Keck Cosmic Web Imager (KCWI) spectra of globular clusters and ultracompact dwarfs in the halo of M87

Using the Keck Cosmic Web Imager, we obtain spectra of several globular clusters (GCs), ultracompact dwarfs (UCDs), and the inner halo starlight of M87, at a similar projected galactocentric radius of ∼5 kpc. This enables us, for the first time, to apply the same stellar population analysis to the GCs, UCDs, and starlight consistently to derive ages, metallicities, and alpha-element abundances in M87. We find evidence for a dual stellar population in the M87 halo light, i.e. an ∼80 per cent component by mass that is old and metal-rich and a ∼20 per cent component that is old but metal-poor. Two red GCs share similar stellar populations to the halo light suggesting they may have formed contemporaneously with the dominant halo component. Three UCDs, and one blue GC, have similar stellar populations, with younger mean ages, lower metallicities, and near solar alpha-element abundances. Combined with literature data, our findings are consistent with the scenario that UCDs are the remnant nucleus of a stripped galaxy. We further investigate the discrepancy in the literature for M87\u27s kinematics at large radii, favouring a declining velocity dispersion profile. This work has highlighted the need for more self-consistent studies of galaxy haloes

Comparative genomic and transcriptomic analysis revealed genetic characteristics related to solvent formation and xylose utilization in Clostridium acetobutylicum EA 2018

<p>Abstract</p> <p>Background</p> <p><it>Clostridium acetobutylicum</it>, a gram-positive and spore-forming anaerobe, is a major strain for the fermentative production of acetone, butanol and ethanol. But a previously isolated hyper-butanol producing strain <it>C. acetobutylicum </it>EA 2018 does not produce spores and has greater capability of solvent production, especially for butanol, than the type strain <it>C. acetobutylicum </it>ATCC 824.</p> <p>Results</p> <p>Complete genome of <it>C. acetobutylicum </it>EA 2018 was sequenced using Roche 454 pyrosequencing. Genomic comparison with ATCC 824 identified many variations which may contribute to the hyper-butanol producing characteristics in the EA 2018 strain, including a total of 46 deletion sites and 26 insertion sites. In addition, transcriptomic profiling of gene expression in EA 2018 relative to that of ATCC824 revealed expression-level changes of several key genes related to solvent formation. For example, <it>spo0A </it>and <it>adhEII </it>have higher expression level, and most of the acid formation related genes have lower expression level in EA 2018. Interestingly, the results also showed that the variation in CEA_G2622 (CAC2613 in ATCC 824), a putative transcriptional regulator involved in xylose utilization, might accelerate utilization of substrate xylose.</p> <p>Conclusions</p> <p>Comparative analysis of <it>C. acetobutylicum </it>hyper-butanol producing strain EA 2018 and type strain ATCC 824 at both genomic and transcriptomic levels, for the first time, provides molecular-level understanding of non-sporulation, higher solvent production and enhanced xylose utilization in the mutant EA 2018. The information could be valuable for further genetic modification of <it>C. acetobutylicum </it>for more effective butanol production.</p

Redox-switch regulatory mechanism of thiolase from Clostridium acetobutylicum

Thiolase is the first enzyme catalysing the condensation of two acetyl-coenzyme A (CoA) molecules to form acetoacetyl-CoA in a dedicated pathway towards the biosynthesis of n-butanol, an important solvent and biofuel. Here we elucidate the crystal structure of Clostridium acetobutylicum thiolase (CaTHL) in its reduced/oxidized states. CaTHL, unlike those from other aerobic bacteria such as Escherichia coli and Zoogloea ramegera, is regulated by the redox-switch modulation through reversible disulfide bond formation between two catalytic cysteine residues, Cys88 and Cys378. When CaTHL is overexpressed in wild-type C. acetobutylicum, butanol production is reduced due to the disturbance of acidogenic to solventogenic shift. The CaTHLV77Q/N153Y/A286K mutant, which is not able to form disulfide bonds, exhibits higher activity than wild-type CaTHL, and enhances butanol production upon overexpression. On the basis of these results, we suggest that CaTHL functions as a key enzyme in the regulation of the main metabolism of C. acetobutylicum through a redox-switch regulatory mechanism.close0

HadISD: A quality controlled global synoptic report database for selected variables at long-term stations from 1973-2011

Abstract. This paper describes the creation of HadISD; an automatically quality-controlled synoptic resolution dataset of temperature, dewpoint temperature, sea-level pressure, wind speed, wind direction and cloud cover from global weather stations for 1973-2011. The full dataset consists of over 6,000 stations, with 3427 long-term stations deemed to have sufficient sampling and quality for climate applications requiring sub-daily resolution. As with other surface datasets, coverage is heavily skewed towards Northern Hemisphere mid-latitudes. The dataset is constructed from a large pre-existing ASCII flatfile data-bank that represents over a decade of substantial effort at data retrieval, reformatting and provision. These raw data have had varying levels of quality control applied to them by individual data providers. The work proceeded in several steps: merging stations with multiple reporting identifiers; reformatting to netcdf; quality control; and then filtering to form a final dataset. Particular attention has been paid to maintaining true extreme values where possible within an automated, objective process. Detailed validation has been performed on a subset of global stations and also on UK data using known extreme events to help finalise the QC tests. Further validation was performed on a selection of extreme events world-wide (Hurricane Katrina in 2005, the cold snap in Alaska in 1989 and heat waves in SE Australia in 2009). Some very initial analyses are performed to illustrate some of the types of problems to which the final data could be applied. Although the filtering has removed the poorest station records, no attempt has been made to homogenise the data thus far, due to the complexity of retaining the true distribution of high-resolution data when applying adjustments. Hence non-climatic, time-varying errors may still exist in many of the individual station records and care is needed in inferring long-term trends from these data. This dataset will allow the study of high frequency variaCorrespondence to: [email protected] tions of temperature, pressure and humidity on a global basis over the last four decades. Both individual extremes and the overall population of extreme events could be investigated in detail to allow for comparison with past and projected climate. A version-control system has been constructed for this dataset to allow for the clear documentation of any updates and corrections in the future

Reassessing changes in diurnal temperature range: Intercomparison and evaluation of existing global data set estimates

Changes in diurnal temperature range (DTR) over global land areas are compared from a broad range of independent data sets. All data sets agree that global-mean DTR has decreased significantly since 1950, with most of that decrease occurring over 1960–1980. The since-1979 trends are not significant, with inter-data set disagreement even over the sign of global changes. Inter-data set spread becomes greater regionally and in particular at the grid box level. Despite this, there is general agreement that DTR decreased in North America, Europe, and Australia since 1951, with this decrease being partially reversed over Australia and Europe since the early 1980s. There is substantive disagreement between data sets prior to the middle of the twentieth century, particularly over Europe, which precludes making any meaningful conclusions about DTR changes prior to 1950, either globally or regionally. Several variants that undertake a broad range of approaches to postprocessing steps of gridding and interpolation were analyzed for two of the data sets. These choices have a substantial influence in data sparse regions or periods. The potential of further insights is therefore inextricably linked with the efficacy of data rescue and digitization for maximum and minimum temperature series prior to 1950 everywhere and in data sparse regions throughout the period of record. Over North America, station selection and homogeneity assessment is the primary determinant. Over Europe, where the basic station data are similar, the postprocessing choices are dominant. We assess that globally averaged DTR has decreased since the middle twentieth century but that this decrease has not been linear

NIBBS-Search for Fast and Accurate Prediction of Phenotype-Biased Metabolic Systems

Understanding of genotype-phenotype associations is important not only for furthering our knowledge on internal cellular processes, but also essential for providing the foundation necessary for genetic engineering of microorganisms for industrial use (e.g., production of bioenergy or biofuels). However, genotype-phenotype associations alone do not provide enough information to alter an organism's genome to either suppress or exhibit a phenotype. It is important to look at the phenotype-related genes in the context of the genome-scale network to understand how the genes interact with other genes in the organism. Identification of metabolic subsystems involved in the expression of the phenotype is one way of placing the phenotype-related genes in the context of the entire network. A metabolic system refers to a metabolic network subgraph; nodes are compounds and edges labels are the enzymes that catalyze the reaction. The metabolic subsystem could be part of a single metabolic pathway or span parts of multiple pathways. Arguably, comparative genome-scale metabolic network analysis is a promising strategy to identify these phenotype-related metabolic subsystems. Network Instance-Based Biased Subgraph Search (NIBBS) is a graph-theoretic method for genome-scale metabolic network comparative analysis that can identify metabolic systems that are statistically biased toward phenotype-expressing organismal networks. We set up experiments with target phenotypes like hydrogen production, TCA expression, and acid-tolerance. We show via extensive literature search that some of the resulting metabolic subsystems are indeed phenotype-related and formulate hypotheses for other systems in terms of their role in phenotype expression. NIBBS is also orders of magnitude faster than MULE, one of the most efficient maximal frequent subgraph mining algorithms that could be adjusted for this problem. Also, the set of phenotype-biased metabolic systems output by NIBBS comes very close to the set of phenotype-biased subgraphs output by an exact maximally-biased subgraph enumeration algorithm ( MBS-Enum ). The code (NIBBS and the module to visualize the identified subsystems) is available at http://freescience.org/cs/NIBBS

Validation of the Aura Microwave Limb Sounder Temperature and Geopotential Height Measurements

Global satellite observations of temperature and geopotential height (GPH) from the Microwave Limb Sounder (MLS) on the EOS Aura spacecraft are discussed. The precision, resolution, and accuracy of the data produced by the MLS version 2.2 processing algorithms are quantified, and recommendations for data screening are made. Temperature precision is 1 K or better from 316 hPa to 3.16 hPa, degrading to ∼3 K at 0.001 hPa. The vertical resolution is 3 km at 31.6 hPa, degrading to 6 km at 316 hPa and to ∼13 km at 0.001 hPa. Comparisons with analyses (Goddard Earth Observing System version 5.0.1 (GEOS-5), European Centre for Medium-range Weather Forecasts (ECMWF), Met Office (MetO)) and other observations (CHAllenging Minisatellite Payload (CHAMP), Atmospheric Infrared Sounder/Advanced Microwave Sounder Unit (AIRS/AMSU), Sounding of the Atmosphere using Broadband Radiometry (SABER), Halogen Occultation Experiment (HALOE), Atmospheric Chemistry Experiment (ACE), radiosondes) indicate that MLS temperature has persistent, pressure-dependent biases which are between −2.5 K and +1 K between 316 hPa and 10 hPa. The 100-hPa MLS v2.2 GPH surface has a bias of ∼150 m relative to the GEOS-5 values. These biases are compared to modeled systematic uncertainties. GPH biases relative to correlative measurements generally increase with height owing to an overall cold bias in MLS temperature relative to correlative temperature measurements in the upper stratosphere and mesosphere

Frequency of extreme Sahelian storms tripled since 1982 in satellite observations

The hydrological cycle is expected to intensify under global warming, with studies reporting more frequent extreme rain events in many regions of the world, and predicting increases in future flood frequency. Such early, predominantly mid-latitude observations are essential because of shortcomings within climate models in their depiction of convective rainfall. A globally important group of intense storms—mesoscale convective systems (MCSs)—poses a particular challenge, because they organize dynamically on spatial scales that cannot be resolved by conventional climate models. Here, we use 35 years of satellite observations from the West African Sahel to reveal a persistent increase in the frequency of the most intense MCSs. Sahelian storms are some of the most powerful on the planet, and rain gauges in this region have recorded a rise in ‘extreme’ daily rainfall totals. We find that intense MCS frequency is only weakly related to the multidecadal recovery of Sahel annual rainfall, but is highly correlated with global land temperatures. Analysis of trends across Africa reveals that MCS intensification is limited to a narrow band south of the Sahara desert. During this period, wet-season Sahelian temperatures have not risen, ruling out the possibility that rainfall has intensified in response to locally warmer conditions. On the other hand, the meridional temperature gradient spanning the Sahel has increased in recent decades, consistent with anthropogenic forcing driving enhanced Saharan warming. We argue that Saharan warming intensifies convection within Sahelian MCSs through increased wind shear and changes to the Saharan air layer. The meridional gradient is projected to strengthen throughout the twenty-first century, suggesting that the Sahel will experience particularly marked increases in extreme rain. The remarkably rapid intensification of Sahelian MCSs since the 1980s sheds new light on the response of organized tropical convection to global warming, and challenges conventional projections made by general circulation models

Assessing bias and uncertainty in the HadAT-adjusted radiosonde climate record

Uncertainties in observed records of atmospheric temperature aloft remain poorly quantified. This has resulted in considerable controversy regarding signals of climate change over recent decades from tem-perature records of radiosondes and satellites. This work revisits the problems associated with the removal of inhomogeneities from the historical radiosonde temperature records, and provides a method for quan-tifying uncertainty in an adjusted radiosonde climate record due to the subjective choices made during the data homogenization. This paper presents an automated homogenization method designed to replicate the decisions made by manual judgment in the generation of an earlier radiosonde dataset [i.e., the Hadley Centre radiosonde temperature dataset (HadAT)]. A number of validation experiments have been conducted to test the system performance and impact on linear trends. Using climate model data to simulate biased radiosonde data, the authors show that limitations in the homogenization method are sufficiently large to explain much of the tropical trend discrepancy between HadAT and estimates from satellite platforms and climate models. This situation arises from the combi-nation of systematic (unknown magnitude) and random uncertainties (of order 0.05 K decade1) in the radiosonde data. Previous assessment of trends and uncertainty in HadAT is likely to have underestimated the systematic bias in tropical mean temperature trends. This objective assessment of radiosonde homog-enization supports the conclusions of the synthesis report of the U.S. Climate Change Science Program (CCSP), and associated research, regarding potential bias in tropospheric temperature records from radio-sondes. 1

A new integrated and homogenized global monthly land surface air temperature dataset for the period since 1900

A new dataset of integrated and homogenized monthly surface air temperature over global land for the period since 1900 [China Meteorological Administration global Land Surface Air Temperature (CMA-LSAT)] is developed. In total, 14 sources have been collected and integrated into the newly developed dataset, including three global (CRUTEM4, GHCN, and BEST), three regional and eight national sources. Duplicate stations are identified, and those with the higher priority are chosen or spliced. Then, a consistency test and a climate outlier test are conducted to ensure that each station series is quality controlled. Next, two steps are adopted to assure the homogeneity of the station series: (1) homogenized station series in existing national datasets (by National Meteorological Services) are directly integrated into the dataset without any changes (50% of all stations), and (2) the inhomogeneities are detected and adjusted for in the remaining data series using a penalized maximal t test (50% of all stations). Based on the dataset, we re-assess the temperature changes in global and regional areas compared with GHCN-V3 and CRUTEM4, as well as the temperature changes during the three periods of 1900–2014, 1979–2014 and 1998–2014. The best estimates of warming trends and there 95% confidence ranges for 1900–2014 are approximately 0.102 ± 0.006 °C/decade for the whole year, and 0.104 ± 0.009, 0.112 ± 0.007, 0.090 ± 0.006, and 0.092 ± 0.007 °C/decade for the DJF (December, January, February), MAM, JJA, and SON seasons, respectively. MAM saw the most significant warming trend in both 1900–2014 and 1979–2014. For an even shorter and more recent period (1998–2014), MAM, JJA and SON show similar warming trends, while DJF shows opposite trends. The results show that the ability of CMA-LAST for describing the global temperature changes is similar with other existing products, while there are some differences when describing regional temperature changes