Biolytix (Switzerland)

During the SARS-CoV-2 pandemic, many countries directed substantial resources toward genomic surveillance to detect and track viral variants. There is a debate over how much sequencing effort is necessary in national surveillance programs for SARS-CoV-2 and future pandemic threats. We aimed to investigate the effect of reduced sequencing on surveillance outcomes in a large genomic data set from Switzerland, comprising more than 143k sequences. We employed a uniform downsampling strategy using 100 iterations each to investigate the effects of fewer available sequences on the surveillance outcomes: (i) first detection of variants of concern (VOCs), (ii) speed of introduction of VOCs, (iii) diversity of lineages, (iv) first cluster detection of VOCs, (v) density of active clusters, and (vi) geographic spread of clusters. The impact of downsampling on VOC detection is disparate for the three VOC lineages, but many outcomes including introduction and cluster detection could be recapitulated even with only 35% of the original sequencing effort. The effect on the observed speed of introduction and first detection of clusters was more sensitive to reduced sequencing effort for some VOCs, in particular Omicron and Delta, respectively. A genomic surveillance program needs a balance between societal benefits and costs. While the overall national dynamics of the pandemic could be recapitulated by a reduced sequencing effort, the effect is strongly lineage-dependent-something that is unknown at the time of sequencing-and comes at the cost of accuracy, in particular for tracking the emergence of potential VOCs.IMPORTANCESwitzerland had one of the most comprehensive genomic surveillance systems during the COVID-19 pandemic. Such programs need to strike a balance between societal benefits and program costs. Our study aims to answer the question: How would surveillance outcomes have changed had we sequenced less? We find that some outcomes but also certain viral lineages are more affected than others by sequencing less. However, sequencing to around a third of the original effort still captured many important outcomes for the variants of concern such as their first detection but affected more strongly other measures like the detection of first transmission clusters for some lineages. Our work highlights the importance of setting predefined targets for a national genomic surveillance program based on which sequencing effort should be determined. Additionally, the use of a centralized surveillance platform facilitates aggregating data on a national level for rapid public health responses as well as post-analyses.

The authenticity of food is of increasing importance for producers, retailers and consumers. All groups benefit from the correct labelling of the contents of food products. Producers and retailers want to guarantee the origin of their products and check for adulteration with cheaper or inferior ingredients. Consumers are also more demanding about the origin of their food for various socioeconomic reasons. In contrast to this increasing demand, correct labelling has become much more complex because of global transportation networks of raw materials and processed food products. Within the European integrated research project ‘Tracing the origin of food’ (TRACE), a DNA-based multiplex detection tool was developed—the padlock probe ligation and microarray detection (PPLMD) tool. In this paper, this method is extended to a 15-plex traceability tool with a focus on products of commercial importance such as the emmer wheat Farro della Garfagnana (FdG) and Basmati rice. The specificity of 14 plant-related padlock probes was determined and initially validated in mixtures comprising seven or nine plant species/varieties. One nucleotide difference in target sequence was sufficient for the distinction between the presence or absence of a specific target. At least 5% FdG or Basmati rice was detected in mixtures with cheaper bread wheat or non-fragrant rice, respectively. The results suggested that even lower levels of (un-)intentional adulteration could be detected. PPLMD has been shown to be a useful tool for the detection of fraudulent/intentional admixtures in premium foods and is ready for the monitoring of correct labelling of premium foods worldwide.