Comparing in vitro protein aggregation modelling using strategies relevant to neuropathologies

doi:10.21203/rs.3.rs-5327214/v1

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Comparing in vitro protein aggregation modelling using strategies relevant to neuropathologies

https://doi.org/10.21203/rs.3.rs-5327214/v1

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Although protein aggregation is involved in physiological ageing-related processes, it is also remarkably associated with several neuropathologies, including Alzheimer´s (AD) and Parkinson´s disease (PD). The first is characterized by hyperphosphorylated tau protein and Aβ peptide deposition, thus forming intracellular neurofibrillary tangles and extracellular senile plaques, respectively; while, in PD, α-synuclein aggregates and deposits as Lewy bodies.

Considerable research has focused on developing protein aggregation models to be explored as research tools. In the present work, four alternative models for studying protein aggregation were explored and compared, namely treatment with: the toxic Aβ peptide, the isoflavone rotenone, the ATP synthase inhibitor oligomycin, and the proteosome inhibitor MG-132.

All treatments result in aggregation-relevant events in a human neuronal cell line, but significant model-dependent differences were observed. In terms of promoting aggregate formation, Aβ and MG-132 provoked the greatest effect, but only MG-132 was associated with an increase in the HSP-70 chaperone. In fact, the type of aggregates formed appear to be dependent on the treatment employed, and supports the hypothesis that Aβ exposure is a relevant AD model, and rotenone is in fact a good model for PD. Furthermore, the results revealed that protein phosphorylation is relevant to aggregate formation and as expected, tau co-localized to the deposits formed in the Aβ peptide aggregate induction cell model. In summary, different molecular processes can be induced by using distinct aggregation modelling strategies, and these can be used to study different protein-aggregation related processes associated with distinct neuropathologies.

Alzheimer´s disease

Parkinson´s disease

Aβ1–42 peptide

Protein aggregation

Mitochondrial dysfunction

In healthy organisms, protein homeostasis is maintained through a series of cellular and organelle based systems: under normal conditions, misfolded proteins are targeted for degradation via ubiquitin-proteasome or lysosomes-autophagy systems¹; the endoplasmic reticulum (ER) and mitochondria have specialized forms of autophagy (ER-phagy and mitophagy, respectively)²; additionally, under proteotoxic stress, the unfolded protein response (UPR) can be activated in the ER or in mitochondria (mtUPR), leading to chaperone upregulation and attenuation of protein translation³. In spite of all these proteostatic mechanisms, cell capability to maintain protein homeostasis is compromised with age and chronic stress, resulting in cellular accumulation of protein aggregates⁴. It is consensual that these processes contribute to late onset neurodegenerative disorders, like Alzheimer’s disease (AD)⁵ and Parkinson’s disease (PD)⁶, but the specific contribution of protein aggregation to pathological conditions remains a matter of debate and intensive research.

The hallmarks of AD are the accumulation of senile plaques and intraneuronal neurofibrillary tangles, resulting from extracellular deposition of the amyloid beta (Aβ) peptide⁷ and intracellular accumulation of hyperphosphorylated tau⁸, respectively.

Aβ peptide is a metabolite of the Amyloid Precursor Protein (APP)^9,10. This transmembranal protein can be sequentially cleaved via alternative pathways¹⁰: Cleavage by α-¹¹ and γ-secretases¹², the non-amyloidogenic processing, releases a soluble N-terminal fragment (sAPPα) and a C-terminal fragment (CTF), the latter subsequently cleaved into P3 and AICD (amyloid precursor protein intracellular domain)¹³. In the amyloidogenic processing pathway, however, APP is alternatively cleaved in the N-terminal domain by β- and γ-secretases, releasing a soluble N-terminal fragment (sAPPβ) and a CTF, which is in turn cleaved, resulting in Aβ40 or Aβ42 peptide (several species are possible outcomes) and AICD^10,14–17.

Microtubule-associated tau has 85 phosphorylatable residues, 45 of which have been found to be phosphorylated in the AD brain, notably Thr231, shown to be specific for AD¹⁸. Thr231 phosphorylation is critical for tau hyperphosphorylation by GSK-3β¹⁹: this residue is part of the microtubule-binding domain of tau, and its phosphorylation promotes tau-microtubule detachment, decreasing microtubule assembly, with dire functional and homeostatic consequences²⁰. As such, evaluation of Thr231 phosphorylation is an important step to identify and characterize ‘in vitro’ AD models.

PD is another significant protein aggregation-related disease, characterized by fibril formation (Lewy Bodies), resulting from aggregation of the protein α-synuclein²¹. Lewy inclusions are found in regions where cell loss occurs, such as neurons in the substantia nigra, olfactory bulbs, hypothalamus and amygdala nuclei, for example, and are the pathological hallmark of several forms of parkinsonism²².

Mitochondrial (dys)function is a cellular anomaly that has been associated with several neurodegenerative disorders, including AD and PD^23–25. The processing and degradation of most proteins is energy dependent, and direct disruption of mitochondria ATP potentiates the accumulation of misfolded proteins, by disturbing the ubiquitin-proteasome system ²⁶, in a process aggravated with ageing²⁷. In vivo studies in rats have established that treatment with rotenone, an inhibitor of mitochondria complex I, results in dopaminergic degeneration, cytoplasmic α-synuclein and ubiquitin inclusions, and motor deficits, all characteristics of parkinsonian pathogenesis^28,29. Moreover, oxidative stress and energy depletion can induce amyloidogenic processing of APP, and consequently Aβ peptide production ^30,31, as is the case of H₂O₂-induced oxidative stress in human neuroblastoma cells, which results in intracellular Aβ accumulation ³². On the other hand, mitochondrial dysfunctions, observed in AD and PD, can be induced by Aβ peptide ³³ or α-synuclein ³⁴, in a feedback loop that illustrates the complex relationship between metabolic homeostasis and proteostasis.

In experimental setups, models of protein aggregation are employed to mimic disease states and thus study the underlying molecular processes associated with pathology. In this study, we characterize four different cellular protein aggregation strategies and compare their responses at a molecular level: protein aggregation was chemically induced by mitochondria complex I inhibition (with the isoflavone rotenone), ATP synthase inhibition (using oligomycin), proteasome inhibition (with MG-132, typically employed to model PD), and treatment with Aβ-peptide (a traditional in vitro model of AD). The different experimental protocols were evaluated by monitoring the levels of relevant proteins involved in specific aggregation-related diseases.

Antibodies

Aβ1–42 peptide (GenicBio) was dissolved in sterile miliQ water to obtain a 1mM stock solution. Rotenone (Taper) was prepared as a 10mM stock in DMSO. Oligomycin (Alomone) was dissolved in DMSO to obtain a 5mM stock solution. MG-132 (Taper) was dissolved in DMSO to obtain a 4mM stock solution.

The primary antibodies used were mouse monoclonal antibody anti-APP, clone 22C11 (1:250, #MAB348, Chemicon International) to detect APP and total sAPP; rabbit polyclonal anti-tau antibody (1:500, #PA5-27287, Invitrogen) to detect total tau; rabbit monoclonal anti-ptau (Thr231), clone 1H6L6 (1:1000, #701056, Invitrogen/Life Technologies) to specifically recognize ptau (Thr231) residue; mouse polyclonal anti-α-synuclein antibody (1:400 WB and 1:50 ICC, #sc-12767, Santa Cruz Biotechnology); and rabbit monoclonal anti-HSP-70 antibody (1:1000, #SPA-812, Stressgen Biotechnologies) to detect Heat Shock Protein 70.

Horseradish peroxidase-conjugated anti-mouse (1:5000) or anti-rabbit (1:5000) IgGs were used as secondary antibodies (Amersham Pharmacia) for immunoblotting.

Cell Culture

SH-SY5Y cells (ATCC® CRL-2266™) were grown and maintained in Minimal Essential Medium MEM/F12 1:1 supplemented with 10% Fetal Bovine Serum (FBS), Sodium pyruvate 0.05 g/L and 1% antibiotic-antimycotic. Cultures were maintained in a humidified chamber at 37°C under 5% CO2. Cells were subcultured when 80–90% confluence was reached ^35,36.

Fibroblasts from 80-years old human donors were commercially obtained (Axol Bioscience) and incubated at 37°C in a humidified atmosphere of 5% CO₂ and 95% air, cultured with Dulbecco’s Modified Eagle’s Medium (DMEM) supplemented with 15% fetal bovine serum (FBS), up to a maximum of 20 passages ²⁷.

Treatments

Cells were incubated with Aβ1–42 peptide, rotenone, oligomycin and MG-132.

Stock solution of Aβ1–42 peptide (1mM) was aggregated in phosphate-buffered saline (PBS, pH 7.4), for 48 hours at 37 ⁰C (100µM aggregated stock) prior to treatment ^37,38. Aggregated peptide was diluted in serum-free medium, before adding to the cells in culture, at a concentration of 10 µM, for 24 h. This concentration had already been tested previously in our laboratory ³⁷.

Stock solutions of rotenone, oligomycin and MG-132 were prepared and diluted in serum-free MEM:F12 (1:1). Rotenone induces a dose-dependent cytotoxic effect, so in this study this mitochondrial inhibitor was added to cells at a concentration of 10nM for 24h ³⁹. Oligomycin and MG-132 were added to cells at a final concentration of 5nM and 5µM, respectively, and left overnight; dose and treatment times were selected in agreement with experience in the laboratory using fibroblasts from human donors ²⁷. Proteasome inhibitor was added to cells at concentrations indicated in Proteostat Aggresome Detection Kit (Enzo Life Sciences).

Resazurin Assay

For the resazurin assay, SH-SY5Y cells were plated in 96-well plates at a density of 2.0x10⁴ cells/well. Following treatments, resazurin dye was added to the cells at a final concentration of 10 µg/mL and incubated at 37°C for 4 hours, before reading absorbance intensity at 570 nm using a microplate reader.

Sample collection and protein analysis

Cells were plated in 6-well plates at a density of 8.0x10⁵ cells/well. Following treatments, cells were washed with ice-cold PBS and collected in RIPA lysis buffer (Sigma) containing a protease inhibitor cocktail (cOmplete, EDTA-free, Roche) and supplemented with NaF (7.5mM) and Na₃VO₄ (1mM). Cell lysates were sonicated (two cycles of 5 seconds) and stored at -20 ⁰C. A BCA assay kit (Alfagene), was performed to determine protein concentration and samples were normalized for protein content. Conditioned media was collected into Sodium Dodecyl Sulfate (SDS) (final concentration 1%) and incubated at 100 ⁰C for 10min.

Samples were electrophoretically separated using 5–20% gradient SDS-PAGE gels and transferred to a nitrocellulose membrane, followed by immunoblotting for proteins of interest. 50 µg total protein were loaded per well per sample and further normalized to ponceau. Detection was performed using the chemiluminescent method with ECL (Amersham pharmacia), and bands were quantified with Chemidoc Touching Images (BioRad). Protein bands were quantified using ImageLab 6.0.1 software.

Immunofluorescence microscopy

Cells were cultured on coverslips in 12-well plates (1.8x10⁵ cells/well), and washed twice with PBS, after treatment, and fixed with 4% formaldehyde for 20 min. Cells were subsequently washed and permeabilized with 0.5% triton X-100 and EDTA 3 mM (pH 8) for 30 min with shaking at 4 ⁰C. After permeabilization, cells were washed with PBS and stained with Proteostat Aggresome Detection Kit (1:3000) (Enzo Life Sciences) for 30 min at room temperature, to detect aggregated proteins. Following sample mounting, with Vectashield Mounting Medium with DAPI (Vector Labs), cells were imaged by fluorescence microscopy using Zeiss Axioimager Z1 microscope. Four fields were randomly analyzed from 3 independent experiments for each condition, samples were scored for protein aggregation positive cells.

For immunocytochemistry, fixed cells were incubated with ptau (Thr231) (1:500) or α-synuclein (1:50) antibodies for 3 h prior to proteostat staining, following which, preparations were incubated with Alexa Fluor 488 (Invitrogen) secondary antibody before mounting, and imaging was carried out as previously described ³⁵.

Quantification and Statistical Analysis

Image Lab 6.0.1 software (Bio-Rad) was used to quantify band intensity in immunoblots and correlate it with protein levels. Data are expressed as mean ± SEM determinations, from at least three independent experiments. Statistical analysis was carried out by one-way ANOVA. When F values were significant, Dunnett test was applied to compare all groups vs. control. For Aβ experiments in human fibroblasts, one-sample t-test analysis was performed. The level of significance accepted was *P < 0.05; **P < 0.01 and ***P < 0.001.

Mitochondrial disruption fails to increase overall protein aggregation in a neuronal cell line

Several different in vitro models are currently being explored to model protein aggregation-associated neuropathologies, but no thorough comparison between these has yet been described. In this work, we explore the three most common types of aggregation protocols: pathology-associated mechanism (treatment with aggregated Aβ1–42 peptide), redox imbalance (inhibition of mitochondrial respiratory chain complex I with rotenone), energy dysfunction (inhibition of mitochondrial ATP synthesis with oligomycin), and direct proteostasis disruption (proteosome inhibition with MG-132).

Cells from the human neuroblastoma cell line SH-SY5Y were thus treated with aggregated Aβ1–42 peptide, rotenone, oligomycin and MG-132. The first parameter evaluated was overall protein aggregate formation. Protein aggregation was measured by fluorescence microscopy, using the proteostat aggresome detection dye. To assist colocalization, nuclei were stained with DAPI (Fig. 1a).

The most marked response was obtained upon incubation with aggregated Aβ1–42 peptide, which resulted in a dramatic 14-fold increase in protein aggregation, when compared to control cells, with large aggregates being detected in most observed cells (Fig. 1a and b). Mitochondrial function and ATP production are essential for protein degradation, and mitochondria dysfunction is an important mechanism underlying several neuropathologies. Thus, to evaluate the effects of oxidative stress, mitochondrial dysfunction, and ATP depletion in protein aggregation, SH-SY5Y were treated with rotenone and oligomycin. Rotenone is an inhibitor of mitochondrial complex I, promoting electron accumulation in the mitochondrial matrix and resulting in increased reactive oxygen species (ROS) production ⁴⁰. Oligomycin induces ATP depletion by inhibiting ATP synthase activity. However, despite the above-described effects on mitochondrial dysfunction, no significant differences were observed in aggregate formation upon cell treatment (although rotenone did reveal a small increase) (Fig. 1a and b). The fact that both treatments failed to promote protein aggregation in SH-SY5Y cells is a surprising result, considering that these treatments are often used in cellular models to study the molecular basis of aggregate forming disorders ^41,42. The final aggregation model tested relies on the proteasome inhibitor MG-132. Due to its mode of action, this aldehyde did elicit a strong response in SH-SY5Y cells. Incubation with this compound resulted in a dramatic 10-fold increase in protein aggregation (Fig. 1a and b), but even so, the increase was not as great as that obtained by incubation with Aβ.

Resazurin assay, commonly used to assess the number of live cells in a sample and monitor cell viability / cytotoxicity, indicated that cells were not particularly affected in terms of viability with any treatments (Fig. 1c), with oligomycin being the only condition to show a small, not statistically significant (p = 0.1351), increase in metabolic rate, compared to control conditions.

Protein folding/misfolding and aggregation can be regulated by different mechanisms; in cells under proteotoxic stress, the activation of the UPR is a significant process, as is consequent upregulation of chaperones. The UPR-associated chaperone HSP-70 is expressed in response to stress; its levels in the different models were thus assessed by western-blotting.

A larger than 4-fold increase was observed with proteasome inhibition, by MG-132, reiterating the dysregulation of protein homeostasis and activation of UPR (Fig. 1d and e), while treatments with Aβ, rotenone, or oligomycin did not alter the levels of HSP-70 (Fig. 1d and e), clearly highlighting that the underlying mechanisms of aggregate formation by Aβ and MG-132 are distinct.

Aggregate heterogeneity: different conditions model different physiological phenomena

Having determined that aggregates formed by Aβ and MG-132 appear to arise by distinct processes, deposit morphology was then analysed. Aggregates are morphologically distinct: Aβ-induced aggregates are larger and tend to agglomerate as a single deposit (Fig. 1a), reinforcing the relevance of this model to study AD related events, as it is reminiscent of processes associated with fragment accumulation ^14,16; in contrast, MG-132 induces several smaller aggregate punctate formations, consistent with processes associated with the UPR response and oxidative stress. As already described, oligomycin and rotenone produce only a few aggregates, and when formed these resemble those obtained with the latter.

Disease-specific protein aggregates are a histopathological hallmark of several neuropathologies, distinguished by the type of deposited protein. PD is notably characterised by the formation of Lewy bodies, resulting from α-synuclein aggregation ²²; being so, α-synuclein levels were evaluated by western blot analysis to characterize these aggregation protocols as possible PD models (Fig. 2). α-synuclein levels tend to increase with all aggregation models tested, as determined by western blot analysis (Fig. 2a and b); strikingly, the treatments provoking the highest response in terms of aggregation formation (Aβ and MG-132) were not the ones promoting more α-synuclein accumulation.

Mitochondria dysregulation is tightly associated with neurodegeneration in PD ^24,43 and some mitochondria-damaging pesticides have been linked with PD incidence and parkinsonian-symptoms ⁴⁴, including α-synuclein deposition and aggregation ⁴⁵. As such, results obtained with rotenone treatment, the most effective protocol to induce the formation of α-synuclein aggregates (Fig. 2 and supplementary Fig. 1), are consistent with the current state-of-the-art and reinforce the notion that rotenone is in fact a good cellular model for PD.

Aggregate formation is associated with increases in tau Thr231 phosphorylation in SH-SY5Y cells

The formation of protein aggregates is often associated with protein phosphorylation- and hyperphosphorylation-related events. Considering the results of mitochondrial dysfunction and proteasomal inhibition, and given the association between AD and tau phosphorylation, its levels were then evaluated. Results revealed that proteasome inhibition with MG-132 had the greatest increase in tau phosphorylation (Fig. 3a), with an almost two-fold increase in p-tau/tau ratio (p = 0.0187) (Fig. 3b).

Considering that tau phosphorylation diminishes its microtubule-binding ability and leads to aggregation [25], the increased ptau/tau ratio resulting from MG-132 treatment can ultimately be resulting in neurofibrillary tangle formation. Although not statistically significant, there is a tendency for Aβ to increase tau phosphorylation; our group had previously described tau phosphorylation to increase in neuronal primary cultures treated with aggregated Aβ1–42 ³⁷, and immunofluorescence studies suggest phosphorylated tau to localize to the cellular aggregates formed after Aβ exposure (Supplementary Fig. 2).

Pathological tau phosphorylation is intimately associated with mitochondria dysfunction: hyperphosphorylated and aggregated tau disrupts mitochondrial axonal transport and dynamics, while mitochondrial dysfunction promotes tau pathology in AD ⁴⁶. Our results revealed a marginal increase in tau phosphorylation with rotenone, albeit not statistically significant (p = 0.8334); however, treatment with oligomycin appears to decrease the ratio of p-tau (Thr231) phosphorylation (Fig. 3b).

APP metabolism can be modulated not only by Aβ1–42, but also by proteosome inhibition

Tau, one of the key proteins involved in AD, is clearly directly affected by the aggregation protocols here assessed. The other protein more obviously linked to AD is APP; as such, procedures were set up to evaluate if proteasomal inhibition and mitochondrial dysfunction can alter APP levels in SH-SY5Y cells. The APP monoclonal antibody 22C11 was used in conditioned medium to assess extracellular secreted APP (esAPP), and cell lysates to detect holo- and intracellular secreted APP (hAPP and isAPP, respectively) (Fig. 4a).

Proteasomal inhibition induced by MG-132 modulates both the levels of esAPP and isAPP (Fig. 4b and c, respectively), while oligomycin appears to marginally decrease APP secretion, with no variations in intracellular APP levels (Fig. 4c). No alterations in esAPP were observed with rotenone (Fig. 4b), but isAPP appears to be slightly increased (Fig. 4c). MG-132 provoked a more marked decrease in secreted APP and in intracellular APP levels, suggesting that it is probably affecting APP transcription itself.

Fitting with our own previous work, the most marked effect was observed with the AD model of treatment with Aβ1–42 peptide, which resulted in a decrease in esAPP (Fig. 4b), contrasted by an increase in intracellular APP (Fig. 4c). We have previously described this accumulation of intracellular APP to result from APP not being secreted ³⁶, and the consistent results here presented suggest that proteasomal inhibition and mitochondrial dysfunction can be important to study other protein-aggregation related disease.

Considering the AD-relevance of this aggregation model based on a cell line, we investigated whether a similar result could be obtained using human cells. Indeed, treatment of fibroblasts from an 80-year-old human healthy donor with aggregated Aβ1–42, mirrored the results obtained in SH-SY5Y cells (Fig. 5), with a significant decrease in extracellular APP (Fig. 5b) and an increase in intracellular APP (Fig. 5c).

Alzheimer’s disease is the most common form of dementia, affecting over 55 million people worldwide (doubling every 25 years), but research is yet to develop preventive or restorative therapies; as such, in vitro models efficiently mimicking this neuropathology are extremely pertinent for current biomedical research, with obvious societal impact, and will continue to be for the foreseeable future. The present study explored and characterised different cell models that can used to study protein aggregation and protein aggregation-related diseases. Moreover, although, the importance of an in vitro AD model based on commercially available cell lines cannot be overstated, a more physiologically significant alternative model would also be of paramount value. One such tool is the use of fibroblasts from human donors, which can be obtained via minimally invasive biopsy, with each cell line reflecting the uniqueness of the donor themself. This work characterises alternative cellular models to mimic AD, one using the neuronal cell line SH-SY5Y, and the other using human fibroblasts from healthy donors.

Incubation of the neuronal cell line SH-SY5Y with aggregated Aβ1–42 greatly increases protein aggregation, relatively to control cells, even more so than proteasome inhibition (Fig. 1a), confirming it as a good model to study the protesostasis-related aspects in AD.

The different models feature distinct aggregates (Fig. 1a). Those induced by Aβ are typical of aggregates formed by the accumulation of peptides: this is the case of Aβ aggregation, but a similar process occurs with the accumulation of huntingtin fragments ^47,48 or synphilin-1 ⁴⁹. The fact that the larger aggregates were obtained upon Aβ addition is consistent with literature, as it has been well reported that aggregated Aβ recruits further fragments to the deposits ⁵⁰ possibly even including secreted APP ³⁶. Given the described aggregate characteristics, it is reasonable to posit that Aβ approximates aggregate formation associated with AD.

The chaperone HSP-70 plays crucial roles in proteostasis, and is currently being explored as a good target to modulate the AD-phenotype, with studies suggesting shown that AD pathology can be supressed by increasing cellular levels of HSP-70 ^51–53. Our results show no differences in HSP-70 levels after treatment with the Aβ peptide, contrary to what was observed with MG-132, indicating that Aβ and MG-132 trigger distinct aggregate formation mechanisms.

We have previously described this model to increase tau phosphorylation in rat primary cortical neuronal cultures ³⁷. Tau has 85 phosphorylatable residues (45 of which found in AD brains) ¹⁸; however, it has been demonstrated that residue Thr231 is the primary phosphorylation site for GSK-3β, critical for tau hyperphosphorylation, and phosphorylation at this residue can destabilize tau-binding to microtubules and promote tau aggregation ¹⁹. Although in this study only a slight increase in Thr231 phosphorylation was suggested in response to incubation with oligomerised Aβ1–42, it appeared to colocalize intensely with increased aggresomes, suggesting that phospho-tau is aggregating or being sequestrated in protein aggregates (Supplementary Fig. 2).

The Aβ1–42 peptide model also exhibits a decrease in extracellular APP and increase in intracellular APP, in both neuronal (Fig. 4) and non-neuronal (Fig. 5) cells lines, suggesting that APP metabolism is hindered, accordant to our previous work with primary neuronal cultures³⁸.

High levels of α-synuclein in cerebrospinal fluid (CSF) have been reported in patients with AD and mild cognitive impairment. Consistently, our results suggest an increase in α-synuclein levels (Fig. 3) and aggregation (Supplementary Fig. 1) upon treatment with Aβ1–42 peptide, strengthening the relevance of this model to study different protein aggregation-related phenotypes.

With aging, mitochondrial function is compromised, impairing metabolism and increasing oxidative stress². Mitochondria-produced ATP is important for several processes of protein degradation and homeostasis; being so, manipulation of mitochondria is a sensible strategy to develop protein-aggregation cell models^26,54. Rotenone was used to induce oxidative stress in SH-SY5Y by inhibiting the mitochondrial electron chain transport, promoting electron accumulation and consequently increasing ROS levels³¹. Using a parallel approach, ATP production was disrupted by inhibiting ATP synthase with oligomycin⁵⁵. Although no significant differences were observed in protein aggregation with both chemicals, a small increase in aggregation occurs with rotenone (Fig. 1), which induced smaller aggregate punctate formation, like MG-132 (Fig. 1). Recent studies in our laboratory described that rotenone-induced protein aggregation in human fibroblasts can be rescued by caloric restriction ²⁷, and previous work has linked starvation with improved mitochondria activity, reducing oxidative stress⁵⁶, which may also contribute to the observed results. Moreover, our results suggest that mitochondria manipulation induces protein aggregation through mechanisms distinct from aggregated Aβ1–42, as it fails to fully induce the AD-phenotype observed with that model.

Another relevant point is that rotenone-induced mitochondrial dysfunction can potentiate accumulation of misfolded proteins, like α-synuclein, being a commonly used model of PD^28,29,31, and our results suggest this pesticide might be increasing the levels and aggregation of α-synuclein (Fig. 2 and Supplementary Fig. 1). While the physiological action of α-synuclein is important for mitochondrial homeostasis, its pathological aggregation can negatively impinge on mitochondrial function^57,58: soluble α-synuclein is targeted to mitochondria⁵⁹, and the interaction of oligomeric α-synuclein with mitochondria results in decreased respiration⁶⁰. Taken together, results support the use of rotenone as a good model to study PD.

The molecular chaperone HSP-70 inhibits α-synuclein fibril formation and alters the characteristics of toxic α-synuclein aggregates⁶¹, with studies in animal models describing rotenone exposure to decrease HSP-70 expression ⁶²; in various diseases, aggregation-induced toxicity is supressed by HSP-70 overexpression, reinforcing its important role in aggregation-related disease ^63,64. However, no differences in HSP-70 levels were observed in SH-SY5Y cells after rotenone exposure, suggesting that other mechanisms of UPR can be altered and be responsible for the observed increase in α-synuclein aggregation.

Cellular homeostasis is maintained via ubiquitin-proteasome and lysosomal-autophagic systems to prevent protein aggregation ². The aldehyde MG-132 binds to the active site of the proteasome, inhibiting its activity ⁶⁵, and is frequently used as a positive control for protein aggregation⁶⁶. As expected, protein aggregation increases with proteasome inhibition (Fig. 1), an increase that is accompanied by an in tau phosphorylation in residue Thr231. Tau hyperphosphorylation is a histological hallmark of many neurodegenerative disorders that can ultimately form tau aggregates, and proteasome inhibition has been reported to promote degradation and oligomeric accumulation of tau⁶⁷. Aggregates produced by MG-132 are typical of aggregates containing ubiquitinated proteins, known as aggresome-like induced structures (ALIS) ⁶⁸. These results are consistent with the state-of-the art, given the effect of MG-132 as a proteasome inhibitor.

On the other hand, work using neuroblastoma cell lines reports proteasome inhibition to result in tau proteolysis⁶⁹, also consistent with the decrease in the levels of total tau observed in this work (Fig. 3). In parallel to decreased tau levels, APP levels (both intra- and extra-cellular) are also decreased by MG-132 (Fig. 4). A cellular safety mechanism to cope with increased protein aggregation is to reduce protein transduction, which can explain these results. Moreover, proteasome inhibition has been described to promote a reduction in mature APP/APLP1 (amyloid beta precursor-like protein 1) via autophagy induction ⁷⁰.

In contrast to the other models explored in this study, HSP-70 expression was found to increase with proteasome inhibition, in agreement with other studies reporting MG-132 to result in accumulation of ubiquitinated proteins and increase in HSPs expression ⁷¹.

To conclude, this study establishes and characterizes different cellular models for protein aggregation-related diseases, which we believe are of great value for studies in related research fields. By adequately applying these protocols to model the more appropriate disease or biological process, several additional scientific questions and disease-related mechanisms can be explored.

The authors declare no competing interests.

No ethics approvals or participation consents were necessary for the work presented. The authors consent to the publication of this manuscript and the availability of the data and material.

Acknowledgments

Image acquisition was performed in the LiM facility of iBiMED, a node of PPBI (Portuguese Platform of BioImaging): POCI-01-0145-FEDER-022122.”

This work was funded by PTDC/DTPPIC/5587/2014, POCI-01-0145-FEDER-016904, EXPL/BTM-SAL/0902/2021, CI21-00276, and also supported by Instituto de Biomedicina (iBiMED)-UIDB/ 04501/2020 and POCI-01-0145-FEDER-007628, the Fundação para a Ciência e Tecnologia (FCT) of the Ministério da Educação e Ciência, COMPETE program, the QREN and the European Union (Fundo Europeu de Desenvolvimento Regional) and by the Integrated Programme of SR&TD “pAGE” (CENTRO-01-0145-FEDER-000003), co-funded by Centro 2020 program, Portugal 2020, European Union, through the European Regional Development Fund. André Nadais (individual PhD grant SFRH/BD/121289/2016) and Diogo Trigo (2020.02006.CEECIND) were supported by the Fundação para a Ciência e Tecnologia of the Ministério da Educação e Ciência,

Author Contributions

André Nadais performed all the experiments and assisted in data analyses and article preparation. Diogo Trigo assisted in experimental set ups. Ana Gabriela Henriques assisted in experimental design and data analyses. Odete A. B. da Cruz e Silva conceived the experimental design, analysed the data and prepared the manuscript. All authors were involved in the writing of the manuscript and figure preparation.

Data Availability Statement

Data is available from the corresponding author on reasonable request

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Comparing in vitro protein aggregation modelling using strategies relevant to neuropathologies

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Abstract

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Introduction

Material and Methods

Antibodies

Cell Culture

Treatments

Resazurin Assay

Sample collection and protein analysis

Immunofluorescence microscopy

Quantification and Statistical Analysis

Results

Mitochondrial disruption fails to increase overall protein aggregation in a neuronal cell line

Aggregate heterogeneity: different conditions model different physiological phenomena

Aggregate formation is associated with increases in tau Thr231 phosphorylation in SH-SY5Y cells

APP metabolism can be modulated not only by Aβ1–42, but also by proteosome inhibition

Discussion

Declarations

References

Additional Declarations

Supplementary Files

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