METHODS AND RESOURCES
A novel approach to determine the critical survival threshold of cellular oxygen
within spheroids via integrating live/dead cell imaging with oxygen modeling
Kuang-Ming Shang,
1
Hiroyuki Kato,
2
Nelson Gonzalez,
2
Fouad Kandeel,
2
Yu-Chong Tai,
1
and
Hirotake Komatsu
2
1
Department of Medical Engineering, California Institute of Technology, Pasadena, California, United States and
2
Department
of Translational Research & Cellular Therapeutics, Arthur Riggs Diabetes & Metabolism Research Institute of City of Hope,
Duarte, California, United States
Abstract
De
fi
ning the oxygen level that induces cell death within 3-D tissues is vital for understanding tissue hypoxia; however, obtaining
accurate measurements has been technically challenging. In this study, we introduce a noninvasive, high-throughput methodol-
ogy to quantify critical survival partial oxygen pressure (pO
2
) with high spatial resolution within spheroids by using a combination
of controlled hypoxic conditions, semiautomated live/dead cell imaging, and computational oxygen modeling. The oxygen-per-
meable, micropyramid patterned culture plates created a precisely controlled oxygen condition around the individual spheroid.
Live/dead cell imaging provided the geometric information of the live/dead boundary within spheroids. Finally, computational ox-
ygen modeling calculated the pO
2
at the live/dead boundary within spheroids. As proof of concept, we determined the critical
survival pO
2
in two types of spheroids: isolated primary pancreatic islets and tumor-derived pseudoislets (2.43 ± 0.08 vs.
0.84 ± 0.04 mmHg), indicating higher hypoxia tolerance in pseudoislets due to their tumorigenic origin. We also applied this
method for evaluating graft survival in cell transplantations for diabetes therapy, where hypoxia is a critical barrier to successful
transplantation outcomes; thus, designing oxygenation strategies is required. Based on the elucidated critical survival pO
2
, 100%
viability could be maintained in a typically sized primary islet under the tissue pO
2
above 14.5 mmHg. This work presents a valu-
able tool that is potentially instrumental for fundamental hypoxia research. It offers insights into physiological responses to hy-
poxia among different cell types and may re
fi
ne translational research in cell therapies.
NEW & NOTEWORTHY
Our study introduces an innovative combinatory approach for noninvasively determining the critical sur-
vival oxygen level of cells within small cell spheroids, which replicates a 3-D tissue environment, by seamlessly integrating three
pivotal techniques: cell death induction under controlled oxygen conditions, semiautomated imaging that precisely identi
fi
es live/
dead cells, and computational modeling of oxygen distribution. Notably, our method ensures high-throughput analysis applicable
to various cell types, offering a versatile solution for researchers in diverse
fi
elds.
cell survival; computational simulation; hypoxia; pancreatic islets; viability assay
INTRODUCTION
Hypoxia, characterized by insuf
fi
cient oxygen availability
at the cellular, tissue, or systemic level, plays a pivotal role in
both physiological adaptation and pathological processes
within the human body. At the molecular level, the response
to hypoxia is intricately regulated by the hypoxia-inducible
factor 1 alpha (HIF-1
a
), a key transcription factor that orches-
trates downstream molecular functions (
1
,
2
). Hypoxia repre-
sents multifaceted adaptive responses that are crucial for
survival, with both bene
fi
cial and detrimental consequences
dictated by the HIF-1
a
downstream molecular functions.
HIF-1
a
activation triggers essential responses for oxygen
delivery including increased erythropoietin to produce red
blood cells (
3
,
4
), secretion of vascular endothelial growth
factor to facilitate angiogenesis (
5
), as well as for CD18-
mediated in
fl
ammation (
6
). In addition, the duality of hy-
poxia is evident in its role in normal tissues and cancer cells.
Cancer cells exploit hypoxia-inducible factors to thrive in
the hostile microenvironment by promoting angiogenesis,
metabolic reprogramming, and resistance to cell death (
7
,
8
)
which contributes to disease progression.
Although hypoxia is widely acknowledged as a crucial phe-
nomenon in biology and physiology, establishing a universal
threshold between normoxia and hypoxia proves challenging.
The diversity among cells and tissue types, exempli
fi
ed by
variations between normal and cancer cells, complicates the
standardization of cut-off values. Consequently, de
fi
ning spe-
ci
fi
ccriticalsurvivalpO
2
values for distinct cell types and
tissues is essential, offering insights into their hypoxia re-
sistance in physiological assessments. Although theoreti-
cally feasible to determine critical survival pO
2
for inducing
Correspondence: H. Komatsu (hirotake.komatsu@ucsf.edu).
Submitted 14 January 2024 / Revised 7 March 2024 / Accepted 8 March 2024
C1262
0363-6143/24 Copyright
©
2024 the American Physiological Society.
http://www.ajpcell.org
Am J Physiol Cell Physiol
326: C1262
–
C1271, 2024.
First published March 18, 2024; doi:
10.1152/ajpcell.00024.2024
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single-cell death in vitro under precisely controlled hypoxia
culture conditions, the ideal scenario involves identifying
such thresholds within in vivo, mimicking 3-D tissues where
physiological cell-cell contact is maintained.
De
fi
ning critical survival pO
2
is essential not only for
understanding cellular and tissue biology but also for devel-
oping cell therapies, particularly evident in pancreatic islet
transplantations for patients with type 1 diabetes (
9
–
12
).
Isolated islet spheroid, a microorgan consisting of thousands
of insulin-secreting cells from the donor pancreas, faces
challenges due to the loss of native microvessels during iso-
lation. Relying on interstitial oxygen, cells within the sphe-
roid compete for oxygen and cells in the spheroid center with
increased diffusion distances (average size of 150
l
mindiame-
ter) are susceptible to hypoxic stress (
13
,
14
). Thus, islet sphe-
roids are at risk of hypoxia-induced central necrosis, reducing
total islet cell mass in culture and transplantation engraftment
in islet cell therapy. Several oxygenation approaches have
been introduced to prevent hypoxia-induced islet graft loss.
Concentrated oxygen was injected into a compartment encas-
ing the transplanted islets (
15
–
17
), and co-transplantation tech-
niques incorporating oxygen-containing or oxygen-generating
materials improved the viability of transplanted islets (
18
–
20
).
Although these approaches were experimentally demonstrated
to be effective, understanding the critical survival pO
2
of islet
cells is crucial for developing improved oxygenation strategies,
particularly in estimating exogenous oxygen requirements that
ensure the viability of grafts.
Although understanding the critical survival pO
2
for cells
and tissues is crucial, accurately measuring this pO
2
value
within 3-D tissues and spheroids presents signi
fi
cant chal-
lenges. Direct measurements, such as needle-like Clark elec-
trodes (
21
,
22
) and optical
fi
ber methods (
23
), necessitate the
insertion of a sensor tip into the tissues to access the necrotic
core; this process intrinsically alters the original oxygen gra-
dient and, thus, compromises the accuracy of the measure-
ment. Silicone microbeads incorporated into a 3-D cell
culture and electron paramagnetic resonance imaging (EPR)
are potential noninvasive approaches. However, the large
size of the beads and the low resolution of EPR are critical
barriers to measuring pO
2
in small 3-D tissues at the
l
mlevel
(
24
–
26
).
In this study, we present a novel and comprehensive
methodology for determining the critical survival pO
2
for
3-D cell spheroids; this method integrates three key techni-
ques:
1
) inducing cell death within spheroids under precisely
regulated oxygen concentrations and geometric parameters
(
27
);
2
) using semiautomated imaging to distinguish live and
dead cells within spheroids (
28
); and
3
)utilizingcomputa-
tional modeling to assess oxygen distribution within sphe-
roids (
29
). Our approach effectively addresses current
challenges in de
fi
ning the critical survival pO
2
within tiny
3-D spheroids, offering a noninvasive technique with high
spatial resolution data.
MATERIALS AND METHODS
Rat Islet Isolation Procedures
Rat islets were isolated from rat pancreata using our
standard procedure (
30
). Male Lewis rats (Charles River,
Wilmington, MA) aged between 16 and 20 wk and weighing
between 400 and 500 g were used as islet donors. Under gen-
eral anesthesia, 9 mL of collagenase solution [2.5 mg/mL
(Sigma-Aldrich, MO), HEPES at 100 mM (Irvine Scienti
fi
c,
Santa Ana, CA) in ice-cold Hanks
’
balanced salt solution
(HBSS; Sigma-Aldrich)] was injected into the pancreatic duct
through the common bile duct. The distended pancreas was
dissected, followed by enzymatic digestion at 37
C for 10
min. The digested pancreas was centrifuged at 300
g
for 3
min. Pellets were washed and subjected to density gradient
centrifugation in HBSS solution and Histopaque-1077 (den-
sity: 1.077 g/mL, Sigma-Aldrich) for 25 min at 300
g
and
24
C. Islets were hand-picked for purity. The use of animals
and animal procedures in this project was approved by City
of Hope/Beckman Research Institute Institutional Animal
Care and Use Committee. Following isolation, all islets from
a single donor were cultured in a 10 cm Petri dish (Corning
Life Sciences) containing 8 mL of CMRL 1,066 culture me-
dium (Corning Life Sciences, Tewksbury, MA) and incubated
overnight at 27
CinaCO
2
incubator for recovery. Due to the
heterogeneous size of the isolated islets, the standardized
unit of Islet Equivalent (IEQ) was used to count the volume-
based, normalized islet number, in which the islet with 150
l
mindiameterisde
fi
ned as 1 IEQ (
31
). Islet yield per donor
ranged from 750 to 1,200 IEQ, assessed after overnight recov-
ery. Islet purity was assessed before initiating hypoxia
experiments and con
fi
rmed to be
>
90% using our standard
procedure with Dithizone staining (iDTZ, Gemini Bio-prod-
ucts, CA) (
32
).
Production of Pseudoislets
A rat beta cell line (INS-1 832/13 Rat Insulinoma Cells, Sigma-
Aldrich) was used to produce 3-D pseudoislets (PsIs). After the
expansionofthecellsinthe2-Dconventionaltissueculture-
treated dishes with RPMI1640 medium (Life Technologies,
Carlsbad, CA) supplemented with 10% heat-inactivated fetal bo-
vine serum (FBS, Atlanta Biologicals, Lawrenceville, GA), 50
mM of 2-Mercaptoethanol (Sigma-Aldrich), 10 mM of HEPES
(Sigma-Aldrich), 1 mM of sodium pyruvate (Sigma-Aldrich), 2
mM of L-glutamine (Sigma-Aldrich), cells were trypsinized into
single cells. Dissociated single cells were seeded on a 35 mm-mi-
crowell plate (EZSPHERE 900SP; 500
l
m-microwell diameters;
AGC Techno Glass, Yoshida, Japan) at the seeding density of
1.25
10
6
cells/dish. After the 2-day culture of the cells to form
the PsIs in a CO
2
incubator at 37
C, PsIs were retrieved for the
subsequent experiments. The standardized unit of IEQ was
used to count the volume-based, normalized PsIs number (
31
).
Culture Conditions of Islet Spheroids
One hundred IEQ per well of either isolated rat primary
islets or PsIs were seeded onto the micropyramid-patterned,
oxygen-permeable bottomed dish (24-well platform) (
27
),
using 1 mL of their speci
fi
c culture medium aforementioned.
The culture dish bottom had the inverse topography of
Aggrewell 400 microwell array (Aggrewell 400, STEMCELL
Technologies, Vancouver, Canada) made of polydimethylsi-
loxane (PDMS), which allows for the separation of seeded
islets in a uniform oxygen environment throughout the well
bottom. The plate was placed within the air-tight modular
incubator chambers (Billups-Rothenberg, San Diego, CA),
DETERMINING CRITICAL SURVIVAL pO
2
FOR ISLET SPHEROIDS
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and the designated mixed gas (1% O
2
,5%CO
2,
and 94% N
2
)
was
fi
lled using the gas mixer (GB3000, MCQ Instruments,
Rome, Italy). The distilled water was added to the chamber
to provide a humidi
fi
ed culture condition (6.2% H
2
O
(g)
).
Once the oxygen was reached to the designated partial pres-
sure, the chamber was tightly sealed and placed into the in-
cubator at 37
C. To monitor the partial oxygen pressure
within the chamber during the subsequent culture period,
the RedEye patch was attached to the inner surface of the
modular incubator chamber to noninvasively measure the
pO
2
in the chamber from the outside using the optical oxy-
gen sensor (NeoFox, Ocean Optics, Dunedin, FL). The sphe-
roids were cultured for 2 days with no culture medium
changes. During the culture period, the pO
2
within the
chamber was maintained at the designated value ± 10% devi-
ation (i.e., 0.9%
–
1.1% O
2
), measured with RedEye patch.
At the end of the culture period, the chamber was opened,
and the actual pO
2
in the culture medium at the bottom level
of the dish, where islets or PsIs were placed, was directly
measured by inserting the
fl
exible needle-type optical oxy-
gen sensor (NeoFox, Ocean Optics) that recon
fi
rmed the pO
2
within the 10% deviation to the designated values.
Viability Assessment of Islet Spheroids Using Image
Analysis
Viability of islet spheroids (both primary islets and PsIs) was
analyzed using live/dead staining by a semiautomated method
previously reported (
33
,
34
). Cultured islet spheroids (100 IEQ/
group) were incubated in 0.48
l
Mof
fl
uorescein diacetate
(FDA; Sigma-Aldrich) and 15
l
M of propidium iodide (PI;
Sigma-Aldrich) solution in phosphate-buffered saline for 5 min
in the dark at room temperature. Subsequently, they were
washed with phosphate-buffered saline and transferred to
a 96-well plate to capture the
fl
uorescent images (IX50,
Olympus, Tokyo, Japan). By setting thresholds for green
(FDA; live cells) and red (PI; dead cells), FDA-positive or
PI-positive areas were automatically calculated by the
imaging software (cellSens, Olympus). FDA-positive area
and PI-positive area were mutually exclusive within the is-
let spheroids for the analysis (sky blue for FDA-positive
areas and magenta for PI-positive areas), and the islet area
was de
fi
ned as the sum of FDA-positive and PI-positive
areas. The volumetric viability of an islet sample was cal-
culated as follows: viability (%)
¼
100
—
[(PI-positive area/
islet area)
3
100]. Shape factor, which numerically describes
the shape of a particle under two-dimensional images in a
microscope (
35
), was calculated for all spheroids by the soft-
ware, and spheroids with shape factor
<
0.7 (regarded as
nonspherical) were excluded from the analyses. A total of
262 primary islets and 107 PsIs were analyzed.
Oxygen Consumption Rate Measurement
The oxygen consumption rate (OCR) assay was performed
for the metabolism assessments of islet spheroids as previ-
ously described (
36
). Approximately 100 IEQ of primary islets
or PsIs were plated on a Seahorse XFe islet capture plates
(Seahorse Bioscience, North Billerica, MA) and preincubated
at 37
C in a non-CO
2
-incubator for 3 h. Measurement of the
OCR was performed using a Seahorse XFe analyzer (Seahorse
Bioscience North Billerica, MA) every 7.5 min at 3 mM glucose
for seven measurements. OCR data were normalized by the
IEQ applied. OCRs of primary islets from
fi
ve rats and seven
preparations of PsIs were individually measured. The OCR
measurement was conducted in an environment with oxygen
levels (pO
2
) exceeding 120 mmHg to minimize the oxygen gra-
dientbetweentheplasticcellplateandthemicrochamber
containing spheroids. This approach reduced the potential for
oxygen diffusion through the plastic cell plate, which could
otherwise result in inaccurate OCR readings. Given that the
measurements took place in a well-oxygenated setting, the
observed OCR was utilized to estimate the maximal OCR val-
ues for the following simulations.
Computational Model of Oxygen Di
ff
usion and Reaction
We used the
fi
nite element method (COMSOL Multiphysics
5.3, MA) to derive the complete pO
2
pro
fi
le within each islet
spheroid and its surrounding microenvironment. The govern-
ing equation for oxygen transport, based on Fick
’
sdiffusion
and reaction, is expressed as:
o
c
o
t
¼
D
r
2
c
R
In this equation,
c
represents the oxygen concentration,
D
is the oxygen diffusion constant, and
R
is the oxygen con-
sumption term. The latter follows Michaelis
–
Menten type
metabolic kinetics:
R
¼
OCR
max
c
c
þ
K
m
Here, OCR
max
indicates the maximal oxygen consumption
rate, and
K
m
is the Michaelis constant, corresponding to the
oxygen concentration at half the maximum consumption
rate. To ensure the continuity of pO
2
across different boun-
daries, we applied Henry
’
s law to relate the oxygen concen-
tration to pO
2
,where
S
indicated the oxygen solubility:
c
¼
S
pO
2
Statistical Analysis
Statistical analyses were conducted utilizing the SciPy
library (
37
). Sample sizes were calculated based on the esti-
mated population variance obtained from a preliminary
study. This calculation incorporated a
z
-score of 2.58 to
achieve 99% con
fi
dence intervals. Data were presented as
means ± standard error of the mean (SEM) with relevant per-
centiles. For the statistical analysis, outliers were excluded if
the data points were beyond the 75th percentile plus 1.5
times the interquartile range or below the 25th percentile
minus 1.5 times the interquartile range. We used Pearson
’
s
correlation coef
fi
cient (
r
) to quantify the linear relationship
between variables. We used Welch
’
s
t
test to address unequal
sample sizes and variances. The results reported the
P
value
and an
a
level of 0.01 to interpret the statistical signi
fi
cance.
RESULTS
The Method to Determine the Survival Threshold of
Cellular Oxygen within a Spheroid Was Developed by
Integrating Live/Dead Cell Imaging with Oxygen Modeling
We used three techniques:
1
) inducing cell death within
spheroids under the precisely controlled oxygen and geometric
DETERMINING CRITICAL SURVIVAL pO
2
FOR ISLET SPHEROIDS
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parameters;
2
) semiautomated live/dead cell imaging of sphe-
roids; and
3
) oxygen computational modeling of spheroids to
determine the critical survival pO
2
within spheroids.
We used the air-tight chamber to apply the 1% oxygen at
37
C under atmospheric conditions to induce the initial step
—
hypoxic cell death within a controlled oxygen microenvir-
onment (
Fig. 1
A
). Subsequently, we seeded spheroids rang-
ing 70
–
300
l
m in diameter at approximately 0.5 spheroids/
mm
2
on the micropyramid arrays (which equates to 100
spheroids per well of a 24-well plate) on the oxygen-permea-
ble, micropyramid patterned culture plates (
27
), with 1,200
micropyramidsperwell.Thiscon
fi
guration ensured the
separation of each islet and prevented the interference of
reduced oxygen by the oxygen-consuming neighboring
spheroids. Moreover, oxygen-permeable PDMS micropyra-
mids allowed for 1% oxygen air in the chamber to effec-
tively diffuse from the bottom of the plate to the culture
medium around the spheroids. We prepared two represen-
tative spheroids, primary rat pancreatic islets and pseudo
pancreatic islets (PsIs) derived from a rat beta cell tumor.
We cultured them for 2 days, inducing hypoxic cell death
in the core of the spheroids. Our culture setup enables
investigators to precisely control the pO
2
levels surrounding
spheroids and minimize uncertainty and variation in the sub-
sequent computational modeling of the pO
2
pro
fi
le.
The second step was to acquire the two-color live/dead
fl
u-
orescent images of spheroids post 2-day hypoxic culture to
extract the parameters required for the subsequent oxygen
O
2
O
2
O
2
A
1% O
2
24-well
Spheroid
PDMS
B
Live
/
Dead
Live
/
Dead
Live
/
Dead
Raw
images
Color
recognition
Concentric
model
Extracting
parameters
r
dead
r
spheroid
Viability
= 39 μm
= 73 μm
= 84.8 %
r
dead
r
spheroid
100 μm
C
Culture
medium
Spheroid
Dead core
Oxygen-permeable,
micropyramid-bottomed,
PDMS plate
Boundary:
Air-PDMS interface
1% O
2
(7.6 mmHg)
200 μm
Boundary:
Air-PDMS interface
1% O
2
(7.6 mmHg)
7
6
5
4
3
2
1
0
pO
2
(mmHg)
Symmetric boundary
Symmetric boundary
Critical survival pO
2
for spheriod is acquired
by averaging the
pO
2
at this boundary
r
dead
&
r
spheroid
are extracted
from live/dead
imaging
D
Figure 1.
Work
fl
ow for determining the
critical survival pO
2
in spheroids.
A
:sphe-
roids are cultured in a controlled hypoxic
environment with 1% oxygen (O
2
). The
structure and material of the culture dish,
micropyramid shape, and oxygen-perme-
able PDMS bottom plate ensure individual
islet separation and a uniform oxygen
environment for each islet cultured.
B
:an
example of the parameter extraction pro-
cess, which includes postculture live/dead
staining and imaging, semiautomated soft-
ware-based color recognition of spheroids
anddeadcores,andconversionintoacon-
centric geometry model to calculate the
spheroid radius (
r
spheroid
) and dead core ra-
dius (
r
dead
). Sky-blue and magenta areas
indicate the viable and dead cells, respec-
tively. Scale bar: 100
l
m.
C
: a steady-state
oxygen diffusion and reaction model for an
individual spheroid requires parameters of
the spheroid, the micropyramid-bottomed
PDMSdish,andtheculturemedium.
Schemas of the 3-D geometry (
left
)and
the cross-sectional pO
2
pro
fi
le (
right
)are
shown. Scale bar: 200
l
m.
D
:integration
of live/dead images (a concentric geom-
etry model,
top
) with oxygen simulations
(
middle
) enables calculation of the critical
survival pO
2
,de
fi
ned as the pO
2
at the
live/dead boundary (
bottom
; a graph dem-
onstrating the pO
2
in the midline cross
section of the spheroid). Simulation details
and coef
fi
cients can be found in
Table 1
.
PDMS, polydimethylsiloxane; pO
2
,partial
oxygen pressure.
Table 1.
Simulation coef
fi
cients of oxygen of primary islet, pseudoislets (PsIs), culture medium, and PDMS
Materials
P
,10
2
14
s
·
mol
·
kg
2
1
D
,10
2
9
m
2
·
s
2
1
S
,10
2
5
s
2
·
mol
·
kg
2
1
·
m
2
2
OCR
max
, mol
·
m
2
3
·
s
2
1
K
m
, mol
·
m
2
3
References
Primary islets
0.99
1.3
0.76
0.0174
0.001
(
29
,
38
)
Pseudoislets (PsIs)
0.99
1.3
0.76
0.0200
0.001
(
29
,
38
)
Culture medium
3.05
2.8
1.09
(
39
,
40
)
PDMS
104
7.9
13.2
(
40
,
41
)
D
, oxygen diffusivity;
K
m
, Michaelis oxygen constant; OCR
max
, maximal oxygen consumption rate;
P
, oxygen permeability; PDMS, pol-
ydimethylsiloxane;
S
, oxygen solubility coef
fi
cient; permeability equals diffusivity times solubility (
P
¼
D
S
).
Measured in our current
study. See also Supplemental Fig. S1.
DETERMINING CRITICAL SURVIVAL pO
2
FOR ISLET SPHEROIDS
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simulations.
Figure 1
B
demonstrates the process to extract
the radius of the spheroid (
r
spheroid
) and dead core (
r
dead
); the
pancreatic islet, approximately 150
l
m in diameter, consist-
ing of thousands of endocrine cells, is presented. Typically,
dead cells are concentrically present in the spheroid
’
score,
which is characteristic of hypoxia-induced central necrosis due
to the oxygen gradient within the spheroid. Subsequently, we
used a software for semiautomated two-color recognition for
live and dead areas to calculate the areas of the spheroid and
the dead core. We introduced the concentric model that
EF
GH
Primary islets
Pseudo-islets (PsIs)
Primary islets
Pseudo-islets (PsIs)
ABCD
Primary islets
Pseudo-islets (PsIs)
Post-culture
Live
/
Dead
Pre-culture
Live
/
Dead
Live
/
Dead
Pre-culture
Live
/
Dead
Post-culture
r
dead
r
spheroid
Viability
= 0 μm
= 78 μm
= 100 %
r
dead
r
spheroid
Viability
= 0 μm
= 76 μm
= 100 %
r
dead
r
spheroid
Viability
= 60 μm
= 85 μm
= 64.8 %
r
dead
r
spheroid
Viability
= 39 μm
= 73 μm
= 84.8 %
100 μm
100 μm
100 μm
100 μm
Live
/
Dead
Live
/
Dead
DETERMINING CRITICAL SURVIVAL pO
2
FOR ISLET SPHEROIDS
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converts the actual shape traced into a completely circular
shape for calculating the estimated radius of the spheroid
(
r
spheroid
)andthedeadcore(
r
dead
).
We established a steady state pO
2
pro
fi
le in the microen-
vironment within the spheroid by integrating the live/dead
imaging parameters in the third step.
Figure 1
C
illustra-
tes the 3-D geometry, boundary conditions, and a cross-
sectional pO
2
pro
fi
le, using a representative spheroid with
r
spheroid
at 73
l
mand
r
dead
at 39
l
m. We designed the oxygen
simulation geometry for the spheroids with the following pa-
rameters: each spheroid comprises a concentric inner dead
core and an outer live shell; the central necrotic area does
not consume oxygen (i.e.,
R
¼
0); oxygen consumption rate
in the outer live shell follows Michaelis
–
Menten metabolic
kinetics; and spheroids were surrounded by culture medium,
forming a tall cuboid geometry. We also constructed the oxy-
gen simulation geometry for a micropyramid-shaped, oxy-
gen-permeable PDMS. The height of the medium was 5.3
mm based on a medium volume of 1 mL in a 24-well plate.
The cuboid
’
s dimensions, both width and length, were 1.4
mm, which was triple the base side length of the micropyra-
mid. The boundary conditions are established with a 1% oxy-
gen concentration (equivalent to 7.6 mmHg) at both the top
and bottom surfaces of the medium. We set the side faces as
symmetrical planes under the assumption of negligible oxygen
interference between spheroids. A comprehensive list of simu-
lation parameters is presented in
Table 1
.TheOCRdataofpri-
mary islets and PsIs are available in Supplemental Fig. S1.
The
fi
nal step was to de
fi
ne the critical survival pO
2
within
the spheroid (
Fig. 1
D
). We calculated the critical survival pO
2
by averaging the pO
2
pro
fi
les at the boundary between the
live shell and the dead core within the spheroid. Collectively,
we developed a new method to de
fi
ne the survival threshold
of cellular oxygen within a spheroid by integrating the three
key techniques.
The Method De
fi
ned the Critical Survival Threshold of
Cellular Oxygen within Pancreatic Endocrine Spheroids
We applied our newly developed approach to determine
the critical survival pO
2
in two types of spheroids for the
proof of concept of this approach. We tested
1
) primary pan-
creatic islets isolated from the native pancreas and
2
) pseu-
doislets derived from the insulin-secreting endocrine cell
line. These spheroids secrete insulin; thus, when trans-
planted as beta cell replacement therapy, they can treat dia-
betes (
42
,
43
). However, spheroids are vulnerable to hypoxia,
which has been one of the roadblocks to their wide-use beta
cell replacement therapy; thousands of oxygen-consuming
cells within the spheroids create a steep oxygen gradient and
subsequent hypoxia-induced central necrosis. Our new
method will determine the physiological oxygen sensitivity
of these spheroids by de
fi
ning the critical survival pO
2
of the
cells within the spheroids.
We cultured these spheroids in hypoxia culture at 1% oxy-
gen for 2 days.
Figure 2
A
demonstrates the representative
live/dead stain images of primary islets at pre- and postcul-
ture timepoints in the typical size at
r
¼
75
l
m. We con-
verted the postculture image into the concentric model image
to measure the
r
spheroid
,
r
dead
, and viability. Integrating cell
imaging data with oxygen modeling identi
fi
ed the critical sur-
vival pO
2
of the primary islets at 2.39 mmHg (
Fig. 2
B
).
Similarly,
Fig. 2
C
demonstrates the representative live/dead
stainimagesofPsIswiththemeasuredr
spheroid
,r
dead
,andvia-
bility data. The critical survival pO
2
of this speci
fi
cPsIswas
0.89 mmHg (
Fig. 2
D
). Subsequently, we collected the data of
r
spheroid
,
r
dead
, viability, and critical survival pO
2
from individ-
ual spheroids of 262 primary islets and 107 PsIs. Live/dead
images in various sizes of spheroids (
r
¼
50, 75, and 100
l
m)
at pre- and posthypoxic culture are available in Supplemental
Fig. S2
A
(primary islets) and S2
B
(PsIs). Distribution of the
spheroid size in primary islets and PsIs is presented in
Supplemental Fig. S2,
C
and
D
.
Figure 2
E
displays all data
plots of
r
spheroid
and
r
dead
in primary islets and PsIs, demon-
strating the positive linear correlations between
r
spheroid
and
r
dead
. The overall viability of primary islets and PsIs on
day 2
was 75.8 ± 1.1% and 78.2 ± 1.1%, respectively (
Fig. 2
F
,
P
¼
0.116).
The viability of all individual spheroids is available in
Supplemental Fig. S2,
E
(primary islets) and
F
(PsIs).
Lastly, we determined the critical survival pO
2
of individual
spheroids and plotted all data according to the spheroid size
(
r
spheroid
,
Fig. 2
G
). The average critical survival pO
2
values of
primary islets and PsIs were 2.43 ± 0.08 mmHg and 0.84 ± 0.04
mmHg, respectively (
Fig. 2
H
); the median and interquartile
range(IQR)valueofcriticalsurvivalpO
2
values of primary
islets and PsIs were 2.24 (IQR 1.52
–
3.24) mmHg and 0.84 (IQR
0.56
–
1.12) mmHg, respectively. The critical survival pO
2
was
lower in PsIs than in primary islets, indicating greater hypoxia
resistance in PsIs (
P
<
0.001). PsIs are derived from
b
cell ma-
lignant tumor cell line, and malignant cells typically exhibit
more hypoxia resistance than the primary nonmalignant cells
(
7
,
8
). Interestingly,
Fig. 2
G
shows the negative correlation
between the critical survival pO
2
and the radius of spheroids
for both primary islets and PsIs [
r
¼
0.15 (
P
¼
0.010) for pri-
mary islets;
r
¼
0.33 (
P
¼
0.005) for PsIs]. A similar correla-
tion between the critical survival pO
2
and the volume of
spheroids (v
spheriod
) for both primary islets and PsIs is also
Figure 2.
ThecriticalsurvivalpO
2
within spheroids. The approach was applied to two types of pancreatic endocrine spheroids: primary pancreatic islets
and pseudoislets (PsIs) derived from the insulin-secreting cell line.
A
: representative live/dead images of primary islets. A primary islet in the preculture
(
top
) and postculture (
bottom
), with the extracted parameters demonstrated. Scale bar: 100
l
m.
B
: the calculation of the critical survival pO
2
, using live/
dead images (concentric geometry model,
top
), oxygen simulations (
middle
), and the pO
2
calculation (
bottom
). The data were retrieved from the speci
fi
c
spheroid shown in
Fig. 2
A
(postculture image). Sky-blue and magenta areas indicate the viable and dead cells, respectively.
C
:representativelive/dead
images of PsIs. A PsIs in the preculture (
top
) and postculture (
bottom
), with the extracted parameters demonstrated. Scale bar: 100
l
m.
D
: the calculation
of the critical survival pO
2
, using live/dead images (concentric geometry model,
top
), oxygen simulations (
middle
), and the pO
2
calculation (
bottom
). The
data were retrieved from the speci
fi
c spheroid shown in
Fig. 2
C
(postculture image).
E
: scatter plots showing the correlation between
r
spheroid
and
r
dead
in primary islets (
left
,
n
¼
262 spheroids) and in PsIs (
right
,
n
¼
107 spheroids).
F
: analysis of the overall viability of spheroids. Box plots demonstrate the
interquartile range, median, and the data range. Black diamond plots indicate the average.
P
¼
0.116 (Welch
’
s
t
test).
G
: scatter plots of individual sphe-
roids with the information of
r
spheroid
and critical survival pO
2
in primary islets (
left
) and in PsIs (
right
).
H
: analysis of the critical survival pO
2
of spheroids.
Box plots demonstrate the interquartile range, median, and the data range. Black diamond plots indicate the average.
P
<
0.001 (Welch
’
s
t
test). pO
2
,
partial oxygen pressure.
DETERMINING CRITICAL SURVIVAL pO
2
FOR ISLET SPHEROIDS
AJP-Cell Physiol
doi:10.1152/ajpcell.00024.2024
www.ajpcell.org
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demonstrated in Supplemental Fig. S3 [
r
¼
0.08 (
P
¼
0.174)
for primary islets;
r
¼
0.33 (
P
¼
0.005) for PsIs]. This may
suggest that larger spheroids could provide a more favorable
microenvironment at the individual cell level due to a more
interconnected organoid structure, despite becoming more
vulnerable to hypoxia at the whole spheroid level. Collectively,
our novel method not only calculated critical survival pO
2
val-
ues of different spheroid types but also elucidated physiologi-
cal characteristics of the cells and spheroids including the
differences in physiological hypoxia resistance of primary ver-
sus malignant cell spheroids.
TheCriticalSurvivalpO
2
Contributes to the Prediction of
the Islet Graft Viability in Various Oxygen Environment
As demonstrated, elucidating the hypoxia resistance with the
critical survival pO
2
values has signi
fi
cance in characterizing
the distinct cells. Another potential application using this
approach is predicting spheroid survival in various oxygen con-
ditions; this insight is particularly valuable in cell transplanta-
tions, including pancreatic islets. Since the hypoxia of the graft
site is one of the leading causes of reducing graft survival in islet
transplantations, several oxygenation strategies to improve the
transplanted islet graft have been developed (
16
,
18
,
44
–
46
).
The critical survival pO
2
values enabled us to accurately simu-
late graft viability under various oxygen conditions. With the
peri-spheroidal pO
2
de
fi
ned as the oxygen on the surface of the
spheroid (
Fig. 3
A
), we used simulations of the spheroid viability
(
Fig. 3
B
). The simulation data estimated the viability for pri-
mary islets and PsIs, according to the peri-spheroidal pO
2
and
spheroid size (
r
spheroid
). This approach provides critical informa-
tion for designing the oxygenation strategy. For instance, trans-
plant site environment at 5 mmHg (peri-spheroidal pO
2
)fora
typical-sized rat primary islet with a
r
spheroid
of 75
l
mcalculates
the estimated viability at 70% with the critical survival pO
2
value at 2.43 mmHg. Conversely, to achieve 100% viability for
the rat islet, a peri-spheroidal environment of pO
2
>
15 mmHg
is required.
DISCUSSION
In this study, we introduced an innovative method for
determining critical survival pO
2
within islet spheroids.
Integrating imaging techniques with computational simu-
lations of 3-D spheroids, we identi
fi
ed the pO
2
at live/dead
cell boundary with high spatial resolution to de
fi
ne the
critical survival pO
2
. Cells remain viable above this thresh-
old while they succumb to death below it. Utilizing this
model, we uncovered the oxygen sensitivity of pancreatic
islet spheroids during acute phases. Importantly, the val-
ues identi
fi
ed a difference in physiological characteristics
of critical survival pO
2
between primary islets and tumor-
derived islet spheroids, con
fi
rming higher hypoxia re-
sistance in tumor cells compared with primary cells.
Nonmalignant primary cells predominantly rely on oxi-
dative phosphorylation for energy production in the pres-
ence of oxygen; in contrast, tumor cells generally display
aerobic glycolysis for energy production, known as the
Warburg effect, contributing to their hypoxia resistance (
47
).
The critical survival pO
2
accurately re
fl
ects such physiologi-
cal processes, underlining the signi
fi
cance of our method in
the physiological characterization of cells within spheroids.
Our study demonstrated another potential application of
thecriticalsurvivalpO
2
value for improving cell transplanta-
tion outcomes. The hypoxic environment limits the success
of pancreatic islet transplantations due to their oxygen-dif-
fusion-limiting spheroidal structure. Correlations among
three critical factors in islet transplantations
—
namely, islet
spheroid size (
r
spheroid
), surrounding oxygen microenviron-
ment (peri-spheroidal pO
2
), and viability of the spheroids
—
can be determined when the critical survival pO
2
of the
A
Predicted viability (%)
%
Predicted viability (%)
%
r
spheroid
Peri-spheriodal
pO
2
Critical survival
pO
2
Predicting viability
BC
Primary islets
Pseudo-islets (PsIs)
Figure 3.
Prediction of the spheroid viability
based on the critical survival pO
2
values.
A
:
a schema demonstrating the concept. By
providing the three values, peri-spheroidal
pO
2
, radius of spheroid, and critical sur-
vival pO
2
de
fi
ned, the viability of the
spheroid can be estimated. Sky-blue
and magenta areas indicate the viable and
dead cells, respectively.
B
:thepredictedvi-
ability of primary islets.
C
:thepredicted
viability of pseudoislets (PsIs). pO
2
,par-
tial oxygen pressure.
DETERMINING CRITICAL SURVIVAL pO
2
FOR ISLET SPHEROIDS
C1268
AJP-Cell Physiol
doi:10.1152/ajpcell.00024.2024
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spheroids is de
fi
ned. Calculating the essential peri-trans-
plantation oxygen levels to achieve a desired graft survival
rate is a key aspect in developing cell transplantation strat-
egies. In addition to the simple examples in RESULTS, it is
particularly important when encapsulation techniques are
used to protect islet graft from host immunity (
48
–
51
).
Macro- and microencapsulation, coating islet spheroids with
hydrogels or microporous membranes, have shown promise
in allogeneic or xenogeneic islet transplantations. Although
effective with respect to immunoisolation, oxygen supply for
their survival should be carefully considered because the
additional layer of hydrogel could restrict oxygen diffusion
to the grafts. Understanding the critical survival pO
2
value of
the graft cells could provide the estimated graft viability
depending on the dimensions and properties of encapsula-
tion materials and devices. In scenarios of severe oxygen de-
privation, such as when a large number of islets are
encapsulated within a con
fi
ned space (
16
), designing the oxy-
genation strategies is especially important in which the criti-
cal survival pO
2
value will serve as a key element to estimate
the viability of transplanted cells under varying oxygen
conditions.
Although previous studies demonstrated methods to
determine the critical survival pO
2
value of the cells, critical
survival pO
2
values of various cell types and tissues have not
been well established. The spearheading work demonstrated
the critical survival pO
2
value of the rat-isolated hepatocyte
cells at 0.1 mmHg (
52
). A second study introduced technical
advancement by utilizing a
fi
ne-tuned, feedback-controlled
oxystat system, maintaining steady-state pO
2
between 0.01
mmHg and 150 mmHg in the culture setting (
53
)butrelied
on conventional trypan blue staining for single-cell viability.
ThecriticalsurvivalpO
2
value obtained from these studies
was applied to islet cells for the oxygen simulation models
(
29
); however, the approximation deviated from the actual
threshold of islet cells, as the values could be cell-type-spe-
ci
fi
c, as demonstrated by others (
54
), as well as our current
study. Advantages of the previous approach include the
straightforward methods applicable to any cell type.
However, the critical survival pO
2
value of the cell could
be only measured in single cells, which could be a crucial
limitation for several reasons: the critical survival pO
2
value is likely different in the single cell state versus actual
tissue environment with cell
–
cell interactions, and the
manipulation of the tissue dissociation into single cells
itself would damage cells to reduce viability (
52
). Our
method enables the calculation of the pO
2
within the cell
spheroids, which mimics the 3-D tissue environment.
Furthermore, our approach has the following advanta-
geous features: broad applicability across various cell
types using noncell-type-speci
fi
c viability assessment by
live/dead staining, high-throughput analytic capability for
large quantities of cells, and indirect measurement or the
maintenance of a low oxygen tension environment, which
eliminates the technical challenges of direct measurements
that are prone to drift and susceptible to inaccuracies.
Some limitations in our approach are as follows: First, it
does not provide cell-type-speci
fi
c critical survival pO
2
val-
ues, particularly when the spheroids are composed of multi-
ple cell types. For example, the primary islets consist of
predominantly insulin-secreting beta cells but contain
multiple endocrine cells and other cell types. Second, the
model operates under the assumption that hypoxia is the
primary factor in
fl
uencing cell survival in the short term
within hours
–
days (
13
,
52
). Multiple molecules, including
nutrients, create concentration gradients and contribute to
cell death in the longer observation period. Therefore, the
method may not be accurate in de
fi
ning critical survival pO
2
in chronic hypoxic conditions. Third, our method does not
de
fi
ne the oxygen threshold of cell function. The cell func-
tion may be reduced in the oxygen condition above the criti-
cal survival pO
2
; therefore, our approach requires other
methods, especially for functional analyses. Fourth, the bio-
logical variation and
fl
uctuations in the OCR of cells must be
carefully considered. For instance, our study utilized pri-
mary islets isolated from young male rats. It is well-docu-
mented that OCR and insulin-secreting functions vary by
sex and age, re
fl
ecting mitochondrial functionality (
36
). In
addition, the OCR is in
fl
uenced by the microenvironment,
such as glucose conditions; high glucose conditions have
been shown to increase cell metabolism including OCR (
36
,
55
). Given that OCR is a critical factor in oxygen simulations,
using accurate OCR values and accounting for these varia-
tions will contribute to more precise results of the critical
survival pO
2
. Finally, we identi
fi
ed a negative correlation
between the critical survival pO
2
and spheroid size, which
may require thorough interpretation. Our results suggest
novel physiological environmental differences between large
and small spheroids
—
the interconnected 3-D organoid
structure in large spheroids likely creates a favorable micro-
environment, despite the occurrence of hypoxia. However,
potential technical biases that could in
fl
uence this size-de-
pendency of the critical survival pO
2
should be carefully con-
sidered, although we did not detect such
fl
aws in our
methodology.
In summary, we have developed a new method to deter-
mine the critical survival pO
2
within 3-D cell spheroids,
offering a high-throughput noninvasive technique with high
spatial resolution data.
DATA AVAILABILITY
Data are available upon request.
SUPPLEMENTAL DATA
Supplemental Figs. S1
–
S3:
https://doi.org/10.6084/m9.
fi
gshare.
24986859
.
ACKNOWLEDGMENTS
The authors thank Drs. Colin Cook and Nicholas Scianmarello
for the insightful discussion. The authors also thank Dr. Sung Hee
Kil for critical reading and editing of the manuscript.
GRANTS
ThisworkwassupportedbyNoraEcclesTreadwellFoundation,
No Grant Number (to H. Komatsu); National Institutes of Health,
Grant Number: R03DK129958-01 (to H. Komatsu); and Juvenile
Diabetes Research Foundation, Grant Number: 3-SRA-2021-1073-
S-B (to H. Komatsu).
DETERMINING CRITICAL SURVIVAL pO
2
FOR ISLET SPHEROIDS
AJP-Cell Physiol
doi:10.1152/ajpcell.00024.2024
www.ajpcell.org
C1269
Downloaded from journals.physiology.org/journal/ajpcell at Caltech Library (131.215.225.183) on December 4, 2024.
DISCLOSURES
No con
fl
icts of interest,
fi
nancial or otherwise, are declared by
the authors.
AUTHOR CONTRIBUTIONS
K.-M.S., H. Kato., and H. Komatsu conceived and designed
research; K.-M.S., H. Kato, N.G, and H. Komatsu performed experi-
ments; K.-M.S., H. Kato, and H. Komatsu analyzed data; K.-M.S.,
H. Kato, and H. Komatsu interpreted results of experiments; K.-M.S., H.
Kato, and H. Komatsu prepared
fi
gures; K.-M.S. and H. Kato drafted
manuscript;K.-M.S.,H.Kato.,Y.-C.T.,andH.Komatsueditedandre-
vised manuscript; K.-M.S., H. Kato, F.K., Y.-C.T., and H. Komatsu
approved
fi
nal version of manuscript.
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