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Molecular pharmacodynamics of amoxicillin-clavulanic acid for urinary tract infections caused by Escherichia coliPresent Address:
VineetDubey1
ChristopherDarlow1,2
AlessandroGerada1,2
JenniferUnsworth1
EshaSheth1
NadaReza1,2
NicolaFarrington1
AlexanderHoward1,2
WilliamHope1,2✉Emailhopew@liverpool.ac.uk
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Department of Clinical Pharmacology and TherapeuticsUniversity of LiverpoolUnited Kingdom2Liverpool Clinical LaboratoriesUniversity Hospitals of Liverpool GroupLiverpoolUnited Kingdom
Vineet Dubey1, Christopher Darlow1,2, Alessandro Gerada1,2, Jennifer Unsworth1, Esha Sheth1, Nada Reza1,2, Nicola Farrington1, Alexander Howard1,2, William Hope1,2*
1Department of Clinical Pharmacology and Therapeutics, University of Liverpool, United Kingdom
2Liverpool Clinical Laboratories, University Hospitals of Liverpool Group, Liverpool, United Kingdom
*Corresponding author: hopew@liverpool.ac.uk
Abstract
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Amoxicillin-clavulanic acid (AMX-CLV) is a widely used oral β-lactam/β-lactamase inhibitor combination against Escherichia coli. Clinical success is largely confined to urinary tract infections. The mechanistic basis for this site-specific efficacy remains unclear. Using a hollow-fibre infection model to replicate human plasma and urinary pharmacokinetics, we show that plasma-like exposures rapidly select for pre-existing resistant subpopulations; whereas, urinary exposures produce sustained bactericidal activity without resistance emergence. Genomic and transcriptomic analyses following plasma drug exposure revealed that treatment selectively enriches pre-existing resistant lineages already harbouring oxidative-stress-associated mutations that activate the SOS response and drive IS-mediated amplification of blaTEM-1, leading to β-lactamase hyperproduction and treatment failure. In contrast, the high urinary concentrations of clavulanic acid exert direct antibacterial activity, eradicating these subpopulations. Our findings demonstrate that local pharmacokinetic environments fundamentally shape evolutionary trajectories under β-lactam/β-lactamase inhibitor therapy, explaining the restricted efficacy of AMX-CLV and revealing a dynamic interplay between stress responses, genome plasticity, and drug partitioning that governs treatment outcome.A
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Introduction
Escherichia coli, a leading cause of community and hospital-acquired infections, can express many antibiotic resistance mechanisms1,2. E. coli is often resistant to narrow-spectrum penicillins such as amoxicillin, and this is mediated by Ambler Class A β-lactamases, such as SHV and TEM enzymes3,4. These enzymes are inhibited by β-lactamase inhibitors such as clavulanic acid and tazobactam. Hence, combinations of antibiotics such as amoxicillin-clavulanic acid (AMX-CLV) and piperacillin-tazobactam are extensively used treatment as first-line agents5–7. Since most E. coli disease occurs in ambulatory settings, orally bioavailable agents such as AMX-CLV are strategically valuable. Hence, a deep understanding of the pharmacodynamics and resistance liabilities of AMX-CLV is paramount.
Emerging evidence suggests that clinical success with AMX-CLV against E. coli is largely confined to urinary tract infections. The European Committee on Antimicrobial Susceptibility Testing (EUCAST) currently restricts recommendations for oral AMX-CLV to the treatment of UTIs8. Understanding the mechanistic basis for site-specific AMX-CLV efficacy could enable novel treatment strategies that: (i) preserve a clinically useful and widely available oral agent; (ii) reduce treatment failures and associated morbidity and mortality; and, (iii) help curb the global AMR crisis.
Here, we provide an understanding that when AMX-CLV is used for E. coli, its use should be restricted to urinary tract infections (UTI). We used a hollow-fibre infection model (HFIM) to replicate human-like pharmacokinetics of AMX-CLV against TEM-1 β-lactamase-producing E. coli. Although initial killing was achieved, AMX-CLV exposure enabled the expansion of pre-existing resistant subpopulations, leading to escape. Genomic analyses identified numerous mutational pathways that enhanced oxidative stress, activation of the SOS response, and mobilised blaTEM-1 via Insertion Sequences (IS)-mediated translocatable units, increasing gene copy number and driving β-lactamase hyperproduction. Simulation of plasma and urinary profiles revealed that site-specific drug exposure determines whether AMX-CLV can suppress these resistant lineages, providing a molecular and pharmacological explanation for its limited efficacy outside the urinary tract.
Results
Clinical E. coli isolates exhibit variable β-lactam susceptibility despite shared AMX-CLV MICs
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A total of 30 clinical isolates of E. coli from a large tertiary clinical microbiology laboratory were recovered from beads. All isolates had MICs > 64 mg/L to AMX alone. However, the combination of AMX-CLV resulted in a 2- to 16-fold reduction in MICs (Table. 1, supplementary Table S1). A total of 16/30 isolates had MIC values ≤ 8 mg/L, which is the current AMX-CLV susceptibility breakpoint for Enterobacterales in all contexts except uncomplicated UTIs.9 From the 30 clinical E. coli, B50, K35 and K67 were chosen for HFIM work as all three had an AMX-CLV MIC of 4 mg/L (Table. 1), providing a matched susceptibility baseline. These strains carried different β-lactamases (i.e., TEM-1 and SHV-1) and originated from distinct clinical backgrounds.Human plasma AMX-CLV exposures rapidly select pre-existing resistant subpopulations
E. coli isolates were exposed to the following human-like plasma profiles in the HFIM for 48h: untreated control, AMX-CLV 500/125 mg q8h, and AMX-CLV 1000/125 mg q8h. The corresponding drug exposure profiles for each arm are shown in Supplementary Fig. S1.
The untreated arm exhibited logarithmic growth, with few resistant colonies recovered on drug-containing plates. Following drug treatment, initial bacterial killing was observed. However, there was rapid regrowth and emergence of a resistant sub-population (Fig. 1). Resistance was confirmed by plating samples on MH agar containing AMX/CLV 32/2.5 mg/L. Colonies isolated from drug-containing plates displayed MIC values in the range of 32–128 mg/L; whereas, colonies from drug-free plates in the untreated arm retained their original MIC values.
Pharmacodynamic failure arises from rare, pre-existing TEM-1 overexpressing E. coli lineages
β-lactams exert antibacterial effects beyond their primary target. Cell wall damage is known to trigger the generation of reactive oxygen species (ROS) and subsequent resistance generation10. To examine ROS dynamics during clinically relevant plasma exposures of AMX-CLV, we sampled E. coli B50 in a HFIM at 24h and 48h with arms consisting of an untreated control and a concentration time profile of AMX/CVL corresponding to 500/125 mg q8h. Total bacterial densities were comparable over time, but treated populations became increasingly dominated by colonies growing on AMX-CLV plates. These colonies exhibited significantly higher intracellular ROS than untreated controls (mean ± s.d.; n = 6; P < 0.01, Student’s t-test) (Fig. 2A), indicating that the drug-selected fraction experienced elevated oxidative stress even after net killing had plateaued.
To test whether ROS directly contributed to resistance generation, we serially passaged B50 in escalating AMX-CLV concentrations (8–32 mg/L) with or without the ROS quencher thiourea (100 mM). The frequency of resistance between these experimental conditions were indistinguishable (Supplementary figure S2), suggesting there was no de novo ROS associated mutagenesis. Together with modest increases in double-strand breaks detected by TUNEL assays (Fig. 2C), these data suggest that elevated ROS is a correlate of a selected state rather than a primary driver of new mutational events that contribute AMX-CLV resistance.
We next investigated whether there were pre-existing resistant subpopulation(s) that preceded drug exposure. Flow cytometry using anti-TEM-1-FITC antibodies revealed basal heterogeneity in TEM-1 abundance in drug-unexposed B50 cultures. Cells sorted from the lowest-fluorescence gate (representing ~ 97–99% of the total population) exhibited AMX-CLV MICs of 4–8 mg/L, whereas those from the highest-fluorescence gate (~ 1–3%) displayed MICs of 64–128 mg/L (Fig. 2D). This demonstrated phenotypically distinct subpopulations with elevated TEM-1 expression are present prior to antibiotic exposure. Population-analysis profiling (PAP) provided consistent results, with clinical isolates (B50, K35, K67) each showing resistant subfractions spanning AMX-CLV MICs of 8-128 mg/L (Fig. 2E). These frequencies (~ 10⁻³-10⁻⁴) are sufficient to account for the bacterial regrowth in HFIM experiments.
Colonies recovered from drug-containing plates displayed striking blaTEM-1 upregulation (~ 8- to > 600-fold relative to ancestral cells) and modest evidence of DNA damage (Fig. 2A, 2C). Combined with flow cytometry and PAP data, these findings support a scenario in which plasma-relevant AMX-CLV exposures preferentially enrich pre-existing TEM-1-high lineages rather than drive the de novo emergence of resistance. The in vitro pharmacodynamic data identify the expansion of a TEM-1 overexpressing subpopulation as a key determinant of regrowth following systemic AMX-CLV exposure.
Resistant subpopulations display transcriptional rewiring and oxidative stress linked genomic instability
To investigate the molecular basis of resistance in the AMX-CLV selected subpopulations, we compared the transcriptomes and genomes of resistant-versus-sensitive isolates derived from the same parental strains.
Differential RNA-seq analysis revealed extensive transcriptional remodelling in resistant populations (Fig. 3A). Genes associated with β-lactam resistance (blaTEM-1), DNA-damage repair (recA, recN), and multiple IS-family transposases were among the most strongly upregulated. These patterns indicate that the high-level blaTEM-1 expression observed phenotypically is accompanied by activation of stress-response and mobile-element pathways, suggesting resistant subpopulations are transcriptionally primed to tolerate and adapt to AMX/CLV exposure.
Functional enrichment analysis of the differentially expressed genes revealed pathway-level reprogramming (See Supplementary Figure S3). Resistant isolates upregulated core metabolic and translational processes (i.e. glycolysis, amino-sugar metabolism, ribosome biogenesis) while downregulating anabolic pathways such as amino-acid and cofactor biosynthesis. This shift implies metabolic prioritisation toward energy production and protein synthesis at the expense of long-term biosynthetic investment, a pattern typical of stress-adapted states that favour short-term survival under antibiotic pressure.
Whole-genome sequencing identified diverse mutations across functional categories (Fig. 3B). High-impact variants included frameshifts and premature stop codons; whereas, moderate-impact variants were largely nonsynonymous SNPs predicted to alter protein structure. Several mutations mapped to oxidative-stress and DNA-damage response genes (mutT, katE, mntH, ahpC, gor) and regulators of general stress responses (rpoS, uspA). These changes collectively point to chronic activation of oxidative-stress management and repair pathways in resistant isolates.
Notably, the convergence of oxidative-stress-associated mutations with transcriptional upregulation of IS-family transposases suggests an environment of elevated genomic plasticity. Increased transposase activity under DNA-stress conditions could facilitate rearrangements and gene amplifications, including expansion of blaTEM-1 copy number.
Increasing AMX-CLV exposure delays but cannot prevent resistance expansion
To evaluate how drug exposure profiles influence bacterial killing and resistance emergence, we used the HFIM to simulate the human pharmacokinetics of AMX and CLV against the TEM-1-producing E. coli strain B50. The two drug components were administered independently, allowing precise control of concentration-time profiles that cannot be achieved in vivo.
Plasma pharmacokinetics of AMX following oral dosing with 500 mg q8h and a continuous infusion of CLV to maintain flat concentrations between 1 and 5 mg/L was simulated. Increasing CLV exposure produced progressively faster and deeper initial killing, but in all arms bacterial regrowth occurred by 48h, and resistant subpopulations ultimately dominated by 48 h (Fig. 4). Thus, higher CLV concentrations enhanced early bactericidal activity but were insufficient to prevent selection of resistant lineages.
Next, we varied AMX concentrations while fixing CLV at 125 mg q8h (approximating plasma exposures achieved with standard oral therapy). AMX was infused to maintain static free concentrations of 40, 80, and 160 mg/L. Increasing AMX concentrations accelerated bacterial killing. Cultures at 40 and 80 mg/L displayed regrowth after 48 h; whereas, at 160 mg/L, counts fell below the limit of quantification for 48 h before rebounding at 72 h (Fig. 4). Even these exposures, which approach or exceed the upper boundary of plasma concentrations achievable in humans, did not result in bacterial eradication. The corresponding drug exposure profiles for each arm are shown in Supplementary Fig. S4. As the regrowth was associated with a TEM-1-enriched subpopulation, we hypothesised that accelerated β-lactam degradation impaired attainment of the intended AMX-CLV exposures; consistent with this, nitrocefin hydrolysis by cells sampled from each dosing arm showed markedly increased β-lactamase activity compared with untreated controls (See Supplementary Fig. S5).
Collectively, these experiments show that dose escalation of either component confers only transient suppression of resistant subpopulations. While the precise molecular mechanisms were not delineated for each regimen, subsequent genomic analyses revealed convergent signatures of blaTEM-1 amplification conditions (see Fig. 5–6), suggesting a shared adaptive pathway to resistance.
IS-mediated amplification and structural remodelling of blaTEM-1 drive high-level resistance
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To define the genomic basis of resistance emerging under intensified AMX-CLV exposure, we quantified blaTEM-1 expression and copy number in isolates recovered from HFIM dose-modulation experiments. Quantitative RT-PCR showed that all resistant isolates expressed blaTEM-1 at markedly higher levels than untreated controls (Fig. 5A). Expression increased by ~ 10- to > 100-fold (regimen dependent), with the strongest induction in isolates exposed to AMX 500 mg/kg plus CLV 7.5–15 mg/L. Even at the highest CLV concentration tested (30 mg/L), transcription remained significantly elevated relative to wild-type cells, indicating that blaTEM-1 overexpression is a consistent feature of resistant populations across regimens.To test whether increased gene dosage contributed to this overexpression, we quantified extrachromosomal transposition units (TUs) carrying blaTEM-1. Resistant isolates contained 1 to 9 copies per cell, compared with the single-copy baseline in sensitive controls (Fig. 5B). Individual colonies exhibited heterogeneous amplification patterns, suggesting that gene-dosage effects arise through dynamic genomic rearrangements and the mobilisation of blaTEM-1-containing elements.
We next examined the local genetic environment of blaTEM-1 in untreated (WT1-WT3) and resistant isolates (R1-R7). In sensitive strains, blaTEM-1 resided within a simple IS26/IS1-flanked transposition unit consistent with a single-copy mobile element. Resistant isolates showed diversified architectures enriched for additional IS families (IS21, IS6), yielding multiple distinct endpoints (Fig. 5C). Rather than random insertion, this pattern is explained most parsimoniously by the selective enrichment of rare, pre-existing high-copy configurations that confer a competitive advantage during AMX-CLV exposure.
To account for these configurations, we developed a model of IS-mediated remodelling (Fig. 6). Under antibiotic pressure, IS26-driven replicative transposition or homologous recombination can duplicate the IS26-blaTEM-1-IS21 module in tandem arrays, whereas secondary recombination events may delete or replace specific IS boundaries, producing variants flanked by IS21 alone, IS1 alone, or no ISs at all. These processes generate a continuum of related architectures that differ in structure but share the outcome of increased blaTEM-1 dosage.
Mapping the genomic positions of IS elements relative to coding sequences and regulatory regions confirmed that resistant isolates exhibit broader IS activity across contexts (Fig. 5D). Upstream insertions were rare and did not create canonical promoter motifs, suggesting that transcriptional activation arises primarily from gene amplification rather than promoter engineering.
To assess whether the observed diversity of blaTEM-1 architectures could occur by chance, we compared the empirical data with a random-insertion model (Fig. 5E). Simulated independent insertions predicted substantially higher structural diversity than observed experimentally. In contrast, real data plateaued at ~ 12 unique architectures; far below the theoretical maximum of 625 possible combinations, indicating that blaTEM-1 mobility is constrained to a limited repertoire of recurrent, evolutionarily favoured configurations.
Together, these results reveal that AMX-CLV exposure promotes amplification of blaTEM-1 through structured IS-mediated rearrangements rather than random transposition. This constrained genomic plasticity stabilises high-level β-lactamase production and underpins the reproducible resistance phenotypes observed across dosing regimens.
Urinary drug exposures achieve sustained bacterial clearance and prevent resistance emergence
Given the predominantly renal elimination of AMX-CLV, we simulated urinary pharmacokinetics for both drugs using a physiology-based pharmacokinetic (PBPK) model (See supplementary Fig. S6). Simulations assumed a micturition frequency of q8h and generated urine Cmax values of 290 mg/L for AMX and 40 mg/L for CLV, consistent with urinary concentrations achieved after standard oral dosing of 500/125mg q8h. Using these parameters, we performed HFIM experiments as follows: untreated control, AMX monotherapy, CLV monotherapy, and AMX-CLV combination therapy. The corresponding drug exposure profiles for each arm are shown in Supplementary Fig. S7.
AMX monotherapy resulted in rapid bacterial regrowth, and expanding resistant subpopulations, consistent with the selection of blaTEM-1 overexpressing lineages (Fig. 7A). In contrast, CLV monotherapy produced a rapid ≥ 3 log₁₀ reduction in CFU within 6 h, but regrowth occurred after 24 h despite the absence of colonies on AMX-CLV containing plates. This pattern indicated that regrowth in the CLV arm was not driven by β-lactamase-mediated resistance. Given that the MIC of CLV against strain B50 was 16 mg/L, these data suggested that at high urinary concentrations, CLV may exert intrinsic antibacterial activity through partial inhibition of penicillin-binding proteins (PBPs).
Checkerboard assays using resistant isolates with AMX-CLV MICs ranging from 4 to 256 mg/L confirmed two distinct clearance mechanisms (Fig. 7B, S8). At moderate concentrations, bacterial killing depended on the synergistic interaction between the β-lactam and the β-lactamase inhibitor; at very high CLV concentrations, direct antibacterial activity of CLV was observed. Competitive bocillin-binding assays confirmed that CLV binds PBP1b, PBP2, and PBP5/6 at concentrations ≥ 40 mg/L (Fig. 7C, See supplementary Fig. S9), consistent with its bactericidal activity in the urinary-exposure arm.
Whole-genome analysis revealed that isolates selected on CLV alone experiment lacked the IS-mediated blaTEM-1 amplifications characteristic of AMX-CLV-selected resistant subpopulations (Fig. 7D). These CLV-resistant isolates exhibited minimal structural rearrangement around blaTEM-1 and no expansion of transposition unit endpoints, suggesting alternative, non-β-lactamase mechanisms of reduced susceptibility potentially involving PBP adaptation (see supplementary Fig. S10). Consistent with this, Western blot analysis showed that CLV-resistant isolates expressed TEM-1 at levels comparable to those of untreated controls, whereas combination-selected resistant clones displayed marked TEM-1 overexpression (Fig. 7E).
In the combination therapy arm of the urinary PK simulation, sustained bacterial eradication was achieved within 24 h with no regrowth or emergence of resistance up to 96 h (Fig. 7A). Together, these findings indicate that high urinary exposures of both AMX and CLV achieve sterilising activity through complementary mechanisms: CLV directly kills E. coli at concentrations where it acts as a weak PBP inhibitor, while AMX augments this activity and prevents the survival of any CLV tolerant cells. This pharmacokinetic context uniquely enables AMX-CLV to clear TEM-1 producing E. coli, explaining its clinical efficacy in urinary tract infections but limited success at other infection sites.
Discussion
Our study reveals a coordinated network of molecular and pharmacodynamic processes underpinning the emergence of high-level resistance to AMX-CLV in E. coli expressing TEM-1 β-lactamase. When plasma pharmacokinetics were simulated in the HFIM, the rapid selection and expansion of pre-existing resistant subpopulations suggest that the rapid emergence of resistance could contribute to treatment failure. This dynamic contrasts with the sustained bacterial clearance achieved following urinary pharmacokinetic profiles.
The emergence of resistance emergence following plasma concentration time profiles was driven by the selection of rare, stress-tolerant subpopulations with elevated blaTEM-1 expression. These cells exhibited oxidative-stress associated mutations and heightened transposase activity, creating conditions conducive to IS-mediated gene amplification. This adaptive network links oxidative stress, SOS activation, and mobile-element dynamics, leading to rapid amplification of β-lactamase determinants. Such findings provide a mechanistic explanation for the limited efficacy of AMX-CLV for diseases caused by E. coli outside the urinary tract.
β-lactamases remain the most common cause of resistance to penicillins11,12. β-lactam/β-lactamase inhibitor combinations, such as AMX-CLV, were developed to extend the therapeutic utility of β-lactams by counteracting β-lactamases13–15. Previous studies typically viewed TEM-1 mediated resistance as a static process arising from promoter upregulation or inhibitor-resistant TEM (IRT) substitutions16–18. In contrast, our data reveal a dynamic amplification mechanism, mediated by IS-driven translocatable units, that enables rapid shifts in gene copy number and expression without requiring stable mutations.
Loss-of-function in mutT and katE enhanced mutagenesis and oxidative imbalance, respectively, facilitate the accumulation of genetic diversity even before antibiotic challenge. Elevated ROS and SOS activation further mobilises IS elements, driving the observed blaTEM-1 amplification and structural rearrangements. Together, these events explain the rapid adaptability of TEM-1 producing E. coli (Fig. 8).
From a clinical perspective, our findings complement recent EUCAST breakpoint revisions that effectively restrict oral AMX-CLV use against E. coli to urinary tract infections9. This policy reflects the inability of systemic exposures achievable with standard regimens to meet pharmacodynamic targets required for bacterial killing. Our data provide a mechanistic rationale for this policy and underscore additional complexity introduced by resistance amplification in different tissue subcompartments.
In contrast, urinary pharmacokinetic simulations demonstrated sustained eradication of both sensitive and resistant subpopulations. This outcome was largely attributable to the direct antibacterial activity of CLV, which at high concentrations inhibits PBPs and complements the bactericidal effect of AMX. Although the intrinsic antibacterial activity of CLV has been previously recognised 19, our data demonstrate PBP1b, PBP2, and PBP5/6 binding at concentrations achievable in urine. The direct antibacterial activity of CLV explains why treatment of urinary infections with AMX-CLV often succeeds.
Isolates selected under CLV monotherapy lacked IS-mediated blaTEM-1 amplification, supporting the notion that resistance under urinary conditions arises through alternative, non-β-lactamase pathways, possibly involving PBP modification. These findings underscore that high local CLV exposure suppresses the evolutionary routes leading to β-lactamase amplification, stabilising treatment success in the urinary tract.
Beyond β-lactamase inhibition, our study highlights broader implications for resistance prevention. Targeting the underlying stress responses and transpositional activity that drive rapid adaptation could represent a new avenue for drug development. Combining β-lactamase inhibitors with compounds that limit SOS induction or inhibit transposition may help forestall the emergence of resistance. Finally, these data underscore the need for diagnostics that assess not only the presence of resistance genes but also their copy number and mobility potential, parameters that more accurately predict resistance trajectories under different pharmacokinetic environments.
Methods
Strains and reagents
All clinical isolates used in this study were obtained from a large clinical laboratory servicing the city of Liverpool, UK (Liverpool Clinical Laboratories, UK). All pure and pharmacological grade antibiotics used for MIC testing were purchased from Sigma-Aldrich (Merck, USA). Media and agar used for growth in all experiments were purchased from Merck.
In vitro susceptibility testing
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MIC testing was performed using broth microdilution assay in 96-well round-bottom plates (Corning, USA), according to EUCAST guidelines. Strains were grown in cation-adjusted Mueller-Hinton (CAMHB II) broth (Merck, USA) at a total volume of 200 µL per well. AMX was serially diluted two-fold, with the concentration of CLV fixed at 2.5 mg/L. The inoculum culture used was maintained at 105 CFU/mL. The plates were incubated at 37°C for 20–24 hours. MIC for all strains were performed in three technical replicates.Simulation of human pharmacokinetics
Plasma pharmacokinetic parameters and drug exposure profiles for orally administered AMX-CLV were derived from published data20. Replication of this drug exposure profile was simulated using HFIM-like conditions in ADAPT 5 to confirm recapitulation of the pharmacokinetic profile, before simulating in the HFIM21,22.
Urinary pharmacokinetics were predicted using physiology-based pharmacokinetic (PBPK) models built in PK-SIM® (Open Systems Pharmacology) known physical-chemical and pharmacological data for both AMX and CLV, and using available published plasma and urinary time-concentration data for both. With acceptably performing PBPK models, simulations of urinary drug concentrations following oral administrations of AMX/CLV 500/125 mg q8h, with q8h frequency micturition were simulated. Using ADAPT, drug infusion parameters were identified that approximated the rate of urinary drug accumulation in a HFIM, along with temporary high media pump settings that would approximate urinary drug clearance through micturition.
Hollow fibre infection model
The HFIM experiments were performed as previously described with minor adjustments23. Each arm of the HFIM setup is demonstrated in Supplementary figure S11. CAMHB II was continuously pumped into the central compartment at a rate to simulate the physiological clearance of both drugs. In the central compartment of the HFIM assembly, 200 mL of CAMHB II was maintained via elimination pumps. The target simulated half-lives for plasma AMX and CLV were 1.35h 20. The urinary pharmacokinetic profile was simulated by infusing drug over 4h, with an experimental half-life within the HFIM model of 1h, to replicate the urinary drug exposure profile simulated by PBPK modelling. Both drugs have negligible protein binding, so no adjustment accounting for this was needed24.
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All experiments were performed as per previously published standard HFIM experiments25. Each arm of the HFIM assay were run for up to 48–96 hours, dependent on the time we observed treatment failure, i.e. when the resistant sub-population is almost equivalent to the total population. The cartridge (Fibre-Cell Systems Inc.; Cat no: c2011) of HFIM were infected with strains at 105 CFU/mL. Each drug was administered into the central compartment every 8 hours till the end of the study. Samples were taken for bioanalysis from the central compartment during the first dosing interval, and during steady state later in the experiment to confirm predicted pharmacokinetic profiles were successfully achieved. For quantification of the total bacterial population, samples were collected from the hollow-fibre cartridge at 0, 1, 3, 6, 8, 24, 48, 72, and 96 hours (the experiment was terminated when the resistant population reached the total population level). Samples were serially diluted 1:10 in PBS, and 100 µL of each sample and its dilution were plated onto drug-free and drug-containing Mueller-Hinton Agar (MHA) plates. Drug-containing plates contain 32 mg/L AMX and 2.5 mg/L CLV.Bioanalysis
Both AMX and CLV (Cambridge Biosciences, UK) were extracted from Mueller Hinton broth and analysed using the following process. The internal standards, [13C6] AMX (Alsachim, France) and sulbactam (Cambridge Biosciences, UK) were prepared in acetonitrile (1 mg/L, Fisher Scientific UK) and 150 uL was added to a 96-well protein precipitation plate [Phenomenex, Cheshire, UK]. Fifty uL each of broth sample, blanks, calibrators in the range 0.1–25 mg/L for avibactam and 0.25–25 mg/L for CLV and quality controls (0.75, 3.75 and 12.5 mg/L) was mixed with the internal standard on a plate shaker for 5 mins at 800 rpm. Liquid was drawn through the protein precipitation plate into a collection plate using a positive pressure manifold. Samples were then dried down under nitrogen for 45 mins followed by reconstitution with water + 0.1% formic acid (150 uL). The plate was sealed and placed onto a plate shaker for 10 mins at 800 rpm before being transferred to the autosampler for analysis by LC-MS-MS.
LC-MS-MS analysis was carried out using a Waters Acquity UPLC coupled to a Waters Xevo TQXS triple quadrupole mass spectrometer fitted with an electrospray source. The LC-MS system was controlled using MassLynx Data Acquisition software (Ver 4.2). Analytes were injected (3 uL) onto a Waters Acquity UPLC HSS T3 (2.1 mm x 100 mm, 1.8 µm) and separated over a 4.5 min. gradient using a mixture of solvents A and B. Solvent A was LC-MS grade water with 0.1% (v/v) formic acid. Solvent B was LC-MS grade acetonitrile with 0.1% (v/v) formic acid. Separations were performed by applying a gradient of 5% to 95% solvent B over 3.0 mins at 0.4 mL/min followed by an equilibration step (1.5 mins at 5% solvent B).
The mass spectrometer was operated in negative ion mode using a Multiple Reaction Monitoring (MRM) method. Following an optimisation process the following mass transitions and collision energies were used for the analysis: 364.2 > 223.1 (Ce 10 ev) for AMX, 370.2 > 229.1 (Ce 12 ev) for 13C6 AMX, 198.1 > 136.1 (Ce 8ev) for CLV and 232.1 > 140.1 (Ce 12ev) for sulbactam. The resultant data were processed using TargetLynx processing software (Ver 4.2).
Population Analysis Profiling (PAP) assay
The bacterial strain was revived from a glycerol stock by streaking onto a MHA plate and incubating at 37°C overnight. A single colony was then picked and inoculated into 5 mL of Mueller-Hinton broth, incubated at 37°C with shaking at 200 rpm for 24 hours. Subsequently, 1 µL of the 24-hour culture was subcultured into 1 mL of fresh Mueller-Hinton broth and incubated under the same conditions for another 24 hours. Drug-containing MH agar plates were prepared with concentrations ranging from 0 to 256 µg/mL in twofold dilutions (e.g., 0, 2, 4, 8… 256 µg/mL). Serial dilutions of the overnight culture were prepared and plated onto both drug-free MH plates and drug-containing MH plates, which were incubated at 37°C for 24–48 hours. Colony-forming units (CFU) were counted on each plate, and the survival percentage at each drug concentration was calculated using the formula:
The resistance profile was analysed by plotting survival percentage against drug concentration.
Intracellular ROS quantification
The bacterial samples were adjusted to an OD600 of 0.2. In microcentrifuge tubes, 1 mL of bacterial samples was exposed to 100 µM DCF-DA (Invitrogen, UK) and incubated at 37°C with shaking at 200 rpm for 20 minutes. 100 µL of the sample was added to Blackwell 96-well plates (Corning, USA), and the fluorescence was measured at excitation and emission wavelengths of 485 nm and 528 nm, respectively (Thermo Scientific, Varioskan LUX, USA). The assay was done in triplicate.
Real-time qPCR
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Total RNA was extracted from bacterial cells using the standard TRIzol (Sigma-Aldrich, Cat no: 93289) protocol. Briefly, 1 µg of total RNA was used to prepare cDNA using the SuperScript III first-strand synthesis kit (NEB, UK). Real-time PCR was performed with the SYBR Green Master Mix (Applied Biosystems) according to the manufacturer’s instructions. Measurements were performed using the QuantStudio 6× real-time PCR system (Applied Biosystems) with the following conditions: 95°C for 10 min, 40 cycles of 95°C for 15 s and 60°C for 1 min, and a final dissociation cycle of 95°C for 2 min, 60°C for 15 s, and 95°C for 15 s. The primers used are 16S rRNA:=Forward primer: CTCCTACGGGAGGCAGCA; Reverse primer: GWATTACCGCGGCKGCTG TEM-1:=Forward primer: GTCCTCCGATCGTTGTCAGAA; Reverse primer: GCATCTTACGGATGGCATGA. Relative gene expression was calculated using the ΔΔCT method, with 16S rRNA as the reference gene. Experiments were performed in biological duplicates and measured in technical triplicates.TUNEL assay
The TUNEL assay was performed using the NEB Live/Dead TUNEL kit (NEB, UK) according to the manufacturer's instructions. The cells were resuspended in 1% paraformaldehyde in PBS (pH 7.4) at a concentration of 106 cells/ml and incubated on ice for 20 min. The cells were washed with PBS three times, then resuspended in 70% ice-cold ethanol and allowed to stand on ice for 30 min. For staining, the cell pellet was resuspended in 1 ml wash buffer. After two washes, the pellet was incubated in 50 µl of TUNEL reaction mixture containing FITC-dUTP and deoxynucleotidyl transferase at 37°C in the dark for 1 h. After incubation, cells were washed twice with rinse buffer and incubated with 5 mg/mL BSA. Samples were washed and then resuspended in PBS for fluorescence-activated cell sorting (FACS) analysis. The FITC signal was analysed with an excitation laser at 488 nm and a 525/15 nm bandpass filter using a Cytomaster flow cytometer (BD Biosciences) with a 70-µm nozzle. Graphs were generated using FCS 7 research edition software.
Cell Sorting
Overnight culture of E. coli B50 was treated with 0.1 mg/mL of lysozyme at 37°C for 1 hour, followed by three washes with 20% glycerol: PBS solution. Cells were incubated with 2% BSA for 20 minutes, then incubated with 1:10000 anti-mouse TEM-1 antibody (Santa Cruz Biotechnology, Cat no: sc-66062). After three washes with 20% glycerol in PBS, the cells were incubated with a 1:1000 secondary anti-mouse goat FITC-conjugated antibody (Fisher Scientific, UK). The cell suspension was passed through the ARES III Cell Sorter instrument. This experiment was repeated twice to gate cells based on low and high fluorescence. The sorted cells were serially diluted, plated onto MH agar, and incubated overnight at 37°C. Ten colonies from each group were selected and tested for MIC determination.
DNA Read Processing and Variant Detection
Raw Illumina paired-end reads were processed by the sequencing facility (Centre for Genomic Research, University of Liverpool) using a standardized whole-genome variant detection workflow. Adapter-trimmed and quality-filtered read pairs were aligned to the appropriate reference genome (E. coli MG1655) using BWA-MEM v0.7.1726. SAM/BAM alignment files were subsequently filtered with SAMtools v1.10 to remove unmapped reads, secondary and supplementary alignments, and reads with a mapping quality < 1027.
PCR duplicate reads were identified and marked using Picard Tools v2.23.3 (Broad Institute). Following duplicate removal, high confidence read alignments were subjected to variant calling using the Genome Analysis Toolkit (GATK) v4.2 28,29. Single nucleotide polymorphisms (SNPs) and small insertions/deletions (indels) were identified using the HaplotypeCaller module following GATK Best Practices.
Variants were subjected to hard filtering based on GATK recommendations to minimize false positives. For SNPs, filtering thresholds included: QD < 2.0, FS > 60.0, MQ < 40.0, SOR > 3.0, MQRankSum < − 12.5, and ReadPosRankSum < − 8.0. For indels, QD < 2.0, FS > 200.0, QUAL < 30.0, and ReadPosRankSum < − 20.0 were applied. High-confidence variants passing all filters were annotated using SnpEff v4.2 30, providing predicted functional effects on protein-coding genes.
Genome Assembly and Functional Annotation
To generate a draft genome assembly for downstream analyses, quality-filtered reads were assembled de novo using SPAdes v3.15.4 with the --isolate mode and default parameters31. Contigs < 500 bp or with < 5× coverage was removed to avoid spurious assembly.
Gene prediction and functional annotation of assembled contigs were performed using Bakta v1.8, which provides standardized annotation of protein-coding genes, RNAs, operons, and prophage-associated features32.
Detection of antimicrobial resistance (AMR) determinants and resistance-associated variants was performed using the Resistance Gene Identifier (RGI) v6.0.0 with default parameters and the CARD database (version current at analysis)33. Perfect and strict hits were retained for interpretation of resistance gene content.
Mobile Genetic Element and Insertion Sequence Detection
Insertion sequences (IS elements) and mobile genetic elements were identified using three complementary tools. ISEScan v1.7.2.3 was used for genome-wide prediction of IS families based on HMM profiles34. ISfinder was used to assign IS family identity based on nucleotide similarity35. MobileElementFinder v1.0.3 was run on assembled contigs using default parameters to annotate mobile elements, insertion sites, and associated genetic cargo36. This combined approach maximizes detection sensitivity and classification accuracy.
RNA-seq Read Processing and Differential Gene Expression Analysis
RNA sequencing libraries were processed by the facility using a reference-based transcriptomic workflow. Quality-checked reads were aligned against the corresponding reference genome (E. coli strain JE86-ST05; NCBI Reference Sequence: NZ_AP022815.1) using the splice-aware aligner HISAT2 v2.2.137. Alignment was performed using default parameters optimized for bacterial gene structures (no introns assumed).
Aligned reads were quantified using HTSeq v2.0 in stranded mode, based on gene models defined in the corresponding GFF3 annotation file38. Genes with low counts were filtered using the filterByExpr function in edgeR to remove features lacking sufficient read coverage for statistical testing39.
Differential expression analysis was performed using DESeq2 v1.34.040. Gene-wise dispersion estimates were fit using empirical Bayes shrinkage, and pairwise contrasts were evaluated using Wald tests with Benjamini-Hochberg correction for multiple comparisons. Genes with adjusted P < 0.05 and |log₂ fold change| > threshold (insert threshold used in your study) were considered differentially expressed.
PacBio HiFi Long-Read Processing and Plasmid Assembly
HiFi long-read sequencing data were processed by the Centre for Genomic Research (University of Liverpool). Circular plasmid-enriched DNA was sequenced using PacBio HiFi chemistry, and high-accuracy reads were assembled de novo using Hifiasm (v0.19.5) in HiFi mode with default parameters41. For each sample, polished contigs representing plasmid candidates were retained for downstream analysis. Samples that did not generate any Hifiasm contigs (19.3_3 and 25.8_8) were excluded.
Clustering of Parental Plasmid Contigs
To establish a non-redundant parental plasmid reference, Hifiasm-assembled contigs from the three untreated parental samples (Set 1–3) were clustered using CD-HIT (v4.8.1) with default nucleotide settings42. This produced a representative set of “parental plasmid contigs” used as the baseline for all comparative analyses.
Identification of Closest Reference Plasmids (PLSDB Search)
Representative parental contigs were compared against the PLSDB plasmid database using MASH (v2.3) with sketching parameters p = 0.1 and d = 0.143. For each contig, the closest high-identity PLSDB plasmid was identified and its corresponding FASTA sequence downloaded. These sequences served as “PLSDB parent references” for structural variant (SV) detection against known plasmid backbones.
Long-Read Structural Variant Detection
SV detection was performed using complementary long-read callers, pbsv (PacBio), following standard long-read SV calling workflows44. Three levels of comparison were performed: Parent vs PLSDB reference; Parent plasmid contigs were aligned to their closest PLSDB plasmid using minimap2 (v2.26), and SVs were identified using pbsv to define baseline plasmid structure45. Derived (resistant) vs PLSDB reference; Derived-sample plasmid contigs were aligned against the same PLSDB references to detect SVs associated with antibiotic-selected evolution. Derived vs clustered parental contigs (direct comparison); To identify de novo structural changes emerging under selection, contigs from derived samples were aligned directly against the clustered parental contigs. SV calling in this comparison captured insertions, deletions, rearrangements, duplications, and cassette movements relative to the ancestral plasmid background. The output for each comparison included: BAM alignments, FASTA/FAI references, VCF files of SVs (importable into IGV). VCF files with no records indicated that no structural variants were detected.
Identification of Rare and Horizontally Acquired Plasmids
To identify low-abundance plasmid elements potentially acquired during evolution, contigs were screened using a distance vs coverage approach. MASH distance was plotted against read depth; contigs with distance < 0.1 but coverage ≤ 30× were classified as high-identity, low-copy plasmids. Unique rare plasmid contigs were summarised (94 total).
Data Availability and Reproducibility
All software versions, parameter settings, and reference genomes used in this study are explicitly described above to ensure computational reproducibility. These files can be deposited in ENA/SRA upon manuscript acceptance.
Analysis of blaTEM-1 Genetic Context Diversity
The genomic environments surrounding blaTEM-1 were analysed to determine whether the observed diversity of insertion sequence (IS) arrangements deviated from random expectation. For each contig containing blaTEM-1, flanking IS elements were identified using outputs from ISEScan, ISFinder, and MobileElementFinder, and their genomic coordinates were parsed to reconstruct ordered gene contexts (e.g., IS26-blaTEM-1-IS1), retaining relative orientation and adjacency.
To quantify empirical context diversity, a bootstrap-based sampling approach was applied. Let N denote the total number of blaTEM-1-containing contigs. For each sampling depth n ∈ [1, N], n contexts were sampled with replacement, and the number of unique structural contexts was recorded. This procedure was repeated 100 times per n to generate bootstrap estimates of diversity accumulation curves.
A null model was generated to evaluate whether observed diversity exceeded expectations under independent IS insertions. Valid IS-blaTEM-1 arrangements were simulated combinatorially, allowing each IS family to appear at most once on either side of blaTEM-1, with symmetric wrapping permitted only where biologically plausible. As with the empirical model, n simulated contexts were sampled with replacement across 100 bootstrap replicates to obtain a null distribution of expected diversity.
Median and interquartile ranges from both empirical and null models were compared to assess whether the structural diversity observed in the dataset was greater than expected under independent IS insertion dynamics. All scripts used to perform these simulations are available at: https://github.com/agerada/tem-1-bootstrap.
Checkerboard assays
Checkerboard assays were performed to assess the interaction between AMX and CLV over a two-dimensional concentration range. AMX and CLV stock solutions were freshly prepared in sterile DMSO and water (filter-sterilised (0.22 µm)(Millex-CV)). Two-fold serial dilutions of each compound were prepared in CAMHB II to generate working solutions spanning the concentration range for each isolate in 100 µL. For plate preparation, AMX dilutions were dispensed horizontally across 96-well microtiter plates, while CLV dilutions were dispensed vertically, creating a two-dimensional matrix of drug combinations. Growth-control wells (no drug) and sterility controls (no inoculum) were included on every plate. Bacterial isolates were grown overnight at 37°C with shaking at 200 rpm in 10 mL CAMHB II. Saturated cultures were diluted 1:10,000 into fresh CAMHB II and incubated to an OD₆₀₀ of ~ 0.4 (mid-log phase). Cultures were subsequently diluted to 10⁵ CFU/mL in CAMHB II, and 100 µL of this inoculum was added to each well of the prepared plates. Plates were incubated statically at 37°C for 16 h.
Competitive Bocillin Binding Assay
Cultures were grown in lysogeny broth (LB) at 37°C with shaking until an optical density at 600 nm of approximately 1.0 was reached, rapidly chilled on ice, and pelleted by centrifugation (5,000 × g, 10 min, 4°C) (Eppendorf 5425R). Cell pellets were resuspended in phosphate-buffered saline (PBS, pH 7.5) and treated sequentially with lysozyme (400 µg mL⁻¹, 1 h, 37°C) and a nuclease mixture containing DNase I and RNase A (10 µg mL⁻¹ each) together with an EDTA-free protease inhibitor cocktail. Cells were disrupted using a French pressure cell (Constant System Ltd), and unbroken debris was removed by centrifugation at 12,000 × g for 10 min at 4°C. Membranes were collected from the supernatant by ultracentrifugation (Thermo Scientific Sorval MTX 150) at 150,000 × g for 40 min at 4°C, resuspended in PBS (300–500 µL), aliquoted, and stored at -80°C. Protein concentration was determined using a BCA assay (Pierce BCA Protein assay kit, Thermo Scientific) with bovine serum albumin standards. For Bocillin FL binding, 17 µg of membrane protein was incubated in PBS (20 µL final volume) with test compounds for 10 min at 30°C, followed by the addition of Bocillin FL (Thermo Fisher) (12.5 µM final) and further incubation for 20 min at 30°C. Reactions were quenched with Laemmli buffer containing freshly added DTT and heated at 95°C for 3 min before SDS-PAGE. Fluorescently labelled PBPs were visualised using a ChemiDoc gel imager (Bio-rad) with ProQ-Emerald 488 settings, and total protein was optionally verified by Coomassie staining. Reactions lacking Bocillin FL served as fluorescence controls, those lacking competitor antibiotics defined maximal labelling, and meropenem was used as a positive control to validate expected PBP-binding profiles. Band-intensity comparisons across conditions quantified the competitive inhibition of Bocillin FL binding by AMX and CLV.
Western Blotting
Bacterial cultures were grown in lysogeny broth (LB) to mid-log phase (O.D.₆₀₀ ≈ 1.0) and harvested by centrifugation (5,000 × g, 10 min, 4°C). Cell pellets were resuspended in PBS, (pH 7.4) containing an EDTA-free protease inhibitor cocktail (Roche Diagnostic, Germany) and lysed by sonication on ice. Lysates were clarified by centrifugation (12,000 × g, 10 min, 4°C), and total protein concentrations were determined using a BCA assay with bovine serum albumin standards. Equal amounts of protein (typically 50 µg per lane) were mixed with Laemmli sample buffer containing DTT, heated at 95°C for 5 min, and resolved by SDS–PAGE on 12% polyacrylamide gels. Proteins were transferred to nitrocellulose membranes (Amersham; Cat no.: 10600002) (0.45 µm pore size) using a wet-transfer apparatus (100 V, 1 h, 4°C). Membranes were blocked for 1 h at room temperature in 5% (w/v) skimmed milk in Tris-buffered saline containing 0.1% Tween-20 (TBST) and incubated overnight at 4°C with mouse polyclonal anti-TEM-1 antibody (1:5,000 dilution in TBST + 1% milk). After three washes in TBST, membranes were incubated with horseradish-peroxidase-conjugated goat anti-mouse IgG secondary antibody (Thermo Fisher Scientific) (1:10,000, 1 h, room temperature). Bands were visualised using enhanced chemiluminescence (ECL) substrate (Amersham) and imaged with a digital chemiluminescence detection system.
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Acknowledgement
This study was supported, in part, by Wellcome Trust funded CAMO-NET grant [Grant number: 226691/Z/22/Z]. Liverpool Clinical Laboratories provided the bacterial strains used in this study. The authors would like to thank Valerie Price for helping with strain retrieval. CD was funded to conduct this work by the National Institute for Healthcare Research (Award Ref. CL-2022-07-001). We thank Dr. Philip Brownridge and Dr. Christopher Ka Sin Law from University of Liverpool, UK for technical support.
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Conflict of InterestW.H. holds, or has recently held, research grants with UKRI, EU (FP7, IMI-1, and IMI-2), Wellcome, F2G, and Global Antimicrobial Research and Development Partnership (GARDP). He is a consultant for GSK, Basilea and Biosergen.
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He was a member of the Specialist Advisory Committee for GARDP (2020–2023), a member of the British Society for Antimicrobial Chemotherapy Breakpoint Committee (2020–2023), a member of Health Technology Appraisal Prioritisation Committee for hospital care, and the Specialty National Co-lead for Infection for the National Institute of Health Research (2020–2024). A.H. declares personal consulting work for Pfizer outside the submitted work, and a donation from Pfizer to the University of Liverpool for a public and professional engagement project outside the submitted work.Supplementary Material:
Electronic Supplementary Material
Below is the link to the electronic supplementary material
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Table 1. Minimum inhibitory concentration of AMX and AMX-CLV combination and AMR genes in UTI E. coli clinical isolates.
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Fig. 1
Plasma pharmacokinetic simulations reveal rapid resistance emergence in TEM-1 producing E. coli isolates. HFIM experiments simulating human plasma pharmacokinetics of AMX and CLV. Black lines indicate total bacterial counts (log₁₀ CFU /mL); orange dashed lines represent resistant subpopulations detected on AMX-CLV supplemented plates. Top row: E. coli B50 exposed to AMX-CLV at 500 mg and 125 mg or 1000 mg and 125 mg shows an initial bactericidal effect followed by regrowth within 24–48 h, consistent with selection of resistant subpopulations. Middle row: E. coli K35 exhibited similar kinetics, with transient killing followed by recovery of resistant colonies despite dose escalation. Bottom row: E. coli K67 displayed early growth suppression followed by rapid rebound, confirming that treatment failure arises across distinct TEM-1/SHV-1 expressing lineages.
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Fig. 2
Pre-existing resistant subpopulations with high blaTEM-1 expression drive treatment failure under AMX-CLV exposure. A. Intracellular reactive oxygen species (ROS) levels in E. coli B50 increased significantly after exposure to plasma PK profiles of AMX-CLV 500 mg + 125 mg for 24 h and 48 h compared with untreated controls (UT), as measured by DCF-DA fluorescence (mean ± s.d., n = 6; P < 0.01, Student’s t-test). B. Quantitative RT-PCR confirmed that resistant cells expressed blaTEM-1 at markedly higher levels than sensitive cells (mean ± s.d., n = 8; **P < 0.0001, unpaired two-tailed t-test). D. Flow cytometry of antibody-labelled spheroplasts demonstrated two distinct subpopulations with high or low TEM-1 abundance, and subsequent cell sorting showed that low-FITC cells exhibited MICs of 4–8 mg/L, whereas high-FITC cells exhibited MICs of 64–128 mg/L. E. Population analysis profiles of E. coli B50, K35, and K67 further revealed heterogeneous resistance, with resistant fractions persisting across a wide range of AMX concentrations (0.5–256 mg/L) in the presence of a fixed CLV concentration (2.5 mg/L), consistent with the selection of pre-existing resistant subpopulations that ultimately undermine treatment efficacy. Blue and red dashed lines are MIC for strain and EUCAST breakpoint for AMX-CLV, respectively.
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Fig. 3
Transcriptomic and genomic alterations distinguish resistant from sensitive subpopulations. A. Differential RNA-seq analysis comparing resistant and sensitive E. coli subpopulations revealed transcriptional upregulation of stress and mobility-associated genes, including blaTEM-1, recA, and IS-family transposases, alongside downregulation of multiple core metabolic pathways. B. Whole-genome sequencing of resistant isolates identified high-impact mutations such as stop codon loss and frameshifts, moderate-impact nonsynonymous SNPs, and low-impact upstream changes, distributed across genes involved in DNA repair, oxidative stress defence, metabolism, and regulatory functions. Visualisation of mutation frequency across functional categories shows resistant isolates are enriched for mutations in stress adaptation and genome plasticity pathways. Count represents how many unique variant sites we found in that gene that are present in the resistant mutants and absent in the ancestral isolates.
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Fig. 4
Increasing AMX-CLV exposure delays but does not prevent resistance expansion. HFIM experiments simulating human plasma pharmacokinetics of AMX and CLV against E. coli strain B50 producing TEM-1 β-lactamase. Each plot shows bacterial population dynamics (log₁₀ CFU/mL) over time under varying dose and infusion regimens. Black lines denote total bacterial counts; orange dashed lines indicate resistant subpopulations detected on AMX-CLV supplemented plates. Top row: Untreated control, AMX monotherapy (500 mg) and infusion of AMX 40 mg/L show uncontrolled bacterial growth. Second row: Infusion of AMX 80 and 160 mg/L shows uncontrolled bacterial growth. Third row: Increasing CLV concentrations (1–5 mg/L) with fixed AMX exposure initially enhanced killing but failed to prevent regrowth by 48 h, indicating that higher CLV exposure alone is insufficient to suppress resistance. Bottom row: Combined AMX-CLV regimens (40–160 mg/L AMX; 125 mg CLV) delayed but did not prevent re-emergence of resistant subpopulations, even at exposures exceeding clinically achievable plasma concentrations.
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Fig. 5
Amplification and structural remodelling of blaTEM-1 in resistant subpopulations. (A) qPCR analysis of blaTEM-1 expression in resistant colonies recovered from dose-optimisation experiments shows significantly elevated transcript levels compared with untreated controls (mean ± s.d.; n = 8; P < 0.01-0.0001). (B) Quantification of extrachromosomal blaTEM-1 copy number in sensitive (n = 3) versus resistant isolates (n = 7), demonstrating increased copy number in resistant subpopulations. (C) Circular mapping of the immediate genetic neighbourhood of blaTEM-1 in sensitive (orange) and resistant (blue) isolates, highlighting diversification of insertion sequence (IS) boundaries around blaTEM-1. (D) Distribution of IS families and their genomic positions relative to coding sequences (CDS), upstream, downstream, or multiple contexts in sensitive and resistant isolates. (E) Rarefaction analysis comparing the observed diversity of blaTEM-1 contexts (blue line) with a null model assuming independent IS family insertions (red line) and the theoretical upper bound (dashed line), showing that resistant isolates are constrained to a limited repertoire of TU architectures.
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Fig. 6
IS-mediated remodelling of blaTEM-1 transposition units. In sensitive isolates, blaTEM-1 is flanked by IS26/IS1 and Tn2/3. Under drug pressure, IS26-driven target conservation capture expands copy number, while IS1 insertions and recombination prune or replace TU boundaries. These processes generate the limited set of TU architectures observed in resistant isolates.
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Fig. 7
Urinary pharmacokinetic simulations reveal sustained bacterial clearance and distinct resistance mechanisms under high AMX-CLV exposure. A. Time-kill curves from HFIM simulations mimicking urinary pharmacokinetics of AMX and CLV. Black lines denote total bacterial counts (CFU/mL); orange lines represent resistant subpopulations detected on AMX-CLV supplemented plates. AMX monotherapy allowed regrowth of resistant subclones, CLV alone produced transient killing followed by regrowth, and the AMX–CLV combination achieved complete sterilisation without resistance emergence. B. Checkerboard assays showing inhibition profiles of resistant isolates spanning AMX-CLV MICs of 4-256 mg/L. Synergistic inhibition was observed across combinations, while very high CLV concentrations alone achieved bactericidal activity, consistent with the intrinsic antibacterial effects of CLV at urinary exposure levels. C. Competitive bocillin-binding assay demonstrating concentration-dependent binding of CLV to PBPs 1b, 2, and 5/6 at ≥ 40 mg/L. Meropenem (MERO) served as a positive control for PBP binding. D. Circular mapping of insertion sequence (IS) family distributions flanking blaTEM-1 in untreated (orange) and CLV-selected (purple) isolates. CLV-selected isolates lacked the expanded IS-mediated transposition unit architectures characteristic of AMX-CLV selected resistant populations. E. Relative abundance of IS families (IS26, IS21, IS1, IS6) across genomic contexts in sensitive and resistant isolates, illustrating reduced IS diversification under CLV selection alone. F. Checkerboard analysis of CLV-selected isolates (MIC 1 mg/L) showing susceptibility to AMX-CLV combination therapy despite partial tolerance to CLV monotherapy. G. Western blot quantification of TEM-1 protein expression in sensitive, AMX-CLV selected resistant, and CLV-selected isolates. CLV-selected isolates displayed basal TEM-1 levels comparable to sensitive controls, confirming that resistance under CLV monotherapy is independent of β-lactamase overproduction.
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Fig. 8
Schematic overview of plasma PK vs urine PK of AMX/CLV: Plasma pharmacokinetics of AMX/CLV selects pre-existing resistant E. coli subpopulations. Genomic defects (katE and mutT loss-of-function) drive ROS accumulation and hypermutation, leading to activation of the SOS response and IS-mediated amplification of the TEM-1 copy number. Elevated β-lactamase production facilitates resistance despite systemic therapy. However, urinary drug concentrations enable AMX/CLV to target susceptible and low-level resistant cells, mediating bacterial clearance.
