Mechanotaxis directs Pseudomonas aeruginosa twitching motility

The opportunistic pathogen Pseudomonas aeruginosa explores surfaces using twitching motility powered by retractile extracellu-lar filaments called type IV pili (T4P). Single cells twitch by sequen-tial T4P extension, attachment, and retraction. How single cells coordinate T4P to efficiently navigate surfaces remains unclear. We demonstrate that P. aeruginosa actively directs twitching in the direction of mechanical input from T4P in a process called mechanotaxis. The Chp chemotaxis-like system controls the bal-ance of forward and reverse twitching migration of single cells in response to the mechanical signal. Collisions between twitching cells stimulate reversals, but Chp mutants either always or never reverse. As a result, while wild-type cells colonize surfaces uni-formly, collision-blind Chp mutants jam, demonstrating a function for mechanosensing in regulating group behavior. On surfaces, Chp senses T4P attachment at one pole, thereby sensing a spatially resolved signal. As a result, the Chp response regulators PilG and PilH control the polarization of the extension motor PilB. PilG stim-ulates polarization favoring forward migration, while PilH inhibits polarization, inducing reversal. Subcellular segregation of PilG and PilH efficiently orchestrates their antagonistic functions, ultimately enabling rapid reversals upon perturbations. The distinct localiza-tion of response regulators establishes a signaling landscape known as local excitation-global inhibition in higher-order organ-isms, identifying a conserved strategy to transduce spatially resolved signals.

Quantitative single cell dynamics of signaling and transcriptional response in mammalian cells

Onur Tidin

Cells live in ever-changing environments, thereby facing a variety of dynamic environmental signals. Environmental stimuli elicit intracellular responses through signaling pathways, which converge on transcriptional activation or repression of target genes. Despite intensive research, dissecting the complex interactions between pathway components that modulate mRNA and protein production still remains a difficult task. To this end, single-cell approaches provide unique insights into intracellular processes and cell responses to environmental stimuli, otherwise inaccessible with traditional bulk studies. Single-cell measurements have revealed that isogenic cells sharing the same environment display substantial heterogeneity in both transcript and protein level. As the initial step in gene expression, transcription is an important source of such variability in eukaryotic cells due to low number of molecules involved, transcription factor dynamics and the discrete nature of biochemical reactions. Notably, production of mRNA during transcription occurs in short periods of activity, termed as transcriptional bursts, followed by longer periods of inactivity. Despite widespread observations of transcriptional dynamics in mammals, upstream molecular mechanisms shaping the eukaryotic transcription remained elusive. In this study, we quantitatively linked upstream factors and transcriptional kinetics by developing an experimental system to temporally monitor, simultaneously, inputs (transcription factors) and outputs (target gene expression) in mammalian cells, in response to stimulus. We established two Tet-On inducible stable cell lines each expressing a fusion protein of a luminescence (Nanoluciferase) reporter to either SMAD4 or SMAD2, the two main transcrip- tion factors downstream of the TGF-Î² pathway. These cell lines that also contain a short-lived firefly luciferase reporter for the expression of the target endogenous connective tissue growth factor (ctgf ) gene allowed us to quantitatively link nuclear accumulation of SMADs upon TGF-Î² stimulation to the target gene expression in real-time single cell measurements. Time- lapse luminescence microscopy and image analysis with the custom developed CAST (Cell Automated Segmentation and Tracking platform) platform provided quantitative single-cell data to link the upstream transcription factor profile to its target gene activity. The data revealed weak single-cell correlations between translocation level and the target gene expression response which suggests a mechanism in which the translocation of SMADs initiates the transcriptional response but affects the response amplitude minimally. However, SMAD4 expression levels influenced the target gene response dynamics such that cells with high SMAD4 abundance favored to respond in a more sustained and even oscillatory manner. This suggests a mechanism consisting of a dynamic interplay between the transcriptional activators and feedback mechanisms in TGF-Î² signaling. We explored further the effect of different factors such as ligand concentration, ligand type on both signaling and target gene response. Taken together, this study proposes an experimental and quantitative framework that dissect mechanisms underlying transcriptional response to stimulus.

EPFL2018

Quantitative single cell dynamics of signaling and transcriptional response in mammalian cells

Onur Tidin

EPFL2018