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]     

Mass Spectrometric Quantification of Histone Post-translational Modifications by a Hybrid Chemical Labeling Method

Mass spectrometry is a powerful alternative to antibody-based methods for the analysis of histone post-translational modifications (marks). A key development in this approach was the deliberate propionylation of histones to improve sequence coverage across the lysine-rich and hydrophilic tails that bear most modifications. Several marks continue to be problematic however, particularly di- and tri-methylated lysine 4 of histone H3 which we found to be subject to substantial and selective losses during sample preparation and liquid chromatography-mass spectrometry. We developed a new method employing a “one-pot” hybrid chemical derivatization of histones, whereby an initial conversion of free lysines to their propionylated forms under mild aqueous conditions is followed by trypsin digestion and labeling of new peptide N termini with phenyl isocyanate. High resolution mass spectrometry was used to collect qualitative and quantitative data, and a novel web-based software application (Fishtones) was developed for viewing and quantifying histone marks in the resulting data sets. Recoveries of 53 methyl, acetyl, and phosphoryl marks on histone H3.1 were improved by an average of threefold overall, and over 50-fold for H3K4 di- and tri-methyl marks. The power of this workflow for epigenetic research and drug discovery was demonstrated by measuring quantitative changes in H3K4 trimethylation induced by small molecule inhibitors of lysine demethylases and siRNA knockdown of epigenetic modifiers ASH2L and WDR5.The field of Epigenetics has become important in drug discovery as many diseases have been linked to aberrations in chromatin and changes of histone post-translational modifications (PTMs)¹ (1, 2). The core histones (H2A, H2B, H3, and H4 and their variants) undergo a multitude of PTMs. Some, like lysine acetylation, lysine mono-, di-, and trimethlyation, and serine/threonine phosphorylation are well documented, with over 100 distinct, albeit generally low abundance, modifications reported for H3 alone (3). Mass spectrometry provides an alternative to antibody-based methods for detecting and quantifying histone PTMs, as the latter are prone to problems of specificity and epitope occlusion (4, 5). The most commonly applied approach to date is known as “bottom-up” mass spectrometry and involves an initial processing of the histones into smaller peptides (6). A key development in histone PTM analysis was the deliberate chemical modification of histone tail lysines by propionic anhydride, preventing digestion of these Lys- and Arg-rich domains into peptides too short or hydrophilic to be detected in reverse-phase liquid chromatography-mass spectrometry experiments (7–9).Despite this advance, some marks like H3K4 di- and tri-methylation remain problematic; in several examples from the recent literature the H3K4me3 mark is detected either only by means of specifically targeted methods (5), with larger quantitative variation than other marks (10), or not reported among detected marks at all (3, 11–13). Alternative approaches include top-down or middle-down mass spectrometry, in which entire histones, or large segments thereof are analyzed directly (14–16), but these techniques still suffer from relatively poor sensitivity in comparison to bottom-up workflows, and must contend with the full combinatorial complexity of histone PTMs (17).The H3K4me3 mark is of low natural abundance, having a very restricted genomic localization strongly associated with active gene promotors and enhancers (18, 19), and aberrant activities of writers and erasers of that mark are associated with a variety of diseases (1, 2). Difficulties in its quantitation thus hinder the investigation of both fundamental biology and the discovery of lifesaving drugs. We therefore undertook a re-evaluation of the bottom-up histone PTM workflow, streamlining sample preparation and investigating sources of bias or sample loss. Alternatives to the standard propionylation technique were also explored, resulting in a new hybrid chemical modification workflow yielding across-the-board improvements in recovery of peptides from the N-terminal tail of histone H3, and dramatically improved detection of hydrophilic peptides with marks like H3K4me2/me3.     

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]     

Phosphorylation Dependence of Hsp27 Multimeric Size and Molecular Chaperone Function

The molecular chaperone Hsp27 exists as a distribution of large oligomers that are disassembled by phosphorylation at Ser-15, -78, and -82. It is controversial whether the unphosphorylated Hsp27 or the widely used triple Ser-to-Asp phospho-mimic mutant is the more active molecular chaperone in vitro. This question was investigated here by correlating chaperone activity, as measured by the aggregation of reduced insulin or α-lactalbumin, with Hsp27 self-association as monitored by analytical ultracentrifugation. Furthermore, because the phospho-mimic is generally assumed to reproduce the phosphorylated molecule, the size and chaperone activity of phosphorylated Hsp27 were compared with that of the phospho-mimic. Hsp27 was triply phosphorylated by MAPKAP-2 kinase, and phosphorylation was tracked by urea-PAGE. An increasing degree of suppression of insulin or α-lactalbumin aggregation correlated with a decreasing Hsp27 self-association, which was the least for phosphorylated Hsp27 followed by the mimic followed by the unphosphorylated protein. It was also found that Hsp27 added to pre-aggregated insulin did not reverse aggregation but did inhibit these aggregates from assembling into even larger aggregates. This chaperone activity appears to be independent of Hsp27 phosphorylation. In conclusion, the most active chaperone of insulin and α-lactalbumin was the Hsp27 (elongated) dimer, the smallest Hsp27 subunit observed under physiological conditions. Next, the Hsp27 phospho-mimic is only a partial mimic of phosphorylated Hsp27, both in self-association and in chaperone function. Finally, the efficient inhibition of insulin aggregation by Hsp27 dimer led to the proposal of two models for this chaperone activity.Oligomeric heat shock protein 27 (Hsp27)² is a ubiquitous mammalian protein with a variety of functions in health and disease (1–8). These functions include ATP-independent chaperone activity in response to environmental stress, e.g. heat shock and oxidative stress, control of apoptosis, and regulation of actin cytoskeleton dynamics. Hsp27 is a member of the α-crystallin small heat shock protein family of which αB-crystallin is the archetype. These proteins are characterized by an α-crystallin domain of 80–90 residues consisting of roughly eight β-strands that form an intermolecular β-sheet interaction interface within a dimer, the basic building subunit of the oligomer (2, 4, 9–11).Hsp27 is in equilibrium between high molecular weight oligomers and much lower molecular weight multimers. It has been reported that unphosphorylated Hsp27 includes predominantly a distribution of high molecular species ranging in size from 12-mer to 35-mer (12–19). Phosphorylation of Hsp27 at serines 15, 78, and 82 by the p38-activated MAPKAP-2 kinase (20–22) or the use of the triple Ser-to-Asp phospho-mimic results in a major shift in the equilibrium toward much smaller multimers (23) and in an alteration of its function (1, 3, 6, 7, 24, 25). The size distribution of the smaller species has been reported to be between monomer and tetramer (12–16, 18, 19).Small heat shock proteins, including Hsp27, behave as ATP-independent molecular chaperones during cellular heat shock. They bind partially unfolded proteins and prevent their aggregation until the proteins can be refolded by larger ATP-dependent chaperones or are digested (7, 8, 26). This function includes the up-regulation and/or phosphorylation of Hsp27.It is not entirely clear what the role of Hsp27 size and phosphorylation state plays in its heat shock function because there are conflicting results in the literature. Some in vitro studies concluded that the unphosphorylated oligomeric Hsp27 (or the murine isoform Hsp25) protects proteins against aggregation better than does the phosphorylation mimic (13, 19, 27), whereas others found no difference (16, 28, 29), and still other studies found that the mimic protects better than does the unphosphorylated wild type (27, 30, 31). In-cell studies found that phosphorylation of Hsp27 was essential for thermo-protection of actin filaments (32), and the Hsp27 phosphorylation mimic decreased inclusion body formation better than did unphosphorylated Hsp27 (33). This study was undertaken to investigate the molecular chaperone function of Hsp27 by correlating chaperone activity with Hsp27 size and by comparing fully phosphorylated Hsp27 with its phospho-mimic.     

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]     

Printor, a Novel TorsinA-interacting Protein Implicated in Dystonia Pathogenesis

Early onset generalized dystonia (DYT1) is an autosomal dominant neurological disorder caused by deletion of a single glutamate residue (torsinA ΔE) in the C-terminal region of the AAA⁺ (ATPases associated with a variety of cellular activities) protein torsinA. The pathogenic mechanism by which torsinA ΔE mutation leads to dystonia remains unknown. Here we report the identification and characterization of a 628-amino acid novel protein, printor, that interacts with torsinA. Printor co-distributes with torsinA in multiple brain regions and co-localizes with torsinA in the endoplasmic reticulum. Interestingly, printor selectively binds to the ATP-free form but not to the ATP-bound form of torsinA, supporting a role for printor as a cofactor rather than a substrate of torsinA. The interaction of printor with torsinA is completely abolished by the dystonia-associated torsinA ΔE mutation. Our findings suggest that printor is a new component of the DYT1 pathogenic pathway and provide a potential molecular target for therapeutic intervention in dystonia.Early onset generalized torsion dystonia (DYT1) is the most common and severe form of hereditary dystonia, a movement disorder characterized by involuntary movements and sustained muscle spasms (1). This autosomal dominant disease has childhood onset and its dystonic symptoms are thought to result from neuronal dysfunction rather than neurodegeneration (2, 3). Most DYT1 cases are caused by deletion of a single glutamate residue at positions 302 or 303 (torsinA ΔE) of the 332-amino acid protein torsinA (4). In addition, a different torsinA mutation that deletes amino acids Phe³²³–Tyr³²⁸ (torsinA Δ323–328) was identified in a single family with dystonia (5), although the pathogenic significance of this torsinA mutation is unclear because these patients contain a concomitant mutation in another dystonia-related protein, ϵ-sarcoglycan (6). Recently, genetic association studies have implicated polymorphisms in the torsinA gene as a genetic risk factor in the development of adult-onset idiopathic dystonia (7, 8).TorsinA contains an N-terminal endoplasmic reticulum (ER)³ signal sequence and a 20-amino acid hydrophobic region followed by a conserved AAA⁺ (ATPases associated with a variety of cellular activities) domain (9, 10). Because members of the AAA⁺ family are known to facilitate conformational changes in target proteins (11, 12), it has been proposed that torsinA may function as a molecular chaperone (13, 14). TorsinA is widely expressed in brain and multiple other tissues (15) and is primarily associated with the ER and nuclear envelope (NE) compartments in cells (16–20). TorsinA is believed to mainly reside in the lumen of the ER and NE (17–19) and has been shown to bind lamina-associated polypeptide 1 (LAP1) (21), lumenal domain-like LAP1 (LULL1) (21), and nesprins (22). In addition, recent evidence indicates that a significant pool of torsinA exhibits a topology in which the AAA⁺ domain faces the cytoplasm (20). In support of this topology, torsinA is found in the cytoplasm, neuronal processes, and synaptic terminals (2, 3, 15, 23–26) and has been shown to bind cytosolic proteins snapin (27) and kinesin light chain 1 (20). TorsinA has been proposed to play a role in several cellular processes, including dopaminergic neurotransmission (28–31), NE organization and dynamics (17, 22, 32), and protein trafficking (27, 33). However, the precise biological function of torsinA and its regulation remain unknown.To gain insights into torsinA function, we performed yeast two-hybrid screens to search for torsinA-interacting proteins in the brain. We report here the isolation and characterization of a novel protein named printor (protein interactor of torsinA) that interacts selectively with wild-type (WT) torsinA but not the dystonia-associated torsinA ΔE mutant. Our data suggest that printor may serve as a cofactor of torsinA and provide a new molecular target for understanding and treating dystonia.