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ABSTRACT: Coiled-coil domains in eukaryotic and prokaryotic proteins contribute to diverse structural and regulatory functions. Here we have used in silico analysis to predict which proteins in the proteome of the enteric pathogen, Salmonella enterica serovar Typhimurium, harbour coiled-coil domains. We found that coiled-coil domains are especially prevalent in virulence-associated proteins, including type III effectors. Using SopB as a model coiled-coil domain type III effector, we have investigated the role of this motif in various aspects of effector function including chaperone binding, secretion and translocation, protein stability, localization and biological activity. Compared with wild-type SopB, SopB coiled-coil mutants were unstable, both inside bacteria and after translocation into host cells. In addition, the putative coiled-coil domain was required for the efficient membrane association of SopB in host cells. Since many other Salmonella effectors were predicted to contain coiled-coil domains, we also investigated the role of this motif in their intracellular targeting in mammalian cells. Mutation of the predicted coiled-coil domains in PipB2, SseJ and SopD2 also eliminated their membrane localization in mammalian cells. These findings suggest that coiled-coil domains represent a common membrane-targeting determinant for Salmonella type III effectors.
Cellular Microbiology 06/2011; 13(10):1497-517. · 5.46 Impact Factor
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ABSTRACT: Based on integrative computational hybrid approaches that combined statistical coupling analysis (SCA), molecular dynamics (MD), and normal mode analysis (NMA), evolutionarily coupled residues involved in functionally relevant motion in the adenylate kinase protein family were identified. The hybrids identified four top-ranking site pairs that belong to a conserved hydrogen bond network that is involved in the enzyme's flexibility. A second group of top-ranking site pairs was identified in critical regions for functional dynamics, such as those related to enzymatic turnover. The high consistency of the results obtained by SCA with NMA (SCA.NMA) and by SCA.MD hybrid analyses suggests that suitable replacement of the matrix of cross-correlation analysis of atomic fluctuations (derived by using NMA) with those based on MD contributes to the identification of such sites by means of a fast computational calculation. The analysis presented here strongly supports the hypothesis that evolutionary forces, such as coevolution at the sequence level, have promoted functional dynamic properties of the adenylate kinase protein family. Finally, these hybrid approaches can be used to identify, at the residue level, protein motion coordination patterns not previously observed, such as in hinge regions.
Proteins Structure Function and Bioinformatics 01/2011; 79(5):1662-71. · 3.39 Impact Factor
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ABSTRACT: Archaea, which represent a large fraction of the phylogenetic diversity of organisms, are prokaryotes with eukaryote-like basal transcriptional machinery. This organization makes the study of their DNA-binding transcription factors (TFs) and their transcriptional regulatory networks particularly interesting. In addition, there are limited experimental data regarding their TFs. In this work, 3,918 TFs were identified and exhaustively analyzed in 52 archaeal genomes. TFs represented less than 5% of the gene products in all the studied species comparable with the number of TFs identified in parasites or intracellular pathogenic bacteria, suggesting a deficit in this class of proteins. A total of 75 families were identified, of which HTH_3, AsnC, TrmB, and ArsR families were universally and abundantly identified in all the archaeal genomes. We found that archaeal TFs are significantly small compared with other protein-coding genes in archaea as well as bacterial TFs, suggesting that a large fraction of these small-sized TFs could supply the probable deficit of TFs in archaea, by possibly forming different combinations of monomers similar to that observed in eukaryotic transcriptional machinery. Our results show that although the DNA-binding domains of archaeal TFs are similar to bacteria, there is an underrepresentation of ligand-binding domains in smaller TFs, which suggests that protein-protein interactions may act as mediators of regulatory feedback, indicating a chimera of bacterial and eukaryotic TFs' functionality. The analysis presented here contributes to the understanding of the details of transcriptional apparatus in archaea and provides a framework for the analysis of regulatory networks in these organisms.
Molecular Biology and Evolution 06/2010; 27(6):1449-59. · 5.55 Impact Factor
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ABSTRACT: Extensive genomic studies on gene duplication in model organisms such as Escherichia coli and Saccharomyces cerevisiae have recently been undertaken. In these models, it is commonly considered that a duplication event may include a transcription factor (TF), a target gene, or both. Following a gene duplication episode, varying scenarios have been postulated to describe the evolution of the regulatory network. However, in most of these, the TFs have emerged as the most important and in some cases the only factor shaping the regulatory network as the organism responds to a natural selection process, in order to fulfil its metabolic needs. Recent findings concerning the regulatory role played by elements other than TFs have indicated the need to reassess these early models. Thus, we performed an exhaustive review of paralogous gene regulation in E. coli and Bacillus subtilis based on published information, available in the NCBI PubMed database and in well-established regulatory databases. Our survey reinforces the notion that despite TFs being the most prominent components shaping the regulatory networks, other elements are also important. These include small RNAs, riboswitches, RNA-binding proteins, sigma factors, protein-protein interactions and DNA supercoiling, which modulate the expression of genes involved in particular metabolic processes or induce a more complex response in terms of the regulatory networks of paralogous genes in an integrated interplay with TFs.
Microbiology 10/2009; 156(Pt 1):14-22. · 3.06 Impact Factor
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ABSTRACT: Escherichia coli K12 and Bacillus subtilis 168 are two of the best characterized bacterial organisms with a long history in molecular biology for understanding various mechanisms in prokaryotic species. However, at the level of transcriptional regulation little is known on a comparative scale. Here we address the question of the degree to which transcription factors (TFs) and their evolutionary families are shared between them. We found that 59 proteins and 28 families are shared between these two bacteria, whereas different subsets were lineage specific. We demonstrate that majority of the common families expand in a lineage-specific manner. More specifically, we found that AraC, ColD, Ebp, LuxR and LysR families are over-represented in E. coli, while ArsR, AsnC, MarR, MerR and TetR families have significantly expanded in B. subtilis. We introduce the notion of regulatory superfamilies based on an empirical number of functional categories regulated by them and show that these families are essentially different in the two bacteria. We further show that global regulators seem to be constrained to smaller regulatory families and generally originate from lineage-specific families. We find that although TF families may be conserved across genomes their functional roles might evolve in a lineage-specific manner and need not be conserved, indicating convergence to be an important phenomenon involved in the functional evolution of TFs of the same family. Although topologically the networks of transcriptional interactions among TF families are similar in both the genomes, we found that the players are different, suggesting different evolutionary origins for the transcriptional regulatory machinery in both bacteria. This study provides evidence from complete repertoires that not only novel families originate in different lineages but conserved TF families expand/contrast in a lineage-specific manner, and suggests that part of the global regulatory mechanisms might originate independently in different lineages.
Computational biology and chemistry 07/2009; 33(4):261-8. · 1.37 Impact Factor
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ABSTRACT: The metabolic, defensive, communicative and pathogenic capabilities of eubacteria depend on their repertoire of genes and ability to regulate the expression of them. Sigma and transcription factors have fundamental roles in controlling these processes. Here, we show that sigma, transcription factors (TFs) and the number of protein coding genes occur in different magnitudes across 291 non-redundant eubacterial genomes. We suggest that these differences can be explained based on the fact that the universe of TFs, in contrast to sigma factors, exhibits a greater flexibility for transcriptional regulation, due to their ability to sense diverse stimuli through a variety of ligand-binding domains by discriminating over longer regions on DNA, through their diverse DNA-binding domains, and by their combinatorial role with other sigmas and TFs. We also note that the diversity of extra-cytoplasmic sigma factors and TF families is constrained in larger genomes. Our results indicate that most widely distributed families across eubacteria are small in size, while large families are relatively limited in their distribution across genomes. Clustering of the distribution of transcription and sigma families across genomes suggests that functional constraints could force their co-evolution, as was observed in sigma54, IHF and EBP families. Our results also indicate that large families might be a consequence of lifestyle, as pathogens and free-living organisms were found to exhibit a major proportion of these expanded families. Our results suggest that understanding proteomes from an integrated perspective, as presented in this study, can be a general framework for uncovering the relationships between different classes of proteins.
Molecular BioSystems 07/2009; 5(12):1494-501. · 3.53 Impact Factor
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ABSTRACT: Twenty amino acids comprise the universal building blocks of proteins. However, their biosynthetic routes do not appear to be universal from an Escherichia coli-centric perspective. Nevertheless, it is necessary to understand their origin and evolution in a global context, that is, to include more 'model' species and alternative routes in order to do so. We use a comparative genomics approach to assess the origins and evolution of alternative amino acid biosynthetic network branches.
By tracking the taxonomic distribution of amino acid biosynthetic enzymes, we predicted a core of widely distributed network branches biosynthesizing at least 16 out of the 20 standard amino acids, suggesting that this core occurred in ancient cells, before the separation of the three cellular domains of life. Additionally, we detail the distribution of two types of alternative branches to this core: analogs, enzymes that catalyze the same reaction (using the same metabolites) and belong to different superfamilies; and 'alternologs', herein defined as branches that, proceeding via different metabolites, converge to the same end product. We suggest that the origin of alternative branches is closely related to different environmental metabolite sources and life-styles among species.
The multi-organismal seed strategy employed in this work improves the precision of dating and determining evolutionary relationships among amino acid biosynthetic branches. This strategy could be extended to diverse metabolic routes and even other biological processes. Additionally, we introduce the concept of 'alternolog', which not only plays an important role in the relationships between structure and function in biological networks, but also, as shown here, has strong implications for their evolution, almost equal to paralogy and analogy.
Genome biology 07/2008; 9(6):R95. · 6.63 Impact Factor
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ABSTRACT: The AraC/XylS family of transcription factors, which include proteins that are involved in the regulation of diverse biological processes, has been of considerable interest recently and has been constantly expanding by means of in silico predictions and experimental analysis. In this work, using a HMM based on the DNA binding domain of 58 experimentally characterized proteins from the AraC/XylS (A/X), 1974 A/X proteins were found in 149 out of 212 bacterial genomes. This domain was used as a template to generate a phylogenetic tree and as a tool to predict the putative regulatory role of the new members of this family based on their proximity to a particular functional cluster in the tree. Based on this approach we assigned a functional regulatory role for 75% of the TFs dataset. Of these, 33.7% regulate genes involved in carbon-source catabolism, 9.6% global metabolism, 8.3% nitrogen metabolism, 2.9% adaptation responses, 8.9% stress responses, and 11.7% virulence. The abundance of TFs involved in the regulation of metabolic processes indicates that bacteria have optimized their regulatory systems to control energy uptake. In contrast, the lower percentage of TFs required for stress, adaptation and virulence regulation reflects the specialization acquired by each subset of TFs associated with those processes. This approach would be useful in assigning regulatory roles to uncharacterized members of other transcriptional factor families and it might facilitate their experimental analysis.
Genetica 06/2008; 133(1):65-76. · 2.15 Impact Factor
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ABSTRACT: Homology detection and protein structure prediction are central themes in bioinformatics. Establishment of relationship between protein sequences or prediction of their structure by sequence comparison methods finds limitations when there is low sequence similarity. Recent works demonstrate that the use of profiles improves homology detection and protein structure prediction. Profiles can be inferred from protein multiple alignments using different approaches. The "Conservatism-of-Conservatism" is an effective profile analysis method to identify structural features between proteins having the same fold but no detectable sequence similarity. The information obtained from protein multiple alignments varies according to the amino acid classification employed to calculate the profile. In this work, we calculated entropy profiles from PSI-BLAST-derived multiple alignments and used different amino acid classifications summarizing almost 500 different attributes. These entropy profiles were converted into pseudocodes which were compared using the FASTA program with an ad-hoc matrix. We tested the performance of our method to identify relationships between proteins with similar fold using a nonredundant subset of sequences having less than 40% of identity. We then compared our results using Coverage Versus Error per query curves, to those obtained by methods like PSI-BLAST, COMPASS and HHSEARCH. Our method, named HIP (Homology Identification with Profiles) presented higher accuracy detecting relationships between proteins with the same fold. The use of different amino acid classifications reflecting a large number of amino acid attributes, improved the recognition of distantly related folds. We propose the use of pseudocodes representing profile information as a fast and powerful tool for homology detection, fold assignment and analysis of evolutionary information enclosed in protein profiles.
Proteins Structure Function and Bioinformatics 02/2008; 70(1):248-56. · 3.39 Impact Factor
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ABSTRACT: Gene duplication followed by divergence is one of the main sources of metabolic versatility. The patchwork and stepwise models of metabolic evolution help us to understand these processes, but their assumptions are relatively simplistic. We used a network-based approach to determine the influence of metabolic constraints on the retention of duplicated genes.
We detected duplicated genes by looking for enzymes sharing homologous domains and uncovered an increased retention of duplicates for enzymes catalyzing consecutive reactions, as illustrated by the ligases acting in the biosynthesis of peptidoglycan. As a consequence, metabolic networks show a high retention of duplicates within functional modules, and we found a preferential biochemical coupling of reactions that partially explains this bias. A similar situation was found in enzyme-enzyme interaction networks, but not in interaction networks of non-enzymatic proteins or gene transcriptional regulatory networks, suggesting that the retention of duplicates results from the biochemical rules governing substrate-enzyme-product relationships. We confirmed a high retention of duplicates between chemically similar reactions, as illustrated by fatty-acid metabolism. The retention of duplicates between chemically dissimilar reactions is, however, also greater than expected by chance. Finally, we detected a significant retention of duplicates as groups, instead of single pairs.
Our results indicate that in silico modeling of the origin and evolution of metabolism is improved by the inclusion of specific functional constraints, such as the preferential biochemical coupling of reactions. We suggest that the stepwise and patchwork models are not independent of each other: in fact, the network perspective enables us to reconcile and combine these models.
Genome biology 02/2007; 8(2):R26. · 6.63 Impact Factor
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ABSTRACT: Bacillus subtilis is one of the best-characterized organisms in Gram-positive bacteria. It represents a paradigm of gene regulation in bacteria due its complex life style (which could involve a transition between stages as diverse as vegetative cell and spore formation). In order to gain insight into the organization and evolution of the B. subtilis regulatory network and to provide an alternative framework for further studies in bacteria, we identified and analyzed its repertoire of DNA-binding transcription factors in terms of their abundance, family distribution and regulated genes.
A collection of 237 DNA-binding Transcription Factors (TFs) was identified in B. subtilis, half of them with experimental evidence. 59% of them were predicted to be repressors, 17% activators, 17% were putatively identified as dual regulatory proteins and the remaining 6.3% could not be associated with a regulatory role. From this collection 56 TFs were found to be autoregulated, most of them negatively, though a significant proportion of positive feedback circuits were also identified. TFs were clustered into 51 regulatory protein families and then traced on 58 genomes from Firmicutes to detect their presence. From this analysis three families were found conserved in all the Firmicutes; fifteen families were distributed in all Firmicutes except in the phyla Mollicutes; two were constrained to Bacillales and finally two families were found to be specific to B. subtilis, due to their specie specific distribution. Repression seems to be the most common regulatory mechanism in Firmicutes due to the high proportion of repressors in the detected collection in these genomes. In addition, six global regulators were defined in B. subtilis based on the number and function of their regulated genes.
In this work we identified and described the characteristics associated to the repertoire of DNA-binding TFs in B. subtilis. We also quantified their abundance, family distribution, and regulatory roles in the context of Firmicutes. This work should not only contribute to our understanding of the regulation of gene expression in bacteria from the perspective of B. subtilis but also provide us the basis for comprehensive modeling of transcriptional regulatory networks in Firmicutes.
BMC Genomics 02/2006; 7:147. · 4.07 Impact Factor
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ABSTRACT: Experimental data on the Escherichia coli transcriptional regulatory system has been used in the past years to predict new regulatory elements (promoters, transcription factors (TFs), TFs' binding sites and operons) within its genome. As more genomes of gamma-proteobacteria are being sequenced, the prediction of these elements in a growing number of organisms has become more feasible, as a step towards the study of how different bacteria respond to environmental changes at the level of transcriptional regulation. In this work, we present TRACTOR_DB (TRAnscription FaCTORs' predicted binding sites in prokaryotic genomes), a relational database that contains computational predictions of new members of 74 regulons in 17 gamma-proteobacterial genomes. For these predictions we used a comparative genomics approach regarding which several proof-of-principle articles for large regulons have been published. TRACTOR_DB may be currently accessed at http://www.bioinfo.cu/Tractor_DB, http://www.tractor.lncc.br/ or at http://www.cifn.unam.mx/Computational_Genomics/tractorDB. Contact Email id is tractor@cifn.unam.mx.
Nucleic Acids Research 02/2005; 33(Database issue):D98-102. · 8.03 Impact Factor
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ABSTRACT: We have addressed the distribution and abundance of 75 transcription factor (TF) families in complete genomes from 90 different bacterial and archaeal species. We found that the proportion of TFs increases with genome size. The deficit of TFs in some genomes might be compensated by the presence of proteins organizing and compacting DNA, such as histone-like proteins. Nine families are represented in all the bacteria and archaea we analyzed, whereas 17 families are specific to bacteria, providing evidence for regulon specialization at an early stage of evolution between the bacterial and archeal lineages. Ten of the 17 families identified in bacteria belong exclusively to the proteobacteria defining a specific signature for this taxonomical group. In bacteria, 10 families are lost mostly in intracellular pathogens and endosymbionts, while 9 families seem to have been horizontally transferred to archaea. The winged helix-turn-helix (HTH) is by far the most abundant structure (motif) in prokaryotes, and might have been the earliest HTH motif to appear as shown by its distribution and abundance in both bacterial and archaeal cellular domains. Horizontal gene transfer and lineage-specific gene losses suggest a progressive elimination of TFs in the course of archaeal and bacterial evolution. This analysis provides a framework for discussing the selective forces directing the evolution of the transcriptional machinery in prokaryotes.
Computational Biology and Chemistry 01/2005; 28(5-6):341-50. · 1.55 Impact Factor
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Nucleic Acids Research. 01/2005; 33:98-102.
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Julio Collado-Vides,
Gabriel Moreno-Hagelsieb, Ernesto Pérez-Rueda,
Heladia Salgado,
Araceli M. Huerta,
Rosa María Gutiérrez,
David A. Rosenblueth,
Andrés Christen,
Esperanza Benítez-Bellón,
Arturo Medrano-Soto,
Socorro Gama-Castro,
Alberto Santos-Zavaleta,
César Bonavides-Martínez,
Edgar Díaz-Peredo,
Fabiola Sánchez-Solano,
Dulce María Millá
Gene Regulations and Metabolism - Postgenomic Computational Approaches; 01/2002
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ABSTRACT: RegulonDB is a database on mechanisms of transcription regulation and operon organization in Escherichia coli K-12. The current version has considerably increased numbers of regulatory elements such as promoters, binding sites and terminators. The complete repertoire of known and predicted DNA-binding transcriptional regulators can be considered to be included in this version. The database now distinguishes different allosteric conformations of regulatory proteins indicating the one active in binding and regulating the different promoters. A new set of operon predictions has been incorporated. The relational design has been modified accordingly. Furthermore, a major improvement is a graphic display enabling browsing of the database with a Java-based graphic user interface with three zoom-levels connected to properties of each chromosomal element. The purpose of these modifications is to make RegulonDB a useful tool and control set for transcriptome experiments. RegulonDB can be accessed on the web at the URL: http://www.cifn.unam.mx/Computational_Biology/regulondb/
