ABSTRACT

   Antibiotic resistance is a recognized and concerning public health
   issue. Gram-negative bacilli, such as Pseudomonas aeruginosa (P.
   aeruginosa), are notorious for their rapid development of drug
   resistance, leading to treatment failures. TanReQing injection (TRQ)
   was chosen to explore its pharmacological mechanisms against clinical
   multidrug-resistant P. aeruginosa (MDR-PA), given its antibacterial and
   anti-inflammatory properties. We revealed the expression of proteins
   and genes in P. aeruginosa after co-culture with TRQ. This study
   developed an assessment method to evaluate clinical resistance of P.
   aeruginosa using MALDI-TOF MS identification and Biotyper database
   searching techniques. Additionally, it combined MIC determination to
   investigate changes in MDR-PA treated by TRQ. TRQ effectively reduced
   the MICs of ceftazidime and cefoperazone and enhanced the confidence
   scores of MDR-PA as identified by mass spectrometry. Using this
   evaluation method, the fingerprints of standard P. aeruginosa and
   MDR-PA were compared, and the characteristic peptide sequence (Seq-PA
   No. 1) associated with flagellum was found. The phenotypic experiments
   were conducted to confirm the effect of TRQ on the motility and
   adhesion of P. aeruginosa. A combination of co-immunoprecipitation and
   proteome analysis was employed, and 16 proteins were significantly
   differentially expressed and identified as potential candidates for
   investigating the mechanism of inhibiting resistance in P. aeruginosa
   treated by TRQ. The candidates were verified by quantitative real-time
   PCR analysis, and TRQ may affect these core proteins (MexA, MexB, OprM,
   OprF, OTCase, IDH, and ASL) that influence resistance of P. aeruginosa.
   The combination of multiple methods helps elucidate the synergistic
   mechanism of TRQ in overcoming resistance of P. aeruginosa.

IMPORTANCE

   Pseudomonas aeruginosa is an opportunistic pathogen closely associated
   with various life-threatening acute and chronic infections. The
   presence of antimicrobial resistance and multidrug resistance in P.
   aeruginosa infections significantly complicates antibiotic treatment.
   The expression of β-lactamase, efflux systems such as MexAB-OprM, and
   outer membrane permeability are considered to have the greatest impact
   on the sensitivity of P. aeruginosa. The study used a method to assess
   the clinical resistance of P. aeruginosa using matrix-assisted laser
   desorption ionization time of flight mass spectrometry identification
   and Biotyper database search techniques. TanReQing injection (TRQ)
   effectively reduced the MICs of ceftazidime and cefoperazone in
   multidrug-resistant P. aeruginosa (MDR-PA) and improved the confidence
   scores for co-cultured MDR-PA. The study found a characteristic peptide
   sequence for distinguishing whether P. aeruginosa is resistant. Through
   co-immunoprecipitation and proteome analysis, we explored the mechanism
   of TRQ overcoming resistance of P. aeruginosa.

   KEYWORDS: Pseudomonas aeruginosa, clinical multidrug-resistant,
   MALDI-TOF MS, overcoming resistance, TanReQing injection

INTRODUCTION

   Pseudomonas aeruginosa is classified as an opportunistic pathogen that
   can cause a wide range of infections in human. These infections can
   range from nosocomial infections to those associated with cystic
   fibrosis, ventilator-associated pneumonia, burns, chronic obstructive
   pulmonary disease, and even those induced by conditions like COVID-19,
   among others, all attributed to P. aeruginosa in clinical settings
   ([42]1[43]–[44]3). . The rapid mutation and adaptation of P. aeruginosa
   to develop antibiotic resistance present significant challenges for
   effective therapy. Patients afflicted with multidrug-resistant (MDR) or
   extensively drug-resistant strains of P. aeruginosa are at higher risk
   for receiving inadequate initial antimicrobial therapy, leading to
   further resistance and increased mortality rates ([45]4, [46]5).
   Antimicrobial resistance is considered as one of the greatest global
   health threats of the 21st century. According to epidemiological
   research, bacterial infections caused by antibiotic resistance claimed
   the lives of up to 700,000 people annually ([47]6). P. aeruginosa is
   one of the six “ESKAPE” superpathogenic bacteria and has been
   classified as a “critical” pathogen by the World Health Organization.
   Innovative and urgent treatments are imperative to confront the
   challenges posed by this highly resistant bacterium ([48]7).

   P. aeruginosa exhibits a complex resistance mechanism, including
   inherent, acquired, and adaptive drug resistance, which allows it to
   develop resistance to a broad spectrum of antibiotics. Factors such as
   restricted outer membrane permeability, efflux systems like MexAB-OprM,
   and antibiotic-inactivating enzymes like β-lactamases, among others,
   collectively contribute to the intrinsic resistance of P. aeruginosa to
   multiple antibiotics at a high level ([49]8, [50]9). For these
   intrinsic resistance mechanisms, the resistance-nodulation-cell
   division (RND) family efflux pumps (MexAB-OprM, MexCD-OprJ, MexEF-OprN,
   and MexXY-OprM) play an important role in antibiotic resistance of P.
   aeruginosa, which is one of the MDR efflux pumps. Unlike traditional
   efflux pumps that usually export a single type of drug, MDR efflux
   pumps have the capacity to excrete a wide range of drugs ([51]10). The
   acquired resistance of antibiotics is caused by resistance genes
   transfer and gene mutations. Additionally, some environmental stimuli
   and bacterial behaviors (e.g., motility, persister cells, and biofilm
   formation) can lead to adaptive resistance. These triggers may affect
   the expression of efflux pumps and AmpC, further contributing to
   antibiotic resistance ([52]11, [53]12).

   Due to the emergence of MDR strains, conventional antibiotic therapy
   for P. aeruginosa infections has progressively lost its effectiveness.
   Current treatment strategies for P. aeruginosa involve the combined use
   of different antibiotics and ongoing research into the development of
   novel antibiotics ([54]3). Furthermore, novel therapeutic approaches
   such as phage therapy, quorum sensing inhibition, immunotherapy, gene
   editing therapy, antimicrobial peptides, and vaccine therapies have
   garnered attention in the field. Nevertheless, it is worth noting that
   the research and development of new antibiotics and other therapeutic
   techniques are progressing at a slow and time-consuming pace ([55]13).
   Therefore, in accordance with the literature, the most cost-effective
   approach against drug-resistant bacteria is to utilize existing
   medications to restore the susceptibility of drug-resistant bacteria to
   antibiotics, coupled with effective management strategies ([56]14).
   Presently, various combinations of antibiotics and synergists, such as
   β-lactamase inhibitors, have been reported, showing promising potential
   for restoring antibiotic susceptibility and reversing resistance in
   resistant pathogens ([57]15). A strategy combining polymers and
   antibiotics has been reported to restore the rifampicin resistance
   phenotype in Acinetobacter baumannii ([58]16). The combination strategy
   has laid the foundation for a novel category of antibiotic adjuvants
   with the potential to reverse drug resistance.

   TanReQing injection (TRQ) is a preparation possessing antibacterial and
   anti-inflammatory properties and is extensively used in the treatment
   of respiratory tract infections, the prophase of pneumonia, and other
   related diseases ([59]17, [60]18). TRQ has obtained approval from the
   State Drug Administration of China and is a mixed extract derived from
   bear gall powder, Scutellariae radix, Forsythiae fructus, Lonicerae
   japonicae flos, and Caprae hirci cornu. The main extracts in TRQ
   include total cholic acid extract of bear gall powder, total amino acid
   extract of Caprae hirci cornu, baicalin extract of Scutellariae radix,
   water extract of Lonicerae japonicae flos, and water extract of
   Forsythiae fructus, with each extract blended in a ratio of
   4:2:25:25:50. Several reports have been published on the qualitative
   and quantitative analyses of the chemical composition of TRQ, detecting
   11, 60, and 126 components in TRQ, respectively ([61]19[62]–[63]21).
   The quantitative determination of baicalin, ursodeoxycholic acid,
   chenodeoxycholic acid, and total amino acids and the qualitative
   detection of fingerprints were performed according to the officially
   used drug standards.

   Antibacterial and anti-inflammatory effects of TRQ have been reported
   in the literature. Furthermore, TRQ has been found to be particularly
   effective when used in conjunction with antibiotics to combat
   methicillin-resistant Staphylococcus aureus pathogens ([64]22). In
   addition, TRQ has been demonstrated to influence Staphylococcus aureus
   division, reducing virulence ([65]23), and it significantly reduced the
   expression of genes regulated by quorum sensing in P. aeruginosa
   ([66]24). P. aeruginosa remains a major pathogen causing respiratory
   tract infections in clinical settings. Several studies indicated that
   the combination of TRQ with antibiotics had better clinical efficacy in
   the treatment of pulmonary infections caused by P. aeruginosa
   ([67]25[68]–[69]27). However, the underlying mechanism responsible for
   this synergy remains unclear.

   In clinical studies, the primary methods for identifying bacterial
   isolates have traditionally relied on phenotypic characteristics,
   including colony morphology, biochemical reactions, growth patterns in
   different media, and Gram staining. While these techniques generally
   provide high accuracy, they can be time consuming and costly ([70]28).
   Currently, matrix-assisted laser desorption ionization time of flight
   mass spectrometry (MALDI-TOF MS) is widely used for the identification
   of various bacteria isolated from clinical samples. This technology
   enables the rapid identification of bacteria by comparing their
   fingerprints with those in the reference databases. MALDI-TOF MS has
   significantly accelerated diagnosis while simultaneously reducing
   medical expenses. Moreover, several academic groups have proposed
   innovative solutions to accelerate antimicrobial susceptibility testing
   (AST) and the detection of bacterial resistance-associated proteins.
   For instance, they have developed methods for the rapid detection of
   carbapenemase production using this method ([71]29[72]–[73]32).

   To investigate the pharmacological mechanism of TRQ on
   multidrug-resistant P. aeruginosa (MDR-PA), we developed an evaluation
   method using P. aeruginosa as a model microorganism to represent
   clinically sensitive and resistant strains. This is the first time that
   MALDI-TOF MS identification has been combined with the minimum
   inhibitory concentration (MIC) to assess the pharmacological effects of
   TRQ on MDR-PA. We tried to find the characteristic peptide sequence by
   comparing the protein fingerprints of standard P. aeruginosa and
   MDR-PA. Additionally, through co-immunoprecipitation (Co-IP) and
   in-depth proteome analysis of the microorganism (standard P. aeruginosa
   and MDR-PA), we explored the pharmacological mechanism of TRQ. This
   study reveals the involvement of several key proteins in MDR-PA
   resistance. After co-cultivation with TRQ, changes in protein
   expression were observed in MDR-PA, indicating that TRQ has the
   potential to sensitize MDR-PA.

   The overview of the experimental workflow is illustrated in [74]Fig. 1.
   In brief, standard P. aeruginosa and MDR-PA were co-cultured with TRQ
   for six generations. Changes in MICs of antibiotics were detected, and
   the confidence scores of co-cultured strains were determined using
   MALDI-TOF-MS. Characteristic peptide sequence was subsequently
   identified through mass spectrometry (MS) identification. To focus on
   the characteristic peptides sequence, antibodies against this peptide
   were obtained through an immunization test conducted in mice. The
   mechanism and the core proteins were explored through Co-IP
   experiments. Proteome analysis was performed by digesting the proteins
   with trypsin and desalting them with a C18 pre-column. The
   identification was performed using liquid chromatography-tandem mass
   spectrometry (LC-MS/MS), and the analysis was conducted using a
   label-free approach to screen out proteins related to TRQ-sensitized
   MDR-PA strains. Finally, the gene expression of these relevant proteins
   was verified through quantitative real-time PCR (RT-qPCR).

Fig 1.

   [75]Fig 1
   [76]Open in a new tab

   Overview of the experimental workflow. First, the sensitization of TRQ
   to MDR-PA strains was determined by phenotype experiment. After
   co-culture of TRQ and MDR-PA/P. aeruginosa (PA) for six generations,
   the MIC values of antibiotics were detected. The confidence scores of
   co-cultured MDR-PA strains were identified by MALDI-TOF -MS, and the
   characteristic peptide sequence was found by fingerprint comparison.
   Second, we obtained antibodies to focused peptides through immunity
   test of mice and found proteins interacting with immune antibodies by
   co-immunoprecipitation (Co-IP). Third, proteins for proteome analysis
   were tryptically digested in solution, desalted using a C18 precolumn,
   and subjected to LC and Q-Exactive analysis. Then, the peptide mixture
   was analyzed with online reversed-phase chromatography and mass
   spectrometry (LC-MS/MS), and a label-free approach was used for the
   quantitative analysis (proteome analysis). Finally, the gene expression
   of MDR-PA strain sensitized by TRQ was detected by RT-qPCR and was
   verified with the change of protein expression.

RESULTS

TRQ decreased the MICs of ceftazidime and cefoperazone against P. aeruginosa

   After co-culturing TRQ with standard P. aeruginosa or MDR-PA for six
   generations, we determined the MICs of different antibiotics. For
   standard P. aeruginosa, the MIC values did not show significant
   changes. However, for MDR-PA, the MIC of cefoperazone and ceftazidime
   tended to decrease after co-culture with TRQ (Table S1; [77]Fig. 2A).
   Before and after co-cultivation with TRQ, the MICs of cefoperazone and
   ceftazidime against the standard P. aeruginosa (PA 27853) strain were
   consistent at 16 µg/mL and 4 µg/mL, respectively. Notably, the MICs of
   cefoperazone for various MDR-PA strains decreased significantly:
   MDR-PA1 from 8,192 μg/mL to 1,024 μg/mL, MDR-PA7 from 8,192 μg/mL to 32
   μg/mL, and MDR-PA8 from ≥8,192 μg/mL to 1,024 μg/mL. Similarly, the
   MICs of ceftazidime against MDR-PA2 decreased from 4,096 μg/mL to 1,024
   μg/mL and against MDR-PA5 decreased from 8,192 μg/mL to 2,048 μg/mL.
   The MIC results suggested that TRQ has an influence on resistance of P.
   aeruginosa.

Fig 2.

   [78]Fig 2
   [79]Open in a new tab

   TRQ sensitizes multidrug-resistant Pseudomonas aeruginosa (MDR-PA). (A)
   MICs of different antibiotics of G0 and G6 strains after co-culture
   with TRQ. (B) The confidence scores of MDR-PA/P. aeruginosa (PA) after
   co-culture with TRQ by MALDI-TOF-MS. (C) The G0 generation of MDR-PA
   fingerprints by MALDI-TOF-MS. (D) The G6 generation of MDR-PA
   fingerprints by MALDI-TOF-MS.

TRQ enhanced the confidence scores of MDR-PA

   The strains, both co-cultured with and without TRQ, were identified
   using MALDI-MS and the Biotyper platform. The result showed a gradual
   increase in the confidence scores for both the original strain and the
   strains co-cultured with TRQ for six generations ([80]Fig. 2B). The
   confidence score reflects the match quality of MS peaks between the
   sample spectrum and the standard fingerprint in the Biotyper database
   identified by the MALDI-TOF MS. A higher score signifies a better
   match, and a score within the range of 1.8 to 2.0 represents a perfect
   match. Notably, the sensitive strain PA27853 exhibited a score within
   the 1.8–2.0 range, signifying a perfect match. The confidence scores of
   MDR-PA strains increased from initially below 1.5 to exceed 1.8,
   progressing after six successive co-cultivation generations. This
   significant increase in scores and confidence levels suggested that TRQ
   may sensitize MDR-PA based on the phenotypic results.

   Following this, the MALDI fingerprints of different generations of
   standard P. aeruginosa and MDR-PA co-cultured with TRQ from 0 to 6
   generation were compared and analyzed using Mascot Engines ([81]Fig. 2C
   and D). This analysis led to the identification of a significant
   differential sequence, which was designated as “Seq-PA No. 1” and
   recognized as a distinctive feature sequence. Meanwhile, it was
   observed that Seq-PA No. 1 might be associated with the flagella
   protein of P. aeruginosa, which prompted further, in-depth research
   into its related functions.

TRQ affected the flagellar motility of P. aeruginosa

   Flagellar motility is a crucial factor associated with the virulence of
   P. aeruginosa, as it plays a pivotal role in bacterial movement,
   colonization, biofilm formation, and adhesion to substrates. To assess
   the impact of TRQ on motility of P. aeruginosa, we conducted tests to
   evaluate swarming, swimming, and twitching motility ([82]Fig. 3A and
   B). Following continuous co-culture of TRQ with bacteria, swimming
   motility exhibited a significant decrease in the diameter of the
   MDR-PA2 colony from 1.8 cm to 1.2 cm (P < 0.001). In swarming motility,
   the MDR-PA1 (G0 = R0) colony exhibited radial growth, which disappeared
   after continuous co-culture with TRQ. In twitching motility, for the
   MDR-PA2 colony, the diameter of the diffuse bacterial zone decreased
   from 1.6 cm to 1.5 cm from G0 to G6 (P > 0.05). The motility assay
   suggested that TRQ may impact the flagellar motility of P. aeruginosa.

Fig 3.

   [83]Fig 3
   [84]Open in a new tab

   The motility and adhesion of MDR-PA after co-culture with TRQ. (A and
   B) The motility assay of P. aeruginosa after co-culture with TRQ. (C)
   The hydrophobicity assay of P. aeruginosa after co-culture with TRQ.
   The data of the bacterial circle diameter were expressed as means ±
   standard deviation and were analyzed by one-way analysis of variance
   (ANOVA) and Tukey’s multiple-comparison test; ***P＜0.001.

TRQ reduced the adhesion of MDR-PA

   The adhesion rate of MDR-PA2 decreased significantly overall after TRQ
   treatment, especially after 4 h ([85]Fig. 3C). This observation
   suggested that TRQ treatment could reduce the surface hydrophobicity of
   MDR-PA, resulting in weakened adhesion ability. This weakening of
   adhesion ability may not be conducive to its local colonization and
   could potentially reduce its pathogenicity.

Co-immunoprecipitation and proteome analysis of P. aeruginosa after TRQ
treatment

   We synthesized the Seq-PA No. 1 antigen and obtained antibody serum
   through mouse immunization. Antibody titer in the sera of immunized
   mice was 1:1,000, and the obtained antibody was subsequently purified.
   We detected the expression of the Seq-PA No. 1 peptide in standard P.
   aeruginosa and MDR-PA by Western blotting. The bands showed that the
   antibody was expressed in both bacterial proteins of standard P.
   aeruginosa and MDR-PA, with higher expression in the standard P.
   aeruginosa ([86]Fig. 4A). Next, total protein lysates of standard P.
   aeruginosa and MDR-PA co-cultured with TRQ were separated by SDS-PAGE,
   but no obvious visual changes were observed in the electrophoresis
   bands ([87]Fig. 4B). To identify differentially expressed proteins
   between standard P. aeruginosa and MDR-PA after TRQ treatment, Co-IP
   was performed using the Seq-PA No. 1 antibody, followed by in-depth
   proteome identification to analyze the protein interactions. Among
   these identified proteins, 1,177 (~85%) were common between standard P.
   aeruginosa and MDR-PA ([88]Fig. 4C and D). Principal component analysis
   (PCA) was then performed, and the data of standard P. aeruginosa and
   MDR-PA after co-culture with TRQ for six generations were divided into
   three groups (0–1 generation, 2–4 generations, and 5–6 generations).
   The PCA results showed a certain degree of differentiation between the
   0–1 and 2–4 generation groups, but the proteins of 5–6 generations
   showed similar expression between standard P. aeruginosa and MDR-PA
   ([89]Fig. 4E). These findings indicated that the trend of drug
   resistance of MDR-PA was partially altered by successive generations of
   TRQ co-cultured. Through differential protein clustering analysis and
   correlation analysis, we discovered that the MDR-PA group and the
   standard P. aeruginosa group could be effectively distinguished from
   one another ([90]Fig. 5A).

Fig 4.

   [91]Fig 4
   [92]Open in a new tab

   The identification and quantitative and bioinformatic analysis of the
   proteome. (A) Expression of immune antibody in standard P. aeruginosa
   (std PA) and MDR-PA bacterial proteins by Western blot. (B) The MDR-PA
   protein expression after co-culture with TRQ for six generations. (C)
   The number of label-free quantified proteins in std PA and MDR-PA group
   by Co-IP. (D) Overlap of highly confident proteins identified between
   the different P. aeruginosa groups (std PA, MDR-PA, std PA1-6, and
   MDR-PA1-6) for proteome. (E) The principal component analysis (PCA)
   between the different groups (std PA0-1, std PA2-4, std PA5-6,
   MDR-PA0-1, MDR-PA2-4, and MDR-PA5-6) after TRQ co-culture.

Fig 5.

   [93]Fig 5
   [94]Open in a new tab

   Bioinformatic analysis of the proteins with significantly altered
   expression in the proteome. (A) Clustering analysis of standard P.
   aeruginosa (std PA) and MDR-PA proteins using proteomic data (all the
   proteins in the x- and y-axis are detailed in Data S1). (B) The
   enrichment of biological processes for significantly altered proteins
   in the proteome of the std PA and MDR-PA by go annotation. (C) The
   enriched biological pathways for significantly altered proteins in the
   proteome of the std PA and MDR-PA by Kyoto Encyclopedia of Genes and
   Genomes (KEGG) pathway analysis. The P value was calculated using the
   hypergeometric distribution method.

KEGG pathway enrichment and Gene Ontology (GO) enrichment of the
significantly altered proteins

   The function of differentially expressed proteins was analyzed using GO
   enrichment analysis. The most significant P value among these proteins
   associated with the biological process was the antibiotic response (GO:
   0046677 ~ response to antibiotic, P = 0.00261), while the cellular
   component found significant was the cytoplasm (GO: 005737 ~ cytoplasm,
   P = 0.000023), and in terms of molecular function, the primary
   association was with ATP binding (GO: 005524 ~ ATP binding, P =
   0.000400) ([95]Fig. 5B). Our study concentrated on exploring the
   “antibiotic response.” The KEGG pathway enrichment analysis revealed a
   significantly enriched “biosynthesis of antibiotic” pathway (P =
   0.00191) ([96]Fig. 5C). The functional proteins were obtained (Table
   S2), which were closely related to antibiotic resistance, cell
   division, biosynthetic pathways, and other relevant processes, and
   further verification needs to be performed.

qPCR validation for these candidates

   To further validate the sensitizing effects of TRQ, we performed qPCR
   verification on different generations (G0, G3, and G6) of standard P.
   aeruginosa and MDR-PA strains after co-culture with TRQ. Results
   confirmed that genes related to antibiotic resistance, cell division,
   biosynthetic pathways, and other processes were significantly
   downregulated in MDR-PA5 and MDR-PA7 strains, which is consistent with
   proteomic analysis. The genes mexA (P < 0.05), mexB (P < 0.01), oprF (P
   < 0.001), and idH (P < 0.01) in MDR-PA5 strain and mexA (P < 0.001),
   mexB (P < 0.001), oprF (P < 0.001), idH (P < 0.001), oprM (P < 0.001),
   purB (P < 0.001), and argF (P < 0.001) in MDR-PA7 strain were
   significantly downregulated. The genes (oprF, purB, argF, and idH) and
   corresponding proteins (OprF, ASL, OTCase, and IDH) in standard P.
   aeruginosa and MDR-PA were compared ([97]Fig. 6A and B). Notably, both
   genes (mexA and mexB) and proteins (MexA and MexB) were downregulated
   in standard P. aeruginosa and MDR-PA. This suggested an association
   with the efflux pump MexAB-OprM in P. aeruginosa ([98]Fig. 7A and B).
   Additionally, the down-regulation of outer membrane porin F (OprF),
   which plays roles in cell shape, ion transport, and transport, revealed
   that TRQ may sensitize antibiotic resistance through these mechanisms.

Fig 6.

   [99]Fig 6
   [100]Open in a new tab

   Selection and validation of the core candidates from STRING by qPCR.
   (A) The protein and gene expression of the core candidates for the
   standard P. aeruginosa (std PA). (B) The protein and gene expression of
   the core candidates for the MDR-PA. The data of the gene expression
   were expressed as means ± standard deviation and were analyzed by
   one-way ANOVA and Tukey’s multiple-comparison test; ***P＜0.001.

Fig 7.

   [101]Fig 7
   [102]Open in a new tab

   Another selection and validation of two candidates by qPCR. (A) The
   protein and gene expression of MexA and MexB associated with efflux
   pump for the standard P. aeruginosa (std PA) and MDR-PA. (B)
   Hierarchical cluster result of the network based on STRING clustering
   analysis. The data of the gene expression were expressed as means ±
   standard deviation and were analyzed by one-way ANOVA and Tukey’s
   multiple-comparison test; ***P＜0.001; **P＜0.01; *P＜0.05.

DISCUSSION

   In this study, we aimed to investigate the antibacterial effect of TRQ
   on clinical MDR-PA and elucidate the associated pharmacological
   mechanisms. We employed multiple methods to explore the main targets of
   TRQ in overcoming resistance of P. aeruginosa. For instance,
   MALDI-TOF-MS detection and Biotyper evaluation scores in [103]Fig. 2B
   revealed an increasing confidence level of MDR-PA after co-culture with
   TRQ for six generations. Furthermore, the results of resistance trend
   of MDR-PA with cefoperazone and ceftazidime were decreased by
   traditional MIC measurement in [104]Fig. 2A. These findings indicated
   that TRQ may affect the resistance of MDR-PA. We utilized protein
   fingerprints to identify a differential sequence, Seq-PA No. 1, which
   was associated with the motility and attachment of flagella. We then
   conducted motility assays and the bacterial cell surface hydrophobicity
   of P. aeruginosa, as shown in [105]Fig. 3. The results revealed that
   TRQ could impact flagellar motility and reduce the surface
   hydrophobicity of MDR-PA. These observations align with previous
   reports ([106]33). Additionally, we employed the Co-IP method to
   identify proteins that interacted with Seq-PA No. 1 in standard P.
   aeruginosa and MDR-PA before and after TRQ co-culture. Furthermore, we
   analyzed the core proteins through proteome analysis, as depicted in
   [107]Fig. 5, which aided in further elucidating the mechanism through
   which TRQ can affect drug resistance in P. aeruginosa.

   Using MALDI-TOF-MS, we obtained the confidence scores and MALDI
   fingerprints (as shown in [108]Fig. 2B through D). We compared MALDI
   fingerprint with Seq-PA No. 1 sequence using the Mascot search engine.
   If the MALDI fingerprint does not match Seq-PA No. 1, the P. aeruginosa
   to be tested is a candidate for drug resistance strain. Conversely, if
   the MALDI fingerprint matches Seq-PA No. 1, the P. aeruginosa to be
   tested is not a candidate for drug resistance strain. The method is
   easy to operate and can quickly and accurately identify drug-resistant
   or drug-sensitive bacteria. The entire process takes less than 10
   minutes, offering the advantages of being less time consuming, highly
   sensitive, and specific. This efficiency can save valuable time for the
   treatment of severe infections caused by this type of bacteria in
   clinical settings.

   β-Lactams, aminoglycosides, and fluoroquinolones are commonly used
   antibiotics in the clinical management of P. aeruginosa infections.
   However, resistance to these antibiotics can lead to treatment failures
   in infections caused by MDR-PA ([109]34). Efflux pumps, such as the RND
   family efflux pumps, can lead to antibiotic resistance in P.
   aeruginosa. RND efflux pumps, such as MexAB-OprM, MexCD-OprJ,
   MexEF-OprN, and MexXY-OprM, are commonly associated with antibiotic
   resistance in P. aeruginosa ([110]13). Among these, the MexAB-OprM
   efflux system is a prominent resistance mechanism in P. aeruginosa, and
   hyper-expression of this system has been reported ([111]35). The
   MexAB-OprM efflux system is composed of a periplasmic membrane fusion
   protein (MexA), an inner membrane drug-proton antiporter (MexB), and an
   outer membrane channel-forming component (OprM) ([112]36). The
   tripartite multidrug efflux system MexAB-OprM utilizes proton gradient
   as a driving force to pump out multiple antibiotics from the bacterial
   cell. The outer membrane barrier interacts with the MexAB-OprM efflux
   system to facilitate the extrusion of substrates. The substrates either
   from the lipid bilayer or from cytoplasmic space are recognized and
   captured by MexB; then, a channel in the outer membrane is formed, and
   the substrates are transported to the extracellular medium through
   OprM. MexA plays a coordinating role in the cooperation between MexB
   and OprM. Efflux pump inhibitors have been found to restore bacterial
   susceptibility to multiple drugs ([113]37, [114]38). In our study, as
   illustrated in [115]Fig. 4 and 5, we conducted Co-IP and proteome
   analysis, which revealed a decrease in the expression of MexA and MexB
   at the protein level. This finding was further confirmed by a
   consistent downward trend at the gene level, as demonstrated in
   [116]Fig. 7. These results suggested that TRQ might regulate the
   expression of the MexAB-OprM efflux pump in MDR-PA. MexAB-OprM is
   primarily responsible for extruding β-lactams and quinolones
   antibiotics. As shown in [117]Fig. 2A; Table S1, the MICs of
   cefoperazone and ceftazidime, both of which are β-lactam antibiotics,
   tended to decrease after TRQ treatment. This phenomenon may explain why
   TRQ can reduce the resistance of MDR-PA to ceftazidime and
   cefoperazone.

   P. aeruginosa resistance is also linked to various porins that can
   affect the penetration of antibiotics. OprF, the predominant porin in
   P. aeruginosa, exhibits low efficiency in allowing antibiotics to
   penetrate the bacterial cell. OprF exists in two conformers; the
   dominant structure of OprF channels is a closed conformer, and less
   than 5% is an open conformer ([118]39). Higher levels of OprF in the
   outer membrane of P. aeruginosa are accompanied by thick biofilms,
   which are closely related to drug resistance ([119]40). In this study,
   co-culturing clinical MDR-PA with TRQ for six generations led to
   downregulation of OprF protein expression, as shown in [120]Fig. 6. In
   [121]Fig. 3C, we also observed a significant reduction in the adhesion
   rate after TRQ treatment. This suggested that TRQ might be effective in
   reducing the resistance of MDR-PA. Researchers have found that the
   adhesion of P. aeruginosa to human lung alveolar epithelial cells was
   at least partially mediated by OprF due to a significant reduction in
   the binding capacity of oprF-negative mutants ([122]40).

   P. aeruginosa has EC 2.1.3.3 and ornithine carbamoyl transferases
   (OTCases). The anabolic OTCase catalyzes the sixth reaction in arginine
   biosynthesis, which is the product of the argF gene. The catabolic
   OTCase is the product of the arcB gene and is related to anaerobic
   arginine catabolism. Both enzymes function unidirectionally in P.
   aeruginosa; no matter arcB or argF is mutated, the anabolic or
   catabolic metabolism will be affected ([123]41). IDH (idh) is relevant
   to the tricarboxylic acid (TCA) cycle–glyoxylate shunt branch point in
   P. aeruginosa. P. aeruginosa mutually regulates ICL and IDH through
   oxaloacetate and pyruvate, thereby coordinating the allocation of
   metabolic flux ([124]42). The ASL (purB) plays a crucial role in
   catalyzing two reactions within the de novo purine nucleotide
   biosynthesis process. IDH, ASL, and OTCase (argF) mainly affect
   bacterial biosynthesis pathway and bacterial growth, and TRQ can also
   downregulate the expression of three proteins above as shown in
   [125]Fig. 6. In addition, it is the first time for our study to report
   that these proteins (IDH, OTCase, and ASL) were associated with the
   resistance synthesis of MDR-PA. It was hypothesized that TRQ changed
   drug resistance by affecting the biosynthesis of P. aeruginosa.

Conclusion

   In this study, a simple and reliable phenotypic identification method
   was established to reflect the clinical drug resistance and sensitivity
   of P. aeruginosa by comparing the fingerprint and the characteristic
   amino acid sequence of the strains. We applied this method to real
   clinical samples, showcasing its rapidity, sensitivity, and
   reliability. Simultaneously, we integrated Co-IP and proteomics and
   performed PCR validation to investigate the mechanism of clinical
   MDR-PA resistance and the pharmacological effects of TRQ on core
   proteins (MexA, MexB, OprM, OprF, OTCase, IDH, and ASL) associated with
   P. aeruginosa resistance. This is the first time that we report the
   mechanism by which TRQ re-sensitizes drug-resistant P. aeruginosa and
   the specific targets of TRQ. The integration of multiple methods offers
   a new direction for screening and developing new drugs and mining drug
   resistance mechanisms and action targets. This approach holds great
   promise for applications in the detection of drug-resistant bacteria
   and beyond.

MATERIALS AND METHODS

Bacterial strains and culture conditions

   P. aeruginosa (ATCC 27853) was purchased from the American Type Culture
   Collection (ATCC, USA). Multidrug-resistant Pseudomonas aeruginosa
   isolates were obtained from the clinical laboratory of Wangjing
   Hospital, Beijing, China. All maintained in cryogenic storage at −80°C.
   Strains were grown in lysogeny broth (LB) or Mueller-Hinton broth (MHB)
   at 37°C under standard storage conditions. The LB and agar were used
   for reversal of drug resistance and the MHB and agar were used for AST.
   Azlocillin, cefoperazone, and ceftazidime antibiotics were selected for
   AST assay.

Animal preparation

   Eight-week-old C57BL/6 male mice weighing 19–21 g were obtained from
   Beijing Weitong Lihua Laboratory Animal Technology Co., Ltd., China.
   Every five mice were kept in a cage with free access to food and water;
   all animals were housed in an environment with a relative humidity of
   50% ± 10% and a temperature of 22°C ± 2°C, along with a 12-h light/12-h
   dark cycle.

MIC assays

   The broth dilution assays were used to determine the MICs as described
   previously ([126]43, [127]44). Briefly, 5 × 10^5 CFU/mL bacterial
   suspension was incubated in 96-well plates with varying concentrations
   of antibiotics. After incubation at 37°C for 18–24 h, the MICs of P.
   aeruginosa were determined before and after TRQ co-cultivation.

Co-culture of TRQ and MDR-PA

   P. aeruginosa were incubated at 37°C in a 1:1 ratio containing TRQ and
   LB medium and shaken at 280 rpm for 18–20 h. Overnight-grown bacterial
   suspensions were diluted with MHB to 10^5 CFU/mL for MIC assays. After
   incubation, the bacteria suspension was streaked over the surface LB
   agar at 37°C for 16–20 h under aerobic condition and recorded as the
   first generation. The operation was repeated in the sixth generation,
   and 14 strains were obtained and stored at 4°C.

Identification of bacterial successive passaged by MALDI-TOF-MS

   P. aeruginosa colonies were extracted using formic acid and then
   subjected to identification using MALDI-TOF-MS (Bruker Daltonics,
   Bremen, Germany) ([128]45). A certain amount (5–10 mg) of purified
   colony was taken from the plate and suspended in 300-µL purified water
   by vortexing and was mixed carefully by adding 900-µL absolute ethanol
   (after this treatment, the sample can be stored at −20°C for several
   weeks). Then, it was centrifuged at 13,000 rpm for 2 min, and the
   supernatant was discarded (if necessary, it was centrifuged again to
   remove ethanol as much as possible); 70% formic acid (50 µL) was added
   and the precipitate was suspended and then mixed by adding acetonitrile
   (50 µL) and centrifuged for 2 min at a high speed. Then, the
   supernatant (1 µL) was placed on a MALDI-TOF MS steel anchor plate
   (BigAnchor 384-well plate; Bruker Daltonics) and dried. The dried
   mixture was covered with the saturated α-cyano-4-hydroxycinnamic acid
   matrix solution (HCCA, 1 µL, Bruker Daltonics) and dried prior to
   analysis using MALDI Biotyper. To avoid protein oxidation, the
   operation should be completed as soon as possible, especially when
   adding the matrix solution. Acquisition parameters were as follows: the
   shots were 500, the scan range was 2,000–20,000 m/z, N2 laser
   wavelength was 337 nm, and laser energy was 85%. Bruker Biotyper 3.0
   software was used to analyze the spectra. Identification was carried
   out using the manufacturer’s recommended and internally determined
   cutoff scores; the protein identification and analysis were carried out
   by mass spectrometry of peptides using MALDI-TOF-MS ([129]46).

Swimming motility assay

   LB agar (0.3%) plates were used to assess the motility of P. aeruginosa
   mediated by flagellum. The overnight LB cultures (aliquots, 1 µL) were
   inoculated in agar, and the diameter of the swimming zone was measured
   after 16-h incubation at 30°C. All assays were performed in triplicate
   ([130]47, [131]48).

Twitching motility assay

   P. aeruginosa isolates were inoculated using a needle placed at the
   bottom of the plates containing 3 mm deep 1% LB agar, followed by
   incubation at 37°C for 24 hours. Subsequently, the twitch zone between
   the agar and the plate bottom was measured. All assays were performed
   in triplicate ([132]49, [133]50).

Swarming motility assay

   The swarming motility of the isolates was tested in plates (0.5% agar,
   0.05% monosodium glutamate, and 0.2% glucose). The overnight LB
   cultures (aliquots, 1 µL) were inoculated on the agar surface; after
   incubating 24 h at 30°C, the radial growth of swarming was observed.
   All assays were performed in triplicate ([134]51, [135]52).

Hydrophobicity assay

   The adhesion to n-hexadecane was used to determine the relative surface
   hydrophobicity of P. aeruginosa by TRQ treatment. Briefly, the bacteria
   were cultured overnight in the logarithmic phase and diluted with a 1:1
   ratio containing TRQ and LB medium or only in LB medium at 37°C and
   shaken at 100 rpm for 5 h. Then, cultures (4 mL) were taken every 30
   min and centrifuged at 4,700 rpm for 5 min. The precipitate was washed
   twice with PBS and suspended in 3-mL PBS, and 0.8 mL of n-hexadecane
   was added. Then, the mixture was vortexed for 30 s. Finally, 1-mL
   n-hexadecane phase was taken, and the absorbance was measured at 540
   nm. The results were determined by the following equation: % adherence
   = [(1 − A/A0)] × 100, where A0 was the initial optical densities of the
   aqueous phase and A was the final optical densities of the aqueous
   phase ([136]53, [137]54). .

Preparation of mouse polyclonal antibody by immunized mice

   Before immunization, antigenic polypeptide (Seq-PA No. 1, 1 mL) was
   emulsified with Freund’s adjuvant (1 mL). Then, Seq-PA No. 1 (100 μg)
   was intraperitoneally injected into C57BL/6 male mice every 2 weeks for
   a total of eight to nine times. Before and after immunization, blood
   samples (1.5–2.0 mL) were collected from the tail of the mice to obtain
   polyclonal antibody serum. The antibody titers in the immunized mice
   were determined by enzyme linked immunosorbent assay (ELISA).

Purification of mouse polyclonal antibody

   The antibody was purified using a protein A column. After rinsing with
   PBS, the antibody was permeabilized with 0.1 M citric acid for 5 min,
   followed by thorough washing, repeated three times. Neutralization was
   conducted with 1 M Tris-HCl (pH 8.0) and PBS equilibrated, followed by
   extensive washes with a 20% ethanol solution. The upper and lower ends
   were sealed and stored at 4°C. The specificity of the antibody was
   determined by SDS-PAGE and Western blot ([138]55).

Extraction and quantification of Pseudomonas aeruginosa protein

   After centrifugation at 5,000 × g for 10 min at 4°C, the bacterial
   culture precipitate was resuspended in 1-mL PBS, then centrifuged again
   at 15,000 rpm for 3 min, and washed three times at 4°C. The proteins
   were extracted in a mixture containing sample, urea, and protease
   inhibitor (5 mg:15 µL:1 µL ratio). The total bacterial protein was
   extracted using ultrasonic crushing for 20 s on ice. Total protein
   content was determined using a BCA protein assay kit (Thermo
   Scientific, Inc.).

Western blotting

   As previously described, we conducted Western blot analysis. Standard
   P. aeruginosa and MDR-PA proteins were separated on a SDS-PAGE. After
   electrophoresis, we performed wet transfer, incubating the membrane at
   4°C for 75 min at 100 V, followed by blocking with skimmed milk powder
   for 1 h. The membranes were then incubated with primary antibodies (the
   purified antibody was used as the primary antibody at a 1:1,000
   dilution, and β-actin served as the internal reference antibody at a
   1:2,500 dilution) at 4°C for 3 h. Subsequently, the membranes were
   washed in TBST for 10 min, four times in total, and the secondary
   antibody (1:5,000) was added and incubated at 4°C for 1 h. The
   membranes were washed four times in TBST. The quantification of blot
   was conducted using ImageJ software (V1.8.0) for grayscale analysis
   ([139]55).

Co-IP assay

   After ultrasonic extraction as described previously, 200 µL of protein
   was taken from each sample. To one tube, 10 µL of antibody-containing
   serum was added, and to the other tube, 10 µL of antibody-free serum
   was added. After sealing, the samples were incubated at 4°C for 24 h.
   Then, 100 µL of protein A/G beads was added, and the samples were
   incubated for 2 h with shaking. The precipitate was collected by
   centrifugation at 1,000 × g for 1 min and washed five times with PBS
   ([140]56).

Trypsin digestion

   In-solution tryptic digestion was conducted following the previously
   described method ([141]57). An 8 M urea was used to denature the
   protein obtained by immunoprecipitation, and 10 mM dithiothreitol and
   55 mM iodoacetamide were used to reduce and alkylate the proteins. The
   sample solution was then diluted with 50 mM NH[4]HCO[3] to reduce the
   urea concentration to 1 M. The proteins were digested overnight at 37°C
   in a trypsin-to-protein ratio of 1:100, and the reaction was stopped by
   adding a final concentration of 0.1% formic acid (FA). The supernatant
   was collected.

Desalination by C18 column

   The C18 column was washed twice with acetonitrile (ACN) and 0.1% formic
   acid (FA), respectively. The supernatant obtained earlier was slowly
   added to the column, and the effluent was collected, repeating this
   step three times. Afterward, the column was washed twice with 0.1% FA.
   The target components were eluted using a mixed solution of 50% ACN and
   0.1% FA, and the eluent was collected for mass spectrometry detection.

Proteomic identification and quantification of Co-IP proteins

   For the LC-MS/MS analysis of peptides, a QExactive-HFX mass
   spectrometer (Thermo Fisher, USA) equipped with an EASY-nano-1000 LC
   system (Thermo Fisher, USA) and a nanoelectrospray ion source (Thermo
   Fisher, USA) was employed ([142]58). A 5-µL sample was injected into a
   self-packed precolumn (20 mm, 5 µm, 100 A) at a flow rate of 300
   nL/min. Separation was achieved using a self-packed reversed-phase C18
   nano-column, with mobile phase A consisting of 0.1% formic acid in
   water and mobile phase B containing 0.1% formic acid in 80%
   acetonitrile. The mass scan ranged from 300 to 1,400 m/z, with a
   resolution of 60,000, and the 20 most intense ions were sequentially
   separated. The electrospray voltage was 1.9 kV, and the capillary
   temperature was maintained at 320°C.

   The fragmentation spectra were searched using the Mascot search engine
   (v 2.2.06), with the Uniport P. aeruginosa database (20190320). For the
   QE data, the precursor and fragment mass tolerances were set to 10 ppm
   and 20 mmu, respectively. There were two missed cleavage sites, and the
   minimum peptide length was set to seven amino acids. The fixed and
   variable modifications included carbamidomethyl (C), acetylation
   (protein N-terminal), and oxidation (M). Peptide ions were filtered
   using cutoff scores from percolators (P < 0.01), ensuring a false
   discovery rate of 1% for peptide identifications. The Proteome
   Discoverer 2.3 proteomic platform was used to process the raw data, and
   label-free quantitative analysis of proteins was performed using an
   in-house software (FileMaker).

RNA isolation and RT-qPCR

   Total bacterial RNA was extracted following the manufacturer’s protocol
   (Tiangen Biotec, China), and the concentrations of RNA were measured
   using NanoDrop (Thermo Fisher, USA). ReverTra Ace qPCR RT Master Mix
   (Toyobo, Japan) was used to synthesize complementary DNA, and mRNA
   quantification was performed using SYBR Green Real-time PCR Master Mix
   (20-µL reaction volume, Toyobo, Japan). The rpoD was used as a
   reference gene. Data analysis was performed using the comparative
   threshold cycle (2^−∆∆Cq) method, and qPCR primers were obtained from
   Sangon Biotech (Shanghai) Co., Ltd.

Bioinformatic analysis

   Gene Ontology annotation ([143]https://geneontology.org) ([144]59),
   DAVID Bioinformatics Resources ([145]https://david.ncifcrf.gov/)
   ([146]60), and STRING database ([147]https://cn.stringdb.org/)
   ([148]61) were employed to explore the subcellular localizations,
   biological functions, related networks, and pathways of the identified
   significant GPs. Statistical Product and Service Solutions (SPSS 19.0)
   software (IBM Corporation, Armonk, New York, USA) was used to analyze
   the remarkably regulated proteins and gene symbols. The P value was
   calculated using the hypergeometric distribution method.

ACKNOWLEDGMENTS