Case study

In vitro diabetic cardiomyopathy model
to evaluate ischemic sensitivity

Tools:
CardioExcyte 96

Dr. Yuanzhao (Nick) Cao,featured by Nanion Technologies
Dr. Yuanzhao (Nick) Cao, Universityof Queensland. His work focuses on
cardiovascular development, stem cell-based
disease modeling and pharmaceutical drug
discovery. Specifically, he concentrates
on ischemic heart injury and diabetic
cardiomyopathy in preclinical cell and animal

were investigated. Compared to control MM conditions, bothcG and vG cardiomyocytes showed greater lipotoxicity andcell stress characterized by increased intracellular uptakeof lipid (Oil red O staining, ORO), as well as an increased
expression of the heart failure bio-marker, brain natriuretic
peptide (BNP). However, there was no significant difference inphenotypes between the two disease models.

models, aiming to develop new drugs toreduce hospitalizations and community health

Next, in vitro DCM models were investigated underburdens.

physiological conditions, by analyzing cell contractility
using the CardioExcyte 96. This platform allows recording ofIndividuals with diabetes have a higher risk of developing
ischemic heart disease, making it the leading cause ofmortality among diabetics 1. Limited preclinical models for comorbidity of diabetes and ischemia are currently available toaddress this significant clinical concern.
Dr. Nick Cao from the University of Queensland aims todevelop in vitro co-morbidity models to study ischemic
sensitivity in preclinical models of diabetes. The researcher
explains: “Individuals living with diabetes have frequent andhigher magnitude glucose spikes. We therefore evaluatedvariable (vG) vs. constant (cG) glycemia in models of diabeticstress. This novel two-step diabetic cardiomyopathy (DCM)
model mimics the postprandial glucose spikes measured
using a monitor in patients to assess blood glucose changes
throughout the day.”In the study shown here, human induced pluripotent stem cellderived cardiomyocytes (hiPSC-CMs) were exposed to control
maturation media (MM) vs diabetic conditions. Constantglucose stress (cG) vs cyclic episodes of high and low glucose(vG), which mimic the glycemic stress of diabetic patients,

Nanion's CardioExcyte 96 platform
The CardioExcyte 96 is a compact, automated,hybrid technology, combining several functional
readouts under physiological conditions. Recordingfrom 96 wells at a time, CardioExcyte 96 captures
both contractility and electrophysiology, withadditional insight into cell viability.

contractility and electrophysiology of cardiac cells 2,3. DCM
cells show impaired contractile performance; displaying
decreased amplitude, beat rate, and compromised velocity.
Interestingly, vG heart cells had greater defects in contractions
compared to cG conditions, reflecting a key distinction
between the two groups on the basis of cardiac physiology.
In contrast, RNA-seq data demonstrate that while MM anddiabetic models have significant differences, cG and vG

“The CardioExcyte has played a pivotal role in advancing ourcomprehension of cardiac physiology and has become an
indispensable tool in our research endeavors.”Nathan J. Palpant, Prof. Dr., University of Queensland

cells have similar gene expression changes. These include

shown in Figure 1 C. Key transcriptional hallmarks of the DCM

alterations in insulin resistance, fatty acid oxidation (FAO),

model include insulin resistance, metabolic reprogrammingglucose oxidation, and signaling pathways associated withand altered functionality.

DCM.
Investigation of possible phenotypic changes revealed
Figure 1 gives an overview of the in vitro DCM model toimpaired contractile performance of the diabetic

evaluate ischemic sensitivity. By exposing healthy hiPSC-CMs

cardiomyocytes (i, ii), indicated by decreased contractile

to increased glucose and neurohormonal mediators, novel

amplitude, beat rate, and compromised velocity (Figure 2).

glycemic variability (vG) and constant glucose models (cG)were developed (Figure 1 A). The disease models were further“The CardioExcyte system has played a pivotal role inused to study exposure to ischemic stress using in vitro IRI

advancing our comprehension of cardiac physiology and hasmodeling. As shown in Figure 1 B, diabetic cardiomyocytes (cGbecome an indispensable tool in our research endeavors.”

and vG) displayed increased lipotoxicity (i-ii) characterized by

was one insight from the team at the University of Queensland.

increased intracellular uptake of lipids and enhanced releaseof the DCM stress marker BNP (ii). Differential gene expression

Nick Cao continues: “Its ability to offer real-time, label-freeclassified in clusters among MM, cG and vG conditions ismeasurements of contractility provides unparalleled insights

FIG2 In vitro DCM modelA

Step 1. In vitro cardiac iPSC differentiation
Pluripotent
stem cells

DAY 0CHIR-99021
XAV-939
B27 + ins
AA + BSA
RPMI-1640

B

12i

Cardiogenic
mesoderm

345

Step 2. In vitro diabetic cardiomyopathy protocol
D15 CMs Maturation[MM]replating

Cardiomyocytes

67MM131415cG

DAY − 1
FAs + ins (MM)MM+ constant glucose
MM+ variable glucose
ET-1Cortisol
HypoxiavGii0122040–1–2012MMMM
MM
cG
cG
cG
vG
vG
vG

0MM
cG
vG

101520 25

nsGlucose oxidation

Functionality

MMMM
MM
cG
cG
cG
vG
vG
vG

MM
MM
MM
cG
cG
cG
vG
vG
vG

Figure 1. DCM model to evaluate ischemic sensitivity induced by variable vs. constant glycemic
stress. A Step 1, Schematic protocol for small-molecule-directed differentiation from pluripotency
into the cardiac lineage (Step 2). Exposing MM-cultured CM to increased glucose andneurohormonal mediators. B Diabetic cardiomyocytes (cG and vG) show increased lipotoxicity (i-ii)
characterized by increased intracellular uptake of lipids and enhanced release of the DCM stressmarker BNP (ii). Scale Bar=30 µm, n=3. C (i) Differential gene expression classified in clusters amongMM, cG and vG conditions, (ii). Key transcriptional hallmarks of the DCM model include insulin
resistance, metabolic reprogramming and altered functionality, n=3.

5

COTN X6ATMNI1 2M ODYRY H6 1
TR R2P
A C3T
A P2A
TP 12A2*MMMMMMvG
cG
cGvG
cGvGcluster
1 2

FA oxidation

BNP secretion

80PFC KLKG MT
6 2PY PD
G GL
Y
LD S1
SL HACSL 2A
CSL 2A3
C 22A
1−1

Insulin resistance

HAD DH
G B
PP AT
2A AR
C A
A AT
C 1
PP AD
A AR SBT GA P5F C1
C 1
C AC A A
PT B
1B0−2

SLC
SR 2A
IR EBP 4
S 1CINS
A R
K
PI T1K3CA

17****ii6**nsvG

25BNP (ng/mL)60*cGk=24% red area
MMi

3

IschemiaReperfusion
injuryLipid accumulation
0C

Diabetes
[cG]
[vG]

MMMM
MMcG
cG
cG
vG
vG
vG

into cardiac dynamics. Our work with the CardioExcyte 96

Based on our experiences, I wholeheartedly recommendsystem has spanned various areas, including hiPSC-CMs

the CardioExcyte and FLEXcyte systems to any scientist or

development and physiology, heart disease modeling, andinstitution seeking to explore cardiac contractility with precision

investigating the effects of human COVID plasma on heart celland efficiency. These systems have undoubtedly enhancedcontractility. Additionally, we have utilized the system to study

the depth and accuracy of our research, contributing

impedance-based cardiac cell death induced by receptor

significantly to answering our scientific questions.”

and ion channel modulators, as well as for physiologicalvalidation of stem cell differentiation-modulated heart cells.

In summary, we show that a diabetic cardiomyopathy in vitro
disease model was successfully validated, and functionallyFurthermore, in our exploration of the FLEXcyte 96 system, wecharacterized, with the impedance-based CardioExcyte 96

have discovered several key capabilities and applications. For

contractility assay.

instance, we aim to utilize it in drug candidate discovery andpharmacological research to assess the effects of compounds

Specifically, as glycemia variability of DCM is susceptible toon contractility, particularly for cardiac protection. The

contractile impairment, IRI-induced cell death, and metabolic

system has helped us to evaluate the cardiotoxic effects ofshift, these findings could be fundamental to establish further

our pharmaceutical inhibitors within an in vivo-mimicking

phenotypic drug screenings for DCM using iPSC-CMs, including

environment. Additionally, it has great potential in facilitating

myocardial ischemia.

mechanistic studies aimed at understanding the cellular andmolecular mechanisms underlying contractility regulation bynovel proteins/receptors.

iMM

ii

cG

vG

Amplitude (Ohm)

01

2

3

4

Beat Rate (BPM)

50MM

Upstroke Velocity (Ohm/s)
01020cG
vG

20

Relaxation Velocity (Ohm/s)− 20 −15 −10*vG

0**cG−5*MM**vG

ns**cGMM30MM

15****vG

10*******

cG

5Figure 2. Nick Cao and Nathan Palpant perform measurements on the CardioExcyte 96 at University ofQueensland. The system is routinely used in the lab to investigate diabetes and ischemia models. Diabetic
cardiomyocytes have impaired contractile performance shown in raw data traces (i) and bar graphs (ii),displaying decreased contractile amplitude, beat rate, and compromised velocity, each with 3 replicates.

“I wholeheartedly recommend the CardioExcyte 96 andFLEXcyte 96 to any scientist seeking to explore cardiac contractility
with precision and efficiency. These systems have undoubtedly
enhanced the depth and accuracy of our research, contributing
significantly to answering our scientific questions.”
Dr. Yuanzhao (Nick) Cao, The University of Queensland

Contact Information

References

Yuanzhao (Nick) Cao

1.

Fan Wenjun. Epidemiology in diabetes mellitus and cardiovascular

Postdoctoral Research Fellow

disease. Cardiovasc Endocrinol. 2017 Feb 15;6(1):8-16. doi: 10.1097/

Institute for Molecular Bioscience (IMB)

XCE.0000000000000116. PMID: 31646113; PMCID: PMC6768526.

The University of QueenslandBrisbane, QLD 4072, Australia

2.

Niels Fertig & Clemens Möller (2015) Novel screening techniques for ion channel
targeting drugs, Channels, 9:6, 367-375, DOI: 10.1080/19336950.2015.1079675

Nathan J. Palpant
Associate Professor

Alison Obergrussberger, Sonja Stölzle-Feix, Nadine Becker, Andrea Brüggemann,

3.

Corina T. Bot, Krisztina Juhasz, Fabian Haeusermann, Liudmila Polonchuk,Institute for Molecular Bioscience (IMB)

Martin Traebert, Sonja Stoelzle-Feix, Cross - site comparison of excitation-The University of Queensland

contraction coupling using impedance and field potential recordings in hiPSC

Brisbane, QLD 4072, Australia

cardiomyocytes, Journal of Pharmacological and Toxicological Methods,
Volume 93, 2018, Pages 46-58, ISSN 1056-8719, https://doi.org/10.1016/j.
vascn.2018.06.006.

Acknowledgments
We thank Nick and Nathan for valuable insights and awonderful collaboration.

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