Resurgence of SARS-CoV-2 Delta after Omicron variant superinfection in an immunocompromised pediatric patient

Abstract

Background: Persistent SARS-CoV-2 infection in immunocompromised hosts is thought to contribute to viral evolution by facilitating long-term natural selection and viral recombination in cases of viral co-infection or superinfection. However, there are limited data on the longitudinal intra-host population dynamics of SARS-CoV-2 co-infection/superinfection, especially in pediatric populations. Here, we report a case of Delta-Omicron superinfection in a hospitalized, immunocompromised pediatric patient.

Methods: We conducted Illumina whole genome sequencing (WGS) for longitudinal specimens to investigate intra-host dynamics of SARS-CoV-2 strains. Topoisomerase PCR cloning of Spike open-reading frame and Sanger sequencing of samples was performed for four specimens to validate the findings. Analysis of publicly available SARS-CoV-2 sequence data was performed to investigate the co-circulation and persistence of SARS-CoV-2 variants.

Results: Results of WGS indicate the patient was initially infected with the SARS-CoV-2 Delta variant before developing a SARS-CoV-2 Omicron variant superinfection, which became predominant. Shortly thereafter, viral loads decreased below the level of detection before resurgence of the original Delta variant with no residual trace of Omicron. After 54 days of persistent infection, the patient tested negative for SARS-CoV-2 but ultimately succumbed to a COVID-19-related death. Despite protracted treatment with remdesivir, no antiviral resistance mutations emerged. These results indicate a unique case of persistent SARS-CoV-2 infection with the Delta variant interposed by a transient superinfection with the Omicron variant. Analysis of publicly available sequence data suggests the persistence and ongoing evolution of Delta subvariants despite the global predominance of Omicron, potentially indicative of continued transmission in an unknown population or niche.

Conclusion: A better understanding of SARS-CoV-2 intra-host population dynamics, persistence, and evolution during co-infections and/or superinfections will be required to continue optimizing patient care and to better predict the emergence of new variants of concern.

Keywords: Delta; Omicron; SARS-CoV-2; Superinfection; Variants of concern.

Fig. 1

Case characteristics of an immunocompromised pediatric patient with persistent COVID-19. (A) Timeline of case patient’s illness, treatments, and COVID-19 testing. (B) Patient’s measured C-reactive protein (blue) and lactate levels (red) over the course of hospital admission. (C) SARS-CoV-2 quantitative RT-PCR cycle threshold (Ct) levels from available patient samples. X-axes for panels B and C are days since the onset of COVID-19 symptoms in the patient and arrowheads indicate SARS-CoV-2 testing dates

Fig. 2

Sequencing of longitudinal nasopharyngeal isolates reveals a Delta-Omicron superinfection. (A) Maximum Likelihood phylogeny of the consensus SARS-CoV-2 whole genome sequences from Illumina short read sequencing. (B) Temporal dynamics of SARS-CoV-2 lineages (Relative abundance for seven days moving average) from Chicago and Cook County during the course of hospitalization. (C) Temporal dynamics of SARS-CoV-2 lineages (Absolute abundance per day) from Chicago and Cook County during the course of hospitalization. (D) Maximum likelihood phylogenetic tree of SARS-CoV-2 genome sequences from the patient samples (large purple dots) with all publicly available sequences from Chicago and surrounding Cook County collected between January and February 15, 2022 (black dots; n = 1,345) and deposited in the GISAID database

Fig. 3

Single amplicon sequencing confirms Delta variant infection with a transient Omicron superinfection. (A) Workflow for Spike amplification, topoisomerase (TOPO) based cloning, and Sanger sequencing of specimens. Created with https://BioRender.com. (B) Quasispecies haplotypes of SARS-CoV-2 Spike region in four selected nasopharyngeal specimens. A maximum likelihood phylogenetic tree of the cloned SARS-CoV-2 Spike fragment sequences was generated from specimens collected on days 4 (light blue; n = 109), 13 (blue; n = 56), 18 (magenta; n = 52), and 31 (cyan; n = 58) since symptom onset. Arrow indicates Delta S gene clone sequence found in the otherwise Omicron-abundant day 18

Fig. 4

Persistence of Delta variants in public sequence data after the emergence of Omicron. A) Temporal dynamics of VOCs during the course of the pandemic based on 13,342,630 high-quality SARS-CoV-2 whole genome sequences from the GISAID database collected between December 2019 and February 2023. B) Temporal dynamics of non-Omicron SARS-CoV-2 genome sequences collected after June 2022. C) Maximum likelihood phylogenetic tree of non-Omicron variants collected after June 2022 (triangles; n = 226) and random subsamples of the same variants collected around their respective peak prevalence (circles; n = 2,195). D) Lineages-Through-Time (LTT) plot derived from Bayesian analysis of SARS-CoV-2 Delta variant genome sequences collected around the peak of prevalence (n = 200) and after June 2022 (n = 200). The plot chronologically represents the accumulation of lineages from September 2020 to March 2023. E) Violin plots displaying pairwise p-distance distributions of SARS-CoV-2 Delta variant genome sequences. Distributions represent all pairwise comparisons between genomes from the peak of prevalence (n = 200), post-June 2022 (n = 200), and the pairwise divergence between these two time points. Each “violin” width is indicative of the kernel density estimation of the data, presenting an overview of genetic divergence within and between the two sample groups. Thick line in each violin shows median pairwise p-distance of each group and whiskers indicate the upper and lower 1.5 interquartile ranges (IQR). P-values were calculated using the Wilcoxon rank-sum test and subjected to adjustment for False Discovery Rate (FDR) using the Benjamini-Hochberg procedure, accounting for multiple comparisons