Comparative advantages of mechanical biosensors
J.L. Arlett
,
E.B. Myers
, and
M.L. Roukes
*
Abstract
Mechanical interactions are fundamental to biology. Mechanical forces of chemical origin
determine motility and adhesion on the cellular scale, and govern transport and affinity on the
molecular scale. Biological sensing in the mechanical domain provides unique opportunities to
measure forces, displacements and mass changes from cellular and subcellular processes.
Nanomechanical systems are particularly well matched in size with molecular interactions, and
provide a basis for biological probes with single-molecule sensitivity. Here we review micro- and
nanoscale biosensors, with a particular focus on fast mechanical biosensing in fluid by mass- and
force-based methods, and the challenges presented by non-specific interactions. We explain the
general issues that will be critical to the success of any type of next-generation mechanical
biosensor, such as the need to improve intrinsic device performance, fabrication reproducibility
and system integration. We also discuss the need for a greater understanding of analyte–sensor
interactions on the nanoscale and of stochastic processes in the sensing environment.
Advances in micro- and nanofabrication technologies are enabling a wide range of new
technologies, including the development of mechanical devices with nanosized moving
parts. The ability to fabricate such structures using standard wafer-scale semiconductor
processing techniques has allowed attention to move from fundamental problems in
biological physics and bioengineering towards the development of practical micro- and
nanoelectromechanical biosensors that can be produced
en masse
.
In general, mechanical biosensors capitalize on attributes that scale advantageously as
physical size is reduced. First, nanoscale mechanical sensors provide exquisite mass
resolution — the minimum detectable added mass is proportional to the total mass of the
device. Nanoelectromechanical systems (NEMS) have achieved zeptogramscale mass
resolution while operating in vacuum, and nanogram resolution while operating in a fluid
environment
1
.
Second, the mechanical compliance of a device — its ability to be displaced or deformed —
greatly increases with uniform reduction of its dimensions. Mechanical compliance converts
an applied force into a measurable displacement (and is the mechanical analogue of gain in
electronic circuits). This enhanced force responsivity opens new opportunities for measuring
the miniscule forces that govern biological interactions. For example, nanomechanical
sensors can resolve forces of
10 pN, which is sensitive enough to detect the rupturing of
individual hydrogen bonds.
Third, small fluidic mechanical devices can exhibit fast response times. This allows
biological processes in fluids to be observed on the timescales of milliseconds or shorter
over which stochastic molecular interactions begin to evolve.
© 2011 Macmillan Publishers Limited.
*
Kavli Nanoscience Institute and Departments of Physics, Applied Physics, and Bioengineering, California Institute of Technology,
MC 149-33 Pasadena, California 91125, USA. roukes@caltech.edu.
Additional information
: The authors declare no competing financial interests
NIH Public Access
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. 2011 April ; 6(4): . doi:10.1038/nnano.2011.44.
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Mechanical biosensors can generally be delineated into four broad categories based on the
chemical interactions between the sensor and the analyte: (1) affinity-based assays where
highly selective target identification and capture is achieved by the employing high
specificity (that is, affinity) between the target and the ‘functionalization’ at the device
surface. Highly specific interactions can exist, for example, between antigens and
antibodies; (2) fingerprint assays that rely on a multiplicity of less-selective
functionalization layers to identify a target through characteristic binding affinities to an
ensemble of sensors; (3) separation-based assays where chemical affinities between
immobilized species and flowing analytes permit spatiotemporal separation of analytes; and
(4) spectrometric assays where, for example, the mass or optical properties of the target are
deduced to enable its identification.
An outstanding challenge in biosensing is to engineer suites of reliable, high-affinity
biochemical agents to capture the target biomarkers we are interested in detecting. High
affinity binding
2
is based on biological molecular recognition, which generally occurs only
in liquid phase. After capture, target detection is ideally performed
in situ,
within the
fluid
1,3,4
. However alternative approaches include removing the detector from the fluid
(after the targets are captured), and desiccating it before measurement
5
. Detection
in situ
is
obviously simpler and immediate, but mechanical sensing in fluid is strongly affected by
viscous damping. As described below, this significantly reduces the mass resolution
compared with that obtained in gas or vacuum.
Two widely used (non-mechanical) biodetection technologies are lateral flow assays (LFAs)
and enzyme-linked immunosorbent assays (ELISAs). LFAs (which are routinely used for
urine analysis) provide quick analysis times (
minutes), ease of use and low cost. However,
their concentration sensitivity (that is, the lowest concentration at which target detection is
possible) is only
0.1
M, which is not good enough to detect many targets of biological
importance. By comparison, ELISA requires a much longer analysis time (
1 hr), but it
offers much better concentration sensitivity (
1 pM).
Achieving optimal performance for both metrics — an analysis time of less than one minute,
and a concentration sensitivity (also known as limit of detection) on the picomolar level or
better — is a critical challenge for any new biosensor. Equally important for real
applications are practical considerations: can the new technology be mass produced? Can it
be integrated with other system components? Can the design of the overall system be kept
simple?
In addition to the four chemistry-based categories outlined above, mechanical biosensors
can be subgrouped according to the physical processes that underpin their operation. These
are described in the next section. Figure 1 and Table 1 summarize the analysis times and
sensitivities of the various existing and emerging biosensing technologies discussed in this
Review.
Different types of mechanical biosensor
The central element in many mechanical biosensors is a small cantilever that is sensitive to
the biomolecule of interest: such devices can either be surface-stress sensors or dynamic-
mode sensors. We will also discuss quartz crystal microbalances and some non-mechanical
biosensors.
Surface-stress mechanical biosensors
These devices measure the quasistatic defection of a miniature mechanical device, usually a
cantilever, caused by biomolecules binding to functional groups on the surface of the device
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(Fig. 2a). As the biomolecules bind, surface stress is developed — owing to electrostatic
repulsion or attraction, steric interactions, hydration and entropic effects — and this can
induce defection of the mechanical element. Reference 6 contains a detailed analysis of the
relationship of surface stress to surface free energy. Binding of protein
4,
, DNA
7–9
and
mRNA
10
have been studied, as have drug interactions
11
and conformational changes of
proteins
12
and DNA
13
. The amount of defection is usually measured by refecting a laser
beam of the cantilever, but electrical (piezoresistive) read out has been employed to measure
binding of proteins
14
and DNA
15
. Individual microcantilevers are susceptible to parasitic
factors that accompany their exposure to a sample aliquot; spurious defections from
proximal changes to index of refraction, temperature and fluidic disturbances can result.
These can be partially circumvented by differential measurements
4
that enable
in situ
comparison between the induced strain on cantilevers that have been functionalized and
those that have been passivated. Reported sensitivities range from
100 pM (ref. 7) to the
few nanomolar range
4
(Fig. 1, Table 1).
Stress within self-assembled monolayers can be deduced from surface-stress sensor
measurements through Stoney' formula
16
for devices with large aspect ratio (that is,
length:thickness > 10). For devices with smaller aspect ratio, the more detailed analysis of
Sader
17
must be used.
Dynamic-mode mechanical biosensors
These devices are not quasi static: rather, they oscillate with a resonance frequency, and this
frequency changes when molecules land on the cantilever (Fig. 2b). Below we describe
different operating environments and different modes of operation for such sensors
Humid environments—
Real-time monitoring of very small-scale bacterial colonies has
been achieved by growing them directly on micromechanical mass sensors. This involves
maintaining the devices in a humid, gas-phase environment, but obviates the need for their
direct immersion in fluid. Monitoring growth of
E. coli
microcultures in less than one
hour
18,19
has been demonstrated, which compares favourably with
one day times for
conventional methods. Moreover, the detection of antibiotic selective growth has been made
in less than two hours
19
. This approach offers potential for simultaneous multiplexed
detection of various bacterial species through device arrays.
Fluid-phase capture and detection in vacuo—
Mechanical biosensors can provide
exquisite mass resolution in vacuum and in air
20,21
. An approach that harnesses this level of
performance for fluidic biosensing involves operating the device in solution, removing it
from solution once the analytes have bound, then desiccating them before mass detection.
However, spurious molecules can bind to the device during desiccation, which leads to
errors (and continuous monitoring is not possible — see below). Early efforts in this area
focused on the detection of relatively massive virus particles
22,23
, and single-virion
resolution was achieved
22
. More recently, a ‘sandwich assay’ was used to detect prostate-
specific antigen (PSA) in serum at femtomolar concentrations
5
. Sandwich assays employ
two affinity-based probes (often two different antibodies) to achieve an effective affinity
that is the product of the affinities of the individual agents. A label is often attached to the
second probe to enable the readout (for example, fluorescent assays) or to enhance the signal
(for example, labelling with relatively massive nanoparticles for mass-based detection
5
).
Continuous operation—
The method described in the previous section is not capable of
continuous monitoring and fast detection. However, if a dynamic-mode mechanical
biosensor is immersed in the fluid, continuous monitoring with picomolar sensitivity and
response times of a few minutes becomes possible. However the concentration sensitivity
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attained depends on the target mass; subpicomolar detection of T5 virions (molecular weight
= 7 × 10
7
Da) is possible
1
, whereas micromolar sensitivity is typical for smaller peptides
such as ferrichrome (molecular weight = 687.7 Da). Dynamic-mode mass sensing has also
been used for mass measurements of individual live cells
24,25
.
Sensitive frequency-shift-based mass detection requires resonators with high vibrational
quality factors, but the quality factor,
Q
, is compromised in fluid by viscous damping
26
.
However, high- frequency operation increases the effective Reynolds number and can
enable operation with higher values of
Q
27
. These higher frequencies can be achieved by
reducing the device dimensions, or by operating with high-order vibrational modes
28,29
.
Figure 1 shows the present state-of-the-art performance.
Several groups report discrepancies between adsorbed mass and induced frequency shift,
both for liquid-phase
30,31
and gas-phase measurements
32
. This has commonly been
attributed to surface stress induced by the adsorbates, yet theoretical estimates of expected
magnitudes are far smaller than what is observed. This is especially true for the case of
microcantilever sensors, where simple extension or contraction can relieve surface stress
33
.
‘Strain-dependent’ surface-stress models have been proposed
33
but their validity is
questioned
34
. It has been shown
34
that clamping effects can significantly affect surface
stresses developed in short cantilevers but, again, the expected stress-induced frequency
shifts are smaller than experimental observations.
Adsorbed analytes can also potentially induce a frequency shift by changing the composite
elasticity of the sensor. It has been proposed that such changes might dominate the
frequency shift induced by mass loading, even when the layer of adsorbed species is much
thinner than the device
35
, and both experimental and theoretical evidence have been
reported for such a stiffening effect from thin antibody layers on 30-nm-thick
microcantilevers
36
.
Suspended microchannel resonators—
An ingenious alternative to immersing
dynamic mass sensors in fluid is to constrain the fluid to channels embedded in the
mechanical resonator itself
37
. Such suspended microchannel resonators (SMRs) can be
measured
in vacuo
where values of
Q
of up to
15,000 can be obtained (Fig. 2c,d).
Measurements of fluidic dissipation in SMR devices suggest that some
Q
degradation may
occur for fluid-filled nanochannels
38,39
, but these results are not fully understood
theoretically
40,41
. So far, despite the high values of
Q
attained, the performance of SMR
biosensors is modest. The glycoprotein ALCAM has been detected in undiluted serum at
300 pM concentrations in several minutes
3
. In this case the detection limit was set by non-
specific binding. (The intrinsic performance should be about two orders of magnitude better
than this.) SMRs have been applied to measurements of cell mass and density during the cell
cycle of yeast
42,43
and have been used to measure growth rates from single cells both for
bacterial and mammalian cells
43
. They have also been used for detection of antibiotic
resistance
44
. Elsewhere we have carefully analysed the ultimate practical limits to SMR
biosensing
45
.
Other mechanical biosensors
There is one other widely used mechanical biosensor — the quartz crystal microbalance —
and also a variety of non-mechanical biosensors, including whispering-gallery microcavity
resonators, optical microring resonators and nanowire biosensors.
Quartz crystal microbalances (QCM)—
These are centimetre-scale mechanical
resonators that can measure the inertial mass of analytes accreting on their surfaces in
vacuum, gas or fluid. A downshift in the resonant frequency occurs with target accretion,
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which is most reliably tracked electronically, in real time. Fluid-based QCM biodetection
spans the nano- to femtomolar range: nanomolar sensitivity is reported for continuous
analyte monitoring using an indirect-competitive assay
46
, whereas
100 fM sensitivity has
been reported for end-point detection assays involving device removal from fluid, post-
capture drying, and subsequent measurement
in vacuo
. Femtomolar sensitivity is reported by
a technique combining this end-point vacuum detection approach with a sandwich assay
providing immuno-specific target-mass enhancement
47,48
. However, as mentioned, the need
to remove samples from fluid and desiccate them before measurements
in vacuo
makes
these assays cumbersome and susceptible to measurement artifacts.
Whispering-gallery microcavity (WGM)—
Consists of a high-finesse toroidal optical
resonator coupled evanescently to an optical fibre. Adsorption of analytes to the surface of
the resonator measurably alters its properties. First efforts reported unprecedented
100 aM
sensitivity with response times
1 s (ref. 49), but these results caused significant
controversy. The data have not been reproduced, and sub sequent analyses suggest they are
incommensurate with expected resonance shifts
50
and binding kinetics. Recently, some of
the authors of ref. 49 have reported follow-up studies showing reproducible, albeit more
conservative, results: detection of the relatively large influenza-A virion at picomolar
concentrations within
10 s (T. Lu
et al.
, manuscript in preparation).
Optical microring resonators (MRRs)—
These devices are similar to WGM devices,
but offer the advantage that they can be fabricated by standard methods and, thus, are more
readily integrated into multiplexed detection systems. However, this advantage comes at the
price of lower optical quality factors and, hence, reduced sensitivity; label-free MRR-based
detection is reported in the nanomolar range with response times
1 min. MRR biosensors
have enabled quantification of unknowns from a mixture of five proteins
51
, and sandwich-
assay detection yielding
6.5 pM sensitivity.
52
Nanowire biosensors—
The conductance of these devices — which are made from
semiconductor nanowires and carbon nanotubes — changes when a target molecule binds to
the surface of the device. This ‘electrochemical gating’ arises from a change in local surface
potential induced by target binding or changes in solution pH. Even for nominally similar
systems, the concentration sensitivities reported for nanowire biosensors span a large range
of values, from the femtomolar
53
to the few-picomolar scale
54,55
. An initial sensitivity of 5
pM can be improved to 0.15 pM through the use of frequency-domain detection
54
, and
optimization by subthreshold biasing can improve this further, to 1.5 fM (ref. 56). Some
reported results are not consistent with recent estimates of binding kinetics
57
— given the
minuscule surface areas available on the surface of a nanowire for binding, estimates
suggest that at fM concentrations there should be only one capture event every few days!
Nanomolar sensitivity has also been reported for label-free protein biosensing with surface-
plasmon resonance (SPR) biosensors
58
and photonic-bandgap (PBG) biosensors
59
. This
level of performance can be improved to the femtomolar range by using sandwich-assay
end-point detection (in which label probes incorporating gold nano-particles that enhance
SPR are employed
60
). Optical fluorescence detection methods are routinely used to achieve
picomolar sensitivity, but they typically require incubation times on the order of hours
61–63
.
Sensitivity versus other performance metrics
The detection of rare biomarkers in blood plasma is an archetypal goal for advanced
biosensors. For many biomedical targets of interest, existing sensors are capable of reaching
the diagnostic level of significance: this is
4 ng ml
−1
(120 pM) for PSA. A number of
other cancer biomarkers have similar thresholds, that is, they are within the sensitivity range
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of other technologies (Fig. 1). However, there is a clear need for biosensors that can
simultaneously detect a number of different biomarkers (that is, fingerprint assays). The case
of prostate cancer illustrates some of these challenges: recent studies haves shown that 70%
of males with PSA levels at or below the current diagnostic level of significance do not
develop this form of cancer
64
, so there is a need for better diagnostics.
For biosensor applications, it is necessary to focus on both the intrinsic device performance
and on the performance of the overall sensor system. Important considerations include: ease
of biofunction-alization and potential for multiplexing; complexity of fabrication and
integration; device robustness and shelf life; the trade-off between sensitivity and frequency
of false positives
65
; and the readiness and adaptability for production
en masse
.
Non-specific binding and the biological noise floor
It is not often appreciated that biosensing is more complex than simply finding ‘a needle in a
haystack’ because of the problem of non-specific binding. Other species are present at much
higher concentrations than the target biomolecule (perhaps at concentrations a billion times
greater than the target), and these species can also bind to the sensor, which results in most
of the sensor interactions being non-specific. Even if the residence times associated with
these non-specific binding events are much shorter than those for specific binding events,
non-specific interactions impose a fundamental biological noise ‘floor’ to achievable limits
of detection.
We illustrate this problem with a simple hypothetical example. Non-specific interactions can
take place at functionalized, passivated and untreated regions of a device; and all can have a
role in limiting detection sensitivity. Representative rates of protein association for non-
specific binding
66,67
,
typically fall within the range of 10
4
– 10
5
M
−1
, whereas generic
target/receptor interactions, such as TNF and TNFR1, have binding affinities
of
10
11
M
−1
. Albumin, the most prevalent protein in blood plasma, is present at concentration
c
prev
600
M. We assume the number of specific and non-specific binding sites of the sensor —
represented as
b
S
and
b
NS
, respectively — are comparable, and define the limit of detection
as yielding a 3:1 signal-to-background ratio. For the example of TNF in plasma, these
considerations result in a background biological noise floor,
that is equivalent to
1.8 nM target concentration. Many
other targets of interest have much weaker binding affinities and will correspond to higher
biological noise levels.
Measurements of ALCAM in serum with suspended microchannel resonators demonstrate
that non-specific binding can be central in determining ultimate detection limits
3
. In these
measurements, the practical detection limit (defined as the standard deviation of the
response to negative controls) was roughly 200 times worse than expected from the mass
resolution of the device. Although non-specific binding is not the only factor that determines
this detection limit (the measurements are performed over a period of approximately 20 min,
so sensor drift might also have a role), these measurements demonstrate that state-of-the-art
technologies have already reached a level where the detection limit is determined not by the
intrinsic device sensitivity but by other factors. Understanding and controlling non-specific
binding is likely to be key to further gains in sensitivity.
Despite the importance of these considerations, little systematic experimental investigation
has been undertaken to quantify biological noise arising from non-specific interactions in
practical situations. Nair and Alam have modelled physisorption onto unpassivated regions
of devices, assuming the rate constants between non-specific and specific binding differ by a
factor of 10
9
. Even though this ratio is somewhat arbitrary, their conclusions underscore the
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importance of dense biofunctionalization surface coverage to achieving high selec-tivity
68
.
Their model indicates that target discrimination remains possible with high coverage of
specific receptors (
2 × 10
12
cm
−2
), even when other species that we are not interested in
are 10
9
times more abundant in solution. They suggest discrimination can be enhanced
further by back-filling ‘voids’ in functionalization with, for example, PEG or other
biopassivation species. Finally, it has also been shown that differential sufficiently to
circumvent false positives arising from biological noise
10
.
Practical signal enhancement
The limitations imposed by non-specific binding can be overcome, at least in part, at the cost
of more complex procedures such as the use of sandwich assays
52,69
to increase target
capture specificity. Variations on the traditional sandwich assays can also be used, such as
the two-step process used to detect PSA at
60 pM (2ng ml
minus;1
) in whole blood within
20 min using a nanoribbon sensor
70
.
Another approach is to amplify the target analyte so that its concentration rises above the
biological noise floor. The widely used polymerase chain reaction (PCR) exponentially
amplifies initial tar get species and has enabled measurements of DNA from individual cells
in volumes > 100
l (ref. 71). At present, protein assays do not achieve such profound
species amplification, but enhancement methods have been developed that provide some
level of signal amplification. The ELISA assay, perhaps the archetypal example, employs an
enzyme bound to a detection antibody. Each enzyme molecule acts as a signal amplifier,
typically producing thousands of signal molecules per second. Although the ELISA process
provides only a linear (rather than exponential) increase in the signal with time, it can still
achieve subpicomolar detection sensitivities (Fig. 1).
Labelling provides another form of signal amplification. A label can serve two purposes: to
enhance detection specificity through sandwich-assay mechanisms, and to directly amplify
the detected signal. For example, SPR sensors achieve nanomolar-concentration sensitivity
in their basic, label-free form (Fig. 1, Table 1). However, substantial enhancement of the
induced plasmonic signal, reportedly to enable femtomolar sensitivity, is possible through
immunospecific attachment of gold nanoparticles to the target in a final labelling step
(although this approach also involved a two-hour incubation period)
60
. Labelling
enhancement is possible with optical (MRR) biosensors; 0.6-nM label-free detection within
several minutes is typical
51
, and labelled detection with 6.5-pM sensitivity, which enables
detection of smaller proteins such as cytokines, has been reported (albeit with a 45-min
incubation period)
52
.
Labelling can also enhance the signals detected by fluidic mechanical biosensors. Gold
nanoparticle labels have been used to seed additional gold precipitation, sufficiently
enhancing their QCM mass signal to enable femtomolar detection of DNA
48
.
‘Biobarcode’ (BBA) sensors combine both amplification and nanoparticle labelling and
have achieved record sensitivities of
500 aM (Fig. 1)
72
.
In general, it is complex to scale labelling and non-PCR amplification methods to highly
multiplexed assays. Also, labelling and sandwich assays are inherently one-shot detection
techniques — they are not readily adaptable to continuous, real-time monitoring.
Furthermore, the most selective sandwich-type assays are predicated on the availability of
two high-affinity capture agents, for example, antibodies. In this context, it is noteworthy
that obtaining robust and effective capture agents is often a limiting factor in immunoassay
development
2
.
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Diffusion, convection, reaction kinetics and response time
Capture kinetics have a critical and underappreciated role in determining the overall sensor
system performance. For most applications, a very fast flow rate is optimal for microfluidic
devices — although this leads to a reduced percentage of captured target molecules, it
increases the actual number of captured molecules per unit time. Although this might seem
wasteful, the small volumes of microfluidic devices and their tiny maximal flow rates result
in the use of very small sample aliquots — often in the range of microlitres, or less.
To illustrate these considerations we summarize the kinetics of analyte capture in a
microfluidic channel. (See Box 1 and ref. 57). We define a critical length,
, where
D
is diffusion rate,
Q
V
is flow rate,
b
m
is the
number of receptor binding sites,
h
chan
is channel height,
k
on
is the rate of association and
w
chan
is channel width, over which analytes, owing to binding, become depleted near the
functionalized surface to 50% of their initial (bulk) concentration. For sensors shorter than
L
*, such depletion and, hence, mass transport itself, can safely be ignored. Conversely, for
sensors significantly longer than
L
*, depletion plays an increasingly important role. Figure 3
shows the strong dependence
L
* has on
k
on
for a variety of microfluidic device geometries.
For typical biological binding affinities — for example,
k
on
10
7
M
−1
s
−1
, characteristic of
TNF binding to TNF-R1
73
—
L
* ranges from micrometres to tens of millimetres depending
on the flow geometry.
These expressions also allow us to estimate the time required to reach steady-state,
ss
. For
the geometries and targets of Fig. 3,
SS
can range from seconds (for interactions with the
lowest affinities) to hours.
Concentration sensitivity versus absolute sensitivity
For very small sample volumes, one may also need to consider depletion in the bulk
solution. Table 2 summarizes the smallest volume at which the bulk concentration remains
within 90% of the initial value at steady state. As microfluidic sample volumes are generally
l, bulk depletion is often negligible. However, recent work on microfluidic single cell
analysis exemplifies an important situation where depletion becomes relevant
63
: a sensitivity
of
2 zeptomoles (10
−20
moles or
1,000 copies) has been achieved by confining
individual cells in a 5-nl chamber in which a bead-based immunofluorescence assay (IFA)
was implemented. These are very small volumes compared with typical
l-scale
microfluidic assays. For reaction-limited systems (see Box 1), the time-dependent capture
profile can be described by the expression,
Here
b
(
t
) is the number of target molecules bound to the surface at time,
t, V
is the total (limited)
volume of sample, and N
A
is Avogadro' number. For detection at very low concentrations,
we ignore terms of order
. Figure 4 shows the fraction of receptors bound after 10
min in such an experiment for a range of target molecules and capture areas.
These considerations illustrate that nanoscale, and even microscale, sensors cannot capture
sufficient targets from solution to become depletion-limited for most applications (Fig. 3). In
cases where the analysis volume is extremely minute (for example, for the single-cell
analyses mentioned previously), depletion can play a role for surface-to-volume ratios on the
order of 100
m
2
nl
−1
or less (Fig. 4). Thus, for a sample volume
nl, Significant gains in
surface density of target molecules (and hence limits of detection) can be realized by scaling
the active sensor surface to an area of roughly 100
m
2
. Except for the highest affinity
targets, further gains cannot be realized with smaller capture cross-sections (Fig. 4). The
volumes at which depletion begins to play a role are summarized in Table 2 for several
sensor geometries.
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Force and energy sensing
Mechanical devices can perform other types of sensing, especially molecular-force and
energy-based sensing. The ability to access other modes of operation highlights the potential
of new sensors to open different avenues of fundamental biological research, and to enable
applications beyond the simple ‘on/off’ indication of target analyte capture.
Chemically functionalized atomic force microscopes have been employed to measure the
force of intramolecular interactions
74–78
, arrays of polydimethylsiloxane (PDMS) posts have
been used to measure forces exerted by cells
79
, and optical tweezers have been used to
measure the elasticity of cells and have measured Significant (three fold) differences in
deformability between cancerous and normal cells
80,81
. Measurement of forces, elasticity
and displacement is ideally suited to the mechanical domain and, in particular, the
unprecedented sensitivity of nanoelectromechanical systems (NEMS) devices. Many of
these applications are just beginning to be explored — a recent example is the use of
surface-stress sensors to measure conformational changes of proteins
12
and DNA
13
. In the
energy domain, micro-fluidic calorimeters with potential for resolving the metabolic output
of individual cells are on the horizon
82
. Here we highlight several of these promising new
areas of research.
Fluid-based force sensing
The atomic force microscope (AFM) is best know for probing various systems with atomic
resolution in vacuum, but it can also image samples at atmospheric pressure and immersed
in fluid. Measurement of the elastic properties of live cells has also been demonstrated
83
. As
with mass sensitivity, improvements in force resolution are achieved by reducing the
dimensions of the sensor (Fig. 5). Current microcantilevers have the sensitivity to resolve
forces at the level of individual hydrogen bonds and to investigate biological molecules
based on their force– extension profile as the molecule is stretched
84,77,78
or ruptured
74
.
Bond lifetime and dynamic force spectroscopy experiments have enabled measurements of
bond formation and dissociation at the single-molecule level, yielding new insights to
molecular behaviour, binding states and reaction pathways. In particular, unbinding force
measurements have been used to study receptor–ligand dissociation rates,
k
off
75,85
.
However, care must be taken in interpreting these rates, as the initial ‘bound state’ and hence
the measured rupture force, is strongly dependent on its history
86
. With careful study,
Significant information on the energy landscape for receptor–ligand bonds can be obtained,
yielding good agreement between simulations
87
and experiments
76
.
Of particular interest in this domain have been studies of cell adhesion and the interaction
between mechanical stimuli and chemical circuitry in the cell
88
. Single-molecule atomic
force microscopy techniques, in which the bonds are stretched but not ruptured, have
allowed studies of the dynamic rearrangement of the active site of an enzyme during
catalysis
77
, and have also been used to investigate protein
78,84
and RNA
89
folding. In
single-cell force spectroscopy, a cell is attached to an AFM cantilever and brought into
contact with a substrate at a predetermined contact force, kept stationary for a fixed time,
and then pulled away from the substrate. Individual bond-breaking events can be resolved,
enabling the investigation of adhesion forces — down to the level of individual receptor
interactions. This has been used to investigate a wide variety of phenomena, from the
properties of cell adhesion itself
90
, to force interaction in cancer
91
and immune response
92
.
Most recently, functionalized surfaces have been used to investigate receptor crosstalk
93
.
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Fluid-based energy sensing devices
The inherently small heat capacities of suspended nanoscale devices make them ideal
candidates for ultrasensitive calorimetry. Indeed, vacuum-based nanoscale devices have
achieved a resolution of 0.5 aJ K
−1
at 2 K (ref. 94). Scaling these chip calorimeters up to
room temperature operation, and embed ding them in integrated microfluidics, offers the
prospect of high-throughput measurements requiring very low sample consumption. In
particular, a power sensitivity on the order of nanowatts, on sample volumes of a few
nanolitres, has been achieved
82
. Next-generation improvements on the horizon suggest that
sensitivities on the scale of picowatts are feasible; this will enable metabolic measurements
at the level of individual cells.
Practical aspects of fluidic mechanical biosensors
A major challenge for all NEMS devices has been development of efficient actuation and
transduction methods. Here we provide a brief overview of common techniques and describe
recent advances (see ref. 95 for a comprehensive discussion).
Optical detection, a cornerstone of microelectromechanical devices such as AFM probes,
becomes increasingly challenging to implement as the device dimensions scale below an
optical wave length. Nevertheless, devices with widths as small as 50 nm have been
measured optically through the use of optical interferometry. Measurements have been
performed both on individual devices
96,97
and on grating-based systems
98
. Recently, near-
field, non-interferometric optical transduction has been identified as a promising alter native
for arrays of nanocantilevers
99
. The latter holds Significant potential for co-integration with
on-chip light sources, because non-interferometric techniques do not require a coherent light
source. Evanescent coupling to the substrate of a propagating light field has also been used
to drive NEMS
100
.
Electrostatic detection and actuation, used ubiquitously in integrated
microelectromechanical systems (MEMS), generally lose efficiency for nanoscale devices.
Capacitance scales as area/separation but practical limits on drive–gate gaps ultimately limit
reduction of their dimensions. Given the higher frequencies of NEMS compared with
MEMS, a large fraction of the electro statically based drive and detection signals are lost
through parasitic capacitances. However, with an appropriate LC network for impedance
transformation it is possible, on resonance, to couple electrostatically through a gate
electrode to the device with reason able efficiency. This technique has been used to measure
a NEMS array with closely spaced resonance frequencies (above 10 MHz) using a single RF
circuit (Fig. 6a,b)
101
.
Termoelastic actuation has been demonstrated — through photo thermal heating in air
102
and liquid
103
, and through integrated electrothermal heating in both air
104
and liquid
105
. The
thermally induced elastic strain, a measure of stored energy density, is generally constant as
the device dimensions are uniformly scaled down. This makes thermoelastic actuation
promising for increasingly smaller NEMS devices.
Piezoelectric actuation has also been used extensively for MEMS devices in both air
106
and
liquid
30
. Advances in the quality of piezoelectric ultra-thin film (< 20 nm) materials have
recently enabled their application to NEMS
107
. An important benefit of pie zoelectric
actuation is its exceptionally small power consumption, owing to the minimal current flow
through the device — especially compared with that of thermoelastic actuation. As the piezo
electric effect itself generates voltages when the NEMS vibrates, it can be used for detection
as well as actuation. As with capacitive detection, however, direct signal transduction faces
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the challenge of relatively small-magnitude, high-frequency signals originating from high-
source impedances, in the presence of substantial parasitic capacitances.
Piezoresistive detection technique is now widely used for room temperature NEMS
applications. Devices with doped semicon ductor piezoresistive sensors have a long history
in MEMS
108–110
. However, the use of these materials in nanoscale devices is challenging
because the doped layer must remain thin compared with the total device thickness.
Requisite structures at nanoscale dimensions also require exceptionally careful processing to
avoid damage to the ultra-thin doped surface layer required. The displacement transducers
that result suffer from high Johnson noise given their relatively high impedance, and from
very high 1/f noise owing to their low carrier concentrations and small volumes
111
. Recent
work shows these difficulties become exacerbated with semiconducting transducers as their
size is scaled downwards, but can be overcome through the use of metallic piezoresistors
112
.
Future nanosystems for complex biosensing
Te ultimate mechanical biosensing systems will combine precise microfluidic sample
handling, automated and complex pre paratory protocols, and highly sensitive
nanomechanical sensing elements in multiplexed device arrays that can be readily mass-
producible by microelectronic fabrication technologies. Although most results published so
far describe measurements from one or, at most, a few biosensors, it has already been shown
that thou sands of suspended cantilevers can be fabricated to ft on a chip measuring a few
millimetres by a few millimetres (Fig. 6c). The outstanding challenges, therefore, are the
difficulty of differentially functionalizing closely packed sensors (which is a front-end issue)
and the complexity of multiplexing the electrical readout of a dense array of devices (which
is a back-end issue).
Effort is at present focused on leveraging the existing infra structure for the very large-scale
integration of silicon micro electronics (that is, complementary metal oxide semiconductor
(CMOS) devices) to facilitate the very large-scale integration of NEMS. Routes being taken
include development of a unified, monolithic NEMS–CMOS process
113
and a multilayer,
multichip, three-dimensional stacking or hybridization process for NEMS and CMOS
114
.
The IBM Millipede project demonstrates that wafer-level transfer of MEMS devices to the
surface of other wafers is both achievable and robust. This project has achieved device
densities
100 cantilevers mm
−2
and interconnect densities
300 mm
-2
. (Fig. 6d; ref. 114).
Highly multiplexed microfluidics have also been demonstrated (Fig. 6e)
115
and are leading
to a growing range of applications
116,117
. The outstanding task is the integration of complex
microfluidics and dense arrays of nanoscale biosensors.
In terms of performance for diagnostic applications, we have already discussed examples
where mechanical biosensors have reached the stage where non-specific binding and other
factors such as sensor drift — rather than the inherent device mass sensitivity — set the limit
of detection. For applications involving the detection of rare biomarkers in serum, enhancing
the limits of detection requires confronting the problem that the concentrations of the most
abundant proteins in samples are many orders of magnitude higher than those of the least
abundant targets. Pre-concentration and/or immunoaffinity depletion can help to some
extent, but the ultimate efficacy of such approaches is compromised by the tendency for
competing molecules to be concentrated along with the target of interest and/or for the target
to be depleted along with the competing molecules.
Another problem is that small, low-abundance target proteins (such as cytokines) can be
sequestered by proteins that are abundant in serum (such as albumin). Indeed it has been
shown that sequestered biomarkers may exist at concentrations that are 10–500 times greater
than that of their free counterparts
118
. Standard procedures for the depletion of albumin can
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lead to Significant depletion of cytokine
119
. Effective solutions to these issues will probably
transcend the simplest of label-free approaches — and involve slower, complex and multi-
step protocols such as high-affinity sandwich assays. For laboratory applications such as
rapid, high-throughput drug screening, however, it may be possible to work with reasonably
pure solutions where the range of concentrations is smaller. For such cases, there will
always be Significant benefit to improving the device sensitivity.
We have seen how microfluidic technology provides researchers with the capability to place
individual cells in chambers with picolitre to nanolitre scale volumes
117,120
. This
circumvents the massive dilution of samples that is inherent to conventional approaches and
can therefore maintain proteins obtained from individual cells — be it by secretion or cell
lysis — at concentrations that are readily detected with the most sensitive technologies,
represented in Fig. 1. Although secretion rates from individual cells are highly variable, and
depend on the specific molecules secreted, detection on the picomolar scale serves as an
important initial benchmark. We illustrate this with the example of native (unstimulated)
human monomyelectic cells, which secrete an average rate of
7,000 TNF-
molecules per
minute per cell
121
. For an individual cell sequestered in a volume of 1 nl, this would
correspond to a concentration increase of 40 fM min
−1
, and this rate can be increased by a
factor of
80 if the cells are stimulated. The levels of detector performance needed to
measure these processes are included in Fig. 1 as an example of an application that requires
sensitivity beyond that needed for many diagnostic assays.
Single-cell analyses also have the potential to improve our under standing of cellular
heterogeneity by exploring in detail variations in the responses of genetically identical cells
to identical stimuli
63,117
. No existing technology can perform simultaneous, real-time,
quantitative assays on large populations (arrays) of individual cells, but Fig. 1 makes it
evident that micro- and nanoscale sensors may soon make this feasible.
Critical to achieving such goals is development of new methods for functionalization,
especially approaches enabling proximal multiplexing. For example, Huber
et al.
have
demonstrated simultaneous protein and DNA detection in a single microcantilever surface-
stress sensor array
122
. Detection of numerous DNA
123
and protein
124
targets has also been
demonstrated. However, existing approaches typically employ methods (such as
functionalization in separate microcapillar-ies
123
or ink-jet spotting,
4,125
) that cannot be
reduced in size to nanos-cale dimensions or scaled upwards to make large, multiplexed
arrays with, say, thousands of elements. Photolabile crosslinkers and photo lithographic
light-directed synthesis, as in gene chips and release pro-tocols
57
, show promise for the
functionalization of arrays of devices, but the diffraction limit makes it difficult to scale this
approach down to the nanoscale. More elaborate techniques, such as scanning-probe-based
coating deposition
126
or localized electrochemical growth
127
, may prove helpful.
Many challenges remain — from the development of better capture agents (see ref. 2 for a
review) to the integration of arrays of advanced nanosensors with conventional
microelectronic fabrication techniques — but the ultimate goal of developing tools that are
capable of high-throughput studies of biological systems at the level of single cells and
individual molecules will continue to drive the field forwards.
Acknowledgments
The authors thank the Defense Advanced Research Projects Agency (HR00110610043 and N66001-08-1-2043) and
the Fondation pour la Recherche et l'Enseignement Superieur for support. M.L.R. acknowledges a Director' Pioneer
Award from the National Institutes of Health (1DP1OD006924). We also thank P. Puget for many discussions.
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