Structure and Mechanism of a Metal-Sensing Regulatory RNA

SummaryOrganisms maintain the correct balance of intracellular metals primarily through metal-sensing proteins that control transport and storage of the target ion(s). Here, we reveal the basis of metal sensing and genetic control by a metalloregulatory RNA. Our data demonstrate that a previously uncharacterized orphan riboswitch, renamed the “M-box,” is a divalent metal-sensing RNA involved in Mg2+ homeostasis. A combination of genetic, biochemical, and biophysical techniques demonstrate that Mg2+ induces a compacted tertiary architecture for M-box RNAs that regulates the accessibility of nucleotides involved in genetic control. Molecular details are provided by crystallographic structure determination of a Mg2+-bound M-box RNA. Given the distribution of this RNA element, it may constitute a common mode for bacterial metal ion regulation, and its discovery suggests the possibility of additional RNA-based metal sensors in modern and primordial organisms

ANALISA PARAMETER DESAIN DRILL STRING PADA DIRECTIONADRILLING SUMUR SRN-4 LAPANGAN SETURIAN PT.CHEVRON PACIFIC INDONESIA

Pada operasi pemboran drill pipe merupakan komponen pembentuk panjang drill string yang utama dan juga sebagai media gaya axial, momen puntir, dan sirkulasi lumpur pemboran, oleh karena itu perhitungan beban kombinasi yang terjadi pada drill pipe perlu dilakukan untuk mencegah terjadinya permasalahan yang disebabkan oleh pembebanan yang terjadi. Untuk menghitung pembebanan yang terjadi dan mengetahui kemampuan serta kekuatan rangkaian drill string, digunakan persamaan yang diturunkan oleh H. Rabia. Sebelum perhitungan pembebanan dilakukan maka perlu diketahui dahulu beban-beban yang terjadi pada rangkaian drill string antara lain, panjang drill pipe maksimum, dan beban puntiran, serta berat dari rangkaian drill string itu sendiri. Untuk mengetahui kekuatan dan kemampuan drill string perlu diketahui safety factor serta harga MOP (Margin Overpull). Perhitungan–perhitungan nanti dapat mengetahui besarnya peregangan yang terjadi pada drill pipe, sedangkan untuk perhitungan beban buckling dilakukan dengan menggunakan persamaan R.F. Mitchel untuk memperkirakan kemungkinan pipa tertekuk. Secara umum dari hasil analisa dan perhitungan desain drill string pemboran pada sumur SRN-4 lapangan Chevron, pada BHA#5 dengan susunan rangkaian OD 5’’ ID 4.25” W DP 19.5 lb/ft L DP 3687ft (119 joint) + HWDP OD 5” ID 3” W HWDP 50 lb/ft L 707.56 ft (24 joint) + DC OD 6 ¾” ID 2 13/16” W DC 100 lb/ft L DC HWDP 57.34 ft (2 joint) untuk build up section dapat dinyatakan aman total beban lebih kecil dibandingan kekutan build up maksimum. Pada tangensial susunan rangkaian BHA#7 OD 4’’ ID 3.1” WDP 14 lb/ft LDP 8302.87ft (268 joint) + HWDP OD 4” ID 2 ½” WHWDP 28 lb/ft LHWDP 608.19 ft (20 joint) + Drill Colar OD 4 ¾” ID 2 ½“ WDC 44 lb/ft LDC 30.37 ft (1 joint) besarnya beban pada rangkaian tersebut lebih kecil dari pada kekuatan tangensial maksimum dan dinyatakan aman

MicroRNA expression distinguishes SCLC from NSCLC lung tumor cells and suggests a possible pathological relationship between SCLCs and NSCLCs

<p>Abstract</p> <p>Background</p> <p>Recent studies have shown that microRNAs (miRNAs) play roles in tumorigenesis and are reliable classifiers of certain cancer types and subtypes. However, the role of miRNAs in the pathogenesis and diagnosis of small cell carcinoma (SCLC), the majority of which represent the most aggressive lung tumors, has not been investigated.</p> <p>Methods</p> <p>In order to explore miRNA involvement in the pathogenesis of small cell lung carcinoma (SCLC) and the potential role of miRNAs in SCLC diagnosis, we compared the miRNA expression profile of a set of SCLC cell lines to that of a set of non-small cell lung cancer (NSCLC) cell lines and normal immortalized human bronchial epithelial cells (HBECs) using microarray analysis.</p> <p>Results</p> <p>Our results show that miRNA profiles reliably distinguish SCLC cell lines from NSCLC and HBEC cell lines. Further analysis of the miRNA expression profile of the two subtypes of lung cancer cell lines indicates that the expression levels of the majority of the miRNAs that are differentially expressed in SCLC cells relative to NSCLC cells and HBECs show a progressive trend from HBECs to NSCLC cells to SCLC cells.</p> <p>Conclusions</p> <p>The distinctive miRNA expression signature of SCLCs relative to NSCLCs and HBECs suggests that miRNA profiles have the potential to serve as a diagnostic marker of SCLC lung tumors. The progressive trend of miRNA profile changes from HBECs to NSCLCs to SCLCs suggests a possible pathological relationship between SCLCs and NSCLCs, and suggests that the increasing dysregulation of miRNA expression may play a role in lung tumor progression. The specific role of these miRNAs in lung tumor pathogenesis and differentiation need to be investigated further in future studies.</p

Ultra-High Resolution 3D Imaging of Whole Cells.

Fluorescence nanoscopy, or super-resolution microscopy, has become an important tool in cell biological research. However, because of its usually inferior resolution in the depth direction (50-80 nm) and rapidly deteriorating resolution in thick samples, its practical biological application has been effectively limited to two dimensions and thin samples. Here, we present the development of whole-cell 4Pi single-molecule switching nanoscopy (W-4PiSMSN), an optical nanoscope that allows imaging of three-dimensional (3D) structures at 10- to 20-nm resolution throughout entire mammalian cells. We demonstrate the wide applicability of W-4PiSMSN across diverse research fields by imaging complex molecular architectures ranging from bacteriophages to nuclear pores, cilia, and synaptonemal complexes in large 3D cellular volumes

Predicting coaxial helical stacking in RNA junctions

RNA junctions are important structural elements that form when three or more helices come together in space in the tertiary structures of RNA molecules. Determining their structural configuration is important for predicting RNA 3D structure. We introduce a computational method to predict, at the secondary structure level, the coaxial helical stacking arrangement in junctions, as well as classify the junction topology. Our approach uses a data mining approach known as random forests, which relies on a set of decision trees trained using length, sequence and other variables specified for any given junction. The resulting protocol predicts coaxial stacking within three- and four-way junctions with an accuracy of 81% and 77%, respectively; the accuracy increases to 83% and 87%, respectively, when knowledge from the junction family type is included. Coaxial stacking predictions for the five to ten-way junctions are less accurate (60%) due to sparse data available for training. Additionally, our application predicts the junction family with an accuracy of 85% for three-way junctions and 74% for four-way junctions. Comparisons with other methods, as well applications to unsolved RNAs, are also presented. The web server Junction-Explorer to predict junction topologies is freely available at: http://bioinformatics.njit.edu/junction

Three Essential Ribonucleases—RNase Y, J1, and III—Control the Abundance of a Majority of Bacillus subtilis mRNAs

Bacillus subtilis possesses three essential enzymes thought to be involved in mRNA decay to varying degrees, namely RNase Y, RNase J1, and RNase III. Using recently developed high-resolution tiling arrays, we examined the effect of depletion of each of these enzymes on RNA abundance over the whole genome. The data are consistent with a model in which the degradation of a significant number of transcripts is dependent on endonucleolytic cleavage by RNase Y, followed by degradation of the downstream fragment by the 5′–3′ exoribonuclease RNase J1. However, many full-size transcripts also accumulate under conditions of RNase J1 insufficiency, compatible with a model whereby RNase J1 degrades transcripts either directly from the 5′ end or very close to it. Although the abundance of a large number of transcripts was altered by depletion of RNase III, this appears to result primarily from indirect transcriptional effects. Lastly, RNase depletion led to the stabilization of many low-abundance potential regulatory RNAs, both in intergenic regions and in the antisense orientation to known transcripts

A simple and efficient method to search for selected primary transcripts: non-coding and antisense RNAs in the human pathogen Enterococcus faecalis

Enterococcus faecalis is a commensal bacterium and a major opportunistic human pathogen. In this study, we combined in silico predictions with a novel 5′RACE-derivative method coined ‘5′tagRACE’, to perform the first search for non-coding RNAs (ncRNAs) encoded on the E. faecalis chromosome. We used the 5′tagRACE to simultaneously probe and characterize primary transcripts, and demonstrate here the simplicity, the reliability and the sensitivity of the method. The 5′tagRACE is complementary to tiling arrays or RNA-sequencing methods, and is also directly applicable to deep RNA sequencing and should significantly improve functional studies of bacterial RNA landscapes. From 45 selected loci of the E. faecalis chromosome, we discovered and mapped 29 novel ncRNAs, 10 putative novel mRNAs and 16 antisense transcriptional organizations. We describe in more detail the oxygen-dependent expression of one ncRNA located in an E. faecalis pathogenicity island, the existence of an ncRNA that is antisense to the ncRNA modulator of the RNA polymerase, SsrS and provide evidences for the functional interplay between two distinct toxin–antitoxin modules

nocoRNAc: Characterization of non-coding RNAs in prokaryotes

<p>Abstract</p> <p>Background</p> <p>The interest in non-coding RNAs (ncRNAs) constantly rose during the past few years because of the wide spectrum of biological processes in which they are involved. This led to the discovery of numerous ncRNA genes across many species. However, for most organisms the non-coding transcriptome still remains unexplored to a great extent. Various experimental techniques for the identification of ncRNA transcripts are available, but as these methods are costly and time-consuming, there is a need for computational methods that allow the detection of functional RNAs in complete genomes in order to suggest elements for further experiments. Several programs for the genome-wide prediction of functional RNAs have been developed but most of them predict a genomic locus with no indication whether the element is transcribed or not.</p> <p>Results</p> <p>We present <smcaps>NOCO</smcaps>RNAc, a program for the genome-wide prediction of ncRNA transcripts in bacteria. <smcaps>NOCO</smcaps>RNAc incorporates various procedures for the detection of transcriptional features which are then integrated with functional ncRNA loci to determine the transcript coordinates. We applied RNAz and <smcaps>NOCO</smcaps>RNAc to the genome of <it>Streptomyces coelicolor </it>and detected more than 800 putative ncRNA transcripts most of them located antisense to protein-coding regions. Using a custom design microarray we profiled the expression of about 400 of these elements and found more than 300 to be transcribed, 38 of them are predicted novel ncRNA genes in intergenic regions. The expression patterns of many ncRNAs are similarly complex as those of the protein-coding genes, in particular many antisense ncRNAs show a high expression correlation with their protein-coding partner.</p> <p>Conclusions</p> <p>We have developed <smcaps>NOCO</smcaps>RNAc, a framework that facilitates the automated characterization of functional ncRNAs. <smcaps>NOCO</smcaps>RNAc increases the confidence of predicted ncRNA loci, especially if they contain transcribed ncRNAs. <smcaps>NOCO</smcaps>RNAc is not restricted to intergenic regions, but it is applicable to the prediction of ncRNA transcripts in whole microbial genomes. The software as well as a user guide and example data is available at <url>http://www.zbit.uni-tuebingen.de/pas/nocornac.htm</url>.</p

Deep sequencing reveals as-yet-undiscovered small RNAs in Escherichia coli

<p>Abstract</p> <p>Background</p> <p>In <it>Escherichia coli</it>, approximately 100 regulatory small RNAs (sRNAs) have been identified experimentally and many more have been predicted by various methods. To provide a comprehensive overview of sRNAs, we analysed the low-molecular-weight RNAs (< 200 nt) of <it>E. coli </it>with deep sequencing, because the regulatory RNAs in bacteria are usually 50-200 nt in length.</p> <p>Results</p> <p>We discovered 229 novel candidate sRNAs (≥ 50 nt) with computational or experimental evidence of transcription initiation. Among them, the expression of seven intergenic sRNAs and three <it>cis</it>-antisense sRNAs was detected by northern blot analysis. Interestingly, five novel sRNAs are expressed from prophage regions and we note that these sRNAs have several specific characteristics. Furthermore, we conducted an evolutionary conservation analysis of the candidate sRNAs and summarised the data among closely related bacterial strains.</p> <p>Conclusions</p> <p>This comprehensive screen for <it>E. coli </it>sRNAs using a deep sequencing approach has shown that many as-yet-undiscovered sRNAs are potentially encoded in the <it>E. coli </it>genome. We constructed the <it>Escherichia coli </it>Small RNA Browser (ECSBrowser; <url>http://rna.iab.keio.ac.jp/</url>), which integrates the data for previously identified sRNAs and the novel sRNAs found in this study.</p