University of Lausanne

About: University of Lausanne is a education organization based out in Lausanne, Switzerland. It is known for research contribution in the topics: Population & Poison control. The organization has 20508 authors who have published 46458 publications receiving 1996655 citations. The organization is also known as: Université de Lausanne & UNIL.

The Global Posttranscriptional Regulator RsmA Modulates Production of Virulence Determinants and N-Acylhomoserine Lactones in Pseudomonas aeruginosa

Abstract: Posttranscriptional control is known to contribute to the regulation of secondary metabolism and virulence determinants in certain gram-negative bacteria. Here we report the isolation of a Pseudomonas aeruginosa gene which encodes a global translational regulatory protein, RsmA (regulator of secondary metabolites). Overexpression of rsmA resulted in a substantial reduction in the levels of extracellular products, including protease, elastase, and staphylolytic (LasA protease) activity as well as the PA-IL lectin, hydrogen cyanide (HCN), and the phenazine pigment pyocyanin. While inactivation of rsmA in P. aeruginosa had only minor effects on the extracellular enzymes and the PA-IL lectin, the production of HCN and pyocyanin was enhanced during the exponential phase. The influence of RsmA on N-acylhomoserine lactone-mediated quorum sensing was determined by assaying the levels of N-(3-oxododecanoyl)homoserine lactone (3-oxo-C12-HSL) and N-butanoylhomoserine lactone (C4-HSL) produced by the rsmA mutant and the rsmA-overexpressing strain. RsmA exerted a negative effect on the synthesis of both 3-oxo-C12-HSL and C4-HSL, which was confirmed by using lasI and rhlI translational fusions. These data also highlighted the temporal expression control of the lasI gene, which was induced much earlier and to a higher level during the exponential growth phase in an rsmA mutant. To investigate whether RsmA modulates HCN production solely via quorum-sensing control, hcn translational fusions were employed to monitor the regulation of the cyanide biosynthesis genes (hcnABC). RsmA was shown to exert an additional negative effect on cyanogenesis posttranscriptionally by acting on a region surrounding the hcnA ribosome-binding site. This suggests that, in P. aeruginosa, RsmA functions as a pleiotropic posttranscriptional regulator of secondary metabolites directly and also indirectly by modulating the quorum-sensing circuitry.

Evolutionary fate of retroposed gene copies in the human genome

Abstract: Given that retroposed copies of genes are presumed to lack the regulatory elements required for their expression, retroposition has long been considered a mechanism without functional relevance. However, through an in silico assay for transcriptional activity, we identify here >1,000 transcribed retrocopies in the human genome, of which at least ≈120 have evolved into bona fide genes. Among these, ≈50 retrogenes have evolved functions in testes, more than half of which were recruited as functional autosomal counterparts of X-linked genes during spermatogenesis. Generally, retrogenes emerge “out of the testis,” because they are often initially transcribed in testis and later evolve stronger and sometimes more diverse spatial expression patterns. We find a significant excess of transcribed retrocopies close to other genes or within introns, suggesting that retrocopies can exploit the regulatory elements and/or open chromatin of neighboring genes to become transcribed. In direct support of this hypothesis, we identify 36 retrocopy–host gene fusions, including primate-specific chimeric genes. Strikingly, 27 intergenic retrogenes have acquired untranslated exons de novo during evolution to achieve high expression levels. Notably, our screen for highly transcribed retrocopies also uncovered a retrogene linked to a human recessive disorder, gelatinous drop-like corneal dystrophy, a form of blindness. These functional implications for retroposition notwithstanding, we find that the insertion of retrocopies into genes is generally deleterious, because it may interfere with the transcription of host genes. Our results demonstrate that natural selection has been fundamental in shaping the retrocopy repertoire of the human genome.

Outstanding Challenges in the Transferability of Ecological Models.

Abstract: Predictive models are central to many scientific disciplines and vital for informing management in a rapidly changing world However, limited understanding of the accuracy and precision of models transferred to novel conditions (their ‘transferability’) undermines confidence in their predictions Here, 50 experts identified priority knowledge gaps which, if filled, will most improve model transfers These are summarized into six technical and six fundamental challenges, which underlie the combined need to intensify research on the determinants of ecological predictability, including species traits and data quality, and develop best practices for transferring models Of high importance is the identification of a widely applicable set of transferability metrics, with appropriate tools to quantify the sources and impacts of prediction uncertainty under novel conditions

Prediction of n-octanol/water partition coefficients from PHYSPROP database using artificial neural networks and E-state indices.

Abstract: A new method, ALOGPS v 2.0 (http://www.lnh.unil.ch/~itetko/logp/), for the assessment of n-octanol/water partition coefficient, log P, was developed on the basis of neural network ensemble analysis of 12 908 organic compounds available from PHYSPROP database of Syracuse Research Corporation. The atom and bond-type E-state indices as well as the number of hydrogen and non-hydrogen atoms were used to represent the molecular structures. A preliminary selection of indices was performed by multiple linear regression analysis, and 75 input parameters were chosen. Some of the parameters combined several atom-type or bond-type indices with similar physicochemical properties. The neural network ensemble training was performed by efficient partition algorithm developed by the authors. The ensemble contained 50 neural networks, and each neural network had 10 neurons in one hidden layer. The prediction ability of the developed approach was estimated using both leave-one-out (LOO) technique and training/test protocol. In case of interseries predictions, i.e., when molecules in the test and in the training subsets were selected by chance from the same set of compounds, both approaches provided similar results. ALOGPS performance was significantly better than the results obtained by other tested methods. For a subset of 12 777 molecules the LOO results, namely correlation coefficient r(2)= 0.95, root mean squared error, RMSE = 0.39, and an absolute mean error, MAE = 0.29, were calculated. For two cross-series predictions, i.e., when molecules in the training and in the test sets belong to different series of compounds, all analyzed methods performed less efficiently. The decrease in the performance could be explained by a different diversity of molecules in the training and in the test sets. However, even for such difficult cases the ALOGPS method provided better prediction ability than the other tested methods. We have shown that the diversity of the training sets rather than the design of the methods is the main factor determining their prediction ability for new data. A comparative performance of the methods as well as a dependence on the number of non-hydrogen atoms in a molecule is also presented.