Pursuing the Promise of Enzymatic Enhancement with Nanoparticle

Oct 16, 2017 - Center for Bio/Molecular Science and Engineering, Code 6900,. §. Electronic Science and Technology Division, ...... layer is of course...
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Pursuing the Promise of Enzymatic Enhancement with Nanoparticle Assemblies James Nicholas Vranish,†,‡ Mario G. Ancona,§ Scott A. Walper,‡ and Igor L. Medintz*,‡ †

National Research Council, Washington, D.C. 20001, United States Center for Bio/Molecular Science and Engineering, Code 6900, §Electronic Science and Technology Division, Code 6800, U.S. Naval Research Laboratory, 4555 Overlook Avenue, SW Washington, D.C. 20375, United States



ABSTRACT: The growing emphasis on green chemistry, renewable resources, synthetic biology, regio-/stereospecific chemical transformations, and nanotechnology for providing new biological products and therapeutics is reinvigorating research into enzymatic catalysis. Although the promise is profound, many complex issues remain to be addressed before this effort will have a significant impact. Prime among these is to combat the degradation of enzymes frequently seen in ex vivo formats following immobilization to stabilize the enzymes for long-term application and to find ways of enhancing their activity. One promising avenue for progress on these issues is via nanoparticle (NP) display, which has been found in a number of cases to enhance enzyme activity while also improving long-term stability. In this feature article, we discuss the phenomenon of enhanced enzymatic activity at NP interfaces with an emphasis on our own work in this area. Important factors such as NP surface chemistry, bioconjugation approaches, and assay formats are first discussed because they can critically affect the observed enhancement. Examples are given of improved performance for enzymes such as phosphotriesterase, alkaline phosphatase, trypsin, horseradish peroxidase, and β-galactosidase and in configurations with either the enzyme or the substrate attached to the NP. The putative mechanisms that give rise to the performance boost are discussed along with how detailed kinetic modeling can contribute to their understanding. Given the importance of biosensing, we also highlight how this configuration is already making a significant contribution to NP-based enzymatic sensors. Finally, a perspective is provided on how this field may develop and how NP-based enzymatic enhancement can be extended to coupled systems and multienzyme cascades. engineering) formats are used.5,6 In the area of commodity chemicals, these approaches take advantage of the ability of enzymes to use biological carbon and other sources and convert them into useful natural products. The usage can involve just one enzyme that executes a single difficult step in a synthesis such as the stereospecific addition of functional groups,7 or it can exploit multiple enzymes to recreate a functional metabolic pathway.5,6,8 In doing so, enzymes impact numerous industrial applications ranging from the processing of complex mixtures of chemicals, such as the breakdown of lignocellulose or the use of proteases and lipases in the production of foods such as cheese, to the use of overexpressed enzymes to catalyze the high-yield production of a single chemical product, such as the vitamin riboflavin.9,10 For clinical and therapeutic needs, enzymes are also of tremendous interest. Diagnostic devices can use enzymes to gauge the concentrations of particular metabolites in biological samples because they are able to recognize specific substrates within complex matrices.11−14

1. INTRODUCTION Enzymes have a remarkable ability to carry out biochemical transformations. Many of their targeted reactions have a halflife of millions of years in the absence of an enzyme catalyst.1 The specificity of enzymatic catalysts is amazing, with these complex catalysts favoring stereospecific transformations at a single site within a complex molecule. Such fine control is essential because it can mean the difference between a potent drug and a benign molecule or a deadly toxin.2 The wealth of catalytic power that nature manifests is far beyond the capabilities of the synthetic chemist, and for this reason, enzymes have drawn much attention as enablers in a plethora of industrial and medicinal applications.3 However, there are many difficulties in working with enzymes, and to date, only a small fraction of the universe of enzymes available in living systems have proven useful in applied settings. In this feature article, we focus on the state-of-the-art in addressing these challenges with in vitro approaches that specifically focus on assembling enzymes onto nanoparticles (NPs) to access enhanced activity as well as long-term stability. In exploiting enzymes in industry and medicine, both in vitro (i.e., cell-free)4 and in vivo (also referred to as metabolic © XXXX American Chemical Society

Received: July 24, 2017 Revised: October 16, 2017

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Table 1. Representative Examples of Enzymatic Acceleration at a Nanoparticle Interface nanoparticle

enzyme

substrate

target application

comparative kinetic parameters (free vs. on NP)

ref

6 nm CdSe/ZnS QD

thrombin

13 nm AuNP 800 nm lipid vesicles

ribonuclease H galactosyltransferase

Configuration: Substrate on NP peptide FRET-based kcat/Km 1.2 mM−1 s−1 vs 3.3 up to 5.6 mM−1 s−1 biosensing peptide FRET-based ∼50-fold increases in kcat/Km biosensing RNA gene regulation activity 0.25 h−1 vs 0.46−0.68 h−1 UDP-galactose cellular research Km > 0.5 mM vs 0.09 mM

5−10 nm CdSe/ZnS QDs 190 nm magnetic NPs

exo- and endogluconase

cellulose

5 xylanases

138

pepsin aldolase cellulase catalytic domain β-galactosidase

hemicellulose digestion sample preparation chemical synthesis biofuel production

5.5-fold increase in production

30 nm AuNPs ∼50 nm AuNPs CdSe QDs

wheat arabinoxylan cytochrome C synthetic cellulose

Km 2.9 vs 2.1 × 10−5 activity 1.1 mM h−1 vs 4.5 mM h−1 7.2-fold increase in sugar yield

139 140 141

synthetic

biosensing

kcat 410 vs 1800 s−1

70

alkaline phosphatase

synthetic

biosensing

25−40% increase in activity

56

phosphotriesterase

paraoxon

bioremediation

kcat 45 vs 194 s−1 kcat/Km 271 vs 591 mM−1 s−1

104

trimeric phosphotriesterase pectate lyase

paraoxon

bioremediation

2-fold increase in kcat and kcat/Km

59

citrus pectin

biodegradation

142

cholesterol oxidase

cholesterol

diagnostics

∼28-fold increase in activity >50-fold increase in 90 °C half-life activation energy 13.6 vs 9.3 kJ/mol

5−6 nm CdSe/ZnS QD trypsin

∼4, 9 nm CdSe/ZnS QDs ∼4, 9 nm CdSe/ZnS QDs ∼4, 9 nm CdSe/ZnS QDs ∼4, 9 nm CdSe/ZnS QDs 10KM) would mean having an NP-peptide substrate in at least low millimolar concentration and then increasing significantly from there.51 Millimolar concentrations of NP dispersions and especially QDs in an aqueous buffer are, however, not a physically accessible reality. We instead base our characterization on a time-integrated Michaelis−Menten (MM) approach that was the method originally used by Michaelis and Menten in their seminal work25 but that has fallen out of common use because it is harder to implement and intepret than the almost ubiquitous excess substrate format currently utilized under most circumstances. In this integrated approach, the substrate (QD-trypsin peptide) is held constant, the enzyme (trypsin) concentration is varied, and data are analyzed using the following version of the MM equation ⎛ a ⎞ kcat*Et = p + KM*ln⎜ o ⎟ ⎝ ao − p ⎠

(1)

where the catalytic rate is given by kcat, E is the enzyme concentration, t is time, a0 is the initial substrate concentration, p is the concentration of reaction product formed, and KM is the Michaelis constant reflecting the enzyme’s affinity for the substrate.51 Monitoring enzyme activity in this format over time yields so-called enzymatic progress curves. The consistency of the measurements with MM kinetics can be assessed (Selwyn’s test) from the degree to which the progress curves superimpose when replotted versus enzyme time (i.e., [trypsin] × time) as illustrated in Figure 2A.50,52 It should also be noted that if the substrate concentration at t = 0 is not greater than ca. 3 times the enzyme’s KM then a fitting of the progress curves with eq 1 will be accurate only in estimating kcat/KM. This ratio, E

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conditions. These results also led us to explore whether this activation could be used to enhance the activity of an enzyme of direct interest to the Department of Defense, namely, phosphotriesterase (PTE), and an in-depth analysis of this enzyme system indeed proved quite informative. PTE is a fascinating enzyme whose natural substrate still has not been definitively identified. As revealed in Raushel’s seminal work, PTE has the ability to catalyze the hydrolysis of a wide variety of organophosphate ester compounds including the nerve agents tabun and sarin and certain structurally related pesticides such as paraoxon.57 This capability makes PTE of direct interest for a variety of biodefense and bioremediation applications. In our experimental format, PTE was expressed with a terminal His6 motif as an obligate dimer where the monomer has a molecular weight of ∼37 kDa. PTE was then ratiometrically self-assembled via metal coordination to smaller, green 525 nm emitting and larger, red 625 nm emitting QDs, and the conjugates were characterized as above to confirm ratiometric bioconjugation (Figure 4). Computer simulations of multiple enzymes packed around a QD enabled estimates of the maximum assembly ratios (Figure 4B). PTE catalysis of paraoxon was observed by a colorimetric p-nitrophenol product, both when free in solution and when assembled into

peptides slowed from the ideal initial-rate curves as the reaction progressed to later time, suggesting that the remaining substrate was harder to encounter, similar to the observations of Algar et al.50 Although no rate enhancement was observed relative to a free peptide substrate, the results are again consistent with a model of enzyme hopping from substrate to substrate around a QD surface. The reasons behind this lack of enhancement were presumed to be a complex interplay of enzyme surface charge and QD ligand chemistry that resulted in nonoptimal interactions. Support for the latter comes from several recent studies that have probed the role of the QD surface ligand in these processes. In one primary example, Wu and Algar showed that thrombin could experience an up to 50-fold variation in its efficiency or specificity constant when varying just the surface ligand chemistry on a QD displaying its peptide substrate.53 Using the exact same format as in ref 50, we recently investigated trypsin kinetics as the QD surface ligand was systematically varied.55 A series of PEG ligands were utilized terminating in different functional groups including an amine (NH2), acetyl (COCH3), methoxy (OMe), hydroxy (OH), carboxy (COOH), and zwitterionic group (CL4). Additionally, a short compact CL4 ligand was tested versus that of a PEGylated CL4 to isolate the effects of the PEG groups’ extended length. As shown in Figure 3A, coating QDs with the compact CL4 ligand resulted in an ∼35-fold increase in the trypsin enzyme efficiency (kcat/KM). To understand this remarkable acceleration in activity, a series of molecular dynamics simulations were undertaken of trypsin interactions with representative QD-ligand complexes displaying a peptide substrate. A complex interplay of factors was found to contribute to the enhancement, including the peptide substrate being prominently displayed extending from the QD surface and not being sterically hindered by the longer surface ligands (highlighted in Figure 3B) in conjunction with the presence of electrostatic and other productive attractive forces between the enzyme and the QD surface. More broadly, it was realized that understanding such critical interactions at this NP-bulk interface can suggest a set of guidelines for the rational design of next-generation high-activity theranostics (jointly combining therapy with diagnostics in a single molecular entity) and bionanocomposites for sensing and assay applications.55

4. ENZYME-ON-NANOPARTICLE FORMAT In more recent work, we have been exploring the effect of placing enzymes rather than substrates on an NP surface. As reflected in Table 1, this format is far more popular because it is easier to interrogate using conventional excess-substrate MM assay formats. In one of our first forays into this realm, Claussen et al. investigated the activity of alkaline phosphatase (AP), which is commonly used as a reporter probe, both freely in solution and as bound to a QD.56 The His6-appended AP version recombinantly expressed for this effort was assembled in a controlled, ratiometric manner on QDs, and this was confirmed using an electrophoretic mobility shift assay and by a dynamic light scattering analysis. In assays of the enzymatic activity, an ∼25% increase in kcat/KM was observed when the QD assembly was used, and this was attributed to an increase in kcat. This activation persisted even when the QD was nearly fully loaded with enzyme (∼12 AP enzymes/QD). Although the enhancement was modest, this finding is still significant because AP catalysis is believed to be diffusion-limited and would not be expected to exhibit further increases under these

Figure 4. QD phosphotriesterase structure and function. (A) Schematic of a CdSe/ZnS core/shell QD surface-functionalized with the DHLA-CL4 ligand whose structure is provided below. PTE is ratiometrically self-assembled into the QD surface by its terminal hexahistidine (His)6 sequence. The average number of PTEs per QD is controlled through the molar stoichiometry added during assembly, and the conjugates are directly utilized without subsequent purification. PTE hydrolysis of the paraoxon substrate to the pnitrophenol product, which absorbs at 405 nm, is shown with the PTE competitive inhibitor triethyl phosphate. Note that this scheme is not to scale. (B) (Left) Representative TEM micrograph of 625-nmemitting CdSe/ZnS QDs with a diameter of 9.2 ± 0.8 nm. (Right) Simulated structure of the 625 QD fully assembled with PTE displayed on the surface. The maximum assembly ratio is estimated to be ∼28 PTE/QD. Reproduced with permission from ref 104. Copyright 2015 American Chemical Society. F

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Figure 5. QD phosphotriesterase bioconjugate activity. (A) Initial rates of p-nitrophenol product formation for 625 QD-(PTE)n bioconjugates assembled at the indicated ratios when exposed to an increasing concentration of paraoxon substrate. The free PTE enzyme is at the equivalent concentration as that used for the QD-bioconjugates. (B) Plots of normalized PTE kcat values from 525 QD-(PTE)8 conjugates (blue) and equivalent amounts of free PTE versus increasing sucrose concentration. (C) Plot comparing the effect of potential changes in k2 on initial PTE rates. The experimental rates of free PTE (green) and 525 QD-(PTE)8 (blue) versus substrate concentration are plotted. An initial k2 value of 145 s−1 was derived from the experimental data. The effect on initial rates of increasing the k2 value by increments of 40 s k2 is then estimated with the red dashed lines. Reproduced with permission from ref 104. Copyright 2015 American Chemical Society.

and k−2. Raushel found that increasing viscosity slowed the reaction (kcat) and thus inferred that it was the product release that was rate-limiting.58 Our analogous work with free PTE confirmed the earlier work, and then we similarly tested QDPTE conjugates with representative results shown in Figure 5B. Rather than slowing down kcat as with free PTE, QD-PTE is seen to speed up even as the viscosity is increased. We therefore conclude that the QD display is somehow accelerating the rate-limiting dissociation step (k2) and that this is further enhanced by the sucrose. How this might occur is commented on below. Interestingly, similar phenomena were observed for a significantly modified recombinant PTE derivative.59 In this case, the motivation was to generate a form of PTE that could be spun into fibers to create fabric capable of neutralizing nerve agents. With this goal in mind, PTE was genetically fused with His-tagged collagen, creating a PTE-labeled trimeric fibril that could bind QDs via an extended helical linker. When bound to QDs, the kcat values improved ∼2.5-fold over freely diffusing enzyme. This improvement was seen at a variety of different ratios of PTE to QD as well as on two differently sized QDs. However, this fibril-modified enzyme’s overall kcat was substantially reduced compared to that of the parent enzyme, and this was ascribed to the significant structural alterations that

QDs. The QD display of PTE was found to give a 4-fold increase in kcat along with a 2-fold improvement in kcat/KM, with some representative data shown in Figure 5A. A number of experiments were then carried out to provide insight into this enhancement. By examining the enzyme’s activity at different temperatures with an Arrenhius analysis, it was found that the enzyme’s activation energy was not changed when attached to the QD. Another test looked at the PTE activity in the presence of the competitive inhibitor triethyl phosphate, and this suggested that no other higher-order or more complex catalytic processes were involved. Further experiments probed the microenvironment around the QD-enzyme bioconjugate in the presence of increasing concentrations of the viscogen sucrose. Raushel previously used this assay to show that enzyme− product (EP) dissociation was the rate-limiting step for PTE.58 This led them to modify the standard MM reaction for PTE as k1

R kcat

k2

E + S XoooY ES ⎯→ ⎯ EP XoooY E + P k−1

k−2

(2)

where the enzyme-substrate complex (ES) and the enzymeproduct complex (EP) are separately considered. In this picture, ES first hydrolyzes to EP in a chemical step with rate constant kRcat, and then the product P is released in a second physical step that occurs with forward and reverse constants k2 G

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Figure 6. QD-DNA phosphotriesterase activity. (A) Schematic of the four different PTE bioconjugates tested: (i) free PTE; (ii) PTE attached to a DNA spacer; (iii) PTE displayed on DHLA-CL4-functionalized CdSe/ZnS core/shell QD surfaces; and (iv) DNA-PTE displayed on PEGylated QDs. PTE-(His)6 and the 38 bp DNA-(His)5 ratiometrically coordinate to the QD or NTA group by metal-affinity coordination. DNA-(His)5 coordinates to the QD surface in a random manner and does not displace the PEG ligands that are not involved in this conjugation. Free PTE coordinates to the Zn surface of DHLA-CL4-functionalized QDs. (B) Initial rates of paraoxon hydrolysis for PTE free in solution (PTE, yellow), PTE attached directly to the 525 nm QD surface (525 QD CL4-PTE, green), PTE attached to the 56 bp dsDNA (DNA-PTE, red), or as displayed on the QD-DNA structure (QD-DNA-PTE, black). Data shown for ratios of 2 PTE per QD or their equivalents in the other configurations. (C) Specific activity (in units of nmols of substrate consumed/min/mg of PTE) of QD-DNA-PTE conjugates versus that of the equivalent amount of free PTE. Reproduced with permission from ref 61. Copyright 2017 Royal Society of Chemistry.

linker was meant to act as a prescribed rigid spacer to probe how far enhancement would persist when the enzyme was placed further away from the QD surface (Figure 6A). In this case, it was found that attachment of the PTE to the DNA alone provided for some type of enhancement and thus attaching the PTE to the QDs via an extended DNA linker did not abrogate the enhancement effect (Figure 6B).61 Interestingly, similar enzymatic enhancement of other enzymes on DNA have also been noted,62 which suggests that this may also be a widely applicable enhancement phenomenon that could be

occurred in the re-engineering. Additionally, these results suggested that the observed QD enhancement may not be limited to the environment immediately adjacent to the QD surface because PTE enzymes in this trimeric configuration reside at distances of greater than 10 nm from the QD surface.59 The enhancement of the PTE trimer was recently replicated when attached to three differently sized AuNPs in pursuit of field-portable pesticide detectors.60 Another interesting set of observations with PTE involved attaching it to DNA.61 In this case, the double-stranded DNA H

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exploited when fully understood. Indeed, the Hess group has made important progress in defining the origins of enhancement within this mixed materials interface.63−65 Focusing on an NP-enzyme conjugate, the question then becomes, does the unique accelerating nanoenvironment around the NP extend out a significant distance from the NP’s surface as suggested by Zobel,66 or do the hydration layers of each of the participants meld into one as suggested by Yan?67 See also the further discussion below. It is also worth noting that such hybrid bionano constructs incorporating a mix of DNA, enzymes, and NPs are growing in popularity because of the access they can provide to designer multifunctional nanomaterials.68,69 In another example of enhancing catalytic activity based on a similar NP display configuration, Brown and co-workers applied it to the enzyme β-galactosidase (β-Gal)70 and in doing so faced two unique challenges. First, β-Gal is an obligate tetramer with a mass that approaches almost 500 kDa, a physical size significantly larger than typical QDs. Second, its kinetics are believed to be diffusion-limited,70,71 so presumably already functioning at maximum capacity thus raised the question, is it possible to improve a so-called perfect enzyme? Given that β-Gal is tetrameric, it will display four His6 motifs, and fortuitously, these binding sites are located at the peripheral corners of this rectangular protein, thereby allowing the QDs to assemble around the enzyme rather than the converse as shown schematically in Figure 7A. This unique assembly was confirmed using TEM, with a representative image given in Figure 7B. Enzymatic assays of the QD-β-Gal conjugates exhibited an ∼3-fold improvement in kcat, whereas the enzymatic efficiency remained unchanged as a result of a corresponding compensation by an increase in the KM value. The latter led us to speculate that perhaps substrate was accumulating around the bioconjugate, giving rise to the superdiffusional performance. Follow-up work on this system, however, suggested that the enhancement may also be due to the alleviation of β-Gal’s rate-limiting step but in a more complex process.72

Figure 7. β-Galactosidase enzymatic enhancement. (A) Schematic of a β-galactosidase enzyme (PDB 1DP0) as attached to 625 nm QDs (red) coated with a CL4 ligand (gray) via the four pendent His6 tags (space-filling) at the enzymes’ periphery. Each of the four tetrameric subunits is shown as a ribbon of a different color with the active sites highlighted in yellow. (B) Representative TEM images of 625 CL4 QD-β-gal assemblies displaying 2-, 3-, and 4-QDs. (C) Results from enzyme assemblies with 625 CL4 QDs comparing plots of initial activity collected from QD-β-gal assemblies versus that of the equivalent amount of free enzyme. Reproduced with permission from ref 70. Copyright 2015 Royal Society of Chemistry.

5. OTHER NANOPARTICLE−ENZYME CONFIGURATIONS WITH ENHANCED ACTIVITY Long before synthetic biology evolved out of molecular biology and exploded into the mainstream, researchers sought to utilize microbes and microbial systems to manufacture enzymes for industrial and medical uses. Traditionally, laboratory strains of bacteria and yeast served as microscopic factories, engineered to produce a specific product. These recombinant compounds could be native to the organism, such as cellulases from Aspergillus species or antibiotics from Streptomyces, or the product of a foreign genetic circuit such as the insulin replacement Humulin, which has been produced in both Escherichia coli and yeast.73 Today, in addition to significant advances in the tools available for genetic engineering, a greater understanding of microbial interactions with hosts and the environment is rapidly emerging. These foundational discoveries have allowed researchers to create systems for enzyme manufacture that harness the amazingly diverse capabilities of the microbial world. In the late 1950s and 1960s, researchers began to observe the presence of bacterial membrane components in culture media when grown under specific conditions of nutrient depletion. Knox et al. conducted a series of experiments with E. coli cultures to identify the composition of these materials shed from bacteria during the logarithmic growth phase.74 What

would be determined in this study and over the next several decades is that both Gram positive and Gram negative bacteria shed portions of their outermost membrane that form free proteoliposomes. These structures, termed outer membrane vesicles (OMV) if originating from Gram negative bacteria or membrane vesicles (MV) if originating from Gram positive bacteria, have lipidic compositions that are most often identical to the parent bacterium and protein components representative of the bacterial membrane, periplasm, and cytoplasm. Although significant efforts have been applied to determine their biogenesis and function, researchers can still only speculate as to the ultimate role of these extracellular vesicular vehicles. Numerous excellent reviews have been published that discuss the properties of OMV/MVs, their role in host−pathogen interactions, and other phenomena.75−77 Theories abound as to the role of OMV/MVs in nature. Given the incredible diversity of the microbial world, OMV/ I

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Figure 8. Enzyme packaging into bacterial OMVs and activity. (A) Recombinant PTE was packaged into E. coli OMV using a protein−protein ligation system referred to as Spycatcher/Spytag. Here a membrane protein (OmpA) was engineered to present the small Spytag peptide on either the N- or C-terminus of the protein that is present in the bacterial periplasm. The PTE enzyme was expressed as a fusion to the Spycatcher protein, which allowed for anchoring of the enzyme to the bacterial outer membrane during expression. The OmpA-PTE structure is pulled into OMVs as they form. (B) The activities of free PTE and OMV-encapsulated enzyme were compared following recovery from either cryostorage or rehydration of lyophilized materials. Encapsulated enzyme maintained activity following iterative cycles of freeze−thaw and after prolonged storage at room temperature for lyophilized materials. (C) Similar activity assays were performed to compare the enzyme activity following prolonged incubations over a range of temperatures. The OMV-encapsulated PTE maintained a significant percent activity for up to 14 days at all temperatures examined. Reproduced with permission from ref 86. Copyright 2015 American Chemical Society.

MVs have been shown to function in pathogen delivery,78 host defense mechanisms,79 horizontal gene transfer,80 and other activities.81 As vehicles of cell delivery, one of the most prominent features of OMV/MVs is the protection they afford to their cargo. In 2004, Ketsy and Kuehn showed that a recombinant protein, in this case green fluorescent protein (GFP), could be passively packaged within an OMV and that the OMV itself would protect GFP from proteolytic degradation.82 These observations would be further validated by other research groups and have led to new efforts to engineer bacterial OMV/MVs for specific purposes. Proteomic profiling of E. coli OMVs and the periplasmic space by Lee et al. indicated that whereas many periplasmic and membrane proteins are found within OMVs, the protein composition of OMVs is not always an accurate representation of cellular protein abundance.83,84 Although the passive packaging of OMVs is achievable as shown by Ketsy et al.,82

recombinant proteins are often not efficiently localized to OMVs as a result of some as yet unexplained phenomenon. In our studies, we sought to encapsulate PTE within E. coli OMVs to generate reagents that could be used for the degradation of organophosphate chemical warfare agents. To facilitate the controlled packaging of PTE into OMVs, we utilized a protein−protein ligation system known as SpyCatcher/SpyTag that results in the formation of an irreversible isopeptidic bond (Figure 8).85,86 The OMV-PTE construct demonstrated a consistent and prolonged ability to degrade the chemical warfare agent simulant within in vitro assays. Unfortunately, because of the complexity of the OMV itself, kinetic characteristics could not be accurately determined. Rather, what could be demonstrated was significant enhancements in enzyme stability. Initially, the enhanced stability was demonstrated by Alves et al. with a direct comparison of enzyme activity between free enzyme and OMV-encapsulated enzyme J

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Table 2. Quantum-Dot-Based Proteolytic Sensors QD/surface chemistrya

substrate dye-labeled peptideb

food safety

caspase-1

525/545 ITK-COOH 550 nm/ DHLA-PEG ∼540 nm/DHLA

dye-labeled peptide

caspase-3

550 nm/DHLA

collagenase trypsin/chymotrypsin

510 nm/DHLA 625 nm/CL4

linker on fluorescent protein dye-labeled peptideb Tb- and dye-labeled peptides

monitoring apoptosis monitoring apoptosis cancer research biosensing assay

elastase HIV-1 protease

580 nm/DHLA-PEG 495 nm/DPA

dye-labeled peptideb dye-labeled peptideb

Kallikrein MMP-7

525 nm/CL4 625 nm/streptavidin

MMP-2

565 nm 800 nm/streptavidin

dye-labeled peptideb dye-labeled Bt-peptideb Bt-inhibitor

papain

530 nm/DHLA

proteinase K

530 nm/DHLA

renin

605 nm/streptavidin

thrombin

530 nm/DHLA

dye-labeled protein dye-labeled protein dye-labeled peptideb dye-labeled

enterokinase

524 nm/glutathione

dye-labeled peptide

aminopeptidase

520 nm/CL4

urokinase-type plasminogen activator

525 nm/streptavidin

DOPA-labeled peptide AuNP quencher peptide

protease botulinum neurotoxin A

target application

notes

ref

direct peptide on QD assay two-step: proteolysis then QD assembly direct peptide on QD assay

91 47

direct protein on QD assay direct peptide on QD assay coupled assay format

47 99

trypsin activates chymotrypsin direct peptide on QD assay direct peptide on QD assay

43 144

2-step: proteolysis then QD assembly surface-attached assay

92 145

various assay formats

146

generic

enzyme labeling/ detection biosensing assay

direct protein on QD assay

147

generic

biosensing assay

direct protein on QD assay

147

Bt-

biomarker assay

single-molecule assay

148

peptide

drug discovery assay multiplexed sensing exopeptidase assay

direct peptide on QD assay

47

assayed 3 proteases simultaneously

96

electron transfer format

149

multiplexed sensing

combined with kinase detection

150

biosensing assay cell-based drug screening drug supply QC cancer research

a QD emission maxima; all materials are CdSe/ZnS core/shell. bPeptide contains a substrate sequence. ITK, innovator’s tool kit. AuNP, gold nanoparticle. Bt, biotin. CL4, compact ligand 4. DHLA, dihydrolipoic acid. DPA, DHLA-PEG-amine. DOPA, 3,4-dihydroxyphenylalanine. MMP-7, matrix metalloproteinase 7. MMP-2, matrix metalloproteinase 2. QC, quality control.

just beginning to explore the potential applications for bioderived NPs such as OMVs, nature has had millennia to perfect these systems. The enhancements to enzyme stability and activity discussed above were shown with common laboratory strains of E. coli. It remains to be seen what advantages will be discovered when we move beyond the traditional strains and begin engineering bacteria from extreme environments such as the gut, icy seas, arid deserts, hot springs, and deep underground.

following iterative cycles of environmental challenge by freezing and thawing.86 The free enzyme rapidly lost activity with each round of freezing and thawing whereas the OMV-encapsulated PTE maintained as much as 85% activity after five cycles. Subsequent work showed that protective properties were also afforded to the OMV-encapsulated enzyme over a range of temperatures and alternate storage conditions.87 OMVencapsulated PTE remained functional when stored for up to 14 days at 4, 30, and 37 °C. Additionally, OMV-encapsulated PTE was amenable to lyophilization and prolonged storage at either room temperature or when refrigerated. The free enzyme, in contrast, did not maintain any significant activity when lyophilized and rehydrated. Although these initial studies focused only on PTE encapsulation, it is believed that these enhancements in stability will likely be conveyed to other packaged enzymes. Although challenging, a few research groups are developing methods to assemble enzyme cascades on the surface of bacterial OMVs. Using a scaffold from an anaerobic bacterium that can be localized to the exterior of an OMV, Park et al. assembled a series of cellulose degrading enzymes on an OMV surface.88 The separate enzyme components were first individually expressed and then assembled on the OMV surface in vitro. Using these self-assembled constructs, enzyme activity was maintained on the OMV surface, and the assembled pathway exhibited a 23-fold increase in cellulose hydrolysis. In summary, the engineering of OMV/MVs for enzymatic purposes is still largely in its infancy. Although researchers are

6. BIOSENSORS, FRET RELAYS, CONCENTRIC FRET, MOLECULAR LOGIC, AND LIGHT HARVESTING When combined with enzymes, QD-conjugates assembled with dye-labeled peptides or other types of labeled moieties can serve a variety of applications including targeted biosensing and as scaffolds for molecular logic and light-harvesting devices. For example, the previously described QD-trypsin system highlighted the overall utility of QD-peptide conjugates as substrates for monitoring proteolytic activity. The combined structure itself is considered to be quite modular, with the QD acting as both a central display scaffold and a FRET donor. The peptides then also have a common sequential, modular structure with a terminal Hisn QD binding module, some type of spacer/linker to extend it away from the QD surface and make it available for enzyme interactions, the protease cleavage sequence, and a site for acceptor dye labeling at the opposite terminus.47 Table 2 presents a representative list of proteases targeted using this design approach. Along with K

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Figure 9. Monitoring two enzymes with one QD vector and time gating. (A) Schematic of the FRET relay configuration for sensing the activation of pro-chymotrypsin (pro-ChT) to ChT by trypsin (TRP). Representative progress curves showing the activation of different concentrations of proChT to ChT as a function of TRP concentration, measured using [SubTRP(Tb)]10-QD-[SubChT(A647)]5 conjugates. (B) ChT activity and (C) TRP activity. Note the increasing ChT activity as the concentrations of both pro-ChT and TRP increase. The arrows in (B) mark the mathematical inflection points for the highest concentration of TRP. The subscripts indicate the average number of each participant self-assembled into the QDs. Reproduced with permission from ref 99. Copyright 2012 American Chemical Society.

the detection of the protease kallikrein, which functions as the initiator of the blood-clotting process and is also adversely activated by contaminants previously found in the anticoagulant heparin.92 When compared to other assay formats, this two-step approach resulted in at least a 10-fold improvement in LOD. It was also noted that commercial QDs coated with proprietary amphiphilic ligands allowed for direct assays in some cases when the QD and peptides were preassembled.91 This suggested that it was the combination of the choice of the QD surface ligand and of a sufficient linker length between the His tag and the cleavage sequence that is critical to inducing an efficient enzyme−substrate interaction near a surface. This is also directly analogous to the results seen for trypsin activity on QD-peptide substrate assemblies when the QDs were surface functionalized with different ligands.55 Another improvement in this type of design was to eliminate the need for peptide synthesis by creating a viable recombinant substitute as was illustrated with a His6-tag-caspase-3 substrate fused to an mCherry fluorescent protein acceptor.93 This expressed protein could be easily assembled onto a QD surface, creating a fluorescent reporter for caspase-3 activity. The kinetics that were measured with this reporter showed an ∼3−

generally requiring far less enzyme and substrate to perform assays, other benefits of this format include a decreased limit of detection (LOD) and even improvements in enzyme activity. These aspects are discussed in more detail in several review articles.48,89,90 These same materials have been utilized in other ways to create interesting sensors and/or sensing formats. For example, Sapsford et al. sought to create a sensor for botulinum neurotoxin A, a potent protein toxin that becomes an active endoprotease that specifically cleaves SNARE (soluble Nethylmaleimide-sensitive attachment protein receptor) proteins that adversely affect neurotransmission.91 In the first iteration tested, the peptide was not readily cleaved by the botulinum protease when bound to a QD, presumably because of steric inhibition and a lack of access to the peptide’s cleavage site. However, if the peptide substrate was first exposed to botulinum neurotoxin A and then assembled on the QD donor, then a time-dependent loss in FRET efficiency was observed, allowing for the facile detection of this toxin. The QD donor is essentially used as a visualization reagent to transduce the signal with the FRET reflecting the level of protease activity. Similar two-step assays have also been developed for L

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Figure 10. Intermittent regeneration cycles for potential set-reset functionality shown schematically with the Tb-QD-A647 three-fluorophore system. PL plots display the output PL intensity immediately (blue) and 55 μs (orange) after 400 or 339 nm UV excitation, respectively. The spectra coding for the six total states with intermittent regeneration are shown as follows: (A) 4 Tb to QD and no A647; (B) 4 Tb to QD and 4 A647; (C) 4 Tb to QD, first regeneration cycle by sequential addition of trypsin (1 mL of 106 mM) that cleaves PEP A-A647 followed by the addition of soybean trypsin inhibitor; (D) 4 Tb to QD and 6 A647; (E) 4 Tb to QD, second regeneration cycle; and (F) 4 Tb to QD and 10 A647. Reproduced with permission from ref 100. Copyright 2013 Royal Society of Chemistry.

5-fold improvement in the KM value compared to assays using similar free peptide substrates. This again might be explained by enzyme hopping along the QD surface from substrate to substrate, although that usually has a larger effect on the catalytic rate kcat. A similar improvement in KM was observed when a fluorescent caspase-3 peptidyl substrate was fused to the QD surface ligand’s proximal terminus using carbodiimide chemistry as an alternative to the Hisn-tag linkage.94 This was another demonstration of the flexibility of this QD-peptide sensor design approach, a point epitomized by the work of the Snee group and their diverse and elegant FRET-based sensors involving QD ligand chemistry.89 Continuing with development based on this same design paradigm, more sophisticated biological sensors have been created by displaying peptides decorated with multiple different labels around QDs. The first such configuration was termed concentric FRET and consisted of placing two separate and

spectrally distinct dye-labeled peptides around a QD. This allowed the QD donor to preferentially sensitize the first dye acceptor that has better spectral overlap with it, and then this, in turn, transfers energy to the second more red-shifted dye acceptor.95 The sequential FRET processes can then be used to monitor two signals corresponding to the activity of two proteases or two DNA oligos. This format has now even been extended to include three acceptor dyes placed around a QD and has shown the ability to track the activity of three proteases.96 A second type of design was based on multistep FRET relays utilizing both dye-labeled and rare earth chelatelabeled peptides. The terbium chelate lumiphore utilized in this sensing assembly displays an excited-state lifetime in the low millisecond range, and this is the key to its utility. The fully assembled QD-Tb-dye peptide conjugates were interrogated in 2 modalities: a prompt mode accessed the QD-dye FRET component with a delay between excitation and measurement M

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Figure 11. Self-illuminating QD-DNA photonic wires. (A) Schematic of the self-assembled energy-transfer system. Luciferase (Luc) appended with a terminal (His)6 ratiometrically coordinates (i.e., control over display valency) to the QD. Dye-labeled DNA wires are formed by prehybridization and include a terminal (His)5-peptido-DNA sequence to facilitate similar QD assembly. Functionally, coelenterazine H substrate (Coel) is enzymatically oxidized by Luc, giving rise to excitonic energy that sensitizes the proximal QD by BRET. The QD then redirects this energy and sensitizes the proximal dye on the DNA photonic wire, giving rise to a sequential FRET cascade. The assembly number of Luc and photonic wires per QD can be controlled, which, along with Coel concentration, provides control over the energy-transfer efficiency. (B) Normalized spectra of Luc6-QD-DNA8 constructs as the displayed acceptor dyes are extended along the DNA from Cy3 up to Cy5.5 (→ = BRET/FRET step). (C) Deconvoluted Luc6QD-DNA8 component spectra. The subscripts indicate the average number of each participant self-assembled into the QDs. Reproduced with permission from ref 101. Copyright 2015 American Chemical Society.

chelate could serve as a unique memory function.56,100 For this work, two peptides containing either the Tb chelate or an Alexa 647 fluorophore were conjugated to QDs to create 3-dye FRET relays composed of the initial Tb lumiphore donor, the QD as either a FRET acceptor or relay, and the terminal Alexa fluorophore acceptor. The logical inputs were the peptide/dye ratios, and the outputs were the ratios of the three different fluorescence signals (either with or without a time delay). This arrangement could be configured to create AND, OR, INHIBIT, XOR, NOR, and NAND Boolean logic gates as well as complex arithmetic circuits including the half adder/ half-subtractor, 2:1 multiplexer/1:2 demultiplexer, and a 3-digit, 16-combination keypad lock.56,100 Moreover, the fact that the fluorophores were bound to the QD via peptides implied that these assemblies could be configured as substrates for proteases. This added another unique aspect to this biophotonic device, the ability to repeatedly reset the signal and toggle the function by treatment with a protease and subsequent addition of a protease inhibitor. This is shown schematically along with some representative data in Figure 10. A later series of studies combined the enzyme luciferase (Luc) with FRET relays and QDs to create self-illuminating

of 55 μs.97 The use of Tb chelates as donors also provides for some of the largest attainable Förster distances (R0), allowing for some of the largest viable donor−acceptor separations (i.e., access to larger bioconjugate sensing assemblies if needed).98 Functionally, this time-delayed relay configuration provides access to two almost orthogonal channels of information allowing independent monitoring of two disparate or linked biological processes in a single QD assembly. The potential of this sensor was initially highlighted by detecting unrelated DNA sequences along with the activity of two proteases.97 Notably, the LOD obtained using the timegated approach was 3−30 fold lower than for a standard QDpeptide-organic dye implementation because of its ability to reject background fluorescence. The long-term potential of this approach was underscored by monitoring the trypsin-catalyzed activation of inactive pro-chymotrypsin to the active chymotrypsin with just a single QD sensor (Figure 9).99 Using similar materials and principles, Claussen and coworkers exploited time-gated fluorescence to create complex photonic logic devices in which the time-delay aspect of the Tb N

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light harvesting systems.101,102 Luc is a bioluminescent enzyme derived from fireflies that utilizes coelenterazine and O2 as substrate to produce light, and it is commonly exploited in many biological assays. Using Luc as an initial bioluminescent resonant energy transfer (BRET) donor that was displayed around QDs allowed the latter to act as a central light harvesting acceptor and redirecting relay. Here the light cascade or FRET relay is enzymatically induced by addition of chemical substrate. The QD then transfers its Luc-derived excitation energy to bound peptide-fluorophores102 or alternatively to bound DNA photonic wires containing a series of sequentially arranged fluorophores (Figure 11).101 In both cases, the efficiency of energy transfer was shown to be dependent on the ratio of Luc to QD and the ratio of terminal FRET acceptors to QD, with these ratios controlled stoichiometrically by selfassembly using Hisn-based metal-affinity coordination. Overall, such devices can cumulatively provide some unique properties including allowing for the colocalization of numerous BRET and FRET donors/acceptors on a common central photonically active nanoscaffold; the nanoscaffold simultaneous acts as a FRET relay, providing for a self-illuminating enzymatically induced signal relay; and offering the designer a degree of input control over the spatial and spectral direction of energy transfer.

insoluble forms leads directly to heterogeneous catalysis, and a prime benefit of NPs is then simply to increase the surface area. In contrast, enzymes are often water-soluble, so surface mounting has the opposite effect of decreasing access. The surface must then be providing other benefits, and one advantage of an NP format is that it minimizes the reduction in access associated with being on a surface. The question then is what are the other benefits? It seems too much to hope that the advantage of mounting enzymes on NPs would result from a single physicochemical mechanism valid for all enzymes. And indeed, a number of possible benefits of being on an NP surface have been either suggested or identified in the literature including (but certainly not limited to) improvements in enzyme conformation, enzyme stability, enzyme affinity (or KM), catalytic energy barrier reduction, localized confinement, substrate trajectory optimization, colocalization, substrate accumulation, and avidity.21,22,104 Thus, it seems likely that multiple processes are at work in what appears to be a complex cooperative process, and their relative importance may depend on the particular circumstance and factors such as the nature of the NP material, the passivating and stabilizing surface ligands, the enzyme, the substrate, and the other solutes. For example, our work with QDs and PTE suggests that the enhancing mechanism is an improvement in the rate-limiting product-dissociation step, whereas the work with β-Gal initially pointed to localized substrate accumulation around the NP-bioconjugate.70,104 Similarly, heterogeneous attachment of AP to QDs with biotin−avidin chemistry resulted in a marked loss in enzymatic activity105 whereas homogeneous attachment of the same enzyme to the same NP material resulted in enhanced activity.56 Given the benefit of all of the other examples described, we do not believe that it is simply just optimizing the enzyme orientation that makes the key difference in this latter example, but it still clearly contributes. Whatever the mechanisms of enhancement, they surely derive from the unique properties of the microenvironment surround the NP. This nanoscopic environment includes the NP surface itself, the surface ligands that stabilize the colloidal NP, the enzymes, and/or substrates that are attached to the NP and all the other reactants/cofactors required for the catalysis along with buffer, ions, and other reaction stabilizers. As presciently observed by Parak and colleagues, this nanoenvironment is very different from the bulk and is influenced by the surroundings along with exerting its own influence.106 Some of the postulated physicochemical characteristics of this interface may extend to density and viscosity gradients; changes in ionic and pH properties; changes in the predicted Debye−Hückel charge and ion screening at the NP surface; changes in the pKa’s, polarity, and solvation; phase separation; and hydrodynamic boundary layers.106 Moreover, enzymes can have substantial mass and their own hydration layers, which will contribute, alter, or be altered as well when inserted into this interfacial environment.67 Confirming the complexity of the NP’s hydration layer, Zobel and colleagues recently reported that water and other organic solvents are structured in the immediate vicinity around an NP and that this is most likely a universal phenomenon.66 Moreover, this structured environment may extend out from the NP surface a distance larger than the NP size. Elucidating how some of these physicochemical properties act in concert, in what may be a conditionally dependent manner, to provide enzymatic enhancement at this interface now seems extremely daunting

7. WHAT IS ACTUALLY BEHIND NANOPARTICLE-INDUCED ENZYMATIC ENHANCEMENT? As suggested by the diversity of examples in Table 1 and related review articles,21,22,24 evidence is building in the scientific literature for the idea that enzymatic enhancement at NP surfaces is a common phenomenon. However, why this should be is a much more difficult question to answer. Why should the mounting of an enzyme on a curved nanoscopic surface enhance its activity? And why should this trick seem to work for a wide variety of enzymes? The complete answers to these questions must remain for now the subject of research, and here we offer only further framing of the issues and some speculative comments. For the purpose of discussion, it is illuminating to consider the parallels between the situations of NP-enhanced enzymes and the well-known acceleration of heterogeneous catalysis that occurs on the nanoscale.103 The most important similarity between the two is the inherent challenges presented by the essentiality of surfaces and of nanoscopic/atomic dimensions. For an in-depth understanding, one would want to study the catalytic behavior of a single NP; however, both fabrication and characterization at this level are exceedingly difficult, especially if atomic/molecular fidelity is needed. Absent this, experiments must focus instead on ensembles of nonidentical NPs, and this necessarily weakens any inferences about the mechanism. Consequently, for both NP-based inorganic and enzyme catalysis, progress has come largely from trial-and-error experiments supported by phenomenological models, and with the understanding limited to identifying plausible mechanisms that are consistent with the ensemble measurements. At the same time, there are important differences between these two types of NP-based catalysis, with the main one being that the inorganic catalysts tend to be individual atoms (e.g., Pt), whereas the organic enzymes are macromolecules (proteins). The difference is not, however, as great as it might seem because enzymes frequently act by expropriating metal ions present in the solution as a key player in their chemical processes. That the inorganic catalysts usually occur in O

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nanoscale. For these reasons, most theory/calculations employ macroscopic or continuum methods phrased in terms of concentrations of the various chemical species that can be defined, at least in principle, as space/time/ensemble averages over the microscopic variables (a process often referred to as coarse-graining or a continuum approximation). Generally speaking, the continuum theory of an enzymatic reaction consists of differential equations describing the relevant chemistries and their coupling to diffusion and possibly to convective fluid flow and thermodynamics. The relative importance of the different phenomena expressed by these equations can be understood in terms of a set of characteristic times associated with the reactions, the diffusion of various species, and so forth. Typically, the dominant flows are diffusive and the relevant parameters are diffusion times (for each species) defined by τD ≡ L/D, where L is a characteristic spatial dimension and D is the relevant diffusion constant. In certain situations such as when L is large (e.g., at very low solute densities),111 D is small (e.g., in confined geometries),112 and/or the reaction rates are very high, the diffusion times can be similar to (or longer than) the reaction times, and it becomes necessary to consider the diffusion explicitly. However, in most situations τD is much shorter than the reaction times, the diffusion is rapid, the concentrations are essentially uniform in space, and the system is said to act as if it is well-stirred. The governing equations then reduce to the ordinary differential equations of chemical kinetics, which are easily solved, often analytically, but if necessary on the computer. Furthermore, when surfaces are involved, a kinetic description is often still viable, with the only modifications being associated with a need to include surface concentrations as well as the volumetric ones. For the NP problems of interest in this review, the surface variables permit a representation of effects of the NP hydration layer, changes in solvation, pH, and ionic strength, all of which are potentially important in the NP enhancement of enzymatic activity. When no NPs are present, the kinetics of free enzymes are most often analyzed using the standard MM model.51,109 As given in eq 2, the associated reaction scheme consists of the reversible formation of an enzyme−substrate complex followed by the reaction and product dissociation, with the latter two steps possibly split as in the work of Raushel113 and as shown in eq 2. The equations that describe these reactions may very often be simplified by assuming (Briggs−Haldane) that the concentration of the complex is quasi-static (which is met when the condition [E]0 ≪ [S]0 + KM is satisfied),109 in which case the reaction velocity obeys the well-known MM formula:

at the least. Moreover, as already noted, this situation is made much more challenging by the almost complete lack of analytical techniques that can provide a detailed characterization of this critical environment.107 Thus, at present we can do little more than acknowledge the complexity of this problem and appreciate that only with much more research can a detailed understanding be approached. This reality has important ramifications not only for NP-enzyme enhancement but also for a host of other biological applications of NPs such as in theranostics, where protein corona buildup around NPs in vivo continues to be a major challenge to further development.108

8. KINETIC MODELING OF NANOPARTICLE-INDUCED ENZYMATIC ENHANCEMENT Although we lack direct robust physical methods to probe the NP interface, we have found kinetic simulations of enzymatic activity in this context to be a powerful tool. In general, the dream of using fundamental theory to understand physicochemical phenomena ab initio continues to attract but remains mostly unrealized. In part, the difficulty comes from the complexity and heterogeneity of the relevant physics/chemistry and the associated computational burden. In particular, there is a need to analyze a large number of atoms residing in aqueous media (with its high dielectric constant) over long periods of time, and this presents challenges despite progress in computer hardware and algorithms. For enzyme-NP systems, the situation is compounded by manifest inadequacies in our ability to experimentally control and characterize their geometry/configuration and behavior on the nanoscale over significant time scales. For these reasons, it seems sure that macroscopic methods will continue to be the workhorse approach for analysis and modeling of enzyme-NP systems for the foreseeable future. Macroscopic or continuum methods are well-matched to ensemble measurements and represent an optimal compromise in which the basic physical and chemical phenomena are captured without being overloaded with superfluous details that cannot be checked experimentally and that add little real understanding. Under most circumstances, it is appropriate to employ such models in the well-stirred kinetic limit, and this makes the equations especially simple and tractable. Indeed, the broad applicability of this limit is one of the chief attractive features of the macroscopic approach. However, the approach can also be extended to include diffusion, convection, correlation, complicated chemistries, allosteric effects, and confined spaces. Finally, macroscopic methods can often provide an overarching framework that can serve to organize data and to identify targets for experiment and/or for microscopic calculation. The simplest example of this is the MM model and its parameters kcat and KM that are so often used to characterize enzymatic action.51,109 Even in the simplest situations of enzymes free in solution, analyzing the action using microscopic theory (i.e., at the level of atoms, force fields, and/or quantum chemistry) is challenging because of the number of atoms and the time scales involved and because of the range of coupled phenomena that must be described.110 The situation becomes even more daunting when NPs enter the picture because of the many experimental uncertainties associated with the lack of control of the geometry/configuration of individual NP-enzyme conjugates and the inadequacy of available physical/chemical analysis tools for precise experimental characterization at the

V≡

k [S][E]0 d[P] d[S] =− = cat dt dt KM + [S]

(3)

The variables here are as defined previously. As this equation shows, MM kinetics are characterized by two coefficients, namely, the catalytic rate kcat and the Michaelis constant KM ≡ (k−1 + kcat)/k1. Equation 3 is typically applied to the initial turnover rate because the conditions at early times are generally best known. And for convenience in interpreting such data, there are a variety of plots in common use that allow the MM parameters in eq 3 to be extracted graphically rather than through numerical regression (e.g., the Lineweaver−Burk double reciprocal plot).51 When the reaction is fast, the initial rate data become harder to obtain, and then the full history (referred to as a progress curve) is modeled, as was discussed P

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A more fruitful approach to NP-enzyme modeling is to develop generalized kinetic models that expand the MM chemical kinetics of eq 2 to include a variety of other surfaceassociated species and chemistries. One example of such a model for the substrate-on-NP configuration was discussed in ref 21. In this model, there was an accounting for the capacity of the NP for the substrate and the disappearance of this substrate under various putative mechanisms such as scooting, where the enzyme reacted with more than one substrate on a given NP. In this way, various physicochemical scenarios could be investigated and compared with experimental measurements to assess their plausibility. Enzyme-NP behaviors become even more complex and interesting when an enzyme cascade is involved (i.e., a situation with two or more enzymes in which the product of one enzyme is the substrate for a second enzyme). One example that we are currently studying involves enzymes of glycolysis and, in particular, pyruvate kinase (PykA) and lactate dehydrogenase (LDH), where the former catalyzes the reaction of adenosine diphosphate (ADP) and phosphoenol pyruvate (PEP) to pyruvate and adenosine triphosphate (ATP) and the latter transforms the pyruvate intermediate plus nicotinamide adenine dinucleotide (NADH) to lactate and NAD+. When attached to NPs, we observed that enzymatic turnover of the PykA-LDH combination was accelerated, and reasons for this are being explored with both experiment and simulation (manuscript in preparation). Because the simulations included various complicating phenomena, such as inhibition, that are needed for physical fidelity but that tend to obscure the basic structure and issues of the modeling approach, for this review we instead continue our discussion using an ideal system consisting of two NP-mounted model enzymes that are assumed to obey MM kinetics. When assembling an enzyme cascade on a NP, a primary aspiration is to further accelerate turnover by accessing a channeling mechanism, whereby the product of the first enzyme (called the intermediate) is fed directly to the nearby second enzyme without going into the solvent as it would were there no NP.116 To be effective, channeling requires that the intermediate (i) be capable of diffusing across the NP surface from one enzyme to the other, and (ii) this diffusion occurs more efficiently than the competing process of escape into the surrounding medium. In these processes, the surface diffusion takes place in the NP’s hydration layer that is composed of the passivating ligand shell, the enzymes, and the water and counterions that are organized around the hydrophilic NP. This layer is of course in intimate contact with the surrounding bulk solvent, and free molecules will generally partition between the two. To create a mathematical model of the behavior, we go beyond generalized kinetics and develop a reaction−diffusion model in which the surface diffusion of the intermediate is explicitly considered. For our situation, the relevant equation is

earlier in connection with the integral of eq 3 as given in eq 1. Finally, there are many generalizations of eqs 1 and 3 for free enzyme kinetics that account for situations such as when a cofactor is involved (e.g., bi kinetics), when inhibition (typically by the substrate or product) occurs, or when the enzyme is allosteric.51 When the enzyme situations involve NPs, the turnover data (e.g., the initial rate versus substrate concentration) will often manifest a saturating characteristic that looks MM-like. In this case, the simplest approach is just to apply eq 3 and deduce eff eff effective constants kcat and KM . As emphasized in this discussion, these constants are often enhanced over their free enzyme values by virtue of the NP attachment, and a variety of reasons for enhancement were discussed earlier. In developing such interpretations, it is important to recognize that excellent curve fits of the data by eq 3 are necessary but not sufficient conditions for the correctness of the chemistry and mechanisms as postulated in eq 2, and it is for this reason that the constants so determined are referred to as effective. Apart from practical concerns (e.g., those associated with limited availability or solubility of the NPs), the main issue of principle has to do with the basic heterogeneity of the system containing NPs. Thus, for example, in the free enzyme case the enzyme concentration is usually easily defined as a uniform value, whereas if the enzymes are concentrated on the NP surfaces then there will be localized regions of much higher concentration. Similarly, the substrate can partition into the NP’s hydration layer, thereby achieving a much lower effective diffusion constant and hence much longer diffusion times, perhaps undermining the kinetic model as discussed earlier. Despite these caveats, the simplicity and familiarity of the MM model are strong reasons for continued use, and although the meaning of its parameters can be questioned, they can still be of practical value for comparing experiments involving NP-enzyme systems. One basic consequence of having a surface-attached enzyme is that the access of the free substrate will be reduced (or analogously for free enzymes in the converse case of surfaceattached substrates). This can enter in two ways, one being a steric blocking or partial blocking of the enzyme’s active site(s) and the other being a slowing of diffusion due to a reduction in the accessible space. Large area surfaces can have other issues associated with hydrodynamic boundary layer stagnation, laminar flow, and other phenomena that are not of concern in this NP-focused review. The latter effects will also impact product escape.114 The steric blocking effect will obviously be most pronounced if the enzymes are attached to the surface in a random fashion because they would then sometimes reside with the active site pointed toward the NP surface and hence would be inaccessible. As was discussed earlier, the situation is much improved if the enzyme attachment scheme is capable of ensuring proper orientation, although this strategy becomes harder to implement with multimeric enzymes. With respect to the reduced access, one approach that has been used is that of collision theory in which the reduction is estimated on the basis of a ballistic model that is then used phenomenologically to adjust the MM parameters.115 A simple prediction of this crude model is that smaller NPs will have less of a shielding effect, with of course no shielding at all in the no-NP limit. Paradoxically, the latter enzyme-only configuration should manifest the best kinetics in this scenario, which is not seen and confirms the need for the NP to contribute to the critical parameter.

∂is − Dis∇s 2 is = kcat1c1 − k 2e 2is + k −2c 2 − k iis + k −ii ∂t

(4)

where is and i are the intermediate concentrations on the NP surface and in solution, respectively, ∇s is the surface gradient operator, Dis is the surface diffusion coefficient of the intermediate, ki and k−i are the respective off and on rate constants describing the partitioning of the intermediate, and the other quantities relate to the MM kinetics of the two enzymes. Also important in solving eq 4 are the relative positions of the enzymes on the NP surface. Q

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Figure 12. Kinetic modeling. (A) Effect of relative distance between NP-bound enzymes on channeling and speed-up of turnover. Arrows in the direction of decreasing distance. (B) Effect of NP surface diffusion coefficient of the intermediates on channeling and speed-up of turnover. Arrows in the direction of increasing diffusion coefficient.

stabilizing a given enzyme polymeric structure and long-term activity. Other characteristics appear to play a somewhat counterintuitive role. For example, increasing the density of enzymes displayed on the NP appears to be counterproductive in many cases, suggesting that some property associated with the interface between the NP and the bulk solution must be maintained. NP size is also important and seems to be inversely correlated with enhancement. However, far more examples still need to be described in order for the previous points to move from just interesting observations to common characteristics. The ability of the NP-enzyme bioconjugate to engage in diffusion, albeit at a much slower rate than for a free enzyme, also appears to be an important contributor. The roles of NP shielding and substrate trajectories are far more complex in this scenario and do not lend themselves to an easy interpretation. Overall, it is quite likely that a very complex interplay among many different variables is jointly responsible for the enhancement; furthermore, the arrangement of variables involved and their individual quantitative contributions may also change with different NP materials and enzymes. One contributor is not in dispute: the presence of the NP and its surrounding interfacial environment is the critical determinant. Future efforts toward understanding the origin of enhanced enzymatic catalysis at an NP interface will be predicated on one major aspect, namely, fundamental studies as related to all aspects of these materials and their function. Clearly, far more work is needed in this regard across a range of related variables. This will include, for example, looking at different classes of enzymes and enzyme activity along with sizes of enzymes/ substrates and differences in NP materials, surface ligands, sizes, and other characteristics. Within these types of studies, a full exploration of any and all changes in enzyme structure and function as related to kinetic activity will be critical. Control over the ability to display enzyme on NPs in different prescribed orientations will also be extremely helpful here. Understanding how enzymes are enhanced by other materials such as DNA can help offer some insight into how these studies should be undertaken.63−65 The concomitant development of powerful new analytical tools with the capability to intimately characterize minute properties of these type of NP-enzyme conjugates will also greatly contribute.68,107 Although only briefly touched upon in the above discussion, in conjunction

To illustrate the above reaction−diffusion model, we consider two situations involving just one enzyme of each type per NP. In one case, the enzyme positions are at the same fixed relative distance from each other on every NP in the ensemble, and in the other case, the enzyme positions are randomly distributed across the ensemble, as would happen in most experiments. For these simulations, we fix the NP size (with a diameter of 10 nm), substrate and enzyme concentrations, MM parameters, and ki and k−i rate constants. In Figure 12A, we compare progress curves for five NP designs in which each NP has one enzyme located at its north pole and the other located at declinations of 0, 45, 90, 135, and 180°. As expected, as the distance between the enzymes decreases (by having a reduced declination), the channeling becomes more effective and the turnover becomes more rapid. In the second simulation example, we consider the randomly distributed enzymes and vary the diffusion coefficient Dis. As seen in Figure 12B, a higher value of Dis results in increased channeling and faster turnover. In interpreting data that potentially involves channeling, one would first characterize each enzyme individually and how it behaves and is often enhanced when attached to an NP. Predictions of the enzyme cascade can then be performed with various values of the intermediate diffusion constant. If the experimental data is not reasonably explained by Dis being small, then that one has strong evidence in favor of a channeling hypothesis becomes the more likely explanation. Microscopic modeling approaches such as ones based on Monte Carlo simulation are possible and can also be appropriate.110−112 As we have noted, the complexity, the time scales, and the uncertainties of most experiments make such approaches unsuitable as a general tool. Instead, they are typically most helpful for understanding mechanisms, both in a qualitative sense and as a way of estimating specific parameters in a macroscopic description

9. OUTLOOK AND PERSPECTIVE So what can we postulate is responsible for the enhanced enzymatic activity so often noted at an NP interface? Some architectural properties of the NP-enzyme conjugates clearly contribute in a positive manner such as controlled enzyme display with the binding site clearly available. In some cases, it is believed that NP attachment even contributes indirectly by R

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Figure 13. GOX-HRP coupled activity. (A) Chemical reactions carried out by GOX and HRP. The hydrogen peroxide produced by GOX is used as a substrate for HRP. The end product is a TMB charge-transfer complex (DTMB) that produces a strong absorption signal. (B) Diagram of the strategy for coupling GOX and HRP activities with QD-immobilized HRP. Free GOX will produce hydrogen peroxide that can be used by QDbound HRP to produce DTMB. (C) Specific activity (S.A.) measurements for the activity of HRP-loaded QDs with H2O2 as a substrate and 1 mM TMB. HRP activity was measured for samples containing 1 nM HRP and varying concentrations of H2O2. The samples contained no QD (black) or 2 nM 655 QD (red) or 2 nM 520 QD (green). (D) The specific activity (S.A.) of the samples containing 2 equiv of 655 QD per HRP (red) as well as samples with no QD (black) was measured at varying ratios of GOX to HRP. Reproduced with permission from ref 133. Copyright 2017 Royal Society of Chemistry.

example, attaching PTE to QDs showed that it took a far higher concentration of a competitive inhibitor to achieve the same effect as that seen for free PTE.104 Moreover, the effects of the in vivo environment and corona buildup on the construct will clearly be of critical importance.108 Sensors that target enzyme activity by recognizing and measuring substrate concentration or enhancing signal transduction by converting an exogenous substrate to a measurable product in conjunction with a sensing event will also benefit greatly from catalytic enhancement at a NP interface. The main payoff will be in the form of increased sensitivity and long-term sensor/conjugate stability. Interestingly, the effects of the NP display on enzyme specificity are currently almost completely unknown but certainly merit investigation. The Algar laboratory’s recent work serves to highlight some novel potential applications in the sensor realm. The ability to simultaneous monitor two or even three separate enzymatic events with a single NP vector using either multistep concentric or time-gated FRET is very promising.96,97 This can greatly simplify the necessary sensor materials used along with reducing the required instrumentation in many cases. Recent work that combined both QD-based FRET and electrontransfer modalities into a single NP sensor highlighted the latter benefits because the readout is just fluorescence.122 As highlighted by the use of QD-based sensors to monitor trypsin

with kinetic modeling the computational chemistry toolbox including density functional theory (DFT), molecular simulation, Markov state theory, and the like have much to offer as tools to probe the multiscale and dynamic interactions between enzymes and NPs.117,118 Looking to the future, the crucial questions are how will research on the NP-enhanced enzyme approach develop, and what will be its impact from a practical perspective? Of course these questions cannot be answered definitively, but some brief speculation is in order. Easiest to see is how lessons learned in current research may be exploited in developing applications, especially because early applied work has already begun to appear in the literature. Such efforts can be loosely organized into three generalized areas: (i) theranostics, (ii) sensors and related NP hybrids, and (iii) directed biocatalysis. Within the field of theranostics, much of the current research utilizes NPs as scaffolds that host the nascent molecular assemblies.119,120 Although the field of theranostics is mostly beyond our current scope, some relevant points are still important to mention. Because most drug targets are enzymes, it is not unreasonable to expect that future theranostic devices will contain enzymes and/or enzyme-inhibiting drugs.121 Thus, many of the lessons learned and the understanding gained from placing either substrate or enzyme on a NP will be relevant to achieving the desired activity in the final composite. For S

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activation of pro-chymotrypsin,99 the ability to target coupled enzymatic events has perhaps the greatest potential because it can allow the tracking of complex coupled events in a spatiotemporally specific manner. The main challenge here with a potentially high payoff is to adapt these sensors for directed application in live cells and other relevant models.123 Beyond just sensing, imaging, and related probe utility, NPenzyme and NP substrate constructs have also much to offer for molecular logic applications.100,124 This may allow some type of information processing to be combined with a sensing event in a rudimentary smart nanosensor. The ability to generate and direct light in a stand-alone manner in these configurations can also help such sensors generate their own energy, communicate, and transduce a signal to an observer.101,102 In terms of directed biocatalysis, as discussed above, NP display can serve as a common in vitro scaffolding approach to closely arrange one or many related enzymes, and it brings with it the potential to access both enhanced activity and long-term stability. The real payoff may be in the ability to loosely colocalize the enzymes that make up a concerted multistep biosynthetic cascade and allow them to engage in what, for all intents and purposes, is channeling behavior.116 Given that only the enzymes of interest are included, this would have the added benefit of removing any and all competing reactions and pathways from the background. Moreover, this strategy may not need to have the enzymes placed in a linear order that exactly matches the steps in the cascade,125 but instead colocalizing them around an NP may be sufficient to mimic the confinement of the native cytoplasmic environment. Indeed, this approach of what is essentially true cell-free synthesis is accepted as a viable avenue of synthetic biology that can deal with many of the issues that surround the use of live cells and the engineering of their metabolic pathways.126,127 However, it has not received nearly as much attention as cellbased formats to date. This presumably arises from the format requirements, which include the need to clone, express, and purify all of the enzymes, optimize reaction formats, minimize diffusional limitations, and regenerate critical cofactors.128 Concerted efforts have already begun to create a solid foundation for this approach. The Chen group has been a pioneer in this area, having investigated the assembly of different enzymatic cascades on various nanoscale scaffolds including OMVs, DNA, and other protein-based assemblies.88,129,130 There are several other examples of similar efforts with different enzyme systems.131,132 Current efforts toward assembling and, more importantly, understanding how to access enhanced multistep biocatalysis on a NP are reflected in two recent reports. Vranish and coworkers showed that NP-driven enzymatic enhancement could be maintained in a coupled enzymatic system even if only one of the enzymes was displayed on an NP while the other remained in solution.133 This format used the prototypical enzyme pair of glucose oxidase (GOX) and horseradish peroxidase (HRP), which is commonly applied for glucose detection along with QDs as the NP scaffold (Figure 13). HRP binding to QDs had a significant beneficial effect on the enzymatic activity, producing a >2-fold improvement in kcat that was postulated to arise from substrate affinity for the QD surface. When coupled to solution-phase GOX, and the ratio of GOX to HRP was adjusted to allow the latter enzyme to be the rate-limiting step, and QD-induced rate enhancements of HRP were maintained. For this complex system, kinetic analysis was essential to understand quantitatively the underlying processes

and to providing insight into the rate-limiting mechanisms. Related to this, the Travis laboratory reported on a 10-step enzyme pathway designed to convert glucose to lactate tethered to 500-nm-diameter microparticles.134 Individual enzyme activity was found to be higher in solution; however, the overall conversion efficiency (defined as [lactate product]/ [glucose consumed]) of the entire pathway was higher when tethered. Although not accessing the NP-enhancement phenomena described here (as evidenced by a lack of enhancement of the individual enzymes), their results nevertheless suggested a benefit from colocalization that presumably would arise from some type of channeling effect. It is not clear why none of the individual enzymes displayed any enhancement effects, but we do note that this particle scaffold is far larger than most of the NPs described in Table 1 for the enzyme on NP configuration. This perhaps indicates the presence of some type of NP size or curvature limit to individual enzyme enhancement or even one that originates from a particular constituent material and clearly also merits further investigation. Beyond the examples described here, it is also highly probably that NP-enzyme constructs displaying enhanced catalytic activity will develop and find applications that are unanticipated. Overall, just as an enzyme can catalyze and speed up a reaction by orders of magnitude, so too will the combination of enzymes and NPs speed up the creation of new multifunctional bionanotechnologies. This pursuit will be directly aided by the elucidation of new enzyme chemistries as more organisms and their genomes are catalogued and their catalytic properties are harnessed in conjunction with the progress in developing improved nanomaterials, bioconjugation chemistries, and the ability to analyze the physicochemical properties of the NP-enzyme conjugates in great detail.



AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. ORCID

Igor L. Medintz: 0000-0002-8902-4687 Notes

The authors declare no competing financial interest. Biographies

James Nicholas Vranish is an assistant professor of chemistry at Ave Maria University. He received his B.S. in biochemistry from the University of Notre Dame in 2006 along with a minor in theology. In 2015, he completed his Ph.D. in the Department of Biochemistry and Biophysics at Texas A&M University in the laboratory of Dr. David T

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Barondeau. From 2015 to 2017, he was a National Research Council fellow at the Naval Research Laboratory in Washington, D.C. in the laboratory of Dr. Igor Medintz. His research interests include enzymology, bioinorganic chemistry, protein engineering, and cellfree metabolic engineering.

Igor L. Medintz received a Ph.D. in molecular, cellular and developmental biology from the City University of New York in 1999. This was followed by a NCI Fellowship with Prof. Richard Mathies of the College of Chemistry, University of California, Berkeley and some industrial experience with Vertex Pharmaceuticals. He began at the Naval Research Laboratory (NRL) as a National Research Council Fellow in 2002 and as a research biologist in 2004. He currently serves as the Navy’s Senior Scientist for Biosensors and Biomaterials with NRL’s Center for Bio/Molecular Science and Engineering. His research interests include how nanoparticles engage in energy transfer and how biological processes are altered at a nanoparticle interface.

Mario G. Ancona received a B.E.S in bioengineering from Johns Hopkins University and an M.S. and Ph.D. in physics/mechanics from Rensselaer Polytechnic Institute. He has been an employee at NRL since 1984 in the Electronics Science and Technology Division, where



his research has mostly involved the modeling and simulation of a

ACKNOWLEDGMENTS The authors acknowledge support from ONR, NRL, the NRL Nanosciences Institute, and the National Institute of Food and Agriculture, U.S. Department of Agriculture, under award number 11901762 for funding the research.

broad range of phenomena in electronics, nanoscience, chemistry, and biology. In addition, he spent 18 years as part-time faculty in the Johns Hopkins University Master’s Program in Applied Physics, teaching many different courses and authoring a textbook titled Computational



Methods for Applied Science and Engineering (Rinton Press, Princeton, 2002).

REFERENCES

(1) Stockbridge, R. B.; Lewis, C. A., Jr.; Yuan, Y.; Wolfenden, R. Impact of Temperature on the Time Required for the Establishment of Primordial Biochemistry, and for the Evolution of Enzymes. Proc. Natl. Acad. Sci. U. S. A. 2010, 107, 22102−22105. (2) Nguyen, L. A.; He, H.; Pham-Huy, C. Chiral Drugs: An Overview. Int. J. Biomed. Sci. 2006, 2, 85−100. (3) Clomburg, J. M.; Crumbley, A. M.; Gonzalez, R. Industrial Biomanufacturing: The Future of Chemical Production. Science 2017, 355, aag0804. (4) Dudley, Q. M.; Karim, A. S.; Jewett, M. C. Cell-Free Metabolic Engineering: Biomanufacturing Beyond the Cell. Biotechnol. J. 2015, 10, 69−82. (5) Nielsen, J.; Keasling, J. D. Engineering Cellular Metabolism. Cell 2016, 164, 1185−1197. (6) Woolston, B. M.; Edgar, S.; Stephanopoulos, G. Metabolic Engineering: Past and Future. Annu. Rev. Chem. Biomol. Eng. 2013, 4, 259−288. (7) Kataoka, M.; Miyakawa, T.; Shimizu, S.; Tanokura, M. Enzymes Useful for Chiral Compound Synthesis: Structural Biology, Directed Evolution, and Protein Engineering for Industrial Use. Appl. Microbiol. Biotechnol. 2016, 100, 5747−5757. (8) Keasling, J. D. Manufacturing Molecules Through Metabolic Engineering. Science 2010, 330, 1355−1358. (9) Kirk, O.; Borchert, T. V.; Fuglsang, C. C. Industrial Enzyme Applications. Curr. Opin. Biotechnol. 2002, 13, 345−351. (10) Abbas, C. A.; Sibirny, A. A. Genetic Control of Biosynthesis and Transport of Riboflavin and Flavin Nucleotides and Construction of Robust Biotechnological Producers. Microbiol. Mol. Biol. Rev. 2011, 75, 321−360. (11) Du, Y.; Zhang, W.; Wang, M. L. Sensing of Salivary Glucose Using Nano-Structured Biosensors. Biosensors 2016, 6, 10.

Scott A. Walper spent his formative years in Mississippi, where he earned his B.S. at The University of Southern Mississippi. He obtained his Ph.D. under the mentorship of Sabine Heinhorst before continuing to the U.S. Naval Research Laboratory as a postdoctoral fellow to work with Ellen Goldman and George Anderson on the isolation and engineering of recombinant antibodies for pathogenic bacteria, viral particles, and toxins. His current research focuses on engineering genetic mechanisms to direct the manufacture and packaging of enzymes into bacterial membrane vesicles for use as deployable catalytic systems. U

DOI: 10.1021/acs.langmuir.7b02588 Langmuir XXXX, XXX, XXX−XXX

Langmuir

Invited Feature Article

(12) Long, Q.; Fang, A.; Wen, Y.; Li, H.; Zhang, Y.; Yao, S. Rapid and Highly-Sensitive Uric Acid Sensing Based on Enzymatic CatalysisInduced Upconversion Inner Filter Effect. Biosens. Bioelectron. 2016, 86, 109−114. (13) Wu, C.; Liu, X.; Li, Y.; Du, X.; Wang, X.; Xu, P. LipaseNanoporous Gold Biocomposite Modified Electrode for Reliable Detection of Triglycerides. Biosens. Bioelectron. 2014, 53, 26−30. (14) Poscia, A.; Messeri, D.; Moscone, D.; Ricci, F.; Valgimigli, F. A Novel Continuous Subcutaneous Lactate Monitoring System. Biosens. Biosens. Bioelectron. 2005, 20, 2244−2250. (15) Sobel, B. E.; Shell, W. E. Serum Enzyme Determinations in the Diagnosis and Assessment of Myocardial Infarction. Circulation 1972, 45, 471−482. (16) Nyhan, W. L.; Barshop, B. A.; Ozand, P. T. Atlas of Metabolic Diseases, 2nd ed.; CRC Press, 2005. (17) Carroll, J. Enzyme Replacement Therapies: Better Lives versus the Bottom Line. Biotechnol. Healthcare 2006, 3, 46−56. (18) Desnick, R. J.; Schuchman, E. H. Enzyme Replacement and Enhancement Therapies: Lessons from Lysosomal Disorders. Nat. Rev. Genet. 2002, 3, 954−966. (19) Angermayr, S. A.; Paszota, M.; Hellingwerf, K. J. Engineering a Cyanobacterial Cell Factory for Production of Lactic Acid. Appl. Env. Microbio. 2012, 78, 7098−7106. (20) DiCosimo, R.; McAuliffe, J.; Poulose, A. J.; Bohlmann, G. Industrial Use of Immobilized Enzymes. Chem. Soc. Rev. 2013, 42, 6437−6474. (21) Johnson, B. J.; Algar, W. R.; Malanoski, A. P.; Ancona, M. G.; Medintz, I. L. Understanding Enzymatic Acceleration at Nanoparticle Interfaces: Approaches and Challenges. Nano Today 2014, 9, 102− 131. (22) Ansari, S. A.; Husain, Q. Potential applications of Enzymes Immobilized on/in Nano Materials: A Review. Biotechnol. Adv. 2012, 30, 512−523. (23) Richter, P.; Ruiz, B. L.; Sanchez Cabezudo, M.; Mottola, H. A. Immobilized Enzyme Reactors. Diffusion/Convection, Kinetics, and a Comparison of Packed-Column and Rotating Bioreactors for Use in Continuous-Flow Systems. Anal. Chem. 1996, 68, 1701−1705. (24) Ding, S. W.; Cargill, A. A.; Medintz, I. L.; Claussen, J. C. Increasing the Activity of Immobilized Enzymes with Nanoparticle Conjugation. Curr. Opin. Biotechnol. 2015, 34, 242−250. (25) Johnson, K. A.; Goody, R. S. The Original Michaelis Constant: Translation of the 1913 Michaelis-Menten Paper. Biochemistry 2011, 50, 8264−8269. (26) Sapsford, K. E.; Algar, W. R.; Berti, L.; Gemmill, K. B.; Casey, B. J.; Oh, E.; Stewart, M. H.; Medintz, I. L. Functionalizing Nanoparticles with Biological Molecules: Developing Chemistries that Facilitate Nanotechnology. Chem. Rev. 2013, 113, 1904−2074. (27) Hildebrandt, N.; Spillmann, C. M.; Algar, W. R; Pons, T.; Stewart, M. H.; Oh, E.; Susumu, K.; Díaz, S. A.; Delehanty, J. B.; Medintz, I. L. Energy Transfer with Semiconductor Quantum Dot Bioconjugates: A Versatile Platform for Biosensing, Energy Harvesting, and Other Developing Applications. Chem. Rev. 2017, 117, 536−711. (28) Algar, W. R.; Susumu, K.; Delehanty, J. B.; Medintz, I. L. Quantum Dots in Bioanalysis: Crossing the Valley of Death. Anal. Chem. 2011, 83, 8826−8837. (29) Oh, E.; Fatemi, F. K.; Currie, M.; Delehanty, J. B.; Pons, T.; Fragola, A.; Leveque-Fort, S.; Goswami, R.; Susumu, K.; Huston, A. L.; Medintz, I. L. PEGylated Luminescent Gold Nanoclusters: Synthesis, Characterization, Bioconjugation, and Application to One- and TwoPhoton Cellular Imaging. Part. Part. Syst. Charact. 2013, 30, 453−466. (30) Boisselier, E.; Astruc, D. Gold Nanoparticles in Nanomedicine: Preparations, Imaging, Diagnostics, Therapies and Toxicity. Chem. Soc. Rev. 2009, 38, 1759−1782. (31) Oh, E.; Delehanty, J. B.; Field, L. D.; Makinen, A. J.; Goswami, R.; Huston, A. L.; Medintz, I. L. Synthesis and Characterization of PEGylated Luminescent Gold Nanoclusters Doped with Silver and Other Metals. Chem. Mater. 2016, 28, 8676−8688. (32) Oh, E.; Huston, A. L.; Shabaev, A.; Efros, A.; Currie, M.; Susumu, K.; Bussmann, K.; Goswami, R.; Fatemi, F. K.; Medintz, I. L.

Energy Transfer Sensitization of Luminescent Gold Nanoclusters: More than Just the Classical Forster Mechanism. Sci. Rep. 2016, 6, 35538. (33) Ling, D. S.; Hackett, M. J.; Hyeon, T. Surface Ligands in Synthesis, Modification, Assembly and Biomedical Applications of Nanoparticles. Nano Today 2014, 9, 457−477. (34) Palui, G.; Aldeek, F.; Wang, W. T.; Mattoussi, H. Strategies for Interfacing Inorganic Nanocrystals with Biological Systems based on Polymer-Coating. Chem. Soc. Rev. 2015, 44, 193−227. (35) Karakoti, A. S.; Shukla, R.; Shanker, R.; Singh, S. Surface Functionalization of Quantum Dots for Biological Applications. Adv. Colloid Interface Sci. 2015, 215, 28−45. (36) Algar, W. R.; Prasuhn, D. E.; Stewart, M. H.; Jennings, T. L.; Blanco-Canosa, J. B.; Dawson, P. E.; Medintz, I. L. The Controlled Display of Biomolecules on Nanoparticles: A Challenge Suited to Bioorthogonal Chemistry. Bioconjugate Chem. 2011, 22, 825−858. (37) Huang, P. J. J.; Pautler, R.; Shanmugaraj, J.; Labbe, G.; Liu, J. W. Inhibiting the Vim-2 Metallo-Beta-Lactamase by Graphene Oxide and Carbon Nanotubes. ACS Appl. Mater. Interfaces 2015, 7, 9898−9903. (38) Medintz, I. Universal Tools for Biomolecular Attachment to Surfaces. Nat. Mater. 2006, 5, 842−8421. (39) Blanco-Canosa, J. B.; Wu, M.; Susumu, K.; Petryayeva, E.; Jennings, T. L.; Dawson, P. E.; Algar, W. R.; Medintz, I. L. Recent Progress in the Bioconjugation of Quantum Dots. Coord. Chem. Rev. 2014, 263-264, 101−137. (40) Wu, M.; Petryayeva, E.; Medintz, I. L.; Algar, W. R. Quantitative Measurement of Proteolytic Rates with Quantum Dot-Peptide Substrate Conjugates and Forster Resonance Energy Transfer. Methods Mol. Biol. 2014, 1199, 215−239. (41) Susumu, K.; Oh, E.; Delehanty, J. B.; Blanco-Canosa, J. B.; Johnson, B. J.; Jain, V.; Hervey, W. J.; Algar, W. R.; Boeneman, K.; Dawson, P. E.; Medintz, I. L. Multifunctional Compact Zwitterionic Ligands for Preparing Robust Biocompatible Semiconductor Quantum Dots and Gold Nanoparticles. J. Am. Chem. Soc. 2011, 133, 9480− 9496. (42) Gemmill, K. B.; Deschamps, J. R.; Delehanty, J. B.; Susumu, K.; Stewart, M. H.; Glaven, R. H.; Anderson, G. P.; Goldman, E. R.; Huston, A. L.; Medintz, I. L. Optimizing Protein Coordination to Quantum Dots with Designer Peptidyl Linkers. Bioconjugate Chem. 2013, 24, 269−281. (43) Prasuhn, D. E.; Blanco-Canosa, J. B.; Vora, G. J.; Delehanty, J. B.; Susumu, K.; Mei, B. C.; Dawson, P. E.; Medintz, I. L. Combining Chemoselective Ligation with Polyhistidine-Driven Self-Assembly for the Modular Display of Biomolecules on Quantum Dots. ACS Nano 2010, 4, 267−278. (44) Prasuhn, D. E.; Susumu, K.; Medintz, I. L. Multivalent Conjugation of Peptides, Proteins, and DNA to Semiconductor Quantum Dots. Methods Mol. Biol. 2011, 726, 95−110. (45) Liu, B. W.; Liu, J. W. Surface Modification of Nanozymes. Nano Res. 2017, 10, 1125−1148. (46) Zhang, Z. J.; Zhang, X. H.; Liu, B. W.; Liu, J. W. Molecular Imprinting on Inorganic Nanozymes for Hundred-Fold Enzyme Specificity. J. Am. Chem. Soc. 2017, 139, 5412−5419. (47) Medintz, I. L.; Clapp, A. R.; Brunel, F. M.; Tiefenbrunn, T.; Uyeda, H. T.; Chang, E. L.; Deschamps, J. R.; Dawson, P. E.; Mattoussi, H. Proteolytic Activity Monitored by Fluorescence Resonance Energy Transfer Through Quantum-Dot-Peptide Conjugates. Nat. Mater. 2006, 5, 581−589. (48) Nagy, A.; Gemmill, K. B.; Delehanty, J. B.; Medintz, I. L.; Sapsford, K. E. Peptide-Functionalized Quantum Dot Biosensors. IEEE J. Sel. Top. Quantum Electron. 2014, 20, 6900512. (49) FRET − Förster Resonance Energy Transfer From Theory to Applications; Medintz, I. L.; Hildebrandt, N., Eds.; Wiley-VCH: Weinheim, Germany, 2013. (50) Algar, W. R.; Malonoski, A.; Deschamps, J. R.; Banco-Canosa, J. B.; Susumu, K.; Stewart, M. H.; Johnson, B. J.; Dawson, P. E.; Medintz, I. L. Proteolytic Activity at Quantum Dot-Conjugates: Kinetic Analysis Reveals Enhanced Enzyme Activity and Localized Interfacial “Hopping. Nano Lett. 2012, 12, 3793−3802. V

DOI: 10.1021/acs.langmuir.7b02588 Langmuir XXXX, XXX, XXX−XXX

Langmuir

Invited Feature Article

(51) Cornish-Bowden, A. Fundamentals of Enzyme Kinetics, 4th ed.; Wiley-Blackwell: Weinheim, Germany, 2012. (52) Duggleby, R. G. Quantitative Analysis of the Time Courses of Enzyme-Catalyzed Reactions. Methods 2001, 24, 168−174. (53) Wu, M.; Algar, W. R. Acceleration of Proteolytic Activity Associated with Selection of Thiol Ligand Coatings on Quantum Dots. ACS Appl. Mater. Interfaces 2015, 7, 2535−2545. (54) Diaz, S. A.; Malonoski, A. P.; Susumu, K.; Hofele, R. V.; Oh, E.; Medintz, I. L. Probing the Kinetics of Quantum Dot-Based Proteolytic Sensors. Anal. Bioanal. Chem. 2015, 407, 7307−7318. (55) Diaz, S. A.; Sen, S.; Boeneman Gemmill, K.; Brown, C. W. I.; Oh, E.; Susumu, K.; Stewart, M. H.; Breger, J. C.; Aragones, G. L.; Field, L. D.; Deschamps, J. R.; Kral, P.; Medintz, I. L. Elucidating Surface Ligand-Dependent Kinetic Enhancement of Proteolytic Activity at Surface-Modified Quantum Dots. ACS Nano 2017, 11, 5884−5896. (56) Claussen, J. C.; Malanoski, A.; Breger, J. C.; Oh, E.; Walper, S. A.; Susumu, K.; Goswami, R.; Deschamps, J. R.; Medintz, I. L. Probing the Enzymatic Activity of Alkaline Phosphatase within Quantum Dot Bioconjugates. J. Phys. Chem. C 2015, 119, 2208−2221. (57) Bigley, A. N.; Mabanglo, M. F.; Harvey, S. P.; Raushel, F. M. Variants of Phosphotriesterase for the Enhanced Detoxification of the Chemical Warfare Agent VR. Biochemistry 2015, 54, 5502−5512. (58) Caldwell, S. R.; Newcomb, J. R.; Schlecht, K. A.; Raushel, F. M. Limits of Diffusion in the Hydrolysis of Substrates by the Phosphotriesterase from Pseudomonas-Diminuta. Biochemistry 1991, 30, 7438−7444. (59) Breger, J. C.; Walper, S. A.; Oh, E.; Susumu, K.; Stewart, M. H.; Deschamps, J. R.; Medintz, I. L. Quantum Dot Display Enhances Activity of a Phosphotriesterase Trimer. Chem. Commun. 2015, 51, 6403−6406. (60) Hondred, J. A.; Breger, J. C.; Garland, N. T.; Oh, E.; Susumu, K.; Walper, S. A.; Medintz, I. L.; Claussen, J. C. Enhanced Enzyme Activity of Phosphotriesterase Trimer Conjugated on Gold Nanoparticles for Pesticide Detection. Analyst 2017, 142, 3261−3271. (61) Breger, J. C.; Buckhout-White, S.; Walper, S. A.; Oh, E.; Susumu, K.; Ancona, M. G.; Medintz, I. L. Assembling High Activity Phosphotriesterase Composites Using Hybrid Nanoparticle PeptideDNA Scaffolded Architectures. Nano Futures 2017, 1, 011002. (62) Zhao, Z.; Fu, J. L.; Dhakal, S.; Johnson-Buck, A.; Liu, M. H.; Zhang, T.; Woodbury, N. W.; Liu, Y.; Walter, N. G.; Yan, H. Nanocaged Enzymes with Enhanced Catalytic Activity and Increased Stability Against Protease Digestion. Nat. Commun. 2016, 7, 10619. (63) Zhang, Y. F.; Tsitkov, S.; Hess, H. Proximity Does Not Contribute to Activity Enhancement in the Glucose OxidaseHorseradish Peroxidase Cascade. Nat. Commun. 2016, 7, 13982. (64) Zhang, Y. F.; Wang, Q.; Hess, H. Increasing Enzyme Cascade Throughput by Ph-Engineering the Microenvironment of Individual Enzymes. ACS Catal. 2017, 7, 2047−2051. (65) Zhang, Y.; Hess, H. Toward Rational Design of High-Efficiency Enzyme Cascades. ACS Catal. 2017, 7, 6018−6027. (66) Zobel, M.; Neder, R. B.; Kimber, S. A. Universal Solvent Restructuring Induced by Colloidal Nanoparticles. Science 2015, 347, 292−4. (67) Fu, J. L.; Liu, M. H.; Liu, Y.; Woodbury, N. W.; Yan, H. Interenzyme Substrate Diffusion for an Enzyme Cascade Organized on Spatially Addressable DNA Nanostructures. J. Am. Chem. Soc. 2012, 134, 5516−5519. (68) Mathur, D.; Medintz, I. L. Analyzing DNA Nanotechnology: A Call to Arms For The Analytical Chemistry Community. Anal. Chem. 2017, 89, 2646−2663. (69) Samanta, A.; Medintz, I. L. Nanoparticles and DNA - A Powerful and Growing Functional Combination in Bionanotechnology. Nanoscale 2016, 8, 9037−9095. (70) Brown, C. W., III; Oh, E.; Hastman, D. A.; Walper, S. A.; Susumu, K.; Stewart, M. H.; Deschamps, J. R.; Medintz, I. L. Kinetic Enhancement of the Diffusion-Limited Enzyme Beta-Galactosidase When Displayed with Quantum Dots. RSC Adv. 2015, 5, 93089− 93094.

(71) Wadiak, D. T.; Carbonell, R. G. Kinetic-Behavior of Microencapsulated Beta-Galactosidase. Biotechnol. Bioeng. 1975, 17, 1157− 1181. (72) Malanoski, A. P.; Breger, J. C.; Brown, C. W. I.; Deschamps, J. R.; Susumu, K.; Oh, E.; Anderson, G. P.; Walper, S. A.; Medintz, I. L. Kinetic Enhancement in High-Activity Enzyme Complexes Attached to Nanoparticles. Nanoscale Horizons 2017, 2, 241−252. (73) Baeshen, N. A.; Baeshen, M. N.; Sheikh, A.; Bora, R. S.; Ahmed, M. M. M.; Ramadan, H. A. I.; Saini, K. S.; Redwan, E. M. Cell Factories for Insulin Production. Microb. Cell Fact. 2014, 13, 141. (74) Knox, K. W.; Cullen, J.; Work, E. An Extracellular Lipopolysaccharide-Phospholipid-Protein Complex Produced by Escherichia Coli Grown Under Lysine-Limiting Conditions. Biochem. J. 1967, 103, 192−201. (75) Kulp, A.; Kuehn, M. J. Biological Functions and Biogenesis of Secreted Bacterial Outer Membrane Vesicles. Annu. Rev. Microbiol. 2010, 64, 163−184. (76) Schwechheimer, C.; Sullivan, C. J.; Kuehn, M. J. Envelope Control of Outer Membrane Vesicle Production in Gram-Negative Bacteria. Biochemistry 2013, 52, 3031−3040. (77) Kuehn, M. J.; Kesty, N. C. Bacterial Outer Membrane Vesicles and the Host-Pathogen Interaction. Genes Dev. 2005, 19, 2645−2655. (78) Bielaszewska, M.; Ruter, C.; Kunsmann, L.; Greune, L.; Bauwens, A.; Zhang, W. L.; Kuczius, T.; Kim, K. S.; Mellmann, A.; Schmidt, M. A.; Karch, H. Enterohemorrhagic Escherichia coli Hemolysin Employs Outer Membrane Vesicles to Target Mitochondria and Cause Endothelial and Epithelial Apoptosis. PLoS Pathog. 2013, 9, e1003797. (79) Liao, Y. T.; Kuo, S. C.; Chiang, M. H.; Lee, Y. T.; Sung, W. C.; Chen, Y. H.; Chen, T. L.; Fung, C. P. Acinetobacter baumannii Extracellular OXA-58 Is Primarily and Selectively Released via Outer Membrane Vesicles after Sec-Dependent Periplasmic Translocation. Antimicrob. Agents Chemother. 2015, 59, 7346−7354. (80) Rumbo, C.; Fernandez-Moreira, E.; Merino, M.; Poza, M.; Mendez, J. A.; Soares, N. C.; Mosquera, A.; Chaves, F.; Bou, G. Horizontal Transfer of the OXA-24 Carbapenemase Gene via Outer Membrane Vesicles: a New Mechanism of Dissemination of Carbapenem Resistance Genes in Acinetobacter baumannii. Antimicrob. Agents Chemother. 2011, 55, 3084−3090. (81) Avila-Calderon, E. D.; Araiza-Villanueva, M. G.; Cancino-Diaz, J. C.; Lopez-Villegas, E. O.; Sriranganathan, N.; Boyle, S. M.; ContrerasRodriguez, A. Roles of bacterial membrane vesicles. Arch. Microbiol. 2015, 197, 1−10. (82) Kesty, N. C.; Kuehn, M. J. Incorporation of Heterologous Outer Membrane and Periplasmic Proteins into Escherichia coli Outer membrane Vesicles. J. Biol. Chem. 2004, 279, 2069−2076. (83) Lee, E. Y.; Bang, J. Y.; Park, G. W.; Choi, D. S.; Kang, J. S.; Kim, H. J.; Park, K. S.; Lee, J. O.; Kim, Y. K.; Kwon, K. H.; Kim, K. P.; Gho, Y. S. Global Proteomic Profiling of Native Outer Membrane Vesicles Derived from Escherichia coli. Proteomics 2007, 7, 3143−3153. (84) Lee, E. Y.; Choi, D. S.; Kim, K. P.; Gho, Y. S. Proteomics in Gram-Negative Bacterial Outer Membrane Vesicles. Mass Spectrom. Rev. 2008, 27, 535−555. (85) Fierer, J. O.; Veggiani, G.; Howarth, M. SpyLigase PeptidePeptide Ligation Polymerizes Affibodies to Enhance Magnetic Cancer Cell Capture. Proc. Natl. Acad. Sci. U. S. A. 2014, 111, E1176−E1181. (86) Alves, N. J.; Turner, K. B.; Daniele, M. A.; Oh, E.; Medintz, I. L.; Walper, S. A. Bacterial Nanobioreactors−Directing Enzyme Packaging into Bacterial Outer Membrane Vesicles. ACS Appl. Mater. Interfaces 2015, 7, 24963−24972. (87) Alves, N. J.; Turner, K. B.; Medintz, I. L.; Walper, S. A. Protecting Enzymatic Function Through Directed Packaging into Bacterial Outer Membrane Vesicles. Sci. Rep. 2016, 6, 24866. (88) Park, M.; Sun, Q.; Liu, F.; DeLisa, M. P.; Chen, W. Positional Assembly of Enzymes on Bacterial Outer Membrane Vesicles for Cascade Reactions. PLoS One 2014, 9, e97103. (89) Shamirian, A.; Ghai, A.; Snee, P. T. QD-Based FRET Probes at a Glance. Sensors 2015, 15, 13028−13051. W

DOI: 10.1021/acs.langmuir.7b02588 Langmuir XXXX, XXX, XXX−XXX

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Invited Feature Article

Determines the Physico-Chemical Properties of the Nanoparticles. J. R. Soc., Interface 2014, 11, 20130931. (107) Sapsford, K. E.; Tyner, K. M.; Dair, B. J.; Deschamps, J. R.; Medintz, I. L. Analyzing Nanomaterial Bioconjugates: A Review of Current and Emerging Purification and Characterization Techniques. Anal. Chem. 2011, 83, 4453−4488. (108) Corbo, C.; Molinaro, R.; Parodi, A.; Furman, N. E. T.; Salvatore, F.; Tasciotti, E. The impact of Nanoparticle Protein Corona on Cytotoxicity, Immunotoxicity and Target Drug Delivery. Nanomedicine 2016, 11, 81−100. (109) Segel, L. A.; Slemrod, M. The Quasi-Steady-State Assumption − A Case-Study in Perturbation. SIAM Rev. 1989, 31, 446−477. (110) Gillespie, D. T.; Hellander, A.; Petzold, L. R. Perspective: Stochastic Algorithms for Chemical Kinetics. J. Chem. Phys. 2013, 138, 170901. (111) Sheehan, P. E.; Whitman, L. J. Detection Limits For Nanoscale Biosensors. Nano Lett. 2005, 5, 803−807. (112) Idan, O.; Hess, H. Origins of Activity Enhancement in Enzyme Cascades on Scaffolds. ACS Nano 2013, 7, 8658−8665. (113) Caldwell, S. R.; Newcomb, J. R.; Schlecht, K. A.; Raushel, F. M. Limits of Diffusion in the Hydrolysis of Substrates by the Phosphotriesterase from Pseudomonas Diminuta. Biochemistry 1991, 30, 7438−7444. (114) Berg, O. G. On Diffusion-Controlled Dissociation. Chem. Phys. 1978, 31, 47−57. (115) Wu, C. S.; Lee, C. C.; Wu, C. T.; Yang, Y. S.; Ko, F. H. SizeModulated Catalytic Activity of Enzyme-Nanoparticle Conjugates: A Combined Kinetic and Theoretical Study. Chem. Commun. 2011, 47, 7446−7448. (116) Castellana, M.; Wilson, M. Z.; Xu, Y. F.; Joshi, P.; Cristea, I. M.; Rabinowitz, J. D.; Gitai, Z.; Wingreen, N. S. Enzyme Clustering Accelerates Processing of Intermediates Through Metabolic Channeling. Nat. Biotechnol. 2014, 32, 1011−1018. (117) Chen, G.; Kong, X. A.; Lu, D. N.; Wu, J. Z.; Liu, Z. Kinetics of Co2 Diffusion in Human Carbonic Anhydrase: A Study Using Molecular Dynamics Simulations and the Markov-State Model. Phys. Chem. Chem. Phys. 2017, 19, 11690−11697. (118) Zhang, Y. F.; Ge, J.; Liu, Z. Enhanced Activity of Immobilized or Chemically Modified Enzymes. ACS Catal. 2015, 5, 4503−4513. (119) Cole, J. T.; Holland, N. B. Multifunctional Nanoparticles for Use in Theranostic Applications. Drug Delivery Transl. Res. 2015, 5, 295−309. (120) Jang, B.; Kwon, H.; Katila, P.; Lee, S. J.; Lee, H. Dual Delivery of Biological Therapeutics for Multimodal and Synergistic Cancer Therapies. Adv. Drug Delivery Rev. 2016, 98, 113−133. (121) Delehanty, J. B.; Boeneman, K.; Bradburne, C. E.; Robertson, K.; Medintz, I. L. Quantum Dots: A Powerful Tool for Understanding the Intricacies of Nanoparticle-Mediated Drug Delivery. Expert Opin. Drug Delivery 2009, 6, 1091−1112. (122) Algar, W. R.; Khachatrian, A.; Melinger, J. S.; Huston, A. L.; Stewart, M. H.; Susumu, K.; Blanco-Canosa, J. B.; Oh, E.; Dawson, P. E.; Medintz, I. L. Concurrent Modulation of Quantum Dot Photoluminescence Using a Combination of Charge Transfer and Forster Resonance Energy Transfer: Competitive Quenching and Multiplexed Biosensing Modality. J. Am. Chem. Soc. 2017, 139, 363− 372. (123) Afsari, H. S.; Dos Santos, M. C.; Lindén, S.; Chen, T.; Qiu, X.; van Bergen en Henegouwen, P. M. P.; Jennings, T. L.; Susumu, K.; Medintz, I. L.; Hildebrandt, N.; Miller, L. W. Time-Gated FRET Nanoassemblies for Rapid and Sensitive Intra and Extracellular Fluorescence Imaging. Sci. Adv. 2016, 2, e1600265. (124) Claussen, J. C.; Hildebrandt, N.; Susumu, K.; Ancona, M. G.; Medintz, I. L. Complex Logic Functions Implemented with Quantum Dot Bionanophotonic Circuits. ACS Appl. Mater. Interfaces 2014, 6, 3771−3778. (125) Dueber, J. E.; Wu, G. C.; Malmirchegini, G. R.; Moon, T. S.; Petzold, C. J.; Ullal, A. V.; Prather, K. L. J.; Keasling, J. D. Synthetic Protein Scaffolds Provide Modular Control Over Metabolic Flux. Nat. Biotechnol. 2009, 27, 753−759.

(90) Zhou, M.; Ghosh, I. Quantum Dots and Peptides: A Bright Future Together. Biopolymers 2007, 88, 325−339. (91) Sapsford, K. E.; Granek, J.; Deschamps, J. R.; Boeneman, K.; Blanco-Canosa, J. B.; Dawson, P. E.; Susumu, K.; Stewart, M. H.; Medintz, I. L. Monitoring Botulinum Neurotoxin A Activity with Peptide-Functionalized Quantum Dot Resonance Energy Transfer Sensors. ACS Nano 2011, 5, 2687−2699. (92) Breger, J. C.; Sapsford, K. E.; Ganek, J.; Susumu, K.; Stewart, M. H.; Medintz, I. L. Detecting Kallikrein Proteolytic Activity with Peptide-Quantum Dot Nanosensors. ACS Appl. Mater. Interfaces 2014, 6, 11529−11535. (93) Boeneman, K.; Mei, B. C.; Dennis, A. M.; Bao, G.; Deschamps, J. R.; Mattoussi, H.; Medintz, I. L. Sensing Caspase 3 Activity with Quantum Dot-Fluorescent Protein Assemblies. J. Am. Chem. Soc. 2009, 131, 3828−3829. (94) Prasuhn, D. E.; Feltz, A.; Blanco-Canosa, J. B.; Susumu, K.; Stewart, M. H.; Mei, B. C.; Yakovlev, A. V.; Loukov, C.; Mallet, J. M.; Oheim, M.; Dawson, P. E.; Medintz, I. L. Quantum Dot Peptide Biosensors for Monitoring Caspase 3 Proteolysis and Calcium Ions. ACS Nano 2010, 4, 5487−5497. (95) Algar, W. R.; Ancona, M. G.; Malanoski, A. P.; Susumu, K.; Medintz, I. L. Assembly of a Concentric Förster Resonance Energy Transfer Relay on a Quantum Dot Scaffold: Characterization and Application to Multiplexed Protease Sensing. ACS Nano 2012, 6, 11044−11058. (96) Massey, M.; Kim, H.; Conroy, E. M.; Algar, W. R. Expanded Quantum Dot-Based Concentric Förster Resonance Energy Transfer: Adding and Characterizing Energy-Transfer Pathways for Triply Multiplexed Biosensing. J. Phys. Chem. C 2017, 121, 13345−13356. (97) Algar, W. R.; Wegner, D.; Huston, A. L.; Blanco-Canosa, J. B.; Stewart, M. H.; Armstrong, A.; Dawson, P. E.; Hildebrandt, N.; Medintz, I. L. Quantum Dots as Simultaneous Acceptors and Donors in Time-Gated Förster Resonance Energy Transfer Relays: Characterization and Biosensing. J. Am. Chem. Soc. 2012, 134, 1876−1891. (98) Wegner, K. D.; Hildebrandt, N. Quantum Dots: Bright and Versatile In Vitro and In Vivo Fluorescence Imaging Biosensors. Chem. Soc. Rev. 2015, 44, 4792−4834. (99) Algar, W. R.; Malanoski, A. P.; Susumu, K.; Stewart, M. H.; Hildebrandt, N.; Medintz, I. L. Multiplexed Tracking of Protease Activity Using a Single Color of Quantum Dot Vector and a TimeGated Förster Resonance Energy Transfer Relay. Anal. Chem. 2012, 84, 10136−10146. (100) Claussen, J. C.; Algar, W. R.; Hildebrandt, N.; Susumu, K.; Ancona, M. G.; Medintz, I. L. Biophotonic Logic Devices Based on Quantum Dots and Temporally-Staggered Förster Energy Transfer Relays. Nanoscale 2013, 5, 12156−12170. (101) Dwyer, C. L.; Diaz, S. A.; Walper, S. A.; Samanta, A.; Susumu, K.; Oh, E.; Buckhout-White, S.; Medintz, I. L. Chemoenzymatic Sensitization of DNA Photonic Wires Mediated through Quantum Dot Energy Transfer Relays. Chem. Mater. 2015, 27, 6490−6494. (102) Samanta, A.; Walper, S. A.; Susumu, K.; Dwyer, C. L.; Medintz, I. L. An Enzymatically-Sensitized Sequential and Concentric Energy Transfer Relay Self-Assembled Around Semiconductor Quantum Dots. Nanoscale 2015, 7, 7603−7614. (103) Schauermann, S.; Nilius, N.; Shaikhutdinov, S.; Freund, H. J. Nanoparticles for Heterogeneous Catalysis: New Mechanistic Insights. Acc. Chem. Res. 2013, 46, 1673−1681. (104) Breger, J. C.; Ancona, M. G.; Walper, S. A.; Oh, E.; Susumu, K.; Stewart, M. H.; Deschamps, J. R.; Medintz, I. L. Understanding How Nanoparticle Attachment Enhances Phosphotriesterase Kinetic Efficiency. ACS Nano 2015, 9, 8491−8503. (105) Iyer, A.; Chandra, A.; Swaminathan, R. Hydrolytic Enzymes Conjugated to Quantum Dots Mostly Retain Whole Catalytic Activity. Biochim. Biophys. Acta, Gen. Subj. 2014, 1840, 2935−2943. (106) Pfeiffer, C.; Rehbock, C.; Hühn, D.; Carrillo-Carrion, C.; de Aberasturi; Merk, V.; Barcikowski, S.; Parak, W. J. Interaction of Colloidal Nanoparticles with Their Local Environment: The (Ionic) Nanoenvironment Around Nanoparticles is Different From Bulk and X

DOI: 10.1021/acs.langmuir.7b02588 Langmuir XXXX, XXX, XXX−XXX

Langmuir

Invited Feature Article

(126) National Academy of Science; Industrialization of Biology: A Roadmap to Accelerate the Advanced Manufacturing of Chemicals; National Academies Press: Washington, D.C., 2015. (127) U.S. Office of Technical Intelligence; Technical Assessment: Synthetic Biology; Office of the Assistant Secretary of Defense for Research & Engineering, 2015. (128) Opgenorth, P. H.; Korman, T. P.; Bowie, J. U. A Synthetic Biochemistry Molecular Purge Valve Module that Maintains Redox Balance. Nat. Commun. 2014, 5, 4113. (129) Chen, R.; Chen, Q.; Kim, H.; Siu, K. H.; Sun, Q.; Tsai, S. L.; Chen, W. Biomolecular scaffolds for enhanced signaling and catalytic efficiency. Curr. Opin. Biotechnol. 2014, 28, 59−68. (130) Sun, Q.; Chen, W. HaloTag Mediated Artificial Cellulosome Assembly on a Rolling Circle Amplification DNA Template for Efficient Cellulose Hydrolysis. Chem. Commun. 2016, 52, 6701−6704. (131) Chen, Z.; Zeng, A. P. Protein Engineering Approaches to Chemical Biotechnology. Curr. Opin. Biotechnol. 2016, 42, 198−205. (132) Li, Y.; Cirino, P. C. Recent Advances in Engineering Proteins for Biocatalysis. Biotechnol. Bioeng. 2014, 111, 1273−1287. (133) Vranish, J. N.; Ancona, M. G.; Oh, E.; Susumu, K.; Medintz, I. L. Enhancing Coupled Enzymatic Activity By Conjugating One Enzyme to a Nanoparticle. Nanoscale 2017, 9, 5172−5187. (134) Mukai, C.; Gao, L. Z.; Nelson, J. L.; Lata, J. P.; Cohen, R.; Wu, L. R.; Hinchman, M. M.; Bergkvist, M.; Sherwood, R. W.; Zhang, S.; Travis, A. J. Biomimicry Promotes the Efficiency of a 10-Step Sequential Enzymatic Reaction on Nanoparticles, Converting Glucose to Lactate. Angew. Chem., Int. Ed. 2017, 56, 235−238. (135) Prigodich, A. E.; Alhasan, A. H.; Mirkin, C. A. Selective Enhancement of Nucleases by Polyvalent DNA-Functionalized Gold Nanoparticles. J. Am. Chem. Soc. 2011, 133, 2120−2123. (136) Noble, G. T.; Craven, F. L.; Voglmeir, J.; Sardzik, R.; Flitsch, S. L.; Webb, S. J. Accelerated Enzymatic Galactosylation of NAcetylglucosaminolipids in Lipid Microdomains. J. Am. Chem. Soc. 2012, 134, 13010−13017. (137) Tsai, S. L.; Park, M.; Chen, W. Size-Modulated Synergy of Cellulase Clustering for Enhanced Cellulose Hydrolysis. Biotechnol. J. 2013, 8, 257−261. (138) Jia, L. L.; Budinova, G.; Takasugi, Y.; Noda, S.; Tanaka, T.; Ichinose, H.; Goto, M.; Kamiya, N. Synergistic Degradation of Arabinoxylan by Free and Immobilized Xylanases and Arabinofuranosidase. Biochem. Eng. J. 2016, 114, 268−275. (139) Holdrich, M.; Sievers-Engler, A.; Lammerhofer, M. Gold Nanoparticle-Conjugated Pepsin for Efficient Solution-Like Heterogeneous Biocatalysis in Analytical Sample Preparation Protocols. Anal. Bioanal. Chem. 2016, 408, 5415−5427. (140) Ardao, I.; Comenge, J.; Benaiges, M. D.; Alvaro, G.; Puntes, V. F. Rational Nanoconjugation Improves Biocatalytic Performance of Enzymes: Aldol Addition Catalyzed by Immobilized Rhamnulose-1Phosphate Aldolase. Langmuir 2012, 28, 6461−6467. (141) Kim, D. M.; Umetsu, M.; Takai, K.; Matsuyama, T.; Ishida, N.; Takahashi, H.; Asano, R.; Kumagai, I. Enhancement of Cellulolytic Enzyme Activity by Clustering Cellulose Binding Domains on Nanoscaffolds. Small 2011, 7, 656−664. (142) Dutta, N.; Mukhopadhyay, A.; Dasgupta, A. K.; Chakrabarti, K. Nanotechnology Enabled Enhancement of Enzyme Activity and Thermostability: Study on Impaired Pectate Lyase from Attenuated Macrophomina phaseolina in Presence of Hydroxyapatite Nanoparticle. PLoS One 2013, 8, e63567. (143) Kouassi, G. K.; Irudayaraj, J.; McCarty, G. Examination of Cholesterol Oxidase Attachment to Magnetic Nanoparticles. J. Nanobiotechnol. 2005, 3, 1. (144) Choi, Y.; Lee, J.; Kim, K.; Kim, H.; Sommer, P.; Song, R. Fluorogenic Assay and Live Cell Imaging of HIV-1 Protease Activity Using Acid-Stable Quantum Dot-Peptide Complex. Chem. Commun. 2010, 46, 9146−9148. (145) Kim, Y. P.; Oh, Y. H.; Oh, E.; Kim, H. S. Chip-Based Protease Assay Using Fluorescence Resonance Energy Transfer Between Quantum Dots and Fluorophores. Biochip J. 2007, 1, 228−233.

(146) Bourguet, E.; Brazhnik, K.; Sukhanova, A.; Moroy, G.; BrassartPasco, S.; Martin, A. P.; Villena, I.; Bellon, G.; Sapi, J.; Nabiev, I. Design, Synthesis, and Use of MMP-2 Inhibitor-Conjugated Quantum Dots in Functional Biochemical Assays. Bioconjugate Chem. 2016, 27, 1067−1081. (147) Clapp, A. R.; Goldman, E. R.; Uyeda, H. T.; Chang, E. L.; Whitley, J. L.; Medintz, I. L. Monitoring of Enzymatic Proteolysis Using Self-Assembled Quantum-Dot Protein Substrate Sensors. J. Sens. 2008, 2008, 797436. (148) Long, Y.; Zhang, L. F.; Zhang, Y.; Zhang, C. Y. Single Quantum Dot Based Nanosensor for Renin Assay. Anal. Chem. 2012, 84, 8846−8852. (149) Palomo, V.; Diaz, S. A.; Stewart, M. H.; Susumu, K.; Medintz, I. L.; Dawson, P. E. 3,4-Dihydroxyphenylalanine Peptides as Nonperturbative Quantum Dot Sensors of Aminopeptidase. ACS Nano 2016, 10, 6090−6099. (150) Lowe, S. B.; Dick, J. A. G.; Cohen, B. E.; Stevens, M. M. Multiplex Sensing of Protease and Kinase Enzyme Activity via Orthogonal Coupling of Quantum Dot Peptide Conjugates. ACS Nano 2012, 6, 851−857.

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