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606 Publications visible to you, out of a total of 606

Abstract (Expand)

Acyl-CoAs play a significant role in numerous physiological and metabolic processes making it important to assess their concentration levels for evaluating metabolic health. Considering the importanthe important role of acyl-CoAs, it is crucial to develop an analytical method that can analyze these compounds. Due to the structural variations of acyl-CoAs, multiple analytical methods are often required for comprehensive analysis of these compounds, which increases complexity and the analysis time. In this study, we have developed a method using a zwitterionic HILIC column that enables the coverage of free CoA and short- to long-chain acyl-CoA species in one analytical run. Initially, we developed the method on a QTOF instrument for the identification of acyl-CoA species, optimizing their chromatography and retention times. Later, a targeted HILIC-MS/MS method was created in scheduled multiple reaction monitoring mode on a QTRAP instrument. The performance of the method was evaluated based on various parameters such as linearity, precision, recovery and matrix effect. This method was applied to identify the difference in acyl-CoA profiles in HepG2 cells cultured in different conditions. Our findings revealed an increase in levels of acetyl-CoA, medium- and long-chain acyl-CoA while a decrease in the profiles of free CoA in the starved state, indicating a clear alteration in the fatty acid oxidation process.

Authors: Madhulika Singh, Ligia Akemi Kiyuna, Christoff Odendaal, Barbara M. Bakker, Amy C Harms, Thomas Hankemeier

Date Published: 11th Sep 2023

Publication Type: Journal

Abstract (Expand)

A series of nine novel ether phospholipid-dinitroaniline hybrids were synthesized in an effort to deliver more potent antiparasitic agents with improved safety profile compared to miltefosine. The compounds were evaluated for their in vitro antiparasitic activity against L. infantum, L.donovani, L. amazonensis, L. major and L. tropica promastigotes, L. infantum and L. donovani intracellular amastigotes, Trypanosoma brucei brucei and against different developmental stages of Trypanosoma cruzi. The nature of the oligomethylene spacer between the dinitroaniline moiety and the phosphate group, the length of the side chain substituent on the dinitroaniline and the choline or homocholine head group were found to affect both the activity and toxicity of the hybrids. The early ADMET profile of the derivatives did not reveal major liabilities. Hybrid 3, bearing an 11-carbon oligomethylene spacer, a butyl side chain and a choline head group, was the most potent analogue of the series. It exhibited a broad spectrum antiparasitic profile against the promastigotes of New and Old World Leishmania spp., against intracellular amastigotes of two L. infantum strains and L. donovani, against T. brucei and against T. cruzi Y strain epimastigotes, intracellular amastigotes and trypomastigotes. The early toxicity studies revealed that hybrid 3 showed a safe toxicological profile while its cytotoxicity concentration (CC50) against THP-1 macrophages being >100 μM. Computational analysis of binding sites and docking indicated that the interaction of hybrid 3 with trypanosomatid α-tubulin may contribute to its mechanism of action. Furthermore, compound 3 was found to interfere with the cell cycle in T. cruzi epimastigotes, while ultrastructural studies using SEM and TEM in T. cruzi showed that compound 3 affects cellular processes that result in changes in the Golgi complex, the mitochondria and the parasite’s plasma membrane. The snapshot pharmacokinetic studies showed low levels of 3 after 24 h following oral administration of 100 mg/Kg, while, its homocholine congener compound 9 presented a better pharmacokinetic profile.

Authors: Marina Roussaki, George E. Magoulas, Theano Fotopoulou, Nuno Santarem, Emile Barrias, Ina Pöhner, Sara Luelmo, Pantelis Afroudakis, Kalliopi Georgikopoulou, Paloma Tejera Nevado, Julia Eick, Eugenia Bifeld, María J. Corral, María Dolores Jiménez-Antón, Bernhard Ellinger, Maria Kuzikov, Irini Fragiadaki, Effie Scoulica, Sheraz Gul, Joachim Clos, Kyriakos C. Prousis, Juan J. Torrado, José María Alunda, Rebecca C. Wade, Wanderley de Souza, Anabela Cordeiro da Silva, Theodora Calogeropoulou

Date Published: 1st Sep 2023

Publication Type: Journal

Abstract

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Authors: Theresa Kouril, Craig October, Stephanie Hollocks, Christoff Odendaal, David D. van Niekerk, Jacky L. Snoep

Date Published: 1st Sep 2023

Publication Type: Journal

Abstract (Expand)

The importance of lipids seen in studies of metabolism, cancer, the recent COVID-19 pandemic and other diseases has brought the field of lipidomics to the forefront of clinical research. Quantitative and comprehensive analysis is required to understand biological interactions among lipid species. However, lipidomic analysis is often challenging due to the various compositional structures, diverse physicochemical properties, and wide dynamic range of concentrations of lipids in biological systems. To study the comprehensive lipidome, a hydrophilic interaction liquid chromatography-tandem mass spectrometry (HILIC-MS/MS)-based screening method with 1200 lipid features across 19 (sub)classes, including both nonpolar and polar lipids, has been developed. HILIC-MS/MS was selected due to its class separation property and fatty acyl chain level information. 3D models of class chromatographic retention behavior were established and evaluations of cross-class and within-class interferences were performed to avoid over-reporting these features. This targeted HILIC-MS/MS method was fully validated, with acceptable analytical parameters in terms of linearity, precision, reproducibility, and recovery. The accurate quantitation of 608 lipid species in the SRM 1950 NIST plasma was achieved using multi-internal standards per class and post-hoc correction, extending current databases by providing lipid concentrations resolved at fatty acyl chain level. The overall correlation coefficients (R(2)) of measured concentrations with values from literature range from 0.64 to 0.84. The applicability of the developed targeted lipidomics method was demonstrated by discovering 520 differential lipid features related to COVID-19 severity. This high coverage and targeted approach will aid in future investigations of the lipidome in various disease contexts.

Authors: Z. Zhang, M. Singh, A. Kindt, A. B. Wegrzyn, M. J. Pearson, A. Ali, A. C. Harms, P. Baker, T. Hankemeier

Date Published: 31st Aug 2023

Publication Type: Journal

Abstract (Expand)

In addition to the ubiquitous big data, one key challenge indata processing and management in the life sciences is the diversity ofsmall data. Diverse pieces of small data have to be transformed intostandards-compliant data. Here, the challenge lies not in the difficulty ofsingle steps that need to be performed, but rather in the fact that manytransformation tasks are to be performed once or only a few times. Thislimits the time that can be put into automated approaches, which inturn severely limits the verifiability of such transformations.As much of the data to be processed is stored in spreadsheets, withinthis paper we justify and propose a lightweight recording-based solutionthat works on a wide variety of spreadsheet programs, from MicrosoftExcel to Google Docs.

Authors: Wolfgang Müller, Lukrécia Mertová

Date Published: 23rd Mar 2023

Publication Type: Journal

Abstract (Expand)

The neuroprotective performance against neuroinflammation of the endocannabinoid system (ECS) can be remarkably improved by indirect stimulation mediated by the pharmacological inhibition of the key ECS catabolic enzyme fatty acid amide hydrolase (FAAH). Based on our previous works and aiming to discover new selective FAAH inhibitors , we herein reported a new series of carbamate-based FAAH inhibitors (4a-t) which showed improved drug disposition properties compared to the previously reported analogues 2a-b. The introduction of ionizable functions allowed us to obtain new FAAH inhibitors of nanomolar potency characterized by good water solubility and chemical stability at physiological pH. Interesting structure-activity relationships (SARs), deeply analyzed by molecular docking and molecular dynamic (MD) simulations, were obtained. All the newly developed inhibitors showed an excellent selectivity profile evaluated against monoacylglycerol lipase and cannabinoid receptors. The reversible mechanism of action was determined by a rapid dilution assay. Absence of toxicity was confirmed in mouse fibroblasts NIH3T3 (for compounds 4e, 4g, 4n-o, and 4s) and in human astrocytes cell line 1321N1 (for compounds 4e, 4n, and 4s). The absence of undesired cardiac effects was also confirmed for compound 4n. Selected analogues (compounds 4e, 4g, 4n, and 4s) were able to reduce oxidative stress in 1321N1 astrocytes and exhibited notable neuroprotective effects when tested in an ex vivo model of neuroinflammation.

Authors: A. Papa, S. Pasquini, F. Galvani, M. Cammarota, C. Contri, G. Carullo, S. Gemma, A. Ramunno, S. Lamponi, B. Gorelli, S. Saponara, K. Varani, M. Mor, G. Campiani, F. Boscia, F. Vincenzi, A. Lodola, S. Butini

Date Published: 15th Jan 2023

Publication Type: Journal

Abstract (Expand)

Abstract The BioCreative National Library of Medicine (NLM)-Chem track calls for a community effort to fine-tune automated recognition of chemical names in the biomedical literature. Chemicals are oneerature. Chemicals are one of the most searched biomedical entities in PubMed, and—as highlighted during the coronavirus disease 2019 pandemic—their identification may significantly advance research in multiple biomedical subfields. While previous community challenges focused on identifying chemical names mentioned in titles and abstracts, the full text contains valuable additional detail. We, therefore, organized the BioCreative NLM-Chem track as a community effort to address automated chemical entity recognition in full-text articles. The track consisted of two tasks: (i) chemical identification and (ii) chemical indexing. The chemical identification task required predicting all chemicals mentioned in recently published full-text articles, both span [i.e. named entity recognition (NER)] and normalization (i.e. entity linking), using Medical Subject Headings (MeSH). The chemical indexing task required identifying which chemicals reflect topics for each article and should therefore appear in the listing of MeSH terms for the document in the MEDLINE article indexing. This manuscript summarizes the BioCreative NLM-Chem track and post-challenge experiments. We received a total of 85 submissions from 17 teams worldwide. The highest performance achieved for the chemical identification task was 0.8672 F-score (0.8759 precision and 0.8587 recall) for strict NER performance and 0.8136 F-score (0.8621 precision and 0.7702 recall) for strict normalization performance. The highest performance achieved for the chemical indexing task was 0.6073 F-score (0.7417 precision and 0.5141 recall). This community challenge demonstrated that (i) the current substantial achievements in deep learning technologies can be utilized to improve automated prediction accuracy further and (ii) the chemical indexing task is substantially more challenging. We look forward to further developing biomedical text–mining methods to respond to the rapid growth of biomedical literature. The NLM-Chem track dataset and other challenge materials are publicly available at https://ftp.ncbi.nlm.nih.gov/pub/lu/BC7-NLM-Chem-track/. Database URL https://ftp.ncbi.nlm.nih.gov/pub/lu/BC7-NLM-Chem-track/

Authors: Robert Leaman, Rezarta Islamaj, Virginia Adams, Mohammed A Alliheedi, João Rafael Almeida, Rui Antunes, Robert Bevan, Yung-Chun Chang, Arslan Erdengasileng, Matthew Hodgskiss, Ryuki Ida, Hyunjae Kim, Keqiao Li, Robert E Mercer, Lukrécia Mertová, Ghadeer Mobasher, Hoo-Chang Shin, Mujeen Sung, Tomoki Tsujimura, Wen-Chao Yeh, Zhiyong Lu

Date Published: 2023

Publication Type: Journal

Abstract

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Authors: Ghadeer Mobasher, Wolfgang Müller, Olga Krebs, Michael Gertz

Date Published: 2023

Publication Type: InProceedings

Abstract (Expand)

Abstract Little is known about the impact of morphological disorders in distinct zones on metabolic zonation. It was described recently that periportal fibrosis did affect the expression of CYP proteins,xpression of CYP proteins, a set of pericentrally located drug-metabolizing enzymes. Here, we investigated whether periportal steatosis might have a similar effect. Periportal steatosis was induced in C57BL6/J mice by feeding a high-fat diet with low methionine/choline content for either two or four weeks. Steatosis severity was quantified using image analysis. Triglycerides and CYP activity were quantified in photometric or fluorometric assay. The distribution of CYP3A4, CYP1A2, CYP2D6, and CYP2E1 was visualized by immunohistochemistry. Pharmacokinetic parameters of test drugs were determined after injecting a drug cocktail (caffeine, codeine, and midazolam). The dietary model resulted in moderate to severe mixed steatosis confined to periportal and midzonal areas. Periportal steatosis did not affect the zonal distribution of CYP expression but the activity of selected CYPs was associated with steatosis severity. Caffeine elimination was accelerated by microvesicular steatosis, whereas midazolam elimination was delayed in macrovesicular steatosis. In summary, periportal steatosis affected parameters of pericentrally located drug metabolism. This observation calls for further investigations of the highly complex interrelationship between steatosis and drug metabolism and underlying signaling mechanisms.

Authors: Mohamed Albadry, Sebastian Höpfl, Nadia Ehteshamzad, Matthias König, Michael Böttcher, Jasna Neumann, Amelie Lupp, Olaf Dirsch, Nicole Radde, Bruno Christ, Madlen Christ, Lars Ole Schwen, Hendrik Laue, Robert Klopfleisch, Uta Dahmen

Date Published: 1st Dec 2022

Publication Type: Journal

Abstract (Expand)

The current study gives a detailed insight into mutualistic collaboration of microalgae and bacteria, including the involvement of competitive interplay between bacteria. We provide experimental evidence provide experimental evidence that Gram-negative bacteria belonging to the Dyadobacter , Porphyrobacter , and Variovorax are the key players in a Scenedesmus quadricauda alga-bacteria interaction.

Authors: Yekaterina Astafyeva, Marno Gurschke, Minyue Qi, Lutgardis Bergmann, Daniela Indenbirken, Imke de Grahl, Elena Katzowitsch, Sigrun Reumann, Dieter Hanelt, Malik Alawi, Wolfgang R. Streit, Ines Krohn

Date Published: 1st Aug 2022

Publication Type: Journal

Abstract (Expand)

Predicting a multicellular organism’s phenotype quantitatively from its genotype is challenging, as genetic effects must propagate across scales. Circadian clocks are intracellular regulators that control temporal gene expression patterns and hence metabolism, physiology and behaviour. Here we explain and predict canonical phenotypes of circadian timing in a multicellular, model organism. We used diverse metabolic and physiological data to combine and extend mathematical models of rhythmic gene expression, photoperiod-dependent flowering, elongation growth and starch metabolism within a Framework Model for the vegetative growth of Arabidopsis thaliana, sharing the model and data files in a structured, public resource. The calibrated model predicted the effect of altered circadian timing upon each particular phenotype in clock-mutant plants under standard laboratory conditions. Altered night-time metabolism of stored starch accounted for most of the decrease in whole-plant biomass, as previously proposed. Mobilization of a secondary store of malate and fumarate was also mis-regulated, accounting for any remaining biomass defect. The three candidate mechanisms tested did not explain this organic acid accumulation. Our results link genotype through specific processes to higher-level phenotypes, formalizing our understanding of a subtle, pleiotropic syndrome at the whole-organism level, and validating the systems approach to understand complex traits starting from intracellular circuits.

Authors: Yin Hoon Chew, Daniel D Seaton, Virginie Mengin, Anna Flis, Sam T Mugford, Gavin M George, Michael Moulin, Alastair Hume, Samuel C Zeeman, Teresa B Fitzpatrick, Alison M Smith, Mark Stitt, Andrew J Millar

Date Published: 1st Jul 2022

Publication Type: Journal

Abstract

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Authors: Pierre Jouannais, Stefan Hindersin, Sarah Löhn, Massimo Pizzol

Date Published: 28th Jun 2022

Publication Type: Journal

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)

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

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

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