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First published online March 2, 2006
Journal of Experimental Biology 209, 1093-1100 (2006)
Published by The Company of Biologists 2006
doi: 10.1242/jeb.02117
Development of the sympatho-vagal balance in the cardiovascular system in zebrafish (Danio rerio) characterized by power spectrum and classical signal analysis
Institute of Zoology and Limnology and Centre for Molecular Biosciences, University of Innsbruck, Innsbruck, Austria
* Author for correspondence (e-mail: thorsten.schwerte{at}uibk.ac.at)
Accepted 23 January 2006
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Summary |
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Key words: cardiovascular system, adrenaline, acetylcholine, sympatho-vagal balance, heart rate variability, zebrafish, Danio rerio
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Introduction |
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).
In some zebrafish heart mutants, at least during the first 10 days of
development, a sufficient oxygen supply is obtained simply by diffusion of
oxygen through the skin, and therefore no beating heart is needed
(Chen et al., 1997; own
observations). Accordingly, cardiac activity is not yet coupled to the
metabolic demand of tissues at this stage. This was also supported by the
observation that disruption of the haemoglobin in early stage zebrafish
(3–12 d.p.f.) has no significant effect on metabolism or on cardiac
performance (Pelster and Burggren,
1996; Jacob et al.,
2002; Schwerte et al.,
2003). This prompts questions about when during development do
cardiovascular control systems appear and which types (intrinsic, neuronal and
humoral) of control are involved during different stages of development.
The use of non-invasive optical methods, like digital motion analysis,
developed in our lab (Schwerte and
Pelster, 2000; Schwerte and
Fritsche, 2003), to analyze the heart appears especially promising
to address the question of cardiovascular control in early larval stages. In
previous studies we used these techniques to investigate cardiovascular and
respiratory responsiveness of developing fish to different environmental
conditions (Schönweger et al.,
2000; Jacob et al.,
2002; Schwerte et al.,
2003; Turesson et al., in
press). The results of these studies indicated that in zebrafish
receptors sensing hypoxic conditions are already present in very early stages
(3 days post fertilization; d.p.f.). Vascular reactivity to nitric oxide was
shown in 5 d.p.f. animals (Fritsche et al.,
2000).
Whereas these studies recorded changes in heart rate over time in response
to the treatment, over the last two decades several studies have shown that
there are fluctuations in the instantaneous heart rate on a beat-to-beat
basis. Changes in heart rate on a beat-to-beat basis are called the heart rate
variability signal (HRVS). This signal may include information about autonomic
(neuronal or intrinsic) mechanisms controlling cardiac activity, especially if
a power spectral analysis is performed, which allows the dissection of the
oscillatory components hidden behind the heart rate variability signal
(Altimiras, 1999). In contrast
to the large number of studies analyzing heart rate variability (HRV) in adult
mammals there is little data available about non-mammalians. Altimiras et al.
(Altimiras et al., 1995) and
Campbell et al. (Campbell et al.,
2004) demonstrated the physiological significance of short-term
heart rate modulation for adult teleost fishes, but to our knowledge nothing
is known about HRV in fishes during early development. In adult animals the
complexity of HRV is mainly based on the autonomic innervation of the
sinoatrial node. Vagotomy, for example, significantly reduces HRV
(Campbell et al., 2004).
However, during embryonic and early larval development the autonomic control
system might not yet be functional (Protas
and Leontieva, 1992; Jacobsson
and Fritsche, 1999; Pelster
and Schwerte, 1999).
Accordingly, HRV initially might have a completely different background, and the adult pattern might become visible only after the vago-sympathetic control system is established. We hypothesize that changes in HRV will reflect the onset of cardiovascular regulation by the autonomic nervous system. The analysis of HRV in small larvae and juveniles of zebrafish is a difficult task. Classical methods such as electrocardiogram or pressure measurements are too invasive and would produce too many artefacts. In the present study we therefore developed a non-invasive method to assess variations in heart rate. We characterized changes in HRV during development in comparison to the onset of adrenergic and cholinergic cardiovascular regulation. To evaluate the method and to show that measured changes in HRV are connected to the autonomic nervous system we used classical pharmacological methods to inhibit autonomic nerve function. We hypothesized that nervous-system-borne HRV will disappear after blocking the autonomous nerve system.
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Materials and methods |
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Animal experiments were performed according to animal ethics permission GZ 66.008/4-BrGT/2004 of the Austrian Bundesministerium für Bildung, Wissenschaft und Kultur.
The imaging system
An inverted microscope (Zeiss Axiovert 25 CF) was placed on a solid,
heavy-weight steel plate to reduce vibration. The microscope was connected to
a digital high speed digital camera (Basler 504k, Ahrensburg, Germany), which
was connected to a personal computer equipped with a Datacube image
acquisition board. Camera configuration tools VLL Toolbox and CCT+ software
(Basler) were used. Recording of the sequences of the single digital pictures
was managed by Video Savant 4.0. Recording frame rate was adjusted to 1000
frames s–1. The region of interest was 240x60 pixels.
Recordings were performed with a 40x objective (resulting pixel size:
0.58 µm2).
Animal anaesthetization
All animals were anaesthetized with an initial concentration of 80 mg
l–1 tricaine (MS-222) neutralized with phosphate buffer.
Retention of the anaesthetization was performed using a concentration of 35 g
l–1 tricaine (40 g l–1 in animals older than
10 d.p.f.). Larvae were transferred into the temperature-controlled incubation
chamber of the microscope stage. The temperature was set to the incubation
temperature of the eggs (28°C).
Analysis of heart rate variations
For analysis of the HRV, images of the beating heart were made with 1000 or
200 frames s–1 and stored on the frame grabber's on-board
memory. A line was drawn beginning outside the heart tissue, crossing the
central ventricle and atrium, ending in the sinus venosus. The luminance
profile of this line was stored in a text file for all image frames of the
whole image sequence. This text file was imported into a custom-made computer
program (using LabView 7.1, National Instruments, Vienna, Austria). This
program allowed for signal analysis of the luminance periodogram on each point
along the drawn line. The changes in signal intensity in the luminance
periodogram in most of the points reflect the periodic event of the beating
heart (Fig. 1). Those points
with the best signal-to-noise ratio were chosen for further analysis. This
analysis consists of four steps. For a first estimation of the frequency
content of the raw signal a power spectrum analysis was performed on the
luminance periodogram. Secondly, the luminance periodogram was filtered by an
equi-ripple low pass filter with a pass frequency of 0.1 Hz and a stop
frequency of 10 Hz. On this filtered signal peak detection was performed. Peak
detection was based on an algorithm that fits a quadratic polynomial to
sequential groups of data points. The number of data points used in the fit
was specified by width of typical peaks found in the acquired signals. For
each peak, the quadratic fit was tested against the threshold level. The
threshold was determined for each animal separately and was dependent on small
differences in illumination and tissue orientation in the embedded animals.
Peaks with heights lower than the threshold level (smaller peaks induced by
movements of the atrium contraction) were ignored. Peaks were detected only
after the procession of approximately half of the data points representing the
width of the peak beyond the location of the peak. Peak-to-peak distances
(reflecting beat-to-beat distances) were converted to a beat-to-beat frequency
for each interval. These frequencies were plotted against time to a
cardiotachogram. This tachogram was analysed by power spectrum analysis to
evaluate frequency domains in the cardiotachogram.
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Stroke volume was determined using digital image analysis
(Schwerte and Pelster, 2000)
and basically followed the method described by Hou and Burggren
(Hou and Burggren, 1995). Video
sequences of the ventricle were saved into computer memory. The perimeter of
the ventricle image was outlined manually during end diastole and during end
systole using a mouse or a graphic tablet. The perimeter was analyzed with a
`fit-to-ellipse' algorithm, which first calculated the centre of mass of the
perimeter and subsequently the best fitting ellipse
(Schwerte and Pelster, 2000).
The major and minor axes of the ellipse were extracted and directly
transferred into a Microsoft Excel worksheet for calculation of stroke volume
using the formula for a prolate spheroid (4/3
ab2)
(Hou and Burggren, 1995). For
analysis, five diastoles and systoles were analyzed, and mean stroke volume
was calculated as the difference between diastolic and systolic ventricular
volume. Cardiac output was calculated as the product of stroke
volumexheart rate.
Experimental protocol for adrenergic and cholinergic pharmacology
The tricaine anaesthetized animals were allowed to settle down for 5 min,
which was shown to be enough in earlier experiments. The tip of a pulled glass
capillary (10 µm tip diameter) filled with test solution and connected to a
WPI UltraMicroPump II (Berlin, Germany) was placed in the immediate proximity
to the heart outside of the fish. After 5 min of control period, 1000 nl
solution were released within 1 min. Changes in heart performance were
analyzed for 20 min after ejection of the desired solution.
Drugs
Isoproterenol, propranolol, acetylcholine and atropine were obtained from
Sigma Chemicals (Vienna, Austria).
Statistical analyses
Significant differences among treatments for these indicators were
evaluated using Student's t-tests. Unless specified otherwise, a
significance level of P<0.05 was used.
Heart rate variability
The frequency bandwidth of the cardiotachograms was measured by determining
mean distance of maximum frequency values from the median. Thresholds over and
under the median values were set to limits enclosing 98% of all interbeat
frequencies closest to the median.
Power spectrum analysis
The power spectrum calculations were made with custom made software using
LabView 7.1 (National Instruments), which includes all necessary mathematical
tools. Luminance periodograms for detection of individual heart beats were
obtained from 1000 frames s–1 acquired video data to fulfil
the Nyquist criterion (a signal must be sampled at a rate at least twice the
rate of its highest frequency component).
To obtain a better estimate of the power spectrum, two different methods were tested: the Welch method and the Blackman–Tukey method. The Welch method is characterized by averaged periodograms of overlapped, windowed segments of a time series. It improves the statistical likelihood of the estimated power spectrum. Using this approach, the signal is divided in segments short enough to be stationary and long enough not to limit the spectral resolution. The Blackman–Tukey Method is based on a Fourier transformation of the smoothed, truncated auto-covariance function. Power spectrum analysis was performed on luminance periodograms (Fig. 1C) and tachograms (Fig. 1D).
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Heart rate variability (frequency bandwidth)
In general, heart rate increased with developmental age until 5 d.p.f.,
reaching a value of about 240 beats min–1. After 5 d.p.f.
mean heart rate decreased slowly down to a value of about 140 beats
min–1 at 15 d.p.f. Power spectrum analysis of the unfiltered
heart rate related luminance signal provided a dominant frequency component
reflecting the mean heart rate and harmonics. This frequency domain was
observed to produce an increasingly broader peak the older the animals became
(Fig. 3A,B). Heart beating
frequency was the dominant compound in luminance signals derived from all
tissues around the heart in an area of several hundred micrometers from the
heart.
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Heart rate related signal power spectrum analysis
The power spectrum analysis of the cardiotachogram of the low-pass filtered
heart rate-related luminance signal did not reveal a stable or reproducible
pattern of dominant frequencies (data not shown) at any of the stages of
development examined.
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TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
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) we refined our anaesthetic protocol to keep any potential
influence on autonomic processes as small as possible. By counting heart rate
and ventilatory movements in anaesthetized and non anaesthetized animals a
maintenance concentration of 35 mg l–1 (40 mg
l–1 in stages older than 10 d.p.f.) MS222 was shown to have
no influence on resting frequencies throughout all stages. A detailed study of
the effect of MS222 on autonomous processes and the survival rate of zebrafish
has also been carried out by Rombough
(Rombough, 2002).
Pharmacological characterization
Cholinergic stimulation significantly decreased heart rate in developing
zebrafish larvae starting at 5 d.p.f., whereas isoproterenol led to a
significant increase in heart rate as early as 4 d.p.f. Statistically
significant changes in heart rate were no longer seen in animals that were
preincubated with either of the receptor-specific blocking agents propranolol
or atropine (Fig. 2A). We
therefore conclude that functional cholinergic receptors are present at 5
d.p.f., but adrenergic receptors become functional by 4 d.p.f. Hsieh and Liao
(Hsieh and Liao, 2002) cloned,
sequenced and characterized a zebrafish M2 muscarinic acetylcholine receptor.
They pharmacologically analyzed the role of this receptor and observed a
response to carbachol at 3 d.p.f. Carbachol, at a high concentration
(10–4 mol l–1) injected directly into the
circulation, induced a decrease in heart rate of about 80%, and this effect
could be completely inhibited by atropine incubation. In the present study, a
cholinergic response was observed only at 5 d.p.f., but we used the
enzymatically degradable acetylcholine and peripheral incubation instead of
injection of a stable agonist like carbachol. It therefore appears quite
possible that the acetylcholine receptor actually did respond a little bit
earlier. Jacobsson and Fritsche (Jacobsson
and Fritsche, 1999) analyzed the early existence of adrenergic and
cholinergic receptors in Xenopus larvae, and they observed that
Xenopus larvae do respond to cholinergic stimulation much earlier
than to adrenaline.
The positive response to an externally applied agonist demonstrates the
presence of a functional receptor, especially if this response can be
suppressed by a specific antagonist. It does not imply, however, that the
receptor can also be reached by a signal from the autonomic nervous system. In
fact, for birds and amphibians it has been reported that functional receptors
are established in the heart long before the autonomic innervation is
completed (Tazawa et al.,
1992; Protas and Leontieva,
1992; Jacobsson and Fritsche,
1999). However, the increase in heart rate observed in 12 d.p.f.
zebrafish larvae upon incubation with atropine clearly indicated the presence
of vagal tone on the heart at this stage. Until 10 d.p.f., cholinergic
stimulation decreased heart rate, but at 11 d.p.f. and later this response was
no longer observed. One possible reason for this may be a cholinergic tone
that is established at about 11 or 12 d.p.f. After establishing the tone,
cholinergic stimulation was not longer as effective as before 11 d.p.f.,
because the heart was already under certain activity of the vagus. Inhibition
of this tone by atropine application therefore resulted in an acceleration of
the heart at 12 d.p.f. and in later stages. It is not very probable that this
tonus could be responsible for the completely missing inhibitory cholinergic
effect, because this would mean that the cholinergic tone would be at a
maximum. Although we know from diffusion experiments with fluorescent dyes
that molecules with molecular mass ranging up to 0.5 kDa diffuse well in the
tissue (unpublished data) it cannot be excluded that the maturing skin of
zebrafish becomes increasing less permeable with age. The inhibitory effect of
atropine and of propranolol revealed that diffusion of these components was
not impaired at this stage. Another possibility would be that increasing
activity of acetylcholine esterase may have lowered the effective
acetylcholine concentration. A quantitative assessment of the magnitude of the
cholinergic tone, however, was beyond the scope of this study.
In contrast to the adrenergic tone that perhaps may be due to the activity
of the autonomic nervous system or to circulating hormones
(Jacobsson and Fritsche, 1999)
it appears unlikely that a cholinergic tonus is caused by circulating
acetylcholine, because of the acetylcholine esterase activity. We therefore
conclude that at 11 or 12 d.p.f. the heart comes mainly under the influence of
the vagus, which is also the dominating influence in many adult fish
(Axelsson et al., 1987;
Taylor et al., 1999;
Campbell et al., 2004).
The picture emerging from our data for the adrenergic response is not as clear as the picture obtained for the cholinergic response. Adrenergic receptor functionality was observed for stages between 4 and 15 d.p.f. Propranolol application (ß-adrenergic antagonist) in turn led to a significant decrease in heart rate at 5 and 7 d.p.f., but the response was in the range of only 5–8%. This situation did not change until 15 d.p.f., so that at some developmental stages the decrease in heart rate induced by propranolol was just significant, on others it was not (Fig. 2B). Accordingly, it is difficult to say whether an adrenergic tone is established at this stage of development in zebrafish larvae. In addition, if present, its physiological significance remains questionable, because it would change heart rate by may be 5–10 beats min–1 at a level of 160–180 beats min–1.
This is in contrast to results reported for Xenopus larvae, in
which at least in some stages (Nieuwkoop and Faber (NF) stage 45–47) a
strong adrenergic tonus appears to be present Jacobsson and Fritsche
(Jacobsson and Fritsche,
1999). However, our results are in line with the results obtained
from adult teleosts, in which the relative importance of the adrenergic
innervation and of circulating hormones remains unclear
(Taylor et al., 1999).
Stroke volume did not show any significant changes as a result of drug
administration. Similarly, Jacobsson and Fritsche
(Jacobsson and Fritsche, 1999)
reported that epinephrine had no effect on stroke volume of Xenopus
larvae (NF stage 33–53). Cholinergic stimulation, however, reduced
stroke volume in Xenopus larvae in stage NF 45–53. From this we
conclude that in zebrafish larvae cardiac output is predominantly determined
by changes in heart rate. In adult fish during strenuous exercise and severe
hypoxic conditions cardiac output appears to be adjusted by changes in stroke
volume and in heart rate, whereas under resting conditions minor adaptations
in cardiac output may be mostly due to adaptations in heart rate
(Nilsson, 1983;
Campbell et al., 2004).
Analysis of heart rate variability
Power spectrum analysis has been shown to be a powerful tool to display the
frequency spectrum in beat-to-beat heart rate changes
(Altimiras et al., 1995;
Altimiras, 1999;
Campbell et al., 2004). To our
knowledge this is the first time that this technique has been used in fish
larvae. One reason for this may be the difficult task to find a clearly
defined reproducible parameter that can be measured to analyze cardiac cycle
timing (Altimiras, 1999). The
analysis of a pressure signal obtained by a micropressure converter
(Pelster and Burggren, 1996)
or the acquisition of an electrocardiogram (ECG)
(Baker et al., 1997) are very
time consuming and, more importantly, are quite invasive for these tiny
animals, and therefore not ideal for the analysis of heart rate variability.
Zebrafish hearts are very sensitive to mechanical manipulation in these early
developmental stages. In adult short-horn sculpin, Myxocephalus
scorpius, a recovery period of about 48 h was necessary to overcome the
stress of handling and surgery, so that `normal' and reproducible beat-to-beat
spectra could be recorded (Campbell et al.,
2004). Given the rapid developmental changes observed in zebrafish
larvae such an experimental time course is not acceptable. Non-invasive
optical methods therefore appeared to be the only option for our study.
Our custom-made program enabled us to extract periodic luminance changes in
images from the heart. Measurements were taken along a line beginning outside
heart tissue, which cross-sectioned the ventricle and atrium. Peaks in this
luminance periodogram (Fig. 1C)
were compiled to a tachogram. Power spectra of these tachograms did not show
stable frequency spectra in our animals. Altimiras et al.
(Altimiras et al., 1995)
analyzed three different teleosts and observed that clear spectral patterns
did not always exist, which was, at least in part, attributed to an erratic
influence of respiratory movements. In 12 d.p.f. zebrafish, for example,
ventilation rate is as low as 1–2 beats min–1 compared
to a heart rate of about 160 beats min–1. Thus, the
interference of respiratory movements cannot be responsible for the lack of
clear spectral patterns in these larvae. Although we avoided the stress of
surgery, handling stress could not be avoided completely but was kept to a
minimum. Given the long time course of recovery observed by Campbell et al.
(Campbell et al., 2004) it
therefore cannot be excluded that the lack of identifiable spectra may be in
part related to handling stress.
The signals analyzed later are qualitatively different. As discussed by
Altimiras (Altimiras, 1999) the
ECG, used by Campbell et al. (Campbell et
al., 2004), is the most precise method of obtaining a reproducible
trigger of cardiac pacemaker performance. All other parameters linked to
cardiac function are more or less indirect and therefore less appropriate to
evaluate heart rate variations. The most common reasons for this are damping
effects, which make the signal flatter, or the pacemaker-related peak broader.
The consequence is that computational peak detection produces less accurate
values than the extremely sharp peaks found in the ECG. The strongest
argument, put forward by Altimiras
(Altimiras, 1999), in other
animals, is the effect of movements, except from cardiac movements that may
influence the exact determination of the event of cardiac contraction.
However, in our experiments this should affect experimental and control
animals in the same way, and therefore does not cause any bias for the results
of our study.
Nevertheless, analysis of the frequency bandwidth (see Figs
3A,B,
4A,B) revealed that heart rate
variability increased with age. In the time frame of our experiments, which
was mainly limited by the changes in transparency of the developing fish, the
greatest variability was registered from 12 to 15 d.p.f. This was exactly the
time, when vagal blocking with atropine led to a significant decrease in heart
rate variability (Fig. 5A,B).
Adrenergic blocking, in turn, did not affect heart rate variability, while the
largest effect was observed when atropine and propranolol were administered
together. These results confirm our conclusion from the pharmacological
experiments that a vagal tone is established on the heart at 11–12
d.p.f., but the influence of the sympathetic trunk is of minor importance.
Whereas heart rate variability was completely abolished after bilateral
vagotomy in the study of Campbell et al.
(2004), we still observed some
variations after application of atropine and propranolol. This can probably be
attributed to the fact that vagotomy is the method of choice to be absolutely
sure that no parasympathetic stimulus reaches the heart. Pharmacological
receptor blocking, especially when applied externally, does not fulfil this
criterion, and therefore cannot block the vagal input completely.
Physiological implications
The developmental time around 12 d.p.f. is not only the start of
sympato-vagal balancing of the heart rate but around this time regulatory
integrity of cardiorespiratory functions are nearing completion. Rombough
(Rombough, 2002) demonstrated
that gills start to function as oxygen uptake organs at 12 d.p.f., whereas
they mainly serve ionoregulatory functions in earlier stages. The study of
Jacob et al. (Jacob et al.,
2002) revealed that 12–14 d.p.f. is the time during
development when bulk diffusion is no longer sufficient to supply oxygen to
the tissues, and convective oxygen transport via the circulatory system needs
to take over oxygen transport functions. NMDA-receptor-mediated regulation of
gill ventilation also starts working at 12 d.p.f.
(Turesson et al., in
press).
In summary, the results of the present study show that adrenergic and
cholinergic receptors are present long before the autonomic innervation
systems are working. Accordingly, humoral control is established at about
hatching time or shortly thereafter. At 11–12 d.p.f. a cholinergic tonus
is established, while the adrenergic tone appears to be weak. Changes in
cardiac performance in response to a hypoxic stimulus observed at 3–5
d.p.f. (Jacob et al., 2002)
therefore have to be attributed to humoral control. The analysis of heart rate
variation was possible using high-speed image analysis. This technique, in
combination with signal analysis, turned out to be an appropriate tool to
investigate heart rate variations non-invasively.
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Acknowledgments |
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References |
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TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
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