Implementation and Evaluation of the Clear Dx Platform for Sequencing SARS-CoV-2 Genomes in a Public Health Laboratory

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is an etiological agent of the ongoing coronavirus disease 2019 (COVID-19) pandemic, which has infected over 750 million people globally, with 1% mortality rate (World Health Organization, accessed 8 February 2023) (1). During this enormous human health crisis, whole-genome sequencing (WGS) has enabled public health agencies to identify circulating SARS-CoV-2 variants, understand vaccine breakthroughs and transmission patterns, and contact tracing investigations (2, 3). WGS involves library preparation, sequencing, and bioinformatics data analysis. However, manual library preparation and data analysis are immensely labor-intensive processes that likely increase workflow errors and reduce the consistency of results. This may have resulted in significant delays to real-time SARS-CoV-2 genomic surveillance and monitoring of the variants for public health action.

Clear Dx (Clear Labs, San Carlos, CA) is a fully automated platform for SARS-CoV-2 detection and genomic surveillance that goes from extracted RNA to bioinformatic data analysis without any human intervention, thereby reducing the analytical errors (4). The City of Milwaukee Health Department Laboratory (MHDL) has verified the performance characteristics of the Clear Dx WGS SARS-CoV-2 assay as recommended by the manufacturer. A total of 75 clinical specimens, such as nasopharyngeal and nasal swabs, comprising 54 SARS-CoV-2-positive specimens and 21 other respiratory viral-pathogen-positive specimens, but negative for SARS-CoV-2 (Table S1 in the supplemental material), from MHDL frozen specimen inventory were included for the verification. Of 54 SARS-CoV-2-positive specimens, 27 were previously sequenced either on the MinION (Oxford Nanopore Technologies, ONT) or MiSeq (Illumina Inc.) platform, while the remaining were sequenced first in Clear Dx and subsequently verified using the MiSeq platform. Two of the samples sequenced in Clear Dx subsequently failed in MiSeq; we therefore continued with the remaining 52 SARS-CoV-2-positive specimens. Based on the verification, 95.9% overall accuracy was obtained with sensitivity of 94.2% (49/52) (in terms of ≥90% genomic and ≥100× sequencing depth/coverages as quality control metrics [QC] of precisely identified SARS-CoV-2 lineage) and specificity of 100% (21/21) (in terms of no amplification and detection of SARS-CoV-2 in the specimens previously positive for other respiratory virus pathogens) (Fig. 1A and B; Table S1). The remaining three (3/52) SARS-CoV-2-positive specimens were assigned accurate lineages with only <90% genomic coverages in Clear Dx (Table S1). The genomic coverage ranges between 54.1 and 99.6% (median, 98.7%; mean, 96.8%) for Clear Dx-generated sequences and 83.9 to 100% (median, 98.9%; mean, 97.3%) for sequences from the other two platforms (Fig. 1B). These results suggest that coverage discrepancies were possibly caused by either an area of low amplification and sequence drop-out due to low performance of ARTIC V3 primer set in that region, or sequencing errors (5). Furthermore, the bases or regions with low amplification possibly caused an erroneous frameshift in the sequence assemblies. A further comparison of the sequences generated on Clear Dx and MinION or MiSeq platforms for 52 specimens identified 0 to 1 mutation difference (Table S1), suggesting that sequences were identical in all regions with coverage, and the same biological conclusions might be drawn irrespective of the sequencing platform and data analysis method.

For precision, 12 previously sequenced SARS-CoV-2-positive specimens that had diverse and descendant lineages with essential QC (in terms of ≥90% genomic and ≥100× sequencing depth/coverage) parameters were selected (Table S2). Repeatability was assessed by testing these specimens in duplicate in the same run by a single operator, and reproducibility was assessed in three separate runs on three different days by multiple operators. Both repeatability and reproducibility of base calling on all these 12 clinical samples met QC requirements, with genome coverage ranges between 97.6 and 99.6% for intra-runs (median, 99.6%; mean, 99.4%) and 91.5 to 99.6% for inter-runs (median, 98.7%; mean, 98.5%), respectively (Fig. 1C and D; Table S2). The sequencing depth ranged from 461× to 11,051× (median, 1,903.5×; mean, 2,692×) for intra- and 211× to 5,433× (median, 664.5×; mean, 1,356×) for interassays. The Nextclade-based analysis confirmed the accuracy in clade assignment for these 12 specimens, indicating the efficiency and stability of Clear Dx in characterizing SARS-CoV-2 genomes.

Between October 2021 and March 2022, an additional 1,440 nasopharyngeal/nasal swabs submitted to MHDL from the City of Milwaukee and surrounding communities were sequenced for SARS-CoV-2 genomes by the Clear Dx platform. Of 1,440 sequenced specimens, 1,224 (85%) of the sequences that fulfilled the established QC metrics were used for further analysis (Table S3) (4). The maximum likelihood phylogeny showed that these sequences were distributed into five clades, in which >95% of the sequences were derived from two clades (21K Omicron, 59.7%; 21J Delta, 35.9%) (Fig. 1E). During this study period, 43 lineages/sublineages belonging to five clades of SARS-CoV-2 were circulating in the local communities (Fig. 1E and F), of which BA.1.1 (22%), AY.103 (13.8%), and BA.1.15 (13.3%) were the most identified sublineages from these specimens (Fig. S1). The overall sequencing lineages from the Clear Dx platform correlate with the Wisconsin SARS-CoV-2 genomic surveillance data (3).

In conclusion, the sequence data generated by Clear Dx automated sequencing platform are being efficiently used for near real-time genomic surveillance, epidemiological investigations, and identifying SARS-CoV-2 variants circulating within the City of Milwaukee jurisdiction. Most importantly, the sequencing turnaround time has significantly decreased from 2 weeks to an average of 5 days from the date of specimen collection. This implementation has also reduced staffing hands-on time, thereby improving workforce capacity assisting other public health testing activities. Though SARS-CoV-2 genome sequencing by Clear Dx platform might be quicker and more user-friendly, the consumables are 1.5- and 2-fold more expensive than the consumables required to manually prepare libraries and sequence them on long-and short-read-based MinION and MiSeq sequencing platforms, respectively, per sample. In the near future, expanding this platform to sequence other emerging and reemerging infectious disease pathogens may potentially assist public health response during an outbreak investigation and surveillance activities.

All 1,224 SARS-CoV-2 genomes sequenced on the Clear Dx platform have been deposited with the Global Initiative on Sharing All Influenza Data (GISAID, https://www.gisaid.org/). The accession numbers for all these sequences are provided in Table S3.

We acknowledge the vital role of the Milwaukee Health Department (MHD) communicable disease and preparedness team in coordinating respiratory specimen collection, case investigations, and contact tracing. The authors are grateful to the partners from the University of Wisconsin—Milwaukee and Marquette University Clinics staff for their support. We appreciate all the support from the MHD administration and leadership team during this study, especially Commissioner of Health Kirsten Johnson and Heather Paradis for their careful review of the manuscript. Thanks to the MHD Laboratory staff and administrative staff who were involved in order entry, extraction of nucleic acids, SARS-CoV-2 PCR setup, and results reporting. Thanks to Kristin Schieble (Operational Manager) and Robert Murphy (CDC LLS Fellow) for assisting with cost analysis. The manuscript contents are those of the authors and do not necessarily represent the official views of, nor an endorsement by, by the City of Milwaukee Health Department.

This publication was partially supported by the Centers for Disease Control and Prevention of the United States Department of Health and Human Services (HHS) as part of a financial assistance award to Epidemiology and Laboratory Capacity for the Prevention and Control of Emerging Infectious Diseases (ELC) COVID-19 enhancing detection efforts.

We declare no conflicts of interest.