Jiao Fan‡a, Xiaomei Jiang‡b, Yumei Hua, Yan Sia, Li Dinga and Weitai Wu*ac
aState Key Laboratory for Physical Chemistry of Solid Surfaces, The Key Laboratory for Chemical Biology of Fujian Province, and Department of Chemistry, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China. E-mail: wuwtxmu@xmu.edu.cn
bClinical Laboratory, Huli Center for Maternal and Child Health, Xiamen 361009, China
cCenter for Molecular Imaging and Translational Medicine, School of Public Health, Xiamen University, Xiamen 361005, China
First published on 10th January 2013
The development of embeddable and remotely interrogatable nanomaterials that allow dynamic quantification of intracellular glucose levels can contribute to a better understanding of physiology. We develop a fluorescent hybrid nanogel glucometer (FNG) that is applicable for intracellular glucometry. Such a FNG (<200 nm) is comprised of ZnO quantum dots covalently bonded onto a loosely-crosslinked gel network of poly(acrylamide), which is interpenetrated in another relatively highly-crosslinked gel network of poly(N-isopropylacrylamide-co-2-acrylamidomethyl-5-fluorophenylboronic acid). This newly developed double-network-structured FNG can adapt to surrounding media of varying glucose levels, and convert the disruptions in homeostasis of glucose level with high reversibility, sensitivity, and selectivity into fluorescence signals at a fast time response. We demonstrate that the FNG can enter the model B16F10 cells and employ the signal transduction ability for fluorescent intracellular glucometry. Furthermore, we show that intracellular glucose level variations associated with a model biological reaction process can be monitored with a high glucose resolution by using the FNG embedded in cells, whilst the reaction mechanism remains nearly unchanged.
Fluorescent materials hold exceptional promise as biosensors.9–11 With the appropriate choice of optical labels, fluorescent biosensors can in theory be excited and the emission interrogated externally. Fluorescent biosensors have been reported for the detection of glucose, but mostly for the macrorealm.12–22 Frommer's group is possibly the first to develop fluorescent biosensors for measuring intracellular glucose levels.2,23–26 In such a typical biosensor, the glucose binding protein (GBP) is coupled terminally with a cyan version of green fluorescent protein (GFP) and a yellow version of GFP. This fluorescent protein based biosensor detected the glucose-induced conformational change in GBP using fluorescence resonance energy transfer (FRET) between the two fluorescent protein variants. An analog fluorescent biosensor was developed by Ye's group by replacing GBP with a glucose indicator protein, which was synthesized by site-directed mutagenesis of GBP at its 16th amino acid residues.27 With those fluorescent protein based biosensors serving as glucometers for intracellular glucometry, image acquisition parameters need to be optimized to obtain the highest possible data quality.25,26 Although even at low signal-to-noise levels (by using little excitation) qualitative data can be obtained, quantitative analysis requires the highest possible signal-to-noise ratio (by using high excitation). However, too-high excitation can lead to photobleaching of the organic fluorophores. As the two fluorophores can have differential photobleaching sensitivity, a change in ratio may be misinterpreted as a FRET change caused by a change in glucose levels. Thus, more stable optical labels, such as quantum dots (QDs), were used in the detection of intracellular glucose.17 This QD based biosensor functioned through the glucose-mediated assembly of 4-((3-boronophenyl)amino)-3-mercapto-4-oxobutanoic acid modified CdTe/ZnTe/ZnS core/shell/shell QDs. The advantages of QDs, including continuous absorption, efficient and tunable emission, and photostability, are significant. Unfortunately, non-glucose induced aggregation (e.g. self aggregation and/or protein induced aggregation) of QDs is inevitable, which often leads to additional changes in fluorescence during glucose monitoring and therefore a rapid decay in sensing abilities.
In this work, we aim to develop a new class of fluorescent QD-polymer hybrid nanogels to demonstrate the concept that a single nanogel particle under a rational design can serve as an embeddable nanoglucometer with high reversibility, as well as negligible interactions with cellular components, for intracellular glucometry. To date, fluorescence sensing of aqueous glucose has been demonstrated on a number of QD-polymer hybrid nanogels, which were prepared by physical immobilization of QDs into the single-network-structured nanogels.18–22 The glucose-induced volume phase transition of the responsive polymer network may change the surface/interface physicochemical environment of the immobilized QDs, leading to changes in fluorescence. Here, we explore this approach in a novel double-network-structured hybrid nanogel. As schematically depicted in Fig. 1a, this newly developed fluorescent hybrid nanogel glucometer (FNG) is comprised of ZnO QDs covalently bonded onto a loosely-crosslinked gel network of poly(acrylamide) [poly(AAm)], which is interpenetrated in another relatively highly-crosslinked gel network of poly(N-isopropylacrylamide-co-2-acrylamidomethyl-5-fluorophenylboronic acid) [poly(NIPAM-co-FPBA)]. It is striking that the single-network-structured hybrid nanogel biosensors reported previously could not be applied in intracellular thermometry because of several remaining issues.18–22 One of the major issues is that they would produce a false response caused by two inevitable problems during repeated swelling–shrinking cycles: (a) gradual shift in the average hydrodynamic radius, 〈Rh〉; (b) slow aggregation or leaching of the physically immobilized QDs from the polymer networks. They would also precipitate in the culture medium. We overcome those problems in the proposed double-network-structured FNG. More importantly, different from previous arts of fluorescent protein based biosensors and QD based biosensors, which were only applied for the measurement of the intracellular glucose level, with the cells being fed with a varying external supply in culture,2,17,23–27 the proposed FNG will be exploited for monitoring the intracellular glucose level variations associated with a biological reaction process.
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| Fig. 1 (a) Schematic diagram of the FNG and chemical structures of the key components. (b) DLS size distribution of the single-network-structured template nanogel (■, □: [Glucose] = 0 mg dL−1) and the double-network-structured FNG (●, ○: [Glucose] = 0 mg dL−1; ▲, △: [Glucose] = 540 mg dL−1). Closed and open symbols denote the size distribution before and after thirty cycles of adding/removing glucose, respectively. (c) TEM images of the FNG. | ||
Secondly, in order to suppress the aggregating/leaching of QDs during repeated swelling–shrinking cycles, QDs were tethered to the FNG via covalent bonds using an allylic metallo-organic compound Zn(MAA)2 as a precursor in the synthesis. The covalent bonding of QDs onto gel network chains manifests as the characteristic FTIR absorption at 1600 cm−1 (C
O) and 1441 cm−1 (C–O) (Fig. 2a) for the bridging coordination modes of the acetate group with Zn.33 As the size of the QDs is directly related to the excitonic peak in the UV-vis absorption spectrum, the size of the QDs can be estimated by empirical functions:34
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| Fig. 2 (a) FTIR, (b) UV-vis absorption, and (c) PL spectra of the FNG. FTIR and UV-vis absorption spectra of poly(NIPAM-co-AA) nanogels and poly(NIPAM-co-FPBA) template nanogels were also presented in both (a) and (b) for comparison. (d) The photograph presents the color for the FNG dispersed in PBS of pH 7.4, taken under a UV lamp. | ||
Thirdly, the FNG was uniquely enriched with ionic sulfate groups by using an extraordinary quantity of initiator ammonium persulfate (APS) in the synthesis. The APS/NIPAM molar ratio was 0.39, which was confirmed by elemental analysis of sulfur (the contents of sulfur in the FNG were determined to be 0.986%), while that in common procedures is 0.01–0.046.18–22 Although from a theoretical viewpoint ζ-potential is electric potential in the interfacial double layer at the location of the slipping plane versus a point in the bulk solution away from the interface,35 the ζ-potential measurements (ζ = −42 ± 2 mV, measured in PBS of pH 7.4) indicated a negative surface of the FNG. In recent studies on intercellular thermometry by using temperature-responsive polymer nanogels, Uchiyama's group has demonstrated that the highly hydrophilic surface created by the sulfate groups can protect the nanogels from precipitation at high ionic strength and from localization on the cytoplasmic membrane.36,37
Furthermore, the size of the double-network-structured FNG can be well tuned through varying the synthetic parameters. For example, an increase in the feeding amount of MBAAm in the synthesis of the second network can significantly reduce the 〈Rh〉 of the hybrid nanogels (Fig. 3a). Interestingly, with an increase in the feeding amount of MBAAm in the synthesis of the second network, the typical λ1/2 of the QDs in the nanogels also exhibited a significant blue shift (Fig. 3b), indicating a decrease in the size of the QDs in the nanogels (Fig. 3c). All hybrid nanogels can be reproducible from batch to batch. To focus the topic of this work on glucometry, the FNG made from Zn(MAA)2–AAm–MBAAm (mol ratio) = 100
:
133
:
1 in the synthesis of the second network was selected for following studies.
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| Fig. 3 (a) The 〈Rh〉 values, (b) UV-vis absorption spectra, and (c) QD size of the FNG synthesized with different molar ratios of Zn(MAA)2/AAm/MBAAm in the synthesis of the second network. To show the effect of the feeding amount of MBAAm, the feeding amounts of Zn(MAA)2 and AAm were set to 0.100 g and 0.040 g, respectively. | ||
000–14
000) and dialysis against flowing PBS at ca. 10 cm s−1 (a possible blood flow rate in the circulation system of the human upper limb),43 the dissociation equilibrium shifts back from boronate ester to boronic acid, leading to nearly a superposition of the deswelling curve with the swelling curve. This indicates that in the glucose level range studied there is negligible hysteresis in one cycle of adding and removing glucose; i.e. the glucose-responsive volume phase transition is highly reversible. Moreover, the glucose-responsive volume change of the FNG is independent of the environmental temperature (16–40 °C; Fig. 4b) and pH (5.0–7.8; Fig. 4c). This is also advantageous because the temperature of living cells may slightly increase by thermogenesis of cellular events, and the local pH may be affected by neighbouring/internal structures and decrease by 1–2.5 units.44–46 Besides, the FNG in intracellular glucometry experiments might undergo a temperature change from the culture temperature of 37 °C to room temperature of 25 °C.![]()  | ||
| Fig. 4 (a) Glucose-dependent 〈Rh〉 of the FNG. Closed and open symbols denote the increasing and decreasing glucose cycles, respectively. The effect of (b) environmental temperature and (c) pH value on the glucose-responsive volume change of the FNG. | ||
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| Fig. 5 (a) Glucose-dependent PL spectra of the FNG. Scans were taken at 30.0 mg dL−1 intervals from top to bottom, from 0.0 to 540.0 mg dL−1. (b) Evolution of the PL intensity (I) at 549 nm as a function of glucose level. The error bars are within the symbols. (c) PL quenching and recovery cycles upon the repeated adding (540.0 mg dL−1) and removing (0.0 mg dL−1) of glucose in the bathing medium. (d) Linear plot showing the glucose-responsive PL properties in reciprocal space. | ||
Both the PL intensity change (Fig. 5b) and the color change (Fig. 6a) as a function of glucose level mirror that of the glucose-responsive volume change of the FNG (Fig. 4a). This observed relationship serves as further confirmation that the key of the glucose-to-fluorescence signal transduction ability of the FNG is its capability of transducing glucose-responsive volume changes into changes in PL properties. As glucose was removed from the bathing medium of the FNG by dialysis against flowing PBS at ca. 10 cm s−1, the FNG collapsed reversibly from the swelling status back to the original deswelling status (Fig. 1b), leading to a recovery of both the spectral profiles (the emission positions can return to nearly 100% of the original basal values) and intensity (return to ≥90% of the original basal values) upon the removal of glucose even after thirty cycles, thus providing a highly reproducible signal transduction (Fig. 5c and 6b), which is crucial for quantitative detection. The linear plot shown in Fig. 5d gives glucose-dependent PL properties in a more orthogonal fashion. The lowest glucose level reliably detectable with color change was approximately 2.3 mg dL−1; it is reduced to as low as 1.2 mg dL−1 when utilizing the PL intensity change.
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| Fig. 6 (a) Evolution of the yellow-green light emission position (λ) as a function of glucose level. (b) PL blue-shift and recovery cycles upon the repeated adding (540.0 mg dL−1) and removing (0.0 mg dL−1) of glucose in the bathing medium. | ||
To estimate the time response of glucose-to-fluorescence signal transduction that is potentially achievable, we monitored the response kinetics in terms of changes in PL intensity of the FNG (10.0 μg mL−1) and at 540.0 mg dL−1 glucose (Fig. 7a). The PL intensity can reach approximately 99% of their maximum change in ca. 22 s after adding glucose. The change in PL intensity can be well described by the single-exponential decay function:22,49
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| Fig. 7 (a) Characteristic kinetics of the FNG upon addition of glucose (540.0 mg dL−1). Solid line: theoretical fit with eqn (2). (b) The effect of the concentration of the FNG on the characteristic response time τsensing. | ||
The characteristic response time τsensing can thus be determined to be 0.71 ± 0.02 s. This τsensing value should reflect the essential feature of an individual FNG particle, because the engaged concentration of the FNG is below the critical value of ca. 10−2 wt% (the so-called dynamic contact concentration) and the inter-particle interactions can be completely ignored, as predicted by the concept of the screening length.50 This can be further confirmed by the result of additional experiments that the τsensing value is nearly independent of the concentration of the FNG in the range 5–80 μg mL−1 (Fig. 7b). It should be noted that the time response of the double-network-structured FNG is nearly 1.5-fold faster than that of a typical single-network-structured nanogel based biosensor reported very recently (with τsensing ≈ 1.1 s at 540.0 mg dL−1 glucose),22 indicating a great improvement on the response speed of a nanogel based biosensor under the presented design. Considering a general procedure of signal transduction on a nanogel based biosensor, several steps related to the subtle physical chemistry, such as the diffusion of glucose molecules, the adsorption/desorption and partitioning/departitioning of glucose at the solution–nanogel interface, the reaction of glucose with the PBA groups, the structural rearrangements inside the nanogel, and finally a change of the local optical electric field at the QD surface, are known to influence the time response.22,49,51 One or several of these steps in tandem could have led to the faster time response of the FNG over the single-network-structured nanogel based biosensors. Nevertheless, a fast time response is a highly desirable feature of a biosensor for applications towards monitoring dynamic changes.
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| Fig. 8 Glucose-responsive (a) PL intensity change and (b) color change in the presence of 20.0 mM L-lactate (□) and 44.0 g L−1 HSA (○), respectively, showing the effect of L-lactate and HSA on the glucose-to-fluorescence signal transduction ability of the FNG dispersed in PBS. The results (spherical symbols) without any L-lactate and HSA were also given for comparison. (c) Isothermal adsorption curve for HSA adsorbed on the FNG. (d) Clarke Error Grid Analysis of glucose sensing in blood serum, showing the glucose-to-fluorescence signal transduction ability of the FNG in a complex bio-system. | ||
In the second series of experiments, various PBS containing D(−)-fructose, D(+)-galactose, D(+)-mannose, pyruvic acid, urea, citric acid, vitamin C, γ-globulins, lysozyme, cholesterol, and common amino acids were investigated, and the relative error of glucose level reading by using the FNG is found to be within ±3.6% (see ESI-4 in ESI† for the data in detail). The FNG clearly shows excellent selectivity for glucose over the non-sugar constituents. As for sugars, while the selectivity of the PBA groups toward glucose is usually inferior to other diols such as fructose,11,38 the concentration of non-glucose sugars in blood (<0.1 mM) is ca. 10 times lower than that of glucose,52 which is thought to also occur in cells (e.g. fructose cannot enter most cells, because they lack glut-5 transporter, which transports fructose into cells),56,57 and hence are not thought to be major interferents. Nonetheless, special design of the boronic acid compounds has been carried out to improve glucose selectivity.39,40,58,59 In recent literature, ortho-substituted aryl boronic acids were demonstrated to be capable of binding fructose with a decreased selectivity relative to glucose under physiological conditions, presumably due to the steric effect of the ortho-positioned methyl substituent, disfavoring the tridentate boronate–fructose complex.60 Besides the local molecular structure of the boronic acids, the synergistic effect derived from the nanogel network structure may also be beneficial to the formation of the bidentate boronate–glucose complex for glucose sensing.20,22,39–41,60 Moreover, the influence of metal ions on the glucose-to-fluorescence signal transduction ability of the FNG was also examined. The relative error of the glucose level reading in the presence of common metal ions (2.0 × 10−3–20.0 mM) found in bio-systems, such as K+, Na+, Ca2+, Mg2+, Ba2+, Al3+, Cu2+, Zn2+, Co2+, and Fe3+, is generally within the range of ±1.0% after taking into account the experimental errors. The slight interference from metal ions is possibly associated with the coordination between the metal ions and the poly(FPBA) units, or simply the enhancement of ionic strength. Both effects would weaken the Donnan potential.
In the third series of experiments, a macro-bio-system, adult blood serum, having an environment similar to the cytoplasm (it is within the cytoplasm that most cellular activities occur)1–3 was adopted as the subject of the FNG. Blood is a specialized connective tissue in fluid form.52 It consists of liquid with cells, proteins, sugars, electrolytes and other substances either dissolved or suspended in the liquid. Plasma and serum are particular liquid components of blood. Plasma is liquid blood with the cells removed, and serum is plasma with the clotting proteins removed. On the basis of the calibration curves in Fig. 5 and 6, the apparent impaired fasting glucose (IFG) of the serums could be obtained, which was compared to the clinical IFG level measured in hospitals by using a standard enzyme-based method. 6% of the data belong to the hypoglycemic range (<70 mg dL−1) versus 56% belonging to the hyperglycemic range (>110 mg dL−1), and 38% were located between them. As shown in Fig. 8d, for the low glucose levels there is a slight overestimation of the readings of the FNG (y axis), and the overestimation increases at the higher levels. According to the definition of the different zones of the Clarke Error Grid Analysis,61 we found that 80% of the points belong to the zones A (accurate zones) and B (acceptable zones), 12% of the total belong to zones C (overcorrection zones) and 8% of the total belong to zones D (dangerous failure). There is no point in zones E (erroneous treatment). Therefore, these results can not only provide further confirmation of the high selectivity of the FNG, but also foreshadow an accurate biosensor for intracellular glucometry.
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| Fig. 9 (a) Scanning confocal fluorescence (left), transmission (centre), and overlaid images (right) of B16F10 cells incubated with the FNG (10.0 μg mL−1). (b,c) Response curves in terms of changes in (b) PL intensity and (c) color of the FNG embedded in cells. The total PL properties of a single cell (n = 5, mean ± s.d.) was adopted as a glucose-dependent parameter by the FNG. | ||
Typically, glucose utilization by a cell depends on transport and metabolism. Most mammalian cells transport hexoses into/out of the cytosol (the liquid portion of the cytoplasm), as mediated by a family of monosaccharide facilitators.1–3 B16F10 cells were grown in sugar-free DMEM. When fed different amounts of glucose, the cells labeled with FNG can be optically differentiated using a confocal microscope. Local analysis of the overall PL of the FNG embedded in a cell indicated the difference in intracellular glucose levels. As for the PL intensity change, the fluorescence signal was obtained from fluorescence images by summing the PL intensities of all the pixels within a single cell (n = 5, mean ± s.d.), while for the color change, the fluorescence signal was read from microscope by creating the lambda series and analysing the spectra through a stack dialog window. As Fig. 9b (intensity change) and Fig. 9c (color change) show, the fluorescence signal of the FNG embedded in cells can sharply change when the cells were fed with an external supply of 30–540 mg dL−1 glucose in culture ([Glucose]ex).
Both the PL intensity change (Fig. 9b) and the color change (Fig. 9c) of the FNG embedded in cells as a function of [Glucose]ex mirror that of the FNG dispersed in PBS (Fig. 5b and 6a correspondingly). Meanwhile, two interesting behaviours were observed: (a) without glucose feeding, the emission position appeared at about 548.8 nm, indicating an initial intracellular glucose level of ca. 31.3 mg dL−1, according to the calibration curve shown in Fig. 6a; and (b) when externally supplied with the same [Glucose]ex over 30–540 mg dL−1, neither the glucose-induced PL quenching degree nor blue-shift degree for the FNG embedded in cells is identical to that for the FNG dispersed in PBS, reflecting the fact that the glucose level in cells is different from that in culture. The latter behaviour is possibly due to the fact that the glucose molecule enters most cells by facilitated diffusion, a form of passive transport requiring no energy but requiring transmembrane proteins.1–3 On the basis of the calibration curve shown in Fig. 6a, the intracellular glucose level [Glucose]cell can be readily correct with [Glucose]ex (Fig. 10a). A possible empirical function was also obtained to described the quantitative relationship between [Glucose]cell and [Glucose]ex. It is clear that at a value of [Glucose]ex over 30–540 mg dL−1, the increment of the intracellular glucose level was generally ca. 43–72% of the external supply. This finding is in accordance with the observations on intracellular glucose detection by using fluorescent protein based biosensors23 and QD based biosensors.17 With the color change as a frame of reference, we can further gain the quantificational relationship between the intracellular glucose levels and the PL intensity change of the FNG embedded in cells (Fig. 10b). The calibration curve for intracellular thermometry using the change in the calibrated PL intensity (Ical) can be obtained by approximating the relationship:
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| Fig. 10 A comparison of the glucose level in cells [Glucose]cell with that in culture [Glucose]ex, where [Glucose]cell was measured with the FNG using the color change. (b) Calibrated response curve for the PL intensity change, where Ical is the calibrated PL intensity measured with the FNG embedded in cells. | ||
Moreover, because the lowest glucose level reliably detectable with the PL intensity change is much lower than that with the color change, the glucose resolution (i.e., the minimum glucose level difference to be significantly discriminated) for the PL intensity change depends on that for the color change. The glucose resolution for the color change was 1.9–2.8 mg dL−1 over the intracellular glucose level range of 30–540 mg dL−1.
For a more practical use of the FNG, intracellular glucose variations induced by biochemical stimuli were considered. Typically, the B16F10 cells labeled with the FNG were fed with lactose (500.0 mg dL−1), a disaccharide sugar that is found most notably in milk and is thought to be associated with cancer,64 and β-galactosidase (4.1 NLU mL−1), which plays an important role in cellular metabolism by breaking down lactose into galactose and glucose (see ESI-7 in ESI†). No noticeable morphological changes were observed on the tested B16F10 cells during the experiment. Fig. 11 indicates the time-domain fluorescence signals (utilizing the PL intensity change) of the FNG embedded in cells exposed to lactose and β-galactosidase, and the corresponding intracellular glucose levels [Glucose]cell,t obtained using the calibration curve shown in Fig. 10b. While a neglectable change in PL properties was observed when fed with an equated amount of lactose, β-galactosidase, or galactose only (see ESI-8 in ESI† for control experiments), it can be seen that the presence of both lactose and β-galactosidase provoked the PL quenching of the FNG embedded in cells. For example, a quenching of ca. 32.5% in Ical occurred after the reaction had proceeded for 5 min, indicating [Glucose]cell,t = 5 min = 36.6 mg dL−1 (Fig. 11a); that is, an intracellular glucose level rising by an increment of 5.3 mg dL−1 was detected. This variation in glucose level greatly exceeded the glucose resolution of the FNG. Moreover, the response kinetics of the FNG (Fig. 7a) is much faster than that of β-galactosidase catalytic hydrolysis of lactose (see ESI-7 in ESI†). Taken together, it allows us to affirm that the FNG can monitor the dynamic changes of intracellular glucose levels.
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| Fig. 11 (a) Time-domain fluorescence signals of the FNG embedded in cells (■; n = 5, mean ± s.d.) and the corresponding intracellular glucose level [Glucose]cell,t (□), upon the addition of lactose and β-galactosidase to the culture medium. (b) Time-dependent conversion showing the kinetics of β-galactosidase catalytic hydrolysis of lactose, measured with the FNG embedded in cells (□) and the FNG dispersed in PBS (○), respectively. Solid lines: 1st-order kinetic fits. | ||
Based on the evolution of glucose level, the apparent rate constant of β-galactosidase (4.1 NLU mL−1) catalytic hydrolysis of lactose can be derived from the fitting of the time-dependent conversion. Here, the conversion was calculated by
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:
1 volume ratio) mixture and dried under vacuum. Acrylic acid (AA) was purified by distillation under reduced pressure. Zn(MAA)2, AAm, MBAAm, sodium dodecyl sulfate (SDS), APS, sodium hydroxide (NaOH), 2,2′-azobis(2-methylpropionamidine) dihydrochloride (AAPH), FPBA, N-(3-dimethylaminopropyl)-N-ethyl-carbodiimide hydrochloride (EDC), potassium dihydrogen phosphate (KH2PO4), dipotassium hydrogenphosphate (K2HPO4), Rhodamine 640, Rhodamine 590, Rhodamine B, D(+)-glucose, β-D-lactose, β-galactosidase, D(−)-fructose, sodium L-lactate, D(+)-galactose, D(+)-mannose, pyruvic acid, urea, citric acid, vitamin C, g-globulins, lysozyme, and amino acids were used as received without further purification. The water used in all experiments was of Millipore Milli-Q grade.
000 rpm, 20 min, 35 °C, Thermo Electron Co. SORVALL® RC-6 PLUS superspeed centrifuge) and 3 days’ dialysis (Spectra/Por® molecular porous membrane tubing, cutoff 12
000–14
000 Dalton MWCO) against water at room temperature. The purified poly(NIPAM-co-AA) nanogels (20 mL) were cooled in an ice bath, and then FPBA (0.235 g) and EDC (0.231 g) were added. The reaction was allowed to proceed for 4 h under stirring in an ice water bath. The resultant poly(NIPAM-co-FPBA) template nanogels were purified by dialysis against water.
000 rpm, 30 min, 35 °C), redispersed in water, and 3 days’ dialysis against water.
000 rpm, and 30 min) and washed by distilled water twice. The protein–FNG complexes were collected and redispersed in PBS (5.0 mL) for analyzing the effect of adsorption of protein on the FNG. Moreover, the protein concentration in the supernatant, CE, was determined using UV-vis absorption at 278 nm, based on the linear calibration curve (R2 > 0.99) measured using the HSA solutions with known concentrations under the same conditions, for the calculation of surface density dHSA of the protein:![]()  | (5) | 
The biochemical stimulus was conducted by quickly replacing the serum/sugar free medium with fresh sugar-free DMEM (1.8 mL), lactose solution (100 μL, in sugar-free DMEM), and β-galactosidase solution (100 μL, in sugar-free DMEM) in a glass base dish containing the FNG-stained B16F10 cells. The temperature of the culture medium was maintained at 37.0 °C during the experiment. Control dishes contained the FNG-stained B16F10 cells plus lactose (plus 100 μL sugar-free DMEM), the FNG-stained B16F10 cells plus β-galactosidase (plus 100 μL sugar-free DMEM), and the FNG-stained B16F10 cells plus galactose (plus 100 μL sugar-free DMEM), respectively.
Live cell imaging was performed on a confocal laser scanning microscope (LEICA TCS SP2 AOBS™) equipped with a HC PL APO CS 20 × 0.7 DRY lens. A UV (405 nm) light was used as the light source. Laser power at the sample plane was 10 mW for all the experiments. A high-resolution Hamamatsu C9100-02 CCD camera was used for acquiring cell images. As for PL intensity change, the fluorescence signal was obtained from fluorescence images by summing the PL intensities of all the pixels within a single cell (n = 5, mean ± s.d.), while for color change, the fluorescence signal was read from the microscope by creating the lambda series and analysing the spectra using the standard LCS software through a stack dialog window.
The glucose resolution (δ[Glucose]cell) was evaluated by:69
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DLS was performed on a 90Plus multi angle particle sizing analyzer equipped with a BI-9000AT digital autocorrelator (Brookhaven Instruments, Inc.) to measure the average hydrodynamic radius 〈Rh〉 and the size distribution. A He-Ne laser (35 mW, 659 nm) was used as the light source. All dispersions were passed through Millipore Millex-HV filters with a pore size of 0.80 μm to remove dust before DLS measurements. In DLS, the Laplace inversion (here the CONTIN method was used) of each measured intensity–intensity time correlation function in a dilute dispersion can lead to a line-width distribution G(Γ). For a purely diffusive relaxation, Γ is related to the translational diffusion coefficient D by (Γ/q2)C→0,q→0 = D, so that G(Γ) can be converted to a transitional diffusion coefficient distribution and 〈Rh〉 distribution by using the Stokes–Einstein equation, 〈Rh〉 = (kBT/6πη)/D, where kB, T, and η are the Boltzmann constant, the absolute temperature, and the solvent viscosity, respectively.70 All DLS measurements were made at scattering angle θ = 90°.
Footnotes | 
| † Electronic supplementary information (ESI) available: Experimental procedures and characterization data. See DOI: 10.1039/c2bm00162d | 
| ‡ These authors contributed equally to this work. | 
| This journal is © The Royal Society of Chemistry 2013 |