Plant Effects on the Dynamic of Frankia Populations in Soil
|dc.contributor.author||Ben Tekaya, Seifeddine ( 0000-0001-7192-2799 )|
|dc.identifier.citation||Tekaya, S. B. (2018). Plant effects on the dynamic of frankia populations in soil (Unpublished dissertation). Texas State University, San Marcos, Texas.|
Frankia are slow growing actinobacteria that are able to form root nodules with some woody non-leguminous plants. Studies on the ecology of these bacteria are hampered by difficulties to isolate them into pure cultures which was a prerequisite for quantitative analyses in the past. We have therefore focused on the development of molecular approaches that allowed us to retrieve quantitative data from environmental samples unbiased by the limitations of culturability. A first objective of the current study was to develop qPCR based methods to distinguish groups within the genus and quantify their populations in soil. Additional attempts were made to distinguish and quantify typical, nitrogen-fixing frankiae from atypical, generally non-nitrogen fixing frankiae. Both SybrGreen- and Taqman-based qPCR methods were subsequently evaluated for the quantification of these populations in different soils. Methods evaluation resulted in a restrained diversity within soils vegetated with Alnus and Betula nigra trees, where usually one group of Frankia was dominant, while prairie soils reflected more diverse distribution represented by all four clusters. These methods are then used to study long term effects of agricultural management practices on abundance and diversity of frankiae. Data from these analyses were contrasted with Illumina sequencing data targeting both 16s rRNA and nifH gene amplicons. Resulting Illumina data revealed homogenous distribution in soils under agricultural treatments, mainly dominated by members of cluster 1 and 3 Frankia, while prairie soils were more diverse showing Frankia representatives of all four clusters. qPCR analysis on the other hand reflected diverse pattern in the prairie soils with high abundance of members of cluster 2 and cluster 4, while the agricultural treatments exhibited patterns mostly dominated by cluster 1b and low numbers of cluster 2 and 4. Both qPCR and Illumina sequencing methods were also applied in analyses of microcosm experiments aiming to investigate the effects of plants species on indigenous populations of Frankia and relate abundance/diversity in soils to root nodule populations. Investigation on the root nodules of six host plants revealed Frankia populations represented by eight different sequences of nifH gene fragments. two of these sequences characterized frankiae in S. argentea nodules, and three frankiae in A.
glutinosa nodules. frankiae in A. cordata nodules were represented by five sequences, one of which was also found in nodules A. glutinosa and C. equistifolia, while another one was detected in nodules from A. glutinosa. A. viridis and Hippophaë rhamnoides did not nodulate. Quantitative PCR assays showed vegetation generally increased the abundance of frankiae in soil, independent of the target gene (i.e. the nifH or the 23S rRNA gene). Targeted Illumina sequencing of Frankia-specific nifH gene fragments detected 24 unique sequences from all rhizosphere soils four of which were also found in nodules, while the remaining four sequences in nodules were not found in soils. Seven of the 24 sequences from soils represented more than 90% of the reads obtained in most samples, with the two most abundant sequences not found in root nodules and only two of these sequences detected in nodules. In the last chapter, both Illumina and quantitative PCR targeting 23S rRNA gene fragments were used to investigate Frankia diversity in soils from five different continents. Illumina sequencing resulted in a generally low diversity of Frankia populations, with only 18 distinct reads obtained from all soils, and with few sequences identical or closely related to those of cultured relatives. Frankia populations in individual soils were generally represented by only one or two abundant reads, with additional reads often very similar. qPCR analysis detected representatives of all clusters in soils from Rwanda, Hungary and Japan, while that from Peru harbored cluster 1a, 2 and 4 frankiae and Alaskan soil cluster 1b frankiae only. Meta-analyses including results from bioassays and clone libraries revealed large quantitative, but also qualitative differences, suggesting the presence of methodological biases such as selective nodulation, PCR amplification artifacts, or short reads length biases that could affect taxonomical assignments.
To conclude, this study made it possible to investigate Frankia dynamics in soils using different methodological tools, from SybrGreen and Taqman-based qPCR that target all clusters to next generation sequencing, that has been proven successful in assessing nitrogen-fixing Frankia diversity in soils. Furthermore, the current study shows that different methodological approaches to analyze Frankia diversity in soils qualitatively and quantitatively might retrieve considerably different diversity patterns, impacted by biases and limitations of each of the approaches used. For future purposes, developing Illumina sequencing methods that target specific rRNA Frankia fragments, such as 23S rRNA gene fragments, would offer a more comparable tool to the actual nifH gene based protocol. In addition, as digital PCR is emerging as a state of the art quantitative tool, it could offer a more suitable method for Frankia quantification generating absolute data rather than the relative numbers delivered by qPCR.
|dc.format.medium||1 file (.pdf)|
|dc.title||Plant Effects on the Dynamic of Frankia Populations in Soil|
|dc.contributor.committeeMember||McLean, Robert J. C.|
|thesis.degree.grantor||Texas State University|
|thesis.degree.name||Doctor of Philosophy|