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Deciphering the Anti-Biofilm Mechanism of Anthraquinone-2-Carboxylic Acid Against MRSA by Comprehensive Multi-Omics Analysis

ABSTRACT: Background: Methicillin-resistant Staphylococcus aureus (MRSA) biofilms exhibit high levels of drug resistance and cause nosocomial infections in humans, thus posing a sustainable global health threat. This underscores the critical need to develop novel antibiofilm therapeutics with high efficacy and well-characterized mechanisms. In this study, we investigated the MRSA biofilm eradication mechanism of anthraquinone-2-carboxylic acid (ACA), a potent natural antibiofilm agent. Methods: The molecular mechanism underpinning the destruction of MRSA biofilm by ACA was systematically explored using integrated proteomic and metabolomic analysis. TMT-based proteomics quantified changes in protein expression, while complementary metabolomic data provided insight into associated pathway alterations. Transcript levels of key differentially expressed genes identified through omics analysis were validated by real-time quantitative polymerase chain reaction (RT-PCR), with intracellular reactive oxygen species (ROS) accumulation measured using the DCFH-DA method. The selected biofilm-associated biomarkers were rigorously validated using targeted parallel reaction monitoring (PRM) mass spectrometry. Conclusions: This study systematically elucidates the molecular mechanisms underlying the ACA-mediated disruption of MRSA biofilms, thereby establishing a robust theoretical framework for the rational design of ACA-based antibiofilm therapeutics. The identified pathways may provide novel targets for developing next-generation antibiofilm agents and pharmacodynamic biomarkers for MRSA biofilm treatment monitoring.

ORGANISM(S): Staphylococcus Aureus

SUBMITTER: KaiLing Wang

PROVIDER: PXD068514 | iProX | Thu Sep 18 00:00:00 BST 2025

REPOSITORIES: iProX

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Project description:Is there a universal genetically programmed defense providing tolerance to antibiotics when bacteria grow as biofilms? A comparison between biofilms of three different bacterial species by transcriptomic and metabolomic approaches uncovered no evidence of one. Single-species biofilms of three bacterial species (Pseudomonas aeruginosa, Staphylococcus aureus, and Acinetobacter baumannii) were grown in vitro for three days then challenged with respective antibiotics (ciprofloxacin, daptomycin, tigecycline) for an additional 24 h. All three microorganisms displayed reduced susceptibility in biofilms compared to planktonic cultures. Global transcriptomic profiling of gene expression comparing biofilm to planktonic and antibiotic-treated biofilm to untreated biofilm was performed. Extracellular metabolites including 18 amino acids, glucose, lactate, acetate, formate, and ethanol were measured to characterize the utilization of carbon sources between biofilms, treated biofilms, and planktonic cells. While all three bacteria exhibited a species-specific signature of stationary phase, no conserved gene, gene set, or common functional pathway could be identified that changed consistently across the three microorganisms. Across the three species, glucose consumption was increased in biofilms compared to planktonic cells and alanine and aspartic acid utilization were decreased in biofilms compared to planktonic cells. The reasons for these changes were not readily apparent in the transcriptomes. No common shift in the utilization pattern of carbon sources was discerned when comparing untreated to antibiotic-exposed biofilms. Overall, our measurements do not support the existence of a common genetic or biochemical basis for biofilm tolerance against antibiotics. Rather, there are likely myriad genes, proteins, and metabolic pathways that influence the physiological state of microorganisms in biofilms contributing to antibiotic tolerance. The Staphylococcus aureus microarray data from the study described above is deposited here.

Project description:Is there a universal genetically programmed defense providing tolerance to antibiotics when bacteria grow as biofilms? A comparison between biofilms of three different bacterial species by transcriptomic and metabolomic approaches uncovered no evidence of one. Single-species biofilms of three bacterial species (Pseudomonas aeruginosa, Staphylococcus aureus, and Acinetobacter baumannii) were grown in vitro for three days then challenged with respective antibiotics (ciprofloxacin, daptomycin, tigecycline) for an additional 24 h. All three microorganisms displayed reduced susceptibility in biofilms compared to planktonic cultures. Global transcriptomic profiling of gene expression comparing biofilm to planktonic and antibiotic-treated biofilm to untreated biofilm was performed. Extracellular metabolites including 18 amino acids, glucose, lactate, acetate, formate, and ethanol were measured to characterize the utilization of carbon sources between biofilms, treated biofilms, and planktonic cells. While all three bacteria exhibited a species-specific signature of stationary phase, no conserved gene, gene set, or common functional pathway could be identified that changed consistently across the three microorganisms. Across the three species, glucose consumption was increased in biofilms compared to planktonic cells and alanine and aspartic acid utilization were decreased in biofilms compared to planktonic cells. The reasons for these changes were not readily apparent in the transcriptomes. No common shift in the utilization pattern of carbon sources was discerned when comparing untreated to antibiotic-exposed biofilms. Overall, our measurements do not support the existence of a common genetic or biochemical basis for biofilm tolerance against antibiotics. Rather, there are likely myriad genes, proteins, and metabolic pathways that influence the physiological state of microorganisms in biofilms contributing to antibiotic tolerance. The Acinetobacter baumannii microarray data from the study described above is deposited here.

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Deciphering the Anti-Biofilm Mechanism of Anthraquinone-2-Carboxylic Acid Against MRSA by Comprehensive Multi-Omics Analysis

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