EcoPlate™ - Biolog | Microbial Community Analysis

Microbial communities provide useful data for studying both applied and Basic environmental events. Microorganisms are present in virtually all environments and are typically the first organisms to react to chemical and physical changes in the environment. Because they are at the bottom of the food chain, changes in microbial communities are often a precursor to changes in the health and viability of the environment as a whole.

The Biolog EcoPlate™ (Figure 1) was created specifically for community analysis and microbial ecological studies. It was originally designed at the request of a group of microbiol ecologists that wanted more replicates than the Biolog GN MicroPlate™ provided.

Community analysis using Biolog MicroPlates was originally described in 1991 by J. Garland and A. Mills.¹ Researchers found that by inoculating Biolog GN MicroPlates with a mixed culture of microorganisms and measuring the community fingerprint over time, they could ascertain characteristics about that community of microbes. This approach called community–level physiological profiling has been demonstrated to be effective at distinguishing spatial and temporal changes in microbial communities. In applied ecological research, the MicroPlates are used as both an assay of the stability of a normal population and to detect and assess changes based upon the variable introduced.

Studies have been done in all areas of environmental science and have demonstrated the fundamental utility of Biolog MicroPlates for this application. Studies demonstrating the utility of Biolog MicroPlates in detecting population change have been done in soil, water, wastewater, activated sludge, compost, and industrial waste. The utility of the information has been documented in over 500 publications using Biolog technology to analyze microbial communities. A bibliography of publications is posted on the Biolog website (www.biolog.com).

A1	A2	A3	A4	A1	A2	A3	A4	A1	A2	A3	A4
Water	β-Methyl-D Glucoside	D- Galactonic Acid γ-Lactone	L-Arginine	Water	β-Methyl-D Glucoside	D-Galactonic Acid γ-Lactone	L-Arginine	Water	β-Methyl-D Glucoside	D-Galactonic Acid γ-Lactone	L-Arginine
B1	B2	B3	B4	B1	B2	B3	B4	B1	B2	B3	B4
Pyruvic Acid Methyl Ester	D-Xylose	D-Galacturonic Acid	L- Asparagine	Pyruvic Acid Methyl Ester	D-Xylose	D-Galacturonic Acid	L-Asparagine	Pyruvic Acid Methyl Ester	D-Xylose	D-Galacturonic Acid	L-Asparagine
C1	C2	C3	C4	C1	C2	C3	C4	C1	C2	C3	C4
Tween 40	i- Erythritol	2- Hydroxy Benzoic Acid	L-Phenylalanine	Tween 40	i- Erythritol	2- Hydroxy Benzoic Acid	L-Phenylalanine	Tween 40	i- Erythritol	2- Hydroxy Benzoic Acid	L-Phenylalanine
D1	D2	D3	D4	D1	D2	D3	D4	D1	D2	D3	D4
Tween 80	D-Mannitol	4- Hydroxy Benzoic Acid	L-Serine	Tween 80	D-Mannitol	4- Hydroxy Benzoic Acid	L-Serine	Tween 80	D-Mannitol	4- Hydroxy Benzoic Acid	L-Serine
F1	F2	F3	F4	F1	F2	F3	F4	F1	F2	F3	F4
Glycogen	D- Glucosaminic Acid	Itaconic Acid	Glycyl-L- Glutamic Acid	Glycogen	D- Glucosaminic Acid	Itaconic Acid	Glycyl-L- Glutamic Acid	Glycogen	D- Glucosaminic Acid	Itaconic Acid	Glycyl-L- Glutamic Acid
G1	G2	G3	G4	G1	G2	G3	G4	G1	G2	G3	G4
D-Cellobiose	Glucose-1- Phosphate	α-Ketobutyric Acid	Phenylethylamine	D-Cellobiose	Glucose-1- Phosphate	α-Ketobutyric Acid	Phenylethylamine	D-Cellobiose	Glucose-1- Phosphate	α-Ketobutyric Acid	Phenylethylamine
H1	H2	H3	H4	H1	H2	H3	H4	H1	H2	H3	H4
α-D-Lactose	D,L-α-Glycerol Phosphate	D-Malic Acid	Putrescine	α-D-Lactose	D,L-α-Glycerol Phosphate	D-Malic Acid	Putrescine	α-D-Lactose	D,L-α-Glycerol Phosphate	D-Malic Acid	Putrescine

Figure 1. Carbon Sources in EcoPlate

EcoPlate™ - Biolog

The Biolog EcoPlate contains 31 of the most useful carbon sources for soil community analysis. These 31 carbon sources are repeated 3 times to give the scientist more replicates of the data. Communities of organisms will give a characteristic reaction pattern called a metabolic fingerprint. These fingerprint reaction patterns rapidly and easily provide a vast amount of information from a single Biolog MicroPlate.

The community reaction patterns are typically analyzed at defined time intervals over 2 to 5 days. The changes in the pattern are compared and analyzed using statistical analysis software. The most popular method of analysis of the data is via Principle Components Analysis (PCA) of average well color development (AWCD) data, but alternative methods may also offer advantages²⁻⁷. The changes observed in the fingerprint pattern provide key data about the microbial population changes over time.

Biolog MicroPlates have been compared to other methods, such as phospholipid fatty-acid analysis, for monitoring community and ecological changes. The MicroPlates were found to be more sensitive to changes in the environment8. Biolog MicroPlates were also indicated as more sensitive to changes in major determinants such as temperature and water. Similar analyses have been performed using the Biolog GN and GN2 MicroPlates. For some applications these MicroPlates may be preferable to the EcoPlate. The individual application will dictate which MicroPlate is best suited for the community or ecological analysis.

Typical Procedure ²

Step 1: Environmental samples are inoculated directly into Biolog MicroPlates either as aqueous samples or after suspension (soil, sludge, sediment, etc…).

Step 2: The Biolog MicroPlates are incubated and analyzed at defined time intervals.

Step 3: The community-level physiological profile is assessed for key characteristics:

•	Pattern development (similarity)
•	Rate of color change in each well
•	Richness of well response (diversity)

Formation of purple color occurs when the microbes can utilize the carbon source and begin to respire. The respiration of the cells in the community reduces a tetrazolium dye that is included with the carbon source.

The reaction patterns are most effectively analyzed with a microplate reader, using the Biolog MicroLog™3E or MicroStation™ Systems. However, any good microplate reader can be used to provide optical density (OD₅₉₀) values.

Statistical analysis of the data is typically performed using standard software packages. Some researchers have found that PCA provides greater resolution than other methods of statistical analysis9.

References

[1]	Classification and characterization of heterotrophic microbial communities on the basis of patterns of community level sole-carbon-source utilization. J.L. Garland, A.L. Mills, Applied and Environmental Microbiology, 1991, v.57, p. 2351-2359.
[2]	Analysis and interpretation of community-level physiological profiles in microbial ecology. J.L. Garland, Federation of European Microbiological Societies, Microbiology Ecology, 1997, v. 24, p289- 300.
[3]	Community analysis by Biolog: curve integration for statistical analysis of activated sludge microbial habitats, J.B. Guckert, G.J. Carr, T.D. Johnson, B.G. Hamm, D.H. Davidson, Y. Kumagai, Journal of Microbiological Methods, 1996, v. 27:2-3, p. 183- 187.
[4]	Statistical analysis of the time-course of Biolog substrate utilization. C.A. Hackett, B.S. Griffiths, Journal of Microbiological Methods, 1997, v. 30, p. 63-69.
[5]	Statistical comparisons of community catabolic profiles. E. Glimm, H. Heuer, B. Engelen, K. Smalla, H. Backhaus, Journal of Microbiological Methods, 1997, v. 30, p. 71-80.
[6]	Application of multivariate analysis of variance and related techniques in soil studies with substrate utilization tests, W. Hitzl, M. Henrich, M. Kessel, and H. Insam, Journal of Microbiological Methods, 1997, v. 30, p. 81-89.
[7]	Using the Gini coefficient with BIOLOG substrate utilization data to provide an alternative quantitative measure for comparing bacterial soil communities, B.D. Harch, R.L. Correll, W. Meech, C.A. Kirkby, and C.E. Pankhurst, Journal of Microbiological Methods, 1997, v. 30, p. 91-101.
[8]	Defining soil quality in terms of microbial community structure. M. Firestone, T. Balser, D. Herman, Annual Reports of Research Projects, UC Berkeley, 1998.
[9]	Defining soil quality in terms of microbial community structure. M. Firestone, T. Balser, D. Herman, Annual Reports of Research Projects, UC Berkeley, 1997.

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