Modelling sponge-symbiont metabolism

Watson, Jabin Reid (2017). Modelling sponge-symbiont metabolism PhD Thesis, School of Biological Sciences, The University of Queensland. doi:10.14264/uql.2017.180

Attached Files (Some files may be inaccessible until you login with your UQ eSpace credentials)
Name Description MIMEType Size Downloads
s40114529_final_thesis.pdf Thesis (open access) application/pdf Bytes 0
Author Watson, Jabin Reid
Thesis Title Modelling sponge-symbiont metabolism
School, Centre or Institute School of Biological Sciences
Institution The University of Queensland
DOI 10.14264/uql.2017.180
Publication date 2017-01-30
Thesis type PhD Thesis
Supervisor Bernie Degnan
Sandie Degnan
Jens Kromer
Total pages 219
Language eng
Subjects 0604 Genetics
0601 Biochemistry and Cell Biology
Formatted abstract
Marine sponges are increasingly being recognised for their nutrient cycling ecosystem services, linking pelagic nutrients with the benthic ecosystem. Furthermore, sponges are the most prolific producers of bioactive secondary metabolites in the marine environment. Despite their ecological and commercial value, little is know about the metabolic processes that are responsible. The inability to produce sufficient sponge biomass, and thus specific bioactive compounds, has been repeatedly identified as a major bottleneck towards commercialising sponge holobiont derived drugs. Likewise, nutrient cycling by sponges has been a relatively recent advancement in marine ecology and the scale of this process is unknown. This thesis takes a systems approach to understanding sponge-symbiont metabolic processes by utilising the genomic resources available for the demosponge Amphimedon queenslandica and its bacterial symbiont AqS1. Specifically, I undertake genome-scale modelling and metabolic flux analyses to investigate the metabolic networks present in this sponge as well as its associated vertically-transmitted microbial symbiont. The goal of this thesis is to generate the data required for, and subsequently develop, a dual-species genome-scale metabolic model for A. queenslandica and AqS1. This will provide a framework to further our understanding of how sponges produce their biomass while living in an oligotrophic, tropical reef environment.

To develop a genome-scale metabolic model, the biochemical composition of the organism must first be determined. Knowledge of the relative quantities of macromolecules and their respective building blocks (e.g. protein and amino acids) is vital, as each requires different substrates, enzymes and cofactors for their synthesis. I adapted and developed methods to characterise the composition and abundance of DNA, RNA, protein, lipids and carbohydrates in a marine sponge. These methods are described in detail that allows them to be easily transferred to other, non-model, large marine organisms. This is followed by a detailed analysis of A. queenslandica’s macromolecular, amino acid, fatty acid and sterol composition. The biochemical data from this chapter was used to generate a biomass equation that represent the average composition of adult A. queenslandica in the metabolic model.

To understand how the metabolic network may work towards producing more biomass, it must be considered in the context of the environmental conditions that naturally constrain growth. The dominant environmental constraint on growth on an oligotrophic reef system is nutrient availability. The abundance of key elements, such as carbon and nitrogen, were quantified throughout the course of a year. To investigate effects on the sponge of any changes in nutrient availability, I concurrently sampled sponges and analysed their biochemical composition to the macromolecular level. Chapter 4 presents these data and discusses a number of trends and correlations in the biochemical composition of the sponges with changing nutrient availability through four seasons of the year. For instance, there was a significant increase in particulate to dissolved organic carbon at the end of summer with a corresponding rise in carbohydrates in A. queenslandica. Of particular importance for the subsequent metabolic modelling, was the separation of carbon into the dissolved and particulate fractions.

Chapter 5 presents the metabolic models and their analysis. Initially, I manually constructed a genome-scale metabolic model for the sponge A. queenslandica. The model construction identified 10 amino acids, 4 vitamins and a plant-derived phytosterol for which A. queenslandica is auxotrophic. These represent nutrients that are essential for sponge growth and may in future form the basis of a defined cell culture medium. The microbial community within A. queenslandica is relatively simple and dominated by a species of sulfur oxidising bacteria, called Aqs1. I generated a genome-scale model for Aqs1, which is able to synthesise all 20 proteinogenic amino acids, in addition to having a diverse range of carbohydrate-specific transporters and enzymes.

To investigate the interactions between the host sponge and Aqs1, the two models were joined using a shared compartment. This was called the extracellular matrix, and represents the area of interaction within the sponge body where metabolite transfers can occur. I measured the pumping rate of A. queenslandica and calculated the average volume of water pumped per hour, standardised to gram dry weight. This was used to constrain the nutrient uptake rate of the model. To investigate how the metabolic network may respond to different nutrient conditions, low and high nutrient conditions were defined using the ratios of particulate and dissolved carbon from the seasonal environmental profiling.

This work represents the first genome-scale model for a sponge-symbiont system, and marine invertebrates in general. The genome-scale metabolic models resulting from this work are an important resource that will guide future work into the metabolic processes of both A. queenslandica and its symbiont, Aqs1.
Keyword Porifera
Genome-scale metabolic reconstruction
Biomass composition
Constraint-based modelling
Flux balance analysis

Document type: Thesis
Collections: UQ Theses (RHD) - Official
UQ Theses (RHD) - Open Access
Version Filter Type
Citation counts: Google Scholar Search Google Scholar
Created: Thu, 19 Jan 2017, 22:00:50 EST by Jabin Watson on behalf of Learning and Research Services (UQ Library)