Here on CleanTechnica we report on clean technology of all kinds, from electric vehicles, renewable energy, recycling, and much more. However, a topic we have never touched on, or rarely touched on is Synthetic Biology.
Random chance vs. Synthetic strategy
Anyone who graduated high school likely knows at least some biology. It is the study of natural biological systems, from tiny viruses to some of the biggest creatures like blue whales. Some people know biology so well that they think they can up the ante on nature and synthesize something better themselves. In some ways, it isn’t that hard to improve upon nature because with evolution, nature took the long path. Every single development took thousands of years and every improvement is a random change that had performed better by 1%. After a thousand years those that didn’t have this tiny, almost irrelevant advantage went extinct. This is dealing with unfathomably large numbers that the human mind can comprehend, so we use scientific notation and have to have faith in these large numbers and faith in science.
So if random mutation is the long way then simulating a new DNA permutation on a computer is the new way. Using intelligence to combine pieces of different evolutionary chains together that result in a path not previously taken by evolution have the potential to unearth new “unevolutionary” advantages. That is the theory behind synthetic biology. Examples of this include Dolly the cloned sheep, potatoes that glow in the dark when they need water, the soy based (leg)hemoglobin that makes Impossible Foods’ delicious new burger possible, golden rice, and the extremely controversial genetically modified HIV-resistant human babies in China that have been all over the news recently.
While each of the cases are solutions to a problem, the real controversies are the 2 significant problems scientists need to solve that make synthetic biology a clean technology. Those 2 significant problems are climate change (no huge shocker there) and a garage designer made superbug epidemic. In two parts we will explore both topics.
When we talk about clean tech, we usually mean clean from greenhouse gases and clean from chemical pollutants. What about clean from unwanted biological pathogens?
An Even Bigger Existential Threat
Humanity has passed through all of the evolutionary steps that took our species from molecules to single- and multi-cellular life to animals, and eventually to the rise of intelligence. We have yet to face what is perhaps our largest challenge so far: to not get annihilated like the dinosaurs and especially not to annihilate ourselves, which we are at a much greater risk of.
These are the existential threats that we always hear about and try to prevent as a global society. Past generations had to contend with the prospect of nuclear annihilation which required a handful of treaties and documents to be signed. Climate change is much more challenging as good policy must be made worldwide (so a LOT of treaties and documents to be signed), and the majority of citizens and businesses have to do their part as well.
The abuse of synthetic biology also has the potential to be a threat to our species. It doesn’t just require to keep our leaders in check, and doesn’t require that most of the population does their part. Instead, it requires safety measures and good moral behavior of every single intelligent being on our planet because with the advent of synthetic biology, with the tools that everyone will have in the next few decades, it will only take any one deeply-troubled person to succeed at annihilating the entire human race, so we need new solutions to combat this threat.
What Is Happening?
The problem presented by synthetic biology is really a convergence of 6 technologies becoming advanced, cheap, and readily available:
- Gene sequencing
- Gene synthesis
- Gene editing a.k.a. CRISPR
- Protein synthesis
- Computational power
- Narrow artificial intelligence
Lets just quickly skim over what these are and do and what’s new with them.
This is the process of reading a strand of DNA and turning it to computer text with the letters A, C, T and G (Adenine, Thymine, Guanine, Cytosine) representing the sequence. The cost of having DNA sequenced and analyzed has gone down from $100 million dollars in 2001, to just $10 million in 2007, to $10 thousand in 2011, $1,000 in 2015. This resulted in $40 dollar test kits in 2019, with the possibility of getting the price down to a single dollar or even cents in the next few years or decades (although to be fair those don’t fully sequence your entire DNA).
Literally the opposite of gene sequencing, it’s printing a strand of DNA from a computer file. The price of that has also significantly gone down but is still lagging about a decade behind sequencing. If we were to synthesize all 3 billion base pairs of the human genome (I know it’s actually 3.2 but let’s just keep it simple here), in the year 1998 that would have cost $300 billion dollars, $15 billion dollars around 2002, $1.5 billion in 2005, $750 million in 2011, below $300 million in 2015, and as of last count was at $90 million in 2016.
Information newer than 2016 is not published yet, however the progression of this technology over the years has been comparable to the now extinct “Moore’s Law” which states that technology doubles in power every two years. In this case, it has become twice as cheap every 2 years, in which case, we could extrapolate the cost to be $45 million dollars. Barring a significant breakthrough, synthesizing DNA won’t drop to the $1,000 price until 2066.
Nonetheless, the cost of synthesizing the whole Human genome might be a useless metric since the cost of replicating the DNA of a virus in 2016 would have cost between $53 and $84,000 depending on the virus. In any case, this makes gene editing very possible and in most cases, not too expensive. So far, a team of researchers have created an entirely new kind of E. coli bacteria where the DNA wasn’t just modified but practically created and printed from scratch. In 2019, the length of that DNA was 4 million base pairs.
This is really impressive since the human genome has 30 million base pairs and the previous record was 1 million. While they didn’t share the price tag to synthesize this genome, we estimate the cost to be between $6 to $12 million dollars, depending on synthesis prices. Imagine the kinds of experiments scientists will be able to do when the prices of gene synthesis drop further.
The process of editing DNA genes. At first it was extremely expensive and only served as a very blunt instrument where the new bases would blend with the DNA at an unpredictable location. Since then, it has become a lot cheaper, a lot more predictable, and reliable. Cheaper, in this context, still means hundreds to thousands of dollars per experiment. However, thanks to the new CRISPR CAS9 technology, it’s now tens to hundreds of dollars per experiment. CRISPR CAS9 is still only 70% effective and on a large strain of DNA like the human DNA, it might cut in the wrong place, with the same repeating bases the CRISPR protein is looking for.
If DNA is an instruction set then Proteins are akin to large molecules, veritable building blocks made of amino-acids that “do all things”. Protein synthesis is the creation of new proteins that can no longer be found in nature due to evolution, extinction or complete synthesis of new proteins that were never in nature to begin with. Proteins are usually made up from an base of 20 canonical amino acids and consist of about 100 amino acids. It is believed that all protein permutations found in nature make up less than one in a thousand of all the possible permutations and that is just using the 20 amino acids nature has used. Imagine what might be possible if we add new synthetic ones to the mix?
While I’m guessing that it isn’t necessary to explain what it is to compute equations, what is important is explaining the effect affordable computational power has on this field. As you can see, the biological programming language consists of numbers ranging in the billions that require a significant amount of computing power to process. A single strand of DNA is code, however a particular base pair is not just a precise command of do this and that. A single base pair can have effects on any number of parts of the body and to a certain extent, have an effect on multiple diseases and disorders, risks to get those diseases and disorders. Combinations of just 2 numbers of bases, located anywhere within the 6 billion slots might combine to have an effect on something.
A good example is cancer. It has links to millions of different bases within the genome. There are some on and off switches that can be turned off or modified but in reality, it’s extremely difficult to simulate the effect of what the alteration or insertion of even one base pair can have on the whole entire 6 billion characters set of code. To understand this, we need extremely complicated and computationally power-hungry simulations. The absolute best visualization I have ever seen of more computational power having on simulating and testing parts of DNA is from the 2014 Google I/O conference. It was captured in the video below and starts at 40:15 and you can stop it after 42:37.
This is the final component that is really important since it is only artificial intelligence and deep learning methodologies that can help come up with simulations, “instinctively” predict what might be an interesting permutation to try, perform the simulation, and report back to the regular old humans when it finds anything worth reporting about. Brute force testing every permutation is simply not an option and would obviously be a huge waste of resources. The smarter the AI, the quicker and more efficiently it will help us turn our ideas into simulations and results.
The Convergence Of These Technologies
Wow, that was a lot of explanation on the convergence of a lot of interesting technologies so lets now get to the problem at hand and possible clean tech solutions we need. It’s important to understand that the tools are already out there today. CRISPR is already used as part of some high school science experiments, give it enough time, and gene editing tools will be as standard as a graphing calculator is today. The problem already exists today as well and we have seen demonstrations.
There is a man who used CRISPR to try to enhance his muscles, live-streaming himself as he injected the syringe. Due to the dosage and method it didn’t have any effect and luckily no side effects, although it was still extremely reckless. That stunt was only good for one thing, raising awareness of the problem. Anyone can get their hands on these tools. A do-it-yourself genetic engineering kit costs just under $2,000 and strands of DNA are available on the market for $20 a pop. The good news is that in computer terms while the hardware is there and simple to use, the programming and software aren’t.
Imagine if someone combines two or more existing viruses to make a super virus that is not only deadly but also has an incubation period of a month. Right now, it would take a genius virologist or a team of really smart virologists at a university or large corporation to make something like that. The real issue is that in the future, these tools allow anyone with the right bachelor diploma or even just a high school diploma (depending on how far in the future we’re talking about) to do dangerous experiments.
Right now, such “geniuses” constantly try to make doomsday viruses to see how bad bad can get and come up with defenses, that is simply science. While in general, it is harmless and advances science, it poses certain risks. A slightly more immediate risk is not that the virus gets out of the lab and released, but rather that the DNA of this superbug, stored on the computer reaches the internet. As some studies show, universities get hacked on a regular basis, so this is not necessarily a fictional scenario. Even if that were to happen, it still would not be an easy task to recreate it with the available tools today. The internet however, does not forget, and a decade or two or three from now, people can still “print” this file when it will be a lot simpler.
Some viruses inject their DNA into ours so that our body makes more copies of the virus. If people can easily print strands of DNA, inject a mouse (or themselves) with CRISPR containing that strand and create a virus that can annihilate all human beings that easily, that is a recipe for abuse (and catastrophe). Especially if anyone can do it in their garage. Right now, mass killings are only limited by the tools available, whether that be a mass stabbing in Japan or mass shootings in the US. As mentioned before, it only takes one deeply troubled person to kill a lot of people, in the future, this technology could make that even easier.
I can already guess your first reaction. It was probably something along the lines of “ban the hell out of all that stuff!” Unfortunately, that really is not an option. This Pandora’s Box has been open for years, the technologies needed to make use of it just weren’t there yet. Our best hope for protection is to develop early warning systems, defenses, and counter-measures.
What Can Be Done?
Smart Pathogen Sensors
A good example is a smoke detector, we have them everywhere. Imagine a device that size that is also a micro viral lab, testing air samples, breaking down any viruses it manages to catch, run simulations on its DNA and sounding the alarm if needed. With the internet-of-things starting to become commonplace, these could all even communicate and work together. Eventually, this could literally be small enough to be part of an implant. There are actually over 7 billion of such sensors already out in the world only they hardly ever get updates and do not work together. We call this system the human immune system.
According to George Church (professor at MIT and Harvard and known by some as the “Father of Modern Synthetic Biology”), a tiny drop of “human bodily fluid” in enough to see what your immune system is reacting to and how. What we need to do is network these sensors together and process all that information together. Imagine large scale studies that currently take many years with varying and often inconclusive results taking only a day to process.
Thanks to new possible permutations of DNA and through protein synthesis, we can use this technology to make universal vaccines for a wide variety of “malicious viral code snippets”. If our immune system is an anti-virus, this could be thought of as an update.
Immune System 2.0
We can use this technology to make a much stronger immune system and bacterial microbiome. Since it is only in recent years that we have understood that much of our health is based on the diversity and numbers of good bacteria we have in our guts.
Faster Cure, Vaccine Creation & Dissemination
Currently, the search for cures and vaccines takes too long. Reactions to the H1N1 flu and Ebola viruses were simply too slow. This is where computational power and AI can really make a big difference. Thanks to the new technologies mentioned above, an internet-connected emergency vaccine printer could become part of every pharmacy or even every household or because our cells currently could technically produce any protein with the correct DNA instructions, it could even be a small implant. Obviously this is still a bit sci-fi for now but the basic technologies are there.
A printer that can currently already print a large number of things on the list already exists. Its currently called a “Digital-to-Biological Converter” and is about the size of a large American fridge that has been flipped to the side. In 2015 Elon Musk was actually interested in using this technology on mars to print bacteria that could terraform the planet. This technology just needs to be improved and miniaturized but we are talking about just a couple of decades or so.
A Better Outbreak Response System
It is the plot of so many movies. Something really infectious gets out, the authorities ground all the planes, but that one guy managed to get on a plane to France (or wherever), and it can’t be stopped. Modern communications technology should be able to speed this up by a lot. If we manage to completely automate shipping, businesses like Amazon could technically eliminate the need to go out for food and water. People could stay at home and work from home to stop a worldwide pandemics in its tracks. The world is safe and the economy is not as severely affected.
Synthetic Biology & Climate Change
As mentioned in the beginning of this article (I know that was a long time ago by now) There is also another way that synthetic biology has to do with clean tech and that is through new technology aimed at combating climate change. Here is a list of some of the things synthetic biology can do for climate change:
Make trees that grow quicker, grow in places they were unable to before, recycle more CO2, and live longer. While this could be done and has been done via selective breeding for decades, it can probably be improved further through synthetic biology. Fossil fuel-created CO2 is carbon taken from deep underground that was not part of the current carbon cycle. Because of that fact, growing more trees will not solve climate change as the carbon stays in the surface carbon cycle. Nonetheless, more trees does improve the circulation of this larger carbon cycle and could help by up to 0.5 degrees according to a recent study published in Science Magazine.
We could modify phytoplankton so that they absorb less heat and potentially even reproduce quicker. Although unlike surface plants, phytoplankton are actually not a very straightforward topic since they don’t lower atmosphere CO2 but instead lower the CO2 found in the ocean and simply increasing their numbers might lead to warmer oceans, which means higher ocean levels, more global warming, and so on. All the possible effects increased phytoplankton might have on the general food chain and ecosystem have to be considered otherwise we will have to start dealing with whale obesity. While the plankton-eating whales example is obviously just a joke, the need for careful informed action is very serious.
Another example of synthetic biology helping prevent climate change is related to nitrogen. Crops like wheat and corn are currently responsible for a very large amount of nitrous oxide, a greenhouse gas that is not talked about as often as CO2 or methane. A synthetically-engineered or modified microbiome might allow for a reduction in the use of soil synthetic nitrogen fertilizer that just adds to the nitrogen oxide in the atmosphere. Instead these microbes could use atmospheric nitrogen for nitrogen fixation.
New Materials & Technologies
Protein synthesis using protein permutations never explored by nature or entirely new proteins from chemicals not found in nature might enable us to also make cheaper, more effective technologies and materials. Think of greenhouse gas filters and other unforeseen technologies that can help us deal with climate change. Unforeseen technologies really are the best way to put it, since they really could improve anything or everything. Better solar panels, better home insulation, cheaper, less complicated ways to create existing technologies and materials or miniaturizing the production, the options are literally so limitless. There is absolutely no way to predict what we can make and what that creation can be used for until we try.
Synthetic biology means we are starting to master what biology did naturally with artificial means. Anything nature has made can do better and can even be turned into a new system, a new technology, a new material. It’s scary that we can’t even predict the boundaries of new possibilities. Perhaps we are “Born too late to explore the earth, born too early to explore space” and while the second part is not a certainty just yet, one thing is for sure: we were certainly born on time to explore scientific possibilities that have never been imagined before.
So, what do you think? Should synthetic biology also fall under clean tech? Let us know in the comments below.
If you are interested in learning more, here are 2 really interesting TED Talks that cover some of the above:
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