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Rapid and Robust Bacterial Species Identification Using Hyperspectral Microscopy and Gram Staining Techniques
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  • Siqi Zhu,
  • Yanzhong Zhou,
  • jieming li,
  • Zhen Li,
  • Hao Yin,
  • Zhenqiang Chen
Siqi Zhu
Jinan University Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communication Technology

Corresponding Author:[email protected]

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Yanzhong Zhou
Jinan University Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communication Technology
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jieming li
Jinan University Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communication Technology
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Zhen Li
Jinan University Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communication Technology
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Hao Yin
Jinan University Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communication Technology
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Zhenqiang Chen
Jinan University
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Abstract

Gram staining can classify bacterial species into two large groups based on cell wall differences. Our study revealed that within the same Gram group (Gram-positive or Gram-negative), subtle cell wall variations can alter staining outcomes, with the peptidoglycan layer and lipid content significantly influencing this effect. Thus, bacteria within the same group can also be differentiated by their spectra. Using hyperspectral microscopy, we identified six species of intestinal bacteria with 98.1% accuracy. Our study also demonstrated that selecting the right spectral band and background calibration can enhance the model’s robustness and facilitate precise identification of varying sample batches. This method is suitable for analyzing bacterial community pathologies.
30 Oct 2023Submitted to Journal of Biophotonics
30 Oct 2023Submission Checks Completed
30 Oct 2023Assigned to Editor
30 Oct 2023Review(s) Completed, Editorial Evaluation Pending
30 Oct 2023Reviewer(s) Assigned