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]     

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]     

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]     

Systems-wide Analysis of K-Ras,Cdc42, and PAK4 Signaling by Quantitative Phosphoproteomics

Although K-Ras, Cdc42, and PAK4 signaling are commonly deregulated in cancer, only a few studies have sought to comprehensively examine the spectrum of phosphorylation-mediated signaling downstream of each of these key signaling nodes. In this study, we completed a label-free quantitative analysis of oncogenic K-Ras, activated Cdc42, and PAK4-mediated phosphorylation signaling, and report relative quantitation of 2152 phosphorylated peptides on 1062 proteins. We define the overlap in phosphopeptides regulated by K-Ras, Cdc42, and PAK4, and find that perturbation of these signaling components affects phosphoproteins associated with microtubule depolymerization, cytoskeletal organization, and the cell cycle. These findings provide a resource for future studies to characterize novel targets of oncogenic K-Ras signaling and validate biomarkers of PAK4 inhibition.The Ras oncoproteins are small monomeric GTPases that transduce mitogenic signals from cell surface receptor tyrosine kinases (RTKs) to intracellular serine/threonine kinases. Approximately thirty percent of human tumors harbor a somatic gain-of-function mutation in one of three RAS genes, resulting in the constitutive activation of Ras signaling and the aberrant hyperactivation of growth-promoting effector pathways (1). Designing therapeutic agents that directly target Ras has been challenging (2, 3), and thus clinical development efforts have focused on targeting effector pathways downstream of Ras. The Raf-MEK-ERK and PI3K-Akt effector pathways have been extensively studied and several small molecule inhibitors targeting these pathways are currently under clinical evaluation (4, 5). However, biochemical studies and mouse models indicate that several additional effector pathways are essential for Ras-driven transformation and tumorigenesis (6–11). Hence, a comprehensive characterization of these effector pathways may reveal additional druggable targets.The Rho GTPase Cdc42 lies downstream of Ras (12–14) and regulates many cellular processes that are commonly perturbed in cancer, including migration, polarization, and proliferation (15) (Fig. 1A). Importantly, Cdc42 is overexpressed in several types of human cancer (16–20) and is required for Ras-driven cellular transformation (13, 21, 22). Recent studies show that genetic ablation of Cdc42 impairs Ras-driven tumorigenesis (13), indicating the potential of Cdc42 and its effectors as drug targets in Ras mutant tumors.Open in a separate windowFig. 1.Experimental workflow. A, K-Ras is a small GTPase that regulates the activity of a variety of downstream proteins including the Rho GTPase Cdc42. The PAK4 serine/threonine kinase is a direct effector of Cdc42 and regulates actin reorganization, microtubule stability, and cell polarity. B, To measure large-scale phosphorylation changes induced by constitutive K-Ras or Cdc42 signaling or PAK4 ablation, the quantitative label-free PTMscan® approach was employed (Cell Signaling Technology). Briefly, for each condition extracted proteins were digested with trypsin and separated from non-peptide material by solid-phase extraction with Sep-Pak C18 cartridges. Three phosphorylation motif antibodies were used serially to isolate phosphorylated peptides in independent immunoaffinity purifications (CDK substrate motif [K R]-pS-P-X-[K R], CK substrate motif pT-[D E]-X-[D E], PKD substrate motif l-X-R-X-X-p[S T]). The samples were run in duplicate and tandem mass spectra were collected with an LTQ-Orbitrap hybrid mass spectrometer. pLPC is an empty vector control.In particular, the p21-activated kinases (PAKs) are Cdc42 effectors that have generated significant interest (23, 24), as they are central components of key oncogenic signaling pathways and regulate cytoskeletal organization, cell migration, and nuclear signaling (25). The PAK family is comprised of six members and is subdivided into two groups (Groups I and II) based on sequence and structural homology. Group I PAKs (PAK1–3) are relatively well characterized, however, much less is known regarding the function and regulation of Group II PAKs (PAK4–6). The kinase domains of Group I and II PAKs share only about 50% identity, suggesting the two groups may recognize distinct substrates and govern unique cellular processes (26).The Group II PAK family member PAK4 is of particular interest as it is overexpressed or genetically amplified in several lung, colon, prostate, pancreas, and breast tumor cell lines and samples (26–30). Furthermore, functional studies have implicated PAK4 in cell transformation, cell invasion, and migration (27, 31). Xenograft studies in athymic mice show an important role for PAK4 in mediating Cdc42- or K-Ras-driven tumor formation, highlighting a critical role for Pak4 downstream of these GTPases (32). Given its roles in transformation, tumorigenesis, and oncogenic signaling, there is significant interest in targeting PAK4 therapeutically (23). PAK4 binds and phosphorylates several proteins involved in cytoskeletal organization and apoptosis, including Lim domain kinase 1 (LIMK1) (33), guanine nucleotide exchange factor-H1 (GEF-H1) (34), Raf-1 (35), and Bad (36). However, the Group I PAK family member PAK1 also phosphorylates several of these PAK4 targets (37). Thus, there remains a need to identify robust and selective pharmacodynamic biomarkers for PAK4 inhibition.Despite the importance of PAK4 and its upstream regulators in cancer development, few studies have sought to comprehensively characterize the spectrum of K-Ras, Cdc42, or PAK4 mediated phosphorylation signaling (37–39). Recent developments in mass spectrometry allow the in-depth identification and quantitation of thousands of phosphorylation sites (40–43). The majority of large-scale efforts have aimed to identify the basal phosphoproteomes of different species (44, 45) or tissues (46) to characterize global steady-state phosphorylation. However, this methodology can also be applied to quantify perturbed phosphorylation regulation in cancer signaling pathways (40, 47–49), and has the potential to reveal novel biomarkers of oncogenic signaling.In this study, we completed a label-free quantitative analysis of K-Ras, Cdc42, and PAK4 phosphorylation signaling using the PTMScan® method, which has proven as robust and reproducible quantitation technology (50, 51). We quantified phosphorylation levels in wild-type and PAK4 knockout NIH3T3 cells expressing oncogenic K-Ras, activated Cdc42, or an empty vector control to elucidate the molecular pathways and functions modulated by these key signaling proteins. We report relative quantitation of 2152 phosphorylated peptides on 1062 proteins among the different conditions, and find that many of the regulated phosphoproteins are associated with microtubule depolymerization, cytoskeletal organization, and the cell cycle. To our knowledge, our study is the first to examine the overlap among signaling networks regulated by K-Ras, Cdc42, and PAK4, and provides a resource for future studies to further interrogate the perturbation of this signaling pathway.