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]     

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]     

Inference of a Probabilistic Boolean Network from a Single Observed Temporal Sequence

The inference of gene regulatory networks is a key issue for genomic signal processing. This paper addresses the inference of probabilistic Boolean networks (PBNs) from observed temporal sequences of network states. Since a PBN is composed of a finite number of Boolean networks, a basic observation is that the characteristics of a single Boolean network without perturbation may be determined by its pairwise transitions. Because the network function is fixed and there are no perturbations, a given state will always be followed by a unique state at the succeeding time point. Thus, a transition counting matrix compiled over a data sequence will be sparse and contain only one entry per line. If the network also has perturbations, with small perturbation probability, then the transition counting matrix would have some insignificant nonzero entries replacing some (or all) of the zeros. If a data sequence is sufficiently long to adequately populate the matrix, then determination of the functions and inputs underlying the model is straightforward. The difficulty comes when the transition counting matrix consists of data derived from more than one Boolean network. We address the PBN inference procedure in several steps: (1) separate the data sequence into "pure" subsequences corresponding to constituent Boolean networks; (2) given a subsequence, infer a Boolean network; and (3) infer the probabilities of perturbation, the probability of there being a switch between constituent Boolean networks, and the selection probabilities governing which network is to be selected given a switch. Capturing the full dynamic behavior of probabilistic Boolean networks, be they binary or multivalued, will require the use of temporal data, and a great deal of it. This should not be surprising given the complexity of the model and the number of parameters, both transitional and static, that must be estimated. In addition to providing an inference algorithm, this paper demonstrates that the data requirement is much smaller if one does not wish to infer the switching, perturbation, and selection probabilities, and that constituent-network connectivity can be discovered with decent accuracy for relatively small time-course sequences.[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]     

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]     

Deletion of the Chloride Transporter Slc26a7 Causes Distal Renal Tubular Acidosis and Impairs Gastric Acid Secretion

SLC26A7 (human)/Slc26a7 (mouse) is a recently identified chloride-base exchanger and/or chloride transporter that is expressed on the basolateral membrane of acid-secreting cells in the renal outer medullary collecting duct (OMCD) and in gastric parietal cells. Here, we show that mice with genetic deletion of Slc26a7 expression develop distal renal tubular acidosis, as manifested by metabolic acidosis and alkaline urine pH. In the kidney, basolateral Cl⁻/HCO₃⁻ exchange activity in acid-secreting intercalated cells in the OMCD was significantly decreased in hypertonic medium (a normal milieu for the medulla) but was reduced only mildly in isotonic medium. Changing from a hypertonic to isotonic medium (relative hypotonicity) decreased the membrane abundance of Slc26a7 in kidney cells in vivo and in vitro. In the stomach, stimulated acid secretion was significantly impaired in isolated gastric mucosa and in the intact organ. We propose that SLC26A7 dysfunction should be investigated as a potential cause of unexplained distal renal tubular acidosis or decreased gastric acid secretion in humans.The collecting duct segment of the distal kidney nephron plays a major role in systemic acid base homeostasis by acid secretion and bicarbonate absorption. The acid secretion occurs via H⁺-ATPase and H-K-ATPase into the lumen and bicarbonate is absorbed via basolateral Cl⁻/HCO₃⁻ exchangers (1–4). The tubules, which are located within the outer medullary region of the kidney collecting duct (OMCD),² have the highest rate of acid secretion among the distal tubule segments and are therefore essential to the maintenance of acid base balance (2).The gastric parietal cell is the site of generation of acid and bicarbonate through the action of cytosolic carbonic anhydrase II (5, 6). The intracellular acid is secreted into the lumen via gastric H-K-ATPase, which works in conjunction with a chloride channel and a K⁺ recycling pathway (7–10). The intracellular bicarbonate is transported to the blood via basolateral Cl⁻/HCO₃⁻ exchangers (11–14).SLC26 (human)/Slc26 (mouse) isoforms are members of a conserved family of anion transporters that display tissue-specific patterns of expression in epithelial cells (15–24). Several SLC26 members can function as chloride/bicarbonate exchangers. These include SLC26A3 (DRA), SLC26A4 (pendrin), SLC26A6 (PAT1 or CFEX), SLC26A7, and SLC26A9 (25–31). SLC26A7 and SLC26A9 can also function as chloride channels (32–34).SLC26A7/Slc26a7 is predominantly expressed in the kidney and stomach (28, 29). In the kidney, Slc26a7 co-localizes with AE1, a well-known Cl⁻/HCO₃⁻ exchanger, on the basolateral membrane of (acid-secreting) A-intercalated cells in OMCD cells (29, 35, 36) (supplemental Fig. 1). In the stomach, Slc26a7 co-localizes with AE2, a major Cl⁻/HCO₃⁻ exchanger, on the basolateral membrane of acid secreting parietal cells (28). To address the physiological function of Slc26a7 in the intact mouse, we have generated Slc26a7 ko mice. We report here that Slc26a7 ko mice exhibit distal renal tubular acidosis and impaired gastric acidification in the absence of morphological abnormalities in kidney or stomach.