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19 Publications visible to you, out of a total of 19

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 (Expand)

Phosphoinositide 3-kinase (PI3K) is a key component of the insulin signaling pathway that controls cellular me-tabolism and growth. Loss-of-function mutations in PI3K signaling and other downstream effectors of the insulin signaling pathway extend the lifespan of various model organisms. However, the pro-longevity effect appears to be sex-specific and young mice with reduced PI3K signaling have increased risk of cardiac disease. Hence, it remains elusive as to whether PI3K inhibition is a valid strategy to delay aging and extend healthspan in humans. We recently demonstrated that reduced PI3K activity in cardiomyocytes delays cardiac growth, causing subnormal contractility and cardiopulmonary functional capacity, as well as increased risk of mortality at young age. In stark contrast, in aged mice, experi-mental attenuation of PI3K signaling reduced the age-dependent decline in cardiac function and extended maximal lifespan, suggesting a biphasic effect of PI3K on cardiac health and survival. The cardiac anti-aging effects of reduced PI3K activity coincided with enhanced oxida-tive phosphorylation and required increased autophagic flux. In humans, explanted failing hearts showed in-creased PI3K signaling, as indicated by increased phos-phorylation of the serine/threonine-protein kinase AKT. Hence, late-life cardiac-specific targeting of PI3K might have a therapeutic potential in cardiac aging and related diseases.

Authors: M. Abdellatif, T. Eisenberg, A. M. Heberle, K. Thedieck, G. Kroemer, S. Sedej

Date Published: 30th Nov 2022

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)

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)

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)

Cells have evolved highly intertwined kinase networks to finely tune cellular homeostasis to the environment. The network converging on the mechanistic target of rapamycin (MTOR) kinase constitutes a central hub that integrates metabolic signals and adapts cellular metabolism and functions to nutritional changes and stress. Feedforward and feedback loops, crosstalks and a plethora of modulators finely balance MTOR-driven anabolic and catabolic processes. This complexity renders it difficult - if not impossible - to intuitively decipher signaling dynamics and network topology. Over the last two decades, systems approaches have emerged as powerful tools to simulate signaling network dynamics and responses. In this review, we discuss the contribution of systems studies to the discovery of novel edges and modulators in the MTOR network in healthy cells and in disease.

Authors: A. M. Heberle, U. Rehbein, M. Rodriguez Peiris, K. Thedieck

Date Published: 26th Feb 2021

Publication Type: Journal

Abstract

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Authors: Mathias Bockwoldt, Dorothée Houry, Marc Niere, Toni I. Gossmann, Ines Reinartz, Alexander Schug, Mathias Ziegler, Ines Heiland

Date Published: 6th Aug 2019

Publication Type: Journal

Abstract

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Authors: Tjaša Kumelj, Snorre Sulheim, Alexander Wentzel, Eivind Almaas

Date Published: 7th Dec 2018

Publication Type: Not specified

Abstract (Expand)

Pseudomonas is a highly versatile genus containing species that can be harmful to humans and plants while others are widely used for bioengineering and bioremediation. We analysed 432 sequenced Pseudomonas strains by integrating results from a large scale functional comparison using protein domains with data from six metabolic models, nearly a thousand transcriptome measurements and four large scale transposon mutagenesis experiments. Through heterogeneous data integration we linked gene essentiality, persistence and expression variability. The pan-genome of Pseudomonas is closed indicating a limited role of horizontal gene transfer in the evolutionary history of this genus. A large fraction of essential genes are highly persistent, still non essential genes represent a considerable fraction of the core-genome. Our results emphasize the power of integrating large scale comparative functional genomics with heterogeneous data for exploring bacterial diversity and versatility.

Authors: J. J. Koehorst, J. C. van Dam, R. G. van Heck, E. Saccenti, V. A. Dos Santos, M. Suarez-Diez, P. J. Schaap

Date Published: 6th Dec 2016

Publication Type: Journal

Abstract (Expand)

The mitochondrial NAD pool is particularly important for the maintenance of vital cellular functions. Although at least in some fungi and plants, mitochondrial NAD is imported from the cytosol by carrier proteins, in mammals, the mechanism of how this organellar pool is generated has remained obscure. A transporter mediating NAD import into mammalian mitochondria has not been identified. In contrast, human recombinant NMNAT3 localizes to the mitochondrial matrix and is able to catalyze NAD(+) biosynthesis in vitro. However, whether the endogenous NMNAT3 protein is functionally effective at generating NAD(+) in mitochondria of intact human cells still remains to be demonstrated. To modulate mitochondrial NAD(+) content, we have expressed plant and yeast mitochondrial NAD(+) carriers in human cells and observed a profound increase in mitochondrial NAD(+). None of the closest human homologs of these carriers had any detectable effect on mitochondrial NAD(+) content. Surprisingly, constitutive redistribution of NAD(+) from the cytosol to the mitochondria by stable expression of the Arabidopsis thaliana mitochondrial NAD(+) transporter NDT2 in HEK293 cells resulted in dramatic growth retardation and a metabolic shift from oxidative phosphorylation to glycolysis, despite the elevated mitochondrial NAD(+) levels. These results suggest that a mitochondrial NAD(+) transporter, similar to the known one from A. thaliana, is likely absent and could even be harmful in human cells. We provide further support for the alternative possibility, namely intramitochondrial NAD(+) synthesis, by demonstrating the presence of endogenous NMNAT3 in the mitochondria of human cells.

Authors: M. R. VanLinden, C. Dolle, I. K. Pettersen, V. A. Kulikova, M. Niere, G. Agrimi, S. E. Dyrstad, F. Palmieri, A. A. Nikiforov, K. J. Tronstad, M. Ziegler

Date Published: 13th Nov 2015

Publication Type: Not specified

Abstract (Expand)

Sustainable production of target compounds such as biofuels and high-value chemicals for pharmaceutical, agrochemical, and chemical industries is becoming an increasing priority given their current dependency upon diminishing petrochemical resources. Designing these strains is difficult, with current methods focusing primarily on knocking-out genes, dismissing other vital steps of strain design including the overexpression and dampening of genes. The design predictions from current methods also do not translate well-into successful strains in the laboratory. Here, we introduce RobOKoD (Robust, Overexpression, Knockout and Dampening), a method for predicting strain designs for overproduction of targets. The method uses flux variability analysis to profile each reaction within the system under differing production percentages of target-compound and biomass. Using these profiles, reactions are identified as potential knockout, overexpression, or dampening targets. The identified reactions are ranked according to their suitability, providing flexibility in strain design for users. The software was tested by designing a butanol-producing Escherichia coli strain, and was compared against the popular OptKnock and RobustKnock methods. RobOKoD shows favorable design predictions, when predictions from these methods are compared to a successful butanol-producing experimentally-validated strain. Overall RobOKoD provides users with rankings of predicted beneficial genetic interventions with which to support optimized strain design.

Authors: N. J. Stanford, P. Millard, N. Swainston

Date Published: 24th Mar 2015

Publication Type: Not specified

Abstract (Expand)

Systems metabolomics, the identification and quantification of cellular metabolites and their integration with genomics and proteomics data, promises valuable functional insights into cellular biology. However, technical constraints, sample complexity issues and the lack of suitable complementary quantitative data sets prevented accomplishing such studies in the past. Here, we present an integrative metabolomics study of the genome-reduced bacterium Mycoplasma pneumoniae. We experimentally analysed its metabolome using a cross-platform approach. We explain intracellular metabolite homeostasis by quantitatively integrating our results with the cellular inventory of proteins, DNA and other macromolecules, as well as with available building blocks from the growth medium. We calculated in vivo catalytic parameters of glycolytic enzymes, making use of measured reaction velocities, as well as enzyme and metabolite pool sizes. A quantitative, inter-species comparison of absolute and relative metabolite abundances indicated that metabolic pathways are regulated as functional units, thereby simplifying adaptive responses. Our analysis demonstrates the potential for new scientific insight by integrating different types of large-scale experimental data from a single biological source.

Authors: T. Maier, J. Marcos, J. A. Wodke, B. Paetzold, M. Liebeke, R. Gutierrez-Gallego, L. Serrano

Date Published: 20th Apr 2013

Publication Type: Not specified

Abstract (Expand)

Mycoplasma pneumoniae, a threatening pathogen with a minimal genome, is a model organism for bacterial systems biology for which substantial experimental information is available. With the goal of understanding the complex interactions underlying its metabolism, we analyzed and characterized the metabolic network of M. pneumoniae in great detail, integrating data from different omics analyses under a range of conditions into a constraint-based model backbone. Iterating model predictions, hypothesis generation, experimental testing, and model refinement, we accurately curated the network and quantitatively explored the energy metabolism. In contrast to other bacteria, M. pneumoniae uses most of its energy for maintenance tasks instead of growth. We show that in highly linear networks the prediction of flux distributions for different growth times allows analysis of time-dependent changes, albeit using a static model. By performing an in silico knock-out study as well as analyzing flux distributions in single and double mutant phenotypes, we demonstrated that the model accurately represents the metabolism of M. pneumoniae. The experimentally validated model provides a solid basis for understanding its metabolic regulatory mechanisms.

Authors: J. A. Wodke, J. Puchalka, M. Lluch-Senar, J. Marcos, E. Yus, M. Godinho, R. Gutierrez-Gallego, V. A. dos Santos, L. Serrano, E. Klipp, T. Maier

Date Published: 4th Apr 2013

Publication Type: Not specified

Abstract

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Authors: Pablo I. Nikel, Víctor de Lorenzo

Date Published: 2013

Publication Type: Not specified

Abstract (Expand)

The high osmolarity glycerol (HOG) pathway in yeast serves as a prototype signalling system for eukaryotes. We used an unprecedented amount of data to parameterise 192 models capturing different hypotheses about molecular mechanisms underlying osmo-adaptation and selected a best approximating model. This model implied novel mechanisms regulating osmo-adaptation in yeast. The model suggested that (i) the main mechanism for osmo-adaptation is a fast and transient non-transcriptional Hog1-mediated activation of glycerol production, (ii) the transcriptional response serves to maintain an increased steady-state glycerol production with low steady-state Hog1 activity, and (iii) fast negative feedbacks of activated Hog1 on upstream signalling branches serves to stabilise adaptation response. The best approximating model also indicated that homoeostatic adaptive systems with two parallel redundant signalling branches show a more robust and faster response than single-branch systems. We corroborated this notion to a large extent by dedicated measurements of volume recovery in single cells. Our study also demonstrates that systematically testing a model ensemble against data has the potential to achieve a better and unbiased understanding of molecular mechanisms.

Authors: J. Schaber, R. Baltanas, A. Bush, E. Klipp, A. Colman-Lerner

Date Published: 15th Nov 2012

Publication Type: Not specified

Abstract

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Authors: Matthew A. Oberhardt, Jacek Puchałka, Vítor A. P. Martins dos Santos, Jason A. Papin

Date Published: 31st Mar 2011

Publication Type: Not specified

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Authors: Seung Bum Sohn, Tae Yong Kim, Jong Myoung Park, Sang Yup Lee

Date Published: 1st Jul 2010

Publication Type: Not specified

Abstract (Expand)

Negative feedback control is a ubiquitous feature of biochemical systems, as is time delay between a signal and its response. Negative feedback in conjunction with time delay can lead to oscillations. In a cellular context, it might be beneficial to mitigate oscillatory behaviour to avoid recurring stress situations. This can be achieved by increasing the distance between the parameters of the system and certain thresholds, beyond which oscillations occur. This distance has been termed resistance. Here, we prove that in a generic three-dimensional negative feedback system the resistance of the system is modified by nested autoinhibitory feedbacks. Our system features negative feedbacks through both input-inhibition as well as output-activation, a signalling component with mass conservation and perfect adaptation. We show that these features render the system applicable to biological data, exemplified by the high osmolarity glycerol system in yeast and the mammalian p53 system. Output-activation is better supported by data than input-inhibition and also shows distinguished properties with respect to the system's stimulus. Our general approach might be useful in designing synthetic systems in which oscillations can be tuned by synthetic autoinhibitory feedbacks.

Authors: J. Schaber, A. Lapytsko, D. Flockerzi

Date Published: No date defined

Publication Type: Not specified

Abstract (Expand)

Mutations in pre-mRNA processing factors (PRPFs) cause 40% of autosomal dominant retinitis pigmentosa (RP), but it is unclear why mutations in ubiquitously expressed PRPFs cause retinal disease. To understand the molecular basis of this phenotype, we have generated RP type 11 (PRPF31-mutated) patient-specific retinal organoids and retinal pigment epithelium (RPE) from induced pluripotent stem cells (iPSC). Impaired alternative splicing of genes encoding pre-mRNA splicing proteins occurred in patient-specific retinal cells and Prpf31+/− mouse retinae, but not fibroblasts and iPSCs, providing mechanistic insights into retinal-specific phenotypes of PRPFs. RPE was the most affected, characterised by loss of apical-basal polarity, reduced trans-epithelial resistance, phagocytic capacity, microvilli, and cilia length and incidence. Disrupted cilia morphology was observed in patient-derived-photoreceptors that displayed progressive features associated with degeneration and cell stress. In situ gene-editing of a pathogenic mutation rescued key structural and functional phenotypes in RPE and photoreceptors, providing proof-of-concept for future therapeutic strategies. eTOC PRPF31 is a ubiquitously expressed pre-mRNA processing factor that when mutated causes autosomal dominant RP. Using a patient-specific iPSC approach, Buskin and Zhu et al. show that retinal-specific defects result from altered splicing of genes involved in the splicing process itself, leading to impaired splicing, loss of RPE polarity and diminished phagocytic ability as well as reduced cilia incidence and length in both photoreceptors and RPE.

Authors: Adriana Buskin, Lili Zhu, Valeria Chichagova, Basudha Basu, Sina Mozaffari-Jovin, David Dolan, Alastair Droop, Joseph Collin, Revital Bronstein, Sudeep Mehrotra, Michael Farkas, Gerrit Hilgen, Kathryn White, Dean Hallam, Katarzyna Bialas, Git Chung, Carla Mellough, Yuchun Ding, Natalio Krasnogor, Stefan Przyborski, Jumana Al-Aama, Sameer Alharthi, Yaobo Xu, Gabrielle Wheway, Katarzyna Szymanska, Martin McKibbin, Chris F Inglehearn, David J Elliott, Susan Lindsay, Robin R Ali, David H Steel, Lyle Armstrong, Evelyne Sernagor, Eric Pierce, Reinhard Luehrmann, Sushma-Nagaraja Grellscheid, Colin A Johnson, Majlinda Lako

Date Published: No date defined

Publication Type: Not specified

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