18 research outputs found

    Quantitative Fitness Analysis Shows That NMD Proteins and Many Other Protein Complexes Suppress or Enhance Distinct Telomere Cap Defects

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    To better understand telomere biology in budding yeast, we have performed systematic suppressor/enhancer analyses on yeast strains containing a point mutation in the essential telomere capping gene CDC13 (cdc13-1) or containing a null mutation in the DNA damage response and telomere capping gene YKU70 (yku70Δ). We performed Quantitative Fitness Analysis (QFA) on thousands of yeast strains containing mutations affecting telomere-capping proteins in combination with a library of systematic gene deletion mutations. To perform QFA, we typically inoculate 384 separate cultures onto solid agar plates and monitor growth of each culture by photography over time. The data are fitted to a logistic population growth model; and growth parameters, such as maximum growth rate and maximum doubling potential, are deduced. QFA reveals that as many as 5% of systematic gene deletions, affecting numerous functional classes, strongly interact with telomere capping defects. We show that, while Cdc13 and Yku70 perform complementary roles in telomere capping, their genetic interaction profiles differ significantly. At least 19 different classes of functionally or physically related proteins can be identified as interacting with cdc13-1, yku70Δ, or both. Each specific genetic interaction informs the roles of individual gene products in telomere biology. One striking example is with genes of the nonsense-mediated RNA decay (NMD) pathway which, when disabled, suppress the conditional cdc13-1 mutation but enhance the null yku70Δ mutation. We show that the suppressing/enhancing role of the NMD pathway at uncapped telomeres is mediated through the levels of Stn1, an essential telomere capping protein, which interacts with Cdc13 and recruitment of telomerase to telomeres. We show that increased Stn1 levels affect growth of cells with telomere capping defects due to cdc13-1 and yku70Δ. QFA is a sensitive, high-throughput method that will also be useful to understand other aspects of microbial cell biology

    Nutritional Systems Biology Modeling: From Molecular Mechanisms to Physiology

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    The use of computational modeling and simulation has increased in many biological fields, but despite their potential these techniques are only marginally applied in nutritional sciences. Nevertheless, recent applications of modeling have been instrumental in answering important nutritional questions from the cellular up to the physiological levels. Capturing the complexity of today's important nutritional research questions poses a challenge for modeling to become truly integrative in the consideration and interpretation of experimental data at widely differing scales of space and time. In this review, we discuss a selection of available modeling approaches and applications relevant for nutrition. We then put these models into perspective by categorizing them according to their space and time domain. Through this categorization process, we identified a dearth of models that consider processes occurring between the microscopic and macroscopic scale. We propose a “middle-out” strategy to develop the required full-scale, multilevel computational models. Exhaustive and accurate phenotyping, the use of the virtual patient concept, and the development of biomarkers from “-omics” signatures are identified as key elements of a successful systems biology modeling approach in nutrition research—one that integrates physiological mechanisms and data at multiple space and time scales

    Iron Behaving Badly: Inappropriate Iron Chelation as a Major Contributor to the Aetiology of Vascular and Other Progressive Inflammatory and Degenerative Diseases

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    The production of peroxide and superoxide is an inevitable consequence of aerobic metabolism, and while these particular "reactive oxygen species" (ROSs) can exhibit a number of biological effects, they are not of themselves excessively reactive and thus they are not especially damaging at physiological concentrations. However, their reactions with poorly liganded iron species can lead to the catalytic production of the very reactive and dangerous hydroxyl radical, which is exceptionally damaging, and a major cause of chronic inflammation. We review the considerable and wide-ranging evidence for the involvement of this combination of (su)peroxide and poorly liganded iron in a large number of physiological and indeed pathological processes and inflammatory disorders, especially those involving the progressive degradation of cellular and organismal performance. These diseases share a great many similarities and thus might be considered to have a common cause (i.e. iron-catalysed free radical and especially hydroxyl radical generation). The studies reviewed include those focused on a series of cardiovascular, metabolic and neurological diseases, where iron can be found at the sites of plaques and lesions, as well as studies showing the significance of iron to aging and longevity. The effective chelation of iron by natural or synthetic ligands is thus of major physiological (and potentially therapeutic) importance. As systems properties, we need to recognise that physiological observables have multiple molecular causes, and studying them in isolation leads to inconsistent patterns of apparent causality when it is the simultaneous combination of multiple factors that is responsible. This explains, for instance, the decidedly mixed effects of antioxidants that have been observed, etc...Comment: 159 pages, including 9 Figs and 2184 reference

    A Nash Equilibrium approach to metabolic network analysis

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    A novel approach to metabolic network analysis using a Nash Equilibrium formulation is proposed. Enzymes are considered to be players in a multi-player game in which each player attempts to minimize the dimensionless Gibbs free energy associated with the biochemical reaction(s) it catalyzes subject to elemental mass balances. Mathematical formulation of the metabolic network as a set of nonlinear programming (NLP) sub-problems and appropriate solution methodologies are described. A small example representing part of the production cycle for acetyl-CoA is used to demonstrate the efficacy of the proposed Nash Equilibrium framework and show that it represents a paradigm shift in metabolic network analysis

    The Changing Firm Landscape and Firm Location Behaviour

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    The landscape of firms in the Netherlands is changing in such a way that small firms are increasingly dominating the Dutch economy. This development suggests a re-evaluation of how firm location decisions are made, which factors are important and consequently the dynamics in firm location and relocation. This chapter argues that with a smaller size the borders of the firm become permeable and non-firm considerations, including residential preferences and other job locations in the family, play an increasingly important role in the firm location decision process. Also, the physical spaces of the residence and the firm premises overlap more often than ever. Rather than regarding the location of the firm as a reflection of the optimal firm location, it is arguably better viewed as a part of the larger locational puzzle which people and households face

    Household Access to Mortgages in the UK

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    We employ the propensity score matching approach to investigate household access to mortgages in the UK using information on 29,732 households between 2003 and 2010. We find that, on average, the probability of obtaining a mortgage is similar for White and Non-White households. However, we find that Black households with low incomes are less likely to have mortgages compared to White households with similar characteristics. Asian households, in contrast, do not seem to have a lower probability of having a mortgage
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