Middle Convolution and Harnad Duality

We interpret the additive middle convolution operation in terms of the Harnad duality, and as an application, generalize the operation to have a multi-parameter and act on irregular singular systems.Comment: 50 pages; v2: Submitted version once revised according to referees' comment

System engineering toolbox for design-oriented engineers

This system engineering toolbox is designed to provide tools and methodologies to the design-oriented systems engineer. A tool is defined as a set of procedures to accomplish a specific function. A methodology is defined as a collection of tools, rules, and postulates to accomplish a purpose. For each concept addressed in the toolbox, the following information is provided: (1) description, (2) application, (3) procedures, (4) examples, if practical, (5) advantages, (6) limitations, and (7) bibliography and/or references. The scope of the document includes concept development tools, system safety and reliability tools, design-related analytical tools, graphical data interpretation tools, a brief description of common statistical tools and methodologies, so-called total quality management tools, and trend analysis tools. Both relationship to project phase and primary functional usage of the tools are also delineated. The toolbox also includes a case study for illustrative purposes. Fifty-five tools are delineated in the text

A pentapeptide as minimal antigenic determinant for MHC class I-restricted T lymphocytes

Peptides that are antigenic for T lymphocytes are ligands for two receptors, the class I or II glycoproteins that are encoded by genes in the major histocompatibility complex, and the idiotypic / chain T-cell antigen receptor1–9. That a peptide must bind to an MHC molecule to interact with a T-cell antigen receptor is the molecular basis of the MHC restriction of antigen-recognition by T lymphocytes10,11. In such a trimolecular interaction the amino-acid sequence of the peptide must specify the contact with both receptors: agretope residues bind to the MHC receptor and epitope residues bind to the T-cell antigen receptor12,13. From a compilation of known antigenic peptides, two algorithms have been proposed to predict antigenic sites in proteins. One algorithm uses linear motifs in the sequence14, whereas the other considers peptide conformation and predicts antigenicity for amphipathic -helices15,16. We report here that a systematic delimitation of an antigenic site precisely identifies a predicted pentapeptide motif as the minimal antigenic determinant presented by a class I MHC molecule and recognized by a cytolytic T lymphocyte clone

A Conditional Yeast E1 Mutant Blocks the Ubiquitin–Proteasome Pathway and Reveals a Role for Ubiquitin Conjugates in Targeting Rad23 to the Proteasome

E1 ubiquitin activating enzyme catalyzes the initial step in all ubiquitin-dependent processes. We report the isolation of uba1-204, a temperature-sensitive allele of the essential Saccharomyces cerevisiae E1 gene, UBA1. Uba1-204 cells exhibit dramatic inhibition of the ubiquitin–proteasome system, resulting in rapid depletion of cellular ubiquitin conjugates and stabilization of multiple substrates. We have employed the tight phenotype of this mutant to investigate the role ubiquitin conjugates play in the dynamic interaction of the UbL/UBA adaptor proteins Rad23 and Dsk2 with the proteasome. Although proteasomes purified from mutant cells are intact and proteolytically active, they are depleted of ubiquitin conjugates, Rad23, and Dsk2. Binding of Rad23 to these proteasomes in vitro is enhanced by addition of either free or substrate-linked ubiquitin chains. Moreover, association of Rad23 with proteasomes in mutant and wild-type cells is improved upon stabilizing ubiquitin conjugates with proteasome inhibitor. We propose that recognition of polyubiquitin chains by Rad23 promotes its shuttling to the proteasome in vivo

Using Sequence Similarity Networks for Visualization of Relationships Across Diverse Protein Superfamilies

The dramatic increase in heterogeneous types of biological data—in particular, the abundance of new protein sequences—requires fast and user-friendly methods for organizing this information in a way that enables functional inference. The most widely used strategy to link sequence or structure to function, homology-based function prediction, relies on the fundamental assumption that sequence or structural similarity implies functional similarity. New tools that extend this approach are still urgently needed to associate sequence data with biological information in ways that accommodate the real complexity of the problem, while being accessible to experimental as well as computational biologists. To address this, we have examined the application of sequence similarity networks for visualizing functional trends across protein superfamilies from the context of sequence similarity. Using three large groups of homologous proteins of varying types of structural and functional diversity—GPCRs and kinases from humans, and the crotonase superfamily of enzymes—we show that overlaying networks with orthogonal information is a powerful approach for observing functional themes and revealing outliers. In comparison to other primary methods, networks provide both a good representation of group-wise sequence similarity relationships and a strong visual and quantitative correlation with phylogenetic trees, while enabling analysis and visualization of much larger sets of sequences than trees or multiple sequence alignments can easily accommodate. We also define important limitations and caveats in the application of these networks. As a broadly accessible and effective tool for the exploration of protein superfamilies, sequence similarity networks show great potential for generating testable hypotheses about protein structure-function relationships

A Genome-Wide Study of DNA Methylation Patterns and Gene Expression Levels in Multiple Human and Chimpanzee Tissues

The modification of DNA by methylation is an important epigenetic mechanism that affects the spatial and temporal regulation of gene expression. Methylation patterns have been described in many contexts within and across a range of species. However, the extent to which changes in methylation might underlie inter-species differences in gene regulation, in particular between humans and other primates, has not yet been studied. To this end, we studied DNA methylation patterns in livers, hearts, and kidneys from multiple humans and chimpanzees, using tissue samples for which genome-wide gene expression data were also available. Using the multi-species gene expression and methylation data for 7,723 genes, we were able to study the role of promoter DNA methylation in the evolution of gene regulation across tissues and species. We found that inter-tissue methylation patterns are often conserved between humans and chimpanzees. However, we also found a large number of gene expression differences between species that might be explained, at least in part, by corresponding differences in methylation levels. In particular, we estimate that, in the tissues we studied, inter-species differences in promoter methylation might underlie as much as 12%–18% of differences in gene expression levels between humans and chimpanzees

Evaluating the Benefits of Aphasia Intervention Delivered in Virtual Reality: Results of a Quasi-Randomised Study

Introduction This study evaluated an intervention for people with aphasia delivered in a novel virtual reality platform called EVA Park. EVA Park contains a number of functional and fantastic locations and allows for interactive communication between multiple users. Twenty people with aphasia had 5 weeks’ intervention, during which they received daily language stimulation sessions in EVA Park from a support worker. The study employed a quasi randomised design, which compared a group that received immediate intervention with a waitlist control group. Outcome measures explored the effects of intervention on communication and language skills, communicative confidence and feelings of social isolation. Compliance with the intervention was also explored through attrition and usage data. Results There was excellent compliance with the intervention, with no participants lost to follow up and most (18/20) receiving at least 88% of the intended treatment dose. Intervention brought about significant gains on a measure of functional communication. Gains were achieved by both groups of participants, once intervention was received, and were well maintained. Changes on the measures of communicative confidence and feelings of social isolation were not achieved. Results are discussed with reference to previous aphasia therapy findings

Target selection and annotation for the structural genomics of the amidohydrolase and enolase superfamilies

To study the substrate specificity of enzymes, we use the amidohydrolase and enolase superfamilies as model systems; members of these superfamilies share a common TIM barrel fold and catalyze a wide range of chemical reactions. Here, we describe a collaboration between the Enzyme Specificity Consortium (ENSPEC) and the New York SGX Research Center for Structural Genomics (NYSGXRC) that aims to maximize the structural coverage of the amidohydrolase and enolase superfamilies. Using sequence- and structure-based protein comparisons, we first selected 535 target proteins from a variety of genomes for high-throughput structure determination by X-ray crystallography; 63 of these targets were not previously annotated as superfamily members. To date, 20 unique amidohydrolase and 41 unique enolase structures have been determined, increasing the fraction of sequences in the two superfamilies that can be modeled based on at least 30% sequence identity from 45% to 73%. We present case studies of proteins related to uronate isomerase (an amidohydrolase superfamily member) and mandelate racemase (an enolase superfamily member), to illustrate how this structure-focused approach can be used to generate hypotheses about sequence–structure–function relationships

A Selection Index for Gene Expression Evolution and Its Application to the Divergence between Humans and Chimpanzees

The importance of gene regulation in animal evolution is a matter of long-standing interest, but measuring the impact of selection on gene expression has proven a challenge. Here, we propose a selection index of gene expression as a straightforward method for assessing the mode and strength of selection operating on gene expression levels. The index is based on the widely used McDonald-Kreitman test and requires the estimation of four quantities: the within-species and between-species expression variances as well as the sequence heterozygosity and divergence of neutrally evolving sequences. We apply the method to data from human and chimpanzee lymphoblastoid cell lines and show that gene expression is in general under strong stabilizing selection. We also demonstrate how the same framework can be used to estimate the proportion of adaptive gene expression evolution