Complex principal component and correlation structure of 16 yeast genomic variables

A quickly growing number of characteristics reflecting various aspects of gene function and evolution can be either measured experimentally or computed from DNA and protein sequences. The study of pairwise correlations between such quantitative genomic variables as well as collective analysis of their interrelations by multidimensional methods have delivered crucial insights into the processes of molecular evolution. Here, we present a principal component analysis (PCA) of 16 genomic variables from Saccharomyces cerevisiae, the largest data set analyzed so far. Because many missing values and potential outliers hinder the direct calculation of principal components, we introduce the application of Bayesian PCA. We confirm some of the previously established correlations, such as evolutionary rate versus protein expression, and reveal new correlations such as those between translational efficiency, phosphorylation density, and protein age. Although the first principal component primarily contrasts genomic change and protein expression, the second component separates variables related to gene existence and expressed protein functions. Enrichment analysis on genes affecting variable correlations unveils classes of influential genes. For example, although ribosomal and nuclear transport genes make important contributions to the correlation between protein isoelectric point and molecular weight, protein synthesis and amino acid metabolism genes help cause the lack of significant correlation between propensity for gene loss and protein age. We present the novel Quagmire database (Quantitative Genomics Resource) which allows exploring relationships between more genomic variables in three model organisms-Escherichia coli, S. cerevisiae, and Homo sapiens (http://webclu.bio.wzw.tum.de:18080/quagmire).     

Knowledge-based selection of targets for structural genomics

The problem of rational target selection for protein structure determination in structural genomics projects on microbes is addressed. A flexible computational procedure is described that directly incorporates the whole body of annotation available in the PEDANT genome database into the sequence clustering and selection process in order to identify proteins that are likely to possess currently unknown structural domains. Filtering out gene products based on predicted structural features, such as known three-dimensional structures and transmembrane regions, allows one to reduce the complexity of neighbor relationships between sequences and all but eliminates the need for further partitioning of single-linkage clusters into disjoint protein groups corresponding to homologous families. The results of a large-scale computation experiment in which exemplary target selection for 32 prokaryotic genomes was conducted are presented.     

No statistical support for correlation between the positions of protein interaction sites and alternatively spliced regions

Background  

Alternative splicing is an efficient mechanism for increasing the variety of functions fulfilled by proteins in a living cell. It has been previously demonstrated that alternatively spliced regions often comprise functionally important and conserved sequence motifs. The objective of this work was to test the hypothesis that alternative splicing is correlated with contact regions of protein-protein interactions.     

Replacement or exclusion of the B-branch bacteriopheophytin in the purple bacterial reaction centre: The HB cofactor is not required for assembly or core function of the Rhodobacter sphaeroides complex

All of the membrane-embedded cofactors of the purple bacterial reaction centre have well-defined functional or structural roles, with the exception of the bacteriopheophytin (H_B) located approximately half-way across the membrane on the so-called inactive- or B-branch of cofactors. Sequence alignments indicate that this bacteriochlorin cofactor is a conserved feature of purple bacterial reaction centres, and a pheophytin is also found at this position in the Photosystem-II reaction centre. Possible structural or functional consequences of replacing the H_B bacteriopheophytin by bacteriochlorophyll were investigated in the Rhodobacter sphaeroides reaction centre through mutagenesis of residue Leu L185 to His (LL185H). Results from absorbance spectroscopy indicated that the LL185H mutant assembled with a bacteriochlorophyll at the H_B position, but this did not affect the capacity of the reaction centre to support photosynthetic growth, or change the kinetics of charge separation along the A-branch of cofactors. It was also found that mutation of residue Ala M149 to Trp (AM149W) caused the reaction centre to assemble without an H_B bacteriochlorin, demonstrating that this cofactor is not required for correct assembly of the reaction centre. The absence of a cofactor at this position did not affect the capacity of the reaction centre to support photosynthetic growth, or the kinetics of A-branch electron transfer. A combination of X-ray crystallography and FTIR difference spectroscopy confirmed that the H_B cofactor was absent in the AM149W mutant, and that this had not produced any significant disturbance of the adjacent ubiquinol reductase (Q_B) site. The data are discussed with respect to possible functional roles of the H_B bacteriopheophytin, and we conclude that the reason(s) for conservation of a bacteriopheophytin cofactor at this position in purple bacterial reaction centres are likely to be different from those underlying conservation of a pheophytin at the analogous position in Photosystem-II.     

Hebbian Plasticity Guides Maturation of Glutamate Receptor Fields In Vivo

1. Download : Download full-size image

     

A trial of digital television cytophotometry

A possible application of modern TV analyzers of microimages for absorption cytochemical investigation is considered. Photometric properties of the TV system are evaluated and methodical approaches to their improvement are given. Data on TV and scanning cytophotometry are compared when studying DNA contents in cells of different types.