Vol. 280, Issue 5, H2006-H2010, May 2001
Direct biologically based biosensing of dynamic physiological
function
David J.
Christini,
Jeff
Walden, and
Jay M.
Edelberg
Division of Cardiology, Department of Medicine, Weill Medical
College of Cornell University, New York, New York 10021
 |
ABSTRACT |
Dynamic regulation of biological systems requires real-time
assessment of relevant physiological needs. Biosensors, which transduce
biological actions or reactions into signals amenable to processing,
are well suited for such monitoring. Typically, in vivo biosensors
approximate physiological function via the measurement of surrogate
signals. The alternative approach presented here would be to use
biologically based biosensors for the direct measurement of
physiological activity via functional integration of relevant
governing inputs. We show that an implanted excitable-tissue biosensor
(excitable cardiac tissue) can be used as a real-time, integrated
bioprocessor to analyze the complex inputs regulating a dynamic
physiological variable (heart rate). This approach offers the potential
for long-term biologically tuned quantification of endogenous
physiological function.
tissue engineering; biosensor; cardiac chronotropy; heart
transplant; pacemaker
 |
INTRODUCTION |
BIOSENSORS DERIVE
UTILITY from their inherent selectivity to specific biological
signals and their physiologically relevant reactions (25).
Most biosensors are molecularly based, relying on a specific
interaction among biomolecules, such as antibodies (4,
26), enzymes (21, 29), ion channels (5,
18), or nucleic acids (8, 20), and a target
compound. Alternatively, cell- and tissue-based biosensors (2,
22-24) offer inherent insight into physiological function
by exploiting the selectivity of the receptors, channels, and enzymes
that are part of the functional structure of a cell. Most cell- and
tissue-based biosensors are used for chemical detection. Although these
biosensors are quite adept at chemical detection, it is not a task for
which they specifically evolved. Here we describe a novel
alternative approach that exploits the inherent biosensing capacity of
excitable tissue in its natural context; as an integrated, multi-input
bioprocessor that could be used to study physiological function. The
present study has employed this approach to measure the contribution of
circulating catecholamines to the dynamic regulation of cardiac chronotropy.
 |
MATERIALS AND METHODS |
All of the experiments involving animals were performed
according to the Institutional Animal Care and Use Committee of the Weill Medical College of Cornell University, which follows federal and
state guidelines. Excitable tissue-based biosensors were developed by
the implantation of chronotropically competent cardiac allografts distant from (and not directly linked to) the endogenous heart. We
transplanted neonatal murine cardiac allografts into the pinnae of
syngeneic adult mice and then monitored cardiac electrophysiological temporal dynamics.
Transplantation.
Neonatal FVB murine hearts were transplanted into the pinnae of 3-mo
FVB mice as previously described (7, 10). Fifteen mouse
hearts were implanted into nine mice (six mice received a transplanted
heart in each ear, whereas three mice received a transplanted heart in
only one ear).
Electrocardiograms.
Between 17 and 41 days after transplantation, electrocardiographic
(ECG) activity of the endogenous and exogenous hearts was measured
after intraperitoneal anesthetization with 2.5% tribromoethanol (Avertin; vol/vol). ECG were acquired for an average of 45 min (range:
27-117 min) via a four-channel differential alternating current
amplifier (model 1700, A-M Systems). The signals were band-pass
filtered between 3.0 and 100.0 Hz, notch filtered at 60.0 Hz, amplified
1,000 times, and sampled at 500 Hz with the use of a data acquisition
board (model AT-MIO-16E-10, National Instruments) on a 266-MHz Intel
Pentium II computer running real-time Linux (3).
Quantitative rate analysis.
Postacquisition automatic (with manual correction as needed) ECG R-wave
annotation was performed with the use of custom-designed Linux C++
software. Mean R-R intervals (RR) were computed every 2 s so that dynamics of the endogenous and exogenous signals, which have
different inherent rates, could be compared quantitatively at
synchronized time slices. We selected 2 s arbitrarily; no
qualitative differences were found for interval lengths of 1, 5, or
10 s. The 15-trial endogenous mean
RRmax
RRmin = 31.2 ± 24.9 ms (where RRmax and
RRmin are maximal and minimal RR),
whereas the exogenous mean RRmax
RRmin = 100.8 ± 72.0 ms.
Each discrete RR time series was fit with the use of Matlab
version 5.3.1 to a continuous-time (t) order (P)
polynomial function given by
(t) = a0tP + a1tP
1 + ... + aP-1t + aP, where a0,
a1, and aP are real
constants. The polynomial function is not meant to model the
system dynamics, but rather, is used as an analytical means to quantify
and compare heart rate temporal variations. P was selected
as that order (P
25) for which:
1)
(t), when evaluated at the same discrete time slices as RR,
accounted for at least 95% of the raw variability of RR (if
this was not satisfied for any P < 25, P
was set to 25), and 2) the exogenous and endogenous
d
(t)/dt functions, computed analytically over the time course of the record, had the highest concordance (i.e., the highest fraction of time that
the two derivatives had the same sign), which is a measure of the
ability of the exogenous heart to track the increases and decreases in
endogenous rate. The correlation coefficient, defined for two
N-length time series x and y as
where
is the mean of x, was
computed between each exogenous and corresponding endogenous
RR time series.
Pharmacological trials.
A new set of mice, with pinnal hearts implanted as before, were
subjected to pharmacological trials between 41 and 62 days posttransplantation. Separate experiments were performed with the use
of propranolol (100 µg ip) and clonidine (2.0 mg ip). To detect
pharmacological rate effects, rate trends of distinct trial stages were
quantified by a normalized rate of change (m) given
by
where
i
and
are the
averages of the initial and final three R-R intervals of a given stage, respectively, and
t is the stage duration.
 |
RESULTS |
Figure 1 shows simultaneous
electrical activity of the endogenous heart and bilateral exogenous
hearts in a representative trial. The three hearts beat at unique but
not unrelated rates (as seen in Fig. 2)
with exogenous rates approximately one-half of the endogenous rate.

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Fig. 1.
Voltage vs. time tracings for the endogenous heart
(A) and two exogenous hearts (B and C)
of a representative adult mouse after bilateral pinnal heart
transplantation. Three hearts beat at unique but not unrelated rates,
with the exogenous hearts beating at rates approximately one-half that
of the endogenous heart.
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Fig. 2.
Mean R-R intervals (RR) vs. time for the
endogenous heart (A) and two exogenous hearts (B
and C) of a representative adult mouse after bilateral
pinnal heart transplantation. Solid curve in each graph is
(t), the best
polynomial curve fit to the data. Occasionally, poor signal quality or
high noise made R-wave annotation impossible, resulting in gaps in the
corresponding graph. R-R interval dynamics of both exogenous hearts
effectively tracked those of the endogenous heart; i.e., there was a
clear relationship between the rate trends (i.e.,
increasing/decreasing) of the 3 hearts. D: first derivative
vs. time
d (t)/dt
for the polynomial fits of the endogenous ( )
and second exogenous heart shown in C ( ).
When time-shifted to account for the exogenous phase lag (i.e., the
72-s mean delay between the endogenous and exogenous derivative zeros),
the two derivatives had the same sign for 79% of the record. Thirteen
of fifteeen trials had concordance >70% (mean 85 ± 11%). Such
high concordance quantitatively confirms that the exogenous heart
effectively tracked increases and decreases in endogenous heart rate.
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|
Quantitative rate analysis.
Mean interbeat interval time series RR illuminated a clear
relationship between exogenous and endogenous dynamics (Fig. 2). The
ability of the exogenous tissue to track relative temporal endogenous
dynamics (i.e., increasing/decreasing trends) was quantified via
analysis of the derivatives of polynomial curves fit to the RR time series (Fig. 2D). For 13 of 15 exogenous
cardiac allografts, the endogenous and exogenous derivative curves had
concordant sign >70% (mean = 85 ± 11%) of the given
trial, indicating that the exogenous tissue was an effective relative
endogenous rate sensor. In addition to their relative tracking ability,
the majority (9 of 13) of exogenous hearts showed evidence of effective
absolute sensing function (i.e., at any given time, the exogenous rate, appropriately scaled, could be used as an effective predictor of the
natural heart rate). Exogenous-to-endogenous RR correlation computation illuminated two types of absolute sensing function behavior: 1) a strong one-to-one linear relationship between
the dynamics of the two hearts for the entire trial (in 5 of 9 exogenous hearts; i.e., Fig.
3A), or 2)
temporally distinct, highly correlated segments during the trial (in 4 of 9 exogenous hearts; i.e., Fig. 3B). Such temporal shifts
in absolute sensing function suggest that the exogenous activity is
mediated by a subset of the multiple inputs that govern the endogenous
dynamics.

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Fig. 3.
Exogenous vs. endogenous RR for two separate
mice (A and B). Solid and dotted lines in each
graph depict the linear regression fit and the 95% confidence interval
of that fit, respectively. A: correlation coefficient
r = 0.94 indicates that there is a strong one-to-one
linear relationship (with slope m = 3.33 ms) between
the exogenous and endogenous RR. Five of 13 positive trials
had r > 0.70 ( = 0.85 ± 0.10, = 2.40 ± 1.15 ms). Four of the remaining eight
positive trials had at least one distinct segment (of at least 500 consecutive seconds) of effective absolute sensing, with
r > 0.85 ( = 0.91 ± 0.04, = 2.06 ± 1.12 ms for segments of at least
500 s). One such trial (the same exogenous heart trial as that of
Fig. 2C) is shown in B.
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Pharmacological trials.
To identify the exogenous input subset, we studied endogenous and
exogenous chronotropic regulation by pharmacological manipulation. Intraperitoneal propranolol was administered in an attempt to block
humoral and autonomic
-adrenergic receptor pathways (Fig. 4A). As expected, shortly
after injection, endogenous rate slowed. The exogenous rate underwent
an even more dramatic decline, indicating that it is controlled by
humoral and/or autonomic inputs. To further define the nature of the
exogenous inputs, we performed intraperitoneal clonidine trials. In six
of the seven trials, a rapid decrease in endogenous heart rate (lasting
10-30 s), which is consistent with the reduction of clonidine in
efferent sympathetic nerve activity (32), was observed
within 20 s postinjection (Fig. 4B). In contrast, there
was a negligible reduction in exogenous heart rate during this time,
suggesting that the exogenous hearts are not under significant direct
autonomic control. After this initial postinjection stage, both hearts
underwent a gradual heart rate reduction, consistent with a humoral
response to the secondary effect of clonidine on norepinephrine release
inhibition (1). The results shown in Fig. 4 strongly
suggest that the chronotropic biosensing of the exogenous excitable
tissue is mediated by predominately humoral influences.

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Fig. 4.
Endogenous and exogenous RR vs. time for one
mouse. A: 100 µg of propranolol was delivered via
intraperitoneal (IP) injection at t = 121 s.
Inset: magnified portion of the endogenous data. Shortly
after injection, endogenous and exogenous rates slowed
(stage B) relative to baseline (stage
A) in 5 of 5 trials (aggregate values, as defined in
MATERIALS AND METHODS, are shown in C).
Exogenous slowing is evidence of autonomic and/or humoral control.
B: same mouse as A, but performed on a different
day; 2.0 mg of clonidine was delivered via intraperitoneal injection at
t = 49 s. Shortly after injection, the endogenous
rate slowed rapidly (stage B') in 6 of 7 trials. In
contrast, the exogenous rate continued its preinjection trend. After
stage B', both the endogenous and exogenous hearts slowed.
In all 6 trials, the endogenous hearts slowed considerably more during
stage B' than stage B, whereas the exogenous
hearts slowed more during stage B than stage
B'.
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 |
DISCUSSION |
Here we have shown that implanted exogenous cardiac allografts can
act as effective sensors of endogenous chronotropic inputs. Through
pharmacological trials, we have demonstrated that the biosensing of the
implanted tissue is mediated predominately by circulating hormonal
signals. This is compelling evidence that excitable tissue can function
as a responsive biosensor of underlying physiological regulation.
In addition to demonstrating the potential role of exogenous tissue to
act as an implanted dynamic biosensor, our studies offer insight into
the importance of circulating catecholamines in chronotropic regulation
of transplanted hearts. It is well known (16, 17, 33) that
the heart rate of the transplanted heart can be markedly influenced by
pharmacological manipulations of the adrenergic system. However,
because the contribution of the circulating catecholamines to such rate
regulation is difficult to quantify, uptake studies (15)
revealed the partial reinnervation of transplanted hearts, and heart
rate variability studies (12, 14, 28, 30, 31) provided
frequency-spectrum evidence of autonomic activity. An improvement in
cardiac chronotropic responsiveness after heart transplantation has
been attributed primarily to sinus node reinnervation in the
transplanted heart (see Ref. 27 for a review). In
contrast, the present study offers clear evidence of the capacity of
circulating catecholamines to highly regulate the dynamics of
transplanted hearts in the absence of direct autonomic inputs.
Future studies will be directed at further exploiting the inherent
capacity of exogenous excitable tissue to sense circulating physiological signals. These studies may focus on expanding input recognition through the targeted molecular manipulation of cellular signaling pathways in excitable tissue (7). It is
projected that through such molecular engineering, the utility of this
approach may extend beyond that of chronotropic-regulation biosensing. For example, molecular manipulation of cellular chronotropic
sensitivity to targeted substances may offer a means of biosensing
physiological and pathophysiological signals that would otherwise not
alter cardiac chronotropy. More importantly, it is anticipated that such developments may employ cardiac myocytes derived from pluripotent stem cells, potentially from endogenous bone marrow, thereby
eliminating the potential for tissue rejection and enabling long-term
use (13, 19). Further advancement may employ the
development of a more uniform biosensor array by culturing excitable
cells on silicon chips (6, 9, 11). Such a combination of
improvements could lead to the development of long-term,
physiologically tuned, functionally integrated bioprocessing interfaces
for a wide range of external or implantable devices.
 |
ACKNOWLEDGEMENTS |
The authors thank Bruce Lerman and Peter Okin for helpful discussions.
 |
FOOTNOTES |
This work was supported by American Heart Association Grant 0030028N
(to D. J. Christini), an American Federation for Aging Research
grant (to J. M. Edelberg), and National Heart, Lung, and Blood
Institute Grant P01-HL-59312.
Address for reprint requests and other correspondence: J. M. Edelberg, Weill Medical College of Cornell Univ., Div. of
Cardiology, 520 E. 70th St., New York, NY 10021 (E-mail:
jme2002{at}mail.med.cornell.edu; dchristi{at}mail.med.cornell.edu).
The costs of publication of this
article were defrayed in part by the
payment of page charges. The article
must therefore be hereby marked
"advertisement"
in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
Received 13 June 2000; accepted in final form 12 December 2000.
 |
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