CryoET reveals organelle phenotypes in huntington disease patient iPSC-derived and mouse primary neurons.
Gong-Her WuCharlene Smith-GeaterJesús G Galaz-MontoyaYingli GuSanket R GupteRanen AvinerPatrick G MitchellJoy HsuRicardo MiramontesKeona Q WangNicolette R GellerCathy HouCristina DanitaLydia-Marie JoubertMichael F SchmidSerena YeungJudith FrydmanWilliam MobleyChengbiao WuLeslie M ThompsonWah ChiuPublished in: Nature communications (2023)
Huntington's disease (HD) is caused by an expanded CAG repeat in the huntingtin gene, yielding a Huntingtin protein with an expanded polyglutamine tract. While experiments with patient-derived induced pluripotent stem cells (iPSCs) can help understand disease, defining pathological biomarkers remains challenging. Here, we used cryogenic electron tomography to visualize neurites in HD patient iPSC-derived neurons with varying CAG repeats, and primary cortical neurons from BACHD, deltaN17-BACHD, and wild-type mice. In HD models, we discovered sheet aggregates in double membrane-bound organelles, and mitochondria with distorted cristae and enlarged granules, likely mitochondrial RNA granules. We used artificial intelligence to quantify mitochondrial granules, and proteomics experiments reveal differential protein content in isolated HD mitochondria. Knockdown of Protein Inhibitor of Activated STAT1 ameliorated aberrant phenotypes in iPSC- and BACHD neurons. We show that integrated ultrastructural and proteomic approaches may uncover early HD phenotypes to accelerate diagnostics and the development of targeted therapeutics for HD.
Keyphrases
- induced pluripotent stem cells
- artificial intelligence
- spinal cord
- wild type
- machine learning
- oxidative stress
- case report
- genome wide
- big data
- protein protein
- cell death
- amino acid
- deep learning
- mass spectrometry
- binding protein
- spinal cord injury
- cell proliferation
- dna methylation
- adipose tissue
- type diabetes
- endoplasmic reticulum
- gene expression
- copy number
- high fat diet induced
- label free
- genome wide identification