During this webinar sponsored by IonOptix, Michiel Helmes, PhD discusses recent advancements in instrumentation that address the shortfalls of low throughput EC coupling characterization. Specifically, Dr. Helmes explains the technology behind faster data acquisition and analysis, as well as improvements to the studies that offer more data acquisition fidelity, and automated data collection. He offers insights into best-practices for proper EC coupling measurement and highlight improvements to data handling, namely faster, automated data analysis. Background: Measuring and analyzing calcium and contractility in isolated cardiomyocytes offers important insights into cardiac function. However, traditional methods of obtaining EC coupling data are somewhat limited to lower throughput — for many applications, particularly drug discovery research, this presents a big challenge. Additionally, low throughput data acquisition and analysis may lack the statistical power necessary to fully resolve differences, or changes, in cardiac function. Isolated myocytes can behave heterogeneously, thus greater sample numbers are essential for accurate and reliable modeling of cardiac behavior.

1. Michiel Helmes, PhD presents new technology and
methodology for fast data acquisition and functional analysis
of cardiac myocytes, leading to better lab practices and data
interpretation.
High Throughput Investigation of
EC Coupling in Isolated Cardiac Myocytes
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2. MultiCell:
Towards a High-Throughput Calcium
& Contractility System
Department of Physiology
VU University Medical Center Amsterdam,
CytoCypher & IonOptix
Michiel Helmes, Ph.D

3. • Thank you for your interest
• What this webinar is it about, what it is not about
• Increasing throughput
• Standardizing Ca++/contractility experiments
Welcome

4. 1970s: first successful
isolation of calcium tolerant
intact myocytes.
For reference, see:
Brady, PHYSIOLOGICAL
REVIEWS Vol. 71, No. 2, 1991
Powell ‘76
The Story Behind CytoCypher

5. Technological Improvements (1980’s)
• Major improvements in isolation
techniques and experimental
equipment
• The first video based edge
detection system! Crescent
Electronics
• 1985: publication of cell-
permeable dyes, Fura, Indo and
Fluo, by the Tsien lab
Spectral characteristics of Fura,
from Grynkiewicz et al. 1985
The ‘Crescent box’, video based edge detection

6. The appearancy of fully integrated systems for
Ca++-Contractility measurements (1990’s)
Improvements of the commercial systems (Crescent, IonOptix, PTI) make calcium/contractility
systems available for more laboratories
Video based edge detection Real time sarcomere length measurements
(Gannier et al, ‘93 , Granzier and Irving, ‘95)

7. Pro
• It is a great assay to study whether drugs, disease or mutations have
an effect on excitation contraction coupling
Cons
• Quality of cell isolation has a strong effect on results
• Cell numbers: Throughput is too low to detect subtle differences, it is
too low to screen compounds
The technique is well-established and the
pros and cons emerge (2000’s)

8. Dose-response curves of cell shortening (A) and the Ca2+ transient amplitude (B) to increasing concentrations of
isoproterenol from 10−8 to 10−6 M. Salt-resistant (DR) (●,n = 11 cells) myocytes showed a progressive increase in
the percentage of cell shortening.
Kohzo Nagata et al. Am J Physiol
Heart Circ Physiol
2000;279:H2502-H2508
©2000 by American Physiological Society

9. Design requirement number one: no compromise on data quality
• High optical resolution (minimally 0.75 NA objectives)
• High temporal resolution (minimally 200 measurements per second for
contractility)
• Every cell has to be followed for a number of seconds to collect
multiple transients
Could we design a HT system?

10. How far can you get with these
design constraints?
Math:
• Measure 5 seconds per cell (pace at 2 Hz)
• 3 seconds to find the next cell (current systems require 2-5 minutes)
• 20 minutes (=1200 seconds) per well
• 1200 sec/8 sec per cell = 150 cells per well in stead of 10 (with the current state of the art)
• 4 hours of measurements: 12 x 150 = 1800 cells / day
So yes, theoretically it is possible

11. For a HT system with serial measurements
we need speed…
✓ Hardware; rapid movement
✓ Software; high speed image processing
✓ Analysis; this has to be fully automatic

12. Setting up a new
company to take on
this challenge
CytoCypher BV,
Amsterdam,
The Netherlands
In close collaboration
with IonOptix and
VU University Medical Center

13. Initial Challenge: Microscope Speed
• If you cannot move the dish fast
enough, you have to move the
microscope
• It is possible to move the microscope
objective instead of the cells, using
infinity corrected optics
How to quickly get to
the next cell?

14. Moving the microscope objective by 50mm has no
effect on the magnification
Building a first concept microscope
Proof Of Principle:
Can You Move The Objective Without Changing The Image?

15. The Microscope

16. The Microscope
✓ Temperature controlled
✓ Light tight
✓ C-mount adapter for camera
attachment
✓ Epi-fluorescent port
click here to learn more >>

17. Navigating The Microscope Field

18. Manual Cell Selection

19. Automated Cell Selection

20. Data Acquisition

21. • Easy overview
• Manual selection of cells, mouse or keyboard shortcuts
• Automated cell finding
• One time or repeated measurements of the cells
• High definition measurements of Ca++/contractility
Summary

22. How Much Can We Do Now?
Last week’s cell isolation:
• 10:00 am – 12:00 pm:
Collect contractility data from 227 cells
• 12:05 pm – 12:06 pm: analyse data for all cells
(1 minute 45 seconds)
• 12:06 pm – 12:30 pm: making graphs
• 12.30 pm: hand system over to next user
• 8:00 am – 12:00 pm: Cell isolation
• 12:00 pm – 2:00 pm: cell plating and adhering
• 3:00 pm – 3:45 pm:
Collect contractility from 182 cells
• 4:00 pm onwards: hand system over to
next user
Day 1 Day 2

23. Frequency distribution %shortening the day after isolation (n=227)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
0
10
20
30
40
Fractional shortening sarcomere length (%)
NumberofCells
Frequency distribution %shortening on day of isolation (n=182)
2
3
4
5
6
7
8
9
10
11
12
13
14
0
10
20
30
40
Fractional shortening sarcomere length (%)
NumberofCells
Frequency distribution %shortening
0 5 10 15 20
0
10
20
30
40
Day 1 (n=182)
Day 2 (n=227)
NumberofCells
Fractional shortening sarcomere length (%)
DataAnalysis
Relation end-diastolic sarcomere length and %shortening
on day of isolation
1.4 1.6 1.8 2.0 2.2
0
5
10
15
BL SL (um)
Fractionalshorteningsarcomerelength(%)
Relation
1.
0
5
10
15
20
Fractionalshorteningsarcomerelength(%)
Frequency distribution %shortening
0 5 10 15 20
0
10
20
30
40
Day 1 (n=182)
Day 2 (n=227)
NumberofCells
Fractional shortening sarcomere length (%)

24. Need For Better (faster) Analysis Tools
• Using the concepts of
IonWizard, improving
on its weaknesses
• Loading batches
of files
• Automatic rejection
criteria
• One click export of all
data to Excel

25. DataAnalysis
• Cloud based or stand-alone
• Beta-testing? cytosolver.cytocypher.com
(mail us at info@cytocypher.com )

26. Data Analysis

27. New Feature: Arrhythmia Detection
• Training tool for
machine learning
• Some parties
want to exclude
arrhythmic
contractions,
some want to
score them

28. Dose-response curves of cell shortening (A) and the Ca2+ transient amplitude (B) to increasing concentrations of
isoproterenol from 10−8 to 10−6 M. Salt-resistant (DR) (●,n = 11 cells) myocytes showed a progressive increase in
the percentage of cell shortening.
Kohzo Nagata et al. Am J Physiol
Heart Circ Physiol
2000;279:H2502-H2508
©2000 by American Physiological Society

29. C
ontrolISO
2.5
nM
ISO
5
nMISO
7.5
nMISO
10
nMISO
15
nM
0
5
10
15
20
Fractionalshortening(%)
Dose Response Curve For Isoproterenol, Revisited
• Data from 1 day
• Responders and non- responders

30. • A creatine kinase inhibitor was added at t=0
Repeated Measures For Multiple Cells In One Experiment
• All but one cell had died by t=31 min

31. Conclusions
• We can do 800 cells a day now (4 hours of measurements)
• In automatic mode, no user intervention, 6 seconds between cells
(80% good measurements)
• Ca++/contractility with no compromise on data quality
• >95% reduction in time needed for data analysis
• New ways to look at data; distribution of parameters in a population

32. Next…
• Pipelining
experiments:
pacing and
perfusion of
individual wells in
multi-well dishes
• Automated
perfusion using
HPLC pumps

33. Where To Go From Here?
• Increase content:
FRET, immuno staining, single cell sequencing, voltage sensitive dyes
• Further increase in throughput
• Cloud platform: opens the road for a cardiac myocyte data repository
• data accessibility
• data for modelers
• better use of animals
• network effects? Exciting times ahead!

34. VU Medical Center:
• Dr. Diedrik Kuster
• Prof. Jolanda van der Velden,
• Max Goebbel
• Cord Brock
• Ruud van der Stappen
IonOptix:
• Tom Udale
• Leo Margaritov
• Sander de Wit
Acknowledgements

35. Thank You
For additional information on the products and applications presented during
this webinar please visit www.ionoptix.com and www.cytocypher.com
Continue the
discussion at
AHA Scientific
Sessions
BOOTH
2229Department of Physiology
VU University Medical Center Amsterdam,
CytoCypher & IonOptix
michiel@cytocypher.com
Michiel Helmes, Ph.D
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