Robust Mutation Profiling of SARS-CoV-2 Variants from Multiple Raw Illumina Sequencing Data with Cloud Workflow.

Several variants of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are emerging all over the world. Variant surveillance from genome sequencing has become crucial to determine if mutations in these variants are rendering the virus more infectious, potent, or resistant to existing vaccines and therapeutics. Meanwhile, analyzing many raw sequencing data repeatedly with currently available code-based bioinformatics tools is tremendously challenging to be implemented in this unprecedented pandemic time due to the fact of limited experts and computational resources. Therefore, in order to hasten variant surveillance efforts, we developed an installation-free cloud workflow for robust mutation profiling of SARS-CoV-2 variants from multiple Illumina sequencing data. Herein, 55 raw sequencing data representing four early SARS-CoV-2 variants of concern (Alpha, Beta, Gamma, and Delta) from an open-access database were used to test our workflow performance. As a result, our workflow could automatically identify mutated sites of the variants along with reliable annotation of the protein-coding genes at cost-effective and timely manner for all by harnessing parallel cloud computing in one execution under resource-limitation settings. In addition, our workflow can also generate a consensus genome sequence which can be shared with others in public data repositories to support global variant surveillance efforts.

Humoral Immunogenicity and Reactogenicity of the Standard ChAdOx1 nCoV-19 Vaccination in Taiwan.

BACKGROUND: The ChAdOx1 nCoV-19 vaccine has been widely administered against SARS-CoV-2 infection; however, data regarding its immunogenicity, reactogenicity, and potential differences in responses among Asian populations remain scarce. METHODS: 270 participants without prior COVID-19 were enrolled to receive ChAdOx1 nCoV-19 vaccination with a prime-boost interval of 8-9 weeks. Their specific SARS-CoV-2 antibodies, neutralizing antibody titers (NT50), platelet counts, and D-dimer levels were analyzed before and after vaccination. RESULTS: The seroconversion rates of anti-RBD and anti-spike IgG at day 28 after a boost vaccination (BD28) were 100% and 95.19%, respectively. Anti-RBD and anti-spike IgG levels were highly correlated (r = 0.7891), which were 172.9 ± 170.4 and 179.3 ± 76.88 BAU/mL at BD28, respectively. The geometric mean concentrations (GMCs) of NT50 for all participants increased to 132.9 IU/mL (95% CI 120.0-147.1) at BD28 and were highly correlated with anti-RBD and anti-spike IgG levels (r = 0.8248 and 0.7474, respectively). Body weight index was statistically significantly associated with anti-RBD IgG levels (p = 0.035), while female recipients had higher anti-spike IgG levels (p = 0.038). The GMCs of NT50 declined with age (p = 0.0163) and were significantly different across age groups (159.7 IU/mL for 20-29 years, 99.4 IU/mL for ≥50 years, p = 0.0026). Injection-site pain, fever, and fatigue were the major reactogenicity, which were more pronounced after prime vaccination and in younger participants (<50 years). Platelet counts decreased and D-dimer levels increased after vaccination but were not clinically relevant. No serious adverse events or deaths were observed. CONCLUSION: The vaccine is well-tolerated and elicited robust humoral immunity against SARS-CoV-2 after standard prime-boost vaccination in Taiwanese recipients.

The Humoral Immune Response of the ChAdOx1 nCoV-19 Vaccine in Maintenance Dialysis Patients without Prior COVID-19 Infection.

BACKGROUND: Chronic kidney disease (CKD) patients tend to have a reduced immune response to infection and vaccination. The efficacy of current available COVID-19 vaccines in CKD patients has not been widely evaluated. METHODS: In the present study, three hundred and eight chronic dialysis patients received ChAdOx1 nCoV-19 (Oxford-AstraZeneca, AZ). Blood tests using an antibody against the receptor-binding domain (RBD) of the S1 subunit of the SARS-CoV-2 spike protein had performed at four designed time points before and after the first and second vaccine. RESULTS: The mean age of patients was 65.5 ± 12.38 years, and the male/female ratio was 61.4%:38.6% (189/119). Two weeks after the first vaccination, only 37.66% of patients had a positive antibody response (>50 AU/mL). However, 65.58% of the participants showed a delayed antibody response ten weeks after the first vaccine. Four weeks after the second vaccine, 94.16% of participants had positive antibody levels. Age was the most significant factor associated with antibody response. Flow cytometry analysis revealed that immune-naïve patients had significantly lower early active B cells and proliferative B cells than the age- and sex-matched immune responders. CONCLUSION: Despite a delayed response, 94.16% of chronic dialysis patients achieved a positive antibody response after two doses of the AZ vaccine. Age is the most significant factor associated with antibody response.

Orchestrating an Optimized Next-Generation Sequencing-Based Cloud Workflow for Robust Viral Identification during Pandemics.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has recently become a novel pandemic event following the swine flu that occurred in 2009, which was caused by the influenza A virus (H1N1 subtype). The accurate identification of the huge number of samples during a pandemic still remains a challenge. In this study, we integrate two technologies, next-generation sequencing and cloud computing, into an optimized workflow version that uses a specific identification algorithm on the designated cloud platform. We use 182 samples (92 for COVID-19 and 90 for swine flu) with short-read sequencing data from two open-access datasets to represent each pandemic and evaluate our workflow performance based on an index specifically created for SARS-CoV-2 or H1N1. Results show that our workflow could differentiate cases between the two pandemics with a higher accuracy depending on the index used, especially when the index that exclusively represented each dataset was used. Our workflow substantially outperforms the original complete identification workflow available on the same platform in terms of time and cost by preserving essential tools internally. Our workflow can serve as a powerful tool for the robust identification of cases and, thus, aid in controlling the current and future pandemics.