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Experimental and Therapeutic Medicine
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Print ISSN: 1792-0981 Online ISSN: 1792-1015
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Article Open Access

Glycolytic reprogramming in host response to Borrelia burgdorferi: A gene signature revealed by integrative bioinformatics analysis and machine learning

  • Authors:
    • Yan Dong
    • Yantong Chen
    • Yanshuang Luo
    • Meng Liu
    • Chao Song
    • Xuesong Chen
    • Fusong Yang
    • Qingyi Luo
    • Guozhong Zhou
  • View Affiliations / Copyright

    Affiliations: Faculty of Life Science and Technology and The Affiliated Anning First People's Hospital, Kunming University of Science and Technology, Kunming, Yunnan 650302, P.R. China, Department of Pain Medicine, The Affiliated Anning First People's Hospital of Kunming University of Science and Technology, Kunming, Yunnan 650302, P.R. China, Department of Ultrasound, Yanan Hospital of Kunming City, The Affiliated Hospital of Kunming Medical University, Kunming, Yunnan 650302, P.R. China, School of Basic Medical Sciences, Kunming University of Science and Technology, Kunming, Yunnan 650500, P.R. China
    Copyright: © Dong et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Article Number: 187
    |
    Published online on: May 12, 2026
       https://doi.org/10.3892/etm.2026.13182
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Abstract

Lyme disease (LD), a multifaceted condition caused by Borrelia burgdorferi (Bb), remains poorly understood, particularly regarding metabolic pathways. This study aimed to evaluate the role of glycolysis‑related genes (GRGs) in LD pathogenesis and identify key genes and mechanisms relevant to diagnosis and therapy. Differentially expressed GRGs were identified and further analyzed by correlation analysis and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. Key genes were screened using least absolute shrinkage and selection operator (LASSO) and support vector machine‑recursive feature elimination, followed by gene set enrichment analysis, gene set variation analysis and immune infiltration analysis using CIBERSORT. Diagnostic value was assessed by receiver operating characteristic and nomogram analyses, and a competing endogenous RNA network and protein‑drug interaction predictions were constructed. The expression of key genes was further validated by reverse transcription‑quantitative PCR (RT‑qPCR) in Bb‑infected THP‑1 cells, and glucose and lactate concentrations in the culture supernatants were measured using commercial colorimetric assay kits. A total of 63 differentially expressed GRGs were identified. Of note, two key genes [lactate dehydrogenase A (LDHA) and thioredoxin (TXN)] exhibited a strong diagnostic performance. Immune infiltration analysis revealed that these genes were associated with regulatory T cells (r=0.33, P=0.05), gamma delta T cells (r=‑0.34, P=0.042), CD4 memory resting T cells (r=‑0.4, P=0.016) and monocytes (r=‑0.36, P=0.03). The potential glycolysis‑targeting drugs were predicted. RT‑qPCR analysis revealed increased LDHA and TXN expression in Bb‑infected THP‑1 cells. In addition, Bb stimulation reduced extracellular glucose levels and increased lactate accumulation in culture supernatants. Overall, this integrative analysis revealed notable alterations in glycolytic genes during Bb infection, suggesting that dysregulation of glycolysis contributes to LD immunopathology. The identified key genes (LDHA and TXN) may serve as infection‑related transcriptional response markers, offering insights into LD mechanisms and potential precision‑based strategies.

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Copy and paste a formatted citation
Spandidos Publications style
Dong Y, Chen Y, Luo Y, Liu M, Song C, Chen X, Yang F, Luo Q and Zhou G: Glycolytic reprogramming in host response to <em>Borrelia burgdorferi</em>: A gene signature revealed by integrative bioinformatics analysis and machine learning. Exp Ther Med 32: 187, 2026.
APA
Dong, Y., Chen, Y., Luo, Y., Liu, M., Song, C., Chen, X. ... Zhou, G. (2026). Glycolytic reprogramming in host response to <em>Borrelia burgdorferi</em>: A gene signature revealed by integrative bioinformatics analysis and machine learning. Experimental and Therapeutic Medicine, 32, 187. https://doi.org/10.3892/etm.2026.13182
MLA
Dong, Y., Chen, Y., Luo, Y., Liu, M., Song, C., Chen, X., Yang, F., Luo, Q., Zhou, G."Glycolytic reprogramming in host response to <em>Borrelia burgdorferi</em>: A gene signature revealed by integrative bioinformatics analysis and machine learning". Experimental and Therapeutic Medicine 32.1 (2026): 187.
Chicago
Dong, Y., Chen, Y., Luo, Y., Liu, M., Song, C., Chen, X., Yang, F., Luo, Q., Zhou, G."Glycolytic reprogramming in host response to <em>Borrelia burgdorferi</em>: A gene signature revealed by integrative bioinformatics analysis and machine learning". Experimental and Therapeutic Medicine 32, no. 1 (2026): 187. https://doi.org/10.3892/etm.2026.13182
Copy and paste a formatted citation
x
Spandidos Publications style
Dong Y, Chen Y, Luo Y, Liu M, Song C, Chen X, Yang F, Luo Q and Zhou G: Glycolytic reprogramming in host response to <em>Borrelia burgdorferi</em>: A gene signature revealed by integrative bioinformatics analysis and machine learning. Exp Ther Med 32: 187, 2026.
APA
Dong, Y., Chen, Y., Luo, Y., Liu, M., Song, C., Chen, X. ... Zhou, G. (2026). Glycolytic reprogramming in host response to <em>Borrelia burgdorferi</em>: A gene signature revealed by integrative bioinformatics analysis and machine learning. Experimental and Therapeutic Medicine, 32, 187. https://doi.org/10.3892/etm.2026.13182
MLA
Dong, Y., Chen, Y., Luo, Y., Liu, M., Song, C., Chen, X., Yang, F., Luo, Q., Zhou, G."Glycolytic reprogramming in host response to <em>Borrelia burgdorferi</em>: A gene signature revealed by integrative bioinformatics analysis and machine learning". Experimental and Therapeutic Medicine 32.1 (2026): 187.
Chicago
Dong, Y., Chen, Y., Luo, Y., Liu, M., Song, C., Chen, X., Yang, F., Luo, Q., Zhou, G."Glycolytic reprogramming in host response to <em>Borrelia burgdorferi</em>: A gene signature revealed by integrative bioinformatics analysis and machine learning". Experimental and Therapeutic Medicine 32, no. 1 (2026): 187. https://doi.org/10.3892/etm.2026.13182
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