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. 2025 May 23;13(2):19.
doi: 10.3390/proteomes13020019.

Unraveling the Central Role of Global Regulator PprI in Deinococcus radiodurans Through Label-Free Quantitative Proteomics

Affiliations

Unraveling the Central Role of Global Regulator PprI in Deinococcus radiodurans Through Label-Free Quantitative Proteomics

Siyu Zhu et al. Proteomes. .

Abstract

Background: Deinococcus radiodurans, renowned for its exceptional resistance to radiation, provides a robust model for elucidating cellular stress responses and DNA repair mechanisms. Previous studies have established PprI as a key regulator contributing to radiation resistance through its involvement in DNA damage repair pathways, oxidative stress response, and metabolic regulation.

Methods: Building upon these foundations, our study employs label-free quantitative (LFQ) proteomics coupled with high-resolution mass spectrometry to systematically map pprI deletion protein networks by comparing the global proteomic profiles of pprI knockout and wild-type D. radiodurans strains.

Results: Under stringent screening criteria, we identified 719 significantly higher and 281 significantly lower abundant proteins in the knockout strain compared to wild-type strains. Functional analysis revealed that PprI deficiency disrupts homologous recombination (HR) repair, activates nucleotide excision repair (NER) and base excision repair (BER) as a compensatory mechanism, and impairs Mn/Fe homeostasis and carotenoid biosynthesis, leading to increased oxidative stress. Furthermore, PprI deficiency induces significant metabolic reprogramming, including impaired purine synthesis, compromised cell wall integrity, etc. Conclusions: These proteomic findings delineate the extensive regulatory network influenced by PprI, revealing coordinated perturbations across multiple stress response systems when PprI is absent.

Keywords: DNA damage repair; antioxidant defense; label-free quantitative proteomics; metabolic regulation; radiation response metalloprotease.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Quality assessment of proteomic data of wild-type strain and pprI knockout strains. (a) Principal component analysis (PCA) of the DR and ΔpprI strains. (b) Heatmap showing the abundance of 2522 proteins identified in the wild-type strain and the knockout strain. (c) Volcano plot showing proteins from the proteomic analysis of the DR and ΔpprI strains. Proteins with significantly differential abundance (|log2FC| > 1; p-adj < 0.05) in the blue and red dots represent lower and higher abundance of proteins in the knockout strain compared to wild-type strains. (The 2-fold threshold was chosen to prioritize proteins with substantial abundance changes, while the Benjamini–Hochberg-adjusted p-value < 0.05 ensured statistical rigor.) Non-significant proteins are shown in gray.
Figure 2
Figure 2
Gene ontology enrichment analysis of differentially abundant proteins. (a) High abundance of proteins enriched with GO annotations. (b) Low abundance of proteins enriched with GO annotations. The enriched terms were visualized based on their log10-transformed p-values and the number of associated proteins (represented by dot size).
Figure 3
Figure 3
COG analysis of differentially abundant proteins. (a) High abundance of protein COG function annotation. (b) Low abundance of protein COG function annotation. The COG functional categories with more than five matched query gene names are highlighted in red boxes, and key genes associated with DNA repair, oxidative stress response, and metabolic reprogramming are annotated in red font.
Figure 4
Figure 4
Protein–protein interaction network diagram of differentially abundant proteins based on GO pathways. Protein–protein interaction networks were constructed using the STRING database and further optimized in Cytoscape with a Kappa consistency threshold of 0.7. Different pathways are indicated by different colors, and interactions between proteins are indicated by colorful lines. The gene names in the red text indicated that the corresponding differentially abundant proteins were in the GO pathways. The protein interaction network shows 11 different connected signaling pathways.
Figure 5
Figure 5
Identifying pprI knockout-associated changes in DNA damage repair, antioxidant defense, and metabolic reprogramming, providing a systems-level view of its regulatory influence.

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