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]     

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]     

Conserved Glutamate Residues Glu-343 and Glu-519 Provide Mechanistic Insights into Cation/Nucleoside Cotransport by Human Concentrative Nucleoside Transporter hCNT3

Human concentrative nucleoside transporter 3 (hCNT3) utilizes electrochemical gradients of both Na⁺ and H⁺ to accumulate pyrimidine and purine nucleosides within cells. We have employed radioisotope flux and electrophysiological techniques in combination with site-directed mutagenesis and heterologous expression in Xenopus oocytes to identify two conserved pore-lining glutamate residues (Glu-343 and Glu-519) with essential roles in hCNT3 Na⁺/nucleoside and H⁺/nucleoside cotransport. Mutation of Glu-343 and Glu-519 to aspartate, glutamine, and cysteine severely compromised hCNT3 transport function, and changes included altered nucleoside and cation activation kinetics (all mutants), loss or impairment of H⁺ dependence (all mutants), shift in Na⁺:nucleoside stoichiometry from 2:1 to 1:1 (E519C), complete loss of catalytic activity (E519Q) and, similar to the corresponding mutant in Na⁺-specific hCNT1, uncoupled Na⁺ currents (E343Q). Consistent with close-proximity integration of cation/solute-binding sites within a common cation/permeant translocation pore, mutation of Glu-343 and Glu-519 also altered hCNT3 nucleoside transport selectivity. Both residues were accessible to the external medium and inhibited by p-chloromercuribenzene sulfonate when converted to cysteine.Physiologic nucleosides and the majority of synthetic nucleoside analogs with antineoplastic and/or antiviral activity are hydrophilic molecules that require specialized plasma membrane nucleoside transporter (NT)³ proteins for transport into or out of cells (1–4). NT-mediated transport is required for nucleoside metabolism by salvage pathways and is a critical determinant of the pharmacologic actions of nucleoside drugs (3–6). By regulating adenosine availability to purinoreceptors, NTs also modulate a diverse array of physiological processes, including neurotransmission, immune responses, platelet aggregation, renal function, and coronary vasodilation (4, 6, 7). Two structurally unrelated NT families of integral membrane proteins exist in human and other mammalian cells and tissues as follows: the SLC28 concentrative nucleoside transporter (CNT) family and the SLC29 equilibrative nucleoside transporter (ENT) family (3, 4, 6, 8, 9). ENTs are normally present in most, possibly all, cell types (4, 6, 8). CNTs, in contrast, are found predominantly in intestinal and renal epithelia and other specialized cell types, where they have important roles in absorption, secretion, distribution, and elimination of nucleosides and nucleoside drugs (1–3, 5, 6, 9).The CNT protein family in humans is represented by three members, hCNT1, hCNT2, and hCNT3. Belonging to a CNT subfamily phylogenetically distinct from hCNT1/2, hCNT3 utilizes electrochemical gradients of both Na⁺ and H⁺ to accumulate a broad range of pyrimidine and purine nucleosides and nucleoside drugs within cells (10, 11). hCNT1 and hCNT2, in contrast, are Na⁺-specific and transport pyrimidine and purine nucleosides, respectively (11–13). Together, hCNT1–3 account for the three major concentrative nucleoside transport processes of human and other mammalian cells. Nonmammalian members of the CNT protein family that have been characterized functionally include hfCNT, a second member of the CNT3 subfamily from the ancient marine prevertebrate the Pacific hagfish Eptatretus stouti (14), CeCNT3 from Caenorhabditis elegans (15), CaCNT from Candida albicans (16), and the bacterial nucleoside transporter NupC from Escherichia coli (17). hfCNT is Na⁺- but not H⁺-coupled, whereas CeCNT3, CaCNT, and NupC are exclusively H⁺-coupled. Na⁺:nucleoside coupling stoichiometries are 1:1 for hCNT1 and hCNT2 and 2:1 for hCNT3 and hfCNT3 (11, 14). H⁺:nucleoside coupling ratios for hCNT3 and CaCNT are 1:1 (11, 16).Although much progress has been made in molecular studies of ENT proteins (4, 6, 8), studies of structurally and functionally important regions and residues within the CNT protein family are still at an early stage. Topological investigations suggest that hCNT1–3 and other eukaryote CNT family members have a 13 (or possibly 15)-transmembrane helix (TM) architecture, and multiple alignments reveal strong sequence similarities within the C-terminal half of the proteins (18). Prokaryotic CNTs lack the first three TMs of their eukaryotic counterparts, and functional expression of N-terminally truncated human and rat CNT1 in Xenopus oocytes has established that these three TMs are not required for Na⁺-dependent uridine transport activity (18). Consistent with this finding, chimeric studies involving hCNT1 and hfCNT (14) and hCNT1 and hCNT3 (19) have demonstrated that residues involved in Na⁺- and H⁺-coupling reside in the C-terminal half of the protein. Present in this region of the transporter, but of unknown function, is a highly conserved (G/A)XKX₃NEFVA(Y/M/F) motif common to all eukaryote and prokaryote CNTs.By virtue of their negative charge and consequent ability to interact directly with coupling cations and/or participate in cation-induced and other protein conformational transitions, glutamate and aspartate residues play key functional and structural roles in a broad spectrum of mammalian and bacterial cation-coupled transporters (20–30). Little, however, is known about their role in CNTs. This study builds upon a recent mutagenesis study of conserved glutamate and aspartate residues in hCNT1 (31) to undertake a parallel in depth investigation of corresponding residues in hCNT3. By employing the multifunctional capability of hCNT3 as a template for these studies, this study provides novel mechanistic insights into the molecular mechanism(s) of CNT-mediated cation/nucleoside cotransport, including the role of the (G/A)XKX₃NEFVA(Y/M/F) motif.     

Semaphorin3A Signaling Mediated by Fyn-dependent Tyrosine Phosphorylation of Collapsin Response Mediator Protein 2 at Tyrosine 32

Collapsin response mediator protein 2 (CRMP2) is an intracellular protein that mediates signaling of Semaphorin3A (Sema3A), a repulsive axon guidance molecule. Fyn, a Src-type tyrosine kinase, is involved in the Sema3A signaling. However, the relationship between CRMP2 and Fyn in this signaling pathway is still unknown. In our research, we demonstrated that Fyn phosphorylated CRMP2 at Tyr³² residues in HEK293T cells. Immunohistochemical analysis using a phospho-specific antibody at Tyr³² of CRMP showed that Tyr³²-phosphorylated CRMP was abundant in the nervous system, including dorsal root ganglion neurons, the molecular and Purkinje cell layer of adult cerebellum, and hippocampal fimbria. Overexpression of a nonphosphorylated mutant (Tyr³² to Phe³²) of CRMP2 in dorsal root ganglion neurons interfered with Sema3A-induced growth cone collapse response. These results suggest that Fyn-dependent phosphorylation of CRMP2 at Tyr³² is involved in Sema3A signaling.Collapsin response mediator proteins (CRMPs)⁴ have been identified as intracellular proteins that mediate Semaphorin3A (Sema3A) signaling in the nervous system (1). CRMP2 is one of the five members of the CRMP family. CRMPs also mediate signal transduction of NT3, Ephrin, and Reelin (2–4). CRMPs interact with several intracellular molecules, including tubulin, Numb, kinesin1, and Sra1 (5–8). CRMPs are involved in axon guidance, axonal elongation, cell migration, synapse maturation, and the generation of neuronal polarity (1, 2, 4, 5).CRMP family proteins are known to be the major phosphoproteins in the developing brain (1, 9). CRMP2 is phosphorylated by several Ser/Thr kinases, such as Rho kinase, cyclin-dependent kinase 5 (Cdk5), and glycogen synthase kinase 3β (GSK3β) (2, 10–13). The phosphorylation sites of CRMP2 by these kinases are clustered in the C terminus and have already been identified. Rho kinase phosphorylates CRMP2 at Thr⁵⁵⁵ (10). Cdk5 phosphorylates CRMP2 at Ser⁵²², and this phosphorylation is essential for sequential phosphorylations by GSK3β at Ser⁵¹⁸, Thr⁵¹⁴, and Thr⁵⁰⁹ (2, 11–13). These phosphorylations disrupt the interaction of CRMP2 with tubulin or Numb (2, 3, 13). The sequential phosphorylation of CRMP2 by Cdk5 and GSK3β is an essential step in Sema3A signaling (11, 13). Furthermore, the neurofibrillary tangles in the brains of people with Alzheimer disease contain hyperphosphorylated CRMP2 at Thr⁵⁰⁹, Ser⁵¹⁸, and Ser⁵²² (14, 15).CRMPs are also substrates of several tyrosine kinases. The phosphorylation of CRMP2 by Fes/Fps and Fer has been shown to be involved in Sema3A signaling (16, 17). Phosphorylation of CRMP2 at Tyr⁴⁷⁹ by a Src family tyrosine kinase Yes regulates CXCL12-induced T lymphocyte migration (18). We reported previously that Fyn is involved in Sema3A signaling (19). Fyn associates with PlexinA2, one of the components of the Sema3A receptor complex. Fyn also activates Cdk5 through the phosphorylation at Tyr¹⁵ of Cdk5 (19). In dorsal root ganglion (DRG) neurons from fyn-deficient mice, Sema3A-induced growth cone collapse response is attenuated compared with control mice (19). Furthermore, we recently found that Fyn phosphorylates CRMP1 and that this phosphorylation is involved in Reelin signaling (4). Although it has been shown that CRMP2 is involved in Sema3A signaling (1, 11, 13), the relationship between Fyn and CRMP2 in Sema3A signaling and the tyrosine phosphorylation site(s) of CRMPs remain unknown.Here, we show that Fyn phosphorylates CRMP2 at Tyr³². Using a phospho-specific antibody against Tyr³², we determined that the residue is phosphorylated in vivo. A nonphosphorylated mutant CRMP2Y32F inhibits Sema3A-induced growth cone collapse. These results indicate that tyrosine phosphorylation by Fyn at Tyr³² is involved in Sema3A signaling.     

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]