Graham J. G. Upton

Dimerization of G-protein-coupled receptors.

The evolutionary trace (ET) method, a data mining approach for determining significant levels of amino acid conservation, has been applied to over 700 aligned G-protein-coupled receptor (GPCR) sequences. The method predicted the occurrence of functionally important clusters of residues on the external faces of helices 5 and 6 for each family or subfamily of receptors; similar clusters were observed on helices 2 and 3. The probability that these clusters are not random was determined using Monte Carlo techniques. The cluster on helices 5 and 6 is consistent with both 5,6-contact and 5,6-domain swapped dimer formation; the possible equivalence of these two types of dimer is discussed because this relates to activation by homo- and heterodimers. The observation of a functionally important cluster of residues on helices 2 and 3 is novel, and some possible interpretations are given, including heterodimerization and oligomerization. The application of the evolutionary trace method to 113 aligned G-protein sequences resulted in the identification of two functional sites. One large, well-defined site is clearly identified with adenyl cyclase, beta/gamma and regulator of G-protein signaling (RGS) binding. The other G-protein functional site, which extends from the ras-like domain onto the helical domain, has the correct size and electrostatic properties for GPCR dimer binding. The implications of these results are discussed in terms of the conformational changes required in the G-protein for activation by a receptor dimer. Further, the implications of GPCR dimerization for medicinal chemistry are discussed in the context of these ET results.

Spatial Data Analysis by Example-Volume 2: Categorical and Directional Data

Keywords: Cartes ; statistiques ; donnees ; traitement Reference Record created on 2005-06-20, modified on 2016-08-08

On-line detection of errors in tipping-bucket raingauges

Tipping-bucket raingauges can produce misleading reports as a consequence of a number of factors. Very fast tips may result from gauge disturbance, faulty bucket positioning or abrupt snow melt. Very slow tips may result from partial blockage. An absence of tips is an indication of a major problem. This paper suggests easily programmable diagnostic checks that may be used to identify any of these problems, using either the data from a single gauge, or by using additional information from neighbouring gauges. The checks were motivated by the need to process 2 years of data from Bolton in the northwest of England. The checks are then tested on archived data from the HYREX experiment, finding 90% of confirmed faults.

MULTIPLE SCLEROSIS ASSOCIATED WITH SINUSITIS: CASE-CONTROLLED STUDY IN GENERAL PRACTICE

In an analysis of general practice records the rate of chronic sinusitis was significantly greater in 92 patients with multiple sclerosis (MS) than in matched controls (p less than 0.0001). MS and chronic sinus infection were also significantly associated in the timing of attacks, in the age at which patients suffered their attacks, and in the seasonal pattern of attacks.

Dual-Doppler Lidar Measurements for Improving Dispersion Models

Abstract Dispersion of pollutants in the urban atmosphere is a subject that is presently under much investigation. In this paper the variables used in turbulent dispersion and plume rise schemes of the Met Office Nuclear Accident Model (NAME) are discussed. Those parameters that can be measured by Doppler lidar are emphasized. Information derived from simultaneous measurements from two Doppler lidars are presented, using methodologies not tried previously, with the aim of improving the forecasting of urban pollution dispersion. The results demonstrate how Doppler lidars can be used as measuring tools for the specific parameters needed within urban dispersion models. A procedure used for carrying out the dual-lidar measurements is outlined. This research shows how dual-lidar measurements can be used to calculate the relevant dispersion parameters, and compares the dual-lidar measurements with model calculations in a case study. Differences between model parameters and lidar observations are discussed. Dual...

Do Plants Contain G Protein-Coupled Receptors?

GCR1 shares the fold and key functional motifs of class A, class B, and class E G protein-coupled receptors. Whether G protein-coupled receptors (GPCRs) exist in plants is a fundamental biological question. Interest in deorphanizing new GPCRs arises because of their importance in signaling. Within plants, this is controversial, as genome analysis has identified 56 putative GPCRs, including G protein-coupled receptor1 (GCR1), which is reportedly a remote homolog to class A, B, and E GPCRs. Of these, GCR2 is not a GPCR; more recently, it has been proposed that none are, not even GCR1. We have addressed this disparity between genome analysis and biological evidence through a structural bioinformatics study, involving fold recognition methods, from which only GCR1 emerges as a strong candidate. To further probe GCR1, we have developed a novel helix-alignment method, which has been benchmarked against the class A-class B-class F GPCR alignments. In addition, we have presented a mutually consistent set of alignments of GCR1 homologs to class A, class B, and class F GPCRs and shown that GCR1 is closer to class A and/or class B GPCRs than class A, class B, or class F GPCRs are to each other. To further probe GCR1, we have aligned transmembrane helix 3 of GCR1 to each of the six GPCR classes. Variability comparisons provide additional evidence that GCR1 homologs have the GPCR fold. From the alignments and a GCR1 comparative model, we have identified motifs that are common to GCR1, class A, B, and E GPCRs. We discuss the possibilities that emerge from this controversial evidence that GCR1 has a GPCR fold.

Similarity between class A and class B G-protein-coupled receptors exemplified through calcitonin gene-related peptide receptor modelling and mutagenesis studies

Modelling class B G-protein-coupled receptors (GPCRs) using class A GPCR structural templates is difficult due to lack of homology. The plant GPCR, GCR1, has homology to both class A and class B GPCRs. We have used this to generate a class A–class B alignment, and by incorporating maximum lagged correlation of entropy and hydrophobicity into a consensus score, we have been able to align receptor transmembrane regions. We have applied this analysis to generate active and inactive homology models of the class B calcitonin gene-related peptide (CGRP) receptor, and have supported it with site-directed mutagenesis data using 122 CGRP receptor residues and 144 published mutagenesis results on other class B GPCRs. The variation of sequence variability with structure, the analysis of polarity violations, the alignment of group-conserved residues and the mutagenesis results at 27 key positions were particularly informative in distinguishing between the proposed and plausible alternative alignments. Furthermore, we have been able to associate the key molecular features of the class B GPCR signalling machinery with their class A counterparts for the first time. These include the [K/R]KLH motif in intracellular loop 1, [I/L]xxxL and KxxK at the intracellular end of TM5 and TM6, the NPXXY/VAVLY motif on TM7 and small group-conserved residues in TM1, TM2, TM3 and TM7. The equivalent of the class A DRY motif is proposed to involve Arg2.39, His2.43 and Glu3.46, which makes a polar lock with T6.37. These alignments and models provide useful tools for understanding class B GPCR function.

Probes containing runs of guanines provide insights into the biophysics and bioinformatics of Affymetrix GeneChips

The reliable interpretation of Affymetrix GeneChip data is a multi-faceted problem. The interplay between biophysics, bioinformatics and mining of GeneChip surveys is leading to new insights into how best to analyse the data. Many of the molecular processes occurring on the surfaces of GeneChips result from the high surface density of probes. Interactions between neighbouring adjacent probes affect their rate and strength of hybridization to targets. Competing targets may hybridize to the same probe, and targets may partially bind to more than one probe. The formation of these partial hybrids results in a number of probes not reaching thermodynamic equilibrium during hybridization. Moreover, some targets fold up, or cross-hybridize to other targets. Furthermore, probes may fold and can undergo chemical saturation. There are also sequence-dependent differences in the rates of target desorption during the washing stage. Improvements in the mappings between probe sequence and biological databases are leading to more accurate gene expression profiles. Moreover, algorithms that combine the intensities of multiple probes into single measures of expression are increasingly dependent upon models of the hybridization processes occurring on GeneChips. The large repositories of GeneChip data can be searched for systematic effects across many experiments. This data mining has led to the discovery of a family of thousands of probes, which show correlated expression across thousands of GeneChip experiments. These probes contain runs of guanines, suggesting that G-quadruplexes are able to form on GeneChips. We discuss the impact of these structures on the interpretation of data from GeneChip experiments.

A Survey of Spatial Defects in Homo Sapiens Affymetrix GeneChips

Modern biology has moved from a science of individual measurements to a science where data are collected on an industrial scale. Foremost, among the new tools for biochemistry are chip arrays which, in one operation, measure hundreds of thousands or even millions of DNA sequences or RNA transcripts. While this is impressive, increasingly sophisticated analysis tools have been required to convert gene array data into gene expression levels. Despite the assumption that noise levels are low, since the number of measurements for an individual gene is small, identifying which signals are affected by noise is a priority. High-density oligonucleotide array (HDONAs) from NCBI GEO shows that, even in the best Human GeneChips 1/4 percent of data are affected by spatial noise. Earlier designs are noisier and spatial defects may affect more than 25 percent of probes. BioConductor R code is available as supplementary material which can be found on the Computer Society Digital Library at http://doi.ieeecomputersociety.org/10.1109/TCBB.2008.108 and via http://bioinformatics.essex.ac.uk/users/wlangdon/TCBB-2007-11-0161.tar.gz.

A Comparative Study of the Impact of G-Stack Probes on Various Affymetrix GeneChips of Mammalia

We have previously discovered that probes containing runs of four or more contiguous guanines are not reliable for measuring gene expression in the Human HG_U133A Affymetrix GeneChip data. These probes are not correlated with other members of their probe set, but they are correlated with each other. We now extend our analysis to different 3′ GeneChip designs of mouse, rat, and human. We find that, in all these chip designs, the G-stack probes (probes with a run of exactly four consecutive guanines) are correlated highly with each other, indicating that such probes are not reliable measures of gene expression in mammalian studies. Furthermore, there is no specific position of G-stack where the correlation is highest in all the chips. We also find that the latest designs of rat and mouse chips have significantly fewer G-stack probes compared to their predecessors, whereas there has not been a similar reduction in G-stack density across the changes in human chips. Moreover, we find significant changes in RMA values (after removing G-stack probes) as the number of G-stack probes increases.