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Accelerated evolution of resistance in multidrug environments.

ABSTRACT: 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.

SUBMITTER: Hegreness M

PROVIDER: S-EPMC2544564 | biostudies-literature | 2008 Sep

REPOSITORIES: biostudies-literature

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Accelerated evolution of resistance in multidrug environments.

Hegreness Matthew M Shoresh Noam N Damian Doris D Hartl Daniel D Kishony Roy R

Proceedings of the National Academy of Sciences of the United States of America 20080908 37

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. ...[more]

PMID: 18779569

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Project description:Different species exposed to a common stress may adapt by mutations in shared pathways or in unique systems, depending on how past environments have molded their genomes. Understanding how diverse bacterial pathogens evolve in response to an antimicrobial treatment is a pressing example of this problem, where discovery of molecular parallelism could lead to clinically useful predictions. Evolution experiments with pathogens in environments containing antibiotics, combined with periodic whole-population genome sequencing, can be used to identify many contending routes to antimicrobial resistance. We separately propagated two clinically relevant Gram-negative pathogens, Pseudomonas aeruginosa and Acinetobacter baumannii, in increasing concentrations of tobramycin in two different environments each: planktonic and biofilm. Independently of the pathogen, the populations adapted to tobramycin selection by parallel evolution of mutations in fusA1, encoding elongation factor G, and ptsP, encoding phosphoenolpyruvate phosphotransferase. As neither gene is a direct target of this aminoglycoside, mutations to either are unexpected and underreported causes of resistance. Additionally, both species acquired antibiotic resistance-associated mutations that were more prevalent in the biofilm lifestyle than in the planktonic lifestyle; these mutations were in electron transport chain components in A. baumannii and lipopolysaccharide biosynthesis enzymes in P. aeruginosa populations. Using existing databases, we discovered site-specific parallelism of fusA1 mutations that extends across bacterial phyla and clinical isolates. This study suggests that strong selective pressures, such as antibiotic treatment, may result in high levels of predictability in molecular targets of evolution, despite differences between organisms' genetic backgrounds and environments.IMPORTANCE The rise of antimicrobial resistance is a leading medical threat, motivating efforts to forecast both its evolutionary dynamics and its genetic causes. Aminoglycosides are a major class of antibiotics that disrupt translation, but resistance may occur by a number of mechanisms. Here, we show the repeated evolution of resistance to the aminoglycoside tobramycin in both P. aeruginosa and A. baumannii via mutations in fusA1, encoding elongation factor G, and ptsP, encoding the nitrogen-specific phosphotransferase system. Laboratory evolution and whole-population genome sequencing were used to identify these targets, but mutations at identical amino acid positions were also found in published genomes of diverse bacterial species and clinical isolates. We also identified other resistance mechanisms associated with growth in biofilms that likely interfere with drug binding or uptake. Characterizing the evolution of multiple species in the presence of antibiotics can identify new, repeatable causes of resistance that may be predicted and counteracted by alternative treatment.

Project description:BackgroundMembers of the small multidrug resistance (SMR) protein family are integral membrane proteins characterized by four alpha-helical transmembrane strands that confer resistance to a broad range of antiseptics and lipophilic quaternary ammonium compounds (QAC) in bacteria. Due to their short length and broad substrate profile, SMR proteins are suggested to be the progenitors for larger alpha-helical transporters such as the major facilitator superfamily (MFS) and drug/metabolite transporter (DMT) superfamily. To explore their evolutionary association with larger multidrug transporters, an extensive bioinformatics analysis of SMR sequences (> 300 Bacteria taxa) was performed to expand upon previous evolutionary studies of the SMR protein family and its origins.ResultsA thorough annotation of unidentified/putative SMR sequences was performed placing sequences into each of the three SMR protein subclass designations, namely small multidrug proteins (SMP), suppressor of groEL mutations (SUG), and paired small multidrug resistance (PSMR) using protein alignments and phylogenetic analysis. Examination of SMR subclass distribution within Bacteria and Archaea taxa identified specific Bacterial classes that uniquely encode for particular SMR subclass members. The extent of selective pressure acting upon each SMR subclass was determined by calculating the rate of synonymous to non-synonymous nucleotide substitutions using Syn-SCAN analysis. SUG and SMP subclasses are maintained under moderate selection pressure in comparison to integron and plasmid encoded SMR homologues. Conversely, PSMR sequences are maintained under lower levels of selection pressure, where one of the two PSMR pairs diverges in sequence more rapidly than the other. SMR genomic loci surveys identified potential SMR efflux substrates based on its gene association to putative operons that encode for genes regulating amino acid biogenesis and QAC-like metabolites. SMR subclass protein transmembrane domain alignments to Bacterial/Archaeal transporters (BAT), DMT, and MFS sequences supports SMR participation in multidrug transport evolution by identifying common TM domains.ConclusionBased on this study, PSMR sequences originated recently within both SUG and SMP clades through gene duplication events and it appears that SMR members may be evolving towards specific metabolite transport.

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Accelerated evolution of resistance in multidrug environments.

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Accelerated evolution of resistance in multidrug environments.

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