ABSTRACT
The immunological picture of how different patients recover from COVID-19, and how those recovery trajectories are influenced by infection severity, remain unclear. We investigated 140 COVID-19 patients from diagnosis to convalescence using clinical data, viral load assessments, and multi-omic analyses of blood plasma and circulating immune cells. Immune-phenotype dynamics resolved four recovery trajectories. One trajectory signals a return to pre-infection healthy baseline, while the other three are characterized by differing fractions of persistent cytotoxic and proliferative T cells, distinct B cell maturation processes, and memory-like innate immunity. We resolve a small panel of plasma proteins that, when measured at diagnosis, can predict patient survival and recovery-trajectory commitment. Our study offers novel insights into post-acute immunological outcomes of COVID-19 that likely influence long-term adverse sequelae.
Subject(s)
COVID-19ABSTRACT
Recovery from COVID-19 is associated with production of anti-SARS-CoV-2 antibodies, but it is uncertain whether these confer immunity. We describe viral RNA shedding duration in hospitalized patients and identify patients with recurrent shedding. We sequenced viruses from two distinct episodes of symptomatic COVID-19 separated by 144 days in a single patient, to conclusively describe reinfection with a new strain harboring the spike variant D614G. With antibody and B cell analytics, we show correlates of adaptive immunity, including a differential response to D614G. Finally, we discuss implications for vaccine programs and begin to define benchmarks for protection against reinfection from SARS-CoV-2.
Subject(s)
COVID-19ABSTRACT
Background: Coronaviruses are a group of viruses that belong to the Family Coronaviridae, Genus Betacoronavirus. In December 2019, a new coronavirus disease (COVID-19) characterized by severe respiratory symptoms was discovered. The causative pathogen was a novel coronavirus known as 2019-nCoV and later as SARS-CoV-2. Within two months of its discovery, COVID-19 became a pandemic causing widespread morbidity and mortality. Methodology: Whole genome sequence data of SARS-CoV-2 isolated from Nigerian COVID-19 cases were retrieved by downloading from GISAID database. A total of 18 sequences that satisfied quality assurance (length > 29700 nts and number of unknown bases denoted as N < 5%) were used for the study. Multiple sequence alignment (MSA) was done in MAFFT (Version 7.471) while SNP calling was implemented in DnaSP (Version 6.12.03) respectively and then visualized in Jalview (Version 2.11.1.0). Phylogenetic analysis was with MEGA X software. Results: Nigerian SARS-CoV-2 had 99.9% genomic similarity with four large conserved genomic regions. A total of 66 SNPs were identified out of which 31 were informative. Nucleotide diversity assessment gave Pi = 0.00048 and average SNP frequency of 2.22 SNPs per 1000 nts. Non-coding genomic regions particularly 5 UTR and 3 UTR had a SNP density of 3.77 and 35.4 respectively. The region with the highest SNP density was ORF10 with a frequency of 8.55 SNPs/1000 nts). Majority (72.2%) of viruses in Nigeria are of L lineage with preponderance of D614G mutation which accounted for 11 (61.1%) out of the 18 viral sequences. Nigeria SARS-CoV-2 revealed 3 major clades namely Oyo, Ekiti and Osun on a maximum likelihood phylogenetic tree. Conclusion and Recommendation: Nigerian SARS-CoV-2 reveals high mutation rate together with preponderance of L lineage and D614G mutants. Implication of these mutations for SARS-CoV-2 virulence and the need for more aggressive testing and treatment of COVID-19 in Nigeria is discussed. Additionally, attempt to produce testing kits for COVID-19 in Nigeria should consider the conserved regions identified in this study. Strict adherence to COVID-19 preventive measure is recommended in view of Nigerian SARS-CoV-2 phylogenetic clustering pattern, which suggests intensive community transmission possibly rooted in communal culture characteristic of many ethnicities in Nigeria.
Subject(s)
COVID-19 , Coronavirus Infections , Severe Acute Respiratory SyndromeABSTRACT
Host immune responses play central roles in controlling SARS-CoV2 infection, yet remain incompletely characterized and understood. Here, we present a comprehensive immune response map spanning 454 proteins and 847 metabolites in plasma integrated with single-cell multi-omic assays of PBMCs in which whole transcriptome, 192 surface proteins, and T and B cell receptor sequence were co-analyzed within the context of clinical measures from 50 COVID19 patient samples. Our study reveals novel cellular subpopulations, such as proliferative exhausted CD8+ and CD4+ T cells, and cytotoxic CD4+ T cells, that may be features of severe COVID-19 infection. We condensed over 1 million immune features into a single immune response axis that independently aligns with many clinical features and is also strongly associated with disease severity. Our study represents an important resource towards understanding the heterogeneous immune responses of COVID-19 patients and may provide key information for informing therapeutic development.