Oxidative Treatment for Reducing Persistent Populations of Escherichia coli Under Amoxicillin and Gentamicin Pressure

TL;DR

This study shows that combining light-based treatment with antibiotics can kill persistent bacteria more effectively and faster.

Contribution

The study introduces optimized PDI with methylene blue to enhance antibiotic efficacy against persistent E. coli.

Findings

PDI reduced MDK99 from >3 to 2 hours under amoxicillin pressure.

PDI suppressed regrowth and reduced MDK99.99 from 3 to 2 hours under gentamicin pressure.

SEM confirmed morphological damage consistent with bacterial persistence.

Abstract

Bacterial persistence is a transient phenotypic state in which a subpopulation of cells survives antibiotic exposure without genetic resistance. These dormant, low‐metabolic cells are linked to recurrent infections and reduced antibiotic efficacy. Photodynamic inactivation (PDI), which generates reactive oxygen species (ROS) through photosensitizer activation under visible light, is a promising strategy to counteract persistence. This study evaluated PDI effects on Escherichia coli under amoxicillin and gentamicin pressure, using time‐kill assays and MDK99/MDK99.99 metrics. PDI, optimized with methylene blue (10 μM) and 10 J/cm2 light at 660 nm, was applied to antibiotic‐exposed cells and progeny. For amoxicillin, PDI reduced MDK99 from > 3 to 2 h; for gentamicin, it suppressed regrowth in progeny and reduced MDK99.99 from 3 to 2 h. Scanning electron microscopy showed morphological damage consistent with persistence. PDI enhanced antibiotic efficacy and shortened treatment time, supporting further investigation of PDI‐antibiotic combinations for chronic infections.

Photodynamic inactivation (PDI) with methylene blue and 660 nm LED enhances antibiotic killing of bacteria, accelerating time‐kill kinetics and reducing the MDK99 compared to antibiotics alone. SEM confirms effective cellular damage, demonstrating that PDI potentiates amoxicillin and gentamicin against tolerant bacterial populations.

Figures

(A) Time‐kill assay with amoxicillin. D1 (squares) represents the time‐kill profile during the initial exposure, indicating persistence induction, while D2 (circles) depicts the killing curve of the progeny derived from D1 survivors. (B) Time‐kill assay with gentamicin. D1 (brown squares) corresponds to cells exposed for persistence induction, and D2 (orange circles) represents their progeny. * denotes statistically significant differences (p < 0.05).

SEM micrographs and size distribution of Escherichia coli. (A) Representative images showing clustered E. coli cells. Blue arrows indicate cells with typical rod‐like morphology, while red arrows highlight those with morphological alterations, including structural damage and size variation. (B) Histogram of cell length distribution, revealing a predominance of cells between 1000 and 1500 nm and a heterogeneous size profile.

Bacterial reduction after irradiation with red light (660 nm) and application of a 10 J/cm2 light dose. The MB concentrations tested were 0 μM (control), 2.5, 5, 10, 15, 20, 25, 35, and 50 μM.

(A) Bacterial killing curves following PDI and time‐kill (TK) treatment with amoxicillin, comparing the original strain (D1, squares) and its progeny (D2, circles). (B) Equivalent assay using gentamicin. In both cases, PDI treatment altered the killing dynamics, reducing bacterial persistence and modifying the behavior of the progeny. * denotes statistically significant differences (p < 0.05).

Bacterial killing curves following PDI treatment and exposure to amoxicillin (A), comparing D1 (dark blue squares) and D2 (light blue circles) groups. Panel B shows bacterial behavior after PDI and exposure to gentamicin, where D1 (brown squares) represents cells from the first day and D2 (orange circles) represents the progeny treated on the second day. * indicates statistically significant differences (p < 0.05).

Full text

Introduction

1

Antibiotic therapy has been the standard treatment for acute, chronic, and recurrent infections since the discovery of antibiotics. Its primary mechanism involves inhibiting bacterial replication by targeting specific essential cellular processes [1]. Despite their initial effectiveness, tolerance and resistance mechanisms against antibiotics naturally emerge, including both genetic mutations and transient phenotypic adaptations. This phenomenon currently represents a major public health threat due to increasing therapeutic failures [2]. According to Murray et al., nearly 5 million deaths in 2019 were associated with antibiotic‐resistant bacterial infections, with projections estimating up to 10 million annual deaths by 2050 [3].

Persistence involves multiple pathways and systems that collectively downregulate translation, DNA replication, and membrane activity, thereby minimizing antibiotic targets. This includes toxin–antitoxin systems (e.g., hipBA and mqsRA), stringent responses mediated by (p)ppGpp, oxidative stress regulation, SOS response activation, and alterations in energy metabolism. Escherichia coli is one of the most extensively studied Gram‐negative models for bacterial persistence, with clinical relevance in urinary tract infections, gastrointestinal infections, and catheter‐associated biofilms, where standard antibiotic therapy often fails to achieve complete eradication [4, 5]. In such cases, ampicillin exposure induces filamentation and metabolic slowdown, while gentamicin treatment selects subpopulations with altered proton motive force (PMF) and reduced drug uptake [5]. Conventional susceptibility tests are insufficient to detect persister cells due to their transient and non‐replicative nature. To address this, time‐kill (TK) kinetics and minimum duration for killing (MDK) analyses have been proposed as functional metrics to distinguish between susceptible, tolerant, and persistent phenotypes. These approaches allow identification of biphasic killing curves, with the second phase representing persistent cells due to their prolonged survival [6].

Given the clinical relevance of bacterial persistence and the limitations of conventional therapies, photodynamic inactivation (PDI) has emerged as an adjunctive treatment, offering a potential strategy to eradicate persister phenotypes by generating reactive oxygen species (ROS) such as singlet oxygen, hydroxyl radicals, and peroxides via activation of a photosensitizer under specific light wavelengths [7]. These ROS induce nonspecific oxidative damage to nucleic acids, proteins, and membrane structures, thereby bypassing traditional resistance and persistence mechanisms. Previous studies have demonstrated that PDI can potentiate antibiotic action, disrupt membrane integrity, and enhance drug uptake, sensitizing even multidrug‐resistant bacteria.

In this study, we investigated whether PDI using methylene blue (MB) and red light (660 nm) could be modulated to inhibit E. coli persistence, a strain with well‐characterized phenotypic history. We examined persistence induced by two antibiotics with distinct mechanisms of action: amoxicillin, a β‐lactam with reduced activity under dormant conditions, and gentamicin, a bactericidal aminoglycoside. We also evaluated the impact of PDI on both antibiotic‐exposed cells and their progeny as part of a broader strategy to combat bacterial persistence.

Materials and Methods

2

Bacterial Strains and Culture Conditions

2.1

The bacterial strain used in this study was E. coli ATCC 25922, a reference strain commonly employed in antimicrobial susceptibility testing. Cryopreserved stocks (20% glycerol in brain heart infusion [BHI]) were thawed and inoculated (1 mL) into 9 mL of fresh BHI medium. Cultures were incubated at 37°C for 18 h in a shaking incubator (Quimis) at 150 rpm. After overnight growth, the culture was standardized to 10^8^ CFU/mL by adjusting the optical density at 600 nm (Cary UV–Vis 50, Varian).

Characterization of Persister Cells

2.2

Minimum Inhibitory Concentration

2.2.1

Minimum inhibitory concentrations (MICs) for amoxicillin and gentamicin sulfate were determined according to Clinical and Laboratory Standards Institute (CLSI) guidelines. A 96‐well microplate containing Mueller–Hinton (MH) broth was inoculated with E. coli at 10^6^ CFU/mL. Antibiotics were serially diluted, and the plates were incubated at 37°C for 24 h. After incubation, 0.015% resazurin was added to each well and allowed to react for 4 h. MIC was determined based on colorimetric changes or absorbance measurements indicating cellular metabolic activity.

TK Assays

2.2.2

TK assays were designed to characterize biphasic bacterial killing curves indicative of persistence. Cultures were diluted (100 μL into 20 mL of BHI) and grown to late exponential phase (~2 h, 150 rpm, 37°C). Antibiotics were added at 10X MIC (amoxicillin: 80 μg/mL; gentamicin: 10 μg/mL). Samples (1 mL) were collected at 0, 0.5, 1, 2, and 3 h, centrifuged (4000 rpm, 10 min), serially diluted in PBS (10^−1^–10^−5^), and plated for CFU/mL enumeration. To evaluate persistence in the progeny population, surviving cells were centrifuged, resuspended in fresh medium, and subsequently regrown for 18 h under identical experimental conditions. Following this incubation period, a 100‐μL aliquot was collected, and the protocol employed on Day 1 (D1) was reapplied to enable a direct comparison between primary and progeny responses. The MDK_99_ and MDK_99.99_ were calculated to quantify antibiotic tolerance.

Scanning Electron Microscopy

2.2.3

Scanning electron microscopy (SEM) was conducted at the Institute of Chemistry of São Carlos (IQSC) using a LEO 440 microscope. Samples were collected from E. coli cultures exposed to amoxicillin for 3 h. Cells were fixed with 2.5% glutaraldehyde in PBS (pH 7.2) for 2 h at 4°C, washed, and dehydrated through a graded ethanol series (30%–100%). After gold sputter coating, images were acquired at 25000× magnification. Due to technical limitations during sample preparation, only amoxicillin‐treated specimens could be successfully visualized. Cell length measurements and morphological analyses were performed using the ImageJ software (NIH, USA), based on four representative micrographs.

PDI

2.3

Subinhibitory Concentration of MB

2.3.1

To determine the ideal subinhibitory concentration of MB FS for PDI, tests were conducted using different FS concentrations. The experimental groups included a control (without FS, only bacteria) and increasing AM concentrations: 2.5, 5, 10, 15, 20, 25, 35, and 50 μM. After incubation, a light dose of 10 J/cm^2^ was applied using red light with a wavelength of 660 nm. The goal was to assess the impact of these concentrations on bacterial reduction and determine the lowest concentration that produced significant effects and achieved complete subinhibitory levels.

PDI With TK Assay

2.3.2

A stock solution of MB at 10 mM was prepared in PBS and diluted to a final concentration of 10 μM. Equal volumes (500 μL) of MB and bacterial suspension (10^8^ CFU/mL) were combined in 1.5 mL Eppendorf tubes and incubated in the dark for 15 min. Irradiation was performed using a Biotable LED device emitting red light at 660 nm, with an irradiance of 35 mW/cm^2^. The light source was positioned at a fixed vertical distance of 5 cm from the sample surface to ensure uniform illumination.

$$[eqn]$$

where D is fluence (J/cm^2^), I is irradiance (35 mW/cm^2^), t is exposure time (s). An energy dose of 10 J/cm^2^ was applied. Control groups included a biological control (PBS only), a dark control (MB without light), a light control (light without MB), and full treatment (MB + light). To evaluate the isolated photodynamic effects, viability assays were performed after PDI in the absence of antibiotics. To investigate the impact of PDI on persister cells and their progeny, two experimental groups were established: (1) PDI applied only on D1 followed by TK assay on Day 2 (D2); (2) PDI applied on both D1 and D2 before TK assay. Procedures were identical to those described above. All experiments were performed in triplicate (n = 9). Shapiro–Wilk normality tests were conducted, followed by Student's t‐test to compare treated groups. Data analysis was conducted using OriginLab Pro 8.5.

Results

3

The MICs determined for E. coli ATCC 25922 were 8 μg/mL for amoxicillin and 1 μg/mL for gentamicin. These values served as reference for all subsequent TK and PDI assays, with antibiotic concentrations applied at 10X MIC.

TK assays revealed characteristic biphasic killing curves, indicative of the presence of antibiotic‐tolerant persister subpopulations. For amoxicillin (Figure 1A), D1 data, represented by square markers, showed a gradual reduction in viable cell counts but without reaching the minimum duration required to kill 99% of the population (MDK_99_) within the 3‐h exposure. This incomplete killing suggests the induction or selection of persister cells. In contrast, the D2 profile, which corresponds to the progeny of D1 survivors (depicted by circular markers), displayed a more pronounced decrease in bacterial viability, with MDK_99_ being achieved in 2.2 ± 0.3 h. This finding indicates a partial resensitization of the population or a transient nature of the persistence phenotype, as the offspring appear more susceptible to amoxicillin.

(A) Time‐kill assay with amoxicillin. D1 (squares) represents the time‐kill profile during the initial exposure, indicating persistence induction, while D2 (circles) depicts the killing curve of the progeny derived from D1 survivors. (B) Time‐kill assay with gentamicin. D1 (brown squares) corresponds to cells exposed for persistence induction, and D2 (orange circles) represents their progeny. * denotes statistically significant differences (p < 0.05).

In the case of gentamicin (Figure 1B), D1 cultures (brown squares) reached the MDK_99_ in 1.9 ± 0.2 h, followed by a plateau phase, which is consistent with the survival of a persister subpopulation. However, the D2 profile (orange circles) deviated notably from the expected pattern. After an initial decline, a regrowth phase was observed as early as 1 h into the treatment. The failure to reach MDK_99_ within the experimental timeframe suggests a possible rebound in tolerance or the emergence of a heteroresistant phenotype among the progeny. This unexpected behavior contrasts with the partial loss of persistence seen in the amoxicillin group and may reflect antibiotic‐specific dynamics in persistence and posttreatment adaptation.

These findings collectively support the notion that persistence is a transient and heterogeneous state and that the response of bacterial progeny to repeated antibiotic exposure can vary significantly depending on the antimicrobial agent.

SEM analysis provided further evidence of phenotypic alterations associated with persistence in E. coli following exposure to amoxicillin. Persistent cells were induced by treating cultures with the antibiotic at 10X MIC for 3 h. Micrographs obtained from four independent fields (Figure 2A) reveal evident morphological heterogeneity. Red arrows indicate cells exhibiting pronounced structural damage, including surface irregularities and possible membrane compromise, which are likely consequences of antibiotic action on the bacterial cell wall. In contrast, blue arrows mark cells with typical rod‐like morphology and mid‐division constrictions, suggesting that a fraction of the population remained in an active or transitional growth state.

SEM micrographs and size distribution of Escherichia coli. (A) Representative images showing clustered E. coli cells. Blue arrows indicate cells with typical rod‐like morphology, while red arrows highlight those with morphological alterations, including structural damage and size variation. (B) Histogram of cell length distribution, revealing a predominance of cells between 1000 and 1500 nm and a heterogeneous size profile.

To quantify the size distribution and assess whether persistence correlates with morphological alterations, a total of 50 cells were randomly selected across the four fields. The histogram in Figure 2B illustrates a predominant population (70%) with lengths ranging from 1000 to 2000 nm, which aligns with the normal size range for E. coli under standard culture conditions. Interestingly, 18% of cells presented with reduced length (< 1000 nm), a feature that may represent an adaptive mechanism associated with persistence. The reduction in cell size is often interpreted as a metabolic downscaling strategy that facilitates survival under antibiotic stress by conserving energy and minimizing metabolic activity.

Furthermore, 10% of the analyzed cells exhibited moderate elongation (2000–3000 nm), and a small subset (2%) displayed extreme elongation, exceeding 6000 nm. This filamentous morphology is consistent with previously reported stress responses in E. coli, where cell division is inhibited under conditions such as DNA damage, antibiotic exposure, or nutrient deprivation. Such filamentation can represent a transient survival strategy, enabling evasion of immune detection or delay in lysis, thereby increasing chances of population recovery once the stressor is removed.

Altogether, these morphological data support the hypothesis that persistence is accompanied by heterogeneous structural adaptations. However, confirmation of the physiological state of these cells, whether they are truly dormant, viable but non‐culturable (VBNC), or metabolically active, requires complementary assays such as viability staining, RNA profiling, or metabolic flux analysis.

It was observed that the concentrations of 2.5 and 5 μM did not induce significant inactivation, as the bacterial survival rates remained similar to the control group, indicating that these concentrations were insufficient to generate ROS at bactericidal levels. Starting from 10 μM, a reduction of approximately 2 log (CFU/mL) was observed, indicating an initial bactericidal effect. The 15 μM concentration showed a variation between 2 and 3 log (CFU/mL), while 20 μM resulted in a consistent reduction of 3 log (CFU/mL). Higher concentrations, such as 25, 35, and 50 μM, had the most significant impact, reducing the bacterial count by approximately 5 logs (CFU/mL).

These results demonstrate a clear dose–response relationship, where increasing concentrations of MB led to greater bacterial inactivation. The concentration of 10 μM, combined with 10 J/cm^2^ of light, was identified as the initial threshold for significant bactericidal action, while concentrations of 20 μM or higher resulted in more pronounced bacterial reductions. The observed behavior reflects the importance of balancing the FS concentration with the applied light dose to optimize the efficiency of FDI (photoantimicrobial therapy), while avoiding the use of excessive concentrations.

The analysis suggests that concentrations ranging from 10 to 20 μM are suitable for future experiments involving subinhibitory doses, particularly in systems where the goal is to achieve moderate bacterial inactivation without completely eliminating the bacterial population (Figure 3). This is especially relevant in experimental settings aimed at evaluating the bacterial response to FDI in combination with other antimicrobial treatments, such as antibiotics.

Bacterial reduction after irradiation with red light (660 nm) and application of a 10 J/cm2 light dose. The MB concentrations tested were 0 μM (control), 2.5, 5, 10, 15, 20, 25, 35, and 50 μM.

When PDI was applied before the TK assays, a significant reduction in bacterial survival was observed for both antibiotics, highlighting the potentiating effect of PDI on antibiotic efficacy (Figure 4). Compared to the control conditions without PDI (Figure 1), the MDK_99_ values were markedly reduced, indicating a more efficient bacterial killing process and reduced persistence.

(A) Bacterial killing curves following PDI and time‐kill (TK) treatment with amoxicillin, comparing the original strain (D1, squares) and its progeny (D2, circles). (B) Equivalent assay using gentamicin. In both cases, PDI treatment altered the killing dynamics, reducing bacterial persistence and modifying the behavior of the progeny. * denotes statistically significant differences (p < 0.05).

For amoxicillin (Figure 4A), the D1 curve (squares) shows a steeper decline in CFU/mL compared to the non‐PDI group in Figure 1A, with MDK_99_ achieved in 2.5 ± 0.2 h (vs. > 3 h in the absence of PDI). Notably, the progeny (D2, circles), which previously exhibited partial sensitization to amoxicillin in the absence of PDI (Figure 1A), now displayed even greater susceptibility, reaching MDK_99_ in just 1.6 ± 0.2 h. This enhanced killing dynamic suggests that PDI not only amplifies the initial antibiotic effect but may also disrupt mechanisms responsible for the persistence phenotype, thereby sensitizing progeny to subsequent antibiotic exposure.

In the gentamicin group (Figure 4B), the application of PDI similarly influenced the bacterial response, albeit with more moderate effects. On D1, the MDK_99_ reached 3.0 ± 0.1 h, representing a marginal improvement over the original D1 curve in Figure 1B, where the plateau phase indicative of persistence was observed. However, the most striking difference was noted in the D2 group, where MDK_99.99_ was reached in 2.1 ± 0.3 h compared to the regrowth pattern seen without PDI (Figure 1B). The elimination of this regrowth suggests that PDI disrupted the mechanisms underlying the tolerance rebound or heteroresistance observed previously.

Overall, the integration of PDI into the treatment protocol altered the bacterial killing dynamics in a substantial way. Not only did it accelerate bacterial clearance, but it also minimized persistence‐associated survival and attenuated the recalcitrant behavior of progeny derived from stressed parental populations. These observations support the hypothesis that PDI may act synergistically with antibiotics by targeting metabolically inactive or tolerant cells, potentially through the induction of oxidative damage that compromises survival pathways exclusive to persistent phenotypes.

The effects of PDI were further explored by assessing the bacterial response to sequential PDI treatments across two consecutive days (Figure 5), allowing for a direct comparison with the previous findings in Figures 1, 2, 3. In the amoxicillin group (Figure 5A), the killing curve of the D1 population (dark blue squares), which received PDI followed by TK on D1, displayed a faster decline in CFU/mL, reaching MDK_99_ earlier, at approximately 1.8 ± 0.2 h. In contrast, the progeny group (D2, light blue circles), exposed only to TK on D2, required a longer period of about 2.9 ± 0.3 h to reach the same threshold, indicating a slower killing rate. These results indicate that the second PDI exposure further sensitized the progeny, building upon the partial resensitization already observed in Figure 1A and the improved killing noted in Figure 3A. In contrast to the initial persistence profile (Figure 1A, D1), where MDK_99_ was not achieved, the data in Figure 4A illustrate a marked suppression of the persistence phenotype following sequential PDI.

Bacterial killing curves following PDI treatment and exposure to amoxicillin (A), comparing D1 (dark blue squares) and D2 (light blue circles) groups. Panel B shows bacterial behavior after PDI and exposure to gentamicin, where D1 (brown squares) represents cells from the first day and D2 (orange circles) represents the progeny treated on the second day. * indicates statistically significant differences (p < 0.05).

For gentamicin (Figure 5B), the improvement was even more pronounced. Progeny cells treated with PDI on both days (D2, orange circles) reached MDK_99_ in just 1.6 ± 0.2 h, a substantial reduction when compared to the D1 group (brown squares), which required 2.0 ± 0.3 h to achieve MDK_99.99_. These results contrast sharply with the D2 group in Figure 1B, where untreated progeny exhibited regrowth and failed to reach MDK_99_, strongly suggesting that PDI effectively prevented the emergence of heteroresistant or tolerant subpopulations. In addition, when comparing with Figure 4B, it is evident that the D2 population in that experiment exhibited a more rapid suppression of survival due to PDI being applied on both D1 and D2. In contrast, Figure 5B illustrates the cumulative effects of a single‐day PDI treatment, resulting in a slower but still significant reduction in survival. The consolidated MDK_99_ and MDK_99.99_ values further support these observations. For amoxicillin, MDK_99_ dropped from > 3 h in controls (Figure 1) to 2.5 ± 0.2 h in D1 after single‐day PDI (Figure 3) and further to 1.6 ± 0.2 h in D2 after 2‐day PDI (Figure 5), revealing a cumulative sensitizing effect. Similarly, for gentamicin, the D2 group in Figure 1B failed to reach MDK_99_ due to regrowth, while this same group achieved MDK_99_ in 1.6 ± 0.2 h in Figure 5B following dual PDI, eliminating the heteroresistant or tolerant subpopulations. The MDK_99.99_ values further confirmed this trend: under gentamicin pressure, D1 reached this threshold in 4.0 ± 0.3 h, while D2 achieved it more rapidly at 2.1 ± 0.3 h. Together, these results highlight the capacity of repeated PDI to mitigate persistence‐associated survival mechanisms and improve the overall efficacy of antibiotic treatment. The suppression of regrowth phenomena and accelerated bacterial killing curves, especially in D2 populations, suggest that sequential photodynamic therapy may represent a viable adjunctive strategy to overcome bacterial tolerance and persistence in recalcitrant infections.

Discussion

4

The results of this study reinforce that bacterial persistence is a reversible phenotypic adaptation, characterized by survival under high antibiotic concentrations in the absence of an increased MIC. The use of concentrations 10‐fold above the MIC in TK assays effectively eliminated susceptible cells, minimized the selection of spontaneously resistant mutants, and revealed persistent subpopulations—findings consistent with previous reports describing the transient and heterogeneous nature of these cells [8]. In Figure 1A, the amoxicillin TK curve on D1 shows incomplete bacterial clearance, indicative of tolerance. However, on D2, the progeny exhibited a significantly reduced survival, reaching an MDK_99_ of 2.2 ± 0.3 h. This reduction in tolerance may reflect partial regrowth of persisters with incomplete recovery of cellular physiology, including metabolic activity and defense systems. Conversely, Figure 1B presents a classical biphasic pattern for gentamicin on D1, with an MDK_99_ of 1.9 ± 0.2 h followed by a survival plateau. On D2, regrowth was observed after 2 h, with no MDK_99_ reached within 3 h, suggesting the possible selection of heteroresistant subpopulations or metabolic adaptations increasing tolerance in the progeny—a scenario previously described in E. coli under intermittent antibiotic pressure [9]. SEM analysis (Figure 2) revealed morphological heterogeneity after amoxicillin exposure, with evidence of filamentation and cell shrinkage, consistent with dormant states and SOS system activation [10]. These structural alterations support the association between persistence and severe physiological stress.

The introduction of PDI significantly altered the TK curves. When applied before antibiotic exposure on both days (Figure 4A,B), PDI reduced the MDK_99_ for amoxicillin from > 3 to 2.5 ± 0.2 h (D1) and 1.6 ± 0.2 h (D2), and the MDK_99.99_ for gentamicin from 4.0 ± 0.3 to 2.1 ± 0.3 h. These results suggest that PDI sensitizes bacteria by inducing membrane disruption and promoting oxidative stress mediated by ROS, thereby enhancing the bactericidal effects of antibiotics [11]. In Figure 5, the application of PDI on D1 alone resulted in greater gentamicin tolerance in D2 cells compared to D1, where susceptibility was restored. This effect indicates that PDI may interfere with the reprogramming of bacterial physiology, affecting persister formation or delaying metabolic recovery. Therefore, the timing of PDI application appears to be critical for its efficacy as an adjuvant treatment [12, 13]. Furthermore, the enhanced effect observed with two consecutive PDI treatments (Figure 5) reinforces the notion that repeated oxidative stress can progressively compromise bacterial resilience mechanisms. In the case of amoxicillin, the sequential application of PDI further decreased the MDK_99_ of D2 progeny compared to D1 cells, suggesting that cumulative oxidative damage over multiple generations may hinder the reestablishment of tolerance‐related pathways. For gentamicin, where D2 control groups originally failed to reach MDK_99_ (Figure 1B), the dual PDI strategy not only restored antibiotic susceptibility but also accelerated the achievement of MDK_99.99_, eliminating regrowth and persistence signatures. This highlights the capacity of PDI to act as both a direct antimicrobial agent and a physiological modulator that weakens bacterial adaptation. Taken together, these findings emphasize that bacterial persistence is not a static phenotype but a dynamic, stress‐responsive state that can be modulated by targeted interventions. The combination of PDI and antibiotics proved effective in reshaping bacterial survival kinetics, not only by enhancing initial killing (as shown by reductions in MDK_99_) but also by impairing long‐term survival (as evidenced by reduced MDK_99.99_ values and the absence of regrowth). The differential impact on D1 and D2 populations underscores the importance of treatment sequencing and reinforces the potential of PDI to alter bacterial population trajectories across generations. The discrepancy between the effects of amoxicillin and gentamicin can be explained by their distinct mechanisms of action. Amoxicillin targets cell wall synthesis, which may be less effective in dormant cells. Gentamicin, in contrast, relies on active transport to inhibit protein synthesis, making it more sensitive to metabolic alterations and PMF, which is often compromised in persisters [14]. Studies have shown that the maintenance of PMF and the tricarboxylic acid (TCA) cycle is essential for persister survival. Disruption of PMF by compounds such as econazole or colistin has proven effective in eradicating tolerant cells by reducing ATP production and membrane potential. PDI, by inducing oxidative stress, may act via a similar mechanism, expanding its therapeutic potential. The data indicate that PDI represents a promising strategy to overcome bacterial persistence by modulating susceptibility to antibiotics, reducing the time required for bacterial clearance, and preventing regrowth. However, elucidating the underlying molecular mechanisms and standardizing combinatory regimens remain challenges to be addressed for successful clinical implementation.

The findings of this study underscore the dynamic and reversible nature of bacterial persistence, characterized by the transient survival of subpopulations under high antibiotic pressure without alterations in MIC values. The application of PDI using MB and red light significantly enhanced bacterial susceptibility to both amoxicillin and gentamicin, reducing the MDK values and suppressing the persistence phenotype in primary and progeny populations. Morphological evidence further supported the occurrence of structural and physiological adaptations associated with persistence. PDI exerted its effects not only through direct antimicrobial action but also by disrupting cellular processes essential for persistence maintenance, including membrane integrity and metabolic homeostasis. Repeated PDI exposures demonstrated a cumulative impact on bacterial susceptibility, particularly by preventing the rebound of tolerance and promoting accelerated bacterial clearance. The potential of PDI as an effective adjunctive strategy to conventional antibiotic therapy in the treatment of recalcitrant infections was observed.

Funding

This work was supported by Fundação de Amparo à Pesquisa do Estado de São Paulo and Empresa Brasileira de Pesquisa e Inovação Industrial.

Conflicts of Interest

The authors declare no conflicts of interest.