Analysis of Free Energy Signals Arising from Nucleotide Hybridization Between rRNA and mRNA Sequences during Translation in Eubacteria

A decoding algorithm is tested that mechanistically models the progressive alignments that arise as the mRNA moves past the rRNA tail during translation elongation. Each of these alignments provides an opportunity for hybridization between the single-stranded, -terminal nucleotides of the 16S rRNA and the spatially accessible window of mRNA sequence, from which a free energy value can be calculated. Using this algorithm we show that a periodic, energetic pattern of frequency 1/3 is revealed. This periodic signal exists in the majority of coding regions of eubacterial genes, but not in the non-coding regions encoding the 16S and 23S rRNAs. Signal analysis reveals that the population of coding regions of each bacterial species has a mean phase that is correlated in a statistically significant way with species () content. These results suggest that the periodic signal could function as a synchronization signal for the maintenance of reading frame and that codon usage provides a mechanism for manipulation of signal phase.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]     

Algorithms for Finding Small Attractors in Boolean Networks

A Boolean network is a model used to study the interactions between different genes in genetic regulatory networks. In this paper, we present several algorithms using gene ordering and feedback vertex sets to identify singleton attractors and small attractors in Boolean networks. We analyze the average case time complexities of some of the proposed algorithms. For instance, it is shown that the outdegree-based ordering algorithm for finding singleton attractors works in time for , which is much faster than the naive time algorithm, where is the number of genes and is the maximum indegree. We performed extensive computational experiments on these algorithms, which resulted in good agreement with theoretical results. In contrast, we give a simple and complete proof for showing that finding an attractor with the shortest period is NP-hard.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]     

The Wavelet-Based Cluster Analysis for Temporal Gene Expression Data

A variety of high-throughput methods have made it possible to generate detailed temporal expression data for a single gene or large numbers of genes. Common methods for analysis of these large data sets can be problematic. One challenge is the comparison of temporal expression data obtained from different growth conditions where the patterns of expression may be shifted in time. We propose the use of wavelet analysis to transform the data obtained under different growth conditions to permit comparison of expression patterns from experiments that have time shifts or delays. We demonstrate this approach using detailed temporal data for a single bacterial gene obtained under 72 different growth conditions. This general strategy can be applied in the analysis of data sets of thousands of genes under different conditions.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29]     

Multipattern Consensus Regions in Multiple Aligned Protein Sequences and Their Segmentation

Decomposing a biological sequence into its functional regions is an important prerequisite to understand the molecule. Using the multiple alignments of the sequences, we evaluate a segmentation based on the type of statistical variation pattern from each of the aligned sites. To describe such a more general pattern, we introduce multipattern consensus regions as segmented regions based on conserved as well as interdependent patterns. Thus the proposed consensus region considers patterns that are statistically significant and extends a local neighborhood. To show its relevance in protein sequence analysis, a cancer suppressor gene called p53 is examined. The results show significant associations between the detected regions and tendency of mutations, location on the 3D structure, and cancer hereditable factors that can be inferred from human twin studies.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27]     

Splitting the BLOSUM Score into Numbers of Biological Significance

Mathematical tools developed in the context of Shannon information theory were used to analyze the meaning of the BLOSUM score, which was split into three components termed as the BLOSUM spectrum (or BLOSpectrum). These relate respectively to the sequence convergence (the stochastic similarity of the two protein sequences), to the background frequency divergence (typicality of the amino acid probability distribution in each sequence), and to the target frequency divergence (compliance of the amino acid variations between the two sequences to the protein model implicit in the BLOCKS database). This treatment sharpens the protein sequence comparison, providing a rationale for the biological significance of the obtained score, and helps to identify weakly related sequences. Moreover, the BLOSpectrum can guide the choice of the most appropriate scoring matrix, tailoring it to the evolutionary divergence associated with the two sequences, or indicate if a compositionally adjusted matrix could perform better.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29]     

Epstein-Barr Virus Lacking Glycoprotein gp42 Can Bind to B Cells but Is Not Able To Infect

The Epstein-Barr virus gH-gL complex includes a third glycoprotein, gp42, which is the product of the BZLF2 open reading frame (ORF). gp42 has been implicated as critical to infection of the B lymphocyte by virtue of its interaction with HLA class II on the B-cell surface. A neutralizing antibody that reacts with gp42 inhibits virus-cell fusion and blocks binding of gp42 to HLA class II; antibody to HLA class II can inhibit infection, and B cells that lack HLA class II can only be infected if HLA class II expression is restored. To confirm whether gp42 is an essential component of the virion, we derived a recombinant virus with a selectable marker inserted into the BZLF2 ORF to interrupt expression of the protein. A complex of gH and gL was expressed by the recombinant virus in the absence of gp42. Recombinant virus egressed from the cell normally and could bind to receptor-positive cells. It had, however, lost the ability to infect or transform B lymphocytes. Treatment with polyethylene glycol restored the infectivity of recombinant virus, confirming that gp42 is essential for penetration of the B-cell membrane.Entry of enveloped viruses into mammalian cells requires that the virion envelope fuse with the cell membrane after attachment to the cell surface. Herpesviruses require the functions of multiple protein species to mediate this event, and in keeping with the common origin and diverse habitats of these viruses, some of the proteins involved in penetration appear to be conserved throughout the family and some appear to be restricted to individual members or more closely related members with similar tropism. The two glycoproteins gH and gL fall into the first category of conserved proteins. Glycoprotein gH has been implicated as a major player in virus-cell fusion in many herpesviruses (8, 10, 11, 22, 28, 32, 34), and gL is an essential partner which is required for folding and transport of gH out of the endoplasmic reticulum (6, 19, 21, 27, 28, 35, 38, 45). The gH and gL homologs of Epstein-Barr virus (EBV) are gp85, the product of the BXLF2 open reading frame (ORF) (13, 31), and gp25, the product of the BKRF2 ORF (45), and these homologs appear to behave much as their counterparts in other herpesviruses do (45). However, a third glycoprotein, gp42, associates with the EBV gH-gL complex and falls into the second category of proteins, those with a more restricted distribution.Glycoprotein gp42 is the product of the BZLF2 ORF (26), and although there may be a functionally similar protein in cytomegalovirus (18, 24), it is not predicted to have a homolog in other human herpesviruses. It does, however, have a homolog in ORF51 of equine herpes virus 2 (43). Both EBV and equine herpes virus 2 infect B lymphocytes (1), and several lines of evidence suggest that, at least in the case of EBV, gp42 is critical to the infection of this cell type. A monoclonal antibody (MAb) called F-2-1 that reacts with gp42 has no affect on EBV attachment to its receptor, complement receptor type 2 (CR2) (CD21), but inhibits fusion of the virus with the B-cell membrane and neutralizes infection (29). Glycoprotein gp42 interacts with the β₁ domain of the HLA class II protein HLA-DR (39), and MAb F-2-1 interferes with this interaction (25). Like F-2-1, a MAb to HLA-DR or a soluble form of gp42 can block B-cell transformation, and B-cell lines which lack expression of HLA class II are not susceptible to superinfection with EBV unless expression of HLA class II is restored (25). Collectively these observations suggest that gp42, probably by virtue of its interaction with HLA class II, is essential to infection of the B lymphocyte. To answer directly the question of whether gp42 is an indispensable glycoprotein, we derived a virus that could be definitively shown to lack expression of the molecule and examined its ability to infect normal resting B lymphocytes. We report here that virus with expression of gp42 blocked can exit cells normally and can bind to receptor-positive target cells. However, it is unable to penetrate into cells and initiate infection.