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Efficient, wide-scale testing for SARS-CoV-2 is crucial for monitoring the incidence of the infection in the community. The gold standard for COVID-19 diagnosis is the molecular analysis of epithelial secretions from the upper respiratory system captured by nasopharyngeal (NP) or oropharyngeal swabs. Given the ease of collection, saliva has been proposed as a possible substitute to support testing at the population level. Here, we used a novel saliva collection device designed to favour the safe and correct acquisition of the sample, as well as the processivity of the downstream molecular analysis. We tested 1003 nasopharyngeal swabs and paired saliva samples self-collected by individuals recruited at a public drive-through testing facility. An overall moderate concordance (68%) between the two tests was found, with evidence that neither system can diagnose the infection in 100% of the cases. While the two methods performed equally well in symptomatic individuals, their discordance was mainly restricted to samples from convalescent subjects. The saliva test was at least as effective as NP swabs in asymptomatic individuals recruited for contact tracing. Our study describes a testing strategy of self-collected saliva samples, which is reliable for wide-scale COVID-19 screening in the community and is particularly effective for contact tracing.

Background: During its persistence in cystic fibrosis (CF) airways, P. aeruginosa develops a series of phenotypic changes by the accumulation of pathoadaptive mutations. A better understanding of the role of these mutations in the adaptive process, with particular reference to the development of multidrug resistance (MDR), is essential for future development of novel therapeutic approaches, including the identification of new drug targets and the implementation of more efficient antibiotic therapy. Although several whole-genome sequencing studies on P. aeruginosa CF lineages have been published, the evolutionary trajectories in relation to the development of antimicrobial resistance remain mostly unexplored to date. In this study, we monitored the adaptive changes of P. aeruginosa during its microevolution in the CF airways to provide an innovative, genome-wide picture of mutations and persistent phenotypes and to point out potential novel mechanisms allowing survival in CF patients under antibiotic therapy.Results: We obtained whole genome sequences of 40 P. aeruginosa clinical CF strains isolated at Trentino Regional Support CF Centre (Rovereto, Italy) from a single CF patient over an 8-year period (2007–2014). Genotypic analysis of the P. aeruginosa isolates revealed a clonal population dominated by the Sequence Type 390 and three closely related variants, indicating that all members of the population likely belong to the same clonal lineage and evolved from a common ancestor. While the majority of early isolates were susceptible to most antibiotics tested, over time resistant phenotypes increased in the persistent population. Genomic analyses of the population indicated a correlation between the evolution of antibiotic resistance profiles and phylogenetic relationships, and a number of putative pathoadaptive variations were identified.Conclusion: This study provides valuable insights into the within-host adaptation and microevolution of P. aeruginosa in the CF lung and revealed the emergence of an MDR phenotype over time, which could not be comprehensively explained by the variations found in known resistance genes. Further investigations on uncharacterized variations disclosed in this study should help to increase our understanding of the development of MDR phenotype and the poor outcome of antibiotic therapies in many CF patients.