Rapid-Kinetics and Spectroscopy: Stopped-Flow; Fluorescence, Absorbance, Circular Dichroism, Anisotropy Spectrometry

Rapid-Kinetics and Spectroscopy software

Bio-Kine32 - Our powerful, friendly software platform

Acquisition and analysis of signals produced by our optical systems is carried out using the Bio-Kine32 software. Bio-Kine32 has been designed to complement our SFM instruments and drive the Bio-Logic spectrometers in the addition to our mixing devices.

Bio-Kine32 operates under the latest version of Windows environment (Win95, Win98, WinME, WinNT, Win2000, WinXP, Vista). It uses an A/D board from National Instruments, probably the best industrial standard in data acquisition systems.

The Bio-Kine32 software is designed to control the following optical systems:

• MOS-200
• MOS-200/M
• MOS-450/AF & /AF-CD
• MOS-DA diode array
• Jasco J-810 CD spectrometer
• Accessories such as:
  • Thermostated bath
  • Peltier cells
  • Acquisition of any other analog signal (-10/+10V)

  It also provides a direct bridge to the Stopped-Flow driver software.

The Bio-Kine32 software can control these instruments and acquire data for transient kinetics, spectral scans, act as a virtual chart recorder and control external devices.
The use of similar controls for all modes makes Bio-Kine32 easy to use and eliminates the hassles of learning multiple programs for different types of experiments.

Transient Recorder
The Transient Recorder is similar to a digital oscilloscope.

Up four data channels of 8000 points each can be acquired and displayed simultaneously. Sampling rates from 50 µs/point (20kHz) to 100 s/point (0.1 Hz) can be used. Both linear and logarithmic sampling is available through the use of up to three times bases. Data can be acquired in two different spectroscopic modes simultaneously (Volt, Transmittance, Absorbance, CD or Anisotropy).

Scanning Spectrophotometer
The Scanning Spectrometer is used to control one or two monochromators to perform spectral scans.

Bio-Kine32 is capable of making spectral acquisitions in the same spectroscopic modes that are available for transient kinetics. In conjunction with the appropriate spectrometer system, Bio-Kine32 can act as a full feature absorbance, fluorescence or CD spectrometer.

Chart Recorder
The Chart Recorder is similar to the Transient Recorder, but specialized for slower acquisitions over long periods of time.

Up to four data channels and two spectroscopic modes can be recorded simultaneously. Data is displayed in real time, and scrolls along acquisition window. Files of several million points can be recorded with event markers being added at anytime.

SFit - Single Value Decomposition analysis software

SFit is complete and easy to use data analysis software to study complex 3D rapid kinetics data. Typically these data consist of an optical measurement, e.g. absorbance, as a function of both reaction time and wavelength. They may be obtained from transient recordings of this optical signal with fast diode array spectrometers or alternatively are reconstructed from a collection of single wavelength transient kinetic traces.
Raw data form large 3D arrays whose analysis requires sophisticated methods such as included in SFit.

SFit includes the following procedures:

• Data handling and initial treatment
• Singular Value Decomposition (SVD)
• Global multiexponential fitting of the SVD treated data
• Introduction and evaluation of kinetic models

Figure 1: Raw data form large 3D arrays

Sfit: data handling

SFit uses Bio-Logic file formats but includes a procedure to import data from most other spectrometers and data acquisition systems. It also features a sophisticated graphic interface for an easy visualisation of the files.

Once acquired, the data can be prepared before treatment.

Figure 2: Data inspection and treatment

SFit: fast SVD analysis

Direct analysis of the original 3D rapid kinetics array of data would require simultaneous (global) fitting of all the kinetics traces recorded at all wavelengths (hundreds of values) . However, because of the high redundancy of the data a drastic size reduction can be obtained by using Singular Value Decomposition (SVD).
In this procedure the original array of data A is transformed into a matrix product:
A = U x S x V  where  U and V are orthogonal matrixes containing kinetics and spectral information respectively, S being a scale factor vector that allows evaluation of the number of significant spectral species involved in the reaction.
For more information on SVD :  http://en.wikipedia.org/wiki/Singular_value_decomposition

Figure 3-1:  UxS vectors

Figure 3-2: V vectors

SFit: global multiexponential fitting

Once reduced by SVD, rapid kinetics analysis becomes highly simplified. Instead of hundreds of kinetics traces, what remain to be fitted are transitions between a few spectral species as in figure 3.1 (typically 2 to 5 species only). Sfit is unique as it proposes two fitting procedures based on Levenberg-Marquardt or Simplex algorithms. This allows very precise determination of the set of rapid kinetics constants involved in the reaction.

Figure 4: Global fit window

Figure 5: Results of Global fit applied to the UxS vectors

SFit: kinetic models

The spectral vectors V obtained after SVD analysis (figure 3.2) do not correspond to real spectral species but are rather mathematical entities resulting from the decomposition. Real spectral species are in fact linear combinations of these spectral vectors.
To get the real spectral species and their amplitudes (absorbance) requires an input from the user which has to make a choice of a reaction models. Kinetics of transitions between these species are linear combination of exponentials terms with rates constants such as evaluated by the global multiexponential fitting.

SFit offers a complete choice of kinetic Models such as: parallel system, fully sequential system, partly sequential or branched kinetics as following:

Figure 6: series kinetic model

Figure 7: Spectral species obtained using the series model

Figure 8: Concentrations of the spectral species as a function of time for a series model