Programa de Pós-Graduação Interunidades em Bioengenharia EESC/FMRP/IQSC, Universidade de São Paulo, Av. Trabalhador Sãocarlense, 400, São Carlos, SP 13566-590, Brazil.
Instituto de Química de São Carlos, Universidade de São Paulo, Av. Trabalhador Sãocarlense, 400, São Carlos, SP 13566-590, Brazil.
Photodiagnosis Photodyn Ther. 2018 Jun;22:26-33. doi: 10.1016/j.pdpdt.2018.02.020. Epub 2018 Feb 27.
Antimicrobial Photodynamic Inactivation (a-PDI) is based on the oxidative destruction of biological molecules by reactive oxygen species generated by the photo-excitation of a photosensitive molecule. When a-PDT is performed with the use of mathematical models, the optimal conditions for maximum inactivation are found. Experimental designs allow a multivariate analysis of the experimental parameters. This is usually made using a univariate approach, which demands a large number of experiments, being time and money consuming. This paper presents the use of the response surface methodology for improving the search for the best conditions to reduce E. coli survival levels by a-PDT using methylene blue (MB) and toluidine blue (TB) as photosensitizers and white light. The goal was achieved by analyzing the effects and interactions of the three main parameters involved in the process: incubation time (IT), photosensitizer concentration (C), and light dose (LD). The optimization procedure began with a full 2 factorial design, followed by a central composite one, in which the optimal conditions were estimated. For MB, C was the most important parameter followed by LD and IT whereas, for TB, the main parameter was LD followed by C and IT. Using the estimated optimal conditions for inactivation, MB was able to inactivate 99.999999% CFU mL of E. coli with IT of 28 min, LD of 31 J cm, and C of 32 μmol L, while TB required 18 min, 39 J cm, and 37 μmol L. The feasibility of using the response surface methodology with a-PDT was demonstrated, enabling enhanced photoinactivation efficiency and fast results with a minimal number of experiments.
抗菌光动力灭活 (a-PDI) 基于通过光敏分子的光激发产生的活性氧物质对生物分子的氧化破坏。当使用数学模型进行 a-PDT 时,会找到最大灭活的最佳条件。实验设计允许对实验参数进行多变量分析。这通常使用单变量方法来完成,需要进行大量的实验,既费时又费钱。本文介绍了如何使用响应面法来改进搜索最佳条件,以使用亚甲蓝 (MB) 和甲苯胺蓝 (TB) 作为光敏剂和白光通过 a-PDT 降低大肠杆菌的存活率。通过分析过程中涉及的三个主要参数的作用和相互作用来实现目标:孵育时间 (IT)、光敏剂浓度 (C) 和光剂量 (LD)。优化过程首先进行完全 2 因子设计,然后进行中心复合设计,在其中估计最佳条件。对于 MB,C 是最重要的参数,其次是 LD 和 IT,而对于 TB,主要参数是 LD,其次是 C 和 IT。使用估计的最佳灭活条件,MB 能够在 IT 为 28 分钟、LD 为 31 J cm 和 C 为 32 μmol L 的情况下灭活 99.999999% CFU mL 的大肠杆菌,而 TB 则需要 18 分钟、39 J cm 和 37 μmol L。证明了使用响应面法与 a-PDT 结合的可行性,实现了增强的光灭活效率,并在最少的实验次数下快速获得结果。