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Background Astrocytes play a central role in maintaining brain energy metabolism, but are also tightly connected to the pathogenesis of Alzheimer’s disease (AD). Our previous studies demonstrate that inflammatory astrocytes accumulate large amounts of aggregated amyloid-beta (Aβ). However, in which way these Aβ deposits influence their energy production remain unclear. Methods The aim of the present study was to investigate how Aβ pathology in astrocytes affects their mitochondria functionality and overall energy metabolism. For this purpose, human induced pluripotent cell (hiPSC)-derived astrocytes were exposed to sonicated Aβ42 fibrils for 7 days and analyzed over time using different experimental approaches. Results Our results show that to maintain stable energy production, the astrocytes initially increased their mitochondrial fusion, but eventually the Aβ-mediated stress led to abnormal mitochondrial swelling and excessive fission. Moreover, we detected increased levels of phosphorylated DRP-1 in the Aβ-exposed astrocytes, which co-localized with lipid droplets. Analysis of ATP levels, when blocking certain stages of the energy pathways, indicated a metabolic shift to peroxisomal-based fatty acid β-oxidation and glycolysis. Conclusions Taken together, our data conclude that Aβ pathology profoundly affects human astrocytes and changes their entire energy metabolism, which could result in disturbed brain homeostasis and aggravated disease progression.

Additional file 5. Mitochondria are distributed between astrocytes via tunneling nanotubes. Arrows indicate transfer of MitoTracker™ Green labeled mitochondria from the top cell to the bottom cell via tunneling nanotubes. The top panel show fluorescent mitochondria in white and the bottom panel show the merged images (GFP and bright field) of the same time points.

Additional file 3. Mitochondrial fusion protein levels are not affected by Aβ exposure. Western blot analysis demonstrated that OPA1 levels remain unchanged by Aβ exposure at 7d and 7d+6d.

Additional file 8. Lipid droplets are found in both Aβ exposed and control astrocytes. Lipid droplets (white asterisks) are observed in Aβ exposed astrocytes (a,b) and in controls (c,c´).

Additional file 1. Astrocytic markers. hiPSC-derived astrocytes were stained with DAPI (blue) and the astrocytic markers: GLAST-1 (A), Vimentin (B) S100β (C), AQP4 (D), GFAP (E), and Nestin (F). Scale bar: 20 μm.

Additional file 2. Aβ exposure affects mitochondrial motility in astrocytes. The parameter displacement, distance, velocity and speed were analyzed with Mitometer (A). Motility analysis showed a significant increase in the mitochondrial speed (B) and velocity (C) in Aβ-exposed astrocytes.

Additional file 7. Aβ exposure does not affect basal respiration of mitochondria, cell viability or apoptosis in astrocytes. Seahorse OCR analysis showed no differences in mitochondrial basal respiration between control and Aβ-exposed astrocytes (A). Alamar blue assay showed no decrease in viability in the astrocyte cultures exposed to Aβ (B). Similarly, WB analysis showed no increase in apoptosis markers caspase-3 and BAX in the Aβ-exposedcultures (C and D).

Additional file 1: Figure S1. Characterization of differentiated SH-SY5Y cells. Figure S2. Cytotoxicity of compounds evaluated in the HTS. Figure S3. Effects of luteolin in respiratory capacity and ΔΨm. Figure S4. Effects of luteolin in mitochondrial biogenesis and cristae organization. Figure S5. Effects of luteolin on calcium levels and characterization of isolated mitochondrial fractions.

Additional File 2. Source data

Additional File 1: Figures S1-8. Figure S1. MIEFs robustly interact with Mfn1 and Mfn2 in the absence of chemical crosslinking. Figure S2. Multiple sequence alignment of MIEF1 orthologs in different vertebrate species. Figure S3. Multiple sequence alignment of MIEF2 orthologs in different vertebrate species. Figure S4. Overexpression of MIEFs and deletion mutants does not induce apoptosis as assessed by western blot analysis with PARP antibody. Figure S5. Knockdown of Mfn1, Mfn2 or OPA1 by siRNA. Figure S6. Exogenous expression of MIEF1 in MIEF1 KO 293T or MIEF2 in MIEF2 KO 293T cells enhances mitochondrial fusion. Figure S7. Mitochondrial localization and dimerization/oligomerization of MIEFs are required for their fusion-promoting ability. Figure S8. MIEFs do not affect the GTPase activities of Mfn1 and Mfn2.

Recent findings have shown that the connectivity and crosstalk between mitochondria and the endoplasmic reticulum (ER) at mitochondria&ndash, ER contact sites (MERCS) are altered in Alzheimer&rsquo, s disease (AD) and in AD-related models. MERCS have been related to the initial steps of autophagosome formation as well as regulation of mitochondrial function. Here, the interplay between MERCS, mitochondria ultrastructure and function and autophagy were evaluated in different AD animal models with increased levels of A&beta, as well as in primary neurons derived from these animals. We start by showing that the levels of Mitofusin 1, Mitofusin 2 and mitochondrial import receptor subunit TOM70 are decreased in post-mortem brain tissue derived from familial AD. We also show that A&beta, increases the juxtaposition between ER and mitochondria both in adult brain of different AD mouse models as well as in primary cultures derived from these animals. In addition, the connectivity between ER and mitochondria are also increased in wild-type neurons exposed to A&beta, This alteration in MERCS affects autophagosome formation, mitochondrial function and ATP formation during starvation. Interestingly, the increment in ER&ndash, mitochondria connectivity occurs simultaneously with an increase in mitochondrial activity and is followed by upregulation of autophagosome formation in a clear chronological sequence of events. In summary, we report that A&beta, can affect cell homeostasis by modulating MERCS and, consequently, altering mitochondrial activity and autophagosome formation. Our data suggests that MERCS is a potential target for drug discovery in AD.

Figure S1. Immuno-labelling of biopsies of frontal cortices of iNPH patients. Representative immunohistochemistry pictures of frontal cortices of patients analysed. Patients were divided in groups according to the presence or absence of amyloid plaques and NFT. Anti-Aβ antibody (6F/3D, M0872; Dako) (first column) and anti-p-Tau antibody (AT8) (second column) were used. The arrow indicate a NFT and the star indicates neuropil threads. Scale bar = 500 μm. Table S1. Electron microscopy measurements and respective averages. Figure S2. Mitochondria number and perimeter are not significantly changed in patients diagnosed with dementia. Quantification of a number and b perimeter of mitochondria profiles from the electron micrographs of iNPH patients’ biopsies according to dementia diagnose. Non-demented patients are #1 to #4 and #6 to #12, demented patients are #5, #13 and #14. Each point represent one iNPH patient. Quantification of c number and d perimeter of mitochondria profiles from the electron micrographs of iNPH patients’ biopsies according to MMSE. MMSE scores represent: MMSE ≥27 – No significant cognitive impairment, 23 ≤ MMSE ≤26 – Minor cognitive impairment, MMSE ≤22 – moderate or severe cognitive impairment. Figure S3. Number and length of MERCS negatively with MMSE. Representation of the correlation between MMSE and mitochondria-ER contact sites a number and b length. Linear regression was performed and the Pearson correlation coefficient (r) calculated. Each point represent one iNPH patient. Figure S4. Amyloid plaques and NFT have no effect in the number of mitochondria profile nor mitochondria perimeter. Quantification of a number and b perimeter of mitochondria profiles from the electron micrographs of iNPH patients biopsies. Aβ−/tau− patients present no amyloid plaques nor NFT; Aβ+/tau− patients presents amyloid plaques but not NFT; and Aβ+/tau+ patients present both amyloid plaques and NFT. Each point represent a different iNPH patient. (PDF 16959 kb)

Neurodegenerative diseases are a spectrum of chronic, debilitating disorders characterised by the progressive degeneration and death of neurons. Mitochondrial dysfunction has been implicated in most neurodegenerative diseases, but in many instances it is unclear whether such dysfunction is a cause or an effect of the underlying pathology, and whether it represents a viable therapeutic target. It is therefore imperative to utilise and optimise cellular models and experimental techniques appropriate to determine the contribution of mitochondrial dysfunction to neurodegenerative disease phenotypes. In this consensus article, we collate details on and discuss pitfalls of existing experimental approaches to assess mitochondrial function in in vitro cellular models of neurodegenerative diseases, including specific protocols for the measurement of oxygen consumption rate in primary neuron cultures, and single-neuron, time-lapse fluorescence imaging of the mitochondrial membrane potential and mitochondrial NAD(P)H. As part of the Cellular Bioenergetics of Neurodegenerative Diseases (CeBioND) consortium ( www.cebiond.org ), we are performing cross-disease analyses to identify common and distinct molecular mechanisms involved in mitochondrial bioenergetic dysfunction in cellular models of Alzheimer's, Parkinson's, and Huntington's diseases. Here we provide detailed guidelines and protocols as standardised across the five collaborating laboratories of the CeBioND consortium, with additional contributions from other experts in the field.