Difference between revisions of "Team:Technion Israel/Measurement"

Introduction

Method

Molecules that penetrate into the silicon pores are observed as a change in the refractive index of the zero-order diffraction - the reflected light which is normal to the pores’ surface.

The intensity of the reflected light is given by the expression:

With the frequency of the cosine being:

I is the intensity of the light, Ψ is the phase delay between the source beam and the reflected one, λ is the free space optical wavelength, L is the depth of the pores (a physical property of the Silicon film) and n0 is the refractive index of the medium filling the pores.

The term 2n₀L is thus the optical path - the path the light travels from the source to the sensor. The factor of two is due to the reflection which means the light travels the length of the pores twice.
This term is named the Effective Optical Thickness - EOT and is the size we are interested in measuring. A fast Fourier transform (FFT) of the reflectivity spectrum provides us with the frequency of the peaks and is a way to directly measure the EOT. Once bacteria enter the pores they induce measurable changes in the EOT since the light has to travel through the bacteria which have a different refraction index than the clear medium.

Experiment General Scheme

The system used in this assay including all of its components, from the Nano-porous chip up to the laptop, was built and provided to us by Prof. Segal’s team . It relies on the same principle of detection explained above, FFT. Moreover, its ability to trap and detect bacteria has been proven beforehand.

As our project focuses on the chemotactic movement of bacteria, a different approach was implemented using their system. The focus of said approach was to study the effects of chemo-effectors, both attractants and repellents, on the bacteria and if it can be measured by RIFTS.

The steps taken in this assay to fit our approach were the same as mentioned above with a slight change. These changes were as follows:
1. Wash the chip with a buffer.
2. Wash the chip with bacteria to fill the pores to full capacity.
3. Wash the chip with clean medium to remove the cells that have not settled into the pores.
4. Insert a chemo-effector into the system to measure the bacterial chemotactic response.

Results

The EOT results of most tests that were conducted with the system following our approach were similar to the one presented in figure 1. The figure represents the EOT vs time of one experience and all 4 steps mentioned can be clearly seen. The main focus was on the 4th step as the first three steps were as predicted.

In four experiments a clear change was seen in the EOT upon the addition of the chemo-effectors (step 4 – yellow arrow). The initial sharp jump, up for the repellent or down for the attractant, was due to the change of the solution to one containing the chemo-effector, that has a different refractive index. Nevertheless, following the sharp jump a continuous trend was observed, again going up for the repellent or down for the attractant, which we believe is the chemotactic response of the bacteria

In order to verify the assumption, further analysis was conducted, for all of the four experiments with promising results. Two normalization steps were done to verify the changes and compare between the different experiments and the results are presented below – figure 2. These normalizations were:

1. Time: this helps in comparing the responses of the different strains over time, the normalization was done according to the following equation:
      Time = Time_n - Time₀
Where:
Time - The normalized time that passed since the introduction of chemo-effector.
Time₀ - The time elapsed since the start till the addition of the chemo-effector.
Time_n - The time that elapsed since the start of the experiment.

2. OT: this allows to measure the change in the EOT while phasing out the initial jump caused by the solution change. The normalization was done as follows:
      EOT = EOT_n - EOT₀
Where:
EOT - The EOT measurement relative to EOT₀.
EOT₀ - The EOT measurement following the introduction of chemo-effector and after the initial jump.
EOT_n - EOT recorded in Time_n.

Fig. 2: Digital chemotaxis measurements – Each of the four lines represents a different experiment done with a different chemo-effector. Light blue – response of positive control (ΔZras) to 50 mM sodium benzoate (repellent). Dark blue – response of positive control (ΔZras) to 50 mM sodium benzoate (repellent). Yellow– response of negative control (UU1250) to 50 mM sodium benzoate (repellent). Red – Dark blue – response of our clone Tar1 to 2mM aspartic acid (attractant). The dashed lines represent digitized ±1.

Discussion & Conclusion - Digital Chemotaxis

The main hypotheses that might explain the above phenomena is when a chemo-effector is introduced to the system, the bacteria senses the gradient in the Z-axis (height) formed by the diffusion of the substance into the pores. This leads to two different responses:

On one hand, if the substance was an attractant, the bacteria will travel up the concentration gradient, which means leaving the pores, to the higher concentration above them, leading to a drop in the EOT, as seen in Results tab-figure 2, red line.

On the other hand, if the substance was a repellent, the bacteria will travel down the gradient, fleeing from the high concentration, deeper into the pores. And thus any bacteria which is not confined will enter the pores as well and will lead to rise in the EOT, Results tab-figure 2 blue lines.

Acknowledgements

We would like to express our gratitude to Prof. Segal and her team whom provided the necessary equipment, guidance and help and without it, this work would not have been accomplished.