Major
Biology
Research Abstract
Studying soil microbial diversity in tropical ecosystems is of high importance to understanding global nutrient cycling. Soil microbes, as decomposers, are primary contributors to terrestrial nutrient cycling. In tropical systems, warm, moist conditions create ideal environments for microbial growth year-round. However, the ability to study these topics in the field is limited by the remoteness and ruggedness of many tropical forest locations, combined with the highly changeable and difficult-to-control conditions present in the field. To that end, proxy study systems have been created that allow researchers to approximate natural conditions, but with better accessibility in terms of location and controllability. / Biosphere 2 is a facility owned by the University of Arizona dedicated to recreating several ecosystems. Among the ecosystems present in this environment are examples of several tropical rainforest biomes, including both lowland, deep-soil forest, as well as highland-type, focusing primarily on Neotropical species. Thus, it is an ideal place to carry out studies on topics like soil nutrient cycling that would be challenging in a natural rainforest biome./ Young et al. 2019 recently did a study where they examined N2O production and microbial community composition and dynamics of the rainforest ecosystem in Biosphere 2 during the dry season, profiling the metabolic and genetic backgrounds of the bacterial and archaeal species present in the soil. However, a similar treatment was not done for the fungi of the soil, leaving their contribution unexamined. The soil fungal biota of the Biosphere 2 itself is not well-understood, and generally consists of whatever fungal symbionts and phoresy that was brought in with the construction of the soil and floral communities. / While fungal sequences from these samples exist, sequencing was completed using two different sets of primers: one is the standard for ITS sequences, and another set was designed by the Joint Genome Institute (JGI), but may be biased against particular taxonomic groups. / In order to better understand the soil fungal communities in the Biosphere 2 rainforest biome, and determine if there are significant sources of bias in the primer sets used, I will analyze the data using several R statistical analysis packages. The sequences will be denoised and cleaned using the DADA2 package. I will use a sequencing dataset built from an artificial mock community of known species (U’ren et al .2019) to test for bias in the primers of both the standard and JGI varieties. Next, I will obtain the standard ITS data from the author, as well as the JGI-primer ITS data from the JGI open-access data portal. Then, the Phyloseq data package will be used to create illustrative graphs to visualize the data from these sources to illustrate the phylogenetic data relevant to the study from both genomic datasets, with the artificial community serving as a control. To examine the diversity present in the data, genetically distinct OUT clusters will be created using the UPARSE-OTU algorithm. After this, the putative OTUs will be filtered through the ITSx software to remove any sequences not bearing the ITS2 region. Afterwards, the remaining sequences will be identified using BLAST against existing sequence databases. From these identified sequences, trees that graphically illustrate the diversity can be created using the tree-based alignment selector toolkit (T-BAS). From these data, both the selection bias of the JGI ITS2 primers as well as the overall diversity of the Biosphere 2 fungal community can be illustrated. / Overall, this study will help increase our understanding of both the ecology of soil fungi in the rainforest biome of Biosphere 2, as well as how the JGI primer set compares in genetic bias to standard primer sets.
Faculty Mentor/Advisor
Naupaka Zimmerman
Included in
Primer Bias in Finding Fungal Diversity in an Artificial Biome
Studying soil microbial diversity in tropical ecosystems is of high importance to understanding global nutrient cycling. Soil microbes, as decomposers, are primary contributors to terrestrial nutrient cycling. In tropical systems, warm, moist conditions create ideal environments for microbial growth year-round. However, the ability to study these topics in the field is limited by the remoteness and ruggedness of many tropical forest locations, combined with the highly changeable and difficult-to-control conditions present in the field. To that end, proxy study systems have been created that allow researchers to approximate natural conditions, but with better accessibility in terms of location and controllability. / Biosphere 2 is a facility owned by the University of Arizona dedicated to recreating several ecosystems. Among the ecosystems present in this environment are examples of several tropical rainforest biomes, including both lowland, deep-soil forest, as well as highland-type, focusing primarily on Neotropical species. Thus, it is an ideal place to carry out studies on topics like soil nutrient cycling that would be challenging in a natural rainforest biome./ Young et al. 2019 recently did a study where they examined N2O production and microbial community composition and dynamics of the rainforest ecosystem in Biosphere 2 during the dry season, profiling the metabolic and genetic backgrounds of the bacterial and archaeal species present in the soil. However, a similar treatment was not done for the fungi of the soil, leaving their contribution unexamined. The soil fungal biota of the Biosphere 2 itself is not well-understood, and generally consists of whatever fungal symbionts and phoresy that was brought in with the construction of the soil and floral communities. / While fungal sequences from these samples exist, sequencing was completed using two different sets of primers: one is the standard for ITS sequences, and another set was designed by the Joint Genome Institute (JGI), but may be biased against particular taxonomic groups. / In order to better understand the soil fungal communities in the Biosphere 2 rainforest biome, and determine if there are significant sources of bias in the primer sets used, I will analyze the data using several R statistical analysis packages. The sequences will be denoised and cleaned using the DADA2 package. I will use a sequencing dataset built from an artificial mock community of known species (U’ren et al .2019) to test for bias in the primers of both the standard and JGI varieties. Next, I will obtain the standard ITS data from the author, as well as the JGI-primer ITS data from the JGI open-access data portal. Then, the Phyloseq data package will be used to create illustrative graphs to visualize the data from these sources to illustrate the phylogenetic data relevant to the study from both genomic datasets, with the artificial community serving as a control. To examine the diversity present in the data, genetically distinct OUT clusters will be created using the UPARSE-OTU algorithm. After this, the putative OTUs will be filtered through the ITSx software to remove any sequences not bearing the ITS2 region. Afterwards, the remaining sequences will be identified using BLAST against existing sequence databases. From these identified sequences, trees that graphically illustrate the diversity can be created using the tree-based alignment selector toolkit (T-BAS). From these data, both the selection bias of the JGI ITS2 primers as well as the overall diversity of the Biosphere 2 fungal community can be illustrated. / Overall, this study will help increase our understanding of both the ecology of soil fungi in the rainforest biome of Biosphere 2, as well as how the JGI primer set compares in genetic bias to standard primer sets.
