The Ebola virus disease (EVD) epidemic in West Africa is the largest on record, responsible for >28,599 cases and >11,299 deaths 1. Genome sequencing in viral outbreaks is desirable in order to characterize the infectious agent to determine its evolutionary rate, signatures of host adaptation, identification and monitoring of diagnostic targets and responses to vaccines and treatments. The Ebola virus genome (EBOV) substitution rate in the Makona strain has been estimated at between 0.87 × 10−3 to 1.42 × 10−3 mutations per site per year. This is equivalent to 16 to 27 mutations in each genome, meaning that sequences diverge rapidly enough to identify distinct sub-lineages during a prolonged epidemic 2-7. Genome sequencing provides a high-resolution view of pathogen evolution and is increasingly sought-after for outbreak surveillance. Sequence data may be used to guide control measures, but only if the results are generated quickly enough to inform interventions 8. Genomic surveillance during the epidemic has been sporadic due to a lack of local sequencing capacity coupled with practical difficulties transporting samples to remote sequencing facilities 9. In order to address this problem, we devised a genomic surveillance system that utilizes a novel nanopore DNA sequencing instrument. In April 2015 this system was transported in standard airline luggage to Guinea and used for real-time genomic surveillance of the ongoing epidemic. Here we present sequence data and analysis of 142 Ebola virus (EBOV) samples collected during the period March to October 2015. We were able to generate results in less than 24 hours after receiving an Ebola positive sample, with the sequencing process taking as little as 15-60 minutes. We show that real-time genomic surveillance is possible in resource-limited settings and can be established rapidly to monitor outbreaks.

Despite the magnitude of the Ebola virus disease (EVD) outbreak in West Africa, there is still a fundamental lack of knowledge about the pathophysiology of EVD1. In particular, very little is known about human immune responses to Ebola virus (EBOV)2,3. Here, we have for the first time evaluated the physiology of the human T cell immune response in EVD patients at the time of admission at the Ebola Treatment Center (ETC) in Guinea, and longitudinally until discharge or death. Through the use of multiparametric flow cytometry established by the European Mobile Laboratory in the field, we have identified an immune signature that is unique in EVD fatalities. Fatal EVD was characterized by high percentage of CD4 and CD8 T cells expressing the inhibitory molecules cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and programmed cell death-1 (PD-1), which was correlated with elevated inflammatory markers and high virus load. Conversely, surviving individuals showed significantly lower expression of CTLA-4 and PD-1 as well as lower inflammation despite comparable overall T cell activation. Concommittant with virus clearance, survivors mounted a robust EBOV-specific T cell response. Our findings suggest that dysregulation of the T cell response is a key component of EVD pathophysiology.

WGS has come of age as a molecular typing tool to inform national surveillance of STEC O157; it can be used in real time to provide the highest strain-level resolution for outbreak investigation. WGS allows linked cases to be identified with unprecedented specificity and sensitivity that will facilitate targeted and appropriate public health investigations.

Surveillance of drug-resistant bacteria is essential for healthcare providers to deliver effective empirical antibiotic therapy. However, traditional molecular epidemiology does not typically occur on a timescale that could affect patient treatment and outcomes. Here, we present a method called 'genomic neighbour typing' for inferring the phenotype of a bacterial sample by identifying its closest relatives in a database of genomes with metadata. We show that this technique can infer antibiotic susceptibility and resistance for both Streptococcus pneumoniae and Neisseria gonorrhoeae. We implemented this with rapid k-mer matching, which, when used on Oxford Nanopore MinION data, can run in real time. This resulted in the determination of resistance within 10 min (91% sensitivity and 100% specificity for S. pneumoniae and 81% sensitivity and 100% specificity for N. gonorrhoeae from isolates with a representative database) of starting sequencing, and within 4 h of sample collection (75% sensitivity and 100% specificity for S. pneumoniae) for clinical metagenomic sputum samples. This flexible approach has wide application for pathogen surveillance and may be used to greatly accelerate appropriate empirical antibiotic treatment.