Embedding next generation sequencing protocols in public health laboratories

临床微生物学实验室进行数千次测试，以确定临床样本中存在何种病原体。当寻找细菌时，通常在选择性培养基上培养这些微生物，并向临床医生报告测试结果是阳性还是阴性。然而，对于许多细菌，以及对于存在多种细菌的一些样品，要么没有可用的培养基，要么由于样品的混合性质，结果令人困惑且难以解释。此外，根据检测到的微生物，测试可能需要3至4天，然后临床医生将被告知结果，然后决定如何进行治疗。此外，在报告阳性结果之前可能需要进行几种不同的测试。基于分子的检测DNA信号的方法的应用已经在临床微生物实验室中使用多年，以识别病毒的存在。最近，这种基于DNA的方法已开始用于检测腹泻患者粪便样本中的细菌病原体。然而，这些测试是专门针对已知的病原体，为了确定存在什么病原体，在检测到阳性信号之前必须进行几项测试。下一代测序平台可以为这些问题提供解决方案，它们可以允许高通量筛选样品以检测病原体，同时不需要关于需要检测什么病原体的预先知识。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，以识别临床标本中的病原体。这项FLIP提案的目的是利用这项技术，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），因此它可以应用于临床环境。交换，Ann Smith博士是一名计算机科学家，将应用下一代测序的知识，并通过信息学管道开发一个简单的用户友好界面来分析这些数据集，并为临床微生物学家提供使用这种使能技术的机会。

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.