Using metaproteomes and models to quantify cellular trade-offs in phytoplankton

Phytoplankton fuel biogeochemical processes in the ocean and are key players influencing the global climate. All biogeochemical processes mediated by microbes are ultimately underpinned by gene expression. In this thesis, I aim to connect gene expression to biogeochemically important cellular proces...

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Bibliographic Details
Main Author: McCain, J Scott P
Other Authors: Department of Biology, Doctor of Philosophy, Ralf Steuer, Sophia Stone, Christopher Algar, Robert Beiko, Julie LaRoche, Erin Bertrand, Not Applicable, Yes
Language:English
Published: 2021
Subjects:
Online Access:http://hdl.handle.net/10222/81092
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spelling ftdalhouse:oai:DalSpace.library.dal.ca:10222/81092 2023-05-15T13:24:10+02:00 Using metaproteomes and models to quantify cellular trade-offs in phytoplankton McCain, J Scott P Department of Biology Doctor of Philosophy Ralf Steuer Sophia Stone Christopher Algar Robert Beiko Julie LaRoche Erin Bertrand Not Applicable Yes 2021-12-16T14:23:00Z http://hdl.handle.net/10222/81092 en eng http://hdl.handle.net/10222/81092 Phytoplankton Metaproteomics Micronutrients Biological Oceanography Antioxidants Cellular modelling 2021 ftdalhouse 2022-03-06T00:11:14Z Phytoplankton fuel biogeochemical processes in the ocean and are key players influencing the global climate. All biogeochemical processes mediated by microbes are ultimately underpinned by gene expression. In this thesis, I aim to connect gene expression to biogeochemically important cellular processes in Southern Ocean phytoplankton. First, I identify and model pervasive biases in metaproteomic analyses and develop methods for overcoming them, leading to more robust inferences (Chapter 2 and Chapter 3). In Chapter 2, I develop a computational model for predicting cofragmentation bias and use this model to study how cofragmentation impacts inferences in metaproteomics. In Chapter 3, I delineate ‘proteomic traits’ across microbial taxa in an Antarctic phytoplankton bloom, connecting differences in gene expression patterns to ecological strategies. I also highlight the importance of database choice and quantify its implications for metaproteomic conclusions. In Chapter 4, I develop a proteomic allocation model to quantify trade-offs associated with iron and manganese bioavailability, and reframe micronutrient-controlled growth in the ocean as a function of cellular costs and constraints. This model offers a novel framework for leveraging metaproteomic data to learn about cellular processes in phytoplankton and for inferring taxon-specific rates and biogeochemical metrics. A key unknown in this model is the various antioxidant systems used by phytoplankton. I, therefore, review various antioxidant mechanisms and synthesize their contributions to cellular elemental stoichiometry in phytoplankton (Chapter 5). Finally, in Chapter 6, I use metaproteomics to determine environmental controls on ribosomal mass fraction across two taxonomic groups in the Amundsen Sea Polynya. Other/Unknown Material Amundsen Sea Antarc* Antarctic Southern Ocean Dalhousie University: DalSpace Institutional Repository Amundsen Sea Antarctic Southern Ocean
institution Open Polar
collection Dalhousie University: DalSpace Institutional Repository
op_collection_id ftdalhouse
language English
topic Phytoplankton
Metaproteomics
Micronutrients
Biological Oceanography
Antioxidants
Cellular modelling
spellingShingle Phytoplankton
Metaproteomics
Micronutrients
Biological Oceanography
Antioxidants
Cellular modelling
McCain, J Scott P
Using metaproteomes and models to quantify cellular trade-offs in phytoplankton
topic_facet Phytoplankton
Metaproteomics
Micronutrients
Biological Oceanography
Antioxidants
Cellular modelling
description Phytoplankton fuel biogeochemical processes in the ocean and are key players influencing the global climate. All biogeochemical processes mediated by microbes are ultimately underpinned by gene expression. In this thesis, I aim to connect gene expression to biogeochemically important cellular processes in Southern Ocean phytoplankton. First, I identify and model pervasive biases in metaproteomic analyses and develop methods for overcoming them, leading to more robust inferences (Chapter 2 and Chapter 3). In Chapter 2, I develop a computational model for predicting cofragmentation bias and use this model to study how cofragmentation impacts inferences in metaproteomics. In Chapter 3, I delineate ‘proteomic traits’ across microbial taxa in an Antarctic phytoplankton bloom, connecting differences in gene expression patterns to ecological strategies. I also highlight the importance of database choice and quantify its implications for metaproteomic conclusions. In Chapter 4, I develop a proteomic allocation model to quantify trade-offs associated with iron and manganese bioavailability, and reframe micronutrient-controlled growth in the ocean as a function of cellular costs and constraints. This model offers a novel framework for leveraging metaproteomic data to learn about cellular processes in phytoplankton and for inferring taxon-specific rates and biogeochemical metrics. A key unknown in this model is the various antioxidant systems used by phytoplankton. I, therefore, review various antioxidant mechanisms and synthesize their contributions to cellular elemental stoichiometry in phytoplankton (Chapter 5). Finally, in Chapter 6, I use metaproteomics to determine environmental controls on ribosomal mass fraction across two taxonomic groups in the Amundsen Sea Polynya.
author2 Department of Biology
Doctor of Philosophy
Ralf Steuer
Sophia Stone
Christopher Algar
Robert Beiko
Julie LaRoche
Erin Bertrand
Not Applicable
Yes
author McCain, J Scott P
author_facet McCain, J Scott P
author_sort McCain, J Scott P
title Using metaproteomes and models to quantify cellular trade-offs in phytoplankton
title_short Using metaproteomes and models to quantify cellular trade-offs in phytoplankton
title_full Using metaproteomes and models to quantify cellular trade-offs in phytoplankton
title_fullStr Using metaproteomes and models to quantify cellular trade-offs in phytoplankton
title_full_unstemmed Using metaproteomes and models to quantify cellular trade-offs in phytoplankton
title_sort using metaproteomes and models to quantify cellular trade-offs in phytoplankton
publishDate 2021
url http://hdl.handle.net/10222/81092
geographic Amundsen Sea
Antarctic
Southern Ocean
geographic_facet Amundsen Sea
Antarctic
Southern Ocean
genre Amundsen Sea
Antarc*
Antarctic
Southern Ocean
genre_facet Amundsen Sea
Antarc*
Antarctic
Southern Ocean
op_relation http://hdl.handle.net/10222/81092
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