14 research outputs found

    Tools for experimental and computational analyses of off-target editing by programmable nucleases

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    Genome editing using programmable nucleases is revolutionizing life science and medicine. Off-target editing by these nucleases remains a considerable concern, especially in therapeutic applications. Here we review tools developed for identifying potential off-target editing sites and compare the ability of these tools to properly analyze off-target effects. Recent advances in both in silico and experimental tools for off-target analysis have generated remarkably concordant results for sites with high off-target editing activity. However, no single tool is able to accurately predict low-frequency off-target editing, presenting a bottleneck in therapeutic genome editing, because even a small number of cells with off-target editing can be detrimental. Therefore, we recommend that at least one in silico tool and one experimental tool should be used together to identify potential off-target sites, and amplicon-based next-generation sequencing (NGS) should be used as the gold standard assay for assessing the true off-target effects at these candidate sites. Future work to improve off-target analysis includes expanding the true off-target editing dataset to evaluate new experimental techniques and to train machine learning algorithms; performing analysis using the particular genome of the cells in question rather than the reference genome; and applying novel NGS techniques to improve the sensitivity of amplicon-based off-target editing quantification.Off-target effects of programmable nucleases remain a critical issue for therapeutic applications of genome editing. This review compares experimental and computational tools for off-target analysis and provides recommendations for better assessments of off-target effects

    mlDEEPre: Multi-Functional Enzyme Function Prediction With Hierarchical Multi-Label Deep Learning

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    As a great challenge in bioinformatics, enzyme function prediction is a significant step toward designing novel enzymes and diagnosing enzyme-related diseases. Existing studies mainly focus on the mono-functional enzyme function prediction. However, the number of multi-functional enzymes is growing rapidly, which requires novel computational methods to be developed. In this paper, following our previous work, DEEPre, which uses deep learning to annotate mono-functional enzyme's function, we propose a novel method, mlDEEPre, which is designed specifically for predicting the functionalities of multi-functional enzymes. By adopting a novel loss function, associated with the relationship between different labels, and a self-adapted label assigning threshold, mlDEEPre can accurately and efficiently perform multi-functional enzyme prediction. Extensive experiments also show that mlDEEPre can outperform the other methods in predicting whether an enzyme is a mono-functional or a multi-functional enzyme (mono-functional vs. multi-functional), as well as the main class prediction across different criteria. Furthermore, due to the flexibility of mlDEEPre and DEEPre, mlDEEPre can be incorporated into DEEPre seamlessly, which enables the updated DEEPre to handle both mono-functional and multi-functional predictions without human intervention

    Next generation cereal crop yield enhancement: From knowledge of inflorescence development to practical engineering by genome editing

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    Artificial domestication and improvement of the majority of crops began approximately 10,000 years ago, in different parts of the world, to achieve high productivity, good quality, and widespread adaptability. It was initiated from a phenotype-based selection by local farmers and developed to current biotechnology-based breeding to feed over 7 billion people. For most cereal crops, yield relates to grain production, which could be enhanced by increasing grain number and weight. Grain number is typically determined during inflorescence development. Many mutants and genes for inflorescence development have already been characterized in cereal crops. Therefore, optimization of such genes could fine-tune yield-related traits, such as grain number. With the rapidly advancing genome-editing technologies and understanding of yield-related traits, knowledge-driven breeding by design is becoming a reality. This review introduces knowledge about inflorescence yield-related traits in cereal crops, focusing on rice, maize, and wheat. Next, emerging genome-editing technologies and recent studies that apply this technology to engineer crop yield improvement by targeting inflorescence development are reviewed. These approaches promise to usher in a new era of breeding practice

    Prospects for Schistosomiasis Elimination

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    Current efforts to limit the ravages of schistosomiasis are pushing the world closer to eliminating a chronic infection that has been associated with human life in the tropics since time immemorial. This notwithstanding, the disease remains a scourge for large populations in sub-Saharan Africa, Latin America, and Southeast Asia, and the main part of this book is made up by papers dealing with its current distribution, discussing ways and means to establish and implement improved control approaches. While chemotherapy limits the symptoms caused by schistosomiasis, the number of infected people will not decrease until the parasite's life cycle is interrupted. To that end, some papers focus on the intermediate snail host, which is notoriously difficult to control, while others discuss human hygiene and sanitation. The latter approach not only prevents infection through avoiding people being infected from the snail, but more importantly, also stops people infecting the snail by leaving contagious feces and urine in nature. With morbidity reduced by chemotherapy, the immediate target now is the interruption of transmission to be achieved by new tools, such as the novel chemotherapies, improved diagnostics (for humans, animals, and snails), and vaccines discussed in several of the papers. As made clear in this book, a complex infection requires new tools as well as work on many fronts, above all; however, a clear idea is needed as to how to skillfully combine the tools available and sustain implemented control activities

    Characterization of the SAM-key – a conserved regulatory domain of the Fun30 nucleosome remodeler

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    Cells need to constantly access their genetic material. However, in eukaryotic cells, DNA is compactly wrapped around nucleosomes and their presence poses a barrier for DNA transactions. To facilitate access, eukaryotes use ATP-driven molecular machines that dynamically shape chromatin structure, called nucleosome remodelers. Budding yeast Fun30 is the prototype member of the Fun30-SMARCAD1-ETL sub-family of nucleosome remodelers important for DNA repair and gene silencing. While the catalytic mechanism has been elucidated for several remodelers, for this family of single-subunit remodelers we lack mechanistic understanding. Here we report the discovery of the SAM-key, an evolutionary conserved domain with a sterile alpha motif (SAM)-like fold with one characteristic, long, protruding helix, using structure prediction, multiple sequence alignment and biochemical characterization. The SAM-key is crucial for Fun30 function, as deletion of the SAM-key from FUN30 in budding yeast leads to DNA repair and gene silencing defects similar to a deletion of FUN30. Biochemical and biophysical characterization of the SAM-key mutant in vitro showed similar folding and stability as wildtype Fun30 as well as wildtype-level binding to DNA and nucleosomes. However, the mutant is deficient in DNA-stimulated ATP hydrolysis as well as nucleosome sliding and eviction. Structure prediction using AlphaFold2 models interaction of the long helix of the SAM-key with protrusion I, a structural element of the conserved 2-lobed ATPase domain that controls catalytic activity in other remodelers. We verified the model and the interaction by crosslinking-mass spectrometry and mutation of the interface with a double point mutant Fun30-ICRR, which phenocopies the SAM-key deletion with defective ATPase activity and nucleosome remodeling. This confirms a regulatory role for the interaction of the SAM-key helix with protrusion I. Our data thereby demonstrate a central role of the SAM-key domain in mediating the activation of Fun30 catalytic activity, a new insight into the biology of this protein and highlighting the importance of allosteric activation for nucleosome remodelers

    Systems microscopy to unravel cellular stress response signalling in drug induced liver injury

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    Toxicological insults are met by cellular adaptive stress response pathway activation. We find that activation of adaptive stress responses occur well before the typical ultimate outcome of chemical cell injury. To increase our understanding of chemically-induced adaptive stress response pathway activation and its contribution to safety assessment we believe that a time-resolved, sensitive and multiplex readout of chemical-induced toxicological relevant cellular stress responses will be essential. For that purpose, we developed a platform containing a panel of distinct adaptive stress response reporter cell lines. These are used for automated high content live cell imaging and quantitative multi-parameter image analysis to elucidate critical adaptive stress response pathway activation that can contribute to human chemical safety assessment. To conserve the endogenous gene regulatory programs, we tag selected reporter target genes with GFP using BAC-transgenomics approaches. In this thesis we demonstrate the functionality of individual BAC-GFP pathway in toxicity reporter cell lines. The application of these reporters in chemical safety assessment in relation to drug-induced liver injury is discussed in detail. We anticipate that ultimately a phenotypic adaptive stress response profiling platform will allow a high throughput and time-resolved classification of chemical-induced stress responses assisting in the safety assessment of chemicals.UBL - phd migration 201
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