Beyond complete genomes: from sequence to structure and function

Comparative transcriptomic and evolutionary analysis of FAD-like genes of Brassica species revealed their role in fatty acid biosynthesis and stress tolerance

BACKGROUND

Fatty acid desaturases (FADs) are involved in regulating plant fatty acid composition by adding double bonds to growing hydrocarbon chain. Apart from regulating fatty acid composition FADs are of great importance, and are involved in stress responsiveness, plant development, and defense mechanisms. FADs have been extensively studied in crop plants, and are broadly classed into soluble and non-soluble fatty acids. However, FADs have not yet been characterized in Brassica carinata and its progenitors.

RESULTS

Here we have performed comparative genome-wide identification of FADs and have identified 131 soluble and 28 non-soluble FADs in allotetraploid B. carinata and its diploid parents. Most soluble FAD proteins are predicted to be resided in endomembrane system, whereas FAB proteins were found to be localized in chloroplast. Phylogenetic analysis classed the soluble and non-soluble FAD proteins into seven and four clusters, respectively. Positive type of selection seemed to be dominant in both FADs suggesting the impact of evolution on these gene families. Upstream regions of both FADs were enriched in stress related cis-regulatory elements and among them ABRE type of elements were in abundance. Comparative transcriptomic data analysis output highlighted that FADs expression reduced gradually in mature seed and embryonic tissues. Moreover, under heat stress during seed and embryo development seven genes remained up-regulated regardless of external stress. Three FADs were only induced under elevated temperature whereas five genes were upregulated under Xanthomonas campestris stress suggesting their involvement in abiotic and biotic stress response.

CONCLUSIONS

The current study provides insights into the evolution of FADs and their role in B. carinata under stress conditions. Moreover, the functional characterization of stress-related genes would exploit their utilization in future breeding programs of B. carinata and its progenitors.

AtGCS promoter-driven clustered regularly interspaced short palindromic repeats/Cas9 highly efficiently generates homozygous/biallelic mutations in the transformed roots by Agrobacterium rhizogenes-mediated transformation

Agrobacterium rhizogenes-mediated (ARM) transformation is an efficient and powerful tool to generate transgenic roots to study root-related biology. For loss-of-function studies, transgenic-root-induced indel mutations by CRISPR/Cas9 only with homozygous/biallelic mutagenesis can exhibit mutant phenotype(s) (excluding recessive traits). However, a low frequency of homozygous mutants was produced by a constitutive promoter to drive Cas9 expression. Here, we identified a highly efficient Arabidopsis thaliana gamma-glutamylcysteine synthetase promoter, termed AtGCSpro, with strong activity in the region where the root meristem will initiate and in the whole roots in broad eudicots species. AtGCSpro achieved higher homozygous/biallelic mutation efficiency than the most widely used CaMV 35S promoter in driving Cas9 expression in soybean, Lotus japonicus, and tomato roots. Using the pAtGCSpro-Cas9 system, the average homozygous/biallelic mutation frequency is 1.7-fold and 8.3-fold higher than the p2 × 35Spro-Cas9 system for single and two target site(s) in the genome, respectively. Our results demonstrate the advantage of the pAtGCSpro-Cas9 system used in ARM transformation, especially its great potential in diploids with multiple-copy genes targeted mutations and polyploid plants with multiplex genome editing. AtGCSpro is conservatively active in various eudicots species, suggesting that AtGCSpro might be applied in a wide range of dicots species.

Microbial genome analysis: the COG approach

For the past 20 years, the Clusters of Orthologous Genes (COG) database had been a popular tool for microbial genome annotation and comparative genomics. Initially created for the purpose of evolutionary classification of protein families, the COG have been used, apart from straightforward functional annotation of sequenced genomes, for such tasks as (i) unification of genome annotation in groups of related organisms; (ii) identification of missing and/or undetected genes in complete microbial genomes; (iii) analysis of genomic neighborhoods, in many cases allowing prediction of novel functional systems; (iv) analysis of metabolic pathways and prediction of alternative forms of enzymes; (v) comparison of organisms by COG functional categories; and (vi) prioritization of targets for structural and functional characterization. Here we review the principles of the COG approach and discuss its key advantages and drawbacks in microbial genome analysis.

On the evolution of protein-adenine binding

Proteins' interactions with ancient ligands may reveal how molecular recognition emerged and evolved. We explore how proteins recognize adenine: a planar rigid fragment found in the most common and ancient ligands. We have developed a computational pipeline that extracts protein-adenine complexes from the Protein Data Bank, structurally superimposes their adenine fragments, and detects the hydrogen bonds mediating the interaction. Our analysis extends the known motifs of protein-adenine interactions in the Watson-Crick edge of adenine and shows that all of adenine's edges may contribute to molecular recognition. We further show that, on the proteins' side, binding is often mediated by specific amino acid segments ("themes") that recur across different proteins, such that different proteins use the same themes when binding the same adenine-containing ligands. We identify numerous proteins that feature these themes and are thus likely to bind adenine-containing ligands. Our analysis suggests that adenine binding has emerged multiple times in evolution.

Identification of potential drug targets and inhibitor of the pathogenic bacteria Shigella flexneri 2a through the subtractive genomic approach

Shigella flexneri 2a is one of the most pathogenic bacteria among the Shigella spp., which is responsible for dysentery and causes masses of deaths throughout the world per year. A proper identification of the potential drug targets and inhibitors is crucial for the treatment of the shigellosis due to their emerging multidrug resistance (MDR) patterns. In this study, a systematic subtractive approach was implemented for the identification of novel therapeutic targets of S. flexneri 2a (301) through genome-wide metabolic pathway analysis of the essential genes and proteins. Ligand-based virtual screening and ADMET analyses were also made for the identification of potential inhibitors as well. Initially, we found 70 essential unique proteins as novel targets. After subsequent prioritization, finally we got six unique targets as the potential therapeutic targets and their three-dimensional models were built thereafter. Aspartate-β-semialdehyde dehydrogenase (ASD), was the most potent target among them and used for docking analysis through ligand-based virtual screening. The compound 3 (PubChem CID: 11319750) suited well as the best inhibitor of the ASD through ADMET and enzyme inhibition capacity analysis. To end, we hope that our proposed therapeutic targets and its inhibitors might give some breakthrough to treat shigellosis efficiently in in vitro.

Enzyme classification using multiclass support vector machine and feature subset selection

Proteins are the macromolecules responsible for almost all biological processes in a cell. With the availability of large number of protein sequences from different sequencing projects, the challenge with the scientist is to characterize their functions. As the wet lab methods are time consuming and expensive, many computational methods such as FASTA, PSI-BLAST, DNA microarray clustering, and Nearest Neighborhood classification on protein-protein interaction network have been proposed. Support vector machine is one such method that has been used successfully for several problems such as protein fold recognition, protein structure prediction etc. Cai et al. in 2003 have used SVM for classifying proteins into different functional classes and to predict their function. They used the physico-chemical properties of proteins to represent the protein sequences. In this paper a model comprising of feature subset selection followed by multiclass Support Vector Machine is proposed to determine the functional class of a newly generated protein sequence. To train and test the model for its performance, 32 physico-chemical properties of enzymes from 6 enzyme classes are considered. To determine the features that contribute significantly for functional classification, Sequential Forward Floating Selection (SFFS), Orthogonal Forward Selection (OFS), and SVM Recursive Feature Elimination (SVM-RFE) algorithms are used and it is observed that out of 32 properties considered initially, only 20 features are sufficient to classify the proteins into its functional classes with an accuracy ranging from 91% to 94%. On comparison it is seen that, OFS followed by SVM performs better than other methods. Our model generalizes the existing model to include multiclass classification and to identify most significant features affecting the protein function.

Basic units of protein structure, folding, and function

Study of the hierarchy of domain structure with alternative sets of domains and analysis of discontinuous domains, consisting of remote segments of the polypeptide chain, raised a question about the minimal structural unit of the protein domain. The hypothesis on the decisive role of the polypeptide backbone in determining the elementary units of globular proteins have led to the discovery of closed loops. It is reviewed here how closed loops form the loop-n-lock structure of proteins, providing the foundation for stability and designability of protein folds/domain and underlying their co-translational folding. Simplified protein sequences are considered here with the aim to explore the basic principles that presumably dominated the folding and stability of proteins in the early stages of structural evolution. Elementary functional loops (EFLs), closed loops with one or few catalytic residues, are, in turn, units of the protein function. They are apparent descendants of the prebiotic ring-like peptides, which gave rise to the first functional folds/domains being fused in the beginning of the evolution of protein structure. It is also shown how evolutionary relations between protein functional superfamilies and folds delineated with the help of EFLs can contribute to establishing the rules for design of desired enzymatic functions. Generalized descriptors of the elementary functions are proposed to be used as basic units in the future computational design.

Identification of potential drug targets by subtractive genome analysis of Escherichia coli O157:H7: an in silico approach

Bacterial enteric infections resulting in diarrhea, dysentery, or enteric fever constitute a huge public health problem, with more than a billion episodes of disease annually in developing and developed countries. In this study, the deadly agent of hemorrhagic diarrhea and hemolytic uremic syndrome, Escherichia coli O157:H7 was investigated with extensive computational approaches aimed at identifying novel and broad-spectrum antibiotic targets. A systematic in silico workflow consisting of comparative genomics, metabolic pathways analysis, and additional drug prioritizing parameters was used to identify novel drug targets that were essential for the pathogen’s survival but absent in its human host. Comparative genomic analysis of Kyoto Encyclopedia of Genes and Genomes annotated metabolic pathways identified 350 putative target proteins in E. coli O157:H7 which showed no similarity to human proteins. Further bio-informatic approaches including prediction of subcellular localization, calculation of molecular weight, and web-based investigation of 3D structural characteristics greatly aided in filtering the potential drug targets from 350 to 120. Ultimately, 44 non-homologous essential proteins of E. coli O157:H7 were prioritized and proved to have the eligibility to become novel broad-spectrum antibiotic targets and DNA polymerase III alpha (dnaE) was the top-ranked among these targets. Moreover, druggability of each of the identified drug targets was evaluated by the DrugBank database. In addition, 3D structure of the dnaE was modeled and explored further for in silico docking with ligands having potential druggability. Finally, we confirmed that the compounds N-coeleneterazine and N-(1,4-dihydro-5H-tetrazol-5-ylidene)-9-oxo-9H-xanthene-2-sulfon-amide were the most suitable ligands of dnaE and hence proposed as the potential inhibitors of this target protein. The results of this study could facilitate the discovery and release of new and effective drugs against E. coli O157:H7 and other deadly human bacterial pathogens.

Computational model for pathway reconstruction to unravel the evolutionary significance of melanin synthesis

Melanogenesis is a complex multistep process of high molecular weight melanins production by hydroxylation and polymerization of polyphenols. Melanins have a wide range of applications other than being a sun - protection pigment. Melanogenesis pathway exists from prokaryotes to eukaryotes. It has evolved over years owing to the fact that the melanin pigment has different roles in diverse taxa of organisms. Melanin plays a pivotal role in the existence of certain bacteria and fungi whereas in higher organisms it is a measure of protection against the harmful radiation. We have done a detailed study on various pathways known for melanin synthesis across species. It was divulged that melanin production is not restricted to tyrosine but there are other secondary metabolites that synthesize melanin in lower organisms. Furthermore the phylogenetic study of these paths was done to understand their molecular and cellular development. It has revealed that the melanin synthesis paths have co-evolved in several groups of organisms. In this study, we also introduce a method for the comparative analysis of a metabolic pathway to study its evolution based on similarity between enzymatic reactions.

Exploring the evolution of protein function in Archaea

Background

Despite recent progress in studies of the evolution of protein function, the questions what were the first functional protein domains and what were their basic building blocks remain unresolved. Previously, we introduced the concept of elementary functional loops (EFLs), which are the functional units of enzymes that provide elementary reactions in biochemical transformations. They are presumably descendants of primordial catalytic peptides.

Results

We analyzed distant evolutionary connections between protein functions in Archaea based on the EFLs comprising them. We show examples of the involvement of EFLs in new functional domains, as well as reutilization of EFLs and functional domains in building multidomain structures and protein complexes.

Conclusions

Our analysis of the archaeal superkingdom yields the dominating mechanisms in different periods of protein evolution, which resulted in several levels of the organization of biochemical function. First, functional domains emerged as combinations of prebiotic peptides with the very basic functions, such as nucleotide/phosphate and metal cofactor binding. Second, domain recombination brought to the evolutionary scene the multidomain proteins and complexes. Later, reutilization and de novo design of functional domains and elementary functional loops complemented evolution of protein function.

Subtractive genomics approach to identify putative drug targets and identification of drug-like molecules for beta subunit of DNA polymerase III in Streptococcus species

The prolonged use of the antibiotics over the years has transformed many organisms resistant to multiple drugs. This has made the field of drug discovery of vital importance in curing various infections and diseases. The drugs act by binding to a specific target protein of prime importance for the cell's survival. Streptococcus agalactiae, Streptococcus pneumoniae, and Streptococcus pyogenes are the few gram positive organisms that have developed resistance to drugs. It causes pneumonia, meningitis, pharyngitis, otitis media, sinusitis, bacteremia, pericarditis, and arthritis infections. The present study was carried out to identify potential drug targets and inhibitors for beta subunit of DNA polymerase III in these three Streptococcus species that might facilitate the discovery of novel drugs in near future. Various steps were adopted to find out novel drug targets. And finally 3D structure of DNA polymerase III subunit beta was modeled. The ligand library was generated from various databases to find the most suitable ligands. All the ligands were docked using Molegro Virtual Docker and the lead molecules were investigated for ADME and toxicity.

Analysis of NCL Proteins from an Evolutionary Standpoint

The Neuronal Ceroid Lipofuscinoses (NCLs) are the most common group of neurodegenerative disorders of childhood. While mutations in eight different genes have been shown to be responsible for these clinically distinct types of NCL, the NCLs share many clinical and pathological similarities. We have conducted an exhaustive Basic Local Alignment Search Tool (BLAST) analysis of the human protein sequences for each of the eight known NCL proteins- CLN1, CLN2, CLN3, CLN5, CLN6, CLN7, CLN8 and CLN10. The number of homologous species per CLN-protein identified by BLAST searches varies depending on the parameters set for the BLAST search. For example, a lower threshold is able to pull up more homologous sequences whereas a higher threshold decreases this number. Nevertheless, the clade confines are consistent despite this variation in BLAST searching parameters. Further phylogenetic analyses on the appearance of NCL proteins through evolution reveals a different time line for the appearance of the CLN-proteins. Moreover, divergence of each protein shows a different pattern, providing important clues on the evolving role of these proteins. We present and review in-depth bioinformatic analysis of the NCL proteins and classify the CLN-proteins into families based on their structures and evolutionary relationships, respectively. Based on these analyses, we have grouped the CLN-proteins into common clades indicating a common evolving pathway within the evolutionary tree of life. CLN2 is grouped in Eubacteria, CLN1 and CLN10 in Viridiplantae, CLN3 in Fungi/ Metazoa, CLN7 in Bilateria and CLN5, CLN6 and CLN8 in Euteleostomi.

Crystal structure of Sulfolobus tokodaii Sua5 complexed with L-threonine and AMPPNP

The hypermodified nucleoside N(6)-threonylcarbamoyladenosine resides at position 37 of tRNA molecules bearing U at position 36 and maintains translational fidelity in the three kingdoms of life. The N(6)-threonylcarbamoyl moiety is composed of L-threonine and bicarbonate, and its synthesis was genetically shown to require YrdC/Sua5. YrdC/Sua5 binds to tRNA and ATP. In this study, we analyzed the L-threonine-binding mode of Sua5 from the archaeon Sulfolobus tokodaii. Isothermal titration calorimetry measurements revealed that S. tokodaii Sua5 binds L-threonine more strongly than L-serine and glycine. The Kd values of Sua5 for L-threonine and L-serine are 9.3 μM and 2.6 mM, respectively. We determined the crystal structure of S. tokodaii Sua5, complexed with AMPPNP and L-threonine, at 1.8 Å resolution. The L-threonine is bound next to AMPPNP in the same pocket of the N-terminal domain. Thr118 and two water molecules form hydrogen bonds with AMPPNP in a unique manner for adenine-specific recognition. The carboxyl group and the side-chain hydroxyl and methyl groups of L-threonine are buried deep in the pocket, whereas the amino group faces AMPPNP. The L-threonine is located in a suitable position to react together with ATP for the synthesis of N(6)-threonylcarbamoyladenosine.

A new procedure for determining the genetic basis of a physiological process in a non-model species, illustrated by cold induced angiogenesis in the carp

BACKGROUND

Physiological processes occur in many species for which there is yet no sequenced genome and for which we would like to identify the genetic basis. For example, some species increase their vascular network to minimise the effects of reduced oxygen diffusion and increased blood viscosity associated with low temperatures. Since many angiogenic and endothelial genes have been discovered in man, functional homolog relationships between carp, zebrafish and human were used to predict the genetic basis of cold-induced angiogenesis in Cyprinus Carpio (carp). In this work, carp sequences were collected and built into contigs. Human-carp functional homolog relationships were derived via zebrafish using a new Conditional Stepped Reciprocal Best Hit (CSRBH) protocol. Data sources including publications, Gene Ontology and cDNA libraries were then used to predict the identity of known or potential angiogenic genes. Finally, re-analyses of cold carp microarray data identified carp genes up-regulated in response to low temperatures in heart and muscle.

RESULTS

The CSRBH approach outperformed all other methods and attained 8,726 carp to human functional homolog relationships for 16,650 contiguous sequences. This represented 3,762 non-redundant genes and 908 of them were predicted to have a role in angiogenesis. The total number of up-regulated differentially expressed genes was 698 and 171 of them were putatively angiogenic. Of these, 5 genes representing the functional homologs NCL, RHOA, MMP9, GRN and MAPK1 are angiogenesis-related genes expressed in response to low temperature.

CONCLUSION

We show that CSRBH functional homologs relationships and re-analyses of gene expression data can be combined in a non-model species to predict genes of biological interest before a genome sequence is fully available. Programs to run these analyses locally are available from http://www.cbrg.ox.ac.uk/~jherbert/.

Large-Scale Structural Biology of the Human Proteome

The large-scale structural biology projects that target human proteins focus predominantly on the catalytic domains of potential therapeutic targets and the domains of human proteins that mediate protein-protein and protein-small-molecule interactions. Their main scientific objective is to elucidate the molecular basis for specificity and selectivity of function within large protein families of therapeutic interest, such as kinases, phosphatases, and proteins involved in epigenetic regulation. Half of the unique human protein structures determined in the past three years derive from these initiatives.

Expressional profiling study revealed unique expressional patterns and dramatic expressional divergence of maize alpha-zein super gene family

The alpha-zein super gene family encodes the most predominant storage protein in maize (Zea mays) endosperm. In maize inbred line B73, it consists of four gene families with 41 member genes. In this study, we combined quantitative real-time PCR and random clone sequencing to successfully profile the expression of alpha-zein super gene family during endosperm development. We found that only 18 of the 41 member genes were expressed, and their expression levels diverge greatly. At the gene family level, all families had characteristic "up-and-down" oscillating expressional patterns that diverged into two major groups. At the individual gene level, member genes showed dramatic divergence of expression patterns, indicating fast differentiation of their expression regulation. A comparison study among different inbred lines revealed significantly different expressed gene sets, indicating the existence of highly diverged haplotypes. Large gene families containing long gene clusters, e.g. z1A or z1C, mainly contributed the highly divergent haplotypes. In addition, allelic genes also showed significant divergence in their expressional levels. These results indicated a highly dynamic and fast evolving nature to the maize alpha-zein super gene family, which might be a common feature for other large gene families.

InteroPORC: automated inference of highly conserved protein interaction networks

MOTIVATION

Protein-protein interaction networks provide insights into the relationships between the proteins of an organism thereby contributing to a better understanding of cellular processes. Nevertheless, large-scale interaction networks are available for only a few model organisms. Thus, interologs are useful for a systematic transfer of protein interaction networks between organisms. However, no standard tool is available so far for that purpose.

RESULTS

In this study, we present an automated prediction tool developed for all sequenced genomes available in Integr8. We also have developed a second method to predict protein-protein interactions in the widely used cyanobacterium Synechocystis. Using these methods, we have constructed a new network of 8783 inferred interactions for Synechocystis.

AVAILABILITY

InteroPORC is open-source, downloadable and usable through a web interface at http://biodev.extra.cea.fr/interoporc/.

Promiscuous anaerobes: new and unconventional metabolism in methanogenic archaea

The development of an oxygenated atmosphere on earth resulted in the polarization of life into two major groups, those that could live in the presence of oxygen and those that could not-the aerobes and the anaerobes. The evolution of aerobes from the earliest anaerobic prokaryotes resulted in a variety of metabolic adaptations. Many of these adaptations center on the need to sustain oxygen-sensitive reactions and cofactors to function in the new oxygen-containing atmosphere. Still other metabolic pathways that were not sensitive to oxygen also diverged. This is likely due to the physical separation of the organisms, based on their ability to live in the presence of oxygen, which allowed for the independent evolution of the pathways. Through the study of metabolic pathways in anaerobes and comparison to the more established pathways from aerobes, insight into metabolic evolution can be gained. This, in turn, can allow for extra- polation to those metabolic pathways occurring in the Last Universal Common Ancestor (LUCA). Some of the unique and uncanonical metabolic pathways that have been identified in the archaea with emphasis on the biochemistry of an obligate anaerobic methanogen, Methanocaldococcus jannaschii are reviewed.

Protein function space: viewing the limits or limited by our view?

Given that the number of protein functions on earth is finite, the rapid expansion of biological knowledge and the concomitant exponential increase in the number of protein sequences should, at some point, enable the estimation of the limits of protein function space. The functional coverage of protein sequences can be investigated using computational methods, especially given the massive amount of data being generated by large-scale environmental sequencing (metagenomics). In completely sequenced genomes, the fraction of proteins to which at least some functional features can be assigned has recently risen to as much as approximately 85%. Although this fraction is more uncertain in metagenomics surveys, because of environmental complexities and differences in analysis protocols, our global knowledge of protein functions still appears to be considerable. However, when we consider protein families, continued sequencing seems to yield an ever-increasing number of novel families. Until we reconcile these two views, the limits of protein space will remain obscured.

Efficient recognition of protein fold at low sequence identity by conservative application of Psi-BLAST: application

Based on a study involving structural comparisons of proteins sharing 25% or less sequence identity, three rounds of Psi-BLAST appear capable of identifying remote evolutionary homologs with greater than 95% confidence provided that more than 50% of the query sequence can be aligned with the target sequence. Since it seems that more than 80% of all homologous protein pairs may be characterized by a lack of significant sequence similarity, the experimental biologist is often confronted with a lack of guidance from conventional homology searches involving pair-wise sequence comparisons. The ability to disregard levels of sequence identity and expect value in Psi-BLAST if at least 50% of the query sequence has been aligned allows for generation of new hypotheses by consideration of matches that are conventionally disregarded. In one example, we suggest a possible evolutionary linkage between the cupredoxin and immunoglobulin fold families. A thermostable hypothetical protein of unknown function may be a circularly permuted homolog to phosphotriesterase, an enzyme capable of detoxifying organophosphate nerve agents. In a third example, the amino acid sequence of another hypothetical protein of unknown function reveals the ATP binding-site, metal binding site, and catalytic sidechain consistent with kinase activity of unknown specificity. This approach significantly expands the utility of existing sequence data to define the primary structure degeneracy of binding sites for substrates, cofactors and other proteins.

Efficient recognition of protein fold at low sequence identity by conservative application of Psi-BLAST: validation

A substantial fraction of protein sequences derived from genomic analyses is currently classified as representing 'hypothetical proteins of unknown function'. In part, this reflects the limitations of methods for comparison of sequences with very low identity. We evaluated the effectiveness of a Psi-BLAST search strategy to identify proteins of similar fold at low sequence identity. Psi-BLAST searches for structurally characterized low-sequence-identity matches were carried out on a set of over 300 proteins of known structure. Searches were conducted in NCBI's non-redundant database and were limited to three rounds. Some 614 potential homologs with 25% or lower sequence identity to 166 members of the search set were obtained. Disregarding the expect value, level of sequence identity and span of alignment, correspondence of fold between the target and potential homolog was found in more than 95% of the Psi-BLAST matches. Restrictions on expect value or span of alignment improved the false positive rate at the expense of eliminating many true homologs. Approximately three-quarters of the putative homologs obtained by three rounds of Psi-BLAST revealed no significant sequence similarity to the target protein upon direct sequence comparison by BLAST, and therefore could not be found by a conventional search. Although three rounds of Psi-BLAST identified many more homologs than a standard BLAST search, most homologs were undetected. It appears that more than 80% of all homologs to a target protein may be characterized by a lack of significant sequence similarity. We suggest that conservative use of Psi-BLAST has the potential to propose experimentally testable functions for the majority of proteins currently annotated as 'hypothetical proteins of unknown function'.

A Methanocaldococcus jannaschii archaeal signature gene encodes for a 5-formaminoimidazole-4-carboxamide-1-beta-D-ribofuranosyl 5'-monophosphate synthetase. A new enzyme in purine biosynthesis

We have identified and characterized a new member of the ATP-grasp enzyme family that catalyzes the ATP- and formate-dependent formylation of 5-aminoimidazole-4-carboxamide-1-beta-D-ribofuranosyl 5'-monophosphate (AICAR) to 5-formaminoimidazole-4-carboxamide-1-beta-D-ribofuranosyl 5'-monophosphate (FAICAR) in the absence of folates. The enzyme, which we designate as PurP, is the product of the Methanocaldococcus jannaschii purP gene (MJ0136), which is a signature gene for Archaea. As is characteristic of reactions catalyzed by this family of enzymes, the other products of the reaction, ADP and P(i), were produced stoichiometrically with the amount of ATP, formate, and AICAR used. Formyl phosphate was found to substitute for ATP and formate in the reaction, yet the methylene analog, phosphonoacetaldehyde, was not an inhibitor or substrate for the reaction. The enzyme, along with PurO, which catalyzes the cyclization of FAICAR to inosine 5'-monophosphate, catalyzes the same overall transformation in purine biosynthesis as is accomplished by PurH in bacteria and eukaryotes. No homology exists between PurH and either PurO or PurP. 1H NMR and gas chromatography-mass spectrometry analysis of an M. jannaschii cell extract showed the presence of free formate that can be used by the enzyme for purine biosynthesis. This formate arises by the reduction of CO2 with hydrogen; this was demonstrated by incorporating 13C into the formate when M. jannaschii cell extracts were incubated with H13CO3- and hydrogen gas. The presence of this signature gene in all of the Archaea indicates the presence of a purine biosynthetic pathway proceeding in the absence of folate coenzymes.

Halometabolites and cellular dehalogenase systems: an evolutionary perspective

We review the role of iodothyronine deiodinases (IDs) in the evolution of vertebrate thyroidal systems within the larger context of biological metabolism of halogens. Since the beginning of life, the ubiquity of organohalogens in the biosphere has provided a major selective pressure for the evolution and conservation of cellular mechanisms specialized in halogen metabolism. Among naturally available halogens, iodine emerged as a critical component of unique developmental and metabolic messengers. Metabolism of iodinated compounds occurs in the three major domains of life, and invertebrate deuterostomes possess several biochemical traits and molecular homologs of vertebrate thyroidal systems, including ancestral homologs of IDs identified in urochordates. The finely tuned cellular regulation of iodometabolite uptake and disposal is a remarkable event in evolution and might have been decisive for the explosive diversification of ontogenetic strategies in vertebrates.

Protein function classification via support vector machine approach

Support vector machine (SVM) is introduced as a method for the classification of proteins into functionally distinguished classes. Studies are conducted on a number of protein classes including RNA-binding proteins; protein homodimers, proteins responsible for drug absorption, proteins involved in drug distribution and excretion, and drug metabolizing enzymes. Testing accuracy for the classification of these protein classes is found to be in the range of 84-96%. This suggests the usefulness of SVM in the classification of protein functional classes and its potential application in protein function prediction.

Diversity, taxonomy and evolution of medium-chain dehydrogenase/reductase superfamily

A comprehensive, structural and functional, in silico analysis of the medium-chain dehydrogenase/reductase (MDR) superfamily, including 583 proteins, was carried out by use of extensive database mining and the blastp program in an iterative manner to identify all known members of the superfamily. Based on phylogenetic, sequence, and functional similarities, the protein members of the MDR superfamily were classified into three different taxonomic categories: (a) subfamilies, consisting of a closed group containing a set of ideally orthologous proteins that perform the same function; (b) families, each comprising a cluster of monophyletic subfamilies that possess significant sequence identity among them and might share or not common substrates or mechanisms of reaction; and (c) macrofamilies, each comprising a cluster of monophyletic protein families with protein members from the three domains of life, which includes at least one subfamily member that displays activity related to a very ancient metabolic pathway. In this context, a superfamily is a group of homologous protein families (and/or macrofamilies) with monophyletic origin that shares at least a barely detectable sequence similarity, but showing the same 3D fold. The MDR superfamily encloses three macrofamilies, with eight families and 49 subfamilies. These subfamilies exhibit great functional diversity including noncatalytic members with different subcellular, phylogenetic, and species distributions. This results from constant enzymogenesis and proteinogenesis within each kingdom, and highlights the huge plasticity that MDR superfamily members possess. Thus, through evolution a great number of taxa-specific new functions were acquired by MDRs. The generation of new functions fulfilled by proteins, can be considered as the essence of protein evolution. The mechanisms of protein evolution inside MDR are not constrained to conserve substrate specificity and/or chemistry of catalysis. In consequence, MDR functional diversity is more complex than sequence diversity. MDR is a very ancient protein superfamily that existed in the last universal common ancestor. It had at least two (and probably three) different ancestral activities related to formaldehyde metabolism and alcoholic fermentation. Eukaryotic members of this superfamily are more related to bacterial than to archaeal members; horizontal gene transfer among the domains of life appears to be a rare event in modern organisms.

Genome-wide comparative phylogenetic analysis of the rice and Arabidopsis Dof gene families

BACKGROUND

Dof proteins are a family of plant-specific transcription factors that contain a particular class of zinc-finger DNA-binding domain. Members of this family have been found to play diverse roles in gene regulation of processes restricted to the plants. The completed genome sequences of rice and Arabidopsis constitute a valuable resource for comparative genomic analyses, since they are representatives of the two major evolutionary lineages within the angiosperms. In this framework, the identification of phylogenetic relationships among Dof proteins in these species is a fundamental step to unravel functionality of new and yet uncharacterised genes belonging to this group.

RESULTS

We identified 30 different Dof genes in the rice Oryza sativa genome and performed a phylogenetic analysis of a complete collection of the 36-reported Arabidopsis thaliana and the rice Dof transcription factors identified herein. This analysis led to a classification into four major clusters of orthologous genes and showed gene loss and duplication events in Arabidopsis and rice, that occurred before and after the last common ancestor of the two species.

CONCLUSIONS

According to our analysis, the Dof gene family in angiosperms is organized in four major clusters of orthologous genes or subfamilies. The proposed clusters of orthology and their further analysis suggest the existence of monocot specific genes and invite to explore their functionality in relation to the distinct physiological characteristics of these evolutionary groups.

Biotechnological manufacture of lysine

L-Lysine has been manufactured using Corynebacterium glutamicum for more than 40 years. Nowadays production exceeds 600,000 tons per year. Based on conventionally bred strains, further improvement of lysine productivity has been achieved by genetic engineering. Pyruvate carboxylase, aspartate kinase, dihydrodipicolinate synthase, homoserine dehydrogenase and the specific lysine exporter were shown to be key enzymes for lysine production and were characterized in detail. Their combined engineering led to a striking increase in lysine formation. Pathway modeling with data emerging from 13C-isotope experiments revealed a coordinated flux through pentose phosphate cycle and tricarboxylic acid cycle and intensive futile cycling between C3 compounds of glycolysis and C4 compounds of tricarboxylic acid cycle. Process economics have been optimized by developing repeated fed-batch techniques and technical continuous fermentations. In addition, on-line metabolic pathway analysis or flow cytometry may help to improve the fermentation performance. Finally, the availability of the Corynebacterium glutamicum genome sequence has a major impact on the improvement of the biotechnological manufacture of lysine. In this context, all genes of the carbon flow from sugar uptake to lysine secretion have been identified and are accessible to manipulation. The whole sequence information gives access to post genome technologies such as transcriptome analysis, investigation of the proteome and the active metabolic network. These multi-parallel working technologies will accelerate the generation of knowledge. For the first time there is a chance of understanding the overall picture of the physiological state of lysine overproduction in a technical environment.

Dictionary-driven protein annotation

Computational methods seeking to automatically determine the properties (functional, structural, physicochemical, etc.) of a protein directly from the sequence have long been the focus of numerous research groups. With the advent of advanced sequencing methods and systems, the number of amino acid sequences that are being deposited in the public databases has been increasing steadily. This has in turn generated a renewed demand for automated approaches that can annotate individual sequences and complete genomes quickly, exhaustively and objectively. In this paper, we present one such approach that is centered around and exploits the Bio-Dictionary, a collection of amino acid patterns that completely covers the natural sequence space and can capture functional and structural signals that have been reused during evolution, within and across protein families. Our annotation approach also makes use of a weighted, position-specific scoring scheme that is unaffected by the over-representation of well-conserved proteins and protein fragments in the databases used. For a given query sequence, the method permits one to determine, in a single pass, the following: local and global similarities between the query and any protein already present in a public database; the likeness of the query to all available archaeal/ bacterial/eukaryotic/viral sequences in the database as a function of amino acid position within the query; the character of secondary structure of the query as a function of amino acid position within the query; the cytoplasmic, transmembrane or extracellular behavior of the query; the nature and position of binding domains, active sites, post-translationally modified sites, signal peptides, etc. In terms of performance, the proposed method is exhaustive, objective and allows for the rapid annotation of individual sequences and full genomes. Annotation examples are presented and discussed in Results, including individual queries and complete genomes that were released publicly after we built the Bio-Dictionary that is used in our experiments. Finally, we have computed the annotations of more than 70 complete genomes and made them available on the World Wide Web at http://cbcsrv.watson.ibm.com/Annotations/.

A theoretical limit to coding space in chromosomes of bacteria

A mathematical model of cluster patterns for mapped genes with known phenotypes in Escherichia coli predicted thatfunctional genes may account for a maximum of two-thirds of the total chromosomal space. The corollary prediction was that one-third of the chromosome comprised noncoding space. Open reading frame (ORF) analyses for 15 phylogenetically diverse bacterial genomes and for 30 fully sequenced prokaryotic genomes supported the gene cluster model prediction of a two-thirds tendency for coding space. Our results suggest that only 3-4% of unassigned ORFs in E. coli represent genes with potential phenotype and that ORFs marking novel genes in prokaryotes are far fewer than previously thought.

Trm7p catalyses the formation of two 2'-O-methylriboses in yeast tRNA anticodon loop

The genome of Saccharomyces cerevisiae encodes three close homologues of the Escherichia coli 2'-O-rRNA methyltransferase FtsJ/RrmJ, designated Trm7p, Spb1p and Mrm2p. We present evidence that Trm7p methylates the 2'-O-ribose of nucleotides at positions 32 and 34 of the tRNA anticodon loop, both in vivo and in vitro. In a trm7Delta strain, which is viable but grows slowly, translation is impaired, thus indicating that these tRNA modifications could be important for translation efficiency. We discuss the emergence of a family of three 2'-O-RNA methyltransferases in Eukaryota and one in Prokaryota from a common ancestor. We propose that each eukaryotic enzyme is located in a different cell compartment, in which it would methylate a different RNA that can adopt a very similar secondary structure.

Bioinformatics tools for whole genomes

The advent of whole-genome data resources--not only sequence but also other genome-scale data collections such as gene expression, protein interaction, and genetic variation--is having two marked, complementary effects on the relatively new discipline of bioinformatics. First, the veritable flood of data is creating a need and demand for new tools for dealing adequately with the deluge, and, second, the unprecedented extent, diversity, and impending completeness of the data sets are creating opportunities for new approaches to discovery based on computational methods.

Gene family evolution and homology: genomics meets phylogenetics

With the advent of high-throughput DNA sequencing and whole-genome analysis, it has become clear that the coding portions of the genome are organized hierarchically in gene families and superfamilies. Because the hierarchy of genes, like that of living organisms, reflects an ancient and continuing process of gene duplication and divergence, many of the conceptual and analytical tools used in phylogenetic systematics can and should be used in comparative genomics. Phylogenetic principles and techniques for assessing homology, inferring relationships among genes, and reconstructing evolutionary events provide a powerful way to interpret the ever increasing body of sequence data. In this review, we outline the application of phylogenetic approaches to comparative genomics, beginning with the inference of phylogeny and the assessment of gene orthology and paralogy. We also show how the phylogenetic approach makes possible novel kinds of comparative analysis, including detection of domain shuffling and lateral gene transfer, reconstruction of the evolutionary diversification of gene families, tracing of evolutionary change in protein function at the amino acid level, and prediction of structure-function relationships. A marriage of the principles of phylogenetic systematics with the copious data generated by genomics promises unprecedented insights into the nature of biological organization and the historical processes that created it.

Comparative genomics using data mining tools

We have analysed the genomes of representatives of three kingdoms of life, namely, archaea, eubacteria and eukaryota using data mining tools based on compositional analyses of the protein sequences. The representatives chosen in this analysis were Methanococcus jannaschii, Haemophilus influenzae and Saccharomyces cerevisiae. We have identified the common and different features between the three genomes in the protein evolution patterns. M. jannaschii has been seen to have a greater number of proteins with more charged amino acids whereas S. cerevisiae has been observed to have a greater number of hydrophilic proteins. Despite the differences in intrinsic compositional characteristics between the proteins from the different genomes we have also identified certain common characteristics. We have carried out exploratory Principal Component Analysis of the multivariate data on the proteins of each organism in an effort to classify the proteins into clusters. Interestingly, we found that most of the proteins in each organism cluster closely together, but there are a few 'outliers'. We focus on the outliers for the functional investigations, which may aid in revealing any unique features of the biology of the respective organisms

TTD: Therapeutic Target Database

A number of proteins and nucleic acids have been explored as therapeutic targets. These targets are subjects of interest in different areas of biomedical and pharmaceutical research and in the development and evaluation of bioinformatics, molecular modeling, computer-aided drug design and analytical tools. A publicly accessible database that provides comprehensive information about these targets is therefore helpful to the relevant communities. The Therapeutic Target Database (TTD) is designed to provide information about the known therapeutic protein and nucleic acid targets described in the literature, the targeted disease conditions, the pathway information and the corresponding drugs/ligands directed at each of these targets. Cross-links to other databases are also introduced to facilitate the access of information about the sequence, 3D structure, function, nomenclature, drug/ligand binding properties, drug usage and effects, and related literature for each target. This database can be accessed at http://xin.cz3.nus.edu.sg/group/ttd/ttd.asp and it currently contains entries for 433 targets covering 125 disease conditions along with 809 drugs/ligands directed at each of these targets. Each entry can be retrieved through multiple methods including target name, disease name, drug/ligand name, drug/ligand function and drug therapeutic classification.

High-density miniaturized thermal shift assays as a general strategy for drug discovery

More general and universally applicable drug discovery assay technologies are needed in order to keep pace with the recent advances in combinatorial chemistry and genomics-based target generation. Ligand-induced conformational stabilization of proteins is a well-understood phenomenon in which substrates, inhibitors, cofactors, and even other proteins provide enhanced stability to proteins on binding. This phenomenon is based on the energetic coupling of the ligand-binding and protein-melting reactions. In an attempt to harness these biophysical properties for drug discovery, fully automated instrumentation was designed and implemented to perform miniaturized fluorescence-based thermal shift assays in a microplate format for the high throughput screening of compound libraries. Validation of this process and instrumentation was achieved by investigating ligand binding to more than 100 protein targets. The general applicability of the thermal shift screening strategy was found to be an important advantage because it circumvents the need to design and retool new assays with each new therapeutic target. Moreover, the miniaturized thermal shift assay methodology does not require any prior knowledge of a therapeutic target's function, making it ideally suited for the quantitative high throughput drug screening and evaluation of targets derived from genomics.

Conserved core structure and active site residues in alkaline phosphatase superfamily enzymes

Cofactor-independent phosphoglycerate mutase (iPGM) has been previously identified as a member of the alkaline phosphatase (AlkP) superfamily of enzymes, based on the conservation of the predicted metal-binding residues. Structural alignment of iPGM with AlkP and cerebroside sulfatase confirmed that all these enzymes have a common core structure and revealed similarly located conserved Ser (in iPGM and AlkP) or Cys (in sulfatases) residues in their active sites. In AlkP, this Ser residue is phosphorylated during catalysis, whereas in sulfatases the active site Cys residues are modified to formylglycine and sulfatated. Similarly located Thr residue forms a phosphoenzyme intermediate in one more enzyme of the AlkP superfamily, alkaline phosphodiesterase/nucleotide pyrophosphatase PC-1 (autotaxin). Using structure-based sequence alignment, we identified homologous Ser, Thr, or Cys residues in other enzymes of the AlkP superfamily, such as phosphopentomutase, phosphoglycerol transferase, phosphonoacetate hydrolase, and GPI-anchoring enzymes (glycosylphosphatidylinositol phosphoethanolamine transferases) MCD4, GPI7, and GPI13. We predict that catalytical cycles of all the enzymes of AlkP superfamily include phosphoenzyme (or sulfoenzyme) intermediates.

Automatic discovery of sub-molecular sequence domains in multi-aligned sequences: a dynamic programming algorithm for multiple alignment segmentation

Automatic identification of sub-structures in multi-aligned sequences is of great importance for effective and objective structural/functional domain annotation, phylogenetic treeing and other molecular analyses. We present a segmentation algorithm that optimally partitions a given multi-alignment into a set of potentially biologically significant blocks, or segments. This algorithm applies dynamic programming and progressive optimization to the statistical profile of a multi-alignment in order to optimally demarcate relatively homogenous sub-regions. Using this algorithm, a large multi-alignment of eukaryotic 16S rRNA was analyzed. Three types of sequence patterns were identified automatically and efficiently: shared conserved domain; shared variable motif; and rare signature sequence. Results were consistent with the patterns identified through independent phylogenetic and structural approaches. This algorithm facilitates the automation of sequence-based molecular structural and evolutionary analyses through statistical modeling and high performance computation.

Sodium ion cycle in bacterial pathogens: evidence from cross-genome comparisons

Analysis of the bacterial genome sequences shows that many human and animal pathogens encode primary membrane Na+ pumps, Na+-transporting dicarboxylate decarboxylases or Na+ translocating NADH:ubiquinone oxidoreductase, and a number of Na+ -dependent permeases. This indicates that these bacteria can utilize Na+ as a coupling ion instead of or in addition to the H+ cycle. This capability to use a Na+ cycle might be an important virulence factor for such pathogens as Vibrio cholerae, Neisseria meningitidis, Salmonella enterica serovar Typhi, and Yersinia pestis. In Treponema pallidum, Chlamydia trachomatis, and Chlamydia pneumoniae, the Na+ gradient may well be the only energy source for secondary transport. A survey of preliminary genome sequences of Porphyromonas gingivalis, Actinobacillus actinomycetemcomitans, and Treponema denticola indicates that these oral pathogens also rely on the Na+ cycle for at least part of their energy metabolism. The possible roles of the Na+ cycling in the energy metabolism and pathogenicity of these organisms are reviewed. The recent discovery of an effective natural antibiotic, korormicin, targeted against the Na+ -translocating NADH:ubiquinone oxidoreductase, suggests a potential use of Na+ pumps as drug targets and/or vaccine candidates. The antimicrobial potential of other inhibitors of the Na+ cycle, such as monensin, Li+ and Ag+ ions, and amiloride derivatives, is discussed.

Isolation of PDX2, a second novel gene in the pyridoxine biosynthesis pathway of eukaryotes, archaebacteria, and a subset of eubacteria

In this paper we describe the isolation of a second gene in the newly identified pyridoxine biosynthesis pathway of archaebacteria, some eubacteria, fungi, and plants. Although pyridoxine biosynthesis has been thoroughly examined in Escherichia coli, recent characterization of the Cercospora nicotianae biosynthesis gene PDX1 led to the discovery that most organisms contain a pyridoxine synthesis gene not found in E. coli. PDX2 was isolated by a degenerate primer strategy based on conserved sequences of a gene specific to PDX1-containing organisms. The role of PDX2 in pyridoxine biosynthesis was confirmed by complementation of two C. nicotianae pyridoxine auxotrophs not mutant in PDX1. Also, targeted gene replacement of PDX2 in C. nicotianae results in pyridoxine auxotrophy. Comparable to PDX1, PDX2 homologues are not found in any of the organisms with homologues to the E. coli pyridoxine genes, but are found in the same archaebacteria, eubacteria, fungi, and plants that contain PDX1 homologues. PDX2 proteins are less well conserved than their PDX1 counterparts but contain several protein motifs that are conserved throughout all PDX2 proteins.

A comparative genomics approach to prediction of new members of regulons

Identifying the complete transcriptional regulatory network for an organism is a major challenge. For each regulatory protein, we want to know all the genes it regulates, that is, its regulon. Examples of known binding sites can be used to estimate the binding specificity of the protein and to predict other binding sites. However, binding site predictions can be unreliable because determining the true specificity of the protein is difficult because of the considerable variability of binding sites. Because regulatory systems tend to be conserved through evolution, we can use comparisons between species to increase the reliability of binding site predictions. In this article, an approach is presented to evaluate the computational predictions of regulatory sites. We combine the prediction of transcription units having orthologous genes with the prediction of transcription factor binding sites based on probabilistic models. We augment the sets of genes in Escherichia coli that are expected to be regulated by two transcription factors, the cAMP receptor protein and the fumarate and nitrate reduction regulatory protein, through a comparison with the Haemophilus influenzae genome. At the same time, we learned more about the regulatory networks of H. influenzae, a species with much less experimental knowledge than E. coli. By studying orthologous genes subject to regulation by the same transcription factor, we also gained understanding of the evolution of the entire regulatory systems.