Life Expectancy: Advancing the aging biology toolkit
A new device for isolating large quantities of old yeast cells expands the experimental boundaries of aging research.
- University of Utah School of Medicine, United States
Aging is a universal feature of life. It occurs at the level of both cells and organisms, and is the single greatest risk factor for disease. Researchers have been working to unlock the mysteries of aging for decades, and have identified several key molecular changes that drive age-associated traits, as well as genetic, pharmacological and metabolic changes that control lifespan. Because aging is a complex and lengthy process, most breakthroughs have come from studies on model organisms with short lifespans, including yeast, flies, worms and mice. Remarkably, these studies have shown that age-associated traits and genes regulating lifespan are highly conserved, raising the hope that therapeutic interventions that target aging are a real possibility in the near future (Bitto et al., 2015).
Of all these model systems, the budding yeast, Saccharomyces cerevisiae, is the simplest, and has been used to study aging since the 1950s. At that time, Robert Mortimer and John Johnston used microdissection, a technique that involves separating yeast daughter cells from their mothers after they divide, to demonstrate that yeast undergo a finite number of divisions before they die (Mortimer and Johnston, 1959). This type of aging is called replicative aging, and it is defined by the number of times an individual yeast cell asymmetrically divides to produce a daughter. Since then, researchers have used yeast to uncover a number of age-associated traits and genetic modifiers of lifespan (Wasko and Kaeberlein, 2014).
Despite the many successes of yeast-aging research, the field has always faced a significant challenge: old yeast cells are exceedingly rare in a growing population. Early on, this obstacle limited the experimental approaches researchers used, because they could not obtain enough old cells for analysis. Over the years, several laboratories have made key technical advances that have enabled the field to overcome this obstacle and harness a larger spectrum of techniques beyond microdissection to identify molecular mechanisms associated with aging (Figure 1).
Figure 1
Key technological advances in yeast-aging research.
The development of new tools to study replicative aging in yeast has been crucial to overcome the limitations imposed by the scarcity of old yeast cells in a growing cell population. This timeline depicts broadly adopted technologies that have enabled both single-cell and large-scale measurements using biochemical or genetic approaches to characterize the molecular mechanisms of aging; see main text for more details. Large circles represent mother yeast cells; small circles represent daughter yeast cells; small circles with a red cross represent daughter cells prevented from maturing.
These developments have included: i) microfluidic imaging devices that enable continuous imaging of individual yeast cells over their lifespan (Chen et al., 2017); ii) centrifugation-based approaches that separate populations of old mother cells from young daughters based on size (elutriation; Egilmez et al., 1990); iii) large-scale isolation of aged mother cells by attaching biotin to their cell wall prior to aging (a process known as biotinylation), and then using magnetic microbeads coated with the protein streptavidin to magnetically separate the biotinylated mother cells from their daughters (Smeal et al., 1996); iv) genetic enrichment of aged mother cells by stopping newborn daughter cells from growing (Lindstrom and Gottschling, 2009).
Combined, these techniques have pushed the yeast-aging field to new heights. However, each method has its limitations. For example, while microfluidic devices permit constant media exchange during aging, they are limited to single-cell analysis. On the other hand, genetic enrichment combined with biotin-based purification strategies allows researchers to isolate large numbers of aged cells for a range of analyses. However, this system requires genetically modified yeast strains and does not allow rapid and continuous media flow.
Now, in eLife, Scott McIsaac and colleagues at Calico Life Sciences – including David Hendrickson as first author – report that they have engineered a new aging platform, called the Miniature-chemostat Aging Device (MAD), which pushes the capabilities of the yeast-aging field one step further (Hendrickson et al., 2018). This new device helps to isolate large numbers of yeast cells across a range of ages and genetic backgrounds without the use of genetically modified systems, but with the benefit of continuously renewed media.
Hendrickson et al. achieved this by combining the Miniature-chemostat (Miller et al., 2013) with magnetic-based streptavidin enrichment of mother cells. The MAD approach worked as follows: cells were biotinylated and attached to streptavidin beads prior to aging. The bead-conjugated cells were then loaded into culture tubes fitted with neodymium ring magnets, which trapped the mother cells along the vessel walls, while allowing the daughter cells to be released. The device was connected to a peristaltic pump, which provided fresh media to the confined mother cells while washing away daughters. Mother cells could be released from the magnet at any point during the aging process, and collected for further analysis.
Hendrickson et al. put their new device to the test, performing several genetic and molecular techniques on purified yeast mother cells of various ages and genetic backgrounds. The results confirmed previous observations that aging in yeast is associated with an activation of the core environmental stress response (a set of genes that respond to stress) and the accumulation of ribosomal DNA transcripts (Sinclair and Guarente, 1997; Lesur and Campbell, 2004). They also demonstrated the tremendous potential of this new device to identify unknown age-associated traits by showing that origins of replication (sites were the replication of DNA is initiated) become less accessible with age, and that gene expression from sub-telomeric regions (regions near the end of the chromosomes) increases with age. Moreover, Hendrickson et al. challenged previous observations in the field that global nucleosome occupancy (the density of nucleosomes on DNA) declines with age (Hu et al., 2014).
Overall, yeast-aging research has come a long way since the pioneering studies of Mortimer and Johnston. While there are still significant hurdles to overcome, the development of MAD opens an exciting new era for yeast-aging research.
References
-
Biochemical genetic pathways that modulate aging in multiple speciesCold Spring Harbor Perspectives in Medicine 5:a025114.https://doi.org/10.1101/cshperspect.a025114
-
Microfluidic technologies for yeast replicative lifespan studiesMechanisms of Ageing and Development 161:262–269.https://doi.org/10.1016/j.mad.2016.03.009
-
Preparation and partial characterization of old yeast cellsJournal of Gerontology 45:B9–B17.https://doi.org/10.1093/geronj/45.1.B9
-
The transcriptome of prematurely aging yeast cells is similar to that of telomerase-deficient cellsMolecular Biology of the Cell 15:1297–1312.https://doi.org/10.1091/mbc.e03-10-0742
-
Design and use of multiplexed chemostat arraysJournal of Visualized Experiments e50262.https://doi.org/10.3791/50262
Article and author information
Author details
Publication history
- Version of Record published: November 28, 2018 (version 1)
Copyright
© 2018, Coody et al.
This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 1,890
- views
-
- 183
- downloads
-
- 2
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Life Expectancy: Advancing the aging biology toolkit
eLife 7:e42976.
https://doi.org/10.7554/eLife.42976
Further reading
-
- Computational and Systems Biology
- Genetics and Genomics
Runs-of-homozygosity (ROH) segments, contiguous homozygous regions in a genome were traditionally linked to families and inbred populations. However, a growing literature suggests that ROHs are ubiquitous in outbred populations. Still, most existing genetic studies of ROH in populations are limited to aggregated ROH content across the genome, which does not offer the resolution for mapping causal loci. This limitation is mainly due to a lack of methods for the efficient identification of shared ROH diplotypes. Here, we present a new method, ROH-DICE (runs-of-homozygous diplotype cluster enumerator), to find large ROH diplotype clusters, sufficiently long ROHs shared by a sufficient number of individuals, in large cohorts. ROH-DICE identified over 1 million ROH diplotypes that span over 100 single nucleotide polymorphisms (SNPs) and are shared by more than 100 UK Biobank participants. Moreover, we found significant associations of clustered ROH diplotypes across the genome with various self-reported diseases, with the strongest associations found between the extended human leukocyte antigen (HLA) region and autoimmune disorders. We found an association between a diplotype covering the homeostatic iron regulator (HFE) gene and hemochromatosis, even though the well-known causal SNP was not directly genotyped or imputed. Using a genome-wide scan, we identified a putative association between carriers of an ROH diplotype in chromosome 4 and an increase in mortality among COVID-19 patients (p-value = 1.82 × 10−11). In summary, our ROH-DICE method, by calling out large ROH diplotypes in a large outbred population, enables further population genetics into the demographic history of large populations. More importantly, our method enables a new genome-wide mapping approach for finding disease-causing loci with multi-marker recessive effects at a population scale.
-
- Biochemistry and Chemical Biology
- Computational and Systems Biology
Previously, Tuller et al. found that the first 30–50 codons of the genes of yeast and other eukaryotes are slightly enriched for rare codons. They argued that this slowed translation, and was adaptive because it queued ribosomes to prevent collisions. Today, the translational speeds of different codons are known, and indeed rare codons are translated slowly. We re-examined this 5’ slow translation ‘ramp.’ We confirm that 5’ regions are slightly enriched for rare codons; in addition, they are depleted for downstream Start codons (which are fast), with both effects contributing to slow 5’ translation. However, we also find that the 5’ (and 3’) ends of yeast genes are poorly conserved in evolution, suggesting that they are unstable and turnover relatively rapidly. When a new 5’ end forms de novo, it is likely to include codons that would otherwise be rare. Because evolution has had a relatively short time to select against these codons, 5’ ends are typically slightly enriched for rare, slow codons. Opposite to the expectation of Tuller et al., we show by direct experiment that genes with slowly translated codons at the 5’ end are expressed relatively poorly, and that substituting faster synonymous codons improves expression. Direct experiment shows that slow codons do not prevent downstream ribosome collisions. Further informatic studies suggest that for natural genes, slow 5’ ends are correlated with poor gene expression, opposite to the expectation of Tuller et al. Thus, we conclude that slow 5’ translation is a ‘spandrel’--a non-adaptive consequence of something else, in this case, the turnover of 5’ ends in evolution, and it does not improve translation.
