An integrated in silico immuno-genetic analytical platform provides insights into COVID-19 serological and vaccine targets
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Abstract
During COVID-19, diagnostic serological tools and vaccines have been developed. To inform control activities in a post-vaccine surveillance setting, we have developed an online “immuno-analytics” resource that combines epitope, sequence, protein and SARS-CoV-2 mutation analysis. SARS-CoV-2 spike and nucleocapsid proteins are both vaccine and serological diagnostic targets. Using the tool, the nucleocapsid protein appears to be a sub-optimal target for use in serological platforms. Spike D614G (and nsp12 L314P) mutations were most frequent (> 86%), whilst spike A222V/L18F have recently increased. Also, Orf3a proteins may be a suitable target for serology. The tool can accessed from: http://genomics.lshtm.ac.uk/immuno (online); https://github.com/dan-ward-bio/COVID-immunoanalytics (source code).
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SciScore for 10.1101/2020.05.11.089409: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources Whole genome sequence data analysis: SARS-CoV-2 nucleotide sequences were downloaded from NCBI (https://www.ncbi.nlm.nih.gov) and GISAID (https://www.gisaid.org). https://www.ncbi.nlm.nih.govsuggested: (GENSAT at NCBI - Gene Expression Nervous System Atlas, RRID:SCR_003923)As a part of an automated in-house pipeline, sequences were aligned using MAFFT software (v7.2) [12] and trimmed to the beginning of the first reading frame (orf1ab-nsp1). MAFFTsuggested: (MAFFT, RRID:SCR_011811)Using data available from the NCBI COVID-19 resource, a modified annotation (GFF) file was generated and open … SciScore for 10.1101/2020.05.11.089409: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources Whole genome sequence data analysis: SARS-CoV-2 nucleotide sequences were downloaded from NCBI (https://www.ncbi.nlm.nih.gov) and GISAID (https://www.gisaid.org). https://www.ncbi.nlm.nih.govsuggested: (GENSAT at NCBI - Gene Expression Nervous System Atlas, RRID:SCR_003923)As a part of an automated in-house pipeline, sequences were aligned using MAFFT software (v7.2) [12] and trimmed to the beginning of the first reading frame (orf1ab-nsp1). MAFFTsuggested: (MAFFT, RRID:SCR_011811)Using data available from the NCBI COVID-19 resource, a modified annotation (GFF) file was generated and open reading frames (ORFs) for each respective viral protein were extracted (taking in to account ribosomal slippage) using bedtools ‘getfasta’ function [13]. bedtoolssuggested: (BEDTools, RRID:SCR_006646)Each ORF was translated using EMBOSS transeq software [14] and the variants for each protein sequence were identified using an in-house script. EMBOSSsuggested: (EMBOSS, RRID:SCR_008493)Using BLASTp [26] we mapped short amino acid epitope sequences onto the canonical sequence of SARS-CoV-2 proteins. BLASTpsuggested: (BLASTP, RRID:SCR_001010)Coronavirus homology analysis: Reference proteomes for SARS, MERS, OC43, 229E, HKU1 and NL63 α and β coronavirus (-CoV) species were sourced from UniProt database. UniProtsuggested: (UniProtKB, RRID:SCR_004426)Homologous peptide sequences with a BLAST bitscore indicating 10 or more residues mapped to the target sequence were recorded and parsed for display on the graph. BLASTsuggested: (BLASTX, RRID:SCR_001653)The BioCircos.js library [10] was used to generate the interactive plot and Datatables.net libraries for the table. BioCircossuggested: NoneFor the temporal/geographic non-synonymous mutation plots, we partitioned the whole genome sequencing dataset by week and continent and plotted non-synonymous allele frequencies using the Google Charts JavaScript libraries. Googlesuggested: (Google, RRID:SCR_017097)Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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