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Record W2955951000 · doi:10.1101/696070

Interaction of a sarcolipin pentamer and monomer with the sarcoplasmic reticulum calcium pump, SERCA

2019· preprint· en· W2955951000 on OpenAlexafffund
John Paul Glaves, Joseph O. Primeau, Przemek A. Gorski, L. Michel Espinoza-Fonseca, M. Joanne Lemieux, Howard S. Young

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIon channel regulation and function
Canadian institutionsUniversity of Alberta
FundersNational Institutes of HealthCanadian Institutes of Health ResearchAlberta InnovatesNatural Sciences and Engineering Research Council of CanadaHeart and Stroke Foundation of Canada
KeywordsSERCAPentamerEndoplasmic reticulumPhospholambanChemistryBiophysicsSkeletal muscleCalciumCalcium pumpCell biologyCalcium ATPaseContractilityBiochemistryATPaseBiologyEndocrinology

Abstract

fetched live from OpenAlex

ABSTRACT The sequential rise and fall of cytosolic calcium underlies the contraction-relaxation cycle of muscle cells. While contraction is initiated by the release of calcium from the sarcoplasmic reticulum, muscle relaxation involves the active transport of calcium back into the sarcoplasmic reticulum. This re-uptake of calcium is catalysed by the sarco-endoplasmic reticulum Ca 2+ -ATPase (SERCA), which plays a lead role in muscle contractility. The activity of SERCA is regulated by small membrane protein subunits, most well-known being phospholamban (PLN) and sarcolipin (SLN). SLN physically interacts with SERCA and differentially regulates contractility in skeletal and atrial muscle. SLN has also been implicated in skeletal muscle thermogenesis. Despite these important roles, the structural mechanisms by which SLN modulates SERCA-dependent contractility and thermogenesis remain unclear. Here, we functionally characterized wild-type SLN and a pair of mutants, Asn 4 -Ala and Thr 5 -Ala, which yielded gain-of-function behavior comparable to what has been found for PLN. Next, we analyzed twodimensional crystals of SERCA in the presence of wild-type SLN by electron cryo-microscopy. The fundamental units of the crystals are anti-parallel dimer ribbons of SERCA, known for decades as an assembly of calcium-free SERCA molecules induced by the addition of decavanadate. A projection map of the SERCA-SLN complex was determined to a resolution of 8.5 Å, which allowed the direct visualization of a SLN pentamer. The SLN pentamer was found to interact with transmembrane segment M3 of SERCA, though the interaction appeared to be indirect and mediated by an additional density consistent with a SLN monomer. This SERCA-SLN complex correlated with the ability of SLN to decrease the maximal activity of SERCA, which is distinct from the ability of PLN to increase the maximal activity of SLN. Protein-protein docking and molecular dynamics simulations provided models for the SLN pentamer and the novel interaction between SERCA and a SLN monomer. STATEMENT OF SIGNIFICANCE This research article describes a novel complex of the sarcoplasmic reticulum calcium pump SERCA and its regulatory subunit sarcolipin. Given the potential role of sarcolipin in skeletal muscle non-shivering thermogenesis, the interactions between SERCA and sarcolipin are of critical importance. Using complementary approaches of functional analysis, electron crystallography, and molecular dynamics simulations, we demonstrate an inherent interaction between SERCA, a sarcolipin monomer, and a sarcolipin pentamer. The interaction involves transmembrane segment M3 of SERCA, which allows sarcolipin to decrease the maximal activity or turnover rate of SERCA. Protein-protein docking and molecular dynamics simulations provided models for the SLN pentamer and the novel interaction between SERCA and a SLN monomer.

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 score0.004

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 head0.012
GPT teacher head0.222
Teacher spread0.210 · 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

Citations1
Published2019
Admission routes2
Has abstractyes

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