Probing the metabolic aberrations underlying mutant huntingtin toxicity in yeast and assessing their degree of preservation in humans and mice

Metabolomics: An Emerging "Omics" Platform for Systems Biology and Its Implications for Huntington Disease Research

Huntington's disease (HD) is a progressive, fatal neurodegenerative disease characterized by motor, cognitive, and psychiatric symptoms. The precise mechanisms of HD progression are poorly understood; however, it is known that there is an expansion of the trinucleotide cytosine-adenine-guanine (CAG) repeat in the Huntingtin gene. Important new strategies are of paramount importance to identify early biomarkers with predictive value for intervening in disease progression at a stage when cellular dysfunction has not progressed irreversibly. Metabolomics is the study of global metabolite profiles in a system (cell, tissue, or organism) under certain conditions and is becoming an essential tool for the systemic characterization of metabolites to provide a snapshot of the functional and pathophysiological states of an organism and support disease diagnosis and biomarker discovery. This review briefly highlights the historical progress of metabolomic methodologies, followed by a more detailed review of the use of metabolomics in HD research to enable a greater understanding of the pathogenesis, its early prediction, and finally the main technical platforms in the field of metabolomics.

Saccharomyces cerevisiae as a Model for Studying Human Neurodegenerative Disorders: Viral Capsid Protein Expression

In this article, we briefly describe human neurodegenerative diseases (NDs) and the experimental models used to study them. The main focus is the yeast Saccharomyces cerevisiae as an experimental model used to study neurodegenerative processes. We review recent experimental data on the aggregation of human neurodegenerative disease-related proteins in yeast cells. In addition, we describe the results of studies that were designed to investigate the molecular mechanisms that underlie the aggregation of reporter proteins. The advantages and disadvantages of the experimental approaches that are currently used to study the formation of protein aggregates are described. Special attention is given to the similarity between aggregates that form as a result of protein misfolding and viral factories-special structural formations in which viral particles are formed inside virus-infected cells. A separate part of the review is devoted to our previously published study on the formation of aggregates upon expression of the insect densovirus capsid protein in yeast cells. Based on the reviewed results of studies on NDs and related protein aggregation, as well as viral protein aggregation, a new experimental model system for the study of human NDs is proposed. The core of the proposed system is a comparative transcriptomic analysis of changes in signaling pathways during the expression of viral capsid proteins in yeast cells.

Metabolic deregulation associated with aging modulates protein aggregation in the yeast model of Huntington's disease

Huntington's disease is associated with increased CAG repeat resulting in an expanded polyglutamine tract in the protein Huntingtin (HTT) leading to its aggregation resulting in neurodegeneration. Previous studies have shown that N-terminal HTT with 46Q aggregated in the stationary phase but not the logarithmic phase in the yeast model of HD. We carried out a metabolomic analysis of logarithmic and stationary phase yeast model of HD expressing different polyQ lengths attached to N-terminal HTT tagged with enhanced green fluorescent protein (EGFP). The results show significant changes in the metabolic profile and deregulated pathways in stationary phase cells compared to logarithmic phase cells. Comparison of metabolic pathways obtained from logarithmic phase 46Q versus 25Q with those obtained for presymptomatic HD patients from our previous study and drosophila model of HD showed considerable overlap. The arginine biosynthesis pathway emerged as one of the key pathways that is common in stationary phase yeast compared to logarithmic phase and HD patients. Treatment of yeast with arginine led to a significant decrease, while transfer to arginine drop-out media led to a significant increase in the size of protein aggregates in both logarithmic and stationary phase yeast model of HD. Knockout of arginine transporters in the endoplasmic reticulum and vacuole led to a significant decrease in mutant HTT aggregation. Overall our results highlight arginine as a critical metabolite that modulates the aggregation of mutant HTT and disease progression in HD.Communicated by Ramaswamy H. Sarma.

Vitamin B6, B12 and folate modulate deregulated pathways and protein aggregation in yeast model of Huntington disease

Huntington's disease (HD) is an incurable and progressive neurodegenerative disease affecting the basal ganglia of the brain. HD is caused due to expansion of the polyglutamine tract in the protein Huntingtin resulting in aggregates. The increased PolyQ length results in aggregation of protein Huntingtin leading to neuronal cell death. Vitamin B6, B12 and folate are deficient in many neurodegenerative diseases. We performed an integrated analysis of transcriptomic, metabolomic and cofactor-protein network of vitamin B6, B12 and folate was performed. Our results show considerable overlap of pathways modulated by Vitamin B6, B12 and folate with those obtained from transcriptomic and metabolomic data of HD patients and model systems. Further, in yeast model of HD we showed treatment of B6, B12 or folate either alone or in combination showed impaired aggregate formation. Transcriptomic analysis of yeast model treated with B6, B12 and folate showed upregulation of pathways like ubiquitin mediated proteolysis, autophagy, peroxisome, fatty acid, lipid and nitrogen metabolism. Metabolomic analysis of yeast model shows deregulation of pathways like aminoacyl-tRNA biosynthesis, metabolism of various amino acids, nitrogen metabolism and glutathione metabolism. Integrated transcriptomic and metabolomic analysis of yeast model showed concordance in the pathways obtained. Knockout of Peroxisomal (PXP1 and PEX7) and Autophagy (ATG5) genes in yeast increased aggregates which is mitigated by vitamin B6, B12 and folate treatment. Taken together our results show a role for Vitamin B6, B12 and folate mediated modulation of pathways important for preventing protein aggregation with potential implications for HD.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03525-y.

Integrated multi-omics analysis of Huntington disease identifies pathways that modulate protein aggregation

Huntington disease (HD) is a neurodegenerative disease associated with polyglutamine expansion in the protein huntingtin (HTT). Although the length of the polyglutamine repeat correlates with age at disease onset and severity, psychological, cognitive and behavioral complications point to the existence of disease modifiers. Mitochondrial dysfunction and metabolic deregulation are both associated with the HD but, despite multi-omics characterization of patients and model systems, their mechanisms have remained elusive. Systems analysis of multi-omics data and its validation by using a yeast model could help to elucidate pathways that modulate protein aggregation. Metabolomics analysis of HD patients and of a yeast model of HD was, therefore, carried out. Our analysis showed a considerable overlap of deregulated metabolic pathways. Further, the multi-omics analysis showed deregulated pathways common in human, mice and yeast model systems, and those that are unique to them. The deregulated pathways include metabolic pathways of various amino acids, glutathione metabolism, longevity, autophagy and mitophagy. The addition of certain metabolites as well as gene knockouts targeting the deregulated metabolic and autophagy pathways in the yeast model system showed that these pathways do modulate protein aggregation. Taken together, our results showed that the modulation of deregulated pathways influences protein aggregation in HD, and has implications for progression and prognosis. This article has an associated First Person interview with the first author of the paper.

The Tiny Drosophila Melanogaster for the Biggest Answers in Huntington's Disease

The average life expectancy for humans has increased over the last years. However, the quality of the later stages of life is low and is considered a public health issue of global importance. Late adulthood and the transition into the later stage of life occasionally leads to neurodegenerative diseases that selectively affect different types of neurons and brain regions, producing motor dysfunctions, cognitive impairment, and psychiatric disorders that are progressive, irreversible, without remission periods, and incurable. Huntington's disease (HD) is a common neurodegenerative disorder. In the 25 years since the mutation of the huntingtin (HTT) gene was identified as the molecule responsible for this neural disorder, a variety of animal models, including the fruit fly, have been used to study the disease. Here, we review recent research that used Drosophila as an experimental tool for improving knowledge about the molecular and cellular mechanisms underpinning HD.

NMR Spectroscopy-based Metabolomics of Drosophila Model of Huntington's Disease Suggests Altered Cell Energetics

Huntington's disease (HD) is a neurodegenerative disorder induced by aggregation of the pathological form of Huntingtin protein that has expanded polyglutamine (polyQ) repeats. In the Drosophila model, for instance, expression of transgenes with polyQ repeats induces HD-like pathologies, progressively correlating with the increasing lengths of these repeats. Previous studies on both animal models and clinical samples have revealed metabolite imbalances during HD progression. To further explore the physiological processes linked to metabolite imbalances during HD, we have investigated the 1D ¹H NMR spectroscopy-based metabolomics profile of Drosophila HD model. Using multivariate analysis (PCA and PLS-DA) of metabolites obtained from methanolic extracts of fly heads displaying retinal deformations due to polyQ overexpression, we show that the metabolite imbalance during HD is likely to affect cell energetics. Six out of the 35 metabolites analyzed, namely, nicotinamide adenine dinucleotide (NAD), lactate, pyruvate, succinate, sarcosine, and acetoin, displayed segregation with progressive severity of HD. Specifically, HD progression was seen to be associated with reduction in NAD and increase in lactate-to-pyruvate ratio. Furthermore, comparative analysis of fly HD metabolome with those of mouse HD model and HD human patients revealed comparable metabolite imbalances, suggesting altered cellular energy homeostasis. These findings thus raise the possibility of therapeutic interventions for HD via modulation of cellular energetics.

Metabolic profiling of presymptomatic Huntington's disease sheep reveals novel biomarkers

The pronounced cachexia (unexplained wasting) seen in Huntington’s disease (HD) patients suggests that metabolic dysregulation plays a role in HD pathogenesis, although evidence of metabolic abnormalities in HD patients is inconsistent. We performed metabolic profiling of plasma from presymptomatic HD transgenic and control sheep. Metabolites were quantified in sequential plasma samples taken over a 25 h period using a targeted LC/MS metabolomics approach. Significant changes with respect to genotype were observed in 89/130 identified metabolites, including sphingolipids, biogenic amines, amino acids and urea. Citrulline and arginine increased significantly in HD compared to control sheep. Ten other amino acids decreased in presymptomatic HD sheep, including branched chain amino acids (isoleucine, leucine and valine) that have been identified previously as potential biomarkers of HD. Significant increases in urea, arginine, citrulline, asymmetric and symmetric dimethylarginine, alongside decreases in sphingolipids, indicate that both the urea cycle and nitric oxide pathways are dysregulated at early stages in HD. Logistic prediction modelling identified a set of 8 biomarkers that can identify 80% of the presymptomatic HD sheep as transgenic, with 90% confidence. This level of sensitivity, using minimally invasive methods, offers novel opportunities for monitoring disease progression in HD patients.

High-Performance Chemical Isotope Labeling Liquid Chromatography-Mass Spectrometry for Profiling the Metabolomic Reprogramming Elicited by Ammonium Limitation in Yeast

Information about how yeast metabolism is rewired in response to internal and external cues can inform the development of metabolic engineering strategies for food, fuel, and chemical production in this organism. We report a new metabolomics workflow for the characterization of such metabolic rewiring. The workflow combines efficient cell lysis without using chemicals that may interfere with downstream sample analysis and differential chemical isotope labeling liquid chromatography mass spectrometry (CIL LC-MS) for in-depth yeast metabolome profiling. Using (12)C- and (13)C-dansylation (Dns) labeling to analyze the amine/phenol submetabolome, we detected and quantified a total of 5719 peak pairs or metabolites. Among them, 120 metabolites were positively identified using a library of 275 Dns-metabolite standards, and 2980 metabolites were putatively identified based on accurate mass matches to metabolome databases. We also applied (12)C- and (13)C-dimethylaminophenacyl (DmPA) labeling to profile the carboxylic acid submetabolome and detected over 2286 peak pairs, from which 33 metabolites were positively identified using a library of 188 DmPA-metabolite standards, and 1595 metabolites were putatively identified. Using this workflow for metabolomic profiling of cells challenged by ammonium limitation revealed unexpected links between ammonium assimilation and pantothenate accumulation that might be amenable to engineering for better acetyl-CoA production in yeast. We anticipate that efforts to improve other schemes of metabolic engineering will benefit from application of this workflow to multiple cell types.

Sampling and analysis of metabolomes in biological fluids

Metabolome analysis involves the study of small molecules that are involved in the metabolic responses that occur through patho-physiological changes caused by genetic stimuli or chemical agents.

Contribution of yeast models to neurodegeneration research

As a model organism Saccharomyces cerevisiae has greatly contributed to our understanding of many fundamental aspects of cellular biology in higher eukaryotes. More recently, engineered yeast models developed to study endogenous or heterologous proteins that lay at the root of a given disease have become powerful tools for unraveling the molecular basis of complex human diseases like neurodegeneration. Additionally, with the possibility of performing target-directed large-scale screenings, yeast models have emerged as promising first-line approaches in the discovery process of novel therapeutic opportunities against these pathologies. In this paper, several yeast models that have contributed to the uncovering of the etiology and pathogenesis of several neurodegenerative diseases are described, including the most common forms of neurodegeneration worldwide, Alzheimer's, Parkinson's, and Huntington's diseases. Moreover, the potential input of these cell systems in the development of more effective therapies in neurodegeneration, through the identification of genetic and chemical suppressors, is also addressed.

Detailed mitochondrial phenotyping by high resolution metabolomics

Mitochondrial phenotype is complex and difficult to define at the level of individual cell types. Newer metabolic profiling methods provide information on dozens of metabolic pathways from a relatively small sample. This pilot study used “top-down” metabolic profiling to determine the spectrum of metabolites present in liver mitochondria. High resolution mass spectral analyses and multivariate statistical tests provided global metabolic information about mitochondria and showed that liver mitochondria possess a significant phenotype based on gender and genotype. The data also show that mitochondria contain a large number of unidentified chemicals.

Cortical metabolites as biomarkers in the R6/2 model of Huntington's disease

To improve the ability to move from preclinical trials in mouse models of Huntington's disease (HD) to clinical trials in humans, biomarkers are needed that can track similar aspects of disease progression across species. Brain metabolites, detectable by magnetic resonance spectroscopy (MRS), have been suggested as potential biomarkers in HD. In this study, the R6/2 transgenic mouse model of HD was used to investigate the relative sensitivity of the metabolite profiling and the brain volumetry to anticipate the disease progression. Magnetic resonance imaging (MRI) and (1)H MRS data were acquired at 9.4 T from the R6/2 mice and wild-type littermates at 4, 8, 12, and 15 weeks. Brain shrinkage was detectable in striatum, cortex, thalamus, and hypothalamus by 12 weeks. Metabolite changes in cortex paralleled and sometimes preceded those in striatum. The entire set of metabolite changes was compressed into principal components (PCs) using Partial Least Squares-Discriminant Analysis (PLS-DA) to increase the sensitivity for monitoring disease progression. In comparing the efficacy of volume and metabolite measurements, the cortical PC1 emerged as the most sensitive single biomarker, distinguishing R6/2 mice from littermates at all time points. Thus, neurochemical changes precede volume shrinkage and become potential biomarkers for HD mouse models.

Simple is good: yeast models of neurodegeneration

The budding yeast, Saccharomyces cerevisiae, is the best-studied eukaryotic cell, at both genetic and physiological levels. As a eukaryote, yeast shares highly conserved molecular and cellular mechanisms with human cells. Thus, this simple fungus is an invaluable model to study the fundamental molecular mechanisms involved in several human diseases. In the particular case of neurodegenerative disorders, yeast models have been able to recapitulate several important features of complex and devastating disorders, such as Huntington's and Parkinson's diseases. Once validated, these models have also been used to accelerate the identification of both novel therapeutic targets and compounds with therapeutic potential. Here, we review the recent contributions of this simple, but powerful model organism toward our understanding of neurodegeneration.

Yeast systems biology: the challenge of eukaryotic complexity

In this chapter, we present an up-to-date view of the optimal characteristics of the yeast Saccharomyces cerevisiae as a model eukaryote for systems biology studies, with main molecular mechanisms, biological networks, and sub-cellular organization essentially conserved in all eukaryotes, derived from a complex common ancestor. The existence of advanced tools for molecular studies together with high-throughput experimental and computational methods, most of them being implemented and validated in yeast, with new ones being developed, is opening the way to the characterization of the core modular architecture and complex networks essential to all eukaryotes. Selected examples of the latest discoveries in eukaryote complexity and systems biology studies using yeast as a reference model and their applications in biotechnology and medicine are presented.

Mass microscopy: high-resolution imaging mass spectrometry

Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) is a technique that localizes the spatial distribution of molecules and identifies structures by their molecular mass signatures. Recently, the resolution of MALDI-IMS has been up to microscopic level. MALDI-IMS does not need either separation or purification procedures of target molecules and enables us to observe the localization of numerous molecules simultaneously. In particular, MALDI-MS time-of-flight/time-of-flight (TOF/TOF) is one of the instruments widely adopted for IMS, which allows the analysis of numerous biomolecules ranging over wide molecular weights. Even in a single data point, hundreds and thousands of mass peaks can be detected, and this makes the resulting mass spectrum extremely complex. This enormous volume of IMS data has driven the development of statistical approaches, especially multivariate analyses. By employing these approaches, researchers can figure out the important characteristics of their IMS data sets. The establishment of automatic molecular identification procedures involving MS(2) analysis, also known as MS/MS, performed by tandem mass spectrometry to obtain the information about molecular structure and composition, and database search available on the web is an important task for the near future. In this review, we introduce IMS-especially MALDI-IMS-with reference to its applications in biomolecular analyses, the workflow of IMS, the principle of IMS and other related technologies.