The Future of Biology: Biocomputing

image from Entrepreneur.com

Throughout history, mankind has continued to usher in new inventions and technologies that led to radical changes in the way people lived their lives and viewed the world. The ever-universal question of “Who am I?” has remained just as elusive on both a literal and internal level. There are countless things in biology we don’t understand or don’t even know exist. Even if it may seem that we are on our way ‘to play God’ with gene-editing, we are still a long way off from fully utilizing and manipulating biology to solve some of our greatest problems. Although in its infancy, biocomputing has the potential to completely revolutionize medicine, computation, the environment, and a variety of other areas we can’t even imagine!

Biocomputing or organic computing is the idea of creating computing systems made of biological materials. Think DNA, RNA, proteins, and other organic structures. It falls under synthetic biology, the idea of redesigning organisms to have new abilities and/or properties.

For example, companies are developing DNA technology that can be used to store the world’s digital data, synthetic biologists are developing genetic circuits for targeted therapies, and countless other applications that haven’t been realized yet!

Even though we often like to separate biology and computer science as two separate domains, the two fields are beginning to overlap in ways that could bring about revolutionary innovation. If you think about it, cells are examples of sophisticated computing ‘devices’ that can take ‘input’ from its environment (i.e. light, etc.) and create a cellular response, or ‘output’, that suits the situation. Likewise, computers take input from its user and creates an output by displaying the desired response.

image from New Scientist.com

“Four Bases are Better Than Two”

This is kind of a knockoff version of the adage “Two heads are better than one”, but the same applies to biocomputing. In fact, four bases are better than two. Let me take a step back and explain.

In the past, whenever someone asked me how a computer worked, I would often give a disinterested response of something along the lines of “you know, a bunch of 0s and 1s.” But now, that’s changed.

These 0s and 1s are known as binary values that store digital information. Binary is a base-two system where there are only two values. In this system, 1 is ON and 0 is OFF. Think of polar opposites like Yes or No, True or False, Right or Wrong.

However, we are reaching a limit as the amount of data we are producing far exceeds our capacity to store all this information. We are reaching the limits of classical computing with our transistors sized down to the point where it’s almost impossible to downsize even more and the nature of the problems we want to solve require more computing power than what is currently available.

graphic from nodegraph

It doesn’t help that estimates by the International Data Corporation (IDC) predict that by 2025, the world’s data will grow to 175 zettabytes or 1,125,899,910,000,000 megabytes!

Thankfully, DNA can provide a solution. As a quick recap, DNA is the blueprint for all living organisms on the planet responsible for biological processes and is ultimately what makes you who you are (as cliché as that sounds). DNA is made up of four bases: Adenine, Guanine, Cytosine, and Thymine. Each has its own corresponding binary values:

image from LansaarResearch.com

Remember what I said about having 175 zettabytes of data by 2025? The crazy thing is that when this technology becomes scalable, you could store all the information on the internet in a shoebox!

But wait…how does this work?

image from Medium

The process starts off by taking digital files and converting them into binary code. From there, the binary code is encoded into nucleotide bases and synthesized into DNA. This information, if stored correctly, can last for hundreds of thousands of years.

When the data needs to be retrieved, the DNA is sequenced and decoded. From there, the binary code is read by a computer to display your desired file.

At the moment, this technology is still being developed. Errors in DNA sequencing hinder DNA digital storage from being scaled up completely. As a result, this solution will first function as long-term storage before trickling downstream to replace current methods of digital storage.

Photo by Umberto on Unsplash

Genetic Circuits & Medicine

Cancer. Aging. Chronic Diseases. Declining health could be a result of genetics, a poor lifestyle, or just old age. However, recent advances in fields such as nanotechnology, personalized medicine, and biocomputing suggest the potential to create nanobots that patrol your body to maintain your health.

When this technology is fully developed, it will be able to respond to signals in their environment and respond efficiently and effectively. One way we can achieve this is by borrowing a concept from electrical engineering: Logic Gates.

Logic gates form the basis of all digital hardware, with hundreds of millions of working in tandem so you can watch a YouTube video or even read this article.

Basically, logic gates take in inputs (binary) and produce outputs based on these input values. You can think of it as functions where based on the numbers that you input, it produces an output based on the rules of that function.

In this article, we are only going to focus on basic logic gates: AND, NOT, OR.

image from Quora

AND: when both inputs are 1, then the output will be 1.

NOT: has one input and one output. The output is the opposite of the input (if your input is 1, the output is 0 and vice versa)

OR: only one input is required to be 1 for the output to be 1 as well.

Utilizing these concepts, genetic circuits can be used for drug delivery, to sense & diagnose diseases, gene therapy, and the list goes on! For instance, in 2015, researchers developed a synthetic circuit that could successfully target cells and cause the cell to undergo apoptosis (cell death).

graphic from https://pubs.acs.org/doi/pdf/10.1021/acs.chemrev.8b00198

First, DNA aptamers bind to their targets located on the surfaces of the cells. Aptamers are short, single-stranded DNA (ssDNA) or RNA (ssRNA) that can bind to specific targets such as antigens, proteins, cells, toxins, etc. When the aptamers bind to these cells, they leave an ssDNA ‘tag’. Then, a small molecule called an effector, will analyze these tags. For this experiment, their effector was a double-stranded DNA (dsDNA) complex that carried a drug/dye specific to the tag profiles attached to the cell of interest. Since they were using an AND probe, that meant that both of the ssDNA tags had to be present for cellular apoptosis. If both are present, a tool called Toehold-Mediated Strand Displacement (TMSD) would exchange the target DNA sequence with their dsDNA complex sequence, resulting in cell death.

In summary:

ssDNA binds to target on cell — leaves a tag — effector analyzes tags:

if has both ssDNA tags, adds drug/dye — TMSD used to exchange target sequence with dsDNA complex sequence — cellular apoptosis

if doesn’t have both ssDNA tags — nothing happens

Closing

As a new and emerging field, biocomputing has enormous potential to revolutionize data storage, medicine, and computation! Since this technology is still in the works, there are countless other applications with profound impacts that we haven’t even considered yet. Despite this, one thing remains clear: the intersection of technology and biology will usher in a new era of innovation that the world has never seen.

Hi! My name is Maggie and I am an ambitious 16-year-old looking to impact the world through emerging biotech. At the moment, I’m looking to explore topics such as biocomputing, philosophy, ethics, and climate change.

If you got to the end, thank you for reading my article! Feel free to connect with me on Linkedin or sign up for my personal newsletter if you would like to receive updates on my biocomputing journey!

A 17-year-old who knows less about life than she thought she did. Fascinated by biology, specifically biocomputing, synthetic biology, and bioinformatics.