COVID-19 Coronavirus Antigen Microarrays

Custom antigen microarray services

In addition to predesigned antigen microarrays, GeneCopoeia offers custom antigen microarray services in the following areas:

• Custom printing and spotting. GeneCopoeia will create custom antigen microarrays built to your specifications.

• Sample processing. Send us your blood, plasma, tissue, or other biological sample and we will prepare it for processing and incubation with any of our predesigned antigen microarrays or custom-built antigen microarrays

• Data analysis. Once samples are processed and incubated with an antigen microarray, we will analyze the raw data. The standard analysis service includes: 1) An Excel file of the Net Signal Intensity (NSI) for each antigen on the array, normalized to internal controls; and 2) a heat map

Additional analysis services, including proteomic analysis, pathway analysis, and more, are also available.

To inquire about custom antigen microarray services, please contact us at inquiry@genecopoeia.com.

GeneCopoeia's OmicsArray™ antigen microarrays contain up to 120 purified proteins spotted onto nitrocellulose filters, which are adhered to glass slides. In addition, 8 spots are included for normalization. Each slide carries 16 identical arrays, and so can be used to process up to 15 samples simultaneously as well as a negative control. As little as 1 ul serum or 50 ul of other bio fluids are needed for each sample.

As shown in Figure 1, arrays are incubated with patient samples, and any antibodies in the  samples bind to their cognate antigens on the array. The arrays are washed to remove unbound antibodies and other proteins, then co-incubated with Cy3- and Cy5-labeled secondary antibodies. The dual labeling strategy is intended to distinguish between immunoglobulin (Ig) subtypes present within samples. For example. a Cy3-labeled anti-IgG secondary antibody is used to detect IgG antibodies, and a Cy5-labeled anti-IgM secondary antibody is used to detect IgM antibodies. Fluorophore-labeled secondary antobodies are available for detecting IgA, IgD, IgE, IgG and IgM immunoglubulins, as well as IgG subclasses IgG1, IgG2, IgG3, and IgG4.

After washing to remove unbound secondary antibodies, signals are detected using a GenePix® 4400A microarray scanner. The raw data is then analyzed using GenePix® 7.0 software.

Figure 1. Workflow for detection of antibodies in samples using GeneCopoeia's OmicsArray™ antigen microarrays.

GeneCopoeia provides data analysis as part of its custom antigen microarray services. After array scanning, raw data are collected and analyzed using GenePix® 7.0 software. The standard service includes data normalization to include fold changes of, for example, disease vs. healthy control, and a heat map showing each antigen ranked by level of fold change. Our service undergoes the following steps:

1. Collection of raw data. After scanning, raw signal intensities are collected in an Excel file, as shown below.

2. Next, the raw data are normalized to controls on the array, and the Net Signal Intensity (NSI) values, as well as the signal-to-noise ratios (SNRs) are tabulated in an Excel file,

3. The final step of the standard analysis package is to determine the "Antibody score" which is the relative enrichment of a given antibody in a sample. The antibody score is determined numerically and displayed in a heat map. A higher score (shifted toward red on the heat map) suggests a stronger antibody-antigen interaction, as shown in the following example:

4. In addition to the standard data analysis package, customers can also choose custom data analysis services. One such service is to classify positive antigens on the array using Gene Ontology (GO) analysis, which classifies genes and proteins based on known biolgical functions. An example of the readout from GO analysis for molecular function is shown below:

Further, GO analysis for biological processes is shown in the following example:

5. Another widely-used tool for bioinformatic analysis is KEGG (Kyoto Enclycopedia for Genes and Genomes) Pathway Analysis, which we use to group positive antibody-antigen interactions on the basis of defined biologica pathways, as displayed in the example below: