Advancing genomic epidemiology by addressing the bioinformatics bottleneck: Challenges, design principles, and a Swiss example.

The SARS-CoV-2 pandemic led to a huge increase in global pathogen genome sequencing efforts, and the resulting data are becoming increasingly important to detect variants of concern, monitor outbreaks, and quantify transmission dynamics. However, this rapid up-scaling in data generation brought with it many IT infrastructure challenges. In this paper, we report about developing an improved system for genomic epidemiology. We (i) highlight key challenges that were exacerbated by the pandemic situation, (ii) provide data infrastructure design principles to address them, and (iii) give an implementation example developed by the Swiss SARS-CoV-2 Sequencing Consortium (S3C) in response to the COVID-19 pandemic. Finally, we discuss remaining challenges to data infrastructure for genomic epidemiology. Improving these infrastructures will help better detect, monitor, and respond to future public health threats.

Identification and functional analysis of the SARS-COV-2 nucleocapsid protein.

BACKGROUND: A severe form of pneumonia, named coronavirus disease 2019 (COVID-19) by the World Health Organization is widespread on the whole world. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was proved to be the main agent of COVID-19. In the present study, we conducted an in depth analysis of the SARS-COV-2 nucleocapsid to identify potential targets that may allow identification of therapeutic targets. METHODS: The SARS-COV-2 N protein subcellular localization and physicochemical property was analyzed by PSORT II Prediction and ProtParam tool. Then SOPMA tool and swiss-model was applied to analyze the structure of N protein. Next, the biological function was explored by mass spectrometry analysis and flow cytometry. At last, its potential phosphorylation sites were analyzed by NetPhos3.1 Server and PROVEAN PROTEIN. RESULTS: SARS-COV-2 N protein composed of 419 aa, is a 45.6 kDa positively charged unstable hydrophobic protein. It has 91 and 49% similarity to SARS-CoV and MERS-CoV and is predicted to be predominantly a nuclear protein. It mainly contains random coil (55.13%) of which the tertiary structure was further determined with high reliability (95.76%). Cells transfected with SARS-COV-2 N protein usually show a G1/S phase block company with an increased expression of TUBA1C, TUBB6. At last, our analysis of SARS-COV-2 N protein predicted a total number of 12 phosphorylated sites and 9 potential protein kinases which would significantly affect SARS-COV-2 N protein function. CONCLUSION: In this study, we report the physicochemical properties, subcellular localization, and biological function of SARS-COV-2 N protein. The 12 phosphorylated sites and 9 potential protein kinase sites in SARS-COV-2 N protein may serve as promising targets for drug discovery and development for of a recombinant virus vaccine.