Fractionated mitochondrial magnetic separation for isolation of synaptic mitochondria from brain tissue

W. Brad Hubbard, Christopher L. Harwood, Paresh Prajapati, Joe E. Springer, Kathryn E. Saatman, Patrick G. Sullivan

Research output: Contribution to journalArticlepeer-review

47 Scopus citations

Abstract

While mitochondria maintain essential cellular functions, such as energy production, calcium homeostasis, and regulating programmed cellular death, they also play a major role in pathophysiology of many neurological disorders. Furthermore, several neurodegenerative diseases are closely linked with synaptic damage and synaptic mitochondrial dysfunction. Unfortunately, the ability to assess mitochondrial dysfunction and the efficacy of mitochondrial-targeted therapies in experimental models of neurodegenerative disease and CNS injury is limited by current mitochondrial isolation techniques. Density gradient ultracentrifugation (UC) is currently the only technique that can separate synaptic and non-synaptic mitochondrial sub-populations, though small brain regions cannot be assayed due to low mitochondrial yield. To address this limitation, we used fractionated mitochondrial magnetic separation (FMMS), employing magnetic anti-Tom22 antibodies, to develop a novel strategy for isolation of functional synaptic and non-synaptic mitochondria from mouse cortex and hippocampus without the usage of UC. We compared the yield and functionality of mitochondria derived using FMMS to those derived by UC. FMMS produced 3x more synaptic mitochondrial protein yield compared to UC from the same amount of tissue, a mouse hippocampus. FMMS also has increased sensitivity, compared to UC separation, to measure decreased mitochondrial respiration, demonstrated in a paradigm of mild closed head injury. Taken together, FMMS enables improved brain-derived mitochondrial yield for mitochondrial assessments and better detection of mitochondrial impairment in CNS injury and neurodegenerative disease.

Original languageEnglish
Article number9656
JournalScientific Reports
Volume9
Issue number1
DOIs
StatePublished - Dec 1 2019

Bibliographical note

Publisher Copyright:
© 2019, The Author(s).

Funding

The authors would like to thank Malinda Spry, Binoy Joseph, Ph.D., Jennifer Gooch, and Hemendra Vekaria, Ph.D. for their technical assistance. We would also like to acknowledge the Biomedical Illustration team of Matt Hazzard and Tom Dolan in University of Kentucky Information Technology. This work was supported by NSF EPSCoR Seed Grant 4978/111315 (National Science Foundation Grant No. 1539068), Kentucky Spinal Cord and Head Injury Research Trust (KSCHIRT) Grant 14–13A, and VA Merit Award 1I01BX003405-01A1.

FundersFunder number
U.S. Department of Energy Chinese Academy of Sciences Guangzhou Municipal Science and Technology Project Oak Ridge National Laboratory Extreme Science and Engineering Discovery Environment National Science Foundation National Energy Research Scientific Computing Center National Natural Science Foundation of China1539068, 4978/111315
U.S. Department of Veterans Affairs1I01BX003405-01A1
Kentucky Spinal Cord and Head Injury Research Trust14–13A
Kansas NSF EPSCoR
Department of Veterans' Affairs, Australian Government

    ASJC Scopus subject areas

    • General

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