Ageing is a complex process with common and distinct features across tissues. Unveiling the underlying processes driving ageing in individual tissues is indispensable to decipher the mechanisms of organismal longevity. Caenorhabditis elegans is a well-established model organism that has spearheaded ageing research with the discovery of numerous genetic pathways controlling its lifespan. However, it remains challenging to dissect the ageing of worm tissues due to the limited description of tissue pathology and access to tissue-specific molecular changes during ageing. In this study, we isolated cells from five major tissues in young and old worms and profiled the age-induced transcriptomic changes within these tissues. We observed a striking diversity of ageing across tissues and identified different sets of longevity regulators therein. In addition, we found novel tissue-specific factors, including irx-1 and myrf-2, which control the integrity of the intestinal barrier and sarcomere structure during ageing respectively. This study demonstrates the complexity of ageing across worm tissues and highlights the power of tissue-specific transcriptomic profiling during ageing, which can serve as a resource to the field.

Ethanol-induced transcriptional changes underlie important physiological responses to ethanol that are likely to contribute to the addictive properties of the drug. We examined the transcriptional responses of Caenorhabditis elegans across a timecourse of ethanol exposure, between 30 min and 8 h, to determine what genes and genetic pathways are regulated in response to ethanol in this model. We found that short exposures to ethanol (up to 2 h) induced expression of metabolic enzymes involved in metabolizing ethanol and retinol, while longer exposure (8 h) had much more profound effects on the transcriptome. Several genes that are known to be involved in the physiological response to ethanol, including direct ethanol targets, were regulated at 8 h of exposure. This longer exposure to ethanol also resulted in the regulation of genes involved in cilia function, which is consistent with an important role for the effects of ethanol on cilia in the deleterious effects of chronic ethanol consumption in humans. Finally, we found that food deprivation for an 8-h period induced gene expression changes that were somewhat ameliorated by the presence of ethanol, supporting previous observations that worms can use ethanol as a calorie source.

is a valuable traditional Chinese medicine in Northeast China. Ginsenoside, the active component of ginseng, has not been investigated much for its effects on aging and its underlying mechanism(s) of action. Here, we investigated the effects of total ginsenoside (TG), a mixture of the primary active ginsenosides from , on the lifespan of (). We found that TG extended the lifespan of and reduced lipofuscin accumulation. Moreover, TG increased the survival of in response to heat and oxidative stress via the reduction of ROS. Next, we used RNA-seq to fully define the antiaging mechanism(s) of TG. The KEGG pathway analysis showed that TG can prolong the lifespan and is involved in the longevity regulating pathway. qPCR showed that TG upregulated the expression of , , , and their downstream genes. TG also reduced the fat accumulation and promoted lipid metabolism. Moreover, TG failed to extend the lifespan of and mutants, highlighting their role in the antiaging effects of TG in . The four main constitution of TG were then confirmed by HPLC and included ginsenoside Re, Rg, Rg and Rd. Of the ginsenosides, only ginsenoside Rd prolonged the lifespan of to levels comparable to TG. These findings provided mechanistic insight into the antiaging effects of ginsenoside in .

INTRODUCTION:Metabolomics and proteomics are two growing fields of science which may shed light on the molecular mechanisms that contribute to neurodegenerative diseases. Studies focusing on these aspects can reveal specific metabolites and proteins that can halt or reverse the progressive neurodegenerative process leading to dopaminergic cell death in the brain. AREAS COVERED:In this article, an overview of the current status of metabolomic and proteomic profiling in the neurodegenerative disease such as Parkinson's disease (PD) is presented. We discuss the importance of state-of-the-art metabolomics and proteomics using advanced analytical methodologies and their potential for discovering new biomarkers in PD. We critically review the research to date, highlighting how metabolomics and proteomics can have an important impact on early disease diagnosis, future therapy development and the identification of new biomarkers. Finally, we will discuss interactions between lipids and α-synuclein (SNCA) and also consider the role of SNCA in lipid metabolism. EXPERT OPINION:Metabolomic and proteomic studies contribute to understanding the biological basis of PD pathogenesis, identifying potential biomarkers and introducing new therapeutic strategies. The complexity and multifactorial nature of this disease requires a comprehensive approach, which can be achieved by integrating just these two omic studies.

Metabolomics has been successfully applied to study neurological and neurodegenerative disorders including Parkinson's disease for (1) the identification of potential biomarkers of onset and disease progression; (2) the identification of novel mechanisms of disease progression; and (3) the assessment of treatment prognosis and outcome. Reproducible and efficient extraction of metabolites is imperative to the success of any metabolomics investigation. Unlike other omics techniques, the composition of the metabolome can be negatively impacted by the preparation, processing, and handling of these samples. The proper choice of data collection, preprocessing, and processing protocols is similarly important to the design of an effective metabolomics experiment. Likewise, the correct application of univariate and multivariate statistical methods is essential for providing biologically relevant insights. In this chapter, we have outlined a detailed metabolomics workflow that addresses all of these issues. A step-by-step protocol from the preparation of neuronal cells and metabolomic tissue samples to their metabolic analyses using nuclear magnetic resonance, mass spectrometry, and chemometrics is presented.