Palmatine and cefquinome sulfate (both 97% purity, Macklin/Yuanye) were dissolved in sterile hot water. Our laboratory collection provided an Escherichia coli strain (ATCC® 25922™) and 19 clinical multidrug-resistant strains isolated from the feces of pigs, dogs, calves, and goats (Supplementary Table S1).

Broth microdilution was conducted using Mueller–Hinton broth (Hope Bio, Qingdao, China) with an inoculum of 1 × 10⁶ CFUs/ml⁻¹. The plates were incubated at 37 °C for 16–20 h, and the MIC was defined as the lowest concentration with no visible bacterial growth. Since cefquinome is not included in the Clinical and Laboratory Standards Institute (CLSI) or the European Committee on Antimicrobial Susceptibility Testing (EUCAST) guidelines, clinical breakpoints for cefquinome were determined based on previous research (Vilaró et al., 2022). Escherichia coli ATCC® 25,922™ was used as the quality-control strain, and all tests were performed in triplicate.

The combined effect of cefquinome and palmatine was evaluated using a checkerboard assay. Briefly, 100 μl of Mueller–Hinton broth was added to each well of a 96-well plate. Cefquinome and palmatine were serially diluted twofold along the x- and y-axes of the plate, respectively. An overnight bacterial culture was diluted 1:100 in Mueller–Hinton broth until the optical density at 600 nm (OD₆₀₀) reached 0.1. The plates were then incubated at 37 °C for 1–20 h, after which the turbidity of each well was measured to assess bacterial growth.

The fractional inhibitory concentration index (FICI) for 20 isolates was measured in triplicate, and the FICI was calculated using the following formula:

The synergistic effect is defined as the effect observed when the FIC index value is ≤ 0.5 (Wachino et al., 2020).

The tested strains were incubated in LB broth (Land Bridge Technology, Beijing, China) at 37 °C until the OD₆₀₀ reached 0.1. After dilution, the strains were evenly divided into conical bottles containing either no palmatine or varying concentrations of palmatine. The initial concentration of bacteria was 5 × 10⁵ CFU (Zhou et al., 2019).

Time-kill assays were used to evaluate the killing effects of cefquinome and palmatine against the tested strains, alone or in combination, by measuring the number of live bacteria at time points up to 24 h. The concentrations of cefquinome and palmatine in the culture medium of E. coli were 0.25 × MIC for the tested strains; the control medium did not contain these drugs. All samples were cultivated at 37 °C. After 0, 1, 3, 5, 7, and 24 h of incubation, 100 μl samples were taken, respectively, and diluted with sterile normal saline. The diluted samples were then inoculated on agar plates at 37 °C overnight, and the number of CFUs was calculated. Each assay was repeated in triplicate.

Overnight bacterial cultures were inoculated into fresh Mueller–Hinton broth media containing either no drug, 0.25 × MIC cefquinome, or 0.25 × MIC cefquinome combined with 0.25 × MIC palmatine. After incubating at 37 °C for 24 h, the cultures were used to determine MIC values in triplicate. Meanwhile, each culture was diluted and transferred to fresh medium to establish the next generation, maintaining the same drug concentrations as in the previous cycle. This process was continued for 10 d.

The tested strains were cultured in MH broth with 0.25 × MIC palmatine, 0.25 × MIC cefquinome, or 0.25 × MIC of the combined drugs for 10 h, respectively. Drug-free MH broth was used as a control. After 10 h, the bacteria were collected and washed with PBS. They were then fixed in 4% glutaraldehyde for 3 h, followed by dehydration in graded ethanol. Before scanning electron microscopy, the bacteria were subjected to critical-point drying in carbon dioxide and gold spraying.

For the biofilm inhibition test, 96-well polystyrene plates were filled with 100 μl of an overnight-cultured bacterial suspension and 100 μl of medium containing either drug-free medium or 0.25 × MIC of single or combination drugs. The biofilm was then cultivated by incubating at 37 °C for 48 h. The bacterial precipitate was washed three times with sterile PBS to remove the floating bacteria. Then, 200 μl of methanol was added to each well for 15 min, and the precipitate was naturally air dried. Each well was stained with 200 μl of 1% crystal violet, incubated at room temperature for 5 min, and washed three times with sterile PBS to remove excess dye. After 10 min of incubation at room temperature, 200 μl of 95% ethanol was added, and the bound crystal violet was eluted. Biofilm formation was measured at OD₅₇₀ nm. All tests were conducted three times, with MH broth as a negative control (Hou et al., 2022).

Confocal laser scanning microscopy (CLSM) was used to assess the inhibitory effects of different drugs on biofilms. Biofilms of the tested strains were cultivated in LB medium in 24-well, glass-bottomed microplates for 24 h at 37 °C under static conditions. The biofilms were then subjected to the drug treatments described above for 24 h, washed, and fixed with paraformaldehyde. Biofilm cells were stained with fluorescent dyes by adding 5 μM of SYTO® 9 green fluorescent nucleic acid stain (Invitrogen, Thermo Fisher Scientific; excitation at 488 nm and emission from 500 to 550 nm) and 5 μM of SYTO® 62 red fluorescent nucleic acid stain (Molecular Probes, Life Technologies; excitation at 652 nm and emission at 676 nm), prepared in 0.9% NaCl, incubated at room temperature for 15 min in the dark, and then washed twice with 0.9% NaCl (Tahrioui et al., 2019).

Multidrug-resistant E. coli E93 was clinically isolated and used in this fluorescence assay. Bacterial pretreatments for all fluorescence measurements were performed using similar protocols. Briefly, the tested bacteria were cultivated overnight at 37 °C, and the cultures were shaken at 200 rpm for 16 h. The tested bacteria were cultured in different medicated media, including drug-free, 0.25 × MIC cefquinome, 0.25 × MIC palmatine, or a combination. Then, the cultures were washed and suspended in PBS. The fluorescent dye was added when the suspension was adjusted to an OD₆₀₀ of 0.5. After incubation at 37 °C for 30 min, the cultures were washed twice using PBS to remove excess unadsorbed fluorescent probes. Fluorescence intensity was measured. Several fluorescent probes were used in this assay as follows.

The bacterial suspensions cultured overnight were evenly mixed with sterile PBS containing 0.25 × MIC cefquinome, 0.25 × MIC palmatine, or both, respectively, and the same volume of drug-free PBS was used as a negative control. The supernatant obtained through centrifugation was incubated at 37 °C for 2 h. The supernatant was filtered through a 0.22-micron membrane, and the bacterial extracellular protein leakage was measured using a BCA protein concentration assay kit (Beyotime, Shanghai, China).

The tested E. coli E93 strain was grown in Mueller–Hinton broth to the early exponential phase and then treated with cefquinome (0.25 × MIC) alone or in combination with palmatine (0.25 × MIC) for 4 h. Each treatment was performed in triplicate. Total RNA was extracted using Trizol reagent (Takara, Tokyo, Japan), quantified using a NanoDrop™ spectrophotometer (Thermo Scientific, MA, USA), and sequenced using the Illumina HiSeq 2000 system (Genedenovo, Guangzhou, China).

mRNA library construction was conducted using the Illumina TruSeq RNA Sample Prep Kit according to the manufacturer’s protocol. Libraries were amplified by bridge PCR with the Illumina TruSeq PE Cluster Kit v3-cBot-HS on a cBot system and sequenced using the HiSeq2000 TruSeq SBS Kit v3-HS (200 cycles) with paired-end reads of 2 × 150 bp (PE150).

Raw sequencing reads were filtered and aligned to the E. coli E93 reference genome. Differentially expressed genes (DEGs) were identified using the FPKM (Fragments Per Kilobase of transcript per Million mapped reads) method, with significance thresholds of p ≤ 0.05 and fold change (FC) ≥ 2 (log₂ FC ≥ 1 or log₂ FC ≤ −1). DEGs were compared between the drug-free and cefquinome-treated groups and between the cefquinome-treated groups. Genes showing reversed expression patterns between these two comparisons were further analyzed.

Sample processing in this experiment followed the same procedure as that used for transcriptome sequencing. E. coli E93 strains were grown to the early exponential phase, incubated, and then treated with cefquinome (0.25 × MIC) alone or in combination with palmatine (0.25 × MIC) for 4 h. Each treatment was performed in triplicate. Then, total RNA was extracted and quantified by its absorbance ratio (260 nm/280 nm). Reverse transcription was performed using the RT reagent kit with gDNA eraser (Dining, Beijing, China). Real-time quantitative PCR (RT-qPCR) was conducted using the SYBR Green qPCR kit (Dining, Beijing, China) on a Tianlong Technology system (Xi’an, China) with optimized primers (Supplementary Table S4). Gene expression levels were analyzed using the 2^-ΔΔCt method.

Swarming Petri dishes (900 mm by 15 mm) contained 20 ml of medium supplemented with 1 mM MgSO₄, 0.2% glucose, 0.5% casamino acids (Land Bridge Technology, Beijing, China), and 0.5% agar (Bru et al., 2019). The medium contained drugs, including 0.25 × MIC cefquinome or 0.25 × MIC combined drugs, and no drugs. The tested strain was cultured overnight (16 to 18 h) at 37 °C. Five microliters of culture were spotted in the center of the medium. Plates were incubated overnight at 37 °C, upright. The diameter of the swimming zone of the tested strain on each plate was measured, and each assay was repeated in triplicate.

The tested strain was cultured overnight from single colonies in LB medium until saturation. It was then inoculated into fresh LB broth containing either no drugs, 0.25 × MIC cefquinome, or 0.25 × MIC cefquinome combined with 0.25 × MIC palmatine, and incubated for 4 h. The bacterial cells were harvested by centrifugation and weighed. The total iron and ferrous ion contents in the bacterial pellets were measured using a Ferrous Ion Colorimetric Test Kit and a Total Iron Ion Colorimetric Assay Kit (Elabscience Biotechnology, Wuhan, China).

The synergistic effect of cefquinome and palmatine was assessed using a checkerboard assay with added taurine uptake inhibitors. β-Alanine is a competitive inhibitor of taurine uptake in E. coli (Jong et al., 2010). Moreover, 5 mM β-alanine was incorporated into Mueller–Hinton broth, and then the change in FICI (Fractional Inhibitory Concentration Index) of palmatine and cefquinome in the presence of the inhibitor was measured.

Female ICR mice aged 6–8 weeks were obtained from Chengdu Dossy Experimental Animals Co., Ltd. (Chengdu, China). The mice were kept at 18–22 °C with 40–60% humidity and acclimated for a week. The Sichuan Experimental Animal Management Committee issued the laboratory animal use license, number SCXK 2021–036. All procedures complied with Northwest A&F University’s laboratory animal management policies and the Guidelines for the Care and Use of Laboratory Animals (ISBN-10: 0–309–15,396-4).

The ICR mice were challenged with a lethal dose of ETEC (1 × 10⁹ CFUs/ml⁻¹, 300 μl) intraperitoneally to induce a systemic infection. The infected mice were randomly assigned to five groups (n = 10): cefquinome (5 mg/kg⁻¹ of body weight), palmatine (10 mg/kg⁻¹ of body weight), a combined drug group, a drug-free control (sterile saline), and a blank control. After 2 h of infection, different treatments were administered to each group of mice. Mouse survival was observed for up to 168 h post-infection.

The ICR mice were inoculated with ETEC (2.5 × 10⁸ CFUs/ml⁻¹, 300 μl) to induce diarrhea. In our preliminary experiment, this dose caused diarrhea in all mice, and they all survived within 24 h. Female ICR mice infected with ETEC were randomly divided into four groups (n = 8). Before the pre-treatment injection, the mice were fasted for 12 h. At the start of the experiment, each mouse was placed in a separate cage covered with filter paper to record their fecal stains.

Mice in different groups were treated with the following treatments: cefquinome (5 mg/kg⁻¹ of body weight, intraperitoneal injection), palmatine (10 mg/kg⁻¹ of body weight, oral gavage), control treatment (intraperitoneal injection and oral gavage with an equal volume of sterile saline), and combination therapy administered 2 h after infection. The mice’s weights were recorded before and 24 h after infection. At 24 h after infection, blood samples were collected simultaneously from the orbit. The mice were anesthetized with Avertin (30 μl /g body weight) (DOWOBIO, Shanghai, China) and euthanized. Liver and intestine samples were then collected.

Here, an evaluation criterion reflecting the severity of diarrhea in mice—loose stools recorded on filter paper—was used in this experiment. The loose stool incidence rate (LSIR) is calculated as the ratio of the number of loose stools to the total number of stools within an animal. The loose stool grade (LSG) is the degree of loose stools, classified into four grades according to the diameter of loose stools on the filter papers: Grade 1 (< 1 cm), Grade 2 (1–2 cm), Grade 3 (2–3 cm), and Grade 4 (>3 cm). The average loose stool grade (ALSG) is calculated as the ratio of the sum of LSGs of each loose stool to the total number of loose stools within an animal. The diarrhea index is calculated by multiplying LSIR by ALSG (Lu et al., 2020).

The dilution plate count evaluated the bacterial load per unit mass of mouse tissue in each group. The collected mouse liver, jejunum, and ileum were weighed. Homogenized tissue and collected anticoagulant blood were diluted in sterilized normal saline containing Triton X-100 (0.05 mol L⁻¹) in multiple dilutions and plated on an LB plate for overnight culture for colony counting. The bacterial content in the tissue was calculated according to the dilution ratio (Guan et al., 2019).

Statistical analysis was performed using GraphPad Prism 9 and SPSS 27.0. All data are presented as mean ± SD. For the in vitro studies, an unpaired t-test was used to calculate p-values for the RT-PCR assay, while one-way ANOVA was used for the other experiments. In the in vivo studies, n represented the number of animals per group, and statistical significance was determined by an unpaired t-test. Differences with a p-value of < 0.05 were considered significant. The number of asterisks indicates significance levels: *p < 0.05, **p < 0.01, ***p < 0.001.

Cefquinome MICs of clinical isolates ranged from 2 to 1,024 μg/ml⁻¹, and palmatine MICs ranged from 2,048 to 16,384 μg/ml⁻¹ (Table 1). The MICs of cefquinome and palmatine for ATCC25922 were 0.08 ± 0.04 μg/ml⁻¹ and 5461.33 ± 2364.83 μg/ml⁻¹ (Table 1). Checkerboard assays revealed synergistic effects (FICI ≤ 0.5) among all 20 strains, with cefquinome MICs reduced by≥ 4-fold (Figure 1d). The mean FICI range was 0.10–0.50, demonstrating consistent potentiation across the tested strains.

The FICI data (Table 1), drug susceptibility results (Supplementary Table S2), and resistance gene profiles of the strains (Supplementary Figure S1) were comprehensively analyzed. The results revealed no direct correlation between the synergistic effect and specific drug-resistance genes or phenotypes. This conclusion is further validated by the consistent synergistic effect observed when combining these drugs with standard strains. Consequently, the synergistic interaction between palmatine and cefquinome exhibits a broad spectrum of activity.

Growth curves confirmed that sub-MIC palmatine (0.25 × MIC) did not affect bacterial proliferation (Figure 2a). Time-kill assays showed that combination therapy (0.25 × MIC each) achieved > 4-log₁₀ CFUs/ml⁻¹ reduction within 24 h, surpassing monotherapy effects (Figures 2b,c). Serial passage experiments demonstrated that palmatine suppressed the development of cefquinome resistance: MICs increased fourfold in cefquinome-only groups but remained stable in combination cohorts (Figure 2d). These results suggest that palmatine treatment could prevent the growth of bacterial resistance.

Scanning electron microscopy (SEM) revealed severe membrane damage in combination-treated cells, including outer membrane perforations (Figure 3a, red arrows). CLSM analysis showed that the combination therapy reduced biofilm thickness and increased the number of cell deaths (Figure 3b). Crystal violet quantification confirmed that biofilm biomass decreased significantly after the combined treatment compared with antibiotics alone (p < 0.01) (Figure 4f).

We further verified that palmatine worsened the damage to bacterial cell membranes caused by cefquinome. To validate our hypothesis, we tested E. coli E93 with cefquinome (0.25 × MIC concentration) and found that the addition of palmatine could enhance the destructive effect of cefquinome on the bacterial outer membrane permeability (p < 0.001) (Figure 4a) and simultaneously cause dissipation of the cytoplasmic membrane potential (p < 0.001) (Figure 4b). Compared with the control group, palmatine monotherapy showed limited efficacy in reducing the intracellular protein leakage of E. coli; its combination with cefquinome significantly potentiated (p < 0.001) (Figure 4c).

In addition, intracellular ROS levels in E. coli increased with the addition of palmatine. The intracellular ROS concentration was also significantly higher in the combination group than in the monotherapy group, indicating that bacterial oxidative damage was intensified (p < 0.001) (Figure 4d).

We previously sequenced the whole genome of E. coli E93 using Nanopore sequencing to provide reference genomes for transcriptome sequencing (Supplementary Figure S2). Transcriptome analysis revealed 4,586 expressed genes across all treatment groups (Figure 5b). After further screening, 174 genes with reversed expression patterns under combination treatment compared to cefquinome alone were identified (Supplementary Table S3). GO and KEGG enrichment analyses highlighted significant changes in ABC transporters, flagellar assembly, two-component systems, and sulfur metabolism (Figures 5c,d). Notably, cefquinome-induced upregulation of genes involved in amino sugar and taurine metabolism was reversed by palmatine (Figure 6). RT-PCR validation confirmed the transcriptomic findings (Figure 7).

Based on the differential change pathway identified by transcriptomic sequencing, we conducted a swarming assay and an iron metabolism experiment to confirm whether this pathway caused phenotypic changes. Bacterial flagellar movement controls swarming, and the two-component system regulates iron metabolism. Swarming assays showed that palmatine restored cefquinome-impaired motility, with swarming diameters increasing from 6.83 ± 1.26 mm to 13.67 ± 2.08 mm (p < 0.05) (Figures 8a,b). Iron quantification revealed that palmatine normalized the Fe²⁺/total Fe ratio, which was significantly elevated by cefquinome treatment (78.69% ± 4.29% vs. 92.21% ± 4.52%, p < 0.05) (Figure 8c).

Our findings revealed a significant change in the synergistic effect when taurine uptake in the sulfur metabolic pathway of Escherichia coli was disrupted. The addition of β-alanine, a competitive inhibitor of taurine uptake, eliminated the synergistic effect of palmatine and cefquinome, shifting the FICI from 0.25 ± 0.03 to 1.12 ± 0.15 (p < 0.05) (Figures 8d,e). These results confirmed the critical role of taurine metabolism in the observed synergistic effect (Table 2).

To evaluate the in vivo therapeutic potential of the palmatine-cefquinome combination, we established two murine models using E. coli 57 (ETEC): a systemic infection model (Figure 9a) and an ETEC diarrhea model (Figure 9c).

Systemic infection model: During the 7-day observation period, all mice in the untreated control and palmatine monotherapy groups succumbed to infection. In contrast, the combination of palmatine and cefquinome significantly improved survival rates from 30% (cefquinome alone) to 60% (Figure 9b).

ETEC diarrhea model: Mice in the combination group exhibited the least weight loss and differed significantly from those in the cefquinome monotherapy group (p < 0.001) within 24 h post-infection (Figure 9e). Histopathology (HE staining) supported reduced tissue damage in combo-treated mice (Supplementary Figure S3). The incidence of loose stools (LSIR) (p < 0.05), the mean loose stools grade (ALSG) (p < 0.05), and the diarrhea index (p < 0.01) were lowest among all groups and were significantly lower than in the control group. At the same time, there was no significant difference in the cefquinome monotherapy group (p > 0.05) (Figures 9f,g).

Quantification of bacterial loads in key tissues demonstrated that the combination treatment significantly reduced colonization in the jejunum (p < 0.05), ileum (p < 0.01), blood (p < 0.01), and liver (p < 0.05) compared to the cefquinome monotherapy group (Figure 10). These findings collectively demonstrate that palmatine potentiates the antibacterial activity of cefquinome in vivo, effectively mitigating ETEC-induced systemic infection and diarrheal pathology while enhancing bacterial clearance.

The global health crisis posed by multidrug-resistant Gram-negative bacteria demands urgent, innovative solutions (Ruegsegger et al., 2022; Tamma and Simner, 2018). With β-lactams losing efficacy against rapidly evolving resistance mechanisms (Kim et al., 2017; López-Jácome et al., 2022), the agricultural use of cephalosporins contributes to the dissemination of zoonotic resistance genes, particularly in veterinary cephalosporins such as the sole fourth-generation cefquinome. Palmatine’s ability to restore drug efficacy in animal-derived strains may disrupt this transmission chain. Adjuvant therapy emerges as a strategic countermeasure (Scientific Advisory Group on Antimicrobials of the Committee for Medicinal Products for Veterinary Use, 2009). This approach leverages existing antibiotics while reducing the pressure to develop resistance, which is a critical advantage given the stagnation in novel antibiotic discovery (Wright, 2016).

Our study identifies palmatine, a bioactive isoquinoline alkaloid from Fibraurea recisa Pierre, as a potent synergist for cefquinome against resistant E. coli. While previous studies have established palmatine’s inhibition of Helicobacter pylori and Escherichia coli, and its efflux pump inhibition against Pseudomonas aeruginosa, we reveal novel mechanisms underlying its synergistic effect with β-lactams (Aghayan et al., 2017; Chen et al., 2020; Rong et al., 2016; Wang P. et al., 2020). Crucially, this synergistic effect transcends specific resistance phenotypes or genotypes, showing consistent potentiation even in reference strains—a finding with broad therapeutic implications.

Palmatine significantly enhanced cefquinome’s membrane-disruptive capacity at sub-inhibitory concentrations (0.25 × MIC), inducing 1.4-fold greater depolarization and a 42% increase in permeability. This membrane destabilization complements β-lactams’ inhibition of cell wall synthesis, creating a dual structural compromise. Furthermore, the combination generated 9.7-fold higher ROS levels than cefquinome monotherapy, exacerbating oxidative damage—a critical factor in bacterial clearance.

Biofilm analysis revealed that palmatine reduced biofilm formation by 36.34% at sub-MIC levels, whereas cefquinome alone showed no effect. The combination further increased biofilm-associated cell death by 9.33%, suggesting that palmatine disrupts this key resistance mechanism. Transcriptomic profiling revealed reversals in several vital pathways: cefquinome upregulated two-component systems and influenced the expression of ABC transporters—known resistance mediators (Azi et al., 2022; Liu et al., 2020)—while downregulating flagellar assembly and sulfur metabolism. Palmatine cotreatment reversed all these adaptations, normalizing nine flagellar genes and seven sulfur metabolism genes to baseline expression levels.

The observed trade-off between flagellar motility and antibiotic resistance supports the resource-allocation theory of microbial physiology. By forcing bacteria to divert energy toward flagellar assembly, palmatine disrupts the metabolic resources needed for efflux pump expression and biofilm matrix production (Lyu et al., 2021)—a vulnerability that can be exploited to reverse resistance.

The role of two-component systems (TCS) pathways as environmental sensors and resistance mediators was particularly evident (Azi et al., 2022; Diagne et al., 2022). Palmatine suppressed cefquinome-induced TCS upregulation, potentially disrupting bacterial stress adaptation. Studies have shown that sulfur metabolism is severely inhibited under β-lactam stress (Bie et al., 2023).

Palmatine effectively reverse-transcribes changes in this pathway, suggesting that metabolic resetting may be a new mechanism for regulating bacterial resistance. The disappearance of the synergistic effect was confirmed by functional inhibition of sulfur metabolism, thereby confirming the key role of this pathway. However, there are few studies on sulfur metabolism at present. To the best of our knowledge, this is the first time that restoring regulatory levels in sulfur metabolism has been associated with the enhanced antimicrobial effects of β-lactams against Gram-negative pathogens. In future research, we need to further investigate the in-depth mechanisms underlying sulfur metabolism regulation and bacterial resistance, providing theoretical support for preventing and controlling antibiotic resistance from a new perspective.

Our research reveals three significant findings: Palmatine synergistically enhances β-lactams’ membrane-disruptive activity by altering membrane dynamics. By forcing energy reallocation from resistance mechanisms to motility, the upregulation of flagellar genes (seven genes restored) breaks the trade-off that bacteria face when allocating energy in response to antibiotic stress—an evolutionary trap that increases antibiotic sensitivity. Under antibiotic stress, the recovery of sulfur metabolism disrupts the bacteria’s survival strategy and diminishes their ability to withstand it.

According to this study, palmatine is a multi-target adjuvant that can reverse bacterial metabolic adaptations to antibiotic stress, interfere with biofilm defenses, and circumvent efflux pump resistance. A new research paradigm has emerged, recognizing that β-lactam resistance is linked to sulfur metabolism. Although earlier research concentrated on membrane proteins and efflux mechanisms (Benameur et al., 2019; Wang et al., 2021), our results show that metabolic pathways are valuable candidates for reversing resistance. The alterations in β-lactam resistance in bacteria will be investigated by expressing and knocking down sulfur metabolic pathway genes using molecular biology of sulfur. Future research should focus on confirming the impact of sulfur metabolism on antibacterial activity in Enterobacteriaceae in vivo and on investigating how iron homeostasis and two-component systems influence bacterial resistance to antibiotics.