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The Systems Biology of Red Cell Meta...
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Yurkovich, James T.
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The Systems Biology of Red Cell Metabolism: Physiology under Storage Conditions.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
The Systems Biology of Red Cell Metabolism: Physiology under Storage Conditions./
作者:
Yurkovich, James T.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2018,
面頁冊數:
209 p.
附註:
Source: Dissertation Abstracts International, Volume: 79-08(E), Section: B.
Contained By:
Dissertation Abstracts International79-08B(E).
標題:
Biomedical engineering. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10745508
ISBN:
9780355822502
The Systems Biology of Red Cell Metabolism: Physiology under Storage Conditions.
Yurkovich, James T.
The Systems Biology of Red Cell Metabolism: Physiology under Storage Conditions.
- Ann Arbor : ProQuest Dissertations & Theses, 2018 - 209 p.
Source: Dissertation Abstracts International, Volume: 79-08(E), Section: B.
Thesis (Ph.D.)--University of California, San Diego, 2018.
The human red blood cell (RBC) is a logical starting point for the development and application of systems biology methods because of its simplicity, intrinsic experimental accessibility, and importance in human health. New "-omics" technologies have been used to study the biochemical and morphological changes that occur in red blood cells during cold storage, collectively referred to as the "storage lesion." Here, we extend these previous efforts by using systems biology to examine the metabolic physiology of RBCs under storage conditions. We first characterized the temperature dependence of the storage process using previously identified storage-age biomarkers as a representation of systems-level trends, showing that the metabolic state of the RBC is conserved but accelerated with increasing temperature. We then questioned whether these biomarkers---which had been shown to be excellent qualitative markers of systemic behavior---held any potential to provide quantitative information about the system. Using simple linear statistical models, we showed that a subset of the biomarkers could be used to predict the quantitative concentration profiles of other metabolites in the RBC network. We expanded these efforts by integrating network structural information into these statistical models to forecast future values of these concentration profiles after measurements made during only the first eight days of storage. Next, we used multiple first principles modeling approaches to understand the underlying mechanisms and temporal dynamics of the observed behaviors and developed a method for the integration of metabolomics data into cell-scale mathematical models. Finally, we developed a method for the integration of quantitative proteomics data into cell-scale models using Escherichia coli as a test case. Collectively, these results provide empirical proof that the RBC metabolome can be represented in a low-dimensional space and offer the starting point for a whole-cell model of the RBC. More broadly, we detail the development and use of systems biology methods on the human RBC, providing a starting point from which we can expand these efforts to other, more complicated cellular systems.
ISBN: 9780355822502Subjects--Topical Terms:
535387
Biomedical engineering.
The Systems Biology of Red Cell Metabolism: Physiology under Storage Conditions.
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The human red blood cell (RBC) is a logical starting point for the development and application of systems biology methods because of its simplicity, intrinsic experimental accessibility, and importance in human health. New "-omics" technologies have been used to study the biochemical and morphological changes that occur in red blood cells during cold storage, collectively referred to as the "storage lesion." Here, we extend these previous efforts by using systems biology to examine the metabolic physiology of RBCs under storage conditions. We first characterized the temperature dependence of the storage process using previously identified storage-age biomarkers as a representation of systems-level trends, showing that the metabolic state of the RBC is conserved but accelerated with increasing temperature. We then questioned whether these biomarkers---which had been shown to be excellent qualitative markers of systemic behavior---held any potential to provide quantitative information about the system. Using simple linear statistical models, we showed that a subset of the biomarkers could be used to predict the quantitative concentration profiles of other metabolites in the RBC network. We expanded these efforts by integrating network structural information into these statistical models to forecast future values of these concentration profiles after measurements made during only the first eight days of storage. Next, we used multiple first principles modeling approaches to understand the underlying mechanisms and temporal dynamics of the observed behaviors and developed a method for the integration of metabolomics data into cell-scale mathematical models. Finally, we developed a method for the integration of quantitative proteomics data into cell-scale models using Escherichia coli as a test case. Collectively, these results provide empirical proof that the RBC metabolome can be represented in a low-dimensional space and offer the starting point for a whole-cell model of the RBC. More broadly, we detail the development and use of systems biology methods on the human RBC, providing a starting point from which we can expand these efforts to other, more complicated cellular systems.
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