Misconnecting the dots: altered mitochondrial protein-protein interactions and their role in neurodegenerative disorders

ABSTRACT

Introduction: Mitochondria (mt) are protein-protein interaction (PPI) hubs in the cell where mt-localized and associated proteins interact in a fashion critical for cell fitness. Altered mtPPIs are linked to neurodegenerative disorders (NDs) and drivers of pathological associations to mediate ND progression. Mapping altered mtPPIs will reveal how mt dysfunction is linked to NDs.

Areas covered: This review discusses how database sources reflect on the number of mt protein or interaction predictions, and serves as an update on mtPPIs in mt dynamics and homeostasis. Emphasis is given to mRNA expression profiles for mt proteins in human tissues, cellular models relevant to NDs, and altered mtPPIs in NDs such as Parkinson’s disease (PD), Amyotrophic lateral sclerosis (ALS) and Alzheimer’s disease (AD).

Expert opinion: We highlight the scarcity of biomarkers to improve diagnostic accuracy and tracking of ND progression, obstacles in recapitulating NDs using human cellular models to underpin the pathophysiological mechanisms of disease, and the shortage of mt protein interactome reference database(s) of neuronal cells. These bottlenecks are addressed by improvements in induced pluripotent stem cell creation and culturing, patient-derived 3D brain organoids to recapitulate structural arrangements of the brain, and cell sorting to elucidate mt proteome disparities between cell types.

KEYWORDS:

• Alzheimer’s disease
• Amyotrophic lateral sclerosis
• mass spectrometry
• interactome
• mitochondria
• mitochondrial proteome
• Parkinson’s disease
• proteomics
• protein-Protein interactions
• systems biology

Article highlights

• The mt human proteome, from established databases, suggests that nearly half of the 1,838 predicted mt proteins are highly expressed in at least some tissue types, while the rest are low to no expression.

• Roughly 13-32% of the non-mt proteins in the human proteome (20,415) are estimated to be associated with mt, implicating the vital role of mt connectivity with other organelles and non-mt structures and functions.

• Computational or three-dimensional structural models on co-complex data can facilitate the identification of binary PPI interface residues and the biophysical impact of variants in NDs.

• The ongoing development and refinement of near-physiological cellular models is becoming a salient requirement in neuroscience to best-mimic ND features.

• PPIs that orchestrate mt functions, dynamics and homeostasis are gaining recognition for their implications in NDs and indisputable therapeutic potential.

• The examination of published mtPPIs linked to PD, ALS and AD can illuminate strategies to target mt dysfunction across different NDs.

• Sporadic or familial forms of PD, ALS and AD are characterized by notable alterations in mtPPIs, and mapping these pathological mtPPI networks in various NDs will be informative in understanding mt changes that are central to shared susceptibility.

• Challenges stemming from the heterogeneity of NDs and uncertain roles of ND variants will require multi-pronged global discovery interaction mapping and structure-function analyses, which can offer considerable advantages to identify and mechanistically examine how ND-related variants impact mt assemblies in the pathobiology of NDs.

• Despite the progress in reports of altered protein levels in PD, ALS and AD, how risk variants and disease remodel mtPPIs to drive disease progression remains an important open question, which has not been systematically studied. More cutting-edge proteomic strategies will be required to target mt dysfunction in these major NDs.

• Regional heterogeneity of the mt interactome in vulnerable brain regions of PD, ALS and AD, and how mtPPIs are rewired in different sporadic and familial forms of these diseases, are unknown.

• Reconciliation of mtPPIs detected by some methods but not others, or identified in some databases but not others, and careful selection of current resources will require extensive examination of cell types, methodologies, and study limitations across existing and novel databases to serve as foundation for future work.

• Combining several omics approaches with near-physiological cellular models is indispensable to decipher the pathological mechanisms of NDs, which can pave the way for precision medicine.

• Functional roles of ND gene drivers can be assigned by integrating genome-wide single-cell transcriptomic data with PPI networks, which has not been attempted for ND patient neurons, hindering a systems level understanding of mt transcript impairments in NDs.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Supplementary Materials

The supplementary data for this article can be accessed here.

Data availability statement

The data described in this article are openly available in the Open Science Framework at DOI:10.17605/OSF.IO/TPA6U.

Additional information

Funding

This work was funded by the Government of Canada, Canadian Institutes of Health Research, grants: [MOP-125952; FDN-154318]; the U.S. National Institutes of Health, and the National Institute of General Medical Sciences grant: [R01GM106019]; and Parkinson Society Canada: [2014-673].