Structural basis for the inhibition of the SARS-CoV-2 RNA-dependent RNA polymerase by favipiravir-RTP (preprint)

The RNA polymerase inhibitor, favipiravir, is currently in clinical trials as a treatment for infection with SARS-CoV-2, despite limited information about the molecular basis for its activity. Here we report the structure of favipiravir ribonucleoside triphosphate (favipiravir-RTP) in complex with the SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) bound to a template:primer RNA duplex, determined by electron cryomicroscopy (cryoEM) to a resolution of 2.5 Ang. The structure shows clear evidence for the inhibitor at the catalytic site of the enzyme, and resolves the conformation of key side chains and ions surrounding the binding pocket. Polymerase activity assays indicate that the inhibitor is weakly incorporated into the RNA primer strand, and suppresses RNA replication in the presence of natural nucleotides. The structure reveals an unusual, non-productive binding mode of favipiravir-RTP at the catalytic site of SARS-CoV2 RdRp which explains its low rate of incorporation into the RNA primer strand. Together, these findings inform current and future efforts to develop polymerase inhibitors for SARS coronaviruses.

Preclinical study of DNA vaccines targeting SARS-CoV-2 (preprint)

To fight against the worldwide COVID-19 pandemic, the development of an effective and safe vaccine against SARS-CoV-2 is required. As potential pandemic vaccines, DNA or RNA vaccines, viral vector vaccines and protein-based vaccines have been rapidly developed to prevent pandemic spread worldwide. In this study, we designed plasmid DNA vaccine targeting the SARS-CoV-2 Spike glycoprotein (S protein) as pandemic vaccine, and the humoral, cellular, and functional immune responses were characterized to support proceeding to initial human clinical trials. After intramuscular injection of DNA vaccine encoding S protein with alum adjuvant (three times at 2-week intervals), the humoral immunoreaction, as assessed by anti-S protein or anti-receptor-binding domain (RBD) antibody titers, and the cellular immunoreaction, as assessed by antigen-induced IFN-g expression, were up-regulated. In IgG subclass analysis, IgG2b was induced as the main subclass. Based on these analyses, DNA vaccine with alum adjuvant preferentially induced Th1-type T cell polarization. We confirmed the neutralizing action of DNA vaccine-induced antibodies via two different methods, a binding assay of RBD recombinant protein with angiotensin-converting enzyme 2 (ACE2), a receptor of SARS-CoV-2, and pseudovirus assay. Further B cell epitope mapping analysis using a peptide array showed that most vaccine-induced antibodies recognized the S2 and RBD subunits, but not the S1 subunit. In conclusion, DNA vaccine targeting the spike glycoprotein of SARS-CoV-2 might be an effective and safe approach to combat the COVID-19 pandemic.

City-level SARS-CoV-2 sewage surveillance (preprint)

The COVID-19 pandemic created a global crisis impacting not only healthcare systems, but also world economies and society. Recent data have indicated that fecal shedding of SARS-CoV-2 is common, and that viral RNA can be detected in wastewater. This suggests that wastewater monitoring is a potentially efficient tool for both epidemiological surveillance, and early warning for SARS-CoV-2 circulation at the population level. In this study we sampled an urban wastewater infrastructure in the city of Ashkelon, Israel, during the end of the first COVID-19 wave in May 2020 when the number of infections seemed to be waning. We were able to show varying presence of SARS-CoV-2 RNA in wastewater from several locations in the city during two sampling periods. This was expressed as a new index, Normalized Viral Load (NVL), which can be used in different area scales to define levels of virus activity such as red (high) or green (no), and to follow morbidity in the population at tested area. Our index showed the rise in viral load between the two sampling periods (one week apart) and indicated an increase in morbidity that was evident a month later in the population. Thus, this methodology may provide an early indication for SARS-CoV-2 infection outbreak in a population before an outbreak is clinically apparent. HIGHLIGHTSO_LIDetecting the presence of SARS-CoV-2 virus RNA in urban wastewater C_LIO_LIThe city sewer system may provide an early indication for SARS-CoV-2 infection and may be used as early warning for SARS-CoV-2 outbreaks C_LIO_LINVL index defines various infected urban zones from red (high) to green (low) C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=128 SRC="FIGDIR/small/20215244v1_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@360a84org.highwire.dtl.DTLVardef@1ec8004org.highwire.dtl.DTLVardef@1c8ae93org.highwire.dtl.DTLVardef@3d670c_HPS_FORMAT_FIGEXP M_FIG C_FIG

A framework for optimizing COVID-19 testing policy using a Multi Armed Bandit approach (preprint)

Testing is an important part of tackling the COVID-19 pandemic. Availability of testing is a bottleneck due to constrained resources and effective prioritization of individuals is necessary. Here, we discuss the impact of different prioritization policies on COVID-19 patient discovery and the ability of governments and health organizations to use the results for effective decision making. We suggest a framework for testing that balances the maximal discovery of positive individuals with the need for population-based surveillance aimed at understanding disease spread and characteristics. This framework draws from similar approaches to prioritization in the domain of cyber-security based on ranking individuals using a risk score and then reserving a portion of the capacity for random sampling. This approach is an application of Multi-Armed-Bandits maximizing exploration/exploitation of the underlying distribution. We find that individuals can be ranked for effective testing using a few simple features, and that ranking them using such models we can capture 65% (CI: 64.7%-68.3%) of the positive individuals using less than 20% of the testing capacity or 92.1% (CI: 91.1%-93.2%) of positives individuals using 70% of the capacity, allowing reserving a significant portion of the tests for population studies. Our approach allows experts and decision-makers to tailor the resulting policies as needed allowing transparency into the ranking policy and the ability to understand the disease spread in the population and react quickly and in an informed manner.

Scientometric Trends for Coronaviruses and Other Emerging Viral Infections (preprint)

COVID-19 is the most rapidly expanding coronavirus outbreak in the past two decades. To provide a swift response to a novel outbreak, prior knowledge from similar outbreaks is essential. Here, we study the volume of research conducted on previous coronavirus outbreaks, specifically SARS and MERS, relative to other infectious diseases by analyzing over 35 million papers from the last 20 years. Our results demonstrate that previous coronavirus outbreaks have been understudied compared to other viruses. We also show that the research volume of emerging infectious diseases is very high after an outbreak and drops drastically upon the containment of the disease. This can yield inadequate research and limited investment in gaining a full understanding of novel coronavirus management and prevention. Independent of the outcome of the current COVID-19 outbreak, we believe that measures should be taken to encourage sustained research in the field.