Center for Biofilm Engineering, Montana State University, Bozeman, MT, USA; Department of Mathematical Sciences, Montana State University, Bozeman, MT, USA.
Centro de Investigación en Matemáticas, Jalisco S/N, Valenciana, GTO, Guanajuato 36023, MEXICO.
J Microbiol Methods. 2020 Jul;174:105943. doi: 10.1016/j.mimet.2020.105943. Epub 2020 May 17.
Beer's Law explains how light attenuates into thick specimens, including thick biofilms. We use a Bayesian optimality criterion, the maximum of the posterior probability distribution, and computationally efficiently fit Beer's Law to the 3D intensity data collected from thick living biofilms by a confocal scanning laser microscope. Using this approach the top surface of the biofilm and an optimal image threshold can be estimated. Biofilm characteristics, such as bio-volumes, can be calculated from this surface. Results from the Bayesian approach are compared to other approaches including the method of maximum likelihood or simply counting bright pixels. Uncertainty quantification (i.e., error bars) can be provided for the parameters of interest. This approach is applied to confocal images of stained biofilms of a common lab strain of Pseudomonas aeruginosa, stained biofilms of Janthinobacterium isolated from the Antarctic, and biofilms of Staphylococcusaureus that have been genetically modified to fluoresce green.
比尔定律解释了光如何衰减进入厚标本，包括厚生物膜。我们使用贝叶斯最优准则，即后验概率分布的最大值，并通过共焦扫描激光显微镜从厚的活生物膜中收集的 3D 强度数据，有效地拟合比尔定律。通过这种方法，可以估计生物膜的顶表面和最佳图像阈值。可以从该表面计算生物膜特征，例如生物量。贝叶斯方法的结果与其他方法进行了比较，包括最大似然法或简单地计算亮像素。可以为感兴趣的参数提供不确定性量化（即误差条）。该方法应用于荧光染色的铜绿假单胞菌常见实验室菌株的生物膜、南极分离的詹氏菌染色生物膜以及经过基因改造发出绿色荧光的金黄色葡萄球菌生物膜的共焦图像。
