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Record W4323351225 · doi:10.1093/jcag/gwac036.059

A59 GLOBAL PROTEOMIC PROFILING OF HUMAN COLONOID MONOLAYERS UNDERGOING IN VITRO CHRONIC DAMAGE

2023· article· en· W4323351225 on OpenAlexaff
S Sandilya, T Steiner, P Lange, William D. Rees

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolomics and Mass Spectrometry Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsProteomicsProteomeCell biologyBiologyChemistryMolecular biologyBioinformaticsBiochemistryGene

Abstract

fetched live from OpenAlex

Abstract Background An in vitro damage model has been established in our lab using human colonoids grown as 2D monolayers. Upon being subjected to repeated rounds of air-liquid interface (ALI) growth and injury by submergence, these colonoid monolayers lost their barrier integrity and regrowth potential. Changes in mRNA expression and DNA methylation in genes from this human model of injury were similar to those that occur in Inflammatory Bowel Disease (IBD) and colon cancer. Significant morphological changes were observed in these monolayers after they were subjected to subsequent rounds of submergence injury, compared to when they were differentiated in ALI. Purpose Submergence injury is predicted to be involved in unfolded protein response (UPR) activation which can specifically alter translation. Hence proteomics studies will help undertand these changes. Method To determine if these changes are mirrored in the proteomes of damaged colonoids, we employed a Single-Plot, Solid-Phase-enhanced Sample Preparation (SP3) technology for Mass Spectrometry (MS) based proteomics analysis to characterize these monolayers at baseline, once they were differentiated in ALI, after one and five rounds of injury after differentiation in ALI, and after stimulation with the Toll-like receptor 5 (TLR5) agonist FliC. Hierarchical clustering, enrichment analysis, volcano plot analysis after pre-processing and normalization of the proteomics data set revealed differentially expressed proteins across various groups of monolayers. Result(s) Preliminary proteomic data analysis revealed changes in the profile of proteins involved in cellular differentiation, mitochondrial proteins, hypoxia upregulated proteins, those responsible for the maintenance and reorganization of the cytoskeletal structure and Golgi structure. These changes in protein profile may account for the significant morphological changes observed in these monolayers when subjected to submergence injury. Some outliers in monolayers subjected to microbial stimulation included proteins involved in regulation of extracellular matrix dependent motility and components of Adaptor Protein Complexes. Further studies are needed to ascertain if these account for the protective effect of FliC on these monolayers. Conclusion(s) This study suggests that the submergence injury to these healthy human derived colonoid monolayers leads to changes in their protein profile which mirror those seen in case of acute and chronic inflammation like IBD and colon cancer. It corroborates with the findings of gene expression and epigenetic analyses using the in vitro model established in our lab. Please acknowledge all funding agencies by checking the applicable boxes below CCC Disclosure of Interest None Declared

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)0.000
metaresearch head score (Gemma)0.000
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.242
Teacher spread0.234 · 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
Published2023
Admission routes1
Has abstractyes

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