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Record W4402507137 · doi:10.1021/acsomega.4c06360

Biochemical Properties of CARM1: Impact on Western Blotting and Proteomic Studies

2024· article· en· W4402507137 on OpenAlexafffund
Julie Bourassa, Geneviève Paris, Laura Trinkle‐Mulcahy, Jocelyn Côté

Bibliographic record

VenueACS Omega · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related gene regulation
Canadian institutionsUniversity of Ottawa
FundersCanadian Institutes of Health ResearchCure SMA
KeywordsBlotProteomicsComputational biologyBiologyBiochemistry

Abstract

fetched live from OpenAlex

CARM1 is an arginine methyltransferase that has crucial roles in a number of cellular pathways and is being explored as a therapeutic target in diseases such as cancer and neurodegenerative disorders. Its deregulation at the protein level was found to have potential prognostic value, and as such, its protein levels are regularly assessed through the common practice of western blotting (WB). Our group uncovered that CARM1 has biochemical properties that complicate its analysis by standard WB sample preparation techniques. Here, we show that CARM1 has the ability to form SDS-resistant aggregates that effectively hinder gel migration in SDS-PAGE. CARM1 levels and the temperature at the denaturation step can both influence CARM1 aggregation, which prompts the use of additional measures to ensure representative detection at the protein level. We have demonstrated the formation of CARM1 aggregates in both cell and tissue extracts, making these findings an important consideration for any CARM1-related study. We also show how aggregate formation in models of CARM1 overexpression can hinder proteomic studies. Having identified factors that can induce CARM1 aggregation, we suggest alternative sample preparation techniques that allow for clear resolution of the protein in stringent denaturing conditions while avoiding aggregation.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.020
Threshold uncertainty score0.310

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.020
GPT teacher head0.296
Teacher spread0.277 · 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 teacher head, 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
Published2024
Admission routes2
Has abstractyes

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