18 SARS-CoV-2 is a novel coronavirus currently causing a pandemic. We show 19 that the majority of amino acid positions, which differ between SARS-CoV-2 and the 20 closely related SARS-CoV, are differentially conserved suggesting differences in 21 biological behaviour. In agreement, novel cell culture models revealed differences 22between the tropism of SARS-CoV-2 and SARS-CoV. Moreover, cellular ACE2 23(SARS-CoV-2 receptor) and TMPRSS2 (enables virus entry via S protein cleavage) 24 levels did not reliably indicate cell susceptibility to SARS-CoV-2. SARS-CoV-2 and 25 SARS-CoV further differed in their drug sensitivity profiles. Thus, only drug testing 26 using SARS-CoV-2 reliably identifies therapy candidates. Therapeutic concentrations 27 of the approved protease inhibitor aprotinin displayed anti-SARS-CoV-2 activity. The 28 efficacy of aprotinin and of remdesivir (currently under clinical investigation against 29 SARS-CoV-2) were further enhanced by therapeutic concentrations of the proton 30 pump inhibitor omeprazole (aprotinin 2.7-fold, remdesivir 10-fold). Hence, our study 31 has also identified anti-SARS-CoV-2 therapy candidates that can be readily tested in 32 patients. 33 34

Motivation SARS-CoV-2 is a novel coronavirus currently causing a pandemic. Here, we performed a combined in-silico and cell culture comparison of SARS-CoV-2 and the closely related SARS-CoV. Results Many amino acid positions are differentially conserved between SARS-CoV-2 and SARS-CoV, which reflects the discrepancies in virus behaviour, i.e. more effective human-to-human transmission of SARS-CoV-2 and higher mortality associated with SARS-CoV. Variations in the S protein (mediates virus entry) were associated with differences in its interaction with ACE2 (cellular S receptor) and sensitivity to TMPRSS2 (enables virus entry via S cleavage) inhibition. Anti-ACE2 antibodies more strongly inhibited SARS-CoV than SARS-CoV-2 infection, probably due to a stronger SARS-CoV-2 S-ACE2 affinity relative to SARS-CoV S. Moreover, SARS-CoV-2 and SARS-CoV displayed differences in cell tropism. Cellular ACE2 and TMPRSS2 levels did not indicate susceptibility to SARS-CoV-2. In conclusion, we identified genomic variation between SARS-CoV-2 and SARS-CoV that may reflect the differences in their clinical and biological behaviour. Supplementary information Supplementary data are available at Bioinformatics online.

Motivation The potential of the Bombali virus, a novel Ebolavirus, to cause disease in humans remains unknown. We have previously identified potential determinants of Ebolavirus pathogenicity in humans by analysing the amino acid positions that are differentially conserved (specificity determining positions; SDPs) between human pathogenic Ebolaviruses and the non-pathogenic Reston virus. Here, we include the many Ebolavirus genome sequences that have since become available into our analysis and investigate the amino acid sequence of the Bombali virus proteins at the SDPs that discriminate between human pathogenic and non-human pathogenic Ebolaviruses. Results The use of 1408 Ebolavirus genomes (196 in the original analysis) resulted in a set of 166 SDPs (reduced from 180), 146 (88%) of which were retained from the original analysis. This indicates the robustness of our approach and refines the set of SDPs that distinguish human pathogenic Ebolaviruses from Reston virus. At SDPs, Bombali virus shared the majority of amino acids with the human pathogenic Ebolaviruses (63.25%). However, for two SDPs in VP24 (M136L, R139S) that have been proposed to be critical for the lack of Reston virus human pathogenicity because they alter the VP24-karyopherin interaction, the Bombali virus amino acids match those of Reston virus. Thus, Bombali virus may not be pathogenic in humans. Supporting this, no Bombali virus-associated disease outbreaks have been reported, although Bombali virus was isolated from fruit bats cohabitating in close contact with humans, and anti-Ebolavirus antibodies that may indicate contact with Bombali virus have been detected in humans. Availability and implementation Data files are available from https://github.com/wasslab/EbolavirusSDPsBioinformatics2019. Supplementary information Supplementary data are available at Bioinformatics online.

The recent West African Ebola virus pandemic, which affected >28,000 individuals increased interest in anti-Ebolavirus vaccination programs. Here, we systematically analyzed the requirements for a prophylactic vaccination program based on the basic reproductive number (R0, i.e., the number of secondary cases that result from an individual infection). Published R0 values were determined by systematic literature research and ranged from 0.37 to 20. R0s ≥ 4 realistically reflected the critical early outbreak phases and superspreading events. Based on the R0, the herd immunity threshold (Ic) was calculated using the equation Ic = 1 − (1/R0). The critical vaccination coverage (Vc) needed to provide herd immunity was determined by including the vaccine effectiveness (E) using the equation Vc = Ic/E. At an R0 of 4, the Ic is 75% and at an E of 90%, more than 80% of a population need to be vaccinated to establish herd immunity. Such vaccination rates are currently unrealistic because of resistance against vaccinations, financial/logistical challenges, and a lack of vaccines that provide long-term protection against all human-pathogenic Ebolaviruses. Hence, outbreak management will for the foreseeable future depend on surveillance and case isolation. Clinical vaccine candidates are only available for Ebola viruses. Their use will need to be focused on health-care workers, potentially in combination with ring vaccination approaches.

22The recent West African Ebola virus pandemic, which affected >28,000 individuals increased 23 interest in anti-Ebolavirus vaccination programs. Here, we systematically analyzed the 24 requirements for a prophylactic vaccination program based on the basic reproductive number 25 (R0, i.e. the number of secondary cases that result from an individual infection). Published R0 26 values were determined by a systematic literature research and ranged from 0.37 to 20. R0s 27 ≥4 realistically reflected the critical early outbreak phases and superspreading events. Based 28 on the R0, the herd immunity threshold (Ic) was calculated using the equation Ic=1-(1/R0). 29The critical vaccination coverage (Vc) needed to provide herd immunity was determined by 30 including the vaccine effectiveness (E) using the equation Vc=Ic/E. At an R0 of 4, the Ic is 31 75% and at an E of 90%, more than 80% of a population need to be vaccinated to establish 32 herd immunity. Such vaccination rates are currently unrealistic because of resistance against 33 vaccinations, financial/ logistical challenges, and a lack of vaccines that provide long-term 34 protection against all human-pathogenic Ebolaviruses. Hence, outbreak management will for 35 the foreseeable future depend on surveillance and case isolation. Clinical vaccine candidates 36 are only available for Ebola viruses. Their use will need to be focused on health care workers, 37 potentially in combination with ring vaccination approaches. 38 39