Measuring Work in Single Isolated Cardiomyocytes:Replicating the Cardiac Cycle

Andy HentonInsideScientific

Sponsored by:

Michiel Helmes, PhDVUMC &IonOptix

InsideScientific is an online educational environment designed for life science researchers. Our goal is to aid in

the sharing and distribution of scientific information regarding innovative technologies, protocols, research tools

and laboratory services.

Measuring Work in Single Isolated Cardiomyocytes: Replicating the Cardiac Cycle

Michiel Helmes PhD

Department of PhysiologyVU University Medical Center

Amsterdam& IonOptix

Copyright 2015 IonOptix & InsideScientific. All Rights Reserved.

IonOptix MyoStretcher

Attach, Stretch, and Record Force in Isolated Cardiac Myocytes

Create “Work-Loops” and measure power output

Use the MyoStretcher to Investigate:

– Accurate diastolic calcium

– Auxotonic and isometric contractions

– Length-dependent activation

– Force-velocity relationship

Thank you to our event sponsor

This webinar IS NOT about PV-loops!

• What we will be discussing is how to measure mechanical work in singleintact cardiomyocytes, and how a simple model of the cardiac cycle can be created

• The resulting “work-loops” are analogous to PV-loops in that they provide information about the contractile properties of the myocyte, and by extension, heart function

What we will cover today:

• History, recent developments, and a review of experimental results for isolated cardiomyocyte “work-loops” to date

• The Technique: what we CAN do and CANNOT do at the bench-top

• Why “work-loops” are valuable and why we should do them

Before we get started:

Where did the journey start?

• Le Guennec et al, ‘90

• Force measurements on isolated intact myocytes

• Carbon fibers, really low force levels

Where did the journey start?

• Le Guennec et al, ‘90

• Force measurements on isolated intact myocytes

• Carbon fibers, really low force levels

• Yasuda in ‘01, and Nishimura in ’04

• Bending of carbon fibers to measureforce

• This is a first attempt at force control

The journey continues...

Nishimura, S. et al. AJP - Heart and Circulatory Physiology 2004 Vol. 287 no. 1, H196-H202

• In 2006, Iribe et. al use carbon fibers with feed forward control

• It works, but is slow

• Equally important, forces are still too low

The journey continues... Le Guennec → Ed White → Peter Kohl

• Work-loops of a single myocyte, constructed using feed-forward control of force

• Feed-forward vs feed-back

The journey continues... Le Guennec → Ed White → Peter Kohl

A B

• Feed-back instead of feed-forward would have been ideal, but couldn’t be done

• The end of the road for carbon fibers and feed-forward force control?

• It did set up a collaboration with the Lederer lab in Baltimore though

The first set of challenges…

Reinvigorated interest with MyoTak

• MyoTak Glue is introduced as a cell adhesive (Prosser et al., Science 2011)

• Mimics physiological cell attachment to extracellular matrix and is bio-compatible

• In parallel, IonOptix upgrades the MyoStretcher system

to force transducer

to length controller

cardiomyocyte

MyoTak coated micro-rods

JY Le Guennec → Ed White → Peter Kohl → Gentaro Iribe → Jon Lederer, Chris Ward and Ben Prosser

Basic Layout of The MyoStretcher

3D micromanipulator

optical rail, microscope mount

arms to reach experimental chamber

• on pressure lead

We wanted force control/force clamps, but…

• Force measurements using fiber bending are not suitable for feed-back; data rate is too slow

• Classic muscle physiology force transducers? Problems with sensitivity and stability in this force range

• We had to come up with something better -> develop our own force transducer

Fiber bending

Force transducer

cantilever

attachmentneedle

read out fiber

• Optical

• Fully submersible

• nN sensitivity

• High resonance frequency (8kHz)

• Stable baseline

IonOptix OptiForce, Revolutionary New Class of Force Transducer

Front view

Raw data from a rat myocyte undergoing a stretch and subsequent release while being paced at 2 Hz

This force transcuer is suitable for developing a force control system at the nN level

Optical force transducer that bridges the gap between AFM & regular force transducers

Cell Chamber View

Force ProbePiezo Motor

System on a Microscope

1. MyoTak -- to attach the cells

2. Mechanics -- to pick up and stretch the myocyte

3. Force transducer -- to get an accurate, stable and reliable force signal

4. Hardware and software -- so the force transducer and piezo can interact (you can only control force by modulating myocyte length) – ex. LabView

5. Algorithm – sequence that more or less mimics the cardiac cycle that can be executed via #4

What you need to do force control and generate work loops

The cardiac cycle

Aorta

Left Atrium

Mitral Valve

Aortic Valve

Left Ventricle

(cardiac cycle animations courtesy of Dr. Gentaro Iribe)

• Schematic of cardiac cycle and construction of PV-loop

100

10

10

LVV (or cell length)

LVP

(o

r fo

rce)

End-diastole

(LVP is ‘left ventricular pressure’, LVV is ‘left ventricular volume’)

100

10

10~100

LVV (or cell length)

LVP

(o

r fo

rce)

Isovolumic Contraction

100

10

100 ~

LVV (or cell length)

LVP

(o

r fo

rce)

End-systole

Ejection Phase

100

10

100~10

LVV (or cell length)

LVP

(o

r fo

rce)

Isovolumic Relaxation

100

10

~10

LVV (or cell length)

LVP

(o

r fo

rce)

Pressure-Volume Loop

Work (J) = Δ P*ΔV

Modulating Force Development By Changing Cell Length

length

forc

e

(I)

(II)

(III)

(IV)

(I)Start contraction, Pre-load > force < afterloadDo nothing

force > afterloadShorten the cell

End of active contractionPre-load > force < afterloadDo nothing

DiastoleForce < pre-loadStretch the cell

(IV)

(II)

(III)

First algorithm used to create work loops:

motor

force

After load

Pre load

d ba c d

Len

gth

ch

ange

(μ

m)

Forc

e (µ

N)

* Mouse myocyte, room temperature

d

b

ac

afterload

preload

Forc

e (u

N)

Length change

First work-loops with feed-back based force control

1. MyoTak -- to attach the cells

2. Lighter mechanics & faster piezo –to pick up and stretch the myocyte with precision and speed

3. Force transducer -- to get an accurate, stable and reliable force signal

4. Hardware and software – upgraded to an FPGA (a programmable, embedded chip designed for real time control) to increase the frequency with which we can run the control algorithm

5. Algorithm – sequence that BETTER mimics the cardiac cycle that can be executed via #4

What you need to do force control and generate work-loops well

Afterload

Preload

Forc

e (

μN

) Isometric contraction

With force clamp

Time (s)

Len

gth

(μ

m)

length

forc

e

(I)

(II)

(III)

(IV)

Afterload

Preload

• Force clamps

• Improved end-systolic switch

• Pacing mark initiates new loop

• Improved speed of algorithm and motor

length

forc

e

(I)

(II)

(III)

(IV)

Afterload

Preload

• Control is good at RT

• Square loops

• No correction for arterial resistance

motor

Afterload

Preload

Mechanical work = Force x length = area in loop, ‘work-loop’

Forc

e (

μN

)

Length (μm)

Force vs length

3 0 4 0 5 0 6 0

1

2

3

4

5

L e n g th ( m )

Fo

rc

e (

N)

2 .0 2 .5 3 .0 3 .5 4 .0

0

5

1 0

1 5

A fte r-L o a d ( N )

Wo

rk

(p

J)

Varying afterload at a fixed preload

Mechanical work as a function of afterload (rat myocyte, RT)

It worked, but better controls were needed for repeatable experiments

1. MyoTak -- to attach the cells

2. Lighter mechanics & faster piezo –to pick up and stretch the myocyte with precision and speed

3. Force transducer -- to get an accurate, stable and reliable force signal

4. Hardware and software – upgraded to an FPGA (a programmable, embedded chip designed for real time control) to increase the frequency with which we can run the control algorithm

5. Algorithm – sequence that BETTER mimics the cardiac cycle that can be executed via #4

6. Control -- the ability to automatically set pre- and afterload levels based on actual force transient

7. Programming -- Implementation of signal generators in software so changes in pre- and afterload can be programmed

8. Temperature control!

The final (?) additions to a complete solution…

Improving the experiment…

Force

Length

Typical protocol:

Pre-load

After-load

(rat cardiac myocytes, 37°C, paced at 2 Hz)

• Automated selection of pre- and afterload based on force trace

• Pre-defined changes in pre- and afterloadusing signal generators

-> Necessary tools to explore the parameter space of preload, afterload and pacing frequency or to do repeated measurements

Recording @ 2 Hz

Recording @, 4 Hz

Recording @ 8 Hz

SL = 1.98 µm 2.03 µm2.02 µm

Forc

e Length

Varying pre- and afterloadFo

rce

Len

gth

End Diastolic and End Systolic force length relation

• Measurements on intact loaded myocytes have come a long way

• The development of a revolutionary new force transducer allows feed-back based force control on the myocyte level

• We have used it to develop a system that can now reproducibly measure work-loops in myocytes

• The work-loop algorithm mimics the the cardiac cycle (in a simplistic way)

• We can vary the preload, afterload at will

Summary so far...

• Work-loop ≠ PV-loop; more sophisticated algorithms neededThe infrastructure is in place

• Force measurements need to be transformed into stressMeasuring cross sectional area reliably is difficult on a standard microscope

• Compliance in the attachment of the celllimits the usefulness of the End Diastolic and End Systolic Force Length relation

• Do we cover the physiological sarcomere length range?With the current attachment strength we can measure work-loops up to 2.1 µm SL

Remaining Challenges...

Improved attachment with the IonOptix cell holders

Slide courtesy of Ben Prosser, U. of Pennsylvania

images courtesy of Ben Prosser, U. of Pennsylvania

Images courtesy of Ben Prosser, U. of Pennsylvania

• Laser etched cell holder

• Cavity is formed to accomodatemyocyte

• Currently 30 micron opening, 10 micron depth, can be adjusted

• Increases the attachment surface for the myocyte

• Much stronger connection, less compliance

Improved attachment with the IonOptix cell holders

1. Because it was a cool thing to do?

2. Myocytes are more accessible than muscle strips

• Ease of use

• No extra-cellular matrix. Pro or con?

• Ease of access for imaging and perfusion; you can ask very detailedscientific questions

3. work-loops are very useful in detecting changes in diastolic properties

Why do “work-loops” on single cells?

Post-rest potentiation, constant length

8 Hz

Post-rest potentiation has a diastolic and systolic component

• At constant length, the systoliccomponent (increased calcium release) dominates the change in signal

• The change in diastolic force (lower calcium level throughprolonged re-uptake) is relatively small

force

sarc len

length

4 Hz

Post-rest potentiation, work loops

Post-rest potentiation has a diastolic and systolic component

force

sarc len

length

1 Hz8 Hz• With force clamps diastolic,

systolic, and force are kept constant (except for an increased force overshoot due to imperfect control)

• Length, instead of force, is the dependent variable and big changes in both diastole andsystole can now be observed

Change in work-loops when switching from 8Hz to 1 Hz

rat myocyte, 37˚C

How do work-loops amplify changes in diastole?

• Linear end systolic and end diastolic force length relation

• Changes in calcium affect the diastolic and systolic phaseequally

• BDM inhibits cross bridge formation, ESFL goes down

• But also improves relaxation, so EDFL will go down as well

• The diastolic effect outweighs the systolic effect

Effect of low levels of BDM on diastolic dysfunction

(mouse, data at room temperature)Length change

Forc

e (

μN

)

after-load

pre-load

No BDM 5 mM BDM

The effect on length when force is constant

Switch to 5 mM BDM

Forc

e (μ

N)

Sarc

Len

(μm

)Le

ngt

h c

han

ge (

μm

)Time (s)

• Myocoyte with Ca++

overload

• BDM reduces the stiffness of the cell in diastole

• The myocyte is pulled at with the same force

• The cell will stretch further

Length control:Decreased performance

Force control:Improved performance

A different perspective

• BDM depresses both the ESFL and EDFL

• Length dependent activation beats cross bridge inhibition

control+ 5mM BDM

Why do “work-loops”? continued…

• The external work done by a myocyte encompasses changes in both systolic and diastolic forces but also takes length dependent activation into account

• Therefore, this also makes it a particularly sensitive assay for drug testing

How to maximize the measurable effect of a drug treatment

Effect of 100nM Isoproterenol

• Work-loop measurements can show both the systolic and diastolic effects of beta-adrenergic stimulation

• The effect of 100nM Iso is 2-4 fold increase in work per loop

• How did we construct this figure?

Determining the work maximum for each preload

0

2

4

6

8

0 2 4 60

10

20

30

40

50

60

0 5 10

Wo

rk (

pJ)

Pow

er (

pW

)

After-load (μN) Pacing frequency (Hz)

Physiological heart ratesa) b) c)

Isometric (w = 0)

Isotonic (w=0)

Forc

e

Length

W=ΔF.Δl Finding the afterload that delivers maximum external work…

3 0 4 0 5 0 6 0

1

2

3

4

5

L e n g th ( m )

Fo

rc

e (

N)

2 .0 2 .5 3 .0 3 .5 4 .0

0

5

1 0

1 5

A fte r-L o a d ( N )

Wo

rk

(p

J)

• 100nM Iso increases work/loop 2-4 fold (n = 10)

• Compared to a 50-75% increase in isometric force (trabeculae at 37˚C)

• Improved signal/noise, increased statistical power

Maximizing the effect of a drug

Work-loop measurements lend themselves well...

• To establish the maximum amount of work a cell can produce

• Detect changes in the work produced with changes in inotropy

• Highlight changes in diastolic function or dysfunction

• Finding drug effects by encompassing both systolic and diastolic effects

What is next...

• Further methodological improvements, mostly reducing end-compliance –Cell holders seem to be the solution

• Further research: Calcium sensitizers and de-sensitizers in disease models? The Anrep effect?

Summary and conclusion

I’d like to thank:

• Aref Najafi – who did most of the actual experiments

• Prof. Jolanda van der Velden – in whose group at the VUmc(Amsterdam) this work took place

• Tom Udale at IonOptix – software and system design, cell holder design

• Alex Nijmeijer – a world class FPGA programmer

--- And the many others who contributed

Acknowledgements

Michiel Helmes, PhDmichiel@ionoptix.com

Thank You!For additional information on solutions for high speed quantitative fluorescence, muscle mechanics, and tissue engineering -- in particular the MyoStretcher System for generating “work-loops” in isolated intact myocytes –please visit:

www.ionoptix.com

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Our goal is to aid in the sharing and distribution of scientific information regarding innovative technologies,

protocols, research tools and laboratory services.