Background

Pilus-mediated twitching motility represents a form of surface-associated bacterial movement that is independent of flagella. Twitching motility is utilized by many bacterial pathogens, including Neisseria gonorrhoeae and Pseudomonas aeruginosa, to interact with moist surfaces and translocate epithelial barriers. In P. aeruginosa, twitching motility is regulated by a large number of genes which allow both extension and retraction of type IV pili to effectively drag the bacterial cell across any given surface in response to environmental cues (Mattick, 2002; Whitchurch et al., 2004; Burrows, 2005). In our studies of P. aeruginosa pathogenesis, twitching motility contributes to bacterial exit from epithelial cells after internalization and bacterial traversal of multilayered corneal epithelia (Alarcon et al., 2009). In a murine model of corneal infection, twitching motility was important for P. aeruginosa virulence (Zolfaghar et al., 2003). Recently, we discovered that the glycoprotein DMBT1 found in mucosal fluids such as human tears and saliva was capable of inhibiting P. aeruginosa twitching motility (Li et al., 2017). In that study, we utilized a novel method to quickly and robustly quantify P. aeruginosa twitching motility. That protocol is presented herein.

The most direct way to quantify twitching motility would be to track all individual bacteria over time. This method was attempted as part of our original study. However, bacterial colonies have a complex 3D structure, with bacteria regularly traversing one another, making tracking feasible only near the colony edge, resulting in sampling bias. Previous methods for quantifying twitching motility also quantified motility only at the colony edge (Alarcon et al., 2009; Semmler et al., 1999). For our study, we wished to extend those methods to be able to quantify twitching behavior throughout a dense bacterial colony. Instead of focusing on the direction of motility, we focused on quantifying the degree of motility at any given point. This turned out to be a simpler problem to solve, since as bacteria move, they modulate light as they pass through a given point. By mapping out the relative magnitudes of this modulation over time, we were able to generate maps of regions of relatively high and low motility in dense, spatially complex colonies.