Biology subjects

Schneider, R.

Publications and source records attributed to Schneider, R..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Lymphostatin: Structure of a large multi-functional virulence factor

Enteropathogenic and Enterohaemorrhagic Escherichia coli are enteric pathogens of global importance and human infections can be life-threatening. Lymphostatin is a key virulence factor of these bacteria, being required for intestinal colonisation and a potent inhibitor of the mitogen- and antigen-activated proliferation of lymphocytes and proinflammatory responses. In some strains, it also mediates adherence to host cells and influences actin nucleation at sites of attachment. This 365 kDa protein requires glycosyltransferase and cysteine protease motifs for activity against lymphocytes, but high-resolution structural information has proven elusive and the molecular mechanisms by which it acts remain unclear. Here, we describe the structure of lymphostatin from the prototype O127:H6 enteropathogenic E. coli strain determined by electron cryo-microscopy. Our results reveal two glycosyltransferase domains, one PaTox-like protease domain, an ADP-ribosyltransferase domain, and a delivery domain. Long linkers act to hold these domains together. These linkers occlude the catalytic sites of the N-terminal glycosyltransferase and protease domains. In this dormant state, lymphostatin binds to HEK-293T cells, where it forms large clusters before being taken up and sequestered into cytosolic foci. With more functional domains than any other known large bacterial toxin, lymphostatin can be regarded as the multifunctional Swiss army knife of pathogenic Escherichia coli, enabling complex interactions with the host cells in different environments.

biophysics↗

bioRxiv2024

Cohort-specific Boolean models highlight different regulatory modules during Parkinson's disease progression

1Parkinsons Disease (PD) is a multifaceted neurodegenerative disorder characterised by complex molecular dysregulations and diverse comorbidities. It is critical to decode the molecular pathophysiology of PD, which involves complex molecular interactions and their changes over time. Systems medicine approaches can help with this by a) encoding knowledge about the mechanisms into computational models b) simulating these models using patient-specific omics data. This study employs the PD map, a detailed repository of PD-related molecular interactions, as a comprehensive knowledge resource. We aim to dissect and understand the intricate molecular pathways implicated in PD by using logical modelling. This approach is essential for capturing the dynamic interplay of molecular components that contribute to the disease. We incorporate cohort-level and real-world patient data to ensure our models accurately reflect PDs subtype-specific pathway deregulations. This integration is crucial for addressing the heterogeneity observed in PD manifestations and responses to treatment. To combine logical modelling with empirical data, we rely on Probabilistic Boolean Networks (PBNs).These networks provide a robust framework, capturing the stochastic nature of molecular interactions and offering insights into the variable progression of the disease. By combining logical modelling with empirical data through PBNs, we achieve a more refined and realistic representation of PDs molecular landscape. The findings provide insights into the molecular mechanisms of PD. We identify key regulatory biomolecules and pathways that differ significantly across PD subtypes. These discoveries have substantial implications for the development of precise medical treatments. The study provides hypothesis for targeted therapeutic interventions by linking molecular dysregulation patterns to clinical phenotypes and advancing our understanding of PD progression and patient stratification.

systems biology↗

bioRxiv2023

Structural basis of tRNA recognition by the m3C-RNA-methyltransferase METTL6 in complex with SerRS seryl-tRNA synthetase

Methylation of cytosine 32 in the anticodon loop of tRNAs to 3-methylcytosine (m3C) is crucial for cellular translation fidelity 1. Misregulation of the RNA methyltransferases setting this modification can cause aggressive cancers and metabolic disturbances 2,3. However, our understanding of the substrate selection and catalysis mode of the m3C RNA methyltransferases is currently still lacking. Here, we report the cryo-electron microscopy structure of the m3C tRNA methyltransferase METTL6 in complex with seryl-tRNA synthetase (SerRS) and their common substrate tRNASer. Through the complex structure, we identify the tRNA binding domain of METTL6. We show that SerRS acts as the tRNASer substrate selection factor for METTL6. We reveal how METTL6 and SerRS jointly coordinate the long variable arm of tRNASer in their interface. We demonstrate that SerRS augments the methylation activity of METTL6 and that direct contacts between METTL6 and SerRS are necessary for efficient tRNASer methylation. Finally, based on the structure of METTL6 in complex with SerRS and tRNASer, we postulate a universal tRNA binding mode for m3C RNA methyltransferases including METTL2 and METTL8, suggesting that these mammalian paralogues use similar ways to engage their respective tRNA substrates and co-factors.

molecular biology↗

bioRxiv2023

A comprehensive study of SARS-CoV-2 main protease (Mpro) inhibitor-resistant mutants selected in a VSV-based system

Nirmatrelvir was the first protease inhibitor (PI) specifically developed against the SARS-CoV-2 main protease (3CLpro/Mpro) and licensed for clinical use. As SARS-CoV-2 continues to spread, variants resistant to nirmatrelvir and other currently available treatments are likely to arise. This study aimed to identify and characterize mutations that confer resistance to nirmatrelvir. To safely generate Mpro resistance mutations, we passaged a previously developed, chimeric vesicular stomatitis virus (VSV-Mpro) with increasing, yet suboptimal concentrations of nirmatrelvir. Using Wuhan-1 and Omicron Mpro variants, we selected a large set of mutants. Some mutations are frequently present in GISAID, suggesting their relevance in SARS-CoV-2. The resistance phenotype of a subset of mutations was characterized against clinically available PIs (nirmatrelvir and ensitrelvir) with cell-based and biochemical assays. Moreover, we showed the putative molecular mechanism of resistance based on in silico molecular modelling. These findings have implications on the development of future generation Mpro inhibitors, will help to understand SARS-CoV-2 protease-inhibitor-resistance mechanisms and show the relevance of specific mutations in the clinic, thereby informing treatment decisions. TeaserUnderstanding how SARS-CoV-2 could counter the antiviral drug nirmatrelvir and what it means for the future of COVID-19 treatment.

microbiology↗

bioRxiv2023

IL-1R signaling drives enteric glia-macrophage interaction in colorectal cancer progression

Enteric glial cells (EGCs) have been implicated in colorectal cancer (CRC) pathogenesis. However, their precise mechanisms of interaction with the CRC immune cell compartment and pro-tumorigenic role remain unclear. This study aimed to investigate the immunomodulatory effects of EGCs on tumor-associated macrophages (TAMs) and their involvement in CRC progression. Using EGC depletion and supplementation models, we assessed the impact of EGCs on the immunomodulation of orthotopic murine CRC. Furthermore, by making use of Bulk RNA-sequencing of CRC EGCs and single-cell sequencing of the tumor microenvironment, we identified the factors involved in the EGC-TAM crosstalk. Findings demonstrate that EGCs acquire a reactive and immunomodulatory phenotype in both murine CRC models and patients, influencing TAM differentiation. Mechanistically, secretion of IL-1 by tumor-infiltrating monocytes and macrophages triggers the phenotypic and functional switch of CRC EGCs via IL-1R. Consequently, tumor EGCs secrete IL-6, promoting the differentiation of monocytes into pro-tumorigenic SPP1+ TAMs. Importantly, the reactive tumor EGCs phenotype correlates with worse disease outcomes in preclinical models and CRC patients. Here we uncover a previously unexplored neuroimmune interaction between EGCs and TAMs within the colorectal tumor microenvironment, informing potential therapeutic strategies and enhancing our understanding of CRC progression. eTOC SummaryOur study unveils a novel neuroimmune interaction between enteric glia and TAMs in colon carcinoma. Monocyte/Macrophage-derived IL-1 activates enteric glia, leading to the differentiation of pro-tumorigenic SPP1+ TAMs via glial-derived IL-6. Blocking glial IL-1R-signaling reduces colonic tumor lesions, highlighting IL-1R as a potential therapeutic target.

cancer biology↗

bioRxiv2023

Applications of Boolean modeling to study the dynamics of a complex disease and therapeutics responses

Computational modeling has emerged as a critical tool in investigating the complex molecular processes involved in biological systems and diseases. In this study, we apply Boolean modeling to uncover the molecular mechanisms underlying Parkinsons disease (PD), one of the most prevalent neurodegenerative disorders. Our approach is based on the PD-map, a comprehensive molecular interaction diagram that captures the key mechanisms involved in the initiation and progression of PD. Using Boolean modeling, we aim to gain a deeper understanding of the disease dynamics, identify potential drug targets, and simulate the response to treatments. Our analysis demonstrates the effectiveness of this approach in uncovering the intricacies of PD. Our results confirm existing knowledge about the disease and provide valuable insights into the underlying mechanisms, ultimately suggesting potential targets for therapeutic intervention. Moreover, our approach allows us to parametrize the models based on omics data for further disease stratification. Our study highlight the value of computational modeling in advancing our understanding of complex biological systems and diseases, emphasizing the importance of continued research in this field. Furthermore, our findings have potential implications for the development of novel therapies for PD, which is a pressing public health concern. Overall, this study represents a significant step forward in the application of computational modeling to the investigation of neurodegenerative diseases, and underscores the power of interdisciplinary approaches in tackling challenging biomedical problems.

systems biology↗

bioRxiv2023

Using interactive platforms to encode, manage and explore immune-related adverse outcome pathways

We address the need for modelling and predicting adverse outcomes in immunotoxicology to improve non-clinical assessments of immunomodulatory therapy safety and efficacy. The integrated approach includes, first, the adverse outcome pathway concept established in the toxicology field, and, second, the systems medicine disease map approach for describing molecular mechanisms involved in a particular pathology. The proposed systems immunotoxicology workflow is demonstrated with CAR T cell treatment as a use case. To this end, the linear adverse outcome pathway (AOP) is expanded into a molecular interaction model in standard systems biology formats. Then it is shown how knowledge related to immunotoxic events can be integrated, encoded, managed and explored to benefit the research community. The map is accessible online via the MINERVA Platform for browsing, commenting and data visualisation (https://minerva.pages.uni.lu). Our work transforms a graphical illustration of an AOP into a digitally structured and standardised form, featuring precise and controlled vocabulary and supporting reproducible computational analyses. Because of annotations to source literature and databases, the map can be further expanded to match the evolving knowledge and research questions.

systems biology↗

bioRxiv2022

3D-Mass Spectrometry Imaging of Micro-scale 3D Cell Culture Models in Cancer Research

Three-dimensional (3D) human cell culture models have emerged as a key technology for personalized medicine and for phenotypic compound screening in more disease-like in-vitro systems. Mass spectrometry imaging (MSI) is one of the most versatile label-free techniques that enables simultaneous generation of spatial maps for multiple relevant molecules in these 3D-models. Here, we present an integrated platform for 3D-MSI of 3D-cell cultures comprising 3D-printed metal casting molds for freezing and embedding, MS imaging of 100 serial cryosections and their computational elastic 3D-reconstruction. With this platform, we monitored multiple lipids that were selectively associated with different cell-types or cell-cell interactions within 300 m-scale fibroblast and colon cancer biculture spheroids. Our findings suggest that 3D-printing-aided precise preparation of serial sections from small spheroids and visualization of marker molecules in 3D can provide a detailed overview of the cellular metabolic interplay in 3D cell culture models in cancer research and drug discovery.

cancer biology↗

bioRxiv2022

Arena3Dweb: Interactive 3D visualization of multilayered networks supporting multiple directional information channels, clustering analysis and application integration

Arena3Dweb is an interactive web tool that visualizes multi-layered networks in 3D space. In this update, Arena3Dweb supports directed networks as well as up to nine different types of connections between pairs of nodes with the use of Bezier curves. It comes with different color schemes (light/gray/dark mode), custom channel coloring, four node clustering algorithms which one can run on-the-fly, visualization in VR mode and predefined layer layouts (zig-zag, star and cube). This update also includes enhanced navigation controls (mouse orbit controls, layer dragging and layer/node selection), while its newly developed API allows integration with external applications as well as saving and loading of sessions in JSON format. Finally, a dedicated Cytoscape app has been developed, through which users can automatically send their 2D networks from Cytoscape to Arena3Dweb for 3D multi-layer visualization. Arena3Dweb is accessible at http://arena3d.pavlopouloslab.info or http://arena3d.org

bioinformatics↗

bioRxiv2022

Nucleation complex behaviour is critical for cortical microtubule array homogeneity and patterning

Plant cell walls are versatile materials that can adopt a wide range of mechanical properties through controlled deposition of cellulose fibrils. Wall integrity requires a sufficiently homogeneous fibril distribution to cope effectively with wall stresses. Additionally, specific conditions, such as the negative pressure in water transporting xylem vessels, may require more complex wall patterns, e.g., bands in protoxylem. The orientation and patterning of cellulose fibrils is guided by dynamic cortical microtubules. New microtubules are predominantly nucleated from parent microtubules causing positive feedback on local microtubule density with the potential to yield highly inhomogeneous patterns. Inhomogeneity indeed appears in all current cortical array simulations that include microtubule-based nucleation, suggesting that plant cells must possess an as-yet unknown balancing mechanism to prevent it. Here, in a combined simulation and experimental approach, we show that the naturally limited local recruitment of nucleation complexes to microtubules can counter the positive feedback, whereas local tubulin depletion cannot. We observe that nucleation complexes are preferentially inserted at microtubules. By incorporating our experimental findings in stochastic simulations, we find that the spatial behaviour of nucleation complexes delicately balances the positive feedback, such that differences in local microtubule dynamics - as in developing protoxylem - can quickly turn a homogeneous array into a patterned one. Our results provide insight into how the plant cytoskeleton is wired to meet diverse mechanical requirements and greatly increase the predictive power of computational cell biology studies. Significance statementThe plant cortical microtubule array is an established model system for self-organisation, with a rich history of complementary experiments, computer simulations, and analytical theory. Understanding how array homogeneity is maintained given that new microtubules nucleate from existing microtubules has been a major hurdle for using mechanistic (simulation) models to predict future wall structures. We overcome this hurdle with detailed observations of the nucleation process from which we derive a more "natural" nucleation algorithm. With this algorithm, we enable various new lines of quantitative, mechanistic research into how cells dynamically control their cell wall properties. At a mechanistic level, moreover, this work relates to the theory on cluster coexistence in Turing-like continuum models and demonstrates its relevance for discrete stochastic entities.

plant biology↗

bioRxiv2022

Arabidopsis PFA-DSP-type phosphohydrolases target specific inositol pyrophosphate messengers

Inositol pyrophosphates are signaling molecules containing at least one phosphoanhydride bond that regulate a wide range of cellular processes in eukaryotes. With a cyclic array of phosphate esters and diphosphate groups around myo-inositol, these molecular messengers possess the highest charge density found in nature. Recent work deciphering inositol pyrophosphate biosynthesis in Arabidopsis revealed important functions of these messengers in nutrient sensing, hormone signaling and plant immunity. However, despite the rapid hydrolysis of these molecules in plant extracts, very little is known about the molecular identity of the phosphohydrolases that convert these messengers back to their inositol polyphosphate precursors. Here, we investigate whether Arabidopsis Plant and Fungi Atypical Dual Specificity Phosphatases (PFA-DSP1-5) catalyze inositol pyrophosphate phosphohydrolase activity. We find that recombinant proteins of all five Arabidopsis PFA-DSP homologs display phosphohydrolase activity with a high specificity for the 5-{beta}-phosphate of inositol pyrophosphates. We further show that heterologous expression of Arabidopsis PFA-DSP1-5 rescues wortmannin-sensitivity and deranged inositol pyrophosphate homeostasis caused by the deficiency of the PFA-DSP-type inositol pyrophosphate phosphohydrolase Siw14 in yeast. Heterologous expression in Nicotiana benthamiana leaves provided evidence that Arabidopsis PFA-DSP1 also displays 5-{beta}-phosphate specific inositol pyrophosphate phosphohydrolase activity in planta. Our findings lay the biochemical basis and provide the genetic tools to uncover the roles of inositol pyrophosphates in plant physiology and plant development.

plant biology↗

bioRxiv2022

Gal1 repression memory in budding yeast

Cells must continuously adapt to changing environments and, thus, have evolved mechanisms allowing them to respond to repeated stimuli. For example, faster gene induction upon a repeated stimulus aids adaptation - a process known as reinduction memory. However, whether such a memory exists for gene repression is unclear. Here, we studied gene repression across repeated carbon source shifts in over 2,500 single Saccharomyces cerevisiae cells. By monitoring the expression of a carbon source-responsive gene, galactokinase 1 (Gal1), and mathematical modeling, we discovered repression memory at the population and single-cell level. Using a repressor model to estimate single-cell repression parameters, we show that repression memory is due to a shortened repression delay, the estimated time gap between carbon source shift and Gal1 expression termination, upon the repeated carbon source shift. Additionally, we show that cells lacking Elp6 display a gain-of-repression-memory phenotype characterized by a stronger decrease in repression delay between two consecutive carbon source shifts. Collectively, our study provides the first quantitative description of repression memory in single cells.

systems biology↗

bioRxiv2021

The MLL3/4 complexes and MiDAC act antagonistically as genome-wide regulators of H4K20ac to control a specific gene expression program

The mitotic deacetylase complex MiDAC has recently been shown to play a vital physiological role in embryonic development and neurite outgrowth. However, how MiDAC functionally intersects with other chromatin-modifying regulators is poorly understood. Here, we describe a physical interaction between the histone H3K27 demethylase UTX, a complex-specific subunit of the enhancer-associated MLL3/4 complexes, and MiDAC. We demonstrate that UTX bridges the association of the MLL3/4 complexes and MiDAC by interacting with ELMSAN1, a scaffolding subunit of MiDAC. Our data shows that MiDAC constitutes a negative genome-wide regulator of H4K20ac, an activity which is counteracted by the MLL3/4 complexes. MiDAC and the MLL3/4 complexes co-localize at many genomic regions, that are enriched for H4K20ac and the enhancer marks H3K4me1, H3K4me2 and H3K27ac. We find that MiDAC antagonizes the recruitment of the MLL3/4 complexes to negatively regulate H4K20ac, H3K4me2 and H3K27ac resulting in transcriptional attenuation of associated genes. In summary, our findings provide a paradigm how the opposing roles of chromatin-modifying components, such as MiDAC and the MLL3/4 complexes, balance the transcriptional output of specific gene expression programs.

molecular biology↗

bioRxiv2021

Large-scale conformational changes of FhaC provide insights into the two-partner secretion mechanism

The Two-Partner secretion pathway mediates protein transport across the outer membrane of Gram-negative bacteria. TpsB transporters belong to the Omp85 superfamily, whose members catalyze protein insertion into, or translocation across membranes without external energy sources. They are composed of a transmembrane {beta} barrel preceded by two periplasmic POTRA domains that bind the incoming protein substrate. Here we used an integrative approach combining in vivo assays, mass spectrometry, nuclear magnetic resonance and electron paramagnetic resonance techniques suitable to detect minor states in heterogeneous populations, to explore transient conformers of the TpsB transporter FhaC. This revealed substantial, spontaneous conformational changes with a portion of the POTRA2 domain coming close to the lipid bilayer and surface loops. Specifically, the amphipathic {beta} hairpin immediately preceding the first barrel strand can insert into the {beta} barrel. We propose that these motions enlarge the channel and hoist the substrate into it for secretion. An anchor region at the interface of the {beta} barrel and the POTRA2 domain stabilizes the transporter in the course of secretion. Our data propose a solution to the conundrum how these transporters mediate protein secretion without the need for cofactors, by utilizing intrinsic protein dynamics.

biophysics↗

bioRxiv2021

Human pluripotent stem cell-derived kidney organoids for personalized congenital and idiopathic nephrotic syndrome modeling

Nephrotic syndrome (NS) is characterized by severe proteinuria as a consequence of kidney glomerular injury due to podocyte damage. In vitro models mimicking in vivo podocyte characteristics are a prerequisite to resolve NS pathogenesis. Here, we report human induced pluripotent stem cell derived kidney organoids containing a podocyte population that heads towards adult podocytes and were superior compared to 2D counterparts, based on scRNA sequencing, super-resolution imaging and electron microscopy. In this study, these next-generation podocytes in kidney organoids enabled personalized idiopathic nephrotic syndrome modeling as shown by activated slit diaphragm signaling and podocyte injury following protamine sulfate treatment and exposure to NS plasma containing pathogenic permeability factors. Organoids cultured from cells of a patient with heterozygous NPHS2 mutations showed poor NPHS2 expression and aberrant NPHS1 localization, which was reversible after genetic correction. Repaired organoids displayed increased VEGFA pathway activity and transcription factor activity known to be essential for podocyte physiology, as shown by RNA sequencing. This study shows that organoids are the preferred model of choice to study idiopathic and congenital podocytopathies. Summary StatementKidney organoid podocytes allow personalized nephrotic sydrome modeling,

molecular biology↗

bioRxiv2021

Systematic identification of yeast mutants with increased rates of cell death reveals rapid stochastic necrosis associated with cell division

Cell death plays a major role in development, pathology and aging and can be triggered by various types of acute stimuli which arrest cell growth. However, little is known about chronic cell death in the context of continuing cell division. Here, we performed a genome-wide search for mutants with this type of death in dividing bakers yeast by assaying staining with phloxine B, which accumulates in dead cells. This screen yielded 83 essential and 43 non-essential gene mutants. Three contrasting types of spatial distribution of dead cells in colonies were observed, which corresponded to gene ontology enrichment for (i) DNA replication and repair, RNA processing, chromatin organization, and nuclear transport; (ii) mitosis and cytokinesis; and (iii) vesicular transport and glycosylation/cell wall homeostasis. To study dynamics of cell death in these mutants, we developed methods for analyzing the death of newborn cells (DON) and cell death in real time using microfluidics-based microscopy. These revealed rapid stochastic necrosis during bud generation or cytokinesis without prior division arrest. Increased death during division was associated with common sensitivity to plasma membrane and cell-wall perturbing agents, and could be mitigated by neutral pH stabilization of the medium. This suggests a common downstream type of cell death caused by a wide range of genetic perturbations.

cell biology↗

bioRxiv2021

COBREXA.jl: constraint-based reconstruction and exascale analysis

COBREXA.jl is a Julia package for scalable, high-performance constraint-based reconstruction and analysis of very large-scale biological models. Its primary purpose is to facilitate the integration of modern high performance computing environments with the processing and analysis of large-scale metabolic models of challenging complexity. We report the architecture of the package, and demonstrate how the design promotes analysis scalability on several use-cases with multi-organism community models. Availability and implementationhttps://doi.org/10.17881/ZKCR-BT30. Contactchristophe.trefois@uni.lu, wei.gu@uni.lu

systems biology↗

bioRxiv2021

OnTheFly2.0: a text-mining web application for automated biomedical entity recognition, document annotation, network and functional enrichment analysis

Extracting and processing information from documents is of great importance as lots of experimental results and findings are stored in local files. Therefore, extracting and analysing biomedical terms from such files in an automated way is absolutely necessary. In this article, we present OnTheFly2.0, a web application for extracting biomedical entities from individual files such as plain texts, Office documents, PDF files or images. OnTheFly2.0 can generate informative summaries in popup windows containing knowledge related to the identified terms along with links to various databases. It uses the EXTRACT tagging service to perform Named Entity Recognition (NER) for genes/proteins, chemical compounds, organisms, tissues, environments, diseases, phenotypes and Gene Ontology terms. Multiple files can be analysed, whereas identified terms such as proteins or genes can be explored through functional enrichment analysis or be associated with diseases and PubMed entries. Finally, protein-protein and protein-chemical networks can be generated with the use of STRING and STITCH services. To demonstrate its capacity for knowledge discovery, we interrogated published meta-analyses of clinical biomarkers of severe COVID-19 and uncovered inflammatory and senescence pathways that impact disease pathogenesis. OnTheFly2.0 currently supports 197 species and is available at http://onthefly.pavlopouloslab.info.

bioinformatics↗