No abstract

Mechanical stimulation of plants can be caused by various abiotic and biotic environmental factors. Apart from the negative consequences, it can also cause positive changes, such as acclimatization of plants to stress conditions. Therefore, it is necessary to study the physiological and biochemical mechanisms underlying the response of plants to mechanical stimulation. Our aim was to evaluate the response of model plant Arabidopsis thaliana to a moderate force of 5 N (newton) for 20 s, which could be compared with the pressure caused by animal movement and weather conditions such as heavy rain. Mechanically stimulated leaves were sampled 1 h after exposure and after a recovery period of 20 h. To study a possible systemic response, unstimulated leaves of treated plants were collected 20 h after exposure alongside the stimulated leaves from the same plants. The effect of stimulation was assessed by measuring oxidative stress parameters, antioxidant enzymes activity, total phenolics, and photosynthetic performance. Stimulated leaves showed increased lipid peroxidation 1 h after treatment and increased superoxide dismutase activity and phenolic oxidation rate after a 20-h recovery period. Considering photosynthetic performance after the 20-h recovery period, the effective quantum yield of the photosystem II was lower in the stimulated leaves, whereas photochemical quenching was lower in the unstimulated leaves of the treated plants. Nonphotochemical quenching was lower in the stimulated leaves 1 h after treatment. Our study suggested that plants sensed moderate force, but it did not induce pronounced change in metabolism or photosynthetic performance. Principal component analysis distinguished three groups-leaves of untreated plants, leaves analysed 1 h after stimulation, while stimulated and unstimulated leaves of treated plants analysed 20 h after treatment formed together the third group. Observed grouping of stimulated and unstimulated leaves of treated plants could indicate signal transduction from the stimulated to distant leaves, that is, a systemic response to a local application of mechanical stimuli.

Single cell sequencing methods facilitate the study of tissues at high resolution, revealing rare cell types with varying transcriptomes or genomes, but so far have been lacking the capacity to investigate cell-cell interactions. Here, we introduce CIM-seq, an unsupervised and high-throughput method to analyze direct physical cell-cell interactions between every cell type in a given tissue. CIM-seq is based on RNA sequencing of incompletely dissociated cells, followed by computational deconvolution of these into their constituent cell types using machine learning. CIM-seq is broadly applicable to studies that aim to simultaneously investigate the constituent cell types and the global interaction profile in a specific tissue.

Single cell sequencing methods facilitate the study of tissues at high resolution, revealing rare cell types with varying transcriptomes or genomes, but so far have been lacking the capacity to investigate cell-cell interactions. Here, we introduce CIM-seq, an unsupervised and high-throughput method to analyze direct physical cell-cell interactions between every cell type in a given tissue. CIM-seq is based on RNA sequencing of incompletely dissociated cells, followed by computational deconvolution of these into their constituent cell types using machine learning. CIM-seq is broadly applicable to studies that aim to simultaneously investigate the constituent cell types and the global interaction profile in a specific tissue.