了解肠道聚集性大肠杆菌O104: H4的毒力

Q4 Health Professions International Journal of Bioinformatics Research and Applications Pub Date : 2015-05-01 DOI:10.1504/IJBRA.2015.069185

B. Kesavan, K. Srividhya, S. Krishnaswamy, M. Raja, N. Vidya, A. Mohan

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引用次数: 2

摘要

O104:H4是一种新的大肠杆菌菌株，在德国引起了疫情。它是从血性腹泻和溶血性尿毒症综合征(HUS)患者中分离出来的。华大基因(www.genomics.cn)对这一新菌株进行了测序和组装。据报道，它对许多对其他大肠杆菌有毒的药物有抗药性，并在感染期间引起严重并发症，最终导致死亡。该菌株具有多药耐药性和高毒力，被认为是通过水平基因转移从不同来源获得的。利用DRAD、prophage Finder和PHAST三种计算工具，从新菌株中共检测到38个噬菌体元件。对这些原噬菌体元件的分析显示了许多毒力蛋白如志贺毒素和多重耐药蛋白编码基因。该菌株的高毒力可能与从其微环境中获得的前噬菌体元素有关。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Understanding the virulence of the entero-aggregative E. coli O104: H4

O104:H4 is a new strain of E. coli that has caused an outbreak in Germany. It was isolated from patients with bloody diarrhoea and Haemolytic Uremic Syndrome (HUS). BGI (www.genomics.cn) sequenced and assembled this new strain. It was reported to show resistance to a number of drugs that are toxic to other E. coli and causes serious complications during infections, which ultimately lead to death. Multi-drug resistance and high virulence of this strain is thought to be acquired from different sources, by horizontal gene transfer. A total of 38 prophage elements were detected from the new strain by using three computational tools viz., DRAD, Prophage Finder and PHAST. Analysis on these prophage elements shows a number of virulence proteins like Shiga toxin and multi-drug resistance protein encoding genes. The high virulence of the strain could be attributed by the prophage elements acquired from its micro environment.

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来源期刊

International Journal of Bioinformatics Research and Applications Health Professions-Health Information Management

CiteScore

0.60

自引率

0.00%

发文量

期刊介绍： Bioinformatics is an interdisciplinary research field that combines biology, computer science, mathematics and statistics into a broad-based field that will have profound impacts on all fields of biology. The emphasis of IJBRA is on basic bioinformatics research methods, tool development, performance evaluation and their applications in biology. IJBRA addresses the most innovative developments, research issues and solutions in bioinformatics and computational biology and their applications. Topics covered include Databases, bio-grid, system biology Biomedical image processing, modelling and simulation Bio-ontology and data mining, DNA assembly, clustering, mapping Computational genomics/proteomics Silico technology: computational intelligence, high performance computing E-health, telemedicine Gene expression, microarrays, identification, annotation Genetic algorithms, fuzzy logic, neural networks, data visualisation Hidden Markov models, machine learning, support vector machines Molecular evolution, phylogeny, modelling, simulation, sequence analysis Parallel algorithms/architectures, computational structural biology Phylogeny reconstruction algorithms, physiome, protein structure prediction Sequence assembly, search, alignment Signalling/computational biomedical data engineering Simulated annealing, statistical analysis, stochastic grammars.