Aging is the time dependent deterioration of an organism's normal biological processes that increases the probability of death. Many genetic factors contribute to alterations in the normal aging process. These factors intersect in complex ways, as evidenced by the wealth of documented links identified and conserved in many organisms. Most of these studies focus on loss-of-function, null mutants that allow for rapid screening of many genes simultaneously. There is much less work that focuses on characterizing the role that overexpression of a gene in this process. In the present work, we present a straightforward methodology to identify and clone genes in the budding yeast, Saccharomyces cerevisiae, for study in suppression of the short-lived chronological lifespan phenotype seen in many genetic backgrounds. This protocol is designed to be accessible to researchers from a wide variety of backgrounds and at various academic stages. The SIR2 gene, which codes for a histone deacetylase, was selected for cloning in the pRS315 vector, as there have been conflicting reports on its effect on the chronological lifespan. SIR2 also plays a role in autophagy, which results when disrupted via the deletion of several genes, including the transcription factor ATG1. As a proof of principle, we clone the SIR2 gene to perform a suppressor screen on the shortened lifespan phenotype characteristic of the autophagy deficient atg1Δ mutant and compare it to an otherwise isogenic, wild type genetic background.
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FEMS Microbiol Lett
December 2024
Department of Biophysics, Yeditepe University School of Medicine, Yeditepe University, Istanbul, Turkey.
Chronological lifespan (CLS) in budding yeast Saccharomyces cerevisiae, which is defined as the time nondividing cells in saturation remain viable, has been utilized as a model to study post-mitotic aging in mammalian cells. CLS is closely related to entry into and maintenance of a quiescent state. Many rearrangements that direct the quiescent state enhance the ability of cells to endure several types of stress.
View Article and Find Full Text PDFMemory
December 2024
Department of Developmental Psychology, Ulm University Ulm, Germany.
Despite the crucial role that the recall of autobiographical memories (AMs) plays for identity, the process of how we recall AMs, and whether retrieval processes undergo , has received little attention. The present study thus examined the order of AMs during recall, with a specific focus on time and centrality as guiding dimensions. A total of 364 participants (aged 18-89 years) recalled up to ten positive and negative AMs.
View Article and Find Full Text PDFBiochim Biophys Acta Mol Cell Biol Lipids
December 2024
Human Aging Research Institute (HARI) and School of Life Science, Nanchang University, and Jiangxi Key Laboratory of Aging and Disease, Nanchang, Jiangxi, China. Electronic address:
Sphingolipids are crucial components of cell membranes and serve as important signaling molecules. Ceramide, as the central hub of sphingolipid metabolism, plays a significant role in various biological processes, including the cell cycle, apoptosis, and cellular aging. Alterations in sphingolipid metabolism are implicated in cellular aging, however, the specific sphingolipid components and intrinsic mechanisms that mediate this process remain largely uncharacterized.
View Article and Find Full Text PDFJ Bone Metab
November 2024
Department of Radiological Technology, Faculty of Allied Health Sciences, Thammasat University, Pathum Thani, Thailand.
Background: Osteoporosis is a significant global public health issue, increasingly affecting younger individuals and placing substantial economic burdens on society. Risk factors vary, with non-modifiable ones like age and ethnicity, as well as modifiable factors including corticosteroid use, caffeine intake, and reduced exercise. This study examines the relationship between bone density, body components, and physical activity (PA) in enhancing bone health, particularly in obese athletes.
View Article and Find Full Text PDFSci Adv
December 2024
Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.
Biological aging clocks produce age estimates that can track with age-related health outcomes. This study aimed to benchmark machine learning algorithms, including regularized regression, kernel-based methods, and ensembles, for developing metabolomic aging clocks from nuclear magnetic resonance spectroscopy data. The UK Biobank data, including 168 plasma metabolites from up to = 225,212 middle-aged and older adults (mean age, 56.
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