MétaCan
Menu
Back to cohort
Record W4405668574 · doi:10.1093/genetics/iyae214

A modular system to label endogenous presynaptic proteins using split fluorophores in <i>Caenorhabditis elegans</i>

2024· article· en· W4405668574 on OpenAlexafffund
Mizuki Kurashina, Andrew William Snow, Kota Mizumoto

Bibliographic record

VenueGenetics · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsVancouver Coastal HealthUniversity of British Columbia
FundersAlzheimer SocietyCanadian Institutes of Health ResearchNational Institutes of HealthAlzheimer Society Research ProgramNatural Sciences and Engineering Research Council of CanadaFondation Brain Canada
KeywordsBiologyCaenorhabditis elegansCas9CRISPRRabNeuronZebrafishScaffold proteinSynapseCell biologyComputational biologyGeneticsGeneNeuroscienceSignal transduction

Abstract

fetched live from OpenAlex

Visualizing the subcellular localization of presynaptic proteins with fluorescent proteins is a powerful tool to dissect the genetic and molecular mechanisms underlying synapse formation and patterning in live animals. Here, we utilize split green and red fluorescent proteins to visualize the localization of endogenously expressed presynaptic proteins at a single-neuron resolution in Caenorhabditis elegans. By using CRISPR/Cas9 genome editing, we generated a collection of C. elegans strains in which endogenously expressed presynaptic proteins (RAB-3/Rab3, SNG-1/Synaptogyrin, CLA-1/Piccolo, SYD-2/Liprin-α, UNC-10/RIM, RIMB-1/RIM-BP, and ELKS-1/ELKS) are tagged with tandem repeats of GFP11 and/or wrmScarlet11. We show that the expression of GFP1-10 and wrmScarlet1-10 under neuron-specific promoters can robustly label presynaptic proteins in different neuron types. We believe that the combination of our knock-in strains and GFP1-10 and wrmScarlet1-10 plasmids is a versatile modular system useful for neuroscientists to examine the localization of endogenous presynaptic proteins in any neuron type in C. elegans.

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 categoriesMeta-epidemiology (narrow)
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 score0.059
Threshold uncertainty score1.000

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 head0.021
GPT teacher head0.242
Teacher spread0.221 · 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.

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
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueGeneticsSame topicGenetics, Aging, and Longevity in Model OrganismsFrench-language works237,207