(222c) Pseudomonas Aeruginosa Single-Cell Level Heterogeneity, Investigated Via Drop-Based Microfluidics | AIChE

(222c) Pseudomonas Aeruginosa Single-Cell Level Heterogeneity, Investigated Via Drop-Based Microfluidics

Authors 

Pratt, S. - Presenter, Montana State University
Akiyama, T., Montana State University
Zath, G., Montana State University
Williamson, K., Montana State University
Franklin, M., Montana State University
Chang, C., Montana State University
Single cell microbial studies can be challenging using traditional microbiology methods; however, single cell studies are critical in understanding cell-to-cell heterogeneity for interpreting bulk microbial growth behavior. This is especially true in biofilms, or microbial communities that express high levels of population heterogeneity and exceptional resilience due to its heterogeneity. Drop-based microfluidics, or the formation and manipulation of picoliter-volume drops of water-in-oil allows for the encapsulation of single cells, providing a platform for single cell studies. In this work, populations of Pseudomonas aeruginosa are examined at the single cell level within microfluidic drops incubated on a microfluidic chip over a period of 24+ hours. Confocal microscopy tracks the expressed plasmid gfp fluorescence of the cells. The resulting data is used to construct growth curves starting from single cells and to quantify the growth rate and lag phase. Our long-term growth study is performed using a device preparation technique that fills the porous microfluidic device with water-saturated carrier oil and allows for thermodynamic stability between the oil and aqueous phases. In absence of this preparation, drops are observed to shrink, foam, or evaporate from the device over time. Bulk studies of P. aeruginosa cells reintroduced to media after 4 days of starvation shows decreased growth in resuscitating cells. However, single cell studies using this incubation method show that these cells have increased and variable lag phase lengths, rather than decreased specific growth rates (Akiyama, et.al. PNAS, 2017). Our results demonstrate the quantification and monitoring of single cell behavior over 24+ hours, which will allow for a deeper understanding of the role of heterogeneity in bacterial populations.