Optical Sensors for Biological and Chemical Measurement

This Literature review is divided into three main parts. They are, Surface Plasmon Resonance, BIACORE 3000 and Winspall. In these three mechanism, Surface Plasmon Resonance stood a basic platform for optical bio- sensing whereas BIACORE 3000 is an extended version. On the other hand, Winspall is a special software used to simulate the reflectivity curves. The first part of the literature review is Surface Plasmon Resonance which explains the basic concept, sensors used in SPR and application in major areas. And also the future trend of Surface Plasmon Resonance sensors has been explained. Similarly the next section has a detailed structure of BIACORE 3000 describing its sensitivity and throughput along with new instrument software. As mention above that Winspall is a special software, it has been clearly discussed in third part. In this discussion, how the reflectivity curve is simulated with the help of Winspall software is explained with taking as an example of Reflection at air- glass interface.

Surface Plasmon Resonance (SPR)

Introduction:

For the past two decades there is a massive increase in the field of research and development of optical sensors for the measurement of chemical and biological quantities. Measuring CO2 and O2 Concentration were developed by optical chemical sensors which is the first optical device based on the measurement changes in absorption spectrum (Lubbers, et al. 1975). The chemical sensors and biosensors use various optical methods such as Ellipsometry, Interferometry, Spectroscopy and Surface Plasmon Resonance (SPR). In these sensors a required amount is determined by measuring the refractive index, absorbance and fluorescence properties of analyte molecules (Wolfbeis et al., 1991). In late seventies, the potential of Surface Plasmon Resonance (SPR) for characterization of thin films (Pockrand et al., 1978) and monitoring processes at metal interfaces (Gordon II et al., 1980) had been recognized. In 1982, Nylander and Liedberg demonstrated the typical use of SPR for gas detection and bio-sensing (Nylander et al., 1982). For the measurement of physical, chemical and biological quantities new SPR sensing configuration as well as application of SPR- sensing devices were developed since from the scientific community SPR had received continuously growing attention. In optical bio- sensing more than 75% of the research are based on the SPR, and SPR sensors are used commercially by several leading organizations in the field of direct real- time observation of the bio- molecular interactions.

What is meant by SPR:

SPR has many practical applications in sensitive detectors and it is having the ability to detect sub-monomolecular coverage. This phenomenon was first observed by Wood in 1902 (Wood, 1902), according to him, SPR is a pattern of “anomalous” dark and light bands in the reflected light when the light is polarised on a mirror with a diffraction grating on its surface. And the phenomenon of physical interpretation was initiated by Lord Rayleigh (Rayleigh, 1907) and additionally it was enhanced (Fano et al., 1941) but since 1968 there is no detail and complete explanation of the phenomenon.

In the same year Otto (Otto, et al. 1969) and Kretschmann and Raether (Kretschmann, et al., 1968) reported in detail about the excitation of surface Plasmon’s.

Optical chemical sensors and biosensors in SPR:

Usually, an Optical sensor is a transducing medium which correlates the optical and bio- chemical domains and the system which supports the optoelectronic components of an electronic system and allowing data processing. The transducing medium converts the quantity of interest change into refractive index change which may be estimated by optically interrogating the SPR. The SPR sensor of an optical system contain two parts, one is the source of optical radiation and another one is the optical structure in which surface Plasma Waves (SPW) is excited and interrogated. In this SPR interrogation process, the electronic system process and generates the electronic signal and the properties of sensors subsystem only determines the major properties of an SPR sensor. The properties of an optical system and the transducing medium is dependent to the sensor sensitivity, stability and resolution whereas the selectivity and response time of the sensor are mostly estimates by the properties of transducing medium.

Technologies and materials used in SPR-sensing devices:

There are various technologies employed in the fabrication of SPR sensors since SPR chemical sensing and bio- sensing has multidisciplinary nature. But in particular there are two technologies which are considered as most important on the fabrication of SPR sensors. They are the fabrication of the optical part of the sensing element and preparation of Opto- chemical transducing medium.

Application of SPR sensors in major areas:

Measurement of physical quantities in SPR

Based upon the sensitivity of SPR to the momentum of the incident light wave the displacement (Margheri et al., 1996) and angular position of SPR sensors is measured. For the development of SPR -sensing devices various optical transducing materials have been exploited including the refractive index changes of porous thin layers and polymers (Weiss et al., 1996) by humidity sensor and a temperature sensor based on the thermo- optic effect (Chadwick, 1993).

SPR chemical sensing:

Direct measurement of refractive index using an SPR sensor can be achieved by complexity variation in the concentration of analyte and due to the adsorption or chemical reaction of an analyte with a transducing medium the measurement of SPR variation are dependent to chemical SPR sensors which results in changes in its optical properties.

Surface Plasmon Resonance Bio- sensing

In 1983, the first application of SPR to bio- sensing was demonstrated (Liedberg, 1983), previously the demonstration was carried out and developed by some other groups (Flanagan et al., 1984). The real time bio- specific interaction analysis method was the first survey on Surface Plasmon Resonance which is appeared on 1994 (Lundström, 1994) frequently used and continuously improved for examination of kinetic and thermodynamics constants of bio- molecular interactions. The direct detection of binding reaction is used for the purpose of analyte quantification, however, the adsorption of small molecules produces the increase in refractive index which is not sufficient to detect directly.

Commercialization of Surface Plasmon Resonance sensor technology:

The first commercial SPR bio- sensor was launched on 1990 by Swedish BIAcore AB which leads to systematic development of SPR bio- sensor technology. Then the BIAcore sensor technology has been further developed in terms of speed, throughput and accuracy. At present BIAcore offers a number of models of SPR bio- sensors (BIACORE 3000, BIACORE 2000, BIACORE X, BIACORE 1000, BiacoreQuant) (Sinclair et al., 1990). By further growth of commercialisation of optical bio- sensor system results in the development of another SPR bio- sensor system (TI- SPR- 1Experimenters Kit, Spreeta Evaluation Kit) by Texas Instrument in USA [127]. There is another SPR bio- sensor system called Kinetic instrument 1 which has been developed by Bio TuL Bio Instruments GmbH (Germany). The recent SPR sensor which is commercially available is waveguide- based device using wavelength interrogation in a multimode optical fibre developed by EBI sensors (Washington, USA).

Future trends in development of Surface Plasmon Resonance sensors

Even though SPR is used in many fields, there is a necessity for detection and analysis of chemical and bio- chemical substances in many significant areas such as medical, environmental monitoring, bio- technology, drug and food monitoring. SPR sensor technology holds potential for applications in the mentioned areas. At present SPR bio- sensors devices compete with other types of bio- sensors (Owen, 1997) and the currently available bio- sensors covers only some degree of area of (bio) chemical monitoring market aiming primarily at research and analytical laboratories. So, a new SPR bio- sensor is need to compete the existing system to cover the specialised laboratories and testing sites on the basis of factor such as cheap, ease of use, robustness, sensitivity and stability.

Conclusion

For the past 10 years there is a great improvement in Surface Plasmon Resonance sensors technology with many numbers of applications. Even more the SPR sensors technology will get growth and extend in the usage by developing new type of bio- sensors which competes the existing system and also designing low- cost, allow sensitive and fast in speed.

BIAcore 3000

Introduction

For label free studies of bio- molecular binding, BIAcore 3000 is considered as highest performance research system which is existing currently. The substances such as lipid vesicles, viruses, bacteria and eukaryotic cells which are ranging from small molecules to crude extracts can be studied. Speed, strength and specificity of binding and determination of active concentration of components questions have been answered by BIAcore 3000 and it is an ideal tool for functional proteomics. For the future trends, there are lot to invent technically which has to meet the highest demands for efficiency, sensitivity and flexibility. The awareness and experience of BIAcore 3000 is an effective guide for the users without effort through preparation, evaluation and experimentation has been incorporated into Wizards. This BIAcore 3000 follows the C- language Conditional IF/THEN statements to response perfectly to changes in run conditions, since it provide a trend analysis and preliminary results at the end of runs. For an individual sample characterisation BIAcore 3000 is used to design, where the highest resolution in kinetic analysis and automation of multi- sample analyses is crucial and it provides a superior performance for kinetic analysis. Highest signal to noise ratio and a high data acquisition achieves increased resolution.

“BIACORE 3000 represents the logical next step in the development of BIACORE systems for sophisticated binding studies, with better sensitivity, higher throughput, improved liquid flow properties and an easier software interface than previous system in the series” (Francis, 1998).

High sensitivity

BIAcore has an working range as little as 10 RU, but it can be able to detect up to 70000 RU (one RU is equivalent to one picogram protein per square millimetre on the sensor surface) and also it has highest sensitivity to monitor the bio- molecular binding which ensures in the interpretation of related kinetic data and in the detection of binding events. The molecular weights of the binding partners and experimental conditions are dependent to the measurement of kinetic and affinity parameters. The controlled experimental conditions ensure precisely in the design of micro- fluidic pathway and in the detection system of BIAcore 3000. By comparing to other BIAcore systems, BIAcore 3000 has the ability to generate twice the signal from the same sample injection time. The micro- fluidic pathway of BIAcore 3000 has four flow cells overlaid in single sensor surface in which the each cell consists with a volume of 0.02 µl. During a single sample injection one cell has used to be as a true reference. The resolution and information from a single run will be maximised by automatic in- line reference subtraction and the signals will be resolved by reducing the background noise.

Improved Throughput

There is a significant difference in the design of IFC, between BIAcore 3000 and to its predecessors, where the height of the flow cells has been reduced to less than half. This may create some trivial sound, but the binding measurement in the screening application and kinetic analysis has important consequences. The mass transfer of analyte to the surface height is improved by the consequence of the lower flow cell, where as the height is inversely proportional to the mass transfer co- efficient for diffusion controlled transfer. If the height is increased by the factor 2, then the mass transfer co- efficient for diffusion will decreases by factor 1.6. Similarly, we can link this to the practical terms, that is, the faster kinetics can be measured without interference from mass transfer process. It also means that same response is achieved in the shorter time in a mass transfer limited situation in which the sample throughput is increased in screening situations. The improved sensitivity enhances the gain which allows the system to work at lower relative response levels confidently. Streamlined wash routines between the introduction of new reagent rack and analysis cycles improves the automated analysis situation by throughput which allows 192 wells in two micro- plates to be used for samples. But some users of BIAcore 3000 says that clogging problems in the flow system is due to the reduced flow cell height when particular samples such as crude extracts or whole cell suspension are used. At the same time the users do not report problems when the clogging in micro- flow systems is quoted as an argument in favour of open curvette systems even when the analyses involving whole cells and there is no cause to think that the lower flow cell height in the BIAcore will built important clogging problems (Francis M, 1998).

Software

The BIAcore 3000 instruments have large improvements technically by introduction of new software’s which is designed to improve the analysis quality and to simplify the operation. Latest versions of the control software BIAcore 2000 have all these features. The BIAcore 2000 and BIAcore 3000 consists two- channel system BIAcore X with line reference subtraction method. Due to this, the users can progress and evaluate their data with confidently and also the data quality improves to large extent. The new IFC (Integrated fluidic cartridge) in the BIAcore 3000 is used to bypass the flow cells and to improve the cost- efficiency of chip operation. The features of BIAcore control software is due to the introduction of application wizards since the application wizard provides step by step information in a clear way to a particular kind of experiment for designing and interpreting the results with on-line help and feedback give the correct chance of achievement. The information’s through on-line functions and the wizards were created based on the experience of binding studies over the years and it provides a new experience to the users and benefits to the company’s expertise.

Conclusion

In summary, BIAcore 3000 is considered as most advanced system in the series of BIAcore and also it represents the present state of the art in technology for affinity- based bio- sensors. The system will extend the range of applications by the technology with higher sensitivity, improve in sampling handling and enhanced kinetic analysis facilities to cover many of the small molecules like cofactors, signalling substances present in the basic science research and drug candidates in the pharmaceutical industry. For dealing the large amount of high quality data, the refinement of hardware and computer software involved in the BIAcore system can provide and this is considered as a developed approach. Processing the data in the system becomes more and more of a bottle neck since the automated analysis becomes faster and more complicated.

Winspall

Introduction:

To simulate the surface Plasmon resonance curves special software is designed based on the Fresnel formalism which is called as Winspall, developed by A. Scheller at the Max Planck Institute for polymer Research (Chifen, 2007). This software is very easy to use and gives accurate results when simulating the reflection curves (RES- TEC, 2010). Similarly, Winspall software is also used to determine the layer thickness in deposited LB (Langmuir- Blodgett) layers (KSV Inst, 2010). In many practical and commercial application electronic components such as sensors, detectors, displays and circuit boards provides the ability to assemble ordered molecular films with tailored functionality over macroscopic lateral dimensions. This technique is called as Langmuir- Blodgett (LB) deposition. In this deposition, technique the air- water interface contains micro particles and nano particles which are to be compressed and transferred to solid substrate. Here, the Winspall software is used to find the deposition thickness between the particle layers and also the Fresnel coefficients of each film/ layer with recursion formalism will be calculated (Chifen, 2007).

Simulation of Reflectivity curve using Winspall:

As mentioned above, Winspall is used to simulate the reflection curves; this section gives a detail view how the reflected curve is simulated using Winspall software with an example. Let us consider an easy prism experiment, base of the prism reflects the laser beam and reflected light is the function of the angle of incidence. Now this reflected curve from the prism is going to be simulating using Winspall. So for this, we need the optical prism constant and air constant.

The Winspall software consists of a special simulation parameter table (Fig 2) where the optical comments are to be filled; depending upon the optical parameters the simulation results will be made. For the above example we have to fill the optical components parameter such as prism and air. The first optical parameter is prism; we have to enter the thickness (no 1) ‘0’ for in the table. And then the real and imaginary part of dielectric constant should be filled. The real part of dielectric constant is 2.29 in our example and the imaginary part is zero due to the absence of adsorption in the glass. The second optical component is air (no 2), no thickness and real part of dielectric constant is 1 and imaginary part is zero. Now the simulation parameters are filled in the table. The next step is to click the ‘OK’ button to get simulation output.

Once the OK button is clicked on the simulation parameter window, we will get a simulation curve as an output (Fig 3) for the filled values in the table in separate window. This is the typical curve describes the total internal reflection occurred in the prism and the reflected light separates high index from low index material. In general whenever a light passes through the interface, there will be no reflection at low angles, when the angle gets large the total internal reflection will occur. Below the window shows the simulation output for the values which were filled in the table. This graph explains that below 39 degree there is no reflection, when the angle increases the light get reflects until the total internal reflection is reached.

Now to modify or to adjust the reflectivity curve, extra optical components value should be added in the table. In the above case, we are going to add another component between the glass and the air. It is 50 nm thick gold layer with the optical constants “Eps-X real”=-12.45 and “Eps-X imag”=1.3. Due to the minor differences in the evaporation process the above mentioned optical constant values for gold varies to some extent. Once these values are entered and we clicked OK button in the simulation parameter window, we will get a curve which is entirely different when compared to previous output (Fig 3). Because of reflective property of gold, first the total internal reflection becomes very thin from 0 to almost 1 and then around 43 degrees a surface Plasmon shows up a strong dip in reflectivity. Due to this strong dip, now the total intensity will jump in this Plasmon and there won’t be any part of light reflection occurs. This simulation output curve describes the optical properties of a typical “blank substrate” used for surface Plasmon measurements.

The below shown window consists of simulation output for newer optical component values

Now to get real Plasmon and thin layers, a 3nm thick gold layer is added on the top with the dielectric constant of 2.11 (n=1.45) – maybe some polymer or a protein. Once the new dielectric constant value in added, there will be a change in the simulation output curve (Fig 4) i.e. the Plasmon resonance shifted a little. We are now about half a degree higher. This shift can be easily measured and for the investigation of such thin layers Surface Plasmon Spectroscopy is well apt. Similarly to get thicker layer 30 nm thick gold layer used on the top which gives result as stronger shift of the Plasmon resonance. But when try to increase the strong shift of Plasmon resonance curve by using 300 nm thick layers a very sharp dip is found in the reflectivity curve at smaller angle. At this smaller a new waveguide mode occurred instead of Plasmon. By increasing the thickness i.e. by adding the thick gold layer with different nm thick on the top we will get more and more waveguides on the reflectivity spectrum. The below window diagram shows the five waveguide modes in the range for 70 degree for 3 micro meter thick layer. At the same time waveguides can also be found in s-polarised light. This s-polarised light waveguides are also can be simulate by Winspall software.

On the other hand, using the Winspall software the Surface Plasmon Resonance curve can be evaluated very easily. This is carried out by the same process, just filling the simulation parameter table.

Conclusion:

Winspall is special user- friendly software to represent the Surface Plasmon Resonance curves and also it very easy to carry the simulation and evaluation of reflectivity curves.