IFNγ and TNF-α, produced by T cells, reduce levels of HBV cccDNA in hepatocytes by inducing deamination and subsequent cccDNA decay.

As the SARS-CoV-2 pandemic continues to spread, thousands of scientists around the globe have changed research direction to understand better how the virus works and to find out how it may be tackled. The number of manuscripts on preprint servers is soaring and peer-reviewed publications using mass spectrometry-based proteomics are beginning to emerge. To facilitate proteomic research on SARS-CoV-2, this report presents deep-scale proteomes (10,000 proteins; >130,000 peptides) of common cell line models, notably Vero E6, Calu-3, Caco-2, and ACE2-A549 that characterize their protein expression profiles including viral entry factors such as ACE2 or TMPRSS2. Using the 9 kDa protein SRP9 and the breast cancer oncogene BRCA1 as examples, we show how the proteome expression data can be used to refine the annotation of protein-coding regions of the African green monkey and the Vero cell line genomes. Monitoring changes of the proteome upon viral infection revealed widespread expression changes including transcriptional regulators, protease inhibitors, and proteins involved in innate immunity. Based on a library of 98 stable-isotope labeled synthetic peptides representing 11 SARS-CoV-2 proteins, we developed PRM (parallel reaction monitoring) assays for nano-flow and micro-flow LC-MS/MS. We assessed the merits of these PRM assays using supernatants of virus-infected Vero E6 cells and challenged the assays by analyzing two diagnostic cohorts of 24 (+30) SARS-CoV-2 positive and 28 (+9) negative cases. In light of the results obtained and including recent publications or manuscripts on preprint servers, we critically discuss the merits of mass spectrometry-based proteomics for SARS-CoV-2 research and testing.

Hepatitis B virus (HBV) is divided into nine genotypes, A to I. Currently, it remains unclear how the individual genotypes contribute to the estimated 250 million chronic HBV infections. We performed a literature search on HBV genotyping data throughout the world. Over 900 publications were assessed and data were extracted from 213 records covering 125 countries. Using previously published HBV prevalence, and population data, we approximated the number of infections with each HBV genotype per country and the genotype distribution among global chronic HBV infections. We estimated that 96% of chronic HBV infections worldwide are caused by five of the nine genotypes: genotype C is most common (26%), followed by genotype D (22%), E (18%), A (17%) and B (14%). Genotypes F to I together cause less than 2% of global chronic HBV infections. Our work provides an up-to-date analysis of global HBV genotyping data and an initial approach to estimate how genotypes contribute to the global burden of chronic HBV infection. Results highlight the need to provide HBV cell culture and animal models that cover at least genotypes A to E and represent the vast majority of global HBV infections to test novel treatment strategies.