Improving flood models using LiDAR: progress and problems

Airborne scanning laser altimetry (LiDAR) is an important new data source for river flood modelling. LiDAR can give dense and accurate DTMs of floodplains for use as model bathymetry. Spatial resolutions of 0.5m or less are possible, with a height accuracy of 0.15m. LiDAR gives a Digital Surface Model (DSM), so vegetation removal software (e.g. TERRASCAN) must be used to obtain a DTM. An example used to illustrate the current state of the art will be the LiDAR data provided by the EA, which has been processed by their in-house software to convert the raw data to a ground DTM and separate vegetation height map. Their method distinguishes trees from buildings on the basis of object size. EA data products include the DTM with or without buildings removed, a vegetation height map, a DTM with bridges removed, etc. Most vegetation removal software ignores short vegetation less than say 1m high. We have attempted to extend vegetation height measurement to short vegetation using local height texture. Typically most of a floodplain may be covered in such vegetation. The idea is to assign friction coefficients depending on local vegetation height, so that friction is spatially varying. This obviates the need to calibrate a global floodplain friction coefficient. It’s not clear at present if the method is useful, but it’s worth testing further. The LiDAR DTM is usually determined by looking for local minima in the raw data, then interpolating between these to form a space-filling height surface. This is a low pass filtering operation, in which objects of high spatial frequency such as buildings, river embankments and walls may be incorrectly classed as vegetation. The problem is particularly acute in urban areas. A solution may be to apply pattern recognition techniques to LiDAR height data fused with other data types such as LiDAR intensity or multispectral CASI data. We are attempting to use digital map data (Mastermap structured topography data) to help to distinguish buildings from trees, and roads from areas of short vegetation. The problems involved in doing this will be discussed. A related problem of how best to merge historic river cross-section data with a LiDAR DTM will also be considered. LiDAR data may also be used to help generate a finite element mesh. In rural area we have decomposed a floodplain mesh according to taller vegetation features such as hedges and trees, so that e.g. hedge elements can be assigned higher friction coefficients than those in adjacent fields. We are attempting to extend this approach to urban area, so that the mesh is decomposed in the vicinity of buildings, roads, etc as well as trees and hedges. A dominant points algorithm is used to identify points of high curvature on a building or road, which act as initial nodes in the meshing process. A difficulty is that the resulting mesh may contain a very large number of nodes. However, the mesh generated may be useful to allow a high resolution FE model to act as a benchmark for a more practical lower resolution model. A further problem discussed will be how best to exploit data redundancy due to the high resolution of the LiDAR compared to that of a typical flood model. Problems occur if features have dimensions smaller than the model cell size e.g. for a 5m-wide embankment within a raster grid model with 15m cell size, the maximum height of the embankment locally could be assigned to each cell covering the embankment. But how could a 5m-wide ditch be represented? Again, this redundancy has been exploited to improve wetting/drying algorithms using the sub-grid-scale LiDAR heights within finite elements at the waterline.

Syk-Dependent Cytokine Induction by Dectin-1 Reveals a Novel Pattern Recognition Pathway for C Type Lectins

Pattern-recognition receptors (PRRs) detect molecular signatures of microbes and initiate immune responses to infection. Prototypical PRRs such as Toll-like receptors (TLRs) signal via a conserved pathway to induce innate response genes. In contrast, the signaling pathways engaged by other classes of putative PRRs remain ill defined. Here, we demonstrate that the β-glucan receptor Dectin-1, a yeast binding C type lectin known to synergize with TLR2 to induce TNFα and IL-12, can also promote synthesis of IL-2 and IL-10 through phosphorylation of the membrane proximal tyrosine in the cytoplasmic domain and recruitment of Syk kinase. syk−/− dendritic cells (DCs) do not make IL-10 or IL-2 upon yeast stimulation but produce IL-12, indicating that the Dectin-1/Syk and Dectin-1/TLR2 pathways can operate independently. These results identify a novel signaling pathway involved in pattern recognition by C type lectins and suggest a potential role for Syk kinase in regulation of innate immunity.

Excision of anabaena PCC 7120 nifD element in escherichia coli: growth kinetics and RecA regulated xisA expression and DNA rearrangement

Anabaena PCC 7120 nifHDK operon is interrupted by an 11 kb DNA element which is excised during the development of heterocysts by Excisase A, encoded by the xisA gene residing on the element. The excision is a site-specific recombination event that occurs at the I I base pair direct repeats flanking the element. Earlier work showed the excision of the I I kb element in Escherichia coli at a frequency 0.3%. We report here the excision of this element at 1.1% and 1.98% in E. coli DH5 alpha, and 1.9% and 10.9% in E. coli JM 101 when grown on Luria broth and minimal media, respectively. Excision of nifD element in isogenic recA(-) (RK1) and recA(+) (RK2) E. coli JM101 P1 transductants, showed similar results to that of E. coli JM101 and DH5 alpha, respectively. A plasmid pMX32, carrying a xisA defective 11 kb element, showed no excision in E. coli RK2 strain. In contrast to Anabaena PCC 7120, excision of nifD element did not increase in E. call DH5 alpha grown in iron-deficient conditions. A PxisA::lacZ transcriptional fusion, used to detect the expression of elusive xisA gene, showed maximal beta-galactosidase activity in the stationary phase. The results suggest that the excision event in E. coli may involve additional factors, such as RecA and that the physiological status can influence the excision of nifD element. (C) 2007 Elsevier Ltd. All rights reserved.

Intrinsic disorder prediction from the analysis of multiple protein fold recognition models

Motivation: Intrinsic protein disorder is functionally implicated in numerous biological roles and is, therefore, ubiquitous in proteins from all three kingdoms of life. Determining the disordered regions in proteins presents a challenge for experimental methods and so recently there has been much focus on the development of improved predictive methods. In this article, a novel technique for disorder prediction, called DISOclust, is described, which is based on the analysis of multiple protein fold recognition models. The DISOclust method is rigorously benchmarked against the top.ve methods from the CASP7 experiment. In addition, the optimal consensus of the tested methods is determined and the added value from each method is quantified. Results: The DISOclust method is shown to add the most value to a simple consensus of methods, even in the absence of target sequence homology to known structures. A simple consensus of methods that includes DISOclust can significantly outperform all of the previous individual methods tested.

Benchmarking consensus model quality assessment for protein fold recognition

Background: Selecting the highest quality 3D model of a protein structure from a number of alternatives remains an important challenge in the field of structural bioinformatics. Many Model Quality Assessment Programs (MQAPs) have been developed which adopt various strategies in order to tackle this problem, ranging from the so called "true" MQAPs capable of producing a single energy score based on a single model, to methods which rely on structural comparisons of multiple models or additional information from meta-servers. However, it is clear that no current method can separate the highest accuracy models from the lowest consistently. In this paper, a number of the top performing MQAP methods are benchmarked in the context of the potential value that they add to protein fold recognition. Two novel methods are also described: ModSSEA, which based on the alignment of predicted secondary structure elements and ModFOLD which combines several true MQAP methods using an artificial neural network. Results: The ModSSEA method is found to be an effective model quality assessment program for ranking multiple models from many servers, however further accuracy can be gained by using the consensus approach of ModFOLD. The ModFOLD method is shown to significantly outperform the true MQAPs tested and is competitive with methods which make use of clustering or additional information from multiple servers. Several of the true MQAPs are also shown to add value to most individual fold recognition servers by improving model selection, when applied as a post filter in order to re-rank models. Conclusion: MQAPs should be benchmarked appropriately for the practical context in which they are intended to be used. Clustering based methods are the top performing MQAPs where many models are available from many servers; however, they often do not add value to individual fold recognition servers when limited models are available. Conversely, the true MQAP methods tested can often be used as effective post filters for re-ranking few models from individual fold recognition servers and further improvements can be achieved using a consensus of these methods.

High throughput profile-profile based fold recognition for the entire human proteome

BACKGROUND: In order to maintain the most comprehensive structural annotation databases we must carry out regular updates for each proteome using the latest profile-profile fold recognition methods. The ability to carry out these updates on demand is necessary to keep pace with the regular updates of sequence and structure databases. Providing the highest quality structural models requires the most intensive profile-profile fold recognition methods running with the very latest available sequence databases and fold libraries. However, running these methods on such a regular basis for every sequenced proteome requires large amounts of processing power.In this paper we describe and benchmark the JYDE (Job Yield Distribution Environment) system, which is a meta-scheduler designed to work above cluster schedulers, such as Sun Grid Engine (SGE) or Condor. We demonstrate the ability of JYDE to distribute the load of genomic-scale fold recognition across multiple independent Grid domains. We use the most recent profile-profile version of our mGenTHREADER software in order to annotate the latest version of the Human proteome against the latest sequence and structure databases in as short a time as possible. RESULTS: We show that our JYDE system is able to scale to large numbers of intensive fold recognition jobs running across several independent computer clusters. Using our JYDE system we have been able to annotate 99.9% of the protein sequences within the Human proteome in less than 24 hours, by harnessing over 500 CPUs from 3 independent Grid domains. CONCLUSION: This study clearly demonstrates the feasibility of carrying out on demand high quality structural annotations for the proteomes of major eukaryotic organisms. Specifically, we have shown that it is now possible to provide complete regular updates of profile-profile based fold recognition models for entire eukaryotic proteomes, through the use of Grid middleware such as JYDE.

Mass spectroscopic characterization of the coronavirus infectious bronchitis virus nucleoprotein and elucidation of the role of phosphorylation in RNA binding by using surface plasmon resonance

Phosphorylation of the coronavirus nucleoprotein (N protein) has been predicted to play a role in RNA binding. To investigate this hypothesis, we examined the kinetics of RNA binding between nonphosphorylated and phosphorylated infectious bronchitis virus N protein with nonviral and viral RNA by surface plasmon resonance (Biacore). Mass spectroscopic analysis of N protein identified phosphorylation sites that were proximal to RNA binding domains. Kinetic analysis, by surface plasmon resonance, indicated that nonphospborylated N protein bound with the same affinity to viral RNA as phosphorylated N protein. However, phosphorylated N protein bound to viral RNA with a higher binding affinity than nonviral RNA, suggesting that phosphorylation of N protein determined the recognition of virus RNA. The data also indicated that a known N protein binding site (involved in transcriptional regulation) consisting of a conserved core sequence present near the 5' end of the genome (in the leader sequence) functioned by promoting high association rates of N protein binding. Further analysis of the leader sequence indicated that the core element was not the only binding site for N protein and that other regions functioned to promote high-affinity binding.

Structure and function analysis of the poliovirus cis-acting replication element (CRE)

The poliovirus cis-acting replication element (CRE) templates the uridylylation of VPg, the protein primer for genome replication. The CRE is a highly conserved structural RNA element in the enteroviruses and located within the polyprotein-coding region of the genome. We have determined the native structure of the CRE, defined the regions of the structure critical for activity, and investigated the influence of genomic location on function. Our results demonstrate that a 14-nucleotide unpaired terminal loop, presented on a suitably stable stem, is all that is required for function. These conclusions complement the recent analysis of the 14-nucleotide terminal loop in the CRE of human rhinovirus type 14. The CRE can be translocated to the 5' noncoding region of the genome, at least 3.7-kb distant from the native location, without adversely influencing activity, and CRE duplications do not adversely influence replication. We do not have evidence for a specific interaction between the CRE and the RNA-binding 3CD(pro) complex, an essential component of the uridylylation reaction, and the mechanism by which the CRE is coordinated and orientated during the reaction remains unclear. These studies provide a detailed overview of the structural determinants required for CRE function, and will facilitate a better understanding of the requirements for picornavirus replication.

The poliovirus 2C cis-acting replication element-mediated uridylylation of VPg is not required for synthesis of negative-sense genomes

Nucleotides in the terminal loop of the poliovirus 2C cis-acting replication element (2C(CRE)), a 61 nt structured RNA, function as the template for the addition of two uridylate (U) residues to the viral protein VPg. This uridylylation reaction leads to the formation of VPgpUpU, which is used by the viral RNA polymerase as a nucleotide-peptide primer for genome replication. Although VPg primes both positive- and negative-strand replication, the specific requirement for 2C(CRE)-mediated uridylylation for one or both events has not been demonstrated. We have used a cell-free in vitro translation and replication reaction to demonstrate that 2C(CRE) is not required for the initiation of the negative-sense strand, which is synthesized in the absence of 2C(CRE)-mediated VPgpUpU formation. We propose that the 3' poly(A) tail could serve as the template for the formation of a VPg-poly(U) primer that functions in the initiation of negative-sense strands.

First 5f-element complexes with the tetradentate BTBP ligand. Synthesis and crystal structure of uranyl(VI) compounds with CyMe4BTBP

Treatment of [UO2(OTf)(2)] or [UO2I2(thf)(3)] with 1 equiv. of CyMe4BTBP in anhydrous acetonitrile led to the formation of [UO2(CyMe4BTBP)(OTf)(2)] (1) and [UO2(CyMe4BTBP)I-2] (2) which crystallized as the cationic forms [UO2(CyMe4BTBP)(py)][OTf](2) (3) and [UO2I(CyMe4BTBP)][I] (4) in pyridine and acetonitrile, respectively. These compounds are unique examples of structurally characterized actinide complexes with a BTBP molecule; this ligand adopts a planar conformation in the equatorial plane of the {UO2}(2+) ion. In pyridine, 1 is dissociated into [UO2(OTf)(2)(PY)(3)] and free CyMe4BTBP and the thermodynamic parameters (K, Delta H, Delta S) of this equilibrium have been determined by H-1 NMR spectroscopy. The ethoxide derivative [UO2(OEt)(CyMe4BTBP)][OTf] (5) crystallized from a solution of I in a mixture of ethanol and acetone under air, and the dinuclear mu-oxo complex [{UO2(CyMe4BTBP)}(2)(mu-O)][I](2) (6) was obtained from [UO2I(thf)(2.7)] and CyMe4BTBP. The crystal structures of 6 and of the analogous derivatives [{UO2(py)(4)}(2)(mu-O)][I](2)(7) and [{UO2(TPTZ)(py)}(2)(mu-O)][I-3](2)(8) exhibit a flexible [{UO2}-O-{UO2}](2+) moiety.

Ligand bridging of the DNA Holliday junction: molecular recognition of a stacked-X four-way junction by a small molecule

Planning a Holliday: A new mode of binding to a stacked-X, four-way Holliday junction is described in which a chromophore molecule binds across the center of the junction and two adenine residues are replaced by the acridine chromophores at either side of the crossover. This binding mode is specific for the Holliday junction and does not cause unwinding of the DNA helices.

Recognition of polyimide sequence information by a molecular tweezer

Specific monomer sequences in aromatic copolyimides are recognized through their -stacking and hydrogen-bonding interactions with a sterically and electronically complementary molecular tweezer. These interactions enable the tweezer molecule to read monomer sequences comprising up to 27 aromatic rings by multiple adjacent binding to neighboring sites on the polymer chain.