Quantifying combined effects of colistin and ciprofloxacin against Escherichia coli in an in silico pharmacokinetic-pharmacodynamic model.

Co-administering a low dose of colistin (CST) with ciprofloxacin (CIP) may improve the antibacterial effect against resistant Escherichia coli, offering an acceptable benefit-risk balance. This study aimed to quantify the interaction between ciprofloxacin and colistin in an in silico pharmacokinetic-pharmacodynamic model from in vitro static time-kill experiments (using strains with minimum inhibitory concentrations, MICCIP 0.023-1 mg/L and MICCST 0.5-0.75 mg/L). It was also sought to demonstrate an approach of simulating concentrations at the site of infection with population pharmacokinetic and whole-body physiologically based pharmacokinetic models to explore the clinical value of the combination when facing more resistant strains (using extrapolated strains with lower susceptibility). The combined effect in the final model was described as the sum of individual drug effects with a change in drug potency: for ciprofloxacin, concentration at half maximum killing rate (EC50) in combination was 160% of the EC50 in monodrug experiments, while for colistin, the change in EC50 was strain-dependent from 54.1% to 119%. The benefit of co-administrating a lower-than-commonly-administrated colistin dose with ciprofloxacin in terms of drug effect in comparison to either monotherapy was predicted in simulated bloodstream infections and pyelonephritis. The study illustrates the value of pharmacokinetic-pharmacodynamic modelling and simulation in streamlining rational development of antibiotic combinations.

Three concurrent mechanisms generate gene copy number variation and transient antibiotic heteroresistance.

Heteroresistance is a medically relevant phenotype where small antibiotic-resistant subpopulations coexist within predominantly susceptible bacterial populations. Heteroresistance reduces treatment efficacy across diverse bacterial species and antibiotic classes, yet its genetic and physiological mechanisms remain poorly understood. Here, we investigated a multi-resistant Klebsiella pneumoniae isolate and identified three primary drivers of gene dosage-dependent heteroresistance for several antibiotic classes: tandem amplification, increased plasmid copy number, and transposition of resistance genes onto cryptic plasmids. All three mechanisms imposed fitness costs and were genetically unstable, leading to fast reversion to susceptibility in the absence of antibiotics. We used a mouse gut colonization model to show that heteroresistance due to elevated resistance-gene dosage can result in antibiotic treatment failures. Importantly, we observed that the three mechanisms are prevalent among Escherichia coli bloodstream isolates. Our findings underscore the necessity for treatment strategies that address the complex interplay between plasmids, resistance cassettes, and transposons in bacterial populations.

Heteroresistance to piperacillin/tazobactam in Klebsiella pneumoniae is mediated by increased copy number of multiple ß-lactamase genes.

Background: Piperacillin/tazobactam is a ß-lactam/ß-lactamase inhibitor combination with a broad spectrum of activity that is often used as empirical and/or targeted therapy among hospitalized patients. Heteroresistance (HR) is a form of antibiotic resistance in which a minority population of resistant cells coexists with a majority susceptible population that has been found to be a cause of antibiotic treatment failure in murine models. Objectives: To determine the prevalence of HR and mechanisms of HR to piperacillin/tazobactam among Klebsiella pneumoniae bloodstream infection (BSI) isolates. Materials: From July 2018 to June 2021, K. pneumoniae piperacillin/tazobactam-susceptible BSI isolates were collected from two tertiary hospitals in Atlanta, GA, USA. Only first isolates from each patient per calendar year were included. Population analysis profiling (PAP) and WGS were performed to identify HR and its mechanisms. Results: Among 423 K. pneumoniae BSI isolates collected during the study period, 6% (25/423) were found to be HR with a subpopulation surviving above the breakpoint. WGS of HR isolates grown in the presence of piperacillin/tazobactam at concentrations 8-fold that of the MIC revealed copy number changes of plasmid-located ß-lactamase genes blaCTX-M-15, blaSHV33, blaOXA-1 and blaTEM-1 by tandem gene amplification or plasmid copy number increase. Conclusions: Prevalence of HR to piperacillin/tazobactam among bloodstream isolates was substantial. The HR phenotype appears to be caused by tandem amplification of ß-lactamase genes found on plasmids or plasmid copy number increase. This raises the possibility of dissemination of HR through horizontal gene transfer and requires further study.

Suppression of the E. coli rnpA49 conditionally lethal phenotype by different compensatory mutations.

RNase P is an essential enzyme found across all domains of life that is responsible for the 5'-end maturation of precursor tRNAs. For decades, numerous studies have sought to elucidate the mechanisms and biochemistry governing RNase P function. However, much remains unknown about the regulation of RNase P expression, the turnover and degradation of the enzyme, and the mechanisms underlying the phenotypes and complementation of specific RNase P mutations, especially in the model bacterium, Escherichia coli. In E. coli, the temperature-sensitive rnpA49 mutation in the protein subunit of RNase P has arguably been one of the most well-studied mutations for examining the enzyme's activity in vivo. Here, we report for the first time naturally-occurring temperature-resistant suppressor mutations of E. coli strains carrying the rnpA49 allele. We find that rnpA49 strains can partially compensate the temperature-sensitive defect via gene amplifications of either RNase P subunit (rnpA49 or rnpB) or by the acquisition of loss-of-function mutations in Lon protease or RNase R. Our results agree with previous plasmid overexpression and gene deletion complementation studies, and importantly suggest the involvement of Lon protease in the degradation and/or regulatory pathway(s) of the mutant protein subunit of RNase P. This work offers novel insights into the behavior and complementation of the rnpA49 allele in vivo and provides direction for follow-up studies regarding RNase P regulation and turnover in E. coli.

Theoretical considerations and empirical predictions of the pharmaco- and population dynamics of heteroresistance.

Antibiotics are considered one of the most important contributions to clinical medicine in the last century. Due to the use and overuse of these drugs, there have been increasing frequencies of infections with resistant pathogens. One form of resistance, heteroresistance, is particularly problematic; pathogens appear sensitive to a drug by common susceptibility tests. However, upon exposure to the antibiotic, resistance rapidly ascends, and treatment fails. To quantitatively explore the processes contributing to the emergence and ascent of resistance during treatment and the waning of resistance following cessation of treatment, we develop two distinct mathematical and computer-simulation models of heteroresistance. In our analysis of the properties of these models, we consider the factors that determine the response to antibiotic-mediated selection. In one model, heteroresistance is progressive, with each resistant state sequentially generating a higher resistance level. In the other model, heteroresistance is non-progressive, with a susceptible population directly generating populations with different resistance levels. The conditions where resistance will ascend in the progressive model are narrower than those of the non-progressive model. The rates of reversion from the resistant to the sensitive states are critically dependent on the transition rates and the fitness cost of resistance. Our results demonstrate that the standard test used to identify heteroresistance is insufficient. The predictions of our models are consistent with empirical results. Our results demand a reevaluation of the definition and criteria employed to identify heteroresistance. We recommend that the definition of heteroresistance should include a consideration of the rate of return to susceptibility.

Bacteria can compensate the fitness costs of amplified resistance genes via a bypass mechanism.

Antibiotic heteroresistance is a phenotype in which a susceptible bacterial population includes a small subpopulation of cells that are more resistant than the main population. Such resistance can arise by tandem amplification of DNA regions containing resistance genes that in single copy are not sufficient to confer resistance. However, tandem amplifications often carry fitness costs, manifested as reduced growth rates. Here, we investigated if and how these fitness costs can be genetically ameliorated. We evolved four clinical isolates of three bacterial species that show heteroresistance to tobramycin, gentamicin and tetracyclines at increasing antibiotic concentrations above the minimal inhibitory concentration (MIC) of the main susceptible population. This led to a rapid enrichment of resistant cells with up to an 80-fold increase in the resistance gene copy number, an increased MIC, and severely reduced growth rates. When further evolved in the presence of antibiotic, these strains acquired compensatory resistance mutations and showed a reduction in copy number while maintaining high-level resistance. A deterministic model indicated that the loss of amplified units was driven mainly by their fitness costs and that the compensatory mutations did not affect the loss rate of the gene amplifications. Our findings suggest that heteroresistance mediated by copy number changes can facilitate and precede the evolution towards stable resistance.

Antibiotic resistance begets more resistance: chromosomal resistance mutations mitigate fitness costs conferred by multi-resistant clinical plasmids.

Plasmids are the primary vectors of horizontal transfer of antibiotic resistance genes among bacteria. Previous studies have shown that the spread and maintenance of plasmids among bacterial populations depend on the genetic makeup of both the plasmid and the host bacterium. Antibiotic resistance can also be acquired through mutations in the bacterial chromosome, which not only confer resistance but also result in changes in bacterial physiology and typically a reduction in fitness. However, it is unclear whether chromosomal resistance mutations affect the interaction between plasmids and the host bacteria. To address this question, we introduced 13 clinical plasmids into a susceptible Escherichia coli strain and three different congenic mutants that were resistant to nitrofurantoin (ΔnfsAB), ciprofloxacin (gyrA, S83L), and streptomycin (rpsL, K42N) and determined how the plasmids affected the exponential growth rates of the host in glucose minimal media. We find that though plasmids confer costs on the susceptible strains, those costs are fully mitigated in the three resistant mutants. In several cases, this results in a competitive advantage of the resistant strains over the susceptible strain when both carry the same plasmid and are grown in the absence of antibiotics. Our results suggest that bacteria carrying chromosomal mutations for antibiotic resistance could be a better reservoir for resistance plasmids, thereby driving the evolution of multi-drug resistance.IMPORTANCEPlasmids have led to the rampant spread of antibiotic resistance genes globally. Plasmids often carry antibiotic resistance genes and other genes needed for its maintenance and spread, which typically confer a fitness cost on the host cell observed as a reduced growth rate. Resistance is also acquired via chromosomal mutations, and similar to plasmids they also reduce bacterial fitness. However, we do not know whether resistance mutations affect the bacterial ability to carry plasmids. Here, we introduced 13 multi-resistant clinical plasmids into a susceptible and three different resistant E. coli strains and found that most of these plasmids do confer fitness cost on susceptible cells, but these costs disappear in the resistant strains which often lead to fitness advantage for the resistant strains in the absence of antibiotic selection. Our results imply that already resistant bacteria are a more favorable reservoir for multi-resistant plasmids, promoting the ascendance of multi-resistant bacteria.

Within-species variability of antibiotic interactions in Gram-negative bacteria.

Treatments with antibiotic combinations are becoming increasingly important even though the supposed clinical benefits of combinations are, in many cases, unclear. Here, we systematically examined how several clinically used antibiotics interact and affect the antimicrobial efficacy against five especially problematic Gram-negative pathogens. A total of 232 bacterial isolates were tested against different pairwise antibiotic combinations spanning five classes, and the ability of all combinations in inhibiting growth was quantified. Descriptive statistics, principal component analysis (PCA), and Spearman's rank correlation matrix were used to determine the correlations between the different combinations on interaction outcome. Several important conclusions can be drawn from the 696 examined interactions. Firstly, within a species, the interactions are in general conserved but can be isolate-specific for a given antibiotic combination and can range from antagonistic to synergistic. Secondly, additive and antagonistic interactions are the most common observed across species and antibiotics, with 87.1% of isolate-antibiotic combinations being additive, 11.6% antagonistic, and only 0.3% showing synergy. These findings suggest that to achieve the highest precision and efficacy of combination therapy, not only isolate-specific interaction profiling ought to be routinely performed, in particular to avoid using drug combinations that show antagonistic interaction and an expected associated reduction in efficacy, but also discovering rare and potentially valuable synergistic interactions.IMPORTANCEAntibiotic combinations are often used to treat bacterial infections, which aim to increase treatment efficacy and reduce resistance evolution. Typically, it is assumed that one specific antibiotic combination has the same effect on different isolates of the same species, i.e., the interaction is conserved. Here, we tested this idea by examining how several clinically used antibiotics interact and affect the antimicrobial efficacy against several bacterial pathogens. Our results show that, even though within a species the interactions are often conserved, there are also isolate-specific differences for a given antibiotic combination that can range from antagonistic to synergistic. These findings suggest that isolate-specific interaction profiling ought to be performed in clinical microbiology routine to avoid using antagonistic drug combinations that might reduce treatment efficacy.

Staphylococcus aureus mutants resistant to the feed-additive monensin show increased virulence and altered purine metabolism.

Ionophores are antibacterial compounds that affect bacterial growth by changing intracellular concentrations of the essential cations, sodium and potassium. They are extensively used in animal husbandry to increase productivity and reduce infectious diseases, but our understanding of the potential for and effects of resistance development to ionophores is poorly known. Thus, given their widespread global usage, it is important to determine the potential negative consequences of ionophore use on human and animal health. In this study, we demonstrate that exposure to the ionophore monensin can select for resistant mutants in the human and animal pathogen Staphylococcus aureus, with a majority of the resistant mutants showing increased growth rates in vitro and/or in mice. Whole-genome sequencing and proteomic analysis of the resistant mutants show that the resistance phenotype is associated with de-repression of de novo purine synthesis, which could be achieved through mutations in different transcriptional regulators including mutations in the gene purR, the repressor of the purine de novo synthesis pathway. This study shows that mutants with reduced susceptibility to the ionophore monensin can be readily selected and highlights an unexplored link between ionophore resistance, purine metabolism, and fitness in pathogenic bacteria.IMPORTANCEThis study demonstrates a novel link between ionophore resistance, purine metabolism, and virulence/fitness in the key human and animal pathogen Staphylococcus aureus. The results show that mutants with reduced susceptibility to the commonly used ionophore monensin can be readily selected and that the reduced susceptibility observed is associated with an increased expression of the de novo purine synthesis pathway. This study increases our understanding of the impact of the use of animal feed additives on both human and veterinary medicine.

High prevalence of heteroresistance in Staphylococcus aureus is caused by a multitude of mutations in core genes.

Heteroresistance (HR) is an enigmatic phenotype where, in a main population of susceptible cells, small subpopulations of resistant cells exist. This is a cause for concern, as this small subpopulation is difficult to detect by standard antibiotic susceptibility tests, and upon antibiotic exposure the resistant subpopulation may increase in frequency and potentially lead to treatment complications or failure. Here, we determined the prevalence and mechanisms of HR for 40 clinical Staphylococcus aureus isolates, against 6 clinically important antibiotics: daptomycin, gentamicin, linezolid, oxacillin, teicoplanin, and vancomycin. High frequencies of HR were observed for gentamicin (69.2%), oxacillin (27%), daptomycin (25.6%), and teicoplanin (15.4%) while none of the isolates showed HR toward linezolid or vancomycin. Point mutations in various chromosomal core genes, including those involved in membrane and peptidoglycan/teichoic acid biosynthesis and transport, tRNA charging, menaquinone and chorismite biosynthesis and cyclic-di-AMP biosynthesis, were the mechanisms responsible for generating the resistant subpopulations. This finding is in contrast to gram-negative bacteria, where increased copy number of bona fide resistance genes via tandem gene amplification is the most prevalent mechanism. This difference can be explained by the observation that S. aureus has a low content of resistance genes and absence of the repeat sequences that allow tandem gene amplification of these genes as compared to gram-negative species.

Vesicle-enriched secretomes alter bacterial competitive abilities and are drivers of evolution in microbial communities.

Microbial membrane vesicles can carry compounds that inhibit bacterial growth, but how they impact the fitness of the vesicle-producing bacterial species and influence community dynamics remain unexplored questions. To address these questions, we examined the effect of vesicle-enriched secretomes (VESs) in different single-species and multi-species systems. Effects of VESs on single-species growth dynamics were determined for nine bacterial species belonging to four genera (Escherichia, Salmonella, Pseudomonas and Bacillus) in nutrient-rich and poor growth media. Results showed both species-specific and nutrient-dependent effects of the VESs on bacterial growth. The strongest antagonistic effects were observed for VES isolated from the natural isolates of E. coli, while those isolated from P. aeruginosa PA14 affected the highest number of species. We further demonstrated that these VESs altered the competitive abilities of the species involved in two-species (S. Typhimurium LT2 and S. arizonae) and three-species systems (E. coli, S. Typhimurium LT2 and B. subtilis). Finally, using experimental evolution we showed that different bacterial species could rapidly acquire mutations that abrogated the antagonistic effects of VESs. This study demonstrates how VESs can contribute in shaping microbial communities, both by increasing the competitive ability of a given bacterial species and as a driver of genetic adaptation.

Theoretical Considerations and Empirical Predictions of the Pharmaco- and Population Dynamics of Heteroresistance.

Antibiotics are considered one of the most important contributions to clinical medicine in the last 100 years. Due to the use and overuse of these drugs, there have been increasing frequencies of infections with resistant pathogens. One form of resistance, heteroresistance, is particularly problematic; pathogens appear sensitive to a drug by common susceptibility tests. However, upon exposure to the antibiotic, resistance rapidly ascends, and treatment fails. To quantitatively explore the processes contributing to the emergence and ascent of resistance during treatment and the waning of resistance following cessation of treatment, we develop two distinct mathematical and computer-simulations models of heteroresistance. In our analysis of the properties of these models, we consider the factors that determine the response to antibiotic-mediated selection. In one model, heteroresistance is progressive, with each resistant state sequentially generating a higher resistance level. In the other model, heteroresistance is non-progressive, with a susceptible population directly generating populations with different resistance levels. The conditions where resistance will ascend in the progressive model are narrower than those of the non-progressive model. The rates of reversion from the resistant to the sensitive states are critically dependent on the transition rates and the fitness cost of resistance. Our results demonstrate that the standard test used to identify heteroresistance is insufficient. The predictions of our models are consistent with empirical results. Our results demand a reevaluation of the definition and criteria employed to identify heteroresistance. We recommend the definition of heteroresistance should include a consideration of the rate of return to susceptibility.

Evolutionary history of Staphylococcus aureus influences antibiotic resistance evolution.

Antibiotic resistance often confers a fitness cost to the resistant cell and thus raises key questions of how resistance is maintained in the absence of antibiotics and, if lost, whether cells are genetically primed for re-evolving resistance. To address these questions, we have examined vancomycin-intermediate Staphylococcus aureus (VISA) strains that arise during vancomycin therapy. VISA strains harbor a broad spectrum of mutations, and they are known to be unstable both in patients and in the laboratory. Here, we show that loss of resistance in VISA strains is correlated with a fitness increase and is attributed to adaptive mutations, leaving the initial VISA-adaptive mutations intact. Importantly, upon a second exposure to vancomycin, such revertants evolve significantly faster to become VISA, and they reach higher resistance levels than vancomycin-naive cells. Further, we find that sub-lethal concentrations of vancomycin stabilize the VISA phenotype, as do the human ß-defensin 3 (hBD-3) and the bacteriocin nisin that both, like vancomycin, bind to the peptidoglycan building block, lipid II. Thus, factors binding lipid II may stabilize VISA both in vivo and in vitro, and in case resistance is lost, mutations remain that predispose to resistance development. These findings may explain why VISA infections often are re-occurring and suggest that previous vancomycin adaptation should be considered a risk factor when deciding on antimicrobial chemotherapy.

Interspecies interaction reduces selection for antibiotic resistance in Escherichia coli.

Evolution of microbial traits depends on the interaction of a species with its environment as well as with other coinhabiting species. However, our understanding of the evolution of specific microbial traits, such as antibiotic resistance in complex environments is limited. Here, we determine the role of interspecies interactions on the dynamics of nitrofurantoin (NIT) resistance selection among Escherichia coli. We created a synthetic two-species community comprised of two variants of E. coli (NIT susceptible and resistant) and Bacillus subtilis in minimal media with glucose as the sole carbon source. We show that the presence of B. subtilis significantly slows down the selection for the resistant E. coli mutant when NIT is present and that this slowdown is not due to competition for resources. Instead, the dampening of NIT resistance enrichment is largely mediated by extracellular compounds produced by B. subtilis with the peptide YydF playing a significant role. Our results not only demonstrate the impact of interspecies interactions on the evolution of microbial traits but also show the importance of using synthetic microbial systems in unravelling relevant interactions and mechanisms affecting the evolution of antibiotic resistance. This finding implies that interspecies interactions should be considered to better understand and predict resistance evolution in the clinic as well as in nature.

Rescue of Escherichia coli auxotrophy by de novo small proteins.

Increasing numbers of small proteins with diverse physiological roles are being identified and characterized in both prokaryotic and eukaryotic systems, but the origins and evolution of these proteins remain unclear. Recent genomic sequence analyses in several organisms suggest that new functions encoded by small open reading frames (sORFs) may emerge de novo from noncoding sequences. However, experimental data demonstrating if and how randomly generated sORFs can confer beneficial effects to cells are limited. Here, we show that by upregulating hisB expression, de novo small proteins (≤50 amino acids in length) selected from random sequence libraries can rescue Escherichia coli cells that lack the conditionally essential SerB enzyme. The recovered small proteins are hydrophobic and confer their rescue effect by binding to the 5' end regulatory region of the his operon mRNA, suggesting that protein binding promotes structural rearrangements of the RNA that allow increased hisB expression. This study adds RNA regulatory elements as another interacting partner for de novo proteins isolated from random sequence libraries and provides further experimental evidence that small proteins with selective benefits can originate from the expression of nonfunctional sequences.

Pervasive Selection for Clinically Relevant Resistance and Media Adaptive Mutations at Very Low Antibiotic Concentrations.

Experimental evolution studies have shown that weak antibiotic selective pressures (i.e., when the antibiotic concentrations are far below the minimum inhibitory concentration, MIC) can select resistant mutants, raising several unanswered questions. First, what are the lowest antibiotic concentrations at which selection for de novo resistance mutations can occur? Second, with weak antibiotic selections, which other types of adaptive mutations unrelated to the antibiotic selective pressure are concurrently enriched? Third, are the mutations selected under laboratory settings at subMIC also observed in clinical isolates? We addressed these questions using Escherichia coli populations evolving at subMICs in the presence of either of four clinically used antibiotics: fosfomycin, nitrofurantoin, tetracycline, and ciprofloxacin. Antibiotic resistance evolution was investigated at concentrations ranging from 1/4th to 1/2000th of the MIC of the susceptible strain (MICsusceptible). Our results show that evolution was rapid across all the antibiotics tested, and selection for fosfomycin- and nitrofurantoin-resistant mutants was observed at a concentration as low as 1/2000th of MICsusceptible. Several of the evolved resistant mutants showed increased growth yield and exponential growth rates, and outcompeted the susceptible ancestral strain in the absence of antibiotics as well, suggesting that adaptation to the growth environment occurred in parallel with the selection for resistance. Genomic analysis of the resistant mutants showed that several of the mutations selected under these conditions are also found in clinical isolates, demonstrating that experimental evolution at very low antibiotic levels can help in identifying novel mutations that contribute to bacterial adaptation during subMIC exposure in real-life settings.

Low levels of tetracyclines select for a mutation that prevents the evolution of high-level resistance to tigecycline.

In a collection of Escherichia coli isolates, we discovered a new mechanism leading to frequent and high-level tigecycline resistance involving tandem gene amplifications of an efflux pump encoded by the tet(A) determinant. Some isolates, despite carrying a functional tet(A), could not evolve high-level tigecycline resistance by amplification due to the presence of a deletion in the TetR(A) repressor. This mutation impaired induction of tetA(A) (encoding the TetA(A) efflux pump) in presence of tetracyclines, with the strongest effect observed for tigecycline, subsequently preventing the development of tet(A) amplification-dependent high-level tigecycline resistance. We found that this mutated tet(A) determinant was common among tet(A)-carrying E. coli isolates and analysed possible explanations for this high frequency. First, while the mutated tet(A) was found in several ST-groups, we found evidence of clonal spread among ST131 isolates, which increases its frequency within E. coli databases. Second, evolution and competition experiments revealed that the mutation in tetR(A) could be positively selected over the wild-type allele at sub-inhibitory concentrations of tetracyclines. Our work demonstrates how low concentrations of tetracyclines, such as those found in contaminated environments, can enrich and select for a mutation that generates an evolutionary dead-end that precludes the evolution towards high-level, clinically relevant tigecycline resistance.

Antibiotic Minimal Selective Concentrations and Fitness Costs during Biofilm and Planktonic Growth.

The use and misuse of antibiotics have resulted in the selection of difficult-to-treat resistant bacteria. Two key parameters that influence the selection of resistant bacteria are the minimal selective concentration (MSC) and the fitness cost of resistance, both of which have been measured during planktonic growth in several studies. However, bacterial growth most often occurs in biofilms, and it is unclear if and how these parameters differ under these two growth conditions. To address this knowledge gap, we compared a selection of several types of antibiotic-resistant Escherichia coli mutants during planktonic and biofilm growth to determine the fitness costs and MSCs. Biofilm-forming Escherichia coli strains are commonly found in catheter-associated and recurrent urinary tract infections. Isogenic strains of a biofilm-forming E. coli strain, differing only in the resistance mechanisms and the fluorescent markers, were constructed, and susceptible and resistant bacteria were grown in head-to-head competitions at various concentrations of antibiotics under planktonic and biofilm conditions. Mutants with resistance to five different antibiotics were studied. The results show that during both planktonic and biofilm growth, selection for the resistant mutants occurred for all antibiotics at sub-MICs far below the MIC of the antibiotic. Even though differences were seen, the MSC values and the fitness costs did not differ systematically between planktonic and biofilm growth, implying that despite the different growth modes, the basic selection parameters are similar. These findings highlight the risk that resistant mutants may, similarly to planktonic growth, also be selected at sub-MICs of antibiotics in biofilms. IMPORTANCE Our understanding of how and where antibiotic resistance is selected in response to antibiotic exposure is still limited, and this is particularly true for selective processes when bacteria are growing in biofilms, arguably the most significant mode of growth of bacteria in human and animal infections as well as in other settings. In this study, we compared how different types of resistant E. coli strains were selected in response to antibiotic exposure during planktonic and biofilm growth. Determination of the minimal selective concentrations (MSCs) and fitness costs of resistance showed that they were comparable under these two different conditions, even though some differences were observed. Importantly, the MSCs were far below the MICs for all mutants under both planktonic and biofilm growth, emphasizing the significance of low antibiotic concentrations in driving the emergence and enrichment of resistant bacteria.

A Microfluidic Chip for Studies of the Dynamics of Antibiotic Resistance Selection in Bacterial Biofilms.

Biofilms are arguably the most important mode of growth of bacteria, but how antibiotic resistance emerges and is selected in biofilms remains poorly understood. Several models to study evolution of antibiotic resistance have been developed, however, their usability varies depending on the nature of the biological question. Here, we developed and validated a microfluidic chip (Brimor) for studying the dynamics of enrichment of antibiotic-resistant bacteria in biofilms using real-time monitoring with confocal microscopy. In situ extracellular cellulose staining and physical disruption of the biomass confirmed Escherichia coli growth as biofilms in the chip. We showed that seven generations of growth occur in 16 h when biofilms were established in the growth chambers of Brimor, and that bacterial death and growth rates could be estimated under these conditions using a plasmid with a conditional replication origin. Additionally, competition experiments between antibiotic-susceptible and -resistant bacteria at sub-inhibitory concentrations demonstrated that the antibiotic ciprofloxacin selected for antibiotic resistance in bacterial biofilms at concentrations 17-fold below the minimal inhibitory concentration of susceptible planktonic bacteria. Overall, the microfluidic chip is easy to use and a relevant model for studying the dynamics of selection of antibiotic resistance in bacterial biofilms and we anticipate that the Brimor chip will facilitate basic research in this area.

Potential risks of treating bacterial infections with a combination of ß-lactam and aminoglycoside antibiotics: A systematic quantification of antibiotic interactions in E. coli blood stream infection isolates.

BACKGROUND: Treatment of Blood Stream Infections (BSIs) with a combination of a ß-lactam and an aminoglycoside antibiotic is widely used in intensive care units (ICUs) around the world. However, no studies have systematically examined how these drugs interact and potentially influence the antimicrobial efficacy of the overall treatment. METHODS: We collected 500 E. coli isolates from the Uppsala University hospital that were isolated from blood of patients with suspicion of infection. Of those we tested the efficacy of combinations of 2 common ß-lactam antibiotics (Ampicillin and Cefotaxime) combined with 2 common aminoglycosides (Gentamicin and Tobramycin) on 254 isolates. The efficacy of all 4 pairwise combinations in inhibiting bacterial growth was then examined on all susceptible strains. That was done by quantifying the Fractional Inhibitory index (FICi), a robust metric for antibiotic combinatorial behaviour, of all possible treatments on every strain. When non additive interactions were identified, results of the original screen were verified with time kill assays. Finally, combination behaviours were analysed for potential cross correlations. FINDINGS: Out of the 4 antibiotic combinations screened none exhibited synergistic effects on any of the 254 strains. On the contrary all 4 exhibited important antagonistic effects on several isolates. Specifically, the combinations of AMP-GEN and CTX-GEN were antagonistic in 1.97% and 1.18% of strains respectively. Similarly, the combinations of AMP-TOB were antagonistic on 0.78% of all strains. PCA analysis revealed that an important factor on the responses to the combination treatments was the choice of a specific aminoglycoside over another. Subsequent cross correlation analysis revealed that the interaction profiles of combinations including the same aminoglycoside are significantly correlated (Spearman's cross correlation test p<0.001). INTERPRETATION: The findings of this study elucidate potential risks of the common combination treatment for blood stream infections. They also demonstrate, previously unquantified metrics on how antibiotics in combination therapies are not interchangeable with others of the same class. Finally, they reiterate the need for case-by-case testing of antibiotic interactions in a clinical setting. FUNDING: This work was funded by grants to DIA from the Swedish Research Council, the Wallenberg foundation and the Swedish Strategic Research Foundation.