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630 Publications visible to you, out of a total of 630

Abstract (Expand)

With recent progress in modeling liver organogenesis and regeneration, the lack of vasculature is becoming the bottleneck in progressing our ability to model human hepatic tissues in vitro. Here, we introduce a platform for routine grafting of liver and other tissues on an in vitro grown microvascular bed. The platform consists of 64 microfluidic chips patterned underneath a 384-well microtiter plate. Each chip allows the formation of a microvascular bed between two main lateral vessels by inducing angiogenesis. Chips consist of an open-top microfluidic chamber, which enables addition of a target tissue by manual or robotic pipetting. Upon grafting a liver microtissue, the microvascular bed undergoes anastomosis, resulting in a stable, perfusable vascular network. Interactions with vasculature were found in spheroids and organoids upon 7 days of co-culture with space of Disse-like architecture in between hepatocytes and endothelium. Veno-occlusive disease was induced by azathioprine exposure, leading to impeded perfusion of the vascularized spheroid. The platform holds the potential to replace animals with an in vitro alternative for routine grafting of spheroids, organoids, or (patient-derived) explants.

Authors: F. Bonanini, D. Kurek, S. Previdi, A. Nicolas, D. Hendriks, S. de Ruiter, M. Meyer, M. Clapes Cabrer, R. Dinkelberg, S. B. Garcia, B. Kramer, T. Olivier, H. Hu, C. Lopez-Iglesias, F. Schavemaker, E. Walinga, D. Dutta, K. Queiroz, K. Domansky, B. Ronden, J. Joore, H. L. Lanz, P. J. Peters, S. J. Trietsch, H. Clevers, P. Vulto

Date Published: 16th Jun 2022

Publication Type: Journal

Abstract (Expand)

Anthrax is a zoonotic infectious disease caused by Bacillus anthracis (anthrax bacterium) that affects not only domestic and wild animals worldwide but also human health. As the study develops in-depth, a large quantity of related biomedical publications emerge. Acquiring knowledge from the literature is essential for gaining insight into anthrax etiology, diagnosis, treatment and research. In this study, we used a set of text mining tools to identify nearly 14 000 entities of 29 categories, such as genes, diseases, chemicals, species, vaccines and proteins, from nearly 8000 anthrax biomedical literature and extracted 281 categories of association relationships among the entities. We curated Anthrax-related Entities Dictionary and Anthrax Ontology. We formed Anthrax Knowledge Graph (AnthraxKG) containing more than 6000 nodes, 6000 edges and 32 000 properties. An interactive visualized Anthrax Knowledge Portal(AnthraxKP) was also developed based on AnthraxKG by using Web technology. AnthraxKP in this study provides rich and authentic relevant knowledge in many forms, which can help researchers carry out research more efficiently. Database URL: AnthraxKP is permitted users to query and download data at http://139.224.212.120:18095/.

Authors: B. Feng, J. Gao

Date Published: 2nd Jun 2022

Publication Type: Journal

Abstract (Expand)

Atlantic salmon (Salmo salar) is the most valuable farmed fish globally and there is much interest in optimizing its genetics and rearing conditions for growth and feed efficiency. Marine feed ingredients must be replaced to meet global demand, with challenges for fish health and sustainability. Metabolic models can address this by connecting genomes to metabolism, which converts nutrients in the feed to energy and biomass, but such models are currently not available for major aquaculture species such as salmon. We present SALARECON, a model focusing on energy, amino acid, and nucleotide metabolism that links the Atlantic salmon genome to metabolic fluxes and growth. It performs well in standardized tests and captures expected metabolic (in)capabilities. We show that it can explain observed hypoxic growth in terms of metabolic fluxes and apply it to aquaculture by simulating growth with commercial feed ingredients. Predicted limiting amino acids and feed efficiencies agree with data, and the model suggests that marine feed efficiency can be achieved by supplementing a few amino acids to plant- and insect-based feeds. SALARECON is a high-quality model that makes it possible to simulate Atlantic salmon metabolism and growth. It can be used to explain Atlantic salmon physiology and address key challenges in aquaculture such as development of sustainable feeds.

Authors: Maksim Zakhartsev, Filip Rotnes, Marie Gulla, Ove Oyas, Jesse van Dam, Maria Suarez Diez, Fabian Grammes, Robert Hafthorsson, Wout van Helvoirt, Jasper Koehorst, Peter Schaap, Yang Jin, Liv Torunn Mydland, Arne Gjuvsland, Sandve Simen, Vitor Martins dos Santos, Jon Olav Vik

Date Published: 1st Jun 2022

Publication Type: Journal

Abstract (Expand)

Microalgae comprise a phylogenetically very diverse group of photosynthetic unicellular pro- and eukaryotic organisms growing in marine and other aquatic environments. While they are well explored for the generation of biofuels, their potential as a source of antimicrobial and prebiotic substances have recently received increasing interest. Within this framework, microalgae may offer solutions to the societal challenge we face, concerning the lack of antibiotics treating the growing level of antimicrobial resistant bacteria and fungi in clinical settings. While the vast majority of microalgae and their associated microbiota remain unstudied, they may be a fascinating and rewarding source for novel and more sustainable antimicrobials and alternative molecules and compounds. In this review, we present an overview of the current knowledge on health benefits of microalgae and their associated microbiota. Finally, we describe remaining issues and limitation, and suggest several promising research potentials that should be given attention.

Authors: Ines Krohn, Simon Menanteau‐Ledouble, Gunhild Hageskal, Yekaterina Astafyeva, Pierre Jouannais, Jeppe Lund Nielsen, Massimo Pizzol, Alexander Wentzel, Wolfgang R. Streit

Date Published: 29th May 2022

Publication Type: Journal

Abstract (Expand)

Indole is produced in nature by diverse organisms and exhibits a characteristic odor described as animal, fecal, and floral. In addition, it contributes to the flavor in foods, and it is applied in the fragrance and flavor industry. In nature, indole is synthesized either from tryptophan by bacterial tryptophanases (TNAs) or from indole-3-glycerol phosphate (IGP) by plant indole-3-glycerol phosphate lyases (IGLs). While it is widely accepted that the tryptophan synthase α-subunit (TSA) has intrinsically low IGL activity in the absence of the tryptophan synthase β-subunit, in this study, we show that Corynebacterium glutamicum TSA functions as a bona fide IGL and can support fermentative indole production in strains providing IGP. By bioprospecting additional bacterial TSAs and plant IGLs that function as bona fide IGLs were identified. Capturing indole in an overlay enabled indole production to titers of about 0.7 g L-1 in fermentations using C. glutamicum strains expressing either the endogenous TSA gene or the IGL gene from wheat.

Authors: Lenny Ferrer, Melanie Mindt, Maria Suarez-Diez, Tatjana Jilg, Maja Zagorščak, Jin-Ho Lee, Kristina Gruden, Volker F. Wendisch, Katarina Cankar

Date Published: 11th May 2022

Publication Type: Journal

Abstract (Expand)

There are two major problems that we are facing currently. Firstly, a growing human population continues to contribute to the increased food demand. Secondly, the volume of organic waste produced will threaten human health and the quality of the environment. Recently, there is an increasing number of efforts placed into farming insect biomass to produce alternative feed ingredients. Black soldier fly larvae (BSFL), Hermetia illucens have proven to convert organic waste into high-quality nutrients for pet foods, fish and poultry feeds, as well as residue fertilizer for soil amendment. However, better BSFL feed formulation and feeding approaches are necessary for yielding a higher nutrient content of the insect body, and if performed efficiently, whilst converting waste into higher value biomass. Lastly, this paper reveals that BSFL, in fact, thrives in various ranges of organic matter composition and with simple rearing systems.

Authors: S. A. Siddiqui, B. Ristow, T. Rahayu, N. S. Putra, N. Widya Yuwono, K. Nisa', B. Mategeko, S. Smetana, M. Saki, A. Nawaz, A. Nagdalian

Date Published: 1st Mar 2022

Publication Type: Journal

Abstract (Expand)

Abstract ICAM-1 is critical for interactions between cells. Previous studies have suggested that ICAM-1 triggers cell-to-cell transmission of HIV-1 or HTLV-1. SARS-CoV-2 shares several features with several features with these viruses in interactions between cells, and SARS-CoV-2 cell-to-cell transmission is associated with COVID-19 severity. However, ICAM-1 and its associated pathways are not identified as essential factors in interactions between cells in COVID-19. For example, the current COVID-19 Disease Map has no entry for those pathways. Therefore, discovering unknown ICAM-1 pathways will be indispensable for clarifying the mechanism of COVID-19. This study builds ICAM1-associated pathways by gene network inference from single-cell omics data and multiple knowledge bases. First, data analyses extracted coexpressed genes with significant differences in expression levels with spurious correlations removed. Second, knowledge bases validate models. Finally, mapping the models onto existing pathways identifies new ICAM1-associated pathways. These pathways indicate that (1) upstream pathways include proteins in noncanonical NF-kappaB pathway and that (2) downstream pathways contain integrins and cytoskeleton or motor proteins for cell transformation. In this way, data-driven and knowledge-based approaches are integrated into gene network inference for ICAM1-associated pathway construction. The results can contribute to repairing and completing the COVID-19 Disease Map, thereby improving our understanding of the mechanisms of COVID-19.

Authors: Mitsuhiro Odaka, Morgan Magnin, Katsumi Inoue

Date Published: 11th Feb 2022

Publication Type: Journal

Abstract (Expand)

Eight ferrocenyl 4-amino-1,8-naphthalimide logic gates for acidity and oxidisability are repurposed as anti-proliferation and cellular imaging agents against MCF-7 and K562 cancer cell lines.er cell lines.

Authors: Alex D. Johnson, Joseph A. Buhagiar, David C. Magri

Date Published: 15th Dec 2021

Publication Type: Journal

Abstract (Expand)

Graphite oxide (GO) has been used for the immobilization of several classes of enzymes, exhibiting very interesting properties as immobilization matrix. However, the effect the nanomaterial has on the enzyme cannot be predicted. Herein, the effect GO has on the catalytic behavior of several (S)-selective amine transaminases ((S)-ATAs) has been investigated. These enzymes were the focus of this work as they are homodimers with pyridoxal 5’-phosphate in their active site, significantly more complex systems than other enzymes previously studied. Addition of GO (up to 0.1 mg/mL) in the reaction medium leads to activation (up to 50% improved activity) for most enzymes studied, while they maintain their temperature profile (they perform better between 40-45ºC), and their stability. However, the effect is not universal and there are enzymes that are negatively influenced by the presence of the nanomaterial. More profound is the effect on the (S)-ATA from Chromobacterium violaceum which loses almost 50% of its activity in the presence of 0.1 mg/mL GO, while the stability was significantly decreased, losing its activity after 2 h incubation at 40°C, in the presence of 25 μg/mL GO. This negative effect seems to rise from minor secondary structure alterations; namely, a loss of α-helices and subsequent increase in random coil (~3% in the presence of 25 μg/mL GO). We hypothesize that the effect the GO has on (S)-ATAs is correlated to the surface chemistry of the enzymes; the less negatively-charged enzymes are deactivated from the interaction with GO. This insight will aid the rationalization of ATA immobilization onto carbon-based nanomaterials.

Authors: Nikolaos Kaloudis, Panagiota Zygouri, Nikolaos Chalmpes, Konstantinos Spyrou, Dimitrios Gournis, Ioannis Pavlidis

Date Published: 6th Dec 2021

Publication Type: Journal

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)

Abstract Stable isotope labelling in combination with high-resolution mass spectrometry approaches are increasingly used to analyze both metabolite and protein modification dynamics. To enable correctynamics. To enable correct estimation of the resulting dynamics, it is critical to correct the measured values for naturally occurring stable isotopes, a process commonly called isotopologue correction or deconvolution. While the importance of isotopologue correction is well recognized in metabolomics, it has received far less attention in proteomics approaches. Although several tools exist that enable isotopologue correction of mass spectrometry data, the majority is tailored for the analysis of low molecular weight metabolites. We here present PICor which has been developed for isotopologue correction of complex isotope labelling experiments in proteomics or metabolomics and demonstrate the importance of appropriate correction for accurate determination of protein modifications dynamics, using histone acetylation as an example.

Authors: Jörn Dietze, Alienke van Pijkeren, Anna-Sophia Egger, Mathias Ziegler, Marcel Kwiatkowski, Ines Heiland

Date Published: 1st Dec 2021

Publication Type: Journal

Abstract (Expand)

Abstract We have developed pISA-tree, a straightforward and flexible data management solution for organisation of life science project-associated research data and metadata. It enables on the flyand metadata. It enables on the fly creation of enriched directory tree structure ( p roject/ I nvestigation/ S tudy/ A ssay), via a series of sequential batch files in a standardised manner based upon the ISA metadata framework. Metadata, according to the system-provided metadata templates, is generated in parallel at each level. The system supports reproducible research and is in accordance with the Open Science initiative and FAIR principles. Compared with similar frameworks, it does not require any systems administration and maintenance as it can be run on a personal computer or network drive. It is complemented with two R packages, pisar and seekr , where the former facilitates integration of the pISA-tree datasets into bioinformatic pipelines and the latter enables synchronisation with the FAIRDOMHub public repository using the SEEK API. Source code and detailed documentation of pISA-tree and its supporting R packages are available from https://github.com/NIB-SI/pISA-tree . We demonstrate the usability of pISA-tree with two examples of medium sized life science projects. Accordingly, it is suitable and also currently used to manage larger projects including several partners from different countries. Since pISA-tree was initiated by end user requirements with an emphasis on practicality, it will facilitate adoption of FAIR data management practices and open science principles.

Authors: Marko Petek, Maja Zagorščak, Andrej Blejec, Živa Ramšak, Anna Coll, Špela Baebler, Kristina Gruden

Date Published: 21st Nov 2021

Publication Type: Journal

Abstract (Expand)

Non-alcoholic fatty liver disease (NAFLD) is a leading cause of chronic liver disease worldwide. We performed network analysis to investigate the dysregulated biological processes in the disease progression and revealed the molecular mechanism underlying NAFLD. Based on network analysis, we identified a highly conserved disease-associated gene module across three different NAFLD cohorts and highlighted the predominant role of key transcriptional regulators associated with lipid and cholesterol metabolism. In addition, we revealed the detailed metabolic differences between heterogeneous NAFLD patients through integrative systems analysis of transcriptomic data and liver-specific genome-scale metabolic model. Furthermore, we identified transcription factors (TFs), including SREBF2, HNF4A, SREBF1, YY1, and KLF13, showing regulation of hepatic expression of genes in the NAFLD-associated modules and validated the TFs using data generated from a mouse NAFLD model. In conclusion, our integrative analysis facilitates the understanding of the regulatory mechanism of these perturbed TFs and their associated biological processes.

Authors: H. Yang, M. Arif, M. Yuan, X. Li, K. Shong, H. Turkez, J. Nielsen, M. Uhlen, J. Boren, C. Zhang, A. Mardinoglu

Date Published: 19th Nov 2021

Publication Type: Journal

Abstract (Expand)

Chemical named entity recognition (NER) is a significant step for many downstream applications like entity linking for the chemical text-mining pipeline. However, the identification of chemical entities in a biomedical text is a challenging task due to the diverse morphology of chemical entities and the different types of chemical nomenclature. In this work, we describe our approach that was submitted for BioCreative version 7 challenge Track 2, focusing on the ‘Chemical Identification’ task for identifying chemical entities and entity linking, using MeSH. For this purpose, we have applied a two-stage approach as follows (a) usage of fine-tuned BioBERT for identification of chemical entities (b) semantic approximate search in MeSH and PubChem databases for entity linking. There was some friction between the two approaches, as our rule-based approach did not harmonise optimally with partially recognized words forwarded by the BERT component. For our future work, we aim to resolve the issue of the artefacts arising from BERT tokenizers and develop joint learning of chemical named entity recognition and entity linking using pre-trained transformer-based models and compare their performance with our preliminary approach. Next, we will improve the efficiency of our approximate search in reference databases during entity linking. This task is non-trivial as it entails determining similarity scores of large sets of trees with respect to a query tree. Ideally, this will enable flexible parametrization and rule selection for the entity linking search.

Authors: Ghadeer Mobasher, Lukrécia Mertová, Sucheta Ghosh, Olga Krebs, Bettina Heinlein, Wolfgang Müller

Date Published: 11th Nov 2021

Publication Type: Proceedings

Abstract (Expand)

Treatment options for COVID-19, caused by SARS-CoV-2, remain limited. Understanding viral pathogenesis at the molecular level is critical to develop effective therapy. Some recent studies have explored SARS-CoV-2–host interactomes and provided great resources for understanding viral replication. However, host proteins that functionally associate with SARS-CoV-2 are localized in the corresponding subnetwork within the comprehensive human interactome. Therefore, constructing a downstream network including all potential viral receptors, host cell proteases, and cofactors is necessary and should be used as an additional criterion for the validation of critical host machineries used for viral processing. This study applied both affinity purification mass spectrometry (AP-MS) and the complementary proximity-based labeling MS method (BioID-MS) on 29 viral ORFs and 18 host proteins with potential roles in viral replication to map the interactions relevant to viral processing. The analysis yields a list of 693 hub proteins sharing interactions with both viral baits and host baits and revealed their biological significance for SARS-CoV-2. Those hub proteins then served as a rational resource for drug repurposing via a virtual screening approach. The overall process resulted in the suggested repurposing of 59 compounds for 15 protein targets. Furthermore, antiviral effects of some candidate drugs were observed in vitro validation using image-based drug screen with infectious SARS-CoV-2. In addition, our results suggest that the antiviral activity of methotrexate could be associated with its inhibitory effect on specific protein-protein interactions.

Authors: Xiaonan Liu, Sini Huuskonen, Tuomo Laitinen, Taras Redchuk, Mariia Bogacheva, Kari Salokas, Ina Pöhner, Tiina Öhman, Arun Kumar Tonduru, Antti Hassinen, Lisa Gawriyski, Salla Keskitalo, Maria K Vartiainen, Vilja Pietiäinen, Antti Poso, Markku Varjosalo

Date Published: 1st Nov 2021

Publication Type: Journal

Abstract (Expand)

We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.

Authors: M. Ostaszewski, A. Niarakis, A. Mazein, I. Kuperstein, R. Phair, A. Orta-Resendiz, V. Singh, S. S. Aghamiri, M. L. Acencio, E. Glaab, A. Ruepp, G. Fobo, C. Montrone, B. Brauner, G. Frishman, L. C. Monraz Gomez, J. Somers, M. Hoch, S. Kumar Gupta, J. Scheel, H. Borlinghaus, T. Czauderna, F. Schreiber, A. Montagud, M. Ponce de Leon, A. Funahashi, Y. Hiki, N. Hiroi, T. G. Yamada, A. Drager, A. Renz, M. Naveez, Z. Bocskei, F. Messina, D. Bornigen, L. Fergusson, M. Conti, M. Rameil, V. Nakonecnij, J. Vanhoefer, L. Schmiester, M. Wang, E. E. Ackerman, J. E. Shoemaker, J. Zucker, K. Oxford, J. Teuton, E. Kocakaya, G. Y. Summak, K. Hanspers, M. Kutmon, S. Coort, L. Eijssen, F. Ehrhart, D. A. B. Rex, D. Slenter, M. Martens, N. Pham, R. Haw, B. Jassal, L. Matthews, M. Orlic-Milacic, A. Senff Ribeiro, K. Rothfels, V. Shamovsky, R. Stephan, C. Sevilla, T. Varusai, J. M. Ravel, R. Fraser, V. Ortseifen, S. Marchesi, P. Gawron, E. Smula, L. Heirendt, V. Satagopam, G. Wu, A. Riutta, M. Golebiewski, S. Owen, C. Goble, X. Hu, R. W. Overall, D. Maier, A. Bauch, B. M. Gyori, J. A. Bachman, C. Vega, V. Groues, M. Vazquez, P. Porras, L. Licata, M. Iannuccelli, F. Sacco, A. Nesterova, A. Yuryev, A. de Waard, D. Turei, A. Luna, O. Babur, S. Soliman, A. Valdeolivas, M. Esteban-Medina, M. Pena-Chilet, K. Rian, T. Helikar, B. L. Puniya, D. Modos, A. Treveil, M. Olbei, B. De Meulder, S. Ballereau, A. Dugourd, A. Naldi, V. Noel, L. Calzone, C. Sander, E. Demir, T. Korcsmaros, T. C. Freeman, F. Auge, J. S. Beckmann, J. Hasenauer, O. Wolkenhauer, E. L. Wilighagen, A. R. Pico, C. T. Evelo, M. E. Gillespie, L. D. Stein, H. Hermjakob, P. D'Eustachio, J. Saez-Rodriguez, J. Dopazo, A. Valencia, H. Kitano, E. Barillot, C. Auffray, R. Balling, R. Schneider

Date Published: 19th Oct 2021

Publication Type: Journal

Abstract (Expand)

Leaf/stem-specific overexpression of SP6A, the FLOWERING LOCUS T homolog in potato (Solanum tuberosum), was previously shown to induce tuberization leading to higher tuber numbers and yield under ambient and abiotic stress conditions. In this study, we investigated the mechanism underlying SP6A action. Overexpression of SP6A reduced shoot growth, mainly by inhibition of stem elongation and secondary growth, and by repression of apical bud outgrowth. In contrast, root growth and lateral shoot emergence from basal nodes was promoted. Tracer experiments using the fluorescent sucrose analogue esculin revealed that stems of SP6A overexpressing plants transport assimilates more efficiently to belowground sinks, e.g. roots and tubers, compared to wild-type plants. This was accompanied by a lower level of sucrose leakage from the transport phloem into neighboring parenchyma cells and the inhibition of flower formation. We demonstrate the ability of SP6A to control assimilate allocation to belowground sinks and postulate that selection of beneficial SP6A alleles will enable potato breeding to alter plant architecture and to increase tuber yield under conditions of expected climate change.

Authors: G. G. Lehretz, S. Sonnewald, U. Sonnewald

Date Published: 6th Oct 2021

Publication Type: Journal

Abstract

Not specified

Authors: Marek Ostaszewski, Anna Niarakis, Alexander Mazein, Inna Kuperstein, Robert Phair, Aurelio Orta‐Resendiz, Vidisha Singh, Sara Sadat Aghamiri, Marcio Luis Acencio, Enrico Glaab, Andreas Ruepp, Gisela Fobo, Corinna Montrone, Barbara Brauner, Goar Frishman, Luis Cristóbal Monraz Gómez, Julia Somers, Matti Hoch, Shailendra Kumar Gupta, Julia Scheel, Hanna Borlinghaus, Tobias Czauderna, Falk Schreiber, Arnau Montagud, Miguel Ponce de Leon, Akira Funahashi, Yusuke Hiki, Noriko Hiroi, Takahiro G Yamada, Andreas Dräger, Alina Renz, Muhammad Naveez, Zsolt Bocskei, Francesco Messina, Daniela Börnigen, Liam Fergusson, Marta Conti, Marius Rameil, Vanessa Nakonecnij, Jakob Vanhoefer, Leonard Schmiester, Muying Wang, Emily E Ackerman, Jason E Shoemaker, Jeremy Zucker, Kristie Oxford, Jeremy Teuton, Ebru Kocakaya, Gökçe Yağmur Summak, Kristina Hanspers, Martina Kutmon, Susan Coort, Lars Eijssen, Friederike Ehrhart, Devasahayam Arokia Balaya Rex, Denise Slenter, Marvin Martens, Nhung Pham, Robin Haw, Bijay Jassal, Lisa Matthews, Marija Orlic‐Milacic, Andrea Senff Ribeiro, Karen Rothfels, Veronica Shamovsky, Ralf Stephan, Cristoffer Sevilla, Thawfeek Varusai, Jean‐Marie Ravel, Rupsha Fraser, Vera Ortseifen, Silvia Marchesi, Piotr Gawron, Ewa Smula, Laurent Heirendt, Venkata Satagopam, Guanming Wu, Anders Riutta, Martin Golebiewski, Stuart Owen, Carole Goble, Xiaoming Hu, Rupert W Overall, Dieter Maier, Angela Bauch, Benjamin M Gyori, John A Bachman, Carlos Vega, Valentin Grouès, Miguel Vazquez, Pablo Porras, Luana Licata, Marta Iannuccelli, Francesca Sacco, Anastasia Nesterova, Anton Yuryev, Anita de Waard, Denes Turei, Augustin Luna, Ozgun Babur, Sylvain Soliman, Alberto Valdeolivas, Marina Esteban‐Medina, Maria Peña‐Chilet, Kinza Rian, Tomáš Helikar, Bhanwar Lal Puniya, Dezso Modos, Agatha Treveil, Marton Olbei, Bertrand De Meulder, Stephane Ballereau, Aurélien Dugourd, Aurélien Naldi, Vincent Noël, Laurence Calzone, Chris Sander, Emek Demir, Tamas Korcsmaros, Tom C Freeman, Franck Augé, Jacques S Beckmann, Jan Hasenauer, Olaf Wolkenhauer, Egon L Wilighagen, Alexander R Pico, Chris T Evelo, Marc E Gillespie, Lincoln D Stein, Henning Hermjakob, Peter D'Eustachio, Julio Saez‐Rodriguez, Joaquin Dopazo, Alfonso Valencia, Hiroaki Kitano, Emmanuel Barillot, Charles Auffray, Rudi Balling, Reinhard Schneider

Date Published: 1st Oct 2021

Publication Type: Journal

Abstract (Expand)

Seizure threshold 2 (SZT2) is a component of the KICSTOR complex which, under catabolic conditions, functions as a negative regulator in the amino acid-sensing branch of mTORC1. Mutations in this genee cause a severe neurodevelopmental and epileptic encephalopathy whose main symptoms include epilepsy, intellectual disability, and macrocephaly. As SZT2 remains one of the least characterized regulators of mTORC1, in this work we performed a systematic interactome analysis under catabolic and anabolic conditions. Besides numerous mTORC1 and AMPK signaling components, we identified clusters of proteins related to autophagy, ciliogenesis regulation, neurogenesis, and neurodegenerative processes. Moreover, analysis of SZT2 ablated cells revealed increased mTORC1 signaling activation that could be reversed by Rapamycin or Torin treatments. Strikingly, SZT2 KO cells also exhibited higher levels of autophagic components, independent of the physiological conditions tested. These results are consistent with our interactome data, in which we detected an enriched pool of selective autophagy receptors/regulators. Moreover, preliminary analyses indicated that SZT2 alters ciliogenesis. Overall, the data presented form the basis to comprehensively investigate the physiological functions of SZT2 that could explain major molecular events in the pathophysiology of developmental and epileptic encephalopathy in patients with SZT2 mutations.

Authors: Cecilia Cattelani, Dominik Lesiak, Gudrun Liebscher, Isabel I. Singer, Taras Stasyk, Moritz H. Wallnöfer, Alexander M. Heberle, Corrado Corti, Michael W. Hess, Kristian Pfaller, Marcel Kwiatkowski, Peter P. Pramstaller, Andrew A. Hicks, Kathrin Thedieck, Thomas Müller, Lukas A. Huber, Mariana Eca Guimaraes de Araujo

Date Published: 1st Oct 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)

In this study we demonstrated through analytic considerations and numerical studies that the mitochondrial fatty-acid beta-oxidation can exhibit bistable-hysteresis behavior. In an experimentally validated computational model we identified a specific region in the parameter space in which two distinct stable and one unstable steady state could be attained with different fluxes. The two stable states were referred to as low-flux (disease) and high-flux (healthy) state. By a modular kinetic approach we traced the origin and causes of the bistability back to the distributive kinetics and the conservation of CoA, in particular in the last rounds of the beta-oxidation. We then extended the model to investigate various interventions that may confer health benefits by activating the pathway, including (i) activation of the last enzyme MCKAT via its endogenous regulator p46-SHC protein, (ii) addition of a thioesterase (an acyl-CoA hydrolysing enzyme) as a safety valve, and (iii) concomitant activation of a number of upstream and downstream enzymes by short-chain fatty-acids (SCFA), metabolites that are produced from nutritional fibers in the gut. A high concentration of SCFAs, thioesterase activity, and inhibition of the p46Shc protein led to a disappearance of the bistability, leaving only the high-flux state. A better understanding of the switch behavior of the mitochondrial fatty-acid oxidation process between a low- and a high-flux state may lead to dietary and pharmacological intervention in the treatment or prevention of obesity and or non-alcoholic fatty-liver disease.

Authors: F. Abegaz, A. M. F. Martines, M. A. Vieira-Lara, M. Rios-Morales, D. J. Reijngoud, E. C. Wit, B. M. Bakker

Date Published: 13th Aug 2021

Publication Type: Journal

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)

As artemisinin combination therapies (ACTs) are compromised by resistance, we are evaluating triple combination therapies (TACTs) comprising an amino-artemisinin, a redox drug, and a third drug withox drug, and a third drug with different mode of action. Thus, here we briefly review efficacy data on artemisone, artemiside, other amino-artemisinins, and 11-aza-artemisinin and conduct absorption, distribution, and metabolism and excretion (ADME) profiling in vitro and pharmacokinetic (PK) profiling in vivo via intravenous (i.v.) and oral (p.o.) administration to mice.

Authors: Daniel J. Watson, Lizahn Laing, Liezl Gibhard, Ho Ning Wong, Richard K. Haynes, Lubbe Wiesner

Date Published: 16th Jul 2021

Publication Type: Journal

Abstract (Expand)

There is an overarching theme in Science Education to integrate in the school and university curriculum interdisciplinary state-of-art innovations. The field of Nanotechnology is such an example, because it combines the aforementioned interdisciplinarity and novelty with a well-documented educational value. Herein, a novel teaching approach concerning size-dependent properties at the nanoscale for chemistry and physics undergraduate students is proposed. The analysis of the scientific content and its following reconstruction for teaching purposes is based on the theoretical framework of the Model of Educational Reconstruction (MER). This analysis yielded two fundamental concepts and a series of activities that can be the main core of teaching Nanotechnology at a university level.

Authors: Ioannis Metaxas, Emily Michailidi, Dimitris Stavrou, Ioannis V. Pavlidis

Date Published: 13th Jul 2021

Publication Type: Journal

Abstract (Expand)

Clostridium beijerinckii is a relatively widely studied, yet non-model, bacterium. While 246 genome assemblies of its various strains are available currently, the diversity of the whole species has notpecies has not been studied, and it has only been analyzed in part for a missing genome of the type strain. Here, we sequenced and assembled the complete genome of the type strain Clostridium beijerinckii DSM 791T, composed of a circular chromosome and a circular megaplasmid, and used it for a comparison with other genomes to evaluate diversity and capture the evolution of the whole species. We found that strains WB53 and HUN142 were misidentified and did not belong to the Clostridium beijerinckii species. Additionally, we filtered possibly misassembled genomes, and we used the remaining 237 high-quality genomes to define the pangenome of the whole species. By its functional annotation, we showed that the core genome contains genes responsible for basic metabolism, while the accessory genome has genes affecting final phenotype that may vary among different strains. We used the core genome to reconstruct the phylogeny of the species and showed its great diversity, which complicates the identification of particular strains, yet hides possibilities to reveal hitherto unreported phenotypic features and processes utilizable in biotechnology.

Authors: Karel Sedlar, Marketa Nykrynova, Matej Bezdicek, Barbora Branska, Martina Lengerova, Petra Patakova, Helena Skutkova

Date Published: 1st Jul 2021

Publication Type: Journal

Abstract (Expand)

Subcellular compartmentation is a fundamental property of eukaryotic cells. Communication and metabolic and regulatory interconnectivity between organelles require that solutes can be transported across their surrounding membranes. Indeed, in mammals, there are hundreds of genes encoding solute carriers (SLCs) which mediate the selective transport of molecules such as nucleotides, amino acids, and sugars across biological membranes. Research over many years has identified the localization and preferred substrates of a large variety of SLCs. Of particular interest has been the SLC25 family, which includes carriers embedded in the inner membrane of mitochondria to secure the supply of these organelles with major metabolic intermediates and coenzymes. The substrate specificity of many of these carriers has been established in the past. However, the route by which animal mitochondria are supplied with NAD(+) had long remained obscure. Only just recently, the existence of a human mitochondrial NAD(+) carrier was firmly established. With the realization that SLC25A51 (or MCART1) represents the major mitochondrial NAD(+) carrier in mammals, a long-standing mystery in NAD(+) biology has been resolved. Here, we summarize the functional importance and structural features of this carrier as well as the key observations leading to its discovery.

Authors: M. Ziegler, M. Monne, A. Nikiforov, G. Agrimi, I. Heiland, F. Palmieri

Date Published: 14th Jun 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

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