Quantitative detection of tumor necrosis factor-α by single moleculecounting based on a hybridization chain reaction

Shuang Dai a, Chunjing Feng a, Wei Li a, Wei Jiang b,n, Lei Wang a,nn

a Key Laboratory of Natural Products Chemical Biology, Ministry of Education, School of Pharmaceutical Sciences,Shandong University, 250012 Jinan, PR Chinab School of Chemistry and Chemical Engineering, Shandong University, 250100 Jinan, PR China

a r t i c l e i n f o

Article history:Received 22 January 2014Received in revised form26 March 2014Accepted 7 April 2014Available online 18 April 2014

Keywords:Single molecule countingHybridization chain reactionTNF-αEnzyme-free

a b s t r a c t

This work reports a novel and sensitive quantitative method for detection of tumor necrosis factor-α(TNF-α) based on single molecule counting and hybridization chain reaction (HCR). In the presence ofTNF-α, sandwich-type immunocomplex was formed on the surface of glass substrate. The streptavidinacted as a bridge bounded to the biotinylated immunocomplex, which provided three sites to fixate thebiotinylated initiator strands. The initiator strands triggered the chain reaction of hybridization to form along double-helix polymer and SYBR Green I, acted as the fluorescence label, intercalated into thegrooves of the long dsDNA polymer. Then, the quantitative detection of TNF-α was realized by singlemolecule counting. Under the optimal conditions, HCR-based single molecule counting quantitativemethod could successfully detect TNF-α in the range of 50 fM to 1 pM, and it revealed a reliable resultfor TNF-α detection in real serum. Moreover, the proposed immunosensor exhibited excellent specificity.These results greatly demonstrated that the proposed method possessed the potentiality in clinicalapplication and it was suitable for quantification of biomarker under low concentration.

& 2014 Elsevier B.V. All rights reserved.

1. Introduction

Single molecule detection (SMD) that is relied on the analysis ofindividual molecules has attracted considerable attention inchemistry analysis and biomedical research (Weiss, 1999; Hanet al., 2009). It has been widely applied into gene expressionprofiling, structural prediction of biomacromoleculs and quantita-tive detection (Korn et al., 2003; Miranda et al., 2010; Zhang et al.,2009). Among those, the quantitative detection, based on countingthe target molecules one by one, represents the ultimate limit ofdetection (Agrawal et al., 2006). In the traditional ensemblemeasurement, the quantitative principle is relied on the relation-ship between the signal intensity and the concentration of target.This is to say, the higher the signal , the higher the measuredconcentration of the species . Unlike ensemble measurement, in anSMD quantitative method, the signal intensity in not importantany more, each molecule generates a signal that can be counted,which guarantees the reliability of the quantitative detection(Walt, 2013). Taking the advantages of SMD into account, greatefforts have been devoted to demonstrate the competence of SMDin quantitative analysis (Chan et al., 2010; Tessler et al., 2009).

In order to realize the SMD quantitative method, the signalintensity of single molecule must be strong enough to be detected(Walt, 2013). One method to guarantee the signal intensity is touse the fluorescence label, such as organic fluorescence dye andquantum dot (QDs) (Yao et al., 2003; Zhang and Johnson, 2008;Hahn et al., 2005). Tan and coworkers successfully utilized thedye-labeled molecular beacon to monitor the reaction dynamics(Yao et al., 2003). However, fluorescence dye encountered twomajor limitations, the relatively low fluorescence intensity and thepoor photostability. Alternatively, QDs as a novel nanolabel havebeen employed in single-molecule detection. Rui and coworkersapplied functionalized individual QDs to realize the quantificationof protein (Li et al., 2008). The experiment results showed thatthe QDs were superior to traditional fluorescence dye in termsof stability and sensitivity. Although QDs possess high quantumyield and excellent photostability, the toxicity of heavy metal ionslimits its further application in protein detection. To overcomethe above-mentioned limitation, another way to amplify the signalintensity of single molecule by employing oligonucleotidesequences as the label is developed (Schopf and Chen, 2010). Theydeveloped a microbead-based DNA detection strategy in whichsingle target molecule can be counted directly after rolling circleamplification (RCA). However, the RCA-based amplification techni-que required the auxiliary of protein enzyme. The protein enzymesare sensitive to reaction conditions and increase the experimentalcomplexity, which may restrict its application. Consequently, the

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Biosensors and Bioelectronics

http://dx.doi.org/10.1016/j.bios.2014.04.0160956-5663/& 2014 Elsevier B.V. All rights reserved.

n Corresponding author. Tel.: þ86 531 88362588; fax: þ86 531 88564464.nn Corresponding author. Tel.: þ86 531 88363888.E-mail addresses: wjiang@sdu.edu.cn (W. Jiang),

wangl-sdu@sdu.edu.cn (L. Wang).

Biosensors and Bioelectronics 60 (2014) 180–184

development of a novel, enzyme-free approach for SMD quantita-tive detection is highly desirable.

Nowadays, there have been ever-growing interests in thedevelopment of enzyme-free amplification techniques, e.g.,hybridization chain reaction (HCR) (Dirks and Pierce, 2004).HCR is achieved using a couple of complementary, kineticallytrapped hairpins to propagate a chain reaction of hybridization,which is powered by the free energy of base pair formation(Zhang et al., 2012; Dai et al., 2014). HCR is conducted under anisothermal and enzyme-free condition. Compared with theenzyme-based amplification techniques, HCR is more robustand cost-effective. Herein, we develop a novel and sensitiveSMD quantitative method based on HCR assisted with SYBRGreen I, taking tumor necrosis factor-α (TNF-α) as the modelanalyte. TNF-α act as one of the biomarkers is a critical peptidecytokine (Old, 1995; Jones et al., 1989). It serves as an endogenousmediator or a factor capable of inducing hemorrhagic necrosis incertain tumors (DeKossodo et al., 1995). Furthermore, a variety ofphysiological and pathological processes has been reported to becorrelated with changes in TNF-α level, such as HIV infection,systemic erythema nodosum liprosum, endotoxic shock andrheumatoid arthritis (Wang et al., 2006; Old, 1987). Therefore,the sensitive detection of TNF-α has considerable practical value.In the developed immunosensor, the formation of immunocom-plex indirectly catalyzed the self-assembly of the hairpins H1 andH2 to form a long double-strand polymer. SYBR Green I, showingan obvious fluorescence signal when it is intercalated into thegroove of ds-DNA, was used as the fluorescence label. Under theinverted fluorescence microscope, each bright dot correspondingto a single target molecule, these bright dots can be detectedunambiguously. The assay exhibited good sensitivity, which iscompared with or even better than the reported articles(Battaglia et al., 2005; Mathias et al., 2008). Moreover, this assaypossessed the capacity in determination of other low-abundantbiomarker for clinical diagnostics.

2. Experimental

2.1. Materials and reagents

Human tumor necrosis factor-α (TNF-α), polyclonal mouse anti-human tumor necrosis factor-α (anti-TNF-α), monoclonal biotinylatedrabbit anti-human tumor necrosis factor-α (Bio-anti-TNF-α) andhuman immunoglobulin G (IgG) were purchased from Abcam. Uricacid (UA) and bovine serum albumin (BSA, 498%) were acquiredfrom Shanghai Sangon Biological Engineering Technology and ServicesCo., Ltd. (Shanghai, China). 3-glycidyloxypropyltrimethoxysilane(C9H20O5Si, GOPS), Tween-20, thrombin and platelet-derived growthfactor (PDGF) was obtained from Sigma-Aldrich Co. (St. Louis, MO,USA). Dopamine (DA) from Aladdin (Shanghai, China), streptavidin(SA) and SYBR Green I from BioTeKe Corporation (Beijing, China) wereused in the work. Microscope cover glasses (22�22mm2) werepurchased from Cole-Parmer (Illinois, USA). The oligonucleotides withthe following sequences were synthesized from Invitrogen (Beijing,China): hairpin probe H1, 50-TTA ACC CAC GCC GAA TCC TAG ACT CAAAGT AGT CTA GGA TTC GGC GTG-3; hairpin probe H2, 50-AGT CTA GGATTC GGC GTG GGT TAA CAC GCC GAA TCC TAG ACT ACT TTG-30;biotinylated initiator strand (Bio-I), 50-AGT CTAGGA TTC GGC GTG GGTTAA TTT TTT TTT-biotin-30. All other chemicals (analytical grade) wereacquired from standard reagent suppliers and used without furtherpurification. Ultrapure water was obtained through a Millipore Milli-Qwater purification system (418.25 MΩ) and all solutions wereprepared using the ultrapure water. Clinical serum samples wereprovided from the Hospital of Shandong University, China.

2.2. Apparatus

Fluorescence imaging was performed with an Olympus IX81fluorescence microscope (Tokyo, Japan) equipped with a mercury lightsource, a high-numerial-aperture 60� (1.45 NA) oil-immersion objec-tive lens, a mirror unit (470–490 nm excitation filter and 510–550 nmemission filter), and a 16-bit thermoelectrically cooled EMCCD (Cas-cade 512B, Tucson, AZ, USA). Imaging acquisition and data analysiswere performed using the MetaMorph software (Universal Imaging,Downingtown, PA, USA).

2.3. The fabrication of sandwich immunoassay

The sandwich immunosaasy was fabricated on a glass slide.Briefly, the epoxy-functionalized glass slides were prepared accord-ing to the previous literatures (Xue et al., 2010; Dai et al., 2014). Theanti-TNF-αwas introduced onto the freshly prepared glass substrateby dropping 50 μL of antibody (20 pM) dissolved in PBS solution(10 mM phosphate buffer, 150 mM NaCl, pH 7.4) at 37 1C for at least12 h in humidity. Afterwards, the substrate was incubated with50 μL of blocking buffer (50 mM ethanolamine) at 37 1C for 5 h in aconstant-humidity chamber to block nonspecific binding sites.Subsequently, the substrate was incubated with 50 μL of TNF-α ofvarious concentrations (1.0, 0.7, 0.5, 0.3, 0.1, 0.07, 0.05 pM) at 37 1Cfor 2 h. The glass substrate coated with antigen–antibody was thenexposed to 50 μL of Bio-anti-TNF-α (30 pM) for 2 h at 37 1C. Throughimmunoreaction between antigen and antibody, the sandwichimmunocomplexes were formed. After each step, it was rinsedthrice with PBS-T (10 mM phosphate buffer, 150 mM NaCl, 0.05%Tween-20, pH 7.4) and PBS to remove the unbounded agents.

2.4. The construction of hybridization chain reaction based sensors

After the immunoreaction, the substrate was incubated with50 μL of streptavidin (30 pM) at 37 1C for 2 h. After washing thricewith PBS-T and PBS, 50 μL of Bio-I (0.1 nM) was added onto thesubstrate and incubated for 2 h at 37 1C. Following the washingstep, the substrate acquired above was incubated with a mixture of10 μL H1 (10 nM) and 10 μL H2 (10 nM) in HCR reaction buffer(50 mM Na2HPO4, 0.5 M NaCl, pH 6.8) for 4 h. H1 and H2 wereheated at 90 1C for 5 min and cooled slowly to room temperaturein TE buffer (10 mM Tris–HCl, 1 mM Na2EDTA, pH 8.0) prior to use.Subsequently, the substrate was washed thrice with PBS-T and PBSto elimate the unreacted hairpins.

2.5. SYBR Green I addition and fluorescence image detection

50 μL of SYBR Green I (10 μM) was added onto the substrate andincubated for 10 min at room temperature. Because of the propertyof SYBR Green I, it specifically intercalates into the groove of DNA toemit fluorescence (Zhang and Guo, 2007). Then, the superfluousSYBR Green I molecule was removed and the substrate was rinsedthrice with PBS-T and PBS. 50 μL of PBS buffer was added and thefluorescence images were taken using the inverted epi-fluorescenceimaging system. By manually moving the XY sample stage, theimages corresponding to different locations were acquired. Theimages were analyzed with MetaMorph software.

3. Result and discussion

3.1. The construction and verification of the sandwichimmunosensor

The preparation process and detection strategy of the sandwichimmunosensor is shown in Scheme 1. In this work, the polyclonal

S. Dai et al. / Biosensors and Bioelectronics 60 (2014) 180–184 181

mouse anti-human TNF-α was first immobilized on the glass slidethrough the epoxy-amine reaction. Then, TNF-α and monoclonalbiotinylated rabbit anti-human TNF-α were successively addedonto the glass substrate. After sandwich immunoreactions, thebiotinylated detection antibody can be fixed on the immunosensorsurface by the formation of immunocomplex. Afterwards, thestreptavidin bound to the biotinylated immunocomplex couldanchor three biotinylated initiators. The initiator strands triggerthe HCR and generate a cascade of hybridization to form thenicked double-helix polymer. In this design, the two complemen-tary hairpins are stable existed and would not open or hybridizewith each other at room temperature. And each hairpin has18-base stems, 6-base loops and 6-base sticky ends. The initiatorstrands pair with the sticky end of H1 to trigger an unbiasedstrand-displacement interaction to open the hairpin. The newlyexposed sticky end of H1 can serve as a toehold to nucleate with H2

and opens the hairpin to expose a sticky end on H2. This sticky endis identical in sequence to the initiator strands. In this way, theregeneration of initiator strand propagates a chain reaction ofhybridization to form a long double-stranded polymer. In thisexperiment, SYBR Green I is used as the signal reporter, whichshows an obvious fluorescence intensity when it is intercalatedinto the groove of DNA. Upon the addition of SYBR Green I, thefluorescence images were acquired by epifluorescence microscopy.The numbers of the bright dots were counted one by one forquantification. In this way, we successfully converted the sand-wich immunoassay event into detectable fluorescence dots.

As described above, the fluorescence dots detected in theproposed immunosensor was attributed to the formation of thelong nicked polymers and the intercalation of numbers SYBRGreen I. To demonstrate the crucial role of the HCR, typicalfluorescence images were shown in Fig. S1 in the Supportinginformation. A large amount of bright dots were observed in thepresence of TNF-α. Inversely, almost no bright dot was found inthe absence of human TNF-α after stained with SYBR Green I.Meanwhile, the control group that was reacted without hairpinprobes exhibited negligible fluorescence dot change. The resultprovided a convincing proof of the detection mechanism of theproposed immunosensors.

3.2. Nonspecific adsorption and blocking

The major concern inherent in protein detection assays is thenonspecific adsorption of other biomolecules (Lee et al., 2011).The nonspecific adsorption directly results in the false positiveevents, which greatly affects the sensitivity of an assay (Wanget al., 2012). Consequently, the selection of blocking reagents is akey factor for the performance of the immunosensor. According tothe previous articles, the blocking reagents with amino-groups areable to inhibit the binding to the epoxy-groups on the silanizedglass substrate (Li et al., 2011). Bovine serum albumin (BSA) orethanolamine has been widely applied to eliminate the nonspe-cific adsorption and binding of different chemical species. So weinvestigated the variety of blocking reagents and the concentrationof blocking reagents to reduce the nonspecific adsorption. Experi-mental results in Fig. 1 showed that 50 mM ethanolamine couldprovide a maximum S/N ratio for the immunosensor.

3.3. Optimization of the reaction conditions of the proposedimmunosensor

To achieve the best performance of the immunosensor, weinvestigated several experimental parameters. Except for thevariety of blocking reagents and the concentration of the blockingreagents, the concentration of streptavidin and the reaction timeof hybridization were also inspected.

According to the previous article, the superfluous streptavidinmay increase the possibility of adsorption (Xue et al., 2010). Asshown in Fig. S2 in the Supporting information, the number offluorescence dots elevated and reached the maximum when theconcentration of streptavidin arrived at 30 pM. Then, the numberof fluorescence dots decreased gradually. Taking this into account,the optimum concentration of streptavidin was 30 pM.

The reaction time of HCR was investigated and the result wasdisplayed in Fig. S3 in the Supporting information. The numberfluorescence dots increased and reached a plateau after 4 h.Therefore, 4 h was selected for the HCR reaction.

Scheme 1. Schematic illustration of the SMD quantitative method based on the hybridization chain reaction.

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3.4. Analytical performance of the proposed immunosensor

Under the optimal conditions, the sensitivity and dynamic rangeof the proposed immunosensor were determined with varyingTNF-α concentration. The number of bright dots was increasedwith the increasing concentration of TNF-α, as shown in Fig. 2. Thecalibration plots showed a good linear relationship between thenumber of dots and the concentrations of TNF-α. The linearregression equation for TNF-α was Y¼1.237þ9.505 C in the rangefrom 50 fM to 1 pM with a correlation coefficient of 0.998. Com-pared with other reported immunosensors, this proposed methodhad a comparable or superior sensitivity for TNF-α detection (Table S1).The improvement of sensitivity might be attributed to the lowerbackground and the amplification of HCR. In addition, in the rangeof lower concentration, this proposed method exhibited thesuperior distinguishing capacity. Even though in half of the orderof magnitude (50 fM to 100 fM), it was easily to differentiate thechange of numbers to its concentration.

3.5. Repeatability, reproducibility, selectivity and recoveryof the proposed immunosensor

In this study, the repeatability and reproducibility of theproposed immunosensor were evaluated by the relative standarddeviation (RSD) of intra- and interassays (n¼5). The intra-assayprecision of the proposed immunosensor was valued by detectiontwo samples containing 1.0 pM and 0.1 pM TNF-α. Each samplewas measured five times using five parallel prepared immuno-sensors. Analyzed from the experimental results, the RSD values ofintra-assay were 3.6%, 3.2% at 1 pM and 0.1 pM TNF-α, respec-tively. In addition, the inter-assay precision was assessed bymeasuring one sample with five immunosensors made under thesame conditions independently. And the RSD values of inter-assaywere 4.2% and 3.8% at the above-described concentrations. Theresults displayed that the proposed immunosensor possessedacceptable precision and reproducibility.

Since the specificity played an important role in the analysis ofbiological samples, it was necessary to check it for the proposedimmunosensor (Tang and Ren, 2008). Some proteins such as BSA,thrombin, human immunoglobulin G (human IgG) and platelet-derived growth factor (PDGF) were used as the possible interfer-ences to assess the specificity of the proposed immunosensor.As shown in Fig. 3, the fluorescence dots of BSA, thrombin, humanIgG and PDGF were much lower than that of TNF-α at the sameconcentration of 1 pM. At the same time, the fluorescence dots ofTNF‐α were compared with that containing an interferentialsubstance of 10 pM. These results indicated that the proposed

immunosensor showed high specificity in TNF-α detection andcould distinguish TNF-α in complex samples containing variousinterference.

In addition, the recovery of TNF-α by spiking TNF-α standardsinto fetal bovine serum was evaluated to examine the reliabilityfor clinical application of the proposed immunosensor. The recov-eries of two samples containing 1.0 pM and 0.1 pM TNF-α were inthe range of 93–95%, which were listed in Table S2. The resultsproved that our strategy for the analysis of TNF-α was reliable.

Fig. 1. (A) Effect of various blocking reagents on the numbers of fluorescence dots: (1) PBS, (2) BSA, (3) BSAþethanolamine, and (4) ethanolamine. (B) Effect of theethanolamine concentration on the numbers of fluorescence dot. Conditions: TNF-α: 1.0 pM; R-Ab: 20 pM; Bio-M-Ab: 30 pM; SA: 30 pM; Bio-I: 0.1 nM; H1: 10 nM; H2:10 nM; T: 37 1C; SYBR Green: 10 μM.

Fig. 2. Linear relationship between the numbers of fluorescence dots and theconcentration of TNF-α (n¼3). Each data point represents an average of 3 measure-ments (each error bar indicates the standard deviation).

Fig. 3. Specificity of the proposed immunosensor to TNF-α by comparing it to thepossible interference at the 1 pM level: (1) BSA; (2) thrombin; (3) human IgG;(4) PDGF; (5) TNF-α; (6) mixed sample (TNF-α was 1 pM, the others were 10 pM).The error bars showed the standard deviation of three replicate determinations.

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3.6. Application in analysis of serum samples

To evaluate the analytical possibility and application potenti-ality of the proposed immunosensor, the interference effect ofsample matrix components was first investigated. Several possiblecomponents which were concomitant in the normal human serumwas selected as the interference, such as Naþ , Cl� , dopamine (DA),uric acid (UA) and glucose (GLU). The reason for choosing theseinterference components is that they usually coexist in the normalhuman serum (Zhang et al., 2012). And the concentration of eachcomponent used in the experiment was close to the highest levelin the normal human serum (Dai et al., 2014). As indicated fromFig. 4, the number of fluorescence dots responding to 1 pM TNF-αwith various interference components was comparable to that ofin the normal sample without any additive. The results clearlydemonstrated that the interference effect of complex matrix onthe proposed immunosensor was negligible.

To further investigate the application of the proposed immuno-sensor for clinical analysis, we examined four serum specimens.As displayed in Table 1, the concentrations of TNF-α in four serumsamples were found from 0.39 pM to 0.52 pM, which were inaccordance with that (from 0.29 pM to 0.58 pM) in the literature(Mathias et al., 2008; Scala et al., 2004). The result highlighted that theproposed immunosensor possessed great potentiality as a reliablemethod for the detection of human TNF-α in real serum samples.

4. Conclusion

In summary, a novel and sensitive fluorescence detectionmethod for TNF-α based on the principle of SMD quantitativemethod and HCR has been developed. To our knowledge, we are thefirst one to employ HCR signal amplification into SMD quantitativemethod. The individual target can be unambiguously quantified

under complex conditions, which is practically impossible forensemble measurements. Under the optimal conditions, the quan-tification of TNF-α was successfully accomplished in the range from50 fM to 1 pM. The proposed immunosensor had acceptable preci-sion and reproducibility. Additionally, it revealed high specificityand low matrix effect. Importantly, the method was successfullyapplied for detecting of TNF-α in real serum sample. Although thepresent assay is concentrated on the determination of TNF-α, it canbe easily extended to detect other low-abundant biomarkers bychanging the corresponding antibody. There is every reason tobelieve that the sensitive and accurate SMD method will become apromising quantification strategy for both diagnostic screening andenvironmental monitoring.

Acknowledgments

This project was supported by the National Natural ScienceFoundation of China (Grant nos. 21175081, 21175082, and 21375078).

Appendix A. Supporting information

Supplementary data associated with this article can be found inthe online version at http://dx.doi.org/10.1016/j.bios.2014.04.016.

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Fig. 4. The interference effects of various matrix components with 1 pM TNF-α onthe number of fluorescence dots: (1) normal sample; (2) Naþ , 146 mM; (3) Cl-,180 μM; (4) GLU, 6.11 mM; (5) UA, 420 μM; (6) DA, 0.8 nM. The error bars showedthe standard deviation of three replicate determinations.

Table 1The analysis of real samples of the immunosensor. Each data represents an averageof 3 measurements.

Sample Concentration (M) RSD (%)

1 4.8�10�13 2.32 5.2�10�13 3.63 3.9�10–13 4.84 4.2�10�13 3.5

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