Multiple structural alignment for distantly related all b structures using TOPS pattern discovery and simulated annealing

Topsalign is a method that will structurally align diverse protein structures, for example, structural alignment of protein superfolds. All proteins within a superfold share the same fold but often have very low sequence identity and different biological and biochemical functions. There is often signi®cant structural diversity around the common scaffold of secondary structure elements of the fold. Topsalign uses topological descriptions of proteins. A pattern discovery algorithm identi®es equivalent secondary structure elements between a set of proteins and these are used to produce an initial multiple structure alignment. Simulated annealing is used to optimize the alignment. The output of Topsalign is a multiple structure-based sequence alignment and a 3D superposition of the structures. This method has been tested on three superfolds: the b jelly roll, TIM (a/b) barrel and the OB fold. Topsalign outperforms established methods on very diverse structures. Despite the pattern discovery working only on b strand secondary structure elements, Topsalign is shown to align TIM (a/b) barrel superfamilies, which contain both a helices and b strands

A computer system to perform structure comparison using TOPS representations of protein structure

We describe the design and implementation of a fast topology–based method for protein structure comparison. The approach uses the TOPS topological representation of protein structure, aligning two structures using a common discovered pattern and generating measure of distance derived from an insert score. Heavy use is made of a constraint-based pattern matching algorithm for TOPS diagrams that we have designed and described elsewhere Gilbert et al. (1999). The comparison system is maintained at the European Bioinformatics Institute and is available over the Web via the at tops.ebi.ac.uk/tops. Users submit a structure description in Protein Data Bank (PDB) format and can compare it with structures in the entire PDB or a representative subset of protein domains, receiving the results by email

Pattern matching and pattern discovery algorithms for protein topologies

We describe algorithms for pattern matching and pattern learning in TOPS diagrams (formal descriptions of protein topologies). These problems can be reduced to checking for subgraph isomorphism and finding maximal common subgraphs in a restricted class of ordered graphs. We have developed a subgraph isomorphism algorithm for ordered graphs, which performs well on the given set of data. The maximal common subgraph problem then is solved by repeated subgraph extension and checking for isomorphisms. Despite the apparent inefficiency such approach gives an algorithm with time complexity proportional to the number of graphs in the input set and is still practical on the given set of data. As a result we obtain fast methods which can be used for building a database of protein topological motifs, and for the comparison of a given protein of known secondary structure against a motif database

Prognostic microRNAs in high-grade glioma reveal a link to oligodendrocyte precursor differentiation.

MicroRNA expression can be exploited to define tumor prognosis and stratification for precision medicine. It remains unclear whether prognostic microRNA signatures are exclusively tumor grade and/or molecular subtype-specific, or whether common signatures of aggressive clinical behavior can be identified. Here, we defined microRNAs that are associated with good and poor prognosis in grade III and IV gliomas using data from The Cancer Genome Atlas. Pathway analysis of microRNA targets that are differentially expressed in good and poor prognosis glioma identified a link to oligodendrocyte development. Notably, a microRNA expression profile that is characteristic of a specific oligodendrocyte precursor cell type (OP1) correlates with microRNA expression from 597 of these tumors and is consistently associated with poor patient outcome in grade III and IV gliomas. Our study reveals grade-independent and subtype-independent prognostic molecular signatures in high-grade glioma and provides a framework for investigating the mechanisms of brain tumor aggressiveness

Continuous automata: bridging the gap between discrete and continuous time system models

The principled use of models in design and maintenance of a system is fundamental to the engineering methodology. As the complexity and sophistication of systems increase so do the demands on the system models required to design them. In particular the design of agent systems situated in the real world, such as robots, will require design models capable of expressing discrete and continuous changes of system parameters. Such systems are referred to as mode-switching or hybrid systems.This thesis investigates ways in which time is represented in automata system models with discretely and continuously changing parameters. Existing automaton approaches to hybrid modelling rely on describing continuous change at a sequence of points in time. In such approaches the time that elapses between each point is chosen non- deterministically in order to ensure that the model does not over-step a discrete change. In contrast, the new approach this thesis proposes describes continuous change by a continuum of points which can naturally and deterministically capture such change. As well as defining the semantics of individual models the nature of the temporal representation is particularly important in defining the composition of modular com­ponents. This new approach leads to a clear compositional semantics based on the synchronization of input and output values.The main contribution of this work is the derivation of a limiting process which provides a theoretical foundation for this new approach. It not only provides a link between dis­crete and continuous time representations, but also provides a basis for deciding which continuous time representations are theoretically sound. The resulting formalism, the Continuous I/O machine, is demonstrated to be comparable to Hybrid Automata in expressibility, but its representation of time gives it a much stronger compositional semantics based on the discrete synchronous machines from which it is derived.TThe conclusion of this work is that it is possible to define an automaton model that describes a continuum of events and that this can be effectively used to model complete mode-switching physical systems in a modular fashion

Depletion of RUNX1/ETO in t(8;21) AML cells leads to genome-wide changes in chromatin structure and transcription factor binding

The t(8;21) translocation fuses the DNA-binding domain of the hematopoietic master regulator RUNX1 to the ETO protein. The resultant RUNX1/ETO fusion protein is a leukemia-initiating transcription factor that interferes with RUNX1 function. The result of this interference is a block in differentiation and, finally, the development of acute myeloid leukemia (AML). To obtain insights into RUNX1/ETO-dependant alterations of the epigenetic landscape, we measured genome-wide RUNX1- and RUNX1/ETO-bound regions in t(8;21) cells and assessed to what extent the effects of RUNX1/ETO on the epigenome depend on its continued expression in established leukemic cells. To this end, we determined dynamic alterations of histone acetylation, RNA Polymerase II binding and RUNX1 occupancy in the presence or absence of RUNX1/ETO using a knockdown approach. Combined global assessments of chromatin accessibility and kinetic gene expression data show that RUNX1/ETO controls the expression of important regulators of hematopoietic differentiation and self-renewal. We show that selective removal of RUNX1/ETO leads to a widespread reversal of epigenetic reprogramming and a genome-wide redistribution of RUNX1 binding, resulting in the inhibition of leukemic proliferation and self-renewal, and the induction of differentiation. This demonstrates that RUNX1/ETO represents a pivotal therapeutic target in AML

Seabed geomorphology: a two-part classification system

The BGS has developed a two- part classification system (‘Morphology’ and ‘Geomorphology’) to facilitate work on a new ‘S eabed Geomorphology’ mapping initia tive, and this classification system is the focus of this report. As stated in the Foreword, the rationale and the basic framework of the classification system were conceived and es tablished within BGS, but recent collaboration within the MAREANO -Norway, INFOMAR -Ireland, and MAREMAP -UK (MIM) partnership has led to significant improvement of the classifi cation system, and this report. To further support this effort, existing BGS GIS tools (SIGMA) ha ve been adapted to apply this two-part classification system for more efficient geom orphological mapping in the marine environment. This report: provides a brief background on seabed mapping and characterisation, as well as how this science has been addressed historically within BGS; describes the current motiva tion to conduct seabed geom orphological mapping, and the requirement for a new set of t ools to facilitate this work; describes the logical framework that underpins the classification system; outlines the attributes of the classification system, how it can be applied, and discusses the advantages and limitations of the approach. It is anticipated that through testing and usage, the classification syst em will be revised and improved over time, with updated versions released through MIM partnershi p. It is also planned that a further ‘user guide’ report will be produced for the classifi cation system and the GIS tools, including thematic details (e.g. background information on ‘coastal’ or ‘glacial’ features) and a feature glossary

An optimized TOPS+ comparison method for enhanced TOPS models

This article has been made available through the Brunel Open Access Publishing Fund.Background Although methods based on highly abstract descriptions of protein structures, such as VAST and TOPS, can perform very fast protein structure comparison, the results can lack a high degree of biological significance. Previously we have discussed the basic mechanisms of our novel method for structure comparison based on our TOPS+ model (Topological descriptions of Protein Structures Enhanced with Ligand Information). In this paper we show how these results can be significantly improved using parameter optimization, and we call the resulting optimised TOPS+ method as advanced TOPS+ comparison method i.e. advTOPS+. Results We have developed a TOPS+ string model as an improvement to the TOPS [1-3] graph model by considering loops as secondary structure elements (SSEs) in addition to helices and strands, representing ligands as first class objects, and describing interactions between SSEs, and SSEs and ligands, by incoming and outgoing arcs, annotating SSEs with the interaction direction and type. Benchmarking results of an all-against-all pairwise comparison using a large dataset of 2,620 non-redundant structures from the PDB40 dataset [4] demonstrate the biological significance, in terms of SCOP classification at the superfamily level, of our TOPS+ comparison method. Conclusions Our advanced TOPS+ comparison shows better performance on the PDB40 dataset [4] compared to our basic TOPS+ method, giving 90 percent accuracy for SCOP alpha+beta; a 6 percent increase in accuracy compared to the TOPS and basic TOPS+ methods. It also outperforms the TOPS, basic TOPS+ and SSAP comparison methods on the Chew-Kedem dataset [5], achieving 98 percent accuracy. Software Availability: The TOPS+ comparison server is available at http://balabio.dcs.gla.ac.uk/mallika/WebTOPS/.This article is available through the Brunel Open Access Publishing Fun

A crucial role for the ubiquitously expressed transcription factor Sp1 at early stages of hematopoietic specification

Mammalian development is regulated by the interplay of tissue-specific and ubiquitously expressed transcription factors, such as Sp1. Sp1 knockout mice die in utero with multiple phenotypic aberrations, but the underlying molecular mechanism of this differentiation failure has been elusive. Here, we have used conditional knockout mice as well as the differentiation of mouse ES cells as a model with which to address this issue. To this end, we examine