Identification of an N-Terminal Region of Sigma 54 Required for Enhancer Responsiveness

Sigma 54 associates with bacterial core RNA polymerase and converts it into an enhancer-responsive enzyme. Deletion of the N-terminal 40 amino acids is known to result in loss of the ability to respond to enhancer binding proteins. In this work PCR mutagenesis and genetic screens were used to identify a small patch, from amino acids 33 to 37, that is required for proper response to activator in vivo. Site-directed single point mutants within this segment were constructed and studied. Two of these were defective in responding to the enhancer binding protein in vitro. The mutants could still direct the polymerase to bind to DNA and initiate transient melting. However, they failed in directing activator-dependent formation of a heparin-stable open complex. Thus, amino acid region 33 to 37 includes critical activation response determinants. This region overlaps the larger leucine patch negative-control region, suggesting that anti-inhibition and positive activation are closely coupled events.     

HiCORE: Hi-C Analysis for Identification of Core Chromatin Looping Regions with Higher Resolution

Genome-wide chromosome conformation capture (3C)-based high-throughput sequencing (Hi-C) has enabled identification of genome-wide chromatin loops. Because the Hi-C map with restriction fragment resolution is intrinsically associated with sparsity and stochastic noise, Hi-C data are usually binned at particular intervals; however, the binning method has limited reliability, especially at high resolution. Here, we describe a new method called HiCORE, which provides simple pipelines and algorithms to overcome the limitations of single-layered binning and predict core chromatin regions with three-dimensional physical interactions. In this approach, multiple layers of binning with slightly shifted genome coverage are generated, and interacting bins at each layer are integrated to infer narrower regions of chromatin interactions. HiCORE predicts chromatin looping regions with higher resolution, both in human and Arabidopsis genomes, and contributes to the identification of the precise positions of potential genomic elements in an unbiased manner.     

A Linear Domain System Identification for Small Unmanned Aerial Rotorcraft Based on Adaptive Genetic Algorithm

<正> This paper proposes a new adaptive linear domain system identification method for small unmanned aerial rotorcraft.Byusing the flash memory integrated into the micro guide navigation control module, system records the data sequences of flighttests as inputs (control signals for servos) and outputs (aircraft's attitude and velocity information).After data preprocessing, thesystem constructs the horizontal and vertical dynamic model for the small unmanned aerial rotorcraft using adaptive geneticalgorithm.The identified model is verified by a series of simulations and tests.Comparison between flight data and the one-stepprediction data obtained from the identification model shows that the dynamic model has a good estimation for real unmannedaerial rotorcraft system.Based on the proposed dynamic model, the small unmanned aerial rotorcraft can perform hovering,turning, and straight flight tasks in real flight tests.     

Enhancer of zeste homolog 2: A potential target for tumor therapy

Enhancer of zeste homolog 2 (EZH2) is a subunit of the Polycomb-Repressive Complex 2 (PRC2), which catalyses the trimethylation of histone H3 on Lys 27 (H3K27) and involves in genes repression. EZH2 is amplified and overexpressed in a variety of cancers, including prostate and breast cancer. Overexpression of EZH2 has been associated with the invasion and progression of malignant cancers, especially with the progression of prostate cancer. Here, we review the structure and biological function of EZH2, especially focused on its activities in the tumorigenesis.     

A Chromatin Assay for Human Brain Tissue

Chronic neuropsychiatric illnesses such as schizophrenia, bipolar disease and autism are thought to result from a combination of genetic and environmental factors that might result in epigenetic alterations of gene expression and other molecular pathology. Traditionally, however, expression studies in postmortem brain were confined to quantification of mRNA or protein. The limitations encountered in postmortem brain research such as variabilities in autolysis time and tissue integrities are also likely to impact any studies of higher order chromatin structures. However, the nucleosomal organization of genomic DNA including DNA:core histone binding - appears to be largely preserved in representative samples provided by various brain banks. Therefore, it is possible to study the methylation pattern and other covalent modifications of the core histones at defined genomic loci in postmortem brain. Here, we present a simplified native chromatin immunoprecipitation (NChIP) protocol for frozen (never-fixed) human brain specimens. Starting with micrococcal nuclease digestion of brain homogenates, NChIP followed by qPCR can be completed within three days. The methodology presented here should be useful to elucidate epigenetic mechanisms of gene expression in normal and diseased human brain.Download video file.^{(88M, mov)}     

Chromatin history: our view from the bridge

Thirty years ago, our conception of chromatin structure underwent a total metamorphosis as the nucleosome era began. In Kurosawa's classic movie 'Rashomon' (1951), each participant had a different perspective of the same pivotal event. This review outlines our perception of history.     

A Lamin-Associated Chromatin Model for Chromosome Organization

We propose a simple model for chromatin organization based on the interaction of the chromatin fibers with lamin proteins along the nuclear membrane. Lamin proteins are known to be a major factor that influences chromatin organization and hence gene expression in the cells. We provide a quantitative understanding of lamin-associated chromatin organization in a crowded macromolecular environment by systematically varying the heteropolymer segment distribution and the strength of the lamin-chromatin attractive interaction. Our minimal polymer model reproduces the formation of lamin-associated-domains and provides an in silico tool for quantifying domain length distributions for different distributions of heteropolymer segments. We show that a Gaussian distribution of heteropolymer segments, coupled with strong lamin-chromatin interactions, can qualitatively reproduce observed length distributions of lamin-associated-domains. Further, lamin-mediated interaction can enhance the formation of chromosome territories as well as the organization of chromatin into tightly packed heterochromatin and the loosely packed gene-rich euchromatin regions.     

基于改进的Winnow算法的剪接位点识别

DNA序列功能位点的识别是目前生物信息学领域的一个研究热点,剪接位点的识别就是其中之一.为了充分利用剪接位点的特征模式,从而更好地识别剪接位点,建立了一个基于改进Winnow算法的剪接位点识别系统.与其他方法相比较,改进的Winnow算法具有更好的鲁棒性,适用于高维特征空间,能够融合多种模式信息,即使在包含很多不相关特征的情况下,也能有很好的性能.同时在训练的时候,对特征集进行了剪枝,把一些对识别几乎没有贡献的特征去除,这样做对结果的影响可以忽略,而且提高了算法的效率.通过实验验证,改进的Winnow算法可以很好地识别剪接位点,其多个性能指标达到或超过目前国际上流行的剪接位点识别软件.     

A Real-Time Atrial Fibrillation Detection Algorithm Based on the Instantaneous State of Heart Rate

Atrial fibrillation (AF), the most frequent cause of cardioembolic stroke, is increasing in prevalence as the population ages, and presents with a broad spectrum of symptoms and severity. The early identification of AF is an essential part for preventing the possibility of blood clotting and stroke. In this work, a real-time algorithm is proposed for accurately screening AF episodes in electrocardiograms. This method adopts heart rate sequence, and it involves the application of symbolic dynamics and Shannon entropy. Using novel recursive algorithms, a low-computational complexity can be obtained. Four publicly-accessible sets of clinical data (Long-Term AF, MIT-BIH AF, MIT-BIH Arrhythmia, and MIT-BIH Normal Sinus Rhythm Databases) were used for assessment. The first database was selected as a training set; the receiver operating characteristic (ROC) curve was performed, and the best performance was achieved at the threshold of 0.639: the sensitivity (Se), specificity (Sp), positive predictive value (PPV) and overall accuracy (ACC) were 96.14%, 95.73%, 97.03% and 95.97%, respectively. The other three databases were used for independent testing. Using the obtained decision-making threshold (i.e., 0.639), for the second set, the obtained parameters were 97.37%, 98.44%, 97.89% and 97.99%, respectively; for the third database, these parameters were 97.83%, 87.41%, 47.67% and 88.51%, respectively; the Sp was 99.68% for the fourth set. The latest methods were also employed for comparison. Collectively, results presented in this study indicate that the combination of symbolic dynamics and Shannon entropy yields a potent AF detector, and suggest this method could be of practical use in both clinical and out-of-clinical settings.     

Formaldehyde Crosslinking: A Tool for the Study of Chromatin Complexes

Formaldehyde has been used for decades to probe macromolecular structure and function and to trap complexes, cells, and tissues for further analysis. Formaldehyde crosslinking is routinely employed for detection and quantification of protein-DNA interactions, interactions between chromatin proteins, and interactions between distal segments of the chromatin fiber. Despite widespread use and a rich biochemical literature, important aspects of formaldehyde behavior in cells have not been well described. Here, we highlight features of formaldehyde chemistry relevant to its use in analyses of chromatin complexes, focusing on how its properties may influence studies of chromatin structure and function.     

A Priori Data-Driven Multi-Clustered Reservoir Generation Algorithm for Echo State Network

Echo state networks (ESNs) with multi-clustered reservoir topology perform better in reservoir computing and robustness than those with random reservoir topology. However, these ESNs have a complex reservoir topology, which leads to difficulties in reservoir generation. This study focuses on the reservoir generation problem when ESN is used in environments with sufficient priori data available. Accordingly, a priori data-driven multi-cluster reservoir generation algorithm is proposed. The priori data in the proposed algorithm are used to evaluate reservoirs by calculating the precision and standard deviation of ESNs. The reservoirs are produced using the clustering method; only the reservoir with a better evaluation performance takes the place of a previous one. The final reservoir is obtained when its evaluation score reaches the preset requirement. The prediction experiment results obtained using the Mackey-Glass chaotic time series show that the proposed reservoir generation algorithm provides ESNs with extra prediction precision and increases the structure complexity of the network. Further experiments also reveal the appropriate values of the number of clusters and time window size to obtain optimal performance. The information entropy of the reservoir reaches the maximum when ESN gains the greatest precision.