A couple of months ago, I attended a talk given by Robert Austin from the Princeton University Physics department. I debated with myself for quite a while about whether to report on this talk for two reasons: the results are largely unpublished, for reasons that will become clear; and, frankly, he has excellent technology and great biology, but it was combined with what seems to be a crappy understanding of evolution.

So, what I will do is present this in reverse order, because the technology should become an important tool to microbiologists, but Austin has poisoned the well so thoroughly that no one will touch it until it is invented independently of him. The part about evolution will be left until last, and it'll be short, and, hopefully, not too ranty.

The device that Austin has created is, on a micro-scale, a pattern of interconnected wells. Each well has enough volume to support a small population of bacteria, while the interconnections allow the population in each well to migrate out. From the outside edge, nutrients, antibiotics, and other things can be added to the wells. If the flow rate is chosen carefully, huge gradients in the amount of nutrient and antibiotics can be created.

So, imagine an experiment where a bacterial population is placed at the center of the well. This is a very food-poor area, so the bacteria immediately migrate to the outside, where there is the largest amount of food. Now let's add some antibiotic to the solution. We end up with three very steep gradients; food, antibiotic, and bacterial populations all have their highest concentrations on the outside.

But these wells are not static. Rather, the populations can move back and forth, while still being partially isolated from each other. This allows bacteria that can't tolerate the antibiotic to move inward and survive, albeit at a slower reproduction rate; bacteria that can tolerate a higher concentration can move outward to get more food. This creates a partial isolation that allows genetic diversity to increase, and different paths to antibiotic resistance end up evolving. These are then strengthened when different populations come into contact with each other and exchange genetic material.

The end result is that E. coli can end up resistant to ciprofloxacin in about ten hours.

The good and the bad

This is both good physics and, I think, good biology. The device highlights how gradients in the fitness landscape, combined with many partially isolated populations, can drive very fast evolution. Austin argues (correctly, I believe) that this is a good analog to fighting cancer in the body. The idea is that the human body consists of many small, partially interconnected populations of cells, which provides the ideal ground to evolve in response to selective pressure.

His point is that the better targeted a drug is, the more likely a tumor is to escape through evolution along the gradient that runs away from its target. I believe that this phenomena is actually observed by oncologists, so I don't think his conclusion is going to draw any ire or adoring fans to his ideas.

Where it all goes wrong, as far as I am concerned is his evolutionary model. He starts with the classic picture of a three dimensional fitness landscape, where there is a global maximum (picture all the bacteria sitting at the peak of a mountain). He argues that classical evolution will place the population with little diversity right near the top of the global maximum, and, when the landscape suddenly changes, the population does not have the genetic diversity to evolve fast enough to survive.

Fair enough, you might think—after all, extinctions are known to happen in the face of sudden changes to the environment. But Austin argues that, even in the face of a fixed landscape, a population retains a large amount of diversity to protect itself against such changes. Since he thinks evolution doesn't predict this, there must be some additional factor involved.

Arguing against the wrong model

He is right: his model of evolution is wrong. There is no such thing as a fixed fitness landscape. The fitness landscape is evolving on all time-scales. The seasonal flu is a great example of evolution on human time-scales: each year, a different flu strain arises as a result of the human population's increasing immunity to the previously dominant strain. On longer time-scales evolution is driven by things like climate change and continental drift.

The point is that most organisms retain genetic diversity because the population members all experience a slightly different fitness landscape, one that varies over time.

It also misses the point that evolution doesn't select for the best; instead, it selects for good enough. Thus, not every cat has, well, cat-like vision. As long as its vision is good enough for successful hunting—or, indeed, if the cat has bad eyes but a better sense of smell and hearing that compensates—then it may survive to reproduce.

The message is that simple evolutionary models are instructive but can be misleading.

He then argues that what his experiments show is that, when faced with stress, the rate of mutation goes up, allowing rapid evolution. This sort of enhanced mutation seems to have been observed when bacteria are placed under various forms of stress. Those results were somewhat controversial, but we're still within the realm of mainstream biology.

But Austin's model has only two parameters: the rate of mutation and the portion of those mutations that are beneficial. It seems to me that he has missed two very important points. When the fitness landscape changes, the portion of mutations that are beneficial must increase, simply because the organisms are no longer as fit as they were. The other important point is that many mutations that were mildly harmful—for instance, slowing reproduction rates—might become neutral.

A neutral mutation can get carried along and spread in a population, and some of these can later be combined with another mutation to produce a beneficial effect. Just allowing for more neutral and beneficial mutations while keeping the rate of mutation constant could well explain Austin's results.

In fact, it is probably important to consider the whole harmful/beneficial/neutral mix far more carefully, because something that might be mildly harmful in one aspect of an organism's life might provide a net benefit in another aspect, making it hard to determine if the mutation is harmful, beneficial, or neutral. Which, again, points to the importance of genetic diversity within classical evolutionary theory.

Annoying the biologists

If you look at Austin's sequencing results, they are all over the map. The genetic diversity in his population increases hugely once the antibiotic is introduced and resistance has evolved. It seems to me that the bacteria are finding multiple routes to drug resistance and carrying along many neutral mutations with them. But this doesn't necessarily involve a switch inside the bacteria that says "get lots of mutations now."

Austin argues that there is such a switch and blames technology aversion among biologists as the reason that he cannot publish his results. I think this is a slap in the face to a field that has embraced a huge amount of technology in a very short time (think genome sequencing and DNA chips). In fact, I think if Austin dropped his dodgy evolutionary theories—and the rather sullen whining about their lack of acceptance—and presented his technical data, he would find a good home for it.

I could say something trite about the hazards of letting physicists do biology. But the point is that Austin's experiments are ingenious, beautiful, and useful. Unfortunately, he has gotten totally out of his depth in interpreting them and would benefit by bringing an experienced evolutionary biologist (along with an experienced cell biologist) into his team to help interpret the results. Until he does so, he will remain on the margins.