Molecular genetics of nucleotide sugar interconversion pathways in plants

Nucleotide sugar interconversion pathways represent a series of enzymatic reactions by which plants synthesize activated monosaccharides for the incorporation into cell wall material. Although biochemical aspects of these metabolic pathways are reasonably well understood, the identification and characterization of genes encoding nucleotide sugar interconversion enzymes is still in its infancy. Arabidopsis mutants defective in the activation and interconversion of specific monosaccharides have recently become available, and several genes in these pathways have been cloned and characterized. The sequence determination of the entire Arabidopsis genome offers a unique opportunity to identify candidate genes encoding nucleotide sugar interconversion enzymes via sequence comparisons to bacterial homologues. An evaluation of the Arabidopsis databases suggests that the majority of these enzymes are encoded by small gene families, and that most of these coding regions are transcribed. Although most of the putative proteins are predicted to be soluble, others contain N-terminal extensions encompassing a transmembrane domain. This suggests that some nucleotide sugar interconversion enzymes are targeted to an endomembrane system, such as the Golgi apparatus, where they may co-localize with glycosyltransferases in cell wall synthesis. The functions of the predicted coding regions can most likely be established via reverse genetic approaches and the expression of proteins in heterologous systems. The genetic characterization of nucleotide sugar interconversion enzymes has the potential to understand the regulation of these complex metabolic pathways and to permit the modification of cell wall material by changing the availability of monosaccharide precursors.     

Evolution and classification of P-loop kinases and related proteins

Sequences and structures of all P-loop-fold proteins were compared with the aim of reconstructing the principal events in the evolution of P-loop-containing kinases. It is shown that kinases and some related proteins comprise a monophyletic assemblage within the P-loop NTPase fold. An evolutionary classification of these proteins was developed using standard phylogenetic methods, analysis of shared sequence and structural signatures, and similarity-based clustering. This analysis resulted in the identification of approximately 40 distinct protein families within the P-loop kinase class. Most of these enzymes phosphorylate nucleosides and nucleotides, as well as sugars, coenzyme precursors, adenosine 5'-phosphosulfate and polynucleotides. In addition, the class includes sulfotransferases, amide bond ligases, pyrimidine and dihydrofolate reductases, and several other families of enzymes that have acquired new catalytic capabilities distinct from the ancestral kinase reaction. Our reconstruction of the early history of the P-loop NTPase fold includes the initial split into the common ancestor of the kinase and the GTPase classes, and the common ancestor of ATPases. This was followed by the divergence of the kinases, which primarily phosphorylated nucleoside monophosphates (NMP), but could have had broader specificity. We provide evidence for the presence of at least two to four distinct P-loop kinases, including distinct forms specific for dNMP and rNMP, and related enzymes in the last universal common ancestor of all extant life forms. Subsequent evolution of kinases seems to have been dominated by the emergence of new bacterial and, to a lesser extent, archaeal families. Some of these enzymes retained their kinase activity but evolved new substrate specificities, whereas others acquired new activities, such as sulfate transfer and reduction. Eukaryotes appear to have acquired most of their kinases via horizontal gene transfer from Bacteria, partly from the mitochondrial and chloroplast endosymbionts and partly at later stages of evolution. A distinct superfamily of kinases, which we designated DxTN after its sequence signature, appears to have evolved in selfish replicons, such as bacteriophages, and was subsequently widely recruited by eukaryotes for multiple functions related to nucleic acid processing and general metabolism. In the course of this analysis, several previously undetected groups of predicted kinases were identified, including widespread archaeo-eukaryotic and archaeal families. The results could serve as a framework for systematic experimental characterization of new biochemical and biological functions of kinases.     

MedicCyc: a biochemical pathway database for Medicago truncatula

MOTIVATION: There is an imperative need to integrate functional genomics data to obtain a more comprehensive systems-biology view of the results. We believe that this is best achieved through the visualization of data within the biological context of metabolic pathways. Accordingly, metabolic pathway reconstruction was used to predict the metabolic composition for Medicago truncatula and these pathways were engineered to enable the correlated visualization of integrated functional genomics data. Results: Metabolic pathway reconstruction was used to generate a pathway database for M. truncatula (MedicCyc), which currently features more than 250 pathways with related genes, enzymes and metabolites. MedicCyc was assembled from more than 225,000 M. truncatula ESTs (MtGI Release 8.0) and available genomic sequences using the Pathway Tools software and the MetaCyc database. The predicted pathways in MedicCyc were verified through comparison with other plant databases such as AraCyc and RiceCyc. The comparison with other plant databases provided crucial information concerning enzymes still missing from the ongoing, but currently incomplete M. truncatula genome sequencing project. MedicCyc was further manually curated to remove non-plant pathways, and Medicago-specific pathways including isoflavonoid, lignin and triterpene saponin biosynthesis were modified or added based upon available literature and in-house expertise. Additional metabolites identified in metabolic profiling experiments were also used for pathway predictions. Once the metabolic reconstruction was completed, MedicCyc was engineered to visualize M. truncatula functional genomics datasets within the biological context of metabolic pathways. Availability: freely accessible at http://www.noble.org/MedicCyc/     

Proteomic identification of M. tuberculosis protein kinase substrates: PknB recruits GarA, a FHA domain-containing protein, through activation loop-mediated interactions

Genes for functional Ser/Thr protein kinases (STPKs) are ubiquitous in prokaryotic genomes, but little is known about their physiological substrates and their actual involvement in bacterial signal transduction pathways. We report here the identification of GarA (Rv1827), a Forkhead-associated (FHA) domain-containing protein, as a putative physiological substrate of PknB, an essential Ser/Thr protein kinase from Mycobacterium tuberculosis. Using a global proteomic approach, GarA was found to be the best detectable substrate of the PknB catalytic domain in non-denatured whole-cell protein extracts from M. tuberculosis and the saprophyte Mycobacterium smegmatis. Enzymological and binding studies of the recombinant proteins demonstrate that docking interactions between the activation loop of PknB and the C-terminal FHA domain of GarA are required to enable efficient phosphorylation at a single N-terminal threonine residue, Thr22, of the substrate. The predicted amino acid sequence of the garA gene, including both the N-terminal phosphorylation motif and the FHA domain, is strongly conserved in mycobacteria and other related actinomycetes, suggesting a functional role of GarA in putative STPK-mediated signal transduction pathways. The ensuing model of PknB-GarA interactions suggests a substrate recruitment mechanism that might apply to other mycobacterial kinases bearing multiple phosphorylation sites in their activation loops.     

Bioinformatic Characterization of Glycyl Radical Enzyme-Associated Bacterial Microcompartments

Bacterial microcompartments (BMCs) are proteinaceous organelles encapsulating enzymes that catalyze sequential reactions of metabolic pathways. BMCs are phylogenetically widespread; however, only a few BMCs have been experimentally characterized. Among them are the carboxysomes and the propanediol- and ethanolamine-utilizing microcompartments, which play diverse metabolic and ecological roles. The substrate of a BMC is defined by its signature enzyme. In catabolic BMCs, this enzyme typically generates an aldehyde. Recently, it was shown that the most prevalent signature enzymes encoded by BMC loci are glycyl radical enzymes, yet little is known about the function of these BMCs. Here we characterize the glycyl radical enzyme-associated microcompartment (GRM) loci using a combination of bioinformatic analyses and active-site and structural modeling to show that the GRMs comprise five subtypes. We predict distinct functions for the GRMs, including the degradation of choline, propanediol, and fuculose phosphate. This is the first family of BMCs for which identification of the signature enzyme is insufficient for predicting function. The distinct GRM functions are also reflected in differences in shell composition and apparently different assembly pathways. The GRMs are the counterparts of the vitamin B₁₂-dependent propanediol- and ethanolamine-utilizing BMCs, which are frequently associated with virulence. This study provides a comprehensive foundation for experimental investigations of the diverse roles of GRMs. Understanding this plasticity of function within a single BMC family, including characterization of differences in permeability and assembly, can inform approaches to BMC bioengineering and the design of therapeutics.     

A Parsimony Approach to Biological Pathway Reconstruction/Inference for Genomes and Metagenomes

A common biological pathway reconstruction approach—as implemented by many automatic biological pathway services (such as the KAAS and RAST servers) and the functional annotation of metagenomic sequences—starts with the identification of protein functions or families (e.g., KO families for the KEGG database and the FIG families for the SEED database) in the query sequences, followed by a direct mapping of the identified protein families onto pathways. Given a predicted patchwork of individual biochemical steps, some metric must be applied in deciding what pathways actually exist in the genome or metagenome represented by the sequences. Commonly, and straightforwardly, a complete biological pathway can be identified in a dataset if at least one of the steps associated with the pathway is found. We report, however, that this naïve mapping approach leads to an inflated estimate of biological pathways, and thus overestimates the functional diversity of the sample from which the DNA sequences are derived. We developed a parsimony approach, called MinPath (Minimal set of Pathways), for biological pathway reconstructions using protein family predictions, which yields a more conservative, yet more faithful, estimation of the biological pathways for a query dataset. MinPath identified far fewer pathways for the genomes collected in the KEGG database—as compared to the naïve mapping approach—eliminating some obviously spurious pathway annotations. Results from applying MinPath to several metagenomes indicate that the common methods used for metagenome annotation may significantly overestimate the biological pathways encoded by microbial communities.     

Sequence and structure classification of kinases

Kinases are a ubiquitous group of enzymes that catalyze the phosphoryl transfer reaction from a phosphate donor (usually ATP) to a receptor substrate. Although all kinases catalyze essentially the same phosphoryl transfer reaction, they display remarkable diversity in their substrate specificity, structure, and the pathways in which they participate. In order to learn the relationship between structural fold and functional specificities in kinases, we have done a comprehensive survey of all available kinase sequences (>17,000) and classified them into 30 distinct families based on sequence similarities. Of these families, 19, covering nearly 98% of all sequences, fall into seven general structural folds for which three-dimensional structures are known. These fold groups include some of the most widespread protein folds, such as Rossmann fold, ferredoxin fold, ribonuclease H fold, and TIM beta/alpha-barrel. On the basis of this classification system, we examined the shared substrate binding and catalytic mechanisms as well as variations of these mechanisms in the same fold groups. Cases of convergent evolution of identical kinase activities occurring in different folds are discussed.     

Metabolic reconstruction of aromatic compounds degradation from the genome of the amazing pollutant-degrading bacterium Cupriavidus necator JMP134

Cupriavidus necator JMP134 is a model for chloroaromatics biodegradation, capable of mineralizing 2,4-D, halobenzoates, chlorophenols and nitrophenols, among other aromatic compounds. We performed the metabolic reconstruction of aromatics degradation, linking the catabolic abilities predicted in silico from the complete genome sequence with the range of compounds that support growth of this bacterium. Of the 140 aromatic compounds tested, 60 serve as a sole carbon and energy source for this strain, strongly correlating with those catabolic abilities predicted from genomic data. Almost all the main ring-cleavage pathways for aromatic compounds are found in C. necator : the β-ketoadipate pathway, with its catechol, chlorocatechol, methylcatechol and protocatechuate ortho ring-cleavage branches; the (methyl)catechol meta ring-cleavage pathway; the gentisate pathway; the homogentisate pathway; the 2,3-dihydroxyphenylpropionate pathway; the (chloro)hydroxyquinol pathway; the (amino)hydroquinone pathway; the phenylacetyl-CoA pathway; the 2-aminobenzoyl-CoA pathway; the benzoyl-CoA pathway and the 3-hydroxyanthranilate pathway. A broad spectrum of peripheral reactions channel substituted aromatics into these ring cleavage pathways. Gene redundancy seems to play a significant role in the catabolic potential of this bacterium. The literature on the biochemistry and genetics of aromatic compounds degradation is reviewed based on the genomic data. The findings on aromatic compounds biodegradation in C. necator reviewed here can easily be extrapolated to other environmentally relevant bacteria, whose genomes also possess a significant proportion of catabolic genes.     

Genome subtraction for novel target definition in Salmonella typhi

Large genomic sequencing projects of pathogens as well as human genome leads to immense genomic and proteomic data which would be very beneficial for the novel target identification in pathogens. Subtractive genomic approach is one of the most useful strategies helpful in identification of potential targets. The approach works by subtracting the genes or proteins homologous to both host and the pathogen and identify those set of gene or proteins which are essential for the pathogen and are exclusively present in the pathogen. Subtractive genomic approach is employed to identify novel target in salmonella typhi. The pathogen has 4718 proteins out of which 300 are found to be essential (“ indispensable to support cellular life”) in the pathogen with no human homolog. Metabolic pathway analyses of these 300 essential proteins revealed that 149 proteins are exclusively involved in several metabolic pathway of S. typhi. 8 metabolic pathways are found to be present exclusively in the pathogen comprising of 27 enzymes unique to the pathogen. Thus, these 27 proteins may serve as prospective drug targets. Sub-cellular localization prediction of the 300 essential proteins was done which reveals that 11 proteins lie on the outer membrane of the pathogen which could be probable vaccine candidates.     

Induction of aromatic catabolic activity in Sphingomonas aromaticivorans strain F199

Enzyme induction studies with Sphingomonas aromaticivorans F199 demonstrated that both toluene and naphthalene induced expression of both naphthalene and toluene catabolic enzymes. However, neither aromatic compound induced expression of all the enzymes required for complete mineralization of either naphthalene or toluene. Activity measurements in combination with gene sequence analyses indicate that growth on either aromatic substrate in the absence of the other is, therefore, sub-optimal and is predicted to lead to the build-up of metabolites due to imbalance in toluene or naphthalene catabolic enzyme activities. Growth on toluene may be further inhibited by the co-expression of two toluene catabolic pathways, as predicted from gene sequence analyses. One of these pathways may potentially result in the formation of a dead-end intermediate, possibly benzaldehyde. In contrast, either p-cresol or benzoate can support high levels of growth. Analyses of promoter region sequences on the F199 aromatic catabolic plasmid, pNL1, suggest that additional regulatory events are modulated through the interaction of BphR with Sigma54 type promoters and through the binding of a regulator upstream of p-cresol catabolic genes and xylM. We hypothesize that the unusual gene clustering in strain F199 is optimized for simultaneous degradation of multiple aromatic compound classes, possibly in response to the heterogeneous composition of aromatic structures in the fossil organic matter present in the deep Atlantic Coastal Plain sediments from which this bacterium was isolated. Received 26 April 1999/ Accepted in revised form 16 August 1999     

Structure-Based Network Analysis of Activation Mechanisms in the ErbB Family of Receptor Tyrosine Kinases: The Regulatory Spine Residues Are Global Mediators of Structural Stability and Allosteric Interactions

The ErbB protein tyrosine kinases are among the most important cell signaling families and mutation-induced modulation of their activity is associated with diverse functions in biological networks and human disease. We have combined molecular dynamics simulations of the ErbB kinases with the protein structure network modeling to characterize the reorganization of the residue interaction networks during conformational equilibrium changes in the normal and oncogenic forms. Structural stability and network analyses have identified local communities integrated around high centrality sites that correspond to the regulatory spine residues. This analysis has provided a quantitative insight to the mechanism of mutation-induced “superacceptor” activity in oncogenic EGFR dimers. We have found that kinase activation may be determined by allosteric interactions between modules of structurally stable residues that synchronize the dynamics in the nucleotide binding site and the αC-helix with the collective motions of the integrating αF-helix and the substrate binding site. The results of this study have pointed to a central role of the conserved His-Arg-Asp (HRD) motif in the catalytic loop and the Asp-Phe-Gly (DFG) motif as key mediators of structural stability and allosteric communications in the ErbB kinases. We have determined that residues that are indispensable for kinase regulation and catalysis often corresponded to the high centrality nodes within the protein structure network and could be distinguished by their unique network signatures. The optimal communication pathways are also controlled by these nodes and may ensure efficient allosteric signaling in the functional kinase state. Structure-based network analysis has quantified subtle effects of ATP binding on conformational dynamics and stability of the EGFR structures. Consistent with the NMR studies, we have found that nucleotide-induced modulation of the residue interaction networks is not limited to the ATP site, and may enhance allosteric cooperativity with the substrate binding region by increasing communication capabilities of mediating residues.     

A human-curated annotation of the Candida albicans genome

Recent sequencing and assembly of the genome for the fungal pathogen Candida albicans used simple automated procedures for the identification of putative genes. We have reviewed the entire assembly, both by hand and with additional bioinformatic resources, to accurately map and describe 6,354 genes and to identify 246 genes whose original database entries contained sequencing errors (or possibly mutations) that affect their reading frame. Comparison with other fungal genomes permitted the identification of numerous fungus-specific genes that might be targeted for antifungal therapy. We also observed that, compared to other fungi, the protein-coding sequences in the C. albicans genome are especially rich in short sequence repeats. Finally, our improved annotation permitted a detailed analysis of several multigene families, and comparative genomic studies showed that C. albicans has a far greater catabolic range, encoding respiratory Complex 1, several novel oxidoreductases and ketone body degrading enzymes, malonyl-CoA and enoyl-CoA carriers, several novel amino acid degrading enzymes, a variety of secreted catabolic lipases and proteases, and numerous transporters to assimilate the resulting nutrients. The results of these efforts will ensure that the Candida research community has uniform and comprehensive genomic information for medical research as well as for future diagnostic and therapeutic applications.     

Deciphering the Arginine-binding preferences at the substrate-binding groove of Ser/Thr kinases by computational surface mapping

Protein kinases are key signaling enzymes that catalyze the transfer of γ-phosphate from an ATP molecule to a phospho-accepting residue in the substrate. Unraveling the molecular features that govern the preference of kinases for particular residues flanking the phosphoacceptor is important for understanding kinase specificities toward their substrates and for designing substrate-like peptidic inhibitors. We applied ANCHORSmap, a new fragment-based computational approach for mapping amino acid side chains on protein surfaces, to predict and characterize the preference of kinases toward Arginine binding. We focus on positions P-2 and P-5, commonly occupied by Arginine (Arg) in substrates of basophilic Ser/Thr kinases. The method accurately identified all the P-2/P-5 Arg binding sites previously determined by X-ray crystallography and produced Arg preferences that corresponded to those experimentally found by peptide arrays. The predicted Arg-binding positions and their associated pockets were analyzed in terms of shape, physicochemical properties, amino acid composition, and in-silico mutagenesis, providing structural rationalization for previously unexplained trends in kinase preferences toward Arg moieties. This methodology sheds light on several kinases that were described in the literature as having non-trivial preferences for Arg, and provides some surprising departures from the prevailing views regarding residues that determine kinase specificity toward Arg. In particular, we found that the preference for a P-5 Arg is not necessarily governed by the 170/230 acidic pair, as was previously assumed, but by several different pairs of acidic residues, selected from positions 133, 169, and 230 (PKA numbering). The acidic residue at position 230 serves as a pivotal element in recognizing Arg from both the P-2 and P-5 positions.