Optimizing information flow in small genetic networks. I

In order to survive, reproduce and (in multicellular organisms) differentiate, cells must control the concentrations of the myriad different proteins that are encoded in the genome. The precision of this control is limited by the inevitable randomness of individual molecular events. Here we explore how cells can maximize their control power in the presence of these physical limits; formally, we solve the theoretical problem of maximizing the information transferred from inputs to outputs when the number of available molecules is held fixed. We start with the simplest version of the problem, in which a single transcription factor protein controls the readout of one or more genes by binding to DNA. We further simplify by assuming that this regulatory network operates in steady state, that the noise is small relative to the available dynamic range, and that the target genes do not interact. Even in this simple limit, we find a surprisingly rich set of optimal solutions. Importantly, for each locally optimal regulatory network, all parameters are determined once the physical constraints on the number of available molecules are specified. Although we are solving an over--simplified version of the problem facing real cells, we see parallels between the structure of these optimal solutions and the behavior of actual genetic regulatory networks. Subsequent papers will discuss more complete versions of the problem

Mobile phone technology for increasing banana productivity among smallholder farmers in Uganda

The assesses the level of mobile phone use in Ugandan agricultural extension, and to establish the extent to which mobile phone Viamo’s 3-2-1 service, hosted by Airtel Uganda, was being accessed and how the facility can be improved to boost banana productivity

Air Monitoring for Hazardous Gas Detection

The Hazardous Gas Detection Lab (HGDL) at Kennedy Space Center is involved in the design and development of instrumentation that can detect and quantify various hazardous gases. Traditionally these systems are designed for leak detection of the cryogenic gases used for the propulsion of the Shuttle and other vehicles. Mass spectrometers are the basis of these systems, which provide excellent quantitation, sensitivity, selectivity, response times and detection limits. A Table lists common gases monitored for aerospace applications. The first five gases, hydrogen, helium, nitrogen, oxygen, and argon are historically the focus of the HGDL

Genome-Wide Requirements for Resistance to Functionally Distinct DNA-Damaging Agents

The mechanistic and therapeutic differences in the cellular response to DNA-damaging compounds are not completely understood, despite intense study. To expand our knowledge of DNA damage, we assayed the effects of 12 closely related DNA-damaging agents on the complete pool of ~4,700 barcoded homozygous deletion strains of Saccharomyces cerevisiae. In our protocol, deletion strains are pooled together and grown competitively in the presence of compound. Relative strain sensitivity is determined by hybridization of PCR-amplified barcodes to an oligonucleotide array carrying the barcode complements. These screens identified genes in well-characterized DNA-damage-response pathways as well as genes whose role in the DNA-damage response had not been previously established. High-throughput individual growth analysis was used to independently confirm microarray results. Each compound produced a unique genome-wide profile. Analysis of these data allowed us to determine the relative importance of DNA-repair modules for resistance to each of the 12 profiled compounds. Clustering the data for 12 distinct compounds uncovered both known and novel functional interactions that comprise the DNA-damage response and allowed us to define the genetic determinants required for repair of interstrand cross-links. Further genetic analysis allowed determination of epistasis for one of these functional groups

Novel insights into iron metabolism by integrating deletome and transcriptome analysis in an iron deficiency model of the yeast Saccharomyces cerevisiae

<p>Abstract</p> <p>Background</p> <p>Iron-deficiency anemia is the most prevalent form of anemia world-wide. The yeast <it>Saccharomyces cerevisiae </it>has been used as a model of cellular iron deficiency, in part because many of its cellular pathways are conserved. To better understand how cells respond to changes in iron availability, we profiled the yeast genome with a parallel analysis of homozygous deletion mutants to identify essential components and cellular processes required for optimal growth under iron-limited conditions. To complement this analysis, we compared those genes identified as important for fitness to those that were differentially-expressed in the same conditions. The resulting analysis provides a global perspective on the cellular processes involved in iron metabolism.</p> <p>Results</p> <p>Using functional profiling, we identified several genes known to be involved in high affinity iron uptake, in addition to novel genes that may play a role in iron metabolism. Our results provide support for the primary involvement in iron homeostasis of vacuolar and endosomal compartments, as well as vesicular transport to and from these compartments. We also observed an unexpected importance of the peroxisome for growth in iron-limited media. Although these components were essential for growth in low-iron conditions, most of them were not differentially-expressed. Genes with altered expression in iron deficiency were mainly associated with iron uptake and transport mechanisms, with little overlap with those that were functionally required. To better understand this relationship, we used expression-profiling of selected mutants that exhibited slow growth in iron-deficient conditions, and as a result, obtained additional insight into the roles of <it>CTI6</it>, <it>DAP1</it>, <it>MRS4 </it>and <it>YHR045W </it>in iron metabolism.</p> <p>Conclusion</p> <p>Comparison between functional and gene expression data in iron deficiency highlighted the complementary utility of these two approaches to identify important functional components. This should be taken into consideration when designing and analyzing data from these type of studies. We used this and other published data to develop a molecular interaction network of iron metabolism in yeast.</p

Aromatherapy in mental health: A brief review

Aromatherapy uses essential oils as the main therapeutic agents. In the present work a brief review was made on the aromatherapy used in mental health. It describes evidence for and against the use of aromatherapy in stress, anxiety, depression, sleep disorders, cognitive disorders and other disorders; as well as data related to its safety, adverse effects, contraindications and mechanisms of action. In conclusion, aromatherapy can be considered as an option that can be used as a complement to treatments aimed to restore mental health and associated disorders.La aromaterapia usa como principales agentes terapéuticos los aceites esenciales. En el presente trabajo se realizó una breve revisión sobre la aromaterapia usada en la salud mental, donde se describe evidencia a favor y en contra del uso de la aromaterapia en el estrés, ansiedad, depresión, trastornos del sueño, trastornos cognitivos y otros trastornos; así como también se presentan datos relacionados a su seguridad, efectos adversos, contraindicaciones y mecanismos de acción; concluyendo que la aromaterapia puede ser considerada como una opción que puede ser utilizada como complemento a los tratamientos destinados al restablecimiento de la salud mental y trastornos asociados

A stochastic model of Escherichia coli AI-2 quorum signal circuit reveals alternative synthesis pathways

Quorum sensing (QS) is an important determinant of bacterial phenotype. Many cell functions are regulated by intricate and multimodal QS signal transduction processes. The LuxS/AI-2 QS system is highly conserved among Eubacteria and AI-2 is reported as a ‘universal' signal molecule. To understand the hierarchical organization of AI-2 circuitry, a comprehensive approach incorporating stochastic simulations was developed. We investigated the synthesis, uptake, and regulation of AI-2, developed testable hypotheses, and made several discoveries: (1) the mRNA transcript and protein levels of AI-2 synthases, Pfs and LuxS, do not contribute to the dramatically increased level of AI-2 found when cells are grown in the presence of glucose; (2) a concomitant increase in metabolic flux through this synthesis pathway in the presence of glucose only partially accounts for this difference. We predict that ‘high-flux' alternative pathways or additional biological steps are involved in AI-2 synthesis; and (3) experimental results validate this hypothesis. This work demonstrates the utility of linking cell physiology with systems-based stochastic models that can be assembled de novo with partial knowledge of biochemical pathways