Antibiotic resistance has been a problem almost as long as antibacterial agents have been available. Antibiotic actually means using a chemical from one microbe that kills another microbe, although it is commonly used to mean antibacterial—a chemical that kills or inhibits bacteria. I will use the word antibiotic in order to be consistent with the DARPA article that follows.
One possible solution to antibiotic resistance is the use of nanotechnology in the form of nanomachines to chew up the bacteria in order to kill bacteria, as presumably the bacteria would not adapt to resist the technology. Katie Drummond writing in Wired reports on the efforts of Defense Advanced Research Projects Agency (DARPA) to accomplish this in a slightly different fashion. DARPA is trying to develop nanomachines that combat, not just bacteria, but all tiny pathogens including viruses and other potential biological weapons. Drummond writes: “Darpa would like to see nanoparticles loaded with ‘small interfering RNA (siRNA)’ — a class of molecules that can target and shut down specific genes. If siRNA could be reprogrammed ‘on-the-fly’ and applied to different pathogens, then the nanoparticles could be loaded up with the right siRNA molecules and sent directly to cells responsible for the infection.” (We discussed nanotechnology for bacterial resistance in our book: What Will We Do If We Don't Experiment On Animals? Medical Research for the Twenty-first Century.)
DARPA states that they actually accomplished this in primates infected with Ebola. While I do not have a lot of confidence that what happens in primates in general will also happen in humans, I do think that what happens in a specific species of monkey will probably also happen in that same species in another location. So, the technology appears to be worth pursuing at least for Ebola and primates. But this leads to another interesting point regarding the use of animals in research. The problem with using animal models to predict human response to drugs and disease is the fact that animals and humans are examples of evolved complex systems. Extrapolating from one complex system to another can be successfully accomplished but only if the perturbation to the system can be described in terms of simple systems. Two examples.
A frog falling out of a plane can be treated as a simple system and described by classic Newtonian physics—a point with a trajectory undergoing acceleration. Everything else about the frog can be ignored. It does not matter if the frog is susceptible to Ebola or HIV or if it is susceptible to Alzheimer’s disease. The same can be said about a human falling out of the same plane. Point, acceleration, trajectory and so forth. The problem arises when one wishes to use a frog to study Alzheimer’s disease in humans. At that level of examination or at that level of organization of complex systems, extrapolation breaks down. Complex systems vary because of initial condition like genetic make-up, respond differently to the same perturbations, and since the whole is greater than the sum of the parts, reductionism can only take us so far in understanding the system. All these things work against using animals to study disease and drug response.
On the other hand, a lot of neat stuff takes place at the level of organization where complex systems can be described in terms of simple systems. The problem DARPA is trying to remedy by using nanomachines, how to kill bacteria, is a good example. Antibiotics kill microbes like bacteria (or inhibit them) because an antibiotic is a chemical, discovered in nature or modified based on a chemical from nature, that kills bacteria. These chemicals are going to do the same thing regardless of what system they find themselves in. So if a chemical kills Staphylococcus aureus in a mouse it will probably kill Staphylococcus aureus in a human. This is not because animals are so similar to humans that they can predict human response to drugs, it is secondary to the fact that the chemical is acting at a level of organization that can be described as a simple system. I would expect the same to be true of nanomachines that kill bacteria mechanically. I am not sure the same will be true of nanomachines that use siRNAs.
Where animal models fail, even with antibiotics, is predicting the effects after exposure to the metabolism by the liver, which varies considerably among species, and predicting side effects. Both of these involve the complex system at a level that cannot be described as a simple system. This is why penicillin, for example, can kill guinea pigs but is largely safe for humans. Of course, the outcome of exposing a bacteria to an antibiotic can also be predicted by using a petri dish colonized by the bacteria and containing an antibiotic disc. An intact living system is not needed. I suspect the Ebola experiment or experiments similar to the Ebola study could have been accomplished in a similar way. (I have addressed the intact systems argument here.)
Nanotechnology is still in its infancy. The potential far outweighs what is actually being accomplished at this point. But the potential is huge. Nanotechnology could be used for drug delivery, treating cancer and heart disease, cleaning up cells, tissue repair, paralysis and stroke, and more. It is not hyperbole to say that it could be revolutionary. It will be interesting to see how DARPA’s concept develops.