Publications

557 Publications visible to you, out of a total of 557

Abstract (Expand)

How an organism copes with chemicals is largely determined by the genes and proteins that collectively function to defend against, detoxify and eliminate chemical stressors. This integrative network includes receptors and transcription factors, biotransformation enzymes, transporters, antioxidants, and metal- and heat-responsive genes, and is collectively known as the chemical defensome. Teleost fish is the largest group of vertebrate species and can provide valuable insights into the evolution and functional diversity of defensome genes. We have previously shown that the xenosensing pregnane x receptor (pxr, nr1i2) is lost in many teleost species, including Atlantic cod (Gadus morhua) and three-spined stickleback (Gasterosteus aculeatus), but it is not known if compensatory mechanisms or signaling pathways have evolved in its absence. In this study, we compared the genes comprising the chemical defensome of five fish species that span the teleosteii evolutionary branch often used as model species in toxicological studies and environmental monitoring programs: zebrafish (Danio rerio), medaka (Oryzias latipes), Atlantic killifish (Fundulus heteroclitus), Atlantic cod, and three-spined stickleback. Genome mining revealed evolved differences in the number and composition of defensome genes that can have implication for how these species sense and respond to environmental pollutants, but we did not observe any candidates of compensatory mechanisms or pathways in cod and stickleback in the absence of pxr. The results indicate that knowledge regarding the diversity and function of the defensome will be important for toxicological testing and risk assessment studies.

Authors: Marta Eide, Xiaokang Zhang, Odd André Karlsen, Jared V. Goldstone, John Stegeman, Inge Jonassen, Anders Goksøyr

Date Published: 1st Dec 2021

Publication Type: Journal

Abstract (Expand)

Structure-based antiviral developments in the past two years have been dominated by the structure determination and inhibition of SARS-CoV-2 proteins and new lead molecules for picornaviruses. The SARS-CoV-2 spike protein has been targeted successfully with antibodies, nanobodies, and receptor protein mimics effectively blocking receptor binding or fusion. The two most promising non-structural proteins sharing strong structural and functional conservation across virus families are the main protease and the RNA-dependent RNA polymerase, for which design and reuse of broad range inhibitors already approved for use has been an attractive avenue. For picornaviruses, the increasing recognition of the transient expansion of the capsid as a critical transition towards RNA release has been targeted through a newly identified, apparently widely conserved, druggable, interprotomer pocket preventing viral entry. We summarize some of the key papers in these areas and ponder the practical uses and contributions of molecular modeling alongside empirical structure determination.

Authors: Zlatka Plavec, Ina Pöhner, Antti Poso, Sarah J Butcher

Date Published: 1st Dec 2021

Publication Type: Journal

Abstract (Expand)

To apply enzymes in technical processes, a detailed understanding of the molecular mechanisms is required. Kinetic and thermodynamic parameters of enzyme catalysis are crucial to plan, model, and implement biocatalytic processes more efficiently. While the kinetic parameters, Km and kcat, are often accessible by optical methods, the determination of thermodynamic parameters requires more sophisticated methods. Isothermal titration calorimetry (ITC) allows the label-free and highly sensitive analysis of kinetic and thermodynamic parameters of individual steps in the catalytic cycle of an enzyme reaction. However, since ITC is susceptible to interferences due to denaturation or agglomeration of the enzymes, the homogeneity of the enzyme sample must always be considered, and this can be accomplished by means of dynamic light scattering (DLS) analysis. We here report on the use of an ITC-dependent work flow to determine both the kinetic and the thermodynamic data for a cofactor-dependent enzyme. Using a standardized approach with the implementation of sample quality control by DLS, we obtain high-quality data suitable for the advanced modeling of the enzyme reaction mechanism. Specifically, we investigated stereoselective reactions catalyzed by the NADPH-dependent ketoreductase Gre2p under different reaction conditions. The results revealed that this enzyme operates with an ordered sequential mechanism and is affected by substrate or product inhibition depending on the reaction buffer. Data reproducibility is ensured by specifying standard operating procedures, using programmed workflows for data analysis, and storing all data in a F.A.I.R. (findable, accessible, interoperable, and reusable) repository (https://doi.org/10.15490/fairdomhub.1.investigation.464.1). Our work highlights the utility for combined binding and kinetic studies for such complex multisubstrate reactions.

Authors: Felix Ott, Kersten S. Rabe, Christof M. Niemeyer, Gudrun Gygli

Date Published: 3rd Sep 2021

Publication Type: Journal

Abstract (Expand)

Single-cell RNA-sequencing (scRNA-seq) provides high-resolution insights into complex tissues. Cardiac tissue, however, poses a major challenge due to the delicate isolation process and the large size of mature cardiomyocytes. Regardless of the experimental technique, captured cells are often impaired and some capture sites may contain multiple or no cells at all. All this refers to "low quality" potentially leading to data misinterpretation. Common standard quality control parameters involve the number of detected genes, transcripts per cell, and the fraction of transcripts from mitochondrial genes. While cutoffs for transcripts and genes per cell are usually user-defined for each experiment or individually calculated, a fixed threshold of 5% mitochondrial transcripts is standard and often set as default in scRNA-seq software. However, this parameter is highly dependent on the tissue type. In the heart, mitochondrial transcripts comprise almost 30% of total mRNA due to high energy demands. Here, we demonstrate that a 5%-threshold not only causes an unacceptable exclusion of cardiomyocytes but also introduces a bias that particularly discriminates pacemaker cells. This effect is apparent for our in vitro generated induced-sinoatrial-bodies (iSABs; highly enriched physiologically functional pacemaker cells), and also evident in a public data set of cells isolated from embryonal murine sinoatrial node tissue (Goodyer William et al. in Circ Res 125:379-397, 2019). Taken together, we recommend omitting this filtering parameter for scRNA-seq in cardiovascular applications whenever possible.

Authors: A. M. Galow, S. Kussauer, M. Wolfien, R. M. Brunner, T. Goldammer, R. David, A. Hoeflich

Date Published: 24th Aug 2021

Publication Type: Manual

Abstract (Expand)

The circadian clock coordinates plant physiology and development. Mathematical clock models have provided a rigorous framework to understand how the observed rhythms emerge from disparate, molecular processes. However, models of the plant clock have largely been built and tested against RNA timeseries data in arbitrary, relative units. This limits model transferability, refinement from biochemical data and applications in synthetic biology. Here, we incorporate absolute mass units into a detailed model of the clock gene network in Arabidopsis thaliana. We re-interpret the established P2011 model, highlighting a transcriptional activator that overlaps the function of REVEILLE 8/LHY-CCA1-LIKE 5. The U2020 model incorporates the repressive regulation of PRR genes, a key feature of the most detailed clock model KF2014, without greatly increasing model complexity. We tested the experimental error distributions of qRT-PCR data calibrated for units of RNA transcripts/cell and of circadian period estimates, in order to link the models to data more appropriately. U2019 and U2020 models were constrained using these data types, recreating previously-described circadian behaviours with RNA metabolic processes in absolute units. To test their inferred rates, we estimated a distribution of observed, transcriptome-wide transcription rates (Plant Empirical Transcription Rates, PETR) in units of transcripts/cell/hour. The PETR distribution and the equivalent degradation rates indicated that the models’ predicted rates are biologically plausible, with individual exceptions. In addition to updated clock models, FAIR data resources and a software environment in Docker, this validation process represents an advance in biochemical realism for models of plant gene regulation.

Authors: Uriel Urquiza Garcia, Andrew J Millar

Date Published: 5th Aug 2021

Publication Type: Journal

Abstract (Expand)

Regulation of glycogen metabolism is of vital importance in organisms of all three kingdoms of life. Although the pathways involved in glycogen synthesis and degradation are well known, many regulatory aspects around the metabolism of this polysaccharide remain undeciphered. Here, we used the unicellular cyanobacterium Synechocystis as a model to investigate how glycogen metabolism is regulated in dormant nitrogen-starved cells, which entirely rely on glycogen catabolism to restore growth. We found that the activity of the enzymes involved in glycogen synthesis and degradation is tightly controlled at different levels via post-translational modifications. Phosphorylation of phosphoglucomutase 1 (Pgm1) on a peripheral residue (Ser63) regulates Pgm1 activity and controls the mobilization of the glycogen stores. Inhibition of Pgm1 activity via phosphorylation on Ser63 appears essential for survival of Synechocystis in the dormant state. Remarkably, this regulatory mechanism seems to be conserved from bacteria to humans. Moreover, phosphorylation of Pgm1 influences the formation of a metabolon, which includes Pgm1, oxidative pentose phosphate cycle protein (OpcA) and glucose-6-phosphate dehydrogenase (G6PDH). Analysis of the steady-state levels of the metabolic products of glycogen degradation together with protein-protein interaction studies revealed that the activity of G6PDH and the formation of this metabolon are under additional redox control, likely to ensure metabolic channeling of glucose-6-phosphate to the required pathways for each developmental stage.

Authors: Sofía Doello, Niels Neumann, Philipp Spät, Boris Maček, Karl Forchhammer

Date Published: 15th Apr 2021

Publication Type: Unpublished

Abstract (Expand)

The circadian clock coordinates plant physiology and development. Mathematical clock models have provided a rigorous framework to understand how the observed rhythms emerge from disparate, molecular processes. However, models of the plant clock have largely been built and tested against RNA timeseries data in arbitrary, relative units. This limits model transferability, refinement from biochemical data and applications in synthetic biology. Here, we incorporate absolute mass units into a detailed, gene circuit model of the clock in Arabidopsis thaliana. We re-interpret the established P2011 model, highlighting a transcriptional activator that overlaps the function of REVEILLE 8/LHY-CCA1-LIKE 5, and refactor dynamic equations for the Evening Complex. The U2020 model incorporates the repressive regulation of PRR genes, a key feature of the most detailed clock model F2014, without greatly increasing model complexity. We tested the experimental error distributions of qRT-PCR data calibrated for units of RNA transcripts/cell and of circadian period estimates, in order to link the models to data more appropriately. U2019 and U2020 models were constrained using these data types, recreating previously-described circadian behaviours with RNA metabolic processes in absolute units. To test their inferred rates, we estimated a distribution of observed, transcriptome-wide transcription rates (Plant Empirical Transcription Rates, PETR) in units of transcripts/cell/hour. The PETR distribution and the equivalent degradation rates indicated that the models’ predicted rates are biologically plausible, with individual exceptions. In addition to updated, explanatory models of the plant clock, this validation process represents an advance in biochemical realism for models of plant gene regulation.

Authors: Uriel Urquiza-Garcia, Andrew J Millar

Date Published: 20th Mar 2021

Publication Type: Tech report

Abstract

Not specified

Authors: Jennifer E. Kay, Joshua J. Corrigan, Amanda L. Armijo, Ilana S. Nazari, Ishwar N. Kohale, Dorothea K. Torous, Svetlana L. Avlasevich, Robert G. Croy, Dushan N. Wadduwage, Sebastian E. Carrasco, Stephen D. Dertinger, Forest M. White, John M. Essigmann, Leona D. Samson, Bevin P. Engelward

Date Published: 1st Mar 2021

Publication Type: Journal

Abstract (Expand)

The enzymatic degradation of polyethylene terephthalate (PET) results in a hydrolysate consisting almost exclusively of its two monomers, ethylene glycol and terephthalate. To biologically valorize the PET hydrolysate, microbial upcycling into high-value products is proposed. Fatty acid derivatives hydroxyalkanoyloxy alkanoates (HAAs) represent such valuable target molecules. HAAs exhibit surface-active properties and can be exploited in the catalytical conversion to drop-in biofuels as well as in the polymerization to bio-based poly(amide urethane). This chapter presents the genetic engineering methods of pseudomonads for the metabolization of PET monomers and the biosynthesis of HAAs with detailed protocols concerning product purification.

Authors: Gina Welsing, Birger Wolter, Henric M.T. Hintzen, Till Tiso, Lars M. Blank

Date Published: 2021

Publication Type: Book

Abstract (Expand)

The oxidative Weimberg pathway for the five-step pentose degradation to α-ketoglutarate is a key route for sustainable bioconversion of lignocellulosic biomass to added-value products and biofuels. The oxidative pathway from Caulobacter crescentus has been employed in in-vivo metabolic engineering with intact cells and in in-vitro enzyme cascades. The performance of such engineering approaches is often hampered by systems complexity, caused by non-linear kinetics and allosteric regulatory mechanisms. Here we report an iterative approach to construct and validate a quantitative model for the Weimberg pathway. Two sensitive points in pathway performance have been identified as follows: (1) product inhibition of the dehydrogenases (particularly in the absence of an efficient NAD+ recycling mechanism) and (2) balancing the activities of the dehydratases. The resulting model is utilized to design enzyme cascades for optimized conversion and to analyse pathway performance in C. cresensus cell- free extracts.

Authors: Lu Shen, Martha Kohlhaas, Junichi Enoki, Roland Meier, Bernhard Schönenberger, Roland Wohlgemuth, Robert Kourist, Felix Niemeyer, David van Niekerk, Christopher Bräsen, Jochen Niemeyer, Jacky Snoep, Bettina Siebers

Date Published: 1st Dec 2020

Publication Type: Not specified

Abstract

Not specified

Authors: Yadi Zhou, Yuan Hou, Jiayu Shen, Yin Huang, William Martin, Feixiong Cheng

Date Published: 1st Dec 2020

Publication Type: Journal

Abstract (Expand)

Using standard systems biology methodologies a 14-compartment dynamic model was developed for the Corona virus epidemic. The model predicts that: (i) it will be impossible to limit lockdown intensity such that sufficient herd immunity develops for this epidemic to die down, (ii) the death toll from the SARS-CoV-2 virus decreases very strongly with increasing intensity of the lockdown, but (iii) the duration of the epidemic increases at first with that intensity and then decreases again, such that (iv) it may be best to begin with selecting a lockdown intensity beyond the intensity that leads to the maximum duration, (v) an intermittent lockdown strategy should also work and might be more acceptable socially and economically, (vi) an initially intensive but adaptive lockdown strategy should be most efficient, both in terms of its low number of casualties and shorter duration, (vii) such an adaptive lockdown strategy offers the advantage of being robust to unexpected imports of the virus, e.g. due to international travel, (viii) the eradication strategy may still be superior as it leads to even fewer deaths and a shorter period of economic downturn, but should have the adaptive strategy as backup in case of unexpected infection imports, (ix) earlier detection of infections is the most effective way in which the epidemic can be controlled, whilst waiting for vaccines.

Authors: Hans V. Westerhoff, Alexey N. Kolodkin

Date Published: 1st Dec 2020

Publication Type: Journal

Abstract

Not specified

Authors: Tatjana Walter, Kareen H. Veldmann, Susanne Götker, Tobias Busche, Christian Rückert, Arman Beyraghdar Kashkooli, Jannik Paulus, Katarina Cankar, Volker F. Wendisch

Date Published: 1st Dec 2020

Publication Type: Journal

Abstract (Expand)

The availability of genome sequences, annotations, and knowledge of the biochemistry underlying metabolic transformations has led to the generation of metabolic network reconstructions for a wide range of organisms in bacteria, archaea, and eukaryotes. When modeled using mathematical representations, a reconstruction can simulate underlying genotype-phenotype relationships. Accordingly, genome-scale metabolic models (GEMs) can be used to predict the response of organisms to genetic and environmental variations. A bottom-up reconstruction procedure typically starts by generating a draft model from existing annotation data on a target organism. For model species, this part of the process can be straightforward, due to the abundant organism-specific biochemical data. However, the process becomes complicated for non-model less-annotated species. In this paper, we present a draft liver reconstruction, ReCodLiver0.9, of Atlantic cod (Gadus morhua), a non-model teleost fish, as a practicable guide for cases with comparably few resources. Although the reconstruction is considered a draft version, we show that it already has utility in elucidating metabolic response mechanisms to environmental toxicants by mapping gene expression data of exposure experiments to the resulting model.

Authors: Eileen Marie Hanna, Xiaokang Zhang, Marta Eide, Shirin Fallahi, Tomasz Furmanek, Fekadu Yadetie, Daniel Craig Zielinski, Anders Goksøyr, Inge Jonassen

Date Published: 26th Nov 2020

Publication Type: Journal

Abstract (Expand)

The congested nature of quaternary carbons hinders their preparation, most notably when stereocontrol is required. Here we report a biocatalytic method for the creation of quaternary carbon centers with broad substrate scope, leading to different compound classes bearing this structural feature. The key step comprises the aldol addition of 3,3-disubstituted 2-oxoacids to aldehydes catalyzed by metal dependent 3-methyl-2-oxobutanoate hydroxymethyltransferase from E. coli (KPHMT) and variants thereof. The 3,3,3-trisubstituted 2-oxoacids thus produced were converted into 2-oxolactones and 3-hydroxy acids and directly to ulosonic acid derivatives, all bearing gem-dialkyl, gem-cycloalkyl, and spirocyclic quaternary centers. In addition, some of these reactions use a single enantiomer from racemic nucleophiles to afford stereopure quaternary carbons. The notable substrate tolerance and stereocontrol of these enzymes are indicative of their potential for the synthesis of structurally intricate molecules.

Authors: Roser Marín-Valls, Karel Hernández, Michael Bolte, Teodor Parella, Jesús Joglar, Jordi Bujons, Pere Clapés

Date Published: 18th Nov 2020

Publication Type: Journal

Abstract (Expand)

How the network around ROS protects against oxidative stress and Parkinson's disease (PD), and how processes at the minutes timescale cause disease and aging after decades, remains enigmatic. Challenging whether the ROS network is as complex as it seems, we built a fairly comprehensive version thereof which we disentangled into a hierarchy of only five simpler subnetworks each delivering one type of robustness. The comprehensive dynamic model described in vitro data sets from two independent laboratories. Notwithstanding its five-fold robustness, it exhibited a relatively sudden breakdown, after some 80 years of virtually steady performance: it predicted aging. PD-related conditions such as lack of DJ-1 protein or increased alpha-synuclein accelerated the collapse, while antioxidants or caffeine retarded it. Introducing a new concept (aging-time-control coefficient), we found that as many as 25 out of 57 molecular processes controlled aging. We identified new targets for "life-extending interventions": mitochondrial synthesis, KEAP1 degradation, and p62 metabolism.

Authors: A. N Kolodkin, R. P. Sharma, A. M. Colangelo, A. Ignatenko, F. Martorana, D. Jennen, J. J. Briede, N. Brady, M. Barberis, T. D. G. A. Mondeel, M. Papa, V. Kumar, B. Peters, A. Skupin, L. Alberghina, R. Balling, H. V. Westerhoff

Date Published: 26th Oct 2020

Publication Type: Journal

Abstract (Expand)

The use of controlled mixed inocula of Saccharomyces cerevisiae and non-Saccharomyces yeasts is a common practice in winemaking, with Torulaspora delbrueckii, Lachancea thermotolerans and Metschnikowia pulcherrima being the most commonly used non-Saccharomyces species. Although S. cerevisiae is usually the dominant yeast at the end of mixed fermentations, some non-Saccharomyces species are also able to reach the late stages; such species may not grow in culture media, which is a status known as viable but non-culturable (VBNC). Thus, an accurate methodology to properly monitor viable yeast population dynamics during alcoholic fermentation is required to understand microbial interactions and the contribution of each species to the final product. Quantitative PCR (qPCR) has been found to be a good and sensitive method for determining the identity of the cell population, but it cannot distinguish the DNA from living and dead cells, which can overestimate the final population results. To address this shortcoming, viability dyes can be used to avoid the amplification and, therefore, the quantification of DNA from non-viable cells. In this study, we validated the use of PMAxx dye (an optimized version of propidium monoazide (PMA) dye) coupled with qPCR (PMAxx-qPCR), as a tool to monitor the viable population dynamics of the most common yeast species used in wine mixed fermentations (S. cerevisiae, T. delbrueckii, L. thermotolerans and M. pulcherrima), comparing the results with non-dyed qPCR and colony counting on differential medium. Our results showed that the PMAxx-qPCR assay used in this study is a reliable, specific and fast method for quantifying these four yeast species during the alcoholic fermentation process, being able to distinguish between living and dead yeast populations. Moreover, the entry into VBNC status was observed for the first time in L. thermotolerans and S. cerevisiae during alcoholic fermentation. Further studies are needed to unravel which compounds trigger this VBNC state during alcoholic fermentation in these species, which would help to better understand yeast interactions.

Authors: Yurena Navarro, María-Jesús Torija, Albert Mas, Gemma Beltran

Date Published: 1st Oct 2020

Publication Type: Journal

Abstract (Expand)

Aryl hydrocarbon receptor (AHR) activation by tryptophan (Trp) catabolites enhances tumor malignancy and suppresses anti-tumor immunity. The context specificity of AHR target genes has so far impeded systematic investigation of AHR activity and its upstream enzymes across human cancers. A pan-tissue AHR signature, derived by natural language processing, revealed that across 32 tumor entities, interleukin-4-induced-1 (IL4I1) associates more frequently with AHR activity than IDO1 or TDO2, hitherto recognized as the main Trp-catabolic enzymes. IL4I1 activates the AHR through the generation of indole metabolites and kynurenic acid. It associates with reduced survival in glioma patients, promotes cancer cell motility, and suppresses adaptive immunity, thereby enhancing the progression of chronic lymphocytic leukemia (CLL) in mice. Immune checkpoint blockade (ICB) induces IDO1 and IL4I1. As IDO1 inhibitors do not block IL4I1, IL4I1 may explain the failure of clinical studies combining ICB with IDO1 inhibition. Taken together, IL4I1 blockade opens new avenues for cancer therapy.

Authors: Ahmed Sadik, Luis F. Somarribas Patterson, Selcen Öztürk, Soumya R. Mohapatra, Verena Panitz, Philipp F. Secker, Pauline Pfänder, Stefanie Loth, Heba Salem, Mirja Tamara Prentzell, Bianca Berdel, Murat Iskar, Erik Faessler, Friederike Reuter, Isabelle Kirst, Verena Kalter, Kathrin I. Foerster, Evelyn Jäger, Carina Ramallo Guevara, Mansour Sobeh, Thomas Hielscher, Gernot Poschet, Annekathrin Reinhardt, Jessica C. Hassel, Marc Zapatka, Udo Hahn, Andreas von Deimling, Carsten Hopf, Rita Schlichting, Beate I. Escher, Jürgen Burhenne, Walter E. Haefeli, Naveed Ishaque, Alexander Böhme, Sascha Schäuble, Kathrin Thedieck, Saskia Trump, Martina Seiffert, Christiane A. Opitz

Date Published: 1st Sep 2020

Publication Type: Journal

Abstract

Not specified

Authors: Sara Sadat Aghamiri, Vidisha Singh, Aurélien Naldi, Tomáš Helikar, Sylvain Soliman, Anna Niarakis

Date Published: 15th Aug 2020

Publication Type: Journal

Abstract (Expand)

Droplet-based microfluidic systems offer a high potential for miniaturization and automation. Therefore, they are becoming an increasingly important tool in analytical chemistry, biosciences, and medicine. Heterogeneous assays commonly utilize magnetic beads as a solid phase. However, the sensitivity of state of the art microfluidic systems is limited by the high bead concentrations required for efficient extraction across the water–oil interface. Furthermore, current systems suffer from a lack of technical solutions for sequential measurements of multiple samples, limiting their throughput and capacity for automation. Taking advantage of the different wetting properties of hydrophilic and hydrophobic areas in the channels, we improve the extraction efficiency of magnetic beads from aqueous nanoliter-sized droplets by 2 orders of magnitude to the low μg/mL range. Furthermore, the introduction of a switchable magnetic trap enables repetitive capture and release of magnetic particles for sequential analysis of multiple samples, enhancing the throughput. In comparison to conventional ELISA-based sandwich immunoassays on microtiter plates, our microfluidic setup offers a 25–50-fold reduction of sample and reagent consumption with up to 50 technical replicates per sample. The enhanced sensitivity and throughput of this system open avenues for the development of automated detection of biomolecules at the nanoliter scale.

Authors: Lukas Metzler, Ulrike Rehbein, Jan-Niklas Schönberg, Thomas Brandstetter, Kathrin Thedieck, Jürgen Rühe

Date Published: 4th Aug 2020

Publication Type: Journal

Abstract (Expand)

Background: The current COVID-19 pandemic has led to a surge of research activity. While this research provides important insights, the multitude of studies results in an increasing segmentation of information. To ensure comparability across projects and institutions, standard datasets are needed. Here, we introduce the "German Corona Consensus Dataset" (GECCO), a uniform dataset that uses international terminologies and health IT standards to improve interoperability of COVID-19 data. Methods: Based on previous work (e.g., the ISARIC-WHO COVID-19 case report form) and in coordination with experts from university hospitals, professional associations and research initiatives, data elements relevant for COVID-19 research were collected, prioritized and consolidated into a compact core dataset. The dataset was mapped to international terminologies, and the Fast Healthcare Interoperability Resources (FHIR) standard was used to define interoperable, machine-readable data formats. Results: A core dataset consisting of 81 data elements with 281 response options was defined, including information about, for example, demography, anamnesis, symptoms, therapy, medications or laboratory values of COVID-19 patients. Data elements and response options were mapped to SNOMED CT, LOINC, UCUM, ICD-10-GM and ATC, and FHIR profiles for interoperable data exchange were defined. Conclusion: GECCO provides a compact, interoperable dataset that can help to make COVID-19 research data more comparable across studies and institutions. The dataset will be further refined in the future by adding domain-specific extension modules for more specialized use cases.

Authors: Julian Sass, Alexander Bartschke, Moritz Lehne, Andrea Essenwanger, Eugenia Rinaldi, Stefanie Rudolph, Kai Uwe Heitmann, Joerg Janne Vehreschild, Christof von Kalle, Sylvia Thun

Date Published: 29th Jul 2020

Publication Type: Journal

Abstract (Expand)

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.

Authors: Dagmar Waltemath, Martin Golebiewski, Michael L Blinov, Padraig Gleeson, Henning Hermjakob, Michael Hucka, Esther Thea Inau, Sarah M Keating, Matthias König, Olga Krebs, Rahuman S Malik-Sheriff, David Nickerson, Ernst Oberortner, Herbert M Sauro, Falk Schreiber, Lucian Smith, Melanie I Stefan, Ulrike Wittig, Chris J Myers

Date Published: 29th Jun 2020

Publication Type: Journal

Abstract (Expand)

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.Not specified

Authors: Falk Schreiber, Björn Sommer, Tobias Czauderna, Martin Golebiewski, Thomas E. Gorochowski, Michael Hucka, Sarah M. Keating, Matthias König, Chris Myers, David Nickerson, Dagmar Waltemath

Date Published: 29th Jun 2020

Publication Type: Journal

Abstract (Expand)

The booming demand for environmentally benign industrial processes relies on the ability to quickly find or engineer a biocatalyst suitable to ideal process conditions. Both metagenomic approaches and directed evolution involve the screening of huge libraries of protein variants, which can only be managed reasonably by flexible platforms for (ultra)high-throughput profiling against the desired criteria. Here, we review the most recent additions toward a growing toolbox of versatile assays using fluorescence, absorbance and mass spectrometry readouts. While conventional solution based high-throughput screening in microtiter plate formats is still important, the implementation of novel screening protocols for microfluidic cell or droplet sorting systems supports technological advances for ultra-high-frequency screening that now can dramatically reduce the timescale of engineering projects. We discuss practical issues of scope, scalability, sensitivity and stereoselectivity for the improvement of biotechnologically relevant enzymes from different classes.

Authors: Yuriy V Sheludko, Wolf-Dieter Fessner

Date Published: 29th Jun 2020

Publication Type: Journal

Abstract

Not specified

Authors: Tatjana Walter, Nour Al Medani, Arthur Burgardt, Katarina Cankar, Lenny Ferrer, Anastasia Kerbs, Jin-Ho Lee, Melanie Mindt, Joe Max Risse, Volker F. Wendisch

Date Published: 1st Jun 2020

Publication Type: Journal

Abstract

Not specified

Authors: Zichen Wang, Amanda B Zheutlin, Yu-Han Kao, Kristin L Ayers, Susan J Gross, Patricia Kovatch, Sharon Nirenberg, Alexander W Charney, Girish N Nadkarni, Paul F O'Reilly, Allan C Just, Carol R Horowitz, Glenn Martin, Andrea D Branch, Benjamin S Glicksberg, Dennis S Charney, David L Reich, William K Oh, Eric E Schadt, Rong Chen, Li Li

Date Published: 4th May 2020

Publication Type: Misc

Abstract (Expand)

The alcohol content in wine has increased due to external factors in recent decades. In recent reports, some non-Saccharomyces yeast species have been confirmed to reduce ethanol during the alcoholic fermentation process. Thus, an efficient screening of non-Saccharomyces yeasts with low ethanol yield is required due to the broad diversity of these yeasts. In this study, we proposed a rapid method for selecting strains with a low ethanol yield from forty-five non-Saccharomyces yeasts belonging to eighteen species. Single fermentations were carried out for this rapid selection. Then, sequential fermentations in synthetic and natural must were conducted with the selected strains to confirm their capacity to reduce ethanol compared with that of Saccharomyces cerevisiae. The results showed that ten non-Saccharomyces strains were able to reduce the ethanol content, namely, Hanseniaspora uvarum (2), Issatchenkia terricola (1), Metschnikowia pulcherrima (2), Lachancea thermotolerans (1), Saccharomycodes ludwigii (1), Torulaspora delbrueckii (2), and Zygosaccharomyces bailii (1). Compared with S. cerevisiae, the ethanol reduction of the selected strains ranged from 0.29 to 1.39% (v/v). Sequential inoculations of M. pulcherrima (Mp51 and Mp FA) and S. cerevisiae reduced the highest concentration of ethanol by 1.17 to 1.39% (v/v) in synthetic or natural must. Second, sequential fermentations with Z. bailii (Zb43) and T. delbrueckii (Td Pt) performed in natural must yielded ethanol reductions of 1.02 and 0.84% (v/v), respectively.

Authors: Xiaolin Zhu, Yurena Navarro, Albert Mas, María-Jesús Torija, Gemma Beltran

Date Published: 1st May 2020

Publication Type: Journal

Abstract (Expand)

Many cancer cells consume glutamine at high rates; counterintuitively, they simultaneously excrete glutamate, the first intermediate in glutamine metabolism. Glutamine consumption has been linked to replenishment of tricarboxylic acid cycle (TCA) intermediates and synthesis of adenosine triphosphate (ATP), but the reason for glutamate excretion is unclear. Here, we dynamically profile the uptake and excretion fluxes of a liver cancer cell line (HepG2) and use genome-scale metabolic modeling for in-depth analysis. We find that up to 30% of the glutamine is metabolized in the cytosol, primarily for nucleotide synthesis, producing cytosolic glutamate. We hypothesize that excreting glutamate helps the cell to increase the nucleotide synthesis rate to sustain growth. Indeed, we show experimentally that partial inhibition of glutamate excretion reduces cell growth. Our integrative approach thus links glutamine addiction to glutamate excretion in cancer and points toward potential drug targets.

Authors: Avlant Nilsson, Jurgen R. Haanstra, Martin Engqvist, Albert Gerding, Barbara M. Bakker, Ursula Klingmüller, Bas Teusink, Jens Nielsen

Date Published: 27th Apr 2020

Publication Type: Journal

Abstract (Expand)

The Simulation Foundry (SF) is a modular workflow for the automated creation of molecular modeling (MM) data. MM allows for the reliable prediction of the microscopic and macroscopic properties of multicomponent systems from first principles. The SF makes MM repeatable, replicable, and findable, accessible, interoperable, and reusable (F.A.I.R.). The SF uses a standardized data structure and file naming convention, allowing for replication on different supercomputers and re-entrancy. We focus on keeping the SF simple by basing it on scripting languages that are widely used by the MM community (bash, Python) and making it reusable and re-editable. The SF was developed to assist expert users in performing parameter studies of multicomponent systems by high throughput molecular dynamics simulations. The usability of the SF is demonstrated by simulations of thermophysical properties of binary mixtures. A standardized data exchange format enables the integration of simulated data with data from experiments. The SF also provides a complete documentation of how the results were obtained, thus assigning provenance. Increasing computational power facilitates the intensification of the simulation process and requires automation and modularity. The SF provides a community platform on which to integrate new methods and create data that is reproducible and transparent (https://fairdomhub.org/studies/639/snapshots/1, https://fairdomhub.org/studies/639/snapshots/2).

Authors: Gudrun Gygli, Juergen Pleiss

Date Published: 27th Apr 2020

Publication Type: Journal

Abstract (Expand)

Background and aims: The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has recently spread worldwide and been declared a pandemic. We aim to describe here the various clinical presentations of this disease by examining eleven cases. Methods: Electronic medical records of 11 patients with COVID-19 were collected and demographics, clinical manifestations, outcomes, key laboratory results, and radiological images are discussed. Results: The clinical course of the eleven cases demonstrated the complexity of the COVID-19 profile with different clinical presentations. Clinical manifestations range from asymptomatic cases to patients with mild and severe symptoms, with or without pneumonia. Laboratory detection of the viral nucleic acid can yield false-negative results, and serological testing of virus specific IgG and IgM antibodies should be used as an alternative for diagnosis. Patients with common allergic diseases did not develop distinct symptoms and severe courses. Cases with a pre-existing condition of chronic obstructive pulmonary disease or complicated with a secondary bacterial pneumonia were more severe. Conclusion: All different clinical characteristics of COVID-19 should be taken into consideration to identify patients that need to be in strict quarantine for the efficient containment of the pandemic.

Authors: Xiang Dong, Yi-yuan Cao, Xiao-xia Lu, Jin-jin Zhang, Hui Du, You-qin Yan, Cezmi A. Akdis, Ya-dong Gao

Date Published: 6th Apr 2020

Publication Type: Journal

Powered by
(v.1.11.2)
Copyright © 2008 - 2021 The University of Manchester and HITS gGmbH

By continuing to use this site you agree to the use of cookies