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用于食源性和水源性病毒病监测的宏基因组测序

Metagenomic Sequencing for Surveillance of Food- and Waterborne Viral Diseases.

作者信息

Nieuwenhuijse David F, Koopmans Marion P G

机构信息

Department of Viroscience, Erasmus Medical Center Rotterdam, Netherlands.

出版信息

Front Microbiol. 2017 Feb 15;8:230. doi: 10.3389/fmicb.2017.00230. eCollection 2017.

Abstract

A plethora of viruses can be transmitted by the food- and waterborne route. However, their recognition is challenging because of the variety of viruses, heterogeneity of symptoms, the lack of awareness of clinicians, and limited surveillance efforts. Classical food- and waterborne viral disease outbreaks are mainly caused by caliciviruses, but the source of the virus is often not known and the foodborne mode of transmission is difficult to discriminate from human-to-human transmission. Atypical food- and waterborne viral disease can be caused by viruses such as hepatitis A and hepatitis E. In addition, a source of novel emerging viruses with a potential to spread via the food- and waterborne route is the repeated interaction of humans with wildlife. Wildlife-to-human adaptation may give rise to self- limiting outbreaks in some cases, but when fully adjusted to the human host can be devastating. Metagenomic sequencing has been investigated as a promising solution for surveillance purposes as it detects all viruses in a single protocol, delivers additional genomic information for outbreak tracing, and detects novel unknown viruses. Nevertheless, several issues must be addressed to apply metagenomic sequencing in surveillance. First, sample preparation is difficult since the genomic material of viruses is generally overshadowed by host- and bacterial genomes. Second, several data analysis issues hamper the efficient, robust, and automated processing of metagenomic data. Third, interpretation of metagenomic data is hard, because of the lack of general knowledge of the virome in the food chain and the environment. Further developments in virus-specific nucleic acid extraction methods, bioinformatic data processing applications, and unifying data visualization tools are needed to gain insightful surveillance knowledge from suspect food samples.

摘要

大量病毒可通过食物和水传播途径传播。然而,由于病毒种类繁多、症状异质性、临床医生缺乏认识以及监测工作有限,对它们的识别具有挑战性。典型的食物和水传播病毒性疾病暴发主要由杯状病毒引起,但病毒来源往往不明,且食物传播途径难以与人际传播区分开来。非典型的食物和水传播病毒性疾病可由甲型肝炎和戊型肝炎等病毒引起。此外,人类与野生动物的反复接触是一种具有通过食物和水传播途径传播潜力的新型病毒的来源。在某些情况下,野生动物向人类的适应性可能会引发自限性疫情,但当完全适应人类宿主时可能具有毁灭性。宏基因组测序已被研究作为一种有前景的监测解决方案,因为它可以在单一方案中检测所有病毒,为疫情追踪提供额外的基因组信息,并检测新型未知病毒。然而,要在监测中应用宏基因组测序,必须解决几个问题。首先,样本制备困难,因为病毒的基因组材料通常被宿主和细菌基因组掩盖。其次,几个数据分析问题阻碍了宏基因组数据的高效、稳健和自动化处理。第三,宏基因组数据的解释很困难,因为缺乏对食物链和环境中病毒组的一般了解。需要在病毒特异性核酸提取方法、生物信息学数据处理应用以及统一数据可视化工具方面取得进一步进展,以便从可疑食物样本中获得有洞察力的监测知识。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e03/5309255/adc4333b9b3d/fmicb-08-00230-g001.jpg

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