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Modeling of glycosyl hydrolases of the Ustilaginaceae family using the online server SWISS-MODEL
Abstract
En este trabajo se realizó la búsqueda de 20 secuencias proteicas de la familia Ustilaginaceae en la base de datos de NCBI para su posterior modelamiento. El modelamiento de estas proteínas utilizando el servidor en línea SWISS-MODEL permitió apreciar las regiones conservadas en 17 proteínas a través de la presencia de estructuras secundarias como α-hélices y hojas-β, sin embargo tres de ellas no presentaron similitud estructural con el resto de las proteínas. Se sugiere realizar estudios sobre la composición de los aminoácidos del sitio activo y sobre la región del péptido señal, así como llevar a cabo un análisis filogenético de las proteínas con mayor similitud.
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Why is an amino acid replacement in a protein accepted during evolution? The answer given by bioinformatics relies on the frequency of change of each amino acid by another one and the propensity of each to remain unchanged. We propose that these replacement rules are recoverable from the secondary structural trends of amino acids. A distance measure between high-resolution Ramachandran distributions reveals that structurally similar residues coincide with those found in substitution matrices such as BLOSUM: Asn ↔ Asp, P™he ↔ Tyr, Lys ↔ Arg, Gln ↔ Glu, Ile ↔ Val, Met → Leu; with Ala, Cys, His, Gly, Ser, Pro, and Thr, as structurally idiosyncratic residues. We also found a high average correlation (R¯ = 0.85) between thirty amino acid mutability scales and the mutational inertia (IX), which measures the energetic cost weighted by the number of observations at the most probable amino acid conformation. These results indicate that amino acid substitutions follow two optimally-efficient principles: (a) amino acids interchangeability privileges their secondary structural similarity, and (b) the amino acid mutability depends directly on its biosynthetic energy cost, and inversely with its frequency. These two principles are the underlying rules governing the observed amino acid substitutions.
The techniques of metagenomics have allowed researchers to access the genomic potential of uncultivated microbes, but there remain significant barriers to determination of gene function based on DNA sequence alone. Functional metagenomics, in which DNA is cloned and expressed in surrogate hosts, can overcome these barriers, and make important contributions to the discovery of novel enzymes. In this study, a soil metagenomic library carried in an IncP cosmid was used for functional complementation for β-galactosidase activity in both Sinorhizobium meliloti (α-Proteobacteria) and Escherichia coli (γ-Proteobacteria) backgrounds. One β-galactosidase, encoded by six overlapping clones that were selected in both hosts, was identified as a member of glycoside hydrolase family 2. We could not identify ORFs obviously encoding possible β-galactosidases in 19 other sequenced clones that were only able to complement S. meliloti. Based on low sequence identity to other known glycoside hydrolases, yet not β-galactosidases, three of these ORFs were examined further. Biochemical analysis confirmed that all three encoded β-galactosidase activity. Lac36W_ORF11 and Lac161_ORF7 had conserved domains, but lacked similarities to known glycoside hydrolases. Lac161_ORF10 had neither conserved domains nor similarity to known glycoside hydrolases. Bioinformatic and structural modeling implied that Lac161_ORF10 protein represented a novel enzyme family with a five-bladed propeller glycoside hydrolase domain. By discovering founding members of three novel β-galactosidase families, we have reinforced the value of functional metagenomics for isolating novel genes that could not have been predicted from DNA sequence analysis alone.
The study of molecular evolution at the level of protein-coding genes often entails comparing large datasets of sequences to infer their evolutionary relationships. Despite the importance of a protein's structure and conformational dynamics to its function and thus its fitness, common phylogenetic methods embody minimal biophysical knowledge of proteins. To underscore the biophysical constraints on natural selection, we survey effects of protein mutations, highlighting the physical basis for marginal stability of natural globular proteins and how requirement for kinetic stability and avoidance of misfolding and misinteractions might have affected protein evolution. The biophysical underpinnings of these effects have been addressed by models with an explicit coarse-grained spatial representation of the polypeptide chain. Sequence–structure mappings based on such models are powerful conceptual tools that rationalize mutational robustness, evolvability, epistasis, promiscuous function performed by ‘hidden’ conformational states, resolution of adaptive conflicts and conformational switches in the evolution from one protein fold to another. Recently, protein biophysics has been applied to derive more accurate evolutionary accounts of sequence data. Methods have also been developed to exploit sequence-based evolutionary information to predict biophysical behaviours of proteins. The success of these approaches demonstrates a deep synergy between the fields of protein biophysics and protein evolution.
beta-D-𝑁-Acetylhexosaminidase, a family 20 glycosyl hydrolase, catalyzes the removal of 𝛽-1,4-linked 𝑁-acetylhexosamine
residues from oligosaccharides and their conjugates. We constructed phylogenetic tree of 𝛽-hexosaminidases to analyze the
evolutionary history and predicted functions of plant hexosaminidases. Phylogenetic analysis reveals the complex history
of evolution of plant 𝛽-hexosaminidase that can be described by gene duplication events. The 3D structure of tomato 𝛽-
hexosaminidase (𝛽-Hex-Sl) was predicted by homology modeling using 1now as a template. Structural conformity studies of the
best fit model showed that more than 98% of the residues lie inside the favoured and allowed regions where only 0.9% lie in the
unfavourable region. Predicted 3D structure contains 531 amino acids residues with glycosyl hydrolase20b domain-I and glycosyl
hydrolase20 superfamily domain-II including the (𝛽/𝛼)8 barrel in the central part.The 𝛼 and 𝛽 contents of the modeled structure
were found to be 33.3% and 12.2%, respectively. Eleven amino acids were found to be involved in ligand-binding site; Asp(330) and
Glu(331) could play important roles in enzyme-catalyzed reactions.The predicted model provides a structural framework that can
act as a guide to develop a hypothesis for 𝛽-Hex-Sl mutagenesis experiments for exploring the functions of this class of enzymes in
plant kingdom.
Background
Identification of protein-protein interactions (PPIs) is essential for a better understanding of biological processes, pathways and functions. However, experimental identification of the complete set of PPIs in a cell/organism (“an interactome”) is still a difficult task. To circumvent limitations of current high-throughput experimental techniques, it is necessary to develop high-performance computational methods for predicting PPIs.
Results
In this article, we propose a new computational method to predict interaction between a given pair of protein sequences using features derived from known homologous PPIs. The proposed method is capable of predicting interaction between two proteins (of unknown structure) using Averaged One-Dependence Estimators (AODE) and three features calculated for the protein pair: (a) sequence similarities to a known interacting protein pair (FSeq), (b) statistical propensities of domain pairs observed in interacting proteins (FDom) and (c) a sum of edge weights along the shortest path between homologous proteins in a PPI network (FNet). Feature vectors were defined to lie in a half-space of the symmetrical high-dimensional feature space to make them independent of the protein order. The predictability of the method was assessed by a 10-fold cross validation on a recently created human PPI dataset with randomly sampled negative data, and the best model achieved an Area Under the Curve of 0.79 (pAUC0.5% = 0.16). In addition, the AODE trained on all three features (named PSOPIA) showed better prediction performance on a separate independent data set than a recently reported homology-based method.
Conclusions
Our results suggest that FNet, a feature representing proximity in a known PPI network between two proteins that are homologous to a target protein pair, contributes to the prediction of whether the target proteins interact or not. PSOPIA will help identify novel PPIs and estimate complete PPI networks. The method proposed in this article is freely available on the web at http://mizuguchilab.org/PSOPIA.
The version of this article published in BMC Genomics 2013, 14: 274, contains 9 unpublished genomes (Botryobasidium botryosum, Gymnopus luxurians, Hypholoma sublateritium, Jaapia argillacea, Hebeloma cylindrosporum, Conidiobolus coronatus, Laccaria amethystina, Paxillus involutus, and P. rubicundulus) downloaded from JGI website. In this correction, we removed these genomes after discussion with editors and data producers whom we should have contacted before downloading these genomes. Removing these data did not alter the principle results and conclusions of our original work. The relevant Figures 1, 2, 3, 4 and 6; and Table 1 have been revised. Additional files 1, 3, 4, and 5 were also revised. We would like to apologize for any confusion or inconvenience this may have caused.
Background
Fungi produce a variety of carbohydrate activity enzymes (CAZymes) for the degradation of plant polysaccharide materials to facilitate infection and/or gain nutrition. Identifying and comparing CAZymes from fungi with different nutritional modes or infection mechanisms may provide information for better understanding of their life styles and infection models. To date, over hundreds of fungal genomes are publicly available. However, a systematic comparative analysis of fungal CAZymes across the entire fungal kingdom has not been reported.
Results
In this study, we systemically identified glycoside hydrolases (GHs), polysaccharide lyases (PLs), carbohydrate esterases (CEs), and glycosyltransferases (GTs) as well as carbohydrate-binding modules (CBMs) in the predicted proteomes of 94 representative fungi from Ascomycota, Basidiomycota, Chytridiomycota, and Zygomycota. Comparative analysis of these CAZymes that play major roles in plant polysaccharide degradation revealed that fungi exhibit tremendous diversity in the number and variety of CAZymes. Among them, some families of GHs and CEs are the most prevalent CAZymes that are distributed in all of the fungi analyzed. Importantly, cellulases of some GH families are present in fungi that are not known to have cellulose-degrading ability. In addition, our results also showed that in general, plant pathogenic fungi have the highest number of CAZymes. Biotrophic fungi tend to have fewer CAZymes than necrotrophic and hemibiotrophic fungi. Pathogens of dicots often contain more pectinases than fungi infecting monocots. Interestingly, besides yeasts, many saprophytic fungi that are highly active in degrading plant biomass contain fewer CAZymes than plant pathogenic fungi. Furthermore, analysis of the gene expression profile of the wheat scab fungus Fusarium graminearum revealed that most of the CAZyme genes related to cell wall degradation were up-regulated during plant infection. Phylogenetic analysis also revealed a complex history of lineage-specific expansions and attritions for the PL1 family.
Conclusions
Our study provides insights into the variety and expansion of fungal CAZyme classes and revealed the relationship of CAZyme size and diversity with their nutritional strategy and host specificity.
The fungal genera Ustilago, Sporisorium and Macalpinomyces represent an unresolved complex. Taxa within the complex often possess characters that occur in more than one genus, creating uncertainty for species placement. Previous studies have indicated that the genera cannot be separated based on morphology alone. Here we chronologically review the history of the Ustilago-Sporisorium-Macalpinomyces complex, argue for its resolution and suggest methods to accomplish a stable taxonomy. A combined molecular and morphological approach is required to identify synapomorphic characters that underpin a new classification. Ustilago, Sporisorium and Macalpinomyces require explicit re-description and new genera, based on monophyletic groups, are needed to accommodate taxa that no longer fit the emended descriptions. A resolved classification will end the taxonomic confusion that surrounds generic placement of these smut fungi.
Background
Oomycetes are fungal-like microorganisms evolutionary distinct from true fungi, belonging to the Stramenopile lineage and comprising major plant pathogens. Both oomycetes and fungi express proteins able to interact with cellulose, a major component of plant and oomycete cell walls, through the presence of carbohydrate-binding module belonging to the family 1 (CBM1). Fungal CBM1-containing proteins were implicated in cellulose degradation whereas in oomycetes, the Cellulose Binding Elicitor Lectin (CBEL), a well-characterized CBM1-protein from Phytophthora parasitica, was implicated in cell wall integrity, adhesion to cellulosic substrates and induction of plant immunity.
Results
To extend our knowledge on CBM1-containing proteins in oomycetes, we have conducted a comprehensive analysis on 60 fungi and 7 oomycetes genomes leading to the identification of 518 CBM1-containing proteins. In plant-interacting microorganisms, the larger number of CBM1-protein coding genes is expressed by necrotroph and hemibiotrophic pathogens, whereas a strong reduction of these genes is observed in symbionts and biotrophs. In fungi, more than 70% of CBM1-containing proteins correspond to enzymatic proteins in which CBM1 is associated with a catalytic unit involved in cellulose degradation. In oomycetes more than 90% of proteins are similar to CBEL in which CBM1 is associated with a non-catalytic PAN/Apple domain, known to interact with specific carbohydrates or proteins. Distinct Stramenopile genomes like diatoms and brown algae are devoid of CBM1 coding genes. A CBM1-PAN/Apple association 3D structural modeling was built allowing the identification of amino acid residues interacting with cellulose and suggesting the putative interaction of the PAN/Apple domain with another type of glucan. By Surface Plasmon Resonance experiments, we showed that CBEL binds to glycoproteins through galactose or N-acetyl-galactosamine motifs.
Conclusions
This study provides insight into the evolution and biological roles of CBM1-containing proteins from oomycetes. We show that while CBM1s from fungi and oomycetes are similar, they team up with different protein domains, either in proteins implicated in the degradation of plant cell wall components in the case of fungi or in proteins involved in adhesion to polysaccharidic substrates in the case of oomycetes. This work highlighted the unique role and evolution of CBM1 proteins in oomycete among the Stramenopile lineage.
Beta-N-acetylhexosaminidases belonging to the glycosyl hydrolase 20 (GH20) family are involved in the removal of terminal beta-glycosidacally linked N-acetylhexosamine residues. These enzymes, widely distributed in microorganisms, animals and plants, are involved in many important physiological and pathological processes, such as cell structural integrity, energy storage, pathogen defence, viral penetration, cellular signalling, fertilization, development of carcinomas, inflammatory events and lysosomal storage diseases. Nevertheless, only limited analyses of phylogenetic relationships between GH20 genes have been performed until now.
Careful phylogenetic analyses of 233 inferred protein sequences from eukaryotes and prokaryotes reveal a complex history for the GH20 family. In bacteria, multiple gene duplications and lineage specific gene loss (and/or horizontal gene transfer) are required to explain the observed taxonomic distribution. The last common ancestor of extant eukaryotes is likely to have possessed at least one GH20 family member. At least one gene duplication before the divergence of animals, plants and fungi as well as other lineage specific duplication events have given rise to multiple paralogous subfamilies in eukaryotes. Phylogenetic analyses also suggest that a second, divergent subfamily of GH20 family genes present in animals derive from an independent prokaryotic source. Our data suggest multiple convergent changes of functional roles of GH20 family members in eukaryotes.
This study represents the first detailed evolutionary analysis of the glycosyl hydrolase GH20 family. Mapping of data concerning physiological function of GH20 family members onto the phylogenetic tree reveals that apparently convergent and highly lineage specific changes in substrate specificity have occurred in multiple GH20 subfamilies.
Biotrophic pathogens, such as the related maize pathogenic fungi Ustilago maydis and Sporisorium reilianum, establish an intimate relationship with their hosts by secreting protein effectors. Because secreted effectors interacting
with plant proteins should rapidly evolve, we identified variable genomic regions by sequencing the genome of S. reilianum and comparing it with the U. maydis genome. We detected 43 regions of low sequence conservation in otherwise well-conserved syntenic genomes. These regions primarily
encode secreted effectors and include previously identified virulence clusters. By deletion analysis in U. maydis, we demonstrate a role in virulence for four previously unknown diversity regions. This highlights the power of comparative
genomics of closely related species for identification of virulence determinants.
SWISS-MODEL (http://swissmodel.expasy.org) is a server for automated comparative modeling of three-dimensional (3D) protein structures. It pioneered the field of automated
modeling starting in 1993 and is the most widely-used free web-based automated modeling facility today. In 2002 the server
computed 120 000 user requests for 3D protein models. SWISS-MODEL provides several levels of user interaction through its
World Wide Web interface: in the ‘first approach mode’ only an amino acid sequence of a protein is submitted to build a 3D
model. Template selection, alignment and model building are done completely automated by the server. In the ‘alignment mode’,
the modeling process is based on a user-defined target-template alignment. Complex modeling tasks can be handled with the
‘project mode’ using DeepView (Swiss-PdbViewer), an integrated sequence-to-structure workbench. All models are sent back via
email with a detailed modeling report. WhatCheck analyses and ANOLEA evaluations are provided optionally. The reliability
of SWISS-MODEL is continuously evaluated in the EVA-CM project. The SWISS-MODEL server is under constant development to improve
the successful implementation of expert knowledge into an easy-to-use server.
The determination of membrane protein (MP) structures has always trailed that of soluble proteins due to difficulties in their overexpression, reconstitution into membrane mimetics, and subsequent structure determination. The percentage of MP structures in the protein databank (PDB) has been at a constant 1-2% for the last decade. In contrast, over half of all drugs target MPs, only highlighting how little we understand about drug-specific effects in the human body. To reduce this gap, researchers have attempted to predict structural features of MPs even before the first structure was experimentally elucidated. In this review, we present current computational methods to predict MP structure, starting with secondary structure prediction, prediction of trans-membrane spans, and topology. Even though these methods generate reliable predictions, challenges such as predicting kinks or precise beginnings and ends of secondary structure elements are still waiting to be addressed. We describe recent developments in the prediction of 3D structures of both α-helical MPs as well as β-barrels using comparative modeling techniques, de novo methods, and molecular dynamics (MD) simulations. The increase of MP structures has (1) facilitated comparative modeling due to availability of more and better templates, and (2) improved the statistics for knowledge-based scoring functions. Moreover, de novo methods have benefitted from the use of correlated mutations as restraints. Finally, we outline current advances that will likely shape the field in the forthcoming decade. © Proteins 2014;. © 2014 Wiley Periodicals, Inc.
Comparative protein structure modeling is a computational approach to build three-dimensional structural models for proteins using experimental structures of related protein family members as templates. Regular blind assessments of modeling accuracy have demonstrated that comparative protein structure modeling is currently the most reliable technique to model protein structures. Homology models are often sufficiently accurate to substitute for experimental structures in a wide variety of applications. Since the usefulness of a model for specific application is determined by its accuracy, model quality estimation is an essential component of protein structure prediction. Comparative protein modeling has become a routine approach in many areas of life science research since fully automated modeling systems allow also nonexperts to build reliable models. In this chapter, we describe practical approaches for automated protein structure modeling with SWISS-MODEL Workspace and the Protein Model Portal.
Filamentous fungi owe powerful abilities for decomposition of the extensive plant material, lignocellulose, and thereby are indispensable for the Earth's carbon cycle, generation of soil humic matter and formation of soil fine structure. The filamentous wood-decaying fungi belong to the phyla Basidiomycota and Ascomycota, and are unique organisms specified to degradation of the xylem cell wall components (cellulose, hemicelluloses, lignins and extractives). The basidiomycetous wood-decaying fungi form brackets, caps or resupinaceous (corticioid) fruiting bodies when growing on wood for dissemination of their sexual basidiospores. In particular, the ability to decompose the aromatic lignin polymers in wood is mostly restricted to the white rot basidiomycetes. The white-rot decay of wood is possible due to secretion of organic acids, secondary metabolites, and oxidoreductive metalloenzymes, heme peroxidases and laccases, encoded by divergent gene families in these fungi. The brown rot basidiomycetes obviously depend more on a non-enzymatic strategy for decomposition of wood cellulose and modification of lignin. This review gives a current ecological, genomic, and protein functional and phylogenetic perspective of the wood and lignocellulose-decaying basidiomycetous fungi.
Family GH16 glycoside hydrolases can be assigned to five subgroups according to their substrate specificities, including xyloglucan transglucosylases/hydrolases (XTHs), (1,3)-β-galactanases, (1,4)-β-galactanases/K-carrageenases, "nonspecific" (1,3/1,3;1,4)-β-D-glucan endohydrolases, and (1,3;1,4)-β-D-glucan endohydrolases. A structured family GH16 glycoside hydrolase database has been constructed (http://www.ghdb.uni-stuttgart.de) and provides multiple sequence alignments with functionally annotated amino acid residues and phylogenetic trees. The database has been used for homology modeling of seven glycoside hydrolases from the GH16 family with various substrate specificities, based on structural coordinates for (1,3;1,4)-β-D-glucan endohydrolases and a κ-carrageenase. In combination with multiple sequence alignments, the models predict the three-dimensional (3D) dispositions of amino acid residues in the substrate-binding and catalytic sites of XTHs and (1,3/1,3;1,4)-β-D- glucan endohydrolases; there is no structural information available in the databases for the latter group of enzymes. Models of the XTHs, compared with the recently determined structure of a Populus tremulos x tremuloides XTH, reveal similarities with the active sites of family GH11 (1,4)-β-D-xylan endohydrolases. From a biological viewpoint, the classification, molecular modeling and a new 3D structure of the P. tremulos x tremuloides XTH establish structural and evolutionary connections between XTHs, (1,3;1,4)-β-D-glucan endohydrolases and xylan endohydrolases. These findings raise the possibility that XTHs from higher plants could be active not only on cell wall xyloglucans, but also on (1,3;1,4)-β-D-glucans and arabinoxylans, which are major components of walls in grasses. A role for XTHs in (1,3;1,4)-β-D-glucan and arabinoxylan modification would be consistent with the apparent overrepresentation of XTH sequences in cereal expressed sequence tags databases.
Depending on whether similar structures are found in the PDB library, the protein structure prediction can be categorized into template-based modeling and free modeling. Although threading is an efficient tool to detect the structural analogs, the advancements in methodology development have come to a steady state. Encouraging progress is observed in structure refinement which aims at drawing template structures closer to the native; this has been mainly driven by the use of multiple structure templates and the development of hybrid knowledge-based and physics-based force fields. For free modeling, exciting examples have been witnessed in folding small proteins to atomic resolutions. However, predicting structures for proteins larger than 150 residues still remains a challenge, with bottlenecks from both force field and conformational search.
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