Toehold-controlled ligation and transcription for accurate COVID-19 genotyping.

The global pandemic of coronavirus disease 2019 (COVID-19) has significant impact on the entire human society. However, in the face of continually emerging more contagious SARS-CoV-2 variant, the risk to bog down into more severe crisis is around us anytime. Here, we introduce an isothermal, ultrasensitive method for identifying important SNV mutations of SARS-CoV-2. It is based on combined specificity of toehold-assisted linear probe ligation and in vitro transcription signal enlargement, TLT. A ready-to-use panel of TLT assay is developed including detection of 80 crucial SARS-CoV-2 SNVs, by which people could response to the next coming contagious virus variant more rapidly. These advanced point-of-care features make TLT one good approach for large scale population testing of special SARS-CoV-2 variants of interesting.

Equitable vaccine distribution promotes socioeconomic benefits globally (preprint)

Ensuring a more equitable distribution of vaccines worldwide is an effective strategy to control the COVID-19 pandemic and support global economic recovery. Here, we analyze the socioeconomic effects - defined as health gains, lockdown-easing benefit, and supply-chain rebuilding benefit - of a set of idealized vaccine distribution scenarios, by coupling an epidemiological model with a global trade-modeling framework. We find that overall a perfectly equitable vaccine distribution across the world (Altruistic Age-informed Distribution Strategy) would increase global economic benefits by 11.7% ($950 billion) per year, compared to a strategy focusing on vaccinating the entire population within vaccine-producing countries first and then distributing vaccines to non-vaccine-producing countries (Selfish Distribution Strategy). With limited doses among mid- and low-income countries, prioritizing the elderly who are at high risk of dying, together with the key workforce who are at high risk of exposure, is found to be economically beneficial. We further show that such a strategy would cascade the protection to other production sectors while rebuilding the supply chains. Our results point to a benefit-sharing mechanism which highlights the potential of collaboration between vaccine-producing and other countries to guide an economically preferable vaccine distribution worldwide.

Network-based analysis revealed significant interactions between risk genes of severe COVID-19 and host genes interacted with SARS-CoV-2 proteins.

Whether risk genes of severe coronavirus disease 2019 (COVID-19) from genome-wide association study could play their regulatory roles by interacting with host genes that were interacted with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteins was worthy of exploration. In this study, we implemented a network-based approach by developing a user-friendly software Network Calculator (https://github.com/Haoxiang-Qi/Network-Calculator.git). By using Network Calculator, we identified a network composed of 13 risk genes and 28 SARS-CoV-2 interacted host genes that had the highest network proximity with each other, with a hub gene HNRNPK identified. Among these genes, 14 of them were identified to be differentially expressed in RNA-seq data from severe COVID-19 cases. Besides, by expression enrichment analysis in single-cell RNA-seq data, compared with mild COVID-19, these genes were significantly enriched in macrophage, T cell and epithelial cell for severe COVID-19. Meanwhile, 74 pathways were significantly enriched. Our analysis provided insights for the underlying genetic etiology of severe COVID-19 from the perspective of network biology.