Introduction to Biology Through Information #4 [Genetic Engineering]

If organisms are vehicles for information, researchers studying them want to know that information by making full use of various methods. To that end, technologies for increasing, reading, and writing information seem useful. This time, focusing on DNA information, I will introduce the field of genetic engineering, which is responsible for tool development in molecular biology. Please also refer to my previous article, which introduced biological tools from a slightly different perspective.

Technologies for increasing DNA

Developed as a technology to increase DNA in a test tube, the PCR (Polymerase Chain Reaction) method won the Nobel Prize in Chemistry in 1993. The PCR method proceeds by repeating the following three steps.

1. In DNA double helix denaturation, the DNA is heated to a high temperature (about 94-98 degrees) to dissociate the double strand into single strands.

2. In primer annealing, the temperature is lowered to 50-65 degrees, and DNA sequences (primers) designed to specifically bind to both ends of the DNA region to be replicated bind to the single strands.

3. In DNA extension, the temperature is raised to about 72 degrees, promoting the binding of DNA polymerase to the primer and the synthesis of a new DNA strand from the primer as dNTPs are incorporated complementarily into the template DNA strand.

By repeating the above steps for 20-40 cycles, the DNA copy number can be increased exponentially. While general proteins are denatured by the high temperature in the first step, it is also important that the PCR reaction uses a heat-resistant DNA polymerase taken from bacteria that live in hot water, allowing the enzyme activity to be maintained without being deactivated during the PCR cycles.

Although it was developed about 40 years ago, it can increase the amount of DNA by orders of magnitude just by mixing reagents and raising and lowering the temperature, so it is still one of the most commonly used techniques in molecular biology experiments, and this situation is unlikely to change unless there is a revolutionary breakthrough in DNA synthesis.

Technologies for reading DNA

As a technology for easily reading DNA, there is sequencing technology, which won the Nobel Prize in Chemistry in 1980. This time, I will explain electrophoresis, a method for separating molecules used in Sanger sequencing.

Electrophoresis is based on the phenomenon where molecules move under an electric field. In the case of DNA, because DNA is negatively charged, it moves toward the positive electrode when a charge is applied. Also, because the agarose gel used for electrophoresis has a fine mesh structure, smaller molecules move faster. Therefore, when electrophoresed for the same amount of time, DNA gathers in bands at different positions depending on the size of the DNA fragments. Once electrophoresis is complete, the gel is stained to visualize the DNA.

In Sanger sequencing, the sequence is decoded by creating partial sequences of the target DNA and separating and comparing the lengths of the partial sequences ending in A, T, G, or C using electrophoresis.

Recently, next-generation sequencers, which read many sequences in parallel, are often used, making it possible to read the human genome for less than 100,000 yen. Furthermore, regarding reading technology, progress is being made for molecules other than DNA; the fields that comprehensively analyze mRNA, proteins, and metabolites are called transcriptomics, proteomics, and metabolomics, respectively, and research called multi-omics, which handles these across fields, has also increased. Single-cell sequencing technology, which comprehensively reads the RNA of individual cells, has also become an important technology used to elucidate various life phenomena.

Technologies for writing DNA

As a technology for writing DNA, the CRISPR-Cas9 system, which won the Nobel Prize in Chemistry in 2020, can be mentioned. The CRISPR-Cas9 system is a gene editing technology composed of CRISPR sequences and the Cas9 protein. CRISPR sequences are short repetitive sequences present in bacterial DNA, with DNA fragments (spacers) derived from foreign sources such as viruses inserted between the repetitive sequences. Guide RNA (gRNA) is RNA transcribed from CRISPR sequences, and when designing it artificially, a sequence complementary to the target DNA is synthesized so that it can guide Cas9 to the target DNA. The Cas9 protein is an endonuclease enzyme that cuts the DNA double helix and forms a complex by binding with the RNA (guide RNA) transcribed from the CRISPR sequence. The cut DNA is repaired by the cell's DNA repair mechanism, but generally, a mechanism called non-homologous end joining is used, and mutations due to DNA insertion or deletion are introduced.

CRISPR-Cas9 was originally a bacterial acquired immune system, and bacteria can remember information about viruses they have been infected with in the past by inserting it as a spacer between CRISPR sequences. When infected with the same virus again, the bacteria generate guide RNA from the CRISPR sequences and form a complex with the Cas9 protein. The guide RNA binds to the viral DNA, and the Cas9 protein cuts and destroys that DNA.

Even though it is called genome editing, in reality, it just cuts the genome, so I felt uncomfortable when I first studied it, but the PRIME Editor announced in 2019 makes it possible to change any base (A, T, G, or C) to any other base, so it can be said that true genome editing has been achieved.

DNA computing

Finally, as an example showing that DNA is not just a medium for holding information but can also perform computational processing, I will introduce research on DNA computing that implemented search algorithms with DNA.

A famous problem in computer science is the Hamiltonian path problem, which determines whether a path exists that visits every vertex of a graph exactly once. The Hamiltonian path problem has been shown to be NP-complete, and there is no general algorithm for solving it efficiently. On the other hand, there are algorithms for solving this problem, such as the following.

1. Generate many random paths on the graph.

2. Keep only paths that start at the start and end at the goal.

3. Keep only paths that pass through the same number of vertices as the total number of vertices in the graph.

4. Keep only paths that pass through all vertices at least once.

5. Determine if any paths remain.

In the paper, this algorithm was implemented using DNA as follows.

1. Design DNA sequences corresponding to each vertex on the graph. By making the DNA sequence representing an edge of the graph complementary to the latter half of the starting sequence and the first half of the ending sequence, the graph is encoded as a DNA sequence. Then, many of these DNA sequences representing vertices and DNA sequences representing edges are mixed together. Utilizing the fact that complementary DNA base sequences form base pairs, a ligation reaction is performed to link the DNA fragments, creating DNA molecules that encode random paths on the graph.

2. Perform a PCR reaction using the DNA sequences corresponding to the start and goal vertices as primers to selectively amplify the DNA sequences corresponding to paths that start at the start and end at the goal among the random paths.

3. Using DNA electrophoresis, extract only those sequences amplified by PCR whose sequence length matches the sum of the sequence lengths of all vertices, and perform DNA extraction.

4. Synthesize DNA sequences complementary to each vertex, and repeat the operation of keeping only those that contain a DNA subsequence that binds complementarily to it for all vertices. Here, a magnetic bead purification system using biotin-avidin binding is used; by biotinylating the DNA sequence to be purified and binding the DNA sequence complementary to the vertex to avidin-modified beads, it is possible to specifically separate and purify only when there is complementary binding with the DNA extracted in step 3.

5. Finally, the product is amplified by a PCR reaction and subjected to electrophoresis to test whether DNA corresponding to the Hamiltonian path is detected.

In this paper, in addition to basic properties such as DNA information retention and selective binding through complementary base pairing, PCR is used for selection of search results, and electrophoresis is used for determining path length. Also, although not introduced this time, the biotin-avidin binding used to check for the inclusion of each fragment is also frequently used in molecular biology experiments as an incredibly strong bond. The author of this research is an information scientist, and it is research that was only possible because of his deep knowledge of information science and his perspective on life from an informational viewpoint. DNA computing has great potential in terms of both computational speed and energy consumption, but as far as I know, it is an uncharted technology that has not yet been put to practical use, and future research is awaited.

References

Molecular Computation of Solutions to Combinatorial Problems | Science

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