How much should we sequence? An analysis of the Swiss SARS-CoV-2 surveillance effort.

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 Swiss Pathogen Surveillance Platform - towards a nation-wide One Health data exchange platform for bacterial, viral and fungal genomics and associated metadata.

The Swiss Pathogen Surveillance Platform (SPSP) is a shared secure surveillance platform between human and veterinary medicine, to also include environmental and foodborne isolates. It enables rapid and detailed transmission monitoring and outbreak surveillance of pathogens using whole genome sequencing data and associated metadata. It features controlled data access, complex dynamic queries, dedicated dashboards and automated data sharing with international repositories, providing actionable results for public health and the vision to improve societal well-being and health.

Fifteen years SIB Swiss Institute of Bioinformatics: life science databases, tools and support.

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) was created in 1998 as an institution to foster excellence in bioinformatics. It is renowned worldwide for its databases and software tools, such as UniProtKB/Swiss-Prot, PROSITE, SWISS-MODEL, STRING, etc, that are all accessible on ExPASy.org, SIB's Bioinformatics Resource Portal. This article provides an overview of the scientific and training resources SIB has consistently been offering to the life science community for more than 15 years.

LC/MS data processing for label-free quantitative analysis.

In this chapter, we describe the use of SuperHirn and MSight, two complementary tools developed to the processing of label-free LC/MS data in view of the quantitation of proteomics samples. While MSight is mainly dedicated to the visualisation and navigation into LC/MS data, SuperHirn is specialised in peak detection, normalisation and alignment of LC/MS runs. These two tools can be used in a complementary way and one of the possible usages is described here.

A suite of tools to analyse and publish 2-DE data.

Bioinformatics tools may assist scientists in all steps of a typical 2-DE gel analysis workflow, that is, from the description of the sample preparation protocols, going through the gel image analysis and protein identification, to the publication of Internet-ready 2-DE gel databases. This short communication highlights in a single and summarised view, this workflow and the current bioinformatics solutions developed by the Proteome Informatics Group at the Swiss Institute of Bioinformatics.

Proteome informatics I: bioinformatics tools for processing experimental data.

Bioinformatics tools for proteomics, also called proteome informatics tools, span today a large panel of very diverse applications ranging from simple tools to compare protein amino acid compositions to sophisticated software for large-scale protein structure determination. This review considers the available and ready to use tools that can help end-users to interpret, validate and generate biological information from their experimental data. It concentrates on bioinformatics tools for 2-DE analysis, for LC followed by MS analysis, for protein identification by PMF, by peptide fragment fingerprinting and by de novo sequencing and for data quantitation with MS data. It also discloses initiatives that propose to automate the processes of MS analysis and enhance the quality of the obtained results.

Homeopathic treatment of children with attention deficit hyperactivity disorder: a randomised, double blind, placebo controlled crossover trial.

UNLABELLED: An increasing number of parents turn to homeopathy for treatment of their hyperactive child. Two publications, a randomised, partially blinded trial and a clinical observation study, conclude that homeopathy has positive effects in patients with attention deficit hyperactivity disorder (ADHD). The aim of this study was to obtain scientific evidence of the effectiveness of homeopathy in ADHD. A total of 83 children aged 6-16 years, with ADHD diagnosed using the Diagnostic and Statistical Manual of Mental Disorders-IV criteria, were recruited. Prior to the randomised, double blind, placebo controlled crossover study, they were treated with individually prescribed homeopathic medications. 62 patients, who achieved an improvement of 50% in the Conners' Global Index (CGI), participated in the trial. Thirteen patients did not fulfill this eligibility criterion (CGI). The responders were split into two groups and received either verum for 6 weeks followed by placebo for 6 weeks (arm A), or vice-versa (arm B). At the beginning of the trial and after each crossover period, parents reported the CGI and patients underwent neuropsychological testing. The CGI rating was evaluated again at the end of each crossover period and twice in long-term follow-up. At entry to the crossover trial, cognitive performance such as visual global perception, impulsivity and divided attention, had improved significantly under open label treatment (P<0.0001). During the crossover trial, CGI parent-ratings were significantly lower under verum (average 1.67 points) than under placebo (P =0.0479). Long-term CGI improvement reached 12 points (63%, P <0.0001). CONCLUSION: The trial suggests scientific evidence of the effectiveness of homeopathy in the treatment of attention deficit hyperactivity disorder, particularly in the areas of behavioural and cognitive functions.

MSight: an image analysis software for liquid chromatography-mass spectrometry.

Images obtained from high-throughput mass spectrometry (MS) contain information that remains hidden when looking at a single spectrum at a time. Image processing of liquid chromatography-MS datasets can be extremely useful for quality control, experimental monitoring and knowledge extraction. The importance of imaging in differential analysis of proteomic experiments has already been established through two-dimensional gels and can now be foreseen with MS images. We present MSight, a new software designed to construct and manipulate MS images, as well as to facilitate their analysis and comparison.