Recombinant protein production by mammalian cells is a core component of today’s multi-billion dollar biopharmaceutical industry. Transcriptome and proteome technologies have been used to probe for cellular components that correlate with higher cell-specific productivity, but have yet to yield results that can be translated into practical metabolic engineering strategies. The recognition of cellular complexity has led to an increasing adoption of systems biology, a holistic investigation approach that aims to bring together different omics technologies and to analyze the resulting datasets under a unifying context. Fluxomics is chosen as the platform context to investigate cell metabolism because it captures the integrated effects of gene expression, enzyme activity, metabolite availability and regulation, thereby providing a global picture of the cell’s metabolic phenotype. At present, the routine quantification of cell metabolism revolves around very basic cellular parameters: growth, substrate utilization and product formation. For a systems approach, however, just measuring gross metabolic features is insufficient; we are compelled to perform high-resolution, large-scale fluxomics in order to match the scale of other omics datasets. The challenges of performing large-scale fluxomics come from two opposing fronts. Metabolic flux analysis (MFA) is the estimation of intracellular fluxes from experimental data using a stoichiometric model, a process very much susceptible to modelling biases. The in silico challenge is to construct the most comprehensive model to represent the metabolism of a specific cell, while the in vivo challenge is to resolve as many fluxes as possible using experimental measurements or constraints. A compromise needs to be established between maximizing the resolution of the MFA model and working within technical limitations of the flux experiment. Conventional MFA models assembled from textbook pathways have been available for animal cell culture for the past 15 years. A state-of-the-art model was developed and used to analyse continuous hybridoma culture and batch CHO cell culture data (Chapter 3). Reasonable metabolic assumptions combined with constraint based analysis exploiting irreversibility constraints enabled the resolution of most fluxes in central carbon metabolism. However, while the results appear consistent, there is insufficient information in conventional measurement of uptake, secretion and growth data to assess the completeness of the model and validity of all assumptions. 13C metabolic flux analysis (13C MFA) can potentially resolve fluxes in the central carbon metabolism using flux constraints generated from 13C enrichment patterns of metabolites, but the multitude of substrate uptakes (glucose and amino acids) seen in mammalian cells, in addition to the lack of 13C enrichment data from proteinogenic amino acids, makes it very difficult to anticipate how a labelling experiment should be carried out. The challenges above have led to the development of a systematic workflow to perform large-scale MFA for mammalian cells. A genome-scale model (GeMs), an accurate compilation of gene-protein-reaction-metabolite associations, is the starting basis to perform whole-cell fluxomics. A semi-automated method was developed in order to rapidly extract a prototype of GeM from KEGG and UniProtKB databases (Chapter 4). Core metabolic pathways in the mouse GeM are mostly complete, suggesting that these databases are comprehensive and sufficient. The rapid prototyping system takes advantage of this, making long term maintenance of an accurate and up-to-date GeM by an individual possible. A large number of under-determined pathways in the mouse GeM cannot be resolved by 13C MFA because they do not produce any distinctive 13C enrichment patterns among the carbon metabolites. This has led to the development of SLIPs (short linearly independent pathways) for visualizing these under-determined metabolic pathways contained in large-scale GeMs (Chapter 5). Certain SLIPs are subsequently removed based on careful consideration of their pathway functions and the implications of their removal. A majority of SLIPs have a cyclic configuration, sharing similar redox or energy co-metabolites; very few represent true conversion of substrates to products. Of the 266 under-determined SLIPs generated from the mouse GeM, only 27 SLIPs were incorporated into the final working model under the criterion that they are significant pathways and are potentially resolvable by tracer experiments. Most of these SLIPs are degradation pathways of essential amino acids and inter-conversion of non-essential amino acids (Chapter 8). In parallel, OpenFLUX was developed to perform large-scale isotopic 13C MFA (Chapter 6). This software was built to accept multiple labelled substrates, and no restriction has been placed on the model type or enrichment data. These are necessary features to support large-scale flux analysis for mammalian cells. This was followed by the development of a design strategy that uses analytical gradients of isotopomer measurements to predict resolvability of free fluxes, from which the effectiveness of various 13C experimental scenarios using different combinations of input substrates and isotopomer measurements can be evaluated (Chapter 7). Hypothetical and experimental results have confirmed the predictions that, when glucose and glutamate/glutamine are simultaneously consumed, two separate experiments using [U-13C]- and [1-13C]-glucose, respectively, should be performed. If there is a restriction to a single experiment, then the 80:20 mixture of [U-13C]- and [1-13C]-glucose can provide a better resolution than other labelled glucose mixtures (Chapter 7 and Chapter 8). The tools and framework developed in this thesis brings us within reach of performing large-scale, high-resolution fluxomics for animal cells and hence realising systems-level investigation of mammalian metabolism. Moreover, with the establishment of a more rigorous, systematic modelling approach and higher functioning computational tools, we are now at a position to validate mammalian cell culture flux experiments performed 15 years ago.

Recombinant protein production by mammalian cells is a core component of today’s multi-billion dollar biopharmaceutical industry. Transcriptome and proteome technologies have been used to probe for cellular components that correlate with higher cell-specific productivity, but have yet to yield results that can be translated into practical metabolic engineering strategies. The recognition of cellular complexity has led to an increasing adoption of systems biology, a holistic investigation approach that aims to bring together different omics technologies and to analyze the resulting datasets under a unifying context. Fluxomics is chosen as the platform context to investigate cell metabolism because it captures the integrated effects of gene expression, enzyme activity, metabolite availability and regulation, thereby providing a global picture of the cell’s metabolic phenotype. At present, the routine quantification of cell metabolism revolves around very basic cellular parameters: growth, substrate utilization and product formation. For a systems approach, however, just measuring gross metabolic features is insufficient; we are compelled to perform high-resolution, large-scale fluxomics in order to match the scale of other omics datasets. The challenges of performing large-scale fluxomics come from two opposing fronts. Metabolic flux analysis (MFA) is the estimation of intracellular fluxes from experimental data using a stoichiometric model, a process very much susceptible to modelling biases. The in silico challenge is to construct the most comprehensive model to represent the metabolism of a specific cell, while the in vivo challenge is to resolve as many fluxes as possible using experimental measurements or constraints. A compromise needs to be established between maximizing the resolution of the MFA model and working within technical limitations of the flux experiment. Conventional MFA models assembled from textbook pathways have been available for animal cell culture for the past 15 years. A state-of-the-art model was developed and used to analyse continuous hybridoma culture and batch CHO cell culture data (Chapter 3). Reasonable metabolic assumptions combined with constraint based analysis exploiting irreversibility constraints enabled the resolution of most fluxes in central carbon metabolism. However, while the results appear consistent, there is insufficient information in conventional measurement of uptake, secretion and growth data to assess the completeness of the model and validity of all assumptions. 13C metabolic flux analysis (13C MFA) can potentially resolve fluxes in the central carbon metabolism using flux constraints generated from 13C enrichment patterns of metabolites, but the multitude of substrate uptakes (glucose and amino acids) seen in mammalian cells, in addition to the lack of 13C enrichment data from proteinogenic amino acids, makes it very difficult to anticipate how a labelling experiment should be carried out. The challenges above have led to the development of a systematic workflow to perform large-scale MFA for mammalian cells. A genome-scale model (GeMs), an accurate compilation of gene-protein-reaction-metabolite associations, is the starting basis to perform whole-cell fluxomics. A semi-automated method was developed in order to rapidly extract a prototype of GeM from KEGG and UniProtKB databases (Chapter 4). Core metabolic pathways in the mouse GeM are mostly complete, suggesting that these databases are comprehensive and sufficient. The rapid prototyping system takes advantage of this, making long term maintenance of an accurate and up-to-date GeM by an individual possible. A large number of under-determined pathways in the mouse GeM cannot be resolved by 13C MFA because they do not produce any distinctive 13C enrichment patterns among the carbon metabolites. This has led to the development of SLIPs (short linearly independent pathways) for visualizing these under-determined metabolic pathways contained in large-scale GeMs (Chapter 5). Certain SLIPs are subsequently removed based on careful consideration of their pathway functions and the implications of their removal. A majority of SLIPs have a cyclic configuration, sharing similar redox or energy co-metabolites; very few represent true conversion of substrates to products. Of the 266 under-determined SLIPs generated from the mouse GeM, only 27 SLIPs were incorporated into the final working model under the criterion that they are significant pathways and are potentially resolvable by tracer experiments. Most of these SLIPs are degradation pathways of essential amino acids and inter-conversion of non-essential amino acids (Chapter 8). In parallel, OpenFLUX was developed to perform large-scale isotopic 13C MFA (Chapter 6). This software was built to accept multiple labelled substrates, and no restriction has been placed on the model type or enrichment data. These are necessary features to support large-scale flux analysis for mammalian cells. This was followed by the development of a design strategy that uses analytical gradients of isotopomer measurements to predict resolvability of free fluxes, from which the effectiveness of various 13C experimental scenarios using different combinations of input substrates and isotopomer measurements can be evaluated (Chapter 7). Hypothetical and experimental results have confirmed the predictions that, when glucose and glutamate/glutamine are simultaneously consumed, two separate experiments using [U-13C]- and [1-13C]-glucose, respectively, should be performed. If there is a restriction to a single experiment, then the 80:20 mixture of [U-13C]- and [1-13C]-glucose can provide a better resolution than other labelled glucose mixtures (Chapter 7 and Chapter 8). The tools and framework developed in this thesis brings us within reach of performing large-scale, high-resolution fluxomics for animal cells and hence realising systems-level investigation of mammalian metabolism. Moreover, with the establishment of a more rigorous, systematic modelling approach and higher functioning computational tools, we are now at a position to validate mammalian cell culture flux experiments performed 15 years ago.

The suprachiasmatic nucleus (SCN) of the hypothalamus is the master mammalian pacemaker, co-ordinating the multitude of cell-autonomous circadian oscillators across the body to ensure internal synchrony, as well as maintaining an adaptive phase relationship with the light-dark cycle via projections from the retina. Intercellular communication between SCN clock neurons synchronises their oscillations, resulting in coherent output signals to the periphery. Vasoactive intestinal peptide (VIP), a neuropeptide expressed in the retinorecipient ventrolateral region of the SCN, is vital to this circuit-level co-ordination by signalling to its cognate VPAC2 receptor. In addition, VIP is important for the integration of light input into the SCN oscillation. The aims of the work presented in this thesis were to determine the roles of the VIP and VPAC2 cells in controlling circadian rhythmicity, and to elucidate the mechanisms of VIP signalling that underpin these roles. The first two experimental chapters utilise intersectional genetics and viral transduction to address separable roles for the VIP and VPAC2 cell populations. By diphtheria toxin-mediated cell ablation, or by adjusting cell-autonomous periodicity or rhythmicity specifically in these cell populations, I have identified that the VPAC2 cells are important for period setting and rhythmicity of both the SCN ex vivo and mouse behaviour in vivo, while the VIP cells play a vital role in behavioural rhythmicity and phase coherence across the SCN. The next two chapters use application of VIP to SCN slices to address mechanisms of phase-resetting through pharmacological manipulation and microarray analysis. I find that VIP has long lasting effects on all major circadian parameters of the SCN slice oscillation at both the cellular and circuit levels, and that it achieves this through a diversity of molecular pathways, in particular through cAMP/Ca2+ response elements within gene promoters. The final chapter focuses primarily on DUSP4, a negative regulator of the MAP kinase pathway that I have demonstrated to be upregulated by VIP. Here I demonstrate that DUSP4 affects the steady-state period of SCN slices, as well as influences phase shifting characteristics of both slices and mice. To conclude, the work presented here furthers our knowledge of neuropeptidergic communication in mammalian pacemaking. I have undertaken extensive characterisation of the molecular mechanisms through which the VIP neuropeptide influences SCN oscillators, and I have determined differential roles for the VIP and VPAC2 neurons in circadian timekeeping.

Successful mammalian development to term requires that embryonic and extra-embryonic tissues communicate and grow in coordination, to form the body. After implanting into the uterus, the mouse embryo is comprised of three cell lineages: first, the embryonic epiblast (EPI) that forms the embryo proper, second, the extra-embryonic ectoderm (ExE) which contributes to the foetal portion of the placenta, and third, the visceral endoderm (VE) that contributes to the yolk sac. These three tissues form a characteristic ‘egg-cylinder’ structure, which allows signals to be exchanged between them and sets the stage for body axis establishment and subsequent tissue patterning. The mechanisms underlying this process are difficult to study in vivo because a different genetically manipulated mouse line must be generated to investigate each factor involved. This difficulty has prompted efforts to model mammalian embryogenesis in vitro, using cell lines, which are more amenable to genetic manipulation. The pluripotent state of the EPI can be captured in vitro as mammalian embryonic stem cells (ESCs). Although mouse ESCs have been shown to contribute to all adult tissues in chimeric embryos, they cannot undertake embryogenesis when allowed to differentiate in culture. Previous studies have shown that ESCs formed into three-dimensional (3D) aggregates, called embryoid bodies, can become patterned and express genes associated with early tissue differentiation. However, embryoid bodies cannot recapitulate embryonic architecture and therefore may not accurately reflect what happens in the embryo. In this study, a new technique was developed to model early mouse development which is more faithful to the embryo. ESCs were co-cultured with stem cells derived from the ExE, termed trophoblast stem cells (TSCs), embedded within extracellular matrix (ECM). These culture conditions lead to the self-assembly of embryo-like structures with similar architecture to the mouse egg cylinder. They were comprised of an embryonic compartment derived from ESCs abutting an extra-embryonic compartment derived from TSCs, and hence were named ‘ETS-embryos’. These structures developed a continuous cavity at their centre, which formed via a similar sequence of events to those that lead to pro-amniotic cavity formation in the mouse embryo, and required active Nodal/Activin signalling. After cavitation, ‘ETS-embryos’ developed regionalised mesodermal tissue and primordial germ cell-like cells originating at the boundary between embryonic and extra-embryonic compartments. Inhibitor studies revealed that this occurred in response to endogenous Wnt and BMP signalling, pathways which also govern these tissue specification events in the early mouse embryo. To demonstrate that ‘ETS-embryos’ were comparable to mouse embryos at the global transcriptional level, RNA-sequencing was then performed on different tissue regions of ‘ETS-embryos’ and the resulting transcriptomes were compared to datasets from mouse embryos. These data showed that ‘ETS-embryos’ were highly similar to mouse embryos at post-implantation stages in their overall gene expression patterns. Taken together, these results indicate that ‘ETS-embryos’ are an accurate in vitro model of mammalian embryogenesis, which can be used to complement studies undertaken in vivo to investigate early development.

The accurate replication of the mammalian genome is a complex and logistically challenging process. The entirety of the genome must undergo a single duplication with as little error as possible. This must occur in a coordinated fashion and over suitably short time scale so as to allow timely cellular division within a cell cycle that is typically around 24 hours in a human cell. A great wealth of knowledge already exists describing various aspects of the S phase, during which this replication of the genome occurs. This data has been gathered over a variety of model systems, ranging from inferences from the replicative mechanics of SV40 through to direct observations of replication in mammalian cells.In order integrate this data and determine the value of inferences from different data sources, quantitative models of the mammalian cell S phase are required. This study documents the development of several such models and the exploration of the influences that experimentally determined parameters and different mechanistic theories can have on the behaviour of a simulated S phase. Of particular exploratory interest were the modes of activating replication of replicon clusters, with the aim of simulating experimentally observed dynamics. Additionally, the study also aimed to investigate the variation of replication fork rates and the density of origins of replication, along with the relationship that occurs between the two during both replicational stress and during a normal S phase. Through an iterative series of models, relevant parameters and key theories are sequentially explored so as to better understand the S phase. Particularly influential parameters were identified and studied in detail, with experimental determination where necessary in order to more accurately inform the model system. Conclusions concerning the behaviour of the system and the potential impact of the results were drawn upon the completion of each level of modelling and experimental work.To conclude the study, a linear model simulating the genome of the MRC5 cell line was used to estimate the modes activation of DNA replication along chromosomes in order to recreate experimentally observed replication dynamics. Experimentally determined profiles of replication fork rates and the density of origin firing were also determined for the MRC5 cell line, and were used to populate the model with accurate and appropriate data. Using the model to simulate S phase through a variety of behavioural parameters, realistic S phase dynamics were found to occur through a combination of de novo activation of replicon clusters and a specific probability of neighbour activation by completed clusters. These derived mechanics, when performed on a system correctly parameterised with suitable data, can simulate experimentally observed phenomena. The development of the model highlighted the requirements of data fit for purpose, and the study also stresses the need for critical consideration of inferences made between different model systems.

The endogenous arachidonate-based lipids that activate cannabinoid receptors have been well characterized in mammals. In plants only 12-18 carbon fatty acid ethanolamides have been identifi ed so far and have been shown to modulate a number of physiological processes including seed and seedling development. However, since moss plants contain arachidonic acid, we hypothesized the occurrence of arachidonate-based metabolites in their tissues. Using selective lipidomics approach, we identifi ed the presence of anandamide or arachidonylethanolamide (a 20C polyunsaturated fatty acid ethanolamide) and its precursors, in Physcomitrella patens that were previously not reported in plants. Comprehensive lipid profi les for protonema and gametophyte tissues of moss also revealed the occurrence of other saturated and unsaturated fatty acid ethanolamides and a distinct phospholipid and galactolipid composition. Further studies showed that anandamide, like abscisic acid, inhibits the growth of gametophytes more severely than saturated fatty acid ethanolamides. Our current studies are focused on understanding the physiological and developmental role of polyunsaturated fatty acid ethanolamides in nonseed plants. In conclusion, discovery of anandamide in moss provided us with an exciting possibility to identify fatty acid ethanolamide metabolic pathway in early land plants and elucidate receptor-mediated endocannabinoid signaling responses in plants that is akin to mammals.

No description available.

Improving crop yield by generating stress tolerant plants is the enduring objective of this research. A small class of bioactive fatty acid derivatives, N-acylethanolamines (NAEs), including anandamide (NAE 20:4), an endocannabinoid receptor ligand, affects a wide range of physiological and behavioral functions in animals. In plants, NAEs to the exclusion of anandamide are found to be ubiquitous and abundant in seed tissues and are shown to be involved in mediating abscisic acid (ABA) -dependent or -independent stress responses. Early land plants such as Physcomitrella patens (moss) have been shown to tolerate abiotic stresses. We hypothesized that NAEs are involved in mediating stress responses in moss. Gas chromatography-mass spectrometry was employed in NAE detection and quantification in moss. Selective lipidomic approach revealed novel NAE metabolites. The endocannabinoid receptor ligand anandamide and its precursor molecules were detected and quantified. Exogenous treatment of NAE 12:0, NAE 20:4 and ABA showed a growth inhibitory effect for all three metabolites. NAE 20:4 was more potent than NAE 12:0 to degrees similar to the plant hormone ABA. In silico analyses of NAE catabolizing enzyme fatty acid amide hydrolase from Arabidopsis showed eight putative FAAH candidates in this moss. Candidates showed high similarities with plants as well as animal FAAH proteins. Primers specific to NAE pathway genes have been designed for expression analysis. Our recent identification of the ligand NAE 20:4 in this moss, provides us with a unique opportunity to address if 1) early land plants, such as mosses, retained the endocannabinoid signaling mechanism that is akin to animals but not to plants and 2) if such distinctive NAE profile and mechanism by which it may function in moss plant is responsible, in part, for their natural ability to resist high temperatures, dehydration, osmotic and salt stresses. Insights into unique lipids composition and signaling pathways that mosses acquire naturally, during their successful transition from water to land, may lead to development of tools necessary to enhance abiotic stress tolerance in vegetative tissues of higher plants and thus contribute to improvement of crop productivity.

京都大学 / 新制・課程博士 / 博士(医学) / 甲第24524号 / 医博第4966号 / 新制||医||1065(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 齊藤 博英, 教授 萩原 正敏, 教授 山崎 渉 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

The requirement of DNA synthesis for the release of Ɣ-radiation-induced mitotic inhibition in mammalian cells has been studied. Mammalian cells in which DNA synthesis had been inhibited by treatment with fluorodeoxyuridine (FUdR) were not released from radiation-induced mitotic inhibition until the FUdR block was removed. After removal of the block, mitotic figures reappeared, but only after a time equivalent to the usual mitotic delay caused by the particular radiation dose employed. This suggests that repair of the mitotic inhibition lesion can not proceed unless the pathway for DNA synthesis is intact. Further evidence for the requirement of DNA synthesis in the release of mitotic inhibition came from the observation of radiation-induced synthesis of DNA during G₂, a stage in the cell cycle normally not associated with such synthesis. / Thesis / Master of Science (MSc)