DNA-mediated oxidation of transcription factor p53

Transcription factor p53 is the most commonly altered gene in human cancer. As a redox-active protein in direct contact with DNA, p53 can directly sense oxidative stress through DNA-mediated charge transport. Electron hole transport occurs with a shallow distance dependence over long distances through the π-stacked DNA bases, leading to the oxidation and dissociation of DNA-bound p53. The extent of p53 dissociation depends upon the redox potential of the response element DNA in direct contact with each p53 monomer. The DNA sequence dependence of p53 oxidative dissociation was examined by electrophoretic mobility shift assays using radiolabeled oligonucleotides containing both synthetic and human p53 response elements with an appended anthraquinone photooxidant. Greater p53 dissociation is observed from DNA sequences containing low redox potential purine regions, particularly guanine triplets, within the p53 response element. Using denaturing polyacrylamide gel electrophoresis of irradiated anthraquinone-modified DNA, the DNA damage sites, which correspond to locations of preferred electron hole localization, were determined. The resulting DNA damage preferentially localizes to guanine doublets and triplets within the response element. Oxidative DNA damage is inhibited in the presence of p53, however, only at DNA sites within the response element, and therefore in direct contact with p53. From these data, predictions about the sensitivity of human p53-binding sites to oxidative stress, as well as possible biological implications, have been made. On the basis of our data, the guanine pattern within the purine region of each p53-binding site determines the response of p53 to DNA-mediated oxidation, yielding for some sequences the oxidative dissociation of p53 from a distance and thereby providing another potential role for DNA charge transport chemistry within the cell.

To determine whether the change in p53 response element occupancy observed in vitro also correlates in cellulo, chromatin immunoprecipition (ChIP) and quantitative PCR (qPCR) were used to directly quantify p53 binding to certain response elements in HCT116N cells. The HCT116N cells containing a wild type p53 were treated with the photooxidant [Rh(phi)2bpy]³⁺, Nutlin-3 to upregulate p53, and subsequently irradiated to induce oxidative genomic stress. To covalently tether p53 interacting with DNA, the cells were fixed with disuccinimidyl glutarate and formaldehyde. The nuclei of the harvested cells were isolated, sonicated, and immunoprecipitated using magnetic beads conjugated with a monoclonal p53 antibody. The purified immounoprecipiated DNA was then quantified via qPCR and genomic sequencing. Overall, the ChIP results were significantly varied over ten experimental trials, but one trend is observed overall: greater variation of p53 occupancy is observed in response elements from which oxidative dissociation would be expected, while significantly less change in p53 occupancy occurs for response elements from which oxidative dissociation would not be anticipated.

The chemical oxidation of transcription factor p53 via DNA CT was also investigated with respect to the protein at the amino acid level. Transcription factor p53 plays a critical role in the cellular response to stress stimuli, which may be modulated through the redox modulation of conserved cysteine residues within the DNA-binding domain. Residues within p53 that enable oxidative dissociation are herein investigated. Of the 8 mutants studied by electrophoretic mobility shift assay (EMSA), only the C275S mutation significantly decreased the protein affinity (KD) for the Gadd45 response element. EMSA assays of p53 oxidative dissociation promoted by photoexcitation of anthraquinone-tethered Gadd45 oligonucleotides were used to determine the influence of p53 mutations on oxidative dissociation; mutation to C275S severely attenuates oxidative dissociation while C277S substantially attenuates dissociation. Differential thiol labeling was used to determine the oxidation states of cysteine residues within p53 after DNA-mediated oxidation. Reduced cysteines were iodoacetamide labeled, while oxidized cysteines participating in disulfide bonds were ¹³C₂D₂-iodoacetamide labeled. Intensities of respective iodoacetamide-modified peptide fragments were analyzed using a QTRAP 6500 LC-MS/MS system, quantified with Skyline, and directly compared. A distinct shift in peptide labeling toward ¹³C₂D₂-iodoacetamide labeled cysteines is observed in oxidized samples as compared to the respective controls. All of the observable cysteine residues trend toward the heavy label under conditions of DNA CT, indicating the formation of multiple disulfide bonds potentially among the C124, C135, C141, C182, C275, and C277. Based on these data it is proposed that disulfide formation involving C275 is critical for inducing oxidative dissociation of p53 from DNA.

Funtzio sintaktikoen gold estandarra eskuz etiketatzeko gidalerroak

[EN]In this report we present the tags we use when annotating the gold standard of syntactic functions and the decisions taken during its annotation. The gold standard is a necessary resource to evaluate the rulebased surface syntactic parser (the one based on the Constraint Grammar formalism), and, moreover, it can be useful to develop and evaluate statistical parsers. The tags we are presenting here follow the Constraint Grammar (CG) formalism (Karlsson et al., 1995). In fact, last experiments show that good results have been obtained when parsing with CG (Karlsson et al., 1995; Samuelsson and Voutilainen,1997; Tapanainen and Järvinen, 1997; Bick, 2000).

Perpaus adberbialen agerpena, maiztasuna eta kokapena EPEC‐DEP corpusean

In this report we present the results obtained analysing the use, frequency of use and the position of adverbial clauses. This analysis has been performed in the Basque Dependency Treebank (BDT). We also have used the descriptive grammars of Euskaltzaindia, the Royal Academy of the Basque.

DNA-Mediated Charge Transport Devices for Protein Detection

Detection of biologically relevant targets, including small molecules, proteins, DNA, and RNA, is vital for fundamental research as well as clinical diagnostics. Sensors with biological elements provide a natural foundation for such devices because of the inherent recognition capabilities of biomolecules. Electrochemical DNA platforms are simple, sensitive, and do not require complex target labeling or expensive instrumentation. Sensitivity and specificity are added to DNA electrochemical platforms when the physical properties of DNA are harnessed. The inherent structure of DNA, with its stacked core of aromatic bases, enables DNA to act as a wire via DNA-mediated charge transport (DNA CT). DNA CT is not only robust over long molecular distances of at least 34 nm, but is also especially sensitive to anything that perturbs proper base stacking, including DNA mismatches, lesions, or DNA-binding proteins that distort the π-stack. Electrochemical sensors based on DNA CT have previously been used for single-nucleotide polymorphism detection, hybridization assays, and DNA-binding protein detection. Here, improvements to (i) the structure of DNA monolayers and (ii) the signal amplification with DNA CT platforms for improved sensitivity and detection are described.

First, improvements to the control over DNA monolayer formation are reported through the incorporation of copper-free click chemistry into DNA monolayer assembly. As opposed to conventional film formation involving the self-assembly of thiolated DNA, copper-free click chemistry enables DNA to be tethered to a pre-formed mixed alkylthiol monolayer. The total amount of DNA in the final film is directly related to the amount of azide in the underlying alkylthiol monolayer. DNA monolayers formed with this technique are significantly more homogeneous and lower density, with a larger amount of individual helices exposed to the analyte solution. With these improved monolayers, significantly more sensitive detection of the transcription factor TATA binding protein (TBP) is achieved.

Using low-density DNA monolayers, two-electrode DNA arrays were designed and fabricated to enable the placement of multiple DNA sequences onto a single underlying electrode. To pattern DNA onto the primary electrode surface of these arrays, a copper precatalyst for click chemistry was electrochemically activated at the secondary electrode. The location of the secondary electrode relative to the primary electrode enabled the patterning of up to four sequences of DNA onto a single electrode surface. As opposed to conventional electrochemical readout from the primary, DNA-modified electrode, a secondary microelectrode, coupled with electrocatalytic signal amplification, enables more sensitive detection with spatial resolution on the DNA array electrode surface. Using this two-electrode platform, arrays have been formed that facilitate differentiation between well-matched and mismatched sequences, detection of transcription factors, and sequence-selective DNA hybridization, all with the incorporation of internal controls.

For effective clinical detection, the two working electrode platform was multiplexed to contain two complementary arrays, each with fifteen electrodes. This platform, coupled with low density DNA monolayers and electrocatalysis with readout from a secondary electrode, enabled even more sensitive detection from especially small volumes (4 μL per well). This multiplexed platform has enabled the simultaneous detection of two transcription factors, TBP and CopG, with surface dissociation constants comparable to their solution dissociation constants.

With the sensitivity and selectivity obtained from the multiplexed, two working electrode array, an electrochemical signal-on assay for activity of the human methyltransferase DNMT1 was incorporated. DNMT1 is the most abundant human methyltransferase, and its aberrant methylation has been linked to the development of cancer. However, current methods to monitor methyltransferase activity are either ineffective with crude samples or are impractical to develop for clinical applications due to a reliance on radioactivity. Electrochemical detection of methyltransferase activity, in contrast, circumvents these issues. The signal-on detection assay translates methylation events into electrochemical signals via a methylation-specific restriction enzyme. Using the two working electrode platform combined with this assay, DNMT1 activity from tumor and healthy adjacent tissue lysate were evaluated. Our electrochemical measurements revealed significant differences in methyltransferase activity between tumor tissue and healthy adjacent tissue.

As differential activity was observed between colorectal tumor tissue and healthy adjacent tissue, ten tumor sets were subsequently analyzed for DNMT1 activity both electrochemically and by tritium incorporation. These results were compared to expression levels of DNMT1, measured by qPCR, and total DNMT1 protein content, measured by Western blot. The only trend detected was that hyperactivity was observed in the tumor samples as compared to the healthy adjacent tissue when measured electrochemically. These advances in DNA CT-based platforms have propelled this class of sensors from the purely academic realm into the realm of clinically relevant detection.

On the optimal usage of labelled examples in semi-supervised multi-class classification problems

In recent years, the performance of semi-supervised learning has been theoretically investigated. However, most of this theoretical development has focussed on binary classification problems. In this paper, we take it a step further by extending the work of Castelli and Cover [1] [2] to the multi-class paradigm. Particularly, we consider the key problem in semi-supervised learning of classifying an unseen instance x into one of K different classes, using a training dataset sampled from a mixture density distribution and composed of l labelled records and u unlabelled examples. Even under the assumption of identifiability of the mixture and having infinite unlabelled examples, labelled records are needed to determine the K decision regions. Therefore, in this paper, we first investigate the minimum number of labelled examples needed to accomplish that task. Then, we propose an optimal multi-class learning algorithm which is a generalisation of the optimal procedure proposed in the literature for binary problems. Finally, we make use of this generalisation to study the probability of error when the binary class constraint is relaxed.

Um problema inverso na modelagem da difusão do calor

O presente trabalho aborda um problema inverso associado a difus~ao de calor em uma barra unidimensional. Esse fen^omeno e modelado por meio da equac~ao diferencial par- cial parabolica ut = uxx, conhecida como equac~ao de difus~ao do calor. O problema classico (problema direto) envolve essa equac~ao e um conjunto de restric~oes { as condic~oes inicial e de contorno {, o que permite garantir a exist^encia de uma soluc~ao unica. No problema inverso que estudamos, o valor da temperatura em um dos extremos da barra n~ao esta disponvel. Entretanto, conhecemos o valor da temperatura em um ponto x0 xo no interior da barra. Para aproximar o valor da temperatura no intervalo a direita de x0, propomos e testamos tr^es algoritmos de diferencas nitas: diferencas regressivas, leap-frog e diferencas regressivas maquiadas.

Bertso transformation with pattern-based sampling

This paper presents a method to generate new melodies, based on conserving the semiotic structure of a template piece. A pattern discovery algorithm is applied to a template piece to extract significant segments: those that are repeated and those that are transposed in the piece. Two strategies are combined to describe the semiotic coherence structure of the template piece: inter-segment coherence and intra-segment coherence. Once the structure is described it is used as a template for new musical content that is generated using a statistical model created from a corpus of bertso melodies and iteratively improved using a stochastic optimization method. Results show that the method presented here effectively describes a coherence structure of a piece by discovering repetition and transposition relations between segments, and also by representing the relations among notes within the segments. For bertso generation the method correctly conserves all intra and inter-segment coherence of the template, and the optimization method produces coherent generated melodies.

Autophagic Marker MAP1LC3B Expression Levels Are Associated with Carotid Atherosclerosis Symptomatology

Objectives: The mechanism by which atheroma plaque becomes unstable is not completely understood to date but analysis of differentially expressed genes in stable versus unstable plaques may provide clues. This will be crucial toward disclosing the mechanistic basis of plaque instability, and may help to identify prognostic biomarkers for ischaemic events. The objective of our study was to identify differences in expression levels of 59 selected genes between symptomatic patients (unstable plaques) and asymptomatic patients (stable plaques). Methods: 80 carotid plaques obtained by carotid endarterectomy and classified as symptomatic (>70% stenosis) or asymptomatic (>80% stenosis) were used in this study. The expression levels of 59 genes were quantified by qPCR on RNA extracted from the carotid plaques obtained by endarterectomy and analyzed by means of various bioinformatic tools. Results: Several genes associated with autophagy pathways displayed differential expression levels between asymptomatic and symptomatic (i.e. MAP1LC3B, RAB24, EVA1A). In particular, mRNA levels of MAP1LC3B, an autophagic marker, showed a 5-fold decrease in symptomatic samples, which was confirmed in protein blots. Immune system-related factors and endoplasmic reticulum-associated markers (i.e. ERP27, ITPR1, ERO1LB, TIMP1, IL12B) emerged as differently expressed genes between asymptomatic and symptomatic patients. Conclusions: Carotid atherosclerotic plaques in which MAP1LC3B is underexpressed would not be able to benefit from MAP1LC3B-associated autophagy. This may lead to accumulation of dead cells at lesion site with subsequent plaque destabilization leading to cerebrovascular events. Identified biomarkers and network interactions may represent novel targets for development of treatments against plaque destabilization and thus for the prevention of cerebrovascular events.