41 research outputs found

    Role of ppGpp in regulating global gene expression in Escherichia coli.

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    Bacteria grow when nutrient availability supports basic biochemical requirements and remain in stationary phase when basic needs go unmet. This deceptively simple phenomenon requires the orchestrated expression of thousands of genes. Free-living bacteria use a nucleotide second messenger, ppGpp, as a physiological signal and effector to appropriately coordinate global gene expression according to the nutritional quality of the environment. Over the last four decades, expression of many individual genes has been tied to the absence or presence of ppGpp, yet the full scope of gene expression mediated by ppGpp remained undefined. This dissertation defines the role of ppGpp in regulating global gene expression in a model bacterium, Escherichia coli

    Role for dithiolopyrrolones in disrupting bacterial metal homeostasis

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    Antibiotic resistance is a rising health threat worldwide, against which novel strategies are urgently needed. We have taken a systems approach to examine a potent and underexplored class of broad-spectrum antibiotics, the dithiolopyrrolones (DTPs). Our results indicate that DTPs disrupt cellular processes by high-affinity chelation of essential metal ions and inhibition of a subset of metalloenzymes. This mode of action is unique amongst antibiotics and may be further explored for treatment of multidrug-resistant infections. Our study also highlights chemical genomics as a powerful approach for the identification of antimicrobial mechanisms of action

    Comparing sensitivity to change using the 6-item versus the 17-item Hamilton Depression Rating Scale in the GUIDED randomized controlled trial

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    BACKGROUND: Previous research suggests that the 17-item Hamilton Depression Rating Scale (HAM-D17) is less sensitive in detecting differences between active treatment and placebo for major depressive disorder (MDD) than is the HAM-D6 scale, which focuses on six core depression symptoms. Whether HAM-D6 shows greater sensitivity when comparing two active MDD treatment arms is unknown. METHODS: This post hoc analysis used data from the intent-to-treat (ITT) cohort (N = 1541) of the Genomics Used to Improve DEpression Decisions (GUIDED) trial, a rater- and patient-blinded randomized controlled trial. GUIDED compared combinatorial pharmacogenomics-guided care with treatment as usual (TAU) in patients with MDD. Percent of symptom improvement, response rate and remission rate from baseline to week 8 were evaluated using both scales. Analyses were performed for the full cohort and for the subset of patients who at baseline were taking medications predicted by the test to have moderate or significant gene-drug interactions. A Mokken scale analysis was conducted to compare the homogeneity of HAM-D17 with that of HAM-D6. RESULTS: At week 8, the guided-care arm demonstrated statistically significant benefit over TAU when the HAM-D6 (∆ = 4.4%, p = 0.023) was used as the continuous measure of symptom improvement, but not when using the HAM-D17 (∆ = 3.2%, p = 0.069). Response rates increased significantly for guided-care compared with TAU when evaluated using both HAM-D6 (∆ = 7.0%, p = 0.004) and HAM-D17 (∆ = 6.3%, p = 0.007). Remission rates also were significantly greater for guided-care versus TAU using both measures (HAM-D6 ∆ = 4.6%, p = 0.031; HAM-D17 ∆ = 5.5%, p = 0.005). Patients in the guided-care arm who at baseline were taking medications predicted to have gene-drug interactions showed further increased benefit over TAU at week 8 for symptom improvement (∆ = 7.3%, p = 0.004) response (∆ = 10.0%, p = 0.001) and remission (∆ = 7.9%, p = 0.005) using HAM-D6. All outcomes showed continued improvement through week 24. Mokken scale analysis demonstrated the homogeneity and unidimensionality of HAM-D6, but not of HAM-D17, across treatment arms. CONCLUSIONS: The HAM-D6 scale identified a statistically significant difference in symptom improvement between combinatorial pharmacogenomics-guided care and TAU, whereas the HAM-D17 did not. The demonstrated utility of pharmacogenomics-guided treatment over TAU as detected by the HAM-D6 highlights its value for future biomarker-guided trials comparing active treatment arms. TRIAL REGISTRATION: Clinicaltrials.gov: NCT02109939. Registered 10 April 2014

    The 2016 UK Space Agency Mars Utah Rover Field Investigation (MURFI)

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    The 2016 Mars Utah Rover Field Investigation (MURFI) was a Mars rover field trial run by the UK Space Agency in association with the Canadian Space Agency's 2015/2016 Mars Sample Return Analogue Deployment mission. MURFI had over 50 participants from 15 different institutions around the UK and abroad. The objectives of MURFI were to develop experience and leadership within the UK in running future rover field trials; to prepare the UK planetary community for involvement in the European Space Agency/Roscosmos ExoMars 2020 rover mission; and to assess how ExoMars operations may differ from previous rover missions. Hence, the wider MURFI trial included a ten-day (or ten-‘sol’) ExoMars rover-like simulation. This comprised an operations team and control centre in the UK, and a rover platform in Utah, equipped with instruments to emulate the ExoMars rovers remote sensing and analytical suite. The operations team operated in ‘blind mode’, where the only available data came from the rover instruments, and daily tactical planning was performed under strict time constraints to simulate real communications windows. The designated science goal of the MURFI ExoMars rover-like simulation was to locate in-situ bedrock, at a site suitable for sub-surface core-sampling, in order to detect signs of ancient life. Prior to “landing”, the only information available to the operations team were Mars-equivalent satellite remote sensing data, which were used for both geologic and hazard (e.g., slopes, loose soil) characterisation of the area. During each sol of the mission, the operations team sent driving instructions and imaging/analysis targeting commands, which were then enacted by the field team and rover-controllers in Utah. During the ten-sol mission, the rover drove over 100 m and obtained hundreds of images and supporting observations, allowing the operations team to build up geologic hypotheses for the local area and select possible drilling locations. On sol 9, the team obtained a subsurface core sample that was then analyzed by the Raman spectrometer. Following the conclusion of the ExoMars-like component of MURFI, the operations and field team came together to evaluate the successes and failures of the mission, and discuss lessons learnt for ExoMars rover and future field trials. Key outcomes relevant to ExoMars rover included a key recognition of the importance of field trials for (i) understanding how to operate the ExoMars rover instruments as a suite, (ii) building an operations planning team that can work well together under strict time-limited pressure, (iii) developing new processes and workflows relevant to the ExoMars rover, (iv) understanding the limits and benefits of satellite mapping and (v) practicing efficient geological interpretation of outcrops and landscapes from rover-based data, by comparing the outcomes of the simulated mission with post-trial, in-situ field observations. In addition, MURFI was perceived by all who participated as a vital learning experience, especially for early and mid-career members of the team, and also demonstrated the UK capability of implementing a large rover field trial. The lessons learnt from MURFI are therefore relevant both to ExoMars rover, and to future rover field trials

    Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking

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    The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry techniques are well-suited to high-throughput characterization of natural products, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social molecular networking (GNPS, http://gnps.ucsd.edu), an open-access knowledge base for community wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of ‘living data’ through continuous reanalysis of deposited data

    A Taxonomically-informed Mass Spectrometry Search Tool for Microbial Metabolomics Data

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    MicrobeMASST, a taxonomically-informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbial-derived metabolites and relative producers, without a priori knowledge, will vastly enhance the understanding of microorganisms’ role in ecology and human health
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