利用MALDI-TOF质谱和机器学习快速鉴定耐碳青霉烯肺炎克雷伯菌

IF 5.7 2区 生物学
Zhiyi Ye, Jin Zhu, Yang Liu, Jun Lu
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引用次数: 0

摘要

利用基质辅助激光解吸电离飞行时间质谱(MALDI-TOF MS)筛选耐碳青霉烯肺炎克雷伯菌(CRKP)的特异性质量峰,比较肠道和血液筛选CRKP的谱峰差异,评估MALDI-TOF MS在快速鉴定各种CRKP来源中的效用。2014 - 2023年衢州市人民医院共采集肺炎克雷伯菌267株,其中ICU患者肠道筛查分离株60株,血流感染分离株207株。使用MALDI-TOF质谱分析CRKP和碳青霉烯敏感肺炎克雷伯菌(CSKP)的肽段,然后使用flexAnalysis和ClinProTools 3.0进行分析。选取具有统计学意义的蛋白峰建立分类模型,用非重复菌株进行验证。MALDI-TOF质谱鉴定肺炎克雷伯菌的准确率达到99.9%。利用特征峰(2523.43、3041.62、4520.11、10079.18 Da)建立耐药分析模型,最佳模型(SNN)对CSKP和CRKP的敏感性为90.08%,特异性为95.80%,鉴定准确率分别为90%和89.66%。另一个使用峰(8876、8993、9139 Da)区分CRKP来源的模型,理想模型(QC)的灵敏度为86.85%,特异性为88.46%,血液和肠道CRKP的准确率分别为81.82%和95.00%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rapid Identification and Typing of Carbapenem-Resistant Klebsiella pneumoniae Using MALDI-TOF MS and Machine Learning

Use matrix-assisted laser desorption ionisation time-of-flight mass spectrometry (MALDI-TOF MS) to screen the specific mass peaks of carbapenem-resistant Klebsiella pneumoniae (CRKP), compare the differences in spectrum peaks between intestinal and bloodstream screening of CRKP, and assess the utility of MALDI-TOF MS in quickly identifying various CRKP sources. From 2014 to 2023, a total of 267 Klebsiella pneumoniae strains were collected at Quzhou People's Hospital, including 60 intestinal screening isolates from ICU patients and 207 bloodstream infection isolates. MALDI-TOF MS was used to profile peptides in CRKP and carbapenem-sensitive Klebsiella pneumoniae (CSKP), followed by analysis with flexAnalysis and ClinProTools 3.0. Statistically significant protein peaks were selected to build classification models, which were verified using non-duplicate strains. MALDI-TOF MS achieved > 99.9% accuracy in identifying Klebsiella pneumoniae. Characteristic peaks (2523.43, 3041.62, 4520.11, 10,079.18 Da) were used to develop resistance analysis models, with the optimal model (SNN) showing 90.08% sensitivity, 95.80% specificity and identification accuracies of 90% for CSKP and 89.66% for CRKP. Another model using peaks (8876, 8993, 9139 Da) differentiated CRKP origins, with the ideal model (QC) achieving 86.85% sensitivity, 88.46% specificity, and accuracies of 81.82% for bloodstream and 95.00% for intestinal CRKP.

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来源期刊
Microbial Biotechnology
Microbial Biotechnology Immunology and Microbiology-Applied Microbiology and Biotechnology
CiteScore
11.20
自引率
3.50%
发文量
162
审稿时长
1 months
期刊介绍: Microbial Biotechnology publishes papers of original research reporting significant advances in any aspect of microbial applications, including, but not limited to biotechnologies related to: Green chemistry; Primary metabolites; Food, beverages and supplements; Secondary metabolites and natural products; Pharmaceuticals; Diagnostics; Agriculture; Bioenergy; Biomining, including oil recovery and processing; Bioremediation; Biopolymers, biomaterials; Bionanotechnology; Biosurfactants and bioemulsifiers; Compatible solutes and bioprotectants; Biosensors, monitoring systems, quantitative microbial risk assessment; Technology development; Protein engineering; Functional genomics; Metabolic engineering; Metabolic design; Systems analysis, modelling; Process engineering; Biologically-based analytical methods; Microbially-based strategies in public health; Microbially-based strategies to influence global processes
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