Exploring synonymous codon usage preferences of disulfide-bonded and non-disulfide bonded cysteines in the E-coli genome

High-quality data about protein structures and their gene sequences are essential to the understanding of the relationship between protein folding and protein coding sequences. Firstly we constructed the EcoPDB database, which is a high-quality database of Escherichia coli genes and their corresponding PDB structures. Based on EcoPDB, we presented a novel approach based on information theory to investigate the correlation between cysteine synonymous codon usages and local amino acids flanking cysteines, the correlation between cysteine synonymous codon usages and synonymous codon usages of local amino acids flanking cysteines, as well as the correlation between cysteine synonymous codon usages and the disulfide bonding states of cysteines in the E. coli genome. The results indicate that the nearest neighboring residues and their synonymous codons of the C-terminus have the greatest influence on the usages of the synonymous codons of cysteines and the usage of the synonymous codons has a specific correlation with the disulfide bond formation of cysteines in proteins. The correlations may result from the regulation mechanism of protein structures at gene sequence level and reflect the biological function restriction that cysteines pair to form disulfide bonds. The results may also be helpful in identifying residues that are important for synonymous codon selection of cysteines to introduce disulfide bridges in protein engineering and molecular biology. The approach presented in this paper can also be utilized as a complementary computational method and be applicable to analyse the synonymous codon usages in other model organisms. (c) 2005 Elsevier Ltd. All rights reserved.

A review of plasma endothelin-1 levels in CABG patient group

Introduction: Endothelin-1 is a potent vasoconstricting growth peptide. In physiologic conditions basal levels maintain vascular homeostasis, conversely in pathological situations it may be expressed in response to chronic and acute vascular injury. Elevated levels of plasma ET-1 have been identified in sub-populations at risk of ischaemic heart disease (IHD) including smokers, diabetics and hyerlipidaemic subjects and in patients with atherosclerotic disease. This peptide may be chronically expressed, such as in congestive heart failure where it has been used as a prognostic marker of disease severity and also acutely, after cardiac revascularisation surgery, possibly as a result of endothelial injury and ischaemia. Aims: The objectives of this study were to (1) identify basal endothelin-1 concentrations in a young healthy control group with no risk factors for IHD (control group 1); (2) to compare; (1) venous plasma ET-1 levels preoperatively and post-operatively in patients undergoing CABG surgery, (3) to compare pre-operative plasma ET-1 levels from the CABG group with an age and gender matched control group (control group 2) and (4) combine all three groups to assess correlations between plasma ET-1 and the various risk factors for IHD, including smoking, hypertension, hyperlipidemia, diabetes and family history. Methods: Venous specimens were collected in chilled EDTA tubes and samples measured using an ELISA assay (Biomedica), following the standard protocol for human EDTA plasma. Results: Forty CABG patients (5F, 35M, mean age 66 yrs), 15 control group 1 subjects (8F, 7M, mean age 29 yrs) and 30 control group 2 subjects (5F, 25M, mean age 61 yrs) participated in the study. No significant difference was detected in plasma ET-1 levels between the controls (1) and (2), and the CABG group, where plasma ET-1 levels were 3.37+/ 5.19 pmol/L, 1.99+/3.74 pmol/L and 1.28+/1.27 pmol/L, respectively. There was a non-significant elevation in post-op ET-1 plasma in comparison with the pre-op levels (2.50+/0.51 Vs 1.45+/6.44). There were also no statistical correlation between risk factors for IHD including smoking, hypertension, NIDDM, hyperlipidemia or family history when data from both patient and controls groups was merged. Conclusion: Contrary to other findings, plasma ET-1 does not appear to a valid marker for IHD or factors which are strongly associated with the pathogenesis of this disease.

Statistical tests of load-unload response ratio signals by lattice solid model: Implication to tidal triggering and earthquake prediction

Statistical tests of Load-Unload Response Ratio (LURR) signals are carried in order to verify statistical robustness of the previous studies using the Lattice Solid Model (MORA et al., 2002b). In each case 24 groups of samples with the same macroscopic parameters (tidal perturbation amplitude A, period T and tectonic loading rate k) but different particle arrangements are employed. Results of uni-axial compression experiments show that before the normalized time of catastrophic failure, the ensemble average LURR value rises significantly, in agreement with the observations of high LURR prior to the large earthquakes. In shearing tests, two parameters are found to control the correlation between earthquake occurrence and tidal stress. One is, A/(kT) controlling the phase shift between the peak seismicity rate and the peak amplitude of the perturbation stress. With an increase of this parameter, the phase shift is found to decrease. Another parameter, AT/k, controls the height of the probability density function (Pdf) of modeled seismicity. As this parameter increases, the Pdf becomes sharper and narrower, indicating a strong triggering. Statistical studies of LURR signals in shearing tests also suggest that except in strong triggering cases, where LURR cannot be calculated due to poor data in unloading cycles, the larger events are more likely to occur in higher LURR periods than the smaller ones, supporting the LURR hypothesis.

On the statistical analysis of the GS-NS0 cell proteome: Imputation, clustering and variability testing

We have undertaken two-dimensional gel electrophoresis proteomic profiling on a series of cell lines with different recombinant antibody production rates. Due to the nature of gel-based experiments not all protein spots are detected across all samples in an experiment, and hence datasets are invariably incomplete. New approaches are therefore required for the analysis of such graduated datasets. We approached this problem in two ways. Firstly, we applied a missing value imputation technique to calculate missing data points. Secondly, we combined a singular value decomposition based hierarchical clustering with the expression variability test to identify protein spots whose expression correlates with increased antibody production. The results have shown that while imputation of missing data was a useful method to improve the statistical analysis of such data sets, this was of limited use in differentiating between the samples investigated, and highlighted a small number of candidate proteins for further investigation. (c) 2006 Elsevier B.V. All rights reserved.