Human glycogene cloning: focus on beta 3-glycosyltransferase and beta 4-glycosyltransferase families

Glycogenes encode proteins involved in glycan synthesis, such as glycosyltransferases, sulfotransferases and sugar-nucleotide transporters. The comprehensive identification and functional analysis of human glycogenes has been ongoing for some time. During the past 20 years, 183 human glycogenes have been cloned and their substrate specificities analyzed. All current information on these human glycogenes and their links with orthologous genes in other species is summarized in the GlycoGene database. In recent years, two glycogene families, beta3-glycosyltransferases and beta4-glycosyltransferases, have been identified and analyzed in particular detail.     

Evolutionarily conserved substrate substructures for automated annotation of enzyme superfamilies

The evolution of enzymes affects how well a species can adapt to new environmental conditions. During enzyme evolution, certain aspects of molecular function are conserved while other aspects can vary. Aspects of function that are more difficult to change or that need to be reused in multiple contexts are often conserved, while those that vary may indicate functions that are more easily changed or that are no longer required. In analogy to the study of conservation patterns in enzyme sequences and structures, we have examined the patterns of conservation and variation in enzyme function by analyzing graph isomorphisms among enzyme substrates of a large number of enzyme superfamilies. This systematic analysis of substrate substructures establishes the conservation patterns that typify individual superfamilies. Specifically, we determined the chemical substructures that are conserved among all known substrates of a superfamily and the substructures that are reacting in these substrates and then examined the relationship between the two. Across the 42 superfamilies that were analyzed, substantial variation was found in how much of the conserved substructure is reacting, suggesting that superfamilies may not be easily grouped into discrete and separable categories. Instead, our results suggest that many superfamilies may need to be treated individually for analyses of evolution, function prediction, and guiding enzyme engineering strategies. Annotating superfamilies with these conserved and reacting substructure patterns provides information that is orthogonal to information provided by studies of conservation in superfamily sequences and structures, thereby improving the precision with which we can predict the functions of enzymes of unknown function and direct studies in enzyme engineering. Because the method is automated, it is suitable for large-scale characterization and comparison of fundamental functional capabilities of both characterized and uncharacterized enzyme superfamilies.     

Metabolites and pathway flexibility

Flexibility of metabolites and enzymes is investigated (i) on the level of the individual molecule, (ii) on the pathway level and (iii) combined effects on the systems and network level. Tools and results from our current research are summarized including data from our metabolite enzyme database. Including our latest census we find frequently used metabolites stimulate evolutionary flexibility in specific enzyme superfamilies. Furthermore, simultaneous changes of reactions and metabolites are observed in these flexible enzyme superfamilies. Both effects provide a strong source for resistance in parasites and pathogens. Specific adaptations scenarios and some counter strategies are discussed.     

Insights into miRNA regulation of the human glycome

Glycosylation is an intricate process requiring the coordinated action of multiple proteins, including glycosyltransferases, glycosidases, sugar nucleotide transporters and trafficking proteins. Work by several groups points to a role for microRNA (miRNA) in controlling the levels of specific glycosyltransferases involved in cancer, neural migration and osteoblast formation. Recent work in our laboratory suggests that miRNA are a principal regulator of the glycome, translating genomic information into the glycocode through tuning of enzyme levels. Herein we overlay predicted miRNA regulation of glycosylation related genes (glycogenes) onto maps of the common N-linked and O-linked glycan biosynthetic pathways to identify key regulatory nodes of the glycome. Our analysis provides insights into glycan regulation and suggests that at the regulatory level, glycogenes are non-redundant.     

Definitions of enzyme function for the structural genomics era

Questions are being asked about how enzyme function is described at the molecular level and the strengths and weaknesses of the EC system for this purpose. A new approach to describing enzyme function has been proposed that might improve our capabilities for functional inference for members of enzyme superfamilies.     

Exploring the evolution of novel enzyme functions within structurally defined protein superfamilies

In order to understand the evolution of enzyme reactions and to gain an overview of biological catalysis we have combined sequence and structural data to generate phylogenetic trees in an analysis of 276 structurally defined enzyme superfamilies, and used these to study how enzyme functions have evolved. We describe in detail the analysis of two superfamilies to illustrate different paradigms of enzyme evolution. Gathering together data from all the superfamilies supports and develops the observation that they have all evolved to act on a diverse set of substrates, whilst the evolution of new chemistry is much less common. Despite that, by bringing together so much data, we can provide a comprehensive overview of the most common and rare types of changes in function. Our analysis demonstrates on a larger scale than previously studied, that modifications in overall chemistry still occur, with all possible changes at the primary level of the Enzyme Commission (E.C.) classification observed to a greater or lesser extent. The phylogenetic trees map out the evolutionary route taken within a superfamily, as well as all the possible changes within a superfamily. This has been used to generate a matrix of observed exchanges from one enzyme function to another, revealing the scale and nature of enzyme evolution and that some types of exchanges between and within E.C. classes are more prevalent than others. Surprisingly a large proportion (71%) of all known enzyme functions are performed by this relatively small set of 276 superfamilies. This reinforces the hypothesis that relatively few ancient enzymatic domain superfamilies were progenitors for most of the chemistry required for life.     

Construction of a human glycogene library and comprehensive functional analysis

Eighteen years have passed after the first mammalian glycosyltransferase was cloned. At the beginning of April, 2001, 110 genes for human glycosyltransferases, including modifying enzymes for carbohydrate chains such as sulfotransferases, had been cloned and analyzed. We started the Glycogene Project (GG project) in April 2001, a comprehensive study on human glycogenes with the aid of bioinformatic technology. The term glycogene includes the genes for glycosyltransferases, sulfotransferases adding sulfate to carbohydrates and sugar-nucleotide transporters, etc. Firstly, as many novel genes, which are the candidates for glycogenes, as possible were searched using bioinformatic technology in databases. They were then cloned and expressed in various expression systems to detect the activity for carbohydrate synthesis. Their substrate specificity was determined using various acceptors.     

Cloning and nucleotide sequences of the homoserine dehydrogenase genes (hom) and the threonine synthase genes (thrC) of the gram-negative obligate methylotroph Methylobacillus glycogenes.

We have cloned the homoserine dehydrogenase genes (hom) from the gram-negative obligate methylotrophs Methylobacillus glycogenes ATCC 21276 and ATCC 21371 by complementation of an Escherichia coli homoserine dehydrogenase-deficient mutant. The 4.15-kb DNA fragment cloned from M. glycogenes ATCC 21371 also complemented an E. coli threonine synthase-deficient mutant, suggesting the DNA fragment contained the thrC gene in addition to the hom gene. The homoserine dehydrogenases expressed in the E. coli recombinants were hardly inhibited by L-threonine, L-phenylalanine, or L-methionine. However, they became sensitive to the amino acids after storage at 4 degrees C for 4 days as in M. glycogenes. The structures of the homoserine dehydrogenases overexpressed in E. coli were thought to be different from those in M. glycogenes, probably in subunit numbers of the enzyme, and were thought to have converted to the correct structures during the storage. The nucleotide sequences of the hom and thrC genes were determined. The hom genes of M. glycogenes ATCC 21276 and ATCC 21371 encode peptides with M(r)s of 48,225 and 44,815, respectively. The thrC genes were located 50 bp downstream of the hom genes. The thrC gene of ATCC 21371 encodes a peptide with an M(r) of 52,111, and the gene product of ATCC 21276 was truncated. Northern (RNA) blot analysis suggests that the hom and thrC genes are organized in an operon. Significant homology between the predicted amino acid sequences of the hom and thrC genes and those from other microorganisms was found.     

糖基因在髓性白血病耐药性中特征性改变

目的通过研究糖基因在髓性白血病中的差异表达,明确这些糖基因与白血病耐药的相关性,从而为预测和诊断髓性白血病耐药性,寻求逆转药物提供新策略和靶点。方法采用real-time PCR技术筛选髓性白血病细胞及其耐药细胞株中差异表达的糖基因,筛选出两组细胞差异表达3倍以上的糖基因,初步探索糖基因在髓性白血病耐药性中的特征性改变;采用流式细胞仪分析髓性白血病耐药细胞株与多种FITC标记植物凝集素的结合能力,表征比较细胞膜表面糖链的特征。结果 12个糖基因在NB4和NB4/ADR细胞株中表达具有显著的差异;高表达的糖基因与FITC标记植物凝集素的结合能力增强。结论髓性白血病细胞及其耐药细胞株中糖基因、细胞膜表面糖链特征均有显著差异,这些特征性改变与白血病多药耐药具有相关性。     

Evolution of function in protein superfamilies, from a structural perspective

The recent growth in protein databases has revealed the functional diversity of many protein superfamilies. We have assessed the functional variation of homologous enzyme superfamilies containing two or more enzymes, as defined by the CATH protein structure classification, by way of the Enzyme Commission (EC) scheme. Combining sequence and structure information to identify relatives, the majority of superfamilies display variation in enzyme function, with 25 % of superfamilies in the PDB having members of different enzyme types. We determined the extent of functional similarity at different levels of sequence identity for 486,000 homologous pairs (enzyme/enzyme and enzyme/non-enzyme), with structural and sequence relatives included. For single and multi-domain proteins, variation in EC number is rare above 40 % sequence identity, and above 30 %, the first three digits may be predicted with an accuracy of at least 90 %. For more distantly related proteins sharing less than 30 % sequence identity, functional variation is significant, and below this threshold, structural data are essential for understanding the molecular basis of observed functional differences. To explore the mechanisms for generating functional diversity during evolution, we have studied in detail 31 diverse structural enzyme superfamilies for which structural data are available. A large number of variations and peculiarities are observed, at the atomic level through to gross structural rearrangements. Almost all superfamilies exhibit functional diversity generated by local sequence variation and domain shuffling. Commonly, substrate specificity is diverse across a superfamily, whilst the reaction chemistry is maintained. In many superfamilies, the position of catalytic residues may vary despite playing equivalent functional roles in related proteins. The implications of functional diversity within supefamilies for the structural genomics projects are discussed. More detailed information on these superfamilies is available at http://www.biochem.ucl.ac.uk/bsm/FAM-EC/.     

Glycomic alterations are associated with multidrug resistance in human leukemia

Correlations of disease phenotypes with glycosylation changes have been analyzed intensively in tumor biology field. In this study we describe glycomic alterations of multidrug resistance in human leukemia cell lines. Using multiple glycan profiling tools: real-time PCR for quantification of glycogenes, FITC-lectin binding for glycan profiling, and mass spectrometry for glycan composition, we compared the glycomics of drug-resistant K562/ADR cells with parental K562 line. The results showed that the expression of glycogenes, glycan profiling and N-glycan composition were different in K562/ADR cells, as compared with those in K562 cells, whereas O-glycans of the two cell lines showed no different mass spectra. Further analysis of the N-glycan regulation by way of tunicamycin application or PNGase F treatment in K562/ADR cells showed partial inhibition of biosynthesis and increased sensitivity to chemotherapeutic drugs in vitro. We targeted glycogene B3GNT8 and ST8SIA4, which were over-expressed in K562/ADR cells, and silenced the expression levels of two glycogenes after using RNA interference approach. The results showed that the silencing of B3GNT8 or ST8SIA4 in K562/ADR cells resulted in increased chemosensitivity to anti-tumor drugs. In conclusion, glycomic alterations are responsible for the overcoming multidrug resistance in human leukemia therapy and the N-linked oligosaccharides are associated with the drug resistance of cancer cells.     

Glycosylation diseases: Quo vadis?

About 250 to 500 glycogenes (genes that are directly involved in glycan assembly) are in the human genome representing about 1–2% of the total genome. Over 40 human congenital diseases associated with glycogene mutations have been described to date. It is almost certain that the causative glycogene mutations for many more congenital diseases remain to be discovered. Some glycogenes are involved in the synthesis of only a specific protein and/or a specific class of glycan whereas others play a role in the biosynthesis of more than one glycan class. Mutations in the latter type of glycogene result in complex clinical phenotypes that present difficult diagnostic problems to the clinician. In order to understand in biochemical terms the clinical signs and symptoms of a patient with a glycogene mutation, one must understand how the glycogene works. That requires, first of all, determination of the target protein or proteins of the glycogene followed by an understanding of the role, if any, of the glycogene-dependent glycan in the functions of the protein. Many glycogenes act on thousands of glycoproteins. There are unfortunately no general methods to identify all the potentially large number of glycogene target proteins and which of these proteins are responsible for the mutant phenotypes. Whereas biochemical methods have been highly successful in the discovery of glycogenes responsible for many congenital diseases, it has more recently been necessary to use other methods such as homozygosity mapping. Accurate diagnosis of many recently discovered diseases has become difficult and new diagnostic procedures must be developed. Last but not least is the lack of effective treatment for most of these children and of animal models that can be used to test new therapies.     

Polycladida phylogeny and evolution: integrating evidence from 28S rDNA and morphology

Polyclad flatworms have a troubled classification history, with two contradicting systems in use. They both rely on a ventral adhesive structure to define the suborders Acotylea and Cotylea, but superfamilies were defined according to eyespot arrangement (Prudhoe’s system) or prostatic vesicle characters (Faubel’s system). Molecular data available cover a very limited part of the known polyclad family diversity and have not allowed testing morphology-based classification systems on Polycladida yet. We thus sampled a suitable marker, partial 28S ribosomal DNA (rDNA), from Polycladida (19 families and 32 genera), generating 136 new sequences and the first comprehensive genetic dataset on polyclads. Our maximum likelihood (ML) analyses recovered Polycladida, but the traditional suborders were not monophyletic, as the supposedly acotyleans Cestoplana and Theama were nested within Cotylea; we suggest that these genera should be included in Cotylea. The partial 28S rDNA trees were generally well supported and robust but in conflict with both Faubel’s and Prudhoe’s superfamilies. Therefore, we compiled morphological and anatomical characters for all taxa used and examined their distribution on our molecular tree. Combining morphological and molecular evidence, we redefined polyclad superfamilies. Acotylea contain tentaculated and atentaculated groups and is now divided in three superfamilies. The suborder Cotylea can be divided in five superfamilies. In general, there is a trait of anteriorization of sensory structures, from the plesiomorphic acotylean body plan to the cotylean gross morphology. Traditionally used characters, such as prostatic vesicle, eyespot distribution, and type of pharynx, are all homoplastic and likely have misled polyclad systematics so far.     

Functional site plasticity in domain superfamilies

We present, to our knowledge, the first quantitative analysis of functional site diversity in homologous domain superfamilies. Different types of functional sites are considered separately. Our results show that most diverse superfamilies are very plastic in terms of the spatial location of their functional sites. This is especially true for protein–protein interfaces. In contrast, we confirm that catalytic sites typically occupy only a very small number of topological locations. Small-ligand binding sites are more diverse than expected, although in a more limited manner than protein–protein interfaces. In spite of the observed diversity, our results also confirm the previously reported preferential location of functional sites. We identify a subset of homologous domain superfamilies where diversity is particularly extreme, and discuss possible reasons for such plasticity, i.e. structural diversity. Our results do not contradict previous reports of preferential co-location of sites among homologues, but rather point at the importance of not ignoring other sites, especially in large and diverse superfamilies. Data on sites exploited by different relatives, within each well annotated domain superfamily, has been made accessible from the CATH website in order to highlight versatile superfamilies or superfamilies with highly preferential sites. This information is valuable for system biology and knowledge of any constraints on protein interactions could help in understanding the dynamic control of networks in which these proteins participate. The novelty of our work lies in the comprehensive nature of the analysis – we have used a significantly larger dataset than previous studies – and the fact that in many superfamilies we show that different parts of the domain surface are exploited by different relatives for ligand/protein interactions, particularly in superfamilies which are diverse in sequence and structure, an observation not previously reported on such a large scale. This article is part of a Special Issue entitled: The emerging dynamic view of proteins: Protein plasticity in allostery, evolution and self-assembly.     

Superfamily active site templates

We show that three-dimensional signatures consisting of only a few functionally important residues can be diagnostic of membership in superfamilies of enzymes. Using the enolase superfamily as a model system, we demonstrate that such a signature, or template, can identify superfamily members in structural databases with high sensitivity and specificity. This is remarkable because superfamilies can be highly diverse, with members catalyzing many different overall reactions; the unifying principle can be a conserved partial reaction or chemical capability. Our definition of a superfamily thus hinges on the disposition of residues involved in a conserved function, rather than on fold similarity alone. A clear advantage of basing structure searches on such active site templates rather than on fold similarity is the specificity with which superfamilies with distinct functional characteristics can be identified within a large set of proteins with the same fold, such as the (beta/alpha)8 barrels. Preliminary results are presented for an additional group of enzymes with a different fold, the haloacid dehalogenase superfamily, suggesting that this approach may be generally useful for assigning reading frames of unknown function to specific superfamilies and thereby allowing inference of some of their functional properties.     

Relationships between functional subclasses and information contained in active‐site and ligand‐binding residues in diverse superfamilies

To investigate the relationships between functional subclasses and sequence and structural information contained in the active‐site and ligand‐binding residues (LBRs), we performed a detailed analysis of seven diverse enzyme superfamilies: aldolase class I, TIM‐barrel glycosidases, α/β‐hydrolases, P‐loop containing nucleotide triphosphate hydrolases, collagenase, Zn peptidases, and glutamine phosphoribosylpyrophosphate, subunit 1, domain 1. These homologous superfamilies, as defined in CATH, were selected from the enzyme catalytic‐mechanism database. We defined active‐site and LBRs based solely on the literature information and complex structures in the Protein Data Bank. From a structure‐based multiple sequence alignment for each CATH homologous superfamily, we extracted subsequences consisting of the aligned positions that were used as an active‐site or a ligand‐binding site by at least one sequence. Using both the subsequences and full‐length alignments, we performed cluster analysis with three sequence distance measures. We showed that the cluster analysis using the subsequences was able to detect functional subclasses more accurately than the clustering using the full‐length alignments. The subsequences determined by only the literature information and complex structures, thus, had sufficient information to detect the functional subclasses. Detailed examination of the clustering results provided new insights into the mechanism of functional diversification for these superfamilies. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

Clustering of protein domains in the human genome

We present a systematic study of the clustering of genes within the human genome based on homology inferred from both sequence and structural similarity. The 3D-Genomics automated proteome annotation pipeline () was utilised to infer homology for each protein domain in the genome, for the 26 superfamilies most highly represented in the Structural Classification Of Proteins (SCOP) database. This approach enabled us to identify homologues that could not be detected by sequence-based methods alone. For each superfamily, we investigated the distribution, both within and among chromosomes, of genes encoding at least one domain within the superfamily. The results indicate a diversity of clustering behaviours: some superfamilies showed no evidence of any clustering, and others displayed significant clustering either within or among chromosomes, or both. Removal of tandem repeats reduced the levels of clustering observed, but some superfamilies still displayed highly significant clustering. Thus, our study suggests that either the process of gene duplication, or the evolution of the resulting clusters, differs between structural superfamilies.     

Evolution of enzyme superfamilies

Enzyme evolution is often constrained by aspects of catalysis. Sets of homologous proteins that catalyze different overall reactions but share an aspect of catalysis, such as a common partial reaction, are called mechanistically diverse superfamilies. The common mechanistic steps and structural characteristics of several of these superfamilies, including the enolase, Nudix, amidohydrolase, and haloacid dehalogenase superfamilies have been characterized. In addition, studies of mechanistically diverse superfamilies are helping to elucidate mechanisms of functional diversification, such as catalytic promiscuity. Understanding how enzyme superfamilies evolve is vital for accurate genome annotation, predicting protein functions, and protein engineering.     

Metabolites: a helping hand for pathway evolution?

The evolution of enzymes and pathways is under debate. Recent studies show that recruitment of single enzymes from different pathways could be the driving force for pathway evolution. Other mechanisms of evolution, such as pathway duplication, enzyme specialization, de novo invention of pathways or retro-evolution of pathways, appear to be less abundant. Twenty percent of enzyme superfamilies are quite variable, not only in changing reaction chemistry or metabolite type but in changing both at the same time. These variable superfamilies account for nearly half of all known reactions. The most frequently occurring metabolites provide a helping hand for such changes because they can be accommodated by many enzyme superfamilies. Thus, a picture is emerging in which new pathways are evolving from central metabolites by preference, thereby keeping the overall topology of the metabolic network.