A method for high-throughput quantitative analysis of yeast chronological life span.
ABSTRACT Chronological aging in yeast has been studied by maintaining cells in a quiescent-like stationary phase culture and monitoring cell survival over time. The composition of the growth medium can have a profound influence on chronological aging. For example, dietary restriction accomplished by lowering the glucose concentration of the medium significantly increases life span. Here we report a novel high-throughput method for measuring yeast chronological life span by monitoring outgrowth of aging cells using a Bioscreen C MBR machine. We show that this method provides survival data comparable to traditional methods, but with decreased variability. In addition to reducing the glucose concentration, we find that elevated amino acid levels or increased osmolarity of the growth medium is sufficient to increase chronological life span. We also report that life-span extension from dietary restriction does not require any of the five yeast sirtuins (Sir2, Hst1, Hst2, Hst3, or Hst4) either alone or in combination.
- [show abstract] [hide abstract]
ABSTRACT: It has been known for some 70 years that restricting the food intake of laboratory rats extends their mean and maximum life span. In addition, such life extension has been observed over the years in many other species, including mice, hamsters, dogs, fish, invertebrate animals, and yeast. Since this life-extending action appears to be due to a restricted intake of energy, this dietary manipulation is referred to as caloric restriction (CR). CR extends life by slowing and/or delaying the ageing processes. The underlying biological mechanism responsible for the life extension is still not known, although many hypotheses have been proposed. The Growth Retardation Hypothesis, the first proposed, has been tested and found wanting. Although there is strong evidence against the Reduction of Body Fat Hypothesis, efforts have recently been made to resurrect it. While the Reduction of Metabolic Rate Hypothesis is not supported by experimental findings, it nevertheless still has advocates. Currently, the most popular concept is the Oxidative Damage Attenuation Hypothesis; the results of several studies provide support for this hypothesis, while those of other studies do not. The Altered Glucose-Insulin System Hypothesis and the Alteration of the Growth Hormone-IGF-1 Axis Hypothesis have been gaining favor, and data have emerged that link these two hypotheses as one. Thus, it may now be more appropriate to refer to them as the Attenuation of Insulin-Like Signaling Hypothesis. Finally, the Hormesis Hypothesis may provide an overarching concept that embraces several of the other hypotheses as merely specific examples of hormetic processes. For example, the Oxidative Damage Attenuation Hypothesis probably addresses only one of likely many damaging processes that underlie aging. It is proposed that low-intensity stressors, such as CR, activate ancient hormetic defense mechanisms in organisms ranging from yeast to mammals, defending them against a variety of adversities and, when long-term, retarding senescent processes.Mechanisms of Ageing and Development 10/2005; 126(9):913-22. · 3.26 Impact Factor
Article: Recent developments in yeast aging.[show abstract] [hide abstract]
ABSTRACT: In the last decade, research into the molecular determinants of aging has progressed rapidly and much of this progress can be attributed to studies in invertebrate eukaryotic model organisms. Of these, single-celled yeast is the least complicated and most amenable to genetic and molecular manipulations. Supporting the use of this organism for aging research, increasing evidence has accumulated that a subset of pathways influencing longevity in yeast are conserved in other eukaryotes, including mammals. Here we briefly outline aging in yeast and describe recent findings that continue to keep this "simple" eukaryote at the forefront of aging research.PLoS Genetics 06/2007; 3(5):e84. · 8.52 Impact Factor
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ABSTRACT: Calorie restriction extends life-span in a wide variety of organisms. Although it has been suggested that calorie restriction may work by reducing the levels of reactive oxygen species produced during respiration, the mechanism by which this regimen slows aging is uncertain. Here, we mimicked calorie restriction in yeast by physiological or genetic means and showed a substantial extension in life-span. This extension was not observed in strains mutant for SIR2 (which encodes the silencing protein Sir2p) or NPT1 (a gene in a pathway in the synthesis of NAD, the oxidized form of nicotinamide adenine dinucleotide). These findings suggest that the increased longevity induced by calorie restriction requires the activation of Sir2p by NAD.Science 10/2000; 289(5487):2126-8. · 31.03 Impact Factor
A Method for High-Throughput Quantitative
Analysis of Yeast Chronological Life Span
Christopher J. Murakami,1Christopher R. Burtner,2Brian K. Kennedy,2
and Matt Kaeberlein1
Departments of1Pathology and2Biochemistry, University of Washington, Seattle.
Chronological aging in yeast has been studied by maintaining cells in a quiescent-like stationary
phase culture and monitoring cell survival over time. The composition of the growth medium can
have a profound influence on chronological aging. For example, dietary restriction accomplished
by lowering the glucose concentration of the medium significantly increases life span. Here we
report a novel high-throughput method for measuring yeast chronological life span by monitoring
outgrowth of aging cells using a Bioscreen C MBR machine. We show that this method provides
survival data comparable to traditional methods, but with decreased variability. In addition to
reducing the glucose concentration, we find that elevated amino acid levels or increased
osmolarity of the growth medium is sufficient to increase chronological life span. We also report
that life-span extension from dietary restriction does not require any of the five yeast sirtuins
(Sir2, Hst1, Hst2, Hst3, or Hst4) either alone or in combination.
Key Words: Longevity—Dietary restriction—Glucose—Amino acids—Osmolarity—Sir2.
dietary restriction (DR), defined as a reduction in nutrient
availability without malnutrition, increases life span and
delays the onset of age-associated disease in yeast, worms,
flies, and rodents (1,2). The mechanisms by which nutrient
availability modulates longevity remain unclear, and a com-
prehensive analysis of how different dietary compositions
affect aging has yet to be performed in any organism.
The budding yeast Saccharomyces cerevisiae has served
as a model of organismal and cellular aging for more than
50 years (3). Two different types of aging have been de-
scribed in yeast: replicative and chronological aging (4).
Replicative life span (RLS) refers to the mitotic capacity
of a yeast cell, as defined by the number of daughter cells
produced by a mother cell prior to senescence. In contrast to
RLS, chronological life span (CLS) refers to the length of
time a nondividing cell can maintain viability, as defined by
its ability to re-enter the cell cycle after a prolonged period
of quiescence. Yeast CLS has therefore been adopted as a
model of the viability of postmitotic cells.
Although both yeast aging paradigms have been generally
accepted as valid organismal aging models, replicative aging
has been more widely used and better characterized than
chronological aging. In the replicative aging paradigm, life-
span extension by DR has been described by either reducing
the glucose concentration of the growth medium (5) or by
reducing the total amino acid concentration (6). It was ini-
tially proposed that the increased RLS associated with DR
was mediated by activation of the Sir2 histone deacetylase
(5), which has been shown to promote longevity in yeast (7),
worms (8), and flies (9). This model has since been chal-
lenged, however, by a series of studies reporting that RLS
NVIRONMENTAL nutrients have been shown to
influence aging in a variety of organisms. For example,
extension from DR occurs in cells lacking Sir2 alone (6,10)
or in cells lacking multiple Sir2-family proteins (sirtuins)
(11,12). An alternative model has been proposed suggesting
that DR increases RLS by decreasing the activity of the
nutrient-responsive target of rapamycin (TOR) kinase along
with Sch9 and protein kinase A (13). A recent report has
suggested that decreased TOR signaling leads to activation
of Sir2 via the stress-responsive transcription factors Msn2
and Msn4 (14); however, this model is difficult to reconcile
with the observation that RLS extension from deletion of
TOR1 or chemical inhibition of TOR does not require Sir2
(13). Furthermore, genetic epistasis experiments definitively
place TOR in a genetic pathway with DR that is distinct
from the longevity-promoting activity of Sir2 (13).
Life-span extension from DR has also been described in
the yeast chronological aging paradigm by transferring cells
from spent culture medium to water (15) or by reducing the
glucose concentration of the growth medium (16). Similar
to the case for RLS, decreased activity of TOR, Sch9, or
protein kinase A is sufficient to increase CLS (17,18), sup-
porting the idea that these nutrient-responsive kinases
may mediate the beneficial longevity effects of DR in both
dividing and nondividing yeast cells. The downstream effec-
tors of these kinases that are important for increased CLS
in response to DR have yet to be determined; however,
increased respiration, stress response, and autophagy have
all been proposed to play a role (17,19,20).
CLS has traditionally been assayed by culturing cells into
stationary phase in liquid culture and measuring the cell
survival as a function of time by dilution and plating onto
a nutrient-rich, agar-based medium (4). Viability is then
calculated based on the number of colonies arising (colony
forming units; CFUs) on the nutrient agar. However, this
Journal of Gerontology: BIOLOGICAL SCIENCES
2008, Vol. 63A, No. 2, 113–121
Copyright 2008 by The Gerontological Society of America
methodology requires a relatively large investment of
investigator time and resources, and is not suited for high-
throughput studies. Recently a high-throughput method for
qualitatively measuring CLS was described in which cells
are aged in 96-well microtiter plates (18). Rather than
monitoring survival of individual cells based on CFUs,
relative cell viability of the population was determined by
diluting the aging culture into rich liquid medium and
measuring the optical density (OD) at 600 nm following an
18-hour outgrowth at 308C. All cell and liquid transfers are
automated using a high-density replica pinning robot.
Although less quantitative than the traditional methodolo-
gies, this drawback is offset by the ability to monitor
survival for several thousand strains simultaneously.
This high-throughput CLS method was used to screen the
yeast homozygous diploid open reading frame (ORF)
deletion collection for long-lived mutants (18). The entire
set of ;5000 deletion mutants was ranked based on relative
survival, and among the 90 highest ranked strains, several
contained deletions in genes implicated in signaling through
the nutrient-responsive TOR signaling pathway (18). The
finding that decreased TOR activity increases yeast CLS
was a significant discovery from this study (18), and further
strengthened the role of TOR as an evolutionarily conserved
mediator of longevity (13,21–23). Only five deletion
mutants (gln3?, lys12?, mep3?, mep2?, and agp1?)
were confirmed to have increased CLS from this genome-
wide screen (18), however, and subsequent attempts to
identify long-lived deletion mutants from among the
highest-ranked strains from this screen have proven less
successful (our unpublished data). Thus, we have concluded
that, although useful for qualitatively identifying long-lived
mutants from among a large collection of strains, the
previously described high-throughput method (18) is not
Here we describe a novel method for determining CLS
with improved quantitative resolution relative to the previ-
ously described assay (18), while also maintaining a capacity
for higher-throughput studies than is possible with CFU-
based methods. This method provides comparable precision
with reduced variability and is easily adaptable to a variety
of environmental and genetic perturbations. As proof of
principle, we have used this method to explore the effects
of medium composition on CLS and to comprehensively
examine the importance of Sir2-family proteins in yeast
chronological aging. We found that, between a range of
0.05% and 20% glucose, CLS correlates inversely with
glucose concentration. Surprisingly, a direct correlation
between total amino acid concentration and CLS was
observed. We also found that CLS extension from DR by
glucose depletion is not only independent of Sir2 as previ-
ously reported (24), but is also capable of increasing life
span in cells simultaneously lacking all five yeast sirtuins.
Strains and Media
Strains were derived from BY4742 (Open Biosystems,
Huntsville, AL). W303AR5 (7) or PSY316AR (25). All
mutant strains used in this study were either derived from
the MATa yeast ORF deletion collection (26) or were
generated by transforming yeast with polymerase chain
reaction (PCR)-amplified deletion constructs containing 45
nucleotides of homology to regions flanking the ORF to be
deleted and either HIS3, LEU2, or URA3 amplified from
pRS403, pRS405, or pRS406 (27), respectively. In each
case, the entire ORF of the deleted gene was removed. All
gene disruptions were verified by PCR. Strains used in this
study are listed in Table 1.
YPD medium contained 2% bacto peptone and 1% yeast
extract supplemented with filter-sterilized glucose at 2%.
The composition of the standard synthetic defined media
used in this study is provided in Table 2. This medium
Table 1. Yeast Strains Used in This Study
MATa his3?1 leu2?0 lys2?0 ura3?0
BY4742 sir2::LEU2 fob1::HIS3 hst1::URA3 hst2::kanMX
hst3::kanMX hst4::kanMX lys2?0::LYS2
MATa ura3-52 leu2-3,112 his3-200 ade2-101 lys2-801
MATa ura3-1 leu2-3,112 trp1-1 his3-11,15 can1-100
Table 2. Synthetic Defined Medium Used for Chronological
Yeast nitrogen base (?AA/AS)
Note: The standard recipe is shown. For some experiments, the concentra-
tion of D-glucose was varied as indicated. For experiments in which amino acid
levels were varied, the concentration of all L-amino acids was varied propor-
tionately, as indicated. Yeast nitrogen base did not contain amino acids (AA) or
ammonium sulfate (AS). For experiments with BY4742 and PSY316AT, the
concentration of lysine was increased to 0.15 g/L. For experiments with
W303AR5, the concentration of tryptophan was increased to 0.2 g/L.
MURAKAMI ET AL.
contains excess concentrations of leucine, histidine, and
uracil to compensate for auxotrophies present in the labora-
tory strains used in this study. Additional auxotrophies were
compensated for on a strain-by-strain basis as follows: For
experiments with BY4742- and PSY316AR-derived strains,
the concentration of lysine was increased to 0.15 g/L; for
experiments with W303AR5-derived strains, the concentra-
tion of tryptophan was increased to 0.2 g/L. Cultures for
chronological aging experiments were prepared by inocu-
lating 50 lL from a YPD overnight culture into 5 mL of
the appropriate aging medium in culture tubes. Tubes were
rotated continuously in a roller drum and maintained at 308C
in a water-jacketed incubator.
Bioscreen C MBR Outgrowth
A Bioscreen C MBR (Growth Curves USA, Piscataway,
NJ) machine was used for all outgrowth assays. For out-
growth of aged cells, 5 lL of the aging culture was inocu-
lated into 145 lL of rich YPD (2% glucose, 2% bacto
peptone, 1% yeast extract) medium in a Bioscreen Honey-
comb 100-well plate (cat no. 9502550). Incubation of the
plate is kept constant at 308C, with the shaking module set
to high continuous shaking. Absorbance readings at 600 nm
(wideband range) are taken every 30 minutes for 24 hours.
OD data were normalized for background prior to pre-
sentation by subtracting the initial OD value at t ¼ 0 from
each subsequent OD reading.
Calculation of viability from CFUs.—To determine
viability using the CFU method, stationary cultures were
serially diluted in YPD to achieve a cell density of roughly
13103to 53103cells/mL. One hundred microliters of the
dilution was spread onto YPD agar plates, incubated at 308C
for 2 days, and manually counted. All cultures were pre-
sumed to be 100% viable at day 2, with subsequent CFU
measurements normalized to day 2 CFUs. Averages and
standard deviations for at least three biological replicates
were calculated for each experiment.
Calculation of viability from Bioscreen data.—The
doubling time for each well in a Bioscreen assay, dW, was
determined by the maximal slope of the semilog plot of OD
as a function of time. This value was defined as the median
of the three lowest d values obtained for every consecutive
pair of OD measurements for that well in that experiment.
For each age-point, a ?t value was calculated as the shift
in the Bioscreen growth curve relative to the initial age-
point for that strain (day 2). The ?t value was calculated by
first determining the linear regression equation of the natural
logarithm of OD600as a function of time for each well
(0.05 ? OD600? 0.3). Based on the linear regression equa-
tion for each well, the time, tOD, at which OD600¼0.3, was
estimated. This OD600value was chosen because it is near
the middle of the linear range on a plot of ln(OD600) versus
time. The tOD value was calculated for each age-point
and the time shift, ?tn, was calculated as the difference of
the tODfor each age-point and the tODfor the first age-point
(day 2 of culture).
Relative survival for each strain at each age-point was
calculated by the formula:
where vn¼viability at age-point n, ?tnequals the time shift
between the outgrowth curves at the initial age-point and
age-point n at OD¼0.2, and d equals the median of the dW
values calculated for that strain at each individual age-point.
The Bioscreen method, as described here, was used to
measure CLS in all of the experiments, except for the data
shown in Figure 2 that were obtained by counting CFUs.
Relative Cell Viability Quantified by a Shift in the
To improve the quantitative capacity and increase the
throughput of the previously described method for high-
throughput CLS screening (18), we explored incorporation
of a Bioscreen C MBR machine (Growth Curves) into yeast
life-span analysis. The Bioscreen C MBR machine is
a computer-controlled shaker/incubator/reader equipped
with eight filters from 405 nm to 600 nm and a temperature
control system that maintains the set temperature in each
well with a 0.18C accuracy. Plates specifically designed for
use with the Bioscreen C MBR avoid condensation of liquid
on the inside of the microplate lid and prevent volume loss
from outer wells. Our group and others have used the
Bioscreen C MBR to determine growth kinetics of yeast
strains under a variety of conditions (12,28). We speculated
that use of a Bioscreen C MBR machine to obtain OD
readings every 30 minutes during outgrowth after dilution of
the aging culture, rather than after a single fixed incubation
period as had been previously done, would greatly improve
the quantitative capacity for measuring relative cell survival
To determine whether the Bioscreen C MBR machine
could be used to accurately measure CLS, we carried out a
proof-of-principle experiment with the haploid ORF de-
letion collection wild-type strain (BY4742) (26). BY4742
cells were aged in 5 mL of synthetic defined (SD) medium
on a rotating drum, and viability was determined at each
age-point by outgrowth in the Bioscreen C MBR machine.
To monitor viability at each age-point, 5 lL of the aging
culture was inoculated into 145 lL of YPD in one well of
a Bioscreen Honeycomb plate. Outgrowth of the inoculated
cells took place in the Bioscreen C machine at 308C with
continuous shaking. OD at the Bioscreen C wideband wave-
length (;600 nm) was determined every 30 minutes for
24 hours (Figure 1).
The growth curves of BY4742 cells showed a distinct
rightward shift with age, such that for a given OD value, the
length of time required to achieve that value increased with
age (Figure 2A). A survival curve was generated from the
Bioscreen growth data, based on the estimated fraction of
cells retaining viability at each age-point (Figure 2B). The
viable fraction was calculated relative to the initial age-point
(viability at day 2 is defined as 100%) based on the
HIGH-THROUGHPUT CHRONOLOGICAL AGING ASSAY
rightward time shift required for outgrowth to reach an OD
value of 0.2 using the formula:
where vn¼viability at age-point n, ?tnequals the time shift
between the outgrowth curves at the initial age-point and
age-point n at OD ¼ 0.2, and d equals the doubling time of
the strain (determined by the maximal slope of the semilog
plot of OD as a function of time).
Reduced Variability with the Bioscreen CLS Method
We next examined the relative variability of cell survival
measurements using the Bioscreen C MBR machine versus
serial dilution and plating for CFUs. A dilution series
ranging from 1.25-fold to 1000-fold was generated from
a 2-day-old culture of BY4742, and the relative survival
was measured both by plating for CFUs and by using the
Bioscreen C MBR machine. The fraction of viable cells
inoculated, relative to the initial dilution, was calculated
using the formula described above and was compared to the
value based on known dilution. The coefficient of variation
was calculated and compared between both methods (Table
3). Relative to CFUs, the Bioscreen CLS method provided
reduced variance over the entire range of dilutions.
A similar trend was observed in the context of a chrono-
logical aging experiment involving two genetic back-
grounds commonly used in aging experiments (W303AR5
and PSY316). At each age-point, the Bioscreen CLS method
and the CFU method gave comparable estimations of
survival (Figure 3). The Bioscreen method did, however,
produce less variable measurements than the CFU method,
as determined by the standard deviation of five biological
replicates (error bars in Figure 3). This trend is most likely
due to variation introduced during serial dilution and plating
of cells, and has held up in multiple different experiments
(our unpublished data).
In addition to survival, the Bioscreen CLS method
provides information about the aging cells (such as doubling
time and final density) that is not available using other
methods. For example, we observed that the growth rate
following dilution does not change substantially with chro-
nological age, because normalizing for the ?t time shift
associated with each age-point causes the growth curves to
overlay (data not shown, but can be visualized in Figure
2A). From this, we conclude that chronological age does
not lead to substantial genetic or epigenetic changes at the
population level in wild-type cells sufficient to alter growth
rate. It will be of interest to determine whether this trend is
also observed in a variety of mutant backgrounds.
Effect of Glucose on CLS
We have used the Bioscreen CLS method experimentally
to explore the relationship between CLS and DR. The
largest increase in RLS from DR has been previously re-
ported to occur at either 0.5% or 0.05% glucose, depending
on the genetic background (11,12,29,30). We began our
Figure 1. A new method for measuring yeast chronological life span. Aging cultures are kept at 308C on a roller drum. At each age-point, 5 lL from each aging
culture is inoculated into 145 lL of rich growth medium in an individual well of the Bioscreen Honeycomb plate. The Bioscreen machine incubates the plates at 308C
under constant agitation, while the optical density (OD) of each well is measured in intervals of 30 minutes. At the end of a specified incubation time (24 hours for our
experiments), outgrowth curves for multiple strains can be plotted from the OD measurements as a function of time.
MURAKAMI ET AL.
analysis by measuring the CLS of cells grown in SD
medium containing 0.05%, 0.5%, 1%, 2%, 10%, or 20%
glucose. As can be observed from the survival curves at
each glucose level, an inverse relationship between glucose
and CLS was observed across the entire range of glucose
concentrations tested (Figure 4). The observation that
glucose levels higher than 2% reduce CLS in a dose-
dependant fashion contrasts dramatically with RLS where
glucose in excess of 2% has been shown to extend life span
in the PSY316 background (29).
Effect of Amino Acid Concentration on CLS
Because decreasing availability of amino acids in yeast
media has been reported to extend RLS (6), the relationship
between amino acid concentration of the growth medium
and CLS was also examined. In contrast to glucose, reduced
amino acid levels (0.5X or 0.1X) did not increase CLS. To
our surprise, 10-fold higher concentrations of amino acids
substantially increased CLS (Figure 5A). This result is
interesting given that CLS can be extended by growth in
medium lacking a single high- or intermediate-nitrogen
quality amino acid, such as asparagine or glutamate (18),
and suggests that total amino acid abundance as well as the
relative amounts of individual amino acids can have
differential effects on longevity.
High Osmolarity Increases CLS
Given that elevated glucose levels shortened CLS but
elevated amino acid levels increased CLS, we considered
the possibility that osmotic stress could influence chrono-
logical aging. To determine whether this was the case, we
measured CLS when cells were grown in the presence of
standard CLS medium (Table 2) supplemented with either
18% sorbitol (an acyclic polyol that cannot be metabolized
as a carbon source) or 300 mM NaCl. Addition of either of
these osmolytes increased CLS (Figure 5B). This trend is
consistent with data demonstrating that high osmolarity
increases RLS (29). Thus, the short CLS associated with
high glucose appears to be glucose-specific, whereas the
Figure 2. Determination of chronological life span using a Bioscreen C MBR
machine. A, Outgrowth curves for following dilution of 5 lL from a culture of
aging yeast cells into 145 lL of YPD measured using a Bioscreen machine. The
rightward shift in curves with age is due to decreased viability in the population
of aging cells. OD¼optical density. B, Survival of BY4742 calculated from the
shift in outgrowth curve at each age-point relative to the initial age-point.
Table 3. The Bioscreen Method Provides Improved Precision for
Estimating Relative Viability in a Population of Yeast Cells
Dilution Factor (% Viability) Bioscreen CFU
Note: A dilution series was prepared from a yeast culture. The relative
fraction of viable cells was measured for each sample using the Bioscreen
method and by plating for colony forming units (CFUs). Based on six technical
replicates for each method, the coefficient of variation for the Bioscreen method
was less than for the CFU method at each dilution.
Figure 3. Comparison of chronological viability estimations obtained from
the Bioscreen method versus the traditional colony forming unit (CFU) method.
Chronological survival of W303AR (A) and PSY316AR (B) cells. Error bars
show standard deviation of five biological replicates.
HIGH-THROUGHPUT CHRONOLOGICAL AGING ASSAY
increased CLS associated with a 10-fold increase in amino
acids may reflect activation of an osmotic stress response
pathway that promotes chronological longevity.
CLS Extension from DR is Independent of Sirtuins
The involvement of Sir2 and Sir2 homologs in DR-
mediated life-span extension has been controversial (31). To
determine if CLS extension by DR requires Sir2 function,
Sir2 was deleted in three different strain backgrounds,
BY4742, W303, and PSY316, and subjected to DR by
reduction of glucose. In all three strains, low glucose at both
0.5% and 0.05% increased CLS extension independently of
Sir2 (Figure 6). This observation is consistent with a prior
report that Sir2 is not required for CLS extension using an
alternate DR method, i.e., aging postmitotic cells in water
(24) and with a more recent report using 0.5% glucose for
DR in BY4742 (16).
To determine if other yeast sirtuins might contribute to
CLS extension from DR, single gene deletions in Hst1, Hst2,
Hst3, and Hst4 in the BY4742 background were assayed
for life span in low-glucose medium. Similar to the case for
RLS (12), DR was sufficient to increase CLS in cells indi-
vidually lacking any of the four Sir2 homologs (Figure 7).
Additionally, DR increased the CLS of cells simultaneously
lacking all five yeast sirtuins (Figure 8), ruling out the
possibility that CLS extension in a strain lacking a single
sirtuin is due to a functionally redundant homolog. Thus, we
conclude that sirtuins do not mediate the CLS extension
associated with DR by growth in reduced glucose medium.
The Bioscreen C MBR method for measuring CLS re-
presents a novel high-throughput CLS assay with improved
Figure 4. Glucose reduced the chronological life span of BY4742 cells. Bioscreen outgrowth curves obtained from aging cell growth in medium with 20% (A), 10%
(B), 2% (C), 0.5% (D), or 0.05% glucose (E). F, Relative survival of cell growth in medium containing different glucose concentrations. Error bars show standard
deviation of five biological replicates.
MURAKAMI ET AL.
accuracy and precision relative to prior methods. We have
used this assay to examine the relationship between nutrient
availability and CLS and to examine the importance of
sirtuins for mediating effects of DR. Similar to the replicative
aging model (5,10), and as others have reported for CLS
(16), we find that CLS is extended by a reduction in glucose.
Also similar to the replicative aging model, this life-span
extension does not require the presence of sirtuins. Although
these data do not rule out a role for sirtuins in mediating
some aspects of DR, they do further support accumulating
evidence in the nematode Caenorhabditis elegans (32–34),
suggesting that DR acts by a sirtuin-independent mechanism
in evolutionarily divergent eukaryotes.
both RLS and CLS, our studies also identified two cases in
of high glucose, for example, is opposite to the increase in
and RLS when sorbitol or NaCl are used as osmolytes (29).
Further studies will be required to characterize the mecha-
nisms by which high osmolarity increases CLS whereas
increased glucose shortens CLS.
The CLS-shortening effect of reducing the total amino
acid levels of the medium was unexpected, as it has been
previously observed that reducing the concentration of either
asparagine or glutamate in the growth medium increases
CLS (18). Thus, it may be the case that CLS is affected
differently by the relative concentrations of individual amino
acids, and it will be of interest to explore this possibility in
future studies. The increase in CLS observed when amino
acid levels are increased is most likely related to increased
osmolarity, as evidenced by the increase in CLS observed at
either 1M sorbitol or 300 mM NaCl.
As demonstrated by our studies, one advantage of the
Bioscreen CLS method is that it is easily adaptable to
varying assay conditions. In the experiments reported here,
we aged the cells in culture tubes on a rolling drum in
a variety of different media compositions. Because viability
is determined by outgrowth in the Bioscreen C machine,
however, other culture conditions (e.g., aeration, tempera-
ture, volume) are equally adaptable to this method. For
example, an alternative protocol for chronologically aging
yeast cells involves growing cells to stationary phase in rich
Figure 5. Elevated amino acid (AA) concentrations and increased osmolarity
extend chronological life span. A, BY4742 cells grown in medium sup-
plemented with 10-fold higher AA levels live longer than cells grown in control
medium or medium with reduced AA levels (0.5X or 0.1X). B, BY4742 cells
grown in medium supplemented with either 18% sorbitol (sorb) or 300 mM
sodium chloride live longer than cells grown in control medium. Glu¼glucose.
Figure 6. Sir2 is not required for chronological life-span extension from
dietary restriction (DR) in multiple genetic backgrounds. Relative to cells grown
in control medium, DR by growth at either 0.5% or 0.05% glucose (glu)
increased life span in BY4742 sir2? (A), PSY316AR sir2? (B), and W303AR
sir2? (C) cells.
HIGH-THROUGHPUT CHRONOLOGICAL AGING ASSAY
medium then transferring them to water. A major difference
between cells aged in SD versus those aged in water is the
metabolic state of the quiescent cells; cells aged in SD
maintain a high metabolic rate, whereas cells transferred to
water from rich medium enter a so-called hypometabolic
state (35,36). The Bioscreen CLS method is equally
adaptable to either method and would be particularly useful
for systematically comparing how different mutants age
under each condition.
From our experience, aside from the initial cost of
purchasing the machine (;$35,000) the use of a Bioscreen
C MBR machine for determining yeast CLS has only two
significant limitations. First, the Honeycomb plates used
with this machine are 100-well plates, which are not easily
adapted for robotic 96- or 384-well assays. There is no
reason in principle that the Honeycomb plates cannot be
made in a 96-well format, and hopefully the manufacturer
will address this limitation in the near future. Second,
a maximum of 200 wells can be assayed per machine per
overnight incubation. This translates to a maximum
throughput of ;600 simultaneous CLS assays per Bioscreen
C MBR machine, assuming two age-points per week, or
1400 assays assuming 1 age-point per week. Thus, this
method provides much higher throughput capacity than
traditional CLS assays involving CFU determination,
without loss of accuracy or precision. Application of this
method in a genome-wide manner should allow for future
comparative analyses of yeast CLS with prior and ongoing
genomic studies of longevity in the yeast replicative aging
paradigm (13,37) and in C. elegans (38–43).
This work was supported by a pilot grant to M. K. from the University of
Washington Nathan Shock Center for Excellence in the Basic Biology of
Aging (National Institutes of Health Grant 5P30 AG013280) and by a grant
to B. K. K. and M. K. from the Ellison Medical Foundation. C. R. B. is
supported by National Institutes of Health Training Grant 5P30 AG013280.
C. J. M. and C. R. B. contributed equally to this work.
Address correspondence to Matt Kaeberlein, PhD, Department of
Pathology, University of Washington, Box 357470, Seattle, WA 98195-
7470. E-mail: email@example.com
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Received September 14, 2007
Accepted October 30, 2007
Decision Editor: Huber R. Warner, PhD
HIGH-THROUGHPUT CHRONOLOGICAL AGING ASSAY