Estimation and identifiability of kinetic parameters in dynamical models of biochemical reaction networks

This dissertation is a partial fulfillment of the requirements for the degree Doctor of Philosophy (PhD) at the Department of Mathematics, University of Bergen. The subject of the thesis is estimation of parameters in dynamical models of biochemical reaction networks

Design of a monitoring program in a varying marine environment

In this thesis we develop methods for optimal design of a monitoring program for offshore geological CO2 storage. The goal is to find the layout of fixed chemical sensors at the seafloor that maximizes the probability of detecting a leakage. Numerical simulations of leakage scenarios are used as origin to predict the regions that sensors monitor. Based on leakage scenarios, this gives the detection probability. All methods are tested using test cases. The methods could be applied to other problems involving monitoring of potential pollutants into the ocean. The main results are inclusion of spatial variability in the estimated leakage footprint and an exact inversion of the resulting footprint.Master i Anvendt og beregningsorientert matematikkMAMN-MABMAB39

Experimental design for parameter estimation in steady-state linear models of metabolic networks

Metabolic networks are typically large, containing many metabolites and reactions. Dynamical models that aim to simulate such networks will consist of a large number of ordinary differential equations, with many kinetic parameters that must be estimated from experimental data. We assume these data to be metabolomics measurements made under steady-state conditions for different input fluxes. Assuming linear kinetics, analytical criteria for parameter identifiability are provided. For normally distributed error terms, we also calculate the Fisher information matrix analytically to be used in the D-optimality criterion. A test network illustrates the developed tool chain for finding an optimal experimental design. The first stage is to verify global or pointwise parameter identifiability, the second stage to find optimal input fluxes, and finally remove redundant measurements.publishedVersio

Single PFAS and PFAS mixtures affect nuclear receptor- and oxidative stress-related pathways in precision-cut liver slices of Atlantic cod (Gadus morhua)

The aim of the present study was to investigate effects of per- and polyfluoroalkyl substances (PFAS), both single compounds and a mixture of these, using precision-cut liver slices (PCLS) from Atlantic cod (Gadus morhua). PCLS were exposed for 48 h to perfluorooctane sulfonate (PFOS), perfluorooctanoate (PFOA) and perfluorononanoate (PFNA) (10, 50 and 100 μM), and three mixtures of these at equimolar concentrations (10, 50 and 100 μM). Transcriptomic responses were assessed using RNA sequencing. Among exposures to single PFAS, PFOS produced the highest number of differentially expressed genes (DEGs) compared to PFOA and PFNA (86, 25 and 31 DEGs, respectively). Exposure to the PFAS mixtures resulted in a markedly higher number of DEGs (841). Clustering analysis revealed that the expression pattern of the PFAS mixtures were more similar to PFOS compared to PFOA and PFNA, suggesting that effects induced by the PFAS mixtures may largely be attributed to PFOS. Pathway analysis showed significant enrichment of pathways related to oxidative stress, cholesterol metabolism and nuclear receptors in PFOS-exposed PCLS. Fewer pathways were significantly enriched following PFOA and PFNA exposure alone. Significantly enriched pathways following mixture exposure included lipid biosynthesis, cancer-related pathways, nuclear receptor pathways and oxidative stress-related pathways such as ferroptosis. The expression of most of the genes within these pathways was increased following PFAS exposure. Analysis of non-additive effects in the 100 μM PFAS mixture highlighted genes involved in the antioxidant response and membrane transport, among others, and the majority of these genes had synergistic expression patterns in the mixture. Nevertheless, 90% of the DEGs following mixture exposure showed additive expression patterns, suggesting additivity to be the major mixture effect. In summary, PFAS exposure promoted effects on cellular processes involved in oxidative stress, nuclear receptor pathways and sterol metabolism in cod PCLS, with the strongest effects observed following PFAS mixture exposure.publishedVersio

Gytefeltskartlegging Nordøstarktisk hyse: Toktnummer 2022609

Gytekartleggingstokt for nordøstarktisk hyse ble gjennomført 8. -19. april 2022 med FF Kristine Bonnevie. Toktet startet i Bodø og ble avsluttet i Tromsø. Toktet dekket det antatte gyteområdet langs Eggakanten mellom Malangsgrunnen og Bjørnøyrenna. Kontinuerlige akustiske registringer ble gjort langs 3194 nautiske mil kurslinjer. Det ble tatt 38 stasjoner med egghåv og CTD, og 29 bunntrål. Gytende hyse ble funnet i de fleste trålhalene. De innsamlete eggene er sendt til genetisk analyse for å kunne skille torsk- og hyseegg.publishedVersio

Integrative omics-analysis of lipid metabolism regulation by peroxisome proliferator-activated receptor a and b agonists in male Atlantic cod

Lipid metabolism is essential in maintaining energy homeostasis in multicellular organisms. In vertebrates, the peroxisome proliferator-activated receptors (PPARs, NR1C) regulate the expression of many genes involved in these processes. Atlantic cod (Gadus morhua) is an important fish species in the North Atlantic ecosystem and in human nutrition, with a highly fatty liver. Here we study the involvement of Atlantic cod Ppar a and b subtypes in systemic regulation of lipid metabolism using two model agonists after in vivo exposure. WY-14,643, a specific PPARA ligand in mammals, activated cod Ppara1 and Ppara2 in vitro. In vivo, WY-14,643 caused a shift in lipid transport both at transcriptional and translational level in cod. However, WY-14,643 induced fewer genes in the fatty acid beta-oxidation pathway compared to that observed in rodents. Although GW501516 serves as a specific PPARB/D ligand in mammals, this compound activated cod Ppara1 and Ppara2 as well as Pparb in vitro. In vivo, it further induced transcription of Ppar target genes and caused changes in lipid composition of liver and plasma. The integrative approach provide a foundation for understanding how Ppars are engaged in regulating lipid metabolism in Atlantic cod physiology. We have shown that WY-14,643 and GW501516 activate Atlantic cod Ppara and Pparb, affect genes in lipid metabolism pathways, and induce changes in the lipid composition in plasma and liver microsomal membranes. Particularly, the combined transcriptomic, proteomics and lipidomics analyses revealed that effects of WY-14,643 on lipid metabolism are similar to what is known in mammalian studies, suggesting conservation of Ppara functions in mediating lipid metabolic processes in fish. The alterations in the lipid profiles observed after Ppar agonist exposure suggest that other chemicals with similar Ppar receptor affinities may cause disturbances in the lipid regulation of fish. Model organism: Atlantic cod (Gadus morhua). LSID: urn:lsid:zoobank.org:act:389BE401-2718-4CF2-BBAE-2E13A97A5E7B. COL Identifier: 6K72F.The study was carried out as part of the project “dCod 1.0: decoding systems toxicology of Atlantic cod” financed by the Norwegian Research Council (project no. 248840) and is part of Centre for Digital Life Norway (DLN), financed by the Research Council of Norway (project no. 248810). This work was also part of the iCod 2.0 project (project no. 244564) financed by the Norwegian Research Council. The UPLC-HRMS analysis was performed in collaboration with another project in DLN, AurOmega (project no. 269432). The Genomics Core Facility (GCF) at the University of Bergen, which is a part of the NorSeq consortium, provided services on RNA sequencing; GCF is supported in part by major grants from the Research Council of Norway (grant no. 245979/F50) and Bergen Research Foundation (BFS) (grant no. BFS2017TMT04 and BFS2017TMT08).Peer reviewe

Design of a monitoring program in a varying marine environment

In this thesis we develop methods for optimal design of a monitoring program for offshore geological CO2 storage. The goal is to find the layout of fixed chemical sensors at the seafloor that maximizes the probability of detecting a leakage. Numerical simulations of leakage scenarios are used as origin to predict the regions that sensors monitor. Based on leakage scenarios, this gives the detection probability. All methods are tested using test cases. The methods could be applied to other problems involving monitoring of potential pollutants into the ocean. The main results are inclusion of spatial variability in the estimated leakage footprint and an exact inversion of the resulting footprint

Estimation and identifiability of kinetic parameters in dynamical models of biochemical reaction networks

This dissertation is a partial fulfillment of the requirements for the degree Doctor of Philosophy (PhD) at the Department of Mathematics, University of Bergen. The subject of the thesis is estimation of parameters in dynamical models of biochemical reaction networks

Experimental design for parameter estimation in steady-state linear models of metabolic networks

Metabolic networks are typically large, containing many metabolites and reactions. Dynamical models that aim to simulate such networks will consist of a large number of ordinary differential equations, with many kinetic parameters that must be estimated from experimental data. We assume these data to be metabolomics measurements made under steady-state conditions for different input fluxes. Assuming linear kinetics, analytical criteria for parameter identifiability are provided. For normally distributed error terms, we also calculate the Fisher information matrix analytically to be used in the D-optimality criterion. A test network illustrates the developed tool chain for finding an optimal experimental design. The first stage is to verify global or pointwise parameter identifiability, the second stage to find optimal input fluxes, and finally remove redundant measurements