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A Regulatory Mechanism for Nuclear Lipid Droplet Biogenesis

2019· article· en· W3175303615 on OpenAlexafffundabout
Jong‐Hwa Lee, Jayme Salsman, Graham Dellaire, Neale D. Ridgway

Bibliographic record

VenueThe FASEB Journal · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid metabolism and biosynthesis
Canadian institutionsDalhousie University
FundersCanadian Institutes of Health Research
KeywordsLipid dropletEndoplasmic reticulumChemistryCell biologyBiogenesisPhospholipidPhosphocholinePromyelocytic leukemia proteinBiochemistryNuclear poreCytosolBiologyNuclear proteinPhosphatidylcholineEnzymeTranscription factorCytoplasmGene

Abstract

fetched live from OpenAlex

Lipid droplets (LDs) are metabolic energy reservoirs that store and release fatty acids in response to nutrient and hormonal signals. Cytosolic LDs (cLDs) are thought to form in the endoplasmic reticulum (ER) by a process that requires a coordinated synthesis of triglycerides (TG) and phosphatidylcholine (PC), the primary phospholipid component of the surface monolayer that stabilizes the neutral lipid core. Nuclear LDs (nLDs) are present in many eukaryotic cells, suggesting a related mechanism for nLD assembly that involves de novo phospholipid and TG synthesis on the inner nuclear membrane (INM). The rate‐limiting enzyme for PC synthesis, CTP:phosphocholine cytidylyltransferase α (CCTα), is activated by translocation to the INM and nLDs. As well, nLDs and CCTα associate with promyelocytic leukemia nuclear bodies (PML‐NBs). PML‐NBs are dynamic sub‐nuclear structures involved in regulating several important biological processes, including gene expression and oxidative stress response. The storage of TG in nLD/PML‐NB/CCTα complexes could buffer the nucleus against fatty acid overload and detect and respond to lipid stress via PML‐NB‐associated signaling pathways. In this study, we investigated how the nLD/PML‐NB/CCTα complex is formed during oleate treatment of human U2OS osteosarcoma cells and Caco2 colorectal adenocarcinoma cells. Super‐Resolution Radial Fluctuation (SRRF) imaging revealed that PML proteins and CCTα co‐localized in a bead‐like ring around the nLD. Quantitative fluorescence microscopy revealed that PML‐NBs and CCTα were localized on larger nLDs in both U2OS and Caco2 cells. Knocking out PML expression by CRISPR/Cas9 in U2OS cells (PML‐KO) resulted in fewer and smaller nLDs, and the remaining nLDs had a 40% reduction in associated CCTα. The size of CCTα‐positive nLDs in control and PML‐KO cells was comparable. In contrast, CRISPR/Cas9 knockout of CCTα in Caco2 cells (CCTα‐KO) increased the size and decreased the number of LDs, resulting in increased association of PML‐NBs with large nLDs. Collectively, these data suggest that PML‐NBs and CCTα are required for regulating the size and number of nLDs in response to exogenous oleate. Fatty acids promote the formation of large nLDs that interact with PML‐NBs. This interaction recruits CCTα to potentially stimulate CCTα activity and PC biosynthesis required for the surface monolayer. Support or Funding Information Canadian Institutes of Health Research This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.206
Teacher spread0.198 · 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
Published2019
Admission routes3
Has abstractyes

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