Dataset Information

InterARTIC: an interactive web application for whole-genome nanopore sequencing analysis of SARS-CoV-2 and other viruses.

ABSTRACT:

Motivation

InterARTIC is an interactive web application for the analysis of viral whole-genome sequencing (WGS) data generated on Oxford Nanopore Technologies (ONT) devices. A graphical interface enables users with no bioinformatics expertise to analyze WGS experiments and reconstruct consensus genome sequences from individual isolates of viruses, such as SARS-CoV-2. InterARTIC is intended to facilitate widespread adoption and standardization of ONT sequencing for viral surveillance and molecular epidemiology.

Results

We demonstrate the use of InterARTIC for the analysis of ONT viral WGS data from SARS-CoV-2 and Ebola virus, using a laptop computer or the internal computer on an ONT GridION sequencing device. We showcase the intuitive graphical interface, workflow customization capabilities and job-scheduling system that facilitate execution of small- and large-scale WGS projects on any common virus.

Availability and implementation

InterARTIC is a free, open-source web application implemented in Python that executes best-practice command line workflows from the ARTIC network. The application can be downloaded as a set of pre-compiled binaries that are compatible with all common Linux distributions, Windows with Linux subsystems, MacOSX and ARM systems. All code can be found on GitHub at https://github.com/Psy-Fer/interARTIC/ and documentation can be found at https://github.com/Psy-Fer/interARTIC/.

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Ferguson JM

PROVIDER: S-EPMC8826086 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

InterARTIC: an interactive web application for whole-genome nanopore sequencing analysis of SARS-CoV-2 and other viruses.

Ferguson James M JM Gamaarachchi Hasindu H Nguyen Thanh T Gollon Alyne A Tong Stephanie S Aquilina-Reid Chiara C Bowen-James Rachel R Deveson Ira W IW

Bioinformatics (Oxford, England) 20220201 5

<h4>Motivation</h4>InterARTIC is an interactive web application for the analysis of viral whole-genome sequencing (WGS) data generated on Oxford Nanopore Technologies (ONT) devices. A graphical interface enables users with no bioinformatics expertise to analyze WGS experiments and reconstruct consensus genome sequences from individual isolates of viruses, such as SARS-CoV-2. InterARTIC is intended to facilitate widespread adoption and standardization of ONT sequencing for viral surveillance and ...[more]

PMID: 34908106

Similar Datasets

Project description:Since the beginning of the Coronavirus Disease-19 (COVID-19) pandemic, multiple Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) mutations have been reported and led to the emergence of variants of concern (VOC) with increased transmissibility, virulence or immune escape. In parallel, the observation of viral fecal shedding led to the quantification of SARS-CoV-2 genomes in wastewater, providing information about the dynamics of SARS-CoV-2 infections within a population including symptomatic and asymptomatic individuals. Here, we aimed to adapt a sequencing technique initially designed for clinical samples to apply it to the challenging and mixed wastewater matrix, and hence identify the circulation of VOC at the community level. Composite raw sewage sampled over 24 h in two wastewater-treatment plants (WWTPs) from a city in western France were collected weekly and SARS-CoV-2 quantified by RT-PCR. Samples collected between October 2020 and May 2021 were submitted to whole-genome sequencing (WGS) using the primers and protocol published by the ARTIC Network and a MinION Mk1C sequencer (Oxford Nanopore Technologies, Oxford, United Kingdom). The protocol was adapted to allow near-full genome coverage from sewage samples, starting from ∼5% to reach ∼90% at depth 30. This enabled us to detect multiple single-nucleotide variant (SNV) and assess the circulation of the SARS-CoV-2 VOC Alpha, Beta, Gamma, and Delta. Retrospective analysis of sewage samples shed light on the emergence of the Alpha VOC with detection of first co-occurring signature mutations in mid-November 2020 to reach predominance of this variant in early February 2021. In parallel, a mutation-specific qRT-PCR assay confirmed the spread of the Alpha VOC but detected it later than WGS. Altogether, these data show that SARS-CoV-2 sequencing in sewage can be used for early detection of an emerging VOC in a population and confirm its ability to track shifts in variant predominance.

Project description:Severe acute respiratory syndrome (SARS-CoV-2) is responsible for the worldwide pandemic, COVID-19. The original viral whole-genome was sequenced by a high-throughput sequencing approach from the samples obtained from Wuhan, China. Real-time gene sequencing is the main parameter to manage viral outbreaks because it expands our understanding of virus proliferation, spread, and evolution. Whole-genome sequencing is critical for SARS-CoV-2 variant surveillance, the development of new vaccines and boosters, and the representation of epidemiological situations in the country. A significant increase in the number of COVID-19 cases confirmed in August 2021 in Kazakhstan facilitated a need to establish an effective and proficient system for further study of SARS-CoV-2 genetic variants and the development of future Kazakhstan's genomic surveillance program. The SARS-CoV-2 whole-genome was sequenced according to SARS-CoV-2 ARTIC protocol (EXP-MRT001) by Oxford Nanopore Technologies at the National Laboratory Astana, Kazakhstan to track viral variants circulating in the country. The 500 samples kindly provided by the Republican Diagnostic Center (UMC-NU) and private laboratory KDL "Olymp" were collected from individuals in Nur-Sultan city diagnosed with COVID-19 from August 2021 to May 2022 using real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR). All samples had a cycle threshold (Ct) value below 20 with an average Ct value of 17.03. The overall average value of sequencing depth coverage for samples is 244X. 341 whole-genome sequences that passed quality control were deposited in the Global initiative on sharing all influenza data (GISAID). The BA.1.1 (n = 189), BA.1 (n = 15), BA.2 (n = 3), BA.1.15 (n = 1), BA.1.17.2 (n = 1) omicron lineages, AY.122 (n = 119), B.1.617.2 (n = 8), AY.111 (n = 2), AY.126 (n = 1), AY.4 (n = 1) delta lineages, one sample B.1.1.7 (n = 1) belongs to alpha lineage, and one sample B.1.637 (n = 1) belongs to small sublineage were detected in this study. This is the first study of SARS-CoV-2 whole-genome sequencing by the ONT approach in Kazakhstan, which can be expanded for the investigation of other emerging viral or bacterial infections on the country level.

Project description:A new human coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged at the end of 2019 in Wuhan, China that caused a range of disease severities; including fever, shortness of breath, and coughing. This disease, now known as coronavirus disease 2019 (COVID-19), quickly spread throughout the world, and was declared a pandemic by the World Health Organization in March of 2020. As the disease continues to spread, providing rapid characterization has proven crucial to better inform the design and execution of control measures, such as decontamination methods, diagnostic tests, antiviral drugs, and prophylactic vaccines for long-term control. Our work at the United States Army's Combat Capabilities Development Command Chemical Biological Center (DEVCOM CBC) is focused on engineering workflows to efficiently identify, characterize, and evaluate the threat level of any potential biological threat in the field and more remote, lower resource settings, such as forward operating bases. While we have successfully established untargeted sequencing approaches for detection of pathogens for rapid identification, our current work entails a more in-depth sequencing analysis for use in evolutionary monitoring. We are developing and validating a SARS-CoV-2 nanopore sequencing assay, based on the ARTIC protocol. The standard ARTIC, Illumina, and nanopore sequencing protocols for SARS-CoV-2 are elaborate and time consuming. The new protocol integrates Oxford Nanopore Technology's Rapid Sequencing Kit following targeted RT-PCR of RNA extracted from human clinical specimens. This approach decreases sample manipulations and preparation times. Our current bioinformatics pipeline utilizes Centrifuge as the classifier for quick identification of SARS-CoV-2 and RAMPART software for verification and mapping of reads to the full SARS-CoV-2 genome. ARTIC rapid sequencing results, of previous RT-PCR confirmed patient samples, showed that the modified protocol produces high quality data, with up to 98.9% genome coverage at >1,000x depth for samples with presumably higher viral loads. Furthermore, whole genome assembly and subsequent mutational analysis of six of these sequences identified existing and unique mutations to this cluster, including three in the Spike protein: V308L, P521R, and D614G. This work suggests that an accessible, portable, and relatively fast sample-to-sequence process to characterize viral outbreaks is feasible and effective.

Dataset Information

InterARTIC: an interactive web application for whole-genome nanopore sequencing analysis of SARS-CoV-2 and other viruses.

Motivation

Results

Availability and implementation

Supplementary information

Publications

InterARTIC: an interactive web application for whole-genome nanopore sequencing analysis of SARS-CoV-2 and other viruses.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets