Course and prospect of microbiological testing: from traditional culture to precision diagnosis_West China Medical Journal

Authors：

WANG Xiao ¹ , LI Yaheng ¹ , LI Xiaoyan ¹ , WU Wenming ¹ , WANG Chunyu ¹ , HE Qi ² ,  HAO Chonghua ¹

1. Department of Clinical Laboratory, Heping Campus, Shanxi Provincial People’s Hospital, Taiyuan, Shanxi 030012, P. R. China;
2. School of Basic Medical Sciences, Shanxi Medical University, Taiyuan, Shanxi 030001, P. R. China;

Corresponding?author：

HAO Chonghua, Email: hch386@126.com

Keywords：

Microbiological testing; rapid diagnosis; automation; multi-omics integration

DOI：

10.7507/1002-0179.202607117

Video：

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Infectious diseases are characterized by acute onset and rapid progression, and the efficiency of their diagnosis and treatment is highly dependent on the timeliness and accuracy of microbiological testing. Focusing on shortening turnaround time and improving result precision, this paper systematically reviews the evolution of microbiological testing across three stages: manual microscopic examination and conventional culture, automated biochemical identification, and mass-spectrometry-based and molecular diagnostics. It summarizes the breakthroughs and limitations of representative technologies in each stage, analyzes the impacts of technological iteration on clinical decision-making, specimen submission practices and antimicrobial stewardship, and prospects future trends including full-process automation, point-of-care testing, and multi-omics integration.

Citation： WANG Xiao, LI Yaheng, LI Xiaoyan, WU Wenming, WANG Chunyu, HE Qi, HAO Chonghua. Course and prospect of microbiological testing: from traditional culture to precision diagnosis. West China Medical Journal, 2026, 41(8): 1343-1348. doi: 10.7507/1002-0179.202607117 Copy

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2.	武潔, 王荃. 病原微生物檢測在感染判定的意義[J]. 中國小兒急救醫學, 2020, 27(3): 175-180.
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4.	Yoshida S, Tsuyuguchi K, Suzuki K, et al. Comparative evaluation of acid-fast staining for the detection of Mycobacterium fortuitum--clinical performance of fluorescent and Ziehl-Neelsen staining[J]. Kekkaku, 2013, 88(5): 461-467.
5.	Wang DD, Jiang X, Hu BT, et al. Comparative analysis of the detection capabilities of BacT/ALERT and BACTEC blood culture systems for simulated and clinical bacteremia specimens[J]. Sci Rep, 2026, 16(1): 15290.
6.	Yadav NK, Raj N, Singh V, et al. Impact of blood volume on pathogen detection and time to positivity in paediatric blood cultures using BACT/ALERT 3D automated systems[J]. Cureus, 2025, 17(7): e88454.
7.	Song SA. Performance evaluation of VITEK^? MS PRIME compared to VITEK^? MS[J]. J Microbiol Methods, 2026, 244: 107479.
8.	Xing Y, Zhang J, Sun L, et al. Non-susceptibility of Enterococcus faecalis to daptomycin detected by VITEK-2 P639 card: clinical reporting is not recommended[J]. Microbiol Spectr, 2026, 14(4): e0265325.
9.	Papadomanolaki A, Siopi M, Karakosta P, et al. Comparative evaluation of Vitek 2 and Etest versus broth microdilution for ceftazidime/avibactam and ceftolozane/tazobactam susceptibility testing of Enterobacterales and Pseudomonas aeruginosa[J]. Antibiotics (Basel), 2022, 11(7): 865.
10.	Mahamdi T, Yanes O. Dry deposition strategies for MALDI-MS imaging: principles, advances and emerging applications[J]. Anal Sci Adv, 2026, 7: e70082.
11.	Zhou M, Zhao L, Li D, et al. Rapid identification of carbapenem-resistant Acinetobacter baumannii based on MALDI-TOF mass spectrometry and machine learning[J]. BMC Microbiol, 2026: 17.
12.	Martiny D, Busson L, Wybo I, et al. Comparison of the Microflex LT and Vitek MS systems for routine identification of bacteria by matrix-assisted laser desorption ionization-time of flight mass spectrometry[J]. J Clin Microbiol, 2012, 50(4): 1313-1325.
13.	Li Y, Wang H, Hou X, et al. Identification by matrix-assisted laser desorption ionization-time of flight mass spectrometry and antifungal susceptibility testing of non-Aspergillus molds[J]. Front Microbiol, 2020, 11: 922.
14.	Vidal-Acu?a MR, Ruiz-Pérez de Pipaón M, Torres-Sánchez MJ, et al. Identification of clinical isolates of Aspergillus, including cryptic species, by matrix assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS)[J]. Med Mycol, 2018, 56(7): 838-846.
15.	Seng P, Drancourt M, Gouriet F, et al. Ongoing revolution in bacteriology: routine identification of bacteria by matrix-assisted laser desorption ionization time-of-flight mass spectrometry[J]. Clin Infect Dis, 2009, 49(4): 543-551.
16.	Zhang L, Xiao M, Wang H, et al. Yeast identification algorithm based on use of the Vitek MS system selectively supplemented with ribosomal DNA sequencing: proposal of a reference assay for invasive fungal surveillance programs in China[J]. J Clin Microbiol, 2014, 52(2): 572-577.
17.	Chen Y, Porter V, Mubareka S, et al. Rapid identification of bacteria directly from positive blood cultures by use of a serum separator tube, smudge plate preparation, and matrix-assisted laser desorption ionization-time of flight mass spectrometry[J]. J Clin Microbiol, 2015, 53(10): 3349-3352.
18.	張浩然, 孫冰清, 徐汀, 等. 基質輔助激光解析電離飛行時間質譜技術在病原微生物鑒定中的應用[J]. 中國獸醫雜志, 2022, 58(1): 106-109.
19.	劉振波, 夏蘇蘇, 康琳, 等. 基質輔助激光解吸電離飛行時間質譜在病原微生物鑒定中的應用[J]. 中國國境衛生檢疫雜志, 2019, 42(3): 225-228.
20.	Beck ET, Buchan BW, Reymann GC, et al. Comparison of ESwab and wound fiber swab specimen collection devices for use with Xpert SA nasal complete assay[J]. J Clin Microbiol, 2016, 54(7): 1904-1906.
21.	Gill CM, Asempa TE, Tickler IA, et al. Evaluation of the Xpert Carba-R NxG assay for detection of carbapenemase genes in a global challenge set of Pseudomonas aeruginosa isolates[J]. J Clin Microbiol, 2020, 58(12): e01098-20.
22.	Detjen AK, DiNardo AR, Leyden J, et al. Xpert MTB/RIF assay for the diagnosis of pulmonary tuberculosis in children: a systematic review and meta-analysis[J]. Lancet Respir Med, 2015, 3(6): 451-461.
23.	Poritz MA, Blaschke AJ, Byington CL, et al. FilmArray, an automated nested multiplex PCR system for multi-pathogen detection: development and application to respiratory tract infection[J]. PLoS One, 2011, 6(10): e26047.
24.	錢克莉, 袁喆. 二代測序技術在病原微生物檢測及感染性疾病診斷中的應用[J]. 西部醫學, 2025, 37(1): 1-4.
25.	石玉如, 谷德健, 吳靜, 等. 靶向捕獲測序技術和宏基因組二代測序技術檢測肺泡灌洗液中結核分枝桿菌的診斷價值[J]. 中國防癆雜志, 2025, 47(3): 305-311.
26.	Miller RR, Montoya V, Gardy JL, et al. Metagenomics for pathogen detection in public health[J]. Genome Med, 2013, 5(9): 81.
27.	Ren LL, Wang YM, Wu ZQ, et al. Identification of a novel coronavirus causing severe pneumonia in human: a descriptive study[J]. Chin Med J (Engl), 2020, 133(9): 1015-1024.
28.	羅越, 胡洋洋, 張興, 等. 《中國宏基因組學第二代測序技術檢測感染病原體的臨床應用專家共識》解讀[J]. 河北醫科大學學報, 2021, 42(7): 745-749.
29.	中國醫療保健國際交流促進會臨床微生物學分會. 靶向高通量測序在感染性疾病中應用與實踐專家共識[J]. 中華醫學雜志, 2024, 104(48): 4375-4383.
30.	Chiu CY, Miller SA. Clinical metagenomics[J]. Nat Rev Genet, 2019, 20(6): 341-355.
31.	Liao JC, Mastali M, Gau V, et al. Use of electrochemical DNA biosensors for rapid molecular identification of uropathogens in clinical urine specimens[J]. J Clin Microbiol, 2006, 44(2): 561-570.
32.	Mach KE, Mohan R, Baron EJ, et al. A biosensor platform for rapid antimicrobial susceptibility testing directly from clinical samples[J]. J Urol, 2011, 185(1): 148-153.
33.	Mach KE, Du CB, Phull H, et al. Multiplex pathogen identification for polymicrobial urinary tract infections using biosensor technology: a prospective clinical study[J]. J Urol, 2009, 182(6): 2735-2741.

1. Vazquez-Guillamet C, Scolari M, Zilberberg MD, et al. Using the number needed to treat to assess appropriate antimicrobial therapy as a determinant of outcome in severe sepsis and septic shock[J]. Crit Care Med, 2014, 42(11): 2342-2349.
2. 武潔, 王荃. 病原微生物檢測在感染判定的意義[J]. 中國小兒急救醫學, 2020, 27(3): 175-180.
3. Thomson RB Jr. One small step for the Gram stain, one giant leap for clinical microbiology[J]. J Clin Microbiol, 2016, 54(6): 1416-1417.
4. Yoshida S, Tsuyuguchi K, Suzuki K, et al. Comparative evaluation of acid-fast staining for the detection of Mycobacterium fortuitum--clinical performance of fluorescent and Ziehl-Neelsen staining[J]. Kekkaku, 2013, 88(5): 461-467.
5. Wang DD, Jiang X, Hu BT, et al. Comparative analysis of the detection capabilities of BacT/ALERT and BACTEC blood culture systems for simulated and clinical bacteremia specimens[J]. Sci Rep, 2026, 16(1): 15290.
6. Yadav NK, Raj N, Singh V, et al. Impact of blood volume on pathogen detection and time to positivity in paediatric blood cultures using BACT/ALERT 3D automated systems[J]. Cureus, 2025, 17(7): e88454.
7. Song SA. Performance evaluation of VITEK^? MS PRIME compared to VITEK^? MS[J]. J Microbiol Methods, 2026, 244: 107479.
8. Xing Y, Zhang J, Sun L, et al. Non-susceptibility of Enterococcus faecalis to daptomycin detected by VITEK-2 P639 card: clinical reporting is not recommended[J]. Microbiol Spectr, 2026, 14(4): e0265325.
9. Papadomanolaki A, Siopi M, Karakosta P, et al. Comparative evaluation of Vitek 2 and Etest versus broth microdilution for ceftazidime/avibactam and ceftolozane/tazobactam susceptibility testing of Enterobacterales and Pseudomonas aeruginosa[J]. Antibiotics (Basel), 2022, 11(7): 865.
10. Mahamdi T, Yanes O. Dry deposition strategies for MALDI-MS imaging: principles, advances and emerging applications[J]. Anal Sci Adv, 2026, 7: e70082.
11. Zhou M, Zhao L, Li D, et al. Rapid identification of carbapenem-resistant Acinetobacter baumannii based on MALDI-TOF mass spectrometry and machine learning[J]. BMC Microbiol, 2026: 17.
12. Martiny D, Busson L, Wybo I, et al. Comparison of the Microflex LT and Vitek MS systems for routine identification of bacteria by matrix-assisted laser desorption ionization-time of flight mass spectrometry[J]. J Clin Microbiol, 2012, 50(4): 1313-1325.
13. Li Y, Wang H, Hou X, et al. Identification by matrix-assisted laser desorption ionization-time of flight mass spectrometry and antifungal susceptibility testing of non-Aspergillus molds[J]. Front Microbiol, 2020, 11: 922.
14. Vidal-Acu?a MR, Ruiz-Pérez de Pipaón M, Torres-Sánchez MJ, et al. Identification of clinical isolates of Aspergillus, including cryptic species, by matrix assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS)[J]. Med Mycol, 2018, 56(7): 838-846.
15. Seng P, Drancourt M, Gouriet F, et al. Ongoing revolution in bacteriology: routine identification of bacteria by matrix-assisted laser desorption ionization time-of-flight mass spectrometry[J]. Clin Infect Dis, 2009, 49(4): 543-551.
16. Zhang L, Xiao M, Wang H, et al. Yeast identification algorithm based on use of the Vitek MS system selectively supplemented with ribosomal DNA sequencing: proposal of a reference assay for invasive fungal surveillance programs in China[J]. J Clin Microbiol, 2014, 52(2): 572-577.
17. Chen Y, Porter V, Mubareka S, et al. Rapid identification of bacteria directly from positive blood cultures by use of a serum separator tube, smudge plate preparation, and matrix-assisted laser desorption ionization-time of flight mass spectrometry[J]. J Clin Microbiol, 2015, 53(10): 3349-3352.
18. 張浩然, 孫冰清, 徐汀, 等. 基質輔助激光解析電離飛行時間質譜技術在病原微生物鑒定中的應用[J]. 中國獸醫雜志, 2022, 58(1): 106-109.
19. 劉振波, 夏蘇蘇, 康琳, 等. 基質輔助激光解吸電離飛行時間質譜在病原微生物鑒定中的應用[J]. 中國國境衛生檢疫雜志, 2019, 42(3): 225-228.
20. Beck ET, Buchan BW, Reymann GC, et al. Comparison of ESwab and wound fiber swab specimen collection devices for use with Xpert SA nasal complete assay[J]. J Clin Microbiol, 2016, 54(7): 1904-1906.
21. Gill CM, Asempa TE, Tickler IA, et al. Evaluation of the Xpert Carba-R NxG assay for detection of carbapenemase genes in a global challenge set of Pseudomonas aeruginosa isolates[J]. J Clin Microbiol, 2020, 58(12): e01098-20.
22. Detjen AK, DiNardo AR, Leyden J, et al. Xpert MTB/RIF assay for the diagnosis of pulmonary tuberculosis in children: a systematic review and meta-analysis[J]. Lancet Respir Med, 2015, 3(6): 451-461.
23. Poritz MA, Blaschke AJ, Byington CL, et al. FilmArray, an automated nested multiplex PCR system for multi-pathogen detection: development and application to respiratory tract infection[J]. PLoS One, 2011, 6(10): e26047.
24. 錢克莉, 袁喆. 二代測序技術在病原微生物檢測及感染性疾病診斷中的應用[J]. 西部醫學, 2025, 37(1): 1-4.
25. 石玉如, 谷德健, 吳靜, 等. 靶向捕獲測序技術和宏基因組二代測序技術檢測肺泡灌洗液中結核分枝桿菌的診斷價值[J]. 中國防癆雜志, 2025, 47(3): 305-311.
26. Miller RR, Montoya V, Gardy JL, et al. Metagenomics for pathogen detection in public health[J]. Genome Med, 2013, 5(9): 81.
27. Ren LL, Wang YM, Wu ZQ, et al. Identification of a novel coronavirus causing severe pneumonia in human: a descriptive study[J]. Chin Med J (Engl), 2020, 133(9): 1015-1024.
28. 羅越, 胡洋洋, 張興, 等. 《中國宏基因組學第二代測序技術檢測感染病原體的臨床應用專家共識》解讀[J]. 河北醫科大學學報, 2021, 42(7): 745-749.
29. 中國醫療保健國際交流促進會臨床微生物學分會. 靶向高通量測序在感染性疾病中應用與實踐專家共識[J]. 中華醫學雜志, 2024, 104(48): 4375-4383.
30. Chiu CY, Miller SA. Clinical metagenomics[J]. Nat Rev Genet, 2019, 20(6): 341-355.
31. Liao JC, Mastali M, Gau V, et al. Use of electrochemical DNA biosensors for rapid molecular identification of uropathogens in clinical urine specimens[J]. J Clin Microbiol, 2006, 44(2): 561-570.
32. Mach KE, Mohan R, Baron EJ, et al. A biosensor platform for rapid antimicrobial susceptibility testing directly from clinical samples[J]. J Urol, 2011, 185(1): 148-153.
33. Mach KE, Du CB, Phull H, et al. Multiplex pathogen identification for polymicrobial urinary tract infections using biosensor technology: a prospective clinical study[J]. J Urol, 2009, 182(6): 2735-2741.

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