3rd Place Contest Entry: Legume-Rhizobium Symbiosis Phenotypes

This is Yoobeen Lee, Teresa Hur, Isaac Min, and Sydni Au Hoy\u27s submission for the 2022 Kevin and Tam Ross Undergraduate Research Prize, which won third place. It contains their essay on using library resources, their bibliography, and a summary of their research project on legume-rhizobium symbiosis phenotypes. All four authors are fourth-year students at Chapman University. Yoobeen is majoring in Psychology, Teresa and Isaac are majoring in Health Sciences, and Syndi Au Hoy is majoring in Biological Sciences. Their faculty mentor is Dr. Kenjiro Quides

Evaluation of qPCR to Detect Shifts in Population Composition of the Rhizobial Symbiont \u3cem\u3eMesorhizobium japonicum\u3c/em\u3e during Serial in Planta Transfers

Microbial symbionts range from mutualistic to commensal to antagonistic. While these roles are distinct in their outcome, they are also fluid in a changing environment. Here, we used the Lotus japonicus–Mesorhizobium japonicum symbiosis to investigate short-term and long-term shifts in population abundance using an effective, fast, and low-cost tracking methodology for M. japonicum. We use quantitative polymerase chain reaction (qPCR) to track previously generated signature-tagged M. japonicum mutants targeting the Tn5 transposon insertion and the flanking gene. We used a highly beneficial wild type and moderately beneficial and non-beneficial mutants of M. japonicum sp. nov. to demonstrate the specificity of these primers to estimate the relative abundance of each genotype within individual nodules and after serial transfers to new hosts. For the moderate and non-beneficial genotypes, qPCR allowed us to differentiate genotypes that are phenotypically indistinguishable and investigate host control with suboptimal symbionts. We consistently found the wild type increasing in the proportion of the population, but our data suggest a potential reproductive trade-off between the moderate and non-beneficial genotypes. The multi-generation framework we used, coupled with qPCR, can easily be scaled up to track dozens of M. japonicum mutants simultaneously. Moreover, these mutants can be used to explore M. japonicum genotype abundance in the presence of a complex soil community

Comparing qPCR and CFU to Verify Rhizobia Genotype Proportions

Legumes and rhizobia engage in a symbiotic relationship that revolves around the nutrient exchange of rhizobia derived nitrogen for legume synthesized carbon that increases the growth of both partners. Here, we use quantitative polymerase chain reaction (qPCR) and compare our results to a traditional colony forming unit (CFU) method for analyzing rhizobial abundance in more complex populations. First, we confirmed that qPCR yielded similar results to CFU estimation for rhizobial populations within individual nodules and then found that genotypes that fix more nitrogen increased in population proportion over time These experiments demonstrate the utility of qPCR for future experiments interested in analyzing rhizobia genotype proportions and how they relate to the level of benefits legumes receive

Comparing qPCR and CFU to Verify Rhizobia Genotype Proportions

Legumes and rhizobia engage in a symbiotic relationship that is a model for studying microbial mutualisms. This interaction revolves around the nutrient exchange of rhizobia derived nitrogen for legume synthesized carbon that increases the growth of both partners. Therefore, measuring rhizobial population size can indicate the amount of beneficial nitrogen legumes receive. However, legumes interact with genotypes of rhizobia that provide varying levels of nitrogen, and it is unclear how rhizobial populations shift over time. Here, we use quantitative polymerase chain reaction (qPCR) to rapidly track simple, two-genotype, populations of rhizobia, and compare our results to a traditional colony forming unit (CFU) method for analyzing rhizobial abundance in more complex populations. First, we confirmed that qPCR yielded similar results to CFU estimation for rhizobial populations within individual nodules. Next, we passaged and tracked our rhizobial population proportions across multiple plant generations and found that genotypes that fix more nitrogen increased in population proportion over time. Taken together, data collected for individual nodules and the passaging experiment validated the qPCR method. These experiments demonstrate the utility of qPCR for future experiments interested in analyzing rhizobia genotype proportions and how they relate to the level of benefits legumes receive

Evaluation of qPCR to Detect Shifts in Population Composition of the Rhizobial Symbiont Mesorhizobium japonicum during Serial in Planta Transfers.

Microbial symbionts range from mutualistic to commensal to antagonistic. While these roles are distinct in their outcome, they are also fluid in a changing environment. Here, we used the Lotus japonicus-Mesorhizobium japonicum symbiosis to investigate short-term and long-term shifts in population abundance using an effective, fast, and low-cost tracking methodology for M. japonicum. We use quantitative polymerase chain reaction (qPCR) to track previously generated signature-tagged M. japonicum mutants targeting the Tn5 transposon insertion and the flanking gene. We used a highly beneficial wild type and moderately beneficial and non-beneficial mutants of M. japonicum sp. nov. to demonstrate the specificity of these primers to estimate the relative abundance of each genotype within individual nodules and after serial transfers to new hosts. For the moderate and non-beneficial genotypes, qPCR allowed us to differentiate genotypes that are phenotypically indistinguishable and investigate host control with suboptimal symbionts. We consistently found the wild type increasing in the proportion of the population, but our data suggest a potential reproductive trade-off between the moderate and non-beneficial genotypes. The multi-generation framework we used, coupled with qPCR, can easily be scaled up to track dozens of M. japonicum mutants simultaneously. Moreover, these mutants can be used to explore M. japonicum genotype abundance in the presence of a complex soil community

Evaluation of qPCR to Detect Shifts in Population Composition of the Rhizobial Symbiont <i>Mesorhizobium japonicum</i> during Serial in Planta Transfers

Microbial symbionts range from mutualistic to commensal to antagonistic. While these roles are distinct in their outcome, they are also fluid in a changing environment. Here, we used the Lotus japonicus–Mesorhizobium japonicum symbiosis to investigate short-term and long-term shifts in population abundance using an effective, fast, and low-cost tracking methodology for M. japonicum. We use quantitative polymerase chain reaction (qPCR) to track previously generated signature-tagged M. japonicum mutants targeting the Tn5 transposon insertion and the flanking gene. We used a highly beneficial wild type and moderately beneficial and non-beneficial mutants of M. japonicum sp. nov. to demonstrate the specificity of these primers to estimate the relative abundance of each genotype within individual nodules and after serial transfers to new hosts. For the moderate and non-beneficial genotypes, qPCR allowed us to differentiate genotypes that are phenotypically indistinguishable and investigate host control with suboptimal symbionts. We consistently found the wild type increasing in the proportion of the population, but our data suggest a potential reproductive trade-off between the moderate and non-beneficial genotypes. The multi-generation framework we used, coupled with qPCR, can easily be scaled up to track dozens of M. japonicum mutants simultaneously. Moreover, these mutants can be used to explore M. japonicum genotype abundance in the presence of a complex soil community

Time of Day Dependence in Plant–Rhizobia Interaction

In nature, plants interact with diverse microorganisms present in the soil. Some of these interactions are mutualistic, where both the plant and the soil microorganism benefit from the interaction. Legumes have established a unique mutualistic relationship with soil bacteria known as rhizobia. As part of this interaction, rhizobia enter the plant root and get housed in special structures on the root called nodules. Once established inside the nodule, rhizobia fix atmospheric nitrogen for the plant host in return for photosynthetic carbon. The plant interaction with the rhizobia greatly enhances plant productivity as they get access to usable form of nitrogen which is the most limiting macronutrient in agricultural production. However, this relationship between the plant and bacteria is very intricate and is influenced by many factors such as the plant variety, rhizobia species, soil nutrient composition, and ambient temperature. The objective of this project is to investigate the effect of time of the day on this interaction. Both plants and animals have internal biological clock that keep track of the time in the outside environment and accordingly adjust various physiological processes. We investigated the success of legume-rhizobia association by introducing the rhizobia to the plant every four-hour interval during a single day in a pouch system. Seeds of Lotus japonicus were germinated in growth pouches in sterile condition and grown for two weeks in 16 hr light/ 8 hr dark photoperiod under controlled environment. Mesorhizobium loti was cultured on a plate and a suspension of 10 billion cells/ml was prepared. The roots of two-week-old L. japonicus were inoculated with the bacterial suspension starting at dawn (ZT0) and every 4 hours until ZT20 (20 hours after dawn). Our results showed time of day effect in this interaction, where the interaction happened most efficiently at ZT12. The results from this project will help us better understand the complexity of this relationship and enable us to device new approaches to increase crop productivity