*
* .05, and *** .001. N genes. The amount of changes did not differ by the severity of reinfection and reinfecting variants were similar to the contemporaneous sequences circulating in the community. Patients with prolonged coronavirus disease 2019 (COVID-19) exhibited more rapid accumulation of sequence changes than seen with community-driven development with continued development during convalescent plasma or monoclonal antibody treatment. Conclusions Reinfecting SARS-CoV-2 viral genomes largely MK-447 mirror contemporaneous circulating sequences in that geographic region, while prolonged COVID-19 has been largely explained in immunosuppressed individuals and is associated with accelerated viral development. culture process. Three cases were excluded due to uncertainty in their classification as either reinfection or persistent contamination cases (Supplementary Methods, Supplementary Table 1, Supplementary Physique 2). Sequences were analyzed for mutations using Nextclade (https://clades.nextstrain.org/) and snp-sites (https://github.com/sanger-pathogens/snp-sites). MK-447 The degree of reinfection severity, either more or less severe compared with the first contamination, was classified based on an explicit determination by the authors of each article or by comparing symptoms, duration of illness, and hospitalization status between both episodes. Sequencing Dataset Compilation and Phylogenetic Tree Construction The sequencing dataset contained a total of 262 globally representative SARS-CoV-2 genomes selected from GISAID (https://www.gisaid.org/) and sequences from your reinfection and persistence cases (Supplementary Methods, Supplementary Data 1). The sampled sequences were chosen to be representative of global sequence diversity throughout the time course of the pandemic. Sequences of variants of concern B.1.1.7 and B.1.351 were also included. Nucleotide sequence alignment was performed using MAFFT (Multiple Alignment using Fast Fourier Transform) [12]. Best-fit nucleotide substitution was calculated using model selection followed by maximum likelihood (ML) phylogenetic tree construction using IQ-Tree with 1000-bootstrap replicates [12]. Mutation Analysis For reinfection cases, mutations were decided in 2 ways. First, nucleotide and amino acid changes were recognized for the reinfection sequences relative to the first contamination sequence. The frequency of nucleotide or amino acid changes within each gene was compared with the frequency of changes in the remainder of the genome by Fishers exact tests with a Bonferroni correction (for multiple comparisons). The relationship between disease severity and quantity of nucleotide or amino acid changes in the genome was assessed using a Mann-Whitney test. Second, to identify unique characteristics of reinfecting viruses, each of the first and reinfection sequences were compared with circulating sequences in the community as defined by the same Nextstrain clade MK-447 sampled within 1 month obtained from the same geographic location uploaded to GISAID (Supplementary Table 2, Supplementary Methods, Supplementary Data 2). Rare mutations were decided as polymorphisms that were present only in the reinfecting sequence (not the initial variant) and found in less than 1% of contemporaneous community sequences. Mutation locations are graphically represented in Circos plots [13]. For persistent infections, sequence changes were assessed at 2 time intervals: before or after convalescent plasma or monoclonal antibody treatment. Sequences sampled before convalescent plasma or antibody treatment were compared with the first sequence sampled. For sequences sampled after convalescent plasma MK-447 or antibody treatment, sequence changes (both nucleotide and amino acid) were decided relative to the last pretreatment sequence. Linear regression was used to estimate the rate of viral changes between 2 Rabbit polyclonal to AVEN intervals. The slope of the trendline was compared with the latest global clock rate (29 March 2021) as estimated by NextStrain (https://nextstrain.org/ncov/global/). Time-Measured Phylogenetic Analysis The temporal transmission of the ML tree was examined in TempEst [14] regressing on root-to-tip divergence, and outliers were inspected in the distribution of residuals. A high degree of clock-like behavior in the whole dataset was observed ((2020)39FNone185Less19A20ARe2To et al [3] (2020)33MNone144Less19A20ERe3Prado-Vivar.
