Approximating the Set of Local Minima in Partial RNA Folding Landscapes

Motivation: We study a stochastic method for approximating the set of local minima in partial RNA folding landscapes associated with a bounded-distance neighbourhood of folding conformations. The conformations are limited to RNA secondary structures without pseudoknots. The method aims at exploring partial energy landscapes pL induced by folding simulations and their underlying neighbourhood relations. It combines an approximation of the number of local optima devised by Garnier and Kallel (2002) with a run-time estimation for identifying sets of local optima established by Reeves and Eremeev (2004).

Results: The method is tested on nine sequences of length between 50 nt and 400 nt, which allows us to compare the results with data generated by RNAsubopt and subsequent barrier tree calculations. On the nine sequences, the method captures on average 92% of local minima with settings designed for a target of 95%. The run-time of the heuristic can be estimated by O(n2D?ln?), where n is the sequence length, ? is the number of local minima in the partial landscape pL under consideration and D is the maximum number of steepest descent steps in attraction basins associated with pL.

A Systems Biology Approach Identifies SART1 as a Novel Determinant of Both 5-Fluorouracil and SN38 Drug Resistance in Colorectal Cancer

Chemotherapy response rates for advanced colorectal cancer remain disappointingly low, primarily because of drug resistance, so there is an urgent need to improve current treatment strategies. To identify novel determinants of resistance to the clinically relevant drugs 5-fluorouracil (5-FU) and SN38 (the active metabolite of irinotecan), transcriptional profiling experiments were carried out on pretreatment metastatic colorectal cancer biopsies and HCT116 parental and chemotherapy-resistant cell line models using a disease-specific DNA microarray. To enrich for potential chemoresistance-determining genes, an unsupervised bioinformatics approach was used, and 50 genes were selected and then functionally assessed using custom-designed short interfering RNA(siRNA) screens. In the primary siRNA screen, silencing of 21 genes sensitized HCT116 cells to either 5-FU or SN38 treatment. Three genes (RAPGEF2, PTRF, and SART1) were selected for further analysis in a panel of 5 colorectal cancer cell lines. Silencing SART1 sensitized all 5 cell lines to 5-FU treatment and 4/5 cell lines to SN38 treatment. However, silencing of RAPGEF2 or PTRF had no significant effect on 5-FU or SN38 sensitivity in the wider cell line panel. Further functional analysis of SART1 showed that its silencing induced apoptosis that was caspase-8 dependent. Furthermore, silencing of SART1 led to a downregulation of the caspase-8 inhibitor, c-FLIP, which we have previously shown is a key determinant of drug resistance in colorectal cancer. This study shows the power of systems biology approaches for identifying novel genes that regulate drug resistance and identifies SART1 as a previously unidentified regulator of c-FLIP and drug-induced activation of caspase-8. Mol Cancer Ther; 11(1); 119-31. (C) 2011 AACR.

Membrane Topology and Identification of Critical Amino Acid Residues in the Wzx O-Antigen Translocase from Escherichia coli O157:H4

Wzx belongs to a family of membrane proteins involved in the translocation of isoprenoid lipid-linked glycans, which is loosely related to members of the major facilitator superfamily. Despite Wzx homologs performing a conserved function, it has been difficult to pinpoint specific motifs of functional significance in their amino acid sequences. Here, we elucidate the topology of the Escherichia coli O157 Wzx (Wzx(EcO157)) by a combination of bioinformatics and substituted cysteine scanning mutagenesis, as well as targeted deletion-fusions to green fluorescent protein and alkaline phosphatase. We conclude that Wzx(EcO157) consists of 12 transmembrane (TM) helices and six periplasmic and five cytosolic loops, with N and C termini facing the cytoplasm. Four TM helices (II, IV, X, and XI) contain polar residues (aspartic acid or lysine), and they may form part of a relatively hydrophilic core. Thirty-five amino acid replacements to alanine or serine were targeted to five native cysteines and most of the aspartic acid, arginine, and lysine residues. From these, only replacements of aspartic acid-85, aspartic acid-326, arginine-298, and lysine-419 resulted in a protein unable to support O-antigen production. Aspartic acid-85 and lysine-419 are located in TM helices II and XI, while arginine-298 and aspartic acid-326 are located in periplasmic and cytosolic loops 4, respectively. Further analysis revealed that the charge at these positions is required for Wzx function since conservative substitutions maintaining the same charge polarity resulted in a functional protein, whereas those reversing or eliminating polarity abolished function. We propose that the functional requirement of charged residues at both sides of the membrane and in two TM helices could be important to allow the passage of the Und-PP-linked saccharide substrate across the membrane.

Computational identification of self-inhibitory peptides from envelope proteins

Fusion process is known to be the initial step of viral infection and hence targeting the entry process is a promising strategy to design antiviral therapy. The self-inhibitory peptides derived from the enveloped (E) proteins function to inhibit the proteinprotein interactions in the membrane fusion step mediated by the viral E protein. Thus, they have the potential to be developed into effective antiviral therapy. Herein, we have developed a Monte Carlo-based computational method with the aim to identify and optimize potential peptide hits from the E proteins. The stability of the peptides, which indicates their potential to bind in situ to the E proteins, was evaluated by two different scoring functions, dipolar distance-scaled, finite, ideal-gas reference state and residue-specific all-atom probability discriminatory function. The method was applied to a-helical Class I HIV-1 gp41, beta-sheet Class II Dengue virus (DENV) type 2 E proteins, as well as Class III Herpes Simplex virus-1 (HSV-1) glycoprotein, a E protein with a mixture of a-helix and beta-sheet structural fold. The peptide hits identified are in line with the druggable regions where the self-inhibitory peptide inhibitors for the three classes of viral fusion proteins were derived. Several novel peptides were identified from either the hydrophobic regions or the functionally important regions on Class II DENV-2 E protein and Class III HSV-1 gB. They have potential to disrupt the proteinprotein interaction in the fusion process and may serve as starting points for the development of novel inhibitors for viral E proteins. 

Detecting sequence dependent transcriptional pauses from RNA and protein number time series

Background: Evidence suggests that in prokaryotes sequence-dependent transcriptional pauses a?ect the dynamics of transcription and translation, as well as of small genetic circuits. So far, a few pause-prone sequences have been identi?ed from in vitro measurements of transcription elongation kinetics.

Results: Using a stochastic model of gene expression at the nucleotide and codon levels with realistic parameter values, we investigate three di?erent but related questions and present statistical methods for their analysis. First, we show that information from in vivo RNA and protein temporal numbers is su?cient to discriminate between models with and without a pause site in their coding sequence. Second, we demonstrate that it is possible to separate a large variety of models from each other with pauses of various durations and locations in the template by means of a hierarchical clustering and a random forest classi?er. Third, we introduce an approximate likelihood function that allows to estimate the location of a pause site.

Conclusions: This method can aid in detecting unknown pause-prone sequences from temporal measurements of RNA and protein numbers at a genome-wide scale and thus elucidate possible roles that these sequences play in the dynamics of genetic networks and phenotype.

Progressive lung cancer determined by expression profiling and transcriptional regulation

Clinically, our ability to predict disease outcome for patients with early stage lung cancer is currently poor. To address this issue, tumour specimens were collected at surgery from non-small cell lung cancer (NSCLC) patients as part of the European Early Lung Cancer (EUELC) consortium. The patients were followed-up for three years post-surgery and patients who suffered progressive disease (PD, tumour recurrence, metastasis or a second primary) or remained disease-free (DF) during follow-up were identified. RNA from both tumour and adjacent-normal lung tissue was extracted from patients and subjected to microarray expression profiling. These samples included 36 adenocarcinomas and 23 squamous cell carcinomas from both PD and DF patients. The microarray data was subject to a series of systematic bioinformatics analyses at gene, network and transcription factor levels. The focus of these analyses was 2-fold: firstly to determine whether there were specific biomarkers capable of differentiating between PD and DF patients, and secondly, to identify molecular networks which may contribute to the progressive tumour phenotype. The experimental design and analyses performed permitted the clear differentiation between PD and DF patients using a set of biomarkers implicated in neuroendocrine signalling and allowed the inference of a set of transcription factors whose activity may differ according to disease outcome. Potential links between the biomarkers, the transcription factors and the genes p21/CDKN1A and Myc, which have previously been implicated in NSCLC development, were revealed by a combination of pathway analysis and microarray meta-analysis. These findings suggest that neuroendocrine-related genes, potentially driven through p21/CDKN1A and Myc, are closely linked to whether or not a NSCLC patient will have poor clinical outcome.

Rice-arsenate interactions in hydroponics: a three-gene model for tolerance

In this study, the genetic mapping of the tolerance of root growth to 13.3 muM arsenate [As(V)] using the BalaxAzucena population is improved, and candidate genes for further study are identified. A remarkable three-gene model of tolerance is advanced, which appears to involve epistatic interaction between three major genes, two on chromosome 6 and one on chromosome 10. Any combination of two of these genes inherited from the tolerant parent leads to the plant having tolerance. Lists of potential positional candidate genes are presented. These are then refined using whole genome transcriptomics data and bioinformatics. Physiological evidence is also provided that genes related to phosphate transport are unlikely to be behind the genetic loci conferring tolerance. These results offer testable hypotheses for genes related to As(V) tolerance that might offer strategies for mitigating arsenic (As) accumulation in consumed rice.

Balancing Inflammatory, Lipid, and Xenobiotic Signaling Pathways by VSL#3, a Biotherapeutic Agent, in the Treatment of Inflammatory Bowel Disease

Background: The interleukin 10 knockout mouse (IL10-KO) is a model of human inflammatory bowel disease (IBD) used to Study host microbial interactions and the action of potential therapeutics. Using Affymetrix data analysis, important signaling pathways and transcription factors relevant to gut inflammation and antiinflammatory probiotics were identified.

Methods: Affymetrix microarray analysis on both wildtype (WT) and IL10-KO mice orally administered with and without the probiotic VSL#3 was performed and the results validated by real-time polymerase chain reaction (PCR), immunocytochemistry, proteomics, and histopathology. Changes in metabolically active bacteria were assessed with denaturing gradient gel electrophoresis (DGGE).

Results: Inflammation in IL10-KO mice was characterized by differential regulation of inflammatory, nuclear receptor, lipid, and xenobiotic signaling pathways. Probiotic intervention resulted in downregulation of CXCL9 (fold change [FC] = -3.98, false discovery rate [FDR] = 0.019), CXCL10 (FC = -4.83, FDR = 0.0008), CCL5 (FC -3.47 FDR = 0.017), T-cell activation (Itgal [FC = -4.72, FDR = 0.00009], Itgae [FC = -2.54 FDR = 0.0044]) and the autophagy gene IRGM (FC = -1.94, FDR = 0.01), a recently identified susceptibility gene in human IBD. Consistent with a marked reduction in integrins, probiotic treatment decreased the number of CCL5+ CD3+ double-positive T Cells and upregulated galectin2, which triggers apoptosis of activated T cells. Importantly, genes associated with lipid and PPAR signaling (PPAR alpha [FC = 2.36, FDR = 0.043], PPARGC1 alpha [FC 2.58, FDR = 0.016], Nrld2 [FC = 3.11, FDR = 0.0067]) were also upregulated. Altered microbial diversity was noted in probiotic-treated mice.

Conclusions: Bioinformatics analysis revealed important immune response. phagocytic and inflammatory pathways dominated by elevation of T-helper cell 1 type (TH1) transcription factors in IL10-KO mice. Probiotic intervention resulted in a site-specific reduction of these pathways but importantly upregulated PPAR, xenobiotic, and lipid signaling genes. potential antagonists of NF-kappa B inflammatory pathways.

Common-sense knowledge for a computer vision system for human action recognition

This work presents a novel approach for human action recognition based on the combination of computer vision techniques and common-sense knowledge and reasoning capabilities. The emphasis of this work is on how common sense has to be leveraged to a vision-based human action recognition so that nonsensical errors can be amended at the understanding stage. The proposed framework is to be deployed in a realistic environment in which humans behave rationally, that is, motivated by an aim or a reason. © 2012 Springer-Verlag.

Gaussian mixture background modelling optimisation for micro-controllers

This paper proposes an optimisation of the adaptive Gaussian mixture background model that allows the deployment of the method on processors with low memory capacity. The effect of the granularity of the Gaussian mean-value and variance in an integer-based implementation is investigated and novel updating rules of the mixture weights are described. Based on the proposed framework, an implementation for a very low power consumption micro-controller is presented. Results show that the proposed method operates in real time on the micro-controller and has similar performance to the original model. © 2012 Springer-Verlag.

Targeting distributed systems in FastFlow

FastFlow is a structured parallel programming framework targeting shared memory multi-core architectures. In this paper we introduce a FastFlow extension aimed at supporting also a network of multi-core workstations. The extension supports the execution of FastFlow programs by coordinating-in a structured way-the fine grain parallel activities running on a single workstation. We discuss the design and the implementation of this extension presenting preliminary experimental results validating it on state-of-the-art networked multi-core nodes. © 2013 Springer-Verlag.

Structured data access annotations for massively parallel computations

We describe an approach aimed at addressing the issue of joint exploitation of control (stream) and data parallelism in a skeleton based parallel programming environment, based on annotations and refactoring. Annotations drive efficient implementation of a parallel computation. Refactoring is used to transform the associated skeleton tree into a more efficient, functionally equivalent skeleton tree. In most cases, cost models are used to drive the refactoring process. We show how sample use case applications/kernels may be optimized and discuss preliminary experiments with FastFlow assessing the theoretical results. © 2013 Springer-Verlag.

An efficient unbounded lock-free queue for multi-core systems

The use of efficient synchronization mechanisms is crucial for implementing fine grained parallel programs on modern shared cache multi-core architectures. In this paper we study this problem by considering Single-Producer/Single- Consumer (SPSC) coordination using unbounded queues. A novel unbounded SPSC algorithm capable of reducing the row synchronization latency and speeding up Producer-Consumer coordination is presented. The algorithm has been extensively tested on a shared-cache multi-core platform and a sketch proof of correctness is presented. The queues proposed have been used as basic building blocks to implement the FastFlow parallel framework, which has been demonstrated to offer very good performance for fine-grain parallel applications. © 2012 Springer-Verlag.