Reannotation des Maize oligonucleotide arrays

Die Microarray-Technologie hat sich zu einem etablierten Ansatz der Hochdurchsatz-Genexpressionsanalyse entwickelt. Das „maize oligonucleotide array“ (maizearray) ist eine der wenigen Microarray-Plattformen, welche für die genomweite Genexpressionsanalyse von Mais (Zea mays L.) erzeugt wurden. Die Sonden wurden basierend auf ESTs (expressed sequence tags) generiert. Mittlerweile ist die Genomsequenz von Mais verfügbar und ermöglicht eine genauere Annotation dieser Sonden. In dieser Arbeit wurden die Genompositionen aller Sonden und basierend darauf die zugrunde liegenden Gene sowie deren funktionelle Annotation bestimmt. Durch die Analyse konnten Redundanzen und nicht eindeutig bindende Sonden aufgedeckt und gleichzeitig die Zahl der Gene mit funktioneller Annotation verdoppelt werden. Unsere Reannotation wird funktionelle Analysen bereits existierender und zukünftiger Datensätze stark verbessern

PDE7A1 hydrolyzes cCMP

AbstractThe degradation and biological role of the cyclic pyrimidine nucleotide cCMP is largely elusive. We investigated nucleoside 3′,5′-cyclic monophosphate (cNMP) specificity of six different recombinant phosphodiesterases (PDEs) by using a highly-sensitive HPLC–MS/MS detection method. PDE7A1 was the only enzyme that hydrolyzed significant amounts of cCMP. Enzyme kinetic studies using purified GST-tagged truncated PDE7A1 revealed a cCMP KM value of 135±19μM. The Vmax for cCMP hydrolysis reached 745±27nmol/(minmg), which is about 6-fold higher than the corresponding velocity for adenosine 3′,5′-cyclic monophosphate (cAMP) degradation. In summary, PDE7A is a high-speed and low-affinity PDE for cCMP

Re-annotation of the maize oligonucleotide array

The microarray technology has become an established approach for large-scale gene expression analysis with mature protocols for sample, microarray, and data processing. The maize oligonucleotide array (maizearray) is one of the few microarray platforms designed for genome-wide gene expression analysis in Zea mays L. Many datasets addressing various genetic, physiological and developmental topics generated with this platform are available. The original 57,452 microarray probes were compiled based on expressed sequence tags (ESTs). Meanwhile the maize genome sequence became available providing the possibility for an improved annotation of the microarray probe set. In this study we determined the genome positions of all maize array probes to obtain current gene annotations and generated current Gene Ontology (GO) annotations. These new data allow tracing redundancy of the probe set and interfering cross-hybridizations, and doubled the number of genes with functional GO data. Our re-annotation will largely improve the functional analysis of available and future datasets generated on this microarray platform

Identifying cloud droplets beyond lidar attenuation from vertically pointing cloud radar observations using artificial neural networks

In mixed-phase clouds, the variable mass ratio between liquid water and ice as well as the spatial distribution within the cloud plays an important role in cloud lifetime, precipitation processes, and the radiation budget. Data sets of vertically pointing Doppler cloud radars and lidars provide insights into cloud properties at high temporal and spatial resolution. Cloud radars are able to penetrate multiple liquid layers and can potentially be used to expand the identification of cloud phase to the entire vertical column beyond the lidar signal attenuation height, by exploiting morphological features in cloud radar Doppler spectra that relate to the existence of supercooled liquid. We present VOODOO (reVealing supercOOled liquiD beyOnd lidar attenuatiOn), a retrieval based on deep convolutional neural networks (CNNs) mapping radar Doppler spectra to the probability of the presence of cloud droplets (CD). The training of the CNN was realized using the Cloudnet processing suite as supervisor. Once trained, VOODOO yields the probability for CD directly at Cloudnet grid resolution. Long-term predictions of 18 months in total from two mid-latitudinal locations, i.e., Punta Arenas, Chile (53.1 S, 70.9 W), in the Southern Hemisphere and Leipzig, Germany (51.3 N, 12.4 E), in the Northern Hemisphere, are evaluated. Temporal and spatial agreement in cloud-droplet-bearing pixels is found for the Cloudnet classification to the VOODOO prediction. Two suitable case studies were selected, where stratiform, multi-layer, and deep mixed-phase clouds were observed. Performance analysis of VOODOO via classification-evaluating metrics reveals precision > 0.7, recall ≈ 0.7, and accuracy ≈ 0.8. Additionally, independent measurements of liquid water path (LWP) retrieved by a collocated microwave radiometer (MWR) are correlated to the adiabatic LWP, which is estimated using the temporal and spatial locations of cloud droplets from VOODOO and Cloudnet in connection with a cloud parcel model. This comparison resulted in stronger correlation for VOODOO (≈ 0.45) compared to Cloudnet (≈ 0.22) and indicates the availability of VOODOO to identify CD beyond lidar attenuation. Furthermore, the long-term statistics for 18 months of observations are presented, analyzing the performance as a function of MWR-LWP and confirming VOODOO's ability to identify cloud droplets reliably for clouds with LWP > 100 g m-2. The influence of turbulence on the predictive performance of VOODOO was also analyzed and found to be minor. A synergy of the novel approach VOODOO and Cloudnet would complement each other perfectly and is planned to be incorporated into the Cloudnet algorithm chain in the near future

Significant continental source of ice-nucleating particles at the tip of Chile's southernmost Patagonia region

The sources and abundance of ice-nucleating particles (INPs) that initiate cloud ice formation remain understudied, especially in the Southern Hemisphere. In this study, we present INP measurements taken close to Punta Arenas, Chile, at the southernmost tip of South America from May 2019 to March 2020, during the Dynamics, Aerosol, Cloud, And Precipitation Observations in the Pristine Environment of the Southern Ocean (DACAPO-PESO) campaign. The highest ice nucleation temperature was observed at −3◦C, and from this temperature down to ∼ −10◦C, a sharp increase of INP number concentration (NINP) was observed. Heating of the samples revealed that roughly 90 % and 80 % of INPs are proteinaceous-based biogenic particles at > −10 and −15◦C, respectively. The NINP at Punta Arenas is much higher than that in the Southern Ocean, but it is comparable with an agricultural area in Argentina and forestry environment in the US. Ice active surface site density (ns) is much higher than that for marine aerosol in the Southern Ocean, but comparable to English fertile soil dust. Parameterization based on particle number concentration in the size range larger than 500 nm (N>500 nm) from the global average (DeMott et al., 2010) overestimates the measured INP, but the parameterization representing biological particles from a forestry environment (Tobo et al., 2013) yields NINP comparable to this study. No clear seasonal variation of NINP was observed. High precipitation is one of the most important meteorological parameters to enhance the NINP in both cold and warm seasons. A comparison of data from in situ and lidar measurements showed good agreement for concentrations of large aerosol particles (> 500 nm) when assuming continental conditions for retrieval of the lidar data, suggesting that these particles were well mixed within the planetary boundary layer (PBL). This corroborates the continental origin of these particles, consistent with the results from our INP source analysis. Overall, we suggest that a high NINP of biogenic INPs originated from terrestrial sources and were added to the marine air masses during the overflow of a maximum of roughly 150 km of land before arriving at the measurement station

Nucleotidyl Cyclase Activity of Particulate Guanylyl Cyclase A: Comparison with Particulate Guanylyl Cyclases E and F, Soluble Guanylyl Cyclase and Bacterial Adenylyl Cyclases Cyaa and Edema Factor

Guanylyl cyclases (GCs) regulate many physiological processes by catalyzing the synthesis of the second messenger cGMP. The GC family consists of seven particulate GCs (pGCs) and a nitric oxide-activated soluble GC (sGC). Rat sGC α1β1 possesses much broader substrate specificity than previously assumed. Moreover, the exotoxins CyaA from Bordetella pertussis and edema factor (EF) from Bacillus anthracis possess nucleotidyl cyclase (NC) activity. pGC-A is a natriuretic peptide-activated homodimer with two catalytic sites that act cooperatively. Here, we studied the NC activity of rat pGC-A in membranes of stably transfected HEK293 cells using a highly sensitive and specific HPLC-MS/MS technique. GTP and ITP were effective, and ATP and XTP were only poor, pGC-A substrates. In contrast to sGC, pGC-A did not use CTP and UTP as substrates. pGC-E and pGC-F expressed in bovine rod outer segment membranes used only GTP as substrate. In intact HEK293 cells, pGC-A generated only cGMP. In contrast to pGCs, EF and CyaA showed very broad substrate-specificity. In conclusion, NCs exhibit different substrate-specificities, arguing against substrate-leakiness of enzymes and pointing to distinct physiological functions of cyclic purine and pyrimidine nucleotides.</p

Vertical aerosol distribution in the southern hemispheric midlatitudes as observed with lidar in Punta Arenas, Chile (53.2° and 70.9° W), during ALPACA

Within this publication, lidar observations of the vertical aerosol distribution above Punta Arenas, Chile (53.2 S and 70.9 W), which have been performed with the Raman lidar PollyXT from December 2009 to April 2010, are presented. Pristine marine aerosol conditions related to the prevailing westerly circulation dominated the measurements. Lofted aerosol layers could only be observed eight times during the whole measurement period. Two case studies are presented showing long-range transport of smoke from biomass burning in Australia and regionally transported dust from the Patagonian Desert, respectively. The aerosol sources are identified by trajectory analyses with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) and FLEXible PARTicle dispersion model (FLEXPART). However, seven of the eight analysed cases with lofted layers show an aerosol optical thickness of less than 0.05. From the lidar observations, a mean planetary boundary layer (PBL) top height of 1150 350m was determined. An analysis of particle backscatter coefficients confirms that the majority of the aerosol is attributed to the PBL, while the free troposphere is characterized by a very low background aerosol concentration. The ground-based lidar observations at 532 and 1064 nm are supplemented by the Aerosol Robotic Network (AERONET) Sun photometers and the space-borne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). The averaged aerosol optical thickness (AOT) determined by CALIOP was 0:02 0:01 in Punta Arenas from 2009 to 2010. © Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License

Aerosol-cloud-radiation interaction during Saharan dust episodes: The dusty cirrus puzzle

Dusty cirrus clouds are extended optically thick cirrocumulus decks that occur during strong mineral dust events. So far they have been mostly documented over Europe associated with dust-infused baroclinic storms. Since today's numerical weather prediction models neither predict mineral dust distributions nor consider the interaction of dust with cloud microphysics, they cannot simulate this phenomenon. We postulate that the dusty cirrus forms through a mixing instability of moist clean air with drier dusty air. A corresponding sub-grid parameterization is suggested and tested in the ICON-ART model. Only with help of this parameterization ICON-ART is able to simulate the formation of the dusty cirrus, which leads to substantial improvements in cloud cover and radiative fluxes compared to simulations without this parameterization. A statistical evaluation over six Saharan dust events with and without observed dusty cirrus shows robust improvements in cloud and radiation scores. The ability to simulate dusty cirrus formation removes the linear dependency on mineral dust aerosol optical depth from the bias of the radiative fluxes. This suggests that the formation of dusty cirrus clouds is the dominant aerosol-cloud-radiation effect of mineral dust over Europe.</p