Embedding next generation sequencing protocols in public health laboratories

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.

Public Health Wales (PHW) currently diagnoses pathogens in stool samples using the Luminex xTAG Gastrointestinal Pathogen Panel, however, the pathogen detection rate is low, 24.8%. To improve this detection rate, we will use next generation sequencing (NGS) and the SSU rRNA gene to profile hundreds of organisms in a sample simultaneously. We predict adoption of NGS will greatly improve the success of PHW to identify pathogens in clinical samples.

Additionally, we will develop bioinformatic pipelines to process and analyse the NGS data. We will use the SSU rRNA gene sequences and analyse the data with the bioinformatic software package Mothur using the MiSeq SOP Pipeline in the R environment. The aim being that the user will only have to "point" the program to the folder containing the raw reads (paired-end .fastq files) and the pipeline will perform all the necessary steps to provide a table of the most abundant species present in the sample. We aim for this method to improve on the current output from PHW existing approaches and we will benchmark against this test for 500 stool samples.

We will develop a novel, automated analytic NGS engine and graphical user interface for clinical laboratory users, which incorporates compatibility, consistency, flexibility, scalability, simplicity and modular features. For example, with respect to compatibility, the analytic engine needs to be able to run on several platforms such as Windows and Linux and in future tablets via cloud computing. The graphical interface will need to display the results in a meaningful manner for a clinician to understand the data. The aim is to design an interface so that the top ten species for each sample are automatically displayed and the user's input will be their own recondite knowledge base as to what is and isn't a pathogen. This project will significantly change how professional users examine clinical samples and data, without prior knowledge of NGS and statistical tools.

Impact for economy and society: The aim of this project, in accordance with the principal rationale protocol for public health research, is to improve health. From a clinical point of view, we aim to make an impact by improving techniques so that patients will be able to get their results as soon as possible, and apply clinical and epidemiological evidence to whole populations. The benefits will provide public health workers across the system with the knowledge, skills and tools to make the right decision at the right time based on the best available evidence. We will do this by efficiently generating, testing and processing data, adding to the evidence base and continuously working to translate this knowledge into diagnostic actions, which will improve and protect the public's health and wellbeing, and reduce inequalities. The benefits and impact will be to promote core next generation sequencing (NGS) tools and expertise, adopting open principles, and developing supporting standards and methodologies. The recent announcement to sequence the genomes of 100,000 NHS patients in the next 3 to 5 years means doctors will gain an understanding of the patient's genetic status and how it might influence management. As the infrastructure and capabilities develop, this will extend beyond the initial remit of conditions. Patient policy and ethics are at the core of medical and translational research. For a genomic revolution in the delivery of health care, much thought is needed to establish decision-making policies and future strategy for the regulatory, ethical, and financial framework. The project will build on this adoption of DNA techniques for guiding the patient journey and develop an automated pipeline to use NGS as a diagnostic tool for pathogen detection. The impact of developing such NGS tools is that it has the potential to make NGS available as a routine tool in clinical diagnostic laboratories.

Benefits to organisation:
Public Health Wales (PHW) would have access to technology of strategic importance, and be in a position to utilise expertise from the academic science base. Both organisations would develop from ongoing collaborations for future research grants. FLIP would increase the skill set for existing staff from the Public Health sector and academia. PHW will also have access to university consultancy facilities and financial support through grant funding. The project will develop an infrastructure to promote the sharing of ideas, data, techniques, tools and knowledge, and take a systematic approach to understanding users' needs, both internal and external, including developing the public health workforce. FLIP will introduce PHW to the latest in NGS as a means to process and analyse their large datasets, and demonstrate its benefits through microbial community analysis. NGS can be applied to other datasets not just stool samples (e.g., salvia samples). For example, NGS can be applied to epidemiology through the sequencing of viral species to facilitate the identification of novel virulence factors. Gene expression studies using RNA-Seq (NGS of RNA) have now started to replace the use of microarray analysis, providing researchers and clinicians with the ability to visualize RNA expression in sequence. The FLIP project will provide the foundation to apply NGS to PHW working environments. This research would pave the way for future research grant applications to explore other areas, such as targeted sequencing, whether of individual genes or whole panels of genomic regions aids in the rapid diagnosis of many genetic diseases.