Dogsa Iztok, Mandic-Mulec Ines
Chair of Microbiology, Department of Microbiology, Biotechnical Faculty, University of Ljubljana, Večna pot 111, 1000, Ljubljana, EU, Slovenia.
Biofilm. 2023 Sep 20;6:100157. doi: 10.1016/j.bioflm.2023.100157. eCollection 2023 Dec 15.
Quantifying the degree of spatial segregation of two bacterial strains in mixed biofilms is an important topic in microbiology. Spatial segregation is dependent on spatial scale as two strains may appear to be well mixed if observed from a distance, but a closer look can reveal strong separation. Typically, this information is encoded in a digital image that represents the binary system, e.g., a microscopy image of a two species biofilm. To decode spatial segregation information, we have developed quantitative measures for evaluating the degree of the spatial scale-dependent segregation of two bacterial strains in a digital image. The constructed algorithm is based on the new segregation measures and overcomes drawbacks of existing approaches for biofilm segregation analysis. The new approach is implemented in a freely available software and was successfully applied to biofilms of two strains and bacterial suspensions for detection of the different spatial scale-dependent segregation levels.
量化混合生物膜中两种细菌菌株的空间分离程度是微生物学中的一个重要课题。空间分离取决于空间尺度，因为从远处观察时，两种菌株可能看起来混合得很好，但仔细观察会发现明显的分离。通常，此信息编码在表示二元系统的数字图像中，例如两种物种生物膜的显微镜图像。为了解码空间分离信息，我们开发了定量方法来评估数字图像中两种细菌菌株的空间尺度依赖性分离程度。构建的算法基于新的分离度量，克服了现有生物膜分离分析方法的缺点。这种新方法在一个免费软件中实现，并成功应用于两种菌株的生物膜和细菌悬浮液，以检测不同空间尺度依赖性的分离水平。
