 and methylated compounds by oxidative metabolism that we here refer to as methylovory to distinguish it from methylotrophy. The data we present also show that the potential for methylovory was highly expressed in a natural oligotrophic ocean surface microbial community dominated by SAR11. Based on these findings, we speculate that C1 oxidation pathways contribute significantly to the marine carbon cycle and in part explain the broad success of SAR11.
Materials and Methods
Bioinformatics analysis and phylogeny
Gene calls and functional assignment of SAR11 Group Ia genomes were performed by an automated pipeline at Oregon State University's Center for Genome Research and Biocomputing (http://bioinfo.cgrb.oregonstate.edu/microbes/index.html). Conserved domains were determined with Pfam [72]. KEGG [73] and MicrobesOnline [74] were used for predicting physiological and metabolic pathways.
For the phylogeny of the Fe-ADHs, Pfam was used to confirm the orthology of the Fe-ADH domain in the three SAR11 strains with that of the known methanol dehydrogenase genes (Pfam Fe-ADH PF00465). The phylogenetic tree was then constructed using these six sequences and those of over 70 of the 100 top hits identified using PSI-BLAST with the HTCC1062 gene (YP_266695) as the query sequence. Sequences were aligned using MUSCLE [75], [76], and manually edited to remove columns with >85% gaps. Substitution modeling was completed using ProtTest [77]. The alignment was then analyzed with RAxML [78] using the WAG substitution model and nodal support was estimated based on 100 bootstrap replications.
Phylogeny of the AMTs was performed by MicobesOnline website and MacVector software. The top 10 matched protein sequences of each AMT (YP_265671, YP_266089, YP_266673, YP_266710) were downloaded using BLAST tools from MicrobesOnline. AMTs were aligned using the ClustalW module of MacVector version 10.5.2, and Phylogenetic trees were constructed using the neighbor-joining method. One-hundred bootstrap replicates were used to estimate the robustness of branches in the phylogenetic tree. Accession numbers are in Table S3.
Homology assessment of methylovory genes was completed using the HAL pipeline [36], [79] (http://aftol.org/pages/Halweb3.htm; http://sourceforge.net/projects/bio-hal/) followed by manual examination of predicted orthologous clusters. For this study, the HAL pipeline directed the following analyses: Protein sequences from 127 publically available Alphaproteobacteria genomes (for a complete list, see [67]) were imported in FASTA format from IMG (http://img.jgi.doe.gov) and subjected to all vs. all BLASTP with the output E-values provided to the program MCL [80], which grouped proteins into orthologous clusters using 13 inflation parameters from 1.1 – 5.0. For homology assessment in Figure S2, we examined clusters formed at the relatively conservative 3.0 inflation parameter, and thus these numbers can be considered as lower estimates of total homologs.
Metagenomic analysis
The reciprocal best BLAST (RBB) approach [81] was used to identify environmental fragments in the global ocean survey (GOS) database originating from SAR11 and encoding genes related to C1 and methyl group oxidation. The amino acid sequences for the genes discussed in this paper were searched with BLASTP (e-value threshold = 1×10−5) against peptide sequences called from GOS metagenomic nucleotide reads. The taxonomies of matching peptides were determined by querying the peptide against the NCBI non-redundant protein database (NR) using BLASTP (e-value threshold = 10). Sequences were only retained if this second search against NR found one of the three Ca. P. ubique strains to be the best match to the environmental peptide. Peptides were lastly searched with BLASTP (e-value threshold = 1×10−5) against all Ca. P. ubique strain HTCC1062 amino acid sequences to ensure that the initial Ca. P. ubique query protein, rather than a paralog, was the best match to the environmental peptide sequence. The number of environmental peptides passing the RBB test, or hits, per gene at each GOS sampling site were normalized to the length of the single-copy essential gene recA and the number of hits to recA at the same sampling site using the formula Pg = (LrecA / Lg)×(Hg / HrecA), where Pg is the percentage abundance related to recA for gene g, LrecA is the length of recA in base-pairs (bp), Lg is the length of gene g in bp, Hg is the number of hits for gene g, and HrecA is the number of hits to recA [82]. GOS sampling sites that had fewer than five hits to recA were removed from downstream analysis.
ATP measurements
HTCC1062 cultures for ATP assays were grown in autoclaved, filtered seawater amended with 1 mM NH4Cl, 100 µM KH2PO4, 1 µM FeCl3, 80 µM pyruvate, 40 µM oxaloacetate, 40 µM taurine, 1 µM GBT, 50 µM glycine, 50 µM methionine, and excess vitamins [62]. C1 and methylated compounds to be tested were added as follows: 1 µM GBT, 20 µM formate, 10 µM methylamine, 5 µM TMAO, 1 µM DMSP, 20 µM methanol and 100 nM formaldehyde. The concentration of GBT used in the assay was the same as routinely used in Ca. P. ubique growth media (1 µM). The concentrations of other compounds utilized in assays were chosen by testing the growth of HTCC1062 with differing concentrations of each compound and selecting concentrations that were not inhibitory (Fig. S3). Cultures were grown in the dark at 16°C. When cultures entered early stationary phase (∼3×108 cells mL−1), 10 mL of each culture were collected and cells were harvested via centrifugation (50 min at 43,700 g, 10°C). Following centrifugation, cells were washed twice in artificial seawater (ASW) [62] and finally resuspended in 5 mL ASW. Then cells were distributed into 1.7 mL tubes (500 µL in each tube) and starved overnight (20 hours in the dark, 16°C). Test treatments and controls were done in triplicate with identical cell suspensions. After 2 hours incubation in the dark, ATP content was measured using a luciferase-based assay (BactTiter Glo, Promega, Madison, WI) as follows: 90 µL of BactTiterGlo reagent were dispensed into white 96 well plates (Tissue culture-treated, BD Biosciences, San Jose, CA). 20 µL of each sample were added per well, and luminescence was measured after 4 min using a multi-functional plate reader (TECAN, Infinite M200) with a 1 s integration and 10 ms settle time. An ATP standard curve was used to calculate the concentration of ATP in the samples. Student's t-test was used to assess statistical significance (p-value<0.01) between controls and treatments. The ATP measurements for other alcohols (20 µM ethanol, 20 µM 1-propanol, 20 µM 2-propanol, 20 µM 1-butanol, 20 µM 2-pentanol, and 20 µM iso-amyl alcohol) were performed as described above.
Radioisotope assays
To distinguish between 14C-labeled compounds incorporated into biomass and oxidized to 14CO2, a method was devised for volatile 14C compounds (e.g., 14C-labeled methanol). Trichloroacetic acid (TCA)-precipitation was used to assess 14C-incorporation into cellular material, and 14CO2 was precipitated by addition of NaOH, Na2CO3 and BaCl2, forming Ba14CO3 and BaOH. Filtration removed unincorporated 14C compounds and BaOH, thus minimizing potential quenching effects of the base.
For experiments with radioisotopes, HTCC1062 was grown in seawater medium as described above for ATP measurements. Cultures were amended with unlabeled test compounds to induce activities (5 μM TMA, 20 μM methanol, or 100 nM formaldehyde; 1 μM GBT was in the seawater medium). Cells were harvested in log phase by centrifugation (1 hour at 43,700 g, 10°C) and resuspended in ASW to about 4×107 cells mL−1. Negative controls (“Killed”) were incubated in 10% formalin for 1 hour before the addition of the isotope to the sample. 1 µM 14C-[methyl]-GBT, 5 µM 14C-TMA, 20 µM 14C-methanol, or 100 nM 14C-formaldehyde were added to both “Live” and “Killed” culture samples. Inoculated cultures (4 mL) were aliquoted into 40 mL sealed vials. Samples were incubated at room temperature. At each time point, reagents were added to cultures using syringes inserted through stoppers. For 14C-incorporation, 2.2 mL 100% w/v cold TCA was added; for trapping 14CO2, 1 mL 1N NaOH, 0.5 mL 0.1 M Na2CO3 and 1 mL 1 M BaCl2 were added. All samples were collected by filtration after incubation at 4°C for 12 hrs. Filters were transferred to vials containing 15 mL Ultima Gold™ XR scintillation fluid (Perkin-Elmer) and kept in dark overnight before counting (Beckman LS-6500 liquid scintillation counter).
For field studies of radiolabeled compound utilization by bacterioplankton in the western Sargasso Sea, seawater was collected from 10 m at Bermuda Hydrostation S using Niskin bottles, and transferred to an acid-washed, autoclaved polycarbonate carboy. For each experiment, microbial plankton were concentrated from 80 L seawater by tangential flow filtration to a final volume of 600 mL, and isotopic labeling was carried out as described above. The concentrations of the tested compounds were 3 µM glucose, 1.7 µM pyruvate, 0.3 µM formate, 1.1 µM formaldehyde, 50 µM methanol and 0.5 µM TMAO. A high concentration of methanol was used because the specific activity of the labeled compound was very low. Some unexpected evaporation of the radio-labeled compounds occurred during transport causing some variability between concentrations of the other compounds used. Nevertheless, in all cases the concentrations used were likely to be substantially higher than typical seawater concentrations, and the results represent potential rates of compound utilization.
Supporting Information
Figure S1.
The abundance of SAR11 C1 metabolism genes in GOS data, relative to SAR11 recA genes. Genes were identified as SAR11 by a reciprocal best BLAST (RBB) approach. SAR11 C1 genes with frequencies less than SAR11 recA (<1x) may indicate that only subpopulations of SAR11 cells possess that gene; genes greater than 1x suggest that multiple copies of that gene are present per cell. Boxes encompass points between the 25th and 75th percentiles, with the median represented as a thick horizontal line. Whiskers span the minimal distance needed to include all points within 1.5 x the interquartile range beyond the interquartile boundary, with points outside of this range rendered individually as circles. For each gene, n = 40. Abbreviations: adj., genomically adjacent genes.
https://doi.org/10.1371/journal.pone.0023973.s001
(TIF)
Figure S2.
Distribution of C1 gene homologs throughout the Alphaproteobacteria. The number of genomes containing homologs of C1 oxidation genes reported by gene and divided by Order. The total number of genomes examined for each order is in parentheses.
https://doi.org/10.1371/journal.pone.0023973.s002
(TIFF)
Figure S3.
Culture experiments to determine the concentrations of C1 and methylated compounds for ATP and radioisotope assays. HTCC1062 cells were cultured in seawater medium amended with 10 µM NH4Cl, 1 µM KH2PO4, 10 nM FeCl3, vitamins, and C1 and methylated compounds at different concentrations.
https://doi.org/10.1371/journal.pone.0023973.s003
(PDF)
Table S1.
Methylovory pathways and associated genes in Candidatus Pelagibacter ubique SAR11 HTCC1062. Table includes genes involved in methylovory in SAR11 HTCC1062 and their associated homologs in other organisms mentioned in the text of the paper. Associated proteins are grouped together. Identifiers and annotated functions are taken from the Integrated Microbial Genomes database (IMG) where available, and from the literature where marked. Clusters of Orthologous Groups assignments (COGS) were taken from the IMG database, where available, and were generated using the COGnitor tool (available from http://www.ncbi.nlm.nih.gov/COG/) for sequences referred to the literature sources. Locus names are taken from IMG where available.
https://doi.org/10.1371/journal.pone.0023973.s004
(XLS)
Table S2.
The percent abundance of SAR11 C1 metabolism genes at each sample site in GOS data, relative to recA.
https://doi.org/10.1371/journal.pone.0023973.s005
(XLS)
Table S3.
Accession numbers used in Figure 3 and Figure 4 .
https://doi.org/10.1371/journal.pone.0023973.s006
(DOC)
Acknowledgments
We thank the crews of the RV Elaka and RV Atlantic Explorer, Craig Carlson, Rachel Parsons and Craig Nelson for their assistance with field studies. We also thank Ludmila Chistoserdova and Marina G. Kalyuzhnaya for stimulating discussions about C1 metabolism.
Author Contributions
Conceived and designed the experiments: JS SJG. Performed the experiments: JS LS. Analyzed the data: JS JCT DPS LS KHH SJG. Contributed reagents/materials/analysis tools: SJG. Wrote the paper: JS JCT LS KHH DPS SJG. Performed the field experiments in Bermuda: KHH AEC SJG ZCL.
References
- 1. Henderson JF (1979) Teaching one-carbon metabolism. Biochem Educ 7: 51–52.
- 2.
McDowell LR (2000) Vitamins in animal and human nutrition: Iowa State University Press. 487 p.
- 3. Chistoserdova L, Vorholt JA, Thauer RK, Lidstrom ME (1998) C1 transfer enzymes and coenzymes linking methylotrophic bacteria and methanogenic Archaea. Science 281: 99–102.
- 4. Chistoserdova L, Chen SW, Lapidus A, Lidstrom ME (2003) Methylotrophy in Methylobacterium extorquens AM1 from a genomic point of view. J Bacteriol 185: 2980–2987.
- 5. Chistoserdova L, Kalyuzhnaya MG, Lidstrom ME (2009) The expanding world of methylotrophic metabolism. Annu Rev Microbiol 63: 477–499.
- 6. Giovannoni SJ, Hayakawa DH, Tripp HJ, Stingl U, Givan SA, et al. (2008) The small genome of an abundant coastal ocean methylotroph. Environ Microbiol 10: 1771–1782.
- 7. Vorholt JA (2002) Cofactor-dependent pathways of formaldehyde oxidation in methylotrophic bacteria. Arch Microbiol 178: 239–249.
- 8. Bicknell B, Owens JD (1980) Utilization of methylamines as nitrogen sources by non-methylotrophs. J Gen Microbiol 117: 89–96.
- 9. Diaz MR, Visscher PT, Taylor BF (1992) Metabolism of dimethylsulfoniopropionate and glycine betaine by a marine bacterium. FEMS Microbiol Lett 96: 61–66.
- 10. Barrett EL, Kwan HS (1985) Bacterial reduction of trimethylamine oxide. Annu Rev of Microbiol 39: 131–149.
- 11. Stefels J (2000) Physiological aspects of the production and conversion of DMSP in marine algae and higher plants. J Sea Res 43: 183–197.
- 12. Heikes BG, Chang W, Pilson MEQ, Swift E, Singh HB, et al. (2002) Atmospheric methanol budget and ocean implication. Global Biogeochem Cycles 16: 1133.
- 13. Singh HB, Tabazadeh A, Evans MJ, Field BD, Jacob DJ, et al. (2003) Oxygenated volatile organic chemicals in the oceans: Inferences and implications based on atmospheric observations and air-sea exchange models. Geophys Res Lett 30: 1862.
- 14. Dixon JL, Beale R, Nightingale PD (2010) Microbial methanol uptake in northeast Atlantic waters. ISME J 5: 704–716.
- 15. Zimmerman PR, Chatfield RB, Fishman J, Crutzen PJ, Hanst PL (1978) Estimates on the production of CO and H2 from the oxidation of hydrocarbon emissions from vegetation. Geophys Res Lett 5: 679–682.
- 16. Goode JG, Yokelson RJ, Ward DE, Susott RA, Babbitt RE, et al. (2000) Measurements of excess O3, CO2, CO, CH4, C2H4, C2H2, HCN, NO, NH3, HCOOH, CH3COOH, HCHO, and CH3OH in 1997 Alaskan biomass burning plumes by airborne Fourier transform infrared spectroscopy (AFTIR). J Geophys Res 105: 22147–22166.
- 17. Mopper K, Zhou X, Kieber RJ, Kieber DJ, Sikorski RJ, et al. (1991) Photochemical degradation of dissolved organic carbon and its impact on the oceanic carbon cycle. Nature 353: 60–62.
- 18. Jones DP, Thor H, Andersson B, Orrenius S (1978) Detoxification reactions in isolated hepatocytes. Role of glutathione peroxidase, catalase, and formaldehyde dehydrogenase in reactions relating to N-demethylation by the cytochrome P-450 system. J Biol Chem 253: 6031–6037.
- 19. Vorholt JA, Chistoserdova L, Stolyar SM, Thauer RK, Lidstrom ME (1999) Distribution of tetrahydromethanopterin-dependent enzymes in methylotrophic bacteria and phylogeny of methenyl tetrahydromethanopterin cyclohydrolases. J Bacteriol 181: 5750–5757.
- 20. Studer A, McAnulla C, Buchele R, Leisinger T, Vuilleumier S (2002) Chloromethane-induced genes define a third C1 utilization pathway in Methylobacterium chloromethanicum CM4. J Bacteriol 184: 3476–3484.
- 21. Wilson SM, Gleisten MP, Donohue TJ (2008) Identification of proteins involved in formaldehyde metabolism by Rhodobacter sphaeroides. Microbiology 154: 296–305.
- 22. Meskys R, Harris RJ, Casaite V, Basran J, Scrutton NS (2001) Organization of the genes involved in dimethylglycine and sarcosine degradation in Arthrobacter spp.: implications for glycine betaine catabolism. Eur J Biochem 268: 3390–3398.
- 23. Grafstrom RC, Fornace AJ , Autrup H, Lechner JF, Harris CC (1983) Formaldehyde damage to DNA and inhibition of DNA repair in human bronchial cells. Science 220: 216–218.
- 24. Craft TR, Bermudez E, Skopek TR (1987) Formaldehyde mutagenesis and formation of DNA-protein crosslinks in human lymphoblasts in vitro. Mutat Res 176: 147–155.
- 25. Morris RM, Rappe MS, Connon SA, Vergin KL, Siebold WA, et al. (2002) SAR11 clade dominates ocean surface bacterioplankton communities. Nature 420: 806–810.
- 26. Rappe MS, Giovannoni SJ (2003) The uncultured microbial majority. Annu Rev Microbiol 57: 369–394.
- 27. Giovannoni SJ, Britschgi TB, Moyer CL, Field KG (1990) Genetic diversity in Sargasso Sea bacterioplankton. Nature 345: 60–63.
- 28. Giovannoni SJ, Tripp HJ, Givan S, Podar M, Vergin KL, et al. (2005) Genome streamlining in a cosmopolitan oceanic bacterium. Science 309: 1242–1245.
- 29. Carlson CA, Morris R, Parsons R, Treusch AH, Giovannoni SJ, et al. (2009) Seasonal dynamics of SAR11 populations in the euphotic and mesopelagic zones of the northwestern Sargasso Sea. ISME J 3: 283–295.
- 30. Chistoserdova L, Laukel M, Portais JC, Vorholt JA, Lidstrom ME (2004) Multiple formate dehydrogenase enzymes in the facultative methylotroph Methylobacterium extorquens AM1 are dispensable for growth on methanol. J Bacteriol 186: 22–28.
- 31. Chistoserdova L, Crowther GJ, Vorholt JA, Skovran E, Portais JC, et al. (2007) Identification of a fourth formate dehydrogenase in Methylobacterium extorquens AM1 and confirmation of the essential role of formate oxidation in methylotrophy. J Bacteriol 189: 9076–9081.
- 32. Guse A, Stevenson CE, Kuper J, Buchanan G, Schwarz G, et al. (2003) Biochemical and structural analysis of the molybdenum cofactor biosynthesis protein MobA. J Biol Chem 278: 25302–25307.
- 33. Wang W, Zhang W, Lu J, Yang Y, Chiao J, et al. (2002) MoeA, an enzyme in the molybdopterin synthesis pathway, is required for rifamycin SV production in Amycolatopsis mediterranei U32. Appl Microbiol Biotechnol 60: 139–146.
- 34. Hasona A, Ray RM, Shanmugam KT (1998) Physiological and genetic analyses leading to identification of a biochemical role for the moeA (molybdate metabolism) gene product in Escherichia coli. J Bacteriol 180: 1466–1472.
- 35.
Robbertse B, Yoder RJ, Boyd A, Reeves J, Spatafora JW (2011) Hal: an automated pipeline for phylogenetic analyses of genomic data. PLoS Curr 3: RRN1213. RRN1213 p. https://doi.org/10.1371/currents
- 36. Chen Y, McAleer KL, Murrell JC (2010) Monomethylamine as a nitrogen source for a nonmethylotrophic bacterium, Agrobacterium tumefaciens. Appl Environ Microbiol 76: 4102–4104.
- 37. Manian SS, Gumbleton R, Buckley AM, O'Gara F (1984) Nitrogen fixation and carbon dioxide assimilation in Rhizobium japonicum. Appl Environ Microbiol 48: 276–279.
- 38. Singh RK, Singh RM (1983) Diverse effects of formate on the assimilatory metabolism of nitrate and nitrite in Rhizobium. J Biosciences 6: 181–184.
- 39. de Vries GE, Arfman N, Terpstra P, Dijkhuizen L (1992) Cloning, expression, and sequence analysis of the Bacillus methanolicus C1 methanol dehydrogenase gene. J Bacteriol 174: 5346–5353.
- 40. Liu X, Dong Y, Zhang J, Zhang A, Wang L, et al. (2009) Two novel metal-independent long-chain alkyl alcohol dehydrogenases from Geobacillus thermodenitrificans NG80-2. Microbiology 155: 2078–2085.
- 41. Antoine E, Rolland JL, Raffin JP, Dietrich J (1999) Cloning and over-expression in Escherichia coli of the gene encoding NADPH group III alcohol dehydrogenase from Thermococcus hydrothermalis. Characterization and comparison of the native and the recombinant enzymes. Eur J Biochem 264: 880–889.
- 42.
Bystrykh LV, Arfman N, Dijkhuizen L (1993) The methanol-oxidizing enzyme systems in Gram-positive methylotrophic bacteria. In: Murrell , JC , Kelly , DP , editors. Andover, UK: Intercept Ltd.. pp. 245–251. Microbial growth on C1 compounds.
- 43. Arfman N, Hektor HJ, Bystrykh LV, Govorukhina NI, Dijkhuizen L, et al. (1997) Properties of an NAD(H)-containing methanol dehydrogenase and its activator protein from Bacillus methanolicus. Eur J Biochem 244: 426–433.
- 44.
Vandecasteele J-P (2008) Petroleum microbiology: concepts environmental implications industrial applications. Paris Editions Technip. 134 p.
- 45. Serra AL, Mariscotti JF, Barra JL, Lucchesi GI, Domenech CE, et al. (2002) Glycine betaine transmethylase mutant of Pseudomonas aeruginosa. J Bacteriol 184: 4301–4303.
- 46. Barra L, Fontenelle C, Ermel G, Trautwetter A, Walker GC, et al. (2006) Interrelations between glycine betaine catabolism and methionine biosynthesis in Sinorhizobium meliloti strain 102F34. J Bacteriol 188: 7195–7204.
- 47. Kiene RP (1998) Uptake of choline and its conversion to glycine betaine by bacteria in estuarine waters. Appl Environ Microbiol 64: 1045–1051.
- 48. Latypova E, Yang S, Wang YS, Wang T, Chavkin TA, et al. (2010) Genetics of the glutamate-mediated methylamine utilization pathway in the facultative methylotrophic beta-proteobacterium Methyloversatilis universalis FAM5. Mol Microbiol 75: 426–439.
- 49. Chlumsky LJ, Zhang L, Jorns MS (1995) Sequence analysis of sarcosine oxidase and nearby genes reveals homologies with key enzymes of folate one-carbon metabolism. J Biol Chem 270: 18252–18259.
- 50. Scott DA, Hickerson SM, Vickers TJ, Beverley SM (2008) The role of the mitochondrial glycine cleavage complex in the metabolism and virulence of the protozoan parasite Leishmania major. J Biol Chem 283: 155–165.
- 51.
Dworkin M, Falkow S, Rosenberg E, Schleifer K-H, Stackebrandt E (2006) The prokaryotes: Symbiotic associations, biotechnology, applied microbiology. Springer. 266 p.
- 52. Howard EC, Henriksen JR, Buchan A, Reisch CR, Burgmann H, et al. (2006) Bacterial taxa that limit sulfur flux from the ocean. Science 314: 649–652.
- 53. Reisch CR, Moran MA, Whitman WB (2008) Dimethylsulfoniopropionate-dependent demethylase (DmdA) from Pelagibacter ubique and Silicibacter pomeroyi. J Bacteriol 190: 8018–8024.
- 54. Teplyakov A, Obmolova G, Sarikaya E, Pullalarevu S, Krajewski W, et al. (2004) Crystal structure of the YgfZ protein from Escherichia coli suggests a folate-dependent regulatory role in one-carbon metabolism. J Bacteriol 186: 7134–7140.
- 55. Scrutton NS, Leys D (2005) Crystal structure of DMGO provides a prototype for a new tetrahydrofolate-binding fold. Biochem Soc Trans 33: 776–779.
- 56. Lin CN, Syu WJ, Sun WS, Chen JW, Chen TH, et al. (2010) A role of ygfZ in the Escherichia coli response to plumbagin challenge. J Biomed Sci 17: 84.
- 57. Goenrich M, Bartoschek S, Hagemeier CH, Griesinger C, Vorholt JA (2002) A glutathione-dependent formaldehyde-activating enzyme (Gfa) from Paracoccus denitrificans detected and purified via two-dimensional proton exchange NMR spectroscopy. J Biol Chem 277: 3069–3072.
- 58. Ras J, Van Ophem PW, Reijnders WN, Van Spanning RJ, Duine JA, et al. (1995) Isolation, sequencing, and mutagenesis of the gene encoding NAD- and glutathione-dependent formaldehyde dehydrogenase (GD-FALDH) from Paracoccus denitrificans, in which GD-FALDH is essential for methylotrophic growth. J Bacteriol 177: 247–251.
- 59. Harms N, Ras J, Reijnders WN, van Spanning RJ, Stouthamer AH (1996) S-formylglutathione hydrolase of Paracoccus denitrificans is homologous to human esterase D: a universal pathway for formaldehyde detoxification? J Bacteriol 178: 6296–6299.
- 60. Karl DM, Beversdorf L, Bjorkman KM, Church MJ, Martinez A, et al. (2008) Aerobic production of methane in the sea. Nature Geosci 1: 473–478.
- 61. Tripp HJ, Schwalbach MS, Meyer MM, Kitner JB, Breaker RR, et al. (2009) Unique glycine-activated riboswitch linked to glycine-serine auxotrophy in SAR11. Environ Microbiol 11: 230–238.
- 62. Schwalbach MS, Tripp HJ, Steindler L, Smith DP, Giovannoni SJ (2009) The presence of the glycolysis operon in SAR11 genomes is positively correlated with ocean productivity. Environ Microbiol 12: 490–500.
- 63. Ben-Bassat A, Goldberg I, Mateles RI (1980) Distribution of methanol carbon between assimilation and oxidation pathways in methanol-grown Pseudomonas C. J Gen Microbiol 116: 213–223.
- 64. Tripp HJ, Kitner JB, Schwalbach MS, Dacey JW, Wilhelm LJ, et al. (2008) SAR11 marine bacteria require exogenous reduced sulphur for growth. Nature 452: 741–744.
- 65. King GM, Weber CF (2007) Distribution, diversity and ecology of aerobic CO-oxidizing bacteria. Nat Rev Microbiol 5: 107–118.
- 66. Sorokin DY, Tourova TP, Kovaleva OL, Kuenen JG, Muyzer G (2010) Aerobic carboxydotrophy under extremely haloalkaline conditions in Alkalispirillum/Alkalilimnicola strains isolated from soda lakes. Microbiology 156: 819–827.
- 67. Thrash JC, Boyd A, Huggett MJ, Grote J, Carini P, et al. (2011) Phylogenomic evidence for a common ancestor of mitochondria and the SAR11 clade. Sci Rep 1:
- 68. Atteia A, Adrait A, Brugiere S, Tardif M, van Lis R, et al. (2009) A proteomic survey of Chlamydomonas reinhardtii mitochondria sheds new light on the metabolic plasticity of the organelle and on the nature of the alpha-proteobacterial mitochondrial ancestor. Mol Biol Evol 26: 1533–1548.
- 69. Appling DR (1991) Compartmentation of folate-mediated one-carbon metabolism in eukaryotes. FASEB J 5: 2645–2651.
- 70. Pike ST, Rajendra R, Artzt K, Appling DR (2009) Mitochondrial C1-tetrahydrofolate synthase (MTHFD1L) supports the flow of mitochondrial one-carbon units into the methyl cycle in embryos. J Biol Chem 285: 4612–4620.
- 71. Gabaldón T, Huynen MA (2007) From endosymbiont to host-controlled organelle: the hijacking of mitochondrial protein synthesis and metabolism. PLoS Comput Biol 3: e219.
- 72. Finn RD, Mistry J, Tate J, Coggill P, Heger A, et al. (2010) The Pfam protein families database. Nucleic Acids Res 38: D211–D222.
- 73. Kanehisa M, Goto S, Furumichi M, Tanabe M, Hirakawa M (2010) KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res 38: D355–D360.
- 74. Dehal PS, Joachimiak MP, Price MN, Bates JT, Baumohl JK, et al. (2009) MicrobesOnline: an integrated portal for comparative and functional genomics. Nucleic Acids Res 38: D396–D400.
- 75. Edgar RC (2004) MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics 5: 113.
- 76. Edgar RC (2004) MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32: 1792–1797.
- 77. Abascal F, Zardoya R, Posada D (2005) ProtTest: selection of best-fit models of protein evolution. Bioinformatics 21: 2104–2105.
- 78. Stamatakis A (2006) RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models. Bioinformatics 22: 2688–2690.
- 79. Robbertse B, Reeves JB, Schoch CL, Spatafora JW (2006) A phylogenomic analysis of the Ascomycota. Fungal Genet Biol 43: 715–725.
- 80.
van Dongen S (2000) Graph Clustering by Flow Simulation. Utrecht, Netherlands: Doctoral dissertation, University of Utrecht. Retrieved July 25, 2011, from website: http://igitur-archive.library.uu.nl/dissertations/1895620/inhoud.htm.
- 81. Wilhelm LJ, Tripp HJ, Givan SA, Smith DP, Giovannoni SJ (2007) Natural variation in SAR11 marine bacterioplankton genomes inferred from metagenomic data. Biol Direct 2: 27.
- 82. Biers EJ, Sun S, Howard EC (2009) Prokaryotic genomes and diversity in surface ocean waters: interrogating the global ocean sampling metagenome. Appl Environ Microbiol 75: 2221–2229.