Tracking the connection between evolutionary and functional shifts using the fungal lipase/feruloyl esterase A family
© Levasseur et al; licensee BioMed Central Ltd. 2006
Received: 06 July 2006
Accepted: 08 November 2006
Published: 08 November 2006
There have been many claims of adaptive molecular evolution, but what role does positive selection play in functional divergence? The aim of this study was to test the relationship between evolutionary and functional shifts with special emphasis on the role of the environment. For this purpose, we studied the fungal lipase/feruloyl esterase A family, whose functional diversification makes it a very promising candidate.
The results suggested functional shift following a duplication event where neofunctionalisation of feruloyl esterase A had occurred with conservation of the ancestral lipase function. Evolutionary shift was detected using the branch-site model for testing positive selection on individual codons along specific lineages. Positively selected amino acids were detected. Furthermore, biological data obtained from site-directed mutagenesis experiments clearly demonstrated that certain amino acids under positive selection were involved in the functional shift. We reassessed evolutionary history in terms of environmental response, and hypothesized that environmental changes such as colonisation by terrestrial plants might have driven adaptation by functional diversification in Euascomycetes (Aspergilli), thus conferring a selective advantage on this group.
The results reported here illustrate a rare example of connection between fundamental events in molecular evolution. We demonstrated an unequivocal connection between evolutionary and functional shifts, which led us to conclude that these events were probably linked to environmental change.
During evolution, new functions are acquired as a consequence of an accumulation of substitutions that alters the coding or regulatory sequences of genes. These evolutionary events are a key factor driving functional shift at transcriptional or biochemical level as well as shifts in sub-cellular localisation. There may be a range of knock-on effects on descent, ranging from no phenotypic novelty to whole new developmental processes such as those triggered by the cascades of gene expression in the case of neo-expression of a master regulator gene . It is a major challenge to establish whether these mutations are fixed into a population by neutral genetic drift or via positive selection, and thereby evaluate the impact of the environment on this fixation. However, the literature reports very few unambiguous connections between changes in amino acid substitution rate (evolutionary shift) and functional shifts, and the role played by the environment is often limited to speculative discussion. Depending authors suggest different criteria are required for establishing a relationship, thus leading to different levels of confidence. Fundamental criteria for studying molecular adaptation during protein evolution would consist in i) detecting evolutionary and functional shifts, ii) linking the sites under positive selection to the functional changes, iii) reassessing these evolutionary events in terms of response to environmental context, iv) studying whether the novelty confers a selective environmental advantage, and v) studying whether functional convergence occurred under the same environmental changes. At present, the most commonly cited examples of adaptation involve the relationships between particular phenotypic shifts in response to a given environmental change, and many of these studies either did not conduct evolutionary analysis or failed to detect positive selection [2, 3]. It is important to confirm that the sites identified as being under positive selection are actually involved in the functional novelty before a clear positive selection-driven connection can be established between evolutionary and functional shifts. Thereafter, the next step is to identify the impact of environment context in these events and establish whether the functional novelty responds to the environmental change and confers a selective advantage for the species. To our knowledge, only a few examples of functional gain fulfil all these criteria. The best studies stem from human artificial selection (antibiotic, herbicide, and insecticide resistance genes) where resistance to drugs is essential for survival [4, 5]. To date, the full set of criteria listed above has only been demonstrated for artificial selections such as drug resistance and for one natural case concerning the digestive RNases in Asian and African leaf monkeys . The case of RNaseI from ruminants also offers a strong example, with the novel biochemical function (i.e. the ability to digest single-stranded RNA at low pH) attributed to positively-selected sites . This functional shift probably occurred in response to the acquisition of herbivory which conferred an advantage for ruminants eating grass. The examples of the retinal-binding membrane protein proteorhodopsin in marine bacteria, where positively-selected sites play a critical role in spectral light absorption, should also be highlighted since it illustrates how the distribution of different λ max is correlated to harvest depth, thus confirming an environmental link . Finally, there are other examples where positively-selected sites are involved in the functional shift but without there being a clear link with the environmental shift [9–12].
Evolutionary shift is usually detected by estimating the rates of synonymous and nonsynonymous substitutions (ω = dN/dS) with ω = 1, < 1 and > 1 indicating neutral evolution, purifying selection and positive selection, respectively [13, 14]. Given the strong selective pressure they are subjected to, many amino acids are not replaced, and adaptive evolution only operates at a few sites over a relatively short evolutionary period. A model that allows ω ratio to vary among sites and lineages was therefore developed to improve the detection of positive selection [13, 15, 16]. This model is specifically designed to analyse the evolution of gene families where functional divergence may have caused adaptive evolution. The detection of functional shift often hinges on preliminary experimental assays. However, there are databases containing experimental records that be retrieved automatically and then used to search for and detect functional divergence in large-scale studies of multigenic families.
In the present study, we tested the robustness of the connections between evolutionary and functional shifts, focussing specifically on the role of the environment. The objective was to conduct a comprehensive analysis of the multigenic families in which functional divergence has been detected, and to test the relationships between evolutionary, functional and environmental shifts. In order to test these connections, we first focused on an analysis of the well-described fungal lipase/feruloyl esterase A family. Type-A feruloyl esterases (E.C. 220.127.116.11) are enzymes responsible for cleaving the ester link between the polysaccharide main chain of xylans or pectins and monomeric or dimeric ferulic acid. Thus, feruloyl esterases make the cell wall increasingly vulnerable to further enzymatic attack . A previous study, proposed a functional classification of the feruloyl esterases with four subclasses that were characterised and termed type-A, B, C and D . However, lipases (E.C. 18.104.22.168) catalyse both the hydrolysis and the synthesis of esters formed from glycerol and long-chain fatty acids . Despite strong structural and sequence similarities, this family presents two distinct enzymatic activities, i.e. lipase and type-A feruloyl esterase, that may have originated from evolutionary events such as functional shift.
The evolutionary history of this family was reconstructed, and the branch-site model was applied to test for positive selection. We tested the connection between evolutionary and functional shifts and then reassessed the connection in terms of response to environmental context..
Evolutionary analysis of the homologous proteins from the lipase/feruloyl esterase A family
Parameter estimates for the lipase/esterase data (n = 29)
Positively selected sites
ω = 0.0685
p0 = 0.452, p1 = 0.170
(p2 + p3) = 0.376
ω2 = 999
Site for foreground lineage: 4Q 13R 17M 19T 22Q 26A 29C 40K 42Y 51W 53L 63T 69G 71D 75Q 76L 78T 80Y 100Y 103G 112E 137S 142T 145Q 147S 163S 195G 198N 204E 215S 236E 238Q 244N (at P > 0.95)
The effects of codon usage bias on LRTs (n = 29)
Estimates under model A
p0 = 0.427, p1 = 0.241
(p2 + p3) = 0.330
ω2 = 11.182
p0 = 0.452, p1 = 0.170
(p2 + p3) = 0.376
ω2 = 999
p0 = 0.469, p1 = 0.157
(p2 + p3) = 0.372
ω2 = 999
Estimates under M1a
p0 = 0.627, p1 = 0.372
ω0 = 0.193
p0 = 0.711, p1 = 0.288
ω0 = 0.126
p0 = 0.730, p1 = 0.269
ω0 = 0.113
Estimates under model A (ω2 = 1)
p0 = 0.437, p1 = 0.259 (p2 + p3) = 0.302
ω0 = 0.187
p0 = 0.480, p1 = 0.189 (p2 + p3) = 0.329
ω0 = 0.121
p0 = 0.505, p1 = 0.178 (p2 + p3) = 0.316
ω0 = 0.107
In order to test whether codon usage bias is lineage-specific (between feruloyl esterase A and lipase group), we used ENC to measure average codon usage bias. The averages measured for the feruloyl esterase A and lipases groups were 52.5 and 47.2, respectively, indicating that codon usage bias was not lineage-specific.
These results demonstrated that positive selection occurred along the branch leading to the feruloyl esterase A function in Aspergilli.
Relationship between evolutionary and functional shifts
Parameter estimates for the lipase/esterase data (n = 12)
Positively selected sites
ω = 0.0621
p0 = 0.503, p1 = 0.102
(p2 + p3) = 0.393
ω2 = 14.201
Sites for foreground lineage: 17M 19T 22Q 29C 51W 63T 70G 71D 74L 75Q 76L 103G 126A 163S 209G 226V 248T 257A (at P > 0.95)
The effects of codon usage bias on LRT (n = 12)
Estimates under model A
p0 = 0.51693, p1 = 0.152
(p2 + p3) = 0.330
ω2 = 11.182
p0 = 0.503, p1 = 0.102
(p2 + p3) = 0.393
ω2 = 14.201
p0 = 0.477, p1 = 0.095
(p2 + p3) = 0.426
ω2 = 999
Estimates under M1a
p0 = 0.732, p1 = 0.267
ω0 = 0.187
p0 = 0.793, p1 = 0.206
ω0 = 0.073
p0 = 0.794, p1 = 0.205
ω0 = 0.062
Estimates under model A (ω2 = 1)
p0 = 0.492, p1 = 0.159
(p2 + p3) = 0.348
ω0 = 0.165
p0 = 0.537, p1 = 0.112
(p2 + p3) = 0.350
ω0 = 0.073
p0 = 0.533, p1 = 0.112
(p2 + p3) = 0.354
ω0 = 0.039
In order to test whether positive selection also occurred in different lineages along the phylogeny, others branches were labelled as foreground branches. The calculations are summarized in Additional File 3. LRTs gave no significant results with ω2 > 1 except for the branches leading to the lipases from Yarrowia lipolytica (ABA54275.1) and Thermomyces lanuginosus (O59952). In both these cases, the sites under positive selection were not involved in a functional shift as the lipase function was conserved. Furthermore, there was no overlap between the positively selected sites and the sites identified for branch b, thus confirming a divergent evolution between lipases and feruloyl esterases A. Therefore, positive selection had also occurred along different branches but only branch b led to neofunctionalisation.
In conclusion, both phylogenetic and evolutionary data suggested that the ancestral function (lipase) had shifted, with molecular adaptation leading to a novel enzyme (type-A feruloyl esterase).
Are positively selected sites involved in the functional shift?
Role of the positively selected sites in the discrepancy between feruloyl esterase A and lipase activities.
Three dimensional localization
Positively selected sites
Site directed mutagenesis
& Role on Lip/FAE discrepancy
1. Flap region (69–80)
catalysis and substrate discrimination
2. Catalytic vicinity
3. Loop (226–244)
structured plasticity to the substrate binding site
Correlating evolutionary, functional and environmental shifts is a delicate task, and there are only a few published studies (described above) that establish a direct link between these shifts. The aim of this study was to extend our investigation into the relationship between evolutionary and functional shifts to focus on the role of the environment. For this purpose, we studied the fungal lipase/feruloyl esterase A family whose functional diversification makes it a promising candidate. One study showed that type-A feruloyl esterases were more sequence-related to lipases than they are to other groups (type B-D), but evolutionary analysis was not performed .
In this study, we constructed phylogenetic trees and identified positive selection along the branch leading to feruloyl esterase (type A) activity. Positively selected sites were identified using the Bayes empirical Bayes (BEB) procedure of the branch-site model A [15, 21]. Indeed, BEB is a reliable method that gives a false-positive rate of less than 5% when sites are identified at the selected cut-off. As codon usage bias could have a stronger effect on estimation of ω than the transition/transversion rate bias, we estimated the effect of codon usage bias on LRTs . The parameter estimates proved relatively stable, thus demonstrating that LRTs were robust to assumptions on codon usage bias. The next level of our analysis was to unambiguously demonstrate that the positively selected sites were indeed involved in the functional shift, which is a sine qua non condition to clearly establishing a connection between evolutionary and functional shifts. Based on site-directed mutagenesis data, we established that three sites under positive selection were involved in the functional shift leading to the type-A feruloyl esterase function. These mutational experiments made it possible to switch both enzymatic functions. Moreover, several positively selected amino acids were located in specific regions known to be of great functional significance for the substrate specificity and enzymatic activity of type-A feruloyl esterases and lipases. Hermoso et al. stated that active site plasticity between lipases and feruloyl esterase A depends on the nature of specific residues and on structural modifications within the active sites . The 33 positively selected sites that we identified offer potential candidates for this plasticity. These results therefore made it possible to connect evolutionary and functional shifts.
Previous studies on site-directed mutagenesis focused on the replacement of target amino acids by comparing alignments between lipase and feruloyl esterase sequences and using 3D data to infer the potential biological importance of targeted sites.
For instance, a homologous position for a particular amino acid that is conserved in one subfamily but highly variable in another can be interpreted as functionally important in the first subfamily but less so in the second. In contrast, when radically different amino acids are fixed between subfamilies, the functional interpretation is that these sites fulfil different but equally important roles in the two subfamilies [24–26]. Positions with variable rates of divergence in different regions of a tree could provide a basis for relating individual amino acid residues to specific functional differences in certain branches [27, 28]. Although these approaches, which are based solely on rate shifts, are implicitly linked to protein evolution and remain complementary to our analysis, they do not estimate the strength or direction of natural selection pressure. Here, we have provided an evolutionary dimension by identifying a branch containing a number of sites evolving very significantly faster than under neutrality. Moreover, these sites caused neofunctionalisation, meaning that functional shift is driven by positive selection.
The final step of our analysis focused on the second level of our investigation concerning the role of the environment in the adaptive evolution of the lipase/feruloyl esterase A family.; thus, evolutionary history was reconstructed and reassessed in terms of response to environmental pressure. There had been a duplication event occurring before the separation of the Hemiascomycetes (yeasts) and Euascomycetes (Aspergilli), and which was followed by a functional shift in the Euascomycetes but gene losses in the Hemiascomycetes. Functional diversification following gene duplication is a frequent event during evolutionary history of multigenic families. Here, phylogenetic and evolutionary data suggested that the ancestral function (lipase) was shifted, leading to enzymatic novelty (type-A feruloyl esterase). It is interesting to note that Aspergilli conserved both functions, i.e. the lipase and feruloyl esterase A activities, which makes it the only genus identified to date that possesses this distinctiveness. However, increasingly powerful genome sequencing capabilities coupled with biochemical experiments may lead to feruloyl esterase A activity being extended to other groups. Moreover, feruloyl esterase A activities could be functionally substituted by non-homologous proteins with similar enzymatic properties, for instance by the type-B feruloyl esterases.
Key insight to understanding the role of the environment would be gained by pinpointing the selective advantages that could be conferred by feruloyl esterase A activity. The Aspergilli genus is a well-known plant cell wall degrader, and feruloyl esterases are able to hydrolyse the ester bonds linking ferulic acid to plant cell wall polysaccharides. Thus, feruloyl esterases facilitated the access of main-chain-degrading enzymes to the polysaccharide backbone, thus allowing efficient lignocellulose degradation. The colonisation by the land plants (Embryophyta) that appeared during the Silurian period (-430 to -400 Myr) could have progressively driven neofunctionalisation in Aspergilli. This period estimation is strengthened by our phylogeny by the fact that the Hemiascomycete yeasts are believed to have diverged from a common ancestral fungus at least 400 million years ago. Enzymatic novelty in Euascomycetes could have generated a selective advantage that became fixed in this group during the emergence of the land plants. The appearance of feruloyl esterase A activities could be regarded as an efficient step among several possible routes towards plant colonisation. Therefore, we hypothesised that a connection between functional and environmental shifts could be established according to the impact of the role played by feruloyl esterase A in plant cell wall degradation. However, based on the knowledge currently available, this connection can only remain hypothetical.
Structural comparison between Clostridium themocellum feruloyl esterases (XynY and XynZ) and AnFAEA revealed that feruloyl esterases could have evolved through functional convergence following evolutionary divergence . Future studies are needed to analyse whether convergence occurred in other enzymes involved in the same plant cell wall degradation functions as type-A feruloyl esterases. Indeed, the occurrence of convergence greatly strengthens the connection between evolutionary shift and environmental changes . At present, several artificial conditions (e.g. antibiotic resistance genes) and only one natural case are able to identify unambiguous convergence via a clear connection between evolutionary (positively selected sites) and functional shifts . It would be useful to study whether generalised environment-driven functional shifts could be have been responsible for enzymatic diversification in fungi kingdom.
The positively selected sites we identified could be used as "probes" for functional inference. These sites also represent potential novel targets in biotechnology for mutational analyses or in paleobiochemical experiments designed to resurrecting the ancestral function of the lipase/feruloyl esterase gene [29–31].
In summary, these results illustrate a rare example of the connection between fundamental events of molecular evolution. We demonstrated that evolutionary shift (positively selected sites) has led to functional diversification that could be related to environmental changes. Future studies are scheduled to test other multigenic families in order to analyse and further characterise the general trends underpinning these connections.
Construction of phylogenetic trees
Phylogenetic analyses were performed using the automated genomic annotation platform FIGENIX  to retrieve sequences and alignments and perform phylogenetic reconstruction. The pipeline used applied three different methods of phylogenetic tree reconstruction, i.e. Maximum Parsimony , Maximum likelihood  and Neighbour Joining , and a midpoint-rooted consensus tree was built. Bootstrapping was carried out with 1000 replications. Bootstrap values are reported for each method (for a detailed description of the pipelines and models used, see ).
Preparation of datasets
Protein and DNA sequences were retrieved from the National Center for Biotechnology Information . The protein sequences were aligned using ClustalW . Correspondence between protein alignment and each DNA sequence was established using the Wise2 software package followed by manual adjustments . The final alignment contained 217 and 226 codons for dataset 1 (n = 29) and dataset 2 (n = 12), respectively.
Detection of positive selection
The codeml program of the PAML (Phylogenetic Analysis by Maximum Likelihood [13, 40]) 3.15 software package was applied to test for positive selection. PAML uses a Maximum Likelihood algorithm to assign likelihood scores to different models for selection. If a higher likelihood score was obtained for a model incorporating positive selection than a null model without positive selection, this constitutes evidence for positive selection. We first used the model A implemented by Yang and Nielsen . This model enables ω (= dN/dS) to vary both between sites and between lineages, and was implemented in the maximum likelihood framework. Branches a and b tested for positive selection were labelled as foreground branches, and all remaining branches were labelled as background branches. This model was then used to construct two likelihood ratio tests (LRTs) by comparison with a model that does not identify positive selection. The null hypothesis for test 1 is the site model M1a  which assumes two site classes with 0 < ω0 < 1 and ω1 = 1 for all branches. For test 2, the null hypothesis is the branch-site model A but with ω2 = 1 fixed. Positively selected sites were identified by the Bayes empirical Bayes (BEB) method . The effect of codon usage bias on LRTs was estimated using two assumptions on codon usage: the Fequal model and Fcodon model.
Measurement of codon usage bias
Visualisation of protein structures
Protein structures were visualised using accelrys® DS Visualizer 1.5, available at . The PDB number of the FAEA from A. niger is 1USW.
feruloyl esterase A from Aspergillus niger
Bayes empirical Bayes
effective number of codon
type-A feruloyl esterase
likelihood ratio test
Phylogenetic Analysis by Maximum Likelihood
Anthony Levasseur is grateful to the Agence Nationale de la Recherche (ANR05 BIO-006 ARD) for his post-doctoral fellowship. Pierre Pontarotti is a CNRS (Centre National de la Recherche Scientifique) research director. We would like to thank Ziheng Yang for generously distributing the PAML software package and Eric A. Gaucher for helpful discussions and critical reading of the manuscript. We sincerely thank the reviewers for their positive reviews and very interesting suggestions that helped to improve the quality of the manuscript.
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