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Record W4366176059 · doi:10.1101/2023.04.13.536711

Validation of Tau Antibodies for Use in Western Blotting and Immunohistochemistry

2023· preprint· en· W4366176059 on OpenAlexaff
Michael J. Ellis, Christiana Lekka, Hanna Tulmin, Darragh P. O’Brien, Shalinee Dhayal, Marie‐Louise Zeissler, Jakob G. Knudsen, Benedikt M. Kessler, Noel G. Morgan, John A. Todd, M. Irina Stefana

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2023
Typepreprint
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsDiscovery Centre
FundersResearch EnglandMedical Research CouncilUniversity of ExeterNational Institute for Health and Care ResearchNIHR Oxford Biomedical Research CentreAlzheimer's SocietyUniversity of OxfordEli Lilly and Company
KeywordsAntibodyWestern blotGene isoformTau proteinImmunohistochemistryNeurodegenerationBlotMolecular biologyBiologyChemistryImmunologyMedicineBiochemistryDiseaseAlzheimer's diseasePathologyGene

Abstract

fetched live from OpenAlex

Abstract Background The microtubule-associated protein Tau has attracted diverse and increasing research interest, with Tau being mentioned in the title/abstract of nearly 34,000 PubMed-indexed publications to date. To accelerate studies into Tau biology, the characterisation of its multiple proteoforms, including disease-relevant post-translational modifications (PTMs), and its role in neurodegeneration, a multitude of Tau-targeting antibodies have been developed, with hundreds of distinct antibody clones currently available for purchase. Nonetheless, concerns over antibody specificity and limited understanding of the performance of many of these reagents has hindered research. Methods We have employed a range of techniques in combination with samples of murine and human origin to characterise the performance and specificity of 53 commercially-available Tau antibodies by Western blot, and a subset of these, 35 antibodies, in immunohistochemistry. Results Continued expression of residual protein was found in presumptive Tau “knockout” human cells and further confirmed through mass-spectrometry proteomics, providing evidence of Tau isoforms generated by exon skipping. Importantly, many total and isoform-specific antibodies failed to detect this residual Tau, as well as Tau expressed at low, endogenous levels, thus highlighting the importance of antibody choice. Our data further reveal that the binding of several “total” Tau antibodies, which are assumed to detect Tau independently of post-translational modifications, was partially inhibited by phosphorylation. Many antibodies also displayed non-specific cross-reactivity, with some total and phospho-Tau antibodies cross-reacting with MAP2 isoforms, while the “oligomer-specific” T22 antibody detected monomeric Tau on Western blot. Regardless of their specificity, with one exception, the phospho-Tau antibodies tested were found to not detect the unphosphorylated protein. Conclusions We identify Tau antibodies across all categories (total, PTM-dependent and isoform-specific) that can be employed in Western blot and/or immunohistochemistry applications to reliably detect even low levels of Tau expression with high specificity. This is of particular importance for studying Tau in non-neuronal cells and peripheral tissues, as well as for the confident validation of knockout cells and/or animal models. This work represents an extensive resource that serves as a point of reference for future studies. Our findings may also aid in the re-interpretation of existing data and improve reproducibility of Tau research.

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)0.008
metaresearch head score (Gemma)0.006
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: none
Teacher disagreement score0.008
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.003

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 head0.045
GPT teacher head0.307
Teacher spread0.262 · 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

Citations12
Published2023
Admission routes1
Has abstractyes

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