The present invention relates to Raman spectroscopy, surface enhanced Raman spectroscopy and surface enhanced resonance Raman spectroscopy.
It is known that there are many techniques to detect the action or presence of analyte molecules. One such technique utilises the Raman Scattering (RS) effect. When light is scattered from a molecule, most of the photons are elastically scattered. The majority of the scattered photons have the same energy (and therefore frequency and wavelength) as the incident photons. However, a small fraction of the light (approximately 1 in 107 photons) is scattered at frequencies different from that of the incident photons. When the scattered photon loses energy to the molecule, it has a longer wavelength than the incident photon (termed Stokes scatter). Conversely, when a scattered photon gains energy, it has a shorter wavelength (termed anti-Stokes scatter). Stokes scatter is usually the stronger effect.
The process leading to this inelastic scatter is termed the Raman effect after Sir C. V. Raman, who first described it in 1928. It is associated with a change in the vibrational, rotational or electronic energy of the molecule, with the energy transferred from the photon to the molecule usually being dissipated as heat. The energy difference between the incident photon and the Raman scattered photon is equal to the energy of a vibrational state or electronic transition of the scattering molecule, giving rise to scattered photons at quantised energy differences from the incident laser. A plot of the intensity of the scattered light versus the energy or wavelength difference is termed the Raman spectrum, and the technique is known as Raman spectroscopy (RS).
Surface enhanced Raman spectroscopy (SERS) is a variant of the RS analytical technique. The strength of the Raman signal can be increased enormously if the molecules are physically close to certain metal surfaces, due to an additional energy transfer between the molecule and the surface electrons (plasmons) of the metal. To perform SERS, the analyte molecules are adsorbed onto a substrate comprising an atomically roughened metal surface and the enhanced Raman scattering is detected. SERS can also be performed using silver colloids in solution as the substrate.
The Raman scattering from a molecule or ion within a few Angstroms of a metal surface can be 103 to 106 fold greater than in solution. For near visible wavelengths, SERS is strongest on silver, but is readily observable on gold and copper as well. Recent studies have shown that a variety of other transition metals may also give useful SERS enhancements. So-called free electron metals, that is metals having a high number of free surface electrons, generally provide SERS enhancements. Furthermore, so-called metallic polymers could also be used; these being organic polymers that have an electronic structure such that they behave in a similar manner to a metal. It will be appreciated that the term metal is not limited to a metallic element or a mixture or alloy of metals and can apply to any material that the skilled person would understand to be a metal. Materials that provide such SERS enhancements are henceforth referred to as Raman enhancing surfaces or metals.
The SERS effect is in essence a resonance energy transfer between the molecule and an electromagnetic field near the surface of the metal. The electric vector of the excitation laser induces a dipole in the surface of the metal, and the restoring forces result in an oscillating electromagnetic field at a resonant frequency of this excitation. The strength and frequency of this resonance is determined mainly by the free electrons at the surface of the metal (the ‘plasmons’) determining the so-called plasmon wavelength, as well as by the dielectric constants of the metal and its environment. Molecules adsorbed on or in close proximity to the surface experience an exceptionally large electromagnetic field in which coupling to vibrational modes normal to the surface are most strongly enhanced. This is the surface plasmon resonance (SPR) effect, which enables a through-space energy transfer between the plasmons and the molecules near the surface. The intensity of the surface plasmon resonance is dependent on many factors including the wavelength of the incident light and the morphology of the metal surface, since the efficiency of energy transfer relies on a good match between the laser wavelength and the plasma wavelength of the metal.
The strength and local density of the field is determined by a variety of parameters. The wavelength of the reflected light determines its energy, and the composition and morphology of the metal determines the strength and efficiency with which the surface plasmons couple to the photon energy. Other factors, such as the relative dielectric properties of the metal and analyte solution, also have strong contributions to the effect. In addition, the efficiency of energy transfer between the field and any molecules close to the metal surface is also determined by resonant energetic states in the molecule itself, including, for example, specific vibrational modes in the infrared spectral region and electronic energy transitions in the ultraviolet. This is the mechanism by which SERRS gains performance over conventional SERS. SERRS can be performed by using a chromophore moiety to provide an additional molecular resonance contribution to the energy transfer.
The intensity of a resonance Raman peak is proportional to the square of the scattering cross section of the molecule. The scattering cross section is, in turn, related to the square of the transition dipole moment, and therefore usually follows the absorption spectrum. If the incident photons have energies close to an absorption peak in their absorbance spectrum, then the molecules are more likely to be in an excited state when the scattering event occurs, thereby increasing the relative strength of the anti-Stokes signal. A combination of the surface and resonance enhancement effects means that SERRS can provide a huge signal enhancement, typically of 109 to 1014 fold over conventional Raman spectroscopy.
In addition to resonance enhancement for Raman scattering, there have recently been descriptions of resonance de-enhancement, in which the Raman signal is reduced in intensity by a resonance energy transfer mechanism. Under specific conditions, an excited energy state close in energy to that of interest can produce a decrease in Raman scattering. In this situation, the Raman intensity is proportional to the square of the sum of the cross sections, and if they are of opposite signs then destructive interference can occur, resulting in the observed resonance de-enhancement. This provides an alternative metric for use in a Raman-based detector system: signals from a particular Raman-active chromophore may be selectively removed from the Raman spectrum by using a laser frequency that promotes this de-enhancement effect.
Surface enhanced Raman spectroscopy (SERS) and its extension, surface enhanced resonance Raman spectroscopy (SERRS) are gaining in popularity as quantitative bioanalytical tools. Both techniques rely to a large degree on an interaction between the ‘plasma’ of mobile conduction electrons at the surface of a metal (the plasmons) and molecular species close to that surface. This interaction results in a substantial enhancement of Raman scattering at specific vibrational energies, yielding a strong spectral signal in the Raman scattered light.
Until recently, a controversy surrounded the understanding of the enhancement mechanisms. The two major factions disagreed on the partitioning of the greater than 106 enhancement factor between the chemical enhancement mechanism and the electromagnetic enhancement mechanism. The chemical enhancement mechanism, now thought to contribute an enhancement factor of 102, asserts that a charge-transfer state is created between the metal and adsorbate molecules. This mechanism is site-specific and analyte dependent. The molecule must be directly adsorbed to the surface in order to experience the chemical enhancement. The electromagnetic enhancement mechanism contributes a greater than 104 times enhancement over normal Raman scattering. In order to understand the electromagnetic enhancement, one must consider the size, shape, and material of the surface's nanoscale roughness features. If the correct wavelength of light strikes a metallic roughness feature, the plasma of conduction electrons will oscillate collectively. Because this collective oscillation is localized at the surface of this plasma of electrons, it is known as a localized surface plasmon resonance (LSPR). The LSPR allows the resonant wavelength to be absorbed and scattered, creating large electromagnetic fields around the roughness feature. If a molecule is placed within the electromagnetic fields, an enhanced Raman signal is measured.
We have appreciated the problem that the Raman scattering effect, even using surface enhanced Raman scattering (SERS), provides a small amount of Raman scattered radiation in comparison to normal scattering (effectively a poor signal to noise ratio). We have further appreciated that, because the Raman signal is weak in comparison to noise, there is a need to introduce a mechanism to help distinguish the Raman signal from the noise.
We have appreciated that reducing diffusion path lengths of analyte molecules can have a dramatic impact on the speed of the biosensor assay. Accordingly, in broad terms, the invention provides an arrangement that reduces the diffusion path lengths of a sample to be tested using spectroscopic techniques.
The invention is defined in the claims to which reference is directed.
An embodiment of the invention provides an improved analyte detector with a Raman enhancing volume located within the reaction region created by depositing a Raman enhancing surface on, or within, a porous 3D support matrix made of a solid support material. The support material is arranged to have a dye distributed within the volume and the response to illumination of the dye is enhanced as a result of the dye being distributed within the volume and proximate to the Raman enhancing surface that is also distributed within the volume.
A reaction carrier for use in an analyte detector, into which a sample for testing is introduced, may be produced according to the invention having a solid support material arranged to define a volume and a metal/Raman enhancing surface distributed and immobilised within the volume. The metal is supported by the support material, which is being porous to a dye that allows the analyte to be detected. The metal is arranged such as to enhance an optical response to illumination of the dye.
Whilst the embodiment(s) of the invention described refer to the improvements provided to the Raman signal and its applications in Raman spectroscopy (particularly SERS and SERRS), it should be appreciated that the invention may be used in any form of spectroscopy in which an improvement in the signal strength can be obtained by using a metal surface being such as to enhance a response to illumination of a dye. This may, for example, include surface absorption fluorescence or any response to illumination that involves a resonant energy transfer to the metal surface.
The term chromophore is well known to the skilled person and is used herein to cover a group having specific optical characteristics. The term “dye” refers to a chromophore that can emit Raman radiation and also has some sort of functionality such as a linking group or a surface-seeking group. Such functionalities could result, for example, from adding a metal surface seeking group, or a group to allow binding to an analyte. The chromophore should strongly absorb the excitation laser at wavelengths suitable for surface enhancement (the most popular Raman lasers are 514 nm, 532 nm, and 785 nm). This is in the green-red visible range, so traditional brightly coloured chromophores are found as a constituent of particularly good Raman-active dyes.
An analyte is any chemical that it is desired to detect or quantify. Examples of suitable analytes include: biological molecules (such as proteins, antibodies, nucleic acids, carbohydrates, proteoglycans, lipids, or hormones), pharmaceuticals or other therapeutic agents and their metabolites, drugs of abuse (for example amphetamines, opiates, benzodiazepines, barbiturates, cannabinoids, cocaine, LSD and their metabolites), explosives (for example nitro-glycerine and nitrotoluenes including TNT, RDX, PETN and HMX), and environmental pollutants (for example herbicides, pesticides).
An analyte sample is any sample that it is desired to test for the presence, or amount, of analyte. There are many situations in which it is desired to test for the presence, absence, or amount, of an analyte. Examples include clinical applications (for example to detect the presence of an antigen or an antibody in a biological sample such as a blood or urine sample), to detect the presence of a drug of abuse (for example in an illicit sample, or a biological sample such as a body fluid or breath sample), to detect explosives, or to detect environmental pollutants (for example in a liquid, air, soil, or plant sample).
In addition to directly detecting analytes themselves, it is also possible to detect them indirectly by using a reporter molecule which is able to generate a detectable change in its Raman signal in the presence of the analyte of interest. An example of this would be the displacement of a dye-labelled peptide from the antigen binding site of an analyte-specific antibody, thereby releasing free reporter molecules which are then able to interact with the SERRS-active metal surface. For our purposes, such reporter molecules can also be regarded as ‘analytes’.
Typically a reporter molecule will comprise a reporter dye, a selective agent binding group, and a metal surface-binding group. The reporter molecule is bound to the selective agent (by means of the selective agent binding group), and the reporter dye is therefore held away from the metal surface, before the analyte sample is introduced to the carrier. Binding of the analyte to the selective agent displaces the reporter molecule, which then binds to the metal surface (by means of the metal surface binding group) thereby causing the reporter dye to move to the region near the metal surface. The term “dye” as referred to above applies equally to a reporter molecule.
A selective agent is any agent that binds selectively to the analyte in the presence of the other components of the analyte sample, and under the conditions in which the detection method is carried out, so that the presence (or amount) of the analyte in the sample can be detected. The nature of the selective agent will of course depend on the identity of the analyte. In many cases, the selective agent will be an antibody. However, other suitable analyte binding partners may be used. For example, if the analyte is an antibody, the selective agent may be an antigen or antigen derivative that is selectively bound by the antibody. If the analyte is nucleic acid, the selective agent may be a nucleic acid, or a nucleic acid analogue, that hybridizes to the analyte nucleic acid.
The dye need not detach from the selective agent upon introduction of the analyte. Instead the selective agent may change configuration upon binding of the analyte such that the dye moves into a new position closer to the metal, thereby resulting in an increase to the Raman signal. It is also possible that the dye is initially held in a position close enough to the metal surface to produce a SERRS signal, but is displaced in the presence of an analyte to be detected, e.g. by binding to a selective agent and displacing the dye from its position near the metal surface. In this instance, rather than looking for an increase in the Raman radiation emitted, it is the reduction in the Raman radiation that allows the absence, presence or quantity to be determined.
The analyte itself may be intrinsically Raman-active. In such embodiments the dye may be chemically identical to the analyte and the presence, absence or quantity of analyte can be determined directly from its Raman signal. Therefore the term “dye” may also include an analyte.
The term “antibody” is used herein to include an antibody, or a fragment (for example a Fab fragment, Fd fragment, Fv fragment, dAb fragment, a F(ab′)2 fragment, a single chain Fv molecule, or a CDR region), or derivative of an antibody or fragment that can selectively bind an analyte to allow detection of the analyte.
In general, it is expected that the components of the dye will be linked together by separate linkers. It will be apparent to the skilled person that there are many possible suitable linkers that could be used. The identity of the linkers will depend on the identity of the components of the dye. If the selective agent binding group comprises a peptide, it is advantageous if the linker is compatible with conventional peptide linking chemistry. For example, the linker may preferably comprise a single carboxylic acid group for reaction with the N-terminus of the peptide.
In some circumstances, depending on the particular components used, it may be possible to link two or more components of the dye together without use of a separate linker, for example by reaction between chemical groups of different components of the dye.
The components of the dye may be linked together in any order, provided that when the dye is bound to the surface by means of its metal surface-binding group, the dye is within the region near the metal surface.
The metal surface-binding group of the dye should be a group that binds preferentially (typically by adsorption) to the metal surface. In some circumstances, it may be desired that binding of the metal surface-binding group to the metal surface is sufficiently strong enough to immobilize the dye to the metal surface. The chemical nature of the metal surface-binding group will depend on the metal surface that is used. Suitable silver binding functional groups include groups having a heterocyclic nitrogen, such as oxazoles, thiazoles, diazoles, triazoles, oxadiazoles, thiadiazoles, oxathiazoles, thiatriazoles, benzotriazoles, tetrazoles, benzimidazoles, indazoles, isoindazoles, benzodiazoles or benzisodiazoles. Other suitable functional groups include amines, amides, thiols, sulphates, thiosulphates, phosphates, thiophosphates, hydroxyls, carbonyls, carboxylates, and thiocarbamates. Amino acids such as cysteine, histidine, lysine, arginine, aspartic acid, glutamic acid, glutamine or arginine also confer silver binding.
The term reaction carrier is used to define the container into which an analyte to be detected is introduced and within which the support material is located.
An embodiment of the invention will now be described, by way of example only, and with reference to the accompanying drawings, in which:
The embodiments described feature an improved substrate for use in spectroscopy. The invention uses a metal distributed within a fine-grained three-dimensional support material to produce a substrate with optimal characteristics for SERS and SERRS. Bringing the metal physically closer to the analyte molecules in solution reduces the diffusion path lengths and can achieve a decrease in assay times, as well as increasing the available metal surface area accessible to the analyte molecules in a given volume of solution. In addition, the Raman illumination laser samples a 3D volume rather than a 2D surface, with benefits not just for signal intensity but also for addressing engineering problems such as focussing. Also, the engineering constraints on the supporting biosensor chip can be relaxed somewhat, since it is the nature of the support material, rather than the reaction carrier dimensions, which has the biggest influence on the sensor performance.
An embodiment of this invention is realised by chemically depositing portions of metal within a support material. Several benefits can be achieved by this, including enhanced sensitivity, prolonged stability of photolabile chromophores, and a vastly reduced assay time. As a preferred feature the metal portions deposited within the support material to form the Raman enhancing surface are silver. The support material is a solid, for example in the form of a silica filter, but this is not a requirement and the support material may, for example, be in the form of a powder or glass balls. A main requirement of the support material is that it keeps the Raman enhancing surface immobilised within the reaction carrier.
A method of producing an improved substrate, using silver deposition chemistry, will now be described and is based on an analytical test for carbohydrates which was developed by the German chemist Bernhard Tollens (1841-1918), and which now bears his name. It will be appreciated by someone skilled in the art that this is not the only means of depositing a metal on a surface and that other methods are within the scope of the invention. It will be further appreciated that whilst silver exhibits many desirable features for use as a Raman enhancing surface in spectroscopy other substances can be used such as, for example, gold and copper. Also, using combinations of these metals may infer advantages on the flexibility of the invention and are discussed below.
Tollens' reaction is a multi-stage process, involving the oxidation of an aldehyde to the carboxylic acid, and reduction of aqueous silver ions to the metal. First, silver hydroxide is prepared from silver nitrate by reacting with sodium hydroxide:
AgNO3+NaOH→AgOH+NaNO3
The hydroxide forms a brown-black precipitate which usually also contains silver oxide. Adding ammonium hydroxide produces a silver diamine complex, as a colourless solution:
AgOH+2NH4OH→[Ag(NH3)2]++OH−+H2O
The diamine complex is stable in aqueous solution and can be stored until needed. The silver deposition process is initiated by adding an aldehyde. The aldehyde reacts with hydroxyl ions in the alkali solution causing it to be oxidised to a carboxylic acid and releasing two electrons:
The aldehyde can come from a variety of sources. In the traditional Tollens reaction, a glucose solution is used. Like most sugars, glucose can exist in a closed-ring or an open-chain form. In water solution both forms are in equilibrium:
The electrons released by the oxidation of the aldehyde can each then reduce a silver diamine complex to give metallic silver and free ammonia:
[Ag(NH3)2]++e−→Ag+2NH3
This redox reaction can be summarised as:
The reduced silver atoms are unstable in aqueous solution, and quickly come together to give metallic silver. If an appropriate solid surface is available, the metal will form at the interface between the surface and the solution. In the traditional Tollens' test for sugars, a clean glass surface is used, and the silver forms a confluent, mirror-like film in a matter of minutes.
Depending on the specific reaction conditions, which are dependent on the analyte in question, and the nature of the available support material, the Raman enhancing surface (preferably silver) may form a suspension of micro to nanometre scale particles, particle clusters, and particles deposited on the support material and within any voids present in the support material.
The abovementioned process is just one method of producing a support material in accordance with the invention. Other methods can be employed including, for example, immobilising silver colloids on or within the support structure.
It is preferred that the support material is a fine-grained, porous, three-dimensional support matrix chosen to have the optical properties of glass. For example, the support material may be in the form of glass balls filling a portion of the reaction carrier. In particular, the support material should not be fluorescent (which would give an unacceptable background interference to the Raman spectra), would ideally be a very biocompatible material, and should not contribute a substantial Raman signals of its own, or at least not within the frequency range of the Raman response of the dye, since this would obscure the Raman signal from the dye. Silica is ideal for these purposes but it should be appreciated that other materials with similar properties could be used without straying from the scope of the invention. Examples of other materials that may be used to form the support material include ceramics, plastics or aerogels.
The support material defines a volume within which the silver particles may be distributed. In one embodiment the silver particles are deposited on the outside of the individual substrate particles that comprise the support material. An example of this can be seen in
An additional embodiment is described below in which the substrate particles comprising the support material are themselves porous to the dye and have silver particles deposited within their internal structure.
A 3D porous material such as silica provides a volume with a much larger internal surface area compared to a flat surface, so there is a much greater surface available for molecular adsorption. Also, instead of illuminating a planar surface spot, the incident laser illuminates a volume within the material, further increasing the surface area that is interrogated by the Raman laser. Both of these factors result in a large increase in the number of SERRS-active molecules within the illumination beam, with a consequent improvement in signal strength.
A planar metal surface may act as a mirror, in which case the molecules in front of the focal point will be in an enhanced EM field (from both the incident beam and its reflection). Where the beams interfere constructively, the molecules will be in a double-strength field. Since Raman intensity is proportional to the square of the field strength, molecules in a doubled field will emit four times the Raman signal. However, half of the molecules will be in regions where the fields interfere destructively, so will contribute nothing to the Raman signal. Overall, the Raman scattering intensity will therefore be twice what it would be without a reflective surface. However, this signal is coming from molecules in a doubled field, so they will consequently photodegrade at a higher rate. Photodegradation occurs when a chromophore is permanently damaged due to photon-induced excitation and subsequent covalent modification. Upon transition from an excited singlet state to the excited triplet state, chromophores are more likely to interact with another molecule to produce irreversible covalent modifications. The triplet state is relatively long-lived with respect to the singlet state, thereby allowing excited molecules a much longer timeframe to undergo chemical reactions with components in the environment. For a given surface area, the within-matrix focus arrangement can therefore give the same intensity of Raman signal as a reflective surface but confers the benefit of a reduced photodegradation rate of the chromophores. If the surface is non-reflective, the matrix arrangement would provide an enhanced signal.
The fine-grained three-dimensional support matrix can be in the form of a silica filter frit (shown, in cross-section in
The matrix voids 111/121 may be, typically, approximately 50-80 μm across, resulting in diffusion paths of 25-40 μm. For a typical 100 kDa protein analyte, this would result in 99% binding within approximately 30 seconds. The 3D matrix confers the reaction speed advantage of a microfluidic system whilst simultaneously enabling the detection volume to be on the millimetre scale or larger due to the relaxed requirements on the laser focusing.
The deposited metal portions have two morphologies. The first form comprises filamentous strands, shown in
If the frit is allowed to float on the surface of the reaction mixture, silver particles are deposited with a much higher density per unit area as illustrated in
Example SERRS spectra from particles prepared on silica filters using the two methods, and on a flat surface, are shown in
Although there are about twice the number of silver particles on the surface prepared by using a floating frit, the SERRS signal is some 3× greater than that from method 1. This is because the signal intensity is not linearly dependent on the number of particles at the surface. Since the particles follow the same size distribution, the disproportionately increased SERRS signal cannot simply be due to the increase in available silver surface, but must have an extra contribution due to an interaction between particles, with the higher packing density leading to an additional SERRS enhancement. It is generally accepted that the particles interact via electromagnetic fields generated by a synchronised motion of conduction electrons within them, and that this interaction is dependent on the distance between particles.
In a further embodiment of the invention it is possible to reduce the average diffusion path length of analyte molecules even further by depositing silver particles within the structure of the substrate particles comprising the support material itself. This can be achieved if the support material is porous. The term porous, in this instance, refers to materials containing pores of a size such that the particles making up the material are porous to the dye being used to detect the analyte. In this embodiment the substrate particles of the support material themselves have voids, or pores, resulting in a completely accessible internal structure.
A good example of a support material made from micro-porous particles is controlled pore glass (CPG) and can be formed from silica. Micro-porous refers to the fact that the pores have a size of the order of several microns, or tens of microns. One method of producing CPG is by acid etching a mixture of glasses wherein one of the glasses is susceptible to corrosion by acid whilst the other is not. The result is a glass/silica material featuring a completely accessible internal structure, the individual silica particles having voids on the nanometre scale that serve to increase the internal surface area available for silver particles to adhere to. An example of such a material is shown in
CPG is widely used as a support matrix for chemical synthesis. Several grades are available, differing in particle size (CPG is usually handled as a particulate powder), void size (typically ranging from ˜100 nm to ˜1 μm) and surface derivatisation (a wide variety of functional groups, to facilitate chemical attachment to the surface). CPG is particularly suitable as a biosensor support matrix since it has a large internal surface area (up to 100 m2/g or more), is chemically inert (unless derivatised to improve its metal binding or particle seeding properties), and does not give rise to substantial Raman peaks, which can cause spectral interference.
The voids should be large enough for the dye to enter and also to accommodate the metal portions/particles. Typical dyes have a size of approximately 1-5 nm, and analytes 5-100 nm. When using metal particles of around 50 nm in size, this means that the void size should be around 150 nm or more.
As an example, one method to make a silver based substrate is to perform the Tollens reaction in the presence of CPG. Surface derivatisation of the CPG with aldehyde, alcohol, or carboxylate groups are particularly suitable for this method
In all embodiments of the invention, the support material may be porous to the analyte to be detected, with the detection chemistry (such as displacement of a reporter molecule or dye by the analyte) occurring within the support structure itself. However, this is not a requirement of the invention. The support material may only be porous to the dye, depending upon the analyte to be detected, and not porous to the analyte or other materials in a sample. Other materials may include anything within the sample that it is not desired to detect, or that it is desired to keep away from the illuminated portion. Examples may include blood cells, or chemicals that may distort the Raman signal. The analyte could displace the dye at the external surface of the support material and the dye may then diffuse into the support material to interact with the Raman enhancing metal particles. The minimum requirement is for the support material to be porous to the dye. Furthermore, the substrate particles may be porous to the dye but not the other materials in the analyte sample. The analyte could displace the dye at the external surface of the support material, or within the support material but outside the substrate particles, and the dye may then diffuse into the substrate particles to interact with the Raman enhancing metal particles.
Where the support structure or substrate particles are only porous to the dye, the analyte may displace the dye from a selective agent at the external surface of the support material or substrate particles. The dye will then diffuse into the support material or substrate particles to interact with the silver particles distributed therein. Of course, in cases where the analyte is also a dye itself there is no need for a separate dye and the support material or substrate particles will be porous to the analyte itself. The analyte, when introduced into the reaction carrier, will diffuse into the support material or substrate particles and interact with the silver particles.
The size of the pores/voids of the support material or substrate particles controls the distribution of Raman enhancing particles throughout the material and the distance a dye must travel to interact with a Raman enhancing surface. Consequently, the void/pore size throughout the support structure should be of the same order of magnitude as the mean free path of the dye being used. The required sizes may be determined from the diffusion coefficients shown in
The distribution of Raman enhancing particles within the voids should, as a preferred feature, be such that the distances between neighbouring metal particles are of the same order as the mean free path of the dye whose Raman response is to be detected.
When a material such as CPG is used, having a large internal surface area, the distance a molecule must diffuse to interact with a metal particle can be large since the pores within the particles can be from 100 nm up to 10,000 nm. When depositing metal within such a structure using methods such as crystallisation or deposition, the distribution of metal particles follows a radial distribution function. Further into the structure, fewer metal particles are present to interact with the dye. However, the dye also diffuses in a similar manner and therefore the majority of dye molecules will be found in regions having high concentrations of metal particles.
A 3D porous support in accordance with the invention experiences two levels of resonance when illuminated by a laser. Firstly there is the surface plasmon resonance experienced by the individual metal particles. In addition, there is also a larger scale resonance resulting from what is essentially a metal placed in a dielectric medium (the sample and the support material). This second resonance level shares similarities with resonance within photonic crystal structures, however the overall dispersion of metal particles within the support structure is not uniform so a direct comparison is difficult.
A support structure having metal distributed and immobilised within it, such as CPG loaded with silver, may to a reasonable approximation (for calculation purposes only) be regarded as being equivalent to a physically immobilised colloidal dispersion. The CPG and sample solution within the voids approximate a dielectric medium, with the metal nanoparticles lining the walls of the CPG internal voids being equivalent to colloidal particles in suspension. The dimensions of the voids and spatial dispersion of nanoparticles on the void walls determine the ‘concentration’ of the colloid analogue.
Optical properties of colloidal particles have been extensively studied. The absorption spectra of colloids can be calculated from Mie theory. For small spherical particles, the absorbance A for a dispersion of N particles per unit volume depends only on the dipole term in the Mie summation, and can be calculated as
where C and I are the absorption cross-section and optical path length respectively. If the particle dimensions are smaller than the mean free path of the conduction electrons, then these electrons will ‘collide’ with the particle walls, giving a lower effective mean free path than that in the bulk material.
In the limit 2πR<λ (where R is the particle radius and λ is the wavelength of light in the surrounding medium), the cross section can be expressed as
where V is the volume of a spherical particle, λ is the incident wavelength (corresponding to a frequency ω) and εm is the permittivity of the medium. The complex relative permittivity of a bulk metal is given by
ε(ω)=ε1(ω)+iε2(ω)
For free-electron metals such as silver, ε1(ω) and ε2(ω) are often well known, having been determined experimentally over a range of wavelengths. From the above equations, it can be seen that a maximum occurs in the absorbance when ε1(ω)=−2εm. The value of ε2(ω) when ε1(ω)=−2εm, and the rate of change of ε1(ω) with wavelength is a factor determining the height and width of the resulting absorption band.
For metal particles with sizes comparable to the mean free path of the conduction electrons (L) the collision rate between the free electrons and the particle walls becomes appreciable. The electron motions are effectively damped, leading to a change in the dielectric properties of the metal. To account for this surface effect, a second term needs to be added to the calculation of the imaginary part of the dielectric function:
where ε2′(ω) is the dielectric parameter corrected for small particles.
As described previously, typical silver particles, as may be distributed on and within a support material provided by the invention, are several tens of nanometres in diameter. A commonly accepted value for L, the mean free path of electrons, in silver is approximately 57 nm. Wavelength-dependent values for the complex dielectric functions for silver, glass and water (a good approximation to a sample) are well known in the field. Using these data, the UV/visible absorption spectrum for silver-loaded CPG can be predicted.
A comparison between the theoretical and experimental results can be seen in
The optimal fit to the experimental data, shown below, is found with a=7×10−6, b=3.34×10−7 and c=3.5×10−8.
The parameter a is simply a scaling factor. The b and c parameters respectively determine the position and width of the Gaussian peak. Subtracting this Gaussian has the effect of applying a ‘notch’ filter to the optical spectrum. This effect can be rationalised if the silver-loaded CPG behaves similarly to a photonic crystal with an excluded band-gap at around 334 nm. The experimental data was collected using a laser of nominal wavelength 532 nm (in a vacuum). The ratio of the nominal to apparent wavelengths (532/334) gives an effective refractive index for the silver-loaded CPG ‘photonic crystal’ of 1.593. The refractive indices of glass, water and silver at this nominal wavelength are approximately 1.520, 1.336, and 0.002 respectively. The silver-loaded CPG is therefore acting as a metamaterial with properties differing from those of its constituent materials.
The geometric dispersion of silver particles within CPG is not a regular crystalline lattice, so conventional theory describing photonic crystals does not necessarily apply. However, there is a degree of local regularity in the particle dispersion, primarily determined by the void size and inter-void spacing within the CPG structure. The situation is further complicated by the fact that the particles are separated not by a uniform dielectric medium, but by a combination of voids filled with the sample (a dilute aqueous solution with undetermined dielectric properties containing at least the dye to be detected and possibly analyte, and other chemicals that are not to be detected), and the inter-void material comprising, in this instance, glass. The exact dielectric properties of a material such as this will to a large degree depend on the precise geometry and spatial configuration of the CPG voids, and a general analytical description is difficult to derive. However, the behaviour of a silver-loaded CPG matrix is predictable using numerical techniques such as finite element analysis or mesh-free methods.
The optical behaviour of the sensing material is therefore determined by two fundamental mechanisms. The first, surface plasmon resonance, is primarily influenced by the size, composition and geometries of the metal particles themselves. The second larger scale resonance is influenced by the composition and spatial distribution of the support matrix, which in turn determines the spatial distribution and dielectric environment in which the metal particles are dispersed. The optical properties of the metal particles themselves can be predicted (and thereby rationally engineered) by using the mathematical techniques described above. The optical properties of the metal-loaded matrix material can be determined by analytical or numerical approaches as appropriate to the complexity of the structure. The differing refractive indices and dielectric properties of the support material and the sample determine the optimal spacing between metal particles required to ensure maximum absorbance of the incident radiation. The average spacing of the metal particles should ideally be half the wavelength of the incident radiation, however the wavelength is dependent upon the material through which the radiation is passing. The ratio of the void diameter to the wall thickness of the support material should preferably equal the ratio of the refractive index of the solution filling the voids and the refractive index of the support material, in which case the actual wavelengths of the excitation photons in both materials would be the same. Consequently, the dimensions of the void/wall structure in the CPG metamaterial should preferably be selected as a weighted average to account for the difference in the volume of the support material comprising voids and the volume comprising solid support material. A spacing of metal particles that is a multiple of half the wavelength of the incident radiation will also give additional resonance harmonics.
Lasers used in Raman spectroscopy typically have a focal area of around 100 μm, although this may extend to as large as 500 μm.
Whilst lasers are typically used in Raman spectroscopy the only requirement is that the source of illumination is monochromatic, having a specified wavelength. There is no requirement for the illumination source to be coherent.
The sizes of the voids can affect the illuminating light if the void size is approximately the same as the wavelength of light used. By using void sizes that are sufficiently less than the wavelength of the light these problems are reduced.
Particle size and shape has a dramatic influence on the ability of the metal particles to couple with the incident laser via resonance with the plasma of conduction electrons at their surfaces (the plasmons). Experimental evidence of this is shown in
By applying non-linear regression modelling to the triangular particle data, an empirical equation relating λmax to the particle width and height can be derived:
λmax=(3.703319918×Width)+(0.000026746×Width3)−(0.00218472×Height3)−(0.000464139×Width2*Height)+(0.001779672×Height2*Width)+242.638583311
This gives a reasonably good fit to the experimental data as shown in
There is a particle width (˜100 nm) above which λmax becomes unacceptably greater than 532 nm. Particles with relatively small widths (<˜50 nm) have unacceptably low predicted values for λmax. For particle widths greater than about 100 nm the optimum height for resonance with a 532 nm laser (Height≈25+0.42×Width). Particles with a width of around 75 nm have optimal heights between below 50 nm, and particles with widths below 75 nm have sub-optimal λmax values less than 532 nm. There is therefore a narrow range of dimensions within which particles of a particular size attached to a surface will exhibit good optical extinction for a specified laser wavelength.
Particles formed by deposition using Tollens reactions will have a range of different sizes, these sizes being distributed by fractal dispersion. One benefit of such a range of sizes is that it ensures there will be a proportion of particles having the appropriate size to provide an enhancement to the response of the dye to illumination from radiation. With Raman spectroscopy this works by the plasmon wavelength being matched to the wavelength of the incoming radiation. It would, however, further increase the surface enhanced Raman effect if only particles of the required size were uniformly distributed on the surface of the substrate. This can be achieved by immobilising silver colloids within the support material since the size of such colloids can be controlled to a greater extent than silver particles produced through deposition techniques.
Assuming that the particles deposited by the Tollens' reaction approximate to particles where a=b=observed diameter, we can estimate that the surface-enhanced Raman signal from a population with the size distribution shown in
One of the key benefits conferred by a microfluidic system is a dramatic reduction in reaction times due to physically limiting the reaction within a volume whose dimensions are comparable to the diffusion path lengths of the molecules involved.
The ability of a molecule to diffuse through a liquid medium is described by its diffusion coefficient, D, which can be estimated using the Stokes-Einstein equation
where k is Boltzmann's constant, and T is the absolute temperature. This model assumes that the molecule is a sphere of radius R freely diffusing in a continuum solvent, the molecular size is at least 5× the solvent size, and that the liquid has a low viscosity (η).
Although proteins are not perfect spheres, their apparent Stokes' radii can be determined experimentally. Typical examples are shown in the table below.
These data can be used to derive an empirical method for predicting the Stokes' radius of a protein from its molecular weight.
A common method for estimating the typical diffusion-limited timescale (tD) in microfluidic systems is to use the equation:
where I is the characteristic length of the system. For a typical protein of mass 100 kDa in a macro-scale system with I=1 cm, tD is about 230 hours. For the same protein in a microfluidic system with I=100 μm, tD is about 84 seconds.
The ‘typical timescale’ calculation shows that a microfluidic biosensor can confer an enormous benefit in assay time, provided the sensing reactions are carried out in a reaction chamber with dimensions comparable to the diffusion paths of the molecular components. However, this calculation does not take into account the depletion of the molecular components which accompanies the binding events at the surface of a molecular sensor. A more realistic model for a biosensor can be obtained using Fick's 1st law of diffusion for the particle flux j due to a concentration gradient:
The concentration of the analyte at height x and time t is defined as c(x,t). The initial state (t=0) has c(x,t)=c0 (the initial concentration), and the depletion at the binding wall, where x=h, is c(h,t)=0. As it proceeds, the binding reaction reduces the concentration of the analyte close to the binding wall. This induces a diffusional flux of the analyte molecules towards this wall, since a concentration gradient has been formed, and over time the chamber becomes depleted of analyte molecules.
The calculation is performed in two phases shown graphically in
The first step is to calculate the time taken for phase 1. From Fick's law, diffusion to the binding wall is driven by the diffusion gradient over the depletion zone, which we've assumed has a linear profile:
The number of free analyte molecules, n, at time t in the chamber is given by:
The rate of change (i.e. the flux) is then
Using the boundary condition that x(0)=0, this leads to
x(t)=√{square root over (4Dt)}
At the end of phase 1, occurring at time t1, x(t1)=h, so
The calculation for phase 2 is similar. Again, we consider the diffusion to the binding wall, but this time we need only consider the depletion zone:
The number of free analyte molecules is then given by
and so the flux is
Using the boundary condition that c(0,0)=c0, we get
Since this is an exponential decay, it would take an infinite time for the concentration of analyte to reach zero. However, we can calculate the time taken for a proportion p of the analyte to bind (0<p<1). We'll call this t2.
so
c(0,t2)=2(1−p)c0
using the exponential decay equation for phase 2, it can be seen that
The time taken for the proportion p of the analyte molecules to bind, tp, is then given by
Comparing this equation with the accepted ‘typical timescale’ equation for microfluidic systems:
It is clear that chamber height h takes the place of the characteristic length l, and there is an additional term describing an exponential decay introduced into the system due to the analyte depletion.
For a typical 100 kDa protein, the time taken to achieve 99% maximal binding for microfluidic reaction chambers of different heights can be calculated and a plot of chamber height against time for 99% binding to occur is shown in
The plot of
A calculated binding time course over 1 hour for the typical 100 kDa protein example is shown in
Number | Date | Country | Kind |
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0606088.3 | Mar 2006 | GB | national |
Filing Document | Filing Date | Country | Kind | 371c Date |
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PCT/GB07/01071 | 3/27/2007 | WO | 00 | 11/4/2009 |