A laboratory framework for ongoing optimization of amplification-based genomic surveillance programs

Abstract

This study provides a laboratory framework to ensure ongoing relevance and performance of amplification-based whole genome sequencing to strengthen public health surveillance during extended outbreaks or pandemics. The framework integrates regular reviews of the performance of a genomic surveillance system and highlights the importance of ongoing monitoring and the identification and implementation of improvements to whole genome sequencing methods to enhance public health responses to pathogen outbreaks.

Keywords: genomic surveillance; public health; viral sequencing; whole genome sequencing.

Fig 1

Violin and box plots for (A) ARTIC v4, (B) Midnight v1, and (C) CIDoMi SARS-CoV-2 whole genome sequencing (WGS) methods. Blue violin and box plots represent equimolar primer pools, whereas yellow violin and box plots have been calculated from primer pools that have been optimized and rebalanced based on sequence read fractions (SRFs) of amplicons from the ARTIC v3, Midnight v1, and CIDoMi SARS-CoV-2 WGS protocols. The black line (SRF = 1) represents ideal amplicon efficiency, and the red dotted line (i.e., SRF < 0.05) is the threshold for critically underperforming amplicons. Medians for all three optimized WGS protocols are higher than their respective equimolar protocols; however, no significant difference was observed (P > 0.1).

Fig 2

An alluvial plot demonstrating the changes in genomic clustering of 159 Delta variant of concern (VOC) samples as a result of simulated 5% (i), 15% (ii), and 25% (iii) reductions in genome coverage. Each horizonal bar within panels A to D represents a single Delta genome, which has been colored according to its cluster membership in panel A. Gray horizonal bars represent singleton Delta genomes that were not clustered. The colored and gray lines between columns trace the movement of individual samples into different genomic clusters as the level of genome coverage is reduced from panels A to D. Panel A depicts the true epidemiological and genomic clustering of all 159 genomes into 11 distinct clusters (depicted with vertical black boxes) when near-complete (>98%) genomes and comprehensive epidemiological data are available. Panels B, C, and D each represent genomic clustering with decreasing levels of genome coverage; (B) at 95% genome coverage, 11 genomic clusters are maintained, but Cluster 1 includes five additional epidemiologically unrelated singletons and excludes two epidemiologically linked cases; (C) at 85% genome coverage, only nine genomic clusters are defined with the loss of resolution of Cluster 2 and Cluster 3; and (D) at 75% genome coverage, only six genomic clusters are defined, with 18 cases known to be epidemiologically and genomically linked (at >98% coverage) that do not maintain the original cluster designation and 14 unlinked cases that join the largest genomic cluster (Cluster 1). The same set of 159 samples was used in each panel.

Fig 3

Genome coverage trends of 23,332 SARS-CoV-2 genomes collected in New South Wales (NSW) from January 2020 to 31 April 2022. (A) The upward trend in the median number of reads per genome over a rolling 1-week period; interquartile ranges of reads are shaded in gray. (B) Each colored dot corresponds to a genome designated as variants of concern (VOCs): Delta (blue), Omicron BA.1 (red) or Omicron BA.2 (yellow), or not typeable (gray). “Other lineage” (green) includes wild-type (Wuhan-like), Alpha, Beta, and Gamma variants. Changes in sequencing protocols over time (Long Amplification, ARTIC v3, and Midnight v1) are labeled in the background of the plot, while the distribution of percent genome coverage for each VOC category is shown in panel C.

Fig 4

A quality framework to maintain and ensure high-quality genomic surveillance of viral pathogens. The framework represents an ongoing iterative process to maintain quality control within a genomic surveillance system, particularly when utilizing amplification-based whole genome sequencing (WGS). Each box represents an action that needs to be taken following the initial establishment of amplification-based viral WGS, while the diamond indicates a decision that needs to be made after considering the outcomes of the WGS review, as well as any results from testing alternative WGS methods. Arrows show the direction between one action and the next and is accompanied by a description of potential outcomes associated with each action.