Embedding next generation sequencing protocols in public health laboratories

将下一代测序方案嵌入公共卫生实验室

• 批准号: BB/N003985/1
• 负责人: Julian Marchesi
• 金额: $ 19.26万
• 依托单位: CARDIFF UNIVERSITY
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FN003985%2F1
• 关键词: Embedding; next; generation; sequencing; protocols

Clinical microbiology laboratories undertake thousands of tests in order to identify what pathogen is present in a clinical sample. When looking for bacteria, it is common to grow these organisms on selective media and report back to the clinician as to whether the test is positive or negative. However, for many bacteria, and for some samples in which there are several bacteria present, there is either no culture media available or due to the mixed nature of the sample, the results are confusing and difficult to interpret. Furthermore, depending on the organism which is being detected, the test can take 3 to 4 days before the clinician will be informed of the results and then make a decision on how to proceed with treatment. Additionally, several different tests may need to be undertaken before a positive result is reported. The application of molecular-based methods, which detect a DNA signal, have been used for many years in clinical microbiology laboratories to identify the presence of viruses. More recently, such DNA-based approaches have started to be adopted for the detection of bacterial pathogens in stool samples from patients with diarrhoea. However, these tests are specifically targeted at known pathogens, and in order to identify what pathogen is present, several tests have to be undertaken before a positive signal is detected. Next-generation sequencing platforms can provide a solution to these problems, they can allow for high throughput screening samples to detect pathogens and at the same time, no pre-knowledge is required as to what pathogen needs to be detected. The next generation sequencing technology can provide clinical microbiology laboratories with a one-stop solution to identifying pathogens in clinical specimens. This FLIP proposal aims to take this technology, which is currently being used for understanding how microbial fuel cells work (on developing it further), so it can be applied in a clinical setting. The interchange, Dr Ann Smith who is a computer scientist, will apply the knowledge of next-generation sequencing, and by Informatics pipelines will develop a simple user-friendly interface for analysing these datasets, and provide clinical microbiologists with access to this enabling technology.

临床微生物学实验室进行了数千次测试，以确定临床样本中存在的病原体。在寻找细菌时，通常是在选择性培养基上种植这些生物，并向临床医生报告该测试是阳性还是阴性。但是，对于许多细菌，对于存在几种细菌的某些样品，没有可用的培养基，或者由于样品的混杂性，结果令人困惑且难以解释。此外，根据要检测到的生物，该测试可能需要3到4天，才能将临床医生告知结果，然后就如何进行治疗做出决定。此外，在报告阳性结果之前，可能需要进行几种不同的测试。在临床微生物学实验室中使用了多年的基于分子的方法（分子方法检测DNA信号）来鉴定病毒的存在。最近，这种基于DNA的方法已开始被采用，以检测腹泻患者的粪便样品中的细菌病原体。但是，这些测试专门针对已知病原体，为了确定存在什么病原体，必须在检测到正信号之前进行几种测试。下一代测序平台可以为这些问题提供解决方案，它们可以允许高吞吐量筛查样品检测病原体，同时，对于需要检测到的病原体，不需要预先知识。下一代测序技术可以为临床微生物实验室提供一站式解决方案，以鉴定临床标本中的病原体。该翻转建议旨在采用这项技术，该技术目前正在用于了解微生物燃料电池的工作原理（进一步开发），因此可以在临床环境中应用。交换的安妮·史密斯博士（Ann Smith）是一名计算机科学家，将应用下一代测序的知识，通过信息学管道，将开发一个简单的用户友好界面，用于分析这些数据集，并为临床微生物学家提供访问该支持技术的临床微生物学家。