127 research outputs found

    Phosphoregulation on mitochondria: Integration of cell and organelle responses

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    Mitochondria are highly integrated organelles that are crucial to cell adaptation and mitigating adverse physiology. Recent studies demonstrate that fundamental signal transduction pathways incorporate mitochondrial substrates into their biological programs. Reversible phosphorylation is emerging as a useful mechanism to modulate mitochondrial function in accordance with cellular changes. Critical serine/threonine protein kinases, such as the c‐Jun N‐terminal kinase (JNK), protein kinase A (PKA), PTEN‐induced kinase‐1 (PINK1), and AMP‐dependent protein kinase (AMPK), readily translocate to the outer mitochondrial membrane (OMM), the interface of mitochondria‐cell communication. OMM protein kinases phosphorylate diverse mitochondrial substrates that have discrete effects on organelle dynamics, protein import, respiratory complex activity, antioxidant capacity, and apoptosis. OMM phosphorylation events can be tempered through the actions of local protein phosphatases, such as mitogen‐activated protein kinase phosphatase‐1 (MKP‐1) and protein phosphatase 2A (PP2A), to regulate the extent and duration of signaling. The central mediators of OMM signal transduction are the scaffold proteins because the relative abundance of these accessory proteins determines the magnitude and duration of a signaling event on the mitochondrial surface, which dictates the biological outcome of a local signal transduction pathway. The concentrations of scaffold proteins, such as A‐kinase anchoring proteins (AKAPs) and Sab (or SH3 binding protein 5—SH3BP5), have been shown to influence neuronal survival and vulnerability, respectively, in models of Parkinson\u27s disease (PD), highlighting the importance of OMM signaling to health and disease. Despite recent progress, much remains to be discovered concerning the mechanisms of OMM signaling. Nonetheless, enhancing beneficial OMM signaling events and inhibiting detrimental protein‐protein interactions on the mitochondrial surface may represent highly selective approaches to restore mitochondrial health and homeostasis and mitigate organelle dysfunction in conditions such as PD

    A rapid and sensitive high-throughput screening method to identify compounds targeting protein-nucleic acids interactions

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    DNA-binding and RNA-binding proteins are usually considered ‘undruggable’ partly due to the lack of an efficient method to identify inhibitors from existing small molecule repositories. Here we report a rapid and sensitive high-throughput screening approach to identify compounds targeting protein– nucleic acids interactions based on protein–DNA or protein–RNA interaction enzyme-linked immunosorbent assays (PDI-ELISA or PRI-ELISA). We validated the PDI-ELISA method using the mammalian highmobility- group protein AT-hook 2 (HMGA2) as the protein of interest and netropsin as the inhibitor of HMGA2–DNA interactions. With this method we successfully identified several inhibitors and an activator for HMGA2–DNA interactions from a collection of 29 DNA-binding compounds. Guided by this screening excise, we showed that netropsin, the specific inhibitor of HMGA2–DNA interactions, strongly inhibited the differentiation of the mouse pre-adipocyte 3T3-L1 cells into adipocytes, most likely through a mechanism by which the inhibition is through preventing the binding of HMGA2 to the target DNA sequences. This method should be broadly applicable to identify compounds or proteins modulating many DNA-binding or RNA-binding proteins

    Fluorescently labeled circular DNA molecules for DNA topology and topoisomerases

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    DNA topology plays essential roles in several fundamental biological processes, such as DNA replication, recombination, and transcription. Typically agarose gel electrophoresis is employed to study DNA topology. Since gel electrophoresis is time-consuming and labor intensive, it is desirable to develop other methods, such as fluorescence-based methods, for such studies. In this paper we report the synthesis of a type of unique fluorescence-labeled DNA molecules that can be used to study DNA topology and topoisomerases by fluorescence resonance energy transfer (FRET). Specifically, we inserted an 82 nt. synthetic DNA oligomer FL905 carrying a 42 nt. AT sequence with fluorescein and dabcyl labels into a gapped DNA molecule to generate relaxed and supercoiled pAB1_FL905. Since the fluorescence intensity of pAB1_FL905 is dependent on its supercoiling status, pAB1_FL905 is a powerful tool to study DNA topology and topoisomerases by FRET. pAB1_FL905 can also be developed into rapid and efficient high-throughput screening assays to identify inhibitors that target various DNA topoisomerases

    Kinetic Study of DNA Topoisomerases by Supercoiling-Dependent Fluorescence Quenching

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    DNA topoisomerases are essential enzymes for all living organisms and important targets for anticancer drugs and antibiotics. Although DNA topoisomerases have been studied extensively, steady-state kinetics has not been systematically investigated because of the lack of an appropriate assay. Previously, we demonstrated that newly synthesized, fluorescently labeled plasmids pAB1_FL905 and pAB1_FL924 can be used to study DNA topoisomerase-catalyzed reactions by fluorescence resonance energy transfer (FRET) or supercoiling-dependent fluorescence quenching (SDFQ). With the FRET or SDFQ method, we performed steady-state kinetic studies for six different DNA topoisomerases including two type IA enzymes ( and DNA topoisomerase I), two type IB enzymes (human and variola DNA topoisomerase I), and two type IIA enzymes ( DNA gyrase and human DNA topoisomerase IIα). Our results show that all DNA topoisomerases follow the classical Michaelis-Menten kinetics and have unique steady-state kinetic parameters, , , and . We found that for all topoisomerases are rather low and that such low values may stem from the tight binding of topoisomerases to DNA. Additionally, we confirmed that novobiocin is a competitive inhibitor for adenosine 5\u27-triphosphate binding to DNA gyrase, demonstrating the utility of our assay for studying topoisomerase inhibitors

    The Pan-STARRS Moving Object Processing System

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    We describe the Pan-STARRS Moving Object Processing System (MOPS), a modern software package that produces automatic asteroid discoveries and identifications from catalogs of transient detections from next-generation astronomical survey telescopes. MOPS achieves > 99.5% efficiency in producing orbits from a synthetic but realistic population of asteroids whose measurements were simulated for a Pan-STARRS4-class telescope. Additionally, using a non-physical grid population, we demonstrate that MOPS can detect populations of currently unknown objects such as interstellar asteroids. MOPS has been adapted successfully to the prototype Pan-STARRS1 telescope despite differences in expected false detection rates, fill-factor loss and relatively sparse observing cadence compared to a hypothetical Pan-STARRS4 telescope and survey. MOPS remains >99.5% efficient at detecting objects on a single night but drops to 80% efficiency at producing orbits for objects detected on multiple nights. This loss is primarily due to configurable MOPS processing limits that are not yet tuned for the Pan-STARRS1 mission. The core MOPS software package is the product of more than 15 person-years of software development and incorporates countless additional years of effort in third-party software to perform lower-level functions such as spatial searching or orbit determination. We describe the high-level design of MOPS and essential subcomponents, the suitability of MOPS for other survey programs, and suggest a road map for future MOPS development.Comment: 57 Pages, 26 Figures, 13 Table

    The HUPO-PSI standardized spectral library format

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    More and more proteomics datasets are becoming available in public repositories. The knowledge embedded in these datasets can be used to improve peptide identification workflows. Spectral library searching provides a straightforward method to boost identification rates using previously identified spectra. Alternatively, machine learning methods can learn from these spectra to accurately predict the behavior of peptides in a liquid chromatography-mass spectrometry system. At the basis of both approaches are spectral libraries: Unified collections of previously identified spectra. Organizations and projects such as the National Institute of Standards and Technology (NIST), the Global Proteome Machine, PeptideAtlas, PRIDE Archive and MassIVE have all compiled spectral libraries for a multitude of species and experimental setups. A large obstacle, however, is that each organization provides libraries in a different file format. At the software level the problem propagates (if not expands), as different software tools require different file formats. The solution is a standardized spectral library format that is sufficiently flexible to meet all users' demands, but that is also standardized enough to be usable across environments and software packages. This balance is achieved by setting up a standardized framework and a controlled vocabulary with metadata terms, and allow the format to be represented in different forms, such as plain text, JSON and HDF. So far, the required (and optional) meta data has been compiled and added to the PSI-MS ontology, and versions of the text and JSON representations have been drafted. The tabular and HDF representations of the format are in development, as well as converters and validators in various programming languages

    The impact of substance use on brain structure in people at high risk of developing schizophrenia

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    Ventricular enlargement and reduced prefrontal volume are consistent findings in schizophrenia. Both are present in first episode subjects and may be detectable before the onset of clinical disorder. Substance misuse is more common in people with schizophrenia and is associated with similar brain abnormalities. We employ a prospective cohort study with nested case control comparison design to investigate the association between substance misuse, brain abnormality, and subsequent schizophrenia. Substance misuse history, imaging data, and clinical information were collected on 147 subjects at high risk of schizophrenia and 36 controls. Regions exhibiting a significant relationship between level of use of alcohol, cannabis or tobacco, and structure volume were identified. Multivariate regression then elucidated the relationship between level of substance use and structure volumes while accounting for correlations between these variables and correcting for potential confounders. Finally, we established whether substance misuse was associated with later risk of schizophrenia. Increased ventricular volume was associated with alcohol and cannabis use in a dose-dependent manner. Alcohol consumption was associated with reduced frontal lobe volume. Multiple regression analyses found both alcohol and cannabis were significant predictors of these abnormalities when simultaneously entered into the statistical model. Alcohol and cannabis misuse were associated with an increased subsequent risk of schizophrenia. We provide prospective evidence that use of cannabis or alcohol by people at high genetic risk of schizophrenia is associated with brain abnormalities and later risk of psychosis. A family history of schizophrenia may render the brain particularly sensitive to the risk-modifying effects of these substances

    Factors deterring schools from mixed attainment teaching practice

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    Mixed-attainment teaching has strong support from research and yet English schools are far more likely to teach students in ‘ability’ groups. Although research has considered some of the specific benefits of mixed-attainment grouping, there has been little attention to the reasons schools avoid it. This article explores data from the pilot and recruitment phases of a large-scale study into grouping practices and seeks to identify reasons for the low rate of mixed attainment grouping in English secondary schools. We report on our struggle to recruit schools, and explore the different explanations provided by teachers as to why mixed attainment practice is seen as problematic. The difficulties are characterised as a vicious circle where schools are deterred by a paucity of exemplars and resources and the educational climate is characterised as fearful, risk-averse and time-poor. Suggestions are made as to strategies to support schools in taking up mixed attainment practices

    Altered Risk-Based Decision Making following Adolescent Alcohol Use Results from an Imbalance in Reinforcement Learning in Rats

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    Alcohol use during adolescence has profound and enduring consequences on decision-making under risk. However, the fundamental psychological processes underlying these changes are unknown. Here, we show that alcohol use produces over-fast learning for better-than-expected, but not worse-than-expected, outcomes without altering subjective reward valuation. We constructed a simple reinforcement learning model to simulate altered decision making using behavioral parameters extracted from rats with a history of adolescent alcohol use. Remarkably, the learning imbalance alone was sufficient to simulate the divergence in choice behavior observed between these groups of animals. These findings identify a selective alteration in reinforcement learning following adolescent alcohol use that can account for a robust change in risk-based decision making persisting into later life

    The state of the Martian climate

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    60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes
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