NANO LETTERS
“Chemical Transformers” from Nanoparticle Ensembles Operated with Logic
2008 Vol. 8, No. 9 2993-2997
Mikhail Motornov, Jian Zhou, Marcos Pita, Venkateshwarlu Gopishetty, Ihor Tokarev, Evgeny Katz,* and Sergiy Minko* Department of Chemistry and Biomolecular Science and NanoBio Laboratory, Clarkson UniVersity, Potsdam, New York 13699-5810 Received July 11, 2008; Revised Manuscript Received July 29, 2008
ABSTRACT The pH-responsive nanoparticles were coupled with information-processing enzyme-based systems to yield “smart” signal-responsive hybrid systems with built-in Boolean logic. The enzyme systems performed AND/OR logic operations, transducing biochemical input signals into reversible structural changes (signal-directed self-assembly) of the nanoparticle assemblies, thus resulting in the processing and amplification of the biochemical signals. The hybrid system mimics biological systems in effective processing of complex biochemical information, resulting in reversible changes of the self-assembled structures of the nanoparticles. The bioinspired approach to the nanostructured morphing materials could be used in future self-assembled molecular robotic systems.
In this work, we propose a novel concept for the reversible signal-directed self-assembly of nanoparticles with a pHsensitive shell into structural aggregates controlled by biochemical computing (logic) operations. The concept is demonstrated by coupling pH-responsive nanoparticles with enzyme-based logic gates. The bottom-up approach for the fabrication of nanostructured materials involves self-assembly of nanoscopic building blocks into complex functional structures.1-3 The key issues in the self-assembly process are the size and shape of the building blocks4 and the structure of the building blocks’ surface layers.5,6 The size, shape, and surface modification can be used to tailor the self-assembly interactions between different building blocks, resulting in their organization through mutual recognition properties.7 Various approaches to the functionalization of the building blocks’ surface have been explored to regulate their directed self-assembly. For example, patterned surfaces of nanoparticles,8-10 specific interactions using antibody-antigen recognition,11,12 conjugating proteins,13-15 DNA-directed assembly,12,16-26 synergetic interactions of nanoparticles with a polymeric matrix,27 magnetic-field-driven self-assembly,28,29 and so forth were applied to control nanoparticles’ assembly. The use of stimuli-responsive polymers or surface modification of nanoparticles with a stimuli-responsive shell offers a new intriguing opportunity to turn on and off and tune interactions between nanoparticles,30,31 allowing control of the directed self-assembly32-35 with external stimuli/signals. * To whom correspondence should be addressed: E-mail: sminko@ clarkson.edu. Phone: 1-315-268-3807 (S.M.). E-mail:
[email protected]. Phone: 1-315-268-4421 (E.K.). 10.1021/nl802059m CCC: $40.75 Published on Web 08/14/2008
2008 American Chemical Society
Natural highly sensitive and adaptive to environmental changes signal-responsive systems were found in living organisms at different levels of complexity from bacterial cells up to human bodies. Mimicking of biological systems resulted in the development of synthetic stimuli-responsive materials interacting with biological systems36-38 and yielding hybrid biomolecular-functionalized nanostructured materials that explore the principles of biorecognition.39-41 These materials are sensitive to a single signal produced by synthetic or biomolecular receptor-groups. However, natural biological systems demonstrate complex adaptive behavior based on sensitivity to multiple signals received from the surrounding environment. In many biomedical and technical applications, this kind of complex communication between responsive hybrid materials and their environment would be advantageous. Particularly, a programmed self-assembly of nanoparticles resulting from processing multiple signals could be important for the self-assembly of therapeutic or contrasting agents, or the operation of implantable devices where the creation or disintegration of materials is controlled by the local conditions of the living tissues.42 A chemical approach to information processing43,44 can bring novel aspects to directed self-assembly upon integration of chemical computing systems with signal-responsive nanoparticles. Bhatia et al.45 reported the use of logic operations with multiple biological signals based on nanoparticles decorated with receptor molecules protected by a specially tailored polymer. The protection was removed in the presence of specific proteins (associated with cancer cells), and then the nanoparticles aggregated because of the specific ligandreceptor interaction. This work resulted in logical nanopar-
Figure 1. Schematics of the grafting route to fabricate the P2VP shell on the silica nanoparticle surface: Step 1, silanization of the surface with BTMS; step 2, grafting of P2VP.
ticle-based biosensors. This example demonstrated that the chemical computing systems could be responsible for collecting multiple external signals, processing the received information, and generating a signal recognized by the group of responsive nanoparticles, which will build up structures/ aggregates. The co-operative response of the nanoparticles could amplify the signal in the form of macroscopic structural changes in the nanoparticle dispersion, thus inducing changes in the chemical/physical properties of the system. In general, hybrid systems composed of information-processing chemical computing elements and signal-amplifying responsive nanoparticles will demonstrate “smart” behavior similar to biological systems, where the specificity to received input signals is combined with the response to multiple signals. In contrast to previous reports, in this work, we propose a novel approach to the reversible (with Reset) signal-responsive hybrid systems operating with enzyme-based logic. The fabrication of nanoparticles with grafted stimuliresponsive polymers has been carried out utilizing both the “grafting to”46,47 and “grafting from”48-50 methods. For example, thermo-responsive polymers,51-56 weak and strong polyelectrolytes, 57-59 and amphiphilic block-copolymer and mixed polymer brushes60-62 were explored to synthesize stimuli-responsive nanoparticles. In this work, we grafted poly-2-vinylpyridine (P2VP), a weak polyelectrolyte responding to changes in the pH of aqueous solutions, to the surface of silica nanoparticles. Silica nanoparticles (200 nm mean diameter) with the responsive P2VP shell were prepared in two steps (Figure 1).63 First, silica particles were functionalized with 11-bromoundodeciltrimethoxisilane (BTMS). P2VP was subsequently grafted onto the functionalized silica nanoparticles using the “grafting to” approach. For the grafting of P2VP, we used the quaternization reaction between nitrogen in the pyridine rings in P2VP and the bromoalkyl groups of the surface-immobilized BTMS. The amount of the grafted polymer was 9 mg m-2 according to the elemental analysis. It was demonstrated that a single P2VP chain undergoes a sharp coil-to-globule phase transition at pH 3.9.64,65 In the grafted polymer layer, the co-operative transition is slightly broadened because of the polydispersity of the grafted polymer chains as well as the interactions between the grafted chains and solid substrate. The isoelectric point of the nanoparticles in diluted dispersions was found (using Zpotential measurements) to be at pH 6.5. Dynamic light scattering (DLS) experiments revealed that at pH < 5 the 2994
dispersion of the nanoparticles was stabilized by charged P2VP molecules. Above pH 5, hydrophobic interactions between the P2PV chains start to dominate, and the nanoparticles aggregate. The aggregation is a reversible process. Upon decreasing pH, the core-shell nanoparticles can be redispersed, and they form a stable dispersion again. In this work, we explore this mechanism of the nanoparticles’ response to trigger the signal-directed self-assembly of the nanoparticles by changes in hydrogen ion concentration in the solution. Chemical computing explores the high selectivity of biochemical interactions of DNA66 and enzymes67 to perform simple Boolean logic operations.68,69 Application of enzymebased computing systems allowed simultaneous operation of several concatenated logic gates without interference in the information processing. Assembling of enzymatic logic gates in complex computing networks could be used for processing of many chemical input signals and therefore yield an output signal dependent on the logic program encoded in the biomolecular system.70,71 In order to couple the enzymebiocomputing systems with signal-responsive nanoparticles, the output signal generated by the enzyme reactions should be in the form of chemical changes acceptable to the nanoparticles and resulting in structural changes in the nanoparticle suspension. We designed enzyme systems performing AND/OR Boolean logic operations and producing pH changes upon biocatalytic reactions and coupled them with the signalresponsive nanoparticles to illustrate the concept of the directed self-assembly with logic. The AND logic gate was composed of an aqueous solution, 0.01 M Na2SO4, containing dissolved sucrose, 10 mM, oxygen (in equilibrium with air), and urea, 2 mM. The enzymes, glucose oxidase (GOx, from Aspergillus niger, type X-S (E.C. 1.1.3.4), 4 units·mL-1) and invertase (Inv, from baker’s yeast, grade VII (E.C. 3.2.1.26), 6 units·mL-1), operated as the input signals (Figure 2A). The absence of each enzyme in the system was considered the input signal “0,” while the presence of the enzyme (in a specific optimized concentration) was considered the input signal “1.” The whole reaction chain included conversion of sucrose to glucose catalyzed by Inv followed by the oxidation of glucose catalyzed by GOx and resulting in the formation of gluconic acid, thus yielding acidic pH values. The reaction chain proceeds only in the presence of both enzymes (input signals “1,1”), while the absence of either one or both (input signals “0,0”; “0,1”; “1,0”) inhibits the Nano Lett., Vol. 8, No. 9, 2008
Figure 2. Biochemical logic gates with the enzymes used as input signals to activate the gate operation: the absence of the enzyme is considered “0”, and the presence is “1” for the input signals. The Reset function was catalyzed by urease. (A) The AND gate based on GOx and Inv catalyzed reactions. (B) The truth table of the AND gate showing the output signals in the form of pH changes generated upon different combinations of the input signals. (C) pH changes generated in situ by the AND gate upon different combinations of the input signals: (a) “0,0”, (b) “0,1”, (c) “1,0” and (d) “1,1”. Inset: Bar diagram showing the pH changes as the output signals of the AND gate. (D) The OR gate based on GOx and Est catalyzed reactions and the Reset biocatalyzed by urease. (E,F) The same as (B,C) for the OR gate.
formation of the acidic medium (Figure 2C). The output signal produced by the biochemical system was considered “0” when the pH changes are small (∆pH < 0.2) and as “1” when ∆pH > 1 (Figure 2C, inset). The system demonstrated AND logic behavior with the characteristic truth table (Figure 2B). After the reaction was completed, another enzyme-input of urease (from jack beans (E.C. 3.5.1.5), 4 units·mL-1) was used to catalyze hydrolysis of urea and to reset the pH value to the original neutral value. The whole AND-Reset cycle mimics the performance of the respective electronic circuitry (Figure 2A). Similarly, the OR logic gate was composed of ethyl butyrate, 10 mM, glucose, 10 mM, oxygen, and urea, 2 mM, dissolved in an aqueous solution, 0.01 M Na2SO4, while two enzymes, GOx (4 units·mL-1) and esterase (Est, from porcine liver (E.C. 3.1.1.1), 4 units·mL-1), were used as input signals (Figure 2D). Both enzymes activated biocatalytic reactions independently: GOx catalytically oxidized glucose, and Est catalytically hydrolyzed ethyl butyrate, both resulting in the acidification of the solution (Figure 2F). Thus, the system preserved the initial neutral pH (∆pH < 0.2; the output signal “0”) only in the absence of both enzymes (input signals “0,0”), while the reactions (either one or both together) yielded acidic media (∆pH > 1; the output signal “1”) upon input signals “0,1”, “1,0” and “1,1”, Figure 2F, inset, demonstrating the behavior typical for the OR gate with the respective truth table (Figure 2E). The logic Nano Lett., Vol. 8, No. 9, 2008
operation resulting in the acidification of the solution was followed by the addition of the reset-enzyme urease (4 units·mL-1) returning the system to the original pH value. The whole reaction set could be expressed in terms of the equivalent electronic system: OR-Reset (Figure 2D). We used an aqueous suspension of the nanoparticles with the P2VP shell as a stock suspension for the experiments with logic self-assembly. The system behavior was monitored in situ using DLS in suspension and ex situ observing the structures deposited from the suspensions on Si wafers using scanning probe microscopy (SPM). This system was combined with the enzyme-based AND/OR logic gates (Figure 3). To activate the AND biochemical logic gate (Figure 2A), we added one or both enzymes (GOx and Inv) as the input signals to the solution with dissolved sucrose, O2, and urea mixed with the 0.2% solution of responsive nanoparticles at pH 6 upon permanent agitation with a magnet stirrer. In the absence of both enzymes in the system (input signals “0,0”), the nanoparticles were in an aggregated state (Figure 3A and Figure 3B,a). SPM (Figure 3B,a), and DLS (Figure 3C) detected 3 µm of average aggregates. Obviously, the same behavior of the nanoparticles suspension was documented if only one of the enzymes (input signals “0,1”; “1,0”) was added to the system. However, if 2995
Figure 3. Signal-responsive nanoparticles coupled with the enzyme-based logic gates. (A) The scheme showing the reversible dissociation/ aggregation of the pH-responsive silica nanoparticles decorated with P2VP shells upon protonation (pH 4) and deprotonation (pH 6) of the pyridine units obtained because of the pH changes produced in situ by AND/OR enzyme logic gates. (B) SPM images of the aggregated (a) and dissociated (b) nanoparticles deposited on the Si-wafers surfaces from the respective solutions. (C,D) The nanoparticle/aggregate sizes derived from the SPM and DLS measurements upon different combinations of the input signals processed by the enzyme AND-Reset and OR-Reset system, respectively.
both enzymes were added (input signals “1,1”), the enzymatic reactions resulted in a pH decrease from pH 6 to pH 4 and dissociation of the aggregates (Figure 3A;B,b). The SPM and DLS experiment detected single 200 nm diameter nanoparticles (Figure 3B,b;C). The AND-Reset cycle, by adding urease, returns the suspension to the aggregated state (Figure 3C). Hydrolysis of urea resulted in the elevation of pH to the original value of pH 6. In the experiment, we observed the formation of 3 µm of aggregates. A similar experiment was conducted with the OR enzymegate72 shown in Figure 2D. In this case, all input signals “0,1”, “1,0” and “1,1” resulted in a decrease in pH and dissociation of aggregates while reset of the system returned the suspension to the aggregated state (Figure 3D). We foresee many possible combinations to control pHresponsive-nanoparticle self-assembly directed by different bimolecular logic gates and their networks exploring various enzymatic reactions. We also foresee that application of nonspherical and patterned nanoparticles with the biocomputing system could bring many additional possibilities for the signaldirected self-assembly of nanoparticles into structures with complex architecture. However, in all cases, the changes in the 2996
nanoparticles’ suspension properties will be controlled by biochemical signals collected by the enzyme systems and processed according to the built-in Boolean logic. In this work, we targeted no particular applications for the proposed approach but rather the demonstration of the concept. Nevertheless, we believe that the suggested approach could be useful for many technical and biomedical applications. Optical and rheological properties of aqueous suspensions can be switched using biocomputing systems. Since many enzymatic reactions result in changes in hydrogen cation concentration, the logic processing could be used for analysis of complex biochemical analytes when the structural changes of the suspensions amplify the output signal. The smart signal-responsive hybrid systems could be applied for the regulation of liquid flow because of the signaldirected aggregationsdissociation of nanoparticles in miniaturized microfluidic processors controlled by a logical operation based on enzymatic reactions. We foresee that the proposed concept opens a new avenue for the development and application of various nanostructured hybrid systems operating with biochemical logic. In long perspective, the Nano Lett., Vol. 8, No. 9, 2008
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