Technology

Evolutionary Optimization

Agricultural operations have long relied on the breeding—which is really just a targeted method of evolution—to improve the characteristics of domesticated plants and animals. Without a doubt, this has been wildly successful. To see this, one need only look at the tremendous variety of domesticated dog breeds that were derived from the gray wolf. Not surprisingly, industrial microbiologists have also long sought a robust method for improving yield and productivity of cellular factories that is akin to breeding and myriad methods have been developed over the years.

However, for much of human history the only method that existed for improving cellular factories was evolutionary optimization via continuous culture, although it is clear that early industrial microbiologists had no idea they were using the method. In evolutionary optimization via continuous culture, cellular factories are continuously grown under relevant industrial conditions, which means that cultures are periodically, grown, diluted and re-grown. This is repeated for thousands of generations and over time, such repetitive cultures facilitate the selection of naturally occurring genetic variants that have become adapted to and optimized for the culture conditions. In this way, microbes with new properties emerge and the key is to make sure that these new properties are compatible with the intended industrial application. Indeed, this is precisely how the brewer’s yeast, Saccharomyces cerevisiae, became so good at fermenting sugar to ethanol — through thousands of years of selection for more productive strains by brewers. Of course, early brewers had little knowledge of microbiology, let alone the process of evolution. More importantly, they lacked the technology to facilitate rapid and robust evolutionary optimization, which is why evolutionary optimization has been widely viewed as being slow and ineffective.

What is required for evolutionary optimization ? The key to evolving cellular factories is the ability to culture them continuously. While establishing a continuous culture of cells is simple, it is practically quite difficult to utilize these cultures to direct rapid and robust evolution. This is because successful evolutionary optimization requires that the method of continuous culture meet the following criteria :

• First, the culture must have a sufficiently large population size. More cells means more genetic diversity upon which to act.

• Second the cultures must be growing at their maximal growth rate to ensure more generations per unit time.

• Third, the ability to monitor population dynamics in real time is crucial in order to know when to increase selective pressure to accelerate evolution or decrease selective pressure as needed or prevent collapse of the population.

• Fourth, evolution acts on genetic diversity within a population. Each cell contains unique mutations that are spontaneously accumulated through natural errors in the machinery that replicates DNA. Thus, evolutionary optimization can be accelerated by increasing the accumulation of these mutations and the ideal method of continuous culture should incorporate a simple method of achieving this.

Evolutionary optimization via continuous culture is an old technology. And, considering that all of the tremendous diversity in nature arose through evolution, why isn’t this powerful technology more widely used ? Clearly, microbiologists and brewers have been unknowingly using evolutionary optimization to produce better cellular factories for millennia. Moreover, following the development of the theory of evolution by Darwin and Wallace in the mid-1800s, microbiologists quickly began applying to theory for the alteration of microbial properties. The earliest published example of experimental evolution via serial batch culture was published by Dallinger in 1878.

Since then, interest in the use of serial batch culture to experimentally evolve microorganisms grew. However, it was recognized early that serial batch culture as a means of maintaining a continuous culture could not meet the criteria needed for facilitating rapid and robust evolution. Two main problems plague this methodology. The first is that it is difficult and often impossible to monitor population dynamics in real time, meaning that selective pressure cannot be consistently applied when it is needed most nor can it be rapidly dialed back when too much pressure is applied. The second is that this methodology is ineffective for evolving cellular factories that don’t grow evenly in suspension or on ‘dirty’ real-world substrates that are mixtures of solubles and particulates.

Beginning around 1930, researchers began to develop the concept of true continuous culture as a means for replacing serial batch culture, culminating in the disputed invention of the chemostat by competing researchers. In continuous culture, exemplified by the chemostat, fresh substrate is continuously fed into a fermenter while spent medium saturated with cells is removed. The in-flow rate of fresh substrate is matched to the out-flow rate of saturated medium and both are matched to the growth rate of the cellular factory. In theory, continuous culture can maintain cultures with high population sizes for indefinite periods of time. Since the earliest publication of a chemostat-like device in 1930, many improvements and iterations of the concept have been developed. However, they all function on the same premise. Unfortunately, continuous culture never reached its potential and has failed to deliver effective microbes for industrial applications. As with serial batch culture, the reasons for this failure are twofold. First, the methodology is ineffective for evolving cellular factories that don’t grow evenly in suspension or on ‘dirty’ real-world substrates that are mixtures of solubles and particulates. Second, since the out-flow of a chemostat-like device is the road to extinction, cells rapidly acquire mutations that allow them to stick to the surfaces inside the chemostat. This problem, called wall growth or biofilm formation, reduces the ability of the user to monitor population dynamics in real time and biofilms can even shield cells from selective pressure. Unfortunately, this problem can be attenuated but never eliminated. The result is that, despite their potential, there are very few examples of the use of chemostats or related devices for improving cellular factories.

The inherent technical difficulties with maintaining serial batch cultures and chemostat-like devices result in the ability to apply weak selective pressure at best. And, with reduced selective pressure, evolution proceeds at a snail’s pace. Still, even with these limitations, evolutionary optimization via serial batch culture or chemostats remained the only tools in the strain developer tool kit until the advent of genetic engineering in the 1970s.

With genetic engineering, developers realized they could accelerate ‘evolution’ by artificially moving DNA around within an organism (cisgenesis) and from one organism to another (transgenesis). Each new iteration of genetic engineering, given trendy names like ‘synthetic biology’ and ‘metabolic engineering’, demonstrate the tremendous potential of genetic engineering. And the use of engineering largely eclipsed interest in evolutionary optimization until recently when strain developers began to realize that, despite the enormous potential, genetic engineering cannot address the robustness problem. In fact, genetic engineering is actually a frequent cause of robustness issues. This has led strain developers back to evolutionary optimization.

Evolugate has developed new continuous culture technology, called the Evolugator™ that circumvents the traditional problems associated with serial batch culture and chemostats. The Evolugator™ allows for real time monitoring of population dynamics, counter-selects against biofilm formation and can support the culturing of any type of cellular factory (from bacteria to mammalian cells) on any type of substrate. Moreover, the technology can incorporate methods for increasing the rate at which mutations are introduced into a population and is highly compatible with genetic engineering, both of which can greatly accelerate the rate of evolutionary optimization. The Evolugator™ represents the first real breakthrough in the use of continuous culture for evolutionary optimization in decades. Improving natural micro-organisms through experimental evolution is now practical and our technology has reopened a wide field of applications for green chemistry using cellular factories.