A Modular Microarray Imaging System for Highly Specific COVID-19 Antibody Testing
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Abstract
To detect the presence of antibodies in blood against SARS-CoV-2 in a highly sensitive and specific manner, here we describe a robust, inexpensive ($200), 3D-printable portable imaging platform (TinyArray imager) that can be deployed immediately in areas with minimal infrastructure to read coronavirus antigen microarrays (CoVAMs) that contain a panel of antigens from SARS-CoV-2, SARS-1, MERS, and other respiratory viruses. Application includes basic laboratories and makeshift field clinics where a few drops of blood from a finger prick could be rapidly tested in parallel for the presence of antibodies to SARS-CoV-2 with a test turnaround time of only 2-4 h. To evaluate our imaging device, we probed and imaged coronavirus microarrays with COVID-19-positive and negative sera and achieved a performance on par with a commercial microarray reader 100x more expensive than our imaging device. This work will enable large scale serosurveillance, which can play an important role in the months and years to come to implement efficient containment and mitigation measures, as well as help develop therapeutics and vaccines to treat and prevent the spread of COVID-19.
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SciScore for 10.1101/2020.05.22.111518: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Antibodies Sentences Resources The microarrays were then washed 3x with T-TBS buffer (20 mM Tris-HCl, 150 mM NaCl, 0.05% Tween-20, adjusted to pH 7.5 and filtered), labeled with secondary antibodies to human IgA and IgG conjugated to quantum dot (QD) fluorophores for 1 h at room temperature, followed by a second 3× wash with T-TBS before drying. human IgAsuggested: NoneSoftware and Algorithms Sentences Resources In the prototype, we used the Python programming language and the following libraries: picamera, numpy, Image, … SciScore for 10.1101/2020.05.22.111518: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Antibodies Sentences Resources The microarrays were then washed 3x with T-TBS buffer (20 mM Tris-HCl, 150 mM NaCl, 0.05% Tween-20, adjusted to pH 7.5 and filtered), labeled with secondary antibodies to human IgA and IgG conjugated to quantum dot (QD) fluorophores for 1 h at room temperature, followed by a second 3× wash with T-TBS before drying. human IgAsuggested: NoneSoftware and Algorithms Sentences Resources In the prototype, we used the Python programming language and the following libraries: picamera, numpy, Image, scipy. scipysuggested: (SciPy, RRID:SCR_008058)Python and packages are freely available at https://www.python.org/. Pythonsuggested: (IPython, RRID:SCR_001658)Therefore, spherical aberrations of the imaging lens were characterized by taking a reference image of a checkerboard pattern (7 × 14 squares) and corrected in the microarray images using the Open Computer Vision (OpenCV) package for Python (https://opencv.org/). OpenCVsuggested: (OpenCV, RRID:SCR_015526)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 8. 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.
- 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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