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]     

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]     

Sip1, a Novel RS Domain-Containing Protein Essential for Pre-mRNA Splicing

Previous studies have shown that protein-protein interactions among splicing factors may play an important role in pre-mRNA splicing. We report here identification and functional characterization of a new splicing factor, Sip1 (SC35-interacting protein 1). Sip1 was initially identified by virtue of its interaction with SC35, a splicing factor of the SR family. Sip1 interacts with not only several SR proteins but also with U1-70K and U2AF65, proteins associated with 5′ and 3′ splice sites, respectively. The predicted Sip1 sequence contains an arginine-serine-rich (RS) domain but does not have any known RNA-binding motifs, indicating that it is not a member of the SR family. Sip1 also contains a region with weak sequence similarity to the Drosophila splicing regulator suppressor of white apricot (SWAP). An essential role for Sip1 in pre-mRNA splicing was suggested by the observation that anti-Sip1 antibodies depleted splicing activity from HeLa nuclear extract. Purified recombinant Sip1 protein, but not other RS domain-containing proteins such as SC35, ASF/SF2, and U2AF65, restored the splicing activity of the Sip1-immunodepleted extract. Addition of U2AF65 protein further enhanced the splicing reconstitution by the Sip1 protein. Deficiency in the formation of both A and B splicing complexes in the Sip1-depleted nuclear extract indicates an important role of Sip1 in spliceosome assembly. Together, these results demonstrate that Sip1 is a novel RS domain-containing protein required for pre-mRNA splicing and that the functional role of Sip1 in splicing is distinct from those of known RS domain-containing splicing factors.Pre-mRNA splicing takes place in spliceosomes, the large RNA-protein complexes containing pre-mRNA, U1, U2, U4/6, and U5 small nuclear ribonucleoprotein particles (snRNPs), and a large number of accessory protein factors (for reviews, see references 21, 22, 37, 44, and 48). It is increasingly clear that the protein factors are important for pre-mRNA splicing and that studies of these factors are essential for further understanding of molecular mechanisms of pre-mRNA splicing.Most mammalian splicing factors have been identified by biochemical fractionation and purification (3, 15, 19, 31–36, 45, 69–71, 73), by using antibodies recognizing splicing factors (8, 9, 16, 17, 61, 66, 67, 74), and by sequence homology (25, 52, 74).Splicing factors containing arginine-serine-rich (RS) domains have emerged as important players in pre-mRNA splicing. These include members of the SR family, both subunits of U2 auxiliary factor (U2AF), and the U1 snRNP protein U1-70K (for reviews, see references 18, 41, and 59). Drosophila alternative splicing regulators transformer (Tra), transformer 2 (Tra2), and suppressor of white apricot (SWAP) also contain RS domains (20, 40, 42). RS domains in these proteins play important roles in pre-mRNA splicing (7, 71, 75), in nuclear localization of these splicing proteins (23, 40), and in protein-RNA interactions (56, 60, 64). Previous studies by us and others have demonstrated that one mechanism whereby SR proteins function in splicing is to mediate specific protein-protein interactions among spliceosomal components and between general splicing factors and alternative splicing regulators (1, 1a, 6, 10, 27, 63, 74, 77). Such protein-protein interactions may play critical roles in splice site recognition and association (for reviews, see references 4, 18, 37, 41, 47 and 59). Specific interactions among the splicing factors also suggest that it is possible to identify new splicing factors by their interactions with known splicing factors.Here we report identification of a new splicing factor, Sip1, by its interaction with the essential splicing factor SC35. The predicted Sip1 protein sequence contains an RS domain and a region with sequence similarity to the Drosophila splicing regulator, SWAP. We have expressed and purified recombinant Sip1 protein and raised polyclonal antibodies against the recombinant Sip1 protein. The anti-Sip1 antibodies specifically recognize a protein migrating at a molecular mass of approximately 210 kDa in HeLa nuclear extract. The anti-Sip1 antibodies sufficiently deplete Sip1 protein from the nuclear extract, and the Sip1-depleted extract is inactive in pre-mRNA splicing. Addition of recombinant Sip1 protein can partially restore splicing activity to the Sip1-depleted nuclear extract, indicating an essential role of Sip1 in pre-mRNA splicing. Other RS domain-containing proteins, including SC35, ASF/SF2, and U2AF65, cannot substitute for Sip1 in reconstituting splicing activity of the Sip1-depleted nuclear extract. However, addition of U2AF65 further increases splicing activity of Sip1-reconstituted nuclear extract, suggesting that there may be a functional interaction between Sip1 and U2AF65 in nuclear extract.     

Biochemical Characterization of the C4-Dicarboxylate Transporter DctA from Bacillus subtilis

Bacterial secondary transporters of the DctA family mediate ion-coupled uptake of C₄-dicarboxylates. Here, we have expressed the DctA homologue from Bacillus subtilis in the Gram-positive bacterium Lactococcus lactis. Transport of dicarboxylates in vitro in isolated membrane vesicles was assayed. We determined the substrate specificity, the type of cotransported ions, the electrogenic nature of transport, and the pH and temperature dependence patterns. DctA was found to catalyze proton-coupled symport of the four C₄-dicarboxylates from the Krebs cycle (succinate, fumurate, malate, and oxaloacetate) but not of other mono- and dicarboxylates. Because (i) succinate-proton symport was electrogenic (stimulated by an internal negative membrane potential) and (ii) the divalent anionic form of succinate was recognized by DctA, at least three protons must be cotransported with succinate. The results were interpreted in the light of the crystal structure of the homologous aspartate transporter Glt_Ph from Pyrococcus horikoshii.The DctA family is one of several diverse families of secondary transporters that catalyze the uptake of C₄-dicarboxylates from the Krebs cycle in bacteria (16, 27). In Escherichia coli, DctA mediates the uptake of succinate, fumurate, and malate under aerobic conditions; genomic disruption of dctA in E. coli prevents growth with malate or fumarate as the sole carbon source, and the mutant grows poorly on succinate (5). Similarly, a dctA knockout mutant of Bacillus subtilis cannot grow with succinate or fumarate as the sole carbon source (1). DctA plays a major role in the symbiotic relationship between nitrogen-fixing rhizobia (43) and root nodule-forming plants (30, 37, 38). Transport assays with Sinorhizobium meliloti cells showed previously that in addition to succinate, malate, and fumarate, orotate is transported and that a range of other substrates such as succinamic acid and succinamide may be transported, because they inhibit the transport of orotate (42). In Corynebacterium glutamicum, malate transport by DctA is inhibited by α-ketoglutarate, oxaloacetate, and glyoxylate, indicating that these compounds may be substrates also (41).DctA transporters belong to a large family of secondary transporters (the DAACS [dicarboxylate/amino acid:cation symporter] family), which also comprises well-characterized glutamate/aspartate transporters and neutral amino acid transporters (32, 33). While DctA-type dicarboxylate transporters are found only in bacteria, glutamate/aspartate transporters of the DAACS family are found both in prokaryotes (e.g., GltT in Bacillus stearothermophilus, GltP in E. coli, and Glt_Ph in Pyrococcus horikoshii [2, 7, 34]) and in higher eukarya, where they play a pivotal role in the reuptake of the excitatory neurotransmitter glutamate from the synaptic cleft (4). Neutral amino acid (alanine, serine, and threonine) transporters are found in mammals (see, e.g., references 36 and 44) as well as bacteria (17).Secondary transporters of the DAACS family use (electro)chemical gradients of cations across the membrane to drive transport. The type of cotransported ions varies among family members: eukaryotic glutamate transporters couple the transport of glutamate to the symport of one proton and three sodium ions and the antiport of one potassium ion (24, 45). Bacterial and archaeal glutamate transporters utilize either sodium ions or protons for symport (2) and are independent of potassium ions (28, 31). The bacterial and mammalian neutral amino acid transporters are sodium ion coupled. Glutamate/aspartate transporters and bacterial serine/threonine transporters (SstTs) are electrogenic, but mammalian neutral amino acid transporters are obligate electroneutral amino acid antiporters (44).Insight into the structure-function relationships of the DAACS family members has greatly increased since crystal structures of the P. horikoshii aspartate transporter Glt_Ph have been determined (2, 29, 40). The protein consists of eight membrane-spanning helices and two reentrant regions (helical hairpins HP1 and HP2) (40). The C-terminal part of the protein (helices 7 and 8 and HP1 and HP2) is most strongly conserved with respect to other family members and binds the substrate and cotransported ions, with HP1 and HP2 functioning as lids that allow alternating access to the substrate- and ion-binding sites from either side of the membrane (3, 29). Glt_Ph forms a homotrimeric complex in which each protomer functions independently of the other subunits (11, 12, 18, 19, 23). The fold and oligomeric state are likely to be conserved throughout the family.Whereas the transport mechanisms of bacterial glutamate and neutral amino acid transporters of the DAACS family have been studied extensively in vitro, the C₄-dicarboxylate transporters of the DAACS family (DctA proteins) have been studied using whole cells only. To fully characterize these transporters, in vitro activity assays using either membrane vesicles or proteoliposomes containing purified protein are necessary. In such assays, the internal and external buffer compositions can be controlled, thus allowing manipulation of the chemical ion gradients and the electrical potential across the membrane. Here, we present the first biochemical characterization of a DctA family member in membrane vesicles. We have studied the DctA homologue from B. subtilis, which is annotated as DctP (1) but which we propose to rename DctA to reflect the homology to other DctA proteins. B. subtilis DctA (DctA_Bs) has 30 to 32% sequence identity to the aspartate transporter Glt_Ph and human excitatory amino acid transporter (EAAT) family members, over 40% sequence identity to the characterized bacterial glutamate transporters from E. coli and B. stearothermophilus, and 41 and 56% identity to DctA homologues from C. glutamicum and E. coli, respectively. We determined the substrate specificity of DctA_Bs, the type of cotransported ions, the electrogenic nature of transport, and the pH and temperature dependence patterns.