Skip to main content
Current Research in Food Science logoLink to Current Research in Food Science
. 2024 Mar 16;8:100718. doi: 10.1016/j.crfs.2024.100718

Rhein against Staphylococcus xylosus by interfering with respiratory metabolism and inducing oxidative stress

Yuyang Li a,c,1, Weiwei Chen a,e,1, Jinxin Ma f,1, Guoying Huang a,e, Guangquan Li a,e, Qiumei He a,e, Xiangyu Kong a,e, Ling Tang a,e, Jinqing Chen a,e, Wenyou Ding b,⁎⁎⁎, Zhongbin Zhang d,⁎⁎, Wenya Ding a,e,
PMCID: PMC10966458  PMID: 38545378

Abstract

Currently, dairy mastitis caused by Staphylococcus xylosus poses a serious challenge for dairy farming. In this study, we explored the role and mechanism of rhein against S. xylosus with the hope of providing new research ideas to solve mastitis in dairy cows and ensure the source safety of dairy products. Through in vitro antimicrobial studies, we found that the minimum inhibitory concentration (MIC) of rhein was 64 μg/mL, and it significantly interfered with the formation of S. xylosus biofilm at sub-MIC. In experiments on mastitis in mice, rhein alleviated inflammation in mammary tissue, reduced the levels of TNF-α and IL-6, and decreased the number of S. xylosus. To explore the anti-S. xylosus mechanism of rhein, we identified the relevant proteins involved in carbon metabolism (Glycolysis/gluconeogenesis, TCA cycle, Fatty acid degradation) through proteomics. Additionally, proteins associated with the respiratory chain, oxidative stress (proteins of antioxidant and DNA repair), and nitrate respiration were also found to be upregulated. Thus, rhein may act as an antibacterial agent by interfering with the respiratory metabolism of S. xylosus and inducing the production of ROS, high levels of which alter the permeability of bacterial cell membranes and cause damage to them. We measured the concentrations of extracellular β-galactosidase and nucleic acids. Additionally, SEM observation of S. xylosus morphology showed elevated membrane permeability and damage to the cell membrane. Finally, RT-PCR experiments showed that mRNAs of key proteins of the TCA cycle (odhA, mqo) and nitrate respiration (nreB, nreC, narG) were significantly up-regulated, consistent with proteomic results. In conclusion, rhein has good anti-S. xylosus effects in vitro and in vivo, by interfering with bacterial energy metabolism, inducing ROS production, and causing cell membrane and DNA damage, which may be one of the important mechanisms of its antimicrobial activity.

Keywords: Rhein, Staphylococcus xylosus, Biofilm, Dairy mastitis, Oxidative stress

Graphical abstract

Image 1

Highlights

  • Rhein has a good bacteriostatic effect and interferes with the biofilm formation of S. xylosus in vitro.

  • Rhein has a good therapeutic effect on mouse mastitis caused by S. xylosus.

  • Rhein interferes with the energy metabolism of S. xylosus, inducing oxidative stress and damaging bacterial DNA and cell membranes.

  • Rhein increases the transcript levels of key proteins in the TCA cycle (odhA, mqo) and nitrate respiration (nreB, nreC, narG).

1. Introduction

Mastitis in dairy cows is a major threat to the dairy industry, causing substantial economic losses globally (Azooz et al., 2020; Alanis et al., 2022; Heikkilä et al., 2018). Additionally, milk from cows with mastitis contains high levels of inflammatory factors, pathogenic bacteria, and residual antibiotics, leading to a significant reduction in nutrition (Ashraf and Imran, 2020; Martins et al., 2020). Currently, antibiotics constitute the primary strategy for treating bovine mastitis (Sharma et al., 2021). It is important to note that prolonged misuse of antibiotics may result in the emergence of superbugs, posing a considerable threat to human health (Torres et al., 2018).

Mastitis in dairy cows caused by coagulase-negative staphylococci is primarily a persistent infection that is challenging to fully cure (Dolder et al., 2017). S. xylosus, originally a foodborne bacterium, has become the predominant strain of coagulase-negative staphylococci in mastitis-affected cows in various regions (Ma et al., 2023; Xu et al., 2015). Furthermore, bacterial biofilm formation is a key factor complicating the treatment of bovine mastitis in clinical practice (Bohl et al., 2021). Clinical isolates of S. xylosus have been shown to possess a high capacity for biofilm formation (Tremblay et al., 2013). These biofilms exhibit complex three-dimensional structures composed of bacterial aggregates (Fulaz et al., 2019). Their formation significantly enhances bacterial antibiotic resistance and provides protection against immune cells, thereby greatly increasing the likelihood of survival in hostile environments (Luo et al., 2021; Jamal et al., 2018).

To address the challenges posed by S. xylosus infections and drug resistance, there is an urgent need to discover new antimicrobial drugs (Kot et al., 2012). A promising approach for identifying novel antimicrobials, which may have low toxicity and a reduced likelihood of resistance development, involves exploring natural medicines (Liu et al., 2022). Rhein, a crucial active ingredient in traditional Chinese medicines like Rheum palmatum and He Shou Wu, is chemically known as 4,5-dihydroxyanthraquinone-2-carboxylic acid (Cheng et al., 2021). Rhein exhibits a broad spectrum of pharmacological activities, including anti-inflammatory, anti-tumor, hypoglycemic, and bacteriostatic effects (Gao et al., 2014; Liu et al., 2021). It has demonstrated effective antibacterial properties against Porphyromonas gingivalis, Staphylococcus aureus, Methicillin-resistant Staphylococcus aureus (MRSA) and so on (Liao et al., 2013; Yu et al., 2008; Raghuveer et al., 2023; Peerzada et al., 2022). However, little is known about the antibacterial effect of rhein against S. xylosus. Therefore, exploring the antibacterial potential of rhein against S. xylosus holds significance for the prevention and control of mastitis in dairy cows.

In this study, we investigated the role of rhein against S. xylosus through a combination of in vitro and in vivo experiments, along with proteomic techniques. In the in vitro antimicrobial experiments, we observed that rhein significantly interfered with biofilm formation at sub-inhibitory concentrations. Furthermore, it demonstrated favorable anti-inflammatory and antibacterial effects in a mouse model of mastitis. Proteomic studies revealed significant up-regulation of proteins associated with the tricarboxylic acid cycle pathway, fatty acid metabolism pathway, respiratory chain-related proteins, antioxidant proteins, and DNA repair proteins under rhein-induced stress. Fatty acid metabolism played a crucial role by providing substantial acetyl coenzyme A for the TCA cycle, generating significant amounts of NADH and FADH2 for the oxidation of the respiratory chain. This resulted in a heightened electron flow through the respiratory chain, creating an opportunity for electron leakage. Additionally, quinones, capable of forming semiquinones in the presence of electrons, transferred electrons to molecular oxygen, resulting in the generation of reactive oxygen species (ROS) (Linzner et al., 2020). Rhein, being an anthraquinone, shared this ability, facilitating the transfer of electrons from the respiratory chain to molecular oxygen and contributing to ROS formation (Egerer et al., 1982). Consequently, S. xylosus responded to oxidative stress by upregulating antioxidant proteins and DNA repair proteins. Surprisingly, our proteomic data revealed the upregulation of the key protein involved in nitrate respiration, which provides H+ for ATP synthesis under anaerobic conditions in S. xylosus. This phenomenon was attributed to the substantial consumption of molecular oxygen by S. xylosus, creating a hypoxic environment for the bacteria. In summary, the antimicrobial effect of rhein is achieved by interfering with respiratory metabolism and inducing ROS generation in S. xylosus. Our exploration of the impact of rhein on S. xylosus aims to provide novel insights for the treatment of mastitis in dairy cows, contributing to the enhancement of milk quality and safety from the product source.

2. Materials and methods

2.1. Materials

Rhein (purchased from Shanghai Aladdin Bio-Chem Technology Co.), TSB (purchased from Qingdao Biotechnology Co.), Crystalline violet (purchased from Shanghai Yuanye Bio-Technology Co.), Methanol and glutaraldehyde (purchased from Shanghai Macklin Biochemical Co.), The β-galactosidase activity assay kit (purchased from Beijing Solarbio Science & Technology Co.), TNF-α and IL-6 Elisa assay kit (purchased from Shanghai Enzyme-linked Biotechnology Co., Ltd.). Reactive oxygen species assay kit (purchased from Biosharp Life Sciences).

Scanning electron microscope (GE Co., USA.), Analytical balance (Shanghai Zhixin Experimental Instrument Technology Co.), Benchtop centrifuge (Beckman Coulter, USA.), Spectrophotometer (Shanghai, Deacon Shanghai Co.).

2.2. Minimum inhibitory concentration of rhein on S. xylosus

Rhein was weighed precisely and dissolved in sterile 0.5% (v/v) ammonia water solution to give a final concentration of 5.12 mg/mL. Using the multiplicative dilution method, the rhein solution was diluted in different concentrations with sterile TSB culture solution and set aside. In the same method, different concentrations of ammonia were prepared as solvent control. S. xylosus (ATCC 700404, purchased from the American Strain Preservation Center) was cultured on TSB agar medium in a 10-cm glass petri dish at 37 °C for 18 h. The minimum inhibitory concentration (MIC) was determined using the broth microdilution method, as per the guidelines set by the Clinical Laboratory Standard Institute (CLSI). Briefly, a single colony of S. xylosus was obtained from the petri dish and grown overnight at 37 °C. The overnight cultures were then diluted in sterile physiological saline to achieve a concentration of 1×108 colony-forming units/mL (CFU/mL). Subsequently, these cultures were further diluted 1:1000 using TSB. Finally, 180 μL of the S. xylosus samples were added to the wells of a 96-well plate, along with 20 μL of different concentrations of rhein in the culture medium. Bacterial control, the solvent control and medium control were incubated without the treatment of rhein. After 16 h of incubation at 37 °C, the MIC was defined as the lowest concentration of rhein that prevented growth. All the assays were conducted in triplicate.

2.3. Rhein intervenes in the formation of S. xylosus biofilm

S. xylosus was cultured overnight at 37 °C. After adjusting the bacterial solution concentration to 1×105 CFU/mL, 180 μL of the bacterial solution was added to a 96-well culture plate. Rhein solution was then added to achieve final concentrations of 1/2, 1/4, 1/8, and 1/16 times the MIC. The plate was incubated at 37 °C for 24 h. Following incubation, the bacterial solution was discarded, and the wells were rinsed with sterile PBS. After air-drying, 200 μL of 99% methanol was added and left for 30 min. The methanol was then discarded. Subsequently, 200 μL of 0.1% crystalline violet was added for 30 min, followed by rinsing. After air-drying, 200 μL of 33% glacial acetic acid was added, and the plate was shaken for 30 min. Negative and positive controls were also cultured. Each group underwent three parallel experiments.

S. xylosus was cultured overnight at 37 °C. After adjusting the bacterial solution concentration to 1×108 CFU/mL, and added to the culture plate with sterile glass slides, then rhein solution was added to the culture plate to a final concentration of 1/2MIC, and S. xylosus bacterial solution was used as the control group, and the incubation was allowed to stand at 37 °C for 24 h. After that, the biofilm was rinsed with sterile PBS, and glutaraldehyde was added, and which was kept away from the light under the condition of 4 °C for overnight. Finally, after washing with PBS, dehydrating, drying for 6 h, coating, and observing, the morphology of S. xylosus biofilm was examined by scanning electron microscope (SEM).

2.4. Treatment of mice mastitis with rhein

S. xylosus was cultured overnight at 37 °C, and the concentration of the bacterial solution was adjusted to approximately 1×109 CFU/mL and set aside. Fifteen female Kunming mice, 7 days after delivery, were acclimatized for 3 days and then randomly divided equally into 3 groups. The mice were fasted from food and water the day before the test.

The negative control group was neither infected nor treated. In the mastitis model group (injected with S. xylosus for 24 h), 100 μL of S. xylosus solution was injected into the fourth pair of nipples of each female rat. In the rhein treatment group, 100 μL of the S. xylosus solution was injected into the fourth pair of nipples of each female rat, and 24 h later, the breasts were perfused with 100 μL (40 μg/kg) rhein solution.

Twenty-four hours after infection, the female mice in the control group and the model group were euthanized. After 48 h, the female mice in the rhein-treated group were sacrificed. The mice were then disinfected with 75% alcohol, and the mammary glands were dissected and exposed to observe the mammary gland changes in each group. Finally, a portion of the breast tissue was placed into paraformaldehyde and stained with H&E.

Approximately 0.01 g of mammary gland tissue was homogenized in 1 mL of sterile saline. Subsequently, 0.04 mL of the homogenate was applied to TSB agar plates, and the number of S. xylosus was determined by colony counting. The homogenate was centrifuged, and the concentration of TNF-α and IL-6 was measured according to the instructions provided with the ELISA kit.

2.5. Proteomics research

2.5.1. Protein extraction and TMT labeling

Protein was extracted from S. xylosus that were treated with 1/2MIC rhein and without rhein. The cells were stored at −80 °C prior to use. The samples were sonicated three times on ice using a high-intensity ultrasonic processor (Scientz) in lysis buffer (8M urea, 1% Protease Inhibitor Cocktail). The remaining debris was removed by centrifugation at 12,000 r/min at 4 °C for 10 min. Finally, the supernatant was collected, and the protein concentration was determined with a BCA kit according to the manufacturer's instructions.

After trypsin digestion, peptides were desalted by a Strata X C18 SPE column (Phenomenex) and vacuum-dried. The peptides were reconstituted in 0.5M TEAB and processed according to the manufacturer's protocol for the TMT kit. Briefly, one unit of TMT reagent was thawed and reconstituted in acetonitrile. The peptide mixtures were then incubated for 2 h at room temperature, pooled, desalted, and dried by vacuum centrifugation.

2.5.2. HPLC fractionation

The tryptic peptides were fractionated into fractions by high-pH reverse-phase HPLC using a Thermo Betasil C18 column (5 μm particles, 4.6 mm diameter, 250 mm length). Briefly, peptides were initially separated with a gradient of 8%–32% acetonitrile (pH = 9.0) over 60 min into 60 fractions. Subsequently, the peptides were combined into 14 fractions and dried by vacuum centrifugation.

2.5.3. LC-MS/MS analysis

The tryptic peptides were dissolved in 0.1% formic acid (solvent A) and directly loaded onto a homemade reversed-phase analytical column (15 cm length, 75 μm i.d.). The gradient consisted of an increase from 8% to 22% solvent B (0.1% formic acid in 98% acetonitrile) over 20 min, followed by 22%–35% in 8 min, climbing to 80% in 3 min, and holding at 80% for the last 3 min, all at a constant flow rate of 500 nL/min on an EASY-nLC 1000 UPLC system.

The peptides were subjected to a nanospray ionization (NSI) source followed by tandem mass spectrometry (MS/MS) in a Q ExactiveTM Plus (Thermo) coupled online to the UPLC. The electrospray voltage applied was 2.2 kV. The scanning range of primary mass spectrometry was set to 400–1500 m/z, and the scanning resolution was set to 70,000. The scanning range of secondary mass spectrometry was fixed at 100 m/z, and the resolution of secondary scanning was set at 17,500. In the data collection mode, the data-dependent scan (DDA) program was used. After the first-level scan, the parent ions of the top 20 peptide segments with the highest signal intensity were selected to enter the HCD collision cell sequentially and fragment with 30% fragmentation energy. The second-level mass spectrometry analysis was also performed successively. To improve the efficiency of MS, the automatic gain control (AGC) was set to 5E4, the signal threshold was set to 63,000 ions/s, the maximum injection time was set to 80 ms, and the dynamic exclusion time of tandem MS scan was set to 30 s to avoid repeated scanning of parent ions.

2.5.4. Database search

The resulting MS/MS data were processed using the MaxQuant search engine (v.1.5.2.8). Tandem mass spectra were searched against the human Uniprot database concatenated with a reverse decoy database. Trypsin/P was specified as the cleavage enzyme, allowing up to 2 missing cleavages. The mass tolerance for precursor ions was set at 20 ppm in the First search and 5 ppm in the Main search, and the mass tolerance for fragment ions was set at 0.02 Da. Carbamidomethyl on Cys was specified as a fixed modification, and acetylation modification and oxidation on Met were specified as variable modifications. The false discovery rate (FDR) was adjusted to < 1%, and the minimum score for modified peptides was set >40.

2.5.5. Bioinformatics

The GO annotation information of the proteins was primarily sourced from the UniProt-GOA database (http://www.ebi.ac.uk/GOA/). Initially, protein IDs were converted to UniProtKB database IDs, and the corresponding GO annotations were then retrieved from UniProt-GOA based on the UniProKB IDs. In cases where identified proteins lacked annotations in the database, the GO classification of the protein was annotated using the InterProScan sequence alignment.

For the annotation of protein metabolic pathways, the Kyoto Encyclopedia of Genes and Genomes (KEGG) database was utilized. Initially, the KEGG online service tool KAAS was employed to annotate the proteins, obtaining the KO numbers corresponding to the KEGG database. Subsequently, the KO numbers were mapped to specific biological pathways using the KEGG online service tool KEGG mapper.

The differential protein database numbers or protein sequences obtained by screening in different comparison groups were extracted from the differential protein interactions, considering a confidence score >0.7, after comparing with the STRING (v.10) protein interactions network database. The resulting differential protein interaction network was then visualized using Cytoscape software.

2.6. Effect of drugs on bacterial cell membrane permeability

2.6.1. Determination of β-galactosidase

After overnight growth of S. xylosus in sterile medium at 37 °C, a culture (5 mL) was taken and centrifuged at 5000 r/min for 5 min. The supernatant was then discarded, and sterile PBS was used to wash the bacterial cells. Rhein was added to the PBS-cells mixture and mixed evenly to achieve a final drug concentration of 1/2MIC. Cells treated with rhein were cultured in a shaking incubator at 37 °C for different durations, with untreated bacteria used as a control. After incubation, the supernatant was discarded by centrifugation, and the bacteria were resuspended in PBS. The bacteria were disrupted by ultrasound for 90 s, followed by centrifugation at 15,000 r/min at 4 °C for 10 min. The supernatant was collected and processed according to the kit's operational method.

2.6.2. Determination of nucleic acid

S. xylosus was grown overnight at 37 °C. The overnight cultures were taken, and washed with 0.9% NaCl to remove excess media, and the absorbance at 630 nm was adjusted to 0.5 ± 0.02. Rhein solution was then added and mixed with the aforementioned S. xylosus suspension to achieve a final concentration of 1/2MIC. The mixture was incubated in a shaking incubator at 37 °C for 0, 1, 2, 4, 6, and 8 h. After incubation, the samples were centrifuged at 12,000 r/min for 3 min and filtered. The absorbance value of the filtrate was measured by spectrophotometer at 260 nm, and each group was conducted in triplicate. The bacterial suspension without the added drug served as the control.

2.6.3. Scanning electron microscopy (SEM) observation

S. xylosus was grown overnight at 37 °C. The bacterial solution was centrifuged at 5000 r/min for 5 min, and the supernatant was discarded. The cells were then resuspended in physiological saline and 1/2MIC rhein solution, respectively, and cultured in a shaking incubator at 37 °C for 1.5 h. After fixing with dialdehyde, washing with PBS, dehydrating, drying for 6 h, coating, and observing, the morphology of S. xylosus was examined by SEM.

2.7. Determination of ROS

S. xylosus was grown overnight at 37 °C. The bacterial solution was adjusted to OD600nm = 0.5 with 0.9 % saline, respectively, and 2 mL of the culture was centrifuged at 8000 r/min for 1 min. The bacteria were resuspended using 2 mL of TSB medium and rhein solution was added to make the concentration of 2MIC and MIC, and incubated at 37 °C for 2 h. After the incubation, the cell were washed once with PBS and 20 μmol 2′,7′-dichlorodihydrofluorescein diacetate (DCFH-DA) probe was added and incubated for 30 min (protected from light, 37 °C). The bacteria were washed twice with PBS, and 200 μL of 0.9 % saline was added to resuspend the bacteria. Take 10 μL drops into a confocal dish and observe the green fluorescence under a laser confocal microscope. Also, a control group without rhein treatment was set up as described above.

2.8. RT-PCR

Key proteins identified in the proteomics data were selected for further examination at the mRNA level using RT-PCR. Centrifuge to collect bacteria, use RNA extraction kit to extract RNA, and also utilize NanoDrop 2000 Ultra-Micro Spectrophotometer to measure RNA, and quickly utilize reverse transcription kit to reverse transcribe 500 ng of RNA into cDNA, and put the reverse transcribed cDNA into −20 °C for storage. The PCR reaction system for fluorescence quantification is shown in Table 1, and the reaction program is shown in Table 2.

Table 1.

The PCR reaction system.

Component Volume
cDNA 0.6 μl
Fast Start DNA Master SYBR Green 5 μl
Forward primers 0.3 μl
Reverse primers 0.3 μl
ddH2O 3.8 μl
Total 20 μl

Table 2.

The PCR reaction process.

Temp (°C) 98 °C 40 cyclcs
72 °C 4 °C
98 °C 60 °C 68 °C
Time 3:00 0:15 0:15 0:15 2:00

2.9. Statistical analysis

In this study, values were expressed as the mean ± standard deviation. One-way ANOVA were performed to examine the statistical differences among the different groups, and P value < 0.05 indicated a significant difference.

3. Results and discussion

3.1. MIC of rhein

The MIC of rhein against S. xylosus was determined by microdilution method. The results showed that the MIC of rhein against S. xylosus was 64 μg/mL, and the solvent do not inhibit the growth of bacteria (Table 3).

Table 3.

MIC experimental results.

Groups Different concentrations rhein (μg/mL)
256 128 64 32 16 8 4 2
Rhein-treated-1 + + +
Rhein-treated-2 + + +
Rhein-treated-3 + + +
Solvent control
Untreated
Culture medium + + + + + + + +

Symbols are: “+” indicates clarified microwells (inhibited); “-” indicates turbid microwells (uninhibited).

3.2. Effect of rhein on biofilm

The intervention of rhein at 1/2MIC on the biofilm formation of S. xylosus was determined by crystalline violet staining. As shown in Fig. 1A, sub-MICs (1/2MIC, 1/4MIC, and 1/8MIC) of rhein significantly interfered with the formation of S. xylosus biofilm. Furthermore, Rhein interfered with the S. xylosus biofilm at different time points under 1/2MIC conditions (Fig. 1B). The results evidenced that rhein has the effect of interfering with the biofilm of S. xylosus.

Fig. 1.

Fig. 1

Effects of rhein on S. xylosus biofilm formation. (A) Effect of sub-MICs of rhein on biofifilm formation. (B) Effect of 1/2MIC of rhein on biofilm at different time points. Symbols are: *P<0.01. (C) SEM observation of the biofilm. a: Bacterial control group; b: Rhein-treated group.

The morphology of S. xylosus biofilm was observed by SEM. Fig. 1C–a shows the biofilm morphology of the bacterial control group, with bacteria closely arranged on the slide surface. Fig. 1C–b shows the biofilm morphology of S. xylosus after 1/2MIC rhein treatment, the colonies were sparser than the control group, which interfered with the biofilm formation. The results showed that rhein had a good intervention effect on the formation of S. xylosus biofilm, which was consistent with the results of crystal violet staining method.

3.3. Mastitis in mice treated with rhein

3.3.1. Clinical observations

It has been demonstrated that the mammary gland structure of mice is similar to that of cows, allowing for the simulation of the bacterial-immune system interaction environment in the mammary gland of cows. Therefore, mice are widely used as a research model for mastitis in cows (Hu et al., 2023). By observing the mammary gland redness and swelling in mice, a successful mouse mastitis model was established, and rhein exhibited promising therapeutic effects on mastitis in mice. The pathological changes of mammary glands in female rats are depicted in Fig. 2A. In the negative control group, the female mammary glands appeared milky white with no observable redness or swelling. In the mouse mastitis model, the mammary glands displayed evident redness and swelling, indicating the successful establishment of the mouse mastitis model. In the rhein-treated group, the female mammary glands exhibited a light red color, and the inflammation was visibly reduced, providing evidence that rhein could effectively treat mastitis in mice.

Fig. 2.

Fig. 2

Rhein for the treatment of mastitis in S. xylosus-infected mice. (A) Observation of tissue and pathological tissue sections. Sections of the control group and the model group were magnified 200 times. Sections of the rhein-treated group were magnified 400 times. (B) Determination of TNF-α and IL-6. (C) Tissue colony counting. Symbols are: *P<0.01.

3.3.2. Pathological tissue sections

During bacterial infection, the infected tissues exhibited obvious inflammatory symptoms of redness and swelling, accompanied by pathological changes (Wang et al., 2018). The efficacy of rhein was assessed by observing the morphology of mammary cell walls and inflammatory cells in mice through sections, and the experimental results are depicted in Fig. 2A. The negative control group demonstrated that the mammary cell wall structure of female mice was intact without pathological changes. In the mouse mastitis model, the glandular vesicle wall was incomplete, and a large number of inflammatory cells were present, confirming the successful establishment of the mouse mastitis model. Upon observing the sections of the rhein-treated group, it was evident that the inflammation symptoms were significantly reduced, the mammary tissue was more intact, and there were fewer inflammatory cells. This finding provided evidence that rhein could effectively treat mastitis caused by S. xylosus in mice. Furthermore, the pathological section results were consistent with the anatomical observations.

3.3.3. Determination of TNF-α and IL-6

Furthermore, rhein can inhibit NF-κB and NALP3 inflammatory pathways, thereby attenuating inflammatory responses (Ge et al., 2017). To assess the therapeutic effect of treatment groups on inflammation, we measured the concentration of inflammatory cytokines in mammary tissue using an ELISA kit. The results demonstrated that rhein significantly reduced TNF-α and IL-6 compared to the model group (Fig. 2B), which was consistent with the trend observed in the pathological section experiments.

3.3.4. Tissue colony counting

The antimicrobial effect of the different treatment groups in vivo was assessed by colony counting, and the results are presented in Fig. 2C. S. xylosus was not found in the blank group, while there was a substantial number of S. xylosus colonies in the mammary glands of the model rats. After treatment with rhein, the number of colonies in the mammary glands of mice significantly decreased, indicating that rhein had a potent antibacterial effect on S. xylosus in vivo. The colony count results were consistent with the trend observed in the TNF-α and IL-6 inflammatory factor content assay.

3.4. Proteomics to explore the mechanism of antibacterial action

Rhein demonstrated a significant anti-S. xylosus effect both in vivo and in vitro. A proteomic approach was employed to investigate the differences in protein expression between 1/2MIC rhein-treated and untreated bacteria. In this study, TMT labeling, HPLC separation, and LC-MS/MS analysis were utilized for the quantitative analysis of the proteome. A total of 2,665 proteins were detected in S. xylosus, out of which 2,345 provided quantitative information. Among them, 239 proteins exhibited differential expression between the rhein-treated and untreated groups, with a fold change of >1.5 or <1/1.5 (P < 0.05). Specifically, 182 proteins were up-regulated, and 57 proteins were down-regulated. (Fig. 3).

Fig. 3.

Fig. 3

Differentially expressed proteins. (A) Quantitative volcano plot of differential proteins. (B) Histogram of differential proteins. Red color represents differential protein upregulation and blue color represents differential protein downregulation. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

3.4.1. GO enrichment analysis

Gene Ontology (GO) serves as a crucial bioinformatics analysis method and tool for expressing various properties of genes and their products (Milano, 2022). GO annotations are categorized into three groups: Biological Process, Molecular Function, and Cellular Component, providing insights into the biological roles of proteins from different perspectives (Ding et al., 2018). The differential proteins obtained from the experiments underwent GO enrichment analysis, with the results depicted in Fig. 4A. In the Biological Process classification, the enriched processes mainly involved metabolic activities such as citrate metabolic process, tricarboxylic acid metabolic process, and enzyme active site formation. Within the Molecular Function classification, the differential proteins were predominantly enriched in activities such as cofactor binding, coenzyme binding, and oxidoreductase activity. In the Cellular Component classification, the differential proteins were mainly associated with structures such as the oxidoreductase complex, oxoglutarate dehydrogenase complex, and dihydrolipoyl dehydrogenase complex. GO enrichment analysis indicated that the mechanism of action of rhein against S. xylosus may be related to carbon metabolism and oxidative stress.

Fig. 4.

Fig. 4

GO enrichment and KEGG pathway enrichment. (A) Statistical histogram of significantly enriched GO terms. (B) Proteins involved in KEGG pathways.

3.4.2. KEGG pathway enrichment

The KEGG pathway serves as an information network connecting known molecular interactions, including metabolic pathways, complexes, and biochemical reactions (Zhou et al., 2018). KEGG pathway analysis enhances our understanding of the effects of rhein on bacteria. Based on the annotation results of all identified differential proteins in the KEGG database, all proteins were mapped to 32 KEGG pathways. The top 20 pathways with significant differences were selected (Fig. 4B), primarily involving Glycolysis/Gluconeogenesis, Pyruvate metabolism, Citrate cycle (TCA cycle), amino acid metabolism, and fatty acid degradation, among others. The results of KEGG analysis were predominantly associated with the metabolism of substances, aligning with the findings of the GO enrichment analysis.

3.4.3. Proteins interactions

The differential protein interaction network was visualized using the 'Cytoscape' tool, as illustrated in Fig. 5. To depict protein-protein interactions (PPI), we screened the top 50 proteins with the closest interactions to construct the PPI network. Within the PPI map, we identified proteins associated with the TCA cycle, fatty acid degradation, DNA repair, and nitrate respiration. These findings were consistent with the results of both GO and KEGG analyses, which also indicated an association with the TCA cycle and fatty acid degradation.

Fig. 5.

Fig. 5

Protein-protein interactions. The circles in the figure indicate differentially expressed proteins and the different colors represent the differential expression of the proteins (Blue for down-regulated proteins and red for up-regulated proteins). The size of the circles represents the number of differentially expressed proteins and their interactions. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

The essence of proteomics is to study various features of proteins, such as protein expression levels, post-translational modifications, and protein interaction information, on a large scale (Aslam et al., 2017). These data contribute to a comprehensive and holistic understanding of cellular metabolism, disease pathogenesis, and other processes. In our proteomic study, we identified 239 differential proteins under rhein stress. Through GO, KEGG, and PPI analyses, we found that these differential proteins were primarily involved in bacterial material metabolism and energy conversion.

3.4.4. Effect of drugs on bacterial TCA cycle proteins

The tricarboxylic acid (TCA) cycle serves as the central hub of substance metabolism in living organisms (Akram, 2014). Bio-oxidation of sugars, lipids, and amino acids in vivo will all produce acetyl CoA, which then enters the TCA cycle for degradation. Past studies have shown that bacteria can promote bacterial resistance by inhibiting the TCA cycle (Alkasir et al., 2018; Gaupp et al., 2015). The promotion of the TCA cycle correlates with ROS production and can promote the ability of bacteria to take up drugs (Fan et al., 2023). Therefore, alterations in TCA cycle activity are of great significance for bacterial survival. Among our differential proteins, TCA-related proteins were found to be upregulated. The effect of rhein on TCA cycle pathway proteins was shown in Tables 4,7 significantly different proteins were measured. A0A418I6B8 (mqo), A0A418IAU5/A0A5F0VF38 (odhA), A7KJJ3 (lpdA), A7KJH7 (sucB), and A0A418I9W9 (fumC), the up-regulation of these key proteins, could promote the TCA cycle (Han et al., 2008; Paudel et al., 2023). The upregulation of odhA, lpdA, and sucB promotes the conversion of α-ketoglutarate to succinyl-CoA. Upregulation of fumC promotes the conversion of fumarate to malate. Upregulation of mqo promotes the conversion of malate to oxaloacetate. Extracellular polysaccharides, and polysaccharide intercellular adhesion (PIA), which is associated with virulence and biofilm formation (Htt et al., 2020). However, the promotion of the TCA cycle, which reduces the entry of fructose 6-phosphate into the PIA synthesis pathway (Sadykov et al., 2008; Vuong et al., 2005), may be one of the reasons why rhein affects the formation of biofilms in S. xylosus (Fig. 6).

Table 4.

Proteins associated with the TCA cycle.

Accession Protein description Gene name Fold change P-value
A0A418I6B8 Probable malate:quinone oxidoreductase mqo 1.746 0.00014
A0A418IAU5 2-oxoglutarate dehydrogenase E1 component odhA 2.103 0.00068
A0A5F0VF38 2-oxoglutarate dehydrogenase E1 component odhA 2.022 0.00014
A0A5F0VH36 2-oxoacid:acceptor oxidoreductase subunit alpha E4T72_00635 2.581 0.00173
A0A512SQ30 2-oxoacid:ferredoxin oxidoreductase subunit beta E4T72_00640 2.996 5.24E-08
A7KJJ3 Dihydrolipoyl dehydrogenase lpdA 1.554 0.00017
A7KJH7 Dihydrolipoyllysine-residue succinyltransferase component of 2-oxoglutarate dehydrogenase complex sucB 1.523 1.68E-06
A0A418I9W9 Fumarate hydratase class II fumC 1.649 3.75E-07
Table 7.

Proteins associated with the antioxidant proteins.

Accession Protein description Gene name Fold change P-value
Q6PXX2 Catalase (Fragment) katA 1.79 0.00654
Q9EV50 Catalase A katA 1.819 0.00358
A0A418IKB1 Organic hydroperoxide resistance protein-like 1 Ohr 1.623 0.00012
A0A2T4QDA0 Thioredoxin BU098_12235 1.913 4.17E-05
A0A512SPC2 thioredoxin reductase (NADPH) trxB 1.516 0.00176
A0A5F0VAL2 Alkyl hydroperoxide reductase subunit F ahpF 2.142 0.00044
Fig. 6.

Fig. 6

Mechanism of anti-S. xylosus by rhein. Red font represents up-regulated and green represents down-regulated. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

3.4.5. Effect of drugs on the respiratory chain of bacteria

The TCA cycle is promoted and more acetyl CoA is consumed, resulting in a large amount of NADH (Navas and Carnero, 2021). NADH passes through the electron respiratory chain to produce ATP (Luengo et al., 2021). Complex I in the respiratory chain is a giant flavin protein complex, including at least 34 peptide chains with flavin proteins (FMN as a cofactor) and iron-sulfur proteins. In our proteomics data, flavin-related proteins (C6ZDJ8, A0A5F0VCX2) and iron-sulfur cluster assembly protein (A0A418I8J2) were found to be significantly upregulated (Table 5). In GO enrichment analysis, 4 Iron-4 sulfur cluster binding was also significantly upregulated. The hydrogen shed by NADH is passed to ubiquinone (UQ) via complex I to produce UQH2. The UQH2 generates 2H+ and electrons 2e-. Electrons is passed from cytochrome C to complex IV and then to oxygen to generate O2-. In the process of biological oxidation, molecular oxygen must receive 4 electrons to be completely reduced to 2O2- to produce water by H+ binding. If there is a leakage of electrons in the electron transfer chain, the peroxide group O22- or superoxide ion (O2-) is generated (Zhao et al., 2019). Peroxide group O22- can combine with H+ to produce H2O2. However, H2O2 has certain physiological roles in the body, for example, granulocytes can produce H2O2 which can be used to kill engulfed bacteria (Root and Metcalf, 1977). Superoxide ions O2-, H2O2, and –OH are collectively referred to as reactive oxygen species (ROS), which are strongly oxidizing, and high concentrations of ROS can be very harmful to organisms (Yang and Lian, 2020). Furthermore, rhein can not only bind competitively with NADH to the relevant sites of complex I, but also readily accepts electrons itself (Egerer et al., 1982). The antimicrobial and toxic effects of quinones are attributed to their electrophilic and oxidizing properties. As an anthraquinone, rhein can form an ‘redox cycling’ (Fig. 6). Rhein (4,5-dihydroxyanthraquinone-2-carboxylic acid) can bind 2H+ in the presence of 2e- and enzymes to produce 4,5,9,10-tetrahydroxyanthraquinone-2-carboxylic acid. Molecular oxygen can gain electrons to form reactive oxygen species, through the electron giving of 4,5,9,10-tetrahydroxyanthraquinone-2-carboxylic acid. This may lead to an insufficient supply of electrons to the electron transport chain, generating the peroxide group O22- or superoxide ion O2-. Excess ROS can cause oxidative DNA damage, protein oxidation, and fatty acid oxidation in bacteria, resulting in bacterial death (Du et al., 2020). In the presence of ADP-Fe3+, NAD(P)H initiates lipid peroxidation. The reaction rate was a biphasic function of the concentration of NADH, with oxygen consumption reaching a maximum and then decreasing at low concentrations of NADH. It was found that rhein not only promoted NAD(P)H-induced lipid peroxidation but also eliminated the inhibitory effect of high concentrations of NADH on lipid oxidation (Glinn et al., 1997).

Table 5.

Proteins associated with the respiratory chain.

Accession Protein description Gene name Fold change P-value
C6ZDJ8 NADH-dependent flavin oxidoreductase BU104_06340 2.286 4.68E-07
A0A5F0VCX2 FMN reductase (NADPH) E4T72_07855 1.552 0.00078
A0A418I9D7 NAD(P)H-dependent oxidoreductase BU104_04575 2.825 6.42E-07
A5H0F5 NADP-dependent oxidoreductase-like protein qorA 1.804 0.00052
A0A418I8J2 Iron-sulfur cluster assembly accessory protein BU104_06425 1.664 0.00417

3.4.6. Effect of drugs on bacterial fatty acid metabolism proteins

Fatty acids are great sources of energy, especially long-chain fatty acids (LCFAs), which are important components of cell membranes (Jaswal et al., 2021). As an energy-rich nutrient, LCFAs have an important role in promoting bacterial survival and infectivity (Kumar et al., 2020). The metabolism of LCFAs can provide large amounts of acetyl CoA, FADH2, and NADH to bacteria. In KEGG enrichment analysis, fatty acid metabolism was upregulated. The effect of rhein on fatty acid metabolic pathway proteins was shown in Table 6, with a total of 8 proteins having significant differences. Metabolism of LCFAs is carried out by Fad (fatty acid degradation) protein, which transports and activates LCFAs, further degrading them to acetyl coenzyme A by β-oxidation (Pavoncello et al., 2022). LCFAs are catalyzed by A0A5F0V9V1 (fadD) protein to produce lipoyl CoA. C6ZDG5 (fadN) and A0A5F0VD52 (fadA) are the key proteins for fatty acid β-oxidation. In the presence of fadN protein, L-β-hydroxylated fatty acid CoA sheds its β-carbon atom and the hydrogen atom on its hydroxyl group to produce β-ketolipidyl CoA. The shed hydrogen atom combines with NAD+ to produce NADH+H+. The β-ketolipidyl CoA is catalyzed by fadA protein and interacts with HSCoA to produce 1 molecule of acetyl CoA and 2 carbon atoms less than the original lipid acyl CoA. The acetyl CoA produced by fatty acid β-oxidation is completely oxidized and energy is released through the TCA cycle and respiratory chain. The newly generated lipid acyl CoA can continue to undergo β-oxidation, which eventually completely breaks down lipid acyl CoA to acetyl CoA. NADH and FADH2 generated by β-oxidation and TCA cycle are oxidized by complex I and complex II, respectively, and the resulting e- is eventually transferred to O2. Degradation of LCFAs increases the ratio of NADH/NAD+ and FADH2/FAD+, which can induce higher levels of ROS production (Agrawal et al., 2017). It was shown that degradation of LCFAs in E.coli could enhance the electron flow in the electron transport chain, which may increase electron leakage (Jaswal et al., 2020). The electron leakage in the electron transport chain may be further facilitated by the electron-accepting effect of rhein. E. coli grown in LCFAs could produce higher levels of ROS compared to cells cultured with glucose as a carbon source (Doi et al., 2014). Therefore, the promotion of ROS production by fatty acid metabolism may be one of the mechanisms by which rhein fights against S. xylosus, which needs to be further investigated.

Table 6.

Proteins associated with the Fatty acid degradation.

Accession Protein description Gene name Fold change P-value
A0A418I6B5 Aldehyde dehydrogenase BU104_10160 1.618 0.00023
A0A5F0V8A2 Aldehyde dehydrogenase family protein E4T72_11990 1.841 1.10E-06
A0A5F0V9V1 Long-chain fatty acid--CoA ligase fadD 2.164 0.00968
A0A5F0V8U0 Zinc-type alcohol dehydrogenase-like protein E4T72_11180 1.9 2.82E-06
C6ZDG5 NAD binding 3-hydroxy acyl-CoA dehydrogenase fadN 1.962 9.55E-05
A0A512SQK0 Glutaryl-CoA dehydrogenase E4T72_08890 1.929 1.63E-05
A0A418I4M6 Aldehyde dehydrogenase BU104_12250 1.729 0.00092
A0A5F0VD52 Thiolase family protein fadA,fadI 3.452 1.22E-06

3.4.7. Effect of drugs on bacterial antioxidant proteins

ROS has a dual role in biological processes that is related to their concentration (Herb et al., 2021). Low levels of ROS are important for cellular signaling pathways or physiological processes. However, high levels of ROS can disrupt the redox balance and put bacteria in a state of oxidative stress. Notably, all bacteria have an inducible antioxidant defense system to cope with the oxidative damage of ROS (Lu and Holmgren, 2014b, Lu and Holmgren, 2014a). Antioxidant-associated proteins were identified in the proteomics data. The effect of rhein on bacterial antioxidant proteins was shown in Table 7, where 6 proteins were significantly upregulated.

Q6PXX2 and Q9EV50 (katA) proteins are catalases that induce the conversion of H2O2 to H2O in bacteria (Linzner et al., 2022). It has been found that disruption of katA can lead to increased levels of ROS in Proteus mirabilis, resulting in increased bacterial susceptibility to H2O2 and reduced biofilm biomass (White et al., 2021). KatA is a detoxifying protein for H2O2 and is considered a virulence factor for S.aureus (Cosgrove et al., 2007). During bacterial infection of the host, host neutrophils can produce ROS as part of the oxidative killing mechanism (Zhou et al., 2023). Bacteria that produce low levels of katA are more sensitive to ROS produced by themselves or neutrophils (Harris et al., 2003). Organic hydroperoxides (Ohps) is also a ROS. A0A418IKB1 (Ohr) is an important scavenger enzyme for Ohps (Meiru et al., 2019). Ohr was upregulated in the oxidative stress response of Staphylococcus and Mycoplasma pneumonia (Pandey et al., 2019; Chen et al., 2018). In addition, in vitro studies have shown that Ohr degrades Ohps and eliminates the damage it causes (Chuchue et al., 2006). The thioredoxin system isa key antioxidant system in organisms and consists of NADPH, thioredoxin reductase (A0A512SPC2, TrxR), and thioredoxin (A0A2T4QDA0, Trx) (Lu and Holmgren, 2014a, Lu and Holmgren, 2014b). The thioredoxin system uses NADPH as an electron donor to scavenge ROS by transferring electrons to ROS (Ren et al., 2018). TrxR can reduce oxidized Trx and is a promising target for antimicrobial drug action (Liang et al., 2016). Inhibition of TrxR enhances the susceptibility of S. aureus to curcumin (Dong et al., 2020). A0A5F0VAL2 (ahpF) is also one of the thiol-dependent antioxidant enzymes (Poole et al., 2000). AhpF transfers electrons directly to the peroxidase alkyl hydroperoxide peroxidase subunit C (ahpC), thereby removing alkyl hydroperoxide. According to the above analysis, we concluded that bacterial symptoms are in a state of ROS stress. It was shown that ROS are involved in oxidative damage, which also includes cell membrane damage and leakage of cell contents (Behera et al., 2019). Higher levels of ROS production are associated with higher cell membrane permeability (Seyedjavadi et al., 2020).

3.4.8. Effect of drugs on bacterial DNA repair proteins

Oxidative DNA damage caused by ROS is an important attack on bacteria (Wang et al., 2013). DNA damage activates a self-protection mechanism in bacteria, a defense mechanism called the ‘SOS response’ (Podlesek and Žgur Bertok, 2020). The identification of DNA damage repair-related proteins in the proteomics data further suggests that bacteria are responding to ROS damage with a stress defense. The effects of rhein on DNA repair proteins were shown in Table 8, where a total of 5 proteins were significantly altered, 4 of which were up-regulated and 1 was down-regulated.

Table 8.

Proteins associated with the DNA repair.

Accession Protein description Gene name Fold change P-value
A0A5F0VD73 DNA mismatch repair protein MutL mutL 1.571 0.01607
A7KJJ5 recombination protein RecA recA 2.018 3.85E-06
A0A418IB53 LexA repressor lexA 0.454 1.01E-06
A0A5F0VCV6 Ribonucleoside-diphosphate reductase nrdE 3.637 1.89E-05
A0A418I741 DNA gyrase subunit B gyrB 1.678 0.01558

A7KJJ5 (recA), A0A418IB53 (lexA), and A0A5F0VD73 (mutL) are key proteins for DNA damage repair (Ha and Edwards, 2021; Didier et al., 2011). LexA protein is a key transcriptional regulator of the SOS response and is a blocker protein of recA protein. When the SOS response occurs, recA acts as a co-protease to stimulate the self-cleavage of lexA protein, thereby relieving the inhibitory effect of lexA on the SOS response, and SOS response-related genes begin to be expressed (Brent and Ptashne, 1981). Furthermore, the recombinant enzyme recA is considered to be a universal drug target for pathogenic bacteria (Pavlopoulou, 2018). RecA plays a key role in activating the SOS response, which is associated with the emergence of microbial drug resistance. In S. aureus, recA deficiency significantly reduced antibiotic-induced resistance (Kiran and Patil, 2023). It has been shown that lexA-deficient mutant strains have a significantly reduced ability to adhere and biofilm formation (Gotoh et al., 2010). Therefore, the reduction of lexA protein may also be one of the reasons for the inhibition of biofilm formation by rhein. MutL is a DNA mismatch repair protein. When DNA mismatch occurs, protein mutS finds the mismatch site and works together with proteins mutL and mutH to repair the mismatched DNA (Fishel, 2015).

3.4.9. Effect of drugs on protein in bacterial nitrate respiration

In the proteomics data, we identified proteins associated with nitrate respiration miraculously. The effects of rhein on proteins related to nitrate respiration were shown in Table 9, with 7 significantly altered proteins. A0A5F0VAF5 (NreB)/A0A418I6F5 (NreC) is a two-component system protein (NreBC protein) that carries out the regulation of oxygen on bacterial nitrate respiration (Fedtke et al., 2002). Increasingly, studies have shown that the two-component system is associated with biofilm formation (Prüß, 2017). NreBC deficiency has a significant effect on the growth advantage of rifampicin-resistant S. aureus mutants in biofilms (Maudsdotter et al., 2019). The upregulation of NreBC protein may be one of the reasons for the intervention of rhein in the growth of S. xylosus biofilm. The cytoplasmic sensor kinase NreB is a direct O2 sensor that uses the [4Fe-4S]2+ cluster to sense O2 and control kinase activity (Nilkens et al., 2014). Under hypoxic conditions, NreB attaches to the [4Fe-4S]2+ cluster, and the protein is then active, catalyzing the autophosphorylation of NreB (Unden and Klein, 2021). The phosphorylation group is transferred to the response regulator NreC. Phosphorylated NreC binds to DNA and stimulates the expression of the A0A418I6E2 (narG) gene. Staphylococci use nitrate as an alternative electron acceptor during anaerobic respiration (Proctor, 2019). When NADH/NADPH is oxidized, large amounts of O2 are consumed, causing NreBC to be upregulated and activating narG genes involved in the reduction of nitrate to ammonia. The upregulation of these proteins also provides side evidence that the bacteria have consumed a large amount of O2, resulting in the generation of higher than normal levels of ROS.

Table 9.

Proteins associated with the nitrate respiration.

Accession Protein description Gene name Fold change P-value
A0A5F0VAF5 Sensor histidine kinase nreB 1.853 1.86E-05
A0A418I6F5 DNA-binding response regulator nreC 2.146 0.01384
A0A418I6E2 Nitrate reductase subunit alpha narG 1.597 0.00028
A0A518P629 Respiratory nitrate reductase subunit gamma narI 1.961 0.00020
A0A5F0VAI9 NarK/NasA family nitrate transporter E4T72_06440 1.591 8.04E-05
A0A5F0VCX8 Nitroreductase family protein E4T72_07910 2.104 0.00384
A0A418I4S0 Nitroreductase family protein BU104_11600 2.251 0.00436

3.5. Effect of rhein on bacterial cell membrane permeability

3.5.1. Effect of β-galactosidase

Higher levels of ROS will result in increased cell membrane permeability (Seyedjavadi et al., 2020). The cell membrane is a protective barrier for the intracellular components of bacteria. Therefore, the release of intracellular components can be used to reflect the integrity of the cell membrane. The β-galactosidase is an intracellular substance, that is present in the cell, but when the cell membrane permeability changes, the intracellular enzyme will leak to the bacterial extracellular (Falla et al., 1996; Zhou et al., 2022). Therefore, the activity of β-galactosidase in S. xylosus can reflect the change in cell membrane permeability. The β-galactosidase activity of S. xylosus after rhein treatment was determined by the method specified in the β-galactosidase activity kit. The results were shown as follows (Fig. 7A): the β-galactosidase enzyme activity in the bacterial solution increased rapidly and significantly higher than that in the control group in 2∼4 h after treatment with rhein. Hence, rhein could improve the permeability of bacterial cell membranes, which was consistent with the results of proteomic analysis (ROS was adjusted upward).

Fig. 7.

Fig. 7

Cell membrane permeability and morphology of S. xylosus under rhein stress. (A) Determination of S. xylosu extracellular β-galactosidase. (B) Determination of S. xylosu extracellular nucleic acids. (C) SEM observation of S. xylosu morphology. a: Bacterial control group; b: Rhein-treated group.

3.5.2. DNA/RNA leakage

Nucleic acid is an intracellular component of bacteria, and its extracellular concentration can reflect the permeability of bacterial cell membranes (Ivask et al., 2014). Nucleic acid has a strong UV absorption at 260 nm. It has been suggested that the absorbance value A at 260 nm can reflect the degree of change of bacterial cell membrane permeability (Chen and Cooper, 2002). Therefore, in this study, the UV absorbance value A of S. xylosus suspension at 260 nm was used to reflect the degree of alteration of cell membrane permeability of S. xylosus by rhein. By UV spectrophotometer, the release of S. xylosus nucleic acid was measured. The results were shown in Fig. 7B. Under the stress of rhein, the release of DNA and RNA (OD260nm) increased rapidly within 2 h, and after 4 h, the OD260nm did not change. Rhein could cause intracellular nucleic acid leakage in S. xylosus, which was consistent with the results of the extracellular β-galactosidase experiment.

3.5.3. Morphological effects

High levels of ROS can cause damage to the cell membrane. Scanning electron microscopy (SEM) was employed to observe the cell membrane morphology of S. xylosus, and the results are shown in Fig. 7C. Fig. 7C–a shows the untreated S. xylosus, and the bacteria were spherical in shape with intact structure. After treatment with rhein (Fig. 7C–b), the structure of S. xylosus underwent significant changes, including extracellular lysates and complete fragmentation of some bacteria. The SEM results demonstrate that rhein has a pronounced effect on the morphology of S. xylosus. The disruption of the bacterial cell membrane led to the exocytosis of S. xylosus contents, contributing to the increased levels of β-galactosidase and nucleic acid outside the cells.

3.6. Determination of ROS

2′,7′-dichlorodihydrofluorescein (DCFH-DA) was used as a probe to detect the formation of ROS in S. xylosus under rhein pressure. As shown in Fig. 8, compared with the bacterial control group without rhein, the fluorescence intensity of S. xylosus under rhein stress was lighter. Moreover, the fluorescence intensity showed a certain dose-dependence with the concentration of rhein administration. Thus, rhein can induce ROS formation in S. xylosus, which is consistent with the analysis results of proteomics.

Fig. 8.

Fig. 8

ROS levels of S. xylosu under rhein. The brighter the green fluorescence, the higher the level of ROS. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

3.7. RT-PCR experiments

We selected key proteins of the TCA cycle (mqo, odhA) with key proteins of nitrate respiration (nreB, nreC, narG), and used RT-PCR to validate them. The PCR results showed that the genes of these proteins were upregulated, which was consistent with the proteomic trend (Fig. 9). Thus, rhein may increase the expression of these proteins by enhancing the transcription of their genes.

Fig. 9.

Fig. 9

RT-PCR validation of key proteins in proteomics. The mRNA expression of TCA and nitrate respiration in S. xylosus with 1/2 MIC of rhein and untreated. Symbols are: *P<0.01.

4. Conclusion

In our experiment, we investigated the anti-S. xylosus effect of rhein in vitro and in vivo, and explored the antibacterial mechanism by proteomics. Our results demonstrated the potent antibacterial effect of rhein, including interference with biofilm formation at subinhibitory concentrations. Proteomic data revealed that continuous rhein stimulation interfered with S. xylosus energy metabolism, leading to increased intracellular ROS production and accumulation. This caused oxidative damage to bacterial cell membranes, DNA, and other organelles, ultimately leading to content leakage and cell death. The RT-PCR experiments also demonstrated elevated levels of gene transcripts for key proteins of the TCA cycle and nitrate respiration. Additionally, the elevated concentrations of extracellular β-galactosidase and nucleic acids, and the altered bacterial morphology observed by SEM further suggest that rhein could cause bacterial membrane damage and leakage of intracapsular material. This study was conducted with a view to providing some ideas and theoretical basis for the research and development of rhein for the treatment of bacterial mastitis in dairy cows.

CRediT authorship contribution statement

Yuyang Li: and. Weiwei Chen: and. Jinxin Ma: performed the experiments and the data analysis. Guoying Huang: and. Guangquan Li: and. Qiumei He: and. Xiangyu Kong: and. Ling Tang: and. Jinqing Chen: provided help during the experiment. Wenyou Ding: provided funding support and guidance on statistical analysis. Zhongbin Zhang: directed the completion of the experiment. Wenya Ding: designed the whole experiment.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This work was supported by Guangxi University of Chinese Medicine and Northeast Agricultural University; Guangxi Natural Science Foundation Project (2023GXNSFAA026461); National Natural Science Foundation of China (82060806); National Natural Science Foundation of China (31802228); Open Fund Project of Key Laboratory of Modern Preparation of TCM. Ministry of Education (zdsys-202207); Interdisciplinary Innovation Research Team for Key Technologies of Traditional Chinese Medicine Emerging Biological Materials and Intelligent Equipment Development (GZKJ2303); Collaborative Innovation Center of Zhuang and Yao Ethnic Medicine (2013NO.20); College Student Innovation and Entrepreneurship Training Program of Guangxi University of Chinese Medicine (S202310600107); College Student Innovation and Entrepreneurship Training Program of Guangxi University of Chinese Medicine (S20221060053). In addition, the support of Guangxi Engineering Research Center for Advantageous Chinese Patent Medicine and Ethnic Medicine Development is gratefully acknowledged. We thank Jingjie PTM Biolab (Hangzhou) Co., Inc., for the help with iTRAQ, sequence database searching, and data analysis. Finally, we would like to thank Thi Minh Hien Truong for touching up our paper to avoid language and presentation errors.

Contributor Information

Wenyou Ding, Email: 12874238@qq.com.

Zhongbin Zhang, Email: 30604640@qq.com.

Wenya Ding, Email: DingWenYa666@163.com.

Data availability

Data will be made available on request.

References

  1. Agrawal S., Jaswal K., Shiver A.L., Balecha H., Patra T., Chaba R. A genome-wide screen in Escherichia coli reveals that ubiquinone is a key antioxidant for metabolism of long-chain fatty acids. J. Biol. Chem. 2017;292:20086–20099. doi: 10.1074/jbc.M117.806240. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Akram M. Citric acid cycle and role of its intermediates in metabolism. Cell Biochem. Biophys. 2014;68:475–478. doi: 10.1007/s12013-013-9750-1. [DOI] [PubMed] [Google Scholar]
  3. Alanis V.M., Tomazi T., Santisteban C., Nydam D.V., Ospina P.A. Calculating clinical mastitis frequency in dairy cows: Incidence risk at cow level, incidence rate at cow level, and incidence rate at quarter level. Prev. Vet. Med. 2022;198 doi: 10.1016/j.prevetmed.2021.105527. [DOI] [PubMed] [Google Scholar]
  4. Alkasir R., Ma Y., Liu F., Li J., Lv N., Xue Y., Hu Y., Zhu B. Characterization and transcriptome analysis of acinetobacter baumannii persister cells. Microb. Drug Resist. 2018;24:1466–1474. doi: 10.1089/mdr.2017.0341. [DOI] [PubMed] [Google Scholar]
  5. Ashraf A., Imran M. Causes, types, etiological agents, prevalence, diagnosis, treatment, prevention, effects on human health and future aspects of bovine mastitis. Anim. Health Res. Rev. 2020;21:36–49. doi: 10.1017/S1466252319000094. [DOI] [PubMed] [Google Scholar]
  6. Aslam B., Basit M., Nisar M.A., Khurshid M., Rasool M.H. Proteomics: Technologies and their applications. J. Chromatogr. Sci. 2017;55 doi: 10.1093/chromsci/bmw167. [DOI] [PubMed] [Google Scholar]
  7. Azooz M.F., El-Wakeel S.A., Yousef H.M. Financial and economic analyses of the impact of cattle mastitis on the profitability of Egyptian dairy farms. Vet. World. 2020;13:1750–1759. doi: 10.14202/vetworld.2020.1750-1759. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Behera N., Arakha M., Priyadarshinee M., Pattanayak B.S., Soren S., Jha S., Mallick B.C. Oxidative stress generated at nickel oxide nanoparticle interface results in bacterial membrane damage leading to cell death. RSC Adv. 2019;9:24888–24894. doi: 10.1039/c9ra02082a. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Bohl L.P., Isaac P., Breser M.L., Orellano M.S., Correa S.G., Tolosa de Talamoni N.G., Porporatto C. Interaction between bovine mammary epithelial cells and planktonic or biofilm Staphylococcus aureus: the bacterial lifestyle determines its internalization ability and the pathogen recognition. Microb. Pathog. 2021;152 doi: 10.1016/j.micpath.2020.104604. [DOI] [PubMed] [Google Scholar]
  10. Brent R., Ptashne M. Mechanism of action of the lexA gene product. Proc. Natl. Acad. Sci. U. S. A. 1981;78:4204–4208. doi: 10.1073/pnas.78.7.4204. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Chen C.Z., Cooper S.L. Interactions between dendrimer biocides and bacterial membranes. Biomaterials. 2002;23:3359–3368. doi: 10.1016/s0142-9612(02)00036-4. [DOI] [PubMed] [Google Scholar]
  12. Chen L.-S., Li C., You X.-X., Lin Y.-W., Wu Y.-M. The mpn668 gene of Mycoplasma pneumoniae encodes a novel organic hydroperoxide resistance protein. Int J Med Microbiol. 2018;308:776–783. doi: 10.1016/j.ijmm.2018.04.006. [DOI] [PubMed] [Google Scholar]
  13. Cheng L., Chen Q., Pi R., Chen J. A research update on the therapeutic potential of rhein and its derivatives. Eur. J. Pharmacol. 2021;899 doi: 10.1016/j.ejphar.2021.173908. [DOI] [PubMed] [Google Scholar]
  14. Chuchue T., Tanboon W., Prapagdee B., Dubbs J.M., Vattanaviboon P., Mongkolsuk S. OhrR and ohr are the primary sensor/regulator and protective genes against organic hydroperoxide stress in Agrobacterium tumefaciens. J. Bacteriol. 2006;188:842–851. doi: 10.1128/JB.188.3.842-851.2006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Cosgrove K., Coutts G., Jonsson I.-M., Tarkowski A., Kokai-Kun J.F., Mond J.J., Foster S.J. Catalase (KatA) and alkyl hydroperoxide reductase (AhpC) have compensatory roles in peroxide stress resistance and are required for survival, persistence, and nasal colonization in Staphylococcus aureus. J. Bacteriol. 2007;189:1025–1035. doi: 10.1128/JB.01524-06. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Didier J.-P., Villet R., Huggler E., Lew D.P., Hooper D.C., Kelley W.L., Vaudaux P. Impact of ciprofloxacin exposure on Staphylococcus aureus genomic alterations linked with emergence of rifampin resistance. Antimicrob. Agents Chemother. 2011;55:1946–1952. doi: 10.1128/AAC.01407-10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Ding W., Zhou Y., Qu Q., Cui W., God’spower B.O., Liu Y., Chen X., Chen M., Yang Y., Li Y. Azithromycin inhibits biofilm formation by Staphylococcus xylosus and affects histidine biosynthesis pathway. Front. Pharmacol. 2018;9:740. doi: 10.3389/fphar.2018.00740. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Doi H., Hoshino Y., Nakase K., Usuda Y. Reduction of hydrogen peroxide stress derived from fatty acid beta-oxidation improves fatty acid utilization in Escherichia coli. Appl. Microbiol. Biotechnol. 2014;98:629–639. doi: 10.1007/s00253-013-5327-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Dolder C., Van den Borne B.H.P., Traversari J., Thomann A., Perreten V., Bodmer M. Quarter- and cow-level risk factors for intramammary infection with coagulase-negative staphylococci species in Swiss dairy cows. J. Dairy Sci. 2017;100:5653–5663. doi: 10.3168/jds.2016-11639. [DOI] [PubMed] [Google Scholar]
  20. Dong C., Zhou J.Z., Wang P., Li T., Zhao Y., Ren X., Lu J., Wang J., Holmgren A., Zou L. Topical therapeutic efficacy of ebselen against multidrug-resistant Staphylococcus aureus LT-1 targeting thioredoxin reductase. Front. Microbiol. 2020;10:3016. doi: 10.3389/fmicb.2019.03016. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Du G.-F., Le Y.-J., Sun X., Yang X.-Y., He Q.-Y. Proteomic investigation into the action mechanism of berberine against Streptococcus pyogenes. J. Proteonomics. 2020;215 doi: 10.1016/j.jprot.2020.103666. [DOI] [PubMed] [Google Scholar]
  22. Egerer P., Bühler M., Simon H. Rhein as an electron acceptor for various flavoproteins and for electron transport particles. Hoppe Seylers Z Physiol Chem. 1982;363:627–633. doi: 10.1515/bchm2.1982.363.1.627. [DOI] [PubMed] [Google Scholar]
  23. Falla T.J., Karunaratne D.N., Hancock R.E. Mode of action of the antimicrobial peptide indolicidin. J. Biol. Chem. 1996;271(32):19298–19303. doi: 10.1074/jbc.271.32.19298. [DOI] [PubMed] [Google Scholar]
  24. Fan L., Pan Z., Liao X., Zhong Y., Guo J., Pang R., Chen X., Ye G., Su Y. Uracil restores susceptibility of methicillin-resistant Staphylococcus aureus to aminoglycosides through metabolic reprogramming. Front. Pharmacol. 2023;14 doi: 10.3389/fphar.2023.1133685. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Fedtke I., Kamps A., Krismer B., Götz F. The nitrate reductase and nitrite reductase operons and the narT gene of Staphylococcus carnosus are positively controlled by the novel two-component system NreBC. J. Bacteriol. 2002;184:6624–6634. doi: 10.1128/JB.184.23.6624-6634.2002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Fishel R. Mismatch repair. J. Biol. Chem. 2015;290:26395–26403. doi: 10.1074/jbc.R115.660142. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Fulaz S., Vitale S., Quinn L., Casey E. Nanoparticle-biofilm interactions: the role of the EPS matrix. Trends Microbiol. 2019;27:915–926. doi: 10.1016/j.tim.2019.07.004. [DOI] [PubMed] [Google Scholar]
  28. Gao Y., Chen X., Fang L., Liu F., Cai R., Peng C., Qi Y. Rhein exerts pro- and anti-inflammatory actions by targeting IKKβ inhibition in LPS-activated macrophages. Free Radic. Biol. Med. 2014;72:104–112. doi: 10.1016/j.freeradbiomed.2014.04.001. [DOI] [PubMed] [Google Scholar]
  29. Gaupp R., Lei S., Reed J.M., Peisker H., Boyle-Vavra S., Bayer A.S., Bischoff M., Herrmann M., Daum R.S., Powers R., Somerville G.A. Staphylococcus aureus metabolic adaptations during the transition from a daptomycin susceptibility phenotype to a daptomycin nonsusceptibility phenotype. Antimicrob. Agents Chemother. 2015;59:4226–4238. doi: 10.1128/AAC.00160-15. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Ge H., Tang H., Liang Y., Wu J., Yang Q., Zeng L., Ma Z. Rhein attenuates inflammation through inhibition of NF-κB and NALP3 inflammasome in vivo and in vitro. Drug Des. Dev. Ther. 2017;11:1663–1671. doi: 10.2147/DDDT.S133069. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Glinn M.A., Lee C.P., Ernster L. Pro- and anti-oxidant activities of the mitochondrial respiratory chain: factors influencing NAD(P)H-induced lipid peroxidation. Biochim. Biophys. Acta. 1997;1318:246–254. doi: 10.1016/s0005-2728(96)00142-9. [DOI] [PubMed] [Google Scholar]
  32. Gotoh H., Kasaraneni N., Devineni N., Dallo S.F., Weitao T. SOS involvement in stress-inducible biofilm formation. Biofouling. 2010;26:603–611. doi: 10.1080/08927014.2010.501895. [DOI] [PubMed] [Google Scholar]
  33. Ha K.P., Edwards A.M. DNA repair in Staphylococcus aureus. Microbiol. Mol. Biol. Rev. 2021;85 doi: 10.1128/MMBR.00091-21. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Han S.O., Inui M., Yukawa H. Transcription of Corynebacterium glutamicum genes involved in tricarboxylic acid cycle and glyoxylate cycle. J. Mol. Microbiol. Biotechnol. 2008;15:264–276. doi: 10.1159/000117614. [DOI] [PubMed] [Google Scholar]
  35. Harris A.G., Wilson J.E., Danon S.J., Dixon M.F., Donegan K., Hazell S.L. Catalase (KatA) and KatA-associated protein (KapA) are essential to persistent colonization in the Helicobacter pylori SS1 mouse model. Microbiology (Reading, England) 2003;149(Pt 3):665–672. doi: 10.1099/mic.0.26012-0. [DOI] [PubMed] [Google Scholar]
  36. Heikkilä A.-M., Liski E., Pyörälä S., Taponen S. Pathogen-specific production losses in bovine mastitis. J. Dairy Sci. 2018;101:9493–9504. doi: 10.3168/jds.2018-14824. [DOI] [PubMed] [Google Scholar]
  37. Htt N., Th N., O M. The staphylococcal exopolysaccharide PIA - biosynthesis and role in biofilm formation, colonization, and infection. Comput. Struct. Biotechnol. J. 2020;18 doi: 10.1016/j.csbj.2020.10.027. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Hu X., Tang R., Zhao C., Mu R., Wang Y., Cao Y., Zhang N., Fu Y. The prevention effect of Bacillus subtilis on Escherichia coli-induced mastitis in mice by suppressing the NF-κB and MAPK signaling pathways. Probiotics Antimicrob Proteins. 2023;15:74–81. doi: 10.1007/s12602-021-09854-9. [DOI] [PubMed] [Google Scholar]
  39. Ivask A., Juganson K., Bondarenko O., Mortimer M., Aruoja V., Kasemets K., Blinova I., Heinlaan M., Slaveykova V., Kahru A. Mechanisms of toxic action of Ag, ZnO and CuO nanoparticles to selected ecotoxicological test organisms and mammalian cells in vitro: a comparative review. Nanotoxicology. 2014;8(Suppl. 1):57–71. doi: 10.3109/17435390.2013.855831. [DOI] [PubMed] [Google Scholar]
  40. Jamal M., Ahmad W., Andleeb S., Jalil F., Imran M., Nawaz M.A., Hussain T., Ali M., Rafiq M., Kamil M.A. Bacterial biofilm and associated infections. J. Chin. Med. Assoc. 2018;81:7–11. doi: 10.1016/j.jcma.2017.07.012. [DOI] [PubMed] [Google Scholar]
  41. Jaswal K., Shrivastava M., Roy D., Agrawal S., Chaba R. Metabolism of long-chain fatty acids affects disulfide bond formation in Escherichia coli and activates envelope stress response pathways as a combat strategy. PLoS Genet. 2020;16 doi: 10.1371/journal.pgen.1009081. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Jaswal K., Shrivastava M., Chaba R. Revisiting long-chain fatty acid metabolism in Escherichia coli: integration with stress responses. Curr. Genet. 2021;67:573–582. doi: 10.1007/s00294-021-01178-z. [DOI] [PubMed] [Google Scholar]
  43. Kiran K., Patil K.N. Characterization of Staphylococcus aureus RecX protein: molecular insights into negative regulation of RecA protein and implications in HR processes. J Biochem mvad039. 2023 doi: 10.1093/jb/mvad039. [DOI] [PubMed] [Google Scholar]
  44. Kot B., Piechota M., Antos-Bielska M., Zdunek E., Wolska K.M., Binek T., Olszewska J., Guliński P., Trafny E.A. Antimicrobial resistance and genotypes of staphylococci from bovine milk and the cowshed environment. Pol. J. Vet. Sci. 2012;15:741–749. doi: 10.2478/v10181-012-0113-4. [DOI] [PubMed] [Google Scholar]
  45. Kumar P., Lee J.-H., Beyenal H., Lee J. Fatty acids as antibiofilm and antivirulence agents. Trends Microbiol. 2020;28:753–768. doi: 10.1016/j.tim.2020.03.014. [DOI] [PubMed] [Google Scholar]
  46. Liang W., Fernandes A.P., Holmgren A., Li X., Zhong L. Bacterial thioredoxin and thioredoxin reductase as mediators for epigallocatechin 3-gallate-induced antimicrobial action. FEBS J. 2016;283:446–458. doi: 10.1111/febs.13587. [DOI] [PubMed] [Google Scholar]
  47. Liao J., Zhao L., Yoshioka M., Hinode D., Grenier D. Effects of Japanese traditional herbal medicines (Kampo) on growth and virulence properties of Porphyromonas gingivalis and viability of oral epithelial cells. Pharmaceut. Biol. 2013;51(12):1538–1544. doi: 10.3109/13880209.2013.801995. [DOI] [PubMed] [Google Scholar]
  48. Linzner N., Fritsch V.N., Busche T., Tung Q.N., Loi V.V., Bernhardt J., Kalinowski J., Antelmann H. The plant-derived naphthoquinone lapachol causes an oxidative stress response in Staphylococcus aureus. Free Radic. Biol. Med. 2020;158:126–136. doi: 10.1016/j.freeradbiomed.2020.07.025. [DOI] [PubMed] [Google Scholar]
  49. Linzner N., Loi V.V., Antelmann H. The catalase KatA contributes to microaerophilic H2O2 priming to acquire an improved oxidative stress resistance in Staphylococcus aureus. Antioxidants. 2022;11:1793. doi: 10.3390/antiox11091793. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Liu Y., Shi C., He Z., Zhu F., Wang M., He R., Zhao C., Shi X., Zhou M., Pan S., Gao Y., Li X., Qin R. Inhibition of PI3K/AKT signaling via ROS regulation is involved in Rhein-induced apoptosis and enhancement of oxaliplatin sensitivity in pancreatic cancer cells. Int. J. Biol. Sci. 2021;17:589–602. doi: 10.7150/ijbs.49514. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Liu B.-G., Xie M., Dong Y., Wu H., He D.-D., Hu G.-Z., Xu E.-P. Antimicrobial mechanisms of traditional Chinese medicine and reversal of drug resistance: a narrative review. Eur. Rev. Med. Pharmacol. Sci. 2022;26:5553–5561. doi: 10.26355/eurrev_202208_29426. [DOI] [PubMed] [Google Scholar]
  52. Lu J., Holmgren A. The thioredoxin antioxidant system. Free Radic. Biol. Med. 2014;66:75–87. doi: 10.1016/j.freeradbiomed.2013.07.036. [DOI] [PubMed] [Google Scholar]
  53. Lu J., Holmgren A. The thioredoxin antioxidant system. Free radical biology & medicine. 2014;66:75–87. doi: 10.1016/j.freeradbiomed.2013.07.036. [DOI] [PubMed] [Google Scholar]
  54. Luengo A., Li Z., Gui D.Y., Sullivan L.B., Zagorulya M., Do B.T., Ferreira R., Naamati A., Ali A., Lewis C.A., Thomas C.J., Spranger S., Matheson N.J., Vander Heiden M.G. Increased demand for NAD+ relative to ATP drives aerobic glycolysis. Mol Cell. 2021;81:691–707.e6. doi: 10.1016/j.molcel.2020.12.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Luo Y., Yang Q., Zhang D., Yan W. Mechanisms and control strategies of antibiotic resistance in pathological biofilms. J. Microbiol. Biotechnol. 2021;31(1):1–7. doi: 10.4014/jmb.2010.10021. [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Ma Y., Gao Y., Xu Y., Zhou H., Zhou K., Li C., Xu B. Microbiota dynamics and volatile metabolite generation during sausage fermentation. Food Chem. 2023;423 doi: 10.1016/j.foodchem.2023.136297. [DOI] [PubMed] [Google Scholar]
  57. Martins L., Barcelos M.M., Cue R.I., Anderson K.L., Santos M.V.D., Gonçalves J.L. Chronic subclinical mastitis reduces milk and components yield at the cow level. J. Dairy Res. 2020;87:298–305. doi: 10.1017/S0022029920000321. [DOI] [PubMed] [Google Scholar]
  58. Maudsdotter L., Ushijima Y., Morikawa K. Fitness of spontaneous rifampicin-resistant Staphylococcus aureus isolates in a biofilm environment. Front. Microbiol. 2019;10:988. doi: 10.3389/fmicb.2019.00988. [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Milano M. Using gene Ontology to annotate and prioritize microarray data. Methods Mol. Biol. 2022;2401:273–287. doi: 10.1007/978-1-0716-1839-4_18. [DOI] [PubMed] [Google Scholar]
  60. Navas L.E., Carnero A. NAD+ metabolism, stemness, the immune response, and cancer. Signal Transduct. Targeted Ther. 2021;6:2. doi: 10.1038/s41392-020-00354-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Nilkens S., Koch-Singenstreu M., Niemann V., Götz F., Stehle T., Unden G. Nitrate/oxygen co-sensing by an NreA/NreB sensor complex of Staphylococcus carnosus. Mol. Microbiol. 2014;91:381–393. doi: 10.1111/mmi.12464. [DOI] [PubMed] [Google Scholar]
  62. Pandey S., Sahukhal G.S., Elasri M.O. The msaABCR operon regulates the response to oxidative stress in Staphylococcus aureus. J. Bacteriol. 2019;201:e00417–e00419. doi: 10.1128/JB.00417-19. [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Paudel S., Guedry S., Obernuefemann C.L.P., Hultgren S.J., Walker J.N., Kulkarni R. Defining the roles of pyruvate oxidation, TCA cycle, and mannitol metabolism in methicillin-resistant Staphylococcus aureus catheter-associated urinary tract infection. Microbiol. Spectr. 2023 doi: 10.1128/spectrum.05365-22. [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. Pavlopoulou A. RecA: a universal drug target in pathogenic bacteria. Front Biosci (Landmark Ed) 2018;23:36–42. doi: 10.2741/4580. [DOI] [PubMed] [Google Scholar]
  65. Pavoncello V., Barras F., Bouveret E. Degradation of exogenous fatty acids in Escherichia coli. Biomolecules. 2022;12:1019. doi: 10.3390/biom12081019. [DOI] [PMC free article] [PubMed] [Google Scholar]
  66. Peerzada Z., M Kanhed A., B Desai K.B. Effects of active compounds from Cassia fistula on quorum sensing mediated virulence and biofilm formation in Pseudomonas aeruginosa. RSC Adv. 2022;12(24):15196–15214. doi: 10.1039/d1ra08351a. [DOI] [PMC free article] [PubMed] [Google Scholar]
  67. Podlesek Z., Žgur Bertok D. The DNA damage inducible SOS response is a key player in the generation of bacterial persister cells and population wide tolerance. Front. Microbiol. 2020;11:1785. doi: 10.3389/fmicb.2020.01785. [DOI] [PMC free article] [PubMed] [Google Scholar]
  68. Poole L.B., Reynolds C.M., Wood Z.A., Karplus P.A., Ellis H.R., Li Calzi M. AhpF and other NADH:peroxiredoxin oxidoreductases, homologues of low Mr thioredoxin reductase. Eur. J. Biochem. 2000;267:6126–6133. doi: 10.1046/j.1432-1327.2000.01704.x. [DOI] [PubMed] [Google Scholar]
  69. Proctor R. Respiration and small colony variants of Staphylococcus aureus. Microbiol. Spectr. 2019;7(3) doi: 10.1128/microbiolspec.GPP3-0069-2019. [DOI] [PMC free article] [PubMed] [Google Scholar]
  70. Prüß B.M. Involvement of two-component signaling on bacterial motility and biofilm development. J. Bacteriol. 2017;199 doi: 10.1128/JB.00259-17. [DOI] [PMC free article] [PubMed] [Google Scholar]
  71. Raghuveer D., Pai V.V., Murali T.S., Nayak R. Exploring anthraquinones as antibacterial and antifungal agents. ChemistrySelect. 2023;8(6) doi: 10.1002/slct.202204537. [DOI] [Google Scholar]
  72. Ren X., Zou L., Lu J., Holmgren A. Selenocysteine in mammalian thioredoxin reductase and application of ebselen as a therapeutic. Free Radic. Biol. Med. 2018;127:238–247. doi: 10.1016/j.freeradbiomed.2018.05.081. [DOI] [PubMed] [Google Scholar]
  73. Root R.K., Metcalf J.A. H2O2 release from human granulocytes during phagocytosis. Relationship to superoxide anion formation and cellular catabolism of H2O2: studies with normal and cytochalasin B-treated cells. J. Clin. Invest. 1977;60:1266–1279. doi: 10.1172/JCI108886. [DOI] [PMC free article] [PubMed] [Google Scholar]
  74. Sadykov M.R., Olson M.E., Halouska S., Zhu Y., Fey P.D., Powers R., Somerville G.A. Tricarboxylic acid cycle-dependent regulation of Staphylococcus epidermidis polysaccharide intercellular adhesin synthesis. J. Bacteriol. 2008;190:7621–7632. doi: 10.1128/JB.00806-08. [DOI] [PMC free article] [PubMed] [Google Scholar]
  75. Seyedjavadi S.S., Khani S., Eslamifar A., Ajdary S., Goudarzi M., Halabian R., Akbari R., Zare-Zardini H., Fooladi A.A.I., Amani J., Razzaghi-Abyaneh M. The antifungal peptide MCh-AMP1 derived from matricaria chamomilla inhibits Candida albicans growth via inducing ROS generation and altering fungal cell membrane permeability. Front. Microbiol. 2020;10:3150. doi: 10.3389/fmicb.2019.03150. [DOI] [PMC free article] [PubMed] [Google Scholar]
  76. Sharma D., Manimaran A., Kumaresan A., Sivaram M., Rajendran D. Antimicrobials use and their indications in dairy farm and individual farmer production conditions in southern India. Trop. Anim. Health Prod. 2021;54:29. doi: 10.1007/s11250-021-03025-2. [DOI] [PubMed] [Google Scholar]
  77. Torres C., Alonso C.A., Ruiz-Ripa L., León-Sampedro R., Del Campo R., Coque T.M. Antimicrobial resistance in Enterococcus spp. ofanimalorigin. Microbiol. Spectr. 2018;6(4) doi: 10.1128/microbiolspec.ARBA-0032-2018. [DOI] [PMC free article] [PubMed] [Google Scholar]
  78. Tremblay Y.D.N., Lamarche D., Chever P., Haine D., Messier S., Jacques M. Characterization of the ability of coagulase-negative staphylococci isolated from the milk of Canadian farms to form biofilms. J. Dairy Sci. 2013;96:234–246. doi: 10.3168/jds.2012-5795. [DOI] [PubMed] [Google Scholar]
  79. Unden G., Klein R. Sensing of O2 and nitrate by bacteria: alternative strategies for transcriptional regulation of nitrate respiration by O2 and nitrate. Environ. Microbiol. 2021;23:5–14. doi: 10.1111/1462-2920.15293. [DOI] [PubMed] [Google Scholar]
  80. Vuong C., Kidder J.B., Jacobson E.R., Otto M., Proctor R.A., Somerville G.A. Staphylococcus epidermidis polysaccharide intercellular adhesin production significantly increases during tricarboxylic acid cycle stress. J. Bacteriol. 2005;187 doi: 10.1128/JB.187.9.2967-2973.2005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  81. Wang Z.-Y., Xiong M., Fu L.-Y., Zhang H.-Y. Oxidative DNA damage is important to the evolution of antibiotic resistance: evidence of mutation bias and its medicinal implications. J. Biomol. Struct. Dyn. 2013;31:729–733. doi: 10.1080/07391102.2012.709457. [DOI] [PubMed] [Google Scholar]
  82. Wang J., Li H., Pan J., Dong J., Zhou X., Niu X., Deng X. Oligopeptide targeting sortase A as potential anti-infective therapy for Staphylococcus aureus. Front. Microbiol. 2018;9:245. doi: 10.3389/fmicb.2018.00245. [DOI] [PMC free article] [PubMed] [Google Scholar]
  83. White A.N., Learman B.S., Brauer A.L., Armbruster C.E. Catalase activity is critical for Proteus mirabilis biofilm development, extracellular polymeric substance composition, and dissemination during catheter-associated urinary tract infection. Infect. Immun. 2021;89(10) doi: 10.1128/IAI.00177-21. [DOI] [PMC free article] [PubMed] [Google Scholar]
  84. Xu J., Tan X., Zhang X., Xia X., Sun H. The diversities of staphylococcal species, virulence and antibiotic resistance genes in the subclinical mastitis milk from a single Chinese cow herd. Microb. Pathog. 2015;88:29–38. doi: 10.1016/j.micpath.2015.08.004. [DOI] [PubMed] [Google Scholar]
  85. Yang S., Lian G. ROS and diseases: role in metabolism and energy supply. Mol. Cell. Biochem. 2020;467:1–12. doi: 10.1007/s11010-019-03667-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  86. Yu L., Xiang H., Fan J., Wang D., Yang F., Guo N., Jin Q., Deng X. Global transcriptional response of Staphylococcus aureus to rhein, a natural plant product. J. Biotechnol. 2008;135:304–308. doi: 10.1016/j.jbiotec.2008.04.010. [DOI] [PubMed] [Google Scholar]
  87. Zhao R.-Z., Jiang S., Zhang L., Yu Z.-B. Mitochondrial electron transport chain, ROS generation and uncoupling. Int. J. Mol. Med. 2019;44:3–15. doi: 10.3892/ijmm.2019.4188. (Review) [DOI] [PMC free article] [PubMed] [Google Scholar]
  88. Zhou Y.-H., Xu C.-G., Yang Y.-B., Xing X.-X., Liu X., Qu Q.-W., Ding W.-Y., Bello-Onaghise G., Li Y.-H. Histidine metabolism and IGPD play a key role in cefquinome inhibiting biofilm formation of Staphylococcus xylosus. Front. Microbiol. 2018;9:665. doi: 10.3389/fmicb.2018.00665. [DOI] [PMC free article] [PubMed] [Google Scholar]
  89. Zhou L., Lian K., Wang M., Jing X., Zhang Y., Cao J. The antimicrobial effect of a novel peptide LL-1 on Escherichia coli by increasing membrane permeability. BMC Microbiol. 2022;22(1):220. doi: 10.1186/s12866-022-02621-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  90. Zhou Z., Yang W., Yu T., Yu Yu, Zhao X., Yu Yanbo, Gu C., Bilotta A.J., Yao S., Zhao Q., Golovko G., Li M., Cong Y. GPR120 promotes neutrophil control of intestinal bacterial infection. Gut Microb. 2023;15 doi: 10.1080/19490976.2023.2190311. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Data will be made available on request.


Articles from Current Research in Food Science are provided here courtesy of Elsevier

RESOURCES