Molecular evolution and the role of oxidative stress in the expansion and functional diversification of cytosolic glutathione transferases
© da Fonseca et al; licensee BioMed Central Ltd. 2010
Received: 31 March 2010
Accepted: 15 September 2010
Published: 15 September 2010
Cytosolic glutathione transferases (cGST) are a large group of ubiquitous enzymes involved in detoxification and are well known for their undesired side effects during chemotherapy. In this work we have performed thorough phylogenetic analyses to understand the various aspects of the evolution and functional diversification of cGSTs. Furthermore, we assessed plausible correlations between gene duplication and substrate specificity of gene paralogs in humans and selected species, notably in mammalian enzymes and their natural substrates.
We present a molecular phylogeny of cytosolic GSTs that shows that several classes of cGSTs are more ubiquitous and thus have an older ancestry than previously thought. Furthermore, we found that positive selection is implicated in the diversification of cGSTs. The number of duplicate genes per class is generally higher for groups of enzymes that metabolize products of oxidative damage.
1) Protection against oxidative stress seems to be the major driver of positive selection in mammalian cGSTs, explaining the overall expansion pattern of this subfamily;
2) Given the functional redundancy of GSTs that metabolize xenobiotic chemicals, we would expect the loss of gene duplicates, but by contrast we observed a gene expansion of this family, which likely has been favored by: i) the diversification of endogenous substrates; ii) differential tissue expression; and iii) increased specificity for a particular molecule;
3) The increased availability of sequence data from diversified taxa is likely to continue to improve our understanding of the early origin of the different cGST classes.
Glutathione transferases (GSTs; EC 22.214.171.124) comprise a superfamily of genes encoding ubiquitous enzymes that are very important in the clinical outcome of cancer therapy because they metabolize and inactivate cancer agents (in particular four classes of GST, alpha, mu, pi and theta) [1, 2]. Furthermore, the interaction of GSTs with pesticides and pollutants makes them an interesting target for protein engineering in plants . The general role of GSTs in detoxification and the metabolism of xenobiotics has been well documented (reviewed in [3–7]), and makes GSTs a promising subject for evolutionary analyses, especially considering temporal fluctuations in toxic chemicals in the environment.
GSTs are an excellent example of how multiple gene duplication events involving further sub- or neofunctionalization has resulted in groups of enzymes with a myriad of functions. Their occurrence either as homodimers or heterodimers further increases the diversity of the GSTs catalytic activities, which are all centered on chemical reactions that use the tripeptide glutathione (GSH). GSTs are involved in metabolic detoxification of reactive electrophiles, the biosynthesis of leukotrienes, prostaglandins, testosterone and progesterone, and in the degradation of tyrosine [3, 5]. Furthermore, some GSTs have also been attributed non-enzymatic regulatory roles [8, 9].
GSTs also have noncatalytic roles that include binding (covalently and noncovalently) dangerous chemicals and biomolecules such as bilirubin and hormones [5, 14]. Binding to reactive electrophiles is thought to be important for preventing DNA damage whereas for other molecules GSTs act as intracellular carriers [5, 14].
Distribution of cGSTs that are present in mammals in major taxa (sequences obtained from GenBank; details in Table 1 in Additional file 1).
In this work, we used Bayesian and maximum likelihood-based molecular phylogenetics approaches to ascertain the overall evolutionary pattern in cGSTs. We then focused on mammalian cGSTS and their natural substrates in order to determine if the role of GSTs in detoxification is the major force driving the expansion of this gene family, as it has been suggested [3, 5]. More than 20 mammalian cGSTs have been identified to date, many metabolizing the same substrates, especially those substrates of anthropomorphic origin. This catalytic promiscuity probably enhances the formation of duplicates, increasing the probability that duplicated genes become fixed in a population, as adaptation will promote reactions that are already catalyzed by the enzyme . We therefore tested available sequence data for the existence of positive selection using both gene and protein based statistical approaches. Although positive selection has been mostly detected in genes involved in host-pathogen interactions, it has also been shown to influence the active site of enzymes and protein-protein interfaces in membrane receptors [17–19]. The gene-based approach is based on the idea that nonsynonymous substitutions may influence the fitness of an individual or population. Thus, adaptive molecular evolution may cause the nonsynonymous substitution rate (dN) to be higher than the synonymous rate (dS), with the ratio ω (dN/dS) being higher than 1 . Likelihood ratio tests (LRTs) implemented in PAML were used to identify genes under positive selection (ω >1) by comparing two probabilistic models of variable ω ratios among sites, the simpler of which does not allow sites with ω >1 and a more general which does . ConTest was used to measure evolutionary rates in protein sequences accounting for the variation of specific biochemical properties, like volume, polarity and charge . Finally, we intertwined the results from the evolutionary analyzes with information regarding the functions of the different classes of cGSTs, and concluded that the activity of cGSTs on endogenous substrates is sufficient to explain the overall expansion pattern of this subfamily.
Results & Discussion
Biological information about the bacterial species present in Figure 3.
Bacteria; Cyanobacteria; Chroococcales; Crocosphaera
Crocosphaera watsonii is a diazotroph that contributes to the global cycling of nitrogen and carbon through the fixation of atmospheric nitrogen and photosynthesis
Bacteria; Proteobacteria; Alphaproteobacteria; Rhizobiales; Bradyrhizobiaceae; Rhodopseudomonas
Rhodopseudomonas bacteria are purple nonsulfur phototrophic organisms that can be found many types of marine environments and soils. It converts sunlight into energy and converts atmospheric carbon dioxide into biomass. R. palustris can degrade and recycle several aromatic compounds that make up lignin, which makes it useful in removing this type of waste from the environment. In addition, R. palustris converts N2 into NH4 and H2 (used as a biofuel)
Rhizobium sp. NGR234
Bacteria; Proteobacteria; Alphaproteobacteria; Rhizobiales; Rhizobiaceae; Rhizobium/Agrobacterium group; Rhizobium.
Rhizobium sp. strain NGR234 is a unique alphaproteobacterium (order Rhizobiales) that forms nitrogen-fixing nodules with more legumes than any other microsymbiont.
Bacteria; Proteobacteria; Alphaproteobacteria; Rhizobiales; Methylobacteriaceae; Methylobacterium.
Aerobic, facultatively methylotrophic, legume root-nodule-forming and nitrogen-fixing bacteria
Bacteria; Proteobacteria; Gammaproteobacteria; Enterobacteriales; Enterobacteriaceae
Gram negative bacterium that is commonly found in soil, water, and sewage. It is an opportunistic pathogen seen in patients with severe burns or long-term indwelling urinary catheters. In animals P. stuartii infections can cause neonatal diarrhea due to P stuartii infection in dairy cows.
Bacteria; Proteobacteria; Gammaproteobacteria; Oceanospirillales; Hahellaceae; Hahella
Marine bacteria that produces an algicidal agent (capable of killing phytoplankton, marine eukaryotic microalgae). Suggested as useful for managing algal blooms.
Bacteria; Proteobacteria; Gammaproteobacteria; Vibrionales; Vibrionaceae; Vibrio
Vibrio shilonii was isolated from the coral Oculina patagonica in the Mediterranean Sea. This organism cause bleaching (loss of the coral endosymbiotic zooxanthellae). This disease only occurs at elevated seawater temperatures.
Bacteria; Proteobacteria; Deltaproteobacteria; Myxococcales; Sorangiineae; Polyangiaceae; Sorangium
Soil-dwelling Gram-negative bacteria of the group myxobacteria. It plays an important role in soil ecology by its ability to degrade cellulosic materials.
Bacteria; Proteobacteria; Deltaproteobacteria; Myxococcales; Cystobacterineae; Myxococcaceae; Myxococcus
Found almost ubiquitously in soil, consists of thin rod shaped, gram-negative cells that exhibit self-organizing behavior as a response to environmental cues. Starving bacteria can self-organize to form dome shaped structures (swarms) of approximately 100,000 cells that, over the course of several days, differentiate into metabolically quiescent and environmentally resistant myxospores.
The N-terminal domain contains residues that are critical for activation of the sulfhydryl group of GSH. Its structure is quite conserved when compared to the substrate binding C-terminal domain (Figure 1C). Conservation in the C-terminal domain is apparent between the elements of the more recently evolved and closely related classes (alpha, mu, pi and sigma), which is in line with their overlapping substrates specificities.
Positive selection analysis on mammalian sequences using site models M7 and M8 in PAML  (probabilistic models of variable w ratios among sites, the simpler M7 which does not allow sites with w >1 and the more general which does M8).
p value (M7 vs M8)
isoform 1 (8)
isoform 2 (8)
isoform 1 (8)
isoform 2 (6)
Functional diversification and asymmetrical family expansion
Sites under positive selection detected by the BEB approach in PAML (bold, PP >0.9) and by ConTest (underlined, p < 0.05).
Experimentally confirmed functional relevance
G, A, V, I, T
C-terminal domain interface
G, N, Q, K, E, H
substrate binding pocket
A, V, L, I, T, F
substrate binding pocket
G, L, M, T, N, E
substrate binding pocket
G, A, L, I, T, R
substrate binding pocket
V, L, I, T, F, Y , H
Residue 110 
I, C, M, T, D, K
G, Q, R, K, E
substrate binding pocket
Q, K, E
G, A, T, S, Q, E
substrate binding pocket
L, I, M, Q, R
substrate binding pocket
V, L, E, K, R,
N-terminal domain interface
substrate binding pocket
A, S, K, R, E
substrate binding pocket
A, V, L, M, T, D, E, P
G, A, L, M, S, T, N
A, S, N, Q, K, Y
Residue 210 
substrate binding pocket
V, I, M, T, Q, K, F, H
I, M, T, N, K, R, E, D
A, L, C, T, D
The expansion of the cGSTs was particularly profuse, but as we can see in mammals, not all the resulting classes of enzymes have duplicated extensively. For example, sigma and zeta cGSTs are involved in pathways that require a more precise regulation, and for which the existence of a duplicate could have been harmful. GSTZ is a key enzyme in the metabolic degradation of phenylalanine and tyrosine and its product can cause the fatal hereditary disease tyrosinemia type I . GSTS produces prostaglandin D2  (prostaglandins are lipid mediators that are involved in the regulation of the respiratory, cardiovascular, central nervous system (CNS), genitourinary, endocrine, and immune systems). In contrast, alpha, mu and theta cGSTs are all involved in the cellular reaction under stress conditions, and have multiple duplicates (up to seven, five and four duplicates for alpha, mu and theta classes, respectively, compared to only one isoform in e.g. sigma and zeta classes) that probably contributed to an increase in fitness by the elimination of a broader range of reactive and harmful chemicals, especially through variation in the substrate binding pocket. Changes of a hypervariable site in this region have been shown to have a central role in defining enzyme specificity . Our hypothesis is thus supported by evidence of several positively selected sites in the substrate binding pocket (Table 5).
The catalytic promiscuity of GSTs has certainly facilitated the process of neofunctionalization and duplicate gene retention for the most populated cGST classes. We further suggest that subsequent loss of duplicates arising from functional redundancy was probably avoided by variation in tissue expression (e.g. human GSTA3 is expressed solely in steroidogenic tissues and GSTM3 is selectively expressed in testis and brain ) and increased specificity for a particular molecule (such as GSTO1 that has an improved efficiency in metabolizing arsenic, see above).
Glutathione transferases enzymes represent a superfamily with many functional roles throughout evolution. This work has revealed that cGSTs are a lot more ubiquitous and old than previously thought, with many cGSTs classes having a bacterial isoform. The need for protection against the products of oxidative damage has no doubt driven the expansion of the family via positive selection on GST duplicates, but on the way GSTs have acquired many other roles such as the metabolism of sex hormones and the regulation of apoptosis, which likely were vital for the retention of duplicates. The metabolism of dangerous xenobiotics is also a major role of GSTs and has been suggested to be driving the expansion of the family. In fact, times when changes in the levels and the toxicity of environmentally available chemicals have occurred, the catalytic promiscuity and an elevated number of sGST isoforms would have constituted a fitness advantage. However, the functional redundancy towards many of these chemicals would eventually lead to a loss in the number of cGST isoforms. We suggest that the expansion of the cGST family was strongly favored by the fact that the different isoforms within a class have acquired new functions towards endogenous substrates. We hypothesize that these roles dictate the number of duplicates per class, being more abundant for classes involved in the metabolism of product of oxidative stress (alpha, mu and theta), but reduced to one when related with tightly regulated biological processes (such is the case for class zeta involved in the metabolism of the aromatic amino acids tyrosine and phenylalanine). The need for duplicates with sometimes overlapping substrate specificities is further supported by differences in tissue specificity and the increase of specificity for a particular reaction that is weakly catalyzed by other isoforms.
Presently it is still difficult to ascertain the most ancient class of cGSTs, with theta and omega being the best candidates. Nevertheless, the information arising from whole-genome sequencing of an increasing number of non-mammalian species will certainly provide further insight into the origins and evolution of this ancient gene family.
Materials and methods
Because of the high sequence divergence of cGSTs, amino acid multiple sequence alignments were done using protein structure information in 3D-Coffee  and PROMALSD (see Additional Files 2 and 3 for the alignments used to build the trees presented on Figures 2 and 3, respectively). The codons in the nucleotide alignment were aligned accordingly. We have chosen a limited number of representative sequences for all clades (the insect epsilon class is omitted as it forms a clade with the delta class). DAMBE and MEGA4 were used for sequence editing and formatting [34, 35].
We have built the various phylogenetic trees based on the nucleotide and amino acid alignments using MrBayes  and PhyML  after determining the optimal model of sequence substitution with Modeltest 3.04 (TVM+I+G)  and Prottest (JTT+I+G) . One cold and four incrementally heated chains were run for 2,000,000 generations with chains I = 2, 3, 4, and 5 incrementally heated with heat being 1/(1+[i-1]T) and T = 0.2. Following a burn-in of 500,000, trees were sampled every 100 generations (well after the chain reached stationarity) and 15,000 trees were used for inferring Bayesian posterior probability. The nucleotide tree was obtained after removal of the third codon position. The trees obtained with PhyML are presented in Figure 2 in Additional file 1. All trees were drawn in FigTree http://tree.bio.ed.ac.uk/software/figtree/.
Likelihood ratio tests (LRTs) implemented in PAML  were used to identify genes under positive selection. These tests are used to identify adaptive molecular evolution which occurs when the nonsynonymous substitution rate (dN) is higher than the synonymous rate (dS), with the ratio ω (dN/dS) being higher than 1 . The LRTs used compare two probabilistic models of variable ω ratios among sites, the simpler of which does not allow sites with ω >1 and a more general which does  (model M7 vs M8). Amino acid sites under positive selection were detected with Bayesian empirical bayes (BEB) inference under the M8 model in PAML , and with CONTEST, that assesses protein changes in biochemical constraints to calculate evolutionary rates . CONTEST accounts for the variation of specific biochemical properties, like volume, polarity and charge and presents a new statistical method based on the comparison of two-rate measures where a site is considered constrained for a given property if it shows high conservation relatively to its total evolutionary rate (some positions may be constrained while having a high substitution rate, provided these substitutions do not affect the biochemical property under constraint). CONTEST can also be used to infer positively selected positions, as it looks for sites that have experienced more nonconservative substitutions than expected by chance under the neutral hypothesis. Sequence alignments were built to perform the positive selection test. For classes where orthology/parology was difficult to assign, tests were done using sets of genes existing in single species (human, macaque, mouse and rat; Table 4 and Table 5).
Multiprot  was used to calculate the root mean square deviation (RMSD) between C-alpha atoms of cGST structures (Table 2 in Additional file 1). Neighbor-joining trees were obtained from the corresponding distance matrices in PAUP .
List of abbreviations used
Haliotis discus discus
Rhizobium sp. NGR234
RRF was funded by FCT (SFRH/BPD/26769/2006). This work was funded in part by the Portuguese Foundation for Science and Technology (FCT) project PTDC/BIA-BDE/69144/2006 and PTDC/AAC-AMB/104983/2008.
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