Measuring Caenorhabditis elegans Life Span on Solid Media

Aging is a degenerative process characterized by a progressive deterioration of cellular components and organelles resulting in mortality. The nematode Caenorhabditis elegans has emerged as a principal model used to study the biology of aging. Because virtually every biological subsystem undergoes functional decline with increasing age, life span is the primary endpoint of interest when considering total rate of aging. In nematodes, life span is typically defined as the number of days an animal remains responsive to external stimuli. Nematodes can be propagated either in liquid media or on solid media in plates, and techniques have been developed for measuring life span under both conditions. Here we present a generalized protocol for measuring life span of nematodes maintained on solid nematode growth media and fed a diet of UV-killed bacteria. These procedures can easily be adapted to assay life span under various common conditions, including a diet consisting of live bacteria, dietary restriction, and RNA interference

Integration of heterogeneous functional genomics data in gerontology research to find genes and pathway underlying aging across species.

Understanding the biological mechanisms behind aging, lifespan and healthspan is becoming increasingly important as the proportion of the world\u27s population over the age of 65 grows, along with the cost and complexity of their care. BigData oriented approaches and analysis methods enable current and future bio-gerontologists to synthesize, distill and interpret vast, heterogeneous data from functional genomics studies of aging. GeneWeaver is an analysis system for integration of data that allows investigators to store, search, and analyze immense amounts of data including user-submitted experimental data, data from primary publications, and data in other databases. Aging related genome-wide gene sets from primary publications were curated into this system in concert with data from other model-organism and aging-specific databases, and applied to several questions in genrontology using. For example, we identified Cd63 as a frequently represented gene among aging-related genome-wide results. To evaluate the role of Cd63 in aging, we performed RNAi knockdown of the C. elegans ortholog, tsp-7, demonstrating that this manipulation is capable of extending lifespan. The tools in GeneWeaver enable aging researchers to make new discoveries into the associations between the genes, normal biological processes, and diseases that affect aging, healthspan, and lifespan

Caenorhabditis elegans orthologs of human genes differentially expressed with age are enriched for determinants of longevity

We report a systematic RNAi longevity screen of 82 Caenorhabditis elegans genes selected based on orthology to human genes differentially expressed with age. We find substantial enrichment in genes for which knockdown increased lifespan. This enrichment is markedly higher than published genomewide longevity screens in C. elegans and similar to screens that preselected candidates based on longevity-correlated metrics (e.g., stress resistance). Of the 50 genes that affected lifespan, 46 were previously unreported. The five genes with the greatest impact on lifespan (>20% extension) encode the enzyme kynureninase (kynu-1), a neuronal leucine-rich repeat protein (iglr-1), a tetraspanin (tsp-3), a regulator of calcineurin (rcan-1), and a voltage-gated calcium channel subunit (unc-36). Knockdown of each gene extended healthspan without impairing reproduction. kynu-1(RNAi) alone delayed pathology in C. elegans models of Alzheimer's disease and Huntington's disease. Each gene displayed a distinct pattern of interaction with known aging pathways. In the context of published work, kynu-1, tsp-3, and rcan-1 are of particular interest for immediate follow-up. kynu-1 is an understudied member of the kynurenine metabolic pathway with a mechanistically distinct impact on lifespan. Our data suggest that tsp-3 is a novel modulator of hypoxic signaling and rcan-1 is a context-specific calcineurin regulator. Our results validate C. elegans as a comparative tool for prioritizing human candidate aging genes, confirm age-associated gene expression data as valuable source of novel longevity determinants, and prioritize select genes for mechanistic follow-up

Genetic interaction with temperature is an important determinant of nematode longevity

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140048/1/acel12658_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/140048/2/acel12658.pd

On the benefits of the tryptophan metabolite 3-hydroxyanthranilic acid in Caenorhabditis elegans and mouse aging.

Tryptophan metabolism through the kynurenine pathway influences molecular processes critical to healthy aging including immune signaling, redox homeostasis, and energy production. Aberrant kynurenine metabolism occurs during normal aging and is implicated in many age-associated pathologies including chronic inflammation, atherosclerosis, neurodegeneration, and cancer. We and others previously identified three kynurenine pathway genes-tdo-2, kynu-1, and acsd-1-for which decreasing expression extends lifespan in invertebrates. Here we report that knockdown of haao-1, a fourth gene encoding the enzyme 3-hydroxyanthranilic acid (3HAA) dioxygenase (HAAO), extends lifespan by ~30% and delays age-associated health decline in Caenorhabditis elegans. Lifespan extension is mediated by increased physiological levels of the HAAO substrate 3HAA. 3HAA increases oxidative stress resistance and activates the Nrf2/SKN-1 oxidative stress response. In pilot studies, female Haao knockout mice or aging wild type male mice fed 3HAA supplemented diet were also long-lived. HAAO and 3HAA represent potential therapeutic targets for aging and age-associated disease

Transcription errors induce proteotoxic stress and shorten cellular lifespan

Transcription errors occur in all living cells; however, it is unknown how these errors affect cellular health. To answer this question, we monitored yeast cells that were genetically engineered to display error-prone transcription. We discovered that these cells suffer from a profound loss in proteostasis, which sensitizes them to the expression of genes that are associated with protein-folding diseases in humans; thus, transcription errors represent a new molecular mechanism by which cells can acquire disease. We further found that the error rate of transcription increases as cells age, suggesting that transcription errors affect proteostasis particularly in aging cells. Accordingly, transcription errors accelerate the aggregation of a peptide that is implicated in Alzheimer’s disease, and shorten the lifespan of cells. These experiments reveal a novel, basic biological process that directly affects cellular health and aging

Elevated Proteasome Capacity Extends Replicative Lifespan in Saccharomyces cerevisiae

Aging is characterized by the accumulation of damaged cellular macromolecules caused by declining repair and elimination pathways. An integral component employed by cells to counter toxic protein aggregates is the conserved ubiquitin/proteasome system (UPS). Previous studies have described an age-dependent decline of proteasomal function and increased longevity correlates with sustained proteasome capacity in centenarians and in naked mole rats, a long-lived rodent. Proof for a direct impact of enhanced proteasome function on longevity, however, is still lacking. To determine the importance of proteasome function in yeast aging, we established a method to modulate UPS capacity by manipulating levels of the UPS–related transcription factor Rpn4. While cells lacking RPN4 exhibit a decreased non-adaptable proteasome pool, loss of UBR2, an ubiquitin ligase that regulates Rpn4 turnover, results in elevated Rpn4 levels, which upregulates UPS components. Increased UPS capacity significantly enhances replicative lifespan (RLS) and resistance to proteotoxic stress, while reduced UPS capacity has opposing consequences. Despite tight transcriptional co-regulation of the UPS and oxidative detoxification systems, the impact of proteasome capacity on lifespan is independent of the latter, since elimination of Yap1, a key regulator of the oxidative stress response, does not affect lifespan extension of cells with higher proteasome capacity. Moreover, since elevated proteasome capacity results in improved clearance of toxic huntingtin fragments in a yeast model for neurodegenerative diseases, we speculate that the observed lifespan extension originates from prolonged elimination of damaged proteins in old mother cells. Epistasis analyses indicate that proteasome-mediated modulation of lifespan is at least partially distinct from dietary restriction, Tor1, and Sir2. These findings demonstrate that UPS capacity determines yeast RLS by a mechanism that is distinct from known longevity pathways and raise the possibility that interventions to promote enhanced proteasome function will have beneficial effects on longevity and age-related disease in humans

The transcriptional landscape of age in human peripheral blood

Disease incidences increase with age, but the molecular characteristics of ageing that lead to increased disease susceptibility remain inadequately understood. Here we perform a whole-blood gene expression meta-analysis in 14,983 individuals of European ancestry (including replication) and identify 1,497 genes that are differentially expressed with chronological age. The age-associated genes do not harbor more age-associated CpG-methylation sites than other genes, but are instead enriched for the presence of potentially functional CpG-methylation sites in enhancer and insulator regions that associate with both chronological age and gene expression levels. We further used the gene expression profiles to calculate the 'transcriptomic age' of an individual, and show that differences between transcriptomic age and chronological age are associated with biological features linked to ageing, such as blood pressure, cholesterol levels, fasting glucose, and body mass index. The transcriptomic prediction model adds biological relevance and complements existing epigenetic prediction models, and can be used by others to calculate transcriptomic age in external cohorts.Peer reviewe

Longevity as a complex genetic trait.

IN: Kaeberlein M, Martin GM, eds. Handbook of the Biology of Aging, Eighth edition. 2016:3-54