54 research outputs found

    In vitro activation of NAD-dependent alcohol dehydrogenases by Nudix hydrolases is more widespread than assumed

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    AbstractIn the Gram-positive methylotroph Bacillus methanolicus, methanol oxidation is catalyzed by an NAD-dependent methanol dehydrogenase (Mdh) that belongs to the type III alcohol dehydrogenase (Adh) family. It was previously shown that the in vitro activity of B. methanolicus Mdh is increased by the endogenous activator protein Act, a Nudix hydrolase. Here we show that this feature is not unique, but more widespread among type III Adhs in combination with Act or other Act-like Nudix hydrolases. In addition, we studied the effect of site directed mutations in the predicted active site of Mdh and two other type III Adhs with regard to activity and activation by Act

    Modeling of continuous PHA production by a hybrid approach based on first principles and machine learning

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    Polyhydroxyalkanoates (PHA) are renewable alternatives to traditional oil-derived poly-mers. PHA can be produced by different microorganisms in continuous culture under specific media composition, which makes the production process both promising and challenging. In order to achieve large productivities while maintaining high yield and efficiency, the continuous culture needs to be operated in the so-called dual nutrient limitation condition, where both the nitrogen and carbon sources are kept at very low concentrations. Mathematical models can greatly assist both design and operation of the bioprocess, but are challenged by the complexity of the system, in particular by the dual nutrient-limited growth phenomenon, where the cells undergo a metabolic shift that abruptly changes their behavior. Traditional, non-structured mechanistic models based on Monod uptake kinetics can be used to describe the bioreactor operation under specific process conditions. However, in the absence of a model description of the metabolic phenomena inside the cell, the extrapolation to a broader operation domain (e.g., different feeding concentrations and dilution rates) may present mismatches between the predictions and the actual process outcomes. Such detailed models may require almost perfect knowledge of the cell metabolism and omic-level measurements, hampering their development. On the other hand, purely data-driven models that learn correlations from experimental data do not require any prior knowledge of the process and are therefore unbiased and flexible. However, many more data are required for their development and their extrapolation ability is limited to conditions that are similar to the ones used for training. An attractive alternative is the combination of the extrapolation power of first principles knowledge with the flexibility of machine learning methods. This approach results in a hybrid model for the growth and uptake rates that can be used to predict the dynamic operation of the bioreactor. Here we develop a hybrid model to describe the continuous production of PHA by Pseudomonas putida GPo1 culture. After training, the model with experimental data gained under different dilution rates and medium compositions, we demonstrate how the model can describe the process in a wide range of operating conditions, including both single and dual nutrient-limited growth.Fil: Luna, Martín Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Ochsner, Andrea M.. University Of Applied Sciences And Arts Western; SuizaFil: Amstutz, Véronique. University Of Applied Sciences And Arts Western ; SuizaFil: von Blarer, Damian. No especifíca;Fil: Sokolov, Michael. No especifíca;Fil: Arosio, Paolo. No especifíca;Fil: Zinn, Manfred. University Of Applied Sciences And Arts Western; Suiz

    Testing gravitational-wave searches with numerical relativity waveforms: Results from the first Numerical INJection Analysis (NINJA) project

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    The Numerical INJection Analysis (NINJA) project is a collaborative effort between members of the numerical relativity and gravitational-wave data analysis communities. The purpose of NINJA is to study the sensitivity of existing gravitational-wave search algorithms using numerically generated waveforms and to foster closer collaboration between the numerical relativity and data analysis communities. We describe the results of the first NINJA analysis which focused on gravitational waveforms from binary black hole coalescence. Ten numerical relativity groups contributed numerical data which were used to generate a set of gravitational-wave signals. These signals were injected into a simulated data set, designed to mimic the response of the Initial LIGO and Virgo gravitational-wave detectors. Nine groups analysed this data using search and parameter-estimation pipelines. Matched filter algorithms, un-modelled-burst searches and Bayesian parameter-estimation and model-selection algorithms were applied to the data. We report the efficiency of these search methods in detecting the numerical waveforms and measuring their parameters. We describe preliminary comparisons between the different search methods and suggest improvements for future NINJA analyses.Comment: 56 pages, 25 figures; various clarifications; accepted to CQ

    Positive Signature-Tagged Mutagenesis in Pseudomonas aeruginosa: Tracking Patho-Adaptive Mutations Promoting Airways Chronic Infection

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    The opportunistic pathogen Pseudomonas aeruginosa can establish life-long chronic infections in the airways of cystic fibrosis (CF) patients. Persistent lifestyle is established with P. aeruginosa patho-adaptive variants, which are clonal with the initially-acquired strains. Several reports indicated that P. aeruginosa adapts by loss-of-function mutations which enhance fitness in CF airways and sustain its clonal expansion during chronic infection. To validate this model of P. aeruginosa adaptation to CF airways and to identify novel genes involved in this microevolution, we designed a novel approach of positive-selection screening by PCR-based signature-tagged mutagenesis (Pos-STM) in a murine model of chronic airways infection. A systematic positive-selection scheme using sequential rounds of in vivo screenings for bacterial maintenance, as opposed to elimination, generated a list of genes whose inactivation increased the colonization and persistence in chronic airways infection. The phenotypes associated to these Pos-STM mutations reflect alterations in diverse aspects of P. aeruginosa biology which include lack of swimming and twitching motility, lack of production of the virulence factors such as pyocyanin, biofilm formation, and metabolic functions. In addition, Pos-STM mutants showed altered invasion and stimulation of immune response when tested in human respiratory epithelial cells, indicating that P. aeruginosa is prone to revise the interaction with its host during persistent lifestyle. Finally, sequence analysis of Pos-STM genes in longitudinally P. aeruginosa isolates from CF patients identified signs of patho-adaptive mutations within the genome. This novel Pos-STM approach identified bacterial functions that can have important clinical implications for the persistent lifestyle and disease progression of the airway chronic infection

    Effects of Aversive Stimuli on Prospective Memory. An Event-Related fMRI Study

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    Prospective memory (PM) describes the ability to execute a previously planned action at the appropriate point in time. Although behavioral studies clearly showed that prospective memory performance is affected by the emotional significance attributed to the intended action, no study so far investigated the brain mechanisms subserving the modulatory effect of emotional salience on PM performance. The general aim of the present study was to explore brain regions involved in prospective memory processes when PM cues are associated with emotional stimuli. In particular, based on the hypothesised critical role of the prefrontal cortex in prospective memory in the presence of emotionally salient stimuli, we expected a stronger involvement of aPFC when the retrieval and execution of the intended action is cued by an aversive stimulus. To this aim BOLD responses of PM trials cued by aversive facial expressions were compared to PM trials cued by neutral facial expressions. Whole brain analysis showed that PM task cued by aversive stimuli is differentially associated with activity in the right lateral prefrontal area (BA 10) and in the left caudate nucleus. Moreover a temporal shift between the response of the caudate nucleus that preceded that of aPFC was observed. These findings suggest that the caudate nucleus might provide an early analysis of the affective properties of the stimuli, whereas the anterior lateral prefrontal cortex (BA10) would be involved in a slower and more deliberative analysis to guide goal-directed behaviour

    The neural substrate of positive bias in spontaneous emotional processing

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    Even in the presence of negative information, healthy human beings display an optimistic tendency when thinking of past success and future chances, giving a positive bias to everyday's cognition. The tendency to actively select positive thoughts suggests the existence of a mechanism to exclude negative content, raising the issue of its dependence on mechanisms like those of effortful control. Using perfusion imaging, we examined how brain activations differed according to whether participants were left to prefer positive thoughts spontaneously, or followed an explicit instruction to the same effect, finding a widespread dissociation of brain perfusion patterns. Under spontaneous processing of emotional material, recruitment of areas associated with effortful attention, such as the dorsolateral prefrontal cortex, was reduced relative to instructed avoidance of negative material (F(1,58) = 26.24, p = 0.047, corrected). Under spontaneous avoidance perfusion increments were observed in several areas that were deactivated by the task, including the perigenual medial prefrontal cortex. Furthermore, individual differences in executive capacity were not associated with positive bias. These findings suggest that spontaneous positive cognitive emotion regulation in health may result from processes that, while actively suppressing emotionally salient information, differ from those associated with effortful and directed control

    Supplement: "Localization and broadband follow-up of the gravitational-wave transient GW150914" (2016, ApJL, 826, L13)

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    This Supplement provides supporting material for Abbott et al. (2016a). We briefly summarize past electromagnetic (EM) follow-up efforts as well as the organization and policy of the current EM follow-up program. We compare the four probability sky maps produced for the gravitational-wave transient GW150914, and provide additional details of the EM follow-up observations that were performed in the different bands

    Serotonin transporter gene polymorphisms and brain function during emotional distraction from cognitive processing in posttraumatic stress disorder

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    BACKGROUND: Serotonergic system dysfunction has been implicated in posttraumatic stress disorder (PTSD). Genetic polymorphisms associated with serotonin signaling may predict differences in brain circuitry involved in emotion processing and deficits associated with PTSD. In healthy individuals, common functional polymorphisms in the serotonin transporter gene (SLC6A4) have been shown to modulate amygdala and prefrontal cortex (PFC) activity in response to salient emotional stimuli. Similar patterns of differential neural responses to emotional stimuli have been demonstrated in PTSD but genetic factors influencing these activations have yet to be examined. METHODS: We investigated whether SLC6A4 promoter polymorphisms (5-HTTLPR, rs25531) and several downstream single nucleotide polymorphisms (SNPs) modulated activity of brain regions involved in the cognitive control of emotion in post-9/11 veterans with PTSD. We used functional MRI to examine neural activity in a PTSD group (n = 22) and a trauma-exposed control group (n = 20) in response to trauma-related images presented as task-irrelevant distractors during the active maintenance period of a delayed-response working memory task. Regions of interest were derived by contrasting activation for the most distracting and least distracting conditions across participants. RESULTS: In patients with PTSD, when compared to trauma-exposed controls, rs16965628 (associated with serotonin transporter gene expression) modulated task-related ventrolateral PFC activation and 5-HTTLPR tended to modulate left amygdala activation. Subsequent to combat-related trauma, these SLC6A4 polymorphisms may bias serotonin signaling and the neural circuitry mediating cognitive control of emotion in patients with PTSD. CONCLUSIONS: The SLC6A4 SNP rs16965628 and 5-HTTLPR are associated with a bias in neural responses to traumatic reminders and cognitive control of emotions in patients with PTSD. Functional MRI may help identify intermediate phenotypes and dimensions of PTSD that clarify the functional link between genes and disease phenotype, and also highlight features of PTSD that show more proximal influence of susceptibility genes compared to current clinical categorizations

    All-sky search for long-duration gravitational wave transients with initial LIGO

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    We present the results of a search for long-duration gravitational wave transients in two sets of data collected by the LIGO Hanford and LIGO Livingston detectors between November 5, 2005 and September 30, 2007, and July 7, 2009 and October 20, 2010, with a total observational time of 283.0 days and 132.9 days, respectively. The search targets gravitational wave transients of duration 10–500 s in a frequency band of 40–1000 Hz, with minimal assumptions about the signal waveform, polarization, source direction, or time of occurrence. All candidate triggers were consistent with the expected background; as a result we set 90% confidence upper limits on the rate of long-duration gravitational wave transients for different types of gravitational wave signals. For signals from black hole accretion disk instabilities, we set upper limits on the source rate density between 3.4×10−5 and 9.4×10−4  Mpc−3 yr−1 at 90% confidence. These are the first results from an all-sky search for unmodeled long-duration transient gravitational waves
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