Isolation and characterization of the full-length cDNA encoding a member of a novel cytochrome p450 family (CYP320A1) from the tropical freshwater snail, Biomphalaria glabrata, intermediate host for Schistosoma mansoni

Cytochrome p450s (cyp450s) are a family of structurally related proteins, with diverse functions, including steroid synthesis and breakdown of toxins. This paper reports the full-length sequence of a novel cyp450 gene, the first to be isolated from the tropical freshwater snail Biomphalaria glabrata, an important intermediate host of Schistosoma mansoni. The nucleotide sequence is 2291 bp with a predicted amino acid sequence of 584aa. The sequence demonstrates conserved cyp450 structural motifs, but is sufficiently different from previously reported cyp450 sequences to be given a new classification, CYP320A1. Initially identified as down-regulated in partially resistant snails in response to S. mansoni infection, amplification of this gene using RT-PCR in both totally resistant or susceptible snail lines when exposed to infection, and all tissues examined, suggests ubiquitous expression. Characterization of the first cyp450 from B. glabrata is significant in understanding the evolution of these metabolically important proteins

Rotated balance in humans due to repetitive rotational movement

We show how asymmetries in the movement patterns during the process of regaining balance after perturbation from quiet stance can be modeled by a set of coupled vector fields for the derivative with respect to time of the angles between the resultant ground reaction forces and the vertical in the anteroposterior and mediolateral directions. In our model, which is an adaption of the model of Stirling and Zakynthinaki (2004), the critical curve, defining the set of maximum angles one can lean to and still correct to regain balance, can be rotated and skewed so as to model the effects of a repetitive training of a rotational movement pattern. For the purposes of our study a rotation and a skew matrix is applied to the critical curve of the model. We present here a linear stability analysis of the modified model, as well as a fit of the model to experimental data of two characteristic “asymmetric” elite athletes and to a “symmetric” elite athlete for comparison. The new adapted model has many uses not just in sport but also in rehabilitation, as many work place injuries are caused by excessive repetition of unaligned and rotational movement patterns

Solving the random diffusion model in an infinite medium: A mean square approach

[EN] This paper deals with the construction of an analytic-numerical mean square solution of the random diffusion model in an infinite medium. The well-known Fourier transform method, which is used to solve this problem in the deterministic case, is extended to the random framework. Mean square operational rules to the Fourier transform of a stochastic process are developed and stated. The main statistical moments of the stochastic process solution are also computed. Finally, some illustrative numerical examples are included.This work has been partially supported by the Ministerio de Economia y Competitividad grant: DPI2010-20891-c0-01, and Universitat Politecnica de Valencia grant: PAID06-11-2070.Casabán, M.; Company Rossi, R.; Cortés, J.; Jódar Sánchez, LA. (2014). Solving the random diffusion model in an infinite medium: A mean square approach. Applied Mathematical Modelling. 38(24):5922-5933. https://doi.org/10.1016/j.apm.2014.04.063S59225933382

Considering scores between unrelated proteins in the search database improves profile comparison

<p>Abstract</p> <p>Background</p> <p>Profile-based comparison of multiple sequence alignments is a powerful methodology for the detection remote protein sequence similarity, which is essential for the inference and analysis of protein structure, function, and evolution. Accurate estimation of statistical significance of detected profile similarities is essential for further development of this methodology. Here we analyze a novel approach to estimate the statistical significance of profile similarity: the explicit consideration of background score distributions for each database template (subject).</p> <p>Results</p> <p>Using a simple scheme to combine and analytically approximate query- and subject-based distributions, we show that (i) inclusion of background distributions for the subjects increases the quality of homology detection; (ii) this increase is higher when the distributions are based on the scores to all known non-homologs of the subject rather than a small calibration subset of the database representatives; and (iii) these all known non-homolog distributions of scores for the subject make the dominant contribution to the improved performance: adding the calibration distribution of the query has a negligible additional effect.</p> <p>Conclusion</p> <p>The construction of distributions based on the complete sets of non-homologs for each subject is particularly relevant in the setting of structure prediction where the database consists of proteins with solved 3D structure (PDB, SCOP, CATH, etc.) and therefore structural relationships between proteins are known. These results point to a potential new direction in the development of more powerful methods for remote homology detection.</p

A framework for protein structure classification and identification of novel protein structures

BACKGROUND: Protein structure classification plays a central role in understanding the function of a protein molecule with respect to all known proteins in a structure database. With the rapid increase in the number of new protein structures, the need for automated and accurate methods for protein classification is increasingly important. RESULTS: In this paper we present a unified framework for protein structure classification and identification of novel protein structures. The framework consists of a set of components for comparing, classifying, and clustering protein structures. These components allow us to accurately classify proteins into known folds, to detect new protein folds, and to provide a way of clustering the new folds. In our evaluation with SCOP 1.69, our method correctly classifies 86.0%, 87.7%, and 90.5% of new domains at family, superfamily, and fold levels. Furthermore, for protein domains that belong to new domain families, our method is able to produce clusters that closely correspond to the new families in SCOP 1.69. As a result, our method can also be used to suggest new classification groups that contain novel folds. CONCLUSION: We have developed a method called proCC for automatically classifying and clustering domains. The method is effective in classifying new domains and suggesting new domain families, and it is also very efficient. A web site offering access to proCC is freely available a

Improving model construction of profile HMMs for remote homology detection through structural alignment

<p>Abstract</p> <p>Background</p> <p>Remote homology detection is a challenging problem in Bioinformatics. Arguably, profile Hidden Markov Models (pHMMs) are one of the most successful approaches in addressing this important problem. pHMM packages present a relatively small computational cost, and perform particularly well at recognizing remote homologies. This raises the question of whether structural alignments could impact the performance of pHMMs trained from proteins in the <it>Twilight Zone</it>, as structural alignments are often more accurate than sequence alignments at identifying motifs and functional residues. Next, we assess the impact of using structural alignments in pHMM performance.</p> <p>Results</p> <p>We used the SCOP database to perform our experiments. Structural alignments were obtained using the 3DCOFFEE and MAMMOTH-mult tools; sequence alignments were obtained using CLUSTALW, TCOFFEE, MAFFT and PROBCONS. We performed leave-one-family-out cross-validation over super-families. Performance was evaluated through ROC curves and paired two tailed t-test.</p> <p>Conclusion</p> <p>We observed that pHMMs derived from structural alignments performed significantly better than pHMMs derived from sequence alignment in low-identity regions, mainly below 20%. We believe this is because structural alignment tools are better at focusing on the important patterns that are more often conserved through evolution, resulting in higher quality pHMMs. On the other hand, sensitivity of these tools is still quite low for these low-identity regions. Our results suggest a number of possible directions for improvements in this area.</p

Subcellular localization and tissue specific expression of amidase 1 from Arabidopsis thaliana

Amidase 1 (AMI1) from Arabidopsis thaliana converts indole-3-acetamide (IAM), into indole-3-acetic acid (IAA). AMI1 is part of a small isogene family comprising seven members in A. thaliana encoding proteins which share a conserved glycine- and serine-rich amidase-signature. One member of this family has been characterized as an N-acylethanolamine-cleaving fatty acid amidohydrolase (FAAH) and two other members are part of the preprotein translocon of the outer envelope of chloroplasts (Toc complex) or mitochondria (Tom complex) and presumably lack enzymatic activity. Among the hitherto characterized proteins of this family, AMI1 is the only member with indole-3-acetamide hydrolase activity, and IAM is the preferred substrate while N-acylethanolamines and oleamide are not hydrolyzed significantly, thus suggesting a role of AMI1 in auxin biosynthesis. Whereas the enzymatic function of AMI1 has been determined in vitro, the subcellular localization of the enzyme remained unclear. By using different GFP-fusion constructs and an A. thaliana transient expression system, we show a cytoplasmic localization of AMI1. In addition, RT-PCR and anti-amidase antisera were used to examine tissue specific expression of AMI1 at the transcriptional and translational level, respectively. AMI1-expression is strongest in places of highest IAA content in the plant. Thus, it is concluded that AMI1 may be involved in de novo IAA synthesis in A. thaliana

Applicant perspectives during selection

We provide a comprehensive but critical review of research on applicant reactions to selection procedures published since 2000 (n = 145), when the last major review article on applicant reactions appeared in the Journal of Management. We start by addressing the main criticisms levied against the field to determine whether applicant reactions matter to individuals and employers (“So what?”). This is followed by a consideration of “What’s new?” by conducting a comprehensive and detailed review of applicant reaction research centered upon four areas of growth: expansion of the theoretical lens, incorporation of new technology in the selection arena, internationalization of applicant reactions research, and emerging boundary conditions. Our final section focuses on “Where to next?” and offers an updated and integrated conceptual model of applicant reactions, four key challenges, and eight specific future research questions. Our conclusion is that the field demonstrates stronger research designs, with studies incorporating greater control, broader constructs, and multiple time points. There is also solid evidence that applicant reactions have significant and meaningful effects on attitudes, intentions, and behaviors. At the same time, we identify some remaining gaps in the literature and a number of critical questions that remain to be explored, particularly in light of technological and societal changes

Gene fusions and gene duplications: relevance to genomic annotation and functional analysis

BACKGROUND: Escherichia coli a model organism provides information for annotation of other genomes. Our analysis of its genome has shown that proteins encoded by fused genes need special attention. Such composite (multimodular) proteins consist of two or more components (modules) encoding distinct functions. Multimodular proteins have been found to complicate both annotation and generation of sequence similar groups. Previous work overstated the number of multimodular proteins in E. coli. This work corrects the identification of modules by including sequence information from proteins in 50 sequenced microbial genomes. RESULTS: Multimodular E. coli K-12 proteins were identified from sequence similarities between their component modules and non-fused proteins in 50 genomes and from the literature. We found 109 multimodular proteins in E. coli containing either two or three modules. Most modules had standalone sequence relatives in other genomes. The separated modules together with all the single (un-fused) proteins constitute the sum of all unimodular proteins of E. coli. Pairwise sequence relationships among all E. coli unimodular proteins generated 490 sequence similar, paralogous groups. Groups ranged in size from 92 to 2 members and had varying degrees of relatedness among their members. Some E. coli enzyme groups were compared to homologs in other bacterial genomes. CONCLUSION: The deleterious effects of multimodular proteins on annotation and on the formation of groups of paralogs are emphasized. To improve annotation results, all multimodular proteins in an organism should be detected and when known each function should be connected with its location in the sequence of the protein. When transferring functions by sequence similarity, alignment locations must be noted, particularly when alignments cover only part of the sequences, in order to enable transfer of the correct function. Separating multimodular proteins into module units makes it possible to generate protein groups related by both sequence and function, avoiding mixing of unrelated sequences. Organisms differ in sizes of groups of sequence-related proteins. A sample comparison of orthologs to selected E. coli paralogous groups correlates with known physiological and taxonomic relationships between the organisms