Understanding the Dynamics of Gene Regulatory Systems : Characterisation and Clinical Relevance of cis-Regulatory Polymorphisms

Peer reviewedPublisher PD

Synthetic biology—putting engineering into biology

Synthetic biology is interpreted as the engineering-driven building of increasingly complex biological entities for novel applications. Encouraged by progress in the design of artificial gene networks, de novo DNA synthesis and protein engineering, we review the case for this emerging discipline. Key aspects of an engineering approach are purpose-orientation, deep insight into the underlying scientific principles, a hierarchy of abstraction including suitable interfaces between and within the levels of the hierarchy, standardization and the separation of design and fabrication. Synthetic biology investigates possibilities to implement these requirements into the process of engineering biological systems. This is illustrated on the DNA level by the implementation of engineering-inspired artificial operations such as toggle switching, oscillating or production of spatial patterns. On the protein level, the functionally self-contained domain structure of a number of proteins suggests possibilities for essentially Lego-like recombination which can be exploited for reprogramming DNA binding domain specificities or signaling pathways. Alternatively, computational design emerges to rationally reprogram enzyme function. Finally, the increasing facility of de novo DNA synthesis—synthetic biology’s system fabrication process—supplies the possibility to implement novel designs for ever more complex systems. Some of these elements have merged to realize the first tangible synthetic biology applications in the area of manufacturing of pharmaceutical compounds.

Needed for completion of the human genome: hypothesis driven experiments and biologically realistic mathematical models

With the sponsorship of ``Fundacio La Caixa'' we met in Barcelona, November 21st and 22nd, to analyze the reasons why, after the completion of the human genome sequence, the identification all protein coding genes and their variants remains a distant goal. Here we report on our discussions and summarize some of the major challenges that need to be overcome in order to complete the human gene catalog.Comment: Report and discussion resulting from the `Fundacio La Caixa' gene finding meeting held November 21 and 22 2003 in Barcelon

Dynamics of transcription factor binding site evolution

Evolution of gene regulation is crucial for our understanding of the phenotypic differences between species, populations and individuals. Sequence-specific binding of transcription factors to the regulatory regions on the DNA is a key regulatory mechanism that determines gene expression and hence heritable phenotypic variation. We use a biophysical model for directional selection on gene expression to estimate the rates of gain and loss of transcription factor binding sites (TFBS) in finite populations under both point and insertion/deletion mutations. Our results show that these rates are typically slow for a single TFBS in an isolated DNA region, unless the selection is extremely strong. These rates decrease drastically with increasing TFBS length or increasingly specific protein-DNA interactions, making the evolution of sites longer than ~10 bp unlikely on typical eukaryotic speciation timescales. Similarly, evolution converges to the stationary distribution of binding sequences very slowly, making the equilibrium assumption questionable. The availability of longer regulatory sequences in which multiple binding sites can evolve simultaneously, the presence of "pre-sites" or partially decayed old sites in the initial sequence, and biophysical cooperativity between transcription factors, can all facilitate gain of TFBS and reconcile theoretical calculations with timescales inferred from comparative genetics.Comment: 28 pages, 15 figure

Molecular mechanisms of transcription initiation—structure, function, and evolution of TFE/TFIIE-like factors and open complex formation

Transcription initiation requires that the promoter DNA is melted and the template strand is loaded into the active site of the RNA polymerase (RNAP), forming the open complex (OC). The archaeal initiation factor TFE and its eukaryotic counterpart TFIIE facilitate this process. Recent structural and biophysical studies have revealed the position of TFE/TFIIE within the pre-initiation complex (PIC) and illuminated its role in OC formation. TFE operates via allosteric and direct mechanisms. Firstly, it interacts with the RNAP and induces the opening of the flexible RNAP clamp domain, concomitant with DNA melting and template loading. Secondly, TFE binds physically to single-stranded DNA in the transcription bubble of the OC and increases its stability. The identification of the β-subunit of archaeal TFE enabled us to reconstruct the evolutionary history of TFE/TFIIE-like factors, which is characterised by winged helix (WH) domain expansion in eukaryotes and loss of metal centres including iron-sulfur clusters and Zinc ribbons. OC formation is an important target for the regulation of transcription in all domains of life. We propose that TFE and the bacterial general transcription factor CarD, although structurally and evolutionary unrelated, show interesting parallels in their mechanism to enhance OC formation. We argue that OC formation is used as a way to regulate transcription in all domains of life, and these regulatory mechanisms coevolved with the basal transcription machinery

Modelling the regulation of thermal adaptation in Candida albicans, a major fungal pathogen of humans

Peer reviewedPublisher PD

A flexible integrative approach based on random forest improves prediction of transcription factor binding sites

Transcription factor binding sites (TFBSs) are DNA sequences of 6-15 base pairs. Interaction of these TFBSs with transcription factors (TFs) is largely responsible for most spatiotemporal gene expression patterns. Here, we evaluate to what extent sequence-based prediction of TFBSs can be improved by taking into account the positional dependencies of nucleotides (NPDs) and the nucleotide sequence-dependent structure of DNA. We make use of the random forest algorithm to flexibly exploit both types of information. Results in this study show that both the structural method and the NPD method can be valuable for the prediction of TFBSs. Moreover, their predictive values seem to be complementary, even to the widely used position weight matrix (PWM) method. This led us to combine all three methods. Results obtained for five eukaryotic TFs with different DNA-binding domains show that our method improves classification accuracy for all five eukaryotic TFs compared with other approaches. Additionally, we contrast the results of seven smaller prokaryotic sets with high-quality data and show that with the use of high-quality data we can significantly improve prediction performance. Models developed in this study can be of great use for gaining insight into the mechanisms of TF binding