17 research outputs found

    Genome-scale resources for Thermoanaerobacterium saccharolyticum

    Get PDF
    Background Thermoanaerobacterium saccharolyticum is a hemicellulose-degrading thermophilic anaerobe that was previously engineered to produce ethanol at high yield. A major project was undertaken to develop this organism into an industrial biocatalyst, but the lack of genome information and resources were recognized early on as a key limitation. Results Here we present a set of genome-scale resources to enable the systems level investigation and development of this potentially important industrial organism. Resources include a complete genome sequence for strain JW/SL-YS485, a genome-scale reconstruction of metabolism, tiled microarray data showing transcription units, mRNA expression data from 71 different growth conditions or timepoints and GC/MS-based metabolite analysis data from 42 different conditions or timepoints. Growth conditions include hemicellulose hydrolysate, the inhibitors HMF, furfural, diamide, and ethanol, as well as high levels of cellulose, xylose, cellobiose or maltodextrin. The genome consists of a 2.7 Mbp chromosome and a 110 Kbp megaplasmid. An active prophage was also detected, and the expression levels of CRISPR genes were observed to increase in association with those of the phage. Hemicellulose hydrolysate elicited a response of carbohydrate transport and catabolism genes, as well as poorly characterized genes suggesting a redox challenge. In some conditions, a time series of combined transcription and metabolite measurements were made to allow careful study of microbial physiology under process conditions. As a demonstration of the potential utility of the metabolic reconstruction, the OptKnock algorithm was used to predict a set of gene knockouts that maximize growth-coupled ethanol production. The predictions validated intuitive strain designs and matched previous experimental results. Conclusion These data will be a useful asset for efforts to develop T. saccharolyticum for efficient industrial production of biofuels. The resources presented herein may also be useful on a comparative basis for development of other lignocellulose degrading microbes, such as Clostridium thermocellum. Electronic supplementary material The online version of this article (doi:10.1186/s12918-015-0159-x) contains supplementary material, which is available to authorized users

    The genetic architecture of the human cerebral cortex

    Get PDF
    The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

    New Methodology for Quantifying Polycyclic Aromatic Hydrocarbons (PAHs) Using High-Resolution Aerosol Mass Spectrometry

    No full text
    <div><p>This article presents a new methodology to potentially quantify polycyclic aromatic hydrocarbon (PAH) isomers using high-resolution time of flight aerosol mass spectrometer (HR-AMS). The fragmentation of PAHs within the HR-AMS is such that significant signal remains at the molecular ion. After quantifying the molecular ion signal and taking into account potential interferences, the amount of the parent PAH in the aerosol may be inferred once its fragmentation pattern is also known. The potential of this approach was evaluated using mixed gasoline and diesel engine exhaust sampled under varying conditions. This dataset led to the identification and quantification within the aerosol mass spectra of the molecular ions associated with 53 PAH isomers, including both unsubstituted and functionalized species. An evaluation of anticipated interferences shows that interferences from larger molecular weight PAHs (i.e., PAH/PAH interferences) could be constrained based on the fragmentation behavior of PAHs from existing HR-AMS laboratory spectra. Other signal interferences for this data set are typically less than 5% of the total signal or, for <sup>13</sup>C isotopic interferents, are well constrained by measurements of the dominant isotope. The experimental data reveal that the fractional PAH molecular ion signal remained stable despite dramatic temporal variability of the total particulate organic signal. The fractional contributions of the molecular ions for grouped PAH species and even individual compounds were remarkably consistent across experiments. The distribution of PAHs showed no apparent dependence on engine load or exhaust type. Full application of this approach will require a greater number of standard HR-AMS spectra for PAHs, so that the relationship between compounds and their molecular ions may be understood more precisely.</p><p>Copyright 2015 American Association for Aerosol Research</p></div

    Genome-scale resources for Thermoanaerobacterium saccharolyticum

    No full text
    Abstract Background Thermoanaerobacterium saccharolyticum is a hemicellulose-degrading thermophilic anaerobe that was previously engineered to produce ethanol at high yield. A major project was undertaken to develop this organism into an industrial biocatalyst, but the lack of genome information and resources were recognized early on as a key limitation. Results Here we present a set of genome-scale resources to enable the systems level investigation and development of this potentially important industrial organism. Resources include a complete genome sequence for strain JW/SL-YS485, a genome-scale reconstruction of metabolism, tiled microarray data showing transcription units, mRNA expression data from 71 different growth conditions or timepoints and GC/MS-based metabolite analysis data from 42 different conditions or timepoints. Growth conditions include hemicellulose hydrolysate, the inhibitors HMF, furfural, diamide, and ethanol, as well as high levels of cellulose, xylose, cellobiose or maltodextrin. The genome consists of a 2.7 Mbp chromosome and a 110 Kbp megaplasmid. An active prophage was also detected, and the expression levels of CRISPR genes were observed to increase in association with those of the phage. Hemicellulose hydrolysate elicited a response of carbohydrate transport and catabolism genes, as well as poorly characterized genes suggesting a redox challenge. In some conditions, a time series of combined transcription and metabolite measurements were made to allow careful study of microbial physiology under process conditions. As a demonstration of the potential utility of the metabolic reconstruction, the OptKnock algorithm was used to predict a set of gene knockouts that maximize growth-coupled ethanol production. The predictions validated intuitive strain designs and matched previous experimental results. Conclusion These data will be a useful asset for efforts to develop T. saccharolyticum for efficient industrial production of biofuels. The resources presented herein may also be useful on a comparative basis for development of other lignocellulose degrading microbes, such as Clostridium thermocellum
    corecore