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Record W3062204540 · doi:10.26685/urncst.188

Using CRISPR-X for Optimization of Antibodies Towards A30P α-synuclein Oligomers in Immunotherapy of Parkinson’s Disease

2020· article· en· W3062204540 on OpenAlexaff
Isabell C. Pitigoi, Courtney E. Ostromecki

Bibliographic record

VenueUndergraduate Research in Natural and Clinical Science and Technology (URNCST) Journal · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsQueen's University
Fundersnot available
KeywordsCRISPRParkinson's diseaseImmunotherapyAntibodyDiseaseComputational biologyVirologyMedicineBiologyImmunologyGeneticsImmune systemGenePathology

Abstract

fetched live from OpenAlex

Introduction: Parkinson’s disease (PD) is a neurodegenerative disorder characterized by progressive cell death in the substantia nigra portion of the midbrain, which results in severe dopamine imbalance and a subsequent loss of refined motor control. Pathogenicity arises from mutations driving the misfolding of alpha synuclein (ɑ-syn), thus leading to oligomerization and formation of Lewy body aggregates in neurons. Previous research has identified the A30P mutated oligomers, which are connected to familial early-onset PD, as particularly toxic intermediates. However, there are insufficient methods of targeting them in isolation of other forms of the ɑ-syn protein. We aim to modify existing approaches to immunotherapy of PD, by use of CRISPR-X and phage display, to design antibodies that are highly specific to the A30P oligomer. Methods: We will use CRISPR-X to produce a diverse library of antibodies by introducing point mutations in the sequences encoding their variable light (VL) and heavy (VH) chains. Then, via insertion into bacteriophages for multiple rounds of phage display selection, we should obtain a polyclonal selection of antibodies that exclusively recognize epitopes on A30P ɑ-syn. Each variant then produces a distinct monoclonal phage colony to be incubated with relevant antigens for affinity testing via enzyme-linked immunosorbent assay (ELISA). Expected Results: We expect that measurements from ELISA would indicate low dissociation constants (KD) within the low micromolar (10-6) to nanomolar (10-7 to 10-9) range, when incubated with A30P oligomers. We predict that the resultant antibodies would have a higher affinity for the A30P oligomeric ɑ-syn than other forms of the protein. Furthermore, the novel antibodies are expected to have a higher specificity to this target antigen than the original antibodies that were modified. Discussion: By determining binding affinity, we verify the effectiveness of this method for improving specificity of in vitro antibody design. Upon further investigation using mice models, we would anticipate these novel antibodies could produce a specific reversal of the toxic effects of A30P in neuronal tissue. Conclusion: This study aims to establish a potential for CRISPR-X and phage selection to be used in antibody optimization for developing an immunotherapeutic treatment for PD.

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.063
GPT teacher head0.442
Teacher spread0.379 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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