Automated ELISA On-Chip for the Detection of Anti-SARS-CoV-2 Antibodies

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Abstract

The COVID-19 pandemic has been the most critical public health issue in modern history due to its highly infectious and deathly potential, and the limited access to massive, low-cost, and reliable testing has significantly worsened the crisis. The recovery and the vaccination of millions of people against COVID-19 have made serological tests highly relevant to identify the presence and levels of SARS-CoV-2 antibodies. Due to its advantages, microfluidic-based technologies represent an attractive alternative to the conventional testing methodologies used for these purposes. In this work, we described the development of an automated ELISA on-chip capable of detecting anti-SARS-CoV-2 antibodies in serum samples from COVID-19 patients and vaccinated individuals. The colorimetric reactions were analyzed with a microplate reader. No statistically significant differences were observed when comparing the results of our automated ELISA on-chip against the ones obtained from a traditional ELISA on a microplate. Moreover, we demonstrated that it is possible to carry out the analysis of the colorimetric reaction by performing basic image analysis of photos taken with a smartphone, which constitutes a useful alternative when lacking specialized equipment or a laboratory setting. Our automated ELISA on-chip has the potential to be used in a clinical setting and mitigates some of the burden caused by testing deficiencies.

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  1. SciScore for 10.1101/2021.08.05.21261664: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    EthicsIRB: 2.1 Sample collection and preparation: Blood samples were collected according to the protocol approved by the Institutional Review Board of the Alfa Medical Center with number AMCCI-TECCOVID-001.
    Consent: All the participants provided written informed consent before sample collection, which took place in a clinical laboratory, that followed the guidelines established by Official Mexican Standards: NOM-007-SSA3-2011, NOM-087-SEMARNAT-SSA1-2002, NOM-010-SSA2-2010, NOM-006-SSA2-2013, and NMX-EC-15189 IMNC-2015.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Next, a 1 hour incubation of 100 µL of anti-human IgG conjugated with HRP (1:15,000 dilution) (Thermo Fisher Scientific, MA, USA) was performed, at room temperature, to identify the presence of anti-spike antibodies; followed by three washes with WB.
    anti-human IgG
    suggested: None
    anti-spike
    suggested: None
    Commercially available microfluidic instrumentation was used to assemble the experimental setup that enabled the automation of our ELISA on-chip assay, from antigen immobilization to the detection of an-ti-SARS-CoV-2 antibodies.
    an-ti-SARS-CoV-2
    suggested: None
    Experimental Models: Organisms/Strains
    SentencesResources
    All the participants provided written informed consent before sample collection, which took place in a clinical laboratory, that followed the guidelines established by Official Mexican Standards: NOM-007-SSA3-2011, NOM-087-SEMARNAT-SSA1-2002, NOM-010-SSA2-2010, NOM-006-SSA2-2013, and NMX-EC-15189 IMNC-2015.
    NOM-006-SSA2-2013
    suggested: None
    Software and Algorithms
    SentencesResources
    The second approach was based on taking photos with a commercial smartphone, of the microplate and microfluidic devices, under same lighting conditions, for further color intensity analysis using the color histogram plugin of the ImageJ software (NIH, MD, USA) to assign a value to each reaction.
    ImageJ
    suggested: (ImageJ, RRID:SCR_003070)
    The results showed non-parametric behavior; therefore, the statistical analysis was performed with the Wilcoxon test, using a p-value < 0.01 and the IBM SPSS Statistics 27 software (IBM Corporation, NY, USA).
    SPSS
    suggested: (SPSS, RRID:SCR_002865)
    DataGraph version 4.7 (Visual Data Tools Inc., NC, USA) and Microsoft Excel (Microsoft Corporation, WA, USA) were employed to graph the results.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)

    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 found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).


    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.

    Results from scite Reference Check: We found no unreliable references.


    About SciScore

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