Medicine and Evolution, Part 9: What was that about evolution having “nothing to do” with antimicrobial resistance?

In my last couple of posts on the risks and benefits of ever more sensitive screening tests for various cancers, and in particular breast cancer, I marveled at a a bit of serendipity that had pointed me to a particular old article a mere few days before multiple new papers about breast cancer screening with mammography and MRI were released. It turns out that that’s not the only serendipity that’s been going on lately, as far as blogging goes. For example, there’s been Dr. Michael Egnor, the creationist professor of neurosurgery who’s become the Discovery Institute’s seemingly favorite “authority” on evolution. In the brief time since he’s entered the blogosphere, he’s made a name for himself spouting some amazingly ignorant and easily debunked fallacies about evolution. Perhaps the most jaw-droppingly dumb fallacy that he’s repeated time and time again is that evolution contributes nothing to our understanding of how microbes develop resistance to antibiotics.

I really, really hope that he sees the latest issue of Nature. He’s not going to like it at all, specifically the article by Chait et al. entitled Antibiotic interactions that select against resistance, whose abstract reads:

Multidrug combinations are increasingly important in combating the spread of antibiotic-resistance in bacterial pathogens. On a broader scale, such combinations are also important in understanding microbial ecology and evolution. Although the effects of multidrug combinations on bacterial growth have been studied extensively, relatively little is known about their impact on the differential selection between sensitive and resistant bacterial populations. Normally, the presence of a drug confers an advantage on its resistant mutants in competition with the sensitive wild-type population. Here we show, by using a direct competition assay between doxycycline-resistant and doxycycline-sensitive Escherichia coli, that this differential selection can be inverted in a hyper-antagonistic class of drug combinations. Used in such a combination, a drug can render the combined treatment selective against the drug’s own resistance allele. Further, this inversion of selection seems largely insensitive to the underlying resistance mechanism and occurs, at sublethal concentrations, while maintaining inhibition of the wild type. These seemingly paradoxical results can be rationalized in terms of a simple geometric argument. Our findings demonstrate a previously unappreciated feature of the fitness landscape for the evolution of resistance and point to a trade-off between the effect of drug interactions on absolute potency and the relative competitive selection that they impose on emerging resistant populations.

“Fitness landscape”? They sure don’t mean the lithe women working out at the health club. “Selection”? They ain’t talking about about the variety of coffees at Starbucks. No, they’re talking about evolution and a neat little trick by which evolutionary concepts might be used to overcome antibiotic resistance. I can’t say that I’ve entirely wrapped my brain around it yet, but no matter how you slice it it’s a clever set of experiments.

Before I can try to explain this paper (and it’s actually kind of hard to explain, leading me to hope that I don’t butcher it), a few terms need to be defined. the key trick in this paper is that the investigators looked at the effects of different drug interactions on selection of bacteria. The concepts of drug interaction used here are very familiar to me as a cancer surgeon, because they are often used in reference to combining cancer chemotherapies. In this case, however, they’re simply using them to describe interactions between antibiotics. In general, whenever two drugs are combined, they can have three different interactions. Most commonly (in cancer chemotherapeutics, at least), their effects will be additive, which means that the effects of each individual drug are added together, and that’s what the effect of the combination is. What we as physicians are hoping for is the second form of interaction, which is a synergistic interaction, defined as when the effects of the two drugs are greater than would be expected from adding the effects of each individual drug. in contrast, what we as physicians hope to avoid is the third form of interaction, which, as you might expect, occurs when the two drugs together produce an effect that is less than would be expected from adding the effects of the individual drugs. This last form of interaction is known as an antagonistic interaction. Of this latter form, the worst case is when the combination of the two drugs is actually worse than either of the single drugs themselves, an interaction known as hyper-antagonistic, or suppressive. Working out whether a drug combination is synergistic, additive, or antagonistic requires a detailed set of assays testing the two drugs at numerous different concentrations and a specific mathematical calculation, although it is often easier to look at the shape of a special curves called an isobole, which have characteristic shapes for each interaction.

What the authors did was to look at a model of the competition between two E. coli strains. One strain was wild type, and thus sensitive to tetracycline. The other strain contained a piece of DNA known as the Tn10 transposon, which encodes a protein that pumps tetracycline out of the cell and thus results in resistance to tetracycline. In this case, the resistant strain required about 100-fold higher concentrations of tetracycline to be killed. Normally, in the additive or synergistic situation, resistance to one of the drugs in the two-drug combination leads to an advantage in the two-drug combination as well. However, the researchers hypothesized that in the case of hyperantagonistic, or suppressive, interactions, the opposite might occur. The concept behind this hypothesis is that, although resistance would indeed diminish the burden imposed by one of the drugs, it might also in doing so remove the suppression, resulting in the combined treatment being more effective against the resistant strain than against the wild type. I have to admit here that I’m not sure why one would hypothesize that this might be the case and the authors didn’t really explain very well beforehand why they thought their hypothesis might be true. However, it turns out that their hypothesis might well have merit, as their subsequent experiments demonstrate.

What the investigators did was to test the effect of two antibiotic pairs, tetracycline plus either ciprofloxacin or erythromycin. These combinations were chosen because tetracycline and erythromycin demonstrate synergistic effects against this strain of E. coli, while tetracycline and ciprofloxacin are hyperantagonistic, or suppressive. As expected, for the assays looking at cell survival, resistance to doxycline merely rescaled the the doxycycline scale on the curve upward by about 100-fold. However, when a competition assay was done, to see whether the resistant or the sensitive strains were selected for, the results were very different. Basically, the end point of such a competition assay is the ratio of sensitive to resistant bacteria after a fixed time of selection under the two drug combination at different doses. Not surprisingly, under the synergistic combination, there were no dosage combinations where the sensitive strain ended up being selected for. The resistant strain always came out on top. In contrast, for the suppressive combination (tetracycline plus ciprofloxacin), there was a region on the curve (i.e., a range of dose combinations for the two drugs) in which the sensitive bacterial ended up being selected for, as evidenced by a much larger ratio of the sensitive E. coli to the resistant E. coli remaining at the end of the experiment. This clever strategy ended up selecting against the resistance gene in the resistant strain, leading the resistant strain to be killed more effectively than even the sensitive strain. The authors conclude:

Our data show that in suppressing drug combinations, a drug can be used to exert competitive selection against its own resistance allele. In contrast, synergistic interactions, while increasing absolute potency against both sensitive and resistant strains, also increase relative selection in favour of resistance. These findings point to an inherent tradeoff, where antagonistic combinations, which require a higher dosage and have therefore typically been shunned in clinical therapy, may have the benefit of reducing and even inverting selection for resistance. Although the molecular mechanisms underlying drug interactions may be complex, suppression between antibiotics is not uncommon. Our simple geometrical approximation anticipates a region of competitive selection against resistance in such suppressive drug combinations when the targeted resistance mechanism works specifically (uniaxially) on one of the drugs. Indeed, for doxycycline-ciprofloxacin, a region of drug concentrations permitting the growth of doxycycline- sensitive but not resistant strains appears for three very distinct mechanisms of resistance to tetracyclines…It would therefore be of considerable interest to employ new multidrug screens to search for reciprocally suppressing drug combinations in which each of the drugs suppresses the effect of the other. Such drug combinations may block the two single-step mutational paths to complete resistance by imposing selection against resistance to each of the drugs. We emphasize that our work is limited to sublethal drug concentrations, in a controlled environment in vitro and that any possible therapeutic implications from these findings are beyond its scope. However, we do hope that these findings may suggest avenues of research into new treatment strategies employing antimicrobial combinations with improved selection against resistance.

Indeed, translating this research into drug combinations that might be clinically useful to combat resistant bacteria in real infections in real patients will require a lot of work. It will be difficult, and it might not be translatable to humans, although there is no inherent reason why it shouldn’t be. One problem that I could foresee is that it would be a tricky business to intentionally use antagonistic drug combinations. After all, the sensitive bacteria being treated are still virulent and need to be dealt with., and working out effective dose combinations of two different drugs to produce concentrations in the blood that result in effective selection against the resistant strain will almost certainly be difficult. Even so, the implications of this work could go beyond just antibiotics. It could apply to combinations of chemotherapeutic agents for cancer therapy. Either way, without an understanding of evolution, it would have been impossible even to consider this hypothesis. What was that again that Dr. Egnor said about evolution supposedly being of “no use” in understanding antibiotic resistance?

I’d love to see what Dr. Egnor would say about this study. No doubt he’d lamely try to call it a “tautology” again. (He’s rather one-note that way.) Even so, it’d be fun to see him try.