Phylogenetic analysis of methionine synthesis genes from Thalassiosira pseudonana
© Bromke and Hesse. 2015
Received: 7 May 2015
Accepted: 17 July 2015
Published: 4 August 2015
Diatoms are unicellular algae responsible for approximately 20% of global carbon fixation. Their evolution by secondary endocytobiosis resulted in a complex cellular structure and metabolism compared to algae with primary plastids. The sulfate assimilation and methionine synthesis pathways provide S-containing amino acids for the synthesis of proteins and a range of metabolites such as dimethylsulfoniopropionate. To obtain an insight into the localization and organization of the sulfur metabolism pathways we surveyed the genome of Thalassiosira pseudonana—a model organism for diatom research. We have identified and annotated genes for enzymes involved in respective pathways. Protein localization was predicted using similarities to known signal peptide motifs. We performed detailed phylogenetic analyses of enzymes involved in sulfate uptake/reduction and methionine metabolism. Moreover, we have found in up-stream sequences of studied diatoms methionine biosynthesis genes a conserved motif, which shows similarity to the Met31, a cis-motif regulating expression of methionine biosynthesis genes in yeast.
KeywordsMethionine synthesis Diatoms Phylogenetics
Diatoms are abundant unicellular algae in aquatic habitats. They produce massive amounts of biomass and are thought to contribute to about 20% of global carbon fixation (Falkowski et al. 1998; Field et al. 1998). Phytoplankton affects the climate on the global scale, not only by sequestration of CO2 but also by production of S-containing volatile compounds. According to the hypothesis proposed in 1987 by Charlson, Lovelock, Andreae and Warren (the CLAW hypothesis) phytoplankton is able to regulate the Earth’s climate through the generation of clouds by producing the precursor of dimethylsulfide (DMS). This volatile compound is oxidized in the atmosphere to give non-sea salt sulfate, which acts as cloud condensation nuclei, which in turn modifies both the degree of cloudiness and the albedo of clouds. Increased cloudiness and albedo would reduce the extent to which the surface of the planet is warmed by the sun (Charlson et al. 1987). Though, it is not clear whether the system acts as a negative feedback loop, in which higher temperature and higher availability of carbon for phytoplankton and consecutive DMS release may modulate the greenhouse effect of increased anthropogenic CO2 input to the atmosphere. Bacterial enzymes are mostly responsible of the formation of DMS from dimethylsulfoniopropionate (DMSP). The amino acid methionine is the precursor for the synthesis of DMSP and underlines the dependence on sulfur and nitrogen metabolism (Gage et al. 1997; Keller et al. 1999) of marine algae.
The carbon backbone of methionine derives from aspartate, which in two steps is metabolized to homoserine. In plants homoserine is activated for further processes in a reaction catalyzed by homoserine kinase (HSK), which phosphorylates the γ-hydroxyl group. In some bacteria activation of homoserine is done by O-succinylation catalyzed by the enzyme homoserine O-succinyltransferase (Zubieta et al. 2007). Phosphorylated or succinylated homoserine is condensed with cysteine by cystathionine γ-synthase to form cystathionine. Subsequently, cystathionine β-lyase hydrolyzes cystathionine to form homocysteine (Hesse and Hoefgen 2003). In fungi and bacteria O-acetylhomoserine and O-succinylhomoserine, respectively, can be directly sulfhydrylated to form homocysteine, the precursor of methionine (Foglino et al. 1995; Kerr and Flavin 1970; Park et al. 1998; Rowbury and Woods 1964). In the final step of methionine synthesis, homocysteine is methylated by two non-homologous enzymes: the cobalamin-dependent methionine synthase (METH-type) in mammals, protists and most bacteria (Evans et al. 2004; Goulding and Matthews 1997; Krungkrai et al. 1989) or the cobalamin-independent methionine synthase (METE-type) as found in bacteria (including cyanobacteria), green plants and fungi (Eichel et al. 1995; Kacprzak et al. 2003; Whitfield et al. 1970; Zeh et al. 2002). Many marine algae require external cobalamin supply to maintain methionine synthesis, though the cobalamin auxotrophy is not restricted to specific phyla (Croft et al. 2005). This suggests multiple events of METE-type enzyme loss the in the evolution of algae. Methionine not only is a proteogenic amino acid but served a substrate for synthesis of many sulfur-containing metabolites, such as a very important cofactor in methylation reactions, S-adenosylmethionine (SAM) (McQueney et al. 2000).
Research on diatoms advanced significantly with publication of the whole genome sequences of Thalassiosira pseudonana (Armbrust et al. 2004) and Phaeodactylum tricornutum (Bowler et al. 2008). Diatoms are amazing organisms derived from a non-photosynthetic eukaryote that domesticated a photoautotrophic eukaryotic cell phylogenetically close to a red alga (Parker et al. 2008). This resulted in an extensive gene transfer events and genomic reorganization. Secondary endocytobiosis also increased the complexity of diatom cell structure, with implications on physiology and biochemistry. An important aspect of diatom cell morphology is that plastids are surrounded by four rather than two membranes with the consequence that all nuclear-encoded plastid proteins have to cross four membranes (Gibbs 1979). The same is true for the exchange of metabolites between plastids and the cytoplasm. There is still little knowledge on the sulfur uptake and assimilation (Bromke and Hesse 2013; Kopriva et al. 2008). To shed more light on the biosynthesis of methionine in the model diatom T. pseudonana, we have performed a detailed phylogenetic analysis of each enzyme from the methionine biosynthesis pathway in this organism. In addition, we have addressed a subcellular localization question in order to present possible models of the pathway.
The compartmentation of sulfate assimilation and methionine synthesis is an intriguing aspect in understanding S-assimilation and methionine synthesis. While sulfate activation takes place in the cytosol and in plastids, OAS and cysteine are synthesized in all three compartments: cytosol, plastid, and mitochondria (Hesse et al. 2004; Krueger et al. 2009). In photosynthetic eukaryotes, sulfate reduction is confined to plastids (Brunold and Schiff 1976; Hesse et al. 2004), the same as the synthesis of cystathionine and homocysteine. Arabidopsis contains three functional isoforms of the cobalamin-independent (CIMS) enzyme. One of them is located in chloroplasts and is devoted to the de novo synthesis of methionine. The two other methionine synthase isoforms in Arabidopsis are located in the cytosol and most probably are responsible for the regeneration of methionine by re-methylation of homocysteine (Ravanel et al. 2004).
To shed more light on the structure of methionine synthesis genes in T. pseudonana as well as to put them in the evolutionary context, we have performed a phylogenetic analysis on eight sequences. These sequences and additional enzyme sequences from homoserine and glutathione synthesis pathways were analyzed to investigate their subcellular localization.
Results and discussion
Identification of methionine biosynthesis pathway proteins in Thalassiosira pseudonana
Predicted target peptides of selected proteins of Thalassiosira pseudonana
Aspartate semialdehyde dehydrogenase
A Maximum Likelihood algorithm implemented in the PhyML software was used to investigate phylogenetic relationships between T. pseudonana protein sequences and their eukaryotic and prokaryotic homologues. A limited species number as representatives of different phyla was selected (listed in Methods). For generation of phylogenetic trees homoserine acetyltransferase, cystathionine γ/β-synthase-like proteins, methionine synthase, and S-adenosylmethionine synthetase orthologues were used. In case of pyridoxal phosphate-dependent enzymes (cystathionine metabolism enzymes) the respective phylogenetic tree was used to predict enzymatic activity of analyzed proteins.
Prediction of intracellular localization
On the basis of the obtained amino acid sequences, the subcellular localization of proteins involved in sulfur assimilation and methionine synthesis was predicted. In the C-terminal parts of analyzed proteins no motifs responsible for retention in the endoplasmic reticulum (KDEL, DEEL or DDEL) were found. Location assignment was performed with TargetP software and it is based on the predicted presence of N-terminal mitochondrial targeting peptide (mTP) or secretory pathway signal peptide (SP). Additionally, the protein sequences were analyzed for any N-terminal sequences longer than 15 amino acids in front of conserved catalytic domains. These pre-sequences might form specific diatomal targeting peptides, which are not recognized by the used software. The results of the prediction are presented in Table 1. The prediction reliability values are a scale from 1 to 5, where 1 indicates the strongest prediction.
Out of analyzed sequences six show a pre-sequence that could be used by the cellular machinery to traffic the proteins to the respective compartment. In two aspartate kinase genes we have detected sequences which according to the used software, would direct these proteins into secretion via endoplasmic reticulum. Due to the evolutionary history of diatoms, the cells of these organisms contain plastids surrounded by additional two layers of plasma membrane, from which the outermost membrane is continuous with the endoplasmic reticulum (Gibbs 1979). The result suggests that these enzymes are directed to the plastid. In fact, we have detected in both aspartate kinase sequences N-terminal bipartite pre-sequences, which consist of a signal and a transit peptide-like domain responsible for directing the nuclear-encoded protein into diatomal chloroplast. As demonstrated experimentally by means of a heterogeneous protein expression system in diatom P. tricornutum, presence of a conserved amino acid motif at the SP cleavage site (ASA-FAP) is associated with plastid-localized proteins (Gruber et al. 2007; Kilian and Kroth 2005). The aspartate kinase sequences do not have the exact ASA-FAP sequence, but contain phenylalanine in the 4th position of the predicted cleavage motif. It has been shown that phenylalanine in this position is crucial for successful transfer to the plastid. In some cases phenylalanine (F in the motif sequence) can be exchanged by other bulky amino acid—tryptophan, tyrosine or leucine (Gruber et al. 2007). Phenylalanine and valine were found in pre-sequences of two genes of the sulfur reduction pathway in diatoms (Bromke and Hesse 2013). One should note that this process in phototrophs takes place exclusively in plastids.
There are four sequences that are predicted to be directed into mitochondria: cystathionine β-lyase-like, homoserine kinase, γ-glutamylcysteine synthetase and methionine γ-lyase-like (Table 1). The prediction reliability values are as low as 5, with an exception for methionine γ-lyase-like, in which case the prediction reaches the class 3. In plants reactions of homoserine phosphorylation by homoserine kinase as well as the downstream synthesis of cystathionine and homocysteine are localized to plastids (Hesse and Hoefgen 2008), whereas these processes take place in the cytosol of fungi (Marzluf 1997). Moreover, methionine-γ-lyase in Arabidopsis thaliana is a cytosolic enzyme (Rebeille et al. 2006). Thus, the prediction of localization of these proteins seems not to be accurate. In animals and fungi γ-glutamylcysteine synthetase and glutathione synthetase gene products are localized to the cytosol (Griffith 1999; Pócsi et al. 2004). In plants, due to the transcript heterogeneity, the synthesis of the glutathione can take place in chloroplast and in cytosol depending on the length of the respective gene transcript (Wachter et al. 2005). Database searches revealed the presence of putative TP sequences for maize γ-glutamylcysteine synthetase and glutathione synthetase proteins (Wachter et al. 2005), despite absence of plastidic TP in cDNA clones reported by Gómez et al. (2004). There is only one sequence of γ-glutamylcysteine synthetase in the genome of T. pseudonana, but it is incomplete as it lacks a starting ATG codon. The gene model of γ-glutamylcysteine synthetase shows high similarity to heteroconts and less to animal sequences. Taking this into consideration, we suggest that the enzyme is localized to the cytosol although TargetP predicts a mitochondrial localization (weak, class 5 prediction). On the other hand, the analysis of the identified glutathione synthetase sequence resulted in a strong score suggesting its cytosolic location of the enzyme. Thus, the glutathione synthesis takes place in the cytosol and is subsequently transported to other cell compartments for biochemical functions.
Analysis of phylogenetic relationship of Thalassiosira pseudonana genes
Phylogenetic analysis of enzymes involved in the transacetylation of homoserine
Phylogenetic analysis of enzymes involved in the phosphorylation of homoserine
The activation of homoserine for synthesis of homocysteine can be done by the phosphorylation of the gamma-hydroxyl group as well. This reaction is catalyzed by the special enzyme homoserine kinase (HSK). The T. pseudonana genome contains only one copy of the HSK (Thaps3: 28592). In the genome of Cyanidioschyzon merolae, the red algae model organisms, no homoserine kinase gene model could be found. Nevertheless, the genome of C. merolae contains genes annotated as aspartate kinase/homoserine dehydrogenase as well as threonine synthase—enzymes producing substrate for HSK and using O-phosphohomoserine (OPH). The synthesis of OPH is the only way of homoserine activation in plants and green algae (Hesse and Hoefgen 2003).
Phylogenetic analysis of enzymes catalyzing the formation of methionine precursors
Due to their high similarity it is impossible to distinguish cystathionine γ/β-synthases from cystathionine β/γ-lyases solely on basis of their sequences. Both types of enzymes utilize pyridoxal 5′-phosphate (PLP) as cofactor in reactions of cystathionine synthesis and/or lysis. A similar catalytic domain can be found in methionine γ-lyase (MgL), also a PLP-dependent enzyme. MgL is a promiscuous enzyme, which catalyses a number of α/γ- and α/β-elimination reactions on methionine and cysteine derivatives. It also catalyses the γ-replacement reaction of the thiomethyl group of substrates such as methionine, homocysteine and ethionine to yield the corresponding S-substituted homocysteine derivative (Lockwood and Coombs 1991). The enzyme has been found and characterized in various bacteria (Dias and Weimer 1998; Faleev et al. 1996; Inoue et al. 1995; Manukhov et al. 2005), protozoans like Trichomonas vaginalis (McKie et al. 1998), and Entamoeba histolytica (Tokoro et al. 2003), and in Arabidopsis (Rebeille et al. 2006). The predicted plant protein has 28–32% identity (48% similarity) with methionine γ-lyase from Pseudomonas putida and E. histolytica, respectively (Rebeille et al. 2006).
Phylogenetic analysis of methionine synthase and SAM synthetases
Analysis of the up-stream DNA sequences of methionine metabolism genes
Predicted conserved motifs in 15 putative promoters of T. pseudonana genes
Aspartate semialdehyde dehydrogenase
Presence of different transcription controllers enables integration of various stimuli and proper response on the level of gene expression. This includes binding of different transcription factors to different DNA-binding sites within a promoter and binding of different members of a transcription factors family to one site in a promoter. In budding yeast, Saccharomyces cerevisiae, organic sulfur metabolism is regulated by the Met4 transcriptional system (Lee et al. 2010). The Met4 cannot bind to DNA but through protein–protein interaction with either of two highly similar DNA-binding proteins, Met31p and Met32p, or with a homodimer of Cbf1 proteins. Met31p and Met32p are C2H2-type zinc finger proteins which bind to consensus motif AAACTGTGG found in 5′-upstream of several genes of the sulfur metabolism in yeast (Blaiseau et al. 1997). The Cbf1 (centromere-binding factor 1) is a basic helix-loop-helix protein, which forms homodimers to bind to sites with consensus CACGTG core present at MET gene promoters (Kuras et al. 1996). This makes it to one of main activators of methionine metabolism and glutathione synthesis genes in yeast. Very little is known about the transcriptional regulation of gene expression in diatoms (Upper 1974). In genomes of T. pseudonana and P. tricornutum as much as 46 and 40 zinc finger transcription factors were identified, respectively. These belong to three types: C2H2, CCCH and TAZ type (Rayko et al. 2010). Neither, Met4p nor Met31p/Met32p yeast orthologs were found in the genome of T. pseudonana. Though, it can not be excluded that the regulation of the sulfur metabolism in this diatom might rely on similar conserved mechanism, including conserved protein binding sites in the promoter regions of the involved genes, as in unicellular organisms like yeast.
Our goal in this study was to identify core features enabling to predict potential exchanges between species and localisation of proteins in order to get insight into the localization of cysteine and methionine pathways in diatoms. Due to the fact that relatively few sequences are known from diatom species, current subcellular localization prediction algorithms are not capable to assign some of the tested protein sequences to their compartments. In most cases it was possible to identify the signal and transit peptide-like domains in sequences of proteins localized to plastids, which was based on the previous observations made in other organisms. However, in other cases the prediction of the localization of proteins known to be targeted to plastids was not possible, which might be caused by modified and/or adapted signal peptides allowing crossing four membranes into the lumen of plastids.
The analysis of gene sequences encoding enzymes of the methionine synthesis pathway revealed that the predicted proteins are specific for algae of the chromalveoates or heterokont type. The homology of the tested proteins drops down comparing the algae proteins with orthologous proteins from plants and even more when compared to bacterial or cyanobacterial proteins. In consequence, the results mirror the distinct evolutionary path of diatoms.
The homology search made it possible to identify two enzymes, HSK and HAT, utilizing homoserine as precursor to direct this compound into pathways forming either threonine or homocysteine, respectively. The analysis does not allow to rule out that similar to yeast acetylated homoserine is the acceptor for reduced sulfur from sulfur assimilation pathway. To proof this finding and specify the true catalytic properties of the PLP-enzymes (CbL-like, CgS-like, and MgL-like) further biochemical studies have to be done. Moreover, the identification of a common motif in promoter regions of 15 genes involved in methionine metabolism of T. pseudonana suggests evolutionary conservation of the regulatory mechanism of the pathway. This finding, together with the homoserine acetyltransferase gene supports the hypothesis of the residual “fungal-type” of sulfur amino acids biosynthesis pathway in diatoms (Bromke and Hesse 2013). Phylogenetic consideration revealed that in T. pseudonana methionine synthase represents the MetH type of identified methionine synthases requiring cobalamin as cofactor. The cobalamin auxotrophy in T. pseudonana is probably the basis for a symbiotic relationship with cobalamin-producing bacteria.
The intensive analysis of the N-terminal site of methionine synthase protein could not identify a transit peptide and thus the result strongly suggests that the synthesis of methionine takes place in the cytosol, which would be in concordance with methionine synthesis in plants. It is likely that during the evolution T. pseudonana lost its cobalamin-independent enzyme. On the other hand SAM synthetase 1 seems to be retained from the phototrophic ancestor algae, whereas the SAMS 2 is a legacy of the heterotrophic ancestor-host cell.
Diatoms are fascinating organisms and studying their biology will bring many interesting observations and conclusions. Sequencing more and different diatoms will help increase our knowledge and to refine the prediction algorithms in order to get insight into diatoms metabolism.
Amino acid sequences of annotated sulfur metabolism gene models of T. pseudonana were used as queries to perform protein–protein BLAST (Altschul et al. 1997) in order to identify the orthologous genes from other organisms. The search was restricted to a set of organisms representing different prokaryotic and eukaryotic organisms: E. coli, Bacillus sp., Synechococcus sp., Nostoc sp., P. tricornutum, E. huxlei, A. anophagefferens, Ostreococcus sp., C. reinhardtii, Phytophthora sp, Selaginella moelendorffi, Physcomitrella patens, A. thaliana, Oryza sativa, Porphyra purpurea, C. merolae, Monosiga brevicollis, Dictyostelium discoideum, and T. cruzi. Hit-results with E value >1e−10 were discarded. The protein sequences obtained from blastp were than analyzed by use of NCBI Conserved Domain Search (http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi) (Marchler-Bauer et al. 2005) for presence of conserved domains. Additionally, InParanoid7 (http://inparanoid.sbc.su.se/) was used to verify orthology of eukaryotic sequences (Ostlund et al. 2010).
The protein sequences of C. merolae were obtained from ‘C. merolae Genome Project’ (http://merolae.biol.s.u-tokyo.ac.jp). Sequences of T. pseudonana, P. tricornutum, S. moellendorffii, E. huxlei, P. sojae, A. anophagefferens, M. brevicollis proteins were acquired from Joint Genome Institute sequencing projects (http://genome.jgi-psf.org). The protein sequences from D. discoideum were obtained from dictyBase (http://dictybase.org). Sequences of proteins from T. cruzi were obtained from GeneDB (http://www.genedb.org). Sequences from other organisms were retrieved from GeneBank (http://blast.ncbi.nlm.nih.gov/Blast.cgi).
Analysis of DNA and protein sequences
Target peptides were sought within amino acid sequences upstream of conserved catalytical domains of proteins of interest. To identify N-terminal extensions from the conserved regions of the proteins, sequences were analyzed with use of NCBI Conserved Domain Search (http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi) (Marchler-Bauer et al. 2005). Prediction of subcellular localization was performed with TargetP 1.1 online software (http://www.cbs.dtu.dk/services/TargetP/). The analysis of sequences longer than 15 amino acids for presence of N-terminal motifs was performed as described in Emanuelsson et al. (2007). Settings were as follows: non plant organisms; prediction of cleavage site and without cut-offs. The output contains final Neuronal Networks scores (NN) (Nielsen et al. 1997) on which the prediction is based. The scores are not probabilities. However, the location with the highest score is the most likely according to TargetP. Each prediction has its reliability class (RC) expressed in number from 1 to 5, where 1 indicates the strongest prediction. Results of the analysis as well as conserved domain starting position are presented in Table 1. Presence of ER retention motifs in analyzed sequences (KDEL, DEEL or DDEL) was verified manually.
The detection of conserved motifs in DNA sequences of the up-stream regions of the T. pseudonana methionine metabolism genes was performed using an online tool MEME (http://meme-suite.org/meme/). The motif search was defined by following parameters: three best results, expected length 6–12 nt, occurrence once or none, ten sequences as a negative set. The sequences used in the analysis were obtained from T. pseudonana genome repository (http://genome.jgi-psf.org/Thaps3/Thaps3.home.html). The length of the DNA promoter region sequence of a gene was chosen to be longer than the half of a region between two ORFs (including UTRs). 5′-UTR, as defined by the repository, was included in the input data. In cases of longer stretches of DNA between genes 1,000 nt-long sequences were retrieved. The lengths, not including UTRs, are given in Table 2. The negative set, which served to verify the MEME results, composed of 5′-regions (500 nt + 5′-UTR) of ten non-sulfur-related proteins: actin-related protein, nitrate reductase, GAPDH, HSF60, citrate synthase, LHCr1, galactose kinase, MAP kinase, ubiquitin, tubulin, lipase. The results of the MEME analysis were applied to TOMTOM (http://meme-suite.org/tools/tomtom), which is the online software performing comparison of given motifs with available databases. Comparisons with plant (Jaspar 2014), prokaryotic (Prodoric 8.9) and yeast (MacIsaak v.1) databases were performed using default settings. The sequence-logo graphics was generated by the TOMTOM.
Phylogenetic trees were inferred using Phylogeny.fr (http://www.phylogeny.fr)—an on-line software package for sequence analysis (Dereeper et al. 2008). Sequences were aligned with MUSCLE 3.7 (Edgar 2004) and curation of the alignments was done with Gblocks 0.92 (Castresana 2000) using following settings:(a) conserved position: in at least half the number of sequences + 1; (b) flank position: at least 85% of the number of sequences; (c) maximum number of contiguous nonconserved positions: 8; (d) 10 amino acids as minimum length of a block; (e) now gaps allowed. The phylogenetic trees were reconstructed using the maximum likelihood method implemented in the PhyML program (v3.0 aLRT) (Guindon and Gascuel 2003). WAG substitution method was used as default. The bootstrapping procedure was replaced by an approximate likelihood-ratio test (aLRT) (Anisimova and Gascuel 2006). The test’s accuracy and power in comparison to the bootstrapping was discussed by Anisimova et al. (2011). Support values are presented at the nodes with a good statistics threshold set to 0.8. FigTree 1.3.1 software (http://tree.bio.ed.ac.uk/software/figtree/) was used to generate graphics.
MAB conduct the analysis, prepared the manuscript; HH prepared the manuscript. Both authors read and approved the final manuscript.
Prof. Dr. Lothar Willmitzer and Dr. Stefanie Hartmann are acknowledged for help and support in conducting the research.
Financial support was provided by Max‐Planck Society and Deutsche Forschungsgemeinschaft and is greatly acknowledged.
Compliance with ethical guidelines
Competing interests This work was supported by Max Planck Society and Deutsche Forschungsgemeinschaft (Grant number HE 3088/4). The authors declare that they have no competing interests.
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