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SUMMARY

Our goal is to determine the risks that genetically engineered alfalfa and rhizobia may have on soil microorganisms. This report describes new methodologies, which will enhance our ability to characterize the soil microbial community. We have developed rapid and efficient methods to extract high yields of both DNA and RNA from soil. The DNA was of sufficient purity to be amplified by PCR and used in dot-blot membrane hybridization experiments. The RNA was shown to be free of DNA contamination and amplifiable by RT-PCR In addition, we also developed an efficient method to analyze microbial populations using rDNA genes. A small hypervariable region (helix 49) of the gene coding for the small subunit of rRNA (SSU rDNA) was shown to be a useful indicator of phylogeny. This region was amplified by PCR, concatamerized using T4 DNA ligase, and then cloned into a plasmid vector. This procedure has resulted in a five-fold increase in our ability to describe the soil microbial diversity, because five rDNA sequences can now be obtained from a single DNA sequencing reaction. This short hypervariable region of SSU rDNA provides sufficient information for the taxonomic assignment of most prokaryotes at the kingdom level. Further sequence information can be obtained from organisms that cannot be assigned by a PCR walking technique.

Key words: Risk assessment, soil DNA extraction, rRNA.

INTRODUCTION

Soil is one of our most valuable resources. It regulates global biogeochemical cycles, filters and remediates anthropogenic pollutants, and enables food production (Kennedy and Smith, 1995; Richards, 1987). One particularly significant component of soil, are the microorganisms. Kennedy et al. (1995) described some of the key processes that are controlled by these organisms including the decomposition of organic material and plant residues; increased nutrient availability of P, Mn, Fe, Zn, Cu; nitrogen fixation; biological control of pests; biodegradation of pesticides and pollutants; and improved soil aggregation. Our objective is to determine if the introduction of genetically engineered alfalfa and Rhizobia alter this crucial soil community.

Alfalfa (Medicago sativa L.) is an important hay and forage legume. It is also an excellent plant species to use to for our risk assessment studies since, in almost all situations, alfalfa roots form associations with nitrogen-fixing bacteria. The formation of root nodules containing bacteria should therefore provide an excellent experimental system to investigate the effects of leakage of foreign proteins from roots. Previous studies have shown that root exudates can have a localized affect on soil microorganisms (Rovira, 1956; Rovira, 1991). These results also suggest that leakage of foreign proteins from the roots of transgenic plants could alter the biology of the rhizosphere and potentially affect overall soil fertility.

Unfortunately, our ability to assess such risks has been temporarily hindered by the size and diversity of the soil microbial community. Comparisons of microbial cell numbers by microscopic counts and by enumeration on culture media have shown that less than 1% of the microorganisms can be cultivated (Alexander, 1977). By measuring the kinetics of denaturation and renaturation of bacterial DNA extracted from soil, Torsvik and colleagues were able to estimate that there were at least 4000 different bacterial genomes in a single grain of soil from a Norwegian forest (Torsvik et al., 1990). Moreover, a recent survey of 124 rDNA clones obtained from a Wisconsin pasture soil provided further evidence of the vast microbial diversity in soil since only two duplicate rDNA sequences were found, and none of the sequences had been previously described (Borneman et al., 1996). These results all demonstrate our limited understanding of soil microorganisms. We believe the primary cause of this deficit is the lack of sufficient tools to study this community. This report describes new methods which will enhance our ability to assess the risks that genetically engineered organisms may have on soil microorganisms.

MATERIALS AND METHODS

Recombinant alfalfa and rhizobia. The Sinorhizobium meliloti inoculum strains and alfalfa lines used in this work are described in Bosworth et al. (1996) and Austin et al. (1995). The strains of S. meliloti used in this work were RMBPC-2, RMB7201, and wild-type PC. Both RMBPC-2 and RMB7201 have been shown to significantly increase alfalfa yield compared to strain PC over three years at three field sites in Wisconsin (Scupham et al., 1996).

Alfalfa propagation. Selected transgenic and control lines were clonally propagated, using apical stem cuttings, which were rooted in water prior to establishment in soil. Each cutting had 2-3 nodes and was generally 34 inches in length. Individuals were clonally propagated over the course of six months to give 200-300 mother plants. In order to have a uniform population for the field test, cuttings were taken from these plants 34 months before the planting date. These final cuttings were rooted in water and then maintained in flats of Jiffy mix in growth room conditions (22C, 16h day length, 350 µEm^-2s^-1) during which time they were cut back to a height of 1-2 in twice. Plants were then maintained in an outdoor cold frame for 4-5 weeks. Prior to planting, all of the plants were cut back to give a top height of 1.5-2 in and roots were trimmed to 2-3 in.

Plant inoculation, field planting and design. The four alfalfa lines were inoculated with one of three rhizobial strains (10⁸ CFU/ml) or water (control inoculum) and planted at the University of Wisconsin's Hancock Research Station (GPS: 4406.88N, 8932.06W). The plot (20 m x 102 m) contained 48 rows (sixteen treatments x 4 replicates), each having 62 plants (plants separated by 30 cm). Each treatment contained one plant line and one inoculum strain.

DNA extraction from soil. A new bead beater system (the FastPrep System), developed by BIO 101 (Vista, CA) and Savant (Farmingdale, NY), was modified to facilitate DNA extraction from soil. Eleven hundred µl of lysis buffer (100 mM sodium phosphate, 100 mM EDTA, 50 mM Tris (pH 8), and 10% (v/v) MT Buffer (BIO 101 Cat # 6511-402) and 500 mg of soil were added to a FastDNA tube containing a matrix designed to lyse most cell types (BIO 101 Cat# 6550-215). The mixture was shaken in the FastPrep bead beater for thirty seconds at 5.5 m/sec, centrifuged for 30 seconds at 16,000 x g, and the supernatant collected. The soil pellet was then washed twice by: adding 1 ml of lysis buffer to the soil pellet, bead beating the mixture for ten seconds at 5.5 m/sec, centrifuging for 30 sec at 16,000 x g, and then collecting the supernatant. The subsequent supernatants were extracted twice with an equal volume of chloroform and centrifugation for 2 min at 16,000 x g. The DNA was precipitated by adding 0.6 volumes of isopropanol, inverting 5 times, and incubated for 1 hour at room temperature. The DNA was collected by a 20 min centrifugation at 16,000 x g, washed with 70% ethanol, dried by vacuum, and resuspended in water.

rDNA sequence analysis. Helix 49 (~100 bases) of the rDNA gene was PCR amplified in 100 µl reactions containing: 10 U Pfu polymerase (Stratagene), 10 µl 10x Pfu buffer, 0.5 mg/ml BSA, 0.25 mM dNTPs, ~200 ng soil DNA template, and 500 nM of each 5'-phosphorylated universal rDNA primer (1406F, TGYACACACCTCCCGT; 1492R, TACCTTGTTACGMYTT). The PCR reactions were done using an Idaho Air Thermal Cycler (Idaho Technologies). The DNA was denatured at 94C for 45 sec. Forty cycles of PCR were performed at: 94C for 0 sec, 45C for 15 sec, 72C for 30 sec; followed by a 72C incubation for 10 min. The PCR products were concentrated by ethanol precipitation and resuspended in 15 µl water. Concatamerization of the PCR fragments were done by ligation for 45 minutes at room temperature using T4 DNA ligase (Sambrook et al., 1989). Ligation was terminated min at 65C for 10 min. The concatamerized fragments were cloned into the SmaI site of pBlueScript. The plasmids were transformed into DH5 E. coli and screened by -complementation (Sambrook et al., 1989).

RESULTS

DNA extraction from soil. This report describes a protocol, which produces large quantities of purified DNA from soil. The DNA has been successfully used for both PCR amplifications and dot-blot membrane hybridizations.

rDNA sequence analysis. The hypervariable region (helix 49) of ninety-five rDNA sequences were assembled into a phylogenetic tree (Figure 1). Congruent clades representing the major bacterial taxa were obtained, demonstrating that this small hypervariable region can be used to obtain useful phylogenetic identifications. However, to efficiently examine numerous rDNA sequences, it was necessary to develop a strategy to sequence multiple rDNA molecules in one reaction. This was accomplished by PCR amplifying the helix 49 region from soil DNA, concatamerizing the amplification product by ligation, and then cloning the larger concatamerized DNA fragments into a plasmid vector. We currently sequence clones, which contain at least five rDNA molecules (helix 49), because 500-600 bases are the present limit of a plasmid, cycle sequencing reaction.

DNA has been extracted from soils collected from all replicates of all treatments. The concatamerization of the amplified hypervariable region is successful and clones are now being sequenced to determine the variability of organisms in each treatment.

DISCUSSION

To determine the risks that genetically engineered alfalfa or rhizobia may have on the soil microbial community, we need to be able to efficiently and accurately measure microbial population changes. Towards this goal, we have developed three new methodologies.

This lab has previously demonstrated a method that can efficiently extract purified DNA from soil in twenty-five minutes (Borneman et al., 1996). This protocol has given us the ability to efficiently extract DNA from hundreds of soil samples, collected from the risk assessment experiment over the last two growing seasons. The new soil DNA extraction method, described here, was developed to obtain significantly higher DNA yields than our previous protocol. This method has proven to be useful for experiments such as dot-blot hybridizations, where the target gene is present in low numbers.

We have also demonstrated that a small hypervariable region, helix 49, of the rDNA gene can be used to obtain useful phylogenetic identifications. Thus, our ability to identify soil microorganisms has increased considerably, because we can now analyze five rDNA sequences with one DNA sequencing reaction. Since the most accurate methods of characterizing uncultured soil microbes use rRNA analyses, we believe this advance is significant. Other methods, such as fatty acid methyl esters (FAMEs) and denaturing gradient gel electrophoresis, can rapidly assess community-level population changes. However, they do not allow the precise phylogenetic identifications, permitted by rRNA sequence analyses.

Finally, we have developed a rapid method of extracting purified RNA from soil (Borneman and Triplett, 1996). The procedure can be completed in about 1 hour and produces RNA that can be amplified by RT-PCR. Because of the numerous and previously described biases of PCR amplification, the use of RNA will certainly become an important tool for microbial ecology and risk assessments. In addition, RNA can also be used to determine the distribution of the actively growing microorganisms, because the growth rate of many organisms are correlated to either their RNA content or to their RNA:DNA ratio. Moreover, the ability to extract RNA from soil permits the monitoring of genes involved in pollution degradation, by measuring their mRNA levels.

ACKNOWLEDGMENTS

This work was supported by funds from USDA NRI grant no. 94-37305-0767, USDA Risk Assessment Program grant no. 94-33120-0433, USEPA Risk Assessment cooperative agreement no. CR-822882-01-0 and Hatch project no. 5201 from the University of Wisconsin-Madison, College of Agricultural and Life Sciences.

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Figure 1. Phylogenetic analysis of 95 partial (1406-1492) small-subunit rRNA sequences. The rRNA sequences were aligned by PILEUP (GCG). A pair-wise distance matrix and phylogenetic tree were calculated by the Jukes-Cantor (Jukes and Cantor, 1969) and Neighbor-Joining (Saitou and Nei, 1987) algorithms. Names of the major taxa are shown in boldface.