Reconstruction of an in silico metabolic model of _Arabidopsis thaliana_ through database integration

The number of genome-scale metabolic models has been rising quickly in recent years, and the scope of their utilization encompasses a broad range of applications from metabolic engineering to biological discovery. However the reconstruction of such models remains an arduous process requiring a high level of human intervention. Their utilization is further hampered by the absence of standardized data and annotation formats and the lack of recognized quality and validation standards.

Plants provide a particularly rich range of perspectives for applications of metabolic modeling. We here report the first effort to the reconstruction of a genome-scale model of the metabolic network of the plant _Arabidopsis thaliana_, including over 2300 reactions and compounds. Our reconstruction was performed using a semi-automatic methodology based on the integration of two public genome-wide databases, significantly accelerating the process. Database entries were compared and integrated with each other, allowing us to resolve discrepancies and enhance the quality of the reconstruction. This process lead to the construction of three models based on different quality and validation standards, providing users with the possibility to choose the standard that is most appropriate for a given application. First, a _core metabolic model_ containing only consistent data provides a high quality model that was shown to be stoichiometrically consistent. Second, an _intermediate metabolic model_ attempts to fill gaps and provides better continuity. Third, a _complete metabolic model_ contains the full set of known metabolic reactions and compounds in _Arabidopsis thaliana_.

We provide an annotated SBML file of our core model to enable the maximum level of compatibility with existing tools and databases. We eventually discuss a series of principles to raise awareness of the need to develop coordinated efforts and common standards for the reconstruction of genome-scale metabolic models, with the aim of enabling their widespread diffusion, frequent update, maximum compatibility and convenience of use by the wider research community and industry

Rhea—a manually curated resource of biochemical reactions

Rhea (http://www.ebi.ac.uk/rhea) is a comprehensive resource of expert-curated biochemical reactions. Rhea provides a non-redundant set of chemical transformations for use in a broad spectrum of applications, including metabolic network reconstruction and pathway inference. Rhea includes enzyme-catalyzed reactions (covering the IUBMB Enzyme Nomenclature list), transport reactions and spontaneously occurring reactions. Rhea reactions are described using chemical species from the Chemical Entities of Biological Interest ontology (ChEBI) and are stoichiometrically balanced for mass and charge. They are extensively manually curated with links to source literature and other public resources on metabolism including enzyme and pathway databases. This cross-referencing facilitates the mapping and reconciliation of common reactions and compounds between distinct resources, which is a common first step in the reconstruction of genome scale metabolic networks and models

Multispectral methods for biological sensing and imaging. Theory and experiments.  

Multispectral molecular imaging exhibits the unique potential to simultaneously probe multiple molecules in living objects. This thesis reports on developments realized on methodological and systems level that aim at applying multispectral concepts to molecular imaging. Research was directed towards various application areas, from surface investigations of intrinsic tissue molecules to volumetric imaging of extrinsic molecular markers. The presented results show the capability of multispectral imaging to asses multiple molecules in-vivo, a property which is of tremendous value in systemic biomedical research.&nbsp

Quantitative multi-spectral oxygen saturation measurements independent of tissue optical properties.

Imaging of tissue oxygenation is important in several applications associated with patient care. Optical sensing is commonly applied for assessing oxygen saturation but is often restricted to local measurements or else it requires spectral and spatial information at the expense of time. Many methods proposed so far require assumptions on the properties of measured tissue. In this study we investigated a computational method that uses only multispectral information and quantitatively computes tissue oxygen saturation independently of tissue optical properties. The method is based on linear transformations of measurements in three isosbestic points. We investigated the ideal isosbestic point combination out of six isosbestic points available for measurement in the visible and near-infrared region that enable accurate oxygen saturation computation. We demonstrate this method on controlled tissue mimicking phantoms having different optical properties and validated the measurements using a gas analyzer. A mean error of 2.9 ± 2.8% O2 Sat was achieved. Finally, we performed pilot studies in tissues in-vivo by measuring dynamic changes in fingers subjected to vascular occlusion, the vasculature of mouse ears and exposed mouse organs

Limited-projection-angle hybrid fluorescence molecular tomography of multiple molecules.

An advantage of fluorescence methods over other imaging modalities is the ability to concurrently resolve multiple moieties using fluorochromes emitting at different spectral regions. Simultaneous imaging of spectrally separated agents is helpful in interrogating multiple functions or establishing internal controls for accurate measurements. Herein, we investigated multimoiety imaging in the context of a limited-projection-angle hybrid fluorescence molecular tomography (FMT), and x-ray computed tomography implementation and the further registration with positron emission tomography (PET) data. Multichannel FMT systems may image fluorescent probes of varying distribution patterns. Therefore, it is possible that different channels may require different use of priors and regularization parameters. We examined the performance of automatically estimating regularization factors implementing priors, using data-driven regularization specific for limited-projection-angle schemes. We were particularly interested in identifying the implementation variations between hybrid-FMT channels due to probe distribution variation. For this reason, initial validation of the data-driven algorithm on a phantom was followed by imaging different agent distributions in animals, assuming superficial and deep seated activity. We further demonstrate the benefits of combining hybrid FMT with PET to gain multiple readings on the molecular composition of disease

Improving limited-projection-angle fluorescence molecular tomography using a co-registered x-ray computed tomography scan.

We examine the improvement in imaging performance, such as axial resolution and signal localization, when employing limited-projection-angle fluorescence molecular tomography (FMT) together with x-ray computed tomography (XCT) measurements versus stand-alone FMT. For this purpose, we employed living mice, bearing a spontaneous lung tumor model, and imaged them with FMT and XCT under identical geometrical conditions using fluorescent probes for cancer targeting. The XCT data was employed, herein, as structural prior information to guide the FMT reconstruction. Gold standard images were provided by fluorescence images of mouse cryoslices, providing the ground truth in fluorescence bio-distribution. Upon comparison of FMT images versus images reconstructed using hybrid FMT and XCT data, we demonstrate marked improvements in image accuracy. This work relates to currently disseminated FMT systems, using limited projection scans, and can be employed to enhance their performance

Multispektrale Methoden zur Erfassung und Bildgebung biologischer Prozesse

Multispectral molecular imaging exhibits the unique potential to simultaneously probe multiple molecules in living objects. This thesis reports on developments realized on methodological and systems level that aim at applying multispectral concepts to molecular imaging. Research was directed towards various application areas, from surface investigations of intrinsic tissue molecules to volumetric imaging of extrinsic molecular markers. The presented results show the capability of multispectral imaging to asses multiple molecules in-vivo, a property which is of tremendous value in systemic biomedical research.Multispektrale molekulare Bildgebung hat die einzigartige Eigenschaft, gleichzeitig mehrere Moleküle in lebenden Organismen detektieren zu können. Diese Dissertation befasst sich mit der Entwickung neuer methodologischer Verfahren sowie Systemen zur Anwendung multispektraler Konzepte in der Molekularen Bildgebung. Verschiedene Andwendungsbereiche wurden dabei untersucht, von der oberflächlichen Detektion gewebeeigener Moleküle, zur volumetrischen Erfassung molekularer Marker. Die erzielten Ergebnisse zeigen, dass multispektrale Bildgebung geeignet ist, mehrere Moleküle in-vivo zu detektieren. Dies ist eine wichtige Eigenschaft für den Einsatz in der biomedizinischen Erforschung systemischer Prozesse