Understanding Antibiotic Resistance
- Author(s): Goulart-Touma, Christiane
- Advisor(s): Barlow, Miriam
- et al.
The evolution of antibiotic resistance among bacteria threatens our continued ability to treat infectious diseases. The need for sustainable strategies to cure bacterial infections has never been greater. So far, all attempts to restore susceptibility after resistance arises have been unsuccessful, including restrictions on prescribing antibiotics (Andersson DI et al.2011) and antibiotic cycling (Andersson DI et al. 2005, Bergstrom CT et al. 2004). Part of the problem may be that those efforts have implemented different classes of unrelated antibiotics, and relied on removal of resistance by random loss of resistance genes from bacterial populations (drift). Moreover, antibiotic resistance results from genetic changes therefore it is a problem that needs to be investigated under the scope of evolution of the causal genetic determinants. TEM β-lactamases enzymatic action is the most prevalent antibiotic resistance mechanism in many clinical populations of bacteria. Nevertheless, the systematic study and analysis of evolutionary traits of TEM β-lactamases are still recent. Here, we show that alternating structurally similar antibiotics can restore susceptibility to antibiotics after resistance has evolved. We found that the resistance phenotypes conferred by variant alleles of the resistance gene encoding the TEM β-lactamase (blaTEM) varied greatly among 15 different β-lactam antibiotics. We captured those differences by characterizing complete adaptive landscapes for the resistance alleles blaTEM-50 and blaTEM-85, each of which differs from its ancestor blaTEM-1 by four mutations. We identified pathways through those landscapes where selection for increased resistance moved in a repeating cycle among a limited set of alleles as antibiotics were alternated. Furthermore, in this study, we investigate the selection process of each variant allele of the gene blaTEM-85 and blaTEM-50 by the 15 different antibiotics we employed in this investigation. Finally, we investigate fitness landscapes
as a central concept in analyzing evolution, in particular for drug resistance mutations in bacteria. We show that the fitness landscapes associated with antibiotic resistance are not compatible with any of the classical models; additive, uncorrelated and block fitness landscapes. It is frequently stated that virtually nothing is known about fitness landscapes in nature. We demonstrate that available records of antimicrobial drug mutations can reveal interesting properties of fitness landscapes in general. We apply the methods to analyze the TEM family of β-lactamases associated with antibiotic resistance. Laboratory results agree with our observations. We suggest that fitness landscapes analysis might provide the necessary tools for finding relations between recombination strategies.
Our results showed that susceptibility to antibiotics can be sustainably renewed by cycling structurally similar antibiotics. We anticipate that these results may provide a conceptual framework for managing antibiotic resistance. This approach may also guide sustainable cycling of the drugs used to treat malaria and HIV.
Our results also showed that among the three categories of β-lactam antibiotics employed in this study, cephalosporins, specifically cefepime have selected for different evolutionary trajectories on the evolution of blaTEM-1 to blaTEM-85. Also our results demonstrate that blaTEM-1 evolved from a specialist gene coding for β-lactamases capable of hydrolyzing only penicillins to blaTEM-50 a generalist gene coding for β-lactamases capable of hydrolyzing a large range of cephlosporins. We anticipate that the knowledge of how β-lactams impact each blaTEM variant allele can aid on the choice of antibiotics to be prescribed on cycling drugs regimes in order to keep antibiotic resistance evolution in a cyclic fashion.