Neuronal insulin resistance is linked to the pathogenesis of Parkinson’s disease through unclear, but potentially targetable, mechanisms. We delineated neuronal and glial mechanisms of insulin resistance and glucagon-like 1 peptide (GLP-1) receptor agonism in human iPSC models of synucleinopathy, and corroborated our findings in patient samples from a Phase 2 trial of a GLP-1R agonist in Parkinson’s ([NCT01971242][1]). Human iPSC models of synucleinopathy exhibit neuronal insulin resistance and dysfunctional insulin signalling, which is associated with inhibition of the neuroprotective Akt pathways, and increased expression of the MAPK-associated p38 and JNK stress pathways. Ultimately, this imbalance is associated with cellular stress, impaired proteostasis, accumulation of α-synuclein, and neuronal loss. The GLP-1R agonist exenatide led to restoration of insulin signalling, associated with restoration of Akt signalling and suppression of the MAPK pathways in neurons. GLP-1R agonism reverses the neuronal toxicity associated with the synucleinopathy, through reduction of oxidative stress, improved mitochondrial and lysosomal function, reduced aggregation of α-synuclein, and enhanced neuronal viability. GLP-1R agonism further suppresses synuclein induced inflammatory states in glia, leading to neuroprotection through non cell autonomous effects. In the exenatide-PD2 clinical trial, exenatide treatment was associated with clinical improvement in individuals with higher baseline MAPK expression (and thus insulin resistance). Exenatide treatment led to a reduction of α-synuclein aggregates, and a reduction in inflammatory cytokine IL-6. Taken together, our patient platform defines the mechanisms of GLP-1R action in neurons and astrocytes, identifies the population likely to benefit from GLP-1R agonism, and highlights the utility of GLP-1R agonism as a disease modifying strategy in synucleinopathies.### Competing Interest StatementThe authors have declared no competing interest. [1]: /lookup/external-ref?link_type=CLINTRIALGOV&access_num=NCT01971242&atom=%2Fbiorxiv%2Fearly%2F2024%2F02%2F28%2F2024.02.28.582460.atom

Parkinson’s disease is a common, incurable neurodegenerative disorder that is clinically heterogeneous: it is likely that different cellular mechanisms drive the pathology in different individuals. So far it has not been possible to define the cellular mechanism underlying the neurodegenerative disease in life. We generated a machine learning-based model that can simultaneously predict the presence of disease and its primary mechanistic subtype in human neurons. We used stem cell technology to derive control or patient-derived neurons, and generated different disease subtypes through chemical induction or the presence of mutation. Multidimensional fluorescent labelling of organelles was performed in healthy control neurons and in four different disease subtypes, and both the quantitative single-cell fluorescence features and the images were used to independently train a series of classifiers to build deep neural networks. Quantitative cellular profile-based classifiers achieve an accuracy of 82%, whereas image-based deep neural networks predict control and four distinct disease subtypes with an accuracy of 95%. The machine learning-trained classifiers achieve their accuracy across all subtypes, using the organellar features of the mitochondria with the additional contribution of the lysosomes, confirming the biological importance of these pathways in Parkinson’s. Altogether, we show that machine learning approaches applied to patient-derived cells are highly accurate at predicting disease subtypes, providing proof of concept that this approach may enable mechanistic stratification and precision medicine approaches in the future.

ABSTRACT Parkinson’s disease (PD) is a common, devastating, and incurable neurodegenerative disorder. Several molecular mechanisms have been proposed to drive PD, with genetic and pathological evidence pointing towards aberrant protein homeostasis and mitochondrial dysfunction. PD is clinically highly heterogeneous, it is likely that different mechanisms underlie the pathology in different individuals, each requiring a specific targeted treatment. Recent advances in stem cell technology and fluorescent live-cell imaging have enabled the generation of patient-derived neurons with different mechanistic subtypes of PD. Here, we performed multi-dimensional fluorescent labelling of organelles in iPSC-derived neurons, in healthy control cells, and in four different disease subclasses. We generated a machine learning-based model that can simultaneously predict the presence of disease, and its primary mechanistic subtype. We independently trained a series of classifiers using both quantitative single-cell fluorescence variables and images to build deep neural networks. Quantitative cellular profile-based classifiers achieve an accuracy of 82%, whilst image based deep neural networks predict control, and four distinct disease subtypes with an accuracy of 95%. The classifiers achieve their accuracy across all subtypes primarily utilizing the organellar features of the mitochondria, with additional contribution of the lysosomes, confirming their biological importance in PD. Taken together, we show that machine learning approaches applied to patient-derived cells are able to predict disease subtypes, demonstrating that this approach may be used to guide personalized treatment approaches in the future.

Alzheimer’s disease, which is the most common form of dementia, is characterized by the aggregation of the amyloid β peptide (Aβ) and by an impairment of calcium homeostasis caused by excessive activation of glutamatergic receptors (excitotoxicity). Here, we studied the effects on calcium homeostasis caused by the formation of Aβ oligomeric assemblies. We found that Aβ oligomers cause a rapid influx of calcium ions (Ca2+) across the cell membrane by rapidly activating extrasynaptic N-methyl-d-aspartate (NMDA) receptors and, to a lower extent, α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors. We also observed, however, that misfolded oligomers do not interact directly with these receptors. Further experiments with lysophosphatidylcholine and arachidonic acid, which cause membrane compression and stretch, respectively, indicated that these receptors are activated through a change in membrane tension induced by the oligomers and transmitted mechanically to the receptors via the lipid bilayer. Indeed, lysophosphatidylcholine is able to neutralize the oligomer-induced activation of the NMDA receptors, whereas arachidonic acid activates the receptors similarly to the oligomers with no additive effects. An increased rotational freedom observed for a fluorescent probe embedded within the membrane in the presence of the oligomers also indicates a membrane stretch. These results reveal a mechanism of toxicity of Aβ oligomers in Alzheimer’s disease through the perturbation of the mechanical properties of lipid membranes sensed by NMDA and AMPA receptors.

The accumulation of protein deposits in neurodegenerative diseases has been hypothesized to depend on a metastable subproteome vulnerable to aggregation. To investigate this phenomenon and the mechanisms that regulate it, we measured the solubility of the proteome in the mouse Neuro2a cell line under six different protein homeostasis stresses: 1) Huntington's disease proteotoxicity, 2) Hsp70, 3) Hsp90, 4) proteasome, 5) endoplasmic reticulum (ER)-mediated folding inhibition, and 6) oxidative stress. Overall, we found that about one-fifth of the proteome changed solubility with almost all of the increases in insolubility were counteracted by increases in solubility of other proteins. Each stress directed a highly specific pattern of change, which reflected the remodeling of protein complexes involved in adaptation to perturbation, most notably, stress granule (SG) proteins, which responded differently to different stresses. These results indicate that the protein homeostasis system is organized in a modular manner and aggregation patterns were not correlated with protein folding stability (ΔG). Instead, distinct cellular mechanisms regulate assembly patterns of multiple classes of protein complexes under different stress conditions.

To function effectively proteins must avoid aberrant aggregation, and hence they are expected to be expressed at concentrations safely below their solubility limits. By analyzing proteome-wide mass spectrometry data of Caenorhabditis elegans, however, we show that the levels of about three-quarters of the nearly 4,000 proteins analyzed in adult animals are close to their intrinsic solubility limits, indeed exceeding them by about 10% on average. We next asked how aging and functional self-assembly influence these solubility limits. We found that despite the fact that the total quantity of proteins within the cellular environment remains approximately constant during aging, protein aggregation sharply increases between days 6 and 12 of adulthood, after the worms have reproduced, as individual proteins lose their stoichiometric balances and the cellular machinery that maintains solubility undergoes functional decline. These findings reveal that these proteins are highly prone to undergoing concentration-dependent phase separation, which on aging is rationalized in a decrease of their effective solubilities, in particular for proteins associated with translation, growth, reproduction, and the chaperone system.

The formation of misfolded protein oligomers during early stages of amyloid aggregation and the activation of neuroinflammatory responses are two key events associated with neurodegenerative diseases. Although it has been established that misfolded oligomers are involved in the neuroinflammatory process, the links between their structural features and their functional effects on the immune response remain unknown. To explore such links, we took advantage of two structurally distinct soluble oligomers (type A and B) of protein HypF-N and compared the elicited microglial inflammatory responses. By using confocal microscopy, protein pull-down, and high-throughput mass spectrometry, we found that, even though both types bound to a common pool of microglial proteins, type B oligomers-with a lower solvent-exposed hydrophobicity-showed enhanced protein binding, correlating with the observed inflammatory response. Furthermore, the interactome associated with inflammatory-mediated neurodegeneration revealed previously unidentified receptors and signaling molecules likely to be involved in the oligomer-elicited innate immune response.

Stress-inducible molecular chaperones have essential roles in maintaining protein homeostasis, but the extent to which they affect overall proteome stability remains unclear. Here, we analyze the effects of the DnaK (Hsp70) system on protein stability in Escherichia coli using pulse proteolysis combined with quantitative proteomics. We quantify ∼1,500 soluble proteins and find ∼500 of these to be protease sensitive under normal growth conditions, indicating a high prevalence of conformationally dynamic proteins, forming a metastable subproteome. Acute heat stress results in the unfolding of an additional ∼200 proteins, reflected in the exposure of otherwise buried hydrophobic regions. Overexpression of the DnaK chaperone system markedly stabilizes numerous thermo-sensitive proteins, including multiple ribosomal proteins and large, hetero-oligomeric proteins containing the evolutionarily ancient c.37 fold (P loop nucleoside triphosphate hydrolases). Thus, the Hsp70 system, in addition to its known chaperone functions, has a remarkable capacity to stabilize proteins in their folded states under denaturing stress conditions.

Background: The nematode worm C. elegans is a model organism widely used for studies of genetics and of human disease. The health and fitness of the worms can be quantified in different ways, such as by measuring their bending frequency, speed or lifespan. Manual assays, however, are time consuming and limited in their scope providing a strong motivation for automation. New method: We describe the development and application of an advanced machine vision system for characterising the behaviour of C. elegans, the Wide Field-of-View Nematode Tracking Platform (WF-NTP), which enables massively parallel data acquisition and automated multi-parameter behavioural profiling of thousands of worms simultaneously. Results: We screened more than a million worms from several established models of neurodegenerative disorders and characterised the effects of potential therapeutic molecules for Alzheimer's and Parkinson's diseases. By using very large numbers of animals we show that the sensitivity and reproducibility of behavioural assays is very greatly increased. The results reveal the ability of this platform to detect even subtle phenotypes. Comparison with existing methods: The WF-NTP method has substantially greater capacity compared to current automated platforms that typically either focus on characterising single worms at high resolution or tracking the properties of populations of less than 50 animals. Conclusions: The WF-NTP extends significantly the power of existing automated platforms by combining enhanced optical imaging techniques with an advanced software platform. We anticipate that this approach will further extend the scope and utility of C. elegans as a model organism. (C) 2018 Published by Elsevier B.V.

In Alzheimer's disease, aggregates of Aβ and tau in amyloid plaques and neurofibrillary tangles spread progressively across brain tissues following a characteristic pattern, implying a tissue-specific vulnerability to the disease. We report a transcriptional analysis of healthy brains and identify an expression signature that predicts-at ages well before the typical onset-the tissue-specific progression of the disease. We obtain this result by finding a quantitative correlation between the histopathological staging of the disease and the expression patterns of the proteins that coaggregate in amyloid plaques and neurofibrillary tangles, together with those of the protein homeostasis components that regulate Aβ and tau. Because this expression signature is evident in healthy brains, our analysis provides an explanatory link between a tissue-specific environmental risk of protein aggregation and a corresponding vulnerability to Alzheimer's disease.

Aging has been associated with a progressive decline of proteostasis, but how this process affects proteome composition remains largely unexplored. Here, we profiled more than 5,000 proteins along the lifespan of the nematode C. elegans. We find that one-third of proteins change in abundance at least 2-fold during aging, resulting in a severe proteome imbalance. These changes are reduced in the long-lived daf-2 mutant but are enhanced in the short-lived daf-16 mutant. While ribosomal proteins decline and lose normal stoichiometry, proteasome complexes increase. Proteome imbalance is accompanied by widespread protein aggregation, with abundant proteins that exceed solubility contributing most to aggregate load. Notably, the properties by which proteins are selected for aggregation differ in the daf-2 mutant, and an increased formation of aggregates associated with small heat-shock proteins is observed. We suggest that sequestering proteins into chaperone-enriched aggregates is a protective strategy to slow proteostasis decline during nematode aging.

Aging has been associated with a progressive decline of proteostasis, but how this process manifests itself at the level of proteome composition remains largely unexplored. Here we profiled more than 5,000 proteins along the lifespan of the nematode C. elegans. We find that one third of proteins change in abundance at least 2-fold during aging, resulting in a severe proteome imbalance. These changes are reduced in the long-lived daf-2 mutant, but enhanced in the short-lived daf-16 mutant. While ribosomal proteins decline and lose normal stoichiometry, proteasome complexes increase. Proteome imbalance is accompanied by widespread protein aggregation, with abundant proteins that exceed solubility contributing most to aggregate load. Notably, the properties by which proteins are selected for aggregation differ in the daf-2 mutant, and an increased formation of aggregates associated with small heat shock …

Ubiquitin-proteasome system (UPS) proteins and proteolytic activity are localized in a recently identified cytoplasmic structure characterized by accumulation of barrel-like particles, which is known as the particulate cytoplasmic structure (PaCS). PaCSs have been detected in neoplastic, preneoplastic, chronically infected, and fetal cells, which produce high amounts of misfolded proteins to be degraded by the UPS. Chaperone molecules are crucial in the early stages of handling misfolded proteins; therefore, we searched for these molecules in PaCSs. Heat shock proteins (Hsp), Hsp90, Hsp70, Hsp40, and Bcl-2associated athanogene (Bag)3 chaperones, although not Bag6, were selectively concentrated into PaCSs of several cell lines and ex vivo fetal or neoplastic cells. Present findings point to PaCSs as an integrated, active UPS center well equipped for metabolism of misfolded proteins, especially in cells under physiological (fetal development) or pathological (neoplasia or inflammation) stress. Stephanie: Nature Plants 1) Article: Associations with rhizosphere bacteria can confer an adaptive advantage to plants Cara H. Haney, Buck S. Samuel, Jenifer Bush & Frederick M. Ausubel Abstract: Host-associated microbiomes influence host health. However, it is unclear whether genotypic variations in host organisms influence the microbiome in ways that have adaptive consequences for the host. Here, we show that wild accessions of Arabidopsis thaliana differ in their ability to associate with the root-associated bacterium Pseudomonas fluorescens, with consequences for plant fitness. In a screen of 196 naturally occurring Arabidopsis accessions we identified lines that actively suppress Pseudomonas growth under gnotobiotic conditions. We planted accessions that support disparate levels of fluorescent Pseudomonads in natural soils; 16S ribosomal RNA sequencing revealed that accession-specific differences in the microbial communities were largely limited to a subset of Pseudomonadaceae species. These accessionspecific differences inPseudomonas growth resulted in enhanced or impaired fitness that depended on the host’s ability to support Pseudomonas growth, the specific Pseudomonas strains present in the soil and the nature of the stress. We suggest that small host-mediated changes in a microbiome can have large effects on host health. Host-associated microbiomes influence host health. However, it is unclear whether genotypic variations in host organisms influence the microbiome in ways that have adaptive consequences for the host. Here, we show that wild accessions of Arabidopsis thaliana differ in their ability to associate with the root-associated bacterium Pseudomonas fluorescens, with consequences for plant fitness. In a screen of 196 naturally occurring Arabidopsis accessions we identified lines that actively suppress Pseudomonas growth under gnotobiotic conditions. We planted accessions that support disparate levels of fluorescent Pseudomonads in natural soils; 16S ribosomal RNA sequencing revealed that accession-specific differences in the microbial communities were largely limited to a subset of Pseudomonadaceae species. These accessionspecific differences inPseudomonas growth resulted in enhanced or impaired fitness that depended on the host’s ability to support Pseudomonas growth, the specific Pseudomonas strains present in the soil and the nature of the stress. We suggest that small host-mediated changes in a microbiome can have large effects on host health. Unraveling the functions of type II-prohibitins in Arabidopsis mitochondria 2) Janusz Piechota, Monika Bereza, Aleksandra Sokołowska, Kondrad Suszyński, Karolina Lech,Hanna Jańska Plant Molecular Biology June 2015, Volume 88, Issue 3, pp 249-267 Date: 21 Apr 2015