The role of input noise in transcriptional regulation

Even under constant external conditions, the expression levels of genes fluctuate. Much emphasis has been placed on the components of this noise that are due to randomness in transcription and translation; here we analyze the role of noise associated with the inputs to transcriptional regulation, the random arrival and binding of transcription factors to their target sites along the genome. This noise sets a fundamental physical limit to the reliability of genetic control, and has clear signatures, but we show that these are easily obscured by experimental limitations and even by conventional methods for plotting the variance vs. mean expression level. We argue that simple, global models of noise dominated by transcription and translation are inconsistent with the embedding of gene expression in a network of regulatory interactions. Analysis of recent experiments on transcriptional control in the early Drosophila embryo shows that these results are quantitatively consistent with the predicted signatures of input noise, and we discuss the experiments needed to test the importance of input noise more generally.Comment: 11 pages, 5 figures minor correction

1965: Abilene Christian College Bible Lectures - Full Text

LIFT UP YOUR EYES” Being the Abilene Christian College Annual Bible Lectures 1965 Price: $3.95 Published by ABILENE CHRISTIAN COLLEGE STUDENTS EXCHANGE ACC Station Abilene. Texa

Correlations between life-detection techniques and implications for sampling site selection in planetary analog missions

We conducted an analog sampling expedition under simulated mission constraints to areas dominated by basaltic tephra of the Eldfell and Fimmvörðuháls lava fields (Iceland). Sites were selected to be “homogeneous” at a coarse remote sensing resolution (10–100 m) in apparent color, morphology, moisture, and grain size, with best-effort realism in numbers of locations and replicates. Three different biomarker assays (counting of nucleic-acid-stained cells via fluorescent microscopy, a luciferin/luciferase assay for adenosine triphosphate, and quantitative polymerase chain reaction (qPCR) to detect DNA associated with bacteria, archaea, and fungi) were characterized at four nested spatial scales (1 m, 10 m, 100 m, and >1 km) by using five common metrics for sample site representativeness (sample mean variance, group F tests, pairwise t tests, and the distribution-free rank sum H and u tests). Correlations between all assays were characterized with Spearman's rank test. The bioluminescence assay showed the most variance across the sites, followed by qPCR for bacterial and archaeal DNA; these results could not be considered representative at the finest resolution tested (1 m). Cell concentration and fungal DNA also had significant local variation, but they were homogeneous over scales of >1 km. These results show that the selection of life detection assays and the number, distribution, and location of sampling sites in a low biomass environment with limited a priori characterization can yield both contrasting and complementary results, and that their interdependence must be given due consideration to maximize science return in future biomarker sampling expeditions

Understanding Microbialite Morphology Using a Comprehensive Suite of Three-Dimensional Analysis Tools

Abstract Microbialites can have complex morphologies that preserve clues to ancient microbial ecology. However, extracting and interpreting these clues is challenging due to both the complexity of microbial structures and the difficulties of connecting morphology to microbial processes. Fenestrate microbialites from the 2521 -3 Ma Gamohaan Formation, South Africa, have intricate structures composed of three distinct microbial structures: steeply dipping supports (surfaces defined by organic inclusions), more shallowly dipping supports with diffuse organic inclusions below them, and draping laminae. In polished slabs, shallowly dipping supports with diffuse organic inclusions show apparent dips from 27°to 60°, and supports without associated zones of diffuse inclusions dip 75°to 88°, which suggests a distinction between support types based on orientation. However, dips exposed in polished slabs are apparent dips, and three-dimensional analysis is required for analysis of true dips. Through the Keck Center for Active Visualization in Earth Sciences (KeckCAVES), we used locally developed software that controls a three-dimensional environment with head and hand tracking (an ''immersive environment'') to visualize and interpret virtual microbialite data sets. Immersive environments have not penetrated into standard scientific work processes (''workflows'') due to their high costs, steep learning curves, and low productivity for users. By contrast, our suite of software tools allowed us to develop a personalized scientific workflow that provides a complete path from initial ideas to characterization of fenestrate microbialites' features. Results of three-dimensional analysis of fenestrate microbialites show that supports with inclusions dip 65°to 75°, whereas supports without inclusions dip 85°to 90°. These results demonstrate that all supports have very steep dips, and a 10°dip gap exists between supports with and without inclusions, which suggests they grew in fundamentally different ways. Results also emphasize how valuable three-dimensional analysis is when combined with a comprehensive workflow for understanding intricate structures such as fenestrate microbialites

Educational Disparities in Rates of Smoking Among Diabetic Adults: The Translating Research Into Action for Diabetes Study

Objectives. We assessed educational disparities in smoking rates among adults with diabetes in managed care settings. Methods. We used a cross-sectional, survey-based (2002–2003) observational study among 6538 diabetic patients older than 25 years across multiple managed care health plans and states. For smoking at each level of self-reported educational attainment, predicted probabilities were estimated by means of hierarchical logistic regression models with random intercepts for health plan, adjusted for potential confounders. Results. Overall, 15% the participants reported current smoking. An educational gradient in smoking was observed that varied significantly (P<.003) across age groups, with the educational gradient being strong in those aged 25 to 44 years, modest in those aged 45 to 64 years, and nonexistent in those aged 65 years or older. Of particular note, the prevalence of smoking observed in adults aged 25–44 years with less than a high school education was 50% (95% confidence interval: 36% to 63%). Conclusions. Approximately half of poorly educated young adults with diabetes smoke, magnifying the health risk associated with early-onset diabetes. Targeted public health interventions for smoking prevention and cessation among young, poorly educated people with diabetes are needed

Crystal structure of rhodopsin bound to arrestin by femtosecond X-ray laser.

G-protein-coupled receptors (GPCRs) signal primarily through G proteins or arrestins. Arrestin binding to GPCRs blocks G protein interaction and redirects signalling to numerous G-protein-independent pathways. Here we report the crystal structure of a constitutively active form of human rhodopsin bound to a pre-activated form of the mouse visual arrestin, determined by serial femtosecond X-ray laser crystallography. Together with extensive biochemical and mutagenesis data, the structure reveals an overall architecture of the rhodopsin-arrestin assembly in which rhodopsin uses distinct structural elements, including transmembrane helix 7 and helix 8, to recruit arrestin. Correspondingly, arrestin adopts the pre-activated conformation, with a ∼20° rotation between the amino and carboxy domains, which opens up a cleft in arrestin to accommodate a short helix formed by the second intracellular loop of rhodopsin. This structure provides a basis for understanding GPCR-mediated arrestin-biased signalling and demonstrates the power of X-ray lasers for advancing the frontiers of structural biology