Sierra SARS-CoV-2 sequence and antiviral resistance analysis program

Tzou, Philip L.; Tao, Kaiming; Sahoo, Malaya K.; Pond, Sergei L. Kosakovsky; Pinsky, Benjamin A.; Shafer, Robert W.

doi:10.1016/j.jcv.2022.105323

Cited by 9 publications

(13 citation statements)

References 53 publications

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“…Input FASTQ sequence alignment with Wuhan-Hu-1 reference was done using MiniMap2 version 2.22 in CodFreq pipeline (https://github.com/hivdb/codfreq). The output of MiniMap2, an aligned SAM file, was converted to a CodFreq file by a publicly available pipeline using a PySam library (version 0.18.0) and further analyzed with the CoVDB ( 49 , 50 ). PCR and sequencing runs were performed once with the appropriate positive and negative controls.…”

Section: Methodsmentioning

confidence: 99%

SARS-CoV-2 viral clearance and evolution varies by type and severity of immunodeficiency

Li,

Choudhary,

Regan

et al. 2024

Sci. Transl. Med.

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Despite vaccination and antiviral therapies, immunocompromised individuals are at risk for prolonged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, but the immune defects that predispose an individual to persistent coronavirus disease 2019 (COVID-19) remain incompletely understood. In this study, we performed detailed viro-immunologic analyses of a prospective cohort of participants with COVID-19. The median times to nasal viral RNA and culture clearance in individuals with severe immunosuppression due to hematologic malignancy or transplant (S-HT) were 72 and 40 days, respectively, both of which were significantly longer than clearance rates in individuals with severe immunosuppression due to autoimmunity or B cell deficiency (S-A), individuals with nonsevere immunodeficiency, and nonimmunocompromised groups ( P < 0.01). Participants who were severely immunocompromised had greater SARS-CoV-2 evolution and a higher risk of developing resistance against therapeutic monoclonal antibodies. Both S-HT and S-A participants had diminished SARS-CoV-2–specific humoral responses, whereas only the S-HT group had reduced T cell–mediated responses. This highlights the varied risk of persistent COVID-19 across distinct immunosuppressive conditions and suggests that suppression of both B and T cell responses results in the highest contributing risk of persistent infection.

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Section: Methodsmentioning

confidence: 99%

SARS-CoV-2 viral clearance and evolution varies by type and severity of immunodeficiency

Li,

Choudhary,

Regan

et al. 2024

Sci. Transl. Med.

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“…Defining of SARS-CoV-2 variant/subvariants and the antiviral resistance mutations that target RdRp and 3CLPro inhibitors were assessed according to the mutation annotations given by CoV-RDB [ 25 ]. In this study, remdesivir (RDV) (Veklury, GS-5734, Gliead Sciences, Inc., Foster City, CA, USA) as RdRp inhibitor, NTV/r (Paxlovid/PF-07321332, Pfizer Labs, New York, NY, USA) and ensitrelvir (ENS) (Xocova/S-217622, Shionogi & Co., Ltd. Osaka, Japan) as 3CLpro inhibitors were assessed.…”

Section: Methodsmentioning

confidence: 99%

“…The resistance mutations included R285C, A449V, D484Y, V557L, S759A, V792I, E796G, C799F, C799R, E802A, and M924R, that are associated with the reduced activity to RdRp, were matched with GISAID mutations for RDV resistance. For the mutations related to the reduced activity against 3CLpro inhibitors, G15S, T21I, T45I, D48Y, M49I, M49T, L50F, G138S, F140L, N142D, N142L, N142S, G143S, S144A/E/L/P/R/T/V/W, C160F, M165T, E166A/G/K/V, L167F, H172Q/Y/T, H173V, V186G, R188S, Q189K, T190I, A191T/V, Q192A, and Q192E mutation patterns were involved and matched with the GISAID mutations for NTV/r and ENS resistance [ 25 ]. Antiviral drug resistance was interpreted for RdRp and 3CLPro inhibitors as medians ≥10-fold, 5–10-fold, 2.5–5, and <2.5-fold reductions in susceptibility, and gray cell as no susceptibility, according to the CoV-RDB protocols [ 25 ].…”

Section: Methodsmentioning

confidence: 99%

Molecular Epidemiology of SARS-CoV-2 Omicron Sub-Lineages Isolated from Turkish Patients Infected with COVID-19

Sayan

Arıkan

Sanlidag

2023

Viruses

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Early detection and characterization of new variants and their impacts enable improved genomic surveillance. This study aims to evaluate the subvariant distribution of Omicron strains isolated from Turkish cases to determine the rate of antiviral resistance of RdRp and 3CLpro inhibitors. The Stanford University Coronavirus Antiviral & Resistance Database online tool was used for variant analyses of the strains uploaded to GISAID as Omicron (n = 20.959) between January 2021 and February,2023. Out of 288 different Omicron subvariants, B.1, BA.1, BA.2, BA.4, BE.1, BF.1, BM.1, BN.1, BQ.1, CK.1, CL.1, and XBB.1 were the main determined subvariants, and BA.1 (34.7%), BA.2 (30.8%), and BA.5 (23.6%) were reported most frequently. RdRp and 3CLPro-related resistance mutations were determined in n = 150, 0.72% sequences, while the rates of resistance against RdRp and 3CLpro inhibitors were reported at 0.1% and 0.6%, respectively. Mutations that were previously associated with a reduced susceptibility to remdesivir, nirmatrelvir/r, and ensitrelvir were most frequently detected in BA.2 (51.3%). The mutations detected at the highest rate were A449A/D/G/V (10.5%), T21I (10%), and L50L/F/I/V (6%). Our findings suggest that continuous monitoring of variants, due to the diversity of Omicron lineages, is necessary for global risk assessment. Although drug-resistant mutations do not pose a threat, the tracking of drug mutations will be necessary due to variant heterogenicity.

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“…VarEPS [7] assesses the risk level of mutations and variants based on their transmissibility and affinity to neutralizing antibodies. Additionally, databases like CoV-RDB [8, 9] and COG-UK-ME [10] have compiled mutations associated with reduced susceptibility to various factors, such as clinical stage SARS-CoV-2 Spike monoclonal antibody (mAb), RNA-dependent RNA polymerase (RdRP) inhibitor, 3C-like protease (3CLpro) inhibitor, or mutations on T cell epitope. However, despite these significant efforts, there are limitations in terms of efficiency and comprehensiveness.…”

Section: Introductionmentioning

confidence: 99%

RCoV19: A One-stop Hub for SARS-CoV-2 Genome Data Integration, Variants Monitoring, and Risk Pre-warning

Li,

Ma,

Zou

et al. 2023

Preprint

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The Resource for Coronavirus 2019 (RCoV19,https://ngdc.cncb.ac.cn/ncov/) is an open-access information resource dedicated to providing valuable data on the genomes, mutations, and variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this updated implementation of RCoV19, we have made significant improvements and advancements over the previous version. Firstly, we have implemented a highly refined genome data curation model. This model now features an automated integration pipeline and optimized curation rules, enabling efficient daily updates of data in RCoV19. Secondly, we have developed a global and regional lineage evolution monitoring platform, alongside an outbreak risk pre-warning system. These additions provide a comprehensive understanding of SARS-CoV-2 evolution and transmission patterns, enabling better preparedness and response strategies. Thirdly, we have developed a powerful interactive mutation spectrum comparison module. This module allows users to compare and analyze mutation patterns, assisting in the detection of potential new lineages. Furthermore, we have incorporated a comprehensive knowledgebase on mutation effects. This knowledgebase serves as a valuable resource for retrieving information on the functional implications of specific mutations. In summary, RCoV19 serves as a vital scientific resource, providing access to valuable data, relevant information, and technical support in the global fight against COVID-19.

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Sierra SARS-CoV-2 sequence and antiviral resistance analysis program

Cited by 9 publications

References 53 publications

SARS-CoV-2 viral clearance and evolution varies by type and severity of immunodeficiency

SARS-CoV-2 viral clearance and evolution varies by type and severity of immunodeficiency

Molecular Epidemiology of SARS-CoV-2 Omicron Sub-Lineages Isolated from Turkish Patients Infected with COVID-19

RCoV19: A One-stop Hub for SARS-CoV-2 Genome Data Integration, Variants Monitoring, and Risk Pre-warning

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