Antibacterial activity and mechanism of X33 antimicrobial oligopeptide against Acinetobacter baumannii

Abstract

Acinetobacter baumannii is a pathogenic bacterium widespread in human environments, especially in intensive care units, and is associated with high morbidity and infection rates. Multiple drug resistance in A. baumannii frequently leads to the death of patients, making the development of multi-effect antibacterial agents against this bacterium a research hotspot. We have previously found that the X33 antimicrobial oligopeptide can effectively inhibit the growth of Penicillium digitatum and Candida albicans. Herein, we evaluated the antibacterial activity of X33 antimicrobial oligopeptide against A. baumannii by determining the minimum inhibitory concentration, inhibition zone, and growth curve. The increase in extracellular alkaline phosphatase and the leakage of intracellular compounds confirmed the effect of X33 antimicrobial oligopeptide on the cell wall and membrane. Changes in reactive oxygen species, malondialdehyde, ATP, reducing sugar, soluble protein, and pyruvate content demonstrated that the incubation with X33 antimicrobial oligopeptide affected energy metabolism and oxidative stress. Consistent with the physiological characteristics, transcriptomics analysis indicated that incubation with X33 antimicrobial oligopeptide significantly induced changes in the expression of 2339 genes, including 1262 upregulated and 1077 downregulated genes, which participate in oxidative phosphorylation, ribosome, quorum sensing, fatty acid degradation, glycolysis/gluconeogenesis, and citrate cycle pathways. These results provide a fundamental basis for investigating the mechanism of X33 antimicrobial oligopeptide as a potential drug against A. baumannii.

Graphical abstract

1. Introduction

Acinetobacter baumannii is the most significant opportunistic pathogen in hospital settings and is capable of high transmissibility, morbidity, and mortality in immunocompromised individuals [1]. Because of its plastic genome, when faced with adversity and stress (desiccation, extreme pH and temperature, nutrient levels, and antibiotic use), the bacterium rapidly mutates to adapt and survive in harsh environments (human or environmental vectors) [2,3]. The use of antibiotics has led to an increase in antibiotic resistance, posing a threat to social health. A. baumannii infections mainly manifest as ventilator-associated pneumonia, meningitis, skin or soft tissue infections, and wound infections [4]. Hospital-acquired infections present in patients with severe trauma or burns, invasive surgical procedures, immunosuppressants, medical device use, and community-acquired infections are common in individuals with serious underlying diseases (diabetes mellitus, alcoholism, and obstructive pulmonary disorders) [5]. A. baumannii has a mortality rate of up to 68% and an attributable mortality rate of up to 36.5% and contributes to the mortality associated with COVID-19 [6,7].

Currently, β-lactams, fluoroquinolones, tetracyclines, polymyxins, aminoglycosides, lincosamides, and macrolides, capable of interfering the synthesis of nucleic acid, protein, cell wall, and cell membrane, are used for the treatment of A. baumannii infections [8,9]. However, A. baumannii develops drug resistance by changing membrane permeability, overexpressing efflux pumps, expressing β-lactamase and aminoglycoside modifying enzyme, and changing the target sites [8]. Thus, owing to the pressure of drug resistance and scarcity, new therapeutic strategies, such as antimicrobial peptides, metabolic interference therapy, photodynamic therapy, and phage therapy are urgently required [8]. Antimicrobial peptides (AMPs) found in various organisms are small molecular peptides generally composed of 10–60 amino acids with excellent antibacterial, antiviral, and antitumor effects. AMPs are effective and promising substitutes for antibiotics because of their ability to destroy cell membranes and walls, inhibit the synthesis of proteins and nucleic acids, and induce apoptosis and necrosis [10]. Almost all known bioactive microbial metabolites are produced by prokaryotes and eukaryotic fungi. Among them, Streptomyces produce 39% of all microbial metabolites in eukaryotes [11]. Secondary metabolites produced by Streptomyces exhibit crucial activities and can be used as drugs to treat cancer, bacterial infections, and other immune diseases [12]. For instance, vancomycin produced by Streptomyces orientalis possesses antimicrobial activity against A. baumannii [13]. In addition, various AMPs, including ZY4, cecropin-4, WLBU2-cationic amphipathic peptide, CL defensin, and FLIP 7 display significant therapeutic effects against A. baumannii infections [8].

In a previous study, we isolated an antimicrobial oligopeptide from Streptomyces lavendulae X33, named X33 antimicrobial oligopeptide (X33 AMOP), and found that it has superior bactericidal effect against Penicillium digitatum [14] and Candida albicans [15]. In the present study, we assessed the antibacterial potential of X33 AMOP against A. baumannii and elucidated its intrinsic inhibitory mechanism. This is the first report on the antibacterial effect and plausible mechanism of action of X33 AMOP against A. baumannii, which contributes to the development of a novel strategy for anti-inflammatory drugs.

2. Materials and methods

2.1. Strains and culture conditions

Acinetobacter baumannii ATCC 17978 was obtained from the Institute of Pathogenic Microorganisms, College of Bioscience and Bioengineering, Jiangxi Agricultural University, China. The strain was cultured on Luria-Bertani (LB) agar at 37 °C and stored at 4 °C for further use. The preparation of the X33 AMOP was consistent with that of a previous study [14].

2.2. Growth inhibition of A. baumannii in response to X33 AMOP

The antibacterial effect of X33 AMOP was studied using the standard broth dilution method and observing A. baumannii visible growth. The lowest X33 AMOP concentration without visible growth after shaking for 24 h is the minimum inhibitory concentration (MIC). To determine the minimum bactericidal concentration (MBC), the suspension from the test tube without visible growth in the MIC determination, was placed on LB agar and the number of colonies was counted after incubation. The MBC is the lowest antimicrobial concentration depicting no bacterial growth on the LB agar, as previously described [16]. The experiment was performed in triplicates.

2.3. Antibacterial assay using the Oxford cup method

The antibacterial effect of X33 AMOP against A. baumannii was determined using the Oxford cup method, as previously described [15]. The diameter of antibacterial circle was expressed as the mean ± standard error.

2.4. Effect of X33 AMOP on A. baumannii growth kinetics

A growth curve was constructed to determine the growth inhibitory effect of X33 AMOP on A. baumannii. The growth kinetics of A. baumannii with and without X33 AMOP treatment was determined. Bacteria were grown at 37 °C with 200 rpm shaking, and the absorbance at 600 nm was determined through ultraviolet spectrophotometry every 2 h. Growth curves were drawn using the absorption determined, as previously described [3].

2.5. Cell viability determination using XTT

XTT [2, 3-bis (2-methoxy-4-nitro-5-sulfophenyl)-2H-tetrazolium-5-carboxanilide] (0.5 mg/mL) was dissolved in PBS, and menadione (1 mmol/L) was dissolved in acetone. XTT and menadione were filtered through a 0.22 μm sterile filter stored at −20 °C. Cells were added to LB medium containing different concentrations of X33 AMOP. For use, menadione was added to XTT at a final concentration of 1 μmmol/L. In this study, the cells were added to the LB media with different concentrations of X33 AMOP for 4 and 8 h. Then, collected the cells by centrifugation and added the XTT-menadione solution to the samples and incubated for 2 h before the absorbance at 490 nm was determined [17].

2.6. Scanning electron microscope and alkaline phosphatase (AKP) assay

To visually observe the effect of X33 AMOP on A. baumannii, we used a scanning electron microscope (SEM). Bacteria were exposed to the MIC for X33 AMOP for 8 h. Bacteria were fixed with 2.5% glutaraldehyde for more than 12 h at low temperatures (4 °C). SEM imaging was performed as described previously [15]. The cells were cultured with concentrations of X33 AMOP, and supernatants samples were taken by centrifugation to measure the content of AKP. The extracellular AKP activity was measured using an AKP kit (Nanjing Jiancheng Bioengineering Institute, Nanjing, China), the measurement method was performed as described previously [16].

2.7. Reducing sugar and protein determinations

To measure reducing sugar and protein leaking from the membrane, bacteria were added to LB media with different X33 AMOP concentrations, and incubated for 4 and 8 h at 37 °C with 200 rpm shaking. Samples were centrifuged at 1000 rpm for 10 min, and the supernatant were collected to determine reducing sugar and proteins.

2.8. Reactive oxygen species (ROS) determination

ROS produced by A. baumannii were evaluated using a ROS assay kit (Nanjing Jiancheng Bioengineering Institute). 2′, 7′-dichlorofluorescein diacetate can be oxidized by ROS to dichlorofluorescein, which has a maximum absorption peak at an excitation wavelength of 488 nm and emission wavelength of 525 nm [18]. The bacterial culture was treatment with X33 AMOP and incubated at 37 °C with 200 rpm shaking. After incubation for 2, 4, 6, and 8 h, the cells were exposed to the DCFH-DA in the dark for 60 min to determine ROS production.

2.9. Membrane lipid peroxidation test

Lipid peroxides are indicators of oxidative stress, and malondialdehyde (MDA) is the product of membrane lipid peroxidation, which reflects the degree of lipid peroxidation and, subsequently, the degree of cellular damage. MDA forms complexes with thiobarbituric acid and can be quantified spectrophotometrically [18]. Briefly, bacterial were treated with X33 AMOP and collected by centrifugation after 4 and 8 h of incubation. After cell disruption, TBA solution was added and incubated at 95 °C for 40 min. The supernatant was centrifuged to determine the absorbance value after cooling to room temperature with ice water.

2.10. Pyruvate determination

Normal pyruvate metabolism is crucial for catabolism and anabolism, affecting the synthesis of carbohydrates and proteins. Therefore, we measured the content of pyruvic acid. Cells and different X33 AMOP concentrations were added to LB medium. The cultured samples were collected and subsequently used to determine the pyruvic acid content, as previously described [19].

2.11. ATP, reducing sugar, and soluble protein determinations

The cells were exposed to different concentrations of X33 AMOP for 8 h at 37 °C with 200 rpm shaking. Centrifuge collection of bacterial cells and the intracellular ATP levels were measured using an ATP content kit ((Nanjing Jiancheng Bioengineering Institute) [20]. Bacteria were collected after culturing for 4 h and 8 h. The supernatant obtained after grinding and crushing bacteria was used to determine the reducing sugar and soluble protein contents. An anthrone-sulfuric acid assay was used to test the reducing sugar content, and protein was detected using a protein detection kit (Nanjing Jiancheng Bioengineering Institute), the measurement method was performed as described previously [15].

2.12. RNA sequencing

Bacteria were cultured in LB medium for 4 h and divided into a treatment group with the MIC for X33 AMOP and a control group without X33 AMOP. After cultured, the cells were collected and RNA was extracted using the TRIzol® reagent. The concentration, purity, and integrity of the RNA were tested and used for subsequent library construction after meeting the requirements. A TruSeq™ RNA sample preparation kit was used to construct the RNA-seq library. After removal of rRNA using the Ribo-Zero Magnetic kit, mRNA was used as template for reverse transcription synthesis of cDNA using the SuperScript double-stranded cDNA synthesis kit, and then an A base was added at the 3′ end. Following PCR amplification, the paired-end RNA-seq library was sequenced using an Illumina HiSeq X Ten.

2.13. Statistical analysis

Data for experimental results were the mean and standard deviation values from three independent experiments and are expressed as mean ± standard deviation. To analyze the difference between control and treatment groups, one-way analysis of variance (ANOVA) and Duncan's post hoc test were performed using SPSS statistical software. P values of <0.05 were regarded significant and asterisks are used to indicate significant differences between control and treatment groups.

3. Results

3.1. X33 AMOP antibacterial activity against A. baumannii

To investigate the antibacterial activity of X33 AMOP against A. baumannii, we first conducted a standard broth dilution method that resulted in a MIC and MBC of 78.13 and 312.50 μg/mL, respectively (Table 1). In addition, the Oxford cup test revealed bacteriostasis when the cells were treated with X33 AMOP. The antimicrobial diameter at X33 AMOP concentration of 1/4 MIC, 1/2 MIC, and MIC reached 14.16 ± 0.83, 15.94 ± 0.87, and 16.88 ± 0.71 mm, respectively (Fig. 1A). The degree of growth disturbance of A. baumannii in response to X33 AMOP was concentration-dependent. Furthermore, the growth of A. baumannii was seriously disturbed by the treatment with X33 AMOP (Fig. 1B). The OD₆₀₀ of the 1/4 MIC treatment group was 0.33 ± 0.0001 after 12 h of cultivation and represents a 68.97% decrease compared with that of the control group (1.07 ± 0.02). To further confirm the growth inhibitory effect of X33 AMOP against A. baumannii, we used the XTT assay, which determines cell viability, to assess the living state of the cells. In viable cells, mitochondrial dehydrogenase reduces XTT to a formazan product, which can be determined through spectrophotometry to evaluate cell viability [17]. As shown in Fig. 1C, after 4 h of X33 AMOP treatment at 1/4 MIC, 1/2 MIC, and MIC, the surviving cells of A. baumannii were 63.18%, 54.82%, and 49.75%, respectively. The surviving cells of A. baumannii decreased by 30.27%, 25.98%, and 23.02%, respectively, after 8 h of X33 AMOP incubation. These findings show that X33 AMOP significantly retarded A. baumannii growth.

Table 1.

The MIC and MFC determination.

Concentrations (μg/mL)	2500	1250	625	312.5	156.25	78.125	39.0625	0
Clear (-, +) a	–	–	–	–	–	+	+	+
Colony (-, +) b	–	–	–	–	+	+	+	+

a Minimum inhibitory concentration, Minimum bactericidal concentration.

Fig. 1.

Effects of X33 AMOP on A. baumannii. (A) The zone of inhibition of different X33 concentrations AMOP against A. baumannii. (B) The growth curves of A. baumannii. The different colors show the growth curves at different X33 AMOP concentrations. (C) Surviving cells of A. baumannii after treatment with X33 AMOP. *p < 0.05, **p < 0.01, NS: p > 0.05.

3.2. Effect of X33 AMOP on cell structure and wall

To investigate the changes in the physiological phenotypes induced by X33 AMOP, we first performed a morphological imaging test that revealed significant variations in A. baumannii. The cell surface of A. baumannii treated with X33 AMOP for 4 h was clearly deformed and sunken, whereas that of the control group (0 h) was smooth and regular (Fig. 2A and B). When treated with X33 AMOP for 8 h, A. baumannii cells were further crumpled into a wrinkled and severely damaged morphology (Fig. 2C). These images indicated that X33 AMOP induced changes in cell morphology and damage. We evaluated AKP activity to determine the effect of X33 AMOP on the cell wall. Changes in extracellular AKP levels reflect changes in the cell wall permeability and integrity. As shown in Fig. 2D, the extracellular AKP levels increased after treatment with X33 AMOP for 4 h. The AKP content for the 1/4 MIC, 1/2 MIC, and MIC treatment groups was 1.85 ± 0.04, 2.15 ± 0.02, and 2.48 ± 0.23 U/L, respectively, which was higher than that of the control group (1.57 ± 0.04). These results suggested that X33 AMOP caused cell wall damage and increased cell wall permeability.

Fig. 2.

Effects of the different X33 AMOP concentrations on A. baumannii cell structure. Scanning electron microscopy of A. baumannii cells treated with X33 AMOP at the MIC for (A) 0 h, (B) 4 h, and (C) 8 h. (D) Alkaline phosphatase activity of the different X33 AMOP concentrations on A. baumannii. (E) Reducing sugar leakage of A. baumannii after treatment by X33 AMOP. (F) Protein leakage of A. baumannii after treatment by X33 AMOP. The different colors show the growth of the different X33 AMOP concentrations. *p < 0.05, **p < 0.01, NS: p > 0.05.

3.3. X33 AMOP incubation destroyed A. baumannii cell membrane integrity

The cell membrane is responsible for the uptake and release of cellular substances. Cell membrane integrity is commonly measured based on the secretion of reducing sugars and proteins [13]. Compared with the control group (37.36 ± 0.47 μg/mL), the extracellular reducing sugar increased by 1.73-fold (1/4 MIC), 1.84-fold (1/2 MIC), and 2.92-fold (MIC) after treatment with X33 AMOP for 4 h (Fig. 2E). In contrast, the extracellular reducing sugar contents reached 62.08 ± 2.25, 84.03 ± 5.41, and 112.22 ± 1.71 μg/mL when exposed to 1/4 MIC, 1/2 MIC, and MIC for X33 AMOP for 8 h, respectively, and represents a higher amount than that of the control group (42.24 ± 0.76 μg/mL) (Fig. 2E). In addition, after the incubation of 1/4 MIC, 1/2 MIC, and MIC of X33 AMOP for 8 h, the protein leakage from A. baumannii reached 14.28 ± 0.10, 16.29 ± 0.03, and 18.51 ± 0.07 μg/mL, higher than that for the control group (12.36 ± 0.13 μg/mL) (Fig. 2F). These findings suggest that X33 AMOP causes dose- and time-dependent protein and reduced sugar leakage in A. baumannii.

3.4. X33 AMOP induced ROS accumulation in A. baumannii

Accumulation of ROS accelerates cell death. In the present study, ROS levels increased after exposure to X33 AMOP in a time- and concentration-dependent manner. As shown in Fig. 3A, the highest ROS levels were observed after exposure to X33 AMOP MIC. The MDA concentration, an oxidative product of ROS, also increased upon exposure to X33 AMOP. As shown in Fig. 3B, the MDA contents after incubation with X33AMOP 1/4 MIC, 1/2 MIC, and MIC reached 8.05 ± 0.08, 9.10 ± 0.38, and 10.14 ± 0.15 μmol/g and represents a remarkable increase in the MDA content in the treatment group. These results suggest that X33 AMOP increases oxidative damage in A. baumannii.

Fig. 3.

Effects of the different X33 AMOP concentrations on the oxidative stress level in A. baumannii. (A) The fluorescence intensity of dichlorofluorescein (fluorescence intensity is proportional to ROS). (B) The MDA contents at the different X33 AMOP concentrations. *p < 0.05, **p < 0.01, NS: p > 0.05.

3.5. Effect of X33 AMOP on changes in the cellular content

To further evaluate whether A. baumannii cell contents were affected by X33 AMOP, we measured the intracellular concentrations of pyruvic acid, ATP, reducing sugars, and proteins. Intracellular pyruvic acid content decreased by 3.47%, 10.52%, and 23.34% after 4 h of incubation with 1/4 MIC, 1/2 MIC, and MIC of X33 AMOP, respectively (Fig. 4A). The amount of pyruvic acid produced decreased over time (Fig. 4A). ATP determination using the luciferase bioluminescence assay showed that the fluorescence significantly decreased after treatment with X33 AMOP, indicating that X33 AMOP inhibited energy metabolism in A. baumannii (Fig. 4B). Subsequently, the intracellular protein levels in A. baumannii were determined at 0, 2, 4, 6, and 8 h after treatment with X33 AMOP. As shown in Fig. 4C, the intracellular A. baumannii proteins were reduced to 6.06, 5.02, and 4.89 g/L when induced with 1/4 MIC, 1/2 MIC, and MIC XXE AMOP concentration and were significantly lower than that of the control group (8.16 g/L). We measured the intracellular content of reducing sugars after 2–8 h of incubation. Consistent with our hypothesis, the intracellular reducing sugar content was significantly reduced following treatment with X33 AMOP (Fig. 4D). These results suggest that X33 AMOP disrupts the anabolism of the cellular components of A. baumannii.

Fig. 4.

Effects of the different X33 AMOP concentrations on the cellular contents of A. baumannii. (A) The pyruvic acid content of A. baumannii at the different X33 AMOP concentrations. (B) The intracellular ATP of A. baumannii at the different X33 AMOP concentrations (The fluorescence value is proportional to ATP). (C) The intracellular protein contents of A. baumannii at the different X33 AMOP concentrations. (D) The intracellular reducing sugar content of A. baumannii at the different X33 AMOP concentrations. The different colors show different concentrations of X33 AMOP. *p < 0.05, **p < 0.01, NS: p > 0.05.

3.6. Transcriptome profiling of A. baumannii exposed to X33 AMOP

According to the physiological and biochemical findings, X33 AMOP inhibited A. baumannii growth. Subsequently, we used RNA-seq to examine the inhibitory mechanisms and determine the molecular mechanism of action of X33 AMOP against A. baumannii, which may serve as a guide for the development of new medications. Quality trimming was applied to the raw reads to produce clean reads. As shown in Table 2,2.55 million clean reads were acquired from 2.91 million raw reads in the control group, while 2.5 million clean reads were obtained from 2.86 million raw reads in the treatment group (treated with 78.13 μg/mL X33 AMOP, or the T group). The read quality macroscopically mirrored the caliber of the library building and sequencing of the sample. The findings demonstrated that Q20 and Q30 were higher than 85% and that the error rate was less than 0.1%, demonstrating that all sequencing samples were clean and met the criteria for transcriptional analysis. Correlations between groups C and T were examined. Higher levels of expression similarity or better correlation between samples were indicated by a correlation coefficient closer to 1. According to Fig. 5A and B, the correlation coefficients between three parallel samples of the C group were 1.00–0.96, while those between C and T group were 0.24–0.41, indicating strong similarity between samples and high disparities across groups. A total of 4376 genes were expressed simultaneously, with 1262 upregulated and 1077 downregulated genes (Fig. 5C).

Table 2.

The quality of sequencing.

Parameters	C gruop	T group
Raw reads (million)	2.91	2.55
Clean Reads (million)	2.86	2.5
Clean Error Rate (%)	0.02	0.02
Clean Q20 (%)	98.22	98.23
Clean Q30 (%)	94.76	94.68

Fig. 5.

Expression analysis of different genes between the samples. (A) Biological replicate correlation analysis of samples. Different colors indicate correlation coefficients, while colors closer to red indicate higher gene expression similarity between samples. (B) Principal component analysis (PCA) of the samples. The x-axis represents the contribution of principal component 1 (PC1) to the sample, and the y-axis represents the contribution of principal component 2 (PC2) to the sample. (C) A volcano plot showing the expression analysis of the different genes. Volcano plot of DEGs with 1262 upregulated gene (red dots), and 1077 downregulated genes (blue dots), and the grey dots represent genes without significant expression differences.

3.7. Kyoto Encyclopedia of genes and genomes (KEGG) and gene ontology (GO) analyses of differentially expressed genes (DEGs)

To extensively examine the biological mechanisms and pathways involving DEGs, their biological functions were annotated and categorized based on GO and KEGG analyses. The top 20 upregulated genes were involved in biological processes and molecular functions according to GO analysis (Fig. 6A). The distribution of DEGs among the biological processes was split between the regulation of RNA, cellular, and protein metabolisms. The DEGs were responsible for the following molecular functions: DNA binding, heterocyclic compound binding, organic cyclic compound binding, nucleic acid binding, transcription regulator activity, and DNA-binding transcription factor activity (Fig. 6A). GO analysis showed that the downregulated genes were enriched in two term types and 64 hierarchies, including oxidoreductase activity, catalytic activity, oxidoreductase activity, NAD(P)H, tricarboxylic acid cycle, carboxylic acid catabolic process, organic acid catabolic process, and cellular catabolic process (Fig. 6B). Next, we performed KEGG pathway annotation and enrichment analysis of these DEGs to understand their functions. As shown in Figs. 6C and 26 upregulated genes were clustered into ribosomes, biosynthesis of various secondary metabolites (part 3), and quorum sensing pathways. Downregulated genes were enriched in 31 pathways (p < 0.05). The top 20 pathways are shown in Fig. 6D, comprising a two-component system, pyruvate metabolism, citrate cycle, glycolysis/gluconeogenesis, and oxidative phosphorylation.

Fig. 6.

The GO and KEGG enrichment analyses of DEGs. The vertical axis represents GO Term or KEGG Pathway, while the horizontal axis represents the enrichment factor. The dot size represents the number of genes in the GO Term or KEGG Pathway, and the dot color corresponds to the different P-values. (A) Top 20 GO functions of the upregulated genes. (B) Top 20 GO functions of the downregulated genes. (C) Top 20 KEGG pathways enrichment of the upregulated genes. (D) Top 20 KEGG pathways enrichment of the upregulated genes.

4. Discussion

As A. baumannii is an opportunistic pathogen, antibiotics are the mainstay of treatment. New non-antibiotic medicines are urgently needed because of the strong bacterial survival owing to the complex drug resistance mechanisms, and AMPs are a possible substitute. To develop novel medications that can replace antibiotics, we explored the mechanism of action of X33 AMOP against A. baumannii.

4.1. Cell wall damage in A. baumannii induced by X33 AMOP

Peptidoglycan is a unique macromolecular structure in the bacterial cell wall that has important structural and physiological functions. Inhibition or interference of peptidoglycan biosynthesis is a key target for bacterial inhibition [21,22]. We found that X33 AMOP affected cell wall-related metabolic pathways, such as those for starch, sucrose, and amino sugar metabolism [23]. The peptidoglycan biosynthesis-related genes, dacC, murC, murF, mrcB, ponA, murG, mrdA, and murB were dramatically downregulated (Table 3). Penicillin-binding proteins (PBPs) participate in the synthesis of the cell wall and are the target proteins of β-lactam drugs. Antibiotics known as β-lactams attach to PBPs, prevent transglycosylase and transpeptidase activity, further impairs peptidoglycan synthesis, and cause cell wall lysis [18,24]. In this study, the transcription of the PBP-encoding genes H0N28_12920, dacC, mrcB, ponA, and mrdA was reduced 1.14- to 4.61-folds, which is consistent with previous results that claimed that tetracycline therapy resulted in considerable downregulation of the genes responsible for the cell wall peptidoglycan production pathway [25]. AKP is present between the cell wall and cell membrane and is an indicator of cell wall integrity [16]. Litsea cubeba essential oil can induce AKP leakage, thereby damaging the cell wall integrity [16]. Similar to the L. cubeba essential oil, the increase in extracellular AKP concentration further revealed the damage caused by X33 AMOP to the cell walls of A. baumannii. X33 AMOP interferes with cell wall synthesis in A. baumannii to achieve bacteriostasis.

Table 3.

Differentially expression genes.

	Gene name	Gene description	Log2FC(Treated/Control)	Padjust	Regulate
Peptidoglycan biosynthesis	dacC	D-alanyl-d-alanine carboxypeptidase PBP5/6	−3.27	2.01E-236	down
	murC	UDP-N-acetylmuramate--l-alanine ligase	−2.58	5.06E-134	down
	murF	UDP-N-acetylmuramoyl-tripeptide--D-alanyl-d-alanine ligase	−1.73	2.69E-52	down
	mrcB	penicillin-binding protein 1B	−1.46	7.12E-81	down
	ponA	penicillin-binding protein PBP1a	−1.34	4.72E-51	down
	murG	undecaprenyldiphospho-muramoylpentapeptide beta-N-acetylglucosaminyltransferase	−1.33	1.81E-59	down
	mrdA	penicillin-binding protein 2	−1.14	2.11E-47	down
	H0N28_17525	d-alanine--d-alanine ligase	−1.09	1.73E-29	down
	murB	UDP-N-acetylmuramate dehydrogenase	−1.02	1.43E-19	down
	H0N28_02540	phosphatase PAP2 family protein	1.12	4.84E-15	up
	H0N28_12920	substrate-binding domain-containing protein	−4.61	0	down
lipopolysaccharide	H0N28_18735	polysaccharide biosynthesis tyrosine autokinase	−1.92	2.13E-127	down
	H0N28_07855	LPS-assembly protein LptD	−1.77	2.62E-87	down
	H0N28_06305	lauroyl acyltransferase	3.01	1.09E-217	up
Two-component system	H0N28_11050	two-component system sensor histidine kinase PmrB	−1.27	1.12E-23	down
	H0N28_14515	DNA-binding response regulator PmrA	−1.83	1.54E-09	down
Histidine metabolism	basG	acinetobactin biosynthesis histidine decarboxylase BasG	1.01	0.003044706	up
	H0N28_00400	imidazolonepropionase	−2.98	2.03E-146	down
	hutG	formimidoylglutamase	−3.23	1.22E-221	down
Catalase	katE	catalase HPII	−4.95	0	down
	katG	catalase/peroxidase HPI	−3.77	0	down
Glutathione peroxidase	H0N28_07425	glutathione peroxidase	−2.57	1.72E-100	down
	H0N28_18175	glutathione peroxidase	−2.13	2.85E-101	down
TCA cycle	H0N28_08825	2-oxo acid dehydrogenase subunit E2	−1.45	6.06E-54	down
	lldD	FMN-dependent l-lactate dehydrogenase LldD	−1.02	3.36E-11	down
	gltA	citrate (Si)-synthase	−1.13	2.58E-45	down
	lpdA	dihydrolipoyl dehydrogenase	−3.02	1.53E-250	down
	lpdA	dihydrolipoyl dehydrogenase	−2.08	1.88E-80	down
	H0N28_14275	2-oxoglutarate dehydrogenase E1 component	−1.04	4.88E-50	down
	odhB	2-oxoglutarate dehydrogenase complex dihydrolipoyllysine-residue succinyltransferase	−2.94	7.45E-218	down
Glycolysis/gluconeogenesis	H0N28_13680	class 1 fructose-bisphosphatase	−1.11	1.81E-42	down
	H0N28_14360	iron-containing alcohol dehydrogenase	−3.2	0	down
	H0N28_02505	NADP-dependent glyceraldehyde-3-phosphate dehydrogenase	−3.08	6.10E-257	down
	pgi	glucose-6-phosphate isomerase	−1.85	1.20E-63	down
	H0N28_04235	phosphomannomutase/phosphoglucomutase	−1.75	1.61E-86	down
	ppsA	phosphoenolpyruvate synthase	−1.13	1.06E-48	down
Oxidative phosphorylation	H0N28_18205	F0F1 ATP synthase subunit alpha	−1.17	1.71E-48	down
	atpB	F0F1 ATP synthase subunit A	−1.61	1.02E-71	down
	atpE	F0F1 ATP synthase subunit C	−1.16	2.37E-30	down
	H0N28_18215	F0F1 ATP synthase subunit B	−1.17	3.45E-36	down
	H0N28_18210	F0F1 ATP synthase subunit delta	−1.08	2.96E-35	down
	H0N28_10020	cytochrome ubiquinol oxidase subunit I	−5.64	0	down
	H0N28_07260	cytochrome ubiquinol oxidase subunit I	−1.55	2.20E-35	down
	cydB	cytochrome d ubiquinol oxidase subunit II	−4.91	0	down
	cydB	cytochrome d ubiquinol oxidase subunit II	−1.01	3.16E-24	down
	cyoB	cytochrome o ubiquinol oxidase subunit I	−2.09	1.66E-168	down
	cyoC	cytochrome o ubiquinol oxidase subunit III	−2.09	1.18E-78	down
	H0N28_11530	cytochrome o ubiquinol oxidase subunit IV	−2.28	2.19E-26	down
	nuoC	NADH-quinone oxidoreductase subunit C/D	−1.14	1.88E-50	down
	nuoE	NADH-quinone oxidoreductase subunit NuoE	−1.39	1.14E-41	down
	nuoF	NADH-quinone oxidoreductase subunit NuoF	−1.94	1.03E-138	down
	nuoG	NADH-quinone oxidoreductase subunit NuoG	−3.06	0	down
	nuoH	NADH-quinone oxidoreductase subunit NuoH	−4.12	5.14E-256	down
	nuoI	NADH-quinone oxidoreductase subunit NuoI	−3.91	4.74E-274	down
	nuoJ	NADH-quinone oxidoreductase subunit J	−4.02	3.30E-224	down
	nuoK	NADH-quinone oxidoreductase subunit NuoK	−4.51	6.96E-92	down
	nuoL	NADH-quinone oxidoreductase subunit L	−3.53	7.57E-289	down
	nuoM	NADH-quinone oxidoreductase subunit M	−3.4	0	down
	nuoN	NADH-quinone oxidoreductase subunit NuoN	−3.1	8.14E-267	down

4.2. Change in A. baumannii cell membrane permeability induced by X33 AMOP

The intracellular environment is partially stabilized by the cell membrane, which serves as a crucial barrier to the entry and exit of chemicals. In the present study, the significant increase in extracellular proteins and reducing sugars, and changes in cell structure (deformation and shrinkage) indicated that X33 AMOP may disrupt the cell membrane structure, leading to changes in the cell composition. Similar results were obtained in our previous study on Candida albicans and Penicillium digitatum [14,15]. Membrane proteins are a crucial part of the cell membrane and are incorporated into the cell via lipopolysaccharides [26]. Downregulation of the genes H0N28_18735 and H0N28_07855 related to lipopolysaccharide biosynthesis indicated that X33 AMOP had an effect on the cell membrane. In addition, we found that the pathways, including glycerophospholipid and glycerolipid metabolisms, related to cell membrane were affected by X33 AMOP [23]. The two-component system is a signal transduction pathway that senses and signals changes in the external environment and consists of a sensor kinase (histidine kinase) and its response regulator [27]. The two-component system is repaired when the cell membrane is damaged. In response to environmental stimuli, PmrB activates PmrA via phosphorylation. Consistent with our assumptions, various crucial genes related to the two-component system pathway were significantly downregulated after treatment with X33 AMOP. Among them, H0N28_14510 encoding the two-component system sensor histidine kinase PmrB, H0N28_14515 encoding the DNA-binding response regulator PmrA, H0N28_00400 encoding imidazolone propionase, and hutG encoding formimidoylglutamase were significantly downregulated (Table 3). The changes in the expression of these genes were similar to those in A. baumannii treated with L. cubeba essential oil [28]. Based on the findings of cell content leakage, SEM, and additional integration with the transcriptome data, X33AMOP interferes with the cell membrane to exert an effect on it.

4.3. X33 AMOP induced oxidative stress in A. baumannii

Oxidative stress refers to the excessive production of ROS or metabolic disorders that exceed the ability of the endogenous antioxidant defense system to eliminate it. ROS include free radicals, which eventually lead to lipid peroxidation and damage cellular proteins, DNA, and ATP [29]. After treatment with X33 AMOP, ROS, and MDA levels increased significantly, suggesting that X33 AMOP induced the production of toxic products. Superoxide dismutase, catalase, and glutathione peroxidase scavenge reactive oxygen species and reduce cell damage [30]. However, the expression of genes encoding catalase (katE and katG) and glutathione peroxidase (H0N28_07425 and H0N28_18175) was downregulated by 2.11- to 4.95-folds, which prevented the synthesis of enzymes that scavenge ROS, resulting in oxidative damage to cells and cell membrane. Similar investigations have revealed that catalase and glutathione peroxidase are downregulated by alpha-mangostin to prevent biofilm development [31,32]. Furthermore, the integrity of the cell membrane may change due to lipid peroxidation, which alters the lipid content of the membrane.

4.4. X33 AMOP induced energy metabolism changes in A. baumannii

Energy metabolism, consisting of the citrate cycle (TCA cycle), pyruvate metabolism, glycolysis, and oxidative phosphorylation, is extremely important for normal cellular activities. X33 AMOP treatment significantly affects the TCA cycle, pyruvate metabolism, glycolytic pathways, and oxidative phosphorylation in A. baumannii. In response to X33 AMOP treatment, A. baumannii showed downregulation of 24 of 28 pyruvate metabolism genes, 16 of 17 TCA cycle genes, 31 of 32 oxidative phosphorylation genes, and 17 genes involved in glycolysis/gluconeogenesis. The rate-limiting enzymes in the pyruvate pathway, H0N28_08825 encoding pyruvate dehydrogenase subunit E2, and lldD encoding FMN-dependent l-lactate dehydrogenase LldD, were considerably downregulated in pyruvate metabolism [33]. In addition, the expression of genes related to TCA and glycolysis/gluconeogenesis were significantly downregulated, including rate-limiting enzyme citrate (Si)-synthase (gltA), α-ketoglutarate dehydrogenase (lpdA, lpdA, H0N28_14275, odhB), fructose-bisphosphatase (H0N28_13680), phosphomannomutase/phosphoglucomutase (H0N28_04235), and phosphoenolpyruvate synthase (ppsA). Similarly, RNA-seq results after tetracycline induction in A. baumannii revealed downregulation of TCA gene expression, along with downregulation of glycolysis/gluconeogenesis gene expression [25,34]. Oxidative phosphorylation is a biochemical process involving coupling reactions between the energy released during the oxidation of substances and the synthesis of ATP by inorganic phosphate and ADP through the respiratory chain. The DEGs involved in energy generation and transformation, including F0F1 ATP synthase (H0N28_18205, atpB, atpE, H0N28_18215, and H0N28_18210), cytochrome ubiquinol oxidase (H0N28_10020, H0N28_07260, cydB, cydB, cyoB, cyoC, and H0N28_11530), and NADH-quinone oxidoreductase (nuoC, nuoE, nuoF, nuoG, nuoH, nuoI, nuoJ, nuoK, nuoL, nuoM, and nuoN) were downregulated, indicating that oxidative phosphorylation was blocked, which is consistent with the results of tobramycin treatment on A. baumannii [35].

Numerous medications that are available to treat infection have MICs greater than X33 AMOP, such as imipenem (256 μg/mL) and Litsea cubeba essential oil (1.04 mg/mL), suggesting that X33 AMOP has a super inhibitory effect [16,18]. However, current medications, like peptide Cec4, have a better therapeutic impact than X33 AMOP [36]. But prior studies have shown that X33 AMOP is non-toxic, has no adverse effects, and inhibits both Penicillium digitatum and Candida albicans. For these reasons, X33 AMOP provides a good alternative against A. baumannii infection.

5. Conclusion

To the best of our knowledge, this is the first study to demonstrate that X33 AMOP can inhibit A. baumannii growth. X33 AMOP interfered with the TCA cycle, glycolysis, oxidative phosphorylation, pyruvate metabolism, and cell composition, which finally inhibited A. baumannii cell growth. The discovery of X33 AMOP as a novel agent against A. baumannii highlights the great potential of peptides in the treatment of bacterial infections. We confirmed the potential efficacy of X33 AMOP in treating A. baumannii infections. Therefore, the results of this study provide a possible target against A. baumannii and a theoretical basis for the antibacterial activity of antimicrobial peptides.

Funding

This study was funded by Major Discipline Academic and Technical Leaders Training Program of Jiangxi Province [No. 20212BCJ23012], the Department of Science Technology of Jiangxi Province (Grant No. 20171ACF60006), the Collaborative Innovation Center of Postharvest Key Technology and Quality Safety of Fruits and Vegetables in Jiangxi Province, and National Natural Science Foundation of China [No. 32000057 and 32360021].

Availability of data and materials

Not application.

CRediT authorship contribution statement

Qunlin Lu: Investigation, Methodology, Writing – original draft. Xiaoyu Wu: Conceptualization, Data curation, Formal analysis, Investigation, Supervision, Writing – original draft. Yuan Fang: Investigation, Methodology. Yuanxiu Wang: Supervision, Validation. Bin Zhang: Conceptualization, Data curation, Funding acquisition, Project administration, Supervision, Writing – review & editing.

Declaration of competing interests

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