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Validating and Optimizing A Combination of INTACT and FACS Techniques for the Isolation of Mouse Astrocyte Nuclei Upon Ablation of the <i>Atrx</i> Intellectual Disability Gene

2019· article· en· W3177236992 on OpenAlexaffabout
Yuxuan Jiang, Miguel A. Pena Ortiz, Yan Jiang, Nathalie G Bérubéé

Bibliographic record

VenueThe FASEB Journal · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMolecular Biology Techniques and Applications
Canadian institutionsChildren’s Health Research InstituteWestern University
Fundersnot available
KeywordsATRXBiologyDeath-associated protein 6AstrocyteCell biologyTelomereHistoneNeuroscienceGeneGeneticsCentral nervous systemMutationNuclear proteinTranscription factor

Abstract

fetched live from OpenAlex

The ATRX gene codes for the ATRX chromatin remodelling protein, which interacts with DAXX protein to deposit histone variant H3.3 at telomeres and pericentromeric heterochromatin. Mutations of the ATRX gene cause intellectual disability. One noticeable example is the ATRX syndrome, which is characterized by distinctive craniofacial features, severe developmental delays, intellectual disability, and mild‐to‐moderate anemia. It is therefore apparent that the ATRX gene likely plays an important role in the central nervous system (CNS). An astrocyte is a cell type that, by the most conservative survey, has the same abundance as neurons in the human brain. However, unlike neurons, astrocyte function is far less understood, and its role other than a supporting function was not known until a decade ago, when astrocytes were discovered to actively participate in higher neuronal processing through the tripartite synapse. The specific role of ATRX in astrocytes has never been reported before. A challenge of elucidating ATRX function in astrocyte is a lack of an optimized technique to isolate a reasonable number of highly enriched Atrx ‐ablated astrocyte nuclei for various sequencing purposes, including ChiP‐seq and RNA‐seq. This project aims to fulfill such research demand by validating and optimizing the Isolation of Nuclei Tagged in Specific Cell Types (INTACT) technique with mouse brain tissue at postnatal day 30. By adjusting various experimental conditions such as tissue homogenization time, the concentration of octylphenoxy poly(ethyleneoxy)ethanol (IGEPAL) in buffer solutions, the dilution ratio of the tissue homogenate and the centrifugation time, a total nuclei yield of 90% was obtained. The structural integrity of nuclei was verified by laser microscopy with nuclei sample stained with 4′,6‐diamidino‐2‐phenylindole (DAPI). However, subsequent enrichment of GFP‐tagged Atrx F/y ; Cre +/− ;Sun1‐GFP +/− nuclei using anti‐G‐protein coated magnetic bead, as per the original INTACT protocol, is plagued with non‐specific binding of less than 32% specificity. To improve the enrichment factor, a preliminary investigation was performed to validate the use of Florescent‐Assisted Cell Sorting (FACS) to enrich Sun1GFP‐tagged nuclei from the previously‐produced total nuclei preparation. A 92% enrichment of GFP‐tagged nuclei was obtained, demonstrating the promising potential of a combined INTACT‐FACS technique to effectively isolate structurally‐sound nuclei from transcriptionally‐sensitive cell types, within a complex and intermingled tissue environment. Support or Funding Information This work was supported by a Dean's Undergraduate Research Opportunity Program award to Yuxuan Jiang and the Canadian Institutes for Health Research MOP#142369. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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)0.001
metaresearch head score (Gemma)0.001
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: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.010
GPT teacher head0.250
Teacher spread0.240 · 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
GenreMethods

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".

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Citations0
Published2019
Admission routes2
Has abstractyes

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