Development and Evaluation of an ARTIC-Based Amplicon Sequencing Assay for Whole-Genome Characterization of Respiratory Syncytial Virus

The Georgia Public Health Laboratory developed and validated a highly accurate, sensitive, and specific ARTIC-based amplicon sequencing assay using a modified Illumina protocol and custom bioinformatics pipeline to enable near real-time whole-genome surveillance of circulating Respiratory Syncytial Virus (RSV) strains.

The Gist

Imagine the Respiratory Syncytial Virus (RSV) as a sneaky, shape-shifting burglar that breaks into homes (our lungs), causing trouble for babies and the elderly. For a long time, public health detectives could only tell if the burglar was there and whether it was "Type A" or "Type B." But they couldn't see the burglar's fingerprints, their unique style, or if they were part of a new, dangerous gang.

This research paper is about how the Georgia Public Health Laboratory (GPHL) built a super-powered "fingerprint scanner" to catch these viruses in high definition.

Here is the story of how they did it, broken down into simple concepts:

1. The Problem: The Old Flashlight vs. The New Camera

Previously, the lab used a standard test (like a flashlight) to see if RSV was present. It was good at saying, "Yes, the burglar is here!" but it couldn't tell which specific version of the burglar it was. To understand how the virus is changing and spreading, they needed a high-resolution camera that could take a picture of the entire virus genome (its full instruction manual).

2. The Solution: The "ARTIC" Blueprint

The scientists tried two different ways to build this camera:

• The Custom Blueprint: They tried to design their own set of tools (primers) from scratch.
• The ARTIC Blueprint: They used a pre-made, proven set of tools (the ARTIC panel) that had been used successfully for other viruses.

The Result: The custom tools were a bit wobbly; they missed some parts of the virus (like a camera with a blurry lens). The ARTIC tools were sharp and clear, capturing the whole virus picture perfectly. So, the lab decided to use the ARTIC tools for the rest of the project.

3. The Process: How the "Fingerprint Scanner" Works

Think of the virus's genetic code as a very long, fragile book. You can't read the whole book at once because it's too big and breaks easily.

1. Cutting the Book: The scientists used the ARTIC tools to cut the virus's genetic book into tiny, manageable chapters (about 400 pages each).
2. Photocopying: They made millions of copies of these tiny chapters so they could read them clearly.
3. Scanning: They fed these copies into a high-tech machine (a NextSeq sequencer) that reads the text of every chapter.
4. Reassembling: A computer program (the "bioinformatics pipeline") took all those tiny chapters and glued them back together to recreate the full, original book.

4. The Test Drive: Did It Work?

The team tested this new system on 214 real patient samples (like test runs with actual burglar evidence).

• Accuracy: It was incredibly accurate. If the virus was there, the scanner found it 96% of the time.
• Sensitivity: It could find the virus even when there was very little of it (like spotting a single fingerprint on a dark night).
• Specificity: It didn't get confused by other viruses. If a patient had the Flu or a cold, the scanner correctly said, "No, this isn't RSV."
• Consistency: If three different people ran the test on the same sample, they all got the exact same result. It was reliable every time.

5. The Payoff: Why Does This Matter?

Now that Georgia has this "high-definition camera," they can do things that were impossible before:

• Track the Gang: They can see exactly which "lineage" (gang) of RSV is causing the current outbreak.
• Spot the Mutations: They can see if the virus is changing its shape (mutating) to become more dangerous or harder to treat.
• Stop the Spread: By knowing exactly who is spreading the virus and where, health officials can target their warnings and resources better, like putting up "Beware of Burglar" signs in the specific neighborhoods where the gang is active.

The Bottom Line

This paper describes the successful construction of a next-generation surveillance system. It's like upgrading from a grainy black-and-white security camera to a 4K color camera with facial recognition. This upgrade helps public health officials stay one step ahead of the virus, protecting communities by understanding the enemy better than ever before.

Technical Summary

1. Problem Statement

Respiratory Syncytial Virus (RSV) is a significant cause of acute respiratory infections, particularly in infants and the elderly. While current surveillance methods (such as RT-PCR and antigen testing) are effective for case detection and subtyping (RSV-A vs. RSV-B), they lack the resolution required for:

• Lineage classification: Identifying specific circulating strains.
• Variant tracking: Detecting emerging variants and mutations.
• Transmission dynamics: Understanding genetic relatedness and outbreak spread.

The Georgia Public Health Laboratory (GPHL) needed a robust, scalable Whole-Genome Sequencing (WGS) assay to transition from basic detection to high-resolution genomic surveillance to support data-driven public health responses.

2. Methodology

The study involved the development, optimization, and validation of an amplicon-based WGS workflow for RSV.

• Primer Design and Selection:

  • Two primer sets were evaluated: a custom-designed set (using PrimalScheme) and a published ARTIC-style set.
  • Custom Set: Designed using 82 RSV-A and 101 RSV-B genomes from GISAID. It utilized longer amplicons (750–800 bp for RSV-A; 650–700 bp for RSV-B) with 27 and 33 primer pairs, respectively.
  • ARTIC Set: Consisted of 50 primer pairs per subtype with shorter amplicons (~400 bp).
  • Selection: The ARTIC set was selected after side-by-side testing showed superior performance in sequencing depth and fewer amplicon dropouts compared to the custom set.

• Sample Collection and Extraction:

  • Specimens: 214 de-identified remnant clinical nasopharyngeal swabs (102 RSV-A, 112 RSV-B) collected in Georgia between Oct 2023 and April 2025.
  • Inclusion Criteria: Specimens with RT-PCR Cycle Quantification (Cq) values < 31.
  • Extraction: Automated using the Chemagic 360 instrument with the Chemagic Viral DNA/RNA 300 Kit.

• Library Preparation and Sequencing:

  • Adapted from the Illumina COVIDSeq Test (RUO) protocol.
  • Workflow: RNA extraction $\rightarrow$ cDNA synthesis $\rightarrow$ PCR amplification using ARTIC RSV primers (divided into even/odd pools) $\rightarrow$ Tagmentation $\rightarrow$ Indexing.
  • Platform: Illumina NextSeq 1000/2000 instruments.

• Bioinformatics Pipeline (GPHL-RSV-PIPE):

  • A custom, reference-based pipeline adapted from the ITER pipeline.
  • Steps: Adapter trimming (fastp), host read removal (Kraken2), k-mer detection (fastv), alignment to subtype-specific references (BBMap/BWA-MEM), primer trimming (iVar), consensus generation, and lineage assignment (Nextclade).
  • Thresholds: Positive samples required $\ge$10% k-mer coverage and mean read depth $\ge$500x. Validation criteria required $\ge$90% genomic coverage and mean depth $\ge$100x.

3. Key Contributions

• Assay Development: Successfully adapted the ARTIC primer strategy for RSV, optimizing it for the Illumina NextSeq platform.
• Bioinformatics Pipeline: Developed and validated the GPHL-RSV-PIPE, a reproducible, automated pipeline for RSV-A and RSV-B subtyping, assembly, and lineage classification.
• Validation Framework: Provided a comprehensive analytical validation including sensitivity, specificity, limits of detection (LOD), intra/inter-run precision, and performance in mixed infections.
• Surveillance Implementation: Established a near real-time genomic surveillance capability at GPHL, enabling the tracking of circulating lineages in Georgia.

4. Key Results

• Performance Comparison: The ARTIC primer set outperformed the custom set, with 78% of specimens showing higher mean depth and coverage. The custom set suffered from amplicon dropouts, particularly in the RSV-B genome (positions 8,300–8,800).
• Sequencing Metrics (Validated Specimens):
  • RSV-A: Median depth 53,433x; Median coverage 97.5%.
  • RSV-B: Median depth 49,699x; Median coverage 98.3%.
  • Pass Rates: 73.5% (75/102) for RSV-A and 67.9% (76/112) for RSV-B met validation criteria.
• Analytical Performance:
  • Accuracy: 92.8% (RSV-A) and 93.2% (RSV-B).
  • Sensitivity: 96.2% (RSV-A) and 97.4% (RSV-B).
  • Specificity: 87.2% (RSV-A) and 84.6% (RSV-B). Note: Specificity was slightly lower than 90% due to subtype misclassification in a few discordant PCR/WGS cases, likely due to primer-binding mutations in the PCR target regions.
  • LOD: 4.4 TCID₅₀/mL for RSV-A and 18.6 TCID₅₀/mL for RSV-B.
• Precision and Specificity:
  • Intra/Inter-run: Nearly 100% consensus genome identity with 0–6 nucleotide differences across replicates, operators, and instruments.
  • Cross-reactivity: No false positives detected in 31 non-RSV samples (including Influenza, SARS-CoV-2, Adenovirus, etc.).
  • Co-infection: Successfully detected and sequenced mixed RSV-A/RSV-B samples at various ratios.
• Phylogenetic Findings:
  • RSV-A: Predominant lineages were A.D.3.1 (35%) and A.D.5.2 (28%).
  • RSV-B: Dominated by lineage B.D.E.1 (91%).
  • The study confirmed greater lineage diversity in RSV-A compared to RSV-B in the sampled population.

5. Significance

This study demonstrates that an ARTIC-based amplicon sequencing assay is a robust, scalable, and cost-effective solution for public health laboratories to perform RSV genomic surveillance.

• Public Health Impact: The assay enables near real-time monitoring of viral evolution, identification of emerging variants, and assessment of transmission dynamics, which are critical for vaccine development and therapeutic strategies.
• Scalability: The workflow serves as a model for other public health labs to enhance their viral surveillance capabilities beyond SARS-CoV-2 and Influenza.
• Limitations & Future Work: The authors acknowledge that rapid viral evolution can lead to amplicon dropouts in primer-binding regions (specifically the G gene). They plan to routinely update primers to maintain high coverage as new variants emerge.

In conclusion, the GPHL has successfully transitioned from basic RSV detection to high-resolution genomic surveillance, strengthening the state's preparedness for future respiratory outbreaks.