होम STEM CELLS Increased Re-Entry into Cell Cycle Mitigates Age-Related Neurogenic Decline in the Murine...

Increased Re-Entry into Cell Cycle Mitigates Age-Related Neurogenic Decline in the Murine Subventricular Zone

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खंड:
29
साल:
2011
भाषा:
english
पृष्ठ:
13
DOI:
10.1002/stem.747
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आप पुस्तक समीक्षा लिख सकते हैं और अपना अनुभव साझा कर सकते हैं. पढ़ूी हुई पुस्तकों के बारे में आपकी राय जानने में अन्य पाठकों को दिलचस्पी होगी. भले ही आपको किताब पसंद हो या न हो, अगर आप इसके बारे में ईमानदारी से और विस्तार से बताएँगे, तो लोग अपने लिए नई रुचिकर पुस्तकें खोज पाएँगे.
TISSUE-SPECIFIC STEM CELLS
Increased Re-Entry into Cell Cycle Mitigates Age-Related Neurogenic
Decline in the Murine Subventricular Zone
ELIZABETH A. STOLL,a,b BEHNUM A. HABIBI,a ANDREI M. MIKHEEV,a JURATE LASIENE,a,c
SUSAN C. MASSEY,d KRISTIN R. SWANSON,e ROBERT C. ROSTOMILY,a,f PHILIP J. HORNERa,b,f
Institute for Stem Cell & Regenerative Medicine, bGraduate Program in Neurobiology & Behavior, dDepartment
of Applied Mathematics, eDepartment of Pathology, and fDepartment of Neurological Surgery, University of
Washington, Seattle, Washington, USA, cLaboratory for Motor Neuron Disease, RIKEN Brain Science Institute,
Wako-shi, Saitama, Japan
a

Key Words. Neurogenesis • Aging • Mitotic rate • Mitotic activity • Survival • Progenitor

ABSTRACT
Although new neurons are produced in the subventricular
zone (SVZ) of the adult mammalian brain, fewer functional neurons are produced with increasing age. The agerelated decline in neurogenesis has been attributed to a
decreased pool of neural progenitor cells (NPCs), an
increased rate of cell death, and an inability to undergo
neuronal differentiation and develop functional synapses.
The time between mitotic events has also been hypothesized to increase with age, but this has not been directly
investigated. Studying primary-cultured NPCs from the
young adult and aged mouse forebrain, we observe that
fewer aged cells are dividing at a given time; however, the
mitotic cells in aged cultures divide more frequently than

mitotic cells in young cultures during a 48-hour period of
live-cell time-lapse imaging. Double-thymidine-analog
labeling also demonstrates that fewer aged cells are dividing at a given time, but those that do divide are significantly more likely to re-enter the cell cycle within a day,
both in vitro and in vivo. Meanwhile, we observed that
cellular survival is impaired in aged cultures. Using our
live-cell imaging data, we developed a mathematical model
describing cell cycle kinetics to predict the growth curves
of cells over time in vitro and the l; abeling index over time
in vivo. Together, these data surprisingly suggest that
progenitor cells remaining in the aged SVZ are highly
proliferative. STEM CELLS 2011;29:2005–2017

Disclosure of potential conflicts of interest is found at the end of this article.

INTRODUCTION
Neural progenitor cells (NPCs) retaining the capacity to produce new neurons in the adult mammalian brain reside primarily in the subventricular zone (SVZ) and the subgranular
zone of hippocampal dentate gyrus [1]. Neuron production
declines in both areas during normal aging [2, 3]; this phenomenon is correlated with cognitive decline [4, 5]. However,
the cellular mechanisms underlying age-related neurogenic
decline are unclear. Neurogenesis is a complex, multistep process, and the documented age-related decline could be due to
a decreased pool of neural stem cells, slower cell cycle progression, a lower survival rate, a deficit in migration capacity,
or an inability to undergo neuronal differentiation and develop
functional synapses.
Although it can be challenging to examine these aspects
of neurogenesis separately, previous investigations into the
cellular mechanism of neurogenic decline have uncovered
fewer neural stem cells existing in aged SVZ [6]. Of these

remaining cells, a lower percentage are capable of differentiating into functional neurons; fewer aged NPCs could evoke
action potentials after differentiation protocols, although those
that did differentiate showed physiological characteristics
indistinguishable by age [7]. In addition, researchers have
observed a survival deficit in aging NPCs under both growth
and differentiation conditions [7, 8]. Much investigation of
the proliferative capacity of aging NPCs in vitro has relied on
gross analyses such as total cell or sphere counts that can be
influenced by multiple confounding factors. Several in vivo
studies, using single or sequential pulses of bromodeoxyuridine (BrdU), have concluded that aging leads to a loss of
NPCs in the SVZ [6, 7]. Others have suggested that neurogenic decline may be due to NPCs undergoing quiescence or
a lengthening of the cell cycle, perhaps due to increased tumor suppressor expression [8, 9] or decreased growth factor
responsiveness [10, 11]. However, cell cycle kinetics have not
been empirically determined in aging NPCs.
Thymidine-analog markers of S-phase can be used to
determine the number of cells dividing at a given time (the

Author contributions: E.A.S.: conception and design, collection and/or assembly of data, data analysis and interpretation, development of
mathematical model, and manuscript writing; B.A.H.: collection and/or assembly of data and data analysis and interpretation; A.M.M.:
conception and design; J.L.: collection and/or assembly of data; S.C.M. and K.R.S.: development of mathematical model; R.C.R. and
P.J.H.: conception and design, financial support, data analysis and interpretation, and manuscript writing.
Correspondence: Elizabeth A. Stoll, University of Washington, 815 Mercer St., Box 358056, Seattle, Washington 98195-8056, USA.
Telephone: 206-897-5717; e-mail: bethstollthecookies@gmail.com; or Philip J. Horner, Ph.D. Telephone: 206-897-5715; Fax:
206-685-1357; e-mail: phorner@uw.edu Received January 19, 2011; accepted for publication September 10, 2011; first published
C AlphaMed Press 1066-5099/2011/$30.00/0 doi: 10.1002/stem.747
online in STEM CELLS EXPRESS September 21, 2011. V

STEM CELLS 2011;29:2005–2017 www.StemCells.com

Cell Cycle Kinetics of Aging Neural Progenitors

2006

mitotic index). The number of cells in S-phase at a given
time gives no information about the rate of cell cycle transit
or re-entry. However, several of these markers can be used in
concert to calculate the time between successive S-phases.
This measure is affected by the amount of time needed to
transit through the cell cycle, as well as the latency and likelihood for NPCs to re-enter the cell cycle, all factors which
could affect net proliferative activity. In this study, we quantified the time between successive S-phase labels and cytokinetic events in young adult and aged adult NPCs. Surprisingly, aged cultures appear to contain both a highly quiescent
population and a highly proliferative population; in contrast,
many young NPCs divide sporadically. This study demonstrates that, although a fewer number of aged cells are cycling
at a given time, the actively cycling NPCs remaining in the
aged mouse forebrain undergo more cell divisions in a given
period of time than those in the young adult forebrain.

MATERIALS

AND

METHODS

NPC Isolation
All experiments were performed as approved by the University of
Washington Institutional Animal Care and Use Committee.
Female C57BL/6 mice were housed at 21 C with access to food
and water ad libitum. Adult NPCs were isolated as previously
described [12]. Briefly, wild-type C57BL/6 mice, 3 months and
18 months of age, were overdosed with Beuthanasia and transcardially perfused with ice-cold saline. Brain tissue, not including
olfactory bulbs or cerebellum, was mechanically and enzymatically dissociated with collagenase-DNase solution. To remove debris, myelin and red blood cells, the cell suspension was mixed
with a percoll solution and centrifuged. The isolated progenitor
cells were grown in proliferation media, consisting of Dulbecco’s
modified Eagle’s medium/F12 supplemented with 2 mM glutamine, 1% N2 (Gibco, Carlsbad, CA, www.invitrogen.com/site/us/
en/home/brands/Gibco.html), 50 lg/ml heparin (Sigma, St Louis,
MO, www.sigmaaldrich.com/united-states.html), 20 ng/ml epidermal growth factor (Peprotech, Rocky Hill, NJ, www.peprotech.
com), and 20 ng/ml fibroblast growth factor-2 (Peprotech). Cultures were passaged by mechanical dissociation, and used for in
vitro experimentation between passages 3 and 15. All in vitro
experiments were performed at least three times; replications
included at least two independent cell isolates of each age.

Cellular Assays
Growth curves were extrapolated from passage rate and viable
cell counts at passage. Forebrain-derived cultures initially formed
neurospheres in vitro and were capable of continued passage as
spheres or a monolayer. Cell number and viability was quantified
at each passage using the ViCell automated cell counting system
(Beckham Coulter, Indianapolis, IN, https://www.beckmancoulter.com). Cells were plated at 106/10 cm tissue culture dish. Four
days after passage, cells were trypsinized and counted. To quantify the mitotic index and live-dead cell count of young and aged
NPCs, live cells were collected and incubated at 37 C with
Hoechst (0.5 mg/ml) for 30 minutes then incubated at 37 C with
propidium iodide (1 lg/ml). Cells were then subjected to sorting
and analysis with FACSdiva (BD Biosciences, Franklin Lakes,
NJ, www.bdbiosciences.com/instruments/software/facsdiva/index.
jsp). Cellular debris and doublets were sorted out by side scatter
analysis, and propidium iodide–positive dead cells were quantified and gated out. Remaining cells were plotted by Hoechst
width to assay mitotic phase ratios. Cell fractions within G1, S,
and G2/M phases were binned and compared with two-tailed t tests
in Excel. Time-lapse live-cell imaging was performed using a
Nikon TiE inverted widefield fluorescence microscope (nikoninstruments.com/Information-Center/Perfect-Focus-System-PFS), with

an environmental chamber for temperature and CO2 control,
attached to an EMCCD camera. Cells were first infected with a
lentiviral construct expressing green fluorescent protein (GFP)
under a constitutive promoter, which was produced in accordance
with NIH guidelines for recombinant DNA. Labeled cells were
plated at low density with uninfected, age-matched cells (1:100) on
poly-L-lysine-coated 60-mm dishes and were photomicrographed
every 15 minutes for 48 hours at 30 under phase and GFP using
NIS Elements software (Nikon Instruments, Melville, NY,
www.nis-elements.com). Time-lapse live-cell imaging data were
analyzed using Fisher’s exact test.

Immunocytochemistry
To characterize markers of progenitor cell phenotype, NPCs were
plated in 24-well plates at a density of 10,000 cells per well on
laminin- and poly-L-lysine-coated glass coverslips for 4 days in
proliferation media. Cells were then fixed in 4% paraformaldehyde at room temperature for 5 minutes, rinsed three times with
phosphate-buffered saline (PBS), and blocked for 1 hour in PBS
with 0.08% Triton X-100 and 5% donkey serum. Cells were then
labeled with anti-Nestin mouse monoclonal antibody (Chemicon
MAB353, 1:1,000, www.millipore.com), anti-CD133 mouse
monoclonal antibody (14-1331-82, 1:333, eBioscience, www.
ebioscience.com), anti–SRY box 2 (anti-Sox2) goat polyclonal
antibody (SC17320, 1:250, Santa Cruz, www.scbt.com) and antiKI67 rabbit polyclonal antibody (NCL-Ki67p, 1:500, Novocastra,
www.leica-microsystems.com/products/total-histology/novocastrareagents). Terminal deoxynucleotidyl transferase dUTP nick end
label–positive (TUNELþ) apoptotic cells were quantified using
TdT Reagent Kit (Chemicon S7160). The following secondary
antibodies were diluted 1:2 in 50% glycerol, then 1:250 in PBS
with 0.08% Triton X-100 and 5% donkey serum: Jackson Labs
(www.jacksonimmuno.com) Cy2-conjugated donkey anti-rat,
RedX-conjugated donkey anti-mouse, and Cy2-conjugated donkey
anti-rabbit. To quantify the number and rate of cycling cells, we
used the antigenically distinct thymidine analogs chlorodeoxyuridine (CldU) (Sigma C6891-100 mg) and iododeoxyuridine (IdU)
(Sigma I7125-5G). Cells were plated on coated coverslips as previously, and exposed to CldU (4.6 lg/ml) and uridine (1 mg/ml)
for 30 minutes to label dividing cells [13]. Although exposure to
thymidine analogs has been reported to have cytotoxic effects on
mammalian cells, no deleterious effects have been observed at
these concentrations. At 12-hour, 15-hour, 18-hour, 21-hour, or
24-hour after removal of CldU, cells were treated with IdU (7.2
lg/ml) for 30 minutes then immediately fixed with 4% paraformaldehyde. Anti-CldU rat monoclonal antibody clone BU1/75
(1:250, Novus, www.novusbio.com) and anti-IdU mouse monoclonal antibody clone B44 (BD Biosciences 347-580, 1:250) were
applied sequentially for 90 minutes at 37 C, followed by incubation with appropriate secondary antibodies for 60 minutes at
room temperature. All cells were costained with 40 ,6-diamidino2-phenylindole (DAPI) (Sigma D9542). Fluorescence microscopy
was performed using a Zeiss Axioskop two with attached
Optronics camera and StereoInvestigator software (MBF Biosciences, Williston, VT, www.mbfbioscience.com/stereo-investigator). Fractions of labeled cells were compared using a twotailed t test in Excel.

Quantification of Dividing Cells In Vivo
To quantify NPCs in the young adult and aged SVZ, mice aged 3
months (n ¼ 8) and 20 months (n ¼ 8) were injected with BrdU
(50 mg/kg) once daily for 12 days. The animals were divided
into two groups, and either euthanized immediately following the
final injection or 28 days after the final injection. To quantify cell
cycle re-entry in the young adult and aged SVZ, mice aged 3
months (n ¼ 6) and 18 months (n ¼ 6) were injected with a single pulse of CldU (50 mg/kg), then with three pulses of IdU (50
mg/kg) 16 hours, 18 hours, and 20 hours later. Animals were euthanized with 0.04 ml Beuthanasia, then transcardially perfused
with ice-cold saline followed by 4% paraformaldehyde. Brains

Stoll, Habibi, Mikheev et al.

were removed and serially sectioned into 20-lm slices. Tissue
sections were stained on glass slides after being subjected to antigen capture using 0.01 M sodium citrate and 2 N HCl. BrdUþ
mitotic cells and BrdU-retaining cells were labeled with antiBrdU rat monoclonal antibody (Novus MB500169, 1:200), antiNestin mouse monoclonal antibody (Chemicon MAB353, 1:250),
anti-Sox2 goat polyclonal antibody (Santa Cruz SC17320, 1:250),
anti–T-box brain 2 (anti-Tbr2) rabbit polyclonal antibody (gifted
from Robert Hevner’s laboratory) and anti-glial fibrillary acidic
protein (anti-GFAP) rabbit polyclonal antibody (Z0334, 1:300,
Dako, www.dako.com). Double-thymidine-analog labeling was
performed by sequentially applying anti-CldU rat monoclonal
antibody clone BU1/75 (Novus, 1:250) overnight at 4 C and antiIdU mouse monoclonal antibody clone B44 (BD Biosciences
347-580, 1:250) for 2 hours at 37 C, followed by incubation with
appropriate secondary antibodies for 2 hours at room temperature.
Cells were counted in 100  200 lm grids on NIS Elements software in 10-20 optical sections. Three-dimensional reconstruction
of z-stack images was performed with Volocity software (Perkin
Elmer, Waltham, MA, www.perkinelmer.com/pages/020/cellularimaging/products/volocity.xhtml). Counts were adjusted for total
SVZ area. Fractions of labeled cells were compared using a twotailed t test in Excel.
To calculate cell cycle transit time using a cumulative BrdU
labeling protocol, animals were injected with BrdU (50 mg/kg)
once every 3 hours for 18 hours. A cohort of animals (n ¼ 4 for
each age group at each time point) was sacrificed 1 hour after
each BrdU injection. Perfusion, BrdU labeling, and cell quantification were performed as described above. The total number of
BrdUþ cells in the SVZ of each animal was plotted, and regression lines were fitted to the points [14, 15]. The x value at which
BrdU labeling reaches a plateau is Tc  Ts, the time required to
transit through the cell cycle subtracted by the time required for
transit through S-phase. The y value at this point is referred to as
GF, the total number of proliferating cells in the SVZ. The y
intercept of the curve, denoting the number of cells labeled at the
first time point, is equal to (Ts/Tc)  GF. Tc and Ts are calculated
based on a curve fit solved for a minimum sum of squares (SS)
[16]. After calculating the SS and degrees of freedom for each
data set compared to a model (the curve fit to the control group),
the data sets were subjected to nonlinear regression analysis and
were compared using an F test.

RESULTS
Mitotic Index in the Aging Brain
Previous investigators have reported a dramatic difference in
the BrdU labeling index in young and aged SVZ using a
single-day BrdU pulsing protocol [8, 11]. Yet the accumulated
number of cells in S-phase over an extended period of time
has not been determined. To calculate the number of BrdUþ
cells in SVZ after an extended labeling protocol, young (3
months, Fig. 1A) and aged (20 months, Fig. 1B) mice were
intraperitoneally injected with 50 mg/kg BrdU for 12 days,
then sacrificed. We observed a 21% fewer BrdUþ cells in the
aged SVZ, compared with the young adult SVZ (p < .05,
Fig. 1C). After this extended labeling protocol, we observed
no difference in the fraction of SOX2þ cells that incorporated
BrdU (p > .05, Fig. 1D). BrdUþ mitotic cells (in green),
colabeled with the neural stem cell marker SOX2 (in red), are
observed in the dorsolateral SVZ of young (Fig. 1E) and aged
adult mice (Fig. 1F), and along the lateral ventricle of young
(Fig. 1G) and aged adult mice (Fig. 1H). BrdUþ cells in the
young (I, K, and M) and aged adult (J, L, and N) SVZ colabel with Nestin (I-J), Tbr2 (K-L), and GFAP (M-N). We
observed significantly more BrdUþ cells in the aged SVZ
colabeled with Sox2 (p < .01) and significantly fewer BrdUþ
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2007

cells in the aged SVZ colabeled with Nestin (p < .001); we
observed no differences in fractions of cells colabeled with
Tbr2 or GFAP (O).
We injected a second group of mice with 50 mg/kg BrdU
intraperitoneally for 12 days, then sacrificed them 28 days
afterward. We then quantified label-retaining cells, the population of slowly dividing cells [1], in the young (Supporting
Information Fig. 1A) and aged (Supporting Information Fig.
1B) SVZ. We observed a 45% decrease in the number of
label-retaining cells in the SVZ with age (p < .05, Supporting
Information Fig. 1C). We also quantified GFAPþ cells in the
young (Supporting Information Fig. 1A) and aged (Supporting
Information Fig. 1B) SVZ. Although we observed greater
numbers of GFAPþ cells with an astrocytic morphology in
the aged brain (p < .001, Fig. 1N), there were no significant
differences in the fraction of GFAPþ-labeled cells in the
population of BrdUþ cells or BrdUþ label-retaining cells
(p > .05, Supporting Information Fig. 1D). The 45% decrease
in BrdUþ label-retaining cells suggests a decrease in the
population of slowly dividing stem-like cells in the aged
brain. To more closely investigate young and aged NPCs, we
carried out in vitro assays on cultured cells.

Growth of Aging NPCs in Culture
Once forebrain-derived cultures entered logarithmic growth
phase and could be actively passaged, we characterized their
immunophenotypes and proliferative activity. Both young
(Fig. 2A-2C) and aged (Fig. 2F-2H) NPCs expressed uniformly high levels of the stem cell markers Nestin (Fig. 2A,
2F), CD133 (Fig. 2B, 2G), and SOX2 (Fig. 2C, 2H), demonstrating that young and aged NPCs are antigenically similar
(p > .05, Fig. 2K-2M). However, a greater percentage of
young NPCs (Fig. 2D) than aged NPCs (Fig. 2I) stained positive for KI67, a marker of active proliferation (p < .05,
Fig. 2N). We further immunophenotyped the KI67þ cells,
and found that a greater fraction of aged KI67þ cells were
SOX2þ (p < .05, Fig. 2Q), although there were no significant
age-related differences in colabeling of KI67 with GFAP or
doublecortin (DCX) (p > .05, Fig. 2P, 2R). Colabeling in the
KI67þ population adds up to more than 100% because there
is likely to be overlap between the KI67þ populations that
are SOX2þ and those that are DCXþ.
Next, we quantified the viability of young (Fig. 2E) and
aged (Fig. 2J) NPCs. Aged cells displayed a significant
increase in TUNELþ staining, an indication of apoptotic activity (p < .01, Fig. 2O). Using the ViCell automated cell
quantification system, we also observed a significant increase
in trypan blueþ nonviable cells in aged cultures (p < .01,
Fig. 2S). To further investigate the mitotic index of these
cells, we quantified the number of young and aged NPCs in
each phase of the cell cycle using Fluorescence-activated
cell sorting (FACS; Fig. 2T, 2U). Live cells were labeled
with 2 lg/ml Hoechst; cellular doublets and debris were
sorted out by side scatter analysis and propidium iodide
exclusion. Remaining cells were binned to assay mitotic
phase ratios. A significantly higher percentage of 3-month
cells were observed in G2/M phase of the cell cycle, compared with 18-month cells (31.0% vs. 12.4%, p < .0001).
Together, these data support the notion that fewer aged adult
cells are undergoing mitosis at a given time, and that these
cells are less viable than young adult cells. We hypothesized
that progression through the cell cycle might be altered in
aged cells as well.

Live-Cell Imaging Analysis
To empirically quantify the time between mitotic events, we
took time-lapse images of live cells. To better visualize

Figure 1. BrdUþ cells are observed in the SVZ of adult and aged mice. Representative images from the SVZs of young (A, E, and G) and
aged (B, F, and H) mice intraperitoneally injected with 50 mg/kg BrdU for 12 days; the line indicates 20 lm. Twenty-one percentage of fewer
BrdUþ cells are observed in aged brains (C, p < .05). No difference was observed in the fraction of SOX2þ cells that incorporated BrdU (D, p
> .05). BrdUþ mitotic cells (in green), colabeled with the neural progenitor cell marker SOX2 (in red), are observed in the dorsolateral SVZ (E
and F) and lateral SVZ (G and H) of young adult (E and G) and aged adult (F and H) mice. Young adult (I, K, and M) and aged adult (J, L, N)
brains contain BrdUþ cells that colabel with Nestin (I and J), Tbr2 (K and L), and GFAP (M and N). Significantly more BrdUþ cells in the
aged SVZ colabel with Sox2 (p < .01), while significantly fewer BrdUþ cells in the aged SVZ colabel with Nestin (p < .001); there were no differences in fractions of cells colabeled with Tbr2 or GFAP (p > .05, O). Abbreviations: BrdU, bromodeoxyuridine; GFAP, glial fibrillary acidic
protein; SOX2, SRY box 2; SVZ, subventricular zone; Tbr2, T-box brain 2.

Stoll, Habibi, Mikheev et al.

2009

Figure 2. Fewer neural progenitor cells (NPCs) derived from aged forebrain are observed in cell cycle at a given time. Similar fractions of
young (A-C) and aged (F-H) NPCs stain positive for stem cell markers Nestin (A and F), CD133 (B and G), and SOX2 (C and H); the line indicates 5 lm. Fewer aged NPCs are labeled with the mitotic marker KI67 (I), compared with young NPCs (D). More aged NPCs are labeled with
the apoptotic marker TUNEL (J), compared with young NPCs (E). Quantification of stem and progenitor cell marker labeling is shown, with
young cells shown in gray and aged cells in black (K-O). No significant differences in Nestin, CD133, or SOX2 expression were observed (K-M,
p > .05); significant differences in expression between groups were observed in KI67 and TUNEL labeling (N and O, p < .05). KI67 cells were
further immunophenotyped; a significantly greater fraction of aged KI67þ cells were SOX2þ (Q, p < .05), but no significant differences in
colabeling with GFAP (P) or DCX (R) were observed (p > .05). Cell death was further investigated using ViCell; trypan blue-viable cells significantly decreased with age (S, p < .01). Live cells were labeled with Hoechst and subjected to fluorescence-activated cell sorting analysis to quantify mitotic index (T). A summary graph indicates that a significantly greater fraction of young cells were in G2/M phase compared with aged
cells (U, p < .001). Abbreviations: DAPI, 40 ,6-diamidino-2-phenylindole; DCX, doublecortin; GFAP, glial fibrillary acidic protein; KI67, antigen
identified by monoclonal antibody KI67; SOX2, SRY box 2; Tdt, terminal deoxynucleotidyl transferase dUTP nick end label (TUNEL labeling).

individual cells, we labeled young and aged NPCs with a lentivirus containing GFP under a constitutive promoter, and
plated them at 1:100 on a layer of unlabeled cells of the same
age. By taking photomicrographs of young and aged NPCs
every 15 minutes for 48 hours, we could track whether a single cell divided, then whether daughter cells divided additional times (Fig. 3A, Supporting Information Videos 1-4).
We categorized these cells, separating the fractions of nondividers (no mitoses in 48 hours), rare dividers (one mitosis in
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48 hours), and prolific dividers (more than one mitosis in 48
hours). We observed that significantly more aged cells had no
mitotic events, compared with young cells (67% vs. 22%, p
< .001). However, comparing only the dividing cells, a
greater proportion of aged NPCs than young NPCs were prolific dividers (56% vs. 29%, p < .05). A 79% decrease was
observed in the rarely dividing population with age (p <
.0001), while a nonsignificant decrease was observed in the
prolifically dividing population with age (p > .05). The

2010

Cell Cycle Kinetics of Aging Neural Progenitors

Figure 3. Live imaging of green fluorescent protein-labeled neural progenitor cells (NPCs). In a period of 48 hours of live-cell time-lapse
imaging, significantly more aged NPCs compared with young NPCs had no mitotic events at all (A, 67% vs. 22%, p < .001). The dividing population in aged cultures had a greater proportion of 2þ dividers, compared with the dividing population in young cultures (A, 56% vs. 29%, p <
.05). No significant differences were observed in the average time between mitotic events (B, 16.8 hours in aged cells, 20.7 hours for young cells,
p ¼ .162). Significantly fewer young cells underwent cell death (C, p < .001). Of total cells, a greater fraction of young cells were observed to
exit the field of view (D, p < .01); of the dividing population, no differences in migration were observed (D, p > .05).

average number of mitotic events for the entire population
was 1.07 for young cells and 0.57 for aged cells, but among
the mitotic population, the average number was 1.37 events
for young cells and 1.70 events for aged cells. In addition, we
measured the time between mitotic events in each culture, by
subtracting the timestamps on frames from consecutive cytokineses. A great deal of variability was observed in times
between cell divisions; aged cells exhibited an average time
between mitoses of 16.8 hours, while young cells that divided
more than once exhibited an average time between mitoses of
20.7 hours (p > .05, Fig. 3B). Similar to results with TUNEL
labeling and ViCell quantification methods (Fig. 2O, 2S),
aged cultures had a significantly greater incidence of cell
death under live-cell imaging (p < .001, Fig. 3C). Of only
dividing cells, aged cultures displayed significantly higher
rates of cell death (p < .05, Fig. 3C). Significantly fewer
aged cells also migrated out of the field of view during the
48-hour period of live-cell imaging (p < .01, Fig. 3D). Of
only dividing cells, however, aged cultures did not have significantly different rates of migration (p > .05, Fig. 3D).
These data provide direct evidence for a rather surprising
result: specifically, that aged NPC cultures have fewer
actively cycling cells than do young NPC cultures, but aged
cells that are cycling undergo a significantly greater number
of divisions.

Double-Thymidine-Analog Labeling
To quantify re-entry into the cell cycle, we sequentially labeled young and aged NPCs with two antigenically distinct

thymidine analogs (Fig. 4A). All mitotic cells were labeled by
30-minute CldU pulse at time 0. After rinsing and further
incubation, cells were labeled with a 30-minute IdU pulse and
immediately fixed, at 3-hour time points throughout the following day. Cells were not presynchronized, but a population
of coincident cells labeled by CldU in an initial S-phase was
investigated for re-entry into cell cycle at multiple independent time points by colabeling with IdU. The fraction of IdUþ
cells of total DAPIþ cells was significantly higher in young
cultures (Fig. 4B) than in aged cultures (Fig. 4C) after a 30minute pulse in vitro, agreeing with previous results that
fewer cells are dividing at a given time in aged cultures (p <
.0001, Fig. 4D). However, a significantly larger fraction of
CldUþ aged cells colabeled with IdU at the 12-, 15-, 18-, and
21-hour time points (12-hour, p < .01; 15-hour, p < .0001;
18-hour, p < .0001; 21-hour, p < .001; 24-hour, p > .05, Fig.
4E). These data suggest that aged cells have an increased
tendency to re-enter the cell cycle within a day of a previous
S-phase labeling.
To test whether this effect was also observed in vivo, we
treated young and aged mice with a single intraperitoneal
injection of 50 mg/kg CldU, followed by intraperitoneal injections of 50 mg/kg IdU at 16 hours, 18 hours, and 20 hours
post-CldU (Fig. 5A). This protocol identifies cells rapidly reentering cell cycle, by covering the peak time between successive mitoses observed in young and aged NPCs in vitro.
We observed double-labeling in 18.2% of the CldUþ cells in
the young adult SVZ (Fig. 5B) and in 34.7% of the CldUþ
cells in the aged adult SVZ (Fig. 5C) after this protocol (p <

Stoll, Habibi, Mikheev et al.

2011

Figure 4. Double-thymidine-analog labeling to assay cell cycle re-entry of neural progenitor cells in vitro. The strategy used to quantify cell cycle
length in vitro is depicted (A); the line indicates 5 lm. Cells were given a single 30-minute pulse of CldU (4.5 lg/ml, in green); at various time
points over the next day, cells were given a single 30-minute pulse of IdU (7.2 lg/ml, in red) and immediately fixed. Colabeled cells have re-entered
S-phase in the period of time since CldU exposure. Representative images of CldUþ and IdUþ cells from young cultures (B) and aged cultures
(C), at the 18-hour post-CldU time point, are shown. The IdUþ labeling index is significantly lower in aged cells, compared with young cells, after
a 30-minute pulse (D, p < .00001). The fraction of CldUþ cells colabeled with IdU at each time point from a representative experiment is quantified (E). S-phase re-entry appeared to peak between 15 hours and 18 hours after CldU exposure for both groups, although the fraction of colabeled
cells in the CldUþ population was significantly higher in aged cultures at the 12-hour (p < .01), 15-hour (p < .0001), 18-hour (p < .0001), and 21hour (p < .001) time points. Abbreviations: CldU, chlorodeoxyuridine; DAPI, 40 ,6-diamidino-2-phenylindole; IdU, iododeoxyuridine.

.001, Fig. 5D). The number of IdUþ cells yields a quantification of the number of cells dividing at a given time. In vivo,
we observed significantly fewer IdUþ cells (p < .00001,
Fig. 5E) and significantly fewer CldUþ cells (p < .0001,
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Fig. 5F) in the aged SVZ. Despite the many complex processes that govern cell genesis in the SVZ, these data confirm
that aged cells are more likely to re-enter cell cycle than
young adult cells over a 22-hour period in vivo.

2012

Cell Cycle Kinetics of Aging Neural Progenitors

Figure 5. Double-thymidine-analog labeling to assay cell cycle re-entry of neural progenitor cells in vivo. The strategy used to quantify cell
cycle re-entry in vivo is depicted (A). Wild-type mice were given a single pulse of CldU (50 mg/kg) at time 0, then given pulses of IdU (50 mg/
kg) 16 hours, 18 hours, and 20 hours later. Colabeled cells have entered S-phase again in the period of time since CldU exposure. Representative
images of CldUþIdUþ cells from young (B) and aged (C) mouse SVZ, after fixation of 22 hours post-CldU, are shown; the line indicates 20
lm. The fraction of CldUþ cells colabeled with IdU is quantified (D); 18.2% of young CldUþ cells and 34.7% of aged CldUþ cells (in green)
were colabeled with IdUþ (in red). IdUþ and CldUþ labeling indices, quantifying the cells dividing at a given time, are shown (E and F, p <
.00001). Abbreviations: CldU, chlorodeoxyuridine; DAPI, 40 ,6-diamidino-2-phenylindole; IdU, iododeoxyuridine; SVZ, subventricular zone.

Cumulative BrdU Labeling to Calculate
Cell Cycle Transit Time
To calculate the time required for cells to transit through Sphase and the entire cell cycle, we performed cumulative
BrdU labeling according to a method developed by Nowakowski and coworkers [14–16]. Young and aged mice were
injected with BrdU once every 3 hours; 1-hour after each
injection, several animals in each age group were sacrificed.
A schematic depicting this protocol is shown (Fig. 6A). Representative pictures of the young (Fig. 6B) and aged (Fig. 6C)
SVZ after 1, 4, and 7 BrdU injections are shown. BrdUþlabeled cells are plotted (Fig. 6D). Cell cycle transit times
were calculated according to two equations: Tc  Ts, the x
value at which labeling reached a plateau and Ts/Tc  GF, the
y value at time 0 (3,360 cells in the young SVZ and 1,516 in
the aged SVZ). GF is equivalent to the number of BrdUþ
cells at the plateau (5,602 cells in the young SVZ and 2,214
cells in the aged SVZ). From these equations, we calculate
that young cells take 9.8 hours to transit through the entire
cell cycle, with 4.9 hours for S-phase, while aged cells take
7.6 hours to transit through the entire cell cycle, with 4.2
hours for S-phase. These curves are significantly different

(p < .001), unless each data point is normalized to its respective GF, suggesting that the total number of cycling cells is
significantly different between groups, but cell cycle length is
not.

Mathematical Modeling of Cell Cycle Kinetics
To verify that the cell expansion observed in vitro is consistent with our time-lapse live-cell imaging data and double-thymidine-analog labeling data, we developed a simple mathematical model applying our empirical data regarding agerelated differences in cell cycle kinetics (Supporting Information Table 1). The number of cells counted in culture (the first
observation), is the starting population (N(0)); this population
was subjected to an iterative equation describing cellular activity over a 48-hour period. The equations used to model the
cell counts over time are described in Figure 7; N(t) equals
the number of cells present in the previous time step and N(t
þ 2) equals the number of cells present in the current step
(after 48 hours). The original cell count (N(0)) is cycled
through this equation describing cell cycle kinetics empirically determined over a 48-hour period under live-cell imaging; the computed result (N(t þ 2)) is then set as the next

Stoll, Habibi, Mikheev et al.

2013

Figure 6. Cumulative BrdU labeling for calculation of cell cycle transit time. Young and aged mice were injected with BrdU once every 3
hours over 18 hours. One hour after each injection, a cohort of animals was sacrificed. A schematic depicting this protocol is shown (A). Representative pictures of the young (B) and aged (C) SVZ from early, middle, and late time points are shown; the line indicates 20 lm. BrdUþ cells
at each time point are plotted (D). Regression curves were fit to all data points, and the point at which labeling reached a plateau (Tc  Ts) was
identified. The number of BrdUþ cells at the plateau (GF) is 5,602 cells in the young SVZ and 2,214 cells in the aged SVZ. The number
of BrdUþ cells at the time 0 (the y intercept) is 3,360 cells in the young SVZ and 1,516 in the aged SVZ. Abbreviations: BrdU, bromodeoxyuridine; DAPI, 40 ,6-diamidino-2-phenylindole; SVZ, subventricular zone.

iteration’s N(t). The predictions over time are plotted against
actual cell counts derived from samples quantified every 4
days from young and aged cultures (Fig. 7).
At each iteration, the previous cell population (N(t)) is
added to the newly divided cells, quantified by the fraction of
cells entering cell cycle in a 48-hour period of live-cell imaging (N(t)  E, shown in Fig. 3A). All cells are subject to
death, so this number was multiplied by the fraction of surviving cells (S) observed after 48 hours under live-cell imaging (Fig. 3C). This simple model, predicting a growth curve
based on cell cycle entry and survival, is depicted in Figure
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7A. The regression values describing the fit between predicted
results and values observed by counting cells at passage are
r2 ¼ .964 for young cells and r2 ¼ .767 for aged cells. Next,
we adapted this simple model to take into account cell cycle
re-entry: the fraction of cells entering cell cycle was multiplied by the number of new cells produced by the dividing
cells (the fraction of cells dividing once create two cells each
(two  D1), the fraction of cells dividing twice create three
cells each (3  D2), and so on, as quantified during 48 hours
of time-lapse live-cell imaging (Fig. 3A). This adapted model
is depicted in Figure 7B. The regression values describing the

2014

Cell Cycle Kinetics of Aging Neural Progenitors

Figure 7. A mathematical model predicting growth curves of cultured cells. At each iteration, cell cycle entry and survival are calculated; the
predicted results are compared with actual growth curves (A). The model is adapted to include cell cycle re-entry, as determined by number of
divisions observed under live-cell imaging over 48 hours (B).

fit between predicted results using this model and values
observed by counting cells at passage are r2 ¼ .998 for young
cells and r2 ¼ .940 for aged cells. This model is therefore
superior to the previous model, which took into account only
the number of actively cycling cells and survival, so we conclude that cell cycle re-entry is an important factor in the net
proliferative activity of a population of NPCs.

We then modeled the thymidine-analog labeling index
over time in vivo, using the number of CldUþ cells after
a single pulse (shown in Fig. 5F), as the starting index
(L(0)). This population of actively dividing cells was subjected to an adapted iterative equation to generate a modelderived final index (L (12) computed), which we fit to the
actual number of BrdUþ cells after 12 thymidine-analog

Stoll, Habibi, Mikheev et al.
pulses (L (12) in vivo), to obtain predicted values of N,
the total number of cells in the SVZ (described in Supporting Information Methods and Supporting Information Table
2). These predicted values of N are 6,334 in the young
adult brain and 4,791 in aged adult brain. The model-predicted labeling indices are compared in Supporting Information Figure 2 to actual BrdUþ cell counts in the young
adult and aged adult SVZ after an extended 12-day labeling
protocol.

DISCUSSION
Although molecular mechanisms regulating proliferation,
including cell cycle regulatory proteins and niche-derived factors, have been manipulated to recover neurogenic activity in
aged NPCs [8–11, 17, 18], an actual slowing of cell cycle
progression in the normal aged brain has not been demonstrated. Decreased number of NPCs, decreased capacity for
differentiation, and decreased cell survival have been shown
to underlie age-related neurogenic decline in the SVZ [6–8].
Several studies additionally suggest that a proliferative deficit
may be responsible for neurogenic decline in vivo [7, 10],
although this phenomenon has been difficult to empirically
separate from changes in cell number or survival rate [6]. In
testing these hypotheses, it has proved notably difficult to
empirically separate a proliferative index (the number of cells
dividing at a given time) from the proliferative activity (specifically, the time between one cell division and the next),
especially considering the problem of heterogenous populations of NPCs. Although a fewer number of aged NPCs are
dividing at a given time, according to FACS analysis, KI67
labeling, and BrdU labeling, we show in the present study
that aged cells that are cycling undergo a greater number of
cell divisions. It is not clear whether the rarely dividing population is selectively lost, or whether cell cycle progression is
sped up in individual remaining cells. Because of the limitations of cell fate identification, it cannot be definitively stated
whether the sizes of stem and progenitor populations are
affected differentially in vivo. Cultures used in this study
were derived from whole forebrain tissue, which increases the
heterogeneity of stem and progenitor cells present. However,
NPCs from the SVZ are thought to be a major contributor to
these cultures. The short time frames of each experiment
were designed to target primarily the NPC population, and the
experiments performed in vivo were designed to test the activity of SVZ progenitors specifically.
Using time-lapse live-cell imaging (Fig. 3), we found that
a lower fraction of the aged culture undergoes cell division,
but aged cells that do divide are highly proliferative dividers.
Compared with young adult cultures, aged cultures contain
fewer rare-divider cells, which divide one time in 48 hours
(55% vs. 15%, p < .0001), and fewer cells that exhibit more
than 20 hours between cell divisions (52% vs. 19%, p ¼
.0516). It is not clear whether this slowly dividing population
is lost or whether aged cells on average speed up cell cycle
progression, since the result in either case would be more cell
divisions on average in the population. In support of the former view, the number of slowly dividing cells that retain
BrdUþ labeling after 28 days are significantly reduced in the
aged animals (Supporting Information Fig. 1). In support of
the latter view, the time between successive cell divisions
observed by time-lapse live-cell imaging or cumulative BrdU
labeling is 20% lower in aged cultures, although these
results are not significant, due to high variability. Two populations can be distinguished in Figure 3B: cells with an interwww.StemCells.com

2015

val greater than 20 hours between cytokinetic events, and
cells with less than 20 hours between cytokinetic events. Calculations of cell cycle length by cumulative BrdU labeling in
vivo are shorter than those calculated by time-lapse imaging
(9.8 hours in young cells and 7.6 hours in aged cells). The
BrdUþ cells under investigation in the accumulation experiment are primarily quickly dividing progenitors, labeled
within an 18-hour timeframe, while some of the cells
observed under time-lapse imaging may have been stem-like,
with more than 20 hours between cytokinetic events. Heterogeneity of progenitor populations is a source of variability
that decreases the statistical power of cell cycle length
comparisons.
Double-thymidine-analog-labeling experiments (Figs. 4, 5)
demonstrate that the proliferative deficit observed in aged animals is due to a decreased number of dividing cells, not
slower cell cycle transit or less cell cycle re-entry. Fewer
aged NPCs were observed in S-phase after a 30-minute thymidine-analog pulse in vitro and in vivo, in agreement with
our data showing less KI67þ labeling and a lower FACS mitotic profile in aged cells. The time between S-phase peaks
was not significantly different between cultures in this experiment. Interestingly, however, higher numbers of aged cells
were observed with double-labeled nuclei at time points
between 12 hours and 21 hours in vitro (Fig. 4E) and between
16 hours and 20 hours in vivo (Fig. 5D). The high doublelabeling index could be interpreted as aged cells being
blocked in S-phase of the cell cycle, but since full cytokinetic
events were observed under live-cell imaging, this possibility
seems unlikely. Therefore, we conclude that aged NPCs
which are actively cycling are more likely to re-enter S-phase
of cell cycle within a day after completing a round of cell
division.
Significant age-related changes in cell cycle re-entry are
demonstrated directly in Figures 4 and 5, using double-thymidine-analog labeling, and indirectly in Figures 3A and 7A and
7B, using live-cell time-lapse imaging and mathematical modeling. In Figures 3A and 7A and 7B, changes in cell cycle
length and cell cycle re-entry are indistinguishable, while cell
cycle re-entry is not quantified in Figure 6 at all. Together,
these results suggest that aged NPCs do not have a significantly different cell cycle length compared with young NPCs,
but are more likely to re-enter into cell cycle. Perhaps, however, increased cell cycle re-entry is caused by an abbreviated
G1 phase—in other words, these two phenomena (cell cycle
length and cell cycle re-entry) may be effectively inseparable
due to empirical limitations.
Cell cycle regulatory proteins may affect the proliferative
activity of NPCs across the lifespan. We demonstrated previously that the remaining population of NPCs in the aged forebrain have lower expression and inducibility of the tumor suppressor protein p53 [19]. Impairment in this cell cycle
regulatory pathway can affect the rate of cell division [9].
However, increased p16 expression has also been reported
with age [8, 19], and p16 null mice have higher rates of new
neuron production in the aged SVZ, compared with wild-type
mice [8]. However, there is evidence that p16 has differential
roles in cell cycle progression depending on cellular context
and age; for example, altered p16 expression in hematopoetic
stem cells does not cause replicative senescence [20, 21]. The
net effect of the bidirectional changes in tumor suppressor
protein expression documented in aging NPCs has not been
thoroughly investigated. However, intriguing correlations have
been shown between a shortened G1 phase of the cell cycle
and an expansion of the progenitor population at the expense
of neuronal differentiation, during development [22, 23], in
adulthood [24], or after injury of the adult brain [15].

Cell Cycle Kinetics of Aging Neural Progenitors

2016

Multiple mechanisms could be responsible for age-related
changes in NPC population size and cell cycle progression,
with the balance between senescence and regeneration
achieved by compensation on a molecular scale. Cellular
selection within the neurogenic niche may also affect the
observed progenitor phenotype. Recently, a loss of morphologically identifiable proliferative subpopulations has been
reported in the aging hippocampus [25]; it is not known
whether similar subpopulations are selectively affected in the
aging SVZ.
Given single or sequential pulses of BrdU over the course
of a single day, previous investigators have observed dramatically decreased numbers of mitotic cells in the aged SVZ [6–
8, 10]. Our data, both in vitro (Figs. 2, 4) and in vivo (Fig.
5E, 5F), also point to a greatly decreased number of cells
undergoing mitosis at a given time. However, aged cells are
more likely to re-enter S-phase of the cell cycle within a day,
both in vitro (Fig. 4E) and in vivo (Fig. 5D). We hypothesized that quicker cell cycle progression could partially compensate for a lower cell number in the aged brain over time.
To test this hypothesis, we developed an iterative mathematical model incorporating empirically derived cell cycle kinetics
to predict the regenerative activity of NPCs over time, as both
the number of cycling cells and the number of cells produced
in a given period of time are taken into account. Mathematical modeling based on empirically derived data has been used
previously to predict cellular activity in the case of a tumor
[26, 27]. These previous models used differential MRI data
from individual patients to predict tumor growth by calculating values describing only proliferation and invasiveness.
Similarly, we are confident that populational activity in vitro
and in vivo can be described here using empirical data. The
data used to build the model were derived from a single in
vitro methodology, while the observed data to which the
model was compared are determined by alternate methodologies. In addition, the variables incorporated into the model
reflect specific cellular phenomena, while observed values are
dependent upon net proliferative activity. While our model
predicts the in vitro growth curves and in vivo thymidine-analog labeling quite well, some factors may not have been fully
accounted for in the models. Quantifying true values for survival, migration, and total cell number in vivo may create a
better fit with the observed data. It is notable that this model,
based on data from live-cell imaging experiments showing
more mitotic events in the actively cycling population of aged
cells, predicts observations of cellular behavior both in vitro
and in vivo with a high level of accuracy. Together, these
models support the hypothesis that aged NPCs partially compensate for a smaller population over time, with more mitotic
events per cell.
Previous authors have observed that the decrease in
BrdUþ cells in the aged SVZ matches the decrease in new
neurons observed in the olfactory bulb [8, 11]. These data

REFERENCES

suggest that a decreased stem cell population is primarily responsible for age-related neurogenic decline; however, survival and differentiation are also significantly impaired with
age. The ability of the remaining population of dividing cells
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then pared down again by impaired survival and differentiation (Supporting Information Fig. 3). While such a case may
be helpful in maintaining some level of olfactory cortical
repair under normal conditions, a dysregulation in cell cycle
kinetics could predispose the remaining population of neural
stem cells to become cancer stem cells. Alterations in cell
cycle progression during normal aging may resolve a paradox
wherein aging leads to both neurogenic decline [2, 6–8, 10,
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investigation of altered cell cycle regulation in aging
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CONCLUSION
Paradoxically, aging leads to both a decreased regenerative
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activity with an increased capacity for proliferation.

ACKNOWLEDGMENTS
We thank Jason Barber for assistance with statistical analysis
and Denise Inman for valuable discussions. E.A.S. is supported
by the University of Washington Training Grant in Developmental Biology (HDO7183-28), the University of Washington
Retirement Association Fellowship in Aging Biology, and the
American Foundation for Aging Research. B.A.H. is supported
by the Mary Gates Undergraduate Fellowship. This work was
supported by AG029406 (R.C.R. and P.J.H.) and NSO46724
(P.J.H.).

DISCLOSURE OF POTENTIAL
CONFLICTS OF INTEREST
The authors indicate no potential conflicts of interest.
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