Phenotypic heterogeneity can have important functional consequences, it can provide individuals and groups with new functionality, and it can also enable survival in stressful conditions such as lack of oxygen and nutrients or antibiotic influence. The emergence of resistance to existing antituberculous therapy has led to the recognition of phenotypic heterogeneity as an important research focus. Mycobacterium smegmatis is a rapidly growing non-pathogenic bacterium that serves as a model for the pathogen Mycobacterium tuberculosis, which is the major cause of tuberculosis. During the infection, fatty acid metabolism in mycobacteria is particularly important. Understanding fatty acid metabolism with odd number of C atoms, methylcitrate cycle and the importance of the prp gene stimulated studies on a propionate-containing media. Using timelapse fluorescent microscopy and movie processing on BactImAS platform, it was possible to study the expression of prp genes and other parameters in time and to observe phenotypic heterogeneity in our experiments. The results were analyzed by cell-to-cell analysis and bulk analysis. In this thesis, in five experiments with the same conditions, the heterogeneity of M. smegmatis was noticed, meaning that the individual cells differed with respect to the expression of genes and other phenotypic traits. There was a difference in the rate of adjustment and the strength of green fluorescence, that corresponds to prp expression level, in individual cells within the same experiment. Sister cells show the difference in the rate of growth and division, cell surface size and number of offspring. In most cases it has been shown that one sister cell inherits faster growth, shorter division time and it has a stronger gene expression. Given the proven heterogeneity, it is not possible to set the exact patterns and rules that apply to the expression of the prp gene in the presence of propionate. No correlation of genetic expression with cell size, growth rate, number of offspring and other investigated parameters has been demonstrated. BactImAS software is a great discovery for mycobacterial analysis. Active usage of the program has been improved and shortcomings are corrected. This work opens up many questions, and the need for new analyses and the exploitation of BactImAS in the study of mycobacteria and heterogeneity.