Proteomic and Metabolomic Signatures Associated With the Immune Response in Healthy Individuals Immunized With an Inactivated SARS-CoV-2 Vaccine
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Abstract
CoronaVac (Sinovac), an inactivated vaccine for SARS-CoV-2, has been widely used for immunization. However, analysis of the underlying molecular mechanisms driving CoronaVac-induced immunity is still limited. Here, we applied a systems biology approach to understand the mechanisms behind the adaptive immune response to CoronaVac in a cohort of 50 volunteers immunized with 2 doses of CoronaVac. Vaccination with CoronaVac led to an integrated immune response that included several effector arms of the adaptive immune system including specific IgM/IgG, humoral response and other immune response, as well as the innate immune system as shown by complement activation. Metabolites associated with immunity were also identified implicating the role of metabolites in the humoral response, complement activation and other immune response. Networks associated with the TCA cycle and amino acids metabolic pathways, such as phenylalanine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, and glycine, serine and threonine metabolism were tightly coupled with immunity. Critically, we constructed a multifactorial response network (MRN) to analyze the underlying interactions and compared the signatures affected by CoronaVac immunization and SARS-CoV-2 infection to further identify immune signatures and related metabolic pathways altered by CoronaVac immunization. These results help us to understand the host response to vaccination of CoronaVac and highlight the utility of a systems biology approach in defining molecular correlates of protection to vaccination.
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SciScore for 10.1101/2021.07.21.21260959: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics Consent: Written informed consent was obtained from each subject and protocols were approved by Institutional Review Boards of Sayan People’s Hospital.
IRB: Written informed consent was obtained from each subject and protocols were approved by Institutional Review Boards of Sayan People’s Hospital.Sex as a biological variable not detected. Randomization Plasma proteomics: Ten of the fifty subjects were randomly selected for plasma proteomic analysis. Blinding not detected. Power Analysis not detected. Table 2: Resources
Antibodies Sentences Resources Plates were coated with either SARS-CoV-2 recombinant antigens or mouse anti-human IgM monoclonal antibody. anti-human IgMsuggested: None… SciScore for 10.1101/2021.07.21.21260959: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics Consent: Written informed consent was obtained from each subject and protocols were approved by Institutional Review Boards of Sayan People’s Hospital.
IRB: Written informed consent was obtained from each subject and protocols were approved by Institutional Review Boards of Sayan People’s Hospital.Sex as a biological variable not detected. Randomization Plasma proteomics: Ten of the fifty subjects were randomly selected for plasma proteomic analysis. Blinding not detected. Power Analysis not detected. Table 2: Resources
Antibodies Sentences Resources Plates were coated with either SARS-CoV-2 recombinant antigens or mouse anti-human IgM monoclonal antibody. anti-human IgMsuggested: NoneSoftware and Algorithms Sentences Resources To remove highly abundant interfering proteins in human plasma, a multiple-affinity removal system liquid chromatography (LC) column (High Select™ Top14 Abundant Protein Depletion Mini Spin Columns; Thermo Fisher Technologies, Santa Clara, CA, USA) was used. Thermo Fisher Technologiessuggested: NoneThe resultant mass spectrometry data were analyzed using Maxquant (Version 1.6.17) and the protein search database used was the Homo sapiens FASTA database downloaded from UniprotKB (UP000005640.fasta). FASTAsuggested: (FASTA, RRID:SCR_011819)UniprotKBsuggested: (UniProtKB, RRID:SCR_004426)All UPLC-MS/MS methods used the ACQUITY 2D UPLC system (Waters, Milford, MA, USA) and Q-Exactive Quadrupole-Orbitrap (Thermo Fisher Scientific™, San Jose, USA) and TripleTOF 5600+ (AB SCIEX, MA, USA) with ESI source and mass analyzer. Thermo Fisher Scientific™suggested: (Thermo Fisher Scientific, RRID:SCR_008452)Open database sources including KEGG and MetaboAnalyst, Human Metabolome Database, were used to identify metabolic pathways. KEGGsuggested: (KEGG, RRID:SCR_012773)Orthogonal partial least squares discrimination analysis (OPLS-DA) and partial least squares-discriminate analysis (PLS-DA) was conducted using MetaboAnalyst 5.0 (http://www.metaboanalyst.ca/MetaboAnalyst/). MetaboAnalystsuggested: (MetaboAnalyst, RRID:SCR_015539)Metscape was used to build the network of metabolites, analyze the correlation of these different metabolites and visualize the networks. Metscapesuggested: ( Metscape , RRID:SCR_014687)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
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: Please consider improving the rainbow (“jet”) colormap(s) used on page 41. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
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- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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