Microbial proteomics is a key approach to understanding and analysing microbial physiology, metabolism, pathogenic mechanisms, and environmental adaptation. Due to limitations in sample purity, throughput, and cost, traditional structural analysis techniques struggle to fully detect the vast number of unknown proteins within the microbial proteome. In recent years, structural elucidation of the microbial proteome has been driven by innovations in cryo-electron microscopy, high-resolution mass spectrometry, AI-based structure prediction, and multi-model integration techniques. This field has evolved from single-protein studies to the entire proteome, from in vitro purification to in situ dynamics, and from static structures to functional networks. The following article provides a systematic review of the latest advances in cryo-EM visualisation of proteomics, in situ mass spectrometry, AI-based structure prediction, and multi-technique integration, offering a reference for the in-depth decoding of microbial protein functional networks.
Sun CC, Li XY, Huang WR, et al., 2025, Large Models for Protein Prediction and Generation: From Sequence, Structure to Function. Life Sciences, 37(12): 1534–1548.
Ma H, Li LW, Bi XY, et al., 2025, Surface-enhanced Raman Spectroscopy (SERS) over 50 years: Theory, Applications, and Prospects. The Journal of Light Scattering, 37(3): 357–514.
Chao TY, Zhao Z, 2025, Research Progress and Development Trends in Cryo-electron Microscopy Sample Preparation and Cryo-thinning Techniques. Hi-Tech & Industrialization, 31(11): 34–36.
Cai F, Ling YY, Li L, et al., 2026, Research Progress in Mass Spectrometry-based Clinical Body Fluid Glycoproteomics. Journal of Chinese Mass Spectrometry Society, preprint, 1–32.
Yin GL, Sun WH, Pang XY, et al., 2022, Application of Cryo-electron Microscopy Technology in Molecular Botany Research. Biotechnology Bulletin, 38(1): 15–32.
Peng Y, Lu Y, Sun H, et al., 2024, Cryo-EM Structures of Candida albicans Cdr1 Reveal Azole-substrate Recognition and Inhibitor Blocking Mechanisms. Nature Communications, 15(1): 7722.
Jamali K, Käll L, Zhang R, et al., 2024, Automated Model Building and Protein Identification in Cryo-EM Maps. Nature, 628(8007): 450–457.
Song Y, Zuo QY, Meng XM, et al., 2025, Frontier Technologies and Development Applications of Cryo-electron Microscopy. Life Sciences, 37(7): 854–867.
Qin CD, Guo Q, Gao N, 2026, Cryo-lift-out Technology for Cryo-electron Tomography of Tissue Samples. Progress in Biochemistry and Biophysics, preprint, 1–20.
Liu W, Han J, Gong W, et al., 2026, Structure of Pancreatic hIAPP Fibrils Derived from Patients with Type 2 Diabetes. Cell, 189(4): 1210.e10.
Du FY, 2025, Research on the Antibacterial Effect and Mechanism of Water-soluble ZnO@APTES Quantum Dots against Methicillin-resistant Staphylococcus aureus, thesis, Shenyang Agricultural University.
Pang MW, 2025, Research on Protein Structure Prediction Methods Based on Cryo-electron Microscopy Detection Data, thesis, Jiangsu University of Technology.
Yang ZY, Yang TT, Wang N, et al., 2026, Progress and Challenges in Intact Protein in situ Ionization and Spatial Omics Mass Spectrometry Technologies for Biological Tissues. Journal of Chinese Mass Spectrometry Society, preprint, 1–21.
Huang GM, 2019, Electrophoretic Effects in Electrospray and their Applications in in situ Mass Spectrometry Analysis of Metabolites and Proteins. Chinese Chemical Society. Proceedings of the 22nd National Chromatographic Academic Symposium and Instrument Exhibition of the Chinese Chemical Society (Volume I). School of Chemistry and Materials Science, University of Science and Technology of China; 2019: 65.
Feng YP, Wang JL, Xue DM, 2025, Research Progress in Nitrogenase. Chinese Journal of Grassland, 47(12): 128–138.
Qin ZY, 2024, Functional Analysis of the htpG Gene in Vibrio mimicus Infection and Pathogenesis, thesis, Sichuan Agricultural University.
Wang HL, Meng XG, Xiao FP, et al., 2024, Application of High-resolution Liquid Chromatography-mass Spectrometry in Protein Chemical Modifications. Experimental Technology and Management, 41(8): 1–14.
Huang PQ, Zhao Y, Zhu J, et al., 2026, Progress and Application of Imaging Mass Spectrometry Technology in Tumor Spatial Proteomics Research. Journal of Chinese Mass Spectrometry Society, preprint, 1–24.
Ouyang ZZ, Ma YC, Kou YT, et al., 2025, Iterative Breakthroughs and Data Strategy Implications of AlphaFold from the Perspective of Scientific Data. Journal of Agricultural Big Data, 7(4): 485–495.
Gong WB, 2024, Major Breakthroughs in AlphaFold Structure Prediction and Its Impacts and Challenges on Protein Research. Progress in Biochemistry and Biophysics, 51(12): 3073–3083.
Ma H, Li LW, Bi XY, et al., 2025, Surface-enhanced Raman Spectroscopy (SERS) over 50 years: Theory, Applications, and Prospects. The Journal of Light Scattering, 37(3): 357–514.
Li XR, Huang GT, 2026, Research Progress in Phage-antibiotic Synergy (PAS) Therapy. Microbiology China, preprint, 1–24. https://doi.org/10.13344/j.microbiol.china.260098
Sun J, Zhu T, Cui Y, et al., 2025, Structure-based Self-supervised Learning Enables Ultrafast Protein Stability Prediction upon Mutation. The Innovation, 6(1): 100750.
Zeng WY, Zheng SY, Zhao XQ, et al., 2026, Progress in Generative Biology and Biologically Inspired Artificial Intelligence. Life Sciences, 38(2): 248–267.
Yu KR, Zhang NN, Liu YB, 2026, Precise Regulatory Tools for O-GlcNAc Modification Targeting Specific Proteins: Disease Mechanism Research and Therapeutic Opportunities. Acta Chimica Sinica, 84(3): 409–424.