Indian Journal of Biotechnology

Vol 7, January 2008, pp 73-82

A preliminary study of smelling agents using electrical potential oscillations at

liquid-liquid interface

U Roy1*, R Shalini

2, S V Vanitha

2, S K Saha

3 and R C Srivastava

4

1Biological Sciences Group, Birla Institute of Technology and Science-Pilani, Goa Campus, Goa 403 726, India 2Biological Sciences Group and 3Chemistry Group, Birla Institute of Technology and Science, Pilani 333 031, India

4ICFAI University, Workstation at Central Electronic Engineering Research Institute, Pilani 333 031, India

Received 16 January 2006; revised 3 May 2007; accepted 8 June 2007

The present paper aims to study the complex oscillations at liquid-liquid interface while mimicking sensing

mechanisms of smell-oscillations of electrical potential differences across a bipolar liquid membrane induced by different

classes of olfactory agents, e.g. amines, alcohols, acids, aldehydes and esters, in vitro. A preliminary attempt was made to

classify and quantify various smelling agents and thereby developing a smell sensor. The bipolarity was induced by

introducing a cationic (cetyl pyridinium chloride) and anionic surfactant (sodium lauryl sulphate) along with the electrolytes

like sodium and potassium chloride in the experimental set-up. The data obtained indicate that olfactory agents of different

groups exhibit characteristically different frequency and amplitude.

Keywords: Amplitude, electrical potential oscillations, fast fourier transform, olfactory agents and olfaction

Introduction

The present study was conducted to figure out the

complex oscillations at liquid-liquid interface while

mimicking sensing mechanisms of smell-oscillations

of electrical potential differences across a bipolar

liquid membrane induced by different classes of

olfactory agents, e.g. amines, alcohols, acids,

aldehydes and esters. There have been various

attempts to classify the primary sensations of smell

oscillations of electrical potential difference across a

bipolar liquid membrane induced by various olfactory

agents in vitro. For mimicking the mechanism of

chemical sensing in biological systems, development

of an oscillatory system was felt and proposed

earlier1. However, the previous working model was

lacking the bipolar system2. The introduction of

bipolarity was needed, because the olfactory cell

membranes derived from the nerve cells are bipolar in

nature. In the experimental set-up, the bipolarity was

induced by introducing a cationic and an anionic

surfactant3 that has also been used for the present

study. Recently, by using the hydrodynamic oscil-

lation and Fast Fourier Transformation (FFT)

analysis, quantitation and tentative classification of

taste spectrum has been performed3,4

. The frequency

and amplitude of the odorants were monitored using

the LABVIEW SOFTWARE. For the Data

Acquisition of the analog values, the card NI 4350

was used to support the LABVIEW operations. In

order to get the frequency spectrum of different

category of smells, the program LABVIEW was run

to perform FFT analysis on the time domain. The FFT

was used for measuring the frequency content of

stationary and transient signal that was then converted

into the polar co-ordinates using the Z-transforms.

Stimulation of Olfactory Cells

The portion of the olfactory cells that responds to

the olfactory chemical stimuli is the cilia. The

membrane of the cilia contains large number of

protein molecules (receptor proteins) that protrude all

the way through the membrane and that can bind with

different odorant substances. These proteins are called

the odorant binding proteins (which has a G-protein

subunit). It is presumed that this binding initiated the

necessary stimulus for exciting the olfactory cell5.

Two different theories have been proposed to

explain the mechanism of excitation. One of them is

as follows: the molecules of the odorant binding

proteins themselves open up to become ion channels

when the odorant binds, allowing mainly large

number of sodium ions to flow to the interior of the

olfactory cell and depolarize it.

_____________

*Author for correspondence:

Tel: 91-832-2580303; Fax: 91-832-.5643017

E-mail: ray_utp@yahoo.co.in

INDIAN J BIOTECHNOL, JANUARY 2008

74

The binding of the odorant molecules causes the

odorant binding protein to become an activated

adenylate cyclase at its end that protrudes to the interior

of the cell. In turn, the cyclase catalyses the formation

of cyclic adenosine monophosphate (cAMP) from

adenosine triphosphate (ATP). The cAMP acts on

many other membrane proteins to open ion channels.

This mechanism provides a sensitive receptor because

of a cascade effect that would occur and allow even the

minutest of stimulation to cause a reaction. Several

physical factors affect the stimu-lation of the olfactory

cells. The three physical characteristics of the olfactory

substances that can be smelled are:-

1. It must be volatile—that is, it must easily

evaporate at normal temperatures and atmospheric

pressures so that molecules of the substance can be

carried through the air into the person's nose.

2. It must be somewhat water soluble—because the

molecules of the substance must pass through the

mucus that coats the inner surface of the nasal cavity

and reach the olfactory cells.

3. It must be lipid soluble—because the olfactory

hairs are composed primarily of lipids and the surface

of the olfactory cells are also lipid containing.

Potentials in Olfactory Cells

The potential of unstimulated olfactory cell

membranes averages about –55 mV. At this potential

many of the cells generate continuous action

potentials at a rate varying from once every 20 sec

upto 2 or 3 per sec.

Most odorants cause depolarization of the olfactory

membrane, decreasing the negative potential in an

olfactory cell from –55 mV down as low as –30 mV

or even less. Along with this, the number of action

potentials increases to about 20 per sec, which is a

very high rate for the very minute-fraction of a

micrometer sized olfactory nerve fibers2. A few

odorants hyperpolarize the olfactory cell membrane;

thus, decreasing, instead of increasing, the nerve

firing rate.

Over a wide range, the rate of olfactory nerve

impulses is approximately proportional to the

logarithm of the stimulus strength, which illustrates

that the olfactory receptors tend to obey the principles

of transduction similar to those of other sensory

receptors.

Materials and Methods In an attempt to classify and quantify the smelling

agents, the smells oscillations of electrical potential

difference across a bipolar liquid membrane induced

by smelling agents were mimicked.

Liquid Membrane System

The materials used for this mimetic system

involved:-

Surfactants—sodium lauryl sulphate [NaLS:CMC

(8.27 mM)] and cetyl pyridinium chloride

[CPCl:CMC (0.9 mM)]; as electrolytes, sodium

chloride and potassium chloride; and the liquid

membrane consisting of an oil layer (90% oleic acid

and 10% 1-propanol containing a pinch of 2,2′-

bipyridine).

The salt bridge consisting of saturated KCl and

0.8% agar (These are the U-tube connecters that

conduct the ions through the compartments to the

electrodes (Fig. 1).

The experimental set-up is indicated in Fig. 1,

which is self-explanatory. The experimental set-up

consisted of a chamber with a partition. In one

compartment NaLS was filled and the other contained

CPCI in equal quantities. The bipolarity was

introduced using cationic surfactant in one aqueous

compartment and an anionic surfactant in the other.

The liquid membrane (approximately 5 mm

thickness) was poured over the two solutions thus

connecting them. A piece of cotton soaked in

olfactory agent (e.g. amines, alcohols, aldehydes and

esters) was placed above the liquid membrane. The

Fig. 1—Diagram of the apparatus used: (a) Aqueous solution (2

mL) of cetyl pyridinium chloride (1 M CMC) containing 0.1 M

KCl; (b) Aquesous solution (2 mL) of sodium lauryl sulphate

(SLS) containing 0.1 M NaCl; (c) liquid membrane (5 mm

thickness) 90% oleic acid and 10% 1-propanol containing 2,2′-

bipyridine; (d) KCl salt bridge; (e) KCl solution; (f) x-t recorder;

(g) Ag/AgCl electrode; (h) glass tube containing cotton soaked in

odorant held 5 mm above the surface of the liquid membrane (oil

phase).

ROY et al: CATEGORIATION OF SMELLING AGENTS USING ELECTRICAL POTENTIAL OSCILLATIONS

75

compartments of the chamber were connected via salt

bridges in U-tubes (Fig. 1). All the experiments were

performed at constant temperature using a thermostat

set at 20±0.2°C. A Faraday cage was used for

shielding the system against stray field fluctuations.

The compartments of the chambers were connected

via salt bridges in U-tubes and other ends of U-tubes

were kept immersed in saturated KCl solutions. In the

saturated salt solutions were placed two electrodes

(Ag/AgCl), using which the potential oscillations

were monitored. The frequency and amplitude of the

odorants were monitored using the LABVIEW

software. The electrical potential oscillations were

monitored using Ag/AgCl electrodes on x-t recorder.

The FFT returned a two-sided spectrum in complex

form. This could be scaled and converted to polar

form to obtain the magnitude and phase.

Labview and Implementation of Smell Sensor

To monitor the potential oscillations generated by

the mimetic system the following methodologies were

adopted:-

LABVIEW is a program development environ-

ment, much like the modern C or BASIC develop-

ment environments. LABVIEW uses a graphical

programming language, G, to create programs in

block diagram form. The LABVIEW programs are

called virtual instruments. VI was an interactive user

interface, a data flow diagram that served as source

code and icon connections that allow the VI to be

called from higher levels. If the data are entered using

a mouse or keyboard the results can be viewed on a

computer screen.

For the Data Acquisition of the analog values the

LABVIEW supports the card NI 4350. The card has

features like low leakage construction, along with

analog and digital filtering, providing excellent

resolution, and accuracy and noise rejection. Fast Fourier Transformation (FFT)

FFT in LABVIEW is a powerful tool for analyzing

and measuring signals from plug in DAQ boards.

Time domain signals can be acquired, their frequency

content can be measured and the results can be

converted to real-world units and can be displayed on

traditional bench-top spectrum and network analyzers.

The advantage of using a Plug-in DAQ device is that

one can build a lower cost measurement system and

avoid communication overhead of working with

stand-alone instrument also. The FFT was used for

measuring the frequency content of stationary and

transient signals. The FFT returns a two-sided

spectrum in complex form. This could be scaled and

converted to polar form to obtain magnitude and

phase. The amplitude of the FFT is related to the

number of points on the time domain scale.

The waveform obtained is made to undergo a FFT

analysis. The FFT is the representation of the complex

waveform in the frequency domain. The horizontal

deflection was the frequency variable and the vertical

deflection was the signals amplitude at that frequency.

The complex waveform (the output obtained in the

form of complex coordinates) was Fast-Fourier

transformed onto a single waveform with average

amplitude and a frequency. The cathode ray

oscilloscope (CRO) was used to find the approximate

frequency range. The various points of the waveform

were also simultaneously stored in an array.

Results and Discussion In a recent study, it has been shown that

hydrodynamic oscillator developed by Yoshikawa and

Matsubara1 could be a good candidate for mimicking

the sensing mechanism3. The present study featured

the modification of the earlier method1. The much-

desired bipolarity was introduced by a cationic

surfactant (CPCl), which would be positively charged

in one aqueous compartment and an anionic surfactant

(SLS), which would be negatively charged in the

other aqueous compartment6. To the oil phase, 2-2′-

bipyridine was added to reduce the impedance, which

diminished the external noise. The external noise was

avoided by shielding with the Faraday cage. The

electrodes of the system were first tested on a cathode

ray oscilloscope (CRO). The oscillations were

observed within few minutes of exposing the

olfactory agents. Dissolution of various olfactory

agents was in the oil-phase. Oscillations ceased when

it was removed. Oscillations were observed above a

threshold concentration only and below a threshold

height. As the height increased the oscillations

decreased. As the concentration was increased, the

oscillations also increased. And the oscillations were

observed in the complex waveforms.

Further, experiments were imitated to find out

whether the system could be workable or not. In this

regard, 0.5 mL of 25% ammonia solution was added

to the oil phase and the electrical potential oscillations

were monitored where immediate oscillations and

magnitude of the oscillations were obtained (Fig. 1a)

that could corroborate the previous findings6,7

.

INDIAN J BIOTECHNOL, JANUARY 2008

76

Different classes of odorants are triggered at

different potentials for the brain to sense the smell.

The frequency and amplitude (voltage) of various

odorants were analysed. In order to get the frequency

spectrum of different smells we have to perform FFTs

on the time domain signal obtained. The LABVIEW

effectively did these operations. The output of the

FFT is a complex signal, which is converted into the

polar co-ordinates using the Z-transformation. The

polar co-ordinates are then bundled and displayed as a

frequency spectrum.

The experimental data obtained for all the classes

of olfactory agents have been shown in Figs 2-7 and

presented in Table 1. On comparison of the

amplitudes of various groups of olfactory agents, it is

clear that aldehydes (Fig. 7) have the strongest smell

followed by amines (Fig. 5), acids (Fig. 4), esters

(Fig. 6) and alcohols (Fig. 3) of Table 1.

When the individual graphs of all the olfactory

agents were analyzed, it was observed that as the

Fig. 2—Data on electrical potential oscillations in the time domain and frequency domain obtained using FFT analysis in case of 25%

ammonia. Number of samples=200; sampling rate=100

ROY et al: CATEGORIATION OF SMELLING AGENTS USING ELECTRICAL POTENTIAL OSCILLATIONS

77

Fig. 3—Data on electrical potential oscillations in the time domain and frequency domain obtained using FFT analysis in case of

different olfactory agents of alcohol group. Concentration in each case 1.0 M; number of samples=200; sampling rate=100

INDIAN J BIOTECHNOL, JANUARY 2008

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Fig. 4—Data on electrical potential oscillations in the time domain and frequency domain obtained using FFT analysis in case of different

olfactory agents of acid group. Concentration in each case 1.0 M; number of samples=100; sampling rate=100

ROY et al: CATEGORIATION OF SMELLING AGENTS USING ELECTRICAL POTENTIAL OSCILLATIONS

79

Fig. 5—Data on electrical potential oscillations in the time domain and frequency domain obtained using FFT analysis in case of different

olfactory agents of amine group. Concentration in each case 1.0 M; number of samples=100; sampling rate=100

INDIAN J BIOTECHNOL, JANUARY 2008

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Fig. 6—Data on electrical potential oscillations in the time domain and frequency domain obtained using FFT analysis in case of different

olfactory agents of ester group. Concentration in each case 1.0 M; number of samples=100; sampling rate=100

ROY et al: CATEGORIATION OF SMELLING AGENTS USING ELECTRICAL POTENTIAL OSCILLATIONS

81

Fig. 7—Data on electrical potential oscillations in the time domain and frequency domain obtained using FFT analysis in case of different

olfactory agents of aldehyde group. Concentration in each case 1.0 M; number of samples=100; sampling rate=100

INDIAN J BIOTECHNOL, JANUARY 2008

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number of carbon atoms in the olfactory agents in

each category increases, the amplitude of the peak

also increases. The odorants of the same chemical

group display almost the same frequency and

amplitude of a small range8 (Figs 3-7). In all the FFT

spectra (Figs 2-7), the horizontal deflection was the

frequency variable and the vertical deflection was the

signals amplitude at that frequency. The amplitude

was the highest for the aromatic agents in all the cases

proving that they have the strongest smell (Figs 5-7).

In order to explain the peaking of the amplitude at 50

KHz, irrespective of the category of the olfactory

agents used, it could be concluded that some kind of

amplitude modulation was found to occur before the

signal dwindled overriding some other noise signals

and due to the superimposing of the two amplification

factors entering the system in operation. This

phenomenon was similar to the way in which the

amplitude of a carrier wave was changed in

accordance with instantaneous value of the

modulating signal, without changing the frequency

and phase of the carrier. It was probably due to this

phenomenon that authors were unable to perform the

same experiment using a spectrum analyzer.

However, some of the other observations made from

the results of running the LABVIEW code were that

the amplitude was highest for the aromatic agents

(Figs 5 & 7) proving that they bear the strongest smell

at least amongst the agents chosen for the present

study.

Acknowledgement

The present work was assisted by Mr R K Purohit

of Electrical and Engineering Group of BITS, Pilani,

Rajasthan.

References 1 Yoshikawa K & Matsubara Y, Oscillation of electrical

potential across a liquid membrane induced by amine vapour,

Langmuir, 1 (1985) 230-232.

2 Upadhyay S, Das A K, Agarwala V & Srivastava R C,

Oscillations of electrical potential differences in the salt-

water oscillator, Langmuir, 8 (1992) 2567-2571.

3 Srivastava R C, Agarwala V, Das A K & Upadhyaya S,

Mimicking sensing mechanism of taste salt-water oscillator

and its non-electrolyte analogues-experiments with

compounds belonging to different taste categories, Indian J

Chem, 33 (1994) 978-984.

4 Roy U, Saha S K, Krishnapriya C R & Srivastava R C,

Quantifying taste using a hydrodynamic oscillator, Instrum

Sci Technol, 31 (2003) 425-437.

5 Guyton A C & Hall J E, Textbook of medical physiology,

10th edn (W B Saunders, UK) 2000, 616-619.

6 Srivastava R C, Das, A K, Upadhyaya S & Agrawala V,

Mimicking sensing mechanism of smell-oscillations of

electrical potential difference across a bipolar liquid

membrane induced by olfactory agents, Indian J Biochem

Biophys, 33 (1996) 195-198.

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8 Roy U, Shalini R, Vanitha S V, Saha S K & Srivastava R C,

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Table 1FFT analysis of various olfactory agents

Class of compounds Frequency Amplitude

Alcohols

Ethanol 49 0.07

Butanol 50 0.11

Benzyl alcohol 50 0.30

Esters

Methyl acetate 50 0.15

Butyl acetate 50 0.28

Methyl salicylate 50 0.42

Acids

Acetic acid 50 0.29

Benzoic acid 49 0.42

Amines

Methyl amine 49 0.40

Diethyl amine 50 0.45

Triethyl amine 50 0.45

Aldehydes

Formaldehyde 49 1.00

Acetaldehyde 50 1.10

Benzaldehyde 50 1.10