Application of Field-modulated Birefringence and

Application of Field-modulated Birefringence and Light Scattering to Biosensing Louis H. Stronga, Daniel B. Halla, Clark M. Edsona, Hiep-hoa Nguyenb, Michael A. Whittc and Gyula Varadia a

Radiation Monitoring Devices, Inc., 44 Hunt Street, Watertown, MA 02472-4699, USA, bTransMembrane Biosciences, Inc, 145 North Sierra Madre Boulevard, Suite 5 Pasadena, California 91107-3376 Pasadena CA, USA, and cDepartment of Molecular Sciences 858 Madison Ave., The University of Tennessee Health Science Center Memphis, TN 38163, USA

ABSTRACT Superparamagnetic nanoparticles (NPs) coated with surface ligands are shown to be an effective means to impart magnetic field modulation to optical signals from targeted receptor complexes. The modulated signals they produce can be used for a number of important high throughput applications in bio-sensing including: detecting (weaponized) viruses, screening recombinant libraries of proteins, identifying pathogenic conversions of microbes, and monitoring gene amplification. We compare the results of two dynamic methods of measuring target binding to NPs: birefringence and field modulated light scattering (FMLS). These measurements reflect complementary manifestations of NP alignment (orientation) and dealignment (relaxation) dynamics. Birefringence originates from the specific crystalline properties of a small subset of paramagnetic NPs (for example, maghemite) when oriented in a magnetic field. Upon quenching the field, it decays at a rate exhibiting the Debye-Stokes-Einstein rotational relaxation constant of target-NP complexes. Birefringence relaxation reflects the particle dynamics of the mixed suspension of NPs, with signal components weighted in proportion to the free and complexed NP size distributions. FMLS relaxation signals, on the other hand, originate predominately from the inherent optical anisotropy of the target complexes, show little contribution from non-complexed NPs when the targets are more optically anisotropic than the NPs, and provide a more direct and accurate method for determining target receptor concentrations. Several illustrations of the broad range of applications possible using these dynamic measurements and the kind of information to be derived from each detection modality will be discussed. Keywords: magneto-optic birefringence, field modulated light scattering, relaxometry, ferrofluid,homogeneous immunoassay, molecular diagnosis, Loop-mediated isothermal nucleic acid amplification, recombinant receptor protein assay

1. Introduction Recent interest in “label-free” biosensor development has emphasized high sensitivity detection under dynamic rather than endpoint conditions, combined with high throughput and abbreviated sample preparation. “Label free” connotes the absence of reporter groups that have to be removed before the assay is read, thus shortening the processing that must occur before the results are known. In a label-free” immunoassay, bound and unbound affinity probes are allowed to remain in the interrogated volume as the assay is processed; hence it is considered homogeneous. “Label-free” also suggests that the assay results may be analyzed in real time- the added time signature often resulting in greater assay accuracy. Examples of “labelfree” assays utilize detection schemes based on: Surface Plasmon Resonance, Isothermal Titration Calorimetry, Nuclear Magnetic Resonance, and Mass Spectrometry, for example. Recently, several groups1-5 described a double refraction detection of biological analytes using field oriented single domain maghemite nanoparticles carrying affinity probes. Using either intermittently pulsed or sinusoidally modulated magnetic fields6, these and other studies concluded that targeted receptors change the relaxation dynamics of the nanoparticles in a manner consistent with the Debye-Einstein-Stokes theory for particle rotation in a viscous fluid. However, measurement of the added mass that produces perturbations in the dynamic responses proved to be difficult to deduce from the rotational dynamics alone. It has been problematical to evaluate the time dependence of added mass and harder yet to determine affinity constants between effectors (ligands) and receptors. The difficulty lies in clearly separating time or frequency components of the signal that are due to the mass adding to the NP effectors from components of the signal representing targeting effectors not involved in binding. The ability to extrapolate quantitative added mass information from the dynamic spectra would make magneto-optic detection a very competitive technology for “label-free” biosensing because the components are cheap, the binding reactions are not confined to a stationary surface (and hence equilibria are achieved faster), and the sensitivity, based on spectral signatures, can be femtomole amounts8.

Frontiers in Biological Detection: From Nanosensors to Systems III, edited by Benjamin L. Miller, Philippe M. Fauchet, Proc. of SPIE Vol. 7888, 78880P · © 2011 SPIE · CCC code: 1605-7422/11/$18 · doi: 10.1117/12.875342

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One complication in realizing a quantitative analysis of analyte load is the fact that the nanoparticles are not usually homogeneous in size before they are grafted to their targeted receptors, and rarely, if ever, after they are grafted. This has caused some investigators to resort to various presorting schemes1,9 to make volume distributions of the premixed NPeffectors more homogeneous at the outset. Others have used curve fitting methods to describe the changes in rotational rate constants resulting from complex formation1. We here show that it is possible obtain a linear mass calibration with spectral difference curves over a limited range of added target. To access a greater target range we use inverse Laplace transformation of the temporal relaxation data to generate probability distributions for rotational rate constants, and from these the size distributions of target-NP complexes. Applying the method of Zhou and Zhuang10, we generate weight distributions of rate constants from the rotation spectra and using these, to back calculate the birefringence relaxation curves showing remarkable similarity to the original curves. The rate constant distributions are then used to generate distributions of added volume, and subsequently added mass. However, accuracy in determining the total analyte load from the relaxation rates alone is still limited, in part by the fact that the spectral inversions do not necessarily yield a unique set of rate constants and their probability densities. Another complication is the formation of multiple target complexes at high target concentrations. We describe the modification of an old detection modality with a new twist that allows the aggregate masses to be determined more directly and the analyte load more accurately. We modified the magneto-optic double refraction experiment to detect polarization dependent light scatter under field pulsing conditions. The anisotropic scattering component is shown to be time varying under field pulsing conditions with intensities that scale with number of NP-receptor complexes formed. Furthermore, the time dependence of anisotropic scattering exhibits a rotational spectrum that can be reconstructed by inverse Laplace transformation to yield a set of rate constants and spectral weights that allow independent determination of target load. The two sets of data may be combined to obtain more accurate evaluation of bound target mass. For many bioanalytes, including intact viruses, bacteria, and many macromolecules, the anisotropic scattering component from the target complex greatly exceeds that from NPs alone. We show how field modulated light scattering (FMLS) can be employed in a label-free assay to identify and quantify a broad range of targeted microbial species using affinity probes and can also be used for sequence specific detection of amplified DNA.

2. Birefringence and FMLS Signal Acquisition and Rate Data Extraction The experimental setup for birefringence and FMLS light collection optics is shown in Figure 1. Polarized light from a HeNe laser (λo = 632 nm) is launched into a sample cell after traversing a quarter wave plate. The sample cell is centered inside a pair of Helmholtz coils whose magnetic axis is orthogonal to the direction of light propagation. The direction of the polarization vector is set at 45o off the magnetic axis. After passing through the sample, the undeflected beam transits a glass polarizer into an Avalanche photodetector (APD). The polarizer and quarter wave plate are set to produce a current null from the APD when the coils are energized. Forward and side scattered light are collected at 15o and 90o respectively with variable selection of polarization direction into PMTs (Hamamatsu model 1617). The forcing field is pulsed on and off with a fast rise and fall (10 µsec). The pulse repetition rate is adjustable from 10 mHz to10 Hz and duty cycle between 20 to 50 %. Field magnitudes up to 100 gauss are achieved. Under these circumstances, the superparamagnetic NPs orient during the field on cycle, and randomize by Brownian diffusion during the off cycle.

Figure 1.

Schematic diagram of the optics setup to collect magneto-optic birefringence data together with magnetic field modulated light scatter in the forward and side directions. The NP suspension produces a birefringence phase shift ζ. Light transmitted into the forward detector is T after adjusting waveplate and analyzer.

Birefringence dynamics For the special case where the nanoparticles are at once superparamagnetic as well as birefringent or possess circular birefringence, the light passing through the sample undergoes a net phase shift that rotates the plane of polarization from its original direction by an amount

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ζ(Β) = 2 π t δn φ / λ0

(1)

where, t is the depth of the light path through the sample, δn is the change in the index of refraction per unit path length in the direction of the intercepted light, and φ is the volume fraction of nanoparticles in the sample. In the absence of a magnetic field, δn is zero for any direction, since the particles are randomly oriented. In the presence of a homogeneous magnetic field B, δn is calculated from the difference in the dielectric susceptibility (χ) along the principal crystalline axes of the nanoparticle. The easy crystalline axis b aligns along the field direction with a probability determined by the Langevin function L(µB/kT), where µ is the magnetic moment of each particle and B is the field strength. This produces a net change in the refractive index given by:

δn0 = |χelaa - χelbb | L(µB/kT) 2√ε1

(2)

where ε1 is the average dielectric constant between the principal axes values. When the magnetic field is quenched, δn returns to zero at an exponential rate given by11 δn = δn0 exp (-6 Θ t)

(3)

where

6 Θ = 1 / τ DES =

3 kB T η Vh

( 2− v 2 ) P (v ) − 1 ( 1 − v 4)

(4)

is the rotational diffusion coefficient of the target complex. Here η is the fluid viscosity, Vh the hydrodynamic volume, and ν is the ratio of the principal axes of the ellipsoidal target complex. P(ν) is a measure of ellipticity of the scattering target complex: P ( v ) = v 2 − 1 v arctan  v 2 − 1    We have normalized the birefringence data collected under different conditions to allow easy comparison of rotation rates. This is tantamount to setting 2 π t δn0 φ/λ =1 in equation (1).

FMLS dynamics Field Modulated Light Scatter can be attributed to be due to scattering from a polarization tensor that is represented by an ellipsoid of revolution (shown in Figure 2).

Figure 2.

a

b

χ

Representation of light scattering by a polarization tensor that may be oriented in a homogeneous magnetic field. The semi-minor and semi-major axes of an ellipsoid of revolution are a and b respectively and are randomly oriented before the field is switched on. The field is assumed to line up along the y axis of the coordinate system. Light possessing polarization components in the x and y directions of the stationary reference frame propagates along the z direction. Single elastic scattering events are assumed, resulting in the deflection of a ray along the wave vector ks. The scattering wave vector has an angular deviation of θ from the incident direction in the lab frame. X is the angle between the long axis of the ellipsoid and the bisector of the complementary scattering angle. Assuming that the magnetic field interaction achieves the necessary threshold to overcome cluster inertia and viscous resistance of the fluid , the b axis of the polarization tensor orients at an angle Ψ with respect to the x axis. If the field is applied for a sufficiently long time, the polarization tensor orients at an angle Ψ= 90o. This brings the long axis of the polarization tensor into coincidence with the field direction. If the field is applied for shorter duration ≠ 0, but nevertheless is well defined and distinguishable from the average direction of random orientation. When the field is quenched, the ellipsoid diffuses (by rotational and translational Brownian motion) into random orientations.

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The Stokes parameters of the outgoing wave front (scattered wave) are related to the Stokes parameters of the incoming light wave by the following equation12: I s   I in      Qs  = < N > < F > Qin  (5) U s  k 2 r 2 U in      Vs  Vin  Here is the ensemble average of the Müller Scattering Matrix, is the average number of scattering centers, k is magnitude of the light propagation vector (k=2π/λ) and r is the distance between the scatterer and detector.

 I in   Io     Qin  = 0  U in   Io     0  Vin 

In the case of incident light at 45o polarization,

When a pulsed field is on for a period sufficiently long to achieve steady state, the scattering ellipsoid orients such that the principal semi-axis lies along the field direction, i.e. = 90o . For this orientaton, the Müller scattering matrix has the elements:

 2 β2  4 + cos 2 θ ( g 2 + β 2 ) g +  9 9   I s    2   4 2  β 4V 2 2 2 2  Q < > N k s  = Io G ( ϑ ,ν , χ ) 2  − g − 9 + cos θ ( g + 9 β ) U s  2r 2   8 π 2    2  β 2 V  s   cos θ ( g − 9 )     0  where

β 2= ( α

1

(6)

− α 2 ) 2 exp(− t / τ DES ) is the square of the anisotropic polarizability scalar

that is relaxing by rotational reorientation

+ 2α 2 ) 2 exp (−q 2 D t ) 9 polarizability scalar that is undergoing translational diffusion, g

2

=

(α

1

is the square of the isotropic

= 4 ki2 sin 2 ϑ is the square of the scattering wave vector, 2 kB T D= P (v ) is the translational diffusion coefficient, 6π η r 0 q

2

and G(θ,ν,χ) is the scatter cross section from a single scattering cluster, depending on scatterer size, shape and the angle of scatter θ. If steady-state is reached at time t after the field is quenched (at t > t0=0), = 1/S2, yielding the difference Stokes vector:

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∆ I s    ∆ Qs  = ∆ U s    ∆ Vs 

( 1 + 5 cos 2ϑ )    2 1 (− 1 + 5 cos 2 θ ) k 4V 2 Io G ( ϑ ,ν , χ )  (α1 −α 2 2 4 − 4 cos θ 24 π r     0

2

)2

exp ( − t / τ DES )

(7)

In arriving at (7), we assumed that there is no translational periodicity of the ellipsoid. The intensity change depends only on the anisotropic component of the cluster polarization tensor. Two practical situations occur. Either the target receptor contains multiple binding sites allowing numerous NPs to attach to each target scaffold (this is usually the case when targets are bacteria, viruses, protists and the like); or the target receptor contains one or only a few binding sites, in which case the added volume (mass) needs to be large compared to the NP volume or somehow amplified to be observed. In the former case, the addition of nanoparticles to the target scaffold increases the anisotropic component of the net polarization tensor, and also causes the scattering to become more forwardly directed. This increases the magnitude of G(θ, ν, χ) as well retards the overall relaxation rate. The theories described by Rayleigh-Debye-Gans and Mie, modified to account for the anisotropy of the aggregate structures 13 and taking account of the intraparticle interference contributions, are needed to evaluate G(θ, ν, χ) accurately. If the target load is desired, this complexity can be avoided by a simple calibration procedure relating an observed intensity shift between the oriented and random extremes, to a titrated amount of target in the presence of a fixed concentration of NPs. In the second case, there are alternative options. If the added mass per receptor is insufficient to substantially change G(θ, ν, χ) and τDES , each NP can be loaded with multiple copies of the same ligand, making it possible to add multiple receptor targets per NP. Alternately, probes can be constructed having different affinity sites; one probe comprising NPs conjugated to one type of ligand, a second probe comprising NPs conjugated to a different ligand that binds elsewhere on the same target, and so on. This panel of affinity probes may be regarded as a set of aggregation effectors. We present below several examples in which the sensitivity and accuracy of determining target load by birefringence and FMLS detection are compared. These include: a model for detecting targeted virus, a model for detecting bacterial targets, a model for screening recombinant proteins, and a model for detecting gene amplification products in real-time.

3. Model for Virus Detection Birefringence from Streptavidin-I1 MAb conjugate Vesicular stomatitis rhabdovirus (VSV) was used as a generic model for capture, detection and identification of a number of pathogenic viruses. It is an ideal system since VSV is generally non-pathogenic to humans and can be easily propagated and harvested in high yields. Moreover, it contains a viral envelope consisting of ~400 glycoproteins (G protein) that are accessible from the surface, vary with individual virus strains, have good antibody reactivity, and can be pseudotyped which exchanges wild type glycoproteins for a large number of other envelope proteins from other viral species. VSV is bullet shaped with a diameter of about 75 nm and a length of 200 nm. This is slightly larger than the maghemite nanoparticles that have been produced to target the virus. Nanoparticle conjugates for virus capture and detection were generated from Miltenyi streptavidin maghemite nanoparticles. I1 monoclonal antibody (mAb), that targets strain specific G protein, was coupled to these using a biotinylated linker. With surface antibody specific to the envelope G protein of Indiana serotype, the targeting nanoparticles exhibited an average relaxation time by birefringence of ~ 400 µs corresponding to a diameter of 90 nm (see Figure 3). When VSV is titrated into a solution containing 1010 I1 mAb derivatized maghemite nanoparticles and the field dependent birefringence phase shift is measured (allowing 0.5 h mixing time for capture), the normalized birefringence decay exhibits an increase in apparent decay time as seen in Figure 3A. The perturbations were observed as incremental increases in the normalized phase change in the time range 0.0005-0.004 seconds after the field quench. A rate constant of ~200 sec-1 could be anticipated based on the calculated hydrodynamic volume of the VSV nanoparticle complex (Vh =6.283 E-21 m3) and (4). The lowest detectable limit (LOD) is 1,000 plaque forming units (pfu) of virus per milliliter. As the actual irradiation volume used to make these measurements was ~ 50µl, we deduce that the absolute limit of detection is LOD is ~ 50 pfu. Titrating additional virus into the mixture raises the difference between the normalized birefringence signals and the 0 VSV signal in the same time range (Figure 3A). We evaluated the differences between normalized relaxation curves and the 0 VSV curve in the relaxation interval between 0-0.060 sec. Figure 3B shows a plot of a representative difference curve between virus added and no virus added. The relative birefringence change rises to a peak in the interval between 0.5-4 msec after field quench and collapses to zero after 20 msec.

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Figure 3A. Normalized Birefringence phase shift versus the time after field quench for I1 coated, streptavidin-linked, maghemite nanoparticles mixed with varying concentrations of VSV in a cuvette of 1 cm optical path length. The smallest distinguishable [VSV] concentration by birefringence relaxation indicates an LOD of ~1,000 pfu/ml. 3B, The instantaneous differences between two relaxation curves representing (in this case) maghemite capture particles and the same concentration of maghemite capture particles plus 11,000 pfu/ml VSV. The differences are nil after 16 msec after the field quench.

The time integral of the difference curves was considered more representative of the total change occurring on binding virus than the instantaneous differences and intrinsically less noisy than the difference curves, particularly in the short time limit. Figure 4A shows a plot of the integrated differences between normalized birefringence curves, measured with respect to relaxation of the capture nanoparticles alone, for the virus addition shown in Figure 3A. The integrated differences start at the instant of field quench and rise to higher plateau values as more virus is added. A plot of the relation between the peak (value at 16 msec after pulse) integrated differences and the amount of added virus is shown in Figure 4B. The variation is reasonably linear (R2= 0.98), indicating that this method of integrating differences between the relaxation curves representing capture particles with and without added virus provides a logical solution for quantifying the virus load in a sample containing a limited amount of virus.

Figure 4A. Plot of the integrated difference curves obtained after VSV addition to the same concentration of capture particles as a function of time elapsed after field quenching. The original data were obtained from Figure 3A. Figure 4B. Plot of the ultimate integrated difference values over the time interval from 0 to 16 msec after the field quench versus added virus. A linear least squares fit to the data yielded the intercept and slope indicated in the figure.

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The subtractive analysis above is mathematically justified under limited conditions, namely when small amounts virus particles representing a relatively small band of different rotational rates are admixed with distributions of faster relaxing particles. The perturbation can then be treated as an exponential function decaying with a single average rate constant. Under these circumstances the integrals of the difference phase curves should scale linearly with the magnitude of the incremental addition. When such admixtures become a significant fraction of the starting distributions, however, or when the admixed fraction exhibits broad distributions of rate constants, the subtractive method will not work and one must find a more accurate representation to evaluate the target load.

A

Reconstruction of the Rate Constant Distribution Using the Phase Function Method

B

Zhou & Zhuang recently developed a phase function approach for separating components of mixtures in exponential decays10. We have used their approach to characterize the size distribution of capture particles as they bind to virus using both birefringence and scattering data. As an example of this analysis we use the relaxation spectra to evaluate the respective rate constants and the spectral weights for virus-nanoparticle cluster rotation using Zhou and Zhuang’s method of reconstruction. To describe relaxation of nanoparticles involved in virus capture from the birefringence data, we normalized the phase change over the interval from t=0 to a maximum value, when the signal amplitude has stabilized, (i.e. d/dt ~0). We designate the normalized value of the ensemble average phase by p(t). The relaxation curves then describe a time distribution of particle orientations, p(t); such that when p=1 the maximum number of particles are aligned with the field, and when p=0, all the particles interrogated are randomly aligned. The inverse of the particle relaxation times, ki, are the relaxation rate constants of the size heterogeneous clusters determined by their rotational relaxation times. The Debye-Stokes-Einstein equation relates the rate variable to a size variable, i.e.

C

ki

-1

= 1/τ DES,i = 6 Θ

A common way to describe the distribution of rate constants is by a different probability distribution in rotational rates, π(k), which is related to p(t) by the Laplace transform: p(t) = ∫ π(k) k e

Figure 5. Experimental (black) and reconstructed (red) spectra of normalized birefringence phase shift versus time after the field quench for three virus concentrations: A. 0 pfu/ml VSV, B. 1,100 pfu/ml VSV, and C. 5,500 pfu/ml VSV. Insets in each case show the calculated probability densities for the rate constant values that were obtained by inverse Laplace transformation of the experimental curves and used to calculate the reconstructed relaxation curves.

-kt

dk

(8)

The evaluation of the rate distribution π(k) is formally obtained from the inverse Laplace transform of p(t). To check the consistency of the calculated distributions, we wrote a program to reconstruct the experimental relaxation curves from the integral in (8), using π(t) calculated by the phase function reconstruction software provided by Professor Zhuang14. We compared the experimental relaxation spectra with the calculated spectra. Figure 5 shows the derived rate constant distributions, the temporal birefringence decays they generated, and the measured birefringence decays for the streptavidin-I1 conjugate above

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under three virus loads. Figure 5 A shows the relaxation behavior with no added virus. All particles relax with a rate constant of 1,000 sec-1 or faster, indicating a spherical diameter of 120 nm and smaller. On the addition of virus (Figure 5B), a peak centered at 180 sec-1 starts to grow in intensity with increasing amounts of virus added. The rate constant is indicative of a particle about 225 nm in diameter, the size of a single virion particle plus pendant nanoparticle attachments. As more virus is added, the peak at 180 sec-1 continues to grow, and an additional peak centered at ~20 sec-1 starts to appear. At 5500 pfu/ml (Figure 5C), the 20 sec-1 component becomes a significant spectral component. With a rate constant corresponding to a 400 nm complex, it is presumed to arise from the formation of duplex virus clusters, formed by two virions bridged by mediating NPs. As more virus is added, keeping the NP-ligand concentration constant, the cluster dimensions grow larger, while concomitantly the fraction of free NPs diminishes. Figure 6 shows how the birefringence relaxation rates decrease with added virus beyond 5,500 pfu/ml. To the extent that the spectral reconstruction is able to resolve separate frequency components, the calculated rate constants for virus clusters appear to fall into discreet bands, based on multiples of the average monomeric rate (180 sec-1). The number of virus particles within a complex is then apparently

A

B

n(k) = (kmonomer/kcomplex)

1/3

; where kmonomer = 180 sec-1. (9)

This suggests that a logical way to evaluate the approximate viral load under high viral burden is to numerically calculate the integral Load = Ν ∫ n(k) π(k) k e-kt dk

(10)

To obtain the fitted spectra, the integral in (8) is replaced by a summation over discreet values of k, each weighted by the probability π(k). To obtain viral load we use (10), setting the current value of n(k) according to (9) for each value of k as long as k < kmonomer; otherwise n(k) is zero. The normalization constant Ν accounts for the variation of birefringence phase shift with NP concentration, as well as the average number of NPs binding to the monomer target.

C

Figure 6. The relaxation of normalized birefringence phase under high virus burden with reconstructed relaxation spectra from the rate constant weights shown in the insets. Black curvemeasured spectra, Red curve -reconstructed spectra. A. 160,000 pfu/ml B. 280,000 pfu/ml C. 440,000 pfu/ml.

The multiplicity of virus particles aggregated in independently rotating clusters increases with virus addition. Figure 6 shows three representative relaxation spectra in which the largest cluster size progressively increases from n=1 to n=4 as the total viral load increases from 5,500 pfu/ml to 440,000 pfu/ml of VSV. Studies are in progress to test the accuracy of (10) in determining viral load under high target concentrations.

4. Model for Bacterial Detection FMLS by Francisella tularensis conjugates

FMLS provides an alternate method for detecting and quantifying viruses, bacteria and the like that adds more information to the birefringence relaxation spectra. We discovered that light scattering was significantly enhanced (particularly in the forward direction) by VSV during intervals of virus

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alignment, and reduced to baseline levels after the field collapsed (data not shown). In these experiments, the magnetic field was applied in the same pulse sequence as was used for birefringence relaxation and light scatter was averaged for several periods of field cycling. With maghemite nanoparticles in a field of 80 G providing the aligning magnetic torque, we determined the LOD to be 50 pfu, which is about the same sensitivity as was achieved by birefringence relaxometry. In control experiments where NPs decorated with irrelevant mAbs were mixed with the same concentrations of VSV, we observed no periodic variation of scattering from the virus complexes. Birefringence and FMLS reflect different manifestations of NP alignment and de-alignment dynamics. While birefringence phase shift originates from the total suspension of NPs (both free and complexed), FMLS derives almost entirely from the virus-NP complexes (save for the small amount of field correlated scatter produced by the uncomplexed NPs). Therefore, FMLS provides a more direct measurement of virus presence and permits calculation of viral load by a simpler path. We then performed light scatter experiments using the live vaccine strain (LVS) of Francisella tularensis (Ft) as the capture target (Figure. 7). This pathogen is a coccobacillus (very short rod shaped) and is considerably larger than VSV. Consequently, Ft is expected to exhibit a slower rotational relaxation rate constant. We found that we could achieve an LOD of 2.0. Both birefringence and Light Scattering indicate similar rotational relaxation time (~15 msec) for the NP-product complexes.

turbidity changes with time because it is totally dependent on achieving loop sequence complementarity to the NP probe. The ability to perform a real-time measurement gives the capacity to run the reaction for as long as necessary to obtain definitive results. Quantitation of product may then be based on cumulative time points during the exponential product growth curve, assuring greater accuracy in extrapolating viral load. In the case of HIV-1, we have shown that scattering intensity is a linear function of product generated. Furthermore, the intensity difference attributable to scattering from fully aligned and randomly oriented, double-stranded, LAMP cauliflower structured products increases exponentially with reaction

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time, so the equivalent of a threshold reaction cycle can be defined as is done in RT-PCR. It appears, therefore, that compared to birefringence relaxometry, FMLS should provide the easier path to quantitatively determining viral load. We will see if this hypothesis holds up.

7. Conclusions Four illustrations were presented showing how relaxometry could be used to obtain “label-free” and real-time assay readout of biological targets. All assays could be conducted in the suspension phase without having to wash out unbound label or remove artifact impurities that co-purified with the samples. Because all reagents are soluble or colloidally stable, mixing is accelerated and measurements can be made during the course of the assay rather than just at the endpoint. This feature often translates to more accurate quantification of target such as is found to be true for RT-PCR vs PCR by itself. Our relaxometry measurements involved optical detection of NP-target complexes by both birefringence phase shift and anisotropic light scattering. Between these, birefringence provides the stronger signal, but is complicated by predominating contributions from unbound probe particles. FMLS, though weaker, is predominated by contributions from the complexes formed between targets and the NP probes. Since both modalities rely on the ability to differentiate the target complex by size or mass, it is necessary to design the NP probes to a fall within a volume dimension considerably different than that of the target. Here the choices of superparamagnetic or paramagnetic NPs one can use are considerably wider for FMLS detection than for birefringence, and hence the range of possible targets is also broader. We have used the theory of Zhou and Zhuang10 to see how relaxation signals can be inverted to determine target loads. As there is some degree of arbitrariness in the normalization of spectral weights given to particular rate constant components, (inverse Laplace transformation does not usually render unique spectral decompositions), the accuracy of measuring target concentrations by relaxation rate changes alone is limited. The spectral reconstructions do, however, lend important information about the quality of data from the assay and whether a positive finding is justified based upon derived target size. This serves as a kind of positive control over assay results. The linear scaling of FMLS intensity with target concentration, however, in combination with derived rate constants, does afford greater quantitative accuracy for measuring target load. Acknowledgements. This work has been partially supported by grants from the National Institutes of Health (5R44ES12515-03 and 1RR43 025724-01).

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