Real-time, portable genome sequencing for Ebola surveillance

By Joshua Quick, Nicholas J. Loman, S. Duraffour, Jared T. Simpson, E. Severi, L. Cowley, J. A. Boré, Raymond Koundouno, G. Dudas, A. Mikhail and 92 more. Nature, 2016

1,345 citations recorded by the source corpus.

The Ebola virus disease epidemic in West Africa is the largest on record, responsible for over 28,599 cases and more than 11,299 deaths. Genome sequencing in viral outbreaks is desirable to characterize the infectious agent and determine its evolutionary rate. Genome sequencing also allows the identification of signatures of host adaptation, identification and monitoring of diagnostic targets, and characterization of responses to vaccines and treatments. The Ebola virus (EBOV) genome substitution rate in the Makona strain has been estimated at between 0.87 × 10−3 and 1.42 × 10−3 mutations per site per year. This is equivalent to 16–27 mutations in each genome, meaning that sequences diverge rapidly enough to identify distinct sub-lineages during a prolonged epidemic. 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. Genomic surveillance during the epidemic has been sporadic owing to a lack of local sequencing capacity coupled with practical difficulties transporting samples to remote sequencing facilities. To address this problem, here we devise 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. We present sequence data and analysis of 142 EBOV samples collected during the period March to October 2015. We were able to generate results less than 24 h after receiving an Ebola-positive sample, with the sequencing process taking as little as 15–60 min. We show that real-time genomic surveillance is possible in resource-limited settings and can be established rapidly to monitor outbreaks.

Subfields: Ecology, Endocrinology, Infectious Diseases

View Paper: https://www.semanticscholar.org/paper/e8ed1741be5c2c17ee4d71507c10cc5ea82aaaf1

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Citations in the corpus

Detecting DNA cytosine methylation using nanopore sequencing (2017, methodology): “1 The nanopolish hidden Markov model In previous work [1, 2] we developed a hidden Markov model to calculate the probability of observing a sequence of electric current events e1, .”
The Third Revolution in Sequencing Technology. (2018, background): “The portability of the MinION allows for the first time sequencing in the field, which is of great importance for the survey of outbreaks in developing countries [72,73].”
Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10 (2018, background): “In particular, fast evolving viruses can now be tracked in near real-time (see, e.g. Quick et al. 2016) to understand their epidemiology and evolutionary dynamics.”
Nanopore sequencing and assembly of a human genome with ultra-long reads (2017, neutral): “GM12878 has been sequenced on a wide variety of platforms, and has well-validated variation call sets, which enabled us to benchmark our results 20 .”
Piercing the dark matter: bioinformatics of long-range sequencing and mapping (2018, methodology): “A final example has been how the hand-held, low-cost oxford nanopore minIon instrument was used for sequencing ebola 128 and Zika 129 virus isolates in West Africa and South America.”
Temporal Detection and Phylogenetic Assessment of SARS-CoV-2 in Municipal Wastewater (2020, background): “3).(25,43,44) The resulting assembly had nearly complete genome coverage (98.”
DeepNano: Deep recurrent neural networks for base calling in MinION nanopore reads (2016, background): “…and the possibility of analyzing the data in real time as they are produced, MinION is very promising for clinical applications, such as monitoring infectious disease outbreaks (Judge et al., 2015; Quick et al., 2015, 2016), and characterizing structural variants in cancer (Norris et al., 2016).”
In‐field molecular diagnosis of plant pathogens: recent trends and future perspectives (2018, background): “The small size and easy connection of the MinION makes it suitable for working even in remote locations (Quick et al., 2016).”
Towards a genomics-informed, real-time, global pathogen surveillance system (2017, methodology): “Importantly, the MinION has been used in field situations, including in diagnostic tent labora tories during the Ebola epidemic 22, 23 and in a roving busbased mobile laboratory in Brazil as part of the ZiBRA project 3, 24 .”
Mapping and elucidating the function of modified bases in DNA (2017, methodology): “Tomkova, M., McClellan, M., Kriaucionis, S. & Schuster-Boeckler, B. 5- hydroxymethylcytosine marks regions with reduced mutation frequency in human DNA.”
Microreact: visualizing and sharing data for genomic epidemiology and phylogeography (2016, methodology): “For example, since its release in June 2015, Microreact has been used and included in publications on the study of post-vaccine evolution of Streptococcus pneumoniae (Croucher et al. , 2015), of gene flow of Yersinia entero-colitica (Reuter et al. , 2015) and within the Ebola outbreak response (Gard”
GISAID: Global initiative on sharing all influenza data – from vision to reality (2017, background): “Such a trusted system could complement and take full advantage of the latest advances in rapid sequencing of specimens in the laboratory and in the field, for outbreak investigation [24] .”