Electronic Theses and Dissertations

Date of Award


Document Type


Degree Name

Ph.D. in Biological Science

First Advisor

Erik Hom

Second Advisor

Stephen Brewer

Third Advisor

Jason Hoeksema

Relational Format



Mutualistic symbioses are ubiquitous and among one of the most crucial biological interactions. Some of the most iconic examples are fungal-photoautotroph mutualisms such as lichens, mycorrhizal-plant, and endophytic fungal-plant symbioses. Yet little is understood about the earliest origins of such microbial mutualisms, and more precisely, how they relate to the origin of land plants. The study of the evolution of fungal-photoautotroph symbioses is often limited to comparative genomic techniques due to the few genetic tools available for studying extant interactions. Recent work suggests that extant fungal-plant interactions have their origins in fungal-algal associations.In Chapter 1, I review the evolution of plant-microbe signaling mechanisms required for the establishment of mutualistic endosymbioses. I provide an overview of what is currently known and highlight knowledge gaps within the literature. I focus on the need to investigate how early beneficial fungal-photoautotroph interactions may have been established. Finally, I challenge the current research bias within the plant-microbe signaling community that focuses on identification of new signaling molecules and propose that future research put more emphasis on analyzing the coordination of signal exchange as opposed to simply the identity of the compounds being exchanged.

In Chapter 2, I describe experiments leveraging genetically tractable model fungi and algae to better understand their capacity to form symbioses and to probe the nature of their interactions. Dual-transcriptomics of naïve fungal-algal tissues formed between symbionts lacking co-evolutionary history revealed a broadly species-driven interaction. Despite exhibiting similar phenotypes, tissues formed with Neurospora crassa show increased photosynthesis in algal symbionts and slowed fungal metabolism while tissues formed with Aspergillus nidulans showed the opposite fungal-algal dynamic. I attempted to manipulate the nature of these symbioses by forming tissues where fungal mutants were obligately dependent on their algal symbiont for nitrogen. Despite changing the nature of their interaction, gene expression remained species-specific and the trade-off between fungal metabolism and algal photosynthesis remained. I performed a meta-analysis of similar dual-transcriptomic studies whereby I compared gene expression patterns of orthologs across a diverse range of natural fungal-plant interactions. I found a strong negative correlation between gene modules associated with fungal metabolism and plant photosynthesis. Like the synthetic symbioses, gene expression was species specific, and annotated interaction type (i.e., pathogenic or mutualistic) was a poor predictor of expression patterns.

In Chapter 3, I assessed the capacity of key representative green algal strains to form symbioses with a diverse set of foliar fungal endophytes using a biomass-based “microbial speed-dating” assay. My aim was to use cell biomass as a proxy for mutualistic capacity, whereby a mutualistic interaction was assumed if co-culture biomass was greater than the sum of the individual fungal/algal monoculture biomasses. After screening interactions between 6 green algae and 33 fungi, I observed that >95% of interactions yielded an “antagonistic” outcome based on biomass. Interestingly, ~35% of fungal pairings with Chlamydomonas reinhardtii formed fungal-algal tissues similar to those analyzed in the dual-transcriptome study. In all cases, the pairings that formed fungal-algal tissues produced less biomass in co-culture than monoculture, calling into question the utility of biomass alone for predicting symbiotic potential. While biomass is often an easy metric to quantify, more resource intensive measures such as cell quantification, nutrient uptake, and/or various “-omics” techniques may be necessary for properly evaluating mutualistic potential.

Available for download on Thursday, December 14, 2023

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