As the field of rapid methods and automation has developed, the boundaries between instrumentation and diagnostic tests have begun to merge. Instrumentation is now playing an important function in improving the efficiency of diagnostic kit systems, and the trend will continue. The following discussions are mainly on instrumentation measuring signals related to microbial growth.
Instruments can be used to monitor changes in a population such as ATP levels, levels of specific enzymes, pH, electrical impedance, conductance and capacitance, generation of heat, radioactivity, carbon dioxide, and others. It is important to note that for the information to be useful, these parameters must be related to viable cell counts of the same sample series. In general, the larger the number of viable cells in the sample, the shorter the detection time of these systems. A scattergram is then plotted and used for further comparison of unknown samples. The assumption is that as the number of microorganisms increases in the sample, these physical, biophysical, and biochemical events will also increase accordingly. When a sample has 5 or 6 log organisms/ml, detection time can be achieved in about 4 hours from the time the sample is placed in the instrument.
All living things utilize ATP. In the presence of a firefly enzyme system (luciferase and luciferin system), oxygen, and magnesium ions, ATP will facilitate the reaction to generate light. The amount of light generated by this reaction is proportional to the amount of ATP in the sample. Thus, the light units can be used to estimate the biomass of cells in a sample. The light emitted by this process can be monitored by a sensitive and automated fluorimeter. Some instruments can detect as little as 100 to 1000 femtograms of ATP (1 femtogram, 1 fg, is —15 log g). The amount of ATP in one colony-forming unit has been reported as 0.47 fg with a range of 0.22 to 1.03 fg. Using this principle, many researchers have used ATP to estimate the number of microbial cells in solid and liquid foods.
Initially, scientists attempted to use ATP to estimate the total viable cell count in foods. The results are inconsistent due to the fact that (1) different microorganisms have different amounts of ATP per cell (e.g., a yeast cell can have 100 times more ATP than a bacterial cell); (2) even for the same organism, the amount of ATP per cell is different at different growth stages; and (3) background ATP from other biomass such as blood and biological fluids in the foods interferes with the target bacterial ATP. Only after much research and development will scientists be able to separate nonmicrobial ATP from micro-bial ATP and obtain reasonable accuracy in relating ATP to viable cell counts in foods. Since obtaining an ATP reading takes only a few minutes, the potential of exploring these methods further exists. To date, ATP has not been applied much to estimation of viable cell counts in food microbiology laboratories.
From another viewpoint, the presence of ATP in certain foods such as wine is undesirable regardless of the source. Thus monitoring ATP can be a useful tool for quality assurance in the winery.
There has been a paradigm shift in the field of ATP detection in recent years. Instead of detecting ATP of microorganisms, systems are now designed to detect ATP from any source for hygiene monitoring. The idea is that a dirty food processing environment will have a high ATP level, and a properly cleansed environment will have a low ATP level regardless of what contributed to the ATP in these environments. Once this concept is accepted by the food industry, there will be an explosion of ATP systems being used in the food industry for hygiene monitoring. In all of these systems, the key is to be able to obtain an ATP reading in the form of relative light units (RLUs) and to relate these units to the cleanliness of food processing surfaces. The scale of RLU readings obtained from different surfaces in food factories encompasses acceptable, marginal, and unacceptable levels. Since there is no standard as to what constitutes an absolutely acceptable ATP level in any given environment, these RLUs are quite arbitrary. In general, a dirty environment will have high RLUs, and after proper cleaning the RLUs will decrease. Besides the sensitivity of the instruments, an analyst should consider the following attributes in selecting a particular system: simplicity of operation, compactness of the unit, computer adaptability, cost of the unit, support from the company, and documentation of usefulness of the system.
Besides the above mentioned issues, Dreibelbis  in a study of five ATP instruments for hygiene monitoring of a food plant considered the following attributes to be important as selection criteria of the systems: the ability of the technicians in the microbiological laboratory to use the ATP bioluminescence hygiene monitoring system without supervision, the reputation of the ATP system in the industry, and the quality of services received from the manufacturer during the evaluation of the product.
Currently the following ATP instruments are available: Lumac (Landgraaf, the Netherlands), BioTrace (Plainsboro, NJ), Lightning (BioControl, Bellevue, WA), Hy-Lite (EM Science, Darmstadt, Germany), Charm 4000 (Charm Sciences, Malden, MA), Celsis system SURE (Cambridge, U.K.), Zylux (Maryville, TN), Profile 1 (New Horizon, Columbia, MD), and others.
As microorganisms grow and metabolize nutrients, large molecules are metabolized to smaller molecules in a liquid system and cause a change in electrical conductivity and resistance in the liquid as well as at the interface of electrodes. These changes can be expressed as impedance, conductance, and capacitance changes. When a population of cells reaches about 5 log CFU/ml, it will cause a change in these parameters. Thus, when a food has a large initial population, the time to make this change will be shorter than with a food that has a smaller initial population. The detection time of the test sample, the time when the curve accelerates upward from the baseline, is inversely proportional to the initial concentration of microorganisms in the food. In order to use these methods, a series of standard curves must be constructed by making viable cell counts in food with different initial concentrations of cells and then measuring the resultant detection time. A scattergram can then be plotted. Thereafter, in the same food system, the number of the initial population of the food can be estimated by the detection time on the scattergram.
The Bactometer (bioMerieux, Hazelwood, MO) has been in use for many years to measure impedance changes by microorganisms in foods, water, cosmetics, and similar products. Samples are placed in the wells of a 16-well module which is then plugged into the incubator to start the monitoring sequence. As the cells reach the critical number (5 to 6 log/ml), the change in impedance increases sharply, and the monitor screen shows a slope similar to the log phase of a growth curve. The detection time can then be obtained to determine the initial population of the sample. If one sets a cut-off point of 6 log CFU/g of food for acceptance or rejection of the product, and the detection time is 4 hours ± 15 minutes, then one can use the detection time as a criterion for quality assurance of the product. Food that exhibits no change of impedance curve after more than 4 hours and 15 minutes in the instrument is acceptable while food that exhibits a change of impedance curve before 3 hours and 45 minutes will not be acceptable. For convenience the instrument is designed such that the sample bar displayed on the screen for a food will flash red for an unacceptable sample, green if acceptable, and yellow for marginally acceptable. The rapid automated bacterial impedance technique (RABIT) is a similar system, marketed by Bioscience International (Bethesda,
MD) for monitoring microbial activities in food and beverages. Instead of the 16-well module used in the Bactometer, individual tubes containing electrodes are used to house the food samples.
The Malthus system (Crawley, U.K.) uses conductance changes of the fluid to indicate microbial growth; it generates conductance curves similar to impedance curves used in the Bactometer. The Malthus system uses individual tubes for food samples. Water heated to the desired temperature (e.g., 35°C) is used as the temperature control instead of heated air as with the previous two systems. All these systems have been evaluated by various scientists in the past 10 to 15 years with satisfactory results. All have their advantages and disadvantages depending on the type of food being analyzed. These systems can also be used to monitor targeted groups of organisms such as coliform or yeast and mold using specially designed culture media. In fact, the Malthus system has a salmonella detection protocol that was approved by AOAC International.
BacT/Alert Microbial Detection System (Organon Teknika, Durham, NC) utilizes colorimetric detection of carbon dioxide production by microorganisms in a liquid system using sophisticated computer algorithms and instrumentation. Food samples are diluted and placed in special bottles with appropriate nutrients for growth of microorganisms and production of carbon dioxide. At the bottom of the bottle there is a sensor that is responsive to the amount of carbon dioxide in the liquid. When a critical amount of the gas is produced, the sensor changes from dark green to yellow, and this change is detected by reflectance colorimetry automatically. The units can accommodate 120 or 240 culture bottles. Detection time of a typical culture of E. coli is about 6 to 8 hours.
BioSys (BioSys, Inc., Ann Arbor, MI) utilizes color changes of media (designed for specific target organisms) during the growth of cultures to detect and estimate organisms in foods and liquid systems. The uniqueness of the system is that the color compounds developed during microbial growth are diffused into an agar column situated at the bottom of the unit, and the changes are measured automatically without the interference of food particles in the chamber. Depending on the initial microbial load in the food, microbial information can be obtained during the same production shift that the sample was taken in a food processing operation. The system is easy to use and can accommodate 32 samples for one incubation temperature or 128 samples for 4 independent incubation temperatures in different models. The system is designed for bioburden testing and HACCP (hazard analysis critical control points) control and can test for indirect total viable cell, coliform, E. coli, yeast, mold, and lactic acid bacteria counts in swab samples and environmental samples.
Basically, any type of instrument that can continuously and automatically monitor turbidity and color changes of a liquid in the presence of microbial growth can be used for rapid detection of the presence of microorganisms. There will definitely be more systems of this nature on the market in years to come.
Was this article helpful?