Robust antibiotic sensitization of pathogenic Pseudomonas aeruginosa via negative hysteresis in the cell envelope

Domain: biology
Published: 2026-03-26
Editorial outcome: major_revision

Abstract
Antibiotic combination in time and space is a key strategy to combat antimicrobial resistance. The success of such treatment designs requires their robust efficacy across treatment conditions and a pathogen's genomic diversity. This study found that an initial treatment with a β-lactam antibiotic causes robust cellular sensitization towards an aminoglycoside antibiotic across the high-risk human pathogen Pseudomonas aeruginosa, including resistant strains. This phenomenon of cellular sensitization, termed negative hysteresis, is modulated by the Cpx envelope stress response system and linked to membrane stress during growth. The increase in efficacy is achieved through a β-lactam induced elevated cellular uptake of the subsequently administered aminoglycoside. Negative hysteresis and the Cpx system are linked in several cases to the expression of synergistic drug interactions, thus enhancing efficacy of antibiotic combinations. Overall, our study identifies the phenomenon of negative hysteresis as a robustly inducible phenotype and thus a unique focus for optimizing antimicrobial therapy.

Introduction
Antimicrobial resistance (AMR) has become a major threat to human health (1–3). It was associated with 4.95 million deaths and directly accounted for 1.27 million deaths in 2019, while future projections suggest a further spread of AMR and an increase in mortality especially among the elderly (2, 3). Pseudomonas aeruginosa is a particularly problematic opportunistic human pathogen in this context (2, 3). It causes acute and chronic infections in hospitalized and immunocompromised patients and is a common pathogenic resident of the respiratory tract in patients with cystic fibrosis (CF) or chronic obstructive pulmonary disease (COPD). Due to the bacterium’s high intrinsic resistance and the ability to rapidly adapt to new conditions (e.g., newly administered drugs), treating P. aeruginosa infections has become challenging (1, 4–6). The World Health Organization (WHO) has thus listed P. aeruginosa as a high priority pathogen (7), for which new treatment options are urgently required. In addition to the costly and time-consuming development of new antimicrobials, multi-drug designs show particular promise as a sustainable counter to AMR, using either simultaneous or sequential application of antimicrobial drugs (1, 8–11).

Sequential therapy has previously been shown to be effective against P. aeruginosa through independent in vitro studies (12–18). One reason for its efficacy is negative cellular hysteresis, where exposure to one antibiotic sensitizes bacterial cells to the subsequently administered antibiotic upon drug switches (12). Hysteresis describes the interactions of antibiotics across time and treatment sequence. In contrast to the interaction profile in a combination treatment where two antibiotics are simultaneously present and may co-induce sensitivity mechanisms, sensitization in a sequential treatment may depend on the specific order of the antibiotics. In particular, one direction of an antibiotic switch may lead to sensitization (i.e., negative hysteresis) while the opposite direction could result in a protective effect (i.e., positive hysteresis) (19). The possible directionality of drug interactions across antibiotic switches was first described in E. coli in 1962 (20), but has since been lost from focus. Only recently has the effect gained new attention, with the discovery of directional and bidirectional negative hysteresis among common antibiotics in P. aeruginosa (12, 13). Generally, many synergies are driven by just one antibiotic of the combination pair, facilitating the activity of the other (21). Therefore, directional, temporal hysteresis interactions, while understudied, are generally expected, and their presence is at least indicated in several pathogens that had been subjected to some form of antibiotic switching (22–24). Negative hysteresis and antibiotic synergy are both caused by physiological stress of bacterial cells. They are thus clearly distinct from collateral sensitivity, where increased sensitivity towards a particular antibiotic has an acquired genetic basis and results from the earlier evolution of resistance towards another antibiotic by mutation or gain of a mobile element (12, 19). In addition, although hysteresis and drug interaction type are related, they are also distinct from one another, because hysteresis effects decay with time post induction when the inducing antibiotic is not present throughout. Despite this transience, negative hysteresis was found to increase bacterial extinction, constrain bacterial adaptation rates as well as reduce resistance evolution during a laboratory-based evolution experiment (12). However, the previous study was focused on a single strain of P. aeruginosa (i.e., the laboratory strain PA14), few drugs (carbenicillin, gentamicin, ciprofloxacin), a narrow concentration space (a 75% inhibitory concentration, IC75), and it implicated a single mutation in the P. aeruginosa gene cpxS, which is part of the Cpx cell envelope stress response system, in contributing to hysteresis (12). Therefore, to date, critical information for the general understanding of this phenomenon as well as its utilization for antibiotic therapy is missing, in particular regarding (i) which antibiotics and switching directions allow for optimal sensitization, (ii) how robust is negative hysteresis across the strain diversity known for P. aeruginosa, (iii) is antibiotic sensitization possible against resistant strains and diverse pathogen populations, and (iv) which role does the Cpx envelope stress response system play in sensitization?

Our study’s overall objective is to establish a fundamental understanding of antibiotic sensitization via negative hysteresis. Thus, to address the current knowledge gaps, we (i) systematically characterized the conditions needed for antibiotic-induced cellular sensitization, (ii) inferred the presence, directionality, and robustness of hysteresis across antibiotics (including distinct β-lactam, fluoroquinolone, and aminoglycoside drugs), and also across the genomic diversity of P. aeruginosa, using the representative major P. aeruginosa clone type (mPact) panel (25–27), single-drug resistant populations (28), and diverse, newly isolated patient populations, and (iii) dissected the underlying mechanism by combining transcriptomics, a functional genetic analysis, and physiological characterizations of the Cpx envelope stress response system. Our results highlight the robust induction of negative hysteresis across P. aeruginosa, especially upon switches from β-lactam drugs to aminoglycosides, and additionally demonstrate a central involvement of the Cpx system in mediating cellular sensitization.

Results
Negative hysteresis is robustly induced in the laboratory strain PA14 upon switches from carbenicillin to gentamicin

We performed a thorough characterization of antibiotic sensitization in PA14, using the β-lactam antibiotics carbenicillin (CAR) and the aminoglycoside gentamicin (GEN). Hysteresis time-kill experiments were performed with varying antibiotic concentrations, switch orders, pre-treatment durations, and durations of the gap between pre- and main treatment (Fig. 1A). To characterize the dose dependency of hysteresis, we initially conducted experiments with a single well-growing culture across a wider range of concentrations (Supplementary Fig. S1A-C) and then validated our observations for selected conditions using repeat experiments (Fig. 1B-D). We found that concentrations below the minimal inhibitory concentration (i.e., sub-MIC concentrations) of the sensitizing drug CAR were sufficient to induce negative hysteresis and that the effect increased gradually with increasing CAR concentration (Fig. 1B, Supplementary Fig. S1B). Doubling the GEN concentration led to a saturation of bacterial killing independent of the pre-treatment concentration (Supplementary Fig. S1B). The increased killing of CAR pre-treated bacteria was not fully explained by the bacteria having spent more time under antibiotic treatment, as pre-treatment with GEN did not increase killing under GEN main treatment to the same degree as CAR pre-treatment (Fig. 1C, Supplementary Fig. S1A). When the order of drugs was reversed (i.e. pre-treatment with GEN, main treatment with CAR), killing was only observed for above MIC pre-treatment concentrations (Fig. 1D, Supplementary Fig. S1C). These findings confirmed the previously described sensitization of CAR pre-treated cells towards GEN and the directionality of the hysteresis effect (12). Negative hysteresis was distinct from the post-antibiotic effect (29) as cells that received CAR pre-treatment behaved similarly to the no-drug control once the antibiotic was removed (Supplementary Fig. S2A, statistical results in Table S1). Removal of possible residual pre-treatment antibiotic by two consecutive washes with phosphate buffered saline did not abolish a significant hysteresis effect (Supplementary Fig. S2B, statistical results in Table S2), consistent with negligible carry-over of unbound CAR into the main treatment. Covalently bound CAR and/or any CAR-induced changes in cellular physiology are thus likely to be sufficient for hysteresis. In addition, negative CAR-GEN hysteresis required actively growing cells since there was no hysteresis effect for bacteria that were growth arrested by strong chloramphenicol treatment that blocks new protein synthesis (Fig. 1E). At a pre-treatment concentration of 400 mg/L (4 x MIC), CAR exposure for 1 min was sufficient to induce negative hysteresis (Fig. 1F). Increasing the pre-treatment duration increased the hysteresis effect in the main treatment, consistent with the accumulation of CAR-induced cellular damage.

To address how long the CAR priming effect lasts, we varied the time during which the bacteria were allowed to grow in antibiotic-free medium between the pre- and main treatment (Fig. 1G). After approximately one generation of growth (≈ 45 min), the hysteresis effect started to vanish, and it more or less disappeared after a pause of 80 min (nearly 2 generations of growth). A possible explanation for this result might be a physiological reset of the CAR-stressed cell envelope after cell division.

Negative hysteresis is induced by pre-treatment with diverse β-lactam drugs and further contributes to the synergism of antibiotic combinations

Next, we assessed which kind of antibiotic switches lead to negative hysteresis, using all possible bidirectional combinations of several clinically used antibiotics, including three β-lactams from different sub-classes (i.e., the carbapenem meropenem (MER); the penicillin antibiotic piperacillin combined with the β-lactamase inhibitor tazobactam (PIT); the cephalosporin ceftazidime (CTZ), the fluoroquinolone ciprofloxacin (CIP), and the aminoglycoside GEN. The results with standardized dosage are summarized in Fig. 2A as a heatmap, showing the mean difference in area under the curve (ΔAUC) of the time-kill curves between the hysteresis treatment (i.e., with a pre-treatment) versus the control treatment, and for all combinations, including a total of 120 time-kill curves. We found that β-lactam pre-treatment robustly induced negative hysteresis when followed by GEN (Fig. 2A). As with CAR, the observed strong negative hysteresis occurred across a wide range of subinhibitory and inhibitory β-lactam pre-treatment concentrations in a dose-dependent manner (Supplementary Fig. S1D-I with extended dosage analysis). Consistent with previous work (12), the reverse switch from GEN to the β-lactams resulted in positive hysteresis (Supplementary Fig. S1D-I). Switches between CIP and GEN produced mild positive hysteresis when CIP was first and strong positive hysteresis when CIP was second. There was weak negative hysteresis for the switches from β-lactams to CIP, and mild varied responses in the reverse direction. Moreover, a switch between two β-lactams produced one case of negative hysteresis (i.e., PIT followed by CTZ) and otherwise positive hysteresis to varying degrees. These results highlight that even switches between two similarly acting drugs may cause negative hysteresis, as previously seen for other β-lactam drugs in P. aeruginosa (13).

In contrast to laboratory conditions where separation of pre- and main treatment is possible, medical implementation of a hysteresis approach would always have a phase where both drugs overlap due to pharmacokinetic processes, possibly resulting in drug interactions. Therefore, we assessed a possible effect of hysteresis on drug interactions and found that some drug pairs with strong negative hysteresis clearly enhanced each other’s effect while applied simultaneously (i.e., synergistic interaction, for example for GEN-PIP or GEN-CTZ; Fig. 2B), while some with strong positive hysteresis showed an additive interaction (especially GEN-CIP; Fig. 2B). In spite of these examples, other tested drug pairs do not indicate a direct translation of hysteresis effects into drug interactions (e.g., CTZ-MER; Fig. 2B), suggesting that these two phenomena can be mediated by the same molecular mechanisms, as proposed before (19), but that they can also be clearly distinct.

Negative hysteresis is robustly induced across P. aeruginosa strains and populations

The efficient utilization of negative hysteresis as a focus for antibiotic therapy requires that it is robustly expressed across diverse strains of the pathogen. To assess such robustness for clinical antibiotics across a wide panel of strains, we developed a high-throughput OD-based hysteresis screening assay with the five clinically relevant antibiotics MER, PIT, CTZ, GEN, and CIP (Supplementary Fig. S3; Supplementary Data 1 and 2). In our screen we included two reference strains PA14 (30) and PAO1 (31), the mPact panel covering the genomic diversity of P. aeruginosa (25–27), several highly resistant strains from a previous evolution experiment (28), and also diverse P. aeruginosa populations newly isolated from COPD patients, thereby yielding a total of around 3.4 million data points and the growth kinetics of over 68,000 cell populations. To account for variation in baseline susceptibility, we adjusted treatment dose to the MIC of each tested sample. By including our PA14 reference strain, we were able to validate the sensitivity of our approach to detect both negative hysteresis upon switches from either β-lactams or CIP to GEN and also positive hysteresis for the reverse switches (Fig. 3A and Supplementary Fig. S4, (12)), thus indicating that our OD-based screen generates data consistent with the CFU-based assays (Fig. 2A, (12)). A Spearman correlation analysis of the CFU to OD relationship using paired data points across the CFU-based hysteresis experiments supported a robust monotonic relationship across pre-treatment antibiotics (Supplementary Fig. S5). Consistent with the induction of cell filamentation and slow lysis by β-lactam antibiotics, β-lactam main treatments produced OD values that were higher and more variable than expected from the number of live cells. However, the obtained paired CFU counts and OD values still showed a significant positive correlation (rho ≥ 0.39, P ≤ 0.0056; Supplementary Fig. S5). Importantly, the potential confounding factors of OD, such as antibiotic induced cell filamentation or cell death without lysis, are more likely to lead to an underestimation of negative hysteresis (i.e., OD values after pre-treatment are higher than expected from the number of alive cells due to presence of dead cells or filamentation, incorrectly suggesting low cell killing) and an overestimation of positive hysteresis. Therefore, following this reasoning, we consider the OD-based hysteresis screen to provide a conservative indication for the occurrence of negative hysteresis and a potentially biased indication of positive hysteresis, especially when β-lactam antibiotics were used for the main treatment. Accordingly, we focused our following evaluation of the screen’s results on the cases showing negative hysteresis.

Our screen of the mPact panel now revealed 121 significant hysteresis cases across the 412 tested antibiotic switches. Most hysteresis was negative, 81/121, and often associated with a switch from a β-lactam to GEN (Fig. 3A; Supplementary Fig. S4; statistical results in Supplementary Data 3). Importantly, the hysteresis response was not contingent on the strain background and included both strains of clinical and environmental origin (strains H01-H08, H10-H14, and the reference strains PA14 and PA01 are of clinical origin; Supplementary Table S3). These results point to a conserved cellular response mechanism that applies to both clinical and non-clinical strain backgrounds. None of the other switch types produced a similarly robust hysteresis phenotype, suggesting that the other cases of negative hysteresis (Fig. 2A) are mediated through mechanisms that vary across genotypes. Therefore, we focused our subsequent analyses on switches between β-lactams and GEN.

As a next step, we characterized hysteresis in strains resistant to the main treatment antibiotic, the pre-treatment antibiotic, or an unrelated antibiotic. We took advantage of evolved PA14 strains available from a previous evolution experiment (28) that had evolved high resistance against either GEN, CIP, PIT, or cefsulodin (CEF). Based on our screening assay, we found that 8/10 PIT resistant clones showed negative hysteresis at least once (β-lactam followed by GEN) (Fig. 3B; Supplementary Fig. S4; statistical results in Supplementary Data 3). Strains resistant to the cephalosporin CEF showed no negative hysteresis (Fig. 3B; statistical results in Supplementary Data 3), those resistant to CIP showed negative hysteresis in 2/3 cases (Fig. 3C; statistical results in Supplementary Data 3), while the GEN-resistant strains only showed negative hysteresis in a single case (Fig. 3C; Supplementary Fig. S4; statistical results in Supplementary Data 3). Overall, these results indicate that with MIC-adjusted pre-treatments, negative hysteresis is induced in a number of antibiotic-resistant strains, in particular those expressing resistance to the sensitizing pre-treatment antibiotic.

Recognizing that chronic P. aeruginosa infections in patients may involve several genotypes (32, 33), we further examined hysteresis in diverse P. aeruginosa populations, where the strains of each population had been isolated from sputum samples of individual COPD patients. We reconstructed six mixed-strains P. aeruginosa populations from four patients (two patients produced positive sampling cultures on different days). The individual patient isolates were initially cultured separately and then combined at equal ratios to reconstruct each respective within-patient population, with each population comprising 8-14 phenotypic isolates. When each was subjected to the hysteresis assay, we found that two of the reconstructed populations showed significant negative hysteresis upon switches from CTZ to GEN. Most switches increased treatment efficacy, none were inhibitory (i.e., there were no cases of positive hysteresis; Fig. 3D; Supplementary Fig. S4; statistical results in Supplementary Data 3). These proof-of-concept findings indicate that negative hysteresis is inducible in a diverse pathogen population, representative of chronic infections.

The Cpx envelope stress response system contributes to antibiotic-induced negative hysteresis

Next, we examined which molecular mechanism(s) underpin negative hysteresis. Considering the previous implication of a particular cpxS mutation in hysteresis (12), we focused our analysis on the Cpx (conjugative pilus expression) two-component, envelope stress response system and its involvement in the β-lactam-induced sensitization of bacterial cells. The Cpx system is well characterized in Escherichia coli, where it regulates inner membrane integrity and efflux pumps (34, 35), influences the susceptibility towards β-lactams and aminoglycosides (36–39), and mediates expression of virulence factors, the latter additionally shown for other Gram-negative bacteria (reviewed in (40)). The distinct Cpx system of P. aeruginosa is currently getting increasing attention (41–44). The left panel of Fig. 4A illustrates the P. aeruginosa Cpx system, highlighting the structural differences in the sensor histidine kinase CpxS with the E. coli CpxA kinase (12). In detail, while the signaling domain (HAMP) and catalytic domains (DHp and CA) superimpose well (Supplementary Fig. S6), the CpxS sensory domain (residues 8-148) is clearly distinct from that of E. coli CpxA. Thus, we used the sensory domain of AbfS, a sensory histidine kinase from Cellvibrio japonicus (PTDB ID: 2VA0) (45), as an alternative template for structural modeling of the sensory domain (right panel, Fig. 4A). In analogy with the Cpx system of E. coli, we assume that in P. aeruginosa, various stressors induce autophosphorylation of CpxS, which in turn phosphorylates the transcription factor CpxR. CpxR should activate – among others – CpxP, which itself should inhibit CpxS in a negative feedback mechanism. Based on this model, we generated mutants for different components of the Cpx system.

As a first step, we re-assessed the previously identified contribution of the specific CpxS T163P mutation to negative hysteresis (12) and confirmed that the mutation consistently abrogated the CAR-mediated sensitization of cells towards GEN in pure and mixed cultures with different ratios of the mutant and wildtype (Fig. 4B; Supplementary Fig. S7). Thereafter, we characterized scar-free deletion mutants of the three Cpx system genes (cpxS, cpxR, cpxP) and two additional cpxS mutants with specific mutations (CpxS DES81-83G and CpxS G188S) originally observed in the previous evolution experiment (12). We always used mutant-adjusted antibiotic concentrations for the hysteresis treatment (0.5 MIC for CAR pre-treatment, 1 MIC for GEN main treatment; Supplementary Table S4) and included PA14 wildtype (WT) as positive and CpxS T163P as negative controls. The results are summarized in Fig. 4C as a heatmap, inferred as above via the ΔAUC between the hysteresis and control treatments (each heatmap tile represents the data of at least six time-kill curves). We found that deletion of cpxR abrogated the WT hysteresis phenotype, whereas deletion of cpxS and cpxP did not (Supplementary Fig. S8A; statistical results in Supplementary Table S5). The three considered cpxS mutations (T163P, DES81-83G, G188S) consistently abolished the hysteresis phenotype present in the ΔcpxS mutant and WT, suggesting that they are CpxS gain-of-function mutants. These gain-of-functions are likely mediated by an increased activity of CpxS. This idea was confirmed by analysis of additional mutants with an inducible CpxS overexpression system in WT as well as cpxS deletion background, for which the induced overexpression of CpxS led to a loss of significant negative hysteresis (Fig. 4D; Supplementary Fig. S8B; statistical results in Supplementary Table S5). Moreover, we found that the loss of negative hysteresis in the CpxS T163P mutant was associated with a significant change of drug interaction profile, whereby WT-level synergistic interactions between both CAR-CIP and CAR-GEN consistently shifted towards an additive interaction in the mutant (Fig. 4E; Supplementary Fig. S9; statistical results in Supplementary Table S6).

To further characterize the molecular underpinnings of CpxS-mediated effects on negative hysteresis, we performed a transcriptomic analysis of WT PA14 and the CpxS T163P mutant with or without CAR pre-treatment (50 mg/L CAR for 30 min). A comparison between pre-treated and untreated WT identified flgB as the only significantly differentially expressed gene (absolute fold-change ≥ 2; down-regulated; statistical results in Supplementary Data 4 and 5 ). More interestingly, the comparison of the gain-of-function CpxS T163P mutation with the WT revealed 124 significantly differentially expressed genes (absolute fold-change ≥ 2; Fig. 4F; statistical results in Supplementary Data 6 and 7) that include genes involved in transmembrane transport, type III secretion, quorum sensing, and pathogenesis, suggesting that CpxS activation in the mutant affects membrane structure and membrane-associated functions (Supplementary Data 5, 6, and 7). In addition, eight of the 124 genes are located close to a consensus CpxR binding site (46), identifying them as the core set of the Cpx regulon, including cpxP as the most strongly upregulated gene (more than 100-fold) in CpxS T163P, supporting the role of CpxP in a feedback loop with CpxS activation (statistical results in Supplementary Data 7). Consistent with our findings, cpxP is also the most positively CpxR-regulated gene in E. coli (47, 48). Furthermore, cpxS itself is strongly upregulated in the CpxS T163P mutant, again supporting the presence of feedback loops in regulating this gene (statistical results in Supplementary Data 7).

Negative hysteresis is associated with changes in membrane stress response and increased uptake of gentamicin

To further examine the mechanisms underlying negative hysteresis, we investigated which cellular changes are mediated by the Cpx envelope stress response system. Considering that the most effectively sensitizing antibiotics (i.e., β-lactam drugs) target cell wall synthesis, that CpxS should be localized in the inner membrane (in analogy with what is known for the E. coli ortholog CpxA), and that the Cpx system responds to membrane stress (34–36), we postulated that disruption of cell envelope integrity and/or increased permeability could lead to negative hysteresis. We tested these ideas with the help of three envelope stressors as pre-treatment: (i) polymyxin B (PMB), which targets the outer cell membrane, (ii) CAR, which targets the peptidoglycan matrix, and (iii) benzyl alcohol (BnOH), a general membrane fluidizer (49). We found that negative hysteresis is induced in the WT PA14 by both CAR and BnOH but not PMB, while the CpxS T163P mutation inhibits WT-level sensitization by CAR (as shown above) but not BnOH (Fig. 5A; statistical results in Supplementary Table S7). These results indicate the involvement of the inner membrane and the peptidoglycan layer in negative hysteresis. Since the CpxS T163P mutant did not inhibit BnOH-mediated sensitization, BnOH may induce negative hysteresis differently or even independently from peptidoglycan-targeted hysteresis.

We then asked how CAR pre-treatment affects membrane stress responses in WT PA14 and the CpxS T163P mutant using Laurdan, a fluorescent membrane dye and sensor for lipid packing that produces a spectral shift towards lower wavelengths with decreasing membrane fluidity (50, 51). We found that CAR exposure led to a significant membrane stress response in the WT (Fig. 5B; statistical results in Supplementary Table S8). Thus, the spectral shift indicated CAR-induced membrane rigidification during early growth at the used sub-lethal concentration. In contrast, the active membrane stress response in the CpxS T163P mutant already produced a rigidified membrane, which was then not significantly affected by an additional CAR pre-treatment (Fig. 5B; Supplementary Table S8). These findings strongly suggest that membrane pre-adaptation via constitutive CpxS expression actively suppressed hysteresis in the mutant. An orthogonal way to modify membrane fluidity are sudden shifts in temperature, to which bacteria respond by fluidity-adjusting membrane remodeling (e.g. (49)). We thus reasoned that a heat-shock could provide an equivalent stimulus as hysteresis-inducing CAR pre-treatments. As a test, we induced a heat shock by a sudden up-shift of temperature from 37°C to 50°C for 15 min, ahead of the pre-treatment step. Consistent with the membrane stress hypothesis, we expected (i) the heat shock by itself to accelerate GEN killing and (ii) the heat shock to suppress the possibly redundant inducing effect of CAR. The experiment confirmed both predictions (Fig. 5C, statistical results in Supplementary Table S9), supporting our model that abrupt changes to the membrane fluidity trigger the CAR induced GEN hysteresis. As low permeability of the inner membrane limits aminoglycoside uptake in Gram-negatives (52), we hypothesized that membrane stress and dynamic membrane remodeling altered aminoglycoside membrane permeation, leading to the observed accelerated lethality of hysteresis. The uptake of aminoglycoside is energized by the proton motive force of the cytoplasmic membrane (53). Thus, induced dynamics of proton motive force may link pre-treatment inhibition to hysteresis lethality. The chemical inhibitor CCCP allows protons to cross the cytoplasmic membrane, collapsing membrane potential such that no dynamic change of the membrane is possible (54). When we pre-incubated cells with 200 µM CCCP, cell numbers did not increase, relative to controls treated with solvent only. This reduction is likely explained by a requirement of membrane potential for growth. The pre-treatment with only CAR was more effective than CCCP at inducing negative hysteresis. Intriguingly, the CCCP incubation precluded any additional effects of CAR pre-treatment on hysteresis (Fig. 5D, statistical results in Supplementary Table S10), further supporting the idea that an altered cell envelope underpins negative hysteresis.

We finally tested to what extent β-lactam-mediated sensitization towards GEN is directly related to an increased uptake and thereby intracellular abundance of the latter drug. Using an ELISA assay for GEN in our hysteresis assay with or without the pre-treatment, we observed a significantly increased intracellular GEN concentration upon CAR pre-treatment in the WT PA14 but not the CpxS T163P mutant (Fig. 5E, statistical results in Supplementary Tables S11 and S12). β-lactam induced negative hysteresis to GEN is thus explained by increased uptake of the aminoglycoside resulting from Cpx-dependent physiological remodeling of the inner cell membrane.

Methods
Ethics statement

Our study included clinical bacterial isolates collected from sputum samples of patients. These patients were enrolled in the clinical observational trial "Airway colonization with Pseudomonas aeruginosa in chronic obstructive pulmonary disease (COPD)/non-CF bronchiectasis - an observational and biomaterial study" at LungenClinic Großhansdorf (Großhansdorf, Germany), approved by the local ethics committee of the Medical Faculty of the University of Lübeck (No. 20-295), available through the German Clinical Trials Register (https://drks.de/, ID DRKS00023975). Prior to enrollment, patients provided written informed consent for participation.

Bacterial strains, culture conditions, and antibiotics

An overview of all bacterial strains, plasmids, and antibiotics used or generated in this project is provided in the Supplementary Data 8, 9, and 10. We used 6 patient populations from four patients all including 8-14 isolates, two patients had two sample time points included, that were collected between January and November 2021. Only three of these samples had additional bacterial species isolated (Supplementary Table S13), whereby we here focused solely on P. aeruginosa as a model pathogen. Further information on the individual isolates, such as morphology and MIC values of the patients, can be found in the Supplementary Data 11.

Antimicrobial susceptibility testing

Antimicrobial susceptibility was assessed by determining the minimum inhibitory concentration (MIC) of an antibiotic, following three main approaches: (i) a broth microdilution approach, (ii) the Vitek®2 (bioMérieux) diagnostic system (always following manufacturer instructions), and (iii) MIC test strips (Liofilchem®, following manufacturer instructions), depending on the respectively required resolution. The MIC determination used was consistent within each panel. The broth microdilution was based on the EUCAST (European Committee for Antimicrobial Susceptibility Testing) guidelines for antimicrobial susceptibility testing (76), using 96-well plates and a 2-fold serial dilution of the antibiotic, incubation statically at 37 °C for approximately 20 h, and measurement of optical density at 600 nm (OD600). MIC was determined as the lowest concentration that resulted in a relative OD (OD relative to growth control) below 0.1.

Hysteresis time-kill assay

Hysteresis time kill assays were used to measure how pre-treatment with one antibiotic affected killing efficacy of a subsequently administered antibiotic. The assays were initiated with a bacterial culture at early exponential phase in M9 medium, which was subjected to a pre-treatment at 37 °C with the antibiotic of interest for up to 30 min, as indicated. Thereafter, the pre-treatment antibiotic was removed by centrifugation. The pellet was resuspended immediately in fresh medium and the main treatment drug was added, as indicated. To assess the persistence of the pre-treatment-induced effect, we introduced a drug-free period of up to 80 min before initiating the main treatment. The samples were then incubated at 37 °C and bacterial survival evaluated as colony forming units (CFU) per mL culture after 0, 2, 4, and 6 h of main treatment, following standard protocols (12). The area under the curve (AUC) of the obtained time-kill curves was calculated based on the CFU or survival data. The hysteresis effect was quantified as the difference in AUC (ΔAUC) between the hysteresis and the corresponding control treatment and summarized in a heatmap. The AUC data were also used in some cases to generate a Nelder-Mead dose-response model (77) of the hysteresis effect size. The significance of differences between hysteresis and control treatments was assessed using a two-sided Student’s t-test. The relationship between CFU per mL and OD was assessed by non-parametric Spearman’s rank sum correlation of paired CFU and OD data points from the 6 h timepoint. The correlation was performed separately for main treatments with β-lactam and for measurements of OD by cuvette or microtiter plate (Supplementary Fig. S5)

Hysteresis wash experiment

To test for a possible role of antibiotic carry-over in hysteresis induction we performed a standard hysteresis experiment (PA14, pre-treatment CAR 50 mg/L 30 min) but inoculated two cultures from each pre-culture so that one group could be treated as usual (with regular carry-over of pre-treatment CAR) and one group washed thoroughly with phosphate buffered saline to remove free and thus unbound CAR (two washes with 5 mL PBS, pellet cells by centrifugation 10 min at 4000g, 4°C) before start of the GEN treatment 1mg/L. Error bars show SEM for n = 3 biological replicates. A two-sided Student’s t-test was used for statistical testing. This treatment will not remove any covalently bound CAR.

Hysteresis experiments with complex pre-treatments

a) Chloramphenicol: To test whether active growth was required for hysteresis, we diluted a dense overnight culture to OD 0.005 in fresh medium and grew it to OD of 0.06-0.07. We then split the growing culture into parallel 5 mL cultures and added 512 mg/L chloramphenicol (8x MIC, stock prepared in ethanol 95%) to stop protein production or an equivalent volume of the solvent (final ethanol concentration in culture 3%). After 15 min, we added CAR 50 mg/L (0.5x MIC) to initiate pre-treatment. After 30 min, cells were pelleted by centrifugation and resuspended in medium containing 1 mg/L GEN (1 x MIC) as the only antibiotic. Survival during GEN treatment was measured using CFU as described in the hysteresis standard protocol. Error bars show SEM for n = 3 biological replicates.

b) Heat shock: To test whether a mild heat shock could functionally replace a CAR pre-treatment, we grew cells from OD of 0.005 (diluted overnight culture) to 0.05 and induced heat shock by shifting half of the culture from 37°C to a heated water bath of 50°C for 15 min before splitting the culture into parallel 5 mL cultures and adding 50 mg/L CAR (0.5 x MIC) for hysteresis induction. After 30 min pre-treatment with CAR, cells were pelleted by centrifugation and resuspended in medium containing 1 mg/L GEN (1 x MIC) as the only antibiotic. Survival during GEN treatment was measured using CFU as described in the hysteresis standard protocol. Error bars show SEM for n = 3 parallel cultures. Statistical analysis was performed by comparing the survival after 4 h (Two-sided Student’s t-test with FDR correction).

c) Membrane potential: To test the role of membrane potential in negative hysteresis, we grew cells from OD of 0.005 (diluted overnight culture) to 0.06 and collapsed membrane potential by adding 0.2 mM carbonyl cyanide 3-chlorophenylhydrazone (CCCP, stock prepared in DMSO) or an equivalent amount of the solvent (final concentration of DMSO in culture was 0.8%). After 15 min, we added CAR 50 mg/L (0.5x MIC) to initiate pre-treatment. After 30 min, cells were pelleted by centrifugation and resuspended in medium containing 1 mg/L GEN (1 x MIC) as the only antibiotic. Survival during GEN treatment was measured using CFU as described in the hysteresis standard protocol. Error bars show SEM for n = 3 biological replicates. Statistical analysis was performed by comparing the survival after 4 h (Two-sided Student’s t-test with FDR correction).

Hysteresis screen experimental design and protocol

We developed a high-throughput screen to assess the presence or absence of hysteresis across a larger number of antibiotics and P. aeruginosa strains. The assay was based on continuous OD-measurements, taken in plate readers (Epoch2, Agilent) in 15-min intervals across a 12 h time period, to infer growth kinetics of bacterial cultures in 384-well plates, which were subjected to hysteresis or corresponding control treatments (i.e., either with or without antibiotic pre-treatment, respectively). Drug concentrations were standardized for each bacterial strain and antibiotic, using information on MIC inferred with the Vitek®2 (bioMérieux) approach (Supplementary Data 1). We used two concentrations for the pre-treatment at 0.75 and 0.075 MIC, and four concentrations for the main treatment at 0.75, 0.375, 0.075, and 0.0375 MIC.

For data analysis, we focused on pre-treatment drug concentrations that did not directly affect growth. Samples were excluded from the statistical analysis, if both used pre-treatment drug concentrations directly inhibited growth. To account for the unidirectional expectation, a one-sided Wilcoxon-rank-sum test adjusted for multiple comparison with the false discovery rate (FDR) was used to determine the inhibitory effect of the pre-treatment. Moreover, we subsequently focused on those main treatment drug concentrations causing the highest level of growth inhibition but not more than 75%. The presence of hysteresis was assessed by calculating the difference in AUC between the hysteresis and the corresponding control treatment with a two-sided Wilcoxon-rank-sum test adjusted for multiple comparison with FDR.

Drug interactions

Drug interaction profiles were determined with the CombiANT approach (78) for a variety of antimicrobial combinations, and additionally a checkerboard assay for one specific combination, using both the for the wildtype PA14 and the CpxS T163P mutant. The CombiANT analysis is based on antibiotic diffusion in agar plates and has been previously validated against standard assays for assessing antibiotic interactions such as time kill and checkerboard assays (78–80). Images of the CombiANT plate were taken with the BIO-RAD ChemiDoc Touch (Colorimetric blot, Epi white, medium size, auto optimal exposure), followed by image analysis with the CombiANT Imager v.3.5 and the nps_v3 analysis pipeline (81). The interaction profile between strains was compared by two-sided Wilcoxon rank sum test for each antibiotic pair separately. A checkerboard approach was performed to assess the interaction between CAR and GEN. Seven concentrations of each antibiotic and three no-drug controls were distributed across a 96-well plate. The plates were incubated for 24 h at 37 °C with constant shaking and OD600 measurements taken every 15 min, followed by inference of growth rates as described previously (82). The degree of synergy was determined using the Bliss independence method (83) (Supplementary Fig. S9).

Secondary structure analysis and 3D homology modeling of CpxS

Secondary structure analysis of the CpxS sequence was conducted using the Self-Optimized Prediction (SOPMA) program (84). For constructing 3D homology modeling of CpxS, SWISS MODEL (85) server and HHpred server (86) were employed. The cytoplasmic portion (residues 175-445), comprising the HAMP, DHp, and CA domains, was modeled using the crystal structure of CpxA (62) (PDB ID: 4BIV) as the template. Concurrently, the homology model of the CpxS sensory domain (residues 8-148) was constructed by using the sensory domain from AbfS (sensor histidine kinase) (45) as the template (PDB ID: 2VA0). The composite full-length model of CpxS, excluding the transmembrane region (TM), was manually assembled in Coot (87). Visualization of the final model was done using PyMol (88).

Construction of mutants

Scar-free deletion mutants and specific cpxS mutants were generated using a two-step allelic exchange approach (89, 90). Briefly, fragments of approximately 700 bp up – and downstream of the mutation of interest were cloned into the plasmid pUIsacB (90) using Gibson Assembly. The resulting plasmid was transformed into E. coli JM109. Tri-parental conjugation followed by two steps of homologous recombination on selective media was used to select for clones containing the mutation of interest. In addition, we also generated mutants with inducible cpxS overexpression in the wildtype PA14 and the cpxS deletion mutant, using a restriction digest – ligation set up. The cpxS open reading frame was cloned into the expression vector pME6032 (91) and transferred to the two strains of interest. The expression of cpxS was induced by IPTG addition to the culture medium, followed by phenotypic analysis.

Transcriptomics

The wildtype PA14 and the Cpx T163P mutant were subjected to a hysteresis or control treatment as above. After 30 min of pre-treatment, cells were collected by centrifugation and total RNA isolated, using the TRIzol lysis and the NucleoSpin miRNA kit (Macherey-Nagel), followed by rRNA depletion (RiboZero Bacterial Kit, Illumina), library preparation (TruSeq stranded total RNA, Illumina) and sequencing (Illumina, HiSeq4000, 1 x 50 bp). Read trimming was carried out via Trimmomatic (92), reads were followingly mapped and counted via Bowtie2 (93) and EDGE-pro (94). Normalization, differential expression analyses among treatments and strains as well as enrichment analyses were performed with edgeR (95), using the quasi-likelihood generalized negative binomial model and associated F tests to assess significant differential expression. We considered genes to be significantly differentially expressed if they showed the FDR-adjusted p value was below 0.05 and the absolute expression fold change was at least 2 (absolute log fold change ≥ 1). Enrichment analyses were performed with clusterprofiler, using an FDR-adjusted p value of 0.05 as cut-off. Reference genome as well as Gene Ontology (GO) and KEGG pathway annotation data were downloaded from the Pseudomonas Genome Database (96) (pseudomonas.com, June 2020).

Membrane stress measurements

The impact of CAR pre-treatment on membrane stress was assessed by measuring general polarization with Laurdan for the wildtype PA14 and the CpxS T163P mutant, subjected to hysteresis and control treatments as above. After 15 min of pre-treatment, Laurdan was added at 100 μM (Supplementary Fig. S10). After a total of 30 min pre-treatment, the cells were collected by centrifugation, washed twice in M9 containing 0.08 % DMF, a final resuspension in M9 and fluorescence measurements in an Infinite M Plex plate reader. The statistical significance of a difference between treatments was assessed with a two-sided Student’s t-test.

ELISA-based inference of intracellular GEN concentrations

Intracellular GEN concentration was measured for the wildtype PA14 and the Cpx T163P mutant subjected to hysteresis or control experiments as above (n = 3 per strain and treatment), followed by 3 x washing of cells in PBS, cell lysis (30 min at 37 °C in provided lysis buffer) and intracellular GEN ELISA measurements (Elabscience®, E-FS-E073), according to the manufacturer’s instructions. The statistical significance of a difference between treatments was assessed with an ANOVA (Supplementary Table S11) followed by Tukey HSD (Honestly Significant Difference) test with FDR correction for multiple comparisons (Supplementary Table S12).

Statistics & Reproducibility

All statistical analyses were conducted in R (version R 3.6.1 – 4.2.2). The detailed statistical tests for each experiment are given in the relevant Methods section. Further information on material and methods is provided in the supplement. The detailed results of the statistical analyses are provided in Supplementary Data files and the Supplementary Tables.

Data availability

The source data of this study is provided in a supplementary Source Data file. The statistical data generated, as well as Key Resources used, are provided in the Supplementary Data files and as Supplementary Tables. The transcriptomic data generated in this study have been deposited in the NCBI's Gene Expression Omnibus under GEO Series accession number GSE290299.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This is a well-executed study that investigates negative hysteresis (NH), an important biological process with implications for treating multidrug-resistant infections. This research builds on a previous finding of NH in the Pseudomonas aeruginosa laboratory strain PA14, where β-lactam treatment increased sensitivity to aminoglycosides (Roemhild et al. 2018). The original experiment identified a SNP in cpxS (T163P) that abrogated NH, indicating a candidate molecular mechanism.\nThe Cpx operon is well-characterized in Escherichia coli as a regulator of efflux pump expression (Raivio and Silhavy 2001), but its ortholog in P. aeruginosa is structurally distinct and less understood. Previous studies in P. aeruginosa elucidated the function of cpxS as a sensor kinase that works in tandem with the cpxR response regulator to influence expression of the mexAB-oprM efflux pump (Tian et al. 2016; Tian and Wang 2023). Mutations in cpxS have also been identified in P. aeruginosa isolated from patients (Hernando-Amado et al. 2025), underscoring clinical relevance.\nThis study extends existing knowledge of NH and the Cpx operon in P. aeruginosa by including multiple antibiotics, performing tests in laboratory strains and clinical isolates, and investigating the physiological impacts and molecular basis of NH. Their key findings are that pretreatment with three β-lactams (meropenem, piperacillin/tazobactam, and ceftazidime) induces NH with gentamicin, that this occurs regardless of genetic background (across all strains of P. aeruginosa tested), and that this can occur even if the strain is already resistant to gentamicin. They also propose a model for the Cpx operon in P. aeruginosa that functions similarly to Cellvibrio japonicus; this was verified by demonstration that membrane stress reduces permeability by aminoglycosides, that cpxS is strongly upregulated during the membrane stress response, and that cpxS and cpxP operate in a negative feedback loop.\nMajor comments\n1. In general there isn’t much review of the literature to contextualize results. Also lacking is a discussion of what these findings indicate for clinical treatment.\n2. How common is hysteresis? Only a few examples are cited (refs 12, 19, and 23), suggesting it is either uncommon or poorly studied. Please add an explanation of why it is uncommon or understudied and what the current outstanding questions are. Related to this, on line 174: please indicate out of how many trials the 121 examples of hysteresis were found.\n3. The T163P mutation in cpxS is a well-studied mutation, and the Introduction/Discussion of this paper lacks a review of what is known about and has already been done with this mutation.\n4. The assay designed to address chronic infections by using mixed populations (Line 193-202) is not explained in sufficient detail within the main text. Please indicate in the text how many populations you constructed and tested from each patient.\nAdditionally:\na. It appears that only P. aeruginosa were isolated from the patient samples (there were likely other bacteria present, so this is a weakness of the approach that should be acknowledged).\nb. Did the isolates exhibit chronic phenotypes like drug resistance or mucoidy?\nc. Line 768 (legend for Fig. 3D) what are the time points and why did you only consider multiple time points for a few populations?\nMinor comments\n1. Fig 2A: the CIP results are mentioned only in the figure caption, please describe them in the main text.\n2. The reference to “standard hysteresis treatment” (Line 295), was confusing since you previously tried inducing hysteresis with multiple drugs. Perhaps rephrase to say this analysis was done with and without pre-treatment with CAR.\n3. In your supplemental methods, please indicate why you used 3 methods to measure MIC and whether you calibrated across methods to ensure comparability.\n4. Fig. S2 has incongruent colors: e.g., the legend indicates blue for CAR pretreatment but there is no blue in the figure, and there’s a black line in the figure but no black line in the legend.\nConclusion\nNH could be a broadly significant concept that enhances our understanding of antibiotic resistance and can be used to address the urgent challenge of treating multidrug-resistant infections. This study demonstrates that temporally fluctuating antibiotic regimes may offer an effective treatment strategy that does not require new drug discovery). As an ESKAPE pathogen, P. aeruginosa is an appropriate and relevant model system.", "reviewer_2": "Review of Bucholz et al. Robust antibiotic sensitization of pathogenic Pseudomonas aeruginosa via negative hysteresis in the cell envelope\nIn this article, the authors test for hysteresis (when pre-treatment to one antibiotic influences subsequent resistance to other antibiotics) in P.aeruginosa. Our overall assessment is that the authors do not present convincing evidence of hysteresis, and the manuscript has important flaws, including non-replicated experiments and incomplete statistical methodology. The authors present convincing evidence that the cpx pathway is involved in antibiotic sensitization. However, our overall assessment is that this manuscript is not suitable for publication, and we recommend rejection.\nMajor points\n1. Methods used to test for hysteresis. To test for hysteresis the authors pre-treat bacteria with one antibiotic and then exchange the media to another antibiotic. The problem with this method is that the antibiotic used for pre-treatment enters either the cytoplasm of bacterial cells (aminoglycosides ie GEN, fluoroquinolones ie CIP) or the periplasmic space (ie B-lactam antibiotics CAR, MER, PIT, CTZ). Exchanging the media creates a diffusion gradient that will favour the diffusion of the pre-treatment antibiotic out of the cell, but this diffusion will be far from instantaneous, especially in Pseudomonas which is notorious for having cells with low permeability. This creates a fundamental problem, as the authors cannot discriminate between effects or pre-treatment that are caused by the damage caused to cells and/or physiological responses to the antibiotics or if the pre-treatment effects are simply the result of the persistence of the pre-treatment antibiotics in bacterial cells when the ‘main’ antibiotic is administered.\nIn Figure 2, the authors show that negative hysteresis is most common among pairs of antibiotics that show synergistic interactions. This key result is consistent with the idea that the negative hysteresis effect could simply be due to the interaction between retained pre-treatment antibiotic and the second antibiotic used for treatment. The short duration of the hysteresis effect (Figure 1F) is also consistent with this idea, and may reflect the the time needed for pre-treatment antibiotics to diffuse out of cells.\n2. Experimental design and experimental method. The ‘gold standard’ method to measure the impact of antibiotics on bacteria viability is to measure how antibiotic exposure influences live bacteria cells counts. The authors use this approach to test for interactions between GEN and CAR in Figure 1. However, the experiments reported in this Figure are not replicated, making it impossible to assess the validity of these results.\nThe authors then go on to test for hysteresis between pairs of antibiotics in clinical isolates. The authors based their measurements of interactions using OD curves. We appreciate that assays like this require high throughput experimental methods, but there are a number of important potential biases and limitations with using OD to measure responses to antibiotics. For example, exposure to B-lactam and fluoroquinolone antibiotics causes changes to bacterial cell morphology (ie cell filamentation) that alter the correlation between cell number and OD. Antibiotics also cause cell death, and OD does not allow for live and dead cells to be distinguished. Owing to these potential limitations, using OD to measure the impact of antibiotics on bacterial growth requires robust validations using methods that assess viable cell counts. We are not convinced by the validation provided by the authors, and we suggest that they should randomly test a fraction of the interactions in their screen instead of cherry picking 1 or 2 interactions, particularly if these are previously known examples of hysteresis.\n3. The use of clinical isolates to test drug interactions is a positive aspect of this study, particularly given that drug interactions and collateral sensitivity are often poorly conserved across strains. However, only a subset of clinical isolates displayed ‘robust’ negative hysteresis, with only two COPD populations, many switches were neutral (lines 197 198). The manuscript would benefit from a clearer framework for why some isolates or resistance phenotypes fail to show the phenomenon\n4. The authors identify the well-known Cpx envelope stress pathway as a key regulatory mechanism. Combining targeted gene deletions, overexpression constructs, and transcriptomic profiling provides a good methodological basis for mechanistic insights into how envelope stress leads to antibiotic sensitisation. The authors provide convincing evidence that the cpx pathway is involved in antibiotic sensitization – however, the data for cpxS mutants (e.g., T163P, G188S) at times yield unexpected outcomes (lines 235 237). Some mutants do not replicate the wild-type phenotype or lead to positive hysteresis. Clarification is needed on how these differences influence the interpretation that CpxS is a key driver of negative hysteresis. Additional biochemical or phenotypic assays (e.g., membrane permeabilisation assays) might help to confirm how each mutation modifies envelope stress responses.\n5. A further limitation of this study is that the statistical methodology is not described very clearly, making it difficult to assess the methods used to analyze the data. For example, it is unclear if the authors treated different measures of the same culture at different time points as independent observations or not (they should not be considered independent) and the degree to which their results were based on comparisons between biological and technical replicates.\nOverall assessment: Our overall assessment is that we are not convinced that hysteresis is a real phenomenon or if the authors have effectively just developed a new assay to measure drug-drug interactions (point 1). This a fundamental problem with the study. The authors are forthcoming about how drug pharmacokinetics may make it difficult to apply sequential antibiotic treatment in the context of infections, but the strong dose dependency (ie comparing results with 1mg/L vs. 2 mg/L GEN in Figure 1B) and transient nature of these interactiosn (ie Figure 1F) also make us skeptical about the potential applications of this work for treating bacterial infections.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "Dear editors,\nWe are pleased to submit our revised manuscript to Nature Communications. We carefully considered\nthe reviewers comments to improve our manuscript. Importantly, we performed several new\nexperiments for a much more comprehensive demonstration of the cellular and physiological changes\nunderlying the phenomenon of negative hysteresis. The results of these new experiments as well as a\nrefined analysis of our data have now been included in the revised manuscript and they clearly\nstrengthen our key conclusions. See Figures 1B, 1C, 1D, 1E, 5C, 5D, S2A, S2B, and S5. Morevoer, we\nfurther carefully refined our arguments and the interpretation of results, in response to the helpful\nadvice given by the reviewers. Therefore, we hope that our manuscript is now acceptable for\npublication.\nNegative hysteresis is a unique and understudied phenomenon that we show for the first time to be\ncommon and robustly expressed in the high priority human pathogen Pseudomonas aeruginosa, that we\nshow for the first time to be caused by cell envelope stress, involving the two-component Cpx system,\nand that we identify as a promising focus for optimizing antibiotic therapy.\nPlease let us know if you have any questions!\nYours sincerely,\nRoderich Roemhild, Hinrich Schulenburg (on behalf of all authors)\nResponse to reviewer comments\nBelow, the original reviewer comments are given in gray and italics, while our response is given in blue.\nWe further provide manuscript and supplement files, in which changes are tracked and in which we use\ncomments to indicate where we modified the manuscript in response to reviewer comments."}, {"round": 2, "reviewer_comments": {"reviewer_1": "My prior review was largely supportive and requested more clarity about methods and some greater context from the literature, which the authors addressed well.\nHowever Reviewer 2 raised important methodological concerns that drew my interest. The biggest one is that the methods didn’t preclude carryover of pretreatment antibiotic in the periplasm/cytoplasm of cells, so you can’t distinguish whether NH is a real, post-drug effect, or an effect of residual intracellular drug. Reviewer 2 also points to the transience of NH as consistent with drug carryover, as the effect could be disappearing once the residual drug diffuses out of cells.\nThe authors did a lot of additional work to address this, but not a direct test (I think you’d need mass spectrometry to estimate intracellular drug concentration). While not totally satisfying, it convinced me that NH is real even if its underlying biology remains unclear. Specific points about this follow:\na. The authors did additional experiments where they wash pretreated cells 2x before their assay for NH. However, I don’t think you can wash away intracellular drug.\nb. They also added experiments showing that other membrane stresses can cause NH: 1) mild heat shock and 2) CCCP (depletion of membrane potential). From this they conclude that “abrupt changes to the membrane fluidity can trigger hysteresis”. This proves their principle, but it’s not a direct test.\nc. They comment: “If antibiotic retention were the sole explanation, we would expect enhanced killing regardless of the second antibiotic used”. It is unclear to me why all drug combinations should produce the same outcome -- wouldn't this depend on mechanism of action?\nd. Finally, the authors argue that increased efflux would expel residual drug and abolish NH. They found that a mexR mutation increased resistance but had no effect on NH, suggesting there NH wasn’t caused by intracellular drug. I believe this because they confirmed that the mutation caused increased efflux via resistance. If increased efflux doesn’t affect NH, than NH can’t all be due to residual drug.\ne. The authors don’t clearly address that the transience of the hysteresis phenotypes may also be a corollary of residual drug diffusion. Rather, they say that NH is not the same as drug interactions because they get different NH types depending on the order of the drug, but it does not mean they are not related.", "reviewer_2": "The authors have made substantial changes to the content and text of the manuscript following peer review. Most of our concerns have been addressed, and the authors have substantially improved this manuscript, apart from one technical concern listed below. Addressing this concern will not substantially alter the conclusions of this manuscript. The only bigger issue that we have with the paper is the link between this work and the authors' previous paper on hysteresis (https://www.pnas.org/doi/epdf/10.1073/pnas.1810004115). It is clear that this paper has advanced our understanding of hysteresis, but we found ourselves in a position where we were questioning whether the advances in understanding presented in this paper were sufficient to warrant publication in a journal like Nat Comms. We think that this is a debatable point, and the editor may wish to consider this issue if it is raised as an issue by other reviewers.\nOutstanding issue:\nThe authors have carried out paired measures of OD and CFUs to test the validity of their approach (Figure S5). When gentamicin is used as the main antibiotic for treatment the OD values and CFUs are well correlated, validating the use of OD. However, the correlation between microtiter plate OD and CFUs is not convincing in any way when B-lactams are used as the antibiotic for main treatment. The authors test for a correlation between logOD and logCFU by linear regression, and this analysis is flawed. The underlying data do not show a bivariate normal distribution (ie normally distributed x and y values) violating a central assumption of linear regression. Violating this assumption tends to lead to inflated r^2 values (for example when linear regression is on data sets that have two ‘clouds’ of points) and we argue that their estimated (low) r^2 value of 0.27 is an overestimate of the true strength of association – cultures with OD of 0.05 and .5 were associated with similar viable cell densities. The authors should drop all of the data from plate reader based assays where B-lactams were used as the main treatment.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": ""}, {"round": 3, "reviewer_comments": {"reviewer_2": "The authors have responded to my technical concerns, but I remain unconvinced by their arguments regarding the novelty and importance of this work, as outlined below and quoting from their response to referees.\n(i) it provides the first evidence of the widespread and robust expression of negative hysteresis across genomic backgrounds for a particular pathogen taxon,\nDemonstrating negative hysteresis in clinical isolates is an advance with respect to the authors’ previously published work. However, I consider this to be an incremental advance as it is effectively confirming a previously reported finding. I think that the authors case here would have been much stronger if they had been able to uncover why clinical isolates differ in their antibiotic responses.\n(ii) it provides the first evidence of the robust expression of negative hysteresis upon switches from a beta lactam drug to an aminoglycoside which is beyond the previously reported switch from carbenicillin to gentamicin,\nI view this as being quite a minor point. Given the similarities in structure and mechanisms of action of different antibiotics from the same class it would be surprising if this negative hysteresesis between B-lactams and aminoglycosides was not widespread. It would have been much more novel if, for example, the authors had been able to demonstrate negative hysteresis across a wide range of combinations of antibiotic class.\n(iii) it provides evidence that negative hysteresis can be induced in resistant strains and pathogen populations isolated from patients, thereby highlighting novel, currently not considered treatment options,\nI think that demonstrating the applicability of negative hysteresis to clinical isolates is important, but the authors present very little data on this in the manuscript – the data in Figure 3 is from isolates collected from n=3 patients!\n(iv) it provides novel information on the molecular basis of negative hysteresis that relies on beta-lactam-induced changes in membrane fluidity and increased intra-cellular concentration of the subsequently administered aminoglycoside drug, and (v) it provides new evidence for the central role of the Cpx cell envelope stress response system in mediating hysteresis based on our detailed functional genetic analysis of mutant strains previously not available (e.g., loss-of-function, gain-of-function, overexpression mutants, as well as mutants of related genes).\nI agree with the authors that they have substantial mechanistic detail to their previously published case of negative hysteresis. The mechanistic work reported by the authors provides a sufficient level of analysis as supporting work, but it does not rise to the level that I would expect, for example, from a paper on AMR mechanisms. Providing supporting mechanistic detail into a previously published phenomenon does not, in my view, constitute the kind of novelty that I expect from papers in Nature Communications.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": ""}]

Decision letter
Dear Professor Schulenburg,
I am writing from Nature Communications on behalf of Dr Rita Ramalhete.
Thank you for submitting your manuscript, ‘Robust antibiotic sensitization of pathogenic Pseudomonas
aeruginosa via negative hysteresis in the cell envelope’. It has now been seen by four referees whose
comments are provided below this message.
For your information, I have provided the expertise of the referees immediately below.
Referees 1 and 4: Antimicrobial resistance evolution, microbial genetics and evolution
Referees 2 and 3: Pseudomonas aeruginosa, evolution and genomics of antimicrobial resistance,
hysteresis
As you will see from the reports, while Referees 1 and 4 find the work of potential interest, Referees 2
and 3 have raised serious concerns about the strength of support for the central conclusions relating to
hysteresis. In particular, we share their concerns about the lack of replication, the potential bias in the
hysteresis screening based on the potential impact of antibiotic usage on cell wall permeability, and the
lack of validation of the OD curves including a lack of random testing of drug-drug interactions. In light of
these concerns, I am afraid that we will not offer to publish the manuscript.
I am sorry that we cannot be more positive on this occasion and thank you for the opportunity to
consider your work.
Best regards,
Ripu
Ripudaman K Bains, PhD
Chief Editor for Microbiology and Infectious Diseases
Nature Communications