174 research outputs found

    Swelling of Transported Smoke from Savanna Fires over the Southeast Atlantic Ocean

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    We use the recently released Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Version 4.1 (V4) lidar data to study the smoke plumes transported from Southern African biomass burning areas. Significant improvements in the CALIPSO V4 Level 1 calibration and V4 Level 2 algorithms lead to a better representation of their optical properties, with the aerosol subtype improvements being particularly relevant to smoke over this area. For the first time, we show evidence of smoke particles increasing in size, evidenced in their particulate color ratios, as they are transported over the South Atlantic Ocean from the source regions over Southern Africa. We hypothesize that this is due to hygroscopic swelling of the smoke particles and is reflected in the higher relative humidity in the middle troposphere for profiles with smoke. This finding may have implications for radiative forcing estimates over this area and is also relevant to the ORACLES field mission

    Swelling of Transported Smoke from Savanna fires over the Southeast Atlantic Ocean

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    We use the recently released Version 4 (V4) lidar data products from CALIPSO to study the smoke plumes transported from Southern African biomass burning areas. The significant improvements in CALIPSO V4 Level 1 calibration and the V4 Level 2 aerosol subtyping algorithms, the latter being particularly relevant to biomass burning smoke over this area, lead to a better representation of their optical properties. For the first time, we show evidence of smoke particles increasing in size, evidenced in their particulate color ratios, as they are transported over the South Atlantic Ocean from the source regions over Southern Africa. This is likely due to hygroscopic swelling of the smoke particles and is reflected in the higher relative humidity in the middle troposphere for profiles with smoke. This finding may have implications for radiative forcing estimates over this area and is relevant to the ORACLES field mission that is currently underway

    Application of high-dimensional fuzzy <i>k</i>-means cluster analysis to CALIOP/CALIPSO version 4.1 cloud–aerosol discrimination

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    This study applies fuzzy k-means (FKM) cluster analyses to a subset of the parameters reported in the CALIPSO lidar level 2 data products in order to classify the layers detected as either clouds or aerosols. The results obtained are used to assess the reliability of the cloud–aerosol discrimination (CAD) scores reported in the version 4.1 release of the CALIPSO data products. FKM is an unsupervised learning algorithm, whereas the CALIPSO operational CAD algorithm (COCA) takes a highly supervised approach. Despite these substantial computational and architectural differences, our statistical analyses show that the FKM classifications agree with the COCA classifications for more than 94&thinsp;% of the cases in the troposphere. This high degree of similarity is achieved because the lidar-measured signatures of the majority of the clouds and the aerosols are naturally distinct, and hence objective methods can independently and effectively separate the two classes in most cases. Classification differences most often occur in complex scenes (e.g., evaporating water cloud filaments embedded in dense aerosol) or when observing diffuse features that occur only intermittently (e.g., volcanic ash in the tropical tropopause layer). The two methods examined in this study establish overall classification correctness boundaries due to their differing algorithm uncertainties. In addition to comparing the outputs from the two algorithms, analysis of sampling, data training, performance measurements, fuzzy linear discriminants, defuzzification, error propagation, and key parameters in feature type discrimination with the FKM method are further discussed in order to better understand the utility and limits of the application of clustering algorithms to space lidar measurements. In general, we find that both FKM and COCA classification uncertainties are only minimally affected by noise in the CALIPSO measurements, though both algorithms can be challenged by especially complex scenes containing mixtures of discrete layer types. Our analysis results show that attenuated backscatter and color ratio are the driving factors that separate water clouds from aerosols; backscatter intensity, depolarization, and mid-layer altitude are most useful in discriminating between aerosols and ice clouds; and the joint distribution of backscatter intensity and depolarization ratio is critically important for distinguishing ice clouds from water clouds.</p

    Metagenomic and Metatranscriptomic Analysis of Microbial Community Structure and Gene Expression of Activated Sludge

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    The present study applied both metagenomic and metatranscriptomic approaches to characterize microbial structure and gene expression of an activated sludge community from a municipal wastewater treatment plant in Hong Kong. DNA and cDNA were sequenced by Illumina Hi-seq2000 at a depth of 2.4 Gbp. Taxonomic analysis by MG-RAST showed bacteria were dominant in both DNA and cDNA datasets. The taxonomic profile obtained by BLAST against SILVA SSUref database and annotation by MEGAN showed that activated sludge was dominated by Proteobacteria, Actinobacteria, Bacteroidetes, Firmicutes and Verrucomicrobia phyla in both DNA and cDNA datasets. Global gene expression annotation based on KEGG metabolism pathway displayed slight disagreement between the DNA and cDNA datasets. Further gene expression annotation focusing on nitrogen removal revealed that denitrification-related genes sequences dominated in both DNA and cDNA datasets, while nitrifying genes were also expressed in relative high levels. Specially, ammonia monooxygenase and hydroxylamine oxidase demonstrated the high cDNA/DNA ratios in the present study, indicating strong nitrification activity. Enzyme subunits gene sequences annotation discovered that subunits of ammonia monooxygenase (amoA, amoB, amoC) and hydroxylamine oxygenase had higher expression levels compared with subunits of the other enzymes genes. Taxonomic profiles of selected enzymes (ammonia monooxygenase and hydroxylamine oxygenase) showed that ammonia-oxidizing bacteria present mainly belonged to Nitrosomonas and Nitrosospira species and no ammonia-oxidizing Archaea sequences were detected in both DNA and cDNA datasets

    A Protein-Protein Interaction Map of the Trypanosoma brucei Paraflagellar Rod

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    We have conducted a protein interaction study of components within a specific sub-compartment of a eukaryotic flagellum. The trypanosome flagellum contains a para-crystalline extra-axonemal structure termed the paraflagellar rod (PFR) with around forty identified components. We have used a Gateway cloning approach coupled with yeast two-hybrid, RNAi and 2D DiGE to define a protein-protein interaction network taking place in this structure. We define two clusters of interactions; the first being characterised by two proteins with a shared domain which is not sufficient for maintaining the interaction. The other cohort is populated by eight proteins, a number of which possess a PFR domain and sub-populations of this network exhibit dependency relationships. Finally, we provide clues as to the structural organisation of the PFR at the molecular level. This multi-strand approach shows that protein interactome data can be generated for insoluble protein complexes

    Denitrification likely catalyzed by endobionts in an allogromiid foraminifer

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    Author Posting. © The Author(s), 2011. This is the author's version of the work. It is posted here by permission of Nature Publishing Group for personal use, not for redistribution. The definitive version was published in The ISME Journal 6 (2012): 951–960, doi:10.1038/ismej.2011.171.Nitrogen can be a limiting macronutrient for carbon uptake by the marine biosphere. The process of denitrification (conversion of nitrate to gaseous compounds, including N2) removes bioavailable nitrogen, particularly in marine sediments, making it a key factor in the marine nitrogen budget. Benthic foraminifera reportedly perform complete denitrification, a process previously considered nearly exclusively performed by bacteria and archaea. If the ability to denitrify is widespread among these diverse and abundant protists, a paradigm shift is required for biogeochemistry and marine microbial ecology. However, to date, the mechanisms of foraminiferal denitrification are unclear and it is possible that the ability to perform complete denitrification is due to symbiont metabolism in some foraminiferal species. Using sequence analysis and GeneFISH, we show that for a symbiont-bearing foraminifer, the potential for denitrification resides in the endobionts. Results also identify the endobionts as denitrifying pseudomonads and show that the allogromiid accumulates nitrate intracellularly, presumably for use in denitrification. Endobionts have been observed within many foraminiferal species, and in the case of associations with denitrifying bacteria, may provide fitness for survival in anoxic conditions. These associations may have been a driving force for early foraminiferal diversification, which is thought to have occurred in the Neoproterozoic when anoxia was widespread.This research was supported by NSF grant EF-0702491 to JMB, KLC and VPE; some ship support was provided by NSF MCB-0604084 to VPE and JMB.2012-06-0

    The Retrograde IFT Machinery of C. elegans Cilia: Two IFT Dynein Complexes?

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    We analyzed the relatively poorly understood IFT-dynein (class DYNC2)-driven retrograde IFT pathway in C. elegans cilia, which yielded results that are surprising in the context of current models of IFT. Assays of C. elegans dynein gene expression and intraflagellar transport (IFT) suggest that conventional IFT-dynein contains essential heavy (CHE-3), light-intermediate (XBX-1), plus three light polypeptide chains that participate in IFT, but no “essential” intermediate chain. IFT assays of XBX-1::YFP suggest that IFT-dynein is transported as cargo to the distal tip of the cilium by kinesin-2 motors, but independent of the IFT-particle/BBSome complexes. Finally, we were surprised to find that the subset of cilia present on the OLQ (outer labial quadrant) neurons assemble independently of conventional “CHE-3” IFT-dynein, implying that there is a second IFT-dynein acting in these cilia. We have found a novel gene encoding a dynein heavy chain, DHC-3, and two light chains, in OLQ neurons, which could constitute an IFT-dynein complex in OLQ neuronal cilia. Our results underscore several surprising features of retrograde IFT that require clarification

    Meta-omics approaches to understand and improve wastewater treatment systems

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    Biological treatment of wastewaters depends on microbial processes, usually carried out by mixed microbial communities. Environmental and operational factors can affect microorganisms and/or impact microbial community function, and this has repercussion in bioreactor performance. Novel high-throughput molecular methods (metagenomics, metatranscriptomics, metaproteomics, metabolomics) are providing detailed knowledge on the microorganisms governing wastewater treatment systems and on their metabolic capabilities. The genomes of uncultured microbes with key roles in wastewater treatment plants (WWTP), such as the polyphosphate-accumulating microorganism Candidatus Accumulibacter phosphatis, the nitrite oxidizer Candidatus Nitrospira defluvii or the anammox bacterium Candidatus Kuenenia stuttgartiensis are now available through metagenomic studies. Metagenomics allows to genetically characterize full-scale WWTP and provides information on the lifestyles and physiology of key microorganisms for wastewater treatment. Integrating metagenomic data of microorganisms with metatranscriptomic, metaproteomic and metabolomic information provides a better understanding of the microbial responses to perturbations or environmental variations. Data integration may allow the creation of predictive behavior models of wastewater ecosystems, which could help in an improved exploitation of microbial processes. This review discusses the impact of meta-omic approaches on the understanding of wastewater treatment processes, and the implications of these methods for the optimization and design of wastewater treatment bioreactors.Research was supported by the Spanish Ministry of Education and Science (Contract Project CTQ2007-64324 and CONSOLIDER-CSD 2007-00055) and the Regional Government of Castilla y Leon (Ref. VA038A07). Research of AJMS is supported by the European Research Council (Grant 323009

    Proteomic Analysis of Grape Berry Cell Cultures Reveals that Developmentally Regulated Ripening Related Processes Can Be Studied Using Cultured Cells

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    The original publication is available at http:/www.plosone.orgBackground: This work describes a proteomics profiling method, optimized and applied to berry cell suspensions to evaluate organ-specific cultures as a platform to study grape berry ripening. Variations in berry ripening within a cluster(s) on a vine and in a vineyard are a major impediment towards complete understanding of the functional processes that control ripening, specifically when a characterized and homogenous sample is required. Berry cell suspensions could overcome some of these problems, but their suitability as a model system for berry development and ripening needs to be established first. Methodology/Principal Findings: In this study we report on the proteomic evaluation of the cytosolic proteins obtained from synchronized cell suspension cultures that were established from callus lines originating from green, véraison and ripe Vitis vinifera berry explants. The proteins were separated using liquid phase IEF in a Microrotofor cell and SDS PAGE. This method proved superior to gel-based 2DE. Principal component analysis confirmed that biological and technical repeats grouped tightly and importantly, showed that the proteomes of berry cultures originating from the different growth/ripening stages were distinct. A total of twenty six common bands were selected after band matching between different growth stages and twenty two of these bands were positively identified. Thirty two % of the identified proteins are currently annotated as hypothetical. The differential expression profile of the identified proteins, when compared with published literature on grape berry ripening, suggested common trends in terms of relative abundance in the different developmental stages between real berries and cell suspensions. Conclusions: The advantages of having suspension cultures that accurately mimic specific developmental stages are profound and could significantly contribute to the study of the intricate regulatory and signaling networks responsible for berry development and ripening. © 2011 Sharathchandra et al.Publishers' Versio
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