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A guide to selecting high-performing antibodies for STING1 (Uniprot ID: Q86WV6) for use in western blot, immunoprecipitation, and immunofluorescence

2025· preprint· en· W4406018855 on OpenAlexafffund
Vera Ruíz Moleón, Charles Alende, Maryam Fotouhi, Riham Ayoubi, Kathleen Southern, Carl Laflamme

Bibliographic record

VenueF1000Research · 2025
Typepreprint
Languageen
FieldImmunology and Microbiology
Topicinterferon and immune responses
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersGovernment of CanadaOntario Genomics InstituteEuropean Federation of Pharmaceutical Industries and AssociationsMerck KGaAMitacsOntario GenomicsGenome CanadaGenentechBayerPfizerBristol-Myers Squibb
KeywordsImmunoprecipitationWestern blotAntibodyImmunofluorescenceUniProtBiologyImmune systemImmunologyComputational biologyGeneGenetics

Abstract

fetched live from OpenAlex

Stimulator of interferon genes protein (STING1) is an immune adaptor protein which promotes innate immune defense mechanisms against pathogens. To enhance our understanding of STING1-associated disease, it is essential to make high-performing antibodies accessible to the scientific community. This study aims to improve reliability of STING1 research as we have characterized sixteen STING1 commercial antibodies for western blot, immunoprecipitation, and immunofluorescence using a standardized experimental protocol based on comparing read-outs in knockout cell lines and isogenic parental controls. These studies are part of a larger, collaborative initiative seeking to address antibody reproducibility issues by characterizing commercially available antibodies for human proteins and publishing the results openly as a resource for the scientific community. While use of antibodies and protocols vary between laboratories, we encourage readers to use this report as a guide to select the most appropriate antibodies for their specific needs.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.220
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0010.001
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 head0.046
GPT teacher head0.375
Teacher spread0.329 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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