Ion mobility spectrometry and mass spectrometry coupled to gas chromatography for analysis of microbial contaminated cosmetic creams

被引:6
|
作者
Garcia-Nicolas, Maria [1 ]
Arroyo-Manzanares, Natalia [1 ]
de Dios Hernandez, Juan [2 ]
Guillen, Isidro [2 ]
Vizcaino, Pascuala [2 ]
Sanchez-Rubio, Marta [2 ]
Lopez-Garcia, Ignacio [1 ]
Hernandez-Cordoba, Manuel [1 ]
Vinas, Pilar [1 ]
机构
[1] Univ Murcia, Fac Chem, Dept Analyt Chem, Reg Campus Int Excellence Campus Mare Nostrum, E-30100 Murcia, Spain
[2] Prod Sur SA Prosur, Ave Francisco Salzillo,P-27-2, Murcia 30169, Spain
关键词
Ion mobility spectrometry; Mass spectrometry; Gas chromatography; Cosmetic creams; Microbial contamination; HEADSPACE; ALLERGENS; QUANTIFICATION; IDENTIFICATION; TARGET;
D O I
10.1016/j.aca.2020.06.069
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
The most commonly used technique for monitoring microbial contamination in cosmetic products is plate counting. In this contribution, headspace - gas chromatography (HS-GC) coupled to mass spectrometry (MS) or ion mobility spectrometry (IMS) is proposed as a technique to evaluate rapidly and accurately the state of microbial colonies in cosmetic creams using the volatile organic compounds produced by microorganisms (MVOC). The work focuses on monitoring two of the microorganisms that most frequently occur in such creams, Candida albicans and Staphylococcus aureus. In addition, two different types of ingredient with antimicrobial properties (a chemical preservative and a natural pre-servative) were added to study the behaviour of these microorganisms under different conditions. The facial creams were elaborated and inoculated with the two above microorganisms, and then sampled weekly for 4 weeks, analysing the evolution of the MVOCs by HS-GC-MS and HS-GC-IMS. In addition, microbial contamination was determined by the classical plate counting method. The pH, colour, viscosity and water activity parameters were also measured. The use of chemometric tools is essential because of the large amount of data generated, and different models based on discriminant analysis with an orthogonal projection on latent structures (OPLS-DA) were constructed. The optimal models obtained by both analytical techniques allowed differentiation between contaminated and non-contaminated creams, with a validation success rate of 94.4%. In addition, MVOC monitoring also allowed assessment of the microbial concentration. (C) 2020 Elsevier B.V. All rights reserved.
引用
收藏
页码:52 / 61
页数:10
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