Co-fractionation-mass spectrometry to characterize native mitochondrial protein assemblies in mammalian neurons and brain.
Mara ZilocchiMatineh RahmatbakhshMohamed Taha MoutaoufikKirsten BroderickAlla GagarinovaMatthew JessulatSadhna PhanseHiroyuki AokiKhaled A AlyMohan BabuPublished in: Nature protocols (2023)
Human mitochondrial (mt) protein assemblies are vital for neuronal and brain function, and their alteration contributes to many human disorders, e.g., neurodegenerative diseases resulting from abnormal protein-protein interactions (PPIs). Knowledge of the composition of mt protein complexes is, however, still limited. Affinity purification mass spectrometry (MS) and proximity-dependent biotinylation MS have defined protein partners of some mt proteins, but are too technically challenging and laborious to be practical for analyzing large numbers of samples at the proteome level, e.g., for the study of neuronal or brain-specific mt assemblies, as well as altered mtPPIs on a proteome-wide scale for a disease of interest in brain regions, disease tissues or neurons derived from patients. To address this challenge, we adapted a co-fractionation-MS platform to survey native mt assemblies in adult mouse brain and in human NTERA-2 embryonal carcinoma stem cells or differentiated neuronal-like cells. The workflow consists of orthogonal separations of mt extracts isolated from chemically cross-linked samples to stabilize PPIs, data-dependent acquisition MS to identify co-eluted mt protein profiles from collected fractions and a computational scoring pipeline to predict mtPPIs, followed by network partitioning to define complexes linked to mt functions as well as those essential for neuronal and brain physiological homeostasis. We developed an R/CRAN software package, Macromolecular Assemblies from Co-elution Profiles for automated scoring of co-fractionation-MS data to define complexes from mtPPI networks. Presently, the co-fractionation-MS procedure takes 1.5-3.5 d of proteomic sample preparation, 31 d of MS data acquisition and 8.5 d of data analyses to produce meaningful biological insights.
Keyphrases
- mass spectrometry
- multiple sclerosis
- liquid chromatography
- cerebral ischemia
- ms ms
- capillary electrophoresis
- resting state
- white matter
- endothelial cells
- electronic health record
- stem cells
- high performance liquid chromatography
- gas chromatography
- protein protein
- functional connectivity
- high resolution
- end stage renal disease
- healthcare
- high throughput
- chronic kidney disease
- induced pluripotent stem cells
- big data
- binding protein
- data analysis
- machine learning
- gene expression
- deep learning
- subarachnoid hemorrhage
- peritoneal dialysis
- spinal cord injury
- patient reported outcomes
- blood brain barrier
- hepatitis c virus
- prognostic factors
- tandem mass spectrometry
- hiv infected
- cell therapy
- simultaneous determination