Investigating the Influence of Bacterial Cell Characteristics on M13 Phage Infection Process

Abstract

Microbial communities are fundamental to ecosystem health and biodiversity, affecting environments from soil to human microbiomes. Bacteriophages, or phages, are vital components of these communities, shaping bacterial dynamics and genetic diversity through mechanisms like gene transfer. Traditional population-level studies, while informative, can obscure the detailed behaviors and interactions present at the individual cell level. This research seeks to mitigate this oversight by applying single-cell analysis techniques to explore the M13 phage infection process.

Focusing specifically on the interactions between the M13 bacteriophage and E. coli, this research employs time-lapse microscopy to investigate how individual bacterial cell characteristics— size, elongation rate, and spatial positioning—impact phage infection susceptibility. The experimental approach incorporates both microfluidic devices and agar pads to compare the effects of direct phage introduction versus in-situ phage production within mixed bacterial cultures. Image processing was conducted using the Ilastik and CellProfiler software, extracting vital cellular metrics, such as size, shape, elongation rate, and spatial distribution, for analysis. Subsequent post-processing, performed with custom MATLAB scripts, generated lineage trees for individual cells, enabling tracking and analysis of cellular behavior over time.

Experimental results demonstrate that E. coli cells exhibiting higher elongation rates and larger sizes were notably more susceptible to M13 phagemid infection. This correlation underscores the significance of physical and physiological cell properties in the infection process. Moreover, this research extends its analysis through computational simulations employing the CellModeller platform, to investigate the M13 bacteriophage infection process beyond what is observable in laboratory experiments. The simulations are particularly concentrated on assessing how variations in phage diffusion rates impact the spatial patterns of infection, especially regarding the proximity of infected cells to those producing phages. The simulation results from this study highlight that an increase in the phage diffusion rate leads to a decrease in the distance between infected cells and those producing phages, suggesting that higher diffusion rates facilitate wider spread and more uniform distribution of the phage within the bacterial population. This pattern is consistent with the hypothesis that phage mobility plays a critical role in the dynamics of infection spread.