Biological Engineering: designing life


What does the laptop or smartphone you are reading this on have in common with bacteria? Well, at first glance one would say nothing, that life is a miracle, that it is ridiculous to compare them — burn them! — But the truth is that as we get a better and better understanding of the mechanisms that govern the deepest aspects of living beings [of the cell], we see more and more the resemblance between them and the way a computer works. This is beautifully illustrated by synthetic biology. Let me explain.

Synthetic biology is engineering the crap out of biology, or in other words, using the building blocks of life (DNA) as Lego blocks to build and design machines with whatever function we want. Manipulating these parts at our will. And this type of biological machine, this castle of Legos, has a huge resemblance to how a computer works. On the one hand, from its conceptual design (Here we think and define what the machine is going to do and how it is going to achieve it) — with pencil and paper — which uses logic and algorithms. And on the other hand, from its actual construction, genetic engineering, DNA modification, -The genetic MS Word-: copy, cut, paste, insert and even “write” new DNA.

Let’s start with a vulgar but pertinent simplification of what a computer is: a machine that can perform arithmetic or logical operations to carry out instructions that a programmer writes on a program. Something like the recipe that the computer follows to achieve what the cook -I mean, the programmer- wants. This recipe is made up of one or many algorithms, and these work like a box full of successive instructions that use logical operations to generate an output. In short, it goes like this: something enters one side of the “box” [input], which can be a number, a word, the ingredients of a pizza, or anything we want; and after applying the instructions, something else comes out [output], -freshly made pizza, hmm-. But let’s take it slow because good things take time, so what better than an example, right?

Let’s create a simple algorithm: our “little box” is going to tell us if a number is greater, equal to, or less than 4. That is the task, the function of this algorithm. It may sound silly, but this is the foundation of almost any program. Let’s continue. The input is going to be any number A, that the user defines, for example “2” [fun fact: in binary 2 is 10, -what? -]. And here comes the importance of memory… The first step is to be able to register or record [memorize] the input number and also the number to compare, in the case of our example, the number 4. For this, we use RAMs (Random Access Memory), something like the short-term memory of computers. With all this memorized we can put this algorithmic box to work. So the first instruction would be: take the input number and compare it with the reference number, then you have to consider the three possible cases: that it is greater, that it is less, or that it is equal, and tell the machine what to do in each case. Finally, it looks like this: if it is greater, the box produces an output “The number is greater”, if it is smaller, “The number is smaller” and if it is equal, you can imagine what will come out. Let’s see it schematically:

Just like when we read this article we start from the top down, a computer “reads” an algorithm also from the top down. Indeed, a computer has to follow steps, it follows an order. It starts with the first comparison or instruction, which in this case I arbitrarily decided to evaluate if the input number (input here example = 2) is greater than 4, and, depending on that first result, performs the next comparison until finishing all the options.

And well, what is the purpose of explaining all this? Well, these concepts of input and output and logical instructions can be applied to many other systems besides computers, for example bacteria [biological system]. In fact, we can model, quite accurately, biological functions in a cell with logical structures like those in our little box above, with a series of steps, comparisons, and instructions. Yes, they can be very complex, but in essence, they are all logical instructions with inputs and outputs. Okay, here is THE example:

The basis of biology is what is commonly and inappropriately called “The Central Dogma of Biology” [It is not a dogma, it is an extensively verified fundamental principle of biology at the molecular level], which states, very briefly, that DNA is transcribed into RNA and RNA is translated into protein. Although there are cases in which it is possible to go from RNA to DNA. The important thing is that both DNA, RNA, and proteins store information and this principle outlines the possible ways in which information can be transformed from one to the other. The figure below illustrates this best.

This first process, the step from DNA to RNA, can also be modeled as an algorithm, but, in this case, each component [the physical object that “performs” the instruction] of the algorithm is a tangible molecular structure. I’ll explain. But first, take a look at this schematic:

Here you can see that it is fundamentally the same as the first box, with some slight modifications. Let’s break it down because I bet you it’s going to be worth your while. The algorithm receives an input DNA region and a transcription factor, that we abbreviate TF. TFs are proteins that function as regulators that can turn genes on and off to make sure that genes are only expressed at the right time, in the right cell, and in the right amounts. Only if both inputs are present can the operation proceed. If both DNA and TF are present, the instruction “Start Transcription” is triggered, which in reality is when an enzyme called RNA polymerase binds to the DNA and TF to start transcribing, or in other words, generating the complementary RNA to this DNA strand. This occurs in small specific regions of the DNA, in genes. However, this is a bit more complex in reality. The important thing is that for several years now, humans have been able to design their own biological instructions, just as we do in a computer. Everything is information: we call some living beings and others objects. Understanding this led to the creation of a new branch, synthetic biology.

Synthetic biology seeks, among other things, to build biological parts, systems, and machines from biological components for a certain application or function. Remember “engineering biology”? So the idea is to play with the two basic aspects: the input and the instructions of the “box” to generate the output we are interested in. Here the analogy with electronic circuits stands out. For your information, it is the integrated circuits that allow a computer to carry out instructions, to execute an algorithm. And just as in circuits we have thousands of parts and components: resistors, LED’s, motors, generators, coils, capacitors, transistors, etc., that we can connect together to achieve some kind of function [such as a radio, a speaker, a cell phone or a drone]; organisms, at the molecular level, also have thousands of biological components or BioBricks [more than 20,000 documented] [9]: promoters, enhancers, terminators, ribosome binding sites [RBS], etc. …and, puff! That’s how biological circuits came to be.

Synthetic biology is based on a hierarchical system:

-Part: pieces of DNA that form a functional unit, such as those mentioned above (promoter and so on).

-Device: a set of complementary parts with a defined function.

-System: a set of devices capable of executing highly complex tasks.

In this genetic MS Word, we can cut-and-paste DNA parts and even synthesize them in the laboratory. And all this is possible thanks to advances in research and genomic engineering that gave us the knowledge, tools, and methodologies needed to build and assemble these biomolecular parts. Years of research trying to understand the complex regulatory processes that are happening right now inside your cells, genes that are constantly turning on and off, signals that arrive and activate or inhibit different processes: hormone release, random mutations, emergence and elimination of cancer cells -believe it or not, our immune system is constantly attacking cancer cells-, viral infections, and more. And imagine what’s left to discover…

So you may be wondering: — Well, that’s a bit scary, but what’s the point? — And although I would normally respond by disagreeing with the utilitarian notion of knowledge and by telling you how fantastic it is for the very fact of being able to understand and manipulate life at that level, the truth is that it has many very interesting applications [2]. In fact, every year there is a competition called iGEM [International Genetically Engineered Machine Competition] in which groups of universities and schools develop biological machines to address problems that the world is facing. I will mention some of the applications below.

Bacteria that can detect and kill tumors? — You got it — . Bacteria have been reprogrammed to detect and colonize certain types of cancer cells [there are many types of cancers] [3] and to achieve this, a module is inserted in which the input is a specific receptor that is highly expressed in this type of cell, such as EGFR [1,8]. And once recognized, the output can be to release antitumor molecules. Or how about bacteria that detect landmines? — You got it too — . You can reprogram bacteria to detect certain residues in the soil that accumulate around explosives [5]. You spray these bacteria on the field and they will start to glow due to fluorescence when they detect the molecule TNT [2,4,6-trinitrotoluene] and its main degradation product DNT [2,3-dinitrotoluene], which are both present in the vast majority of landmines. But how? Well, the input is TNT or DNT, and the presence of these triggers the production of a fluorescent protein GFP (Green Fluorescent Protein) [output], and because we know that it is only produced if either of these two compounds is present, this would mean that there is a mine lurking around. Another widely used application is to modify bacteria or yeast (such as beer) to produce certain drugs or molecules, for example, yeast designed to produce artemisinin, a drug to treat malaria, which due to its high cost is difficult to access for the most vulnerable population [7]. These are just a few examples out of thousands, not to mention those to come in the future. What surprises will synthetic biology bring us tomorrow?

Computation is the ability of a system to manipulate information, whether it is a digital computer manipulating zeros and ones allowing me to write this article in Word or bacteria manipulating the “letters” of its DNA (A, T, G, C) to degrade lactose. Both systems are very similar and in both cases, we can define how they manipulate information, in other words, design. Synthetic biology defined a paradigm for manipulating DNA using an analogy with electrical circuits. Standardized parts, diagrams, and logic gates. The possibilities are endless. Perhaps biological computers in a few years?

Relatively new fields such as synthetic biology are a victory for interdisciplinarity. For in a world that seemed to be tending towards hyper-specificity, fields like this were only made possible by the integration and synergy of many areas of science: physics, chemistry, mathematics, and biology. Like Da Vinci who was a painter, engineer, physiologist, musician, and much more… someone of insatiable curiosity and feverishly inventive imagination. Perhaps we should aim at developing a comprehensive and broad knowledge, in various disciplines. Polymathy. A second Renaissance.


  1. Ahsan, Aarif, et al. “Efficacy of an EGFR-specific peptide against EGFR-dependent cancer cell lines and tumor xenografts.” Neoplasia 16.2 (2014): 105-W2.

2. Khalil, A. S., & Collins, J. J. (2010). Synthetic biology: applications come of age. Nature Reviews Genetics, 11(5), 367–379. doi:10.1038/nrg2775

3. Anderson, J. C., Clarke, E. J., Arkin, A. P., & Voigt, C. A. (2006). Environmentally controlled invasion of cancer cells by engineered bacteria. Journal of molecular biology, 355(4), 619–627.

4. Gujrati V, Kim S, Kim SH, Min JJ, Choy HE, Kim SC, Jon S (February 2014). “Bioengineered bacterial outer membrane vesicles as cell-specific drug-delivery vehicles for cancer therapy”. ACS Nano. 8 (2): 1525–37.

5. Belkin, S., Yagur-Kroll, S., Kabessa, Y., Korouma, V., Septon, T., Anati, Y., … & Agranat, A. J. (2017). Remote detection of buried landmines using a bacterial sensor. Nature biotechnology, 35(4), 308.

6. Hale, V., Keasling, J. D., Renninger, N., & Diagana, T. T. (2007). Microbially derived artemisinin: a biotechnology solution to the global problem of access to affordable antimalarial drugs. The American journal of tropical medicine and hygiene, 77(6_Suppl), 198–202.

7. Paddon, Christopher J., et al. “High-level semi-synthetic production of the potent antimalarial artemisinin.” Nature 496.7446 (2013): 528.

8. Sigismund, Sara, Daniele Avanzato, and Letizia Lanzetti. “Emerging functions of the EGFR in cancer.” Molecular oncology 12.1 (2018): 3–20.

9. Knight, Thomas. “Idempotent vector design for standard assembly of biobricks.” (2003).

10. Alon, Uri. An introduction to systems biology: design principles of biological circuits. Chapman and Hall/CRC, 2006

I am a science communicator, biologist, microbiologist, and musician. I like to learn, research and explain things.

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store