GHOST: global hepatitis outbreak and surveillance technology

被引：31

作者：

Longmire, Atkinson G. ^{[1
,6
]}

Sims, Seth ^{[1
,2
,6
]}

Rytsareva, Inna ^{[1
]}

Campo, David S. ^{[1
]}

Skums, Pavel ^{[1
,2
]}

Dimitrova, Zoya ^{[1
]}

Ramachandran, Sumathi ^{[1
]}

Medrzycki, Magdalena ^{[1
]}

Thai, Hong ^{[1
]}

Ganova-Raeva, Lilia ^{[1
]}

Lin, Yulin ^{[1
]}

Punkova, Lili T. ^{[1
]}

Sue, Amanda ^{[1
]}

Mirabito, Massimo ^{[3
,6
]}

Wang, Silver ^{[3
,6
]}

Tracy, Robin ^{[3
,6
]}

Bolet, Victor ^{[5
]}

Sukalac, Thom ^{[3
]}

Lynberg, Chris ^{[4
]}

Khudyakov, Yury ^{[1
]}

机构：

[1] Ctr Dis Control & Prevent, Div Viral Hepatitis, Mol Epidemiol & Bioinformat Lab, Atlanta, GA 30333 USA

[2] Georgia State Univ, Dept Comp Sci, Atlanta, GA 30303 USA

[3] Ctr Dis Control & Prevent, NCHHSTP Informat Off, Atlanta, GA USA

[4] Ctr Dis Control & Prevent, IT Res & Dev Off, Atlanta, GA USA

[5] Ctr Dis Control & Prevent, ITSO Applicat Hosting Branch, Atlanta, GA USA

[6] Northrop Grumman Corp, Falls Church, VA USA

来源：

BMC GENOMICS | 2017年 / 18卷

关键词：

HVR1; HCV; Liver cancer; Threshold; Transmission; Outbreak detection; Surveillance; Public health; Cloud; Virtual diagnostics; C VIRUS-INFECTION; UNITED-STATES; VIRAL-HEPATITIS; YOUNG-ADULTS; MORTALITY; TRANSMISSION; POPULATION; CANCER; TOOL;

D O I：

10.1186/s12864-017-4268-3

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

Background: Hepatitis C is a major public health problem in the United States and worldwide. Outbreaks of hepatitis C virus (HCV) infections associated with unsafe injection practices, drug diversion, and other exposures to blood are difficult to detect and investigate. Effective HCV outbreak investigation requires comprehensive surveillance and robust case investigation. We previously developed and validated a methodology for the rapid and cost-effective identification of HCV transmission clusters. Global Hepatitis Outbreak and Surveillance Technology (GHOST) is a cloud-based system enabling users, regardless of computational expertise, to analyze and visualize transmission clusters in an independent, accurate and reproducible way. Results: We present and explore performance of several GHOST implemented algorithms using next-generation sequencing data experimentally obtained from hypervariable region 1 of genetically related and unrelated HCV strains. GHOST processes data from an entire MiSeq run in approximately 3 h. A panel of seven specimens was used for preparation of six repeats of MiSeq libraries. Testing sequence data from these libraries by GHOST showed a consistent transmission linkage detection, testifying to high reproducibility of the system. Lack of linkage among genetically unrelated HCV strains and constant detection of genetic linkage between HCV strains from known transmission pairs and from follow-up specimens at different levels of MiSeq-read sampling indicate high specificity and sensitivity of GHOST in accurate detection of HCV transmission. Conclusions: GHOST enables automatic extraction of timely and relevant public health information suitable for guiding effective intervention measures. It is designed as a virtual diagnostic system intended for use in molecular surveillance and outbreak investigations rather than in research. The system produces accurate and reproducible information on HCV transmission clusters for all users, irrespective of their level of bioinformatics expertise. Improvement in molecular detection capacity will contribute to increasing the rate of transmission detection, thus providing opportunity for rapid, accurate and effective response to outbreaks of hepatitis C. Although GHOST was originally developed for hepatitis C surveillance, its modular structure is readily applicable to other infectious diseases. Worldwide availability of GHOST for the detection of HCV transmissions will foster deeper involvement of public health researchers and practitioners in hepatitis C outbreak investigation.

引用

页数：12

共 34 条

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