Anti Evolution

29 October, 2008

Glowing Bacteria

Glowing Bacteria

Evolution is a cruel mistress. Since the 1940s millions of people have had their lives saved and immeasurably improved by the use of antibiotics. Bacterial infection weakens and kills us, and until antibiotics came along fresh air and rest were often the only prescription that doctors could give. All of us are covered and filled with bacteria, but these are mostly symbiotic in nature, we use them as much as we use our own cells to function. But those bacteria which harm us have to be dealt with, and with something more subtle than bleach. Sure we have chemicals that kill almost everything they touch, but unfortunately that means we can’t take them inside our bodies to help fight the bacteria harming us. To do that we use antibiotics, special chemicals that target the specific types of bacteria we want to get rid of.

Some antibiotics kill bacteria. They explode the cell wall and leave nothing functioning behind. Other antibiotics prevent bacteria from multiplying. The bacterium grows and grows but cannot divide and so is restricted in its ability to harm us. In each case we stop the bacteria but introduce a powerful natural selector. Any strain of bacteria that has resistance to the antibiotic will thrive, it will have no competition from its siblings who are dying or being prevented from reproducing. In the sixty or so years since antibiotics started to be used on a mass scale bacteria have evolved which are resistant to almost all of our drugs. With some, such as MRSA, anyone found infected with it is put onto the ‘drug of last choice’ – the only known antibiotic with some effectiveness against it. It is only a matter of time before we inadvertently breed resistance against this drug too.

So is it time to invest a lot of money in more of these antibiotics? Very few companies seem willing. With a development time of a decade, and hundreds of millions of euros spent on clinical trials, companies like to see a profit returned in the first ten years or so of a drug being put out onto market. Unfortunately most new antibiotics have a shelf life of only a few years before resistance crops up again. It’s unprofitable and fighting against an enemy that moves faster than we can. So what’s the solution?

One possible way forward has been revealed by luminescent bacteria. Several types of sea creatures hold glowing bacteria in translucent pouches which are used as lures, or signalling devices. But some types of these bacteria have an interesting property. Looking at a few of them under a microscope and you wouldn’t see any glow. But put enough of them together and they start to emit light. This is known as quorum sensing, the bacteria emit chemical signals and when they receive enough of them back they know it’s worth their while to perform some operation – in this case to shine.

Quorum sensing has since been found in other bacteria, but this time the bacteria wait until there is a large enough group before turning virulent. It makes sense for the bacteria not to alert a bodies defence mechanisms until it has a good chance of surviving, and those large numbers make it easier to survive. And so a possible solution to the problem of evolving bacteria presents itself. If drugs can be developed that stop the quorum sensing chemicals from being released, or from being detected, then the bacteria will happily grow without ever turning nasty. In this way, rather than the hammer of death leading to new strains, the original strains will still be around, but rendered harmless.

We are some way from seeing if this idea will work in practice, but unless some new ideas come to the table our short but highly successful victory over many kinds of disease will soon be coming to an end.

Modelling

1 October, 2008

It is often the case that the more we look into a subject the more nuanced it becomes. With a little knowledge we can paint things in broad brush strokes and make sweeping generalisations. A more in depth understanding leads to the inevitable exceptions to the rules. One danger that is often pointed out by communicators of science to the general public is that scientists very often want to be correct, even if that means muddying the waters and diluting a narrative. Which is to be preferred, absolute accuracy where no one follows you, or a rough approximation which doesn’t tell the whole story?

When learning sciences through school we often make use of models that are later shown to be inadequate. An example I have heard from psychology is that during first year in university the various theories of mind are presented, followed by the reasons why that very theory is wrong, leaving nothing at the end! I have also heard someone mention how when they got to college they were told that all their prior understanding of chemistry was wrong and now they were going to deal with how things really work.

For the second case at least I think the complaint is unjustified (although the lecturer does seem to have an odd way of putting things!). When we learn about the history of the development of our understanding of the atom we hear about the ‘plum pudding’ model, and then the ‘miniature solar system’ model leading on to models with fuzzy electron clouds. Each of these models is not reality, in fact we know they do not show the whole story, and each one is an improvement on the others. But for other models their use is entirely dependent on what questions we ask.

As an example, if we were interested in how many cars travelled through Dog River each week we could lay down a wire across the road which would increment a stored number each time a car passed over it. As long as someone doesn’t just keep driving over it and reversing again we can get a good indication of traffic on that street. But notice that in our model of traffic cars are represented just by a single number. There is no indication of what colour the car is, or how many people were in it, or what speed it was going at. Of course not, because it’s not needed for our purposes. If we were developing safety features and developing computer models to simulate car crashes you can be sure there would be a lot more detail about the car, but it would still not be a complete description of the reality of a car. They may not have the colour of the car coded in, and nor should they need to. It is likely that some version of Newton’s Laws will be in place though.

It is often said that Newton’s Laws are a nice first approximation, and indeed they are. For almost all physical force interactions that we deal with Newton’s Laws are fine and dandy. If you wanted you could add in Einstein’s modifications to those Laws but for most everyday calculations the difference to the final result would be minuscule. There’s no point in using too complicated a model for a simple job, since the more complicated the model the more chance of human error creeping in. Of course there are some cases where we have to use the more detailed model. GPS satellites for instance, have to take into account the time dilation effect of Relativity since they travel so fast around the Earth. If engineers did not take account of Relativity due to both the satellite’s speed and its distance from the gravity well of the Earth then the clocks would quickly be out of sync with those on the ground. Within a day the GPS network would not even be accurate to within one kilometre.

So in school those chemistry models, biology models, physics models and probably even the descriptions we get of how our government works are probably not the full story, but they give us an overall idea of how things work. And if they aren’t 100% accurate that’s no big deal since no model is 100% accurate, only accurate enough within acceptable errors. And those simple models are usually more right than they are wrong. If someone tells you the Earth is a sphere they’re technically not correct, but they are certainly more correct than someone who tells you that it’s a disc.

So while presenting information can be difficult without falling back on exceptions and footnotes, I think that we are better off with general descriptions of the way things work than no knowledge at all. We cannot possibly all be polymaths in this age of specialisation and so we rely on simple enough models to give us our understanding of the world, while always being aware that there is more going on than we can ever learn in one lifetime.