Network-based identification of feedback modules that control RhoA activity and cell migration

Cancer cell migration enables metastatic spread causing most cancer deaths. Rho-family GTPases control cell migration, but being embedded in a highly interconnected feedback network, the control of their dynamical behavior during cell migration remains elusive. To address this question, we reconstructed the Rho-family GTPases signaling network involved in cell migration, and developed a Boolean network model to analyze the different states and emergent rewiring of the Rho-family GTPases signaling network at protrusions and during extracellular matrix-dependent cell migration. Extensive simulations and experimental validations revealed that the bursts of RhoA activity induced at protrusions by EGF are regulated by a negative-feedback module composed of Src, FAK, and CSK. Interestingly, perturbing this module interfered with cyclic Rho activation and extracellular matrix-dependent migration, suggesting that CSK inhibition can be a novel and effective intervention strategy for blocking extracellular matrix-dependent cancer cell migration, while Src inhibition might fail, depending on the genetic background of cells. Thus, this study provides new insights into the mechanisms that regulate the intricate activation states of Rho-family GTPases during extracellular matrix-dependent migration, revealing potential new targets for interfering with extracellular matrix-dependent cancer cell migratio

Predicting the Occurrence of Variants in RAG1 and RAG2

Abstract: While widespread genome sequencing ushers in a new era of preventive medicine, the tools for predictive genomics are still lacking. Time and resource limitations mean that human diseases remain uncharacterized because of an inability to predict clinically relevant genetic variants. A strategy of targeting highly conserved protein regions is used commonly in functional studies. However, this benefit is lost for rare diseases where the attributable genes are mostly conserved. An immunological disorder exemplifying this challenge occurs through damaging mutations in RAG1 and RAG2 which presents at an early age with a distinct phenotype of life-threatening immunodeficiency or autoimmunity. Many tools exist for variant pathogenicity prediction, but these cannot account for the probability of variant occurrence. Here, we present a method that predicts the likelihood of mutation for every amino acid residue in the RAG1 and RAG2 proteins. Population genetics data from approximately 146,000 individuals was used for rare variant analysis. Forty-four known pathogenic variants reported in patients and recombination activity measurements from 110 RAG1/2 mutants were used to validate calculated scores. Probabilities were compared with 98 currently known human cases of disease. A genome sequence dataset of 558 patients who have primary immunodeficiency but that are negative for RAG deficiency were also used as validation controls. We compared the difference between mutation likelihood and pathogenicity prediction. Our method builds a map of most probable mutations allowing pre-emptive functional analysis. This method may be applied to other diseases with hopes of improving preparedness for clinical diagnosis

The impact of bisphosphonates on the osteoblast proliferation and Collagen gene expression in vitro

<p>Abstract</p> <p>Background</p> <p>Bisphosphonates are widely used in the clinical treatment of bone diseases with increased bone resorption. In terms of side effects, they are known to be associated with osteonecrosis of the jaw (BONJ).</p> <p>The objective of this study was to evaluate the effect of bisphosphonates on osteoblast proliferation by cell count and gene expression analysis of cyclin D1 <it>in vitro</it>. Furthermore, the gene expression of the extracellular matrix protein collagen type I was evaluated. Nitrogen-containing and non-nitrogen-containing bisphosphonates have been compared on gene expression levels.</p> <p>Methods</p> <p>Human osteoblast obtained from hip bone were stimulated with zoledronate, ibandronate and clodronate at concentrations of 5 × 10^-5M over the experimental periods of 1, 2, 5, 10 and 14 days. At each point in time, the cells were dissolved, the mRNA extracted, and the gene expression level of cyclin D1 and collagen type I were quantified by Real-Time RT-PCR. The gene expression was compared to an unstimulated osteoblast cell culture for control.</p> <p>Results</p> <p>The proliferation appeared to have been influenced only to a small degree by bisphosphonates. Zolendronate led to a lower cyclin D1 gene expression after 10 days. The collagen gene expression was enhanced by nitrogen containing bisphosphonates, decreased however after day 10. The non-nitrogen-containing bisphosphonate clodronate, however, did not significantly influence cyclin D1 and collagen gene expression.</p> <p>Conclusions</p> <p>The above data suggest a limited influence of bisphosphonates on osteoblast proliferation, except for zoledronate. The extracellular matrix production seems to be initially advanced and inhibited after 10 days. Interestingly, clodronate has little influence on osteoblast proliferation and extracellular matrix production in terms of cyclin D1 and collagen gene expression.</p

Cosmic Hydrogen Was Significantly Neutral a Billion Years After the Big Bang

The ionization fraction of cosmic hydrogen, left over from the big bang, provides crucial fossil evidence for when the first stars and quasar black holes formed in the infant universe. Spectra of the two most distant quasars known show nearly complete absorption of photons with wavelengths shorter than the Ly-alpha transition of neutral hydrogen, indicating that hydrogen in the intergalactic medium (IGM) had not been completely ionized at a redshift z~6.3, about a billion years after the big bang. Here we show that the radii of influence of ionizing radiation from these quasars imply that the surrounding IGM had a neutral hydrogen fraction of tens of percent prior to the quasar activity, much higher than previous lower limits of ~0.1%. When combined with the recent inference of a large cumulative optical depth to electron scattering after cosmological recombination from the WMAP data, our result suggests the existence of a second peak in the mean ionization history, potentially due to an early formation episode of the first stars.Comment: 14 Pages, 2 Figures. Accepted for publication in Nature. Press embargo until publishe

Evaluation of the psychometric properties of the SF-36 health survey for use among Turkish and Moroccan ethnic minority populations in the Netherlands

Purpose: To evaluate the psychometrics of the SF-36 Health Survey among Turkish and Moroccan ethnic minority populations in the Netherlands and to compare the results to those based on the indigenous Dutch population. Methods: Data were derived from the Second Dutch National Survey of General Practice. In total, SF-36 data were available for 409 Turkish, 377 Moroccan, and 9,628 Dutch respondents. Language subgroup analyses were performed for the Turkish (n = 162) and Moroccan-Arabic (n = 52) versions of the SF-36. Psychometric properties were evaluated by descriptive statistics, factor analysis, internal consistency estimates, known-group comparisons, and differential item function (DIF) analysis. Results Low levels of missing SF-36 data were observed across all groups. Confirmatory factor analysis supported the hypothesized SF-36 scale structure for the Dutch and Turkish group, but high correlations between the MH and VT factors were observed in the Moroccan group. All Cronbach’s alpha coefficients were above 0.70, except for the Vitality scale in the Moroccan group and the Vitality and Social Functioning scales in the Moroccan-Arabic language subgroup. Known-groups validity was found across samples using age, sex, education, and comorbidity as grouping variables, but not marital status. Some evidence for DIF was found in both ethnic group samples. Conclusions: The results generally support the use of the SF-36 for general population research among Turkish and Moroccan ethnic minorities in the Netherlands. Additional studies are needed to confirm the psychometrics of the questionnaire when used among these populations in other Western European countries. (aut. ref.

An extracellular steric seeding mechanism for Eph-ephrin signaling platform assembly

Erythropoetin-producing hepatoma (Eph) receptors are cell-surface protein tyrosine kinases mediating cell-cell communication. Upon activation, they form signaling clusters. We report crystal structures of the full ectodomain of human EphA2 (eEphA2) both alone and in complex with the receptor-binding domain of the ligand ephrinA5 (ephrinA5 RBD). Unliganded eEphA2 forms linear arrays of staggered parallel receptors involving two patches of residues conserved across A-class Ephs. eEphA2-ephrinA5 RBD forms a more elaborate assembly, whose interfaces include the same conserved regions on eEphA2, but rearranged to accommodate ephrinA5 RBD. Cell-surface expression of mutant EphA2s showed that these interfaces are critical for localization at cell-cell contacts and activation-dependent degradation. Our results suggest a 'nucleation' mechanism whereby a limited number of ligand-receptor interactions 'seed' an arrangement of receptors which can propagate into extended signaling arrays

An ongoing case-control study to evaluate the NHS Bowel Cancer Screening Programme

© 2014 Massat et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated

A Small Conductance Calcium-Activated K⁺ Channel in C. elegans, KCNL-2, Plays a Role in the Regulation of the Rate of Egg-Laying

In the nervous system of mice, small conductance calcium-activated potassium (SK) channels function to regulate neuronal excitability through the generation of a component of the medium afterhyperpolarization that follows action potentials. In humans, irregular action potential firing frequency underlies diseases such as ataxia, epilepsy, schizophrenia and Parkinson's disease. Due to the complexity of studying protein function in the mammalian nervous system, we sought to characterize an SK channel homologue, KCNL-2, in C. elegans, a genetically tractable system in which the lineage of individual neurons was mapped from their early developmental stages. Sequence analysis of the KCNL-2 protein reveals that the six transmembrane domains, the potassium-selective pore and the calmodulin binding domain are highly conserved with the mammalian homologues. We used widefield and confocal fluorescent imaging to show that a fusion construct of KCNL-2 with GFP in transgenic lines is expressed in the nervous system of C. elegans. We also show that a KCNL-2 null strain, kcnl-2(tm1885), demonstrates a mild egg-laying defective phenotype, a phenotype that is rescued in a KCNL-2-dependent manner. Conversely, we show that transgenic lines that overexpress KCNL-2 demonstrate a hyperactive egg-laying phenotype. In this study, we show that the vulva of transgenic hermaphrodites is highly innervated by neuronal processes and by the VC4 and VC5 neurons that express GFP-tagged KCNL-2. We propose that KCNL-2 functions in the nervous system of C. elegans to regulate the rate of egg-laying. © 2013 Chotoo et al

FindFoci: a focus detection algorithm with automated parameter training that closely matches human assignments, reduces human inconsistencies and increases speed of analysis

Accurate and reproducible quantification of the accumulation of proteins into foci in cells is essential for data interpretation and for biological inferences. To improve reproducibility, much emphasis has been placed on the preparation of samples, but less attention has been given to reporting and standardizing the quantification of foci. The current standard to quantitate foci in open-source software is to manually determine a range of parameters based on the outcome of one or a few representative images and then apply the parameter combination to the analysis of a larger dataset. Here, we demonstrate the power and utility of using machine learning to train a new algorithm (FindFoci) to determine optimal parameters. FindFoci closely matches human assignments and allows rapid automated exploration of parameter space. Thus, individuals can train the algorithm to mirror their own assignments and then automate focus counting using the same parameters across a large number of images. Using the training algorithm to match human assignments of foci, we demonstrate that applying an optimal parameter combination from a single image is not broadly applicable to analysis of other images scored by the same experimenter or by other experimenters. Our analysis thus reveals wide variation in human assignment of foci and their quantification. To overcome this, we developed training on multiple images, which reduces the inconsistency of using a single or a few images to set parameters for focus detection. FindFoci is provided as an open-source plugin for ImageJ