Differences in environmental stress response between yeasts is consistent with species-specific lifestyles

Defining how organisms respond to environmental change has always been an important step toward understating their adaptive capacity and physiology. Variation in transcription during stress has been widely described in model species, especially in the yeastSaccharomyces cerevisiae, which helped to shape general rules regarding how cells cope with environmental constraints as well as decipher the functions of many genes. Now, comparison of the environmental stress response (ESR) across species is essential to obtain a better insight into the common and species-specific features of stress defense. In this context, we explored the transcriptional landscape of the yeastLachancea kluyveri(formerlySaccharomyces kluyveri) in response to diverse stresses, using RNA-seq. We investigated variation in gene expression and observed a link between genetic plasticity and environmental sensitivity. We identified the ESR genes in this species and compared them to those already found inS. cerevisiae We observed common features between the two species as well as divergence in the regulatory networks involved. Interestingly, some changes were related to differences in species lifestyle. Thus, we were able to decipher how adaptation to stress has evolved among different yeast species. Finally, by analyzing patterns of coexpression, we were able to propose potential biological functions for 42% of genes and furthermore annotate 301 genes for which no function could be assigned by homology. This large dataset allowed for the characterization of the evolution of gene regulation and provides an efficient tool to assess gene function

Integrative Analysis of the Mitochondrial Proteome in Yeast

In this study yeast mitochondria were used as a model system to apply, evaluate, and integrate different genomic approaches to define the proteins of an organelle. Liquid chromatography mass spectrometry applied to purified mitochondria identified 546 proteins. By expression analysis and comparison to other proteome studies, we demonstrate that the proteomic approach identifies primarily highly abundant proteins. By expanding our evaluation to other types of genomic approaches, including systematic deletion phenotype screening, expression profiling, subcellular localization studies, protein interaction analyses, and computational predictions, we show that an integration of approaches moves beyond the limitations of any single approach. We report the success of each approach by benchmarking it against a reference set of known mitochondrial proteins, and predict approximately 700 proteins associated with the mitochondrial organelle from the integration of 22 datasets. We show that a combination of complementary approaches like deletion phenotype screening and mass spectrometry can identify over 75% of the known mitochondrial proteome. These findings have implications for choosing optimal genome-wide approaches for the study of other cellular systems, including organelles and pathways in various species. Furthermore, our systematic identification of genes involved in mitochondrial function and biogenesis in yeast expands the candidate genes available for mapping Mendelian and complex mitochondrial disorders in humans

Plasma-liquid interactions: a review and roadmap

Plasma-liquid interactions represent a growing interdisciplinary area of research involving plasma science, fluid dynamics, heat and mass transfer, photolysis, multiphase chemistry and aerosol science. This review provides an assessment of the state-of-the-art of this multidisciplinary area and identifies the key research challenges. The developments in diagnostics, modeling and further extensions of cross section and reaction rate databases that are necessary to address these challenges are discussed. The review focusses on non-equilibrium plasmas

Turnip mosaic virus in oilseed rape activates networks of sRNA-mediated interactions between viral and host genomes

16 p.-7 fig.Virus-induced plant diseases in cultivated plants cause important damages in yield. Although the mechanisms of virus infection are intensely studied at the cell biology level, only little is known about the molecular dialog between the invading virus and the host genome. Here we describe a combinatorial genome-wide approach to identify networks of sRNAs-guided posttranscriptional regulation within local Turnip mosaic virus (TuMV) infection sites in Brassica napus leaves. We show that the induction of host-encoded, virus-activated small interfering RNAs (vasiRNAs) observed in virus-infected tissues is accompanied by site-specific cleavage events on both viral and host RNAs that recalls the activity of small RNA-induced silencing complexes (RISC). Cleavage events also involve virus-derived siRNA (vsiRNA)–directed cleavage of target host transcripts as well as cleavage of viral RNA by both host vasiRNAs and vsiRNAs. Furthermore, certain coding genes act as virus-activated regulatory hubs to produce vasiRNAs for the targeting of other host genes. The observations draw an advanced model of plant-virus interactions and provide insights into the complex regulatory networking at the plant-virus interface within cells undergoing early stages of infection.This work has been subject to the trinational PLANT-KBBE 2012 project GAMAVIR. We acknowledge funding from the French Agence National de la Recherche (grant ANR-13-KBBE-0005-01), the Swiss National Science Foundation (SNF, grant 31003A_140694), and the Région Alsace (PhD fellowship for N.P.) to M.H., from the Spanish Ministerio de Economia y Competitividad (MINECO, PCIN-213-064 and BIO2015-70752-R) to C.L., and the Deutsche Forschungsgemeinschaft (DFG, grant 031A324) to M.W.Peer reviewe

Evaluation of the relevance and access of EHR-based variables to support personalized medicine in breast cancer

Background: The increasing number of available cancer therapies render medical decision-making (MDM) less straightforward. Patients want to know about the outcomes of similarly treated patients. Objective: The goal of this study was to design a breast cancer dashboard (BCD) tool that presents survival information to support MDM activities. Methods: Clinical variables during the clinic visit were determined via provider meetings and evaluated for accessibility from medical databases. Women with breast cancer (BC) were interviewed about their health care experiences after cancer diagnosis. We created a cohort of BC adult women treated at our institution from 1995 to 2012, from which clinical scenarios were defined and used to test survival outcomes. For the BCD, a simple, graphical user interface was built to present point-of-care clinical and survival data. Results: It is feasible to build the BCD using our institution’s databases and generate survival plots to facilitate MDM activities. Patients with early-stage BC had the highest survival rate (82.3%) and the longest mean life years of 7.0 (SD 4.5) years. In late-stage BC, poor prognosis outweighs the influence of number of comorbidities on mortality. The BCD tool promotes more predictive, personalized, and collaborative health care

The Hidden Complexity of Mendelian Traits across Natural Yeast Populations

Mendelian traits are considered to be at the lower end of the complexity spectrum of heritable phenotypes. However, more than a century after the rediscovery of Mendel’s law, the global landscape of monogenic variants, as well as their effects and inheritance patterns within natural populations, is still not well understood. Using the yeast Saccharomyces cerevisiae, we performed a species-wide survey of Mendelian traits across a large population of isolates. We generated offspring from 41 unique parental pairs and analyzed 1,105 cross/trait combinations. We found that 8.9% of the cases were Mendelian. Further tracing of causal variants revealed background-specific expressivity and modified inheritances, gradually transitioning from Mendelian to complex traits in 30% of the cases. In fact, when taking into account the natural population diversity, the hidden complexity of traits could be substantial, confounding phenotypic predictability even for simple Mendelian traits

Fate of a terminal olefin with Drosophila microsomes and its inhibitory effects on some P-450 dependent activities

International audienc

Program in Personalized Health Care

Abstract: Background: The increasing number of available cancer therapies render medical decision-making (MDM) less straightforward. Patients want to know about the outcomes of similarly treated patients. Objective: The goal of this study was to design a breast cancer dashboard (BCD) tool that presents survival information to support MDM activities. Methods: Clinical variables during the clinic visit were determined via provider meetings and evaluated for accessibility from medical databases. Women with breast cancer (BC) were interviewed about their health care experiences after cancer diagnosis. We created a cohort of BC adult women treated at our institution from 1995 to 2012, from which clinical scenarios were defined and used to test survival outcomes. For the BCD, a simple, graphical user interface was built to present point-of-care clinical and survival data. Results: It is feasible to build the BCD using our institution's databases and generate survival plots to facilitate MDM activities. Patients with early-stage BC had the highest survival rate (82.3%) and the longest mean life years of 7.0 (SD 4.5) years. In late-stage BC, poor prognosis outweighs the influence of number of comorbidities on mortality. The BCD tool promotes more predictive, personalized, and collaborative health care. ABOUT THE AUTHORS The authors work across the University of Utah Health Sciences in oncology clinical practice, bioinformatics, and pharmacotherapy outcomes research. Our work is aimed at improving patient care via outcomes research and assessment. The Center's personnel have expertise in health economics, modeling, various clinical subspecialties (including oncology), drug information, statistical analysis and programming, and database management. PUBLIC INTEREST STATEMENT As more breast cancer treatment options become available, the shared medical decision-making relationship between physician and patient is becoming less straightforward. To support this important interaction, we have created an institution-specific medical communication tool. Decision aids have been shown to improve the health care experience of patients and ultimately lead to the achievement of higher-quality decisions. Our communication tool, named the breast cancer dashboard (BCD), was designed to be used during the clinic visit. It specifically address patients' needs to know about the survival outcomes of similar patients treated at our cancer specialty hospital. The BCD brings together comprehensive and breast cancerspecific clinical information. It allows both the provider and patient to navigate the information using a patient-friendly graphic interface. By enhancing shared decision-making, there would be a shift toward patient care that is more predictive, preventive, personalized, and collaborative