Few crucial links assure checkpoint efficiency in the yeast cell-cycle network

Motivation: The ability of cells to complete mitosis with high fidelity relies on elaborate checkpoint mechanisms. We study S- and M-phase checkpoint responses in silico in the budding yeast with a stochastic dynamical model for the cell-cycle. We aim to provide an unbiased functional classification of network interactions that reflect the contribution of each link to checkpoint efficiency in the presence of cellular fluctuations. Results: We developed an algorithm BNetDyn to compute stochastic dynamical trajectories for an input gene network and its structural perturbations. User specified output measures like the mutual information between trigger and output nodes are then evaluated on the stationary state of the Markov process. Systematic perturbations of the yeast cell-cycle model by Li et al. classify each link according to its effect on checkpoint efficiencies and stabilities of the main cell-cycle phases. This points to the crosstalk in the cascades downstream of the SBF/MBF transcription activator complexes as determinant for checkpoint optimality; a finding that consistently reflects recent experiments. Finally our stochastic analysis emphasizes how dynamical stability in the yeast cell-cycle network crucially relies on backward inhibitory circuits next to forward induction. Availability: C++ source code and network models can be downloaded at Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin

Few crucial links assure checkpoint efficiency in the yeast cell-cycle network

MOTIVATION: The ability of cells to complete mitosis with high fidelity relies on elaborate checkpoint mechanisms. We study S- and M-phase checkpoint responses in silico in the budding yeast with a stochastic dynamical model for the cell-cycle. We aim to provide an unbiased functional classification of network interactions that reflect the contribution of each link to checkpoint efficiency in the presence of cellular fluctuations. RESULTS: We developed an algorithm BNetDyn to compute stochastic dynamical trajectories for an input gene network and its structural perturbations. User specified output measures like the mutual information between trigger and output nodes are then evaluated on the stationary state of the Markov process. Systematic perturbations of the yeast cell-cycle model by Li et al. classify each link according to its effect on checkpoint efficiencies and stabilities of the main cell-cycle phases. This points to the crosstalk in the cascades downstream of the SBF/MBF transcription activator complexes as determinant for checkpoint optimality; a finding that consistently reflects recent experiments. Finally our stochastic analysis emphasizes how dynamical stability in the yeast cell-cycle network crucially relies on backward inhibitory circuits next to forward induction. AVAILABILITY: C++ source code and network models can be downloaded at http://www.vital-it.ch/Software

Genomic and Expression Analysis of the 12p11-p12 Amplicon Using EST Arrays Identifies Two Novel Amplified and Overexpressed Genes

We performed parallel array comparative genomic hybridization and array expression analysis of the 12p11-p12 amplicon in human testicular seminomas and an ovarian carcinoma cell line using an expressed se- quence tags (ESTs) array spotted with 8254 ESTs. The data were normal- ized using a robust statistical modeling and the significance inferred from the local SD. We identified two ESTs within the chromosomal amplicon that were amplified and overexpressed in >75–100% of analyzed tumors with the 12p11-p12 amplicon. These sequences, belonging to coding re- gions of two novel genes designated here as GCT1 and GCT2, were broadly expressed in a panel of human tissues, including testis and ovary. GCT1 and GCT2 were overexpressed in 92 and 71%, respectively, of a panel of seminomas tested. Combined array comparative genomic hybridization and array expression analysis is a valid approach for gene discovery in large chromosomal amplicons

Quantitative Analysis and Modeling Probe Polarity Establishment in C. elegans Embryos

Cell polarity underlies many aspects of metazoan development and homeostasis, and relies notably on a set of PAR proteins located at the cell cortex. How these proteins interact in space and time remains incompletely understood. We performed a quantitative assessment of polarity establishment in one-cell stage Caenorhabditis elegans embryos by combining time-lapse microscopy and image analysis. We used our extensive data set to challenge and further specify an extant mathematical model. Using likelihood-based calibration, we uncovered that cooperativity is required for both anterior and posterior PAR complexes. Moreover, we analyzed the dependence of polarity establishment on changes in size or temperature. The observed robustness of PAR domain dimensions in embryos of different sizes is in agreement with a model incorporating fixed protein concentrations and variations in embryo surface/volume ratio. In addition, we quantified the dynamics of polarity establishment over most of the viable temperatures range of C. elegans. Modeling of these data suggests that diffusion of PAR proteins is the process most affected by temperature changes, although cortical flows appear unaffected. Overall, our quantitative analytical framework provides insights into the dynamics of polarity establishment in a developing system

CAST: An automated segmentation and tracking tool for the analysis of transcriptional kinetics from single-cell time-lapse recordings

Fluorescence and bioluminescence time-lapse imaging allows to investigate a vast range of cellular processes at single-cell or even subcellular resolution. In particular, time-lapse imaging can provide uniquely detailed information on the fine kinetics of transcription, as well as on biological oscillations such as the circadian and cell cycles. However, we face a paucity of automated methods to quantify time-lapse imaging data with single-cell precision, notably throughout multiple cell cycles. We developed CAST (Cell Automated Segmentation and Tracking platform) to automatically and robustly detect the position and size of cells or nuclei, quantify the corresponding light signals, while taking into account both cell divisions (lineage tracking) and migration events. We present here how CAST analyzes bioluminescence data from a short-lived transcriptional luciferase reporter. However, our flexible and modular implementation makes it easily adaptable to a wide variety of time-lapse recordings. We exemplify how CAST efficiently quantifies single-cell gene expression over multiple cell cycles using mouse NIH3T3 culture cells with a luminescence expression driven by the Bmal1 promoter, a central gene of the circadian oscillator. We further illustrate how such data can be used to quantify transcriptional bursting in conditions of lengthened circadian period, revealing thereby remarkably similar bursting signature compared to the endogenous circadian condition despite marked period lengthening. In summary, we establish CAST as novel tool for the efficient segmentation, signal quantification, and tracking of time-lapse images from mammalian cell culture

Chemotaxis behavior mediated by single larval olfactory neurons in Drosophila

BACKGROUND: Odorant receptors (ORs) are thought to act in a combinatorial fashion, in which odor identity is encoded by the activation of a subset of ORs and the olfactory sensory neurons (OSNs) that express them. The extent to which a single OR contributes to chemotaxis behavior is not known. We investigated this question in Drosophila larvae, which represent a powerful genetic system to analyze the contribution of individual OSNs to odor coding. RESULTS: We identify 25 larval OR genes expressed in 21 OSNs and generate genetic tools that allow us to engineer larvae missing a single OSN or having only a single or a pair of functional OSNs. Ablation of single OSNs disrupts chemotaxis behavior to a small subset of the odors tested. Larvae with only a single functional OSN are able to chemotax robustly, demonstrating that chemotaxis is possible in the absence of the remaining elements of the combinatorial code. We provide behavioral evidence that an OSN not sufficient to support chemotaxis behavior alone can act in a combinatorial fashion to enhance chemotaxis along with a second OSN. CONCLUSIONS: We conclude that there is extensive functional redundancy in the olfactory system, such that a given OSN is necessary and sufficient for the perception of only a subset of odors. This study is the first behavioral demonstration that formation of olfactory percepts involves the combinatorial integration of information transmitted by multiple ORs

Genotypic Features of Lentivirus Transgenic Mice▿ †

Lentivector-mediated transgenesis is increasingly used, whether for basic studies as an alternative to pronuclear injection of naked DNA or to test candidate gene therapy vectors. In an effort to characterize the genetic features of this approach, we first measured the frequency of germ line transmission of individual proviruses established by infection of fertilized mouse oocytes. Seventy integrants from 11 founder (G0) mice were passed to 111 first generation (G1) pups, for a total of 255 events corresponding to an average rate of transmission of 44%. This implies that integration had most often occurred at the one- or two-cell stage and that the degree of genotypic mosaicism in G0 mice obtained through this approach is generally minimal. Transmission analysis of eight individual proviruses in 13 G2 mice obtained by a G0-G1 cross revealed only 8% of proviral homozygosity, significantly below the 25% expected from purely Mendelian transmission, suggesting counter-selection due to interference with the functions of targeted loci. Mapping of 239 proviral integration sites in 49 founder animals revealed that about 60% resided within annotated genes, with a marked tendency for clustering in the middle of the transcribed region, and that integration was not influenced by the transcriptional orientation. Transcript levels of a set of arbitrarily chosen target genes were significantly higher in two-cell embryos than in embryonic stem cells or adult somatic cells, suggesting that, as previously noted in other settings, lentiviral vectors integrate preferentially into regions of the genome that are transcriptionally active or poised for activation

Genomic and expression analysis of the 12p11-p12 amplicon using EST arrays identifies two novel amplified and overexpressed genes

We performed parallel array comparative genomic hybridization and array expression analysis of the 12p11-p12 amplicon in human testicular seminomas and an ovarian carcinoma cell line using an expressed sequence tags (ESTs) array spotted with 8254 ESTs. The data were normalized using a robust statistical modeling and the significance inferred from the local SD. We identified two ESTs within the chromosomal amplicon that were amplified and overexpressed in > or =75-100 percent of analyzed tumors with the 12p11-p12 amplicon. These sequences, belonging to coding regions of two novel genes designated here as GCT1 and GCT2, were broadly expressed in a panel of human tissues, including testis and ovary. GCT1 and GCT2 were overexpressed in 92 and 71 percent, respectively, of a panel of seminomas tested. Combined array comparative genomic hybridization and array expression analysis is a valid approach for gene discovery in large chromosomal amplicons