Team:Harvard/Engineering

Overview

After designing and cross-validating an antibody scoring function, we successfully created a Differential Evolution algorithm which induced targeted mutations in a given CDR-H3 sequence to optimize its ability to bind and neutralize SARS-CoV-2. In particular, our model was able to consistently demonstrate a rate of 27% improvement (with respect to our scoring function) within only 500 epochs; this number is likely to increase with access to more computing power. (For more details about these results, check out our Results page.) In accordance with the principles of the Research → Imagine → Design → Build → Test → Learn → Improve → Research design cycle, we decided to design a series of lab experiments to test the efficacy of our computationally validated data.

Throughout our extensive collaboration with the UIUC iGEM team, we received several antibody sequences which they have validated and also plan to use those in our assays. Although we were unfortunately unable to have lab access during the timeframe of our project, we still strongly believe that having a plan for future lab validation is integral to the success of our project.

Experiments

Nucleic acid nanoparticles have broad biomedical applications, including material organization and biocomputing (Afonin et al. 2020). This project aims to utilize nucleic acid nanoparticles for a therapeutic vaccine for SARS CoV-2. Currently, there are a variety of therapeutic targets for SARS CoV-2; in particular, this project will focus on the spike protein (Andersen et al. 2020). Current SARS CoV-2 treatment platforms are insufficient. Vaccines rely on the immune system producing effective antibodies, whereas antibody treatments are not scalable for sufficient delivery on a population level. This project provides a new model, addressing these concerns, for a therapeutic vaccine treating SARS CoV-2.

We recognize that experimental validation is critical for any project. To that end, we have listed a few of the experiments we are currently planning for validation in the lab.

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Figure 1: Overview of DNA MOT Box design. The antibody mRNA is carried to the B-cell, which translates the sequence into antibodies that ultimately neutralize the SARS CoV-2 virus.

Antibody Validation

In order to validate the mRNA sequence, we must first show that it produces a viable protein. Thus, we plan to conduct an In Vitro Translation (IVT) Assay that translates mRNA sequences in vitro. We will use our optimized mRNA sequence, a sequence from our collaborator, and a sequence from the literature as a control. Each sequence will be purified and tagged for identification with HA and His tags. Our optimized machine-learning sequence will be compared against a literature sequence for viability. After determining that mRNA sequences do produce proteins, we will test the efficacy of that protein. In particular, we plan to test whether or not our antibodies bind to the SARS CoV-2 spike protein through an enzyme-linked immunosorbent assay (ELISA). An ELISA is a plate-based assay technique that detects and quantifies solutions such as peptides, proteins, antibodies, and hormones. Detection is accomplished by measuring the activity of the reporter enzyme through incubation with the appropriate substrate to produce the product. Given positive binding results, we may then quantify binding affinities (binding curve, and estimated dissociation constant) between antibody candidates and spike protein using the direct ligand-receptor interaction ELISA method detailed by Syedbasha et. al., 2016 (https://doi.org/10.3791/53575).

Machine-Learning Origami Therapeutic (MOT) Box Validation

To experimentally verify the MOT Box design, we first plan to test assembly of the design by running a series of folding assays at varying temperatures and magnesium concentrations (Engelhardt et al. 2019). A folding reaction is a mixture that has scaffold DNA, staple DNA, water, buffer to stabilize pH, and other salt ions. Folding is when the sample is subjected to thermal denaturation and renaturation. Folding reactions will be prepared in PCR tubes with standardized volumes. Varying magnesium concentrations will be used as magnesium has a drastic effect on the quality of folding of a DNA origami vehicle. We will use 8 different concentrations, ranging from 12 mM to 26 mM. We will also conduct reactions at a gradient of folding temperatures. We will conduct gel electrophoresis to validate size of folding objects (with 2% agarose gel loaded with the DNA). Next, in order to validate structure, we will use negative-staining Transmission Electron Microscopy (TEM). This will involve adsorption of the origami objects onto a TEM grid, prepared for TEM by coating and evaporation of a collodion plastic film, followed by staining of the adsorbed objects with 2% aqueous uranyl-formate and imaging with the electron microscope.

After validating the structure itself, we plan to test release mechanisms by conducting a series of assays that will test the pH-triggered i-motif hinge as well as the temperature sensitive mRNA handle (Daljit Sing et al. 2019). Finally, we plan to test the entire system in vitro utilizing Ramos Blue Cells.