Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Protocol
  • Published:

Ex vivo immunocapture and functional characterization of cell-type-specific mitochondria using MitoTag mice

Nature Protocols volume 18, pages 2181–2220 (2023)Cite this article

Subjects

Abstract

Mitochondria are key bioenergetic organelles involved in many biosynthetic and signaling pathways. However, their differential contribution to specific functions of cells within complex tissues is difficult to dissect with current methods. The present protocol addresses this need by enabling the ex vivo immunocapture of cell-type-specific mitochondria directly from their tissue context through a MitoTag reporter mouse. While other available methods were developed for bulk mitochondria isolation or more abundant cell-type-specific mitochondria, this protocol was optimized for the selective isolation of functional mitochondria from medium-to-low-abundant cell types in a heterogeneous tissue, such as the central nervous system. The protocol has three major parts: First, mitochondria of a cell type of interest are tagged via an outer mitochondrial membrane eGFP by crossing MitoTag mice to a cell-type-specific Cre-driver line or by delivery of viral vectors for Cre expression. Second, homogenates are prepared from relevant tissues by nitrogen cavitation, from which tagged organelles are immunocaptured using magnetic microbeads. Third, immunocaptured mitochondria are used for downstream assays, e.g., to probe respiratory capacity or calcium handling, revealing cell-type-specific mitochondrial diversity in molecular composition and function. The MitoTag approach enables the identification of marker proteins to label cell-type-specific organelle populations in situ, elucidates cell-type-enriched mitochondrial metabolic and signaling pathways, and reveals functional mitochondrial diversity between adjacent cell types in complex tissues, such as the brain. Apart from establishing the mouse colony (6–8 weeks without import), the immunocapture protocol takes 2 h and functional assays require 1–2 h.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Workflow for the isolation of cell-type-specific mitochondria.
Fig. 2: Outline of Steps 12–32 to capture cell-type-specific mitochondria.
Fig. 3: Sample pictures and tools for the capture of cell-type-specific mitochondria (Steps 15–32).
Fig. 4: Optimization and performance of the immunocapture protocol for cell-type-specific mitochondria.
Fig. 5: Anticipated results for IC and functional characterization of cell-type-specific mitochondria.
Fig. 6: Outline of Step 32C to functionally probe mitochondrial bioenergetics via the Seahorse analyzer.
Fig. 7: Outline of Step 32D to functionally probe for mitochondrial Ca2+ uptake ex vivo.

Similar content being viewed by others

Data availability

Data presented in this article have been previously published and associated raw data are provided in the related article6.

References

  1. Pagliarini, D. J. & Rutter, J. Hallmarks of a new era in mitochondrial biochemistry. Genes Dev. 27, 2615–2627 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Pagliarini, D. J. et al. A mitochondrial protein compendium elucidates complex I disease biology. Cell 134, 112–123 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Nunnari, J. & Suomalainen, A. Mitochondria: in sickness and in health. Cell 148, 1145–1159 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Weinberg, S. E., Sena, L. A. & Chandel, N. S. Mitochondria in the regulation of innate and adaptive immunity. Immunity 42, 406–417 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Motori, E. et al. Neuronal metabolic rewiring promotes resilience to neurodegeneration caused by mitochondrial dysfunction. Sci. Adv. 6, eaba8271 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Fecher, C. et al. Cell-type-specific profiling of brain mitochondria reveals functional and molecular diversity. Nat. Neurosci. 22, 1731–1742 (2019).

    Article  CAS  PubMed  Google Scholar 

  7. Bayraktar, E. C. et al. MITO-tag mice enable rapid isolation and multimodal profiling of mitochondria from specific cell types in vivo. Proc. Natl Acad. Sci. USA 116, 303–312 (2019).

    Article  CAS  PubMed  Google Scholar 

  8. Barros, L. F. et al. Current technical approaches to brain energy metabolism. Glia 66, 1138–1159 (2018).

    Article  PubMed  Google Scholar 

  9. Misgeld, T. & Schwarz, T. L. Mitostasis in neurons: maintaining mitochondria in an extended cellular architecture. Neuron 96, 651–666 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Plucinska, G. & Misgeld, T. Imaging of neuronal mitochondria in situ. Curr. Opin. Neurobiol. 39, 152–163 (2016).

    Article  CAS  PubMed  Google Scholar 

  11. Pekkurnaz, G. & Wang, X. Mitochondrial heterogeneity and homeostasis through the lens of a neuron. Nat. Metab. 4, 802–812 (2022).

    Article  PubMed  Google Scholar 

  12. Bomba-Warczak, E., Edassery, S. L., Hark, T. J. & Savas, J. N. Long-lived mitochondrial cristae proteins in mouse heart and brain. J. Cell Biol. 220, e202005193 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Sanz, E. et al. Cell-type-specific isolation of ribosome-associated mRNA from complex tissues. Proc. Natl Acad. Sci. USA 106, 13939–13944 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Franko, A. et al. Efficient isolation of pure and functional mitochondria from mouse tissues using automated tissue disruption and enrichment with anti-TOM22 magnetic beads. PLoS One. 8, e82392 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  15. Horie, C., Suzuki, H., Sakaguchi, M. & Mihara, K. Characterization of signal that directs C-tail-anchored proteins to mammalian mitochondrial outer membrane. Mol. Biol. Cell 13, 1615–1625 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Chen, W. W., Freinkman, E., Wang, T., Birsoy, K. & Sabatini, D. M. Absolute quantification of matrix metabolites reveals the dynamics of mitochondrial metabolism. Cell 166, 1324–1337.e1311 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Zambrowicz, B. P. et al. Disruption of overlapping transcripts in the ROSA beta geo 26 gene trap strain leads to widespread expression of beta-galactosidase in mouse embryos and hematopoietic cells. Proc. Natl Acad. Sci. USA 94, 3789–3794 (1997).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Meeusen, S., McCaffery, J. M. & Nunnari, J. Mitochondrial fusion intermediates revealed in vitro. Science 305, 1747–1752 (2004).

    Article  CAS  PubMed  Google Scholar 

  19. Breckwoldt, M. O. et al. Multiparametric optical analysis of mitochondrial redox signals during neuronal physiology and pathology in vivo. Nat. Med. 20, 555–560 (2014).

    Article  CAS  PubMed  Google Scholar 

  20. Fecher, C. Mitochondrial Diversity Probed in Mouse Cerebellum Elucidates Cell Type-Specific Fine-Tuning of Mitochondrial Biology. PhD thesis, LMU München (2020).

  21. Wynne, M. E. et al. Heterogeneous expression of nuclear encoded mitochondrial genes distinguishes inhibitory and excitatory neurons. eNeuro. https://doi.org/10.1523/eneuro.0232-21.2021 (2021).

  22. das Neves, R. P. et al. Connecting variability in global transcription rate to mitochondrial variability. PLoS Biol. 8, e1000560 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  23. Medini, H., Cohen, T. & Mishmar, D. Mitochondrial gene expression in single cells shape pancreatic beta cells’ sub-populations and explain variation in insulin pathway. Sci. Rep. 11, 466 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Hubbard, W. B. et al. Fractionated mitochondrial magnetic separation for isolation of synaptic mitochondria from brain tissue. Sci. Rep. 9, 9656 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Suomalainen, A. & Battersby, B. J. Mitochondrial diseases: the contribution of organelle stress responses to pathology. Nat. Rev. Mol. Cell Biol. 19, 77–92 (2018).

    Article  CAS  PubMed  Google Scholar 

  26. De Stefani, D., Rizzuto, R. & Pozzan, T. Enjoy the trip: calcium in mitochondria back and forth. Ann. Rev. Biochem. 85, 161–192 (2016).

    Article  PubMed  Google Scholar 

  27. Ahier, A., Onraet, T. & Zuryn, S. Cell-specific mitochondria affinity purification (CS-MAP) from Caenorhabditis elegans. STAR Protoc. 2, 100952 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Harbauer, A. B. et al. Neuronal mitochondria transport Pink1 mRNA via synaptojanin 2 to support local mitophagy. Neuron 110, 1516–1531.e1519 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Hansen, F. M. et al. Mitochondrial phosphoproteomes are functionally specialized across tissues. Preprint at bioRxiv https://doi.org/10.1101/2022.03.23.485457 (2022).

  30. Cabrera-Orefice, A., Potter, A., Evers, F., Hevler, J. F. & Guerrero-Castillo, S. Complexome profiling-exploring mitochondrial protein complexes in health and disease. Front. Cell Dev. Biol. 9, 796128 (2021).

    Article  PubMed  Google Scholar 

  31. Roh, H. C. et al. Simultaneous transcriptional and epigenomic profiling from specific cell types within heterogeneous tissues in vivo. Cell Rep. 18, 1048–1061 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Bensley, R. R. & Hoerr, N. L. Studies on cell structure by the freezing-drying method V. The chemical basis of the organization of the cell. Anat. Rec. 60, 251–266 (1934).

    Article  CAS  Google Scholar 

  33. Hogeboom, G. H., Schneider, W. C. & Pallade, G. E. Cytochemical studies of mammalian tissues: I. Isolation of intact mitochondria from rat liver; some biochemical properties of mitochondria and submicroscopic particulate material. J. Biol. Chem. 172, 619–635 (1948).

    Article  CAS  PubMed  Google Scholar 

  34. Frezza, C., Cipolat, S. & Scorrano, L. Organelle isolation: functional mitochondria from mouse liver, muscle and cultured filroblasts. Nat. Protoc. 2, 287–295 (2007).

    Article  CAS  PubMed  Google Scholar 

  35. Sims, N. R. & Anderson, M. F. Isolation of mitochondria from rat brain using Percoll density gradient centrifugation. Nat. Protoc. 3, 1228–1239 (2008).

    Article  CAS  PubMed  Google Scholar 

  36. Russo, G. L. et al. CRISPR-mediated induction of neuron-enriched mitochondrial proteins boosts direct glia-to-neuron conversion. Cell. Stem Cell. 28, 524–534.e527 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Rath, S. et al. MitoCarta3.0: an updated mitochondrial proteome now with sub-organelle localization and pathway annotations. Nucleic Acids Res. 49, D1541–D1547 (2021).

    Article  CAS  PubMed  Google Scholar 

  38. Alvarez-Castelao, B. et al. Cell-type-specific metabolic labeling of nascent proteomes in vivo. Nat. Biotechnol. 35, 1196–1201 (2017).

    Article  CAS  PubMed  Google Scholar 

  39. Alvarez-Castelao, B., Schanzenbächer, C. T., Langer, J. D. & Schuman, E. M. Cell-type-specific metabolic labeling, detection and identification of nascent proteomes in vivo. Nat. Protoc. 14, 556–575 (2019).

    Article  CAS  PubMed  Google Scholar 

  40. Smith, A. C. & Robinson, A. J. MitoMiner v4.0: an updated database of mitochondrial localization evidence, phenotypes and diseases. Nucleic Acids Res. 47, D1225–D1228 (2019).

    Article  PubMed  Google Scholar 

  41. Benador, I. Y. et al. Mitochondria bound to lipid droplets have unique bioenergetics, composition, and dynamics that support lipid droplet expansion. Cell Metab. 27, 869–885.e866 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Misgeld, T., Kerschensteiner, M., Bareyre, F. M., Burgess, R. W. & Lichtman, J. W. Imaging axonal transport of mitochondria in vivo. Nat. Methods 4, 559–561 (2007).

    Article  CAS  PubMed  Google Scholar 

  43. Pham, A. H., McCaffery, J. M. & Chan, D. C. Mouse lines with photo-activatable mitochondria to study mitochondrial dynamics. Genesis 50, 833–843 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Agarwal, A. et al. Transient opening of the mitochondrial permeability transition pore induces microdomain calcium transients in astrocyte processes. Neuron 93, 587–605.e587 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. MacDonald, J. A. et al. A nanoscale, multi-parametric flow cytometry-based platform to study mitochondrial heterogeneity and mitochondrial DNA dynamics. Commun. Biol. 2, 258 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Cavelier, L., Johannisson, A. & Gyllensten, U. Analysis of mtDNA copy number and composition of single mitochondrial particles using flow cytometry and PCR. Exp. Cell Res. 259, 79–85 (2000).

    Article  CAS  PubMed  Google Scholar 

  47. Fieni, F. et al. Voltage-dependent inwardly rectifying potassium conductance in the outer membrane of neuronal mitochondria. J. Biol. Chem. 285, 27411–27417 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Zhang, S. et al. High-throughput multiparameter analysis of individual mitochondria. Anal. Chem. 84, 6421–6428 (2012).

    Article  CAS  PubMed  Google Scholar 

  49. Luo, L. et al. Optimizing nervous system-specific gene targeting with Cre driver lines: prevalence of germline recombination and influencing factors. Neuron 106, 37–65.e35 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Wanders, R. J. A., Waterham, H. R. & Ferdinandusse, S. Metabolic interplay between peroxisomes and other subcellular organelles including mitochondria and the endoplasmic reticulum. Front. Cell Dev. Biol. https://doi.org/10.3389/fcell.2015.00083 (2016).

  51. Shai, N. et al. Systematic mapping of contact sites reveals tethers and a function for the peroxisome-mitochondria contact. Nat. Commun. 9, 1761 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  52. Herculano-Houzel, S. The glia/neuron ratio: how it varies uniformly across brain structures and species and what that means for brain physiology and evolution. Glia 62, 1377–1391 (2014).

    Article  PubMed  Google Scholar 

  53. Sharma, K. et al. Cell type- and brain region-resolved mouse brain proteome. Nat. Neurosci. 18, 1819–1831 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Murgia, M. et al. Proteomics of cytochrome c oxidase-negative versus positive muscle fiber sections in mitochondrial myopathy. Cell Rep. 29, 3825–3834.e3824 (2019).

    Article  CAS  PubMed  Google Scholar 

  55. Schiaffino, S., Reggiani, C., Kostrominova, T. Y., Mann, M. & Murgia, M. Mitochondrial specialization revealed by single muscle fiber proteomics: focus on the Krebs cycle. Scand. J. Med. Sci. Sports 25, 41–48 (2015).

    Article  PubMed  Google Scholar 

  56. Gella, A. et al. Mitochondrial proteome of affected glutamatergic neurons in a mouse model of leigh syndrome. Front. Cell Dev. Biol. 8, 660 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  57. Fünfschilling, U. & Reichardt, L. F. Cre-mediated recombination in rhombic lip derivatives. Genesis 33, 160–169 (2002).

    Article  PubMed  PubMed Central  Google Scholar 

  58. Davidson, B. L. & Breakefield, X. O. Viral vectors for gene delivery to the nervous system. Nat. Rev. Neurosci. 4, 353–364 (2003).

    Article  CAS  PubMed  Google Scholar 

  59. Wang, M., Misgeld, T. & Brill, M. S. Neural labeling and manipulation by neonatal intraventricular viral injection in mice. STAR Protoc. 3, 101081 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Hughes, C. S. et al. Single-pot, solid-phase-enhanced sample preparation for proteomics experiments. Nat. Protoc. 14, 68–85 (2019).

    Article  CAS  PubMed  Google Scholar 

  61. Iuso, A., Repp, B., Biagosch, C., Terrile, C. & Prokisch, H. Assessing mitochondrial bioenergetics in isolated mitochondria from various mouse tissues using Seahorse XF96 analyzer. Methods Mol. Biol. 1567, 217–230 (2017).

    Article  CAS  PubMed  Google Scholar 

  62. Calvo, S. E., Clauser, K. R. & Mootha, V. K. MitoCarta2.0: an updated inventory of mammalian mitochondrial proteins. Nucleic Acids Res. 44, D1251–D1257 (2016).

    Article  CAS  PubMed  Google Scholar 

  63. Wettmarshausen, J. & Perocchi, F. Assessing calcium-stimulated mitochondrial bioenergetics using the Seahorse XF96 analyzer. Methods Mol. Biol. 1925, 197–222 (2019).

    Article  CAS  PubMed  Google Scholar 

  64. Wettmarshausen, J. & Perocchi, F. Isolation of functional mitochondria from cultured cells and mouse tissues. Methods Mol. Biol. 1567, 15–32 (2017).

    Article  CAS  PubMed  Google Scholar 

  65. Zambrowicz, B. P. et al. Disruption of overlapping transcripts in the ROSA βgeo 26 gene trap strain leads to widespread expression of β-galactosidase in mouse embryos and hematopoietic cells. Proc. Natl Acad. Sci. USA 94, 3789–3794 (1997).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Daigle, T. L. et al. A suite of transgenic driver and reporter mouse lines with enhanced brain-cell-type targeting and functionality. Cell 174, 465–480.e422 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Komatsu, M. et al. Loss of autophagy in the central nervous system causes neurodegeneration in mice. Nature 441, 880–884 (2006).

    Article  CAS  PubMed  Google Scholar 

  68. Nectow, A. R. et al. Rapid molecular profiling of defined cell types using Viral TRAP. Cell Rep. 19, 655–667 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank all authors of the related article6 for their contribution to the establishment and validation of the MitoTag mouse model. Work in T.M.’s laboratory is supported by the DFG: CRC870 A11-ID 118803580, TRR 274/1 B03/ C02-ID 408885537, Mi 694/7-1, Mi 694/8-1, Mi 694/9-1 A03-ID 428663564, FOR ImmunoStroke and the ERC under the European Union’s Seventh Framework Program (FP/2007-2013; ERC grant agreement no. 616791). T.M. is a member of and supported by the German Center for Neurodegenerative Diseases (DZNE) and by the Munich Center for Systems Neurology (SyNergy EXC 2145; Project ID 390857198). N.P.d.M. and C.F. were enrolled in the Munich Graduate School of Systemic Neurosciences (GSC 82–ID 24184143). Work in F.P.’s laboratory is supported by the Munich Center for Systems Neurology (SyNergy EXC 2145; Project ID 390857198) and the ExNet-0041-Phase2-3 (‘SyNergy-HMGU’) through the Initiative and Network Fund of the Helmholtz Association. The authors thank H.C. Delgado de la Herran, Y. Hufnagel and M. Feng for help with material and data collection.

Author information

Author notes

  1. These authors contributed equally: Natalia Prudente de Mello, Caroline Fecher.

  2. These authors jointly supervised this work: Fabiana Perocchi, Thomas Misgeld.

Authors and Affiliations

  1. Institute of Neuronal Cell Biology, Technical University of Munich, Munich, Germany

    Natalia Prudente de Mello, Caroline Fecher, Adrian Marti Pastor, Fabiana Perocchi & Thomas Misgeld

  2. Institute for Diabetes and Obesity, Helmholtz Zentrum München, Munich, Germany

    Natalia Prudente de Mello & Fabiana Perocchi

  3. Graduate School of Systemic Neurosciences, Ludwig-Maximilians Universität München, Munich, Germany

    Natalia Prudente de Mello & Caroline Fecher

  4. Department of Cell Biology & Physiology, School of Medicine, Washington University in St Louis, St Louis, MO, USA

    Caroline Fecher

  5. Munich Cluster for Systems Neurology, Munich, Germany

    Fabiana Perocchi & Thomas Misgeld

  6. German Center for Neurodegenerative Diseases, Munich, Germany

    Thomas Misgeld

Authors
  1. Natalia Prudente de Mello
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Caroline Fecher
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Adrian Marti Pastor
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Fabiana Perocchi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Thomas Misgeld
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

N.P.d.M. and C.F. collected and analyzed the data. C.F. and N.P.d.M designed the figures with help from F.P. and T.M. A.M.P generated the video. All authors contributed to writing, editing and revision of the manuscript.

Corresponding authors

Correspondence to Fabiana Perocchi or Thomas Misgeld.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Protocols thanks Elisenda Sanz and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Related links

Key reference using this protocol

Fecher, C. et al. Nat. Neurosci. 22, 1731–1742 (2019): https://doi.org/10.1038/s41593-019-0479-z

Extended data

Extended Data Fig. 1 MitoTag genetic strategy.

a, MitoTag locus recombination within the endogenous Rosa26 locus occurs during the crossing of MitoTag mice with Cre-driver lines generating recombined animals (F1) that express GFP-OMM in Cre+ cells (green element). e1/2, exon 1/2; P*, cell-type-specific promoter. b, MitoTag PCR result demonstrating PCR primer specificity for the MitoTag allele. PCR products: wild-type Rosa26 locus (WT), ~600 bp (see lane 3); MitoTag transgene, 324 bp (see lane 6). Consult Step 3A(iv–xiii) for genotyping protocol. The Rosa26-tm4(CAG-EGFP*) reporter mouse is another Rosa26 knock-in model that Cre-conditionally expresses GFP localized to the mitochondrial matrix (mito-EGFP). Note the absence of PCR product in this homozygous sample in lane 5. Primers are specific for both alleles, GFP-OMM and the endogenous Rosa26 locus. The sample in lane 5 is from a homozygous Rosa26-tm4(CAG-EGFP*) mouse. A PCR against GFP would not discriminate between the two Rosa26 reporter mouse models. All animal experiments were approved by the responsible regulatory agencies (Regierung von Oberbayern). a, adapted from ref. 6, Springer Nature Ltd.

Extended Data Fig. 2 MitoTag recombination in astrocytes through a number of Cre-driver lines and adeno-associated viral vector.

a-f, MitoTag mice were recombined with different Cre-driver lines for the expression in astrocytes: a, mGFAP:Cre (77.6); b, hGFAP:CreERT2; c, Aldh1¦1:Cre; d, Sept4:Cre; and e, Plp1:Cre/ERT; or neonatally injected with AAV9-CamkII.Cre virus (f, cerebellum and cortex). In cerebellum, two populations of astrocytes are present, namely Bergmann glia in the molecular layer (ML) with their cell body localized in the Purkinje cell layer (PCL) and protoplasmic astrocytes in the granule cell layer (GCL). Asterisks indicate leaky expression and off-target recombination. Scale bar, 1 mm for sagittal brain, 50 µm for detailed images. Further information on the Cre-driver lines is given in Table 1. All animal experiments were approved by the responsible regulatory agencies (Regierung von Oberbayern). a, adapted from ref. 6, Springer Nature Ltd.

Extended Data Fig. 3 Essential equipment for the tissue homogenization Step 16.

a, Dounce glass tissue homogenizers of different sizes (volume and clearance, see Table 4). #A can be used for soft tissue and homogenization by hand, while #20, 22-24 are used in combination with a motorized rotor (300 rpm for the present protocol) and for different tissue sources (brain, liver, muscle tissue). b, Sample pictures illustrating the final immunocapture in Step 29 and 31. Note, final samples can vary in size and color between IC Tom and IC GFP dependent on the abundance of GFP-OMM tagged mitochondria in tissue lysate and the amount of microbeads used. Microbeads are present as dark central spot within the sample pellet and we have not observed adverse effects due to their presence in functional downstream assays. All animal experiments were approved by the responsible regulatory agencies (Regierung von Oberbayern).

Extended Data Fig. 4 Troubleshooting of mitochondrial viability via oxygen consumption rate (OCR) measurement.

a, Protocol stage 2 illustrating the generation of a single-cell tissue homogenate in Step 16. For mitochondrial bioenergetics, two tissue lysate concentrations were generated in IB+: 5 mg/ml and 20 mg/ml, as recommended in our protocol. Immunocapture with IC Tom was performed from both samples as outlined in the PROCEDURE. b, Oxygen consumption ratio (OCR) via complex I (pyruvate/malate) from samples outlined in a (5 mg/ml, light orange; 20 mg/ml, orange) using 2 ug mitochondria/well supplemented with 10 mM pyruvate and 2 mM malate. The following compounds and concentrations were injected in the assay: ADP (4 mM), oligomycin A (Oligo, 1.5 µM), CCCP (10 µM), and rotenone (2 µM) together with antimycin A (4 µM; AA). The graph shows that mitochondrial functionality can be affected by the initial dilution during homogenisation, which is observed by the low OCR levels and unresponsiveness to the compounds of the 5 mg/ml sample (light orange) compared with the expected mitochondrial modulator responses of the standard sample (orange). Line graph: mean ± s.e.m. from ≥8 technical replicates. All animal experiments were approved by the responsible regulatory agencies (Regierung von Oberbayern).

Source data

Extended Data Fig. 5 Single-channel information from MitoTag/Gfap:Cre/Thy1:mitoRFP image represented in Fig. 4d.

Cortex from MitoTag/Gfap:Cre/Thy1:mitoRFP animals used as tissue source in the ‘spike-in’ experiment. a, Merged image shown in Fig. 4d and corresponding single channels. b, Detail from a. Scale bar, 20 µm for a, 10 µm for b.

Supplementary information

Reporting Summary

Supplementary Video 1

Description of how to perform Steps 17–20 corresponding to plasma membrane permeabilization using nitrogen cavitation.

Source data

Source Data

Unprocessed western blots and statistical source data for Figs. 4b,c,e,f and 5a–e and Extended Data Fig. 4b.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

de Mello, N.P., Fecher, C., Pastor, A.M. et al. Ex vivo immunocapture and functional characterization of cell-type-specific mitochondria using MitoTag mice. Nat Protoc 18, 2181–2220 (2023). https://doi.org/10.1038/s41596-023-00831-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41596-023-00831-w

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Advanced search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research