Multiple N-glycans cooperate in balancing misfolded BRI1 secretion and ER retention

In-Depth Analysis of the N-Glycome of Colorectal Cancer Cell Lines

Colorectal cancer (CRC) is the third most commonly diagnosed cancer and the second leading cause of cancer deaths worldwide. A well-known hallmark of cancer is altered glycosylation. Analyzing the N-glycosylation of CRC cell lines may provide potential therapeutic or diagnostic targets. In this study, an in-depth N-glycomic analysis of 25 CRC cell lines was conducted using porous graphitized carbon nano-liquid chromatography coupled to electrospray ionization mass spectrometry. This method allows for the separation of isomers and performs structural characterization, revealing profound N-glycomic diversity among the studied CRC cell lines with the elucidation of a number of 139 N-glycans. A high degree of similarity between the two N-glycan datasets measured on the two different platforms (porous graphitized carbon nano-liquid chromatography electrospray ionization tandem mass spectrometry (PGC-nano-LC-ESI-MS) and matrix-assisted laser desorption/ionization time of flight-mass spectrometry (MALDI-TOF-MS)) was discovered. Furthermore, we studied the associations between glycosylation features, glycosyltransferases (GTs), and transcription factors (TFs). While no significant correlations between the glycosylation features and GTs were found, the association between TF CDX1 and (s)Le antigen expression and relevant GTs FUT3/6 suggests that CDX1 contributes to the expression of the (s)Le antigen through the regulation of FUT3/6. Our study provides a comprehensive characterization of the N-glycome of CRC cell lines, which may contribute to the future discovery of novel glyco-biomarkers of CRC.

The functional specificity of ERECTA-family receptors in Arabidopsis stomatal development is ensured by molecular chaperones in the endoplasmic reticulum

Stomata are epidermal pores that control gas exchange between plants and the atmosphere. In Arabidopsis, the ERECTA family (ERECTAf) receptors, including ERECTA, ERECTA-LIKE 1 (ERL1) and ERL2, redundantly play pivotal roles in enforcing the 'one-cell-spacing' rule. Accumulating evidence has demonstrated that the functional specificities of receptors are likely associated with their differential subcellular dynamics. The endoplasmic reticulum (ER)-resident chaperone complex SDF2-ERdj3B-BiP functions in many aspects of plant development. We employed pharmacological treatments combined with cell biological and biochemical approaches to demonstrate that the abundance of ERECTA was reduced in the erdj3b-1 mutant, but the localization and dynamics of ERECTA were not noticeably affected. By contrast, the erdj3b mutation caused the retention of ERL1/ERL2 in the ER. Furthermore, we found that the function of SDF2-ERdj3B-BiP is implicated with the distinct roles of ERECTAf receptors. Our findings establish that the ERECTAf receptor-mediated signaling in stomatal development is ensured by the activities of the ER quality control system, which preferentially maintains the protein abundance of ERECTA and proper subcellular dynamics of ERL1/ERL2, prior to the receptors reaching their destination - the plasma membrane - to execute their functions.

Identification and characterization of the LRR repeats in plant LRR-RLKs

Background

Leucine-rich-repeat receptor-like kinases (LRR-RLKs) play central roles in sensing various signals to regulate plant development and environmental responses. The extracellular domains (ECDs) of plant LRR-RLKs contain LRR motifs, consisting of highly conserved residues and variable residues, and are responsible for ligand perception as a receptor or co-receptor. However, there are few comprehensive studies on the ECDs of LRR-RLKs due to the difficulty in effectively identifying the divergent LRR repeats.

Results

In the current study, an efficient LRR motif prediction program, the “Phyto-LRR prediction” program, was developed based on the position-specific scoring matrix algorithm (PSSM) with some optimizations. This program was trained by 16-residue plant-specific LRR-highly conserved segments (HCS) from LRR-RLKs of 17 represented land plant species and a database containing more than 55,000 predicted LRRs based on this program was constructed. Both the prediction tool and database are freely available at http://phytolrr.com/ for website usage and at http://github.com/phytolrr for local usage. The LRR-RLKs were classified into 18 subgroups (SGs) according to the maximum-likelihood phylogenetic analysis of kinase domains (KDs) of the sequences. Based on the database and the SGs, the characteristics of the LRR motifs in the ECDs of the LRR-RLKs were examined, such as the arrangement of the LRRs, the solvent accessibility, the variable residues, and the N-glycosylation sites, revealing a comprehensive profile of the plant LRR-RLK ectodomains.

Conclusion

The “Phyto-LRR prediction” program is effective in predicting the LRR segments in plant LRR-RLKs, which, together with the database, will facilitate the exploration of plant LRR-RLKs functions. Based on the database, comprehensive sequential characteristics of the plant LRR-RLK ectodomains were profiled and analyzed.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12860-021-00344-y.