m<sup>6</sup>A reader YTHDC1 modulates autophagy by targeting SQSTM1 in diabetic skin
Bibliographic record
Abstract
Dysregulation of macroautophagy/autophagy contributes to the delay of wound healing in diabetic skin. N6-methyladenosine (m6A) RNA modification is known to play a critical role in regulating autophagy. In this study, it was found that SQSTM1/p62 (sequestosome 1), an autophagy receptor, was significantly downregulated in two human keratinocyte cells lines with short-term high-glucose treatment, as well as in the epidermis of diabetic patients and a db/db mouse model with long-term hyperglycemia. Knockdown of SQSTM1 led to the impairment of autophagic flux, which was consistent with the results of high-glucose treatment in keratinocytes. Moreover, the m6A reader protein YTHDC1 (YTH domain containing 1), which interacted with SQSTM1 mRNA, was downregulated in keratinocytes under both the acute and chronic effects of hyperglycemia. Knockdown of YTHDC1 affected biological functions of keratinocytes, which included increased apoptosis rates and impaired wound-healing capacity. In addition, knockdown of endogenous YTHDC1 resulted in a blockade of autophagic flux in keratinocytes, while overexpression of YTHDC1 rescued the blockade of autophagic flux induced by high glucose. In vivo, knockdown of endogenous Ythdc1 or Sqstm1 inhibited autophagy in the epidermis and delayed wound healing. Interestingly, we found that a decrease of YTHDC1 drove SQSTM1 mRNA degradation in the nucleus. Furthermore, the results revealed that YTHDC1 interacted and cooperated with ELAVL1/HuR (ELAV like RNA binding protein 1) in modulating the expression of SQSTM1. Collectively, this study uncovered a previously unrecognized function for YTHDC1 in modulating autophagy via regulating the stability of SQSTM1 nuclear mRNA in diabetic keratinocytes. Abbreviations: ACTB: actin beta; AGEs: glycation end products; AL: autolysosome; AP: autophagosome; ATG: autophagy related; AKT: AKT serine/threonine kinase; ANOVA: analysis of variance; BECN1: beclin 1; Co-IP: co-immunoprecipitation; DEGs: differentially expressed genes; DM: diabetes mellitus; ELAVL1: ELAV like RNA binding protein 1; FTO: FTO alpha-ketoglutarate dependent dioxygenase; G: glucose; HaCaT: human keratinocyte; GO: Gene Ontology; GSEA: Gene Set Enrichment Analysis; HE: hematoxylin-eosin; IHC: immunohistochemical; IRS: immunoreactive score; KEAP1: kelch like ECH associated protein 1; KEGG: Kyoto Encyclopedia of Genes and Genomes; m6A: N6-methyladenosine; M: mannitol; MANOVA: multivariate analysis of variance; MAP1LC3: microtubule associated protein 1 light chain 3; MAP1LC3B: microtubule associated protein 1 light chain 3 beta; MeRIP: methylated RNA immunoprecipitation; METTL3: methyltransferase 3, N6-adenosine-methytransferase complex catalytic subunit; MTOR: mechanistic target of rapamycin kinase; MTORC1: mechanistic target of rapamycin complex 1; NBR1: NBR1 autophagy cargo receptor; NFE2L2: nuclear factor, erythroid 2 like 2; NG: normal glucose; NHEK: normal human epithelial keratinocyte; OE: overexpressing; p-: phospho-; PI: propidium iodide; PPIN: Protein-Protein Interaction Network; RBPs: RNA binding proteins; RIP: RNA immunoprecipitation; RNA-seq: RNA-sequence; RNU6–1: RNA, U6 small nuclear 1; ROS: reactive oxygen species; siRNAs: small interfering RNAs; SQSTM1: sequestosome 1; SRSF: serine and arginine rich splicing factor; T2DM: type 2 diabetes mellitus; TEM: transmission electron microscopy; TUBB: tubulin beta class I; WT: wild-type; YTHDC1: YTH domain containing 1.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".