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Initially discovered in yeast, mitochondrial retrograde signalling has long been recognised as an essential in the perception of stress by eukaryotes. However, how to maintain the optimal amplitude and duration of its activation under natural stress conditions remains elusive in plants. Here, we show that TaSRO1, a major contributor to the agronomic performance of bread wheat plants exposed to salinity stress, interacted with a transmembrane domain-containing NAC transcription factor TaSIP1, which could translocate from the endoplasmic reticulum (ER) into the nucleus and activate some mitochondrial dysfunction stimulon (MDS) genes. Overexpression of TaSIP1 and TaSIP1-∆C (a form lacking the transmembrane domain) in wheat both compromised the plants' tolerance of salinity stress, highlighting the importance of precise regulation of this signal cascade during salinity stress. The interaction of TaSRO1/TaSIP1, in the cytoplasm, arrested more TaSIP1 on the membrane of ER, and in the nucleus, attenuated the trans-activation activity of TaSIP1, therefore reducing the TaSIP1-mediated activation of MDS genes. Moreover, the overexpression of TaSRO1 rescued the inferior phenotype induced by TaSIP1 overexpression. Our study provides an orchestrating mechanism executed by the TaSRO1-TaSIP1 module that balances the growth and stress response via fine tuning the level of mitochondria retrograde signalling.

Plant cells have two endosymbiotic organelles, chloroplasts, and mitochondria. These organelles perform specific functions that depend on organelle-specific proteins. The majority of chloroplast and mitochondrial proteins are specifically imported by the transit peptide and presequence, respectively. However, a significant number of proteins are also dually targeted to these two organelles. Currently, it is not fully understood how proteins are dually targeted to both chloroplasts and mitochondria. In this study, the mechanism underlying mitochondrial targeting of dual targeting AtSufE1 in Arabidopsis was elucidated. The N-terminal fragment containing 80 residues of AtSufE1 (AtSufE1N80) was sufficient to confer dual targeting of reporter protein, AtSufE1N80:GFP, in protoplasts. Two sequence motifs, two arginine residues at 15

Chloroplasts and mitochondria are subcellular organelles that evolved from cyanobacteria and α-proteobacteria, respectively. Although they have their own genomes, the majority of their proteins are encoded by nuclear genes, translated by cytosolic ribosomes, and imported via outer and inner membrane translocon complexes. The unfolding of mature regions of proteins is thought to be a prerequisite for the import of the proteins into these organelles. However, it is not fully understood how protein folding properties affect their import into these organelles. In this study, we examined the import behavior of chloroplast and mitochondrial reporters with normal green fluorescent protein (GFP) and two GFP variants with enhanced folding propensity, superfolder GFP (sfGFP) and extra-superfolder GFP (esGFP), which is folded better than sfGFP. sfGFP and esGFP were less dependent on the sequence motifs of the transit peptide (TP) and import machinery during protein import into Arabidopsis (Arabidopsis thaliana) chloroplasts, compared with normal GFP. sfGFP and esGFP were efficiently imported into chloroplasts by a mutant TP with an alanine substitution in the N-terminal MLM motif, whereas the same mutant TP showed a defect in importing normal GFP into chloroplasts. Moreover, sfGFP and esGFP were efficiently imported into plastid protein import 2 (ppi2) and heat shock protein 93-V (hsp93-V) plants, which have mutations in atToc159 and Hsp93-V, respectively. In contrast, the presequence-mediated mitochondrial import of sfGFP and esGFP was severely impaired. Based on these results, we propose that the chloroplast import machinery is more tolerant to different folding states of preproteins, whereas the mitochondrial machinery is more specialized in the translocation of unfolded preproteins.

This paper presents a theoretical basis to realize a high-quality digital zooming using two camera modules with different focal lengths. First, we describe an image degradation model of the asymmetric dual camera system to analyze the characteristic of the wide- and tele-view images. In an asymmetric dual camera system, we assume that the shorter focal length module produces the wide-view image with the low-resolution. On the other hand, the longer focal length module produces the tele-view image by an optical zooming. To reconstruct a wide-view image of a continuous digital zooming, the proposed method first estimates the point spread function (PSF) between the wide- and tele-view images. Next, the proposed method performs variational-based image restoration using the estimated PSF. In addition, since the tele-view image inserted into appropriate region of the wide-view image, the proposed method can provide significantly improved wide-view image.

This paper presents a novel variational framework for low-light image enhancement. The proposed enhancement algorithm simultaneously performs brightness enhancement and noise reduction using a variational optimization. An edge-preserved noise reduction is performed by minimizing the total variation constraint term in the energy function. In addition, the proposed method estimates the optimal transmission map to restore the low-light image by minimizing the l 2 -norm smoothness and data-fidelity terms. To minimize the proposed energy functional, the proposed method splits the l 1 -derivative term under the split Bregman iteration framework. The performance of the proposed method is evaluated using both simulated and natural low-light images. Experimental results show that the proposed enhancement method can significantly improve the quality of the low-light images without noise amplification.

Asymmetric dual camera system needs a preprocessing for registration in two input images due to the difference of brightness and color information. To solve this problem, this paper presents a framework that corrects the brightness and color between two input images. The proposed framework consists of three steps : i) selection of the reference and source images based on the contrast, ii) brightness enhancement using the brightness compensation map to minimize the difference of average brightness level of two input images, and iii) color correction of source image using color information of the reference image to compensate the disparity based on the illumination condition and exposure parameters. Experimental results show that proposed brightness and color correction method improves the performance of image registration in an asymmetric dual camera system.

Existing sparse representation model uses image statistics in the form of neighborhood correlation, learning algorithm for use of redundant dictionary, etc. The ill-posed nature of the problem means that there is no exact solution so any solution is an approximate of the actual solution and this often leads to discrepancy in the form of degradation as global smoothing of the final high resolution image. In our paper we propose overcome this drawback by using point spread function (PSF) or blur prior which will remove the degradations to give us an final super enhanced high resolution image. The PSF prior is integrated in to the SRM thereby preserving the computational complexity. The experimental results using the proposed method is compared with the existing state of the art methods for performance comparison.

This paper presents a super-resolution (SR) method for the asymmetric dual-camera system. The proposed method restores the high-resolution (HR) image using the local self-similarity between two input images as wide- and tele-view images. The proposed method consists of three steps: i) registration and warping processes to reduce the disparity between the input images, ii) high-frequency patch extraction from the tele-view image, and iii) super-resolution reconstruction using local self-similarity property. Experimental results show that the proposed method can significantly restore the HR image than existing interpolation and SR methods.