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

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

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

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

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

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

An Improvement of Shotgun Proteomics Analysis by Adding Next-Generation Sequencing Transcriptome Data in Orange

BACKGROUND: Shotgun proteomics data analysis usually relies on database search. Because commonly employed protein sequence databases of most species do not contain sufficient protein information, the application of shotgun proteomics to the research of protein sequence profile remains a big challenge, especially to the species whose genome has not been sequenced yet. METHODOLOGY/PRINCIPAL FINDINGS: In this paper, we present a workflow with integrated database to partly address this problem. First, we downloaded the homologous species database. Next, we identified the transcriptome of the sample, created a protein sequence database based on the transcriptome data, and integtrated it with homologous species database. Lastly, we developed a workflow for identifying peptides simultaneously from shotgun proteomics data. CONCLUSIONS/SIGNIFICANCE: We used datasets from orange leaves samples to demonstrate our workflow. The results showed that the integrated database had great advantage on orange shotgun proteomics data analysis compared to the homologous species database, an 18.5% increase in number of proteins identification

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

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

Meta-omics approaches to understand and improve wastewater treatment systems

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

Initial results of secukinumab drug survival in patients with psoriasis: A multicentre daily practice cohort study

Interleukin 17-antagonist secukinumab demonstrated high efficacy for treatment of psoriasis in randomized controlled trials. However, performance in daily practice may differ from trials. Drug survival is a comprehensive outcome covering effectiveness and safety, suitable for analyses of daily practice. The aim of this study was to evaluate drug survival of secukinumab in a daily practice psoriasis cohort. Data were collected from 13 hospitals. Drug survival was analysed using Kaplan–Meier survival curves, split for reason of discontinuation. In total, 196 patients were included (83% biologic experienced). Overall, 12 and 18 months drug survival of secukinumab was 76% and 67%, respectively, and was mostly determined by ineffectiveness. There was a trend towards shorter drug survival in women and in biologic experienced patients. Thirteen percent of patients experienced at least one episode of fungal infection. This is one of the first studies of drug survival of secukinumab in patients with psoriasis treated in daily practice

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

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

Intraflagellar Transport (IFT) Protein IFT25 Is a Phosphoprotein Component of IFT Complex B and Physically Interacts with IFT27 in Chlamydomonas

BACKGROUND: Intraflagellar transport (IFT) is the bidirectional movement of IFT particles between the cell body and the distal tip of a flagellum. Organized into complexes A and B, IFT particles are composed of at least 18 proteins. The function of IFT proteins in flagellar assembly has been extensively investigated. However, much less is known about the molecular mechanism of how IFT is regulated. METHODOLOGY/PRINCIPAL FINDINGS: We herein report the identification of a novel IFT particle protein, IFT25, in Chlamydomonas. Dephosphorylation assay revealed that IFT25 is a phosphoprotein. Biochemical analysis of temperature sensitive IFT mutants indicated that IFT25 is an IFT complex B subunit. In vitro binding assay confirmed that IFT25 binds to IFT27, a Rab-like small GTPase component of the IFT complex B. Immunofluorescence staining showed that IFT25 has a punctuate flagellar distribution as expected for an IFT protein, but displays a unique distribution pattern at the flagellar base. IFT25 co-localizes with IFT27 at the distal-most portion of basal bodies, probably the transition zones, and concentrates in the basal body region by partially overlapping with other IFT complex B subunits, such as IFT46. Sucrose density gradient centrifugation analysis demonstrated that, in flagella, the majority of IFT27 and IFT25 including both phosphorylated and non-phosphorylated forms are cosedimented with other complex B subunits in the 16S fractions. In contrast, in cell body, only a fraction of IFT25 and IFT27 is integrated into the preassembled complex B, and IFT25 detected in complex B is preferentially phosphorylated. CONCLUSION/SIGNIFICANCE: IFT25 is a phosphoprotein component of IFT particle complex B. IFT25 directly interacts with IFT27, and these two proteins likely form a subcomplex in vivo. We postulate that the association and disassociation between the subcomplex of IFT25 and IFT27 and complex B might be involved in the regulation of IFT