Multidrug-resistant (MDR) Acinetobacter baumannii is a critical threat to human health globally. We constructed a genome-scale metabolic model iAB5075 for the hypervirulent, MDR A. baumannii strain AB5075. Predictions of nutrient utilization and gene essentiality were validated using Biolog assay and a transposon mutant library. In vivo transcriptomics data were integrated with iAB5075 to elucidate bacterial metabolic responses to the host environment. iAB5075 contains 1530 metabolites, 2229 reactions, and 1015 genes, and demonstrated high accuracies in predicting nutrient utilization and gene essentiality. At 4 h post-infection, a total of 146 metabolic fluxes were increased and 52 were decreased compared to 2 h post-infection; these included enhanced fluxes through peptidoglycan and lipopolysaccharide biosynthesis, tricarboxylic cycle, gluconeogenesis, nucleotide and fatty acid biosynthesis, and altered fluxes in amino acid metabolism. These flux changes indicate that the induced central metabolism, energy production, and cell membrane biogenesis played key roles in establishing and enhancing A. baumannii bloodstream infection. This study is the first to employ genome-scale metabolic modeling to investigate A. baumannii infection in vivo. Our findings provide important mechanistic insights into the adaption of A. baumannii to the host environment and thus will contribute to the development of new therapeutic agents against this problematic pathogen.

Motivation Large metabolic models, including genome-scale metabolic models (GSMMs), are nowadays common in systems biology, biotechnology and pharmacology. They typically contain thousands of metabolites and reactions and therefore methods for their automatic visualisation and interactive exploration can facilitate a better understanding of these models. Results We developed a novel method for the visual exploration of large metabolic models and implemented it in LMME (Large Metabolic Model Explorer), an add-on for the biological network analysis tool VANTED. The underlying idea of our method is to analyse a large model as follows. Starting from a decomposition into several subsystems, relationships between these subsystems are identified and an overview is computed and visualised. From this overview, detailed subviews may be constructed and visualised in order to explore subsystems and relationships in greater detail. Decompositions may either be predefined or computed, using built-in or self-implemented methods. Realised as add-on for VANTED, LMME is embedded in a domain-specific environment, allowing for further related analysis at any stage during the exploration. We describe the method, provide a use case, and discuss the strengths and weaknesses of different decomposition methods. Availability The methods and algorithms presented here are implemented in LMME, an open-source add-on for VANTED. LMME can be downloaded from www.cls.uni-konstanz.de/software/lmme and VANTED can be downloaded from www.vanted.org. The source code of LMME is available from GitHub, at https://github.com/LSI-UniKonstanz/lmme.

The Tiled Stereoscopic 3D Display Wall (TS3DW) is a monitor system consisting of six consumer 3D TVs. Two monitors reside on a mobile display mount. One standard configuration is to use them in a 135-degree angle to each other, having one mobile mount in the center, and one at each side. In this way, the system can be transported to multiple locations across a campus as well as used in different application scenarios. This system was already used for a number of research projects and presentations. In this work, we present the concept, applications and evaluation of the implemented system. First, we will discuss the hardware setup, the passive circular polarization technology provided by the LG 3D TVs and its limitations. Then, two application cases making use of Stereoscopic 3D visualization will be discussed and compared to previous work: • Visualization and Analysis of Bird Trajectories, • Visualization and Analysis of Meteorite Data. Finally, we discuss a comprehensive evaluation of the system and its stereoscopic capabilities featuring 16 participants with different body heights. Three major questions were evaluated: • Is TS3DW an appropriate environment for group presentations? • If so, which aspects have to be taken into account during its configuration? • Does TS3DW show potential to be used in the context of static and/or dynamic bird visualization?

Figure 1: TEAMwISE on a tiled display wall, showing several synchronised view perspectives on a flock of storks: Overview (lower right), focus bird (upper right), and use of thermals in the flock, with altitude analysis charts and data windows (left).

Biomolecular networks, including genome-scale metabolic models (GSMMs), assemble the knowledge regarding the biological processes that happen inside specific organisms in a way that allows for analysis, simulation, and exploration. With the increasing availability of genome annotations and the development of powerful reconstruction tools, biomolecular networks continue to grow ever larger. While visual exploration can facilitate the understanding of such networks, the network sizes represent a major challenge for current visualisation systems. Building on promising results from the area of immersive analytics, which among others deals with the potential of immersive visualisation for data analysis, we present a concept for a hybrid user interface that combines a classical desktop environment with a virtual reality environment for the visual exploration of large biomolecular networks and corresponding data. We present system requirements and design considerations, describe a resulting concept, an envisioned technical realisation, and a systems biology usage scenario. Finally, we discuss remaining challenges.