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Record W4245474533 · doi:10.32920/ryerson.14638659

The effects of Mitogenic and Metabolic cues on clathrin-mediated endocytosis

2021· preprint· en· W4245474533 on OpenAlexaff
Ralph Christian Delos Santos

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular transport and secretion
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsInternalizationEndocytosisCell biologyBiologyClathrinCalcium signalingCell growthCellSignal transductionBiochemistry

Abstract

fetched live from OpenAlex

The cell ‘surfaceome’ collectively describes proteins found on the plasma membrane (PM), which functions in fundamental cellular processes including growth and proliferation. The surfaceome undergoes dynamic remodeling via the addition/removal of surface proteins in response to changing environmental conditions. In mammalian cells, surfaceome remodeling is predominantly facilitated by clathrin-mediated endocytosis (CME) which involves the invagination and internalization of PM regions via clathrin-coated structures—removing proteins from the cell surface. As a major regulator of the surfaceome, it is important to understand the underlying mechanisms governing CME, given that its dysregulation has been implicated in human pathologies including neurologic and oncogenic disorders. Cellular cues including mitogenic (e.g. growth factors) and metabolic signals (e.g. cellular energy levels) induce diverse cellular processes (e.g. growth and proliferation) requiring surfaceome/PM remodeling. Precisely how mitogenic and metabolic signals may induce surfaceome remodeling however, is under-examined. As a major regulator of the surfaceome, CME is a likely mechanism through which cellular cues may remodel the PM. Poorly understood, I thus sought to investigate how mitogenic and metabolic signals may regulate CME. Mitogenic signaling by the epidermal growth factor receptor (EGFR) triggers PLCγ1-calcium signals, which I found a requirement for CME of EGFR—likely via calcium control of the Sjn1 protein. Consistently, using TIRF-M imaging coupled to automated software analysis, I demonstrate that inhibition of PLCγ1-calcium signals impairs the formation/assembly of GFR-containing clathrin structures. In addition, I hypothesize that PLCγ1-calcium signals also regulates the CME of other surface proteins given its robust control of Sjn1—which localizes broadly amongst clathrin-coated structures. AMPK is a cellular energy sensor activated by metabolic stress (e.g. starvation). Using TIRF-M imaging coupled to automated software analysis, I found that AMPK activation broadly reduces the formation/assembly of bona fide clathrin-coated pits, without impairing the internalization rates of CME cargoes (e.g. EGFR, TfR and β1-integrin). Furthermore, I found that AMPK may regulate CME throughcontrol of the Arf6 protein. Collectively, my findings uncover and provide novel mechanisms by which mitogenic (via EGFR-induced calcium signals) and metabolic signals (via AMPK control of Arf6) may induce regulation of CME—in eliciting global reorganization of the plasma membrane. 1,2,11–13,3–10

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 score0.002
Threshold uncertainty score0.006

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 communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.215
Teacher spread0.209 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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