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Institute
- Theodor-Boveri-Institut für Biowissenschaften (39) (remove)
EU-Project number / Contract (GA) number
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To fire action-potential-like electrical signals, the vacuole membrane requires the two-pore channel TPC1, formerly called SV channel. The TPC1/SV channel functions as a depolarization-stimulated, non-selective cation channel that is inhibited by luminal Ca\(^{2+}\). In our search for species-dependent functional TPC1 channel variants with different luminal Ca\(^{2+}\) sensitivity, we found in total three acidic residues present in Ca\(^{2+}\) sensor sites 2 and 3 of the Ca\(^{2+}\)-sensitive AtTPC1 channel from Arabidopsis thaliana that were neutral in its Vicia faba ortholog and also in those of many other Fabaceae. When expressed in the Arabidopsis AtTPC1-loss-of-function background, wild-type VfTPC1 was hypersensitive to vacuole depolarization and only weakly sensitive to blocking luminal Ca\(^{2+}\). When AtTPC1 was mutated for these VfTPC1-homologous polymorphic residues, two neutral substitutions in Ca\(^{2+}\) sensor site 3 alone were already sufficient for the Arabidopsis At-VfTPC1 channel mutant to gain VfTPC1-like voltage and luminal Ca\(^{2+}\) sensitivity that together rendered vacuoles hyperexcitable. Thus, natural TPC1 channel variants exist in plant families which may fine-tune vacuole excitability and adapt it to environmental settings of the particular ecological niche.
Interleukin-4 (IL-4) plays a key role in atopic diseases. It coordinates T-helper cell differentiation to subtype 2, thereby directing defense toward humoral immunity. Together with Interleukin-13, IL-4 further induces immunoglobulin class switch to IgE. Antibodies of this type activate mast cells and basophilic and eosinophilic granulocytes, which release pro-inflammatory mediators accounting for the typical symptoms of atopic diseases. IL-4 and IL-13 are thus major targets for pharmaceutical intervention strategies to treat atopic diseases. Besides neutralizing antibodies against IL-4, IL-13, or its receptors, IL-4 antagonists can present valuable alternatives. Pitrakinra, an Escherichia coli-derived IL-4 antagonist, has been evaluated in clinical trials for asthma treatment in the past; however, deficits such as short serum lifetime and potential immunogenicity among others stopped further development. To overcome such deficits, PEGylation of therapeutically important proteins has been used to increase the lifetime and proteolytic stability. As an alternative, glycoengineering is an emerging strategy used to improve pharmacokinetics of protein therapeutics. In this study, we have established different strategies to attach glycan moieties to defined positions in IL-4. Different chemical attachment strategies employing thiol chemistry were used to attach a glucose molecule at amino acid position 121, thereby converting IL-4 into a highly effective antagonist. To enhance the proteolytic stability of this IL-4 antagonist, additional glycan structures were introduced by glycoengineering utilizing eucaryotic expression. IL-4 antagonists with a combination of chemical and biosynthetic glycoengineering could be useful as therapeutic alternatives to IL-4 neutralizing antibodies already used to treat atopic diseases.
Recent studies link increased ozone (O\(_3\)) and carbon dioxide (CO\(_2\)) levels to alteration of plant performance and plant-herbivore interactions, but their interactive effects on plant-pollinator interactions are little understood. Extra floral nectaries (EFNs) are essential organs used by some plants for stimulating defense against herbivory and for the attraction of insect pollinators, e.g., bees. The factors driving the interactions between bees and plants regarding the visitation of bees to EFNs are poorly understood, especially in the face of global change driven by greenhouse gases. Here, we experimentally tested whether elevated levels of O\(_3\) and CO\(_2\) individually and interactively alter the emission of Volatile Organic Compound (VOC) profiles in the field bean plant (Vicia faba, L., Fabaceae), EFN nectar production and EFN visitation by the European orchard bee (Osmia cornuta, Latreille, Megachilidae). Our results showed that O\(_3\) alone had significant negative effects on the blends of VOCs emitted while the treatment with elevated CO\(_2\) alone did not differ from the control. Furthermore, as with O\(_3\) alone, the mixture of O\(_3\) and CO\(_2\) also had a significant difference in the VOCs’ profile. O\(_3\) exposure was also linked to reduced nectar volume and had a negative impact on EFN visitation by bees. Increased CO\(_2\) level, on the other hand, had a positive impact on bee visits. Our results add to the knowledge of the interactive effects of O\(_3\) and CO\(_2\) on plant volatiles emitted by Vicia faba and bee responses. As greenhouse gas levels continue to rise globally, it is important to take these findings into consideration to better prepare for changes in plant-insect interactions.
Natural DNA storage allows cellular differentiation, evolution, the growth of our children and controls all our ecosystems. Here, we discuss the fundamental aspects of DNA storage and recent advances in this field, with special emphasis on natural processes and solutions that can be exploited. We point out new ways of efficient DNA and nucleotide storage that are inspired by nature. Within a few years DNA-based information storage may become an attractive and natural complementation to current electronic data storage systems. We discuss rapid and directed access (e.g. DNA elements such as promotors, enhancers), regulatory signals and modulation (e.g. lncRNA) as well as integrated high-density storage and processing modules (e.g. chromosomal territories). There is pragmatic DNA storage for use in biotechnology and human genetics. We examine DNA storage as an approach for synthetic biology (e.g. light-controlled nucleotide processing enzymes). The natural polymers of DNA and RNA offer much for direct storage operations (read-in, read-out, access control). The inbuilt parallelism (many molecules at many places working at the same time) is important for fast processing of information. Using biology concepts from chromosomal storage, nucleic acid processing as well as polymer material sciences such as electronical effects in enzymes, graphene, nanocellulose up to DNA macramé , DNA wires and DNA-based aptamer field effect transistors will open up new applications gradually replacing classical information storage methods in ever more areas over time (decades).
Infection research largely relies on classical cell culture or mouse models. Despite having delivered invaluable insights into host-pathogen interactions, both have limitations in translating mechanistic principles to human pathologies. Alternatives can be derived from modern Tissue Engineering approaches, allowing the reconstruction of functional tissue models in vitro. Here, we combined a biological extracellular matrix with primary tissue-derived enteroids to establish an in vitro model of the human small intestinal epithelium exhibiting in vivo-like characteristics. Using the foodborne pathogen Salmonella enterica serovar Typhimurium, we demonstrated the applicability of our model to enteric infection research in the human context. Infection assays coupled to spatio-temporal readouts recapitulated the established key steps of epithelial infection by this pathogen in our model. Besides, we detected the upregulation of olfactomedin 4 in infected cells, a hitherto unrecognized aspect of the host response to Salmonella infection. Together, this primary human small intestinal tissue model fills the gap between simplistic cell culture and animal models of infection, and shall prove valuable in uncovering human-specific features of host-pathogen interplay.
In the fast-evolving landscape of biomedical research, the emergence of big data has presented researchers with extraordinary opportunities to explore biological complexities. In biomedical research, big data imply also a big responsibility. This is not only due to genomics data being sensitive information but also due to genomics data being shared and re-analysed among the scientific community. This saves valuable resources and can even help to find new insights in silico. To fully use these opportunities, detailed and correct metadata are imperative. This includes not only the availability of metadata but also their correctness. Metadata integrity serves as a fundamental determinant of research credibility, supporting the reliability and reproducibility of data-driven findings. Ensuring metadata availability, curation, and accuracy are therefore essential for bioinformatic research. Not only must metadata be readily available, but they must also be meticulously curated and ideally error-free. Motivated by an accidental discovery of a critical metadata error in patient data published in two high-impact journals, we aim to raise awareness for the need of correct, complete, and curated metadata. We describe how the metadata error was found, addressed, and present examples for metadata-related challenges in omics research, along with supporting measures, including tools for checking metadata and software to facilitate various steps from data analysis to published research.
Highlights
• Data awareness and data integrity underpins the trustworthiness of results and subsequent further analysis.
• Big data and bioinformatics enable efficient resource use by repurposing publicly available RNA-Sequencing data.
• Manual checks of data quality and integrity are insufficient due to the overwhelming volume and rapidly growing data.
• Automation and artificial intelligence provide cost-effective and efficient solutions for data integrity and quality checks.
• FAIR data management, various software solutions and analysis tools assist metadata maintenance.
Machine learning techniques are excellent to analyze expression data from single cells. These techniques impact all fields ranging from cell annotation and clustering to signature identification. The presented framework evaluates gene selection sets how far they optimally separate defined phenotypes or cell groups. This innovation overcomes the present limitation to objectively and correctly identify a small gene set of high information content regarding separating phenotypes for which corresponding code scripts are provided. The small but meaningful subset of the original genes (or feature space) facilitates human interpretability of the differences of the phenotypes including those found by machine learning results and may even turn correlations between genes and phenotypes into a causal explanation. For the feature selection task, the principal feature analysis is utilized which reduces redundant information while selecting genes that carry the information for separating the phenotypes. In this context, the presented framework shows explainability of unsupervised learning as it reveals cell-type specific signatures. Apart from a Seurat preprocessing tool and the PFA script, the pipeline uses mutual information to balance accuracy and size of the gene set if desired. A validation part to evaluate the gene selection for their information content regarding the separation of the phenotypes is provided as well, binary and multiclass classification of 3 or 4 groups are studied. Results from different single-cell data are presented. In each, only about ten out of more than 30000 genes are identified as carrying the relevant information. The code is provided in a GitHub repository at https://github.com/AC-PHD/Seurat_PFA_pipeline.
CRISPR/Cas9 gene editing has revolutionised loss-of-function experiments in Leishmania, the causative agent of leishmaniasis. As Leishmania lack a functional non-homologous DNA end joining pathway however, obtaining null mutants typically requires additional donor DNA, selection of drug resistance-associated edits or time-consuming isolation of clones. Genome-wide loss-of-function screens across different conditions and across multiple Leishmania species are therefore unfeasible at present. Here, we report a CRISPR/Cas9 cytosine base editor (CBE) toolbox that overcomes these limitations. We employed CBEs in Leishmania to introduce STOP codons by converting cytosine into thymine and created http://www.leishbaseedit.net/ for CBE primer design in kinetoplastids. Through reporter assays and by targeting single- and multi-copy genes in L. mexicana, L. major, L. donovani, and L. infantum, we demonstrate how this tool can efficiently generate functional null mutants by expressing just one single-guide RNA, reaching up to 100% editing rate in non-clonal populations. We then generated a Leishmania-optimised CBE and successfully targeted an essential gene in a plasmid library delivered loss-of-function screen in L. mexicana. Since our method does not require DNA double-strand breaks, homologous recombination, donor DNA, or isolation of clones, we believe that this enables for the first time functional genetic screens in Leishmania via delivery of plasmid libraries.
PRO-Simat is a simulation tool for analysing protein interaction networks, their dynamic change and pathway engineering. It provides GO enrichment, KEGG pathway analyses, and network visualisation from an integrated database of more than 8 million protein-protein interactions across 32 model organisms and the human proteome. We integrated dynamical network simulation using the Jimena framework, which quickly and efficiently simulates Boolean genetic regulatory networks. It enables simulation outputs with in-depth analysis of the type, strength, duration and pathway of the protein interactions on the website. Furthermore, the user can efficiently edit and analyse the effect of network modifications and engineering experiments. In case studies, applications of PRO-Simat are demonstrated: (i) understanding mutually exclusive differentiation pathways in Bacillus subtilis, (ii) making Vaccinia virus oncolytic by switching on its viral replication mainly in cancer cells and triggering cancer cell apoptosis and (iii) optogenetic control of nucleotide processing protein networks to operate DNA storage. Multilevel communication between components is critical for efficient network switching, as demonstrated by a general census on prokaryotic and eukaryotic networks and comparing design with synthetic networks using PRO-Simat. The tool is available at https://prosimat.heinzelab.de/ as a web-based query server.
Grading, immunohistochemistry and c-kit mutation status are criteria for assessing the prognosis and therapeutic options of canine cutaneous mast cell tumours (MCTs). As a subset, canine digital MCTs have rarely been explored in this context. Therefore, in this retrospective study, 68 paraffin-embedded canine digital MCTs were analysed, and histological grading was assessed according to Patnaik and Kiupel. The immunohistochemical markers KIT and Ki67 were used, as well as polymerase chain reaction (PCR) for mutational screening in c-kit exons 8, 9, 11 and 14. Patnaik grading resulted in 22.1% grade I, 67.6% grade II and 10.3% grade III tumours. Some 86.8% of the digital MCTs were Kiupel low-grade. Aberrant KIT staining patterns II and III were found in 58.8%, and a count of more than 23 Ki67-positive cells in 52.3% of the cases. Both parameters were significantly associated with an internal tandem duplication (ITD) in c-kit exon 11 (12.7%). French Bulldogs, which tend to form well-differentiated cutaneous MCTs, had a higher proportion of digital high-grade MCTs and ITD in c-kit exon 11 compared with mongrels. Due to its retrospective nature, this study did not allow for an analysis of survival data. Nevertheless, it may contribute to the targeted characterisation of digital MCTs.