Whole-genome sequencing of SARS-CoV-2 in Uganda: implementation of the low-cost ARTIC protocol in resource-limited settings

Introduction

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19) which has now spread throughout the entire world, causing more than 175 million infections and over 3.7 million deaths globally.¹ During early 2020, whole-genome sequencing (WGS) enabled researchers to rapidly identify SARS-CoV-2, and knowing the genome sequence allowed rapid development of diagnostic tests and other appropriate tools needed for the response to this novel infection. Continued genome sequencing supports the monitoring of the disease’s spread, activity, viral evolution as well as emerging new viral variants.² The COVID-19 pandemic is still ongoing and the global response will have to continue for the foreseeable future; the World Health Organization (WHO) has recommended WGS to be further adopted as well as implemented in new settings and new uses to better understand the world of emerging pathogens and their interactions with humans in a variety of climates, ecosystems, cultures, lifestyles, biomes² and genetic backgrounds.

Uganda has had approximately 60,250 COVID-19 cases and 423 deaths by June 12, 2021.³ As more countries move to implement genome sequencing programmes, Uganda is among those embracing SARS-CoV-2 WGS. Of the 131 Uganda full SARS-CoV-2 genomes analysed in December 2020, 50 (38%) belonged to lineage A and the rest belonged to a variety of B lineages with the majority lineages being B.1 (N = 30; 23%) and B.1.5 (N = 17; 13%) which were found predominantly in cross border truck drivers seeking to enter the country.⁴ As of April 26, 2021, a total of 328 SARS-CoV-2 samples had been sequenced and deposited in the GISAID⁵ by the Uganda Virus Research Institute (UVRI).⁶ This represented 0.8% of the total COVID-19 cases that had been detected in the country at that time. This situation is very similar to almost all other African countries, yet this ongoing global pandemic has already demonstrated the importance of widespread access to rapid novel pathogen discovery and subsequent surveillance, as well as comprehensive pathogen information sharing.

We piloted sequencing of SARS-CoV-2 samples at the Molecular Diagnostics Laboratory located in the Department of Immunology and Molecular Biology, Makerere University for two reasons: (i) to test the feasibility of ARTIC amplicon-based genome sequencing at our local institution; and (ii) to extend genomic analyses for COVID-19 surveillance in Uganda. ARTIC protocol was selected due to its low cost and high sensitivity, as well as its scalability compared to other sequencing methods.⁷ Routine SARS-CoV-2 genome sequencing in many places still faces difficulties such as an unreliable supply-chain for WGS reagents, since many of these are imported from western countries, limited technical expertise as well as genomic infrastructure, and relatively high costs of genome sequencing. Consequently, this work also served as a feasibility study to assess the implementation, practicality, and adoption of ARTIC amplicon-based sequencing in Ugandan’s resource-limited settings, allowing future efforts to integrate and expand into routine laboratory diagnostic pipelines. This current study served as a proof-of-concept to extend genomic capacity for COVID-19 surveillance at Makerere University, College of Health Sciences (MakCHS) Molecular Diagnostic Laboratory. This laboratory has been performing SARS-CoV-2 reverse transcription quantitative polymerase chain reaction (RT-qPCR) since March 2020 and was among the first facilities in Uganda to be accredited by the Ministry of Health to carry out routine SARS-CoV-2 testing. We sought to perform WGS of 30 SARS-CoV-2 RT-qPCR positive samples using the COVID-19 ARTIC v3 amplicon-based sequencing protocol in our settings using the Illumina MiSeq sequencing platform. We considered samples based on the criteria below;

Methods

Sequencing and bioinformatics analysis

These samples had been collected and previously stored from patients diagnosed with COVID-19 using real-time RT-qPCR. Metadata associated with the patient samples included the date of sample collection, gender, nationality, and purpose of testing (Routine, Contact, Alert, Travelers, Quarantine, Case, and Professional jobs requiring COVID-19 PCR test). ARTIC amplicon-based sequencing was used to generate 400 bp amplicons with 75 bp overlaps covering the length of the ~ 29.9 kB SARS-CoV-2 genome as described elsewhere.¹² Briefly, cDNA synthesis was carried out with random primers (Protoscript II First Strand cDNA Synthesis Kit, E6560S) followed by PCR amplification using ARTIC primers. Genomic library preparation was carried out using the Nextera XT DNA Library Preparation kit (15032355) according to manufactures' recommendations, and sequencing was carried out on the Illumina MiSeq platform (Illumina, CA, USA) using MiSeq Reagent Kit v3 (600-cycle, #MS-102-3003), according to manufacturer’s protocol.

Quality control (QC) was carried out before viral genome fasta generation, as previously described.¹³ Briefly, demultiplexed fastq files generated by sequencing were used as an input data for the analysis. Reads were trimmed based on quality scores with a cutoff threshold of Q30 to remove low-quality regions, in addition to adapter sequences. QC assessment for sequence reads was performed using FastQC (v0.11.9)¹⁴ and MultiQC (v1.9).¹⁵

For those reads passing the QC cutoff, we used Pangolin COVID-19 lineage assigner (v3.0.5)¹⁶ to assign SARS-CoV-2 viral lineages. Phylogenetic analysis was carried out in order to understand the evolution of this virus within the Ugandan population, including other SARS-CoV-2 genomes from Uganda that had been submitted by the Uganda Virus Research Institute (UVRI) to the GISAID database by April 22, 2021, and only complete sequences were included, totaling 328 SARS-CoV-2 genomes.

Multiple sequence alignment of 328 Ugandan SARS-CoV-2 genomes and 28 from MakCHS Molecular Diagnostics Laboratory was performed using the web version of MAFFT v.7.475.¹⁷ In each alignment, the SARS-CoV-2 reference sequence (NCBI Reference Sequence: SARS-CoV-2 isolate Wuhan-Hu-1, complete genome, NC_045512.2) was included. The alignment from MAFFT was then subjected to snp-sites v2.3.3¹⁸ to generate a phylip file format, which was later used to infer a maximum likelihood tree using PhyML v3.3.3¹⁹ with the tool’s default parameters. The tree generated by PhyML was stored in a newick file format. The file was then uploaded to the interactive tree of life (iTOL v4.0)²⁰ - an online tool for phylogenetic tree display and annotation for visualization (Figure 1). We then used snipit v1.0.3²¹ to zoom into the 28 genomes from MakCHS sequencing lab to visualize their snps in reference to the SARS-CoV-2 reference genome (Figure 2).

Figure 1. Phylogenetic analysis of 356 SARS-CoV-2 genome isolates (Lineages A and B) from Uganda.

Figure 2. Nucleotide alignment showing variants covering the SARS-CoV-2 sample genome lengths.

Results

Discussion

Due to the fact that 28/30 of SARS-CoV-2 genomes were successfully sequenced on the MiSeq platform, we have demonstrated a proof-of-concept project on SARS-CoV-2 WGS using archived clinical nasopharyngeal swab samples from the IBRH3AU. This study has successfully optimized and validated SARS-CoV-2 WGS using the ARTIC amplicon sequencing protocol. This has enabled us to adopt SARS-CoV-2 WGS at MakCHS Molecular Diagnostic Laboratory. As of June 8, 2021, Uganda had registered 53,961 COVID-19 cases and more than half (~26,000) of the samples are stored at the IBR3HAU biorepository.

Globally, researchers are being encouraged to sequence and share more genomes of SARS-CoV-2 via the GISAID platform, and there are currently more than 1.8 million coronavirus genome sequences from 172 countries and territories, which is a great testament to the hard work of researchers around the world during the COVID-19 global pandemic.²² Ironically, approximately 98% of these genomes have been submitted by high-income countries, underscoring the need to build a similar capacity in lower-middle-income settings (LIMC).

In this study, we estimated that the cost of WGS per SARS-CoV-2 clinical specimen in our laboratory to be $110 compared to $57.87²³ in the United States using a multiplex PCR followed by sequencing on an Illumina MiSeq apparatus. In the United Arab Emirates, the cost of SARS-CoV-2 full genome sequencing was estimated to be ~$87 per specimen when sequencing 96 samples in a batch at 400× using the target enrichment method.²⁴ It should be noted that target enrichment sequencing is still a more cost-effective approach and is scalable in many settings that handle large volumes of these samples. As of June 8, 2021, GISAID had 1,885,406 hCoV-19 genomic data with only a total of 19,065 submissions being from Africa while on June 1 2021, a total of 4,843,874 COVID-19 cases and 130,814 deaths (CFR: 2.7%) had been reported in 55 African Union (AU) member states representing 3% of all cases reportedly globally.²⁵ However, a majority of the low-quality SARS-CoV-2 genomes submitted in this same online genome database have been submitted from sequencing facilities in Africa.

As many countries and territories globally continue to find the optimal approach in managing the health-related consequences of COVID-19, more laboratories in these settings must find the best or affordable protocols to implement WGS of SARS-CoV-2 to inform public health measures. We performed WGS of 30 samples and specifically successfully evaluated the performance of ARTIC SARS-CoV-2 sequencing protocol performance in our settings using the Illumina MiSeq platform. In this study, genomic libraries were generated using RNA samples isolated from either newly prepared nasopharyngeal swabs in AVL buffer, which is a lysis buffer intended for purifying viral nucleic acids, or previously collected and frozen nasopharyngeal swabs preserved in AVL buffer. Therefore, the findings of this study offer guidance on implementing the low-cost ARTIC SARS-CoV-2 genome sequencing protocol to study SARS-CoV-2 genomic variations in resource limited settings. Many of these settings are currently unable to perform real-time WGS of such samples either due to absence of sequencing infrastructure, which in some cases has been overcome by establishing collaborations with sequencing facilities in other countries and therefore requiring shipment of the samples, unsustainable supply of sequencing reagents, or lack of trained genomics and bioinformatics personnel. WGS of SARS-CoV-2 remains vital in elucidating COVID-19 disease²⁶ for the unforeseeable future as researchers globally continue to identify new SARS-CoV-2 variants of concern and interests such as B.1.1.7 (Alpha), B.1351 (Beta), P.1 (Gamma), B.1.617.2 (Delta) and B.1.427/B.1.429 (Epsilon), P.2 (Zeta), B.1.525 (B.1.525), P.3 (Theta), B.1.526 (Iota), and B.1.617.1 (Kappa) respectively.²⁷ WGS allows detection and characterization of these emerging viral variants, generating essential new information about their genomic, immunologic, virologic, epidemiologic, and clinical characteristics.

Incomplete epidemiological and clinical characteristics as well as lack of COVID-19 disease severity of study participants are some of the limitations of this study. Also, the small sample size used as well as sequencing of samples that had been collected from Kampala metropolitan area may not represent the true proportion of identified SARS-CoV-2 lineages and variants in Uganda during the study period.

We recommend the establishment of more collaborative consortia between researchers, as well between National Public Health Institutions in LIMCs and developed countries to build low-cost, sustainable, functioning pathogen genome sequencing facilities to accelerate pathogen discovery and outbreak surveillance using WGS. Furthermore, these facilities can equally utilize recently developed multiplex RT-qPCR assays to screen for SARS-CoV-2 variants of concern or interest and monitor their frequencies. These variant genotyping assays not only complement WGS in such settings but also offer a cost-effective way to identify which samples can be prioritized for WGS, especially those that are unidentifiable by routine genotyping tests. Even during the vaccination phase of COVID-19, documenting incidences and prevalence of these SARS-CoV-2 re-or-emerging variants is key in identifying vaccine escape mutants. This offers the opportunity for judicious use of WGS for rapid discovery of novel SARS-CoV-2 variants.

Conclusion

In conclusion, our proof-of-concept study shows that ARTIC SARS-CoV-2 sequencing protocol on Illumina MiSeq is sensitive and accurate at higher SARS-Cov-2 template concentration (e.g., Ct value <25) in the Ugandan settings. We successfully validated the protocol and evaluated the process in mappability, genome length, GC-content, viral genome coverage, and variations in SNV calling. The result of our study provides a thorough affirmation of carrying out whole-genome sequencing for clinical SARS-CoV-2 samples in resource limited settings, thereby providing information to mitigate the impact of COVID-19 on our society. We have further contributed to SARS-CoV-2 global dataset.

Author contributions

MLJ conceived and designed the study. EN and RK helped the patient nasopharyngeal swab sample collection. DPK, BSB, MW, ML, JMK, EK, SK and AFK performed experiments including RNA isolation, qRT-PCR, SARS-CoV-2 WGS library construction and sequencing. GM, SM, PN, SK and EK performed bioinformatics data analyses and drafted the manuscript. EN helped coordinate the project meetings and IRB application. All authors reviewed the final manuscript.