monitoring of bioprocess

12B702 -Bioprocess Engineering

UNIT- III

MONITORING OF BIOPROCESSES

1. INTRODUCTION

For most modern industrial production methods, process monitoring plays a key role;

bioprocess systems are no exception to this rule. Effective methods of monitoring are required

in order to develop, optimize, and maintain biological reactors at maximum efficiently. An

optimized process should lead to streamlined performance, reductions in running and material

costs, and improvements in quality control. A number of bioprocess monitoring instruments

have been regular features of the industry for many years (Fig.1), in particular, sensors capable

of measuring physical parameters. The challenge is to develop cost-effective devices capable of

measuring a much wider range of parameters, providing process operators with a deeper

insight into the process. Eventually effective monitoring will lead to better control systems,

providing cost and quality benefits.

Figure 1. Major areas of bioprocess monitoring.

Progress in monitoring, modeling and control of bioprocesses

The rapid development in biotechnology during the last few years was enhanced by progress in

genetic engineering. The successful application of the recombinant micro-organisms and cells

for industrial production of therapeutically important proteins and in less extent of primary and

secondary metabolites impaired by the lack of suitable production processes. An adaptation

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and improvement of the bioprocess engineering to the new demands was necessary. Quickly

turned out that beside improved medium optimisation more efficient process monitoring is

needed, which allows better process modeling and closer process control. Especially, quick

analysis methods are needed, which allow immediate response to the changes in a cultivation

process. Highly selective in situ and on-line methods are developed for process monitoring and

applied in laboratories. In addition, new analysis principles are discovered and miniaturization

of instruments is promoted.

However, some key variables, such as cell concentration and viability cannot be monitored

online. Therefore, they are identified by means of measured data and suitable process model

and the estimated state is used for state estimation and process control.

2. OPERATING FEATURES

For any measuring technique, there are a number of criteria that the device must satisfy if it is

too accepted by commercial bioprocess operators (Fig. 2). The following list of desirable

characteristic is not exhaustive, but does cover the main areas of concern.

Reliability

Reliability is a key issue for bioprocess monitoring equipment. Confidence in the ability of an

instrument to maintain its credibility in terms of performance is a fundamental parameter. This

encompasses a number of features relating to the operation of the instrument, for example,

ease of use, maintenance, repair, and replacement. A successful monitoring instrument will

have a low failure rate; again, this is related to reliability.

Accuracy

Accuracy can be described as the relationship between the measured value (by the instrument)

and the actual value of a bioprocess variable. An accurate instrument will achieve a low

percentage error between these two values. Generally this can be stated as

% error =(measured value - true value)/true value x 100%

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Figure 2. Main criteria for a bioprocess monitoring instrument

Precision

Precision is a measure of instrument reproducibility, that is, the ability to obtain the same value

with repeated measurements of a process variable (at a constant level). It follows that a precise

instrument may not, necessarily, be accurate. Therefore it is important to distinguish between

these two parameters.

Response time

The measurement of any process variable will entail a time delay between change in the

parameter and display of the measured value. This response time should not be detrimental to

the progress of the bioprocess, particularly if the measurement is linked to a control action.

Response times will be affected not only by the type of instrument but also by the method of

measurement. Off-line sampling and measuring can involve a number of time-consuming steps.

In contrast, in situ devices can provide a real-time measurement.

Calibration

In order to maintain the accuracy of a sensor it is (generally) desirable to carry out a calibration

step. This is carried out using set standards of comparison. The effects of calibration can

impinge on the process; in other words, it may be difficult to carry out calibration of an in situ

sensor, whereas an on-line device could easily incorporate a calibration step(s) during routine

running.

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Linearity

Under ideal conditions, the output signal from a sensor would be directly proportional to the

analyte concentration. However, this is not always the case, and other models have to be used

to reach a true value. Despite this drawback, linearity is not an overriding prerequisite for a

successful monitoring instrument. Developments in modern software can be adapted to

compensate for nonlinearity.

Threshold and Sensitivity

Sensitivity is the magnitude of the output signal per unit change in the target analyte

concentration. The lowest level of detection is related to the sensitivity and the signal-to-noise

ratio. A number of factors influence the sensitivity of a monitoring device, including sensor

design, the operating environment, periods of maintenance, and interfering noise levels. The

sensitivity will influence the dynamic range above which the device becomes saturated; the

highest level of detection will be the threshold limit for the device.

3. METHODS OF MONITORING

In addition to the variety of monitoring devices available, a number of methods (for carrying

out the measurement exist (Fig. 3). Sampling and sample handling is a vital issue, affecting both

the accuracy and frequency of measurements. Broadly, the main approaches to sampling can

be described in one of several ways.

Figure 3. Methods of monitoring.

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Off-Line or At-Line Monitoring

Off-line monitoring involves taking a sample from the bioreactor and carrying out the

measurement at a different site, usually under laboratory conditions. Off-line sampling can be

detrimental in terms of cost, efficiency, and threat to asepsis. Manually removing and

measuring a sample requires technical labor. The received signal will not be “real time” because

of the delays. In order to obtain the sample, the sterility of the bioreactor must be maintained.

Hence, provision must be made to achieve this. In some cases, decentralized equipment has

become available that allows measurements to be made simply close to the production process

(at-line), reducing some of the delays associated with laboratory analysis.

In Situ or In-Line Monitoring

In situ sensors are placed directly in the bioprocess vessel. The use of in situ sensors has long

been established in the bioprocess industry, where “dip-in” devices are used to monitor a

number of parameters such as pH and dissolved gas concentrations. A number of advantages

are gained by operating sensors in this fashion, including real-time monitoring (sampling-

related time delays are eliminated) with the sensors operating continuously (any rapid change

in the analyte concentration can be readily observed), and labor requirements and problems of

contamination are both significantly reduced. However, in situ sensors can have a number of

drawbacks, for example, the sensor system must be amenable to sterilization; if the lifetime is

short, replacement may be difficult (during a process run); the surface of the sensor could

become fouled by components of the growth medium, affecting the signal output.

On-Line Monitoring

Methods of on-line monitoring involve the automatic removal and measurement of sample or

sample stream from the bioreactor. One example of this has been the development (since the

early 1980s) of flow injection analysis (FIA). This is a liquid handling technique that has proved

flexible in adapting to most chemical and biochemical reaction procedures, representing an

effective compromise between the desirability of in situ monitoring and the technical ease of

off-line measurements. The main advantages of on-line methods include the following: sensor

sterilization can be readily accomplished, sample pretreatment (e.g., gassing, dilution, removal

of interferents), and sensor calibration can be built into the system. The main disadvantages are

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a need for an effective and reliable sampling system and the fact that the signal is

discontinuous; frequency measuring rate is determined by the limitation of the overall FIA

arrangement. All of these methods have their advantages and disadvantages. The choice of

approach adopted depends on a number of factors, not least of which will be the availability of

both sensor and system.

4. MEASUREMENT OF DIFFERENT PARAMETERS

Introduction

The widespread use of advanced control and process automation for biochemical

applications has been lagging as compared with industries such as refining and petrochemicals

whose feedstocks are relatively easy to characterize and whose chemistry is well understood

and whose measurements are relatively straightforward. Biological processes are

extraordinarily complex and subject to considerable variability. The reaction kinetics cannot be

completely determined in advance in a fermentation process because of variations in the

biological properties of the innoculant. Therefore, information regarding the activity of the

process must be gathered as the fermentation progresses. Directly measuring all the necessary

variables which characterize and govern the competing biochemical reactions, even under

optimum laboratory conditions, is not yet achievable. Developing mathematical models, which

can be utilized to infer the biological processes underway from the measurements available,

although useful, is still not sufficiently accurate. Add to this the constraints and compromises

imposed by the manufacturing process and the task of accurately predicting and controlling the

behavior of biological production processes is formidable indeed. The knowledge base in

fermentation and biotechnology has expanded at an explosive rate in the past twenty-five years

aided in part by the development of sophisticated measurement, analysis and control

technology. Much of this research and technology development has progressed to the point

where commercialization of many of these products is currently underway.

Measurement Technology

Measurements are the key to understanding and therefore controlling any process. As it

relates to biochemical engineering, measurement technology can be separated into three

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broad categories. These are biological, such as cell growth rate, florescence, and protein

synthesis rate; chemical, such as glucose concentration, dissolved oxygen, pH and offgas

concentrations of CO2, O2, N2, ethanol, ammonia and various other organic substances; and

physical, such as temperature, level, pressure, flow rate and mass. The most prevalent are the

physical sensors while the most promising for the field of biotechnology are the biological

sensors.

Cell Mass Measurement

The on-line direct measurement of cell mass concentration by using optical density

principles promises to dramatically improve the knowledge of the metabolic processes

underway within a bioreactor. This measurement is most effective on spherical cells such as E.

Coli. The measurement technology is packaged in a sterilizable stainless steel probe which is

inserted directly into the bioreactor itself via a flange or quick-disconnect mounting.

By comparing the mass over time, cell growth rate can be determined. This measurement

can be used in conjunction with metabolic models which employ such physiological parameters

as oxygen uptake rate (OUR), carbon dioxide evolution rate (CER) and respiratory quotient (RQ)

along with direct measurements such as dissolved oxygen concentration, pH, temperature, and

off gas analysis to more precisely control nutrient addition, aeration rate and agitation. Harvest

time can be directly determined as can shifts in metabolic pathways possibly indicating the

production of an undesirable by-product. Cell mass concentrations of up to 100 grams per liter

are directly measured using the optical density probe. In this probe, light of a specific

wavelength, created by laser diode or passing normal light through a sapphire crystal, enters a

sample chamber containing a representative sample of the bioreactor broth and then passes to

optical detection electronics. The density is determined by measuring the amount of light

absorbed, compensating for backscatter. Another technique used to determine cell density is

spectrophotometric titration which is a laboratory procedure which employs the same basic

principles as the probes discussed above. This requires a sample to be withdrawn from the

broth during reaction and therefore exposes the batch to contamination.

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Chemical Composition

The most widely used method for determining chemical composition is chromatography.

Several categories have been developed depending upon the species being separated. These

include gas chromatography and several varieties of liquid chromatography including low

pressure (gel permeation) and high pressure liquid chromatography and thin layer

chromatography. The basic principle behind these is the separation of the constituents traveling

through a porous, sorptive material such as a silica gel. The degree of retardation of each

molecular species is based on its particular affinity for the sorbent. Proper selection of the

sorbent is the most critical factor in determining separation. Other environmental factors such

as temperature and pressure also play a key role.

The chemical basis for separation may include adsorption, covalent bonding or pore size of

the material. Gas chromatography is used for gases and for liquids with relatively low boiling

points. Since many of the constituents in a biochemical reaction are of considerable molecular

weight, high pressure liquid chromatography is the most commonly used. Specialized apparatus

is needed for performing this analysis since chromtograph pressures can range as high as

10,000 psi. Thin layer chromatography requires no pressure but instead relies on the capillary

action of a solvent through a paper-like sheet of sorbent. Each constituent travels a different

distance and the constituents are thus separated. Analysis is done manually, typically using

various coloring or fluorescing reagents.

Gel permeation chromatography utilizes a sorbent bed and depends on gravity to provide

the driving force but usually requires a considerable time to effect a separation. All of these

analyses are typically performed in a laboratory; therefore they require the removal of samples.

As the reaction is conducted in a sterile environment, special precautions and sample removal

procedures must be utilized to prevent contaminating the contents of the reactor.

Oxygen

Generally, oxygen measurement falls into two main categories: dissolved oxygen and exit

gas analysis. For most aerobic fermentations, an accurate determination of the dissolved

oxygen concentration is of particular importance, for example, in maintaining the concentration

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above a specified minimal level. In addition, oxygen transport processes can be determined

only by using an accurate method of measurement. The exit gas analysis for oxygen, usually in

conjunction with CO2 measurement, can be used to determine the metabolic state of aerobic

microorganisms and their oxygen uptake.

Ex: Dissolved Oxygen Probes

Galvanic Electrodes

O2 Optodes.

Dissolved oxygen is one of the most important indicators in a fermentation or bioreactor

process. It determines the potential for growth. The measurement of dissolved oxygen is made

by a sterilizable probe inserted directly into the aqueous solution of the reactor. Two principles

of operation are used for this measurement: the first is an electrochemical reaction while the

second employs an amperometric (polarographic) principle. The electrochemical approach uses

a sterilizable stainless steel probe with a cell face constructed of a material which will enable

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oxygen to permeate across it and enter the electrochemical chamber which contains two

electrodes of dissimilar reactants (forming the anode and cathode) immersed in a basic

aqueous solution. The entering oxygen initiates an oxidation-reduction reaction which in turn

produces an EMF which is amplified into a signal representing the concentration of oxygen in

the solution.

In the amperometric (polarographic) approach, oxygen again permeates a diffusion barrier

and encounters an electrochemical cell immersed in basic aqueous solution. A potential

difference of approximately 1.3 V is maintained between the anode and cathode. As the oxygen

encounters the cathode, an electrochemical reaction occurs:

The hydroxyl ion then travels to the anode where it completes the electrochemical reaction

process:

The concentration of oxygen is directly proportional to the amount of current passed

through the cell.

Viscosity

Information on the rheology, or viscosity, can help in ensuring the efficiency of a biological

process. An example of this would be the effectiveness of oxygen transfer throughout a

medium and determining the degree of branching of filamentous microorganisms. In addition,

viscosity can effect pumping, mass transfer, and mixing. Viscosity is the apparent shear

resistance between adjacent layers of liquids or gases moving at different speeds. Typically, in

fluids this is the result of molecular cohesion; rising temperatures lead to a decrease in

viscosity. In contrast, viscosity increases for gases under conditions of rising temperature. This

results from an increased measured molecular activity.

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Ex: Cone and plate viscometer.

Coaxial cylinder rotary viscometer.

Impeller viscometer.

Exhaust Gas Analysis

Much can be learned from the exchange of gases in the metabolic process such as O2, CO2,

N2, and ethanol. Infact, most of the predictive analysis is based upon such calculations as oxygen

uptake rate, carbon dioxide exchange rate or respiratory quotient. This information is best

obtained by a component material balance across the reactor. A key factor in determining this

is the analysis of the bioreactor off gas and the best method for measuring this is with a mass

spectrometer because of its high resolution.

Measurement of pH

Metabolic processes are typically highly susceptible to even slight changes in pH, and

therefore, proper control of this parameter is critical. Precise manipulation of pH can determine

the relative yield of the desired species over competing by-products. Deviations o as little as 0.2

to 0.3 may adversely affect a batch in some cases. Like the cell mass probe and dissolved

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oxygen probes described earlier, the pH probe is packaged in a sterilizible inert casing with

permeable electrode facings for direct insertion into the bioreactor.

The measurement principle is the oxidation-reduction potential of the hydrogen ion and the

electrode materials are selected for that purpose. Measuring pH, along with temperature, is

one of the most common practices in bioprocess monitoring. Correcting action can be taken,

either manually or automatically, to prevent unwanted increases or decreases in pH. The most

common form of pH sensor used for fermentation monitoring is based on the electrode design

introduced by Ingold in 1947.

Temperature

Maintaining optimum conditions for any bioprocess will invariably involve monitoring and

controlling the temperature of the broth. Precise temperature control and profiling are key

factors in promoting biomass growth and controlling yield.

Generally, bioprocesses are monitored over a temperature range of between 0 0C and 100 0C (excluding the sterilization cycle). Furthermore, this may require a control regime operating

within a narrow range of temperatures. A number of devices are available for obtaining an

accurate measurement of temperature conditions during a bioprocess operation, based on a

range of techniques.

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Ex: Thermistors

Resistance Thermometers.

Thermocouples

Mercury-in-Glass Thermometers.

Bimetallic Thermometers.

Pressure

Many bioprocesses operate under conditions of overpressure. Monitoring the magnitude of

this pressure is an important factor, both in terms of safety and optimization of the process.

Industrial and laboratory fermenters are designed to operate up to a safe working pressure.

Increasing the applied pressure above the upper limit can be dangerous. Furthermore,

maintaining a positive reactor head pressure can prevent contamination of the bioreactor. In

order to facilitate effective sterilization, fermenters need an accurate pressure monitor.

Pressure will also affect the solubility of gases (such as O2 and CO2). Several different

approaches have been used in the development of pressure gauges.

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Ex: Bourdon Tube Pressure Gauge.

Strain Gauges

Piezoelectric Manometers.

Diaphragm-Type and Pressure Bellows Sensors

Weight

Monitoring fluctuations in the weight of a vessel used for bioprocesses is an effective way of

measuring the contents and flow rate of additions. There are a number of load cells available

for this task. The principle of a load cell is based on measuring the compressive strain that is

placed on the device (e.g., a solid or tubular steel cylinder) when under an axial load. Electrical

resistance strain gauges can be included in the device structure. A proportional electrical

resistance to the applied load can then be measured; this varies in relation to changes in load.

Obviously, a temperature compensator must be included in the instrument to account for heat

effects on the resistors. These devices need to be rugged and have long-term stability. For

reasons of safety, it is also desirable for the device to be accurate. A load cell designed to detect

tensile forces can be used for weight measurements of suspended vessels.

Fig: Schematic of the installation of a load cell.

Liquid Level Measurement

Liquid levels in a vessel can be determined using a number of techniques. Determining the

level can assist in formulating mass balances and measuring nutrient additions. Hydrostatic

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pressure can be measured using a single sensor positioned at the bottom of the vessel.

Alternatively, two sensors spaced at the top and bottom of the vessel (differential design) can

be employed. These sensors are electromechanical devices based on the deformation of a

spring; the resulting signal is displayed as an electrical signal (capacitance or reactance).

Volumetric Flow Rate

Quite a number of technologies are available for measuring volumetric flow rates. These

include differential pressure transmitters, vortex meters and magnetic flow meters. Each has its

advantages and disadvantages. The differential pressure transmitter is the most popular and

has been in use the longest. Its measurement principle is quite simple. Create a restriction in

the line with an orifice plate and measure the pressure drop across the restriction. The

measurement takes advantage of the physical relationship between pressure drop and flow.

The primary disadvantages of the differential pressure producing flow measurements are

the permanent pressure drop caused by the restriction in the line; sediment buildup behind the

orifice plate (which could be a source of bacterial buildup) and loss of accuracy over time as the

edge of the plate is worn by passing fluid and sediment.

Broth Level

As the broth in a fermenter or bioreactor becomes more viscous and is subjected to

agitation from sparging (the introduction of tiny sterilized air bubbles at the bottom of the

liquid) and from mixing by the impeller, it has a tendency to foam. This can be a serious

problem as the level may rise to the point where it enters the exhaust gas lines clogging the

ultrafilters and possibly jeopardizing the sterile environment within the reactor. Various

antifoam strategies can be employed to correct this situation, however, detection of the

condition is first required.

Regulatory Control

Automatic regulatory control systems have been in use in the process industries for over

fifty years. Utilizing simple feedback principles, measurements were driven toward their set

points by manipulating a controlled variable such as flow rate through actuators like throttling

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control valves. Through successive refinements in first mechanical, then pneumatic, then

electronic and finally digital electronic systems, control theory and practice has progressed to a

highly sophisticated state.

Carbon Dioxide

For many bioprocesses, the measurement of CO2 is an important feature. Increased levels

of dissolved carbon dioxide can inhibit growth and reduce the production of secondary

metabolites.

Redox Potential

Monitoring the redox potential of a bioprocess medium can provide information about the

equilibrium between oxidizing and reducing species (electron acceptors and donors,

respectively) present. Measurement of redox potential is achieved using a combined metal-

reference electrode system.

Mass Spectrometry

The use of on-line mass spectroscopy (MS) has developed since the first report of Reus et al.

A wide range of gasses, both free and dissolved (e.g., CO2, O2, CH4), can be measured. In

addition, volatile organic compounds such as methanol, ethanol, acetone, and simple organic

acids can be monitored. The technique is based on the rupture of molecules by a high-energy

source into corresponding ions.

Conductivity Sensors.

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Conductivity sensors are particularly suited to monitoring levels of foam (in a number of

fermentations), where in excess it can cause problems. The sensor consists of a stainless steel

probe, insulated except for the tip. The device can be used with noncorrosive conducting fluids.

If the liquid or foam level rises to contact with the tip, an electric current is passed through the

sensor; the foam acts as an electrolyte and the vessel as a ground. The sensor can be coupled to

a control device that dispenses antifoam to counter the increased level.

Capacitance Sensors.

Capacitance sensors operate by detecting changes in the relative dielectric constant of the

media, compared with air. Measurements are made by detecting variations in electrical

capacity brought about by changes in the liquid level.

Acoustic Sensors.

Acoustic sensors operate via transducers that generate and detect ultrasonic waves. Two

formats are available: a single device that both transmits and receives the signal, and two

separate transducers with one function. By monitoring the time it takes for the sound wave to

travel, the liquid level can be determined. With the single device the sound wave is directed

onto the liquid surface. When the level rises, the time delay is shortened.

Temperature Probes.

Liquid levels can be measured using a series of thermistors sited vertically through the vessel.

During operation, an electrical current is applied to the sensors, raising their temperature

above the ambient. When the liquid (or foam) level reaches a sensor positioned lower down

the vessel, the sensor cools. This causes a temperature difference and, hence, a change in

electrical resistance. The resistance can be displayed as an output signal indicating the liquid

level.

Flow Measurement

Flow measurement is an important feature for many bioprocesses, for both gases and

liquids. These measurements are carried out on both the influent and effluent streams.The

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most common form of gas and liquid measurement is carried out using a variable area flow

meter, or rotameter.

Rotameter

This device consists of vertically mounted (usually conical) tube enclosing a free-floating

body that is able to move up (floating in the gas flow of interest) and down a tapered bore

running through the tube body. Typically, the tube is constructed of glass or metal and the float

is a ball or hollow thimble shape. Because the position adopted by the flow rate is dependant

on both the gas flow and the viscosity of the medium, the instrument requires careful

calibration.

METHODS OF BIOMASS ESTIMATION

The monitoring of biomass concentration can be carried out using a number of techniques.

Conventionally, biomass concentration is measured off-line using labor intensive, time-

consuming methods such as dry weight cell, plate or microscopic cell count, and measuring the

optical density of diluted samples. However, a number of more rapid methods have been

developed. Of particular interest is the development of real-time on-line methods.

Generally, methods for determining biomass concentration can be divided into two

classifications: direct and indirect. The former is based on determining the physical properties

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of the cell and its components. In contrast, indirect methods measure factors related to the cell

and its activity (e.g., respiration, electrochemical behavior, and nutrient fluctuation).

Direct Biomass Measurements

Some measure of the bacterial cell mass or numbers of a culture is almost always used as

the reference basis for measurements of cellular metabolic activities, the types of

morphological characters, or the amount of chemical constituent; biomass and cell numbers

are the two basic independent parameters of bacterial growth. The methods for measuring

biomass seem obvious and straightforward, but in fact they are complicated if accuracy if

sought. Furthermore, the results may be expressed in different ways and, in some of these

ways, the values may be more relative than absolute.

Wet Weight

A nominal wet weight of bacterial cells originally in liquid suspension is obtained by

weighing a sample in a tared pan after separation and washing the cells by filtration or

centrifugation. In either case, however, diluent is trapped in the interstitial (intercellular) space

and contributes to the total weight of the mass. The amount of interstitial diluent may be

substantial. A mass of close-packed, rigid spheres contains in its interstices 27% of space. This is

independent of sphere size. A mixture of sizes packs more densely, and close-packed bacterial

cells may contain an intersticial volume of 5 to 30 %, depending on their shape and amount of

deformation. This is a problem that is readily solved if the washing step can be carried out with

pure water. Simple weighing or just measuring the packed volume of cells can be an excellent

and rapid method with filamentous organisms or those that grow as pellets. Then filter, wash

and weigh or centrifuge, and measure the height of the pellet. Both can be very rapid, and the

procedures can be calibrated to correct for the exogenous water or shapes of centrifuge tubes.

Because the particulate matter in the medium has different physical properties, it can be

possible to separate the cells from the particulates and estimate the cell volume directly. This

correction could be established with radioactive or fluorescent dextrans or other molecules

that are too big to enter the cells.

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Dry Weight

A nominal dry weight (solids content) of bacterial cells originally in a liquid suspension is

obtained by drying a measured wet weight or volume in an oven at 80oC for 10 hrs to constant

weight. The cells could be washed with water (possibly extracting cell components), or (better)

a correction could be made for medium or diluent constituents that are dried along with the

cells. Separating the cells by filtration poses particular problems. More problems arise if volatile

components of the cells can be lost by oven drying, or if some degradation and volatilization

occurs, evidenced by discoloration (particularly if a higher temperature is used). Some regain of

moisture occurs during the transferring and weighing process in room atmosphere, so this

should be done quickly within a fixed time for all replicate samples, especially if the relative

humidity is high. It is best, of course, to use tared weighing vessels that can be sealed after

drying.

The dry weight of cells may be expressed on a wet weight basis (grams of solids per gram of

wet cells) or on a wet volume basis (grams of solids per cubic centimeter of wet cells or per

cubic centimeter of cell suspension). Because the drying can be a time-consuming process, and

adequate knowledge about the possibility of volatilization of some cell components is not

known, in the future, adequate drying quickly at lower temperature could be done in specially

designed vacuum ovens. Such procedures could also be calibrated for the residual water

content. Often, a practical method is to dry the cells in a microwave oven.

Indirect Biomass Measurements

Bioluminescence and Chemiluminescence: The use of bioluminescent techniques is based

on determining levels of adenosine triphosphate (ATP) concentration. Generally, levels of ATP

remain constant for living cells, decreasing when the cells die. ATP concentration can,

therefore, be related to biomass. A particular enzyme that has proved useful for this method is

luciferase, which catalyzes the following reaction:

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By detecting the light produced by this reaction, ATP concentrations, and hence, biomass,

can be determined. This method can detect cell numbers as low as 105 cells per ml; it can be

automated, and the assay time is fairly rapid. However, the method does suffer from several

drawbacks, for example, the extraction of ATP may be incomplete, there may be free ATP

present from other sources, and there maybe degradation of ATP by the extraction reagents.

Chemiluminescence is based on the detection of light produced by the protein-catalyzed

oxidation of luminol in the presence of hydrogen peroxide.

Acoustic Resonance Densitometry. Acoustic resonance density is based on determining the

change in a resonant frequency that results from changes in cell density. This is a noninvasive

method that does not require contact between the instrument and the culture medium. The

method incorporates an oscillatory circuit, amplifier, and test cell. Theoretically, the fluid

density of the sample can be calculated from the square of its oscillation. Recent reports have

described using this approach to monitor cultures of hybridomas and human lymphoma cells.

Further advantages for this method include independence from flow rate and viscosity.

However, there are disadvantages including the need for a filtration system (to enable the

resonance density of the medium to be measured in the absence of cells), with the inherent

problems associated with such systems, including poor sensitivity and problems caused by

bubbles and particulate matter.

Capacitance, Conductivity, and Electrochemical Methods.

The electrical properties of cells have been exploited in the development of a number of

techniques. Changes in media capacitance have been related to biomass concentration (e.g., a

decreasing capacitance coupled with an increasing biomass concentration. In addition, it has

been suggested that cell viability is linked to capacitance measurements. Several in situ

commercial instruments are currently available for determining biomass concentration based

on capacitance measurements. The Biomass Monitor measures the radio frequency

conductance and capacitance of a cell suspension using a constant voltage, four-terminal,

phase-sensitive detector system. Furthermore, the probes can be inserted directly into

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bioreactors using a standard 25- mm-diameter port. The probes are fully sterilizable and can be

cleaned in situ during operation.

Fluorescence.

Fluorescence is a characteristic possessed by a number of important biological compounds

including proteins, enzymes, and coenzymes. Simply de- fined, it is the absorbance of light

energy at a particular wavelength, followed by reemission at a longer wavelength. After the

passage of light energy, the compound returns to its ground-state level. In the field of

bioprocess monitoring, fluorescence has been used, in particular, to monitor reduced

nicotinamide adenine dinucleotide (NADH) and reduced nicotinamide adenine dinucleotide

phosphate (NADPH) concentrations. These compounds are irradiated at 340 nm and emit at

450 nm. Both compounds are present in living organisms and are vital components of metabolic

processes. By monitoring the intensity of fluorescence at the characteristic emission

wavelength, it should be possible to calculate the total biomass concentration. Unfortunately,

the use of fluorescence as a marker for cell concentration does suffer from a number of

drawbacks including that the fluorescence signal can originate from changes in metabolic state

and not from cell concentration levels, sensitivity may be affected by the presence of

compounds that can quench both the excitation and emission wavelengths, and other

compounds may fluoresce at the same wavelength.

Flow Cytometry.

Flow cytometry is a measuring technique based on the irradiation of a sample solution

(containing a cell population) with a suitable light source, followed by monitoring of the

scattered or absorbed light. In addition, fluorescence can be used as the measuring parameter.

This technique can be used to ascertain a number of cellular features, such as the accumulation

of cellular components (e.g., DNA, RNA, and proteins), and cell dynamics (e.g., cell size

distribution). Furthermore, flow cytometry can be used to differentiate and quantify a range of

species populations present in a mixed medium.

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Light Scattering and Turbidity.

Optical techniques based on either the scattering of light (nephelometry) or the degree of

transmitted light or optical density (turbidity) have been developed for determining biomass. By

monitoring the degree of light scattering using nephelometry, both cell numbers and mass can

be determined. This approach is particularly suited for bioprocesses that involve low cell

concentrations, where the background (compared) level is near zero.

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Turbidity measurement can be used for both online and off-line determination of biomass.

Light scattering by a turbid medium results from a number of factors including particle size,

shape, and number. Quantification is based on the Lambert-Beer law

5. MICROBIAL CALORIMETRY

Introduction

Calorimetry is the science of measuring the heat of chemical reactions or physical changes.

Calorimetry involves the use of a calorimeter. Heat is a universal and unavoidable by product of

all biological phenomena, including those that are exploited in biotechnology at technical scale.

Any change in growth rate, metabolism, biocatalytic activities and in other biological

phenomena occurring in technical reactors will invariably affect the rate at which heat is

released.

Yet heat effects in cellular cultures often go unnoticed when one is working with

conventional laboratory equipment because most of the heat released by the culture is lost to

the environment too quickly to give rise to a perceivable temperature increase. This, however,

is completely different at large scale. As opposed to laboratory reactors, industrial size

fermenters operate nearly adiabatically due to their much smaller surface to volume ratio. Thus

all the heat released by the culture must be removed by appropriate cooling facilities.

Systematic monitoring of heat generation rates by the culture in large-scale bioreactors

would clearly be of considerable benefit for process optimization and control. The information

contained in this signal could be used together with data on other relevant process parameters

to obtain quantitative on-line estimates of the activity, the metabolism and the state of the

culture.

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One method of determining the energy exchange between the reaction system and its

environment is to conduct a calorimetric analysis. A calorimeter is a thermally insulated

container where a reaction system can be performed and the energy exchange between the

system and its environment can be measured. The calorimeter and its contents are considered

the environment. The reaction system is a chemical or physical process that occurs within the

confines of the calorimeter.

Qsurr = Qcal + Qcontents

The Qcal can be determined if one knows the Heat Capacity of the calorimeter. This Heat

Capacity can be experimentally determined and is expressed in Kilojoules / C degree. In order to

determine the Qcal you multiply the Heat Capacity of the calorimeter by the difference between

the final and initial temperature. For example if the Heat Capacity of a calorimeter was

determined to be 25.4 KJ/Celsius Degree, determine the Qcal if the initial temperature during a

calorimetric analysis was 30 C and the final temperature was 50 C.

Qcal = Heat Capacity ( final temp - initial temp) = 25.4 Kj/C ( 50 - 30 C) = 508 Kj

Calorimetric Equipment

In order to make use of heat release measurements in bioprocess control algorithms,

suitable models must be available which relate the heat evolution rate of the culture to other

relevant process variables, such as substrate consumption, growth rate or oxygen up-take.

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Numerous workers have studied these relationships in calorimetric experiments at the

laboratory scale. The need for maintaining technically relevant, strictly controlled culture

conditions made it difficult to obtain meaningful results in micro calorimeters.

Applications: Heat as a quantitative indicator of cell metabolism

Control of fermentations by calorimetry

6. FLOW INJECTION ANALYSIS

The concept of flow injection analysis (FIA) was proposed in 1975 by Ruzicka and Hansen.

The fast and intensive development of the FIA methodology was due to several factors essential

for routine analytical determinations, such as very limited sample consumption, the short

analysis time based on a transient signal measurement in a flow-through detector and an on-

line carrying out difficult operations of separation, preconcentration or physicochemical

conversion of analytes into detectable species.

Principle of the FIA

The three principles or cornerstones of FIA were identified by Ruzicka and Hansen as sample

injection, controlled dispersion of the injected sample zone, and reproducible timing of the

movement of the injected zone from the injection point to the detector.

(C=carrier; P=pump; S=point of sample injection; RC=reaction coil; D=detector; W=waste)

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Schematic diagram of the basic FI system

In the simplest form of FIA the sample is injected into a continuous flow of reagent solution

(carrier), dispersed, and transported to detector. Sample dispersion is controlled through the

suitable choice of the injected sample volume, flow rate of carrier, length of the reaction coil,

and diameter of the tubing used. A schematic diagram of the basic FI system is shown in Figure

Flow Injection Analysis (FIA), the first generation of FIA techniques, is also probably the most

widely utilized. In its simplest form, the sample zone is injected into a flowing carrier stream of

reagent. As the injected zone moves downstream, the sample solution disperses into the

reagent, causing the product to form. A flow through detector placed downstream records the

desired physical parameter such as colorimetric absorbance or fluorescence.

The modern Flow Injection Analysis system usually consists of a high quality multichannel

peristaltic pump, an injection valve, a coiled reactor, a detector such as a photometric flow cell,

and an autosampler. Additional components may include a flow through heater to increase the

speed of chemical reactions, columns for sample reduction, debubblers, and filters for

particulate removal.

The typical FIA flow rate is one milliliter per minute, typical sample volume consumption is

100 microliters per sample, and typical sampling frequency is two samples per minute. FIA

assays usually result in sample concentration accuracies of a few percent.

Sequential Injection Analysis

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Sequential Injection Analysis (SIA) is the second generation approach to FIA compatible

assays. SIA usually consists of a single-channel high precision bi-directional pump, a holding coil,

a multiposition valve, and a flow through detector. The system is initially filled with a carrier

stream into which a zone of sample and a zone of reagent(s) are sequentially aspirated into a

holding coil, forming a linear stack. These zones become overlapped due the parabolic profile

induced by differences between flow velocities of adjacent streamlines. Flow reversals and flow

acceleration further promote mixing. The multi position valve is then switched to the detector

position, and the flow direction is reversed, propelling the sample/reagent zones through the

flow cell.

The advantage of SIA over the more traditional flow injection analysis (FIA) is that SIA

typically consumes less than one-tenth the reagent and produces far less waste – an important

feature when dealing with expensive chemicals, hazardous reagents, or online/remote site

applications. One disadvantage of SIA is that it tends to run slower than FIA.

Online process monitoring using SIA is often an ideal solution. The low reagent/sample

consumption, waste production, and nearly hands-off robustness make SIA the perfect choice.

Example online applications include fermentation monitoring of ammonia, glycerol, and

glucose. Or automated sample dilutions prior to absorbance monitoring, perhaps many

thousands fold. Also remote site monitoring, where the system may run for days without user

intervention.

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Biosensors

One possible answer to the problem of monitoring metabolites, both in situ and on-line,

may be solved in the near future by the use of biosensors. Since their conception in the 1960s,

these devices have generated considerable interest. This has spread to a diverse range of fields

including clinical diagnostics, environmental protection, bioprocess monitoring, and defence

applications (56). In general the operation of a biosensor is characterized by three functional

steps: recognition, physiochemical signal generation, and signal processing. The biological

component (e.g.,enzyme, whole cell, antibody, and cell receptor) imparts a high degree of

selectivity on the biosensor. Coupled to the biological component; the transducer is designed to

respond to the changing physicochemical parameters caused by the specific interaction of the

biological component with the substrate. A range of transducers have been used in the

development of biosensors and include the electrochemical (potentiometric and

amperometric), optical, calorimetric, piezoelectric, and thermometric . Most of these types

have been adopted in the development of biosensors intended for bioprocess monitoring.

Enzyme-modified field effect transistors (FETs), whereby the biologically active layer is

positioned on top of the ion electrode membrane, have also been used for bioprocess

monitoring. The instrument can be used to determine a range of metabolites (e.g., glucose,

lactate, and ethanol). Recently the company has introduced an on-line instrument. Indeed, on-

line biosensor systems have been demonstrated using a variety of biological-transducer

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systems . A wide range of metabolites have been monitored using various bioprocess regimes .

Commercially, a significant number of biosensor devices are available for measuring a range of

analytes. However, at present, the majority of these devices are aimed at the medical

diagnostic market. The goal is to develop cheap, reliable sensors that can operate under a range

of bioprocess conditions for extended periods with a minimum of maintenance.

Nuclear Magnetic Resonance

Nuclear magnetic resonance is based on the detection of the response from particular

nuclei when exposed to a magnetic field and electromagnetic radiation. Following absorption,

the resonance frequency is shifted in a characteristic response pattern, according to the

environment of the sample under detection. This approach can be used to determine a range of

intracellular factors such as ATP, ADP, sugar phosphate, and polyphosphate, as well as pH. In

these examples, concentrations of 31P are used to characterize the compounds. This is an off-

line monitoring system that is currently expensive; hence, its use is primarily in the research

field, not in routine production environments.

Artificial Intelligence

The data obtained using the various measuring instruments already discussed are invariably

used to control and optimize the bioprocess being carried out. Recent developments in the field

of artificial intelligence have led to investigations into the use of such systems for improving

bioprocess control, based on the received measurement output signals. This has included the

use of both knowledge-based expert systems (64,65) and neural networks (e.g., 66,67) during

bioprocess operation. A recent report (68) described the successful use of a neural network as a

tool for evaluating the received measurement from an enzyme (penicillin-G amidase) pH-FET

sensor linked to a flow injection system. Undoubtedly, the adaptation of such “intelligent”

systems will develop over the coming years and will play an important role in the precise

control of bioprocess applications.

Conclusion

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Although a diverse range of monitoring equipment is available, only a relatively narrow

range of the more reliable instruments is used routinely in practice. As culture techniques

become more elaborate and high-value-added products are produced, conventional methods

will either prove insufficient or require supplementation with a range of sensors able to directly

monitor key process parameters. Despite a clear demand for new sensors (e.g., lactate,

glutamine, and glutamate for animal cell culture), cell cultivation represents only a modest

market for analytical instrument manufacturers. Hence, while progress is to be expected, it may

be slower than might be wished.

During the last 20 years, considerable developments have been obtained in on-line and in

situ process monitoring. Non-measurable variables are now monitored by observers:state

estimators and software sensors. For process control, mathematical models and hybrid models

are applied. The latter cover mathematical models, literature and live data as well as expert

knowledge. Instead of looking for particular reactions, the network of biochemical reactions is

considered by metabolic flux analysis. The central metabolism of micro-organisms and cells is

well known. Also the biosynthesis paths of secondary metabolites are well known. By metabolic

flux analysis, the quantitative fluxes can be determined. Most of their genes of the metabolite

network are identified and expressed. In spite of the fact that no great improvement of the

productivity could be obtained, because the regulation of the metabolic network is still

unknown. Metabolic engineering will be possible, if the dynamic regulation the metabolic

network is determined. This is the aim the next 20 years.

8. COMPUTER BASED DATA ACQUISITION

Traditionally, measurements are done on stand alone instruments of various types-

oscilloscopes, multi meters, counters etc. However, the need to record the measurements and

process the collected data for visualization has become increasingly important. Data acquisition

involves gathering signals from measurement sources and digitizing the signal for storage,

analysis, and presentation on a personal computer (PC).

There are five components to be considered when building a basic DAQ system (Figure 1):

Transducers and sensors

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Signals

Signal conditioning

DAQ hardware

Driver and application software

Figure 1. Data Acquisition System

Data acquisition is the sampling of the real world to generate data that can be manipulated

by a computer. Sometimes abbreviated DAQ, data acquisition typically involves acquisition of

signals and waveforms and processing the signals to obtain desired information. The

components of data acquisition systems include appropriate sensors that convert any

measurement parameter to an electrical signal, which is acquired by data acquisition hardware.

Acquired data typically is displayed, analyzed, and stored on a PC. This is achieved by using

vendor supplied interactive control software and hardware such as PowerLab, or custom

displays and control can be accomplished using a programming language such as experix,

LabVIEW, Visual Basic, or C. EPICS is used to build large scale data acquisition systems.

How Data is acquired

Transducers convert measurable physical phenomenon into electric signals. Examples of

tranducers include microphones for sound and photocells for light.

Signals may be digital or analog depending on the tranducer used.

Signal conditioning may be necessary if the signal from the tranducer is not suitable for the

DAQ hardware to be used. The signal may be amplified or deamplified, or may require filtering.

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DAQ hardware is what usually interfaces between a the signal and a PC. It could be in the form

of modules that can be connected to the computer's ports (parallel, serial, USB, etc...) or cards

connected to slots (PCI, ISA) in the mother board

Driver Software that usually comes with the DAQ hardware or from other vendors, allows the

operating system to recognize the DAQ hardware and programs to access the signals being read

by the DAQ hardware.

Transducers

Data acquisition begins with the physical phenomenon to be measured. This physical

phenomenon could be the temperature of a room, the intensity of a light source, the pressure

inside a chamber, the force applied to an object, or many other things.

An effective DAQ system can measure all of these different phenomena.

A transducer is a device that converts a physical phenomenon into a measurable electrical

signal, such as voltage or current. The ability of a DAQ system to measure different phenomena

depends on the transducers to convert the physical phenomena into signals measurable by the

DAQ hardware. Transducers are synonymous with sensors in DAQ systems. There are specific

transducers for many different applications, such as measuring temperature, pressure, or fluid

flow. Figure 2 shows a short list of some common transducers and the phenomena they can

measure.

Figure 2. Phenomena and Existing Transducers

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Data Acquisition Systems

Data acquisition systems, as the name implies, are products and/or processes used to

collect information to document or analyze some phenomenon. In the simplest form, a

technician logging the temperature of an oven on a piece of paper is performing data

acquisition. As technology has progressed, this type of process has been simplified and made

more accurate, versatile, and reliable through electronic equipment. Equipment ranges from

simple recorders to sophisticated computer systems. Data acquisition products serve as a focal

point in a system, tying together a wide variety of products, such as sensors that indicate

temperature, flow, level, or pressure.

Searching for the Right Data Acquisition Software

Remember when companies had fully staffed departments dedicated to developing test

systems and programs for you? Those days are gone. To stay competitive in today's job market,

you need to put your own test system together. Choosing the most appropriate data acquisition

software for your application is critical to accomplishing this task.

The first steps toward finding a data acquisition software package that fits your application

are understanding your current and future application requirements and determining the types

of tasks you would like to be able to perform. These usually include one or more of the

following:

Verifying signal connections.

Logging and streaming data to disk.

Monitoring real-time data.

Controlling a test or process.

Analyzing the acquired data.

Generating reports in a variety of graphical formats.

Designing turnkey applications that can be used by lesser-skilled operators.

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10. LABVIEW FOR MEASUREMENT AND DATA ANALYSIS

Thousands of engineers and scientists rely on LabVIEW for a variety of applications: test and

measurement, process control and automation, monitoring and simulation. LabVIEW is the tool

of choice due to its unparalleled connectivity to instruments, powerful data acquisition

capabilities, natural dataflow-based graphical programming interface, scalability, and overall

function completeness. One need that persists regardless of the area of expertise is the fact

that users must manipulate data and measurements, and make decisions based on it.

Users generally start their work by acquiring data into an application or program, because

their tasks typically require interaction with physical processes. In order to extract valuable

information from that data, make decisions on the process, and obtain results, the data needs

to be manipulated and analyzed. Unfortunately, combining analysis with data acquisition and

data presentation is not always a straightforward process. Application software packages

typically address one component of the application, but seldom address all aspects and needs

to get to a complete solution. LabVIEW was designed to address the requirements for a start-

to-finish, fully-integrated solution, so that customers can seamlessly integrate all phases of

their application in a single environment.

Figure 1. LabVIEW Virtual Instrument Block Diagram

While there are many tools that independently address each of the requirements, only

LabVIEW combines all of them with the power of graphical programming and state-of-the-art

data acquisition hardware, using the power of your PC. It is the combination of data acquisition,

data analysis, and presentation of results, that truly maximizes the power of Virtual

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Instrumentation. A virtual instrument consists of an industry-standard computer or workstation

equipped with powerful application software, cost-effective hardware such as plug-in boards,

and driver software, which together perform the functions of traditional instruments. This is

why applications and programs built with LabVIEW are referred to as VIs (virtual instruments).

Computer based Data Acquisition Overview:

This overview will help you to understand the basics of data acquisition on a computer.

Traditionally, measurements are done on stand alone instruments of various types-

oscilloscopes, multi meters, counters etc. However, the need to record the measurements and

process the collected data for visualization has become increasingly important. There are

several ways in which the data can be exchanged between instruments and a computer. Many

instruments have a serial port which can exchange data to and from a computer or another

instrument. Use of GPIB interface board (General purpose Instrumentation Bus) allows

instruments to transfer data in a parallel format and gives each instrument an identity among a

network of instruments. All HP instruments in the EE Undergraduate Laboratories and PCs are

equipped with GPIB interfaces. Another way to measure signals and transfer the data into a

computer is by using a Data Acquisition board. A typical commercial DAQ card contains ADC

and DAC that allows input and output of analog and digital signals in addition to digital

input/output channels. In the following overview we will attempt to explain various aspects of a

DAQ card and DAQ system used in the EE Undergraduate Lab.

Sampling.

The data is acquired by an ADC using a process called sampling. Sampling a analog signal

involves taking a sample of the signal at discrete times. This rate at which the signal is sampled

is known as sampling frequency. The process of sampling generates values of signal at time

interval as shown in following figure.

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The sampling frequency determines the quality of the analog signal that is converted. Higher

sampling frequency achieves better conversion of the analog signals. The minimum sampling

frequency required to represent the signal should at least be twice the maximum frequency of

the analog signal under test (this is called the Nyquist rate). In the following figure an example

of sampling is shown. If the sampling frequency is equal or less then twice the frequency of the

input signal, a signal of lower frequency is generated from such a process (this is called aliasing).

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