Prediction of protein subcellular localization by support vector machines using multi-scale energy and pseudo amino acid composition

As more and more genomes have been discovered in recent years, there is an urgent need to develop a reliable method to predict the subcellular localization for the explosion of newly found proteins. However, many well-known prediction methods based on amino acid composition have problems utilizing the sequence-order information. Here, based on the concept of Chou's pseudo amino acid composition (PseAA), a new feature extraction method, the multi-scale energy (MSE) approach, is introduced to incorporate the sequence-order information. First, a protein sequence was mapped to a digital signal using the amino acid index. Then, by wavelet transform, the mapped signal was broken down into several scales in which the energy factors were calculated and further formed into an MSE feature vector. Following this, combining this MSE feature vector with amino acid composition (AA), we constructed a series of MSEPseAA feature vectors to represent the protein subcellular localization sequences. Finally, according to a new kind of normalization approach, the MSEPseAA feature vectors were normalized to form the improved MSEPseAA vectors, named as IEPseAA. Using the technique of IEPseAA, C-support vector machine (C-SVM) and three multi-class SVMs strategies, quite promising results were obtained, indicating that MSE is quite effective in reflecting the sequence-order effects and might become a useful tool for predicting the other attributes of proteins as well.     

<Emphasis Type="Italic">Hau-Pax6A</Emphasis> expression in the central nervous system of the leech embryo

The leech Helobdella sp. (Austin) has two genes of the Pax6 subfamily, one of which is characterized in detail. Hau-Pax6A was expressed during embryonic development in a pattern similar to other bilaterian animals. RNA was detected in cellular precursors of the central nervous system (CNS) and in peripheral cells including a population associated with the developing eye. The CNS of the mature leech is a ventral nerve cord composed of segmental ganglia, and embryonic Hau-Pax6A expression was primarily localized to the N teloblast lineage that generates the majority of ganglionic neurons. Expression began when the ganglion primordia were four cells in length and was initially restricted to a single cell, n_s.a, whose descendants will form the ganglion’s anterior edge. At later stages, the Hau-Pax6A expression pattern expanded to include additional CNS precursors, including some descendants of the O teloblast. Expression persisted through the early stages of ganglion morphogenesis but disappeared from the segmented body trunk at the time of neuronal differentiation. The timing and iterated pattern of Hau-Pax6A expression in the leech embryo suggests that this gene may play a role in the segmental patterning of CNS morphogenesis.     

TagSmart: analysis and visualization for yeast mutant fitness data measured by tag microarrays

Background  

A nearly complete collection of gene-deletion mutants (96% of annotated open reading frames) of the yeast Saccharomyces cerevisiae has been systematically constructed. Tag microarrays are widely used to measure the fitness of each mutant in a mutant mixture. The tag array experiments can have a complex experimental design, such as time course measurements and drug treatment with multiple dosages.     

Generation of a transgenic mouse model with chondrocyte-specific and tamoxifen-inducible expression of Cre recombinase

Postnatal cartilage development and growth are regulated by key growth factors and signaling molecules. To fully understand the function of these regulators, an inducible and chondrocyte-specific gene deletion system needs to be established to circumvent the perinatal lethality. In this report, we have generated a transgenic mouse model (Col2a1-CreER(T2)) in which expression of the Cre recombinase is driven by the chondrocyte-specific col2a1 promoter in a tamoxifen-inducible manner. To determine the specificity and efficiency of the Cre recombination, we have bred Col2a1-CreER(T2) mice with Rosa26R reporter mice. The X-Gal staining showed that the Cre recombination is specifically achieved in cartilage tissues with tamoxifen-induction. In vitro experiments of chondrocyte cell culture also demonstrate the 4-hydroxy tamoxifen-induced Cre recombination. These results demonstrate that Col2a1-CreER(T2) transgenic mice can be used as a valuable tool for an inducible and chondrocyte-specific gene deletion approach.     

Enhanced Photodegradation of PNP on Soil Surface under UV Irradiation with TiO2

Photodegradation of p-nitrophenol (PNP) on soil surface was investigated to explore the photochemical remediation of soil polluted by nitrophenols. Soil samples spiked with PNP were irradiated by UV light with and without the addition of TiO ₂ . The addition of 0.5–2 wt% TiO ₂ enhanced PNP photodegradation with approximately 1.36 times increase in apparent rate of PNP disappearance. Soil moisture, humic acid and soil pH were important factors influencing the rate of PNP photodegradation. Increase in soil moisture improved the degradation significantly, whereas humic acid reduced the degradation rate. Changes in soil pH resulted in different degradation rates, and higher degradation efficiencies were observed under alkaline condition.     

Functional anthology of intrinsic disorder. 3. Ligands, post-translational modifications, and diseases associated with intrinsically disordered proteins

Currently, the understanding of the relationships between function, amino acid sequence, and protein structure continues to represent one of the major challenges of the modern protein science. As many as 50% of eukaryotic proteins are likely to contain functionally important long disordered regions. Many proteins are wholly disordered but still possess numerous biologically important functions. However, the number of experimentally confirmed disordered proteins with known biological functions is substantially smaller than their actual number in nature. Therefore, there is a crucial need for novel bionformatics approaches that allow projection of the current knowledge from a few experimentally verified examples to much larger groups of known and potential proteins. The elaboration of a bioinformatics tool for the analysis of functional diversity of intrinsically disordered proteins and application of this data mining tool to >200 000 proteins from the Swiss-Prot database, each annotated with at least one of the 875 functional keywords, was described in the first paper of this series (Xie, H.; Vucetic, S.; Iakoucheva, L. M.; Oldfield, C. J.; Dunker, A. K.; Obradovic, Z.; Uversky, V.N. Functional anthology of intrinsic disorder. 1. Biological processes and functions of proteins with long disordered regions. J. Proteome Res. 2007, 5, 1882-1898). Using this tool, we have found that out of the 710 Swiss-Prot functional keywords associated with at least 20 proteins, 262 were strongly positively correlated with long intrinsically disordered regions, and 302 were strongly negatively correlated. Illustrative examples of functional disorder or order were found for the vast majority of keywords showing strongest positive or negative correlation with intrinsic disorder, respectively. Some 80 Swiss-Prot keywords associated with disorder- and order-driven biological processes and protein functions were described in the first paper (see above). The second paper of the series was devoted to the presentation of 87 Swiss-Prot keywords attributed to the cellular components, domains, technical terms, developmental processes, and coding sequence diversities possessing strong positive and negative correlation with long disordered regions (Vucetic, S.; Xie, H.; Iakoucheva, L. M.; Oldfield, C. J.; Dunker, A. K.; Obradovic, Z.; Uversky, V. N. Functional anthology of intrinsic disorder. 2. Cellular components, domains, technical terms, developmental processes, and coding sequence diversities correlated with long disordered regions. J. Proteome Res. 2007, 5, 1899-1916). Protein structure and functionality can be modulated by various post-translational modifications or/and as a result of binding of specific ligands. Numerous human diseases are associated with protein misfolding/misassembly/misfunctioning. This work concludes the series of papers dedicated to the functional anthology of intrinsic disorder and describes approximately 80 Swiss-Prot functional keywords that are related to ligands, post-translational modifications, and diseases possessing strong positive or negative correlation with the predicted long disordered regions in proteins.     

Description of two nitrogen-fixing bacteria,Geomonas fuzhouensis sp. nov. and Geomonas agri sp. nov., isolated from paddy soils

Two strictly anaerobic nitrogen-fixing strains, designated RG17^T and RG53^T, were isolated from paddy soils in China. Strains RG17^T and RG53^T showed the highest 16S rRNA gene sequence similarities to the type strain Geomonas paludis (97.9–98.4%). Phylogenetic tree based on 16S rRNA gene sequences showed that two strains clustered with members of the genus Geomonas. Growth of strain RG17^T was observed at 20–42 °C, pH 5.5–8.5 and 0–0.3% (w/v) NaCl while strain RG53^T growth was observed at 20–42 °C, pH 5.5–9.5 and 0–0.7% (w/v) NaCl. Strains RG17^T and RG53^T contained MK-8 as main menaquinone and C_15:1 ω6c, iso-C_15:0, and Summed Feature 3 as the major fatty acids. The genomic DNA G?+?C content of strains RG17^T and RG53^T were 61.6 and 60.7%, respectively. The digital DNA–DNA hybridization (dDDH) and average nucleotide identity (ANI) values between the isolated strains and the closely related Geomonas species were lower than the cut-off value (dDDH 70% and ANI 95–96%) for prokaryotic species delineation. Both strains possessed nif genes nifHDK and nitrogenase activities. Based on the above results, the two strains represent two novel species of the genus Geomonas, for which the names Geomonas fuzhouensis sp. nov. and Geomonas agri sp. nov., are proposed. The type strains are RG17^T (=?GDMCC 1.2687^T?=?KTCC 25332^T) and RG53^T (=?GDMCC 1.2630^T?=?KCTC 25331^T), respectively.