Voltage-gated calcium flux mediates Escherichia coli mechanosensation.
Giancarlo Noe BruniR Andrew WeekleyBenjamin J T DoddJoel M KraljPublished in: Proceedings of the National Academy of Sciences of the United States of America (2017)
Electrically excitable cells harness voltage-coupled calcium influx to transmit intracellular signals, typically studied in neurons and cardiomyocytes. Despite intense study in higher organisms, investigations of voltage and calcium signaling in bacteria have lagged due to their small size and a lack of sensitive tools. Only recently were bacteria shown to modulate their membrane potential on the timescale of seconds, and little is known about the downstream effects from this modulation. In this paper, we report on the effects of electrophysiology in individual bacteria. A genetically encoded calcium sensor expressed in Escherichia coli revealed calcium transients in single cells. A fusion sensor that simultaneously reports voltage and calcium indicated that calcium influx is induced by voltage depolarizations, similar to metazoan action potentials. Cytoplasmic calcium levels and transients increased upon mechanical stimulation with a hydrogel, and single cells altered protein concentrations dependent on the mechanical environment. Blocking voltage and calcium flux altered mechanically induced changes in protein concentration, while inducing calcium flux reproduced these changes. Thus, voltage and calcium relay a bacterial sense of touch and alter cellular lifestyle. Although the calcium effectors remain unknown, these data open a host of new questions about E. coli, including the identity of the underlying molecular players, as well as other signals conveyed by voltage and calcium. These data also provide evidence that dynamic voltage and calcium exists as a signaling modality in the oldest domain of life, and therefore studying electrophysiology beyond canonical electrically excitable cells could yield exciting new findings.
Keyphrases
- escherichia coli
- induced apoptosis
- cell cycle arrest
- emergency department
- type diabetes
- multidrug resistant
- electronic health record
- physical activity
- machine learning
- spinal cord injury
- cell death
- spinal cord
- cystic fibrosis
- climate change
- big data
- small molecule
- deep learning
- cell proliferation
- artificial intelligence
- endoplasmic reticulum stress
- signaling pathway
- klebsiella pneumoniae
- endothelial cells
- data analysis
- human health