Publications by authors named "Falk Schreiber"

104 Publications

Visual Exploration of Large Metabolic Models.

Bioinformatics 2021 May 10. Epub 2021 May 10.

Department of Computer and Information Science, University of Konstanz, Konstanz, Germany.

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.
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http://dx.doi.org/10.1093/bioinformatics/btab335DOI Listing
May 2021

Genome-Scale Metabolic Modeling Reveals Metabolic Alterations of Multidrug-Resistant in a Murine Bloodstream Infection Model.

Microorganisms 2020 Nov 16;8(11). Epub 2020 Nov 16.

Infection and Immunity Program, Department of Microbiology, Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia.

Multidrug-resistant (MDR) is a critical threat to human health globally. We constructed a genome-scale metabolic model AB5075 for the hypervirulent, MDR 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 AB5075 to elucidate bacterial metabolic responses to the host environment. AB5075 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 bloodstream infection. This study is the first to employ genome-scale metabolic modeling to investigate infection in vivo. Our findings provide important mechanistic insights into the adaption of to the host environment and thus will contribute to the development of new therapeutic agents against this problematic pathogen.
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http://dx.doi.org/10.3390/microorganisms8111793DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7696501PMC
November 2020

Simulations of octapeptin-outer membrane interactions reveal conformational flexibility is linked to antimicrobial potency.

J Biol Chem 2020 11 10;295(47):15902-15912. Epub 2020 Sep 10.

Biomedicine Discovery Institute, Infection & Immunity Program, Department of Microbiology, Monash University, Melbourne, Victoria, Australia. Electronic address:

The octapeptins are lipopeptide antibiotics that are structurally similar to polymyxins yet retain activity against polymyxin-resistant Gram-negative pathogens, suggesting they might be used to treat recalcitrant infections. However, the basis of their unique activity is unclear because of the difficulty in generating high-resolution experimental data of the interaction of antimicrobial peptides with lipid membranes. To elucidate these structure-activity relationships, we employed all-atom molecular dynamics simulations with umbrella sampling to investigate the conformational and energetic landscape of octapeptins interacting with bacterial outer membrane (OM). Specifically, we examined the interaction of octapeptin C4 and FADDI-115, lacking a single hydroxyl group compared with octapeptin C4, with the lipid A-phosphoethanolamine modified OM of Octapeptin C4 and FADDI-115 both penetrated into the OM hydrophobic center but experienced different conformational transitions from an unfolded to a folded state that was highly dependent on the structural flexibility of their respective N-terminal fatty acyl groups. The additional hydroxyl group present in the fatty acyl group of octapeptin C4 resulted in the molecule becoming trapped in a semifolded state, leading to a higher free energy barrier for OM penetration. The free energy barrier for the translocation through the OM hydrophobic layer was ∼72 kcal/mol for octapeptin C4 and 62 kcal/mol for FADDI-115. Our results help to explain the lower antimicrobial activity previously observed for octapeptin C4 compared with FADDI-115 and more broadly improve our understanding of the structure-function relationships of octapeptins. These findings may facilitate the discovery of next-generation octapeptins against polymyxin-resistant Gram-negative 'superbugs.'
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http://dx.doi.org/10.1074/jbc.RA120.014856DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7681018PMC
November 2020

Molecular dynamics simulations informed by membrane lipidomics reveal the structure-interaction relationship of polymyxins with the lipid A-based outer membrane of Acinetobacter baumannii.

J Antimicrob Chemother 2020 12;75(12):3534-3543

Biomedicine Discovery Institute, Infection & Immunity Program and Department of Microbiology, Monash University, Melbourne, Australia.

Background: MDR bacteria represent an urgent threat to human health globally. Polymyxins are a last-line therapy against life-threatening Gram-negative 'superbugs', including Acinetobacter baumannii. Polymyxins exert antimicrobial activity primarily via permeabilizing the bacterial outer membrane (OM); however, the mechanism of interaction between polymyxins and the OM remains unclear at the atomic level.

Methods: We constructed a lipid A-based OM model of A. baumannii using quantitative membrane lipidomics data and employed all-atom molecular dynamics simulations with umbrella sampling techniques to elucidate the structure-interaction relationship and thermodynamics governing the penetration of polymyxins [B1 and E1 (i.e. colistin A) representing the two clinically used polymyxins] into the OM.

Results: Polymyxin B1 and colistin A bound to the A. baumannii OM by the initial electrostatic interactions between the Dab residues of polymyxins and the phosphates of lipid A, competitively displacing the cations from the headgroup region of the OM. Both polymyxin B1 and colistin A formed a unique folded conformation upon approaching the hydrophobic centre of the OM, consistent with previous experimental observations. Polymyxin penetration induced reorientation of the headgroups of the OM lipids near the penetration site and caused local membrane disorganization, thereby significantly increasing membrane permeability and promoting the subsequent penetration of polymyxin molecules into the OM and periplasmic space.

Conclusions: The thermodynamics governing the penetration of polymyxins through the outer leaflet of the A. baumannii OM were examined and novel structure-interaction relationship information was obtained at the atomic and membrane level. Our findings will facilitate the discovery of novel polymyxins against MDR Gram-negative pathogens.
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http://dx.doi.org/10.1093/jac/dkaa376DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7662177PMC
December 2020

Outer Membranes of Polymyxin-Resistant with Phosphoethanolamine-Modified Lipid A and Lipopolysaccharide Loss Display Different Atomic-Scale Interactions with Polymyxins.

ACS Infect Dis 2020 10 15;6(10):2698-2708. Epub 2020 Sep 15.

Biomedicine Discovery Institute, Infection & Immunity Program, Department of Microbiology, Monash University, Melbourne, VIC 3800, Australia.

Resistance to the last-line polymyxins is increasingly reported in multidrug-resistant Gram-negative pathogens, including , which develops resistance via either lipid A modification (e.g., with phosphoethanolamine [pEtN]) or even lipopolysaccharide (LPS) loss in the outer membrane (OM). Considering these two different mechanisms, quantitative membrane lipidomics data were utilized to develop three OM models representing polymyxin-susceptible and -resistant strains. Through all-atom molecular simulations with enhanced sampling techniques, the effect of lipid A-pEtN modification and LPS loss on the action of colistin (i.e., polymyxin E) was examined for the first time, with a focus on the dynamics and energetics of colistin penetration into these OMs. Lipid A-pEtN modification improved the OM stability, impeding the penetration of colistin into the OM; this differed from the current literature that lipid A-pEtN modification confers resistance by diminishing the initial interaction with polymyxins. In contrast, the LPS deficiency significantly reduced the negative charges on the OM surface, diminishing the binding of colistin. Moreover, both lipid A-pEtN modification and LPS loss also constituted colistin resistance through disturbing the conformational transitions of the colistin molecule. Collectively, atomic-scale interactions between polymyxins and different bacterial OMs are very different and the findings may facilitate the discovery of new-generation polymyxins against Gram-negative 'superbugs'.
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http://dx.doi.org/10.1021/acsinfecdis.0c00330DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7554230PMC
October 2020

Polymyxins Bind to the Cell Surface of Unculturable and Cause Unique Dependent Resistance.

Adv Sci (Weinh) 2020 Aug 8;7(15):2000704. Epub 2020 Jun 8.

Infection & Immunity Program Biomedicine Discovery Institute and Department of Microbiology Monash University Melbourne 3800 Australia.

Multidrug-resistant is a top-priority pathogen globally and polymyxins are a last-line therapy. Polymyxin dependence in (i.e., nonculturable on agar without polymyxins) is a unique and highly-resistant phenotype with a significant potential to cause treatment failure in patients. The present study discovers that a polymyxin-dependent strain possesses mutations in both (lipopolysaccharide biosynthesis) and (reactive oxygen species scavenging) genes. Correlative multiomics analyses show a significantly remodeled cell envelope and remarkably abundant phosphatidylglycerol in the outer membrane (OM). Molecular dynamics simulations and quantitative membrane lipidomics reveal that polymyxin-dependent growth emerges only when the lipopolysaccharide-deficient OM distinctively remodels with ≥ 35% phosphatidylglycerol, and with "patch" binding on the OM by the rigid polymyxin molecules containing strong intramolecular hydrogen bonding. Rather than damaging the OM, polymyxins bind to the phosphatidylglycerol-rich OM and strengthen the membrane integrity, thereby protecting bacteria from external reactive oxygen species. Dependent growth is observed exclusively with polymyxin analogues, indicating a critical role of the specific amino acid sequence of polymyxins in forming unique structures for patch-binding to bacterial OM. Polymyxin dependence is a novel antibiotic resistance mechanism and the current findings highlight the risk of 'invisible' polymyxin-dependent isolates in the evolution of resistance.
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http://dx.doi.org/10.1002/advs.202000704DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7403960PMC
August 2020

Specifications of standards in systems and synthetic biology: status and developments in 2020.

J Integr Bioinform 2020 Jun 29;17(2-3). Epub 2020 Jun 29.

University Medicine Greifswald, Greifswald, Germany.

This special issue of the Journal of Integrative Bioinformatics presents papers related to the 10th COMBINE meeting together with the annual update of COMBINE standards in systems and synthetic biology.
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http://dx.doi.org/10.1515/jib-2020-0022DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7756620PMC
June 2020

The first 10 years of the international coordination network for standards in systems and synthetic biology (COMBINE).

J Integr Bioinform 2020 Jun 29;17(2-3). Epub 2020 Jun 29.

Centre for Discovery Brain Sciences, The University of Edinburgh, Edinburgh, UK.

This paper presents a report on outcomes of the 10th Computational Modeling in Biology Network (COMBINE) meeting that was held in Heidelberg, Germany, in July of 2019. The annual event brings together researchers, biocurators and software engineers to present recent results and discuss future work in the area of standards for systems and synthetic biology. The COMBINE initiative coordinates the development of various community standards and formats for computational models in the life sciences. Over the past 10 years, COMBINE has brought together standard communities that have further developed and harmonized their standards for better interoperability of models and data. COMBINE 2019 was co-located with a stakeholder workshop of the European EU-STANDS4PM initiative that aims at harmonized data and model standardization for in silico models in the field of personalized medicine, as well as with the FAIRDOM PALs meeting to discuss findable, accessible, interoperable and reusable (FAIR) data sharing. This report briefly describes the work discussed in invited and contributed talks as well as during breakout sessions. It also highlights recent advancements in data, model, and annotation standardization efforts. Finally, this report concludes with some challenges and opportunities that this community will face during the next 10 years.
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http://dx.doi.org/10.1515/jib-2020-0005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7756615PMC
June 2020

Erratum to Machine learning prediction of cyanobacterial toxin (microcystin) toxicodynamics in humans.

ALTEX 2020 ;37(2):337-338

Human and Environmental Toxicology, University of Konstanz, Konstanz, Germany.

In this manuscript, which appeared in ALTEX (2020), 37(1), 24-36, doi:10.14573/altex.1904031 , there were errors in Tables 1 and 3.
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http://dx.doi.org/10.14573/altex.1904031eDOI Listing
January 2020

JIB.tools 2.0 - A Bioinformatics Registry for Journal Published Tools with Interoperability to bio.tools.

J Integr Bioinform 2020 Jan 8;16(4). Epub 2020 Jan 8.

Royal College of Art, School of Design, London, UK.

JIB.tools 2.0 is a new approach to more closely embed the curation process in the publication process. This website hosts the tools, software applications, databases and workflow systems published in the Journal of Integrative Bioinformatics (JIB). As soon as a new tool-related publication is published in JIB, the tool is posted to JIB.tools and can afterwards be easily transferred to bio.tools, a large information repository of software tools, databases and services for bioinformatics and the life sciences. In this way, an easily-accessible list of tools is provided which were published in JIB a well as status information regarding the underlying service. With newer registries like bio.tools providing these information on a bigger scale, JIB.tools 2.0 closes the gap between journal publications and registry publication. (Reference: https://jib.tools).
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http://dx.doi.org/10.1515/jib-2019-0059DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7074141PMC
January 2020

Corrigendum to A high-throughput approach to identify specific neurotoxicants / developmental toxicants in human neuronal cell function assays.

ALTEX 2019 ;36(3):505

In vitro Toxicology and Biomedicine, Dept inaugurated by the Doerenkamp-Zbinden foundation, University of Konstanz, Konstanz, Germany.

In this manuscript, which appeared in ALTEX 35 , 235-253 ( doi:10.14573/altex.1712182 ), the Acknowledgements should read: This work was supported by the Land BW, the Doerenkamp-Zbinden Foundation, the DFG (RTG1331, KoRS-CB), the BMBF (NeuriTox), and it has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 681002 (EU-ToxRisk).
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http://dx.doi.org/10.14573/altex.1904111DOI Listing
January 2019

Specifications of Standards in Systems and Synthetic Biology: Status and Developments in 2019.

J Integr Bioinform 2019 Jul 13;16(2). Epub 2019 Jul 13.

University Medicine Greifswald, Greifswald, Germany.

This special issue of the Journal of Integrative Bioinformatics presents an overview of COMBINE standards and their latest specifications. The standards cover representation formats for computational modeling in synthetic and systems biology and include BioPAX, CellML, NeuroML, SBML, SBGN, SBOL and SED-ML. The articles in this issue contain updated specifications of SBGN Process Description Level 1 Version 2, SBML Level 3 Core Version 2 Release 2, SBOL Version 2.3.0, and SBOL Visual Version 2.1.
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http://dx.doi.org/10.1515/jib-2019-0035DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6798822PMC
July 2019

Machine learning prediction of cyanobacterial toxin (microcystin) toxicodynamics in humans.

ALTEX 2020 2;37(1):24-36. Epub 2019 Jul 2.

Human and Environmental Toxicology, University of Konstanz, Konstanz, Germany.

Microcystins (MC) represent a family of cyclic peptides with approx. 250 congeners presumed harmful to human health due to their ability to inhibit ser/thr-proteinphosphatases (PPP), albeit all hazard and risk assessments (RA) are based on data of one MC-congener (MC-LR) only. MC congener structural diversity is a challenge for the risk assessment of these toxins, especially as several different PPPs have to be included in the RA. Consequently, the inhibition of PPP1, PPP2A and PPP5 was determined with 18 structurally different MC and demonstrated MC congener dependent inhibition activity and a lower susceptibility of PPP5 to inhibition than PPP1 and PPP2A. The latter data were employed to train a machine learning algorithm that should allow prediction of PPP inhibition (toxicity) based on MCs 2D chemical structure. IC50 values were classified in toxicity classes and three machine learning models were used to predict the toxicity class, resulting in 80-90% correct predictions.
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http://dx.doi.org/10.14573/altex.1904031DOI Listing
November 2020

Mental-Map Preserving Visualisation of Partitioned Networks in Vanted.

J Integr Bioinform 2019 Jun 14;16(3). Epub 2019 Jun 14.

Department of Computer and Information Science, University of Konstanz, 78464 Konstanz, Germany.

Biological networks can be large and complex, often consisting of different sub-networks or parts. Separation of networks into parts, network partitioning and layouts of overview and sub-graphs are of importance for understandable visualisations of those networks. This article presents NetPartVis to visualise non-overlapping clusters or partitions of graphs in the Vanted framework based on a method for laying out overview graph and several sub-graphs (partitions) in a coordinated, mental-map preserving way.
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http://dx.doi.org/10.1515/jib-2019-0026DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6798853PMC
June 2019

Systems Biology Graphical Notation: Process Description language Level 1 Version 2.0.

J Integr Bioinform 2019 Jun 13;16(2). Epub 2019 Jun 13.

cBio Center, Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA 02215, USA.

The Systems Biology Graphical Notation (SBGN) is an international community effort that aims to standardise the visualisation of pathways and networks for readers with diverse scientific backgrounds as well as to support an efficient and accurate exchange of biological knowledge between disparate research communities, industry, and other players in systems biology. SBGN comprises the three languages Entity Relationship, Activity Flow, and Process Description (PD) to cover biological and biochemical systems at distinct levels of detail. PD is closest to metabolic and regulatory pathways found in biological literature and textbooks. Its well-defined semantics offer a superior precision in expressing biological knowledge. PD represents mechanistic and temporal dependencies of biological interactions and transformations as a graph. Its different types of nodes include entity pools (e.g. metabolites, proteins, genes and complexes) and processes (e.g. reactions, associations and influences). The edges describe relationships between the nodes (e.g. consumption, production, stimulation and inhibition). This document details Level 1 Version 2.0 of the PD specification, including several improvements, in particular: 1) the addition of the equivalence operator, subunit, and annotation glyphs, 2) modification to the usage of submaps, and 3) updates to clarify the use of various glyphs (i.e. multimer, empty set, and state variable).
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http://dx.doi.org/10.1515/jib-2019-0022DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6798820PMC
June 2019

Corrigendum to Stage-specific metabolic features of differentiating neurons: Implications for toxicant sensitivity Toxicol Appl Pharmacol, 354 (2018) 64-80.

Toxicol Appl Pharmacol 2019 Jun 16;372:70. Epub 2019 Apr 16.

In Vitro Toxicology and Biomedicine, Dept Inaugurated by the Doerenkamp-Zbinden Foundation, University of Konstanz, 78457 Konstanz, Germany; CAAT-Europe, University of Konstanz, Konstanz 78457, Germany. Electronic address:

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http://dx.doi.org/10.1016/j.taap.2019.04.010DOI Listing
June 2019

Fly with the flock: immersive solutions for animal movement visualization and analytics.

J R Soc Interface 2019 04;16(153):20180794

1 Department of Computer and Information Science, University of Konstanz , Fach 76, 78457 Konstanz , Germany.

Understanding the movement of animals is important for a wide range of scientific interests including migration, disease spread, collective movement behaviour and analysing motion in relation to dynamic changes of the environment such as wind and thermal lifts. Particularly, the three-dimensional (3D) spatial-temporal nature of bird movement data, which is widely available with high temporal and spatial resolution at large volumes, presents a natural option to explore the potential of immersive analytics (IA). We investigate the requirements and benefits of a wide range of immersive environments for explorative visualization and analytics of 3D movement data, in particular regarding design considerations for such 3D immersive environments, and present prototypes for IA solutions. Tailored to biologists studying bird movement data, the immersive solutions enable geo-locational time-series data to be investigated interactively, thus enabling experts to visually explore interesting angles of a flock and its behaviour in the context of the environment. The 3D virtual world presents the audience with engaging and interactive content, allowing users to 'fly with the flock', with the potential to ascertain an intuitive overview of often complex datasets, and to provide the opportunity thereby to formulate and at least qualitatively assess hypotheses. This work also contributes to ongoing research efforts to promote better understanding of bird migration and the associated environmental factors at the global scale, thereby providing a visual vehicle for driving public awareness of environmental issues and bird migration patterns.
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http://dx.doi.org/10.1098/rsif.2018.0794DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6505562PMC
April 2019

Metabolic Responses to Polymyxin Treatment in ATCC 19606: Integrating Transcriptomics and Metabolomics with Genome-Scale Metabolic Modeling.

mSystems 2019 Jan-Feb;4(1). Epub 2019 Feb 5.

Infection & Immunity Program, Monash Biomedicine Discovery Institute and Department of Microbiology, Monash University, Melbourne, Australia.

Multidrug-resistant (MDR) Acinetobacter baumannii has emerged as a very problematic pathogen over the past decades, with a high incidence in nosocomial infections. Discovered in the late 1940s but abandoned in the 1970s, polymyxins (i.e., polymyxin B and colistin) have been revived as the last-line therapy against Gram-negative "superbugs," including MDR A. baumannii. Worryingly, resistance to polymyxins in A. baumannii has been increasingly reported, urging the development of novel antimicrobial therapies to rescue this last-line class of antibiotics. In the present study, we integrated genome-scale metabolic modeling with multiomics data to elucidate the mechanisms of cellular responses to colistin treatment in A. baumannii. A genome-scale metabolic model, ATCC19606, was constructed for strain ATCC 19606 based on the literature and genome annotation, containing 897 genes, 1,270 reactions, and 1,180 metabolites. After extensive curation, prediction of growth on 190 carbon sources using ATCC19606 achieved an overall accuracy of 84.3% compared to Biolog experimental results. Prediction of gene essentiality reached a high accuracy of 86.1% and 82.7% compared to two transposon mutant libraries of AB5075 and ATCC 17978, respectively. Further integrative modeling with our correlative transcriptomics and metabolomics data deciphered the complex regulation on metabolic responses to colistin treatment, including (i) upregulated fluxes through gluconeogenesis, the pentose phosphate pathway, and amino acid and nucleotide biosynthesis; (ii) downregulated TCA cycle and peptidoglycan and lipopolysaccharide biogenesis; and (iii) altered fluxes over respiratory chain. Our results elucidated the interplay of multiple metabolic pathways under colistin treatment in A. baumannii and provide key mechanistic insights into optimizing polymyxin combination therapy. Combating antimicrobial resistance has been highlighted as a critical global health priority. Due to the drying drug discovery pipeline, polymyxins have been employed as the last-line therapy against Gram-negative "superbugs"; however, the detailed mechanisms of antibacterial killing remain largely unclear, hampering the improvement of polymyxin therapy. Our integrative modeling using the constructed genome-scale metabolic model ATCC19606 and the correlative multiomics data provide the fundamental understanding of the complex metabolic responses to polymyxin treatment in A. baumannii at the systems level. The model ATCC19606 may have a significant potential in antimicrobial systems pharmacology research in A. baumannii.
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http://dx.doi.org/10.1128/mSystems.00157-18DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6365644PMC
February 2019

Heuristic Modeling and 3D Stereoscopic Visualization of a Chlamydomonas reinhardtii Cell.

J Integr Bioinform 2018 Jul 11;15(2). Epub 2018 Jul 11.

Computational Life Sciences, Department of Computer and Information Science, University of Konstanz, Konstanz, Germany.

The structural modeling and representation of cells is a complex task as different microscopic, spectroscopic and other information resources have to be combined to achieve a three-dimensional representation with high accuracy. Moreover, to provide an appropriate spatial representation of the cell, a stereoscopic 3D (S3D) visualization is favorable. In this work, a structural cell model is created by combining information from various light microscopic and electron microscopic images as well as from publication-related data. At the mesoscopic level each cell component is presented with special structural and visual properties; at the molecular level a cell membrane composition and the underlying modeling method are discussed; and structural information is correlated with those at the functional level (represented by simplified energy-producing metabolic pathways). The organism used as an example is the unicellular Chlamydomonas reinhardtii, which might be important in future alternative energy production processes. Based on the 3D model, an educative S3D animation was created which was shown at conferences. The complete workflow was accomplished by using the open source 3D modeling software Blender. The discussed project including the animation is available from: http://Cm5.CELLmicrocosmos.org.
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http://dx.doi.org/10.1515/jib-2018-0003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6167046PMC
July 2018

The Virtual-Spine Platform-Acquiring, visualizing, and analyzing individual sitting behavior.

PLoS One 2018 13;13(6):e0195670. Epub 2018 Jun 13.

Department of Computer and Information Science, University of Konstanz, Konstanz, Baden-Württemberg, Germany.

Back pain is a serious medical problem especially for those people sitting over long periods during their daily work. Here we present a system to help users monitoring and examining their sitting behavior. The Virtual-Spine Platform (VSP) is an integrated system consisting of a real-time body position monitoring module and a data visualization module to provide individualized, immediate, and accurate sitting behavior support. It provides a comprehensive spine movement analysis as well as accumulated data visualization to demonstrate behavior patterns within a certain period. The two modules are discussed in detail focusing on the design of the VSP system with adequate capacity for continuous monitoring and a web-based interactive data analysis method to visualize and compare the sitting behavior of different persons. The data was collected in an experiment with a small group of subjects. Using this method, the behavior of five subjects was evaluated over a working day, enabling inferences and suggestions for sitting improvements. The results from the accumulated data module were used to elucidate the basic function of body position recognition of the VSP. Finally, an expert user study was conducted to evaluate VSP and support future developments.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0195670PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5999082PMC
November 2018

Genome-scale metabolic modeling of responses to polymyxins in Pseudomonas aeruginosa.

Gigascience 2018 04;7(4)

Monash Biomedicine Discovery Institute, Department of Microbiology, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne 3800, Australia.

Background: Pseudomonas aeruginosa often causes multidrug-resistant infections in immunocompromised patients, and polymyxins are often used as the last-line therapy. Alarmingly, resistance to polymyxins has been increasingly reported worldwide recently. To rescue this last-resort class of antibiotics, it is necessary to systematically understand how P. aeruginosa alters its metabolism in response to polymyxin treatment, thereby facilitating the development of effective therapies. To this end, a genome-scale metabolic model (GSMM) was used to analyze bacterial metabolic changes at the systems level.

Findings: A high-quality GSMM iPAO1 was constructed for P. aeruginosa PAO1 for antimicrobial pharmacological research. Model iPAO1 encompasses an additional periplasmic compartment and contains 3022 metabolites, 4265 reactions, and 1458 genes in total. Growth prediction on 190 carbon and 95 nitrogen sources achieved an accuracy of 89.1%, outperforming all reported P. aeruginosa models. Notably, prediction of the essential genes for growth achieved a high accuracy of 87.9%. Metabolic simulation showed that lipid A modifications associated with polymyxin resistance exert a limited impact on bacterial growth and metabolism but remarkably change the physiochemical properties of the outer membrane. Modeling with transcriptomics constraints revealed a broad range of metabolic responses to polymyxin treatment, including reduced biomass synthesis, upregulated amino acid catabolism, induced flux through the tricarboxylic acid cycle, and increased redox turnover.

Conclusions: Overall, iPAO1 represents the most comprehensive GSMM constructed to date for Pseudomonas. It provides a powerful systems pharmacology platform for the elucidation of complex killing mechanisms of antibiotics.
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http://dx.doi.org/10.1093/gigascience/giy021DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6333913PMC
April 2018

Specifications of Standards in Systems and Synthetic Biology: Status and Developments in 2017.

J Integr Bioinform 2018 Mar 29;15(1). Epub 2018 Mar 29.

University of Rostock, Rostock, Germany.

Standards are essential to the advancement of Systems and Synthetic Biology. COMBINE provides a formal body and a centralised platform to help develop and disseminate relevant standards and related resources. The regular special issue of the Journal of Integrative Bioinformatics aims to support the exchange, distribution and archiving of these standards by providing unified, easily citable access. This paper provides an overview of existing COMBINE standards and presents developments of the last year.
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http://dx.doi.org/10.1515/jib-2018-0013DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6167034PMC
March 2018

A high-throughput approach to identify specific neurotoxicants/ developmental toxicants in human neuronal cell function assays.

ALTEX 2018 21;35(2):235-253. Epub 2018 Jan 21.

In vitro Toxicology and Biomedicine, Dept inaugurated by the Doerenkamp-Zbinden foundation, University of Konstanz, Konstanz, Germany.

The (developmental) neurotoxicity hazard is still unknown for most chemicals. Establishing a test battery covering most of the relevant adverse outcome pathways may close this gap, without requiring a huge animal experimentation program. Ideally, each of the assays would cover multiple mechanisms of toxicity. One candidate test is the human LUHMES cell-based NeuriTox test. To evaluate its readiness for larger-scale testing, a proof of concept library assembled by the U.S. National Toxicology Program (NTP) was screened. Of the 75 unique compounds, seven were defined as specifically neurotoxic after the hit-confirmation phase and additional ten compounds were generally cytotoxic within the concentration range of up to 20 micromolar. As complementary approach, the library was screened in the PeriTox test, which identifies toxicants affecting the human peripheral nervous system. Of the eight PeriTox hits, five were similar to the NeuriTox hits: rotenone, colchicine, diethylstilbestrol, berberine chloride, and valinomycin. The unique NeuriTox hit, methyl-phenylpyridinium (MPP+) is known from in vivo studies to affect only dopaminergic neurons (which LUHMES cells are). Conversely, the known peripheral neurotoxicant acrylamide was picked up in the PeriTox, but not in the NeuriTox assay. All of the five common hits had also been identified in the published neural crest migration (cMINC) assay, while none of them emerged as cardiotoxicant in a previous screen using the same library. These comparative data suggest that complementary in vitro tests can pick up a broad range of toxicants, and that multiple test results might help to predict organ specificity patterns.
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http://dx.doi.org/10.14573/altex.1712182DOI Listing
January 2019

Stage-specific metabolic features of differentiating neurons: Implications for toxicant sensitivity.

Toxicol Appl Pharmacol 2018 09 24;354:64-80. Epub 2017 Dec 24.

In Vitro Toxicology and Biomedicine, Dept Inaugurated by the Doerenkamp-Zbinden Foundation, University of Konstanz, 78457 Konstanz, Germany; CAAT-Europe, University of Konstanz, Konstanz 78457, Germany. Electronic address:

Developmental neurotoxicity (DNT) may be induced when chemicals disturb a key neurodevelopmental process, and many tests focus on this type of toxicity. Alternatively, DNT may occur when chemicals are cytotoxic only during a specific neurodevelopmental stage. The toxicant sensitivity is affected by the expression of toxicant targets and by resilience factors. Although cellular metabolism plays an important role, little is known how it changes during human neurogenesis, and how potential alterations affect toxicant sensitivity of mature vs. immature neurons. We used immature (d0) and mature (d6) LUHMES cells (dopaminergic human neurons) to provide initial answers to these questions. Transcriptome profiling and characterization of energy metabolism suggested a switch from predominantly glycolytic energy generation to a more pronounced contribution of the tricarboxylic acid cycle (TCA) during neuronal maturation. Therefore, we used pulsed stable isotope-resolved metabolomics (pSIRM) to determine intracellular metabolite pool sizes (concentrations), and isotopically non-stationary C-metabolic flux analysis (INST C-MFA) to calculate metabolic fluxes. We found that d0 cells mainly use glutamine to fuel the TCA. Furthermore, they rely on extracellular pyruvate to allow continuous growth. This metabolic situation does not allow for mitochondrial or glycolytic spare capacity, i.e. the ability to adapt energy generation to altered needs. Accordingly, neuronal precursor cells displayed a higher sensitivity to several mitochondrial toxicants than mature neurons differentiated from them. In summary, this study shows that precursor cells lose their glutamine dependency during differentiation while they gain flexibility of energy generation and thereby increase their resistance to low concentrations of mitochondrial toxicants.
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http://dx.doi.org/10.1016/j.taap.2017.12.013DOI Listing
September 2018

BioVis Explorer: A visual guide for biological data visualization techniques.

PLoS One 2017 1;12(11):e0187341. Epub 2017 Nov 1.

Faculty of Information Technology, Monash University, Clayton, Australia.

Data visualization is of increasing importance in the Biosciences. During the past 15 years, a great number of novel methods and tools for the visualization of biological data have been developed and published in various journals and conference proceedings. As a consequence, keeping an overview of state-of-the-art visualization research has become increasingly challenging for both biology researchers and visualization researchers. To address this challenge, we have reviewed visualization research especially performed for the Biosciences and created an interactive web-based visualization tool, the BioVis Explorer. BioVis Explorer allows the exploration of published visualization methods in interactive and intuitive ways, including faceted browsing and associations with related methods. The tool is publicly available online and has been designed as community-based system which allows users to add their works easily.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0187341PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5665558PMC
December 2017

Specifications of Standards in Systems and Synthetic Biology: Status and Developments in 2016.

J Integr Bioinform 2016 Dec 18;13(3):289. Epub 2016 Dec 18.

Standards are essential to the advancement of science and technology. In systems and synthetic biology, numerous standards and associated tools have been developed over the last 16 years. This special issue of the Journal of Integrative Bioinformatics aims to support the exchange, distribution and archiving of these standards, as well as to provide centralised and easily citable access to them.
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http://dx.doi.org/10.2390/biecoll-jib-2016-289DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5431574PMC
December 2016