Tracking bacterial lineages in complex and dynamic environments with applications for growth control and persistence

Area of Science:

• Microbiology
• Cell Biology
• Systems Biology

Background:

• Bacteria exhibit significant changes in size, morphology, and gene expression during the transition from exponential to stationary growth phases.
• Individual cell responses to growth phase transitions vary, making it challenging to track cell lineages and understand dormancy entry/exit dynamics.
• Understanding cell size control and its correlation with dormancy and stress response is crucial for microbial physiology.

Purpose of the Study:

• To develop a high-throughput platform for tracking individual bacterial cell lineages through growth curves.
• To investigate the dynamics of cell size regulation during entry and exit from stationary phase in Escherichia coli and Bacillus subtilis.
• To correlate cell division patterns during stationary phase entry with dormancy survival and antibiotic resistance.

Main Methods:

• Developed a novel platform capable of tracking over 10^5 parallel bacterial cell lineages in dense, dynamic cultures.
• Validated that the tracked cell populations accurately represent the overall batch culture behavior.
• Analyzed cell size, division patterns, and survival rates of individual lineages throughout growth and dormancy.

Main Results:

• Bacterial growth mode shifts from 'adder' in exponential phase to a mix of 'adder-timers' entering stationary phase.
• Cells transition to a 'sizer' mode upon exiting stationary phase, rapidly narrowing cell size distribution.
• Cells undergoing more divisions upon entering stationary phase exhibit reduced long-term dormancy survival but enhanced persistence against antibiotics.

Conclusions:

• Bacterial cell size control mechanisms dynamically adapt to growth phases, influencing population heterogeneity.
• The mode of entry into stationary phase significantly impacts bacterial fate, including survival during dormancy and response to antibiotics.
• This study provides a powerful tool for dissecting complex cellular behaviors in microbial populations.