RR:C19 Evidence Scale rating by reviewer:
Reliable. The main study claims are generally justified by its methods and data. The results and conclusions are likely to be similar to the hypothetical ideal study. There are some minor caveats or limitations, but they would/do not change the major claims of the study. The study provides sufficient strength of evidence on its own that its main claims should be considered actionable, with some room for future revision.
This manuscript proposes a new methodology to evaluate mutations in the Spike gene of SARS-CoV-2 and reports the results of its application to about 25,000 samples analyzed in Austria from January through May 2021. The method to determine the mutations present in each sample is a combination of a reliable procedure for high-throughput processing of SARS-CoV-2 samples, SARSeq, and a sequencing strategy with slight but relevant modifications on the popular ARTIC protocol. This combination of procedures, which is described in detail to allow for easy implementation by other laboratories, further improves previous methods by reducing the number of steps without compromising reliability and efficiency. The result is a cheap and highly scalable system for identifying mutations in the most relevant portions of the S gene that might be applied with adequate equipment to simultaneously analyze thousands of samples.
The method proposed is very interesting as an alternative to whole genome sequencing for the surveillance of mutations in the spike gene and can identify new mutations in the portion of the gene covered by sequencing 13 amplicons. It has been used extensively by the authors in the surveillance of variants and mutations of interest in Austrian samples, a clear sign that the method can be applied in real-life conditions. The authors detail the strengths and weaknesses of the method when compared to the gold standard for the analysis of SARS-CoV-2 variants, complete genome sequencing. They also present several interesting comparisons to reinforce the reliability and precision of their approach, showing that efficiency and repeatability of the results are very high and more than enough for surveillance purposes, as originally designed. Nevertheless, there are two points that need to be considered when applying this methodology, denoted as SARSseq tiling: the method only analyzes 60% of the spike gene length, thus leaving aside a significant portion of potential mutations. The authors claim that none of the mutations of interest are associated with variants of concern or interest discovered so far is present in the absent regions. This might change in the future, but the method could also be adapted or extended easily to incorporate new regions in these or other portions of the viral genome. Another claim that is not fully backed by the data obtained is that the methodology can be applied to tens of thousands of samples in a single experiment. Their implementation includes only a few hundred samples, which is already a big improvement over other methods, and they simply analyze how it might be expanded to include several thousands in a single analysis. I doubt that these numbers are necessary, or even desirable in real-life conditions because a fast turnaround time is better than waiting to gather those many samples to reduce costs at the expense of a slower response.