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Development and evaluation of a numerical identification kit for Pseudomonas species
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Xiaozheng ZHENG1, 2, Xinyu ZHAO2, Qiang WAN3, Qingping WU1, 2, Wenjie WEI1, 2, Jian SUN1, 2, Yingwang YE1, Yuwei WU2, *, Qinghua YE2, *
Acta Microbiologica Sinica | 2025, 65(11) : 5172 - 5182
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Acta Microbiologica Sinica | 2025, 65(11): 5172-5182
• Technology and Method •
Development and evaluation of a numerical identification kit for Pseudomonas species
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Xiaozheng ZHENG1, 2, Xinyu ZHAO2, Qiang WAN3, Qingping WU1, 2, Wenjie WEI1, 2, Jian SUN1, 2, Yingwang YE1, Yuwei WU2, *, Qinghua YE2, *
Affiliations
  • 1 School of Food and Biological Engineering, Hefei University of Technology, Hefei, Anhui, China
  • 2 State Key Laboratory of Applied Microbiology Southern China, Guangdong Provincial Key Laboratory of Microbial Safety and Health, National Health Commission Science and Technology Innovation Platform for Nutrition and Safety of Microbial Food, Key Laboratory of Food Microbial Safety Big Data Technology (State Administration for Market Regulation), Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, Guangdong, China
  • 3 Guangdong Huankai Biotechnology Co. , Ltd. , Zhaoqing, Guangdong, China
Published: 2025-11-04 doi: 10.13343/j.cnki.wsxb.20250298
Outline
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Objective Bacteria of Pseudomonas are the main cause of food-borne and clinical infections. At present, mass spectrometry and 16S rRNA gene are widely used to identify Pseudomonas, while the facilities relied on are expensive and require cumbersome operation. Internationally, the numerical identification products require manual single-sample loading procedures, which are cumbersome. This study aims to develop a numerical identification kit for Pseudomonas with high accuracy and simple operation. Methods On the basis of the existing biochemical reaction data of Pseudomonas, we developed a numerical identification model via the branching diagram method and designed and optimized 11 biochemical matrix formulas for microquantization. We then used the kit to identify the standard strains and isolates of Pseudomonas and compared the results with those from mass spectrometry and PCR to evaluate the performance of the kit. Results A numerical identification kit was developed, and it was capable of identifying 10 species of Pseudomonas with just one sample addition. The accuracy rate of the kit in the identification for 5 standard strains and 135 isolates reached 97.04%, and the accuracy rate in actual samples was 97.74%. The biochemical test was stable and reproducible, and the identification cost (25 CNY/sample) of the kit was only 10% of that (240 CNY/sample) of the comparable product from bioMérieux (France). Conclusion The numerical identification kit developed in this study for Pseudomonas has simple operation, a low price, and high accuracy, which can be used in clinical diagnosis and food detection.

Pseudomonas  /  numerical identification kit  /  performance evaluation
Xiaozheng ZHENG, Xinyu ZHAO, Qiang WAN, Qingping WU, Wenjie WEI, Jian SUN, Yingwang YE, Yuwei WU, Qinghua YE. Development and evaluation of a numerical identification kit for Pseudomonas species[J]. Acta Microbiologica Sinica, 2025 , 65 (11) : 5172 -5182 . DOI: 10.13343/j.cnki.wsxb.20250298
Funding
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  • National Key Research and Development Program of China(2022YFF1100700)
  • Outstanding Youth Project of the Natural Science Foundation of Guangdong Province(2022B1515020068)
  • Talent Project of Guangdong Academy of Sciences(2023GDASQNRC-0102)
Appendix
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Year 2025 volume 65 Issue 11
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269
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Article Info
doi: 10.13343/j.cnki.wsxb.20250298
  • Receive Date：2025-04-10
  • Online Date：2025-11-10
  • Published：2025-11-04
Article Data
Affiliations
History
  • Received：2025-04-10
  • Accepted：2025-06-03
Funding
National Key Research and Development Program of China(2022YFF1100700)
Outstanding Youth Project of the Natural Science Foundation of Guangdong Province(2022B1515020068)
Talent Project of Guangdong Academy of Sciences(2023GDASQNRC-0102)
Affiliations
    1 School of Food and Biological Engineering, Hefei University of Technology, Hefei, Anhui, China
    2 State Key Laboratory of Applied Microbiology Southern China, Guangdong Provincial Key Laboratory of Microbial Safety and Health, National Health Commission Science and Technology Innovation Platform for Nutrition and Safety of Microbial Food, Key Laboratory of Food Microbial Safety Big Data Technology (State Administration for Market Regulation), Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, Guangdong, China
    3 Guangdong Huankai Biotechnology Co. , Ltd. , Zhaoqing, Guangdong, China

Corresponding:

*E-mail: YE Qinghua,
WU Yuwei,
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https://castjournals.cast.org.cn/joweb/wswxb/EN/10.13343/j.cnki.wsxb.20250298
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表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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