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Record W4409710287 · doi:10.1101/2025.04.17.647851

Molecular and Epigenetic Pathways Underlying Epithelial Damage and Repair in Necrotizing Enterocolitis via Multi-omics Approach

2025· preprint· en· W4409710287 on OpenAlexafffund
Yi Xiong, Andrea Zito, George Biouss, Jielin Yang, Felicia Balsamo, M Yeganeh, Carol Lee, Dorothy Lee, Chenyi Wang, Nareh Tahmasian, Jinling Huang, Adam Minich, Mehrsa Feizi, Shiwen Wang, Yina Tian, Paolo De Coppi, Brian T. Kalish, Paul Delgado-Olguı́n, Haitao Zhu, Bo Li, Agostino Pierro

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Languageen
FieldNursing
TopicInfant Nutrition and Health
Canadian institutionsSunnybrook HospitalUniversity of TorontoHeart and Stroke FoundationSunnybrook Health Science CentreMental Health Research CanadaHospital for Sick Children
FundersCanadian Institutes of Health ResearchShanghai Science and Technology Development FoundationXiamen Municipal Bureau of Science and Technology
KeywordsNecrotizing enterocolitisEpigeneticsOmicsComputational biologyBiologyBioinformaticsMedicineGeneticsGeneInternal medicine

Abstract

fetched live from OpenAlex

Abstract Introduction Neonatal necrotizing enterocolitis (NEC) is a severe gastrointestinal disorder with high mortality, characterized by epithelial cell injury and compromised epithelial repair. The mechanisms underlying defective epithelial regeneration remain poorly understood despite advances in single-cell omics. Addressing these challenges is essential for elucidating the pathogenesis of NEC and identifying therapeutic targets to restore epithelial regeneration and replace the damaged epithelial layer. Methods Multi-omics approaches were employed to investigate molecular and spatial changes in experimental NEC at epigenetic and transcriptomic levels. These included bulk RNA sequencing, single-nucleus RNA sequencing (snRNA-seq), single-nucleus assay for transposase-accessible chromatin sequencing (snATAC-seq), and multiplexed error-robust fluorescence in situ hybridization (MERFISH) for spatial transcriptomics. Complementary in vitro experiments and in vivo mouse models were utilized to evaluate NEC phenotypes, intestinal tissue morphology, and organoid formation. Results Changes in cell type composition, transcriptional network remodeling, and chromatin accessibility were observed in the small intestine of neonatal mice with NEC. Chromatin accessibility significantly changed in epithelial cells, highlighting their pivotal roles in NEC. A marked reduction in intestinal stem cells (ISCs) and transit-amplifying cells, along with an increased proportion of enteroendocrine cells, indicates disrupted epithelial regeneration and functional differentiation. These changes correlated with disrupted WNT signaling and stem cell maintenance genes (e.g., Lgr5, Smoc2, Axin2) and activation of inflammatory and hypoxia-related pathways (e.g., Il6, Tnfα). The epigenetic regulator Ezh2 was identified as a critical factor in maintaining LGR5+ ISCs and epithelial homeostasis. Knockdown of Ezh2 reduced stemness and proliferation-related gene expression and exacerbated inflammation. Reactivation of WNT signaling restored Ezh2 and Lgr5 expression, improving intestinal regeneration. Conclusion This study reveals dynamic transcriptomic, epigenetic, and spatial changes in NEC and highlights Ezh2 as a key regulator of LGR5+ intestinal stem cell function and epithelial regeneration. These findings provide insights into NEC pathogenesis and a basis for therapies targeting Ezh2 and WNT signaling to restore intestinal integrity. Abstract Figure

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.028
GPT teacher head0.259
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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