Final Report for GNC04-030
The objective of this study was to compare sustainable agricultural management practices using bacterial diversity as the measure of soil health. The original plan was to create a melting and re-association profile for the bacterial community from each soil type maintained under different agronomic management practices. This procedure was developed by Torsvik (1990) and requires a large amount of DNA (i.e. a total amount of 600 µg DNA in a 1.5 ml sample) to create the profiles. However the amount of DNA obtained from a 200 g soil sample by a fractionated centrifugation method yielded a much lower amount of DNA than is required for this specific analysis. Multiple combined DNA extractions also yielded insufficient amounts of DNA to follow the Torsvik procedure. After attempts to maximize the yields became unsuccessful, we used a polymerase chain reaction (PCR) based method to create Denatured Gradient Gel Electrophoresis (DGGE) profiles to compare bacterial diversity in soils maintained under different management practices. PCR-DGGE methods have been adapted from the medical field into soil science to study microbial community analysis (Muyzer et. al. 1993). Initially after being used for simpler ecosystems, PCR-DGGE has been applied to characterize the microbial diversity in more complex terrestrial ecosystems (Duineveld et al., 1998; Heuer et. al., 1997; Jensen et al., 1998; Nakatsu et. al., 2000).
The results of this study indicated that management practices greatly influence bacterial diversity in a particular ecosystem. Among the different soils, no-till soil had the most diverse dominant population of bacteria as evident from the highest number of distinct bands observed in the DGGE profiles. Other management practices such as organic farming and crop rotation resulted in less bacterial diversity. Since, no-till soil had the most number of distinct DGGE bands compared to any other soil, we conclude that tillage and especially excessive tillage, is a principal factor in reducing bacterial diversity. By extension, we also conclude that no-till soil has the widest diversity of soil biochemical functions compared to soils managed by other means. Organic farming practices that maintain long rotations with crops that would not require tillage, such as a legume hay crop, would also be predicted to have greater bacterial and functional diversity than crop rotations that require tillage every season.
Soil health can be characterized by the ability of a particular soil to perform a range of biochemical processes required for that system to sustain long-term agricultural productivity with minimal environmental impact (Arias et. al., 2005). Several studies have reported that soil microbial diversity is a key component in maintaining the long-term sustainability of agroecosystems (Garbeva et. al., 2004; Janvier et. al., 2007). Bacteria constitute a major component of the soil microbial pool that performs a host of soil biogeochemical functions and it is well known that bacterial diversity influences overall ecosystem function and health.
Soil health has been measured in various ways including the use of indices such as plant productivity, soil nutrient concentrations, soil organic carbon content, and the concentration of various chemical and biochemical components such as pesticides and microbial growth factors. Increasingly soil is being viewed as a living entity containing a mixture of inorganic and organic materials that are constantly being influenced and altered by soil animals, fungi and bacteria. Consequently, emphasis is being applied to the use of biological indicators such as enzyme activity, microbial biomass, and microbial respiration rate to determine soil health. Therefore it is appropriate to assess soil health using a biological component such as bacteria or, more precisely, bacterial diversity in a particular ecosystem.
The objective of this project was to assess soil health and sustainability of agro-ecosystems using bacterial diversity as an indicator.
Soil Sampling and Processing
In order to compare the different soils and management practices, we selected eight different sites from which to obtain soil samples. These included two organic farm soils and six other soils. All of these soils came from fields located either on the Ohio Agricultural Research and Development Center (OARDC) near Wooster or on private farms including the Spray and Moomaw farms.
Besides a contrast in organic versus inorganic management systems, the other major variable studied was tillage with the tillage treatments on the OARDC VanDoren/Triplett plots being maintained for 45 years at the time of sampling. The crop being grown at each site at the time of sampling was corn with the exception of the Moomaw Farm II site where the crop was potato.
Composite soil samples (0-5 cm) were collected from each site using a shovel. The samples were collected in Ziploc bags, labeled and transported from the field in coolers and stored at 4o C until they were processed. Two replicate samples were obtained from each site during the last week of August. After being transported to the laboratory, soil samples were processed by sieving through a 2 mm sieve to remove large plant debris and roots.
DNA extraction and PCR
DNA extraction and purification was carried out using the Megaprep Ultra Soil DNA Kit (MoBio Laoratories, CA). Since the effectiveness of the technique will depend on the successful extraction of all bacterial DNA, we used 10 g soil sample instead of smaller quantities typically used for PCR based methods. Purity of extracted DNA was measured and quantified using a Nanodrop 1000 Spectrophotometer (Thermo Scientific, Wilmington, DE).
A polymerase chain reaction (PCR) was conducted using a set of universal bacterial primers – PRBA338F and PRUN518R primers that amplify the 338 to 518 region of the 16s rDNA of bacteria. For PCR reactions 100 µl of final mixture volume was used containing 1 µM of each primer, 0.2 mM dNTPs, 0.5% BSA, 1X PCR buffer, and 2.5 units of Taq polymerase (Promega, Madison, WI). The PCR reactions were performed using an automated thermal cycler (PTC-100, MJ Research, Waltham, MA). The temperature program for the PCR reaction started with a 94ºC denaturation step for 9 min. Then 30 cycles were conducted in which each cycle included a denaturing step of 94ºC for 30 s, an annealing step of 55ºC for 30 s and an extension step of 72ºC for 30 s. The last step in the PCR program was a final extension at 72ºC for 7 min. The samples were then held at 4ºC before being stored in a freezer at -20ºC.
A BioRad DCode apparatus (BioRad, Hercules, CA) was used to conduct the denaturing gradient gel electrophoresis (DGGE) analysis. An 8% (w/v) polyacrylamide gel, with denaturing gradients ranging from 15 – 55% and 35 – 65%, were used for separation of PCR products obtained as described above. The amplified DNA was analyzed using DGGE electrophoresis using a 0.5X TAE buffer (20 mM tris-Cl, 10 mM acetate, 0.5 mM Na2EDTA) maintained at 60ºC. Gels were then stained with ethidium bromide and visualized on a UV transilluminator and photographed (Gel Logic Unit, Kodak, California, USA).
Bacterial Richness Index
A diversity richness index was initially calculated using the DGGE banding patterns to quantify the different soils numerically. The arithmetic mean for the number of bands for each soil was used to calculate this richness index. A maximum value of 1.00 was assigned to the OARDC VanDoren/Triplett Plot II soil due to the maximum number of bands for this soil. Values for other soils were calculated as a simple ratio of bands in the gel for a treatment divided by the number of bands in the OARDC VanDoren/Triplett Plot II soil.
Where, NQis the number of bands in the query soil, NT is the number of bands in the test soil and ND is the number of bands common to both soils.
[To view the tables and figures associated with this report, contact the Coordinator].
The loading of DNA onto the gels resulted in many bands, some of which were often only faintly observed. For our analyses, bands that could be clearly discerned as being distinct and separated from other bands, even if faint, were marked. The results indicate that among all the different soils used in the study, the no-till soil had the highest number of distinguishable bands in the gel. While the two replicates of the no-till soils had 19 and 18 discernible bands, the two replicate organic soil samples from the Spray farm had only 7 bands each. The Badger Farm I organic soil had a higher number of bands than the Spray Farm’s organic soil but less than the no-till soils. The Badger Farm I organic soils had more bands compared to the Badger Farm II inorganic soils. The Badger Farm I organic soil, the OARDC VanDoren/Triplett inorganic chisel till soil, and the Moomaw Farm II potato soil all had a similar number of bands. We had anticipated that the OARDC VanDoren/Triplett inorganic plow till soil would have the least number of distinguishable bands. However, this was not the case as we were able to discern 12 and 11 bands in these two replicate soil samples.
Another DGGE profile with a different denaturing gradient (35-65%) was used to further resolve the PCR products. The DGGE profile thus obtained also confirmed that the no-till soils had more bands compared to other soils used in this study (data not shown). Thus we can safely conclude that no-till soils had the highest number of dominant bacteria among the different soils used in this study.
The phylotype richness (or band richness) was calculated for each soil and was normalized in comparison to the OARDC VanDoren/Triplett Plot II soil that was assigned an index value of 1.00 (Table 2). In this evaluation of richness, the higher the value, the more diverse in terms of number of dominant species that were in the soil sample. Thus, the OARDC VanDoren/Triplett Plot II soil had the greatest diversity of domiant bacterial species and the Spray Farm organic soil the least. Many management factors can affect bacterial diversity and a more direct comparison of organic and inorganic farming systems is the comparison of diversity for the OARDC Badger Farm I soil and the OARDC Badger Farm II soil. This comparison indicates that the organic crop production system where corn is being grown supports greater bacterial diversity than a similar corn crop grown using inorganic management systems. The one soil that was collected from where potatoes instead of corn was being grown, i.e. the Moomaw Farm II soil, had a richness index identical to the soil where the chisel till treatment had been maintained for growing corn on the OARDC VanDoren/Triplett Plot I.
The Dice similarity index results were calculated based on the number of dominant bands in the DGGE gel. Since no-till soil had the most number of bands, other soils were compared using no-till soil as the test soil. The values for all other soils in this study, with the exception of the OARDC VanDoren/Triplett plot III inorganic plow till soil, had Dice similarity index values between 0.42-0.55. The long-term OARDC VanDoren/Tripplett plot III inorganic plow till soil had the lowest Dice similarity index value, being only 0.19. It is clear that the Dice similarity index assigned a much lower diversity value to the plow till soil from the long-term OARDC VanDoren/Triplett plot III than did the simple ratio or band richness index method. We believe that the Dice similarity index is a more robust way of calculating bacterial diversity.
The results from the Dice similarity index also show that tillage greatly impacts the species distribution and abundance as evident from the least similarity between the no-till plot and the plow till plot. Most likely this is due to the effect of colonizers that are more suited after tillage or disturbance rather than persisters that are more dominant in undisturbed ecosystems.
Organic agricultural soils are widely believed “better” when compared to non-organic agricultural soils. However, this study demonstrated that if a non-organic no-till crop production system is continuously practiced, it can have higher bacterial diversity than an organic system where tillage is required to control weeds and to prepare the seedbed. It must be noted, however, that in this study the no-till system had been maintained for 45 years, a condition not typical of most no-till soils. Since species diversity and richness have been linked to better ecosystem functioning, a higher diversity of bacteria for the no-till soil may be interpreted as an indication of better soil health for this soil compared to the other soils studied.
Although a systematic comparison was not done to evaluate the effect of cultural practices such as crop rotation, tillage, or type of crop grown the results of this particular study revealed that the most important criterion for bacterial diversity in soil is tillage (i.e. soil disturbance).
Arias, M. Enriqueta; J. A. Gonzalez-Perez, F. J. Gonzalez-Vila, and A. S. Ball. 2005. Soil health -a new challenge for microbiologists and chemists. International Microbiology. 8:13-21.
Duineveld, B.M., A.S. Rosado, J.D. van Elsas, and J.A. van Veen. 1998. Analysis of the dynamics of bacterial communities in the rhizosphere of the chrysanthemum via denaturing gradient gel electrophoresis and substrate utilization patterns. Appl. Environ. Microbiol. 64:4950–4957.
Heuer, H., M. Krsek, P. Baker, K. Smalla, and E.M.H. Wellington. 1997. Analysis of actinomycete communities by specific amplification of genes encoding 16S rRNA and gel electrophoretic separation in denaturing gradients. Appl. Environ. Microbiol. 63:3233–3241.
Garbeva, P., J. A. VanVeen, and J. D. Van Elsas. 2004. Microbial diversity in soil: selection of microbial populations by plant and soil type and implications for soil suppressiveness. Annu Rev of Phytopathol 42:243–270
Janvier C., F. Villeneuve, C. Alabouvette, V. Edel-Hermann, T. Mateille, and C. Steinberg. 2007. Soil health through soil disease suppression: which strategy from descriptors to indicators? Soil Biol Biochem 39:1–23.
Jensen, S., L. Ovreas, F.L. Daae, and V. Torsvik. 1998. Diversity in methane enrichments from agricultural soil revealed by DGGE separation of PCR amplified 16S rDNA fragments. FEMS Microbiol. Ecol. 26:17–26.
Muyzer, G., E.C. de Waal, and A.G. Uitterlinden. 1993. Profiling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplified genes coding for 16S rRNA. Appl. Environ. Microbiol. 59:695–700.
Nakatsu, C. H., V. Torsvik, and L. Øvrea°s. 2000. Soil Community Analysis Using DGGE of 16s rDNA Polymerase Chain Reaction Products. Soil Sci. Soc. Am. J. 64:1382–1388
Sigler, W. V., C. Miniaci, and J. Zeyer. 2004. Electrophoresis time impacts the denaturing gradient gel electrophoresis-based assessment of bacterial community structure. J Micro. Methods. 57:17-22.
Torsvik V, J. Goksoyr and F. L. Daae. 1990. High Diversity in DNA of soil bacteria. Appl. Environ. Microbiol. 56:782-787.
Educational & Outreach Activities
The findings of this study will be presented at the Soil Science Society of America meeting, 2008, which is a national meeting of the crop, soils and agronomy professionals that will be held in Houston, Texas from October 4 – 8, 2008. We also plan to share these results with the Agroecosystem Management Program and the Organic Food and Farming Education and Research Program of The Ohio State University, although no specific time has yet been set for this to occur. These two programs at The Ohio State University have close contacts with stakeholders, producers and scientific community of the organic farming community in this region of Ohio and the United States. In addition, we plant to publish this data, along with some additional data we have collected that was not part of the SARE project, as a paper in a peer-reviewed journal directed towards the appropriate audience.
This study provides a snap shot of diversity at a specific time of the year and specific time in the growth cycle of a corn crop. All of the samples were collected in late August during the period of rapid grain fill. An assessment of diversity at other times of the year, for example at planting, during seedling growth, during the rapid vegetative growth phase of the corn plant, at harvest, and then after harvest after residues have been deposited back onto the soil could all yield different results. We believe that the results of this study, however, do have value because they show how one variable, tillage, plays an important role in bacterial diversity in soil, even several months after the tillage treatment had been applied. Of course in the no-till treatment, it has been years since the soil has been disturbed other than that due to the planter cutting a slot in the soil for seed drop.
The method used to measure bacterial diversity in this study only measures the diversity of the most abundant bacterial species. Two soils with equal diversity of the dominant or most abundant bacterial species could still differ quite widely in diversity of other species that are found in lower numbers in a soil. However, the relevance of these less abundant bacterial species, in terms of creating a more sustainable and functionally robust soil, is more difficult to assess and often remain unknown.
We had hoped that we could develop a rapid and inexpensive method to assess bacterial diversity in soils collected from fields under different management systems, including organic farming systems. Such a method would have provided a valuable tool for organic researchers and producers who understand that bacterial diversity is a key component of a healthy and sustainable system. A rapid and inexpensive method would also help assess whether adopting various management practices are beneficial in terms of creating and maintaining bacterial diversity. However, we found that the method proposed by Torsvik (1990) was not sufficiently sensitive enough because it requires large amounts of DNA. We were unable to improve on the method so that much smaller amounts of DNA would suffice. However, we did not want to return to SARE without any results at all and the failure of achieving our original research objective led us to the use of the Denaturing Gradient Gel Electrophoresis (DGGE) method to assess bacterial diversity. This method is quite mature and has become quite widely used to assess bacterial communities. It suffers, however, from being limited to assessing bacterial diversity of only the most abundant bacterial species in a soil and cannot be used to assess the total diversity, as is the case for the method of Torsvik (1990). We still believe that that a quantitative method of separating agricultural practices, based on bacterial community diversity, will be an excellent biological approach to assess overall soil health and sustainability of crop production systems.
No economic analysis was conducted for this project.
This project was not meant to develop a specific management practice that could be adopted by farmers. Instead, the goal was to develop a tool that could be used to assess the relative impacts of various management practices on total bacterial diversity.
Areas needing additional study
Our study showed that tillage was the biggest impediment towards the development of a diverse population of bacteria in soil. Tillage is also known to reduce soil organic carbon by promoting decomposition of residues and increasing CO2 in the atmosphere where it is partially responsible for global warming. This suggests that resources should be made available to develop a crop production system that combines organic farming practices with no-tillage. This would lead to better nutrient cycling, improved soil health, sustainable agricultural production and reduced global warming.
Combining no-tillage with organic farming practices obviously introduces many challenges with probably the greatest being weed control. Research is needed to evaluate organic herbicides, cover crops and combinations of these two variables as means of controlling weeds in an organic no-till system.