Abstract
We review the contribution of bioimaging in building a coherent understanding of Ca signalling during legume-bacteria symbiosis. Currently, two different calcium signals are believed to control key steps of the symbiosis: a Ca gradient at the tip of the legume root hair is involved in the development of an infection thread, while nuclear Ca oscillations, the hallmark signal of this symbiosis, control the formation of the root nodule, where bacteria fix nitrogen. Additionally, different Ca spiking signatures have been associated with specific infection stages. Bioimaging is intrinsically a cross-disciplinary area that requires integration of image recording, processing and analysis. We used experimental examples to critically evaluate previously-established conclusions and draw attention to challenges caused by the varying nature of the signal-to-noise ratio in live imaging. We hypothesise that nuclear Ca spiking is a wide-range signal involving the entire root hair and that the Ca signature may be related to cytoplasmic streaming.
Highlights
Nitrogen is the most common limiting nutrient for plant growth, but a particular class of plants, legumes, can overcome this limitation with the help of bacteria [1,2]
We have considered some of the fundamental imaging studies that have informed the current understanding of Ca2+ signalling during the initiation of legume-bacteria symbiosis
Each of them contributed to the construction of a coherent narrative of symbiotic calcium signalling based on imaging
Summary
Nitrogen is the most common limiting nutrient for plant growth, but a particular class of plants, legumes, can overcome this limitation with the help of bacteria [1,2]. The root hair tip swells and curls to entrap the bacteria (see Figure 1), which enter the root upon the formation of a plant-made tunnel-like structure called the infection thread. With the development of fluorescent calcium sensors, live imaging has revealed diverse spatiotemporal Ca2+ dynamics [5,6,7,8,9] This has profoundly impacted the field, as it indicated where to look for the components of the Ca2+ signalling machinery. In this case, the primary regions of interest are the root hair tip that curls to entrap bacteria and the nucleus where transcription takes place. This review will provide examples of how implicit assumptions in image processing and analysis can bias the images we see
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