Bacterial Cell Growth Analysis and Cell Division Time Determination using Fuzzy Inference System

One of the important characteristics of a bacterial population growth is the cell division times during cell growth. This aspect is useful for antibiotic drug susceptibility tests conducted during drug design for effective control of diseases caused by the bacteria. The objective of the present study is to develop an automated tool to determine the bacterial cell growth phases and division time of the individual cell of a bacterial population. The proposed strategy is to capture digital images of cells growing on agar and to use changes in the dimensions of each cell to identify a parameter that could be used to estimate the division time. The geometric features of cells are used to estimate the cell size properties, which are useful for cell division time determination. The classification of cell growth phases has been done using fuzzy inference system. The experimentation has been done for two cell species, namely, E. coli and S. aureus. The proposed method is expected to be useful in drug design and antibiotic susceptibility tests. The experimental results are compared with the manual results obtained by the microbiology expert and demonstrate the efficacy of the proposed method