Quantifying bacterial structure of aerobic granular sludge using image analysis

This Master’s project entitled ’Quantifying Bacterial Structure of Aerobic Granular Sludge using Image Analysis’ aims to quantitatively describe various aspects of cell activity inside aerobic granular sludge using image analysis. It entails the theory of aerobic granular sludge as well as that of image analysis, details the methods followed to obtain the results, and discusses those results in the context of available literature. A thorough review of the literature available on the topic is presented in order to identify knowledge gaps, long-standing hypotheses, and points on which studies have not reached a consensus. The main postulations that serve as a guiding theme for this project are ones pertaining to the modeling of aerobic granular sludge, particularly models based on strict concentric layers of microbial activity inside the granule. Further, to put some of these hypotheses to test, this project involves analyzing images of the available aerobic granular sludge, using a program developed for the specific goal of quantifying the bacterial structure of the granules. Using the open source software ImageJ, the program was written in such a manner that it accurately identifies the contour of the granule and stores, for every pixel, the intensity and the shortest distance from the edge. The numerical results from 2D slices and 3D stacks of images of granules were then used to generate graphs that allow for the quantification of cell activity inside the granule. Image analysis was also used to investigate different aspects of the granules such as their shape and the positions of different types of bacteria. The results allow to put in question some of the hypotheses used to model aerobic granular sludge and substantiate others, especially more recent ones that have shown the granules as having a more complex interior than previously modeled. The results also show the likelihood of a homogeneous interior with sustained cell activity even at the deepest parts of the granules, a clustering of high-density cells near the edge, and a non-spherical shape common between granules. Additionally, this project discusses the advantages and disadvantages of using the method of shortest distance from the edge and of analyzing granules in three dimensions. Finally, this report includes the codes of the aforementioned image analysis program and instructions to running them in order to obtain accurate results for any images or stacks of images of aerobic granular sludge.