8,809 research outputs found

    Systematic analyses with genomic and metabolomic insights reveal a new species, Ophiocordyceps indica sp. nov. from treeline area of Indian Western Himalayan region

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    Ophiocordyceps is a species-rich genus in the order Hypocreales (Sordariomycetes, Ascomycota) depicting a fascinating relationship between microbes and insects. In the present study, a new species, Ophiocordyceps indica sp. nov., is discovered infecting lepidopteran larvae from tree line locations (2,202–2,653 m AMSL) of the Kullu District, Himachal Pradesh, Indian Western Himalayan region, using combinations of morphological and molecular phylogenetic analyses. A phylogeny for Ophiocordyceps based on a combined multigene (nrSSU, nrLSU, tef-1α, and RPB1) dataset is provided, and its taxonomic status within Ophiocordycipitaceae is briefly discussed. Its genome size (~59 Mb) revealed 94% genetic similarity with O. sinensis; however, it differs from other extant Ophiocordyceps species based on morphological characteristics, molecular phylogenetic relationships, and genetic distance. O. indica is identified as the second homothallic species in the family Ophiocordycipitaceae, after O. sinensis. The presence of targeted marker components, viz. nucleosides (2,303.25 μg/g), amino acids (6.15%), mannitol (10.13%), and biological activity data, suggests it to be a new potential source of nutraceutical importance. Data generated around this economically important species will expand our understanding regarding the diversity of Ophiocordyceps-like taxa from new locations, thus providing new research avenues

    Studies on human cancer variant and mycobacterial isocitrate dehydrogenases

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    Mutations in human IDH genes occur in cancer and result in active site IDH variants with a gain-of-function ability to reduce the normal 2-oxoglutarate (2-OG) product of IDH catalysis to 2-hydroxyglutarate (2-HG). As reviewed in Chapter 1, elevated 2-HG levels are proposed to promote tumorigenesis via chromatin remodelling. Efficient IDH1 variant inhibitors bind in an allosteric manner at the dimer-interface and hinder binding of 2-OG and Mg2+. Ivosidenib is an IDH1 variant inhibitor that is approved for acute myeloid leukaemia (AML) treatment; however, acquired second-site S280F mutations to IDH1 render cancer cells resistant to ivosidenib treatment. The research described in this thesis investigated the mechanism of action of the second site IDH1 mutation and how to overcome resistance due to it. Kinetic analyses show that the IDH1 S280F substitution not only leads to resistance against ivosidenib but results in a higher affinity for 2-OG and Mg2+, and consequently, more efficient turnover of 2-OG to 2-HG. 1H Nuclear magnetic resonance (NMR) studies reveal that IDH1 cancer variants can turn over D-isocitrate to 2-HG. The rate of conversion of D-isocitrate to 2-HG by S280F substituted variants is more efficient than for IDH1 wildtype or active site variants without the S280F substitution. Mechanistic studies on IDH1 variants provide insights into the influence of various R132 substitutions and the role of the dimer-interface in IDH1 catalysis. In addition to resistance enabled by more efficient 2-HG production, ivosidenib binding is hindered by the loss of a hydrogen bond to S280, steric hindrance due to the S280F substitution, formation of a new hydrophobic pocket at the dimer-interface, and higher enzymatic affinity for 2-OG and Mg2+. Certain IDH1 variant inhibitors were shown to retain activity against isolated IDH1 R132C S280F and R132H S280F, some with high potency. Non-denaturing mass spectrometry (MS) reveals that inhibitors retaining activity bind with a stoichiometry of two inhibitors per IDH1 variant dimer, in contrast to ivosidenib, which binds with a stoichiometry of one inhibitor per dimer. Several inhibitors reduce 2-HG levels in cell lines overexpressing IDH1 R132C S280F or R132H S280F. Some of these inhibitors are in phase 2 clinical studies (FT-2102, DS-1001B) indicating that S280F-mediated ivosidenib resistance can be overcome by using alternative inhibitors. Targeting metabolism has also been of long-standing interest in the antibacterial field, including for Mycobacterium tuberculosis (Mtb) and Mycobacterium smegmatis (Msm). After establishing production strategies and an activity assay for Mtb IDH1/IDH2 and Msm IDH, kinetic studies support the proposal that Mtb IDH2 is likely the essential IDH isoform for oxidative decarboxylation of isocitrate in Mtb metabolism. Mtb IDH2 activity is enhanced by several reactive carbonyl group containing metabolites. Most Hs IDH1 cancer variant inhibitors are not active against Mtb IDH1/IDH2 and Msm IDH but some exhibit weak activity. The overall results provide mechanistic insights into resistance to Hs IDH1 variant inhibitors and show how this can be overcome. The studies suggest that targeting IDH may be a viable strategy for mycobacterial treatment

    Using machine learning to predict pathogenicity of genomic variants throughout the human genome

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    Geschätzt mehr als 6.000 Erkrankungen werden durch Veränderungen im Genom verursacht. Ursachen gibt es viele: Eine genomische Variante kann die Translation eines Proteins stoppen, die Genregulation stören oder das Spleißen der mRNA in eine andere Isoform begünstigen. All diese Prozesse müssen überprüft werden, um die zum beschriebenen Phänotyp passende Variante zu ermitteln. Eine Automatisierung dieses Prozesses sind Varianteneffektmodelle. Mittels maschinellem Lernen und Annotationen aus verschiedenen Quellen bewerten diese Modelle genomische Varianten hinsichtlich ihrer Pathogenität. Die Entwicklung eines Varianteneffektmodells erfordert eine Reihe von Schritten: Annotation der Trainingsdaten, Auswahl von Features, Training verschiedener Modelle und Selektion eines Modells. Hier präsentiere ich ein allgemeines Workflow dieses Prozesses. Dieses ermöglicht es den Prozess zu konfigurieren, Modellmerkmale zu bearbeiten, und verschiedene Annotationen zu testen. Der Workflow umfasst außerdem die Optimierung von Hyperparametern, Validierung und letztlich die Anwendung des Modells durch genomweites Berechnen von Varianten-Scores. Der Workflow wird in der Entwicklung von Combined Annotation Dependent Depletion (CADD), einem Varianteneffektmodell zur genomweiten Bewertung von SNVs und InDels, verwendet. Durch Etablierung des ersten Varianteneffektmodells für das humane Referenzgenome GRCh38 demonstriere ich die gewonnenen Möglichkeiten Annotationen aufzugreifen und neue Modelle zu trainieren. Außerdem zeige ich, wie Deep-Learning-Scores als Feature in einem CADD-Modell die Vorhersage von RNA-Spleißing verbessern. Außerdem werden Varianteneffektmodelle aufgrund eines neuen, auf Allelhäufigkeit basierten, Trainingsdatensatz entwickelt. Diese Ergebnisse zeigen, dass der entwickelte Workflow eine skalierbare und flexible Möglichkeit ist, um Varianteneffektmodelle zu entwickeln. Alle entstandenen Scores sind unter cadd.gs.washington.edu und cadd.bihealth.org frei verfügbar.More than 6,000 diseases are estimated to be caused by genomic variants. This can happen in many possible ways: a variant may stop the translation of a protein, interfere with gene regulation, or alter splicing of the transcribed mRNA into an unwanted isoform. It is necessary to investigate all of these processes in order to evaluate which variant may be causal for the deleterious phenotype. A great help in this regard are variant effect scores. Implemented as machine learning classifiers, they integrate annotations from different resources to rank genomic variants in terms of pathogenicity. Developing a variant effect score requires multiple steps: annotation of the training data, feature selection, model training, benchmarking, and finally deployment for the model's application. Here, I present a generalized workflow of this process. It makes it simple to configure how information is converted into model features, enabling the rapid exploration of different annotations. The workflow further implements hyperparameter optimization, model validation and ultimately deployment of a selected model via genome-wide scoring of genomic variants. The workflow is applied to train Combined Annotation Dependent Depletion (CADD), a variant effect model that is scoring SNVs and InDels genome-wide. I show that the workflow can be quickly adapted to novel annotations by porting CADD to the genome reference GRCh38. Further, I demonstrate the integration of deep-neural network scores as features into a new CADD model, improving the annotation of RNA splicing events. Finally, I apply the workflow to train multiple variant effect models from training data that is based on variants selected by allele frequency. In conclusion, the developed workflow presents a flexible and scalable method to train variant effect scores. All software and developed scores are freely available from cadd.gs.washington.edu and cadd.bihealth.org

    Resilience and food security in a food systems context

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    This open access book compiles a series of chapters written by internationally recognized experts known for their in-depth but critical views on questions of resilience and food security. The book assesses rigorously and critically the contribution of the concept of resilience in advancing our understanding and ability to design and implement development interventions in relation to food security and humanitarian crises. For this, the book departs from the narrow beaten tracks of agriculture and trade, which have influenced the mainstream debate on food security for nearly 60 years, and adopts instead a wider, more holistic perspective, framed around food systems. The foundation for this new approach is the recognition that in the current post-globalization era, the food and nutritional security of the world’s population no longer depends just on the performance of agriculture and policies on trade, but rather on the capacity of the entire (food) system to produce, process, transport and distribute safe, affordable and nutritious food for all, in ways that remain environmentally sustainable. In that context, adopting a food system perspective provides a more appropriate frame as it incites to broaden the conventional thinking and to acknowledge the systemic nature of the different processes and actors involved. This book is written for a large audience, from academics to policymakers, students to practitioners

    Pea breeding for resistance to rhizospheric pathogens

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    Pea (Pisum sativum L.) is a grain legume widely cultivated in temperate climates. It is important in the race for food security owing to its multipurpose low-input requirement and environmental promoting traits. Pea is key in nitrogen fixation, biodiversity preservation, and nutritional functions as food and feed. Unfortunately, like most crops, pea production is constrained by several pests and diseases, of which rhizosphere disease dwellers are the most critical due to their long-term persistence in the soil and difficulty to manage. Understanding the rhizosphere environment can improve host plant root microbial association to increase yield stability and facilitate improved crop performance through breeding. Thus, the use of various germplasm and genomic resources combined with scientific collaborative efforts has contributed to improving pea resistance/cultivation against rhizospheric diseases. This improvement has been achieved through robust phenotyping, genotyping, agronomic practices, and resistance breeding. Nonetheless, resistance to rhizospheric diseases is still limited, while biological and chemical-based control strategies are unrealistic and unfavourable to the environment, respectively. Hence, there is a need to consistently scout for host plant resistance to resolve these bottlenecks. Herein, in view of these challenges, we reflect on pea breeding for resistance to diseases caused by rhizospheric pathogens, including fusarium wilt, root rots, nematode complex, and parasitic broomrape. Here, we will attempt to appraise and harmonise historical and contemporary knowledge that contributes to pea resistance breeding for soilborne disease management and discuss the way forward

    The bacterial Sec-machinery as an antibiotic target

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    Molecular Research in Rice: Agronomically Important Traits 2.0

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    This volume presents recent research achievements concerning the molecular genetic basis of agronomic traits in rice. Rice (Oryza sativa L.) is the most important food crop in the world, being a staple food for more than half of the world’s population. Recent improvements in living standards have increased the worldwide demand for high-yielding and high-quality rice cultivars. To develop novel cultivars with superior agronomic performance, we need to understand the molecular basis of agronomically important traits related to grain yield, grain quality, disease resistance, and abiotic stress tolerance. Decoding the whole rice genome sequence revealed that ,while there are more than 37,000 genes in the ~400 Mbp rice genome, there are only about 3000 genes whose molecular functions are characterized in detail. We collected in this volume the continued research efforts of scholars that elucidate genetic networks and the molecular mechanisms controlling agronomically important traits in rice

    Feature Papers in Compounds

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    This book represents a collection of contributions in the field of the synthesis and characterization of chemical compounds, natural products, chemical reactivity, and computational chemistry. Among its contents, the reader will find high-quality, peer-reviewed research and review articles that were published in the open access journal Compounds by members of the Editorial Board and the authors invited by the Editorial Office and Editor-in-Chief

    Modelling, Monitoring, Control and Optimization for Complex Industrial Processes

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    This reprint includes 22 research papers and an editorial, collected from the Special Issue "Modelling, Monitoring, Control and Optimization for Complex Industrial Processes", highlighting recent research advances and emerging research directions in complex industrial processes. This reprint aims to promote the research field and benefit the readers from both academic communities and industrial sectors
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