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Biological and Medical Applications of Materials and Interfaces

Bacteria-Instructed Click Chemistry between Functionalized Gold Nanoparticles for Point-of-Care Microbial Detection Xiao-Zhou Mou, Xiao-Yi Chen, Jian-Hao Wang, Zhaotian Zhang, Yanmei Yang, Zhang-Xuan Shou, Yue-Xing Tu, Xuancheng Du, Chun Wu, Yuan Zhao, Lin Qiu, Pengju Jiang, Chunying Chen, Dong-Sheng Huang, and Yong-Qiang Li ACS Appl. Mater. Interfaces, Just Accepted Manuscript • DOI: 10.1021/acsami.9b09279 • Publication Date (Web): 11 Jun 2019 Downloaded from http://pubs.acs.org on June 12, 2019

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ACS Applied Materials & Interfaces

Bacteria-Instructed Click Chemistry between Functionalized Gold Nanoparticles for Point-of-Care Microbial Detection Xiao-Zhou Mou, †,§ Xiao-Yi Chen, †,§ Jianhao Wang,┴,§ Zhaotian Zhang,‡ Yanmei Yang,*,║ ZhangXuan Shou, † Yue-Xing Tu, † Xuancheng Du,┴ Chun Wu,‡ Yuan Zhao,┴ Lin Qiu,┴ Pengju Jiang,┴ Chunying Chen,# Dong-Sheng Huang,*, † Yong-Qiang Li*, ‡ † Key

Laboratory of Tumor Molecular Diagnosis and Individualized Medicine of Zhejiang

Province, Zhejiang Provincial People’s Hospital (People’s Hospital of Hangzhou Medical College), Hangzhou 310014, China. ‡ State

Key Laboratory of Radiation Medicine and Protection, School of Radiation Medicine and

Protection, Collaborative Innovation Center of Radiological Medicine of Jiangsu Higher Education Institutions, Soochow University, Suzhou 215123, China. ║

College of Chemistry, Chemical Engineering and Materials Science, Shandong Normal

University, Jinan 250014, China. #

CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, National

Center for Nanoscience and Technology of China, Beijing 100190, China.

ACS Paragon Plus Environment

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School of Pharmaceutical Engineering and Life Science, Changzhou University, Changzhou

213164, China. KEYWORDS: antimicrobial hydrogel, biofilm eradication, chronic wound healing, pHswitchable drug release, nanofibers

ABSTRACT: Bacterial infections pose mounting public health concerns and cause an enormous medical and financial burden today. Rapid and sensitive detection of pathogenic bacteria at the point of care (POC) remains a paramount challenge. Here we report a novel concept of bacteriainstructed click chemistry and employ it for POC microbial sensing. In this concept of bacteriainstructed click chemistry, we demonstrate for the first time that pathogenic bacteria can capture and reduce exogenous Cu2+ to Cu+ by leveraging their unique metabolic processes. The produced Cu+ subsequently acts as a catalyst to trigger the click reaction between gold nanoparticles (AuNPs) modified with azide and alkyne functional molecules, resulting in the nanoparticles to aggregate with a color change of the solution from red to blue. In this process, signal amplification from click chemistry is complied with the aggregation of functionalized AuNPs, thus presenting a robust colorimetric strategy for sensitive POC sensing of pathogenic bacteria. Notably, this colorimetric strategy is easily integrated in a smartphone app as a portable platform to achieve one-click detection in mobile way. Moreover, with the help of magnetic preseparation process, this smartphone app-assisted platform enables rapid (within 1 h) detection of Escherichia coli with high sensitivity (40 colony-forming units/mL) in the complex artificial sepsis blood samples, showing great potential for clinical early diagnosis of bacterial infections.


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1. INTRODUCTION Bacterial infectious diseases pose a significant source of morbidity and mortality, and cause enormous medical and financial burden.1,2 Early diagnosis is prerequisite and crucial to overcoming bacterial infectious threats.3 Standard diagnostic methods, bacterial culture and polymerase chain reaction-based assay, are laborious and usually take hours to obtain results, limiting their extensive applications in point-of-care (POC) detection particularly in resourceconstrained environments.4-6 Recently, several elegant techniques have been developed for bacterial detection such as fluorescence imaging, surface-enhanced Raman spectroscopy, immunological and colorimetric assays.7-10 In particular, colorimetric assay is convenient and attractive in POC and bedside diagnosis since it can be rapidly and easily monitored with the naked eye, without the aid of trained operators and advanced instruments.11 Several exquisite colorimetric assays that enable the POC detection of pathogenic bacteria have been developed based on colloidal gold nanoparticles (AuNPs).12-16 However, its sensitivity has not reached that of gold standard bacterial culture, making it difficult to distinguish bacteria with low concentrations. Moreover, the AuNPs-based colorimetric assay is usually susceptible to interference from ambient conditions (i.e., pH value, ion concentration and solvent), thus compromising the specificity and accuracy of bacterial detection.12 To address these challenges, colorimetric assay that enables POC detection of bacteria with high selectivity and sensitivity is highly desired. By harnessing the metabolic pathways of microbes to catalyze exogenous reactions and produce desired materials, research into bacterial metabolic engineering provides a unique perspective for colorimetric POC sensing of bacteria.17,18 In particular, recent investigation on microbial copper-homeostasis mechanisms has found that bacteria can adapt to copper-rich


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surroundings through their metabolic pathway involving a variety of copper-binding systems and redox enzyme cascades for toxic Cu2+ binding and reduction.19,20 In this process, the cupric reductase NDH-2 in bacteria is responsive for Cu2+ reduction, and the formed Cu+ can then be transmitted to the CopA (a Cu+-translocating P-type ATPase) for cytoplasmic Cu+ detoxification.19 In virtue of this unique capability for Cu2+ binding and reduction, bacteria can instruct various specific chemical reactions catalyzed by Cu+.21 Inspired by this, it would be particularly advantageous for the colorimetric POC detection of bacteria if we can specifically correlate the bacteria-instructing chemical reactions with AuNPs-based colorimetric assays. Cu+catalyzed click chemistry (alkyne-azide cycloaddition) would be an ideal candidate since it can be selectively catalyzed by trace amount of Cu+, and the reaction processes are generally tolerant to ambient conditions.22 Meanwhile, based on the aggregation of AuNPs functionalized with azide and alkyne functional molecules, click chemistry-assisted colorimetric systems have been developed and widely used in biosensing and bioanalysis.23-26 Therefore, we hypothesize that by co-opting bacterial metabolic processes to instruct the click chemistry between functionalized AuNPs, a robust strategy amenable for the colorimetric POC detection of pathogenic bacteria could be developed. Herein, we present the colorimetric strategy of bacteria-instructed click chemistry for POC microbial sensing based on AuNPs modified with azide and alkyne functional molecules, respectively (azide-, and alkyne-AuNPs). In this strategy, exogenous Cu2+ is firstly captured and reduced to Cu+ by pathogenic bacteria of detected samples, where Cu+ subsequently acts as a catalyst to trigger the click reaction between the azide-, and alkyne-AuNPs, resulting in the nanoparticles to aggregate with a color change of the solution from red to blue (as illustrated in Scheme 1). Based on this color change of AuNPs solution, POC detection of pathogenic bacteria


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can be rapidly and easily achieved just by naked eyes. By considering the signal amplification of fixed-point click reaction and its tolerance to ambient conditions, the colorimetric strategy of bacteria-instructed click chemistry would possess high detection sensitivity and selectivity. Furthermore, by combining this strategy with a magnetic pre-separation process and home-made smartphone app, field-portable platform for one-click sensing of bacteria with outstanding sensitivity and selectivity could be easily achieved without any professional training or complex instrumentation, showing great potential for POC detection of pathogenic bacteria in clinical settings. 2. RESULTS AND DISCUSSION 2.1. Synthesis and Characterization of Azide-, and Alkyne-AuNPs. In typical experiments, the azide-, and alkyne-AuNPs were prepared by first modifying AuNPs with 11mercaptoundecanoic acid (11-MUA) based on the ligand-exchange process,27 and then azide and alkynyl functional molecules were conjugated with the carboxyl group of 11-MUA respectively, through a chemical covalent coupling method (Figure S1 and Figure S2).28 Thiol-containing polyethylene glycol molecules were also used in the ligand-exchange process as a stabilizing agent to keep the functionalized AuNPs stably dispersed.29 The whole preparation process of azide- and alkyne-AuNPs was easily monitored by the broader and redshifted surface plasmon resonance absorption peaks (Figure 1a) as well as increased hydrodynamic sizes (Figure 1b) and dramatically changed zeta potentials of AuNPs (Figure 1c). The considerably small zeta potentials of azide-, and alkyne-AuNPs (-9.6 and -8.8 mV) were essential to minimize the effect of electrostatic interaction between the functionalized AuNPs and interfering substances on the colorimetric result.30 From the transmission electron microscopy (TEM) images, it was found that the prepared azide-, and alkyne-AuNPs both had the homogeneous spherical structures with


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the size around 14 nm (Figure S3). Moreover, dynamic light scattering measurement showed that the hydrodynamic sizes of azide-, and alkyne-AuNPs remained stable during 6 days of storage in PBS buffer, showing high structural stability and excellent solubility (Figure 1d). 2.2. Bacteria-Instructed Click Chemistry between Azide-, and Alkyne-AuNPs.

To

evaluate the feasibility of bacteria-instructed click chemistry between the azide-, and alkyneAuNPs, a model bacterium of Escherichia coli (E. coli) with concentration of 106 colonyforming unit/mL (CFU/mL) was added into the mixture of azide-, and alkyne-AuNPs in presence of Cu2+ at room temperature. As we expected, the color of the mixture changed from red to blue after incubation with E. coli for 1 h (Figure 2a, photograph 3 and 4), proving our hypothesis that bacteria can reduce Cu2+ to Cu+ in situ and then instruct the click reaction between the azide-, and alkyne-AuNPs to result in the aggregation of AuNPs. This change in aggregation state of the functionalized AuNPs systems was also observed by UV-vis absorption spectroscopy analysis (Figure S4), TEM and dynamic light scattering measurement (Figure 2b), confirming the occurrence of Cu+-catalyzed click reaction between azide-, and alkyne-AuNPs. In addition, compared to the solution of functionalized AuNPs (Figure 2a, photograph 1), there was no color change for the mixture of E. coli and functionalized AuNPs without Cu2+ (Figure 2a, photograph 2), indicating the necessity of copper source reduction in this bacteria-instructed click reaction. Moreover, this bacteria-instructed click chemistry was found to be tolerant to different ambient conditions (pH value, ion concentration and solvent), thus exhibiting great potential for POC microbial detection in different clinical samples (Figure S5). Furthermore, to investigate the aggregation of functionalized AuNPs (azide- and alkyne-AuNPs) in complex sample and confirm the specific Cu2+ reduction-associated mechanism of bacteria-instructed click chemistry, the aggregation of functionalized AuNPs-Cu2+ ensemble were studied after incubation with bare


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blood (for sepsis sensing purpose), blood with E. coli, or blood containing a reductant (sodium ascorbate), respectively. As shown in Figure S6, no aggregation was observed for the AuNPsCu2+ ensemble after incubation with the bare blood, indicating the good stability of our functionalized AuNPs in complex sample. By contrast, significant aggregation was found for the AuNPs-Cu2+ ensemble after incubation with the blood containing E. coli as well as sodium ascorbate (Figure S6). This result combined with Figure 2 can confirm the specific bacteriainstructed Cu2+ reduction mechanism underlying the aggregation of azide- and alkyne-AuNPs. According to the previous paper on the copper homeostasis in bacteria, the cupric reductase NDH-2 in bacteria is responsive for Cu2+ reduction, and only Cu+ is formed in this process.19 Since the aggregation of functionalized AuNPs can be monitored visually, the bacteria-instructed click chemistry provides a convenient but robust colorimetric strategy to report the presence of pathogenic microbes. 2.3. Click Chemistry-Assisted Colorimetric Strategy for POC Detection of Pathogenic Bacteria. For high-sensitivity detection of pathogenic bacteria, the essential components of this bacteria-instructed click chemistry system (concentrations of functionalized AuNPs and Cu2+, bacteria reaction time), were systematically optimized. Firstly, E. coli bacteria with lower concentration (103 CFU/mL) were added into the mixture of Cu2+ and functionalized AuNPs with various concentrations, to study the effect of functionalized AuNPs’ concentration (azideAuNP : alkyne-AuNP = 1:1) on colorimetric bacteria detection. As shown in Figure 3a, with the decrease of functionalized AuNPs concentration, the color of the mixture of E. coli, Cu2+ and functionalized AuNPs changed from red to purple, indicating that the concentration of functionalized AuNPs indeed had obvious effect on bacteria detection sensitivity. The shapes of UV-vis absorption spectra were consistent with the solution color changes in which the


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absorption at 625 nm gradually increased with the decrease of functionalized AuNPs concentration, indicating greater degrees of AuNPs aggregation in solutions (Figure 3a). From the plot of A625/A522 obtained from above result of UV-vis absorption spectrum versus concentration of functionalized AuNPs, 5.4 nM of functionalized AuNPs was chosen for optimal colorimetric detection of bacteria (Figure 3b). Similarly, the effect of Cu2+ concentration on colorimetric detection of bacteria was also investigated. As shown in Figure S7 and Figure 3c, by comprehensively considering the influence of Cu2+ concentration on bacteria growth and bacteria-instructed click reaction, the optimal 100 nM of Cu2+ was determined. Finally, the effect of bacteria reaction time on colorimetric detection was studied. As shown in Figure 3d, after incubation with E. coli bacteria for 30 min, the A625/A522 values for the mixture of Cu2+ and functionalized AuNPs stopped increasing and became stable. Therefore, the reaction time for this bacteria-instructed click chemistry system was fixed at 0.5 h in our experiments. To evaluate the detection limit of the bacteria-instructed click chemistry, E. coli with various concentrations were added into the optimal click chemistry system (2.7 nM of azide-, and alkyne-AuNPs, 100 nM of Cu2+, 0.5 h of bacteria reaction time), and corresponding phenomena of color changes of the click chemistry system were investigated. As shown in Figure 4a, it was found that distinct color change of the system was not be observed when bacteria concentrations below 103 CFU/mL, indicating that the minimum concentration of E. coli detected by naked eye for the bacteria-instructed click chemistry was approximately 103 CFU/mL. Although this detection limit of bacteria is acceptable for naked eye, it is still not sensitive enough for bacterial detection in practical applications. It is well known that the change of RGB pixel values is more sensitive than that of colors, and the widespread adoption of smartphone provides a portable platform for photo imaging and data analysis.31-33 Therefore, we further developed a smartphone


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app (“Bacteria Analyzer”) with RGB pixel values recording and quantification ability to analyze the color difference of the bacteria-instructed click chemistry system. This smartphone app was developed in SWIFT language and compiled to run on IOS 9.3 operating system (Figure S8 and S9, refer to Methods and Experiments for details). Figure 4b shows the “Color Scan” function interface of this app, by which the color card and RGB pixel values of photographs of the bacteria-instructed click chemistry system could be directly outputted. Figure 4c shows the obtained color cards corresponding to the systems of bacteria-instructed click chemistry shown in Figure 3a. With regard to RGB pixel alone (Figure S10), the ratio of blue to red pixel (B/R) was calculated in the app to reflect the color change of the bacteria-instructed click chemistry system from red to blue. As shown in Figure 4d, a linear calibration curve (y = -0.14605 + 0.16254x, R2 = 0.996) was obtained between the B/R values and E. coli bacteria concentrations ranged from 102 to 107 CFU/mL. More importantly, it is worth to note that linear calibration curves were also obtained for other pathogenic bacteria including Bacillus. subtilis (B. subtilis) (y = -0.15219 + 0.15339x, R2 = 0.986), Staphyloccus aureus (S. aureus) (y = -0.14126 + 0.15591x, R2 = 0.992), and Pesudomonas aeruginosa (P. aeruginosa) (y = -0.13723 + 0.1683x, R2 = 0.983) between the B/R values and bacteria concentrations (Figure 4e and Figure S11). For the slope difference of linear calibration curves obtained for different pathogenic bacteria, we speculate that it may be closely related with the reduction ability of these bacteria for Cu2+.34 By importing the linear calibration curves obtained into the app, one-click determination of bacteria concentration in unknown samples could be easily achieved via the consecutive steps of “Color Scan” and “Concentration Analyze”, providing a portable platform for POC sensing of pathogenic bacteria (Figure S12).


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2.4. Portable Platform for Selective POC Detection of Pathogenic Bacteria in Complex Sepsis Blood Samples. In addition to general bacterial sensing, selective detection of specific bacterial strain in the presence of other bacterial strains, the common condition in actual samples, has greater clinical significance.35,36 To this end, we further constructed the bacterial separation system based on our previous work and combined it with the smartphone app-assisted colorimetric platform. This bacterial separation system was based on iron oxide magnetic nanoparticles functionalized with bacterial species-identifiable aptamers to achieve selective separation and enrichment of specific bacterial strain (Figure S13 and S14).37 After magnetic separation, the enriched bacteria was released from the magnetic nanoparticles upon the treatment of DNase to instruct the click reaction between azide-, and alkyne-AuNPs, and finally diagnosed by the smartphone app-assisted platform (Figure 5a). The magnetic pre-separation process can improve bacterial detection sensitivity by enrichment on one hand, and achieve bacterial detection selectivity on the other hand. Here the functionalized magnetic system specifically

targeting E. coli (MSE.

coli)

was prepared at the current stage, and its performance for E. coli

capture and DNase–triggered release was evaluated. As shown in Figure 5b, the MSE. coli system exhibited outstanding capture efficiency (>85%) towards E. coli with different numbers ranging from 10 to 107 CFU within short times (about 20 min). Conversely, only a small fraction of S. aureus was captured (capture efficiency90%), laying a solid foundation for subsequent smartphone appassisted selective POC sensing of E. coli (Figure 5c).


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By combining the MSE.

coli

system with the smartphone app-assisted colorimetric platform,

selective E. coli detection in complex artificial sepsis blood samples (5 mL containing around 200 CFU of E. coli and 104 CFU of B. subtilis, S. aureus and P. aeruginosa) was carried out. Sepsis caused by the presence of pathogenic bacteria in the bloodstream, is a serious infection syndrome with high mortality.38,39 As shown Figure 6a, after magnetic separation and DNasetriggered release, enriched E. coli from the complex sepsis blood samples were added into the optimal click reaction system (1 mL) and finally diagnosed by the smartphone app. Figure 6b shows the “Concentration Analyze” function interface of the smartphone app for E. coli concentration determination. By making use of the B/R values obtained (0.23) and the linear calibration curve (y = -0.14605 + 0.16254x, R2 = 0.996), E. coli concentration (205 CFU/mL) was directly outputted on the screen. In addition, more parallel trials were conducted to test the repeatability of our method. As shown in Figure 6c, for the four parallel trials, the smartphone app-based platform provided consistent results, which have a good match with the numbers of added E. coli in the artificial sepsis blood sample measured by the gold standard blood culture method. Compared to the long turnaround time (>24 h) of bacterial blood culture, the whole process of bacterial magnetic separation, DNase-triggered release and smartphone app sensing can be completed within 1 h, meeting the time requirements of clinical POC sensing. Furthermore, the magnetic bacterial separation and enrichment process improve the sensitivity of detection, achieving the early diagnosis of sepsis down to trace concentrations of blood bacteria (around 40 CFU/mL). The preparation of more magnetic systems targeting other pathogenic bacterial strains besides E. coli is now in progress (Figure S16 and S17), and it is foreseeable that early POC diagnosis of clinical bacterial infections with high sensitivity would become more convenient based on our portable platform in the near future.


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3. CONCLUSION In summary, by hijacking the bacterial metabolic process for Cu2+ binding and reduction to instruct the click chemistry between azide-, and alkyne-AuNPs, we report a general and robust colorimetric strategy for POC detection of pathogenic bacteria. In virtue of the signal amplification of fixed-point click reaction and its tolerance to ambient conditions, this colorimetric strategy enables rapid, selective and sensitive POC bacterial detection by naked eyes. Notably, this strategy is easily integrated in a smartphone app to achieve one-click reads in mobile way. Moreover, by combining this field-portable smartphone platform with a magnetic pre-separation process, selective detection of E. coli with high sensitivity down to trace concentration in complex artificial sepsis blood sample is successfully realized within 1 h, showing great potential for clinical POC diagnosis of bacterial infections. We believe that the proposed concept of bacteria-instructed click chemistry could also be employed as a potential strategy to design microbe-activated theranostic materials against bacterial infections.

4. METHODS AND EXPERIMENTS 4.1. Materials. Tetrachloroauric acid tetrahydrate (HAuCl4·3H2O), 11-mercaptoundecanoic acid, HS-PEG (MW = 350) and trisodium citrate was purchased from Sinopharm Chemical Reagent.

N-(3-(dimethylamino)propyl-N’-ethylcarbodiimide)

hydrochloride

(EDC),

N-

hydroxysulfosuccinimide sodium salt (NHS), Iron(III) chloride hexahydrate (FeCl3·6H2O), 1octadecene, poly(allylamine hydrochloride) (PAH, Mw = 15000 Da), 11-azido-3,6,9trioxaundecan-1-amine, sodium oleate, and propargylamine were purchased from Sigma-Aldrich. The E. coli identifiable aptamers (5’-HOOC-ACACCATAATATGCCGTAAGGAGAGGCCTG


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TTGGGAGCGCCGTAGAG-3’) were purchased from Sangon Biotech. All other chemicals were obtained from Adamas-beta, and used without further purification. Deionized (DI) water (Millipore Milli-Q grade, 18.2 MΩ) was used in all the experiments. 4.2. Preparation of Azide-, and Alkyne-AuNPs. AuNPs were synthesized by the classic citrate reduction method.40,41 Briefly, 2 mL of 1% gold(III) chloride trihydrate solution was added into 200 mL of double-distilled water and heated under reflux until boiling. Then, 5 mL of 1% trisodium citrate solution were added under vigorous stirring. Boiling was continued for 15 min to obtain the AuNPs with size around 14 nm. For azide and alkyne groups functionalization, AuNPs were first modified by HS-PEG (MW = 350) and 11-mercaptoundecanoic acid (11MUA) (HS-PEG : 11-MUA : AuNPs = 1500:1000:1) to obtain the PEG-AuNPs-COOH through ligand-exchange

reactions,27,42

and

then

11-azido-3,6,9-trioxaundecan-1-amine

and

propargylamine (11-azido-3,6,9-trioxaundecan-1-amine/propargylamine : 11-MUA = 5:1) were conjugated with the carboxyl group of PEG-AuNPs-COOH through standard EDC/NHS chemical covalent coupling procedures,28,43 to obtain the azide- and alkyne-AuNPs, respectively. 4.3. Bacteria Culture. Bacteria of Staphyloccus aureus (S. aureus) (ATCC 6538), Bacillus. subtilis (B. subtilis) (ATCC 6051), Escherichia coli (E. coli) (ATCC 8739), and Pesudomonas aeruginosa (P. aeruginosa) (ATCC 9027) were used in our experiments. Prior to experiments, the bacteria were grown overnight in Luria-Bertani broth medium (LB) and harvested at the exponential growth phase via centrifugation. The supernatant was then discarded and the cell pellet was re-suspended in PBS. The bacteria concentration could be monitored photometrically by measuring the optical density (OD) at a wavelength of 600 nm. Before performing bacteria colorimetric detection experiments, the OD600 values of bacteria stock solutions were re-adjusted to 0.1, which corresponded to the concentrations of 2×108, 1×108, 2×108 and 1.5×108 CFU/mL


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for S. aureus, B. subtilis, E. coli and P. aeruginosa, respectively, obtained based on the gold standard colony counting method . 4.4. Toxicity of Cu2+ to Bacteria Growth. Different volumes of CuCl2 solution (100 μM) were added into 1 mL of E. coli LB solution with concentration of 1×103 CFU/mL to make final Cu2+ concentrations ranging from 10 nM to 10 μM in the mixture. After 12 h incubation, the optical density readings of bacteria solutions were monitored by measuring the OD600. The bacteria solution without Cu2+ was used as control. By comparing the OD600 values of bacteria solution with Cu2+ to the control, the toxicity of Cu2+ to bacteria growth was evaluated. 4.5. Bacteria-Instructed Click Reaction between Azide-, and Alkyne-AuNPs. To prepare the click reaction system, azide- and alkyne-functionalized AuNPs solutions with same concentrations were first mixed, and then CuCl2 solution was added as the copper-ion source for subsequent bacteria reduction and click reaction. To conduct the bacteria-instructed click reaction, the mixtures of functionalized AuNPs and Cu2+ were incubated with different kinds of pathogenic bacteria PBS solutions, and the color changes of the mixtures after incubation were analyzed by UV-vis absorption spectroscopy. For the optimization of the click reaction system for bacteria detection, the effects of functionalized AuNPs concentration (azide-AuNP : alkyneAuNP = 1:1), Cu2+ concentration, and bacteria reaction time were systematically investigated. To investigate the tolerance of the click reaction system to mediums, three different mediums including DI water, NaCl (0.1 M) and PBS (0.01 M, pH 7.4), were added into the mixture of functionalized AuNPs and Cu2+, respectively, and the color changes of the mixtures after incubation were investigated. 4.6. Development of “Bacteria Analyzer” Smartphone App. The homemade “Bacteria Analyzer” smartphone app is developed in SWIFT language (Eclipse code) and compiled to run


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on IOS 9.3 operating system. This smartphone app can be downloaded from the Apple app store, and the whole code of this smartphone app is available upon request. The flow chart of this software is shown in the supporting information (Figure S8). The main menu and user interface of this smartphone app consists of 2 function buttons called “Color Scan” and “Concentration Analyze”, and works as follows. Upon touching the button of “Color Scan”, the corresponding “Color Scan” function interface will be loaded by which RGB values of images of the system of bacteria-instructed click reaction can be recorded and quantified. In the “Color Scan” function interface, images of the system of bacteria-instructed click reaction can be either taken by the smartphone camera or loaded from smartphone album, and RGB values of the selected zone from the center of images will be calculated and outputted by touching the “Scan” function button on-screen. With regard to RGB values, the ratio of blue to red (B/R) is calculated to judge the color difference of the system of bacteria-instructed click reaction, and linear calibration curves between B/R values and bacteria concentrations ranged from 102 to 107 CFU/mL are obtained in our previous experiments. These linear calibration curves for different pathogenic bacteria are imported into the app in advance, and quantitative bacteria concentration in detected sample can be determined and directly outputted in the “Concentration Analyze” function interface, based on the B/R values obtained from the corresponding images of the bacteriainstructed click reaction system. In order to reduce the effects of lighting conditions on RGB values variations during the process of images taken by the smartphone camera, a tight box with LED light was used during the process of samples taken by smartphone camera to protect the environmental light and control illumination inside the box. In addition, focal length of approximate 5 cm between


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sample and smartphone camera was fixed to improve the precision and accuracy of sample image. 4.7. MSE. coli System-based E. coli Separation and Enrichment. To prepare the MSE. coli system, magnetic Fe3O4 nanoparticles with size of 17 nm were firstly synthesized by thermal decomposition of iron-oleate complex, and then coated with PAH and modified by the E. coliidentifiable aptamer according to our previously work.37 Subsequently, PBS solution was spiked with different concentrations of E. coli (10, 102, 103, 104, 105, 106 CFU/mL) to produce E. colicontaminated samples. For E. coli identification and separation, the MSE. coli system (50 μg/mL of iron element) was incubated with 1 mL of E. coli-contaminated samples for 20 min at 37 oC. After incubation, an external magnet was applied to achieve magnetic separation of E. coli. The capture efficiency (C%) is defined as the proportion of E. coli separated from the test samples, and it is calculated based on the equation: C% = 1-(Na/Nb). In this equation, the “Na” and “Nb” represent the number of E. coli in the test samples after and before magnetic separation, respectively, and they are determined using the standard colony counting method in our experiments. To trigger the release of magnetic enriched E. coli, DNase was added into the MSE. coli system with E. coli binding and incubated for 8 min to release the enriched E. coli. After incubation, an external magnet was applied to retrieve the magnetic nanoparticles. The release efficiency (R%) is defined as the proportion of E. coli released from the magnetic nanoparticles, and it is calculated based on the equation: R% = 1-(Nc/Nd). In this equation, the “Nc” and “Nd” represent the number of E. coli binding on the magnetic nanoparticles after and before DNase treatment, respectively, and they are determined using the standard colony counting method in our experiments.


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4.8. Selective Detection of E. coli in Artificial Sepsis Blood Samples. 5 mL of fresh whole blood obtained from the eyeball of healthy mice was spiked with 200 CFU of E. coli and 104 CFU of B. subtilis, S. aureus and P. aeruginosa to produce the complex artificial sepsis blood sample. After magnetic separation by MSE. coli system (50 μg/mL of iron element), the enriched E. coli was release upon the treatment of DNase, and then was added into the optimal click reaction system (1 mL, 2.7 nM of azide-, and alkyne-AuNPs, 100 nM of Cu2+). After 30 min incubation, the solution of the mixture was imaged, and RGB value of the image obtained was recorded and quantified based on the “Color Scan” function of our smartphone app. Based on the B/R values obtained above and the linear calibration curves stored in the smartphone app, the concentrations of bacteria could be determined and directly outputted by the “Concentration Analyze” function of our smartphone app.


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Scheme 1. Conceptual illustration of the colorimetric strategy of bacteria-instructed click chemistry for POC microbial detection.


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Figure 1. a) UV-vis absorption spectra of AuNPs, azide-, and alkyne-AuNPs in DI water. b) Hydrodynamic sizes of AuNPs, azide-, and alkyne-AuNPs in DI water. c) Zeta potentials of AuNPs, azide-, and alkyne-AuNPs in DI water. d) Hydrodynamic sizes of AuNPs, azide-, and alkyne-AuNPs in PBS buffer during 6 days storage. In (b), (c) and (d), the values of hydrodynamic size and zeta potential represent the mean of three independent experiments, and the error bars indicate the standard deviation (SD) from the mean.


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Figure 2. a) Photographs of 1-4 showed the essential components of the bacteria-instructed click reaction system listed in the table below. b) TEM images and hydrodynamic sizes of the corresponding solutions of photograph 3 and 4 shown in a.


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Figure 3. a) UV-vis absorption spectra of the mixtures of Cu2+ (100 nM) and functionalized AuNPs with various concentrations (Azide-AuNP : Alkyne-AuNP = 1:1) after incubation 103 CFU/mL of E. coli for 1 h. The inset shows the corresponding photographs of the mixtures. b) The effect of functionalized AuNPs’ concentration on the bacteria-instructed click reaction. c) The effect of Cu2+ concentration on the bacteria-instructed click reaction. The concentration of functionalized AuNPs used was 5.4 nM, and the bacteria reaction time was 1 h. d) The effect of bacteria reaction time on the bacteria-instructed click reaction. The concentrations of functionalized AuNPs and Cu2+ used were 5.4 and 100 nM, respectively. In (b), (c) and (d), the A625/A522 values obtained from the corresponding UV-vis absorption spectra, represent the mean of three independent experiments, and the error bars indicate the SD from the mean.


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Figure 4. a) Typical photographs of the click chemistry system with different concentrations of E. coli from 102 to 107 CFU/mL. b) The “Color Scan” function interface of our smartphone app in the condition of 107 CFU/mL of E. coli. c) Color card obtained by the app corresponding to the photographs shown in a. d) The linear calibration curve between the B/R values and E. coli concentrations ranging from 102 to 107 CFU/mL. e) The linear calibration curves between the B/R values and B. subtilis, S. aureus, and P. aeruginosa concentrations respectively, ranging from 102 to 107 CFU/mL. In (d) and (e), the B/R values represent the mean of nine photographs from three independent experiments, and the error bars indicate the SD from the mean.


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Figure 5. a) Schematic illustration of the process of selective POC sensing of specific bacterial strain by combining bacterial magnetic separation and smartphone app-assisted colorimetric detection. b) Capture efficiency of the MSE.

coli

system towards E. coli bacteria with different

concentrations ranging from 10 to 107 CFU after 20 min incubation. c) DNase-triggered release efficiencies of E. coli with different concentrations captured by the MSE. coli system. In (b) and (c), the values of capture and release efficiency represent the mean of three independent experiments, and the error bars indicate the SD from the mean.


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Figure 6. a) Experimental photographs for the selective POC sensing of E. coli from complex artificial sepsis blood samples. b) The “Concentration Analyze” function interface of the smartphone app for concentration determination of enriched E. coli from the artificial sepsis blood samples. c) The detected E. coli numbers of four parallel artificial sepsis blood samples by the smartphone app-based platform.


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ASSOCIATED CONTENT Supporting Information The Supporting Information is available free of charge via the Internet at http://pubs.acs.org. Additional experimental data (PDF) AUTHOR INFORMATION Corresponding Authors *Email: [email protected] (Y. Yang) [email protected] (D.-S. Huang) [email protected] (Y.-Q. Li) ORCID Chunying Chen: 0000-0002-6027-0315 Yong-Qiang Li: 0000-0003-1551-3020 Author Contributions § X.-Z.

Mou, X.-Y. Chen, and J. Wang contributed equally to this work.

Notes The authors declare no competing financial interest. ACKNOWLEDGMENT This work was supported by the National Natural Science Foundation of China (31500802, 21628201), the Natural Science Foundation of Jiangsu Province (BK20150350), Funds of Science Technology Department of Zhejiang Province (LGF18H180008), and A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions


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(PAPD). This work was also supported by the 333 Project of Jiangsu Province (BRA2017437), and Jiangsu Key Research and Development Plan (Society Development) (BE2018639).


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REFERENCES (1)

Peleg, A. Y.; Hooper, D. C. Hospital-Acquired Infections Due to Gram-Negative Bacteria. N. Engl. J. Med. 2010, 362, 1804-1813.

(2)

Zhao, Z.; Yan, R.; Yi, X.; Li, J.; Rao, J.; Guo, Z.; Yang, Y.; Li, W.; Li, Y.-Q.; Chen, C. Bacteria-Activated Theranostic Nanoprobes against Methicillin-Resistant Staphylococcus aureus Infection. ACS Nano 2017, 11, 4428-4438.

(3)

Ducret, A.; Quardokus, E. M.; Brun, Y. V. MicrobeJ, A Tool for High Throughput Bacterial Cell Detection and Quantitative Analysis. Nat. Microbiol. 2016, 1, 16077.

(4)

Chung, H. J.; Castro, C. M.; Im, H.; Lee, H.; Weissleder, R. A Magneto-DNA Nanoparticle System for Rapid Detection and Phenotyping of Bacteria. Nat. Nanotechnol. 2013, 8, 369-375.

(5)

Meyer, T.; Franke, G.; Polywka, S. K. A.; Lutgehetmann, M.; Gbadamosi, J.; Magnus, T.; Aepfelbacher, M. Improved Detection of Bacterial Central Nervous System Infections by Use of A Broad-Range PCR Assay. J. Clin. Microbiol. 2014, 52, 1751-1753.

(6)

Hsieh, K.; Ferguson, B. S.; Eisenstein, M.; Plaxco, K. W.; Soh, H. T. Integrated Electrochemical Microsystems for Genetic Detection of Pathogens at The Point of Care. Acc. Chem. Res. 2015, 48, 911-920.

(7)

Disney, M. D.; Zheng, J.; Swager, T. M.; Seeberger, P. H. Detection of Bacteria with Carbohydrate-Functionalized Fluorescent Polymers. J. Am. Chem. Soc. 2004, 126, 1334313346.

(8)

Gracie, K.; Correa, E.; Mabbott, S.; Dougan, J. A.; Graham, D.; Goodacre, R.; Faulds, K. Simultaneous Detection and Quantification of Three Bacterial Meningitis Pathogens by SERS. Chem. Sci. 2014, 5, 1030-1040.


27


(9)

Page 28 of 33

Ganesh, N. V.; Sadowska, J. M.; Sarkar, S.; Howells, L.; McGiven, J.; Bundle, D. R. Molecular Recognition of Brucella A and M Antigens Dissected by Synthetic Oligosaccharide Glycoconjugates Leads to A Disaccharide Diagnostic for Brucellosis. J. Am. Chem. Soc. 2014, 136, 16260-16269.

(10)

Adkins, J. A.; Boehle, K.; Friend, C.; Chamberlain, B.; Bisha, B.; Henry, C. S. Colorimetric and Electrochemical Bacteria Detection Using Printed Paper- and Transparency-Based Analytic Devices. Anal. Chem. 2017, 89, 3613-3621.

(11)

Shen, L.; Hagen, J. A.; Papautsky, I. Point-of-Care Colorimetric Detection with A Smartphone. Lab Chip 2012, 12, 4240-4243.

(12)

Miranda, O. R.; Li, X.; Garcia-Gonzalez, L.; Zhu, Z.-J.; Yan, B; Bunz, U. H. F.; Rotello, V. M. Colorimetric Bacteria Sensing Using A Supramolecular Enzyme-Nanoparticle Biosensor. J. Am. Chem. Soc. 2011, 133, 9650-9653.

(13)

Sung, Y. J.; Suk, H.-J.; Sung, H. Y.; Li, T.; Poo, H.; Kim, M.-G. Novel Antibody/Gold Nanoparticle/Magnetic Nanoparticle Nanocomposites for Immunomagnetic Separation and Rapid Colorimetric Detection of Staphylococcus aureus in Milk. Biosens. Bioelectron. 2013, 43, 432-439.

(14)

Zagorovsky, K.; Chan, W. C. W. A Plasmonic DNAzyme Strategy for Point-of-Care Genetic Detection of Infectious Pathogens. Angew. Chem. Int. Ed. 2013, 52, 3168-3171.

(15)

Wang, S.; Singh, A. K.; Senapati, D.; Neely, A.; Yu, H.; Ray, P. C. Rapid Colorimetric Identification and Targeted Photothermal Lysis of Salmonella Bacteria by Using Bioconjugated Oval-Shaped Gold Nanoparticles. Chem. Eur. J. 2010, 16, 5600-5606.


28

Page 29 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(16)

Xu, S.; Ouyang, W.; Xie, P.; Lin, Y.; Qin, B.; Lin, Z.; Chen, G.; Guo, L. Highly Uniform Gold Nanobipyramids for Ultrasensitive Colorimetric Detection of Influenza Virus. Anal. Chem. 2017, 89, 1617-1623.

(17)

Nguyen, P. Q.; Courchesne, N. M. D.; Duraj-Thatte, A.; Praveschotinunt, P.; Joshi, N. S. Engineered Living Materials: Prospects and Challenges for Using Biological Systems to Direct the Assembly of Smart Materials. Adv. Mater. 2018, 30, 1704847.

(18)

Fan, G.; Dundas, C. M.; Graham, A. J.; Lynd, N. A.; Keitz, B. K. Shewanella oneidensis as A Living Electrode for Controlled Radical Polymerization. Proc. Natl. Acad. Sci. U. S. A. 2018, 115, 4559-4564.

(19)

Rensing, C.; Grass, G. Escherichia coli Mechanisms of Copper Homeostasis in A Changing Environment. FEMS Microbiol. Rev. 2003, 27, 197-213.

(20)

Pontel, L. B.; Soncini, F. C. Alternative Periplasmic Copper-Resistance Mechanisms in Gram Negative Bacteria. Mol. Microbiol. 2009, 73, 212-225.

(21)

Magennis, E. P.; Fernandez-Trillo, F.; Sui, C.; Spain, S. G.; Bradshaw, D. J.; Churchley, D.; Mantovani, G.; Winzer, K.; Alexander, C. Bacteria-Instructed Synthesis of Polymers for Self-Selective Microbial Binding and Labelling. Nat. Mater. 2014, 13, 748-755.

(22)

Deraedt, C.; Pinaud, N.; Astruc, D. Recyclable Catalytic Dendrimer Nanoreactor for PartPer-Million Cu-I Catalysis of "Click" Chemistry in Water. J. Am. Chem. Soc. 2014, 136, 12092-12098.

(23)

Zhou, Y.; Wang, S.; Zhang, K.; Jiang, X. Visual Detection of Copper(II) by Azide- and Alkyne-Functionalized Gold Nanoparticles Using Click Chemistry. Angew. Chem. Int. Ed. 2008, 47, 7454-7456.


29


(24)

Page 30 of 33

Zhu, K.; Zhang, Y.; He, S.; Chen, W.; Shen, J.; Wang, Z.; Jiang, X. Quantification of Proteins by Functionalized Gold Nanoparticles Using Click Chemistry. Anal. Chem. 2012, 84, 4267-4270.

(25)

Qu, W.; Liu, Y.; Liu, D.; Wang, Z.; Jiang, X. Copper-Mediated Amplification Allows Readout of Immunoassays by the Naked Eye. Angew. Chem. Int. Ed. 2011, 50, 34423445.

(26)

Xianyu, Y.; Wang, Z.; Jiang, X. A Plasmonic Nanosensor for Immunoassay via EnzymeTriggered Click Chemistry. ACS Nano 2014, 8, 12741-12747.

(27)

Li, Y.-Q.; Guan, L.-Y.; Zhang, H.-L.; Chen, J.; Lin, S.; Ma, Z.-Y.; Zhao, Y.-D. DistanceDependent Metal-Enhanced Quantum Dots Fluorescence Analysis in Solution by Capillary Electrophoresis and Its Application to DNA Detection. Anal. Chem. 2011, 83, 4103-4109.

(28)

Zhao, Z.; Yan, R.; Wang, J.; Wu, H.; Wang, Y.; Chen, A.; Shao, S.; Li, Y.-Q. A BacteriaActivated Photodynamic Nanosystem Based on Polyelectrolyte-Coated Silica Nanoparticles. J. Mater. Chem. B 2017, 5, 3572-3579.

(29)

Qian, X.; Peng, X.-H.; Ansari, D. O.; Yin-Goen, Q.; Chen, G. Z.; Shin, D. M.; Yang, L.; Young, A. N.; Wang, M. D.; Nie, S. In Vivo Tumor Targeting and Spectroscopic Detection with Surface-Enhanced Raman Nanoparticle Tags. Nat. Biotechnol. 2008, 26, 83-90.

(30)

Otsuka, H.; Nagasaki, Y.; Kataoka, K. PEGylated Nanoparticles for Biological and Pharmaceutical Applications. Adv. Drug Delivery Rev. 2003, 55, 403-419.


30

Page 31 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(31)

Azzarelli, J. M.; Mirica, K. A.; Ravnsbaek, J. B.; Swager, T. M. Wireless Gas Detection with A Smartphone via rf Communication. Proc. Natl. Acad. Sci. U. S. A. 2014, 111, 18162-18166.

(32)

Wei, Q.; Qi, H.; Luo, W.; Tseng, D.; Ki, S. J.; Wan, Z.; Gorocs, Z.; Bentolila, L. A.; Wu, T.-T.; Sun, R.; Ozcan, A. Fluorescent Imaging of Single Nanoparticles and Viruses on A Smart Phone. ACS Nano 2013, 7, 9147-9155.

(33)

Laksanasopin, T.; Guo, T. W.; Nayak, S.; Sridhara, A. A.; Xie, S.; Olowookere, O. O.; Cadinu, P.; Meng, F.; Chee, N. H.; Kim, J.; Chin, C. D.; Munyazesa, E.; Mugwaneza, P.; Rai, A. J.; Mugisha, V.; Castro, A. R.; Steinmiller, D.; Linder, V.; Justman, J. E.; Nsanzimana, S.; Sia, S. K. A Smartphone Dongle for Diagnosis of Infectious Diseases at The Point of Care. Sci. Transl. Med. 2015, 7, 273rel.

(34)

Yan, R.; Shou, Z.; Chen, J.; Wu, H.; Zhao, Y.; Qiu, L.; Jiang, P.; Mou, X.-Z.; Wang, J.; Li, Y.-Q. On-Off-On Gold Nanocluster-Based Fluorescent Probe for Rapid Escherichia coli Differentiation, Detection and Bactericide Screening. ACS Sustainable Chem. Eng. 2018, 6, 4504-4509.

(35)

El-Boubbou, K.; Gruden, C.; Huang, X. Magnetic Glyco-Nanoparticles: A Unique Tool for Rapid Pathogen Detection, Decontamination, and Strain Differentiation. J. Am. Chem. Soc. 2007, 129, 13392-13393.

(36)

Fluit, A. C.; Terlingen, A. M.; Andriessen, L.; Ikawaty, R.; van Mansfeld, R.; Top, J.; Stuart, J. W. C.; Leverstein-van Hall, M. A.; Boel, C. H. E. Evaluation of the DiversiLab System for Detection of Hospital Outbreaks of Infections by Different Bacterial Species. J. Clin. Microbiol. 2010, 48, 3979-3989.


31


(37)

Page 32 of 33

Wang, J.; Wu, H.; Yang, Y.; Yan, R.; Zhao, Y.; Wang, Y.; Chen, A.; Shao, S.; Jiang, P.; Li, Y.-Q. Bacterial Species-Identifiable Magnetic Nanosystems for Early Sepsis Diagnosis and Extracorporeal Photodynamic Blood Disinfection. Nanoscale 2018, 10, 132-141.

(38)

Cohen, J. The Immunopathogenesis of Sepsis. Nature 2002, 420, 885-891.

(39)

Hotchkiss, R. S.; Karl, I. E. Medical Progress: The Pathophysiology and Treatment of Sepsis. N. Engl. J. Med. 2003, 348, 138-150.

(40)

Haiss, W.; Thanh, N. T. K.; Aveyard, J.; Fernig, D. G. Determination of Size and Concentration of Gold Nanoparticles from UV-Vis Spectra. Anal. Chem. 2007, 79, 42154221.

(41)

Guo, S.; Huang, Y.; Jiang, Q.; Sun, Y.; Deng, L.; Liang, Z.; Du, Q.; Xing, J.; Zhao, Y.; Wang, P. C.; Dong, A.; Liang, X.-J. Enhanced Gene Delivery and siRNA Silencing by Gold Nanoparticles Coated with Charge-Reversal Polyelectrolyte. ACS Nano 2010, 4, 5505-5511.

(42)

Dam, D. H. M.; Lee, R. C.; Odom, T. W. Improved in Vitro Efficacy of Gold Nanoconstructs by Increased Loading of G-quadruplex Aptamer. Nano Lett. 2014, 14, 2843-2848.

(43)

Pieper, J. S.; Hafmans, T.; Veerkamp, J. H.; van Kuppevelt, T. H. Development of TailorMade Collagen-Glycosaminoglycan Matrices: EDC/NHS Crosslinking, and Ultrastructural Aspects. Biomaterials 2000, 21, 581-593.


32

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Table of Contents

The concept of bacteria-instructed click chemistry between functionalized gold nanoparticles is reported. This concept can be used as a colorimetric strategy for selective and sensitive point-ofcare detection of pathogenic bacteria in mobile way.


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Bacteria-Instructed Click Chemistry between ... - ACS Publications

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