CiliaCarta: An integrated and validated compendium of ciliary genes.

The cilium is an essential organelle at the surface of mammalian cells whose dysfunction causes a wide range of genetic diseases collectively called ciliopathies. The current rate at which new ciliopathy genes are identified suggests that many ciliary components remain undiscovered. We generated and rigorously analyzed genomic, proteomic, transcriptomic and evolutionary data and systematically integrated these using Bayesian statistics into a predictive score for ciliary function. This resulted in 285 candidate ciliary genes. We generated independent experimental evidence of ciliary associations for 24 out of 36 analyzed candidate proteins using multiple cell and animal model systems (mouse, zebrafish and nematode) and techniques. For example, we show that OSCP1, which has previously been implicated in two distinct non-ciliary processes, causes ciliogenic and ciliopathy-associated tissue phenotypes when depleted in zebrafish. The candidate list forms the basis of CiliaCarta, a comprehensive ciliary compendium covering 956 genes. The resource can be used to objectively prioritize candidate genes in whole exome or genome sequencing of ciliopathy patients and can be accessed at http://bioinformatics.bio.uu.nl/john/syscilia/ciliacarta/.

A Polymer Model for the Quantitative Reconstruction of Chromosome Architecture from HiC and GAM Data.

It is widely believed that the folding of the chromosome in the nucleus has a major effect on genetic expression. For example, coregulated genes in several species have been shown to colocalize in space despite being far away on the DNA sequence. In this manuscript, we present a new, to our knowledge, method to model the three-dimensional structure of the chromosome in live cells based on DNA-DNA interactions measured in high-throughput chromosome conformation capture experiments and genome architecture mapping. Our approach incorporates a polymer model and directly uses the contact probabilities measured in high-throughput chromosome conformation capture experiments and genome architecture mapping experiments rather than estimates of average distances between genomic loci. Specifically, we model the chromosome as a Gaussian polymer with harmonic interactions and extract the coupling coefficients best reproducing the experimental contact probabilities. In contrast to existing methods, we give an exact expression of the contact probabilities at thermodynamic equilibrium. The Gaussian effective model reconstructed with our method reproduces experimental contacts with high accuracy. We also show how Brownian dynamics simulations of our reconstructed Gaussian effective model can be used to study chromatin organization and possibly give some clue about its dynamics.

Multiple links connect central carbon metabolism to DNA replication initiation and elongation in Bacillus subtilis.

DNA replication is coupled to growth by an unknown mechanism. Here, we investigated this coupling by analyzing growth and replication in 15 mutants of central carbon metabolism (CCM) cultivated in three rich media. In about one-fourth of the condition tested, defects in replication resulting from changes in initiation or elongation were detected. This uncovered 11 CCM genes important for replication and showed that some of these genes have an effect in one, two or three media. Additional results presented here and elsewhere (Jannière, L., Canceill, D., Suski, C., et al. (2007), PLoS One, 2, e447.) showed that, in the LB medium, the CCM genes important for DNA elongation (gapA and ackA) are genetically linked to the lagging strand polymerase DnaE while those important for initiation (pgk and pykA) are genetically linked to the replication enzymes DnaC (helicase), DnaG (primase) and DnaE. Our work thus shows that the coupling between growth and replication involves multiple, medium-dependent links between CCM and replication. They also suggest that changes in CCM may affect initiation by altering the functional recruitment of DnaC, DnaG and DnaE at the chromosomal origin, and may affect elongation by altering the activity of DnaE at the replication fork. The underlying mechanism is discussed.

Interactions of the Bacillus subtilis DnaE polymerase with replisomal proteins modulate its activity and fidelity.

During Bacillus subtilis replication two replicative polymerases function at the replisome to collectively carry out genome replication. In a reconstituted in vitro replication assay, PolC is the main polymerase while the lagging strand DnaE polymerase briefly extends RNA primers synthesized by the primase DnaG prior to handing-off DNA synthesis to PolC. Here, we show in vivo that (i) the polymerase activity of DnaE is essential for both the initiation and elongation stages of DNA replication, (ii) its error rate varies inversely with PolC concentration, and (iii) its misincorporations are corrected by the mismatch repair system post-replication. We also found that the error rates in cells encoding mutator forms of both PolC and DnaE are significantly higher (up to 15-fold) than in PolC mutants. In vitro, we showed that (i) the polymerase activity of DnaE is considerably stimulated by DnaN, SSB and PolC, (ii) its error-prone activity is strongly inhibited by DnaN, and (iii) its errors are proofread by the 3' > 5' exonuclease activity of PolC in a stable template-DnaE-PolC complex. Collectively our data show that protein-protein interactions within the replisome modulate the activity and fidelity of DnaE, and confirm the prominent role of DnaE during B. subtilis replication.

Analysis tools for the interplay between genome layout and regulation.

BACKGROUND: Genome layout and gene regulation appear to be interdependent. Understanding this interdependence is key to exploring the dynamic nature of chromosome conformation and to engineering functional genomes. Evidence for non-random genome layout, defined as the relative positioning of either co-functional or co-regulated genes, stems from two main approaches. Firstly, the analysis of contiguous genome segments across species, has highlighted the conservation of gene arrangement (synteny) along chromosomal regions. Secondly, the study of long-range interactions along a chromosome has emphasised regularities in the positioning of microbial genes that are co-regulated, co-expressed or evolutionarily correlated. While one-dimensional pattern analysis is a mature field, it is often powerless on biological datasets which tend to be incomplete, and partly incorrect. Moreover, there is a lack of comprehensive, user-friendly tools to systematically analyse, visualise, integrate and exploit regularities along genomes. RESULTS: Here we present the Genome REgulatory and Architecture Tools SCAN (GREAT:SCAN) software for the systematic study of the interplay between genome layout and gene expression regulation. GREAT: SCAN is a collection of related and interconnected applications currently able to perform systematic analyses of genome regularities as well as to improve transcription factor binding sites (TFBS) and gene regulatory network predictions based on gene positional information. CONCLUSIONS: We demonstrate the capabilities of these tools by studying on one hand the regular patterns of genome layout in the major regulons of the bacterium Escherichia coli. On the other hand, we demonstrate the capabilities to improve TFBS prediction in microbes. Finally, we highlight, by visualisation of multivariate techniques, the interplay between position and sequence information for effective transcription regulation.

From multiple pathogenicity islands to a unique organized pathogenicity archipelago.

Pathogenicity islands are sets of successive genes in a genome that determine the virulence of a bacterium. In a growing number of studies, bacterial virulence appears to be determined by multiple islands scattered along the genome. This is the case in a family of seven plant pathogens and a human pathogen that, under KdgR regulation, massively secrete enzymes such as pectinases that degrade plant cell wall. Here we show that their multiple pathogenicity islands form together a coherently organized, single "archipelago" at the genome scale. Furthermore, in half of the species, most genes encoding secreted pectinases are expressed from the same DNA strand (transcriptional co-orientation). This genome architecture favors DNA conformations that are conducive to genes spatial co-localization, sometimes complemented by co-orientation. As proteins tend to be synthetized close to their encoding genes in bacteria, we propose that this architecture would favor the efficient funneling of pectinases at convergent points within the cell. The underlying functional hypothesis is that this convergent funneling of the full blend of pectinases constitutes a crucial strategy for successful degradation of the plant cell wall. Altogether, our work provides a new approach to describe and predict, at the genome scale, the full virulence complement.

An organelle-specific protein landscape identifies novel diseases and molecular mechanisms.

Cellular organelles provide opportunities to relate biological mechanisms to disease. Here we use affinity proteomics, genetics and cell biology to interrogate cilia: poorly understood organelles, where defects cause genetic diseases. Two hundred and seventeen tagged human ciliary proteins create a final landscape of 1,319 proteins, 4,905 interactions and 52 complexes. Reverse tagging, repetition of purifications and statistical analyses, produce a high-resolution network that reveals organelle-specific interactions and complexes not apparent in larger studies, and links vesicle transport, the cytoskeleton, signalling and ubiquitination to ciliary signalling and proteostasis. We observe sub-complexes in exocyst and intraflagellar transport complexes, which we validate biochemically, and by probing structurally predicted, disruptive, genetic variants from ciliary disease patients. The landscape suggests other genetic diseases could be ciliary including 3M syndrome. We show that 3M genes are involved in ciliogenesis, and that patient fibroblasts lack cilia. Overall, this organelle-specific targeting strategy shows considerable promise for Systems Medicine.

GREAT: a web portal for Genome Regulatory Architecture Tools.

GREAT (Genome REgulatory Architecture Tools) is a novel web portal for tools designed to generate user-friendly and biologically useful analysis of genome architecture and regulation. The online tools of GREAT are freely accessible and compatible with essentially any operating system which runs a modern browser. GREAT is based on the analysis of genome layout -defined as the respective positioning of co-functional genes- and its relation with chromosome architecture and gene expression. GREAT tools allow users to systematically detect regular patterns along co-functional genomic features in an automatic way consisting of three individual steps and respective interactive visualizations. In addition to the complete analysis of regularities, GREAT tools enable the use of periodicity and position information for improving the prediction of transcription factor binding sites using a multi-view machine learning approach. The outcome of this integrative approach features a multivariate analysis of the interplay between the location of a gene and its regulatory sequence. GREAT results are plotted in web interactive graphs and are available for download either as individual plots, self-contained interactive pages or as machine readable tables for downstream analysis. The GREAT portal can be reached at the following URL https://absynth.issb.genopole.fr/GREAT and each individual GREAT tool is available for downloading.

Phase Behavior of DNA in the Presence of DNA-Binding Proteins.

To characterize the thermodynamical equilibrium of DNA chains interacting with a solution of nonspecific binding proteins, we implemented a Flory-Huggins free energy model. We explored the dependence on DNA and protein concentrations of the DNA collapse. For physiologically relevant values of the DNA-protein affinity, this collapse gives rise to a biphasic regime with a dense and a dilute phase; the corresponding phase diagram was computed. Using an approach based on Hamiltonian paths, we show that the dense phase has either a molten globule or a crystalline structure, depending on the DNA bending rigidity, which is influenced by the ionic strength. These results are valid at the thermodynamical equilibrium and therefore should be consistent with many biological processes, whose characteristic timescales range typically from 1 ms to 10 s. Our model may thus be applied to biological phenomena that involve DNA-binding proteins, such as DNA condensation with crystalline order, which occurs in some bacteria to protect their chromosome from detrimental factors; or transcription initiation, which occurs in clusters called transcription factories that are reminiscent of the dense phase characterized in this study.

Thermodynamics of long supercoiled molecules: insights from highly efficient Monte Carlo simulations.

Supercoiled DNA polymer models for which the torsional energy depends on the total twist of molecules (Tw) are a priori well suited for thermodynamic analysis of long molecules. So far, nevertheless, the exact determination of Tw in these models has been based on a computation of the writhe of the molecules (Wr) by exploiting the conservation of the linking number, Lk=Tw+Wr, which reflects topological constraints coming from the helical nature of DNA. Because Wr is equal to the number of times the main axis of a DNA molecule winds around itself, current Monte Carlo algorithms have a quadratic time complexity, O(L(2)), with respect to the contour length (L) of the molecules. Here, we present an efficient method to compute Tw exactly, leading in principle to algorithms with a linear complexity, which in practice is O(L(1.2)). Specifically, we use a discrete wormlike chain that includes the explicit double-helix structure of DNA and where the linking number is conserved by continuously preventing the generation of twist between any two consecutive cylinders of the discretized chain. As an application, we show that long (up to 21 kbp) linear molecules stretched by mechanical forces akin to magnetic tweezers contain, in the buckling regime, multiple and branched plectonemes that often coexist with curls and helices, and whose length and number are in good agreement with experiments. By attaching the ends of the molecules to a reservoir of twists with which these can exchange helix turns, we also show how to compute the torques in these models. As an example, we report values that are in good agreement with experiments and that concern the longest molecules that have been studied so far (16 kbp).

PreCisIon: PREdiction of CIS-regulatory elements improved by gene's positION.

Conventional approaches to predict transcriptional regulatory interactions usually rely on the definition of a shared motif sequence on the target genes of a transcription factor (TF). These efforts have been frustrated by the limited availability and accuracy of TF binding site motifs, usually represented as position-specific scoring matrices, which may match large numbers of sites and produce an unreliable list of target genes. To improve the prediction of binding sites, we propose to additionally use the unrelated knowledge of the genome layout. Indeed, it has been shown that co-regulated genes tend to be either neighbors or periodically spaced along the whole chromosome. This study demonstrates that respective gene positioning carries significant information. This novel type of information is combined with traditional sequence information by a machine learning algorithm called PreCisIon. To optimize this combination, PreCisIon builds a strong gene target classifier by adaptively combining weak classifiers based on either local binding sequence or global gene position. This strategy generically paves the way to the optimized incorporation of any future advances in gene target prediction based on local sequence, genome layout or on novel criteria. With the current state of the art, PreCisIon consistently improves methods based on sequence information only. This is shown by implementing a cross-validation analysis of the 20 major TFs from two phylogenetically remote model organisms. For Bacillus subtilis and Escherichia coli, respectively, PreCisIon achieves on average an area under the receiver operating characteristic curve of 70 and 60%, a sensitivity of 80 and 70% and a specificity of 60 and 56%. The newly predicted gene targets are demonstrated to be functionally consistent with previously known targets, as assessed by analysis of Gene Ontology enrichment or of the relevant literature and databases.

CTCF-mediated transcriptional regulation through cell type-specific chromosome organization in the ß-globin locus.

The principles underlying the architectural landscape of chromatin beyond the nucleosome level in living cells remains largely unknown despite its potential to play a role in mammalian gene regulation. We investigated the three-dimensional folding of a 1 Mbp region of human chromosome 11 containing the ß-globin genes by integrating looping interactions of the CCCTC-binding insulator protein CTCF determined comprehensively by chromosome conformation capture (3C) into a polymer model of chromatin. We find that CTCF-mediated cell type-specific interactions in erythroid cells are organized to favor contacts known to occur in vivo between the ß-globin locus control region (LCR) and genes. In these cells, the modeled ß-globin domain folds into a globule with the LCR and the active globin genes on the periphery. In contrast, in non-erythroid cells, the globule is less compact with few but dominant CTCF interactions driving the genes away from the LCR. This leads to a decrease in contact frequencies that can exceed 1000-fold depending on the stiffness of the chromatin and the exact position of the genes. Our findings show that an ensemble of CTCF contacts functionally affects spatial distances between control elements and target genes contributing to chromosomal organization required for transcription.

The layout of a bacterial genome.

Recently the mismatch between our newly acquired capacity to synthetize DNA at genome scale, and our low capacity to design ab initio a functional genome has become conspicuous. This essay gathers a variety of constraints that globally shape natural genomes, with a focus on eubacteria. These constraints originate from chromosome replication (leading/lagging strand asymmetry; gene dosage gradient from origin to terminus; collisions with the transcription complexes), from biased codon usage, from noise control in gene expression, and from genome layout for co-functional genes. On the basis of this analysis, lessons are drawn for full genome design.

Genomic organization of evolutionarily correlated genes in bacteria: limits and strategies.

The need for efficient molecular interplay in time and space within a cell imposes strong constraints that could be partially relaxed if relative gene positions along chromosomes were appropriate. Comparative genomics studies have demonstrated the short-scale conservation of gene proximity along bacterial chromosomes. Additionally, the long-range periodic positioning of evolutionarily correlated genes within Escherichia coli has recently been highlighted. To gain further insight into these different genetic organizations, we examined the compromise between chromosomal proximity and periodicity for all available eubacterial genomes by evaluating groups of evolutionarily correlated genes from a benchmark data set. In enterobacteria, strict chromosomal proximity is found to be limited to groups under 20 genes, whereas periodicity is significant in all groups over 50. The E. coli K12 genome bears 511 periodic genes (12% of the genome), whose orthologs are found to be periodic in all eubacterial phyla. These periodic genes predominantly function in macromolecular synthesis and spatial organization of cellular components. They are enriched in essential and housekeeping genes and tend to often be constitutively expressed. On this basis, it is argued that chromosomal proximity and periodicity are ubiquitous complementary genomic strategies that favor the build-up of local concentrations of co-functional molecules. In particular, the periodic layout may facilitate chromosome folding to spatially organize the construction of major cell components. The transition at 20 genes is reminiscent of the size of the longest operons and of topological microdomains. The range for which DNA neighborhood optimizes biochemical interactions might therefore be defined by DNA topology.

Computing with bacterial constituents, cells and populations: from bioputing to bactoputing.

The relevance of biological materials and processes to computing-alias bioputing-has been explored for decades. These materials include DNA, RNA and proteins, while the processes include transcription, translation, signal transduction and regulation. Recently, the use of bacteria themselves as living computers has been explored but this use generally falls within the classical paradigm of computing. Computer scientists, however, have a variety of problems to which they seek solutions, while microbiologists are having new insights into the problems bacteria are solving and how they are solving them. Here, we envisage that bacteria might be used for new sorts of computing. These could be based on the capacity of bacteria to grow, move and adapt to a myriad different fickle environments both as individuals and as populations of bacteria plus bacteriophage. New principles might be based on the way that bacteria explore phenotype space via hyperstructure dynamics and the fundamental nature of the cell cycle. This computing might even extend to developing a high level language appropriate to using populations of bacteria and bacteriophage. Here, we offer a speculative tour of what we term bactoputing, namely the use of the natural behaviour of bacteria for calculating.

Periodic pattern detection in sparse boolean sequences.

BACKGROUND: The specific position of functionally related genes along the DNA has been shown to reflect the interplay between chromosome structure and genetic regulation. By investigating the statistical properties of the distances separating such genes, several studies have highlighted various periodic trends. In many cases, however, groups built up from co-functional or co-regulated genes are small and contain wrong information (data contamination) so that the statistics is poorly exploitable. In addition, gene positions are not expected to satisfy a perfectly ordered pattern along the DNA. Within this scope, we present an algorithm that aims to highlight periodic patterns in sparse boolean sequences, i.e. sequences of the type 010011011010... where the ratio of the number of 1's (denoting here the transcription start of a gene) to 0's is small. RESULTS: The algorithm is particularly robust with respect to strong signal distortions such as the addition of 1's at arbitrary positions (contaminated data), the deletion of existing 1's in the sequence (missing data) and the presence of disorder in the position of the 1's (noise). This robustness property stems from an appropriate exploitation of the remarkable alignment properties of periodic points in solenoidal coordinates. CONCLUSIONS: The efficiency of the algorithm is demonstrated in situations where standard Fourier-based spectral methods are poorly adapted. We also show how the proposed framework allows to identify the 1's that participate in the periodic trends, i.e. how the framework allows to allocate a positional score to genes, in the same spirit of the sequence score. The software is available for public use at http://www.issb.genopole.fr/MEGA/Softwares/iSSB_SolenoidalApplication.zip.

Challenges in experimental data integration within genome-scale metabolic models.

A report of the meeting "Challenges in experimental data integration within genome-scale metabolic models", Institut Henri Poincaré, Paris, October 10-11 2009, organized by the CNRS-MPG joint program in Systems Biology.