Physcomitrella patens MAX2 characterization suggests an ancient role for this F-box protein in photomorphogenesis rather than strigolactone signalling.

Strigolactones (SLs) are key hormonal regulators of flowering plant development and are widely distributed amongst streptophytes. In Arabidopsis, SLs signal via the F-box protein MORE AXILLARY GROWTH2 (MAX2), affecting multiple aspects of development including shoot branching, root architecture and drought tolerance. Previous characterization of a Physcomitrella patens moss mutant with defective SL synthesis supports an ancient role for SLs in land plants, but the origin and evolution of signalling pathway components are unknown. Here we investigate the function of a moss homologue of MAX2, PpMAX2, and characterize its role in SL signalling pathway evolution by genetic analysis. We report that the moss Ppmax2 mutant shows very distinct phenotypes from the moss SL-deficient mutant. In addition, the Ppmax2 mutant remains sensitive to SLs, showing a clear transcriptional SL response in dark conditions, and the response to red light is also altered. These data suggest divergent evolutionary trajectories for SL signalling pathway evolution in mosses and vascular plants. In P. patens, the primary roles for MAX2 are in photomorphogenesis and moss early development rather than in SL response, which may require other, as yet unidentified, factors.

A miR169 isoform regulates specific NF-YA targets and root architecture in Arabidopsis.

In plants, roots are essential for water and nutrient acquisition. MicroRNAs (miRNAs) regulate their target mRNAs by transcript cleavage and/or inhibition of protein translation and are known as major post-transcriptional regulators of various developmental pathways and stress responses. In Arabidopsis thaliana, four isoforms of miR169 are encoded by 14 different genes and target diverse mRNAs, encoding subunits A of the NF-Y transcription factor complex. These miRNA isoforms and their targets have previously been linked to nutrient signalling in plants. By using mimicry constructs against different isoforms of miR169 and miR-resistant versions of NF-YA genes we analysed the role of specific miR169 isoforms in root growth and branching. We identified a regulatory node involving the particular miR169defg isoform and NF-YA2 and NF-YA10 genes that acts in the control of primary root growth. The specific expression of MIM169defg constructs altered specific cell type numbers and dimensions in the root meristem. Preventing miR169defg-regulation of NF-YA2 indirectly affected laterial root initiation. We also showed that the miR169defg isoform affects NF-YA2 transcripts both at mRNA stability and translation levels. We propose that a specific miR169 isoform and the NF-YA2 target control root architecture in Arabidopsis.

Innovative prognostic modeling in ESCC: leveraging scRNA-seq and bulk-RNA for dendritic cell heterogeneity analysis.

Background: Globally, esophageal squamous cell carcinoma (ESCC) stands out as a common cancer type, characterized by its notably high rates of occurrence and mortality. Recent advancements in treatment methods, including immunotherapy, have shown promise, yet the prognosis remains poor. In the context of tumor development and treatment outcomes, the tumor microenvironment (TME), especially the function of dendritic cells (DCs), is significantly influential. Our study aims to delve deeper into the heterogeneity of DCs in ESCC using single-cell RNA sequencing (scRNA-seq) and bulk RNA analysis. Methods: In the scRNA-seq analysis, we utilized the SCP package for result visualization and functional enrichment analysis of cell subpopulations. CellChat was employed to identify potential oncogenic mechanisms in DCs, while Monocle 2 traced the evolutionary trajectory of the three DC subtypes. CopyKAT assessed the benign or malignant nature of cells, and SCENIC conducted transcription factor regulatory network analysis, offering a preliminary exploration of DC heterogeneity. In Bulk-RNA analysis, we constructed a prognostic model for ESCC prognosis and immunotherapy response, based on DC marker genes. This model was validated through quantitative PCR (qPCR) and immunohistochemistry (IHC), confirming the gene expression levels. Results: In this study, through intercellular communication analysis, we identified GALECTIN and MHC-I signaling pathways as potential oncogenic mechanisms within dendritic cells. We categorized DCs into three subtypes: plasmacytoid (pDC), conventional (cDC), and tolerogenic (tDC). Our findings revealed that pDCs exhibited an increased proportion of cells in the G2/M and S phases, indicating enhanced cellular activity. Pseudotime trajectory analysis demonstrated that cDCs were in early stages of differentiation, whereas tDCs were in more advanced stages, with pDCs distributed across both early and late differentiation phases. Prognostic analysis highlighted a significant correlation between pDCs and tDCs with the prognosis of ESCC (P< 0.05), while no significant correlation was observed between cDCs and ESCC prognosis (P = 0.31). The analysis of cell malignancy showed the lowest proportion of malignant cells in cDCs (17%), followed by pDCs (29%), and the highest in tDCs (48%), with these results being statistically significant (P< 0.05). We developed a robust ESCC prognostic model based on marker genes of pDCs and tDCs in the GSE53624 cohort (n = 119), which was validated in the TCGA-ESCC cohort (n = 139) and the IMvigor210 immunotherapy cohort (n = 298) (P< 0.05). Additionally, we supplemented the study with a novel nomogram that integrates clinical features and risk assessments. Finally, the expression levels of genes involved in the model were validated using qPCR (n = 8) and IHC (n = 16), thereby confirming the accuracy of our analysis. Conclusion: This study enhances the understanding of dendritic cell heterogeneity in ESCC and its impact on patient prognosis. The insights gained from scRNA-seq and Bulk-RNA analysis contribute to the development of novel biomarkers and therapeutic targets. Our prognostic models based on DC-related gene signatures hold promise for improving ESCC patient stratification and guiding treatment decisions.

The improved blood-brain barrier permeability of endomorphin-1 using the cell-penetrating peptide synB3 with three different linkages.

Endomorphins, although they have high analgesic activity and few undesirable side effects, are not in clinical use because of the blood-brain barrier (BBB). One promising solution is to use cell-penetrating peptides (CPPs). CPPs have the ability to translocate cell membranes and have been successfully applied for delivery of therapeutic molecules across the BBB. However, little is known about the transport efficiency of different conjugation strategies between cargo and CPPs. In this study, endomorphin-1 (EM-1) was conjugated with SynB3, an efficient CPP-carrier, via amide, maleimide and disulfide linkages. The delivery efficiency of three linkers was compared in terms of pharmacodynamics and in vitro metabolic stability. Near-infrared fluorescent and fluorescent microscopy experiments were applied to detect the brain uptake and distribution of CPP delivery qualitatively and quantitatively. After the most successful linkage was screened out, the further mechanisms were discussed. We concluded that compared with the other two linkages, the disulfide bond was the most efficient linkage to deliver EM-1 across the BBB and confirmed that it could be reduced at physiological conditions in the brain and release its active form. These findings indicate that for those who need to release a free drug in the brain and maintain activity, a disulfide bond might be the most efficient linkage across the BBB.