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D Thieffry

Publications and source records attributed to D Thieffry.

At least 19 recordsLinked to original sources
PubMed2001

A logical analysis of the Drosophila gap-gene system.

This manuscript focuses on the formal analysis of the gap-gene network involved in Drosophila segmentation. The gap genes are expressed in defined domains along the anterior-posterior axis of the embryo, as a response to asymmetric maternal information in the oocyte. Though many of the individual interactions among maternal and gap genes are reasonably well understood, we still lack a thorough understanding of the dynamic behavior of the system as a whole. Based on a generalized logical formalization, the present analysis leads to the delineation of: (1) the minimal number of distinct, qualitative, functional levels associated with each of the key regulatory factors (the three maternal Bcd, Hb and Cad products, and the four gap Gt, Hb, Kr and Kni products); (2) the most crucial interactions and regulatory circuits of the earliest stages of the segmentation process; (3) the ordering of different regulatory interactions governed by each of these products according to corresponding concentration scales; and (4) the role of gap-gene cross-interactions in the transformation of graded maternal information into discrete gap-gene expression domains. The proposed model allows not only the qualitative reproduction of the patterns of gene expression characterized experimentally, but also the simulation and prediction of single and multiple mutant phenotypes.

Animals↗
PubMed1999

From global expression data to gene networks.

Allowing the parallel monitoring of the transcription of thousands of genes, microarrays constitute a powerful technique for functional genomics. In a recent paper, a clustering method and a local alignment software were combined to identify DNA motifs in sets of yeast genes endowed with similar transcription profiles throughout mitosis (1). Identifying various known transcriptional binding sites together with new putative ones, the authors made a significant step towards a systematic characterization of the regulatory structure of genomic networks. BioEssays 1999;21:895-899.

Biosensing Techniques↗
PubMed1999

The modularity of biological regulatory networks.

A useful approach to complex regulatory networks consists of modeling their elements and interactions by Boolean equations. In this context, feedback circuits (i.e. circular sequences of interactions) have been shown to play key dynamical roles: whereas positive circuits are able to generate multistationarity, negative circuits may generate oscillatory behavior. In this paper, we principally focus on the case of gene networks. These are represented by fully connected Boolean networks where each element interacts with all elements including itself. Flexibility in network design is introduced by the use of Boolean parameters, one associated with each interaction or group of interactions affecting a given element. Within this formalism, a feedback circuit will generate its typical dynamical behavior (i.e. multistationarity or oscillations) only for appropriate values of some of the logical parameters. Whenever it does, we say that the circuit is 'functional'. More interestingly, this formalism allows the computation of the constraints on the logical parameters to have any feedback circuit functional in a network. Using this methodology, we found that the fraction of the total number of consistent combinations of parameter values that make a circuit functional decreases geometrically with the circuit length. From a biological point of view, this suggests that regulatory networks could be decomposed into small and relatively independent feedback circuits or 'regulatory modules'.

Feedback↗
PubMed1998

RegulonDB: a database on transcriptional regulation in Escherichia coli.

RegulonDB is a DataBase that integrates biological knowledge of the mechanisms that regulate the transcription initiation in Escherichia coli , as well as knowledge on the organization of the genes and regulatory signals into operons in the chromosome. The operon is the basic structure used in RegulonDB to describe the elements and properties of transcriptional regulation. The current version contains information around some 500 regulation mechanisms, essentially for sigma 70 promoters.

Databases, Factual↗
PubMed1998

From specific gene regulation to genomic networks: a global analysis of transcriptional regulation in Escherichia coli.

Because a large number of molecular mechanisms involved in gene regulation have been described during the last decades, it is now becoming possible to address questions about the global structure of gene regulatory networks, at least in the case of some of the best-characterized organisms. This paper presents a global characterization of the transcriptional regulation in Escherichia coli on the basis of the current data. The connectivity of the corresponding network was evaluated by analyzing the distribution of the number of genes regulated by a given regulatory protein, and the distribution of the number of regulatory genes regulating a given regulated gene. The mean connectivity found (between 2 and 3) shows a rather loosely interconnected structure. Special emphasis is given to circular sequences of interactions ("circuits") because of their critical dynamical properties. Only one-element circuits were found, in which negative autoregulation is the dominant architecture. These global properties are discussed in light of several pertinent theoretical approaches, as well as in terms of physiological and evolutionary considerations.

Bacterial Proteins↗
PubMed1998

Prediction of transcriptional regulatory sites in the complete genome sequence of Escherichia coli K-12.

MOTIVATION: As one of the best-characterized free-living organisms, Escherichia coli and its recently completed genomic sequence offer a special opportunity to exploit systematically the variety of regulatory data available in the literature in order to make a comprehensive set of regulatory predictions in the whole genome. RESULTS: The complete genome sequence of E.coli was analyzed for the binding of transcriptional regulators upstream of coding sequences. The biological information contained in RegulonDB (Huerta, A.M. et al., Nucleic Acids Res.,26,55-60, 1998) for 56 different transcriptional proteins was the support to implement a stringent strategy combining string search and weight matrices. We estimate that our search included representatives of 15-25% of the total number of regulatory binding proteins in E.coli. This search was performed on the set of 4288 putative regulatory regions, each 450 bp long. Within the regions with predicted sites, 89% are regulated by one protein and 81% involve only one site. These numbers are reasonably consistent with the distribution of experimental regulatory sites. Regulatory sites are found in 603 regions corresponding to 16% of operon regions and 10% of intra-operonic regions. Additional evidence gives stronger support to some of these predictions, including the position of the site, biological consistency with the function of the downstream gene, as well as genetic evidence for the regulatory interaction. The predictions described here were incorporated into the map presented in the paper describing the complete E.coli genome (Blattner,F.R. et al., Science, 277, 1453-1461, 1997). AVAILABILITY: The complete set of predictions in GenBank format is available at the url: http://www. cifn.unam.mx/Computational_Biology/E.coli-predictions CONTACT: ecoli-reg@cifn.unam.mx, collado@cifn.unam.mx

Bacterial Proteins↗
PubMed1998

Qualitative analysis of gene networks.

In this paper, we review the qualitative tools developed by our group for the analysis of regulatory networks. Focusing on the dynamical and biological roles of feedback circuits, this method can be applied in the context of both logical and differential formalisms. This approach already led to several interesting results about the relation between the network structure and the corresponding dynamical properties. In particular, it could be shown that at least one positive regulatory circuit is necessary to generate multistationarity (i.e., alternative states of gene expression), whereas at least one negative circuit is necessary to generate a stable oscillatory behavior. Applications to the analysis of complex gene networks, as well as to the synthesis of regulatory models to account for global expression data are discussed.

Animals↗
PubMed1997

Establishement of the dorso-ventral pattern during embryonic development of drosophila melanogasater: a logical analysis

This report focuses on dorso-ventral patterning in the segmented region of the Drosophila melanogaster embryo. According to the concept of positional information, this pattern results from the different response of cells to the Dorsal-protein morphogen. This protein shows a distribution gradient along the dorso-ventral axis, with the highest concentration on the ventral side. Using the generalized logical formalism developed by R. Thomas and co-workers, the different cellular responses were analysed in terms of the intracellular loops between the regulatory genes. Two positive loops were found to be involved, each constituting a switch which can be acted upon by the Dorsal morphogen to determine the different cell types that make up the embryonic dorso-ventral pattern. The novelty in this use of generalized logical formalism is the employment of a multilevel variable to represent a morphogen gradient. The proposed model accounts for the essential qualitative effects of the Dorsal gradient in the dorso-ventral determination process. Three main conclusions may be drawn. Firstly, the gene twist needs to have two functional threshold concentrations, one for autoactivation and the other for activation of the gene snail. Secondly, the autoactivation threshold must be smaller than that which activates snail. Thirdly, the action of the gene snail on the maintenance function of the gene twist is crucial for cells to be able to choose between the mesoderm or neuroectoderm developmental pathways. Furthermore, it is predicted that if the gene snail shows autoregulation, this will not be crucial for the determination of the embryonic D-V pattern. Copyright 1997 Academic Press Limited Copyright 1997 Academic Press Limited

Journal Article↗
PubMed1997

Contributions of the 'Rouge-Cloître group' to the notion of 'messenger RNA'.

Most biographical and historical works agree on a common scheme and a few 'founding papers' for the 'discovery' of mRNA. However, a closer scrutiny of these 'founding papers' leads to several unresolved questions with respect to the origin of the notion of mRNA. This paper focuses on the analysis of a set of contributions made by the group of the Rouge-Cloître in order to fill in some of the remaining gaps in the 'standard history'.

Animals↗
PubMed1997

Definite-clause grammars for the analysis of cis-regulatory regions in E. coli.

Based on an extensive collection of sigma 70 associated regulatory mechanisms, a grammatical model has been constructed that define the functional positions and combinations of sites within DNA regulatory regions. The syntactic rules and the dictionary implemented in a Prolog program were coupled to consensus matrices used as "sensors" to integrate a syntactic recognizer. A systematic comparison between the syntactic recognizer and the standard weight matrix methodology is presented using 12 regulatory proteins and the whole collection of about 130 sigma 70 DNA regulatory regions. On the average an increased sensitivity of 5 to 10 fold is obtained with this novel approach.

Binding Sites↗
PubMed1996

Toxicity and neuroendocrine regulation of the immune response: a model analysis.

Various models have been proposed for the regulation of the primary immune response. Most of the models focus on the ability of the immune system to control a multiplying pathogen, and take into account the cross-regulations between different immune components. In the present study, we integrate the immune system in the general physiology of the host and consider the interaction between the immune and neuroendocrine systems. In addition to pathogen growth and toxicity, our four-variable model takes into account the toxic consequences for the organism of the immune response itself, as well as a neuro-hormonal retro-control of this immune response. Formally, the dynamics of the model is first explored on the basis of a discrete caricature, with special emphasis on the role of the constitutive feedback loops for determining the essential dynamical behavior of the system. This logical analysis is then completed by a classical continuous approach using differential equations. From a biological point of view, our model accounts for four stable regimes which can be described as "pathogen elimination/organism healthy", "pathogen elimination/ organism death", "pathogen growth/organism death" and "chronic infection". The size of the basins of attraction of these different regimes varies as a function of some crucial parameters. Our model allows moreover to interpret the interplay between pathogen immunogenicity and neuro-hormonal feedback, the effects of stress on immunity and the toxic shock syndrome, in terms of transitions among the steady states.

Animals↗
PubMed1996

Syntactic recognition of regulatory regions in Escherichia coli.

MOTIVATION: One of the most common methodologies to identify cis-regulatory sites in regulatory regions in the DNA is that of weight matrices, as testified by several articles in this issue. An alternative to strengthen the computational predictions in regulatory regions is to develop methods that incorporate more biological properties present in such DNA regions. The grammatical implementation presented in this paper provides a concrete example in this direction. RESULTS: On the basis of the analysis of an exhaustive collection of regulatory regions in Escherichia coli, a grammatical model for the regulatory regions of sigma 70 promoters has been developed. The terminal symbols of the grammar represent individual sites for the binding of activator and repressor proteins, and include the precise position of sites in relation to transcription initiation. Combining these symbols, the grammar generates a large number of different sentences, each of which can be searched for matching against a collection of regulatory regions by means of weight matrices specific for each set of sites for individual proteins. On the basis of this grammatical model, a Prolog syntactic recognizer is presented here. Specific subgrammars for ArgR, LexA and TyrR were implemented. When parsing a collection of 128 sigma 70 promoter regions, the syntactic recognizer produces a much lower number of false-positive sites than the standard search using weight matrices.

Algorithms↗