We will develop a cheap, rapid tool for measuring the size of soybean inoculant populations in field soils in North Dakota. In the same way as a soil test can inform fertilizer decisions, we hope to give growers the ability to predict whether or not soybean fields require re-inoculating in the spring prior to planting. To develop a tool with this capability we plan to utilize a breakthrough technology called digital PCR. Once we have a digital PCR assay for inoculant populations in the soil, we will apply it to soils in Western North Dakota facing conditions that are challenging to inoculant strain survival. By doing this we will validate the tool using real world conditions, and gain valuable agronomy information regarding the necessity to reinoculate soybeans in Western North Dakota following the initial inoculation in the first year or two that soybeans are planted.

1) Design and test a digital PCR primer set to identify soybean inoculant strains and discriminate them from other soil microbes
2) Validate digital PCR as a tool for absolute quantification of B. japonicum numbers from soil and translate population size estimates to predictions of successful or unsuccessful soybean nodulation
3) Use the new digital PCR assay to address inoculant strain survival in in soils with challenging conditions and previous soybean planting and inoculation history in Western North Dakota

1) Evidence for the efficacy of digital PCR as a cost effective and rapid solution for quantifying inoculant populations in field soils compared to traditional approaches.

2) Understanding of how long inoculant strains persist in Western North Dakota soils with challenging conditions (drought, acidic pH, saline)

Updated December 1, 2021:
Geddes lab min-term progress report to North Dakota Soybean Council:
A tool for Cheap and Rapid Tracking of Soybean Inoculant Populations in Field Soil

a. Objectives of the Research

Objective 1: Design and test a digital PCR primer set to identify soybean inoculant strains and discriminate them from other soil microbes

Objective 2: Validate digital PCR as a tool for absolute quantification of B. japonicum numbers from soil and translate population size estimates to predictions of successful or unsuccessful soybean nodulation

Objective 3: Use the new digital PCR assay to address inoculant strain survival in in soils with challenging conditions and previous soybean planting and inoculation history in Western North Dakota

b. Completed Work

Objective 1: We designed five primer sets and tested them in combination with one primer set from the literature. The primer sets were successfully evaluated for sensitivity and specificity and optimized with different cycle parameters (see preliminary results).

Objective 2: The validated primer sets were tested with digital PCR as well as qPCR with both a genomic DNA standard curve and a “spike-in” soil assay. Overall, in our hands qPCR showed superior performance than dPCR, and therefore as an outcome from this work we recommend transition to a qPCR-based assay for further development and testing (see preliminary results)

Although not initially proposed in the grant, we further used a greenhouse assay to establish the nodulation response of soybean to different levels of rhizobia in the soil. This allowed us to determine a sensitivity threshold that our assay needs to exceed in order to make a reliable recommendation to farmers for when they should see a positive response to inoculation.

c. Preliminary Results

Evaluation of primer sets in prototype dPCR and qPCR assays
In molecular quantitation approaches such as dPCR and qPCR, primer sets are short DNA sequences that are used to target a specific molecular signature for detection. To start out we designed 5 primer sets, and identified one from the literature to target the nod genes (nodZ and nodYA) of Bradyrhizobium japonicum. These genes are present only in symbiotic Bradyrhizobium, thus ensuring we only quantify the microbes with capacity to form symbiosis with soybeans (Table 1).
Table 1. Primer sets tested for qPCR and dPCR assay
Primer set Forward primer sequence Reverse primer sequence
nodZ A GGTTTGGCGACTGTCTGTGGTC TTCCACCATGTTGGAAAGAATGGTCC
nodZ B GGTTGAAGACATTGGCGGAG CGCGTTCCCTGAAAATCTGC
nodZ C CGCGATTCCAAAGCAGTTCC CAGCGGGCAAGGAGATACAT
nodZ D GGTTGAAGACATTGGCGGAG TTCCACCATGTTGGAAAGAATGGTCC
nodZ E GGTTTGGCGACTGTCTGTGGTC AGACTGGAAAGGCATTGGTG
nodYA GCATCTCAGCATTCATCGGC GGGGAGACGGCAATGTTCAT

For evaluation of primer sets we used both the new-to-market technology digital PCR (dPCR) and the more traditional approach that has been more routinely successfully employed, quantitative PCR (qPCR). Both approaches utilize the same design principles and parameters for DNA amplification, and thus we were able to test all the primer sets using both technologies.
Sensitivity was evaluated based on the lowest concentration Bradyrhizobium japonicum genomic DNA able to be detected (based on a 10 fold dilution standard curve). Initial tests indicated a similar sensitivity, able to detect the equivalent of ~1000 rhizobia/gram of soil. Specificity was evaluated by comparing the “positive” signal in a soil sample that contained high amounts of Bradyrhizobium (Spring 2021 collection from field planted to soybean and inoculated in the previous year) to the “negative” signal in a soil sample expected to contain low to no Bradyrhizobium (Collected from National Grasslands in South Dakota, at least 30 years without farming). Specificity evaluation suggested a good ability to differentiate high from low populations of Bradyrhizobia in soils via qPCR, but a poor ability in digital PCR due to a high non-specific signal from the no Bradyrhizobium control (data not shown).

Optimization of specificity and sensitivity in qPCR
The five primer sets were optimized in an effort to maximize sensitivity and specificity by altering the anneal temperature parameter of the PCR reaction, and contrasted with one another for sensitivity and specificity across annealing temperatures in qPCR(from 56 to 66oC). Sensitivity was defined by the amplification of the target at an earlier cycle threshold (Ct), and specificity was defined based on the absence of amplification in the no Bradyrhizobium control soil sample, and a melting curve from the high Bradyrhizobium soil sample that matched the genomic DNA (gDNA) standard curve (Figure 1). A reaction condition which rendered all primer sets highly specific in qPCR (based on no amplification of the no Bradyrhizobia control microbiome sample) was identified (66oC annealing temperature), therefore the primer set with the greatest sensitivity (nodZ B) was selected to proceed utilizing these reaction conditions. The nodZ B primer set was tested with dPCR using the 66oC annealing temperature but continued to show poor specificity (high non-specific signal) with the dPCR technology (data not shown).

Figure 1. Sensitivity and specificity of tested primer sets.

Calibrating qPCR result to optimal nodulation of soybean
With an optimal primer set selected, we next set out to calibrate Bradyrhizobium detection with the amount of Bradyrhizobium that need to be present in the soil for optimal nodulation in a greenhouse assay. To perform this assay we spiked Bradyrhizobium-free soil with known concentrations of Bradyrhizobia (from 0 to 1,000,000 cells). The spiked soil was then used directly for DNA extraction and qPCR assay, and for planting of soybean plants. After 4 weeks the soybean plants were removed from the pots and the nodulation was assessed by counting nodules, with optimal nodulation defined as a concentration of Bradyrhizobia after which no increased nodulation was achieved. Optimal nodulation was observed at concentrations greater than 1,000 cells per gram. When the qPCR assay using the nodZ B primer set was done with the spiked soil, results correlated nicely with the estimated rhizobia number from a gDNA standard curve. The current assay was able to detect Bradyrhizobia at concentrations greater than ~1,000 cells per gram (Figure 2). Therefore, we are already capable of detecting if sufficient Bradyrhizobia are present for optimal nodulation based on the greenhouse assay, though we believe the reliability of the assay would be improved by enhancing the detectable limits to low, non-optimal numbers of Bradyrhizobia in field soil.


Figure 2. Spiked soil assay for soybean nodulation and detection by qPCR assay.

d. Work to be Completed

Remaining to be completed is Objective 3. In the spring, we will put the current iteration of the assay to the test by evaluating inoculant populations from Soybean fields from Western ND. Since qPCR has proven a more reliable technology for the assay than dPCR thus far, we plan to carry out this objective using qPCR rather than dPCR as originally intended.

View uploaded report

Updated August 19, 2022:
Geddes lab annual progress report to North Dakota Soybean Council:
A tool for Cheap and Rapid Tracking of Soybean Inoculant Populations in Field Soil (Renewed 2023)

a. Objectives of the Research

Objective 1: Design and test a digital PCR primer set to identify soybean inoculant strains and discriminate them from other soil microbes

Objective 2: Validate digital PCR as a tool for absolute quantification of B. japonicum numbers from soil and translate population size estimates to predictions of successful or unsuccessful soybean nodulation

Objective 3: Use the new digital PCR assay to address inoculant strain survival in in soils with challenging conditions and previous soybean planting and inoculation history in Western North Dakota

b. Completed Work

Objective 1: We designed five primer sets and tested them in combination with one primer set from the literature. The primer sets were successfully evaluated for sensitivity and specificity and optimized with different cycle parameters.

Objective 2: The validated primer sets were tested with digital PCR as well as qPCR with both a genomic DNA standard curve and a “spike-in” soil assay. Overall, in our hands qPCR showed superior performance than dPCR. Based on these data from Objective 1 and 2 we finalized a prototype version of the assay for quantifying rhizobia in ND field soil (NDSoy1.0).
We used a greenhouse assay to establish the nodulation response of soybean to different levels of rhizobia in the soil. This allowed us to determine a sensitivity threshold of NDSoy1.0 which was determined to be ~1000 rhizobia per gram of soil.

Objective 3: We sampled 13 fields from growers and Research Extension Centers from Western North Dakota with varied previous planting/inoculation histories in Spring 2022 and employed the current assay (NDSoy1.0) to predict the residual rhizobia present in these fields after different numbers of years post soybean planting and inoculation.

c. Results so far

Evaluation of primer sets in prototype dPCR and qPCR assays
In molecular quantitation approaches such as dPCR and qPCR, primer sets are short DNA sequences that are used to target a specific molecular signature for detection. To start out we designed 5 primer sets, and identified one from the literature to target the nod genes (nodZ and nodYA) of Bradyrhizobium japonicum. These genes are present only in symbiotic Bradyrhizobium, thus ensuring we only quantify the microbes with capacity to form symbiosis with soybeans (Table 1).
Table 1. Primer sets tested for qPCR and dPCR assay
Primer set Forward primer sequence Reverse primer sequence
nodZ A GGTTTGGCGACTGTCTGTGGTC TTCCACCATGTTGGAAAGAATGGTCC
nodZ B GGTTGAAGACATTGGCGGAG CGCGTTCCCTGAAAATCTGC
nodZ C CGCGATTCCAAAGCAGTTCC CAGCGGGCAAGGAGATACAT
nodZ D GGTTGAAGACATTGGCGGAG TTCCACCATGTTGGAAAGAATGGTCC
nodZ E GGTTTGGCGACTGTCTGTGGTC AGACTGGAAAGGCATTGGTG
nodYA GCATCTCAGCATTCATCGGC GGGGAGACGGCAATGTTCAT

For evaluation of primer sets we used both the new-to-market technology digital PCR (dPCR) and the more traditional approach that has been more routinely successfully employed, quantitative PCR (qPCR). Both approaches utilize the same design principles and parameters for DNA amplification, and thus we were able to test all the primer sets using both technologies.
Sensitivity was evaluated based on the lowest concentration Bradyrhizobium japonicum genomic DNA able to be detected (based on a 10 fold dilution standard curve). Initial tests indicated a similar sensitivity, able to detect the equivalent of ~1000 rhizobia/gram of soil. Specificity was evaluated by comparing the “positive” signal in a soil sample that contained high amounts of Bradyrhizobium (Spring 2021 collection from field planted to soybean and inoculated in the previous year) to the “negative” signal in a soil sample expected to contain low to no Bradyrhizobium (Collected from National Grasslands in South Dakota, at least 30 years without farming). Specificity evaluation suggested a good ability to differentiate high from low populations of Bradyrhizobia in soils via qPCR, but a poor ability in digital PCR due to a high non-specific signal from the no Bradyrhizobium control (data not shown).

Optimization of specificity and sensitivity in qPCR and establishment of NDSoy1.0 Assay
The five primer sets were optimized in an effort to maximize sensitivity and specificity by altering the anneal temperature parameter of the PCR reaction, and contrasted with one another for sensitivity and specificity across annealing temperatures in qPCR (from 56 to 66oC). Sensitivity was defined by the amplification of the target at an earlier cycle threshold (Ct), and specificity was defined based on the absence of amplification in the no Bradyrhizobium control soil sample, and a melting curve from the high Bradyrhizobium soil sample that matched the genomic DNA (gDNA) standard curve (Figure 1). A reaction condition which rendered all primer sets highly specific in qPCR (based on no amplification of the no Bradyrhizobia control microbiome sample) was identified (66oC annealing temperature), therefore the primer set with the greatest sensitivity (nodZ B) was selected to proceed utilizing these reaction conditions. The nodZ B primer set was tested with dPCR using the 66oC annealing temperature but continued to show poor specificity (high non-specific signal) with the dPCR technology (data not shown).Thus the qPCR assay utilizing nodZ B at 66oC annealing was selected as the final conditions for the first version of our assay which we named NDSoy1.0 (Figure 2).


Figure 1. Sensitivity and specificity of tested primer sets.

Figure 2. Final assay conditions of NDSoy1.0

Calibrating NDSoy1.0 to optimal nodulation of soybean
With an optimal primer set selected, we next set out to calibrate Bradyrhizobium detection with the amount of Bradyrhizobium that need to be present in the soil for optimal nodulation in a greenhouse assay. To perform this assay we spiked Bradyrhizobium-free soil with known concentrations of Bradyrhizobia (from 0 to 1,000,000 cells). The spiked soil was then used directly for DNA extraction and qPCR assay, and for planting of soybean plants. After 4 weeks the soybean plants were removed from the pots and the nodulation was assessed by counting nodules, with optimal nodulation defined as a concentration of Bradyrhizobia after which no increased nodulation was achieved. Optimal nodulation was observed at concentrations greater than 1,000 cells per gram. When the qPCR assay using the nodZ B primer set was done with the spiked soil, results correlated nicely with the estimated rhizobia number from a gDNA standard curve. The current assay was able to detect Bradyrhizobia at concentrations greater than ~1,000 cells per gram (Figure 3). Therefore, we are already capable of detecting if sufficient Bradyrhizobia are present for optimal nodulation based on the greenhouse assay, though we believe the reliability of the assay would be improved by enhancing the detectable limits to low, non-optimal numbers of Bradyrhizobia in field soil.


Figure 3. Spiked soil assay for soybean nodulation and detection by qPCR assay.

Application of NDSoy1.0 assay to fields from Western ND
We set out to pilot deployment of NDSoy1.0 using field soil samples from Western ND collected in Spring 2022. Sites were selected from Western ND with varied years since planting soybeans and used to estimate the populations of Bradyrhizobium in the soil. As an example for future implementation, we proposed a tentative inoculation recommendation based on our preliminary greenhouse data that <1000 rhizobia per gram resulted in sub-optimal nodulation. Rhizobia populations of <10,000 rhizobia per gram were assigned a recommendation to inoculate, between 10,000 and 100,000 rhizobia per gram suggested to inoculate if soybeans were grown the following year, and rhizobia >100,000 per gram were recommended not to inoculate. Overall Western ND soils (S103-S114) showed lower estimated rhizobia per gram than eastern ND controls (S100/101). We reached an inoculation recommendation threshold with 5/12 fields tested, ranging from 2-6 years since the last soybean crop. By sampling inside or outside the irrigated zones of fields we also investigated the effect of irrigation at two sites that were continuously irrigated and had soybeans either 1 (S109/S110) or 5 years ago (S111/S112). In both cases the non-irrigated parts of the field had less rhizobia, and in the case of the 5 year previous field, the population was either robust or nearing levels that inoculation would be suggested. These results demonstrate the importance and impact of field conditions on the rhizobia populations.

Table 2. Rhizobia levels in Western ND soils estimated by NDSoy1.0



It is important to note that more work is needed to validate critical rhizobia populations at which nodulation, symbiosis and ultimately yield are not optimal before reliable recommendations can be made to farmers. These values may change under different weather conditions, for eg. drought, where poor nitrogen fixation has been correlated with yield loss in drought. In FY24 we hope to collaborate with RECs and to utilize the updated version of the tool finalized in FY223 to investigate these questions.

d. Work to be Completed

With good success from FY22 and establishment and employment of NDSoy1.0, we are poised to further improve the assay in FY23. The objectives for the coming year include:

Objective 1: Evaluate improvement of sensitivity with TaqMan probes and finalize technology
Platform

Objective 2: Establish reliability using different soil types and sampling procedures, and
optimize as necessary

Objective 3: Test finalized assay using farmer’s field soil, with a focus on inoculant survival in
acidic soils from Western ND

View uploaded report

View uploaded report 2

Success in developing the digital PCR assay could lead to the implementation of a service for North Dakota farmers wherein the levels of inoculant in their soils could be assessed in the spring prior to planting. This would allow a decision to be made about the cost-effectiveness of re-inoculating soybean fields in the cropping years following first-time planting of soybeans and inoculation. The assay would be extremely cost effective and could save the farmer thousands of dollars wasted money re-inoculating soybeans when it is unnecessary, or from large yield losses due to insufficient levels of inoculant strains present.
The agronomic outcomes from this project will lead to enhanced advice for farmers in Western North Dakota regarding requirements to re-inoculate soybeans in fields with conditions that may be challenging to inoculant strain survival in the years between soybean planting.