Published online 21 May 2007 Nucleic Acids Research, 2007, Vol. 35, No. 10 e76doi:10.1093/nar/gkm113

Tentacle probes: eliminating false positives withoutsacrificing sensitivityBrent C. Satterfield1,2, Jay A.A. West2,* and Michael R. Caplan1

1Harrington Department of Bioengineering, Arizona State University Tempe, AZ, USA and2Arcxis Biotechnologies, Pleasanton CA, USA

Received January 10, 2007; Revised February 7, 2007; Accepted February 8, 2007

ABSTRACT

The majority of efforts to increase specificity orsensitivity in biosensors result in trade-offs withlittle to no gain in overall accuracy. This is because abiosensor cannot be more accurate than the affinityinteraction it is based on. Accordingly, we havedeveloped a new class of reagents based onmathematical principles of cooperativity to enhancethe accuracy of the affinity interaction. Tentacleprobes (TPs) have a hairpin structure similar tomolecular beacons (MBs) for enhanced specificity,but are modified by the addition of a capture probefor increased kinetics and affinity. They producekinetic rate constants up to 200-fold faster than MBwith corresponding stem strengths. Concentration-independent specificity was observed with no falsepositives at up to 1mM concentrations of variantanalyte. In contrast, MBs were concentrationdependent and experienced false positives above3.88 mM of variant analyte. The fast kinetics of thislabel-free reagent may prove important for extrac-tion efficiency, hence sensitivity and detectiontime, in microfluidic assays. The concentration-independent specificity of TPs may prove extremelyuseful in assays where starting concentrations andpurities are unknown as would be the case inbioterror or clinical point of care diagnostics.

INTRODUCTION

Field-deployable biosensors require more rapid andsensitive, single-step identification methods. However,efforts to enhance assay rapidity, sensitivity and simplicitycan result in an increase in false positives or in falsenegatives (1). Such false positives and negatives can haveimmense impact in biosensing for medical and biowarfareapplications as even rare occurrences can have disastrousconsequences. A paradigm shift in understanding and

designing for the specificity–sensitivity trade-off isabsolutely essential to developing field-deployable biosen-sors experiencing few to no false positives and negatives.Molecular beacons (MBs) are one probe methodology

used to move towards more rapid, single-step genomicsensors (2,3). A fluorescent label is attached to one end ofa polynucleotide and a quencher is attached to the other.Complementary base-pairs near the label and quenchercause a hairpin-like structure, placing the fluorophore andquencher in proximity. This hairpin opens in the presenceof the target producing an increase in fluorescence.The proximity of the quencher to the fluorophore canresult in reductions of fluorescent intensity of up to 98%(4). The perceived efficiency can further be adjustedby altering the stem strength (length of the stem) whichaffects the number of beacons in the open state in theabsence of the target. Accordingly, one trade-off a MBexperiences is with regard to its stem strength, lowstrength limits fluorescent increase upon hybridizationwhereas high strength limits kinetics of hybridization (5).Regardless of the detection platform or strategy,

the majority of biosensors incorporate molecular recogni-tion through a biological affinity interaction. A biosensorcannot be more accurate than this interaction (6). Thisinteraction is used for one or more functions that includeidentifying the presence of a given analyte, determiningchanges in expression level and quantifying the agent (7).Specificity and sensitivity in biosensor research oftenrefer to the ability of the sensor to eliminate false positivesand negatives respectively for one or more of theforegoing objectives. Unfortunately, there is usually atrade-off between specificity and sensitivity (7,8) as shownin Figure 1.In support of the limitations in improving biosensor

accuracy, the numbers tell a compelling story. By wayof identification of the presence of specific species,Peplies et al. tested six strains of bacteria with a 1% rateof false positives and 41% rate of false negatives (9).Diagnostic PCR, although rarely having false-negativesowing to its extreme sensitivity, experiences areported rate of false-positives between 9 and 57% (10).

*To whom correspondence should be addressed. Tel: þ1-925-461-1300; Fax: þ1-925-265-9000; Email: jwest@arcxis.com

� 2007 The Author(s)

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/

by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Detectors monitoring expression level are worse having a10–30% false negative rate for samples above thesensitivity threshold and a false positive rate of 10%(11). While this rate of false positives and negatives maybe damaging for phenotypic or other biological explora-tion, even one error can prove lethal in clinical diagnosticsand could result in loss of life (false negative) or economicharm (false positive) in homeland security applications.In order to overcome the deficiency with these reagents

and assays, we have developed a new class of reagentthat performs with heightened affinity and with greaterselectivity compared to single oligomer reagents.We adapted the principles of cooperativity abundantlydescribed in cell targeting (12–16) to combat thespecificity–sensitivity trade-off. Cooperativity has alreadybeen shown to enhance SNP detection and assaysensitivity (17,18). Here, we combine principles ofcooperativity with a label-free hairpin in what weterm tentacle probes (TPs). We discuss the effects ofcooperativity on sensitivity, specificity and kinetics,demonstrating an increase in each without sacrificing theothers. These faster, more sensitive and more specificprobes may offer a number of advantages in many of thediagnostic applications where MBs have already beenapplied.In this study, we derive a mathematical model

predicting the cooperative behavior of TPs. We testtheoretical descriptions of increased kinetics and specifi-city over MBs and demonstrate these results withouta loss in sensitivity. By so doing, we introduce the firstclass of reagents to our knowledge to be originated as amathematical solution to problems associated withmolecular recognition in biosensors.

MATERIALS AND METHODS

Oligonucleotide synthesis

MBs, TPs and target sequences were synthesized andpurified through dual HPLC by Biosearch Technologies(Novato, CA). MBs were made with stem lengths fromfive to nine bases. Analogous TPs were created byattaching a capture region to the hairpin via a poly-ethylene glycol (PEG) sequence (9 mer). This requiredmodifying the 50 dye in the MB to be an internal dyeattached to an inert base. In order to demonstrate that thePEG linker and internally modified dye were not thesource of difference between TPs and MBs, the MBs weremodified at their 50 end to include a PEG linker attachedto an internally modified dye identical to that used in thecooperative probes.

Four target sequences were synthesized representing thewild-type target (WT), a single nucleotide polymorphism(SNP) in the capture region of the TP (SNPcap), a SNP inthe detection region (SNPdet) and a SNP in both regions(SNPboth). All probes and target sequences were sus-pended in TE buffer (10mM Tris-HCl, 1mM EDTA, pH7.0) with 0.18M NaCl and 0.1% SDS and are summarizedin Table 1.

Kinetics

Kinetics were measured on a Victor2 plate reader (PerkinElmer) at room temperature. Due to the rapidity of the TPreactions, low concentrations were used and samples hadto be run individually. For the TPs, 20 ml of each probe(100 nM) was inserted into the plate. Here, 20 ml of anexcess of target (1 mM) was quickly (55 s) added to eachwell and the measurements were started. Ninety-nine

Figure 1. These isotherms show the results of typical methods of altering sensitivity/specificity. The y-axis shows the fraction of probes bound andthe x-axis shows the analyte concentration. The intersection of the noise level (horizontal lines in both graphs) and the fraction bound is theapproximate location of the detection limit. Multiple curves are present representing fraction of specific and nonspecific analyte bound. (A) showsthat increasing the signal-to-noise ratio may increase sensitivity as it is the focus of many instrument designers, but at the expense of specificity.Decreasing the signal-to-noise ratio has the opposite effect. (B) shows an increase in specificity by lowering affinity as it is often done by increasingtemperatures or lowering salt concentrations causes losses in sensitivity. Increasing the affinity causes an increase in sensitivity at the loss ofspecificity. The absolute accuracy of the assay is not changed in either case, as indicated by the ratio of detection limits.

e76 Nucleic Acids Research, 2007, Vol. 35, No. 10 PAGE 2 OF 11

measurements were taken over 10min. The experimentwas repeated three times. MB kinetics were measuredidentically except 10 mM target was used and fluorescencewas monitored over 1 h.

Fluorescent data was plotted against time and the rateconstants were fit using the kinetic equation for poly-nucleotide reactions in an excess of target by minimizingthe sum of square errors. The rate constants from each ofthree trials were averaged and plotted against stemstrength with 95% confidence intervals.

F ¼ Fmax 1� eð�kfTÞt� �

ð1Þ

where F is fluorescence, Fmax is the maximumfluorescence achieved at equilibrium, kf is the effectiveforward rate constant, T is the target concentration andt is time.

Selecting optimal probes

Melting curves of each TP and MB were generated foreach target type on a Stratagene Mx4000 plate reader.Here, 20 ml of solutions with final probe concentration of50 nM and target concentrations of 50 nM, 500 nM, 5 mMand 50 mM were prepared. Fluorescence was monitoredfrom 90 to 158C at the end of a 15-min incubation periodfollowing each 18C increment. The experiment was alsorepeated from 15 to 908C. All melting curve resultspresented came from this set of experiments.

The fluorescence ratio of specific (WT) to nonspecific(SNPdet) targets was calculated for the 50-nM target

concentration and plotted versus temperature. The TP andMB with the largest peaks were selected as the optimumprobes after verifying first that their kinetic rate constantswere each above 1000M�1 s�1.

Fitting melting curves

Melting curves were fit to an adaptation of models usedby others in describing MB thermodynamics (19,20).These models were enhanced by the addition of acooperative stem and the possibility of more configura-tions (Figure 2). Cooperative models are derivedfrom collision theory, where the rate of the first bindingevent is proportional to the product of the reagentconcentrations:

pr � v � p � R2� �

� P � T ¼ kf � P � T ð2Þ

where pr is the probability of reaction, v is the averagevelocity, R is the sum of the radii of the two molecules, Pis the probe concentration, T is the target concentrationand kf is the association rate constant. The second bindingevent follows the same model, but with an enhanced localprobe concentration, PL¼ 1 molecule/(volume swept outby linker length�Avogadro’s number), reacting with thenewly formed complex, C, and with an adjusted coopera-tive reaction probability, pr, coop, reflecting enthalpic andentropic penalties:

pr, coop � v � p � R2� �

� PL � C ¼ kf, coop � PL � C ð3Þ

Table 1. The abbreviated terms for each probe and target sequence

Name Sequence

Tentacle ProbesTp 5 GAT TAA AAT GTC CAG TGT ACC AG - PEG 9mer - CF560 - c TGG CGG AAA AGC TAA TAT AGT AA gccaga - BHQ1Tp 6 GAT TAA AAT GTC CAG TGT ACC AG - PEG 9mer - CF560 - c TGG CGG AAA AGC TAA TAT AGT AA cgccaga -

BHQ1Tp 7 GAT TAA AAT GTC CAG TGT ACC AG - PEG 9mer - CF560 - c TGG CGG AAA AGC TAA TAT AGT AA ccgccaga -

BHQ1Tp 8 GAT TAA AAT GTC CAG TGT ACC AG - PEG 9mer - CF560 - cc TGG CGG AAA AGC TAA TAT AGT AA ccgccagga -

BHQ1Tp 9 GAT TAA AAT GTC CAG TGT ACC AG - PEG 9mer - CF560 - ccc TGG CGG AAA AGC TAA TAT AGT AA ccgccaggga -

BHQ1Molecular BeaconsMB 5 PEG 9 mer - CF560 - c TGG CGG AAA AGC TAA TAT AGT AA gccaga - BHQ1MB 6 PEG 9 mer - CF560 - c TGG CGG AAA AGC TAA TAT AGT AA cgccaga - BHQ1MB 7 PEG 9mer - CF560 - c TGG CGG AAA AGC TAA TAT AGT AA ccgccaga - BHQ1MB 8 PEG 9mer - CF650 - cc TGG CGG AAA AGC TAA TAT AGT AA ccgccagga - BHQ1MB 9 PEG 9mer - CF560 - ccc TGG CGG AAA AGC TAA TAT AGT AA ccgccaggga - BHQ1TargetsWT ATT ATT ACT TTA CTA TAT TAG CTT TTC CGC CAT CTA AAA TTC TAT TTT CTG GTA CAC TGG ACA TTT TAA

TCA ATG TAT TCSNPcap ATT ATT ACT TTA CTA TAT TAG CTT TTC CGC CAT CTA AAA TTC TAT TTT CTG GAT CAC TGG ATA TTT TAA

TCA ATG TAT TCSNPdet ATT ATT ACT TTA CTA TAT TAT CTT TTC CGC CAT CTA AAA TTC TAT TTT CTG GTA CAC TGG ACA TTT TAA

TCA ATG TAT TCSNPboth ATT ATT ACT TTA CTA TAT TAT CTT TTC CGC CAT CTA AAA TTC TAT TTT CTG GTA CAC TGG ATA TTT TAA

TCA ATG TAT TC

The numbers in the names represent the number of bases in the stem. TP, MB, CF560, BHQ1, WT, SNPcap, SNPdet, SNPboth stand for tentacleprobes, molecular beacons, Cal-fluor 560 fluorescent dye, Black Hole Quencher-1, wild type, SNP in the capture region SNP in the detection regionand SNP in both regions respectively. Lower case bases in the probes represent bases added to help form the stem. Italics in the target representcomplementary regions to the probes and bold letters are SNPs.

PAGE 3 OF 11 Nucleic Acids Research, 2007, Vol. 35, No. 10 e76

Assuming no cross-reactions, the following equilibriumconstants for TPs can be derived:

Kdet ¼Cdet

PTð4Þ

Kcap ¼Ccap

PTð5Þ

PLFpenKdetKcap ¼Cboth

PTð6Þ

Keff ¼ Kdet þ Kcap þ PLFpenKdetKcap ¼Ccap þ Cdet þ Cboth

PTð7Þ

where K is the equilibrium constant, with added sub-scripts, cap, det, both and eff, referring to capture probe,detection probe, both capture and detection probes,and effective, respectively, P¼P0�Ccap�Cdet�Cboth,T¼T0�Ccap�Cdet�Cboth, where P0 and T0 are initialprobe and target concentrations respectively, Fpen refers tothe collective enthalpic and entropic penalties(Fpen¼ e(��Hpen/Tþ�Spen)/R), and all other variables areas previously defined.Fluorescence as a function of temperature can be

adapted from models for MBs (19,20) by:

F ¼ �Cdet þ Cbothð Þ

P0þ �

Ccap, cl þ Pcl

� �P0

þ �Ccap, op þ Pop

� �P0

ð8Þ

where F is fluorescence as a function of temperature.Alpha, beta and gamma refer to characteristic fluores-cence of bound probes, closed probes (subscript cl) andrandom coil probes (subscript op) respectively.

For T0�P0, which eliminates calculation of quadratics:

F¼ �KdetþPLFpenKdetKcap

Keff

T0Keff

1þT0Keff

� �

þ� 1�KdetþPLFpenKdetKcap

Keff

T0Keff

1þT0Keff

� �� �

�1

1þKstemþ� 1�

KdetþPLFpenKdetKcap

Keff

T0Keff

1þT0Keff

� �� �

�Kstem

1þKstemð9Þ

Kstem is fit first by measuring fluorescence as a function oftemperature for beacons with no target and minimizingsum of square errors as performed by Bonnet et al. andTsourkas et al. (19,20):

F ¼ �1

1þ Kstemþ �

Kstem

1þ Kstemð10Þ

Next Kdet is fit on probes with no capture probe (e.g. onan MB):

F ¼ �T0Kdet

1þ T0Kdet

� �þ � 1�

T0Kdet

1þ T0Kdet

� �� �1

1þ Kstem

þ � 1�T0Kdet

1þ T0Kdet

� �� �Kstem

1þ Kstemð11Þ

The thermodynamic parameters necessary for calculatingKcap were estimated with Mfold (21) for 0.18M NaCl(about the same sodium concentration as 1�SSC). Usingthe Mfold estimates provided, theoretical curves thatdiverged at �618C for differing concentrations of targetwith TP 5, while adjusting the predicted entropy from�0.4989 to �0.494 kcalmol�1K�1 moved the divergenceto �658C forming a more accurate visual fit to the data.Therefore the latter value was used for all remaining tests.Finally, Fpen was fit to the fluorescent curves of threedifferent dilutions of target mixed with TPs using theoriginal equation. All parameters necessary for calcula-tions are summarized in Table 2.

The best fit enthalpies and entropies were used tocalculate the equilibrium constants which in turn wereused to calculate the amount of analyte bound to thedetection probe and producing fluorescence as a functionof temperature in an excess of target for MBs for specific(subscript s) and nonspecific (subscript ns) analyte:

Cs

P0¼

Kdet, s � T0

1þ Kdet, s � T0ð12Þ

Cns

P0¼

Kdet, ns � T0

1þ Kdet, ns � T0ð13Þ

Figure 2. Tentacle probes function similarly to molecular beaconsexcept the presence of a capture region allows additional pathways. Inthe lower left, the probe (P) and target (T) can interact forming ahybrid with either the detection probe (Cdet) or the capture probe(Ccap). Once the first binding event occurs, a second binding event canoccur at a much accelerated rate over the free solution rate due to theenhanced local concentration, forming a hybrid with both detectionprobes (Cboth). The equilibrium constants together with effectiveequilibrium constants for each state are shown between the statesand are as defined in Equations (4)–(7).

e76 Nucleic Acids Research, 2007, Vol. 35, No. 10 PAGE 4 OF 11

And for TP:

Cs

P0¼

Kdet, s þ PLFpen, sKdet, sKcap, s

� �� T0

1þ Keff, s � T0ð14Þ

Cns

P0¼

Kdet, ns þ PLFpen, nsKdet, nsKcap, ns

� �� T0

1þ Keff, ns � T0ð15Þ

These equations were then matched with normalizedfluorescent data in order to verify accuracy of thermo-dynamic parameters in predictions at the lowest detectablebinding levels and to identify trends in binding below thelevel of detection. Thermodynamic values provided frombest fits often fit high-level binding tightly at the expenseof fitting low-level binding data due to inequalities arisingfrom the sum of square errors. A manual adjustment tothe best fit (e.g. �0.6 kcalmol�1 for enthalpy and�0.0016 kcalmol�1K�1 for entropy) provided a fit thatmore thoroughly represented both high and low bindingdata. Once the parameters provided a perfect visual fit tolow-level binding as well as high-level binding, they werekept constant in order to make predictions.

Specificity and sensitivity

The Stratagene Mx4000 plate reader was used to read thefluorescence of 1-mM nine-base stem TP and 1-mM five-base stem MB (both probes chosen as described inSelecting Optimal Probes) in WT and SNPdet targets atconcentrations of 0, 2, 10, 20, 100 nM, 1 and 10 mM.Higher concentrations of 100 mM and 1mM SNPdet werealso used where detection limits had not yet beenestablished. Fluorescence was read at equilibrium forboth probe types. The reading was performed at 608C forthe TP and 558C for the MB. Three replicates of each typewere performed.

The predicted binding curves as a function of targetconcentration were generated using best fit thermody-namic parameters for MBs:

Cdet

P0¼

P0þT0þð1=KdetÞð Þ�

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiP0þT0þð1=KdetÞð Þ

2�4P0T0

q2P0

ð16Þ

And for TP:

CdetþCboth

P0

¼P0þT0þð1=KeffÞð Þ�

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiP0þT0þð1=KeffÞð Þ

2�4P0T0

q2P0

24

35

�KdetþPLFpenKdetKcap

Keffð17Þ

These predictions were compared to experimental dataplotted with 95% confidence intervals. Before plotting,data was normalized by subtracting the backgroundfluorescence measured at 0 nM target concentration anddividing by the maximum intensity experienced at 100 mMWT target at room temperature. The background fluores-cence level plotted was the average plus one standarddeviation of the signals of experiments run below andincluding the highest concentration that could not bestatistically confirmed as having fluorescence greater thanthe preceding concentrations (t-test, P40.05).The detection limits were determined as the analyte

concentration at which the theoretical binding curveintersected with the background fluorescence level andwere validated by experimental data. The ratio of detectionlimits was also calculated. Accordingly, the ratio ofdetection limits can be viewed as a measure of diagnosticaccuracy, giving the total range of concentrations overwhich an assay is expected to achieve 100% true positivesand negatives. Throughout this article, this ratio is referredto as the molecular or absolute accuracy of an assay.

RESULTS

Kinetics

TPs have measured rate constants ranging from 100 to200 times larger than their MB counterparts (Figure 3).In comparison with literature, the TP rates are severaltimes faster than those reported for standard linear DNA-probe-binding kinetics and stand in contrast to the MBrates which are slightly slower than literature values (20).The faster rates of TP over linear probes can be explainedby the presence of two probes, a capture and a detection

Table 2. Parameters used in theoretical calculations and source of values

Table of parameters

Fitted parameteres Known parameters

a Equal to greatest fluorescence in presence of target P0 Initial probe concentrationb Equal to lowest fluorescence in absence of target T0 Initial target concentrationg Equal to greatest fluorescence when hairpin melts�Hstem Fit to probes with no target�Sstem Fit to probes with no target�Hdet Fit to molecular beacons with target Estimated parameters�Sdet Fit to molecular beacons with target PL Calculated from linker length�Hpen Fit to tentacle probes with target �Hcap Estimated by Mfold�Spen Fit to tentacle probes with target �Scap Estimated by Mfold

PAGE 5 OF 11 Nucleic Acids Research, 2007, Vol. 35, No. 10 e76

probe, providing for increased probability of reaction. Inaddition, these probes are longer than the linear probesused by Tsourkas et al. (20). The MB’s slower reactionthan what was reported in literature can be explained bytheir longer stems and the fact that the reactions weremonitored at room temperature instead of 378C. Althoughmolecular beacons are not expected to perform well atroom temperature, this setting was selected to bettercontrast TPs with MBs. The rate constants indicate thatTPs react in�1% of the time that MBs with the same stemstrength require. The room temperature rates of TPs arestill410-fold faster than those reported by Tsourkas et al.using MBs with short stems and higher reaction tempera-tures (20).

Fitting melting curves

Melting curves were used to extract thermodynamicconstants (Figure 4, Table 3). As was expected, theenthalpy of the stem increased with stem length, whereasthe enthalpy of the hybridization reaction decreased. Theenthalpic and entropic penalties also decreased withincreasing stem strength, as did the kinetic rate constants.The only unexpected finding was that for the shorter stems(five and six bases), the stem melting temperature variedgreatly between TP and MB. Since these two probe typeswere constructed identically including choice of dyes andeven the attachment of a PEG linker, the only otherexplanation for this difference in melting temperatures

appeared to be that the proximity of the capture probeallowed for some interaction with the stem-loop structure.

Tsourkas et al. have performed the most extensive workon thermodynamics in MBs (20). Their data for MBenthalpies of reaction ranged from �80 to�221 kcalmol�1 and entropies of reaction ranged from�0.21 to �0.61 kcalmol�1K�1. While these numbersappear similar to what was recorded in our experiments,it should be noted that our beacons were larger, whichshould produce larger enthalpies, and had stronger stems,which should result in lower net enthalpies for probe–target interactions. Therefore a direct comparison cannotbe made. However, we feel confident in the accuracy of thethermodynamic parameters recorded inasmuch as addingthe energetic losses due to the stem to the probe enthalpy(��Hstemþ�Hdet) produces consistent values near thepredicted enthalpies for binding to linear probes of�175.3 kcalmol�1 and similarly for the predicted entro-pies of �0.4936 kcalmol�1K�1 (21).

The capture probe parameters were calculated onMfold. The predicted enthalpy and entropy of reactionwere �175.8 kcalmol�1 and �0.4989 kcalmol�1K�1,respectively (21). It should be noted that the designcriterion for both the detection probe and capture probeaffinities was a melting temperature 108C above thedesired reaction temperature. The optimal TP stemstrength was designed to have a melting temperature308C above the reaction temperature. In practice, in orderto achieve specificity, we had to increase the reactiontemperature such that the predicted melting temperaturesfor the detection and capture probes were 58C below thereaction temperature, whereas the predicted stem meltingtemperature was only 158C above the reactiontemperature.

Once the parameters were fitted, they could be used tocalculate binding curves and be double checked foraccuracy by comparing theoretical curves against normal-ized data in a semi-log plot (Figure 5). These predictionsreveal a slightly different binding pattern for TP than forMB. TP exhibit a slight bend in the binding curves �708C.This is mathematically due to the melting of the captureprobe, causing an instant loss in the cooperative interac-tion and consequent signal.

Figure 3. Rate constants are shown for TP (dark bars) and MB (lightbars) for each stem strength with 95% confidence intervals.

Figure 4. Example of fitted melting curves. (A) shows MB (50 nM probe with seven-base stem in 500 nM SNP target) and (B) shows TP (50 nMprobe with eight-base stem in 5mM wild type target) fitted curves with data (squares with target, triangles probe only).

e76 Nucleic Acids Research, 2007, Vol. 35, No. 10 PAGE 6 OF 11

Selecting optimal probes

Optimal candidates were selected by looking at the specificto nonspecific signal ratio for each stem at 50 nM probeand target concentrations (data not shown). The optimalcandidates were then verified with the kinetic results inorder to assure that the kinetics were ideal as well. SinceTP 9 had the greatest signal differentiation and its kineticswere still much faster than the fastest MB, it was selectedas the optimal TP. MB 5 was the fastest and most selectiveof the MBs, so it was chosen as the best MB.

Application in SNP detection

Negligible differences exist between the melting curves ofWT and SNPcap and between SNPdet and SNPboth forboth the TP and MB (Figure 6, data not shown for MB).This is most likely due to the relatively high affinity of thecapture probes. By utilizing a capture probe which doesnot respond to SNPs, the location of a SNP can bepinpointed to the region of the detection probe. However,if greater selectivity is required, it may be possible todesign the capture probe to respond to SNPs by reducingthe probe length. This also indicates that the design of thecapture region is probably not as significant as the choiceof the detection probe.

Because of the cooperative interaction of TP, theirmelting curves do not change significantly over a widerange of concentrations (Figure 7). A reaction tempera-ture can be chosen for TPs (vertical line in Figure 7A) suchthat there is 100% accuracy in SNP determination basedmerely on whether or not a signal is detected. This wouldbe ideal for real-time PCR in SNP discrimination.

Table 3. Enthalpies and entropies for beacon stems, capture probes and detection probes in addition to kinetic data for the wild-type target

Name �Hstem �Sstem �Hdet �Sdet �Hcap �Scap �Hpen �Spen Rate

MB 5 �70.03 �0.2030 �93.43 �0.2596 NA NA NA NA 1000.1MB 6 �72.20 �0.2070 �85.44 �0.2373 NA NA NA NA 562.4MB 7 �76.13 �0.2161 �83.27 �0.2323 NA NA NA NA 362.4MB 8 �84.60 �0.2392 �76.56 �0.2118 NA NA NA NA 219.3MB 9 �93.91 �0.2639 �70.26 �0.1947 NA NA NA NA 205.0TP 5 �56.59 �0.1654 �93.43 �0.2596 �175.80 �0.4940 69.32 0.1993 96 233.9TP 6 �62.42 �0.1804 �85.44 �0.2373 �175.80 �0.4940 67.49 0.1948 79 300.5TP 7 �76.69 �0.2188 �83.27 �0.2323 �175.80 �0.4940 57.28 0.1657 72 428.2TP 8 �78.78 �0.2237 �76.56 �0.2118 �175.80 �0.4940 52.33 0.1500 58 422.9TP 9 �91.02 �0.2568 �70.26 �0.1947 �175.80 �0.4940 39.79 0.1129 55 861.1

Units are in kcalmol�1 for enthalpic parameters, kcalmol�1K�1 for entropic values and in M�1 s�1 for rate constants. TP detection probes wereassumed to have the same thermodynamic parameters as the molecular beacons. Sign convention is for hairpin closing then binding with target.

Figure 5. Log plot of the fraction of probes bound by wild type (filled squares) and SNP targets (open triangles) in 1 mM concentrations as a functionof temperature. Fitted curves are also displayed for wild type (solid line) and SNP containing analyte (dashed line). (A) shows molecular beaconbinding and (B) shows tentacle probe binding.

Figure 6. Melting curves for 50 nM TP 9 with 500 nM of eachtarget type.

PAGE 7 OF 11 Nucleic Acids Research, 2007, Vol. 35, No. 10 e76

Additional mismatches, such as are common in organismdetection, should allow for greater resolution. In contrast,the melting temperatures of MB change with concentra-tion making it difficult to find a reaction temperaturewhich allows for discrimination over a wide range ofconcentrations.

Specificity and sensitivity

We performed an experiment at the optimum SNPresolution temperatures for both TP (608C) and MB(558C). Theoretical predictions were graphed alongsidethe experimental results for binding as a function of targetconcentration (Figure 8). The theoretical predictionsappeared to describe experimental data well. TP isothermsreveal wild-type detection limit of 15.4 nM and no SNPdetection at concentrations tested up to 1mM. The modelpredictions indicate that binding to mutant targetspossessing a SNP will never be sufficient to cause asignal above the background resulting in false positivesregardless of how high the concentration is. In contrast,

mutant targets resulted in false-positive signals for MB atconcentrations above 3.88mM, 154 times greater than thedetection limit for the wild-type target of 22.7 nM. Theratio of specific to nonspecific detection limits for the TPwas tested in excess of 53 200 and is predicted to increaseindefinitely. In contrast with Figure 1, TP specificity wasimproved without sacrificing sensitivity.

DISCUSSION

Due to the thermodynamic principles that governmolecular interactions, it is extremely difficult to developan assay that increases specificity without sacrificingsensitivity. Likewise, sensitivity is not easily increasedwithout a loss in specificity. We have developed a newclass of reagents that does not improve specificity orsensitivity via a trade-off, but that improves overall assayaccuracy as indicated by the ratio of detection limits byutilizing cooperativity.

Figure 8. Isotherms of wild-type binding (solid diamonds) and SNP binding (open triangles) as a function of target concentration performed at 608C(TP, Figure 8A) and 558C (MB, Figure 8B). Theoretical predictions (solid line—WT, dashed line—SNP) are produced from thermodynamicconstants extracted from melting curves and are plotted against experimental data. The 95% confidence intervals are shown for each data point butare not visible on higher binding values because of the log axis. Lower confidence intervals do not appear on some data points because they includezero. The horizontal line is the detection threshold set at one standard deviation over background and shows that even with this sensitive threshold,SNPs do not cause false positives for tentacle probes even at millimolar concentrations.

Figure 7. Melting curves for 50 nM TP 9 (A) and 50 nM MB 5 (B) for WT and SNPdet analyte concentrations from 50 nM to 50 mM.

e76 Nucleic Acids Research, 2007, Vol. 35, No. 10 PAGE 8 OF 11

The difficulty in increasing sensitivity or specificitywithout sacrificing the other lies in the fact that efforts toaddress assay performance are often directed at instru-mentation and buffers. For example, the temperature israised to increase specificity or lowered to increasesensitivity. Salt concentrations are raised and lowered tooptimize binding. Detection volumes are decreased andfilter sets are optimized to increase sensitivity (22,23).However none of these methods addresses the funda-mental issue of how affinity reagents recognize and bindan analyte. Altering instrumentation does not affectthermodynamic parameters governing binding and thusonly affects the threshold of detection. Altering thethreshold merely results in a sensitivity–specificity trade-off as demonstrated by receiver operating curve analysis(1). Raising the temperature or decreasing salt concentra-tions lowers the equilibrium constant for both specific andnonspecific binding, leading to greater specificity at theexpense of sensitivity. Likewise decreasing the temperatureor increasing salt concentrations increases the equilibriumconstant for specific and nonspecific binding, resulting inincreased sensitivity at the expense of specificity. None ofthese methods decreases the nonspecific equilibriumconstant while maintaining or increasing the specificequilibrium constant. Accordingly, trade-offs in specificityand sensitivity can be achieved but the ability of theaffinity reagent to discriminate between specific andnonspecific targets remains largely unchanged.

TPs represent a novel innovation inasmuch as they aremathematically engineered to manipulate thermodynamicprinciples that govern affinity reagent recognition of abiomolecule. Collision theory dictates that a secondbinding event from a molecule already bound to asubstrate and held at an enhanced local concentrationwill typically occur at a faster rate than it would in freesolution. This principle was used to develop mathematicalmodels that predicted both enhanced kinetics andspecificity of cooperative probes. For a homovalentprobe pair with no penalty term, the effective equilibriumconstant reduces to Keff¼Keq(2þPL �Keq), which isidentical to antibody theory as originally derived byCrothers and Metzger (24) and as embodied by Kaufmanand Jain (25). Others have also used this approximationfor modeling bivalent interactions and have experimen-tally confirmed its accuracy (26–29). However, we are thefirst to our knowledge to use this model to examine thespecificity–sensitivity trade-off in biosensors. These deri-vations of the equilibrium constant apply a differentapproach from that which has already been done formultivalent systems (16,25,30,31). However, the resultconfirms thermodynamic estimates where the avidity isequal to the sum of the free energies of each individualreaction plus an interaction effect, which is typically anentropic penalty (32,33).

It might be expected in cooperative interactions that anSNP would not be as easily recognized due to an overallhigher binding affinity. However, in our experiments,the bivalent accuracy was 4345-fold greater than themonovalent accuracy (the ratio of concentrations at whichthe signal is greater than the detection limit, fromFigure 8). This added enhancement to selectivity in our

experiments is due to the unique structure of the TPs.By utilizing only one probe in the pair as the detectionprobe, cooperativity can be designed to allow theoreticallyasymptotic separation of specific and nonspecific detectionlimits. For analyte concentrations greater than probeconcentrations, the capture probe has a sufficiently highaffinity to present the detection probe with a constantlocal concentration of bound target. This allows fordetection that is independent of increasing concentrations,effectively reducing the mechanism in Figure 2 to the toptwo reaction states. With no shift in the melting curve forincreasing concentrations, SNPs can be identified withgreater confidence using TPs than with conventionalprobes.For analyte concentrations below the probe concentra-

tion, melting curves were observed to shift with increasinganalyte concentrations (data not shown). We believe thereason that concentration independence occurs only fortarget concentrations above the probe concentration isdue to target saturation of the detection-probe-bindingsite. For relatively low target concentrations, thedetection-probe-binding sites are not saturated and cancontinue to bind more analyte as it is added to solution,presenting a variable concentration to the detection probe.However, once the capture probes have been saturatedwith analyte, a constant local concentration is presented tothe detection probes, causing concentration independenceof reaction. Having biphasic concentration dependence isan advantage of TPs. Quantification of analyte can beperformed for anlayte concentrations below the probeconcentration. However, once analyte concentrationsexceed probe concentrations entering into the nonlinearregion of binding where quantification is no longerpossible, melting curves cease to be affected by concentra-tion and specificity is rendered concentration independent.As the analyte concentrations continue to increase,

it might be thought that the unreacted hairpins in thedetection probe would be forced to bind, such that eachTP would be bound to two target molecules (one on thecapture probe and one on the detection probe). However,as observed in the TPs with even the weakest stem, themelting curves still remained immobile with increasingconcentrations (data not shown). The analogous MB, onthe other hand, continued to show increases in fluores-cence with increasing analyte concentrations (Figure 6),demonstrating that the hairpin strength was not the causeof failure to fluoresce in TPs. Rather, the lack of anincrease in fluorescence with increasing analyte concentra-tions in TPs demonstrates that a second molecule is notbound to the free detection probe. We believe that themechanism preventing a second binding event to thedetection probe at high analyte concentrations mayinvolve the affinity between the detection probe and thecaptured analyte. While the affinity is not enough to keepthe captured analyte firmly bound to the detection probe,we believe it is sufficient to keep the captured analyteclose, continually binding and releasing it, therebyprecluding a binding event from the bulk solution.Taken together, the constant local concentration and theability to preclude binding of more than one molecule,these mathematically designed assets give TPs an accuracy

PAGE 9 OF 11 Nucleic Acids Research, 2007, Vol. 35, No. 10 e76

in SNP discrimination that is matched by no other probeset to our knowledge.MBs, on the other hand, are known to possess greater

specificity than linear probes due to the competition fromstem formation (19). Discrimination between wild type andmismatched targets is expected to increase with stemstrength (20). However, utility of stronger stems in MBs iscompromised by reduced sensitivity from lower affinityand by slower kinetics. By combining the unique secondarystructure of MBs with the idea of cooperative probes,we have created a label-free, highly specific reagent that hasgreater specificity than a MB, but that reacts up to200 times faster. Again TPs show no sign of a trade-off.This may make the use of TPs in room temperature assayswhere MB reaction rates are extremely slow or incontinuous flow detection where reagents passing by onlyhave a short time to react an ideal candidate over MB.The sensitivity loss from stronger stems in MBs has

been studied by Tsourkas et al. (20). The loss influorescence experienced by MBs is replaced by gains inTPs with identical stem strengths because of the lower freeenergy available from cooperative binding. We collectedthermodynamic parameters in order to compare with theresults of Tsourkas et al. In order to get their thermo-dynamic parameters, they fit a line through the fluores-cence at the melting temperature of six differentconcentrations of target. We deviated from this methodbecause we felt it was statistically more relevant to use theentire set of fluorescent data for each concentration ratherthan a single point. Also, their method did not directlyapply to fitting thermodynamic parameters for TPs.In addition to a melting curve which does not shift

significantly with target concentration, Figure 5 reveals adifference between TP and regular probes in the amount ofspecific and nonspecific binding resulting in fluorescenceas a function of temperature. Data points are plotted towhere fluorescent levels are no longer distinguishable fromthe background. Since the actual data could not beobserved at low amounts of binding, the fitted thermo-dynamic parameters were used to calculate binding as afunction of temperature beyond where data could becollected. Since the models and fitted parameters accountfor the majority of the TP behavior, and because thesemodels have been derived for other applications aspreviously discussed, we feel justified in their use toexamine the thermodynamic patterns of cooperativebinding.As a further justification of the use of the models in

describing TP behavior, the models were used to predictbinding as a function of concentration (Figure 8).Theoretical predictions estimated that a target moleculepossessing a SNP in the detection region would never bedetected by TPs regardless of target concentration,virtually eliminating false positives. We were able to testthis hypothesis to 1mM SNP concentrations with no falsedetections. We note that the models were sufficientlyaccurate to predict this trend. We also note that themodels predict the ability to concentrate nonspecificanalyte to levels that are not physically possible withoutfalse positives. This is supported by the fluorescent signalsof TP 9 at 608C, which seem to be completely independent

of target concentration (Figure 7). The fact that we wereunable to create SNP analyte concentrations sufficientlyhigh for TP detection without sacrificing the sensitivityof wild-type detection illustrates the point of this article.This stands in stark contrast to any other probe set ofwhich we are aware. By creating cooperative probes,we have been able to effectively reduce false positiveswithout sacrificing sensitivity.

This high level of specificity may find utility in a numberof research and diagnostic applications. Real-time PCR,for example, is often required to perform SNP discrimina-tion. While comparative analysis of a multiplexed assayoften yields good results in a laboratory, field tests do notalways have the same options of sample purity ormultiplexing and those running the tests do not alwayshave the capacity to interpret the results. Rather manyfield test units resolve the complexity of analysis byresorting to a signal/no signal report. Few probes possessthe capacity to distinguish SNPs by the presence orabsence of a signal. This problem is compounded inhomeland security where a number of select agents likeBacillus anthracis and Yersinia pestis have near neighborswith large portions of similar genetic content (34,35).TPs may again provide an answer to this real-world need.

Although TPs have shown benefits in several areas,there is still room for improvement. This set of experi-ments only examined the effect of stem length on binding.Other options for adaptation include linker length andcomposition, capture and detection probe affinities, thedistance between capture and detection regions on thetarget polynucleotide, and the interactions of each of thesefeatures. Given the large enthalpic and entropic penalties,there may be a great deal of room for improvement,potentially producing a much sharper slope in the meltingcurves. This in turn could lead to higher signal-to-noiseratios and greater detection limit ratios, while maintainingthe incredible specificity.

Six years ago, Iqbal et al. called for the creation of newaffinity reagents as the most important means of improv-ing biosensor accuracy (6). We have created a new class oflabel-free affinity reagents, TPs. These special beaconsmanipulate thermodynamic principles in order to increasekinetics up to 200-fold and molecular accuracy in SNPdetection by at least 345-fold, with predicted enhance-ments of near infinite improvement. Because of theircooperative interaction, they truly allow significantenhancements in sensitivity, specificity and kinetics with-out a trade-off.

ACKNOWLEDGEMENTS

M.R.C. is funded by the National Institute of Dental andCraniofacial Research Career Development and FacultyTransition Award (K22 DE014846) and an NIHExploratory Research Grant R21 (NS). B.C.S. performedthis research while on appointment as a U.S. Departmentof Homeland Security (DHS) Fellow under the DHSScholarship and Fellowship Program, a program adminis-tered by the Oak Ridge Institute for Science andEducation (ORISE) for DHS through an interagency

e76 Nucleic Acids Research, 2007, Vol. 35, No. 10 PAGE 10 OF 11

agreement with the U.S. Department of Energy (DOE).ORISE is managed by Oak Ridge Associated Universitiesunder DOE contract number DE-AC05-00OR22750.All opinions expressed in this article are the authors’and do not necessarily reflect the policies and views ofDHS, DOE or ORISE. Portions of this research werefunded by the Department of Homeland Security under aSmall Business Innovative Research grant awarded toArcxis Biotechnologies under contract # NBCHC060031.Funding to pay the Open Access publication charge wasprovided by Arcxis Biotechnologies, Inc.

Conflict of interest statement. None declared.

REFERENCES

1. Khodarev,N.N., Park,J., Kataoka,Y., Nodzenski,E., Hellman,S.,Roizman,B., Weichselbaum,R.R. and Pelizzari,C.A. (2003) Receiveroperating characteristic analysis: a general tool for DNA array datafiltration and performance estimation. Genomics, 81, 202–209.

2. Drake,T.J. and Tan,W. (2004) Molecular beacon DNA probes andtheir bioanalytical applications. Appl. Spectrosc., 58, 269A–280A.

3. Marras,S.A., Tyagi,S. and Kramer,F.R. (2006) Real-time assayswith molecular beacons and other fluorescent nucleic acid hybridi-zation probes. Clin. Chim. Acta, 363, 48–60.

4. Marras,S.A., Kramer,F.R. and Tyagi,S. (2002) Efficiencies offluorescence resonance energy transfer and contact-mediatedquenching in oligonucleotide probes. Nucleic Acids Res., 30, e122.

5. Yao,Y., Nellaker,C. and Karlsson,H. (2006) Evaluation of minorgroove binding probe and Taqman probe PCR assays: influence ofmismatches and template complexity on quantification.Mol. Cell. Probes., 20, 311–316.

6. Iqbal,S.S., Mayo,M.W., Bruno,J.G., Bronk,B.V., Batt,C.A. andChambers,J.P. (2000) A review of molecular recognitiontechnologies for detection of biological threat agents.Biosens. Bioelectron., 15, 549–578.

7. Call,D.R. (2005) Challenges and opportunities for pathogendetection using DNA microarrays. Crit. Rev. Microbiol., 31, 91–99.

8. Bhanot,G., Louzoun,Y., Zhu,J. and DeLisi,C. (2003) Theimportance of thermodynamic equilibrium for high throughput geneexpression arrays. Biophys. J., 84, 124–135.

9. Peplies,J., Glockner,F.O. and Amann,R. (2003) Optimizationstrategies for DNA microarray-based detection of bacteriawith 16S rRNA-targeting oligonucleotide probes.Appl. Environ. Microbiol., 69, 1397–1407.

10. Borst,A., Box,A.T. and Fluit,A.C. (2004) False-positive results andcontamination in nucleic acid amplification assays: suggestions for aprevent and destroy strategy. Eur. J. Clin. Microbiol. Infect. Dis.,23, 289–299.

11. Draghici,S., Chen,D. and Reifman,J. (2004) Applications andchallenges of DNA microarray technology in military medicalresearch. Mil. Med., 169, 654–659.

12. Mammen,M., Choi,S. and Whitesides,G.M. (1998) Polyvalentinteractions in biological systems: implications for design and use ofmultivalent ligands and inhibitors. Angew. Chem. Int. Ed., 37,2754–2794.

13. Kiessling,L.L., Gestwicki,J.E. and Strong,L.E. (2000) Syntheticmultivalent ligands in the exploration of cell-surface interactions.Curr. Opin. Chem. Biol., 4, 696–703.

14. Holland,P.M., Abramson,R.D., Watson,R. and Gelfand,D.H.(1991) Detection of specific polymerase chain reaction product byutilizing the 50-30 exonuclease activity of Thermus aquaticus DNApolymerase. Proc. Natl. Acad. Sci. USA, 88, 7276–7280.

15. Handl,H.L., Vagner,J., Han,H., Mash,E., Hruby,V.J. andGillies,R.J. (2004) Hitting multiple targets with multimeric ligands.Expert Opin. Ther. Targets, 8, 565–586.

16. Caplan,M.R. and Rosca,E.V. (2005) Targeting drugs to combina-tions of receptors: a modeling analysis of potential specificity.Ann. Biomed. Eng., 33, 1113–1124.

17. Bates,S.R., Baldwin,D.A., Channing,A., Gifford,L.K., Hsu,A. andLu,P. (2005) Cooperativity of paired oligonucleotideprobes for microarray hybridization assays. Anal. Biochem., 342,59–68.

18. Gentalen,E. and Chee,M. (1999) A novel method for determininglinkage between DNA sequences: hybridization to paired probearrays. Nucleic Acids Res., 27, 1485–1491.

19. Bonnet,G., Tyagi,S., Libchaber,A. and Kramer,F.R. (1999)Thermodynamic basis of the enhanced specificity ofstructured DNA probes. Proc. Natl. Acad. Sci. USA, 96,6171–6176.

20. Tsourkas,A., Behlke,M.A., Rose,S.D. and Bao,G. (2003)Hybridization kinetics and thermodynamics of molecular beacons.Nucleic Acids Res., 31, 1319–1330.

21. Zuker,M. (2003) Mfold web server for nucleic acid folding andhybridization prediction. Nucleic Acids Res., 31, 3406–3415.

22. Zarrin,F. and Dovichi,N.J. (1985) Sub-picoliter detection with thesheath flow cuvette. Anal. Chem., 57, 2690.

23. Chain,P.S., Carniel,E., Larimer,F.W., Lamerdin,J., Stoutland,P.O.,Regala,W.M., Georgescu,A.M., Vergez,L.M., Land,M.L. et al.(2004) Insights into the evolution of Yersinia pestis throughwhole-genome comparison with Yersinia pseudotuberculosis.Proc. Natl. Acad. Sci. USA, 101, 13826–13831.

24. Crothers,D.M. and Metzger,H. (1972) The influence of polyvalencyon the binding properties of antibodies. Immunochemistry, 9,341–357.

25. Kaufman,E.N. and Jain,R.K. (1992) Effect of bivalentinteraction upon apparent antibody affinity: experimentalconfirmation of theory using fluorescence photobleachingand implications for antibody binding assays. Cancer Res., 52,4157–4167.

26. Dmitriev,D.A., Massino,Y.S., Segal,O.L., Smirnova,M.B.,Pavlova,E.V., Gurevich,K.G., Gnedenko,O.V., Ivanov,Y.D.,Kolyaskina,G.I. et al. (2002) Analysis of the binding of bispecificmonoclonal antibodies with immobilized antigens (human IgG andhorseradish peroxidase) using a resonant mirror biosensor.J. Immunol. Methods, 261, 103–118.

27. Dmitriev,D.A., Massino,Y.S. and Segal,O.L. (2003) Kinetic analysisof interactions between bispecific monoclonal antibodies andimmobilized antigens using a resonant mirror biosensor.J. Immunol. Methods, 280, 183–202.

28. DeLisi,C. (1976) Antigen Antibody Interactions.. Springer, Berlin.29. Perelson,A.S., Goldstein,B. and Rocklin,S. (1980) Optimal strate-

gies in immunology III. The IgM-IgG switch. J. Math. Biol., 10,209–256.

30. Kitov,P.I. and Bundle,D.R. (2003) On the nature of themultivalency effect: a thermodynamic model. J. Am. Chem. Soc.,125, 16271–16284.

31. Huskens,J., Mulder,A., Auletta,T., Nijhuis,C.A., Ludden,M.J. andReinhoudt,D.N. (2004) A model for describing thethermodynamics of multivalent host-guest interactions at interfaces.J. Am. Chem. Soc., 126, 6784–6797.

32. Jencks,W.P. (1981) On the attribution and additivity of bindingenergies. Proc. Natl. Acad. Sci. USA, 78, 4046–4050.

33. Christensen,T., Gooden,D.M., Kung,J.E. and Toone,E.J. (2003)Additivity and the physical basis of multivalency effects: athermodynamic investigation of the calcium EDTA interaction.J. Am. Chem. Soc., 125, 7357–7366.

34. Chase,C.J., Ulrich,M.P., Wasieloski,L.P.Jr, Kondig,J.P.,Garrison,J., Lindler,L.E. and Kulesh,D.A. (2005) Real-time PCRassays targeting a unique chromosomal sequence of Yersinia pestis.Clin. Chem., 51, 1778–1785.

35. Hurtle,W., Bode,E., Kulesh,D.A., Kaplan,R.S., Garrison,J.,Bridge,D., House,M., Frye,M.S., Loveless,B. et al. (2004) Detectionof the Bacillus anthracis gyrA gene by using a minor groove binderprobe. J. Clin. Microbiol., 42, 179–185.

PAGE 11 OF 11 Nucleic Acids Research, 2007, Vol. 35, No. 10 e76