Expanding the conversation on high-throughput virome sequencing standards to include consideration of microbial contamination sources.
Expanding the conversation on high-throughput virome sequencing standards to include consideration of microbial contamination sources.
复制标题
扩大有关高通量病毒组测序标准的讨论，以纳入对微生物污染源的考虑。
DOI：
10.1128/mbio.01989-14
复制
发表时间：
2014
期刊：
影响因子：
6.4
通讯作者：
Flemington,ErikK
中科院分区：
文献类型：
--
作者：
Strong,MichaelJ;Lin,Zhen;Flemington,ErikK
我们感谢Ladner和他的同事就高通量(HT)测序技术衍生的标准化病毒基因组序列进行的对话。在2014年5月至6月出版的《mBio(1)》杂志上发表的社论《高通量测序时代的病毒基因组测序标准》中，他们提出了标准化问题，并建议开发定义病毒基因组组合的类别。这些都是及时的讨论要点，可能会促进更强大的病毒基因组序列储存库。与此同时，他们的讨论可能会提出未来几年需要解决的其他重要问题。在一系列问题中，Ladner等人。描述使用羟色胺测序作为一种方法在全球范围内筛选微生物污染的病毒库。污染在这里是一个重要的问题，因为在宿主组织培养细胞中分离和维持病毒库存以及在哺乳动物物种中制造疫苗容易造成潜在的微生物污染。使用HT测序筛选生物制剂的安全性和纯度已被证明是有用的，例如在几种减毒活病毒疫苗中识别非传染性病毒序列，包括在人类轮状病毒疫苗制剂中识别猪圆环病毒[2]。羟色胺测序最近也被用来在接种了马源生物制剂的马身上鉴定神秘的泰勒氏病的病原体(3)。在这种情况下，由此产生的罪魁祸首被确定为一种新的病毒，泰勒氏病相关病毒(TDAV)(3)。除病毒污染物外，支原体属(Mycodium sp.)是细胞培养中的一种常见污染物，可以转移到病毒库中。纳米细菌。以前在一个美国牛群的100%牛血清中发现了这种细菌(4)，这可能导致细胞培养受到污染，因为它被发现干扰了细胞的生长(5)。毫无疑问，羟色胺测序的高灵敏度和高特异度使其非常适合于检测生物体中广泛的遗传物质。尽管有这种潜力，但这项技术还有一个不可想象的障碍需要解决。在过去的几年里，我们的实验室询问了HT测序数据集，以识别和表征病毒和细菌病原体(6-10)。在我们的调查过程中，我们注意到，在我们分析的几乎每个样本中，都有令人惊讶的高水平的微生物遗传物质，包括被认为是原始的样本。在斯特朗等人的工作中(11)，我们描述了微生物读数在跨队列、样本类型(例如，细胞系或活组织检查材料)和研究方案的测序数据中的渗透性。在那项研究中，我们确定大量微生物读数并不代表真正的感染，很可能来自样品准备/测序过程。一些污染源已经被
We thank Ladner and colleagues for their conversation about standardizing viral genome sequences derived from highthroughput (HT) sequencing technology. In their editorial “Standards for Sequencing Viral Genomes in the Era of High-Throughput Sequencing,” published in the May-June 2014 issue of mBio (1), they raise standardization issues and propose the development of categories to define viral genome assemblies. These are timely discussion points that will likely foster more robust repositories of viral genome sequences. At the same time, their discussion will likely raise additional issues that are important to address in the coming years. Among a number of issues, Ladner et al. describe the use of HT sequencing as an approach to globally screen viral stocks for microbial contamination. Contamination is an important issue here since the isolation and maintenance of viral stocks in host tissue culture cells and the manufacturing of vaccines in mammalian species lend themselves to potential microbial contamination. Screening biologicals for safety and purity using HT sequencing has already proven useful, as exemplified by the identification of noninfectious viral sequences in several live-attenuated viral vaccines, including the identification of porcine circovirus in a human rotavirus vaccine preparation (2). HT sequencing was also recently used to identify the causative agent of the mysterious Theiler’s disease in horses inoculated with equine-derived biologicals (3). In this case, the resulting culprit was identified as a novel virus, Theiler’s disease-associated virus (TDAV)(3). In addition to viral contaminants, Mycoplasma sp. is a common contaminant in cell culture that can be transferred to viral stocks. Nanobacteriumsp. was previously identified in 100% of cattle serum in a US herd (4), which likely led to the contamination of cell cultures where it was found to interfere with cell growth (5). Without a doubt, the high sensitivity and specificity of HT sequencing lend themselves exceedingly well to the detection of a broad range of genetic material across organisms. Despite this potential, there is an unassumed impediment to this technology that needs to be addressed.In the past several years, our laboratory has interrogated HT sequencing data sets for the identification and characterization of viral and bacterial pathogens (6–10). In the course of our investigations, we noted surprisingly high levels of a spectrum of microbial genetic materials in nearly every sample that we have analyzed, including samples that were thought to be pristine. In the work of Strong et al.(11), we describe the pervasiveness of microbial reads in sequencing data across cohorts, sample types (eg, cell line or biopsy material), and study protocols. In that study, we determine that the bulk of microbial reads did not represent bona fide infections and likely originated from sample preparation/sequencing procedures. Some sources of contamination have been