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Time-resolved proteomic adaptation of multidrug-resistant Acinetobacter baumannii to antimicrobial stress induced by partially purified fraction from Caesalpinia pulcherrima flower using DEqMS.

UNLABELLED: The global prevalence of multidrug-resistant (MDR) bacteria represents an urgent public health challenge, emphasizing the critical need for novel antimicrobial agents. MDR Acinetobacter baumannii, a nosocomial pathogen of critical global concern owing to its capacity to acquire and disseminate antimicrobial resistance, was employed as a bacterial model to investigate the antimicrobial potential of natural products derived from Caesalpinia pulcherrima (L.) Sw. (Fabaceae). This medicinal plant represents a promising reservoir of novel bioactive compounds; however, its molecular effects on the A. baumannii proteome had not previously been characterized. The partially purified ethyl acetate fraction of C. pulcherrima flowers (CPF4) exhibited potent bactericidal activity against susceptible A. baumannii (minimum inhibitory concentration and minimum bactericidal concentration = 31.25 µg/mL), and time-resolved label-free quantitative LC-MS/MS proteomics was subsequently performed on MDR A. baumannii cultures treated with CPF4 at 24 h, 48 h, and 72 h post-treatment alongside untreated controls in biological triplicate, with differential protein expression assessed using differential expression of quantified mass spectrometry data. No significantly differentially expressed proteins were detected at 24 h or 48 h relative to the control, indicating that the proteomic effects of CPF4 manifest predominantly at the late treatment stage. In contrast, a robust late-phase response was identified at 72 h, comprising the coordinated induction of proteins associated with DNA damage repair, transcriptional regulation, and cell surface glycosylation remodeling. The sensor histidine kinase PmrB was significantly upregulated at 72 h vs 48 h (adjusted P = 0.029), implicating the PmrA/PmrB two-component system in late-phase colistin tolerance acquisition under sustained CPF4 exposure. IMPORTANCE: These findings provide mechanistic insight into the adaptive survival strategies employed by multidrug-resistant Acinetobacter baumannii in response to plant-derived antimicrobial challenge and support the further development of Caesalpinia pulcherrima-derived natural products as candidate antimicrobial agents.

Acinetobacter baumannii

LimROTS: a hybrid method integrating empirical Bayes and reproducibility-optimized statistics for robust differential expression analysis.

MOTIVATION: Differential expression analysis plays a vital role in omics research enabling precise identification of features that associate with different phenotypes. This process is critical for uncovering biological differences between conditions, such as disease versus healthy states. In proteomics, several statistical methods have been used, ranging from simple t-tests to more advanced methods like DEqMS, limma and ROTS. However, a flexible method for reproducibility-optimized statistics tailored for clinical omics data has been lacking. RESULTS: In this study, we developed LimROTS, a hybrid method that integrates a linear regression model and the empirical Bayes approach with reproducibility optimized statistics, to create a novel moderated ranking statistic, for robust and flexible analysis of proteomics data. We validated its performance using twenty-one proteomics gold standard spike-in datasets with different protein mixtures, MS instruments, and techniques for benchmarking. This hybrid approach improves accuracy and reproducibility of complex proteomics data, making LimROTS a powerful tool for high-dimensional omics data analysis. AVAILABILITY AND IMPLEMENTATION: LimROTS has been implemented as an R/Bioconductor package, available at https://doi.org/doi:10.18129/B9.bioc.LimROTS. Additionally, the code used in this study is available in GitHub repository https://github.com/AliYoussef96/LimROTSmanuscript.

Bayes Theorem