A common method to quantify protease activity is based on Fluorescence Resonance Energy Transfer5
(FRET) measurements using fluorescently tagged protein substrates. A major drawback to this approach is that a chemically modified substrate may not exhibit the same reactivity as the native substrate. While fluorescent labels can provide high sensitivity, the attachment of a probe requires an extra step that increases analysis time and complexity. In addition, fluorescent probes can be subject to photochemical degradation and pH-dependent responses. Porous Si-based interferometers operate by measuring a change in refractive index in a volume of solution contained within the porous nanostructure, and they have been shown to provide a simple, label-free method for detection of proteins that minimizes the quantity of reagents used6-9
. Recently, the advantage of using more complicated porous Si optical structures to correct for zero-point drift or non-specific binding has been demonstrated10,11
. Additionally, recent work has shown how catalytic reactions can be harnessed to improve sensitivity of these nanosensory systems12,13
The two-layer porous Si nanostructure was prepared by electrochemical etching of silicon in an HF-containing electrolyte. The double layer was then thermally oxidized (600 °C for 1.5 h, in air) to generate a stable silicon oxide (SiO2
) surface. The size, shape, and population of the pores in a film are determined by the current, allowing one to “dial in” a specific porosity pattern14
. Thus a double layer containing large pores on top of small pores is prepared by decreasing the applied current density midway through the etch, resulting in the abrupt decrease in pore size shown in the cross-sectional scanning electron microscope (SEM) image of . The tunability of the pore etching process provides a convenient means to build such nanostructured matrices that can act as reservoirs15
or size exclusion membranes4,16
. The programmability can also be used to build optical structures with useful sensing properties.
The average diameter of the pores in the present structure is ~100 nm in the top layer and ~6 nm in the bottom. Being smaller than the wavelength of visible light, the features in this nanostructure do not scatter light, and the sample displays well-resolved Fabry-Pérot interference fringes in the optical reflectivity spectrum (). The reflectivity spectrum displays an interference pattern that arises from a combination of Fabry-Pérot interference from the very flat interfaces bordering the two layers.
Reflectivity spectrum (a) and corresponding Fourier transform (b) of a porous Si double layer film
It has been shown that the Fourier transform of the reflectivity spectrum yields peaks that correspond to the optical thickness 2ni
of each layer or combination of layers, where ni
is the refractive index and Li
the thickness of layer i in the stack10,11
. The optical spectrum can be used to sense molecules because it is sensitive to the refractive index of any substance filling the pores. Most biomolecules and proteins have a refractive index of ~1.40, whereas aqueous buffers posses an index close to 1.34. The introduction or removal of a chemical or biochemical species from a porous layer is thus detected as a shift in the value of 2nL9-11,13,17
. Differential responses between two stacked layers have been used to correct for zero point drift in the detection of proteins and antibodies10,11
. The method is referred to as Reflective Interferometric Fourier Transform Spectroscopy, or RIFTS. For the double-layer structure used in the present work, it is found that the method can also quantify the partitioning of molecules between the two layers, by measurement of the position of the peaks in the Fourier transform spectrum that correspond to each layer.
The nano-reactor layer is loaded with an enzyme by electrostatic adsorption from an aqueous buffer solution at pH 2.0 (). Pepsin was chosen as a model protease because it and its reaction kinetics are well-characterized18
. Pepsin is continually cycled through a flow cell containing the porous Si sample for 90 min, at which point the cell is flushed with pure pH 2.0 buffer to remove excess pepsin not adsorbed to the sample. The adsorption of pepsin into the nano-reactor layer is detected as a ~15 nm increase in the value of 2nL in the Fourier transform spectrum, corresponding to a loading of 200 ng of enzyme in the 5 nanoliter volume probed by the optic (Supplemental Table 1
). The surface of oxidized porous Si is negatively charged at pH 2.06
, leading to a strong attraction between the surface and pepsin, which carries a net positive charge at this pH19
. Because of this non-specific adsorption, the effective concentration of enzyme in the pores is ~ 2 mM, representing an increase by a factor of 70 relative to the free solution concentration. The relatively large pepsin molecule (35 kDa, 10 × 6 × 20 nm)20
is excluded from the smaller pores in the second layer of the porous Si double layer (Supplemental Figure S1
Nanoreactor used to process protein and quantify proteolytic activity
Reactions were carried out in the enzyme-loaded nanoreactor by introducing various substrate/inhibitor combinations into the flow stream of the cell. The reactions were monitored in real-time by acquisition of reflectivity spectra from the double-layer; the Fourier transform provides a direct measure of the amount of protein infiltrated in each layer. (and Supplemental Figures S1
) shows the effect of introduction of the protein substrate α-casein into the nanoreactor. The top layer of the nanostructure (Layer 1), containing 100 nm-diameter pores, admits α-casein and the value of the optical thickness, 2nL, initially increases as protein accumulates in this layer. The value of 2nL decreases as pepsin digests the protein and the digestion products escape into solution and into Layer 2 of the reactor. The value of 2nL for this lower layer increases as the smaller products of enzymatic digestion diffuse into the ~6 nm-diameter pores of the lower nanostructure. Control experiments performed with no pepsin (or with an inhibitor present) verify that intact α-casein does not enter the small pores of Layer 2. The digestion results are similar if the enzyme is loaded from a more complex buffer solution resembling Eagle’s medium, that contains a mixture of amino acids, sugars, and vitamins (Supplemental Figure S2
). It is important to point out that the temporal behavior of the two layers, in particular the transient of Layer 1, is a characteristic of the action of the enzyme on the substrate. Introduction of small molecules that are not digested by the enzyme produce a signal-time characteristic in both of the layers that are similar to that observed in Layer 2 for the digested substrate.
Optical response of the two layers in a pepsin-loaded nanoreactor upon introduction of α-casein
The optical spectra can be used to quantify the kinetics of the enzymatic reaction. shows Δ2nL vs time traces obtained for several different initial concentrations of α-casein. The response of Layer 2 is monitored; its small pores exclude the intact protein and the protease while admitting the smaller digestion products generated by the action of the protease. The quantity 2nL is proportional to mass8
, and so the increasing value of Δ2nL as a function of time depicted in is indicative of the entry of protein fragments into Layer 2. As expected, the initial slope and the final steady-state value of the traces in increase with increasing concentration of α-casein. A double reciprocal plot of the steady-state value of Δ(2nL) and [α-casein] is linear (), consistent with a reaction that is 1st order in substrate.
Kinetics of digestion of α-casein by pepsin in the nanoreactor as a function of casein concentration
The data are consistent with the known kinetics of the enzyme in free solution. Initial reaction velocity (Vo
) is typically characterized as the mass of product formed per unit time during the initial stage of conversion of substrate to product. In the case of the nano-reactor, the mass of products generated is proportional to the value of Δ(2nL) measured in Layer 2. Vo
was obtained by a linear fit of the initial phase of the curves depicted in . A non-linear least-squares fit of Vo
vs concentration of substrate α-casein (Supplemental Fig. S3
) yields a value of 0.35 μM/min for the maximum reaction velocity (Vmax
) and 18 μM for the Michaelis-Menten constant (Km
). These kinetic parameters are somewhat smaller than the literature values for pepsin (Vmax
= 1.20-2.69 μM/min; Km
= 37-109 μM)21
. The enzymatic reaction in the nanoreactor is thus apparently slower than in free solution, which may be a result of the restricted dimensions in the porous matrix or adsorption of substrate to the pore walls.
The aspartic protease inhibitor pepstatin A was used to perform enzymatic inhibition studies. Pepstatin A is a competitive inhibitor of pepsin. The initial rate of digestion of α-casein was quantified using a series of pepsin-infused nano-reactors that were treated with solutions containing various concentrations of α-casein and a fixed concentration of the inhibitor (1μM). A non-linear least-squares fit of Vo
vs. α-casein in the presence of 1μM pepstatin A (Supplemental Fig. S4
) yields a rate of competitive inhibition Ki
of 84 nM, somewhat larger than the literature value of 1 nM22
. The larger value of Ki
relative to the literature is attributed to adsorption of the inhibitor in the porous nanostructure, leading to a reduction in the effective concentration of inhibitor available to the enzyme.
In summary, a self-reporting nano-reactor that is able to capture enzymes, host a catalytic reaction in a mesoporous cavity, isolate and quantify the reaction products, and provide information on the reaction kinetics in a volume of ~5 nanoliters has been demonstrated. This work provides a general method to quantify kinetics of an immobilized enzymatic reaction. The specific example in this work involved quantification of protease activity, but the approach is applicable to a range of reactions of interest to the high-throughput analytical and synthetic communities, such as DNA amplification, polymerization, enzyme-linked assays, and protein purification.