If you enjoy studying evolution, there are many career fields you could consider going into
Evolution by natural selection is such a powerful concept that it’s being adopted far and wide by scientists and engineers working in chemical synthesis, biotechnology and computer modelling.
The key principles of evolutionary approaches, as in biological natural selection, are variation, selection and ‘inheritance’ – maintaining desired features. The main difference is that the desired endpoint is specified in advance – hence the use of the term ‘directed evolution’.
One application might be the design of an enzyme catalyst by ‘test-tube evolution’. Suppose a researcher has isolated an enzyme but wants it to behave slightly differently – perhaps to work with a different substrate or at a different temperature. Engineering these changes into the enzyme would be very difficult, as the required structure would probably not be known.
An alternative approach is to make many slight variations of the enzyme, essentially at random, and to see which variants best meet the new criteria. These can be pulled out (selected) and used to create a new set of variants. Over several generations, the enzyme will be gradually refined so that it has the desired qualities.
In 2013, US researchers used this approach to create an enzyme that could link together RNA subunits, starting with a simple protein scaffold. Over many cycles of selection and variation, a new structure ‘evolved’ that was far more effective at carrying out the enzymatic reaction.
A variation is used in drug development. Through the process of combinatorial chemistry – creating a ‘soup’ of chemical compounds by randomly combining a mix of slightly different components – huge ‘libraries’ of compounds can be produced. These can then be screened to see which bind to drug targets.
A nice example is the ‘phage display library’, which is used to generate antibodies that are very specific to a target molecule. The phage, a virus of bacteria, carries genes for an antibody. When it infects a bacterium, the antibody protein is made and sits on the outside of the host (it is ‘displayed’).
The genetic code of the phage can easily be altered, so a huge range of phage can be produced, each making a slightly different antibody. These can be screened to see which bind most tightly to the target molecule. Selected phage can be mutated again, and the selection cycle repeated, so binding strength increases with each generation.
A very similar principle can be used in computing. Code can be written to achieve some purpose, then random modifications introduced. If some changes make the algorithm work better, they are selected for. Again, using multiple cycles of mutation and selection leads to optimum solutions.
These kinds of approaches are used in a wide variety of applications: they are used in research but also used, for example, to work out the best way of laying out a factory or to create complex timetables.
The key point of all these applications is that the end point, or solution, is unknown and would be difficult to predict on the basis of known principles. But the combination of variation and selection, in repeated cycles, can lead to the optimum solution.
This is exactly the same process as biological evolution. The eye, for example, is a solution to detecting the outside world – a huge competitive advantage. The eye probably began as a few light-sensitive cells. The endless cycles of natural selection then refined them into the range of eye structures seen today.
Solutions may look tailor made, just as the antibody produced by the phage display process is a perfect fit for its target molecule. But the antibody was never ‘designed’ to fit its target.
Evolution is not by itself a common degree course in the UK – only a handful of UK universities offer courses in which it is the major focus. Rather, evolution is usually taught as part of more general courses in the biological sciences and areas such as environmental science, anthropology and geology.
More specialised study in evolution can begin with Master’s study. PhD research projects may also focus on specific questions in evolutionary biology. These can be a stepping-stone to an academic career in research on evolution. Typically, evolution research focuses on the mechanisms of evolutionary change in animal and plant populations, and hence has a heavy emphasis on ecology, genetics and molecular biology, as well as computer modelling.
A background in evolution opens up other opportunities outside scientific research. There are strong links between evolution and the environment and ecology, providing a foundation for conservation-related work or careers in environmental management.
Expertise in taxonomy and systematics is also a good basis for work in museums and collections.
Evolution is also a highly mathematical subject and is heavily dependent on computer modelling. Mathematical and programming skills are in great demand from a wide range of employers, opening up opportunities in multiple fields (including the IT sector and the financial services industry).