Revealing spatiotemporal transmission patterns and stages of COVID-19 in China using individual patients' trajectory data.

Gauging viral transmission through human mobility in order to contain the COVID-19 pandemic has been a hot topic in academic studies and evidence-based policy-making. Although it is widely accepted that there is a strong positive correlation between the transmission of the coronavirus and the mobility of the general public, there are limitations to existing studies on this topic. For example, using digital proxies of mobile devices/apps may only partially reflect the movement of individuals; using the mobility of the general public and not COVID-19 patients in particular, or only using places where patients were diagnosed to study the spread of the virus may not be accurate; existing studies have focused on either the regional or national spread of COVID-19, and not the spread at the city level; and there are no systematic approaches for understanding the stages of transmission to facilitate the policy-making to contain the spread. To address these issues, we have developed a new methodological framework for COVID-19 transmission analysis based upon individual patients' trajectory data. By using innovative space-time analytics, this framework reveals the spatiotemporal patterns of patients' mobility and the transmission stages of COVID-19 from Wuhan to the rest of China at finer spatial and temporal scales. It can improve our understanding of the interaction of mobility and transmission, identifying the risk of spreading in small and medium-sized cities that have been neglected in existing studies. This demonstrates the effectiveness of the proposed framework and its policy implications to contain the COVID-19 pandemic.

Whole genome sequencing and comparative genomics analysis of Pectobacterium carotovorum identifies key pathogenic genes.

Based on Single moleculereal time(SMRT)sequencing technology, the high-quality whole genome sequence of Pectobacterium carotovorum (PC1) was obtained by the PacBio RS II sequencer. The genome is a single circular chromosome of 5.3 Mb in size, containing three kinds of m6A methylation modification by SMRT Portal analysis. Genome annotation showed that 575 virulence factor genes, 304 drug resistance genes, 774 pathogen genes, 7 secretory systems and 22 pairs of two-component regulatory system could be relevant to bacterial pathogenicity. In addition, the average nucleotide identities (ANI) analysisshowed that the PC1 exhibited the highest homology with the Pectobacteriumcarotovorumsubsp.carotovorumstrain BP201601.1 (NZ_CP034236). There are 28 unique gene families to PC1 using cluster analysis of gene families. According to the analysis of key pathogenic genes, we have obtained three kinds of highly conserved genes related to cell wall degrading enzymes, including 19 pectinase genes, 25 cellulase genes and 22 protease genes. Our studies have provided a theoretical basis for investigation of bacterial soft rot and biological specific bactercides of PC1.

[Purification and bacteriostatic identification of CpxP protein from Pectobacterium carotovorum subsp. carotovorum].

Pectobacterium carotovorum subsp. carotovorum is one of the world's top ten plant pathogens, mainly infecting cruciferous economic crops and ornamental flowers. In this study, an antibacterial gene cpxP (Gene ID: 29704421) was cloned from the genome of Pectobacterium carotovorum subsp. carotovorum, and constructed on the prokaryotic expression plasmid pET-15b, and the recombinant plasmid was transformed into Escherichia coli BL21 (DE3), then stability and bacteriostatic experiments of the purified CpxP protein were performed. The final concentration of IPTG was 1 mmol/L, obtaining high-efficiency exogenous expression of the CpxP protein. There was no other protein after purification, and the destined protein exhibited good thermal stability and pH stability. The antibacterial test results showed that the inhibition rate of the CpxP protein on carrot slice was 44.89% while the inhibition rate on potato slice was 59.41%. To further explain its antibacterial mechanism, studying the spatial structure of this protein can provide new ideas for the control of soft rot and new protein pesticide targets.