Draft Genome Sequence of Amycolatopsis lurida NRRL 2430, Producer of the Glycopeptide Family Antibiotic Ristocetin.

We report here the first draft genome sequence for Amycolatopsis lurida NRRL 2430, the producer of the glycopeptide antibiotic ristocetin. The 9-Mbp genome is predicted to harbor 8,143 genes, including those belonging to the ristocetin biosynthesis cluster and 31 additional predicted secondary metabolite gene clusters.This work was supported by the grants from the Royal Society (516002.K5877/ROG) and the Medical Research Council (G0700141).This paper was originally published in Genome Announcements (Kwun MJ, Hong H-J, Genome Announcements 2014, 2(5):e01050-14. doi:10.1128/genomeA.01050-14)

The activity of glycopeptide antibiotics against resistant bacteria correlates with their ability to induce the resistance system.

Glycopeptide antibiotics containing a hydrophobic substituent display the best activity against vancomycin-resistant enterococci, and they have been assumed to be poor inducers of the resistance system. Using a panel of 26 glycopeptide derivatives and the model resistance system in Streptomyces coelicolor, we confirmed this hypothesis at the level of transcription. Identification of the structural glycopeptide features associated with inducing the expression of resistance genes has important implications in the search for more effective antibiotic structures.This work was supported by the Royal Society (516002.K5877/ROG) and the Medical Research Council (G0700141).This is the accepted manuscript version. The final version is available from ASM at http://aac.asm.org/content/early/2014/07/30/AAC.03668-14.abstract

Genome Sequence of Streptomyces toyocaensis NRRL 15009, Producer of the Glycopeptide Antibiotic A47934.

Here we report the draft genome sequence of Streptomyces toyocaensis strain NRRL 15009 which is the producer of the glycopeptide antibiotic A47934. The genome sequence is predicted to harbor a total of 26 secondary metabolite biosynthetic gene clusters including the A47934 cluster.This work was supported by grants from the Royal Society (516002.K5877/ ROG) and the Medical Research Council (G0700141).This is the final published version, also available from ASM at http://genomea.asm.org/content/2/4/e00749-14

Measurement Enhancement on Two-Dimensional Temperature Distribution of Methane-Air Premixed Flame Using SMART Algorithm in CT-TDLAS

In this study, the temperature distribution of the Methane-Air premixed flame was measured. In order to enhance the measurement accuracy of the CT-TDLAS (Computed tomography-tunable diode laser absorption spectroscopy), the SMART (simultaneous multiplicative algebraic reconstruction technique) algorithm has been adopted. Further, the SLOS (summation of line of sight) and the CSLOS (corrective summation of line of sight) methods have been adopted to increase measurement accuracies. It has been verified that the relative error for the temperatures measured by the thermocouples and calculated by the CT-TDLAS was about 10%

In Vivo Characterization of the Activation and Interaction of the VanR-VanS Two-Component Regulatory System Controlling Glycopeptide Antibiotic Resistance in Two Related Streptomyces Species.

This is the author accepted manuscript. The final version is available from the American Society for Microbiology via http://dx.doi.org/10.1128/AAC.01367-15The VanR-VanS two-component system is responsible for inducing resistance to glycopeptide antibiotics in various bacteria. We have performed a comparative study of the VanR-VanS systems from two streptomyces strains, Streptomyces coelicolor and Streptomyces toyocaensis, to characterize how the two proteins cooperate to signal the presence of antibiotics and to define the functional nature of each protein in each strain background. The results indicate that the glycopeptide antibiotic inducer specificity is determined solely by the differences between the amino acid sequences of the VanR-VanS two-component systems present in each strain rather than by any inherent differences in general cell properties, including cell wall structure and biosynthesis. VanR of S. coelicolor (VanRsc) functioned with either sensor kinase partner, while VanR of S. toyocaensis (VanRst) functioned only with its cognate partner, S. toyocaensis VanS (VanSst). In contrast to VanRsc, which is known to be capable of phosphorylation by acetylphosphate, VanRst could not be activated in vivo independently of a VanS sensor kinase. A series of amino acid sequence modifications changing residues in the N-terminal receiver (REC) domain of VanRst to the corresponding residues present in VanRsc failed to create a protein capable of being activated by VanS of S. coelicolor (VanSsc), which suggests that interaction of the response regulator with its cognate sensor kinase may require a region more extended than the REC domain. A T69S amino acid substitution in the REC domain of VanRst produced a strain exhibiting weak constitutive resistance, indicating that this particular amino acid may play a key role for VanS-independent phosphorylation in the response regulator protein.This work was supported by funding from the Medical Research Council, UK (G0700141) and the Royal Society, UK (516002.K5877/ROG). the American Society for Microbiology

SOLiDzipper: A High Speed Encoding Method for the Next-Generation Sequencing Data

Background Next-generation sequencing (NGS) methods pose computational challenges of handling large volumes of data. Although cloud computing offers a potential solution to these challenges, transferring a large data set across the internet is the biggest obstacle, which may be overcome by efficient encoding methods. When encoding is used to facilitate data transfer to the cloud, the time factor is equally as important as the encoding efficiency. Moreover, to take advantage of parallel processing in cloud computing, a parallel technique to decode and split compressed data in the cloud is essential. Hence in this review, we present SOLiDzipper, a new encoding method for NGS data. Methods The basic strategy of SOLiDzipper is to divide and encode. NGS data files contain both the sequence and non-sequence information whose encoding efficiencies are different. In SOLiDzipper, encoded data are stored in binary data block that does not contain the characteristic information of a specific sequence platform, which means that data can be decoded according to a desired platform even in cases of Illumina, Solexa or Roche 454 data. Results The main calculation time using Crossbow was 173 minutes when 40 EC2 nodes were involved. In that case, an analysis preparation time of 464 minutes is required to encode data in the latest DNA compression method like G-SQZ and transmit it on a 183 Mbit/s bandwidth. However, it takes 194 minutes to encode and transmit data with SOLiDzipper under the same bandwidth conditions. These results indicate that the entire processing time can be reduced according to the encoding methods used, under the same network bandwidth conditions. Considering the limited network bandwidth, high-speed, high-efficiency encoding methods such as SOLiDzipper can make a significant contribution to higher productivity in labs seeking to take advantage of the cloud as an alternative to local computing. Availability http://szipper.dinfree.com . Academic/non-profit: Binary available for direct download at no cost. For-profit: Submit request for for-profit license from the web-site

EVALUATION OF 3D MEASUREMENT USING CT-TDLAS

In order to satisfy the requirements of high quality and optimal material manufacturing process, it is important to control the environment of the manufacturing process. Depending on these processes, it is possible to improve the quality of the product by adjusting various gases. With the advent of the TDLAS (Tunable laser absorption spectroscopy) technique, the temperature and concentration of the gases can be measured simultaneously. Among them, CT-TDLAS (Computed tomography-tunable diode laser absorption spectroscopy) is the most important technique for measuring the distributions of temperature and concentration across the 2-dimensional planes. In this study, suggest a 3-dimensional measurement to consider the irregular flow of supplying gases. Used the SMART (simultaneous multiplicative algebraic reconstruction technique) algorithm among the CT algorithms. Phantom data sets have been generated by the using Gaussian distribution method. It can be shown expected temperature and concentration distributions. The HITRAN database in which the thermo-dynamical properties and the light spectra of H2O are listed were used for the numerical test. The relative average temperature error ratio in the results obtained by the SMART algorithm was about 3.2% for temperature. The maximum error was 86.8K

Measurement of Three-Dimensional Combustion Distribution using CT-TDLAS

에너지 자원을 효율적으로 사용하기 위해서는 연소 가스에 대한 정확한 측정이 필요하다. TDLAS 기술로 대상 가스의 온도와 농도를 동시 측정할 수 있다. 현재 가스의 정밀 제어가 필요한 산업공정에 2차원 또는 3차원의 정보를 측정한 실험적 보고는 미비하다. 본 연구에서는 산업공정의 연소를 제어하 고 모니터링하고자 CT-TDLAS 시스템을 이용한다. 메탄-공기 예혼합화염의 3차원 온도 분포는 CT-TDLAS 시스템에 의해 측정되었으며, 3차원 온도 분포는 2차원 셀의 5개 층으로 측정하였다. 특히 흡수 스펙트럼의 3차원 재구성에 SMART 알고리즘을 적용하였다. 열전대와 CT-TDLAS로 모든 층의 온도를 비교한 결과 온도의 평균 상대오차가 19.7K로 정확하게 측정되었다.In order to use energy resources efficiently, accurate measurement of combustion gases is necessary. Measurement of the temperature and concentration of a target gas is possible with tunable laser absorption spectroscopy (TDLAS) technique. The TDLAS technique can be used to control and monitor combustion in industrial processes. The 3-dimensional temperature distribution of methane-air premixed flame was measured using the constructed computed tomography tunable diode laser absorption spectroscopy (CT-TDLAS) system. The 3-dimensional temperature distributions are measured by five layers of the 2-dimensional cell. The simultaneous multiplicative algebraic reconstruction technique (SMART) algorithm was adopted for reconstructing the absorption coefficients on the meshes. As a result of comparing the temperatures for all the layers using thermocouples and the CT-TDLAS technique, it was possible to accurately measure the average relative error of temperature as 19.7 K