Here we present an experimental method to test the role of multicopy plasmids in the evolution of antibiotic resistance.
Multicopy plasmids are extremely abundant in prokaryotes but their role in bacterial evolution remains poorly understood. We recently showed that the increase in gene copy number per cell provided by multicopy plasmids could accelerate the evolution of plasmid-encoded genes. In this work, we present an experimental system to test the ability of multicopy plasmids to promote gene evolution. Using simple molecular biology methods, we constructed a model system where an antibiotic resistance gene can be inserted into Escherichia coli MG1655, either in the chromosome or on a multicopy plasmid. We use an experimental evolution approach to propagate the different strains under increasing concentrations of antibiotics and we measure survival of bacterial populations over time. The choice of the antibiotic molecule and the resistance gene is so that the gene can only confer resistance through the acquisition of mutations. This "evolutionary rescue" approach provides a simple method to test the potential of multicopy plasmids to promote the acquisition of antibiotic resistance. In the next step of the experimental system, the molecular bases of antibiotic resistance are characterized. To identify mutations responsible for the acquisition of antibiotic resistance we use deep DNA sequencing of samples obtained from whole populations and clones. Finally, to confirm the role of the mutations in the gene under study, we reconstruct them in the parental background and test the resistance phenotype of the resulting strains.
Antibiotic resistance in bacteria is a major health problem1. At a fundamental level, the spread of antibiotic resistance in pathogenic bacteria is a simple example of evolution by natural selection2,3. Put simply, the use of antibiotics generates selection for resistant strains. A key problem in evolutionary biology, therefore, is to understand the factors that influence the ability of bacterial populations to evolve resistance to antibiotics. Selection experiments have emerged as a very powerful tool to investigate the evolutionary biology of bacteria, and this field has produced incredible insights into a wide range of evolutionary problems4,5,6. In experimental evolution, bacterial populations initiated from a single parental strain are serially passaged under defined and tightly controlled conditions. Some of the mutations that occur during the growth of these cultures increase bacterial fitness, and these spread through the cultures by natural selection. During the experiment, samples of the populations are periodically cryogenically preserved to create a non-evolving frozen fossil record. A wide number of approaches can be used to characterize evolving bacterial populations, but the two most common methods are fitness assays, that measure the ability of evolved bacteria to compete against their distant ancestors, and whole genome sequencing, that is used to identify the genetic changes that drive adaptation. Following pioneering work by Richard Lenski and colleagues7,8, the standard approach in experimental evolution has been to challenge a relatively small number of replicate populations (typically <10) with adapting to a new environmental challenge, such as new carbon sources, temperature, or a predatory phage.
Infections caused by antibiotic resistant bacteria become a big problem when resistance is high enough that it is not possible to increase antibiotic concentrations to lethal levels in patient tissues. Clinicians are therefore interested in what allows bacteria to evolve resistance to high doses of antibiotic that are above this threshold antibiotic concentration, the clinical breakpoint. How to study this experimentally? If a small number of bacterial populations are challenged with a high dose of antibiotic, as in a Lenski-style experiment, then the most likely outcome is that the antibiotic will drive all of the populations to extinction. At the same time, if the dose of antibiotic that is used is low, below the minimal inhibitory concentration (MIC) of the parental strain, then it is unlikely that the bacterial populations will evolve clinically relevant levels of resistance, especially if resistance carries a large cost. One compromise between these two scenarios is to use an "evolutionary rescue" experiment9,10,11. In this approach, a very large number of cultures (typically >40) is challenged with doses of antibiotics that increase over time, typically by doubling antibiotic concentration every day12. The hallmark of this experiment is that any population that does not evolve increased resistance will be driven to extinction. Most populations that are challenged in this way will be driven extinct, but a small minority will persist by evolving high levels of resistance. In this paper, we show how this experimental design can be used to investigate multicopy plasmid contribution to the evolution of resistance.
Bacteria acquire resistance to antibiotics through two principal routes, chromosomal mutations, and acquisition of mobile genetic elements, mostly plasmids13. Plasmids play a key role in the evolution of antibiotic resistance because they are able to transfer resistance genes between bacteria by conjugation14,15. Plasmids can be divided into two groups according to their size and biology: "small", with high copy number per bacterial cell and "large", with low copy number16,17. The role of large plasmids in the evolution of antibiotic resistance has been extensively documented because they include conjugative plasmids, which are key drivers of the dissemination of resistance and multi resistance among bacteria15. Small multicopy plasmids are also extremely common in bacteria17,18, and they often code for antibiotic resistance genes19. However, the role of small multicopy plasmids in the evolution of antibiotic resistance has been studied to a lesser extent.
In a recent work, we proposed that multicopy plasmids could accelerate the evolution of the genes they carry by increasing gene mutation rates due to the higher gene copy number per cell12. Using an experimental model with E. coli strain MG1655 and the β-lactamase gene blaTEM-1 it was shown that multicopy plasmids accelerated the rate of appearance of TEM-1 mutations conferring resistance to the third-generation cephalosporin ceftazidime. These results indicated that multicopy plasmids might play an important role in the evolution of antibiotic resistance.
Here, we present a detailed description of the method we have developed to investigate the multicopy plasmid-mediated evolution of antibiotic resistance. This method has three different steps: first, insertion of the gene under study either in a multicopy plasmid or the chromosome of the host bacteria. Second, use of experimental evolution (evolutionary rescue) to assess the potential of the different strains to adapt to the selective pressure. And third, determining the molecular basis underlying plasmid-mediated evolution using DNA sequencing and reconstructing the suspected mutations individually in the parental genotype.
Finally, although the protocol described here was designed to investigate the evolution of antibiotic resistance, one can argue that this method could be generally useful to analyze the evolution of innovations acquired by mutations in any multicopy plasmid-encoded gene.
1. Construction of the Experimental System Encoding Antibiotic Resistance Gene
Note: Here E. coli MG1655 was used as the recipient strain of the plasmid- or chromosome-encoded antibiotic resistance gene. The antibiotic resistance gene is encoded in the chromosome or a multicopy plasmid in an otherwise isogenic strain (Figure 1).
2. Evolutionary Rescue Approach to Experimentally Evolve Antibiotic Resistance (Figure 1)
3. Molecular Basis of the Evolution of Antibiotic Resistance (Figure 1)
In our previous work, the evolution the β-lactamase gene blaTEM-1 towards conferring resistance to the third generation cephalosporin ceftazidime12 was investigated. This gene was selected because, although TEM-1 does not confer resistance to ceftazidime, mutations in blaTEM-1 can expand the range of activity of TEM-1 to hydrolyze cephalosporins such as ceftazidime29. Mutations in antibiotic resistance enzymes such as β-lactamases or aminoglycoside modifying enzymes leading to changes in their range of activity are common29,30. This experimental system is ideal to explore the evolution of this type of enzymes. For a detailed report of a successful experiment following this protocol please see San Millan et al. 201612.
Here, an example of the possible outcomes of this experimental system is presented to illustrate the protocol (note that the data used for this example is not real). To investigate the potential role of multicopy plasmids in the evolution of the antibiotic resistance gene under study in this example (let's call it resA), we develop the experimental system following section 1 of the protocol described above. The experiments produce three strains: MG1655, MG1655::resA and MG1655/pRESA. The evolution of resistance to two different ß-lactam antibiotics (ceftazidime and meropenem) was tested following the steps described in section 2 of the protocol. Figure 2 shows the survival curves of the populations under study. In this example, there is a significant increase in the survival of populations belonging to MG1655/pRESA evolving in ceftazidime compared to those from MG1655 or MG1655::resA (log-rank test, P< 0.05). On the other hand, in the case of meropenem, there are no significant differences in the survival of the populations belonging to the different strains (log-rank test, P> 0.05). Therefore, these results suggest that the presence of gene resA in a multicopy plasmid potentiates the evolution of resistance to ceftazidime but not to meropenem.
In the final step of the experiment, the molecular basis of antibiotic resistance is investigated, as explained in section 3 of the protocol. First, DNA sequencing will reveal the mutations in resA that could be responsible for the resistance phenotype. And second, reconstruction of resA mutations in the parental MG1655 (both in the chromosome and plasmid) will confirm or discard their role on the antibiotic resistance phenotype.
Figure 1. Schematic representation of the different phases of the protocol. From left to right: (i) Construction of the experimental system: MG1655, MG1655::resA and MG1655/pRESA. Bacterial chromosome is represented in brown, the plasmid in blue and the resA gene in red. (ii) Evolutionary rescue approach to experimentally evolve antibiotic resistance: several populations of the different strains are propagated under increasing concentration of the antibiotic. (iii) Analysis of the molecular basis of antibiotic resistance: sequencing of DNA samples from the evolved populations and clones, detection of the antibiotic resistance mutations and reconstruction of these mutations in the parental strain. Please click here to view a larger version of this figure.
Figure 2. Survival curves with increasing concentrations of antibiotics. Representation of the number of viable populations belonging to strains MG1655, MG1655::resA, and MG1655/pRESA over time. 48 populations of each strain were propagated under increasing concentrations of antibiotics ceftazidime and meropenem, starting with 1/8 of the MIC on day 1 and doubling the antibiotic concentration every day. The red dashed vertical line represents the MIC of the antibiotics under study. Note that in the case of ceftazidime there are significant differences in the survival of the populations belonging to different strains over time (log-rank test, P< 0.05). Crucially, only populations carrying the plasmid are able to survive up to high-level concentrations of antibiotic. On the other hand, in the case of meropenem, there are no significant differences in the survival of the different populations over time (log-rank test, P> 0.05). Please click here to view a larger version of this figure.
We present a new protocol combining molecular biology, experimental evolution and deep DNA sequencing designed to investigate the role of multicopy plasmids in the evolution of antibiotic resistance in bacteria. Although this protocol combines techniques from different fields, all the methods required to develop it are simple, and can be performed in a regular microbiology laboratory. The most critical steps in the protocol probably are the construction of the model system strains and the reconstruction of the mutations observed after the experimental evolution (which are performed using the exact same method). However, the isothermal assembly system21, simplifies significantly this protocol so any user with an intermediate level of experience in molecular biology can implement it.
Another critical step of the protocol is the experimental evolution under increasing concentrations of antibiotics. As an example, this protocol starts the experiment with ¼-1/8 of the MIC of the strains and then doubling the concentration of antibiotic every day. However, a lower rate of antibiotic change could increase the chance of evolutionary rescue from extinction26. Therefore, the rate of change of antibiotic concentrations is one of the parameters that can be modified to promote the evolution of antibiotic resistance.
DNA sequencing and analysis are also key aspects of the experimental design. Results are more straightforward when sequencing is performed on DNA samples both from whole populations and from individual clones, at different time points in the experiment. Sequencing results from populations will reveal general differences in the mutation profiles among treatments, as well as selective sweeps of beneficial mutations over time and potential events of clonal interference. When analyzing sequences from populations, it is better to filter mutations that never surpassed 10% frequency in any population. Sequences from individual clones help confirm the results obtained from populations and, most importantly, reveal the specific combinations between the different mutations observed at the population level. These specific associations may help uncover epistatic interactions between mutations, which play a critical role in bacterial adaptation31.
Using this method, we have recently shown that multicopy plasmids accelerate the evolution of antibiotic resistance, first by increasing the rate of appearance of novel mutations and then by amplifying the effect of mutations due to increased gene dosage12. Therefore, we developed the method as a tool to investigate the evolution of antibiotic resistance, but it may have a much broader range of applications. Namely, this system could be used to investigate the ability of any bacterial gene to evolve towards a new or improved function in a more general way. This system could be used, for example, to test the ability of a metabolic enzyme/pathway to use new carbon substrates32. Also, it could be used instead of hypermutators (bacteria with a defect in the cellular systems involved in DNA mismatch repair) to investigate adaptive gene evolution in bacteria, avoiding the mutational bias introduced by hypermutators.
The authors have nothing to disclose.
This work was supported by the Instituto de Salud Carlos III (Plan Estatal de I+D+i 2013-2016): grants CP15-00012, PI16-00860, and CIBER (CB06/02/0053), co-financed by the European Development Regional Fund ''A way to achieve Europe'' (ERDF). JAE is supported by the Atracción de talento program of the government of the region of Madrid (2016-T1/BIO-1105) and the I+D Excelencia of the Spanish Ministerio de Economía, Industria y Competitividad (BIO2017-85056-P). ASM is supported by a Miguel Servet Fellowship from the Instituto de Salud Carlos III (MS15/00012) co-financed by The European Social Fund "Investing in your future" (ESF) and ERDF.
Thermocycler | BioRad | C1000 | |
Electroporator | BiorRad | 1652660 | |
Electroporation cuvettes | Sigma-Aldrich | Z706078 | |
NanoDrop 2000/2000c | Thermo Fisher Scientific | ND-2000 | Determine DNA quality measuring the ratios of absorbance 260nm/280nm and 260nm/230nm |
Incubator | Memmert | UF1060 | |
Incubator (shaker) | Cole-Parmer Ltd | SI500 | |
Electrophoresis power supply | BioRad | 1645070 | Agarose gel electrophoresis |
Electrophoresis chamber | BioRad | 1704405 | Agarose gel electrophoresis |
Pippettes | Biohit | 725020, 725050, 725060, 725070 | |
Multi-channel pippetes | Biohit | 728220, 728230, 728240 |
|
Plate reader Synergy HTX | BioTek | BTS1LF | |
Inoculating loops | Sigma-Aldrich | I8388 | |
96-well plates | Falcon | 351172 | |
LB | BD Difco | DF0446-17-3 | |
LB agar | Fisher scientific | BP1425-500 | |
Phusion Polymerase | Thermo Fisher Scientific | F533S | |
Gibson Assembly | New England Biolabs | E2611S | |
Resctriction enzymes | Fermentas FastDigest | ||
Antibiotics | Sigma-Aldrich | ||
QIAprep Spin Miniprep Kit | Qiagen | 27104 | Plasmid extraction kit |
Wizard Genomic DNA Purification Kit | Promega | A1120 | gDNA extraction kit |
DNeasy Blood & Tissue Kits | Qiagen | 69506 | gDNA extraction kit |
Electroporation cuvettes | Sigma-Aldrich | Z706078 | |
Petri dishes | Sigma-Aldrich | D9054 | |
Cryotubes | ClearLine | 390701 | |
96-well plates (-80ºC storage) | Thermo Fisher Scientific | 249945 | |
QuantiFluor dsDNA System | Promega | E2670 | Quantification of DNA concentartion |
Agarose | BioRad | 1613100 | Agarose gel electrophoresis |
50x TAE buffer | BioRad | 1610743 | Agarose gel electrophoresis |
T4 Polynucleotide Kinase | Thermo Fisher Scientific | EK0031 | |
T4 DNA Ligase | Thermo Fisher Scientific | EL0014 |