BioQuakes

AP Biology class blog for discussing current research in Biology

Author: ethanelab

How are new COVID variants identified?

COVID variants are of high concern for scientists studying the disease. Some variants can be more infectious or cause more severe illness. Additionally, some variants can evade vaccines by having different surface proteins than the variant the vaccine was created for. This causes the antibodies produced from the vaccine to be less effective against other variants. In AP Biology class we discussed how the Delta Variant, first identified in December 2020, has a different spike protein structure than the original virus from which the vaccine was created from. This allows the variant to be more infectious, and make the vaccine less effective against it. But, what are COVID variants? And how are they discovered? Hand with surgical latex gloves holding Coronavirus and A Variant of Concern text

COVID variants are “versions” of the virus with a different genetic code than the original one discovered. However, not every mutation leads to a new variant. This is because the genetic code of the virus codes for proteins. Some mutations will not change the structure of the protein and thus not change the virus. So, COVID variants can be defined as versions of the virus with a significantly different genetic code than the original virus.

To detect new COVID variants, scientists sequence the genetic code of virus which appears in positive COVID tests. Scientists look at the similarity of the genetic sequences they find. Then, if many of the sequences they get look very similar to each other, but different to any other known virus, a variant has been discovered.

To sequence the RNA of the virus, scientists use what is called Next Generation Sequencing (NGS). To understand how NGS works, it is best to start with what is called Sanger Sequencing. Sanger Sequencing utilizes a modified PCR reaction called chain-termination PCR to generate DNA or RNA fragments of varying length. The ending nucleotide of each sequence is called a ddNTP, which contains a florescent die corresponding to the type of nucleotide. The addition of a ddNTP also terminates the copying of the particular sequence. The goal of this PCR reaction is to generate a fragment of every length from the start to the end of the sequence. The sequences can then be sorted by length using a specialized form of gel electrophoresis. The sequence is then read by using a laser to check the color of the fluorescent die at the end of each sequence. Based on the color and size, the nucleotide at that position of the genomic sequence can be found.

Sanger Sequencing Example

The difference with NGS is that many sequences can be done in parallel, allowing for very high throughput. In other words, with NGS many COVID tests can be sequenced in once.

Progress Towards Solving a 50-year-old Problem in Biology

Protein structures revealed at record pace

One of the hardest problems in biology is predicting the structure of a protein. Proteins are complicated. There are many interactions  between both the side chains and backbones of the proteins, making it very difficult to predict how a protein will fold into its 3D structure solely based on the amino acid sequence (primary structure). In our AP Biology class, we talked extensively about how this 3D (tertiary) structure of the protein is extremely important as it determines the function of the protein. For example, the success of the delta variant of SARS-CoV-2 is largely due to the change in the tertiary structure of it’s spike proteins. Thus, if the 3D structure of a protein is known, it is much easier to predict the function of that protein, and how well it performs the function. However, the methods of determining the tertiary structure of proteins is extremely costly. To determine the structure of a single protein, it can take up to $120,000 and one year.

AlphaFold 2.0 is a breakthrough in this long thought impossible problem. AlphaFold, created by Deepmind, uses deep learning to predict protein’s tertiary structures. In particular, it uses an architecture of transformers, a relatively new and increasingly popular deep learning technique. Using this method AlphaFold is able to achieve remarkably accurate and detailed results, even on an atomic level.

Because of its ability to predict the structure of unknown proteins, AlphaFold can be used to determine how a single nucleotide mutation can affect the structure of a protein. Interestingly, many diseases result from an improperly folded protein, these include: Cystic Fibrosis, Alzheimer’s, and Parkinson’s. While the protein structures themselves do not often lead to the creation of new treatments, they do offer a better understanding of how the protein works. This deeper understanding can then be used to develop new therapies. Thus, AlphaFold has the potential to accelerate new treatments for many untreatable diseases at a much lower cost.

In addition to diseases resulting from misfolded proteins, AlphaFold can be used to predict the effect mutations will have on the folding of the SARS-CoV-2 spike proteins. This can help to quickly determine how a mutation will change the shape (and thus function) of the spike proteins. This makes it much easier to predict how these mutations will affect the spread and severity of the new variants and, using this info, classify the new variants.

However, AlphaFold is not perfect. While most predictions are quite good, a small percentage of the protein structures generated are clearly  inaccurate, putting hydrophobic amino acids on the outside of the protein. Knowing this, it is still necessary to analyze any prediction made by the computational model before using it for biological analysis.  Nonetheless, AlphaFold is a powerful tool for prediction of protein structure and will revolutionize the field of computational protein structure prediction.

If you want to experiment yourself with AlphaFold, a working notebook can be found here. Any PDB sequence can be queried, and the AlphaFold model will predict the structure to the best of its ability.

 

 

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