Drug interactions and the evolution of antibiotic resistance.

Large-scale, systems biology approaches now allow us to systematically map synergistic and antagonistic interactions between drugs. Consequently, drug antagonism is emerging as a powerful tool to study biological function and relatedness between cellular components as well as to uncover mechanisms of drug action. Furthermore, theoretical models and new experiments suggest that antagonistic interactions between antibiotics can counteract the evolution of drug resistance.

Accelerated evolution of resistance in multidrug environments.

The emergence of resistance during multidrug chemotherapy impedes the treatment of many human diseases, including malaria, TB, HIV, and cancer. Although certain combination therapies have long been known to be more effective in curing patients than single drugs, the impact of such treatments on the evolution of drug resistance is unclear. In particular, very little is known about how the evolution of resistance is affected by the nature of the interactions--synergy or antagonism--between drugs. Here we directly measure the effect of various inhibitory and subinhibitory drug combinations on the rate of adaptation. We develop an automated assay for monitoring the parallel evolution of hundreds of Escherichia coli populations in a two-dimensional grid of drug gradients over many generations. We find a correlation between synergy and the rate of adaptation, whereby evolution in more synergistic drug combinations, typically preferred in clinical settings, is faster than evolution in antagonistic combinations. We also find that resistance to some synergistic combinations evolves faster than resistance to individual drugs. The accelerated evolution may be due to a larger selective advantage for resistance mutations in synergistic treatments. We describe a simple geometric model in which mutations conferring resistance to one drug of a synergistic pair prevent not only the inhibitory effect of that drug but also its enhancing effect on the other drug. Future study of the profound impact that synergy and other drug-pair properties can have on the rate of adaptation may suggest new treatment strategies for combating the spread of antibiotic resistance.

Evolution exacerbates the paradox of the plankton.

Can biodiversity evolve and persist in a uniform environment? This question is at the heart of the plankton paradox: in the natural world we observe many species sharing few resources, whereas the principle of competitive exclusion would lead us to expect that only a few species could coexist in such circumstances. To bridge the gap between theory and observation, previous studies have shown that the maximum number of species that can stably coexist is equal to the number of essential resources and that even more species can coexist out of equilibrium. These studies were viewed as a significant step toward a resolution of the paradox. Evolutionary dynamics, however, have been studied in this context only in limited cases, and it is largely unknown how mutations impact ecologically stable multispecies states, and whether large species consortia can spontaneously evolve. In the present study we introduce evolution to the standard ecological model of competition for essential resources. Combining numeric and analytic approaches, we find that ecologically stable species communities are severely destabilized by long-term evolutionary dynamics. Moreover, the number of species in spontaneously evolved consortia is much lower than the number of available resources. Contrary to expectations based on studies of two resources, these limits on biodiversity are not results of the occasional emergence of superspecies, superior to all competitors; nor are they alleviated by the inclusion of tradeoffs in resource utilization. Rather, we show that it is an accelerated depletion of limiting resources, combined with the essentiality of resources to all species, that leads invariably to catastrophic extinctions.

Exposing the fitness contribution of duplicated genes.

Duplicate genes from the whole-genome duplication (WGD) in yeast are often dispensable--removing one copy has little or no phenotypic consequence. It is unknown, however, whether such dispensability reflects insignificance of the ancestral function or compensation from paralogs. Here, using precise competition-based measurements of the fitness cost of single and double deletions, we estimate the exposed fitness contribution of WGD duplicate genes in metabolism and bound the importance of their ancestral pre-duplication function. We find that the functional overlap between paralogs sufficiently explains the apparent dispensability of individual WGD genes. Furthermore, the lower bound on the fitness value of the ancestral function, which is estimated by the degree of synergistic epistasis, is at least as large as the average fitness cost of deleting single non-WGD genes. These results suggest that most metabolic functions encoded by WGD genes are important today and were also important at the time of duplication.

Analysis of genetic systems using experimental evolution and whole-genome sequencing.

The application of whole-genome sequencing to the study of microbial evolution promises to reveal the complex functional networks of mutations that underlie adaptation. A recent study of parallel evolution in populations of Escherichia coli shows how adaptation involves both functional changes to specific proteins as well as global changes in regulation.

An equivalence principle for the incorporation of favorable mutations in asexual populations.

Rapid evolution of asexual populations, such as that of cancer cells or of microorganisms developing drug resistance, can include the simultaneous spread of distinct beneficial mutations. We demonstrate that evolution in such cases is driven by the fitness effects and appearance times of only a small minority of favorable mutations. The complexity of the mutation-selection process is thereby greatly reduced, and much of the evolutionary dynamics can be encapsulated in two parameters-an effective selection coefficient and effective rate of beneficial mutations. We confirm this theoretical finding and estimate the effective parameters for evolving populations of fluorescently labeled Escherichia coli. The effective parameters constitute a simple description and provide a natural standard for comparing adaptation between species and across environments.