1alpha,25-Dihydroxyvitamin D3 [1,25(OH)2D3] regulates calcium homeostasis and controls cellular differentiation and proliferation. The vitamin D receptor (VDR) is a ligand-regulated transcription factor that recognizes cognate vitamin D response elements (VDREs) formed by direct or everted repeats of PuG(G/T)TCA motifs separated by 3 or 6 bp (DR3 or ER6). Here, we have identified direct 1,25(OH)2D3 target genes by combining 35,000+ gene microarrays and genome-wide screens for consensus DR3 and ER6 elements, and DR3 elements containing single nucleotide substitutions. We find that the effect of a nucleotide substitution on VDR binding in vitro does not predict VDRE function in vivo, because substitutions that disrupted binding in vitro were found in several functional elements. Hu133A microarray analyses, performed with RNA from human SCC25 cells treated with 1,25(OH)2D3 and protein synthesis inhibitor cycloheximide, identified more than 900 regulated genes. VDREs lying within -10 to +5 kb of 5'-ends were assigned to 65% of these genes, and VDR binding was confirmed to several elements in vivo. A screen of the mouse genome identified more than 3000 conserved VDREs, and 158 human genes containing conserved elements were 1,25(OH2)D3-regulated on Hu133A microarrays. These experiments also revealed 16 VDREs in 11 of 12 genes induced more than 10-fold in our previous microarray study, five elements in the human gene encoding the epithelial calcium channel TRPV6, as well as novel 1,25(OH2)D3 target genes implicated in regulation of cell cycle progression. The combined approaches used here thus provide numerous insights into the direct target genes underlying the broad physiological actions of 1,25(OH)2D3.

Phenotype switching is commonly observed in nature. This prevalence has allowed the elucidation of a number of underlying molecular mechanisms. However, little is known about how phenotypic switches arise and function in their early evolutionary stages. The first opportunity to provide empirical insight was delivered by an experiment in which populations of the bacterium Pseudomonas fluorescens SBW25 evolved, de novo, the ability to switch between two colony phenotypes. Here we unravel the molecular mechanism behind colony switching, revealing how a single nucleotide change in a gene enmeshed in central metabolism (carB) generates such a striking phenotype. We show that colony switching is underpinned by ON/OFF expression of capsules consisting of a colanic acid-like polymer. We use molecular genetics, biochemical analyses, and experimental evolution to establish that capsule switching results from perturbation of the pyrimidine biosynthetic pathway. Of central importance is a bifurcation point at which uracil triphosphate is partitioned towards either nucleotide metabolism or polymer production. This bifurcation marks a cell-fate decision point whereby cells with relatively high pyrimidine levels favour nucleotide metabolism (capsule OFF), while cells with lower pyrimidine levels divert resources towards polymer biosynthesis (capsule ON). This decision point is present and functional in the wild-type strain. Finally, we present a simple mathematical model demonstrating that the molecular components of the decision point are capable of producing switching. Despite its simple mutational cause, the connection between genotype and phenotype is complex and multidimensional, offering a rare glimpse of how noise in regulatory networks can provide opportunity for evolution.

Predicting evolutionary change poses numerous challenges. Here we take advantage of the model bacterium Pseudomonas fluorescens in which the genotype-to-phenotype map determining evolution of the adaptive ‘wrinkly spreader’ (WS) type is known. We present mathematical descriptions of three necessary regulatory pathways and use these to predict both the rate at which each mutational route is used and the expected mutational targets. To test predictions, mutation rates and targets were determined for each pathway. Unanticipated mutational hotspots caused experimental observations to depart from predictions but additional data led to refined models. A mismatch was observed between the spectra of WS-causing mutations obtained with and without selection due to low fitness of previously undetected WS-causing mutations. Our findings contribute toward the development of mechanistic models for forecasting evolution, highlight current limitations, and draw attention to challenges in predicting locus-specific mutational biases and fitness effects.

By consuming and producing environmental resources, organisms inevitably change their habitat. The consequences of such environmental modifications can be detrimental or beneficial not only to the focal organism but also to other organisms sharing the same environment. Social evolution theory has been very influential in studying how social interactions mediated by public goods or bads evolve by emphasising the role of spatial structure. The environmental dimensions driving these interactions, however, are typically abstracted away. Here we propose a new, environmentally-mediated taxonomy of social behaviours where organisms are categorised by their production or consumption of environmental factors that help or harm others in the environment. We discuss microbial examples of our classification and highlight the importance of environmental intermediates more generally.

Background-In various heart disease paradigms, atria show stronger fibrotic responses than ventricles. The possibility that atrial and ventricular fibroblasts respond differentially to pathological stimuli has not been examined. Methods and Results-We compared various morphological, secretory, and proliferative response indexes of canine atrial versus ventricular fibroblasts. Cultured atrial fibroblasts showed faster cell surface area increases, distinct morphology at confluence, and greater ␣-smooth muscle actin expression than ventricular fibroblasts. Atrial fibroblast proliferation ([ 3 H]thymidine incorporation) responses were consistently greater for a range of growth factors, including fetal bovine serum, platelet-derived growth factor (PDGF), basic fibroblast growth factor, angiotensin II, endothelin-1, and transforming growth factor-␤ 1 . Normal atrial tissue showed larger myofibroblast density compared with ventricular tissue, and the difference was exaggerated by congestive heart failure. Congestive heart failure atria showed larger fractions of fibroblasts in mitotic phases compared with ventricles and displayed enhanced gene expression of fibroblast-selective markers (collagen-1, collagen-3, fibronectin-1). Gene microarrays revealed 225 differentially expressed transcript probe sets between paired atrial and ventricular fibroblast samples, including extracellular matrix (eg, fibronectin, laminin, fibulin), cell signaling (PDGF, PDGF receptor, angiopoietin, vascular endothelial growth factor), structure (keratin), and metabolism (xanthine dehydrogenase) genes, identifying PDGF as a candidate contributor to atrial-ventricular fibroblast differences. PDGF receptor gene expression was greater in normal atrium compared with ventricle, and congestive heart failure differentially enhanced atrial versus ventricular PDGF and PDGF receptor gene expression. PDGF receptor protein expression and ␣-smooth muscle actin protein expression were enhanced in isolated congestive heart failure fibroblasts. The PDGF receptor tyrosine kinase inhibitor AG1295 eliminated fetal bovine serum-and transforming growth factor-␤ 1 -stimulated atrial-ventricular fibroblast proliferative response differences. Conclusions-Atrial

Microbes maintain themselves through a variety of processes. Several of these processes can be reduced or shut down entirely when resource availability declines. In pure culture conditions with ample substrate supply, a relationship between the maximum growth rate and the energy invested in maintenance has been reported widely. However, at the other end of the resources spectrum, bacteria are so extremely limited by energy that no growth occurs and metabolism is constrained to the most essential functions only. These minimum energy requirements have been called the basal power requirement. While seemingly different from each other, both aspects are likely components of a continuum of regulated maintenance processes. Here, we analyze cross-species tradeoffs in cellular physiology over the range of bacterial size and energy expenditure and determine the contributions to maintenance metabolism at each point along the size-energy spectrum. Furthermore, by exploring the simplest bacteria within this framework– which are most affected by maintenance constraints– we uncover which processes become most limiting. For the smallest species, maintenance metabolism converges on total metabolism, where we predict that maintenance is dominated by the repair of proteins. For larger species the relative costs of protein repair decrease and maintenance metabolism is predicted to be dominated by the repair of RNA components. These results provide new insights into which processes are likely to be regulated in environments that are extremely limited by energy.

SignificanceEpidemiological evidence suggests that vitamin D can protect women from developing breast cancer (BC). This study reveals that vitamin D and its receptor regulate autophagy in both normal mammary epithelial cells and luminal BCs, and suggests a potential mechanism underlying the link between vitamin D levels and BC risk. In addition, this work suggests that vitamin D receptor ligands could be exploited therapeutically for the treatment of a significant subset of BCs.

Cells must respond to environmental changes to remain viable, yet the information they receive is often noisy. Through a biochemical implementation of Bayes's rule, we show that genetic networks can act as inference modules, inferring from intracellular conditions the likely state of the extracellular environment and regulating gene expression appropriately. By considering a two-state environment, either poor or rich in nutrients, we show that promoter occupancy is proportional to the (posterior) probability of the high nutrient state given current intracellular information. We demonstrate that single-gene networks inferring and responding to a high environmental state infer best when negatively controlled, and those inferring and responding to a low environmental state infer best when positively controlled. Our interpretation is supported by experimental data from the lac operon and should provide a basis for both understanding more complex cellular decision-making and designing synthetic inference circuits.biochemical networks ͉ systems biology ͉ Bayesian inference F or cells to interact with their environment, the DNA and regulatory machinery, which are intracellular, require information from the cell surface. This information is conveyed through gene and protein networks and is transferred via biochemical reactions that are potentially significantly stochastic (1-4). Stochastic fluctuations will undermine both signal detection and transduction. Cells are therefore confronted with the task of predicting the state of the extracellular environment from noisy and potentially unreliable intracellular signals. For example, a bacterium must decide from intracellular levels of a nutrient whether or not the nutrient is sufficiently abundant extracellularly to express the appropriate catabolic enzymes. Similarly, a smooth muscle cell must decide from concentrations of second messengers whether or not extracellular hormone levels are high enough to warrant contracting.Here, we consider if, and how, it is possible for biochemical networks to correctly infer properties of the extracellular environment based on noisy, intracellular signals. Suppose that the cell should respond under high concentrations of an extracellular molecule. Suppose further that the concentration of an intracellular signaling molecule is related to the concentration of the extracellular molecule through a signal transduction mechanism. A simple inference network could establish a concentration threshold for the intracellular molecule. Only if the molecule is above threshold is the extracellular concentration judged to be high enough for a cellular response. This network performs poorly, however, in fluctuating extracellular and intracellular environments. First, fluctuations lead to input molecules crossing threshold even when the state of the environment is unchanged. Second, a threshold scheme cannot specify the degree of certainty in the inference, which may be important for the ultimate response. For example, a bacterium may express a catabolic...