Application of MALDI-TOF MS to rapid identification of anaerobic bacteria.


Journal

BMC infectious diseases
ISSN: 1471-2334
Titre abrégé: BMC Infect Dis
Pays: England
ID NLM: 100968551

Informations de publication

Date de publication:
07 Nov 2019
Historique:
received: 17 04 2019
accepted: 21 10 2019
entrez: 9 11 2019
pubmed: 9 11 2019
medline: 15 1 2020
Statut: epublish

Résumé

Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has been rapidly developed and widely used as an analytical technique in clinical laboratories with high accuracy in microorganism identification. To validate the efficacy of MALDI-TOF MS in identification of clinical pathogenic anaerobes. Twenty-eight studies covering 6685 strains of anaerobic bacteria were included in this meta-analysis. Fixed-effects models based on the P-value and the I-squared were used for meta-analysis to consider the possibility of heterogeneity between studies. Statistical analyses were performed by using STATA 12.0. The identification accuracy of MALDI-TOF MS was 84% for species (I Our research showed that MALDI-TOF-MS was satisfactory in genus identification of clinical pathogenic anaerobic bacteria. However, this method still suffers from different drawbacks in precise identification of rare anaerobe and species levels of common anaerobic bacteria.

Sections du résumé

BACKGROUND BACKGROUND
Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has been rapidly developed and widely used as an analytical technique in clinical laboratories with high accuracy in microorganism identification.
OBJECTIVE OBJECTIVE
To validate the efficacy of MALDI-TOF MS in identification of clinical pathogenic anaerobes.
METHODS METHODS
Twenty-eight studies covering 6685 strains of anaerobic bacteria were included in this meta-analysis. Fixed-effects models based on the P-value and the I-squared were used for meta-analysis to consider the possibility of heterogeneity between studies. Statistical analyses were performed by using STATA 12.0.
RESULTS RESULTS
The identification accuracy of MALDI-TOF MS was 84% for species (I
CONCLUSIONS CONCLUSIONS
Our research showed that MALDI-TOF-MS was satisfactory in genus identification of clinical pathogenic anaerobic bacteria. However, this method still suffers from different drawbacks in precise identification of rare anaerobe and species levels of common anaerobic bacteria.

Identifiants

pubmed: 31699042
doi: 10.1186/s12879-019-4584-0
pii: 10.1186/s12879-019-4584-0
pmc: PMC6836477
doi:

Types de publication

Journal Article Meta-Analysis

Langues

eng

Sous-ensembles de citation

IM

Pagination

941

Subventions

Organisme : Science and Technology Innovative Research Team in Higher Educational Institutions of Hunan Province
ID : 17KJB360014
Organisme : the National Natural Science Foundation of China
ID : 81871734
Organisme : Jiangsu Privincial Natural Science Foundation
ID : BK20151154
Organisme : Jiangsu Privincial Medical Talent
ID : ZDRCA2016053
Organisme : Six talent peaks project of Jiangsu Province
ID : WSN-135
Organisme : Advanced health talent of six-one project of Jiangsu Province
ID : LGY2016042
Organisme : the Natural Science Foundation of Jiangsu Province
ID : Grants No BK20150209
Organisme : the National Natural Science Foundation of China
ID : 81902040
Organisme : the National Natural Science Foundation of China
ID : 81471994

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Auteurs

Ying Li (Y)

School of Medical Technology, Xuzhou Medical University, Xuzhou, 221004, China.

Mingzhu Shan (M)

School of Medical Technology, Xuzhou Medical University, Xuzhou, 221004, China.

Zuobin Zhu (Z)

Department of Genetics, Xuzhou Medical University, Xuzhou, 221004, China.

Xuhua Mao (X)

Department of Clinical Laboratory, Yixing People's Hospital, Wuxi, 214200, China.

Mingju Yan (M)

School of Medical Technology, Xuzhou Medical University, Xuzhou, 221004, China.

Ying Chen (Y)

School of Medical Technology, Xuzhou Medical University, Xuzhou, 221004, China.

Qiuju Zhu (Q)

Jiangsu Key Laboratory of Brain Disease Bioinformation, Xuzhou Medical University, Xuzhou, 221004, China.

Hongchun Li (H)

School of Medical Technology, Xuzhou Medical University, Xuzhou, 221004, China.
Department of Laboratory Medicine, Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221002, China.

Bing Gu (B)

School of Medical Technology, Xuzhou Medical University, Xuzhou, 221004, China. gb20031129@163.com.
Department of Laboratory Medicine, Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221002, China. gb20031129@163.com.

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