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]     

Proinsulin and the Genetics of Diabetes Mellitus

Insulin plays a central role in the regulation of vertebrate metabolism. The hormone, the post-translational product of a single-chain precursor, is a globular protein containing two chains, A (21 residues) and B (30 residues). Recent advances in human genetics have identified dominant mutations in the insulin gene causing permanent neonatal-onset DM² (1–4). The mutations are predicted to block folding of the precursor in the ER of pancreatic β-cells. Although expression of the wild-type allele would in other circumstances be sufficient to maintain homeostasis, studies of a corresponding mouse model (5–7) suggest that the misfolded variant perturbs wild-type biosynthesis (8, 9). Impaired β-cell secretion is associated with ER stress, distorted organelle architecture, and cell death (10). These findings have renewed interest in insulin biosynthesis (11–13) and the structural basis of disulfide pairing (14–19). Protein evolution is constrained not only by structure and function but also by susceptibility to toxic misfolding.Insulin plays a central role in the regulation of vertebrate metabolism. The hormone, the post-translational product of a single-chain precursor, is a globular protein containing two chains, A (21 residues) and B (30 residues). Recent advances in human genetics have identified dominant mutations in the insulin gene causing permanent neonatal-onset DM² (1–4). The mutations are predicted to block folding of the precursor in the ER of pancreatic β-cells. Although expression of the wild-type allele would in other circumstances be sufficient to maintain homeostasis, studies of a corresponding mouse model (5–7) suggest that the misfolded variant perturbs wild-type biosynthesis (8, 9). Impaired β-cell secretion is associated with ER stress, distorted organelle architecture, and cell death (10). These findings have renewed interest in insulin biosynthesis (11–13) and the structural basis of disulfide pairing (14–19). Protein evolution is constrained not only by structure and function but also by susceptibility to toxic misfolding.     

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]     

Architecture and Molecular Mechanism of PAN, the Archaeal Proteasome Regulatory ATPase

In Archaea, an hexameric ATPase complex termed PAN promotes proteins unfolding and translocation into the 20 S proteasome. PAN is highly homologous to the six ATPases of the eukaryotic 19 S proteasome regulatory complex. Thus, insight into the mechanism of PAN function may reveal a general mode of action mutual to the eukaryotic 19 S proteasome regulatory complex. In this study we generated a three-dimensional model of PAN from tomographic reconstruction of negatively stained particles. Surprisingly, this reconstruction indicated that the hexameric complex assumes a two-ring structure enclosing a large cavity. Assessment of distinct three-dimensional functional states of PAN in the presence of adenosine 5′-O-(thiotriphosphate) and ADP and in the absence of nucleotides outlined a possible mechanism linking nucleotide binding and hydrolysis to substrate recognition, unfolding, and translocation. A novel feature of the ATPase complex revealed in this study is a gate controlling the “exit port” of the regulatory complex and, presumably, translocation into the 20 S proteasome. Based on our structural and biochemical findings, we propose a possible model in which substrate binding and unfolding are linked to structural transitions driven by nucleotide binding and hydrolysis, whereas translocation into the proteasome only depends upon the presence of an unfolded substrate and binding but not hydrolysis of nucleotide.In eukaryotic cells most protein breakdown in the cytosol and nucleus is catalyzed by the 26 S proteasome. This ∼2.5-MDa (1) complex degrades ubiquitin-conjugated and certain non-ubiquitinated proteins in an ATP-dependent manner (2, 3). The 26 S complex is composed of one or two 19 S regulatory particles situated at the ends of the cylindrical 20 S proteasome. Within the 26 S complex, proteins are hydrolyzed in the 20 S proteasome. Tagged substrates, however, first bind to the 19 S regulatory particle, which catalyzes their unfolding and translocation into the 20 S subcomplex (4, 5). The 19 S regulatory particle consists of at least 17 different subunits (1, 6). Nine of these subunits form a “lid,” whereas the other eight subunits, including six ATPases, comprise the base of the 19 S particle. Electron microscopy (7–10) as well as cross-linking experiments (11, 12) have demonstrated that the six homologous ATPases are associated with the α rings of the 20 S particle.Unlike eukaryotes, Archaea and certain eubacteria contain homologous 20 S particles but lack ubiquitin. Their proteasomes degrade proteins in association with a hexameric ATPase ring complex termed PAN (13). PAN appears to be the evolutionary precursor of the 19 S base, predating the coupling of ubiquitination and proteolysis in eukaryotes (14). In addition, PAN recognizes the bacterial targeting sequence ssrA (in analogy to the polyubiquitin conjugates in eukaryotes) and efficiently unfolds and translocates globular substrates, like green fluorescent protein, when tagged with ssrA (15). In both PAN and the 19 S proteasome regulatory complexes, ATP is essential for substrate unfolding and translocation and for opening of the gated channel in the α ring through which substrates enter the 20 S particle (15–17). Because this portal is quite narrow (18–20), only extended polypeptides can enter the 20 S proteasome. Consequently, a globular substrate must be unfolded by the associated ATPase complex to be translocated and digested within the 20 S particle.PAN and the six ATPases found at the base of the 19 S particle are members of the AAA+ superfamily of multimeric ATPases which also includes the ATP-dependent proteases Lon and FtsH and the regulatory components of the bacterial ATP-dependent proteases ClpAP, ClpXP, and HslUV (8, 21). For mechanistic studies of the roles of ATP, the simpler archaeal PAN-20 S system offers many technical advantages over the much more complex 26 S proteasome. For example, prior studies of PAN (17, 22) demonstrated that unfolding of globular substrates (e.g. green fluorescent protein-ssrA) requires ATP hydrolysis. The same was also shown for the Escherichia coli ATP-dependent proteases ClpXP (23) and ClpAP (24). We have also shown that unfolding by PAN can take place on the surface of the ATPase ring in the absence of translocation (15). Thus, unfolding seems to proceed independently from protein translocation into the 20 S proteolytic particle. It is noteworthy that other studies suggest that proteins are unfolded by energy-dependent translocation through the ATPase ring (25, 26). These studies have suggested that the translocation of an unfolded polypeptide from the ATPase into the 20 S core is an active process that is coupled to ATP hydrolysis. A key to underline a detailed molecular mechanism for substrate binding, unfolding, and translocation by the proteasome regulatory ATPase complex is improved understanding of its architecture and the nucleotide-dependent structural transitions that afford these functions.To date we and others have failed to generate micrographs suitable for three-dimensional reconstruction of PAN using single-particle EM analysis. Likewise, structural information regarding the three-dimensional architecture and subunit organization within the 19 S particle is very limited. In fact, high resolution three-dimensional information on the 19 S complex is not yet available. Most knowledge available is based on cross-linking experiments (11, 12) as well as EM structural analysis (7–10), which provided a three-dimensional model outline of the general architecture of the 26 S complex. Unlike the 19 S complex, the structure of the 20 S subcomplex was determined by x-ray crystallography (18, 19). In contrast to the highly homogenous structure of the 20 S complex, the structural heterogeneity and flexibility of the 19 S subcomplex is presumably reflected in multiple conformations, which in turn also contribute to the difficulty in generating a high resolution three-dimensional structural model of the 26 S proteasome. Accordingly, the initial goal of this study was to generate a three-dimensional model of PAN that will allow us to determine its general architecture and to correlate unique conformational transitions within this ATPase with the nucleotide state of the complex (i.e. in the presence of ATPγS, ADP, or in the absence of nucleotides).Smith et al. (27) suggested a general architecture for the PAN-20 S complex based on two-dimensional averaging of a Thermoplasma acidophilum (TA)³ 20 S proteasome and Methanococcus jannaschii (MJ) PAN hybrid complex in the presence of ATPγS. Based on side-view projections of that complex, these authors proposed that PAN assumes an overall structure similar to E. coli HslU (28–30).We realized that although PAN appears heterogeneous in electron micrographs, it does not occupy all possible orientations when adsorbed to carbon-coated electron microscopy (EM) grids, a prerequisite for single particle analysis. This problem was overcome by applying electron tomography in conjunction with a three-dimensional averaging procedure that accounts for the missing wedge in the Fourier space of electron tomograms (31, 32). The three-dimensional model generated revealed an unexpected architecture leading to a possible molecular mechanism describing the function of PAN and presumably the 19 S ATPases.     

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]     

Synthetic Effects of secG and secY2 Mutations on Exoproteome Biogenesis in Staphylococcus aureus

The Gram-positive pathogen Staphylococcus aureus secretes various proteins into its extracellular milieu. Bioinformatics analyses have indicated that most of these proteins are directed to the canonical Sec pathway, which consists of the translocation motor SecA and a membrane-embedded channel composed of the SecY, SecE, and SecG proteins. In addition, S. aureus contains an accessory Sec2 pathway involving the SecA2 and SecY2 proteins. Here, we have addressed the roles of the nonessential channel components SecG and SecY2 in the biogenesis of the extracellular proteome of S. aureus. The results show that SecG is of major importance for protein secretion by S. aureus. Specifically, the extracellular accumulation of nine abundant exoproteins and seven cell wall-bound proteins was significantly affected in an secG mutant. No secretion defects were detected for strains with a secY2 single mutation. However, deletion of secY2 exacerbated the secretion defects of secG mutants, affecting the extracellular accumulation of one additional exoprotein and one cell wall protein. Furthermore, an secG secY2 double mutant displayed a synthetic growth defect. This might relate to a slightly elevated expression of sraP, encoding the only known substrate for the Sec2 pathway, in cells lacking SecG. Additionally, the results suggest that SecY2 can interact with the Sec1 channel, which would be consistent with the presence of a single set of secE and secG genes in S. aureus.Staphylococcus aureus is a well-represented component of the human microbiota as nasal carriage of this Gram-positive bacterium has been shown for 30 to 40% of the population (32). This organism can, however, turn into a dangerous pathogen that is able to infect almost every tissue in the human body. S. aureus has become particularly notorious for its high potential to develop resistance against commonly used antibiotics (20, 49). Accordingly, the S. aureus genome encodes an arsenal of virulence factors that can be expressed when needed at different stages of growth. These include surface proteins and invasins that are necessary for colonization of host tissues, surface-exposed factors for evasion of the immune system, exotoxins for the subversion of protective host barriers, and resistance proteins for protection against antimicrobial agents (37, 57).Most proteinaceous virulence factors of S. aureus are synthesized as precursors with an N-terminal signal peptide to direct their transport from the cytoplasm across the membrane to an extracytoplasmic location, such as the cell wall or the extracellular milieu (38, 45). As shown for various Gram-positive bacteria, the signal peptides of S. aureus are generally longer and more hydrophobic than those of Gram-negative bacteria (38, 54). On the basis of signal peptide predictions using a variety of algorithms, it is believed that most exoproteins of S. aureus are exported to extracytoplasmic locations via the general secretory (Sec) pathway (38). This seems to involve precursor targeting to the Sec machinery via the signal recognition particle instead of the well-characterized proteobacterial chaperone SecB, which is absent from Gram-positive bacteria (16, 19, 53). The preproteins are then bound by the translocation motor protein SecA (38, 45). Through repeated cycles of ATP binding and hydrolysis, SecA pushes the protein in an unfolded state through the membrane-embedded SecYEG translocation channel (12, 30, 33, 52). Upon initiation of the translocation process, the proton motive force is thought to accelerate preprotein translocation through the Sec channel (26). Recently, the structure of the SecA/SecYEG complex from the Gram-negative bacterium Thermotoga maritima was solved at 4.5 Å resolution (58). In this structure, one SecA molecule is bound to one set of SecYEG channel proteins. The core of the Sec translocon consists of the SecA, SecY, and SecE proteins, which are essential for growth and viability of bacteria, such as Escherichia coli and Bacillus subtilis (6, 9, 22). In contrast, the channel component SecG is dispensable for growth, cell viability, and protein translocation (26, 48). Nevertheless, SecG does enhance the efficiency of preprotein translocation through the SecYE channel (26, 48). This is of particular relevance at low temperatures and in the absence of a proton motive force (17). Several studies suggest that E. coli SecG undergoes topology inversion during preprotein translocation (25, 27, 43). Even so, van der Sluis et al. reported that SecG cross-linked to SecY is fully functional despite its fixed topology (46). During or shortly after membrane translocation of a preprotein through the Sec channel, the signal peptide is removed by signal peptidase. This is a prerequisite for the release of the translocated protein from the membrane (1, 47).Several pathogens, including Streptococcus gordonii, Streptococcus pneumoniae, Bacillus anthracis, Bacillus cereus, and S. aureus, contain a second set of chromosomal secA and secY genes named secA2 and secY2, respectively (39). Comparison of the amino acid sequences of the SecY1 and SecY2 proteins shows that their similarity is low (about 20% identity) and that the conserved regions are mainly restricted to the membrane-spanning domains. It has been shown for S. gordonii that the transport of at least one protein is dependent on the presence of SecA2 and SecY2. This protein, GspB, is a large cell surface glycoprotein that is involved in platelet binding (4). The protein contains an unusually long N-terminal signal peptide of 90 amino acids, large serine-rich repeats, and a C-terminal LPXTG motif for covalent cell wall binding. The gspB gene is located in a gene cluster with the secA2 and secY2 genes. Two other genes in this cluster encode the glycosylation proteins GftA and GftB, which seem to be necessary for stabilization of pre-GspB. Furthermore, the asp4 and asp5 genes in the secA2 secY2 gene cluster show similarity to secE and secG, and they are important for GspB export by S. gordonii (44). Despite this similarity, SecE and SecG cannot complement for the absence of Asp4 and Asp5, respectively. The secA2-secY2 gene cluster is also present in S. aureus, but homologues of the asp4 and asp5 genes are lacking. This seems to suggest that SecA2 and SecY2 of S. aureus share the SecE and SecG proteins with SecA1 and SecY1. The sraP gene in the secA2-secY2 gene cluster of S. aureus encodes a protein with features similar to those described for GspB. Siboo and colleagues (41) have shown that SraP is glycosylated and capable of binding to platelets. Importantly, the disruption of sraP resulted in a decreased ability to initiate infective endocarditis in a rabbit model. Consistent with the findings in S. gordonii, SraP export was shown to depend on SecA2/SecY2 (40). However, it has remained unclear whether other S. aureus proteins are also translocated across the membrane in an SecA2/SecY2-dependent manner.The present studies were aimed at defining the roles of two Sec channel components, SecG and SecY2, in the biogenesis of the S. aureus exoproteome. The results show that secG and secY2 are not essential for growth and viability of S. aureus. While the absence of SecY2 by itself had no detectable effect, the absence of SecG had a profound impact on the composition of the exoproteome of S. aureus. Various extracellular proteins were present in decreased amounts in the growth medium of secG mutant strains, which is consistent with impaired Sec channel function. However, a few proteins were present in increased amounts. Furthermore, the absence of secG caused a serious decrease in the amounts of the cell wall-bound Sbi protein. Most notable, a secG secY2 double mutant strain displayed synthetic growth and secretion defects.     

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]