Open-Source Genomic Analysis of Shiga-Toxin–Producing<i>E. coli</i>O104:H4

Rohde, Holger; Qin, Junjie; Cui, Yu‐Jun; Li, Dongfang; Loman, Nicholas J.; Hentschke, Moritz; Chen, Wen‐Tong; Pu, Fei; Peng, Yangqing; Li, Junhua; Xing, Feng; Li, Shenghui; Yin, Li; Zhang, Zhaoxi; Yang, Xianwei; Zhao, Meiru; Wang, Peng; Guan, Yuanlin; Cen, Zhong; Zhao, Xiangna; Martin, Coralie; Kobbe, Robin; Loos, Sebastian; Oh, Jun; Yang, Liang; Danchin, Antoine; Gao, George F.; Song, Yajun; Li, Yingrui; Yang, Huanming; Wang, Jian; Xu, Jianguo; Pallen, Mark J.; Wang, Jun; Aepfelbacher, Martin; Yang, Ruifu

doi:10.1056/nejmoa1107643

Cited by 394 publications

(348 citation statements)

References 21 publications

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“…Detection of other virulence-associated genes characterizing both EAEC and EHEC indicated that the virulence backbone of the outbreak strain should be EAEC. In addition, bacteriophage-encoding Shiga toxin 2 was acquired from EHEC or an unknown environment, along with other antibiotics-resistant genes from unknown sources [33,[36][37][38]. …”

Section: The Pathogen Of E Coli O104 : H4mentioning

confidence: 99%

“…Concurrent with the epidemiological investigation, scientists around the world rushed to sequence the whole genome of the outbreak strains to understand their phenotypic and virulent features, as well as acquire the strain-specific sequences using in designation of PCR diagnostic primers [37,38,[40][41][42]. We sequenced one outbreak strain, TY2482, isolated by the University Medical Center Hamburg-Eppendorf during the early phase of the outbreak from a 16-yearold female patient suffering from hemorrhagic enterocolitis.…”

Section: Genome Sequencing and Comparative Genomics Of O104 : H4mentioning

confidence: 99%

“…About a week later, the sequencing data from the Illumina HiSeq 2000 sequencing system was acquired and used to improve the assembly results. Finally, one chromosome and three plasmids were assembled and identified from this strain [37].…”

Section: Genome Sequencing and Comparative Genomics Of O104 : H4mentioning

confidence: 99%

“…The EAEC strain 55989 was only associated with persistent diarrhea, whereas TY2482 can cause HUS [37]. We carried out whole genome comparative studies between the two strains to explore the possible genetic mechanisms of different virulence phenotypes.…”

Section: Genome Sequencing and Comparative Genomics Of O104 : H4mentioning

confidence: 99%

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Shiga toxin-producing Escherichia coli O104:H4: An emerging important pathogen in food safety

Cui

2013

Chin. Sci. Bull.

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In 2011, Shiga toxin-producing Escherichia coli O104 : H4 resulted in a large outbreak of bloody diarrhea and hemolytic uremic syndrome (HUS) in Germany and 15 other countries in Europe and North America. This event raised a serious public health crisis and caused more than two billion US dollars in economic losses. In this review, we describe the classification of E. coli, the Germany outbreak, and the characteristics and epidemical source-tracing of the causative agent. We also discuss the genomics analysis of the outbreak organism and propose an open-source genomics analysis as a new strategy in combating the emerging infectious diseases.

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Section: The Pathogen Of E Coli O104 : H4mentioning

confidence: 99%

Section: Genome Sequencing and Comparative Genomics Of O104 : H4mentioning

confidence: 99%

Section: Genome Sequencing and Comparative Genomics Of O104 : H4mentioning

confidence: 99%

Section: Genome Sequencing and Comparative Genomics Of O104 : H4mentioning

confidence: 99%

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Shiga toxin-producing Escherichia coli O104:H4: An emerging important pathogen in food safety

Cui

2013

Chin. Sci. Bull.

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“…Another potential trend is the rise of crowd‐sourced microbial bioinformatics analyses, performed by bioinformaticians around the globe – there have already been proof‐of‐principle cases (Rohde et al ., 2011; Gardy et al ., 2015) and we are likely to see more of this by 2020, particularly in response to public‐health emergencies. Similarly, microbial bioinformaticians are likely to embrace cloud computing (Drake, 2014), which brings economies of scale in effort and costs and liberates end users from the hassle of maintaining systems and setting up commonly used software, while also delivering improvements in the sharing of pipelines and data, which in turn will enhance the reproducibility of bioinformatics analyses.…”

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confidence: 99%

Microbial bioinformatics 2020

Pallen

2016

Microbial Biotechnology

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SummaryMicrobial bioinformatics in 2020 will remain a vibrant, creative discipline, adding value to the ever‐growing flood of new sequence data, while embracing novel technologies and fresh approaches. Databases and search strategies will struggle to cope and manual curation will not be sustainable during the scale‐up to the million‐microbial‐genome era. Microbial taxonomy will have to adapt to a situation in which most microorganisms are discovered and characterised through the analysis of sequences. Genome sequencing will become a routine approach in clinical and research laboratories, with fresh demands for interpretable user‐friendly outputs. The “internet of things” will penetrate healthcare systems, so that even a piece of hospital plumbing might have its own IP address that can be integrated with pathogen genome sequences. Microbiome mania will continue, but the tide will turn from molecular barcoding towards metagenomics. Crowd‐sourced analyses will collide with cloud computing, but eternal vigilance will be the price of preventing the misinterpretation and overselling of microbial sequence data. Output from hand‐held sequencers will be analysed on mobile devices. Open‐source training materials will address the need for the development of a skilled labour force. As we boldly go into the third decade of the twenty‐first century, microbial sequence space will remain the final frontier!

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A Culture-Independent Sequence-Based Metagenomics Approach to the Investigation of an Outbreak of Shiga-Toxigenic Escherichia coli O104:H4

Loman¹,

Constantinidou²,

Martin³

et al. 2013

JAMA

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HE OUTBREAK OF SHIGA-TOXIgenic Escherichia coli (STEC), which struck Germany in May-June 2011, illustrated the effects of a bacterial epidemic on a wealthy, modern, industrialized society, with more than 3000 cases and more than 50 deaths. 1 During an outbreak, rapid and accurate pathogen identification and characterization is essential for the management of individual cases and of an entire outbreak. Traditionally, clinical bacteriology has relied primarily on laboratory isolation of bacteria in pure culture as a prerequisite to identification and characterization of an outbreak strain. Often, however, in vitro culture proves slow, difficult, or even impossible, and recognition of an out-See also pp 1531 and 1533.

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Open-Source Genomic Analysis of Shiga-Toxin–ProducingE. coliO104:H4

Cited by 394 publications

References 21 publications

Shiga toxin-producing Escherichia coli O104:H4: An emerging important pathogen in food safety

Shiga toxin-producing Escherichia coli O104:H4: An emerging important pathogen in food safety

Microbial bioinformatics 2020

A Culture-Independent Sequence-Based Metagenomics Approach to the Investigation of an Outbreak of Shiga-Toxigenic Escherichia coli O104:H4

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