Browsing by Author "Slater, A. W."

Now showing 1 - 6 of 6
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    Computer-based annotation of putative AraC/XylS-family transcription factors of known structure but unknown function
    (2012) Schüller, Andreas; Slater, A. W.; Norambuena, T.; Cifuentes, J. J.; Almonacid, L. I.; Melo Ledermann, Francisco Javier
    Currently, about 20 crystal structures per day are released and deposited in the Protein Data Bank. A significant fraction of these structures is produced by research groups associated with the structural genomics consortium. The biological function of many of these proteins is generally unknown or not validated by experiment. Therefore, a growing need for functional prediction of protein structures has emerged. Here we present an integrated bioinformatics method that combines sequence-based relationships and three-dimensional (3D) structural similarity of transcriptional regulators with computer prediction of their cognate DNA binding sequences. We applied this method to the AraC/XylS family of transcription factors, which is a large family of transcriptional regulators found in many bacteria controlling the expression of genes involved in diverse biological functions. Three putative new members of this family with known 3D structure but unknown function were identified for which a probable functional classification is provided. Our bioinformatics analyses suggest that they could be involved in plant cell wall degradation (Lin2118 protein from Listeria innocua, PDB code 3oou), symbiotic nitrogen fixation (protein from Chromobacterium violaceum, PDB code 3oio), and either metabolism of plant-derived biomass or nitrogen fixation (protein from Rhodopseudomonas palustris, PDB code 3mn2).
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    Metabolic and transcriptomic response of the wine yeast Saccharomyces cerevisiae strain EC1118 after an oxygen impulse under carbon-sufficient, nitrogen-limited fermentative conditions
    (2014) Orellana, M.; Aceituno, F. F.; Slater, A. W.; Almonacid, L. I.; Melo Ledermann, Francisco Javier; Agosin T., Eduardo
    During alcoholic fermentation, Saccharomyces cerevisiae is exposed to continuously changing environmental conditions, such as decreasing sugar and increasing ethanol concentrations. Oxygen, a critical nutrient to avoid stuck and sluggish fermentations, is only discretely available throughout the process after pump-over operation. In this work, we studied the physiological response of the wine yeast S. cerevisiae strain EC1118 to a sudden increase in dissolved oxygen, simulating pump-over operation. With this aim, an impulse of dissolved oxygen was added to carbon-sufficient, nitrogen-limited anaerobic continuous cultures. Results showed that genes related to mitochondrial respiration, ergosterol biosynthesis, and oxidative stress, among other metabolic pathways, were induced after the oxygen impulse. On the other hand, mannoprotein coding genes were repressed. The changes in the expression of these genes are coordinated responses that share common elements at the level of transcriptional regulation. Beneficial and detrimental effects of these physiological processes on wine quality highlight the dual role of oxygen in ‘making or breaking wines’. These findings will facilitate the development of oxygen addition strategies to optimize yeast performance in industrial fermentations.
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    Novel α-ketoglutarate dioxygenase tfdA-related genes are found in soil DNA after exposure to phenoxyalkanoic herbicides
    (2010) Gazitúa, M. C.; Slater, A. W.; Melo Ledermann, Francisco Javier; González, B.
    Phenoxyalkanoic herbicides such as 2,4-dichlorophenoxyacetate (2,4-D), 2,4-dichlorophenoxybutyrate (2,4-DB) or mecoprop are widely used to control broad-leaf weeds. Several bacteria have been reported to degrade these herbicides using the α-ketoglutarate-dependent, 2,4-dichlorophenoxyacetate dioxygenase encoded by the tfdA gene, as the enzyme catalysing the first step in the catabolic pathway. The effects of exposure to different phenoxyalkanoic herbicides in the soil bacterial community and in the tfdA genes diversity were assessed using an agricultural soil exposed to these anthropogenic compounds. Total community bacterial DNA was analysed by terminal restriction fragment length polymorphism of the 16S rRNA and the tfdA gene markers, and detection and cloning of tfdA gene related sequences, using PCR primer pairs. After up to 4 months of herbicide exposure, significant changes in the bacterial community structure were detected in soil microcosms treated with mecoprop, 2,4-DB and a mixture of both plus 2,4-D. An impressive variety of novel tfdA gene related sequences were found in these soil microcosms, which cluster in new tfdA gene related sequence groups, unequally abundant depending on the specific herbicide used in soil treatment. Structural analysis of the putative protein products showed small but significant amino acid differences. These tfdA gene sequence variants are, probably, required for degradation of natural substrate(s) structurally related to these herbicides and their presence explains self-remediation of soils exposed to phenoxyalkanoic herbicides.
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    Oxygen response of the wine yeast Saccharomyces cerevisiae EC1118 grown under carbon-sufficient, nitrogen-limited enological conditions
    (2012) Aceituno, F. F.; Orellana, M.; Torres, J.; Mendoza, S.; Slater, A. W.; Melo Ledermann, Francisco Javier; Agosin T., Eduardo
    Discrete additions of oxygen play a critical role in alcoholic fermentation. However, few studies have quantitated the fate of dissolved oxygen and its impact on wine yeast cell physiology under enological conditions. We simulated the range of dissolved oxygen concentrations that occur after a pump-over during the winemaking process by sparging nitrogen-limited continuous cultures with oxygen-nitrogen gaseous mixtures. When the dissolved oxygen concentration increased from 1.2 to 2.7 μM, yeast cells changed from a fully fermentative to a mixed respirofermentative metabolism. This transition is characterized by a switch in the operation of the tricarboxylic acid cycle (TCA) and an activation of NADH shuttling from the cytosol to mitochondria. Nevertheless, fermentative ethanol production remained the major cytosolic NADH sink under all oxygen conditions, suggesting that the limitation of mitochondrial NADH reoxidation is the major cause of the Crabtree effect. This is reinforced by the induction of several key respiratory genes by oxygen, despite the high sugar concentration, indicating that oxygen overrides glucose repression. Genes associated with other processes, such as proline uptake, cell wall remodeling, and oxidative stress, were also significantly affected by oxygen. The results of this study indicate that respiration is responsible for a substantial part of the oxygen response in yeast cells during alcoholic fermentation. This information will facilitate the development of temporal oxygen addition strategies to optimize yeast performance in industrial fermentations.
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    StAR: a simple tool for the statistical comparison of ROC curves
    (2008) Vergara, I. A.; Norambuena, T.; Ferrada, E.; Slater, A. W.; Melo Ledermann, Francisco Javier
    Background As in many different areas of science and technology, most important problems in bioinformatics rely on the proper development and assessment of binary classifiers. A generalized assessment of the performance of binary classifiers is typically carried out through the analysis of their receiver operating characteristic (ROC) curves. The area under the ROC curve (AUC) constitutes a popular indicator of the performance of a binary classifier. However, the assessment of the statistical significance of the difference between any two classifiers based on this measure is not a straightforward task, since not many freely available tools exist. Most existing software is either not free, difficult to use or not easy to automate when a comparative assessment of the performance of many binary classifiers is intended. This constitutes the typical scenario for the optimization of parameters when developing new classifiers and also for their performance validation through the comparison to previous art. Results In this work we describe and release new software to assess the statistical significance of the observed difference between the AUCs of any two classifiers for a common task estimated from paired data or unpaired balanced data. The software is able to perform a pairwise comparison of many classifiers in a single run, without requiring any expert or advanced knowledge to use it. The software relies on a non-parametric test for the difference of the AUCs that accounts for the correlation of the ROC curves. The results are displayed graphically and can be easily customized by the user. A human-readable report is generated and the complete data resulting from the analysis are also available for download, which can be used for further analysis with other software. The software is released as a web server that can be used in any client platform and also as a standalone application for the Linux operating system. Conclusion A new software for the statistical comparison of ROC curves is released here as a web server and also as standalone software for the LINUX operating system.
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    Towards the development of standardized methods for comparison, ranking and evaluation of structure alignments
    (2013) Slater, A. W.; Castellanos, J. I.; Sippl, M. J.; Melo Ledermann, Francisco Javier
    Motivation: Pairwise alignment of protein structures is a fundamental task in structural bioinformatics. There are numerous computer programs in the public domain that produce alignments for a given pair of protein structures, but the results obtained by the various programs generally differ substantially. Hence, in the application of such programs the question arises which of the alignment programs are the most trustworthy in the sense of overall performance, and which programs provide the best result for a given pair of proteins. The major problem in comparing, evaluating and judging alignment results is that there is no clear notion of the optimality of an alignment. As a consequence, the numeric criteria and scores reported by the individual structure alignment programs are largely incomparable. Results: Here we report on the development and application of a new approach for the evaluation of structure alignment results. The method uses the translation vector and rotation matrix to generate the superposition of two structures but discards the alignment reported by the individual programs. The optimal alignment is then generated in standardized form based on a suitably implemented dynamic programming algorithm where the length of the alignment is the single most informative parameter. We demonstrate that some of the most popular programs in protein structure research differ considerably in their overall performance. In particular, each of the programs investigated here produced in at least in one case the best and the worst alignment compared with all others. Hence, at the current state of development of structure comparison techniques, it is advisable to use several programs in parallel and to choose the optimal alignment in the way reported here. Availability and implementation: The computer software that implement the method described here is freely available at http://melolab.org/stovca.