Rapid removal of unincorporated label and proteins from DNA sequencing reactions

This article presents a simple and rapid method for removal of unincorporated label and proteins from DNA sequencing reactions by using Wizard purification resin. This method can be successfully applied for preparation of end-labeled oligonucleotides free of unincorporated label, which is important in experiments (including DNA sequencing) when the level of background should be as low as possible. Also, this method is effective in removal of proteins from DNA sequencing reactions.     

Utilizing logical relationships in genomic data to decipher cellular processes

The wealth of available genomic data has spawned a corresponding interest in computational methods that can impart biological meaning and context to these experiments. Traditional computational methods have drawn relationships between pairs of proteins or genes based on notions of equality or similarity between their patterns of occurrence or behavior. For example, two genes displaying similar variation in expression, over a number of experiments, may be predicted to be functionally related. We have introduced a natural extension of these approaches, instead identifying logical relationships involving triplets of proteins. Triplets provide for various discrete kinds of logic relationships, leading to detailed inferences about biological associations. For instance, a protein C might be encoded within an organism if, and only if, two other proteins A and B are also both encoded within the organism, thus suggesting that gene C is functionally related to genes A and B. The method has been applied fruitfully to both phylogenetic and microarray expression data, and has been used to associate logical combinations of protein activity with disease state phenotypes, revealing previously unknown ternary relationships among proteins, and illustrating the inherent complexities that arise in biological data.     

Novel search method for the discovery of functional relationships

MOTIVATION: Numerous annotations are available that functionally characterize genes and proteins with regard to molecular process, cellular localization, tissue expression, protein domain composition, protein interaction, disease association and other properties. Searching this steadily growing amount of information can lead to the discovery of new biological relationships between genes and proteins. To facilitate the searches, methods are required that measure the annotation similarity of genes and proteins. However, most current similarity methods are focused only on annotations from the Gene Ontology (GO) and do not take other annotation sources into account. RESULTS: We introduce the new method BioSim that incorporates multiple sources of annotations to quantify the functional similarity of genes and proteins. We compared the performance of our method with four other well-known methods adapted to use multiple annotation sources. We evaluated the methods by searching for known functional relationships using annotations based only on GO or on our large data warehouse BioMyn. This warehouse integrates many diverse annotation sources of human genes and proteins. We observed that the search performance improved substantially for almost all methods when multiple annotation sources were included. In particular, our method outperformed the other methods in terms of recall and average precision.     

Tumor-promoting activity of p-hydroxybenzenediazonium is accelerated in Mg-deficient rats

Tumor-promoting activity caused by the short-term administration of p-hydroxybenzenediazonium (PDQ) has been assayed in rats fed on a Mg-deficient diet as a reference model versus rats fed on a standard diet as controls. For 5 weeks groups of 20 rats, fed either on the Mg-deficient or standard diet, were treated simultaneously with PDQ. A group of 10 Mg-deficient rats remained untreated. Topical application of PDQ was followed by the appearance of macroscopic alterations in the skin, which were more evident in the Mg-deficient rats. No deaths occurred during the treatment. After 5 weeks' PDQ treatment the rats were killed and histological analyses were made. Tissues from the skin, liver, heart, kidney, lung and thymus were screened by conventional staining methods. Both the PDQ-treated Mg-deficient and PDQ-treated control rats presented tissue lesions, although to a different extent. The untreated Mg-deficient rats showed no such lesions. Mg-deficient rats treated with PDQ developed significant incipient fibrosarcomas (p<0.05) and extended hyperplasia (p<0.001), particularly in the skin, accompanied by a significant increase in the thickness of collagen (mean value: 445.4+/-47.2microm, p<0.05) compared to the control PDQ-treated group (mean values: 258.7+/-36.4microm). The overall results provide objective proof of tumor-promoting activity after 5 weeks' treatment with PDQ. Such a fast response is interpreted as being linked to the increased vulnerability of the membrane caused by Mg deficiency, which would more readily facilitate the toxic activity of p-hydroxybenzenediazonium ions.     

Locally defined protein phylogenetic profiles reveal previously missed protein interactions and functional relationships

Phylogenetic profiles encode patterns of presence or absence of genes across genomes, and these profiles can be used to assign functional relationships to nonhomologous pairs of proteins (Pellegrini et al., Proc Natl Acad Sci USA 1999;96:4284-4288). Although it is well known that many proteins were created from combinations of domains, most of the existing implementations of phylogenetic profiles do not consider this fact. Here, we introduce an extension that considers the multidomain nature of proteins and test the method against the known interaction data sets. Whereas earlier implementations associated one entire sequence with one protein phylogenetic profile (Single-Profile), our method instead breaks the sequence into a set of segments of predetermined size and constructs a separate profile for each segment (Multiple-Profile). The results show that the Multiple-Profile method performs as well as the Single-Profile method. However, the two methods share, surprisingly, a small fraction of their predictions, indicating that the Multiple-Profile method can detect known interactions missed by the Single-Profile method. Thus, the Multiple-Profile method can be used with other methods to determine functional relationships on a genome scale with wider coverage.     

The Arabidopsis co-expression tool (ACT): a WWW-based tool and database for microarray-based gene expression analysis

We present a new WWW-based tool for plant gene analysis, the Arabidopsis Co-Expression Tool (ACT), based on a large Arabidopsis thaliana microarray data set obtained from the Nottingham Arabidopsis Stock Centre. The co-expression analysis tool allows users to identify genes whose expression patterns are correlated across selected experiments or the complete data set. Results are accompanied by estimates of the statistical significance of the correlation relationships, expressed as probability (P) and expectation (E) values. Additionally, highly ranked genes on a correlation list can be examined using the novel clique finder tool to determine the sets of genes most likely to be regulated in a similar manner. In combination, these tools offer three levels of analysis: creation of correlation lists of co-expressed genes, refinement of these lists using two-dimensional scatter plots, and dissection into cliques of co-regulated genes. We illustrate the applications of the software by analysing genes encoding functionally related proteins, as well as pathways involved in plant responses to environmental stimuli. These analyses demonstrate novel biological relationships underlying the observed gene co-expression patterns. To demonstrate the ability of the software to develop testable hypotheses on gene function within a defined biological process we have used the example of cell wall biosynthesis genes. The resource is freely available at http://www.arabidopsis.leeds.ac.uk/ACT/     

Dediazoniation of p-hydroxybenzenediazonium ion in a neutral aqueous medium

The dediazoniation of p-hydroxybenzenediazonium ion (PDQ) in a neutral aqueous medium has been studied under controlled experimental conditions to prevent photochemical and/or heterolytic side-reactions. Oxygen increased the dediazoniation rate of PDQ and caused the appearance of quinone and hydroquinone. An accumulation of quinone deriving from the reduction of PDQ by hydroquinone was also observed. In ESR analyses with different spin traps, the most stable signal was identified as belonging to the adduct of the p-hydroxyphenyl radical, even in the presence of dimethylsulfoxide or ethanol. A general scheme is proposed including three pathways for the homolytic dediazoniation of PDQ. Pathway 1 represents dediazoniation induced by a hydroxyl ion, a slow process at neutral pH and an even slower one with deaerated samples; a favored quinoid structure is put forward to explain these results. In pathway 2, the formation of a semiquinone radical via the reaction of an aryl radical with oxygen is put forward to justify the increase in the dediazoniation rate in the presence of oxygen. In pathway 3, hydroquinone, produced by semiquinone dismutation, may act as a reducing agent.     

Gene products of Escherichia coli: sequence comparisons and common ancestries

Sequences of 1,862 chromosomally encoded Escherichia coli K12 proteins were examined to identify genes likely to have arisen by duplication of genes in an ancestral chromosome. The criteria for sequence relatedness were an alignment of at least 100 amino acid residues and a PAM distance (number of accepted point mutations per 100 residues separating two sequences) below 250. A total of 971 of the 1,862 proteins examined were found in 2,329 sequence-related pairs that met these criteria. Most proteins of the sequence-related pairs were related in cellular function, as judged by biochemical and/or physiological features. Many of the pairs of proteins could be grouped into sequence-related families. If such groupings were generated from ancestral genes by duplication and divergence events, through these sequence comparisons we can identify putative ancestral sequences of the present-day genes of E. coli and other organisms. The results suggest that the 971 paralogous genes could have been derived from only 204 ancestral genes. We have also shown that the process of duplication and divergence is not the exclusive mechanism of evolution of all E. coli genes. Indeed, the relationships among the sequences of multiple (in the sense of redundant) enzymes indicate that nearly half could have arisen either by convergent evolution or by lateral transfer. Therefore, not all functionally related genes need arise by duplication and divergence.      

Gene function

The problem of gene function--of the relationships between hereditary material and the characteristics of organisms--preceded the rediscovery of Mendel's laws and accompanied the development of genetics in the XXth century. Molecular biologists replaced the simple gene-character relationship by two relationships: the first, between genes and proteins, was well defined, whereas the second between proteins and the complex structural and functional characteristics of organisms remained unknown. I will describe in this article the experimental approaches which helped to characterize during the last twenty years the relationships between proteins and characters. Four principles of macromolecular organization emerged from these studies: conservation of the elementary components during evolution, existence of pathways and networks, pleiotropy and redundancy. These principles are the explanation of the surprising experimental observations that have been made in recent years. The existence of these principles makes problematic any prediction on the consequences of gene modification. It both sounds the death-knell of the simplistic reductionist approach of many biologists, whereby genes were considered as responsible for specific functions, and definitely prevents the distribution of genes in separate, well defined categories.     

Comparison of proteins of ADP-glucose pyrophosphorylase from diverse sources

Summary The primary structures of 11 proteins of ADP-glucose pyrophosphorylase are aligned and compared for relationships among them. These comparisons indicate that many domains are retained in the proteins from both the enteric bacteria and the proteins from angiosperm plants. The proteins from angiosperm plants show two main groups, with one of the main groups demonstrating two subgroups. The two main groups of angiosperm plant proteins are based upon the two subunits of the enzyme, whereas the subgroups of the large subunit group are based upon the tissue in which the particular gene had been expressed. Additionally, the small subunit group shows a slight but distinct division into a grouping based upon whether the protein is from a monocot or dicot source. Previous structure-function studies with the Escherichia coli enzyme have identified regions of the primary structure associated with the substrate binding site, the allosteric activator binding site, and the allosteric inhibitor binding site. There is conservation of the primary structure of the polypeptides for the substrate binding site and the allosteric activator binding site. The nucleotide sequences of the coding regions of the genes of 11 of these proteins are compared for relationships among them. This analysis indicates that the protein for the small subunit has been subject to greater selective pressure to retain a particular primary structure. Also, the coding region of the precursor gene for the small subunit diverged from the coding region of the precursor gene for the large subunits slightly prior to the divergence of the two coding regions of the genes for the two tissue-specific large subunit genes.Offprint requests to: J. Preiss     

Related Arabidopsis serine carboxypeptidase-like sinapoylglucose acyltransferases display distinct but overlapping substrate specificities

The Arabidopsis (Arabidopsis thaliana) genome encodes 51 proteins annotated as serine carboxypeptidase-like (SCPL) enzymes. Nineteen of these SCPL proteins are highly similar to one another, and represent a clade that appears to be unique to plants. Two of the most divergent proteins within this group have been characterized to date, sinapoyl-glucose (Glc):malate sinapoyltransferase and sinapoyl-Glc:choline sinapoyltransferase. The fact that two of the least related proteins within this clade are acyltransferases rather than true serine carboxypeptidases suggests that some or all of the remaining members of this group may have similar activities. The gene that encodes sinapoyl-Glc:malate sinapoyltransferase (sinapoyl-Glc accumulator1 [SNG1]: At2g22990) is one of five SCPL genes arranged in a cluster on chromosome 2. In this study, an analysis of deletion mutant lines lacking one or more genes in this SCPL gene cluster reveals that three of these genes also encode sinapoyl-Glc-dependent acyltransferases. At2g23000 encodes sinapoyl-Glc:anthocyanin acyltransferase, an enzyme that is required for the synthesis of the sinapoylated anthocyanins in Arabidopsis. At2g23010 encodes an enzyme capable of synthesizing 1,2-disinapoyl-Glc from two molecules of sinapoyl-Glc, an activity shared by SNG1 and At2g22980. Sequence analysis of these SCPL proteins reveals pairwise percent identities that range from 71% to 78%, suggesting that their differing specificities for acyl acceptor substrates are due to changes in a relatively small subset of amino acids. The study of these SCPL proteins provides an opportunity to examine enzyme structure-function relationships and may shed light on the role of evolution of hydroxycinnamate ester metabolism and the SCPL gene family in Arabidopsis and other flowering plants.     

A protein interaction network associated with asthma

Identifying candidate genes related to complex diseases or traits and mapping their relationships require a system-level analysis at a cellular scale. The objective of the present study is to systematically analyze the complex effects of interrelated genes and provide a framework for revealing their relationships in association with a specific disease (asthma in this case). We observed that protein-protein interaction (PPI) networks associated with asthma have a power-law connectivity distribution as many other biological networks have. The hub nodes and skeleton substructure of the result network are consistent with the prior knowledge about asthma pathways, and also suggest unknown candidate target genes associated with asthma, including GNB2L1, BRCA1, CBL, and VAV1. In particular, GNB2L1 appears to play a very important role in the asthma network through frequent interactions with key proteins in cellular signaling. This network-based approach represents an alternative method for analyzing the complex effects of candidate genes associated with complex diseases and suggesting a list of gene drug targets. The full list of genes and the analysis details are available in the following online supplementary materials: http://biosoft.kaist.ac.kr:8080/resources/asthma_ppi.     

Comparative genomics of the RBR family,including the Parkinson's disease-related gene parkin and the genes of the ariadne subfamily

Genes of the RBR family are characterized by the RBR signature (two RING finger domains separated by an IBR/DRIL domain). The RBR family is widespread in eukaryotes, with numerous members in animals (mammals, Drosophila, Caenorhabditis) and plants (Arabidopsis). But yeasts, such as Saccharomyces cerevisiae or Schizosaccharomyces pombe, contain only two RBR genes. We determined the phylogenetic relationships and the most likely orthologs in different species of several family members for which functional data are available. These include: (1) parkin, whose mutations are involved in forms of familial Parkinson's disease; (2) the ariadne genes, recently characterized in Drosophila and mammals; (3) XYbp and Dorfin, two mammalian genes whose products interact with the centrosome; (4) XAP3, RBCK1, and UIP28, mammalian genes encoding Protein Kinase-C-binding proteins; and (5) ARA54, an androgen receptor coactivator. Because several of these genes are involved in ubiquitination, we used phylogenetic and structural analyses to explore the hypothesis that all RBR proteins might play a role in ubiquitination. We show that the involvement of RBR proteins in ubiquitination predates the animals-plants-fungi divergence. On the basis of the evidence provided by cases of gene fusion, we suggest that Ariadne proteins interact with cullin domain-containing proteins to form complexes with ubiquitin-ligase activity.     

Analysis of protein sequence and interaction data for candidate disease gene prediction

Linkage analysis is a successful procedure to associate diseases with specific genomic regions. These regions are often large, containing hundreds of genes, which make experimental methods employed to identify the disease gene arduous and expensive. We present two methods to prioritize candidates for further experimental study: Common Pathway Scanning (CPS) and Common Module Profiling (CMP). CPS is based on the assumption that common phenotypes are associated with dysfunction in proteins that participate in the same complex or pathway. CPS applies network data derived from protein–protein interaction (PPI) and pathway databases to identify relationships between genes. CMP identifies likely candidates using a domain-dependent sequence similarity approach, based on the hypothesis that disruption of genes of similar function will lead to the same phenotype. Both algorithms use two forms of input data: known disease genes or multiple disease loci. When using known disease genes as input, our combined methods have a sensitivity of 0.52 and a specificity of 0.97 and reduce the candidate list by 13-fold. Using multiple loci, our methods successfully identify disease genes for all benchmark diseases with a sensitivity of 0.84 and a specificity of 0.63. Our combined approach prioritizes good candidates and will accelerate the disease gene discovery process.