Emergence of SARS-CoV-2 Spike Mutations during Prolonged Infection in Immunocompromised Hosts.

Immunocompromised hosts with prolonged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections have been implicated in the emergence of highly mutated SARS-CoV-2 variants. Spike mutations are of particular concern because the spike protein is a key target for vaccines and therapeutics for SARS-CoV-2. Here, we report the emergence of spike mutations in two immunocompromised patients with persistent SARS-CoV-2 reverse transcription (RT)-PCR positivity (>90 days). Whole-genome sequence analysis of samples obtained before and after coronavirus disease 2019 (COVID-19) treatment demonstrated the development of partial therapeutic escape mutations and increased intrahost SARS-CoV-2 genome diversity over time. This case series thus adds to the accumulating evidence that immunocompromised hosts with persistent infections are important sources of SARS-CoV-2 genome diversity and, in particular, clinically important spike protein diversity. IMPORTANCE The emergence of clinically important mutations described in this report highlights the need for sustained vigilance and containment measures when managing immunocompromised patients with persistent COVID-19. Even as jurisdictions across the globe start lifting pandemic control measures, immunocompromised patients with persistent COVID-19 constitute a unique group that requires close genomic monitoring and enhanced infection control measures, to ensure early detection and containment of mutations and variants of therapeutic and public health importance.

Metagenomics-enabled microbial surveillance.

Lessons learnt from the COVID-19 pandemic include increased awareness of the potential for zoonoses and emerging infectious diseases that can adversely affect human health. Although emergent viruses are currently in the spotlight, we must not forget the ongoing toll of morbidity and mortality owing to antimicrobial resistance in bacterial pathogens and to vector-borne, foodborne and waterborne diseases. Population growth, planetary change, international travel and medical tourism all contribute to the increasing frequency of infectious disease outbreaks. Surveillance is therefore of crucial importance, but the diversity of microbial pathogens, coupled with resource-intensive methods, compromises our ability to scale-up such efforts. Innovative technologies that are both easy to use and able to simultaneously identify diverse microorganisms (viral, bacterial or fungal) with precision are necessary to enable informed public health decisions. Metagenomics-enabled surveillance methods offer the opportunity to improve detection of both known and yet-to-emerge pathogens.

SARS-CoV-2 N Gene G29195T Point Mutation May Affect Diagnostic Reverse Transcription-PCR Detection.

Rapid onsite whole-genome sequencing of two suspected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) N gene diagnostic escape samples revealed a previously unreported N gene point mutation at genome position 29195. Because the G29195T mutation occurs within a region probed by a commonly referenced U.S. CDC N gene reverse transcription (RT)-PCR assay, we hypothesize that the G29195T mutation rendered the N gene target of a proprietary commercial assay undetectable. The putative diagnostic escape G29195T mutation demonstrates the need for nearly real-time surveillance, as emergence of a novel SARS-CoV-2 variant with the potential to escape diagnostic tests continues to be a threat. IMPORTANCE Accurate diagnostic detection of SARS-CoV-2 currently depends on the large-scale deployment of RT-PCR assays. SARS-CoV-2 RT-PCR assays target predetermined regions in the viral genomes by complementary binding of primers and probes to nucleic acid sequences in the clinical samples. Potential diagnostic escapes, such as those of clinical samples harboring the G29195T mutation, may result in false-negative SARS-CoV-2 RT-PCR results. The rapid detection and sharing of potential diagnostic escapes are essential for diagnostic laboratories and manufacturers around the world, to optimize their assays as SARS-CoV-2 continues to evolve.

CalmBelt: Rapid SARS-CoV-2 Genome Characterization for Outbreak Tracking.

Background: The ongoing COVID-19 pandemic is a global health crisis caused by the spread of SARS-CoV-2. Establishing links between known cases is crucial for the containment of COVID-19. In the healthcare setting, the ability to rapidly identify potential healthcare-associated COVID-19 clusters is critical for healthcare worker and patient safety. Increasing sequencing technology accessibility has allowed routine clinical diagnostic laboratories to sequence SARS-CoV-2 in clinical samples. However, these laboratories often lack specialized informatics skills required for sequence analysis. Therefore, an on-site, intuitive sequence analysis tool that enables clinical laboratory users to analyze multiple genomes and derive clinically relevant information within an actionable timeframe is needed. Results: We propose CalmBelt, an integrated framework for on-site whole genome characterization and outbreak tracking. Nanopore sequencing technology enables on-site sequencing and construction of draft genomes for multiple SARS-CoV-2 samples within 12 h. CalmBelt's interactive interface allows users to analyse multiple SARS-CoV-2 genomes by utilizing whole genome information, collection date, and additional information such as predefined potential clusters from epidemiological investigations. CalmBelt also integrates established SARS-CoV-2 nomenclature assignments, GISAID clades and PANGO lineages, allowing users to visualize relatedness between samples together with the nomenclatures. We demonstrated multiple use cases including investigation of potential hospital transmission, mining transmission patterns in a large outbreak, and monitoring possible diagnostic-escape. Conclusions: This paper presents an on-site rapid framework for SARS-CoV-2 whole genome characterization. CalmBelt interactive web application allows non-technical users, such as routine clinical laboratory users in hospitals to determine SARS-CoV-2 variants of concern, as well as investigate the presence of potential transmission clusters. The framework is designed to be compatible with routine usage in clinical laboratories as it only requires readily available sample data, and generates information that impacts immediate infection control mitigations.