A Prediction Model to Prioritize Individuals for a SARS-CoV-2 Test Built from National Symptom Surveys.

BACKGROUND: The gold standard for COVID-19 diagnosis is detection of viral RNA through PCR. Due to global limitations in testing capacity, effective prioritization of individuals for testing is essential. METHODS: We devised a model estimating the probability of an individual to test positive for COVID-19 based on answers to 9 simple questions that have been associated with SARS-CoV-2 infection. Our model was devised from a subsample of a national symptom survey that was answered over 2 million times in Israel in its first 2 months and a targeted survey distributed to all residents of several cities in Israel. Overall, 43,752 adults were included, from which 498 self-reported as being COVID-19 positive. FINDINGS: Our model was validated on a held-out set of individuals from Israel where it achieved an auROC of 0.737 (CI: 0.712-0.759) and auPR of 0.144 (CI: 0.119-0.177) and demonstrated its applicability outside of Israel in an independently collected symptom survey dataset from the US, UK, and Sweden. Our analyses revealed interactions between several symptoms and age, suggesting variation in the clinical manifestation of the disease in different age groups. CONCLUSIONS: Our tool can be used online and without exposure to suspected patients, thus suggesting worldwide utility in combating COVID-19 by better directing the limited testing resources through prioritization of individuals for testing, thereby increasing the rate at which positive individuals can be identified. Moreover, individuals at high risk for a positive test result can be isolated prior to testing. FUNDING: E.S. is supported by the Crown Human Genome Center, Larson Charitable Foundation New Scientist Fund, Else Kroener Fresenius Foundation, White Rose International Foundation, Ben B. and Joyce E. Eisenberg Foundation, Nissenbaum Family, Marcos Pinheiro de Andrade and Vanessa Buchheim, Lady Michelle Michels, and Aliza Moussaieff and grants funded by the Minerva foundation with funding from the Federal German Ministry for Education and Research and by the European Research Council and the Israel Science Foundation. H.R. is supported by the Israeli Council for Higher Education (CHE) via the Weizmann Data Science Research Center and by a research grant from Madame Olga Klein - Astrachan.

The RapP-PhrP quorum-sensing system of Bacillus subtilis strain NCIB3610 affects biofilm formation through multiple targets, due to an atypical signal-insensitive allele of RapP.

The genome of Bacillus subtilis 168 encodes eight rap-phr quorum-sensing pairs. Rap proteins of all characterized Rap-Phr pairs inhibit the function of one or several important response regulators: ComA, Spo0F, or DegU. This inhibition is relieved upon binding of the peptide encoded by the cognate phr gene. Bacillus subtilis strain NCIB3610, the biofilm-proficient ancestor of strain 168, encodes, in addition, the rapP-phrP pair on the plasmid pBS32. RapP was shown to dephosphorylate Spo0F and to regulate biofilm formation, but unlike other Rap-Phr pairs, RapP does not interact with PhrP. In this work we extend the analysis of the RapP pathway by reexamining its transcriptional regulation, its effect on downstream targets, and its interaction with PhrP. At the transcriptional level, we show that rapP and phrP regulation is similar to that of other rap-phr pairs. We further find that RapP has an Spo0F-independent negative effect on biofilm-related genes, which is mediated by the response regulator ComA. Finally, we find that the insensitivity of RapP to PhrP is due to a substitution of a highly conserved residue in the peptide binding domain of the rapP allele of strain NCIB3610. Reversing this substitution to the consensus amino acid restores the PhrP dependence of RapP activity and eliminates the effects of the rapP-phrP locus on ComA activity and biofilm formation. Taken together, our results suggest that RapP strongly represses biofilm formation through multiple targets and that PhrP does not counteract RapP due to a rare mutation in rapP.