Buchmann Institut für Molekulare Lebenswissenschaften (BMLS)
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EphrinB2 and GRIP1 stabilize mushroom spines during denervation-induced homeostatic plasticity
(2021)
Highlights
• Denervation induces mushroom spine loss and AMPAR redistribution to the surface
• GRIP1 and ephrinB2 mediate homeostatic mechanisms after lesion
• Stimulation with the ephrinB2 receptor EphB4 promotes a surface shift of AMPARs
• AMPARs surface shift restores impaired spine recovery after lesion in GRIP1 mutants
Summary
Despite decades of work, much remains elusive about molecular events at the interplay between physiological and structural changes underlying neuronal plasticity. Here, we combined repetitive live imaging and expansion microscopy in organotypic brain slice cultures to quantitatively characterize the dynamic changes of the intracellular versus surface pools of GluA2-containing α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs) across the different dendritic spine types and the shaft during hippocampal homeostatic plasticity. Mechanistically, we identify ephrinB2 and glutamate receptor interacting protein (GRIP) 1 as mediating AMPAR relocation to the mushroom spine surface following lesion-induced denervation. Moreover, stimulation with the ephrinB2 specific receptor EphB4 not only prevents the lesion-induced disappearance of mushroom spines but is also sufficient to shift AMPARs to the surface and rescue spine recovery in a GRIP1 dominant-negative background. Thus, our results unravel a crucial role for ephrinB2 during homeostatic plasticity and identify a potential pharmacological target to improve dendritic spine plasticity upon injury.
Highlights
• Enables immunostaining and visualization of epitopes deep within brain slices
• Utilizes expansion microscopy to increase imaging resolution
• Optimized for brain organotypic slice cultures and tested in acute brain slices
• Analysis workflow for protein distribution (surface vs. intracellular pool) using Imaris
Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.
Summary
Assessing protein distribution with super-resolution in tissue is often complicated and restrictive. Here, we describe a protocol for immunostaining and expansion microscopy imaging of mouse brain organotypic slice cultures. We detail an Imaris analysis workflow to analyze the surface vs intracellular distribution of AMPA receptors at super-resolution during homeostatic plasticity. We have optimized the protocol for brain organotypic slice culture and tested in acute brain slices. This protocol is suitable to study protein distribution under multiple plasticity paradigms.
The increasing incidence of infected skin wounds poses a major challenge in clinical practice, especially when conventional antibiotic therapy fails. In this context, bacteriophages emerged as promising alternatives for the treatment of antibiotic-resistant bacteria. However, clinical implementation remains hampered by the lack of efficient delivery approaches to infected wound tissue. In this study, bacteriophage-loaded electrospun fiber mats were successfully developed as next-generation wound dressings for the treatment of infected wounds. We employed a coaxial electrospinning approach, creating fibers with a protective polymer shell, enveloping bacteriophages in the core while maintaining their antimicrobial activity. The novel fibers exhibited a reproducible fiber diameter range and morphology, while the mechanical fiber properties were ideal for application onto wounds. Further, immediate release kinetics for the phages were confirmed as well as the biocompatibility of the fibers with human skin cells. Antimicrobial activity was demonstrated against Staphylococcus aureus and Pseudomonas aeruginosa and the core/shell formulation maintained the bacteriophage activity for 4 weeks when stored at − 20 °C. Based on these promising characteristics, our approach holds great potential as a platform technology for the encapsulation of bioactive bacteriophages to enable the translation of phage therapy into clinical application.
Spaceflight affects the body on every level. Reports on astronaut health identify bone marrow remodelling and dysfunction of the innate immune system as significant health risks of long-term habitation in space. Microgravity-induced alterations of the bone marrow induce physical changes to the bone marrow stem cell niche. Downstream effects on innate immunity are expected due to impaired hematopoiesis and myelopoiesis. To date, few studies have investigated these effects in real microgravity and the sparsely available literature often reports contrasting results. This emphasizes a need for the development of physiologically relevant in vitro models of the bone marrow stem cell niche, capable of delivering appropriate sample sizes for robust statistics. Here, we review recent findings on the impact of spaceflight conditions on innate immunity in in vitro and animal models and discusses the latest in vitro models of the bone marrow stem cell niche and their potential translatability to gravitational biology research.
MicroRNAs (miRNAs) are critical post-transcriptional regulators in many biological processes. They act by guiding RNA-induced silencing complexes to miRNA response elements (MREs) in target mRNAs, inducing translational inhibition and/or mRNA degradation. Functional MREs are expected to predominantly occur in the 3' untranslated region and involve perfect base-pairing of the miRNA seed. Here, we generate a high-resolution map of miR-181a/b-1 (miR-181) MREs to define the targeting rules of miR-181 in developing murine T-cells. By combining a multi-omics approach with computational high-resolution analyses, we uncover novel miR-181 targets and demonstrate that miR-181 acts predominantly through RNA destabilization. Importantly, we discover an alternative seed match and identify a distinct set of targets with repeat elements in the coding sequence which are targeted by miR-181 and mediate translational inhibition. In conclusion, deep profiling of MREs in primary cells is critical to expand physiologically relevant targetomes and establish context-dependent miRNA targeting rules.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions, using signals from nanopore direct RNA sequencing. CHEUI processes observed and expected signals with convolutional neural networks to achieve high single-molecule accuracy and outperform other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A significant roadblock hindering progress in epitranscriptomics is the identification of more than one modification in individual transcript molecules. We address this with CHEUI (CH3 (methylation) Estimation Using Ionic current). CHEUI predicts N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual molecules from the same sample, the stoichiometry at transcript reference sites, and differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals to achieve high single-molecule, transcript-site, and stoichiometry accuracies in multiple tests using synthetic RNA standards and cell line data. CHEUI’s capability to identify two modification types in the same sample reveals a co-occurrence of m6A and m5C in individual mRNAs in cell line and tissue transcriptomes. CHEUI provides new avenues to discover and study the function of the epitranscriptome.
The expanding field of epitranscriptomics might rival the epigenome in the diversity of the biological processes impacted. However, the identification of modifications in individual RNA molecules remains challenging. We present CHEUI, a new method that detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) at single-nucleotide and single-molecule resolution from Nanopore signals. CHEUI predicts methylation in Nanopore reads and transcriptomic sites in a single condition, and differential m6A and m5C methylation between any two conditions. Using extensive benchmarking with Nanopore data derived from synthetic and natural RNA, CHEUI showed higher accuracy than other existing methods in detecting m6A and m5C sites and quantifying the site stoichiometry levels, while maintaining a lower proportion of false positives. CHEUI provides a new capability to detect RNA modifications with high accuracy and resolution that can be cost-effectively expanded to other modifications to unveil the full span of the epitranscriptome in normal and disease conditions.
Upon infection of host cells, Legionella pneumophila releases a multitude of effector enzymes into the cells cytoplasm that hijack a plethora of cellular activities, including the hosts ubiquitination pathways. Effectors belonging to the SidE-family are involved in non-canonical serine phosphoribosyl ubiquitination of host substrate proteins contributing to the formation of a Legionella-containing vacuole that is crucial in the onset of Legionnaires’ disease. This dynamic process is reversed by effectors called Dups that hydrolyse the phosphodiester in the phosphoribosyl ubiquitinated protein. We installed reactive warheads on chemically prepared ribosylated ubiquitin to generate a set of probes targeting these Legionella enzymes. In vitro tests on recombinant DupA revealed that a vinyl sulfonate warhead was most efficient in covalent complex formation. Mutagenesis and x-ray crystallography approaches were used to identify the site of covalent crosslinking to be an allosteric cysteine residue. The subsequent application of this probe highlights the potential to selectively enrich the Dup enzymes from Legionella-infected cell lysates.
Targeted protein degradation (TPD) has recently emerged as an exciting new drug modality. However, the strategy of developing small molecule-based protein degraders has evolved over the past two decades and has now established molecular tags that are already in clinical use, as well as chimeric molecules, PROteolysis TArgeting Chimeras (PROTACs), based mainly on ligand systems developed for the two E3 ligases CRBN and VHL. The large size of the human E3 ligase family suggests that PROTACs can be developed by targeting a large diversity of E3 ligases, some of which have restricted expression patterns with the potential to design disease- or tissue-specific degraders. Indeed, many new E3 ligands have been published recently, confirming the druggability of E3 ligases. This review summarises recent data on E3 ligases and highlights the challenges in developing these molecules into efficient PROTACs rivalling the established degrader systems.
MicroRNAs (miRNAs) are critical post-transcriptional regulators in many biological processes. They act by guiding RNA-induced silencing complexes to miRNA response elements (MREs) in target mRNAs, inducing translational inhibition and/or mRNA degradation. Functional MREs are expected to predominantly occur in the 3’ untranslated region and involve perfect base-pairing of the miRNA seed. Here, we generate a high-resolution map of miR-181a/b-1 (miR-181) MREs to define the targeting rules of miR-181 in developing murine T-cells. By combining a multi-omics approach with computational high-resolution analyses, we uncover novel miR-181 targets and demonstrate that miR-181 acts predominantly through RNA destabilization. Importantly, we discover an alternative seed match and identify a distinct set of targets with repeat elements in the coding sequence which are targeted by miR-181 and mediate translational inhibition. In conclusion, deep profiling of MREs in primary cells is critical to expand physiologically relevant targetomes and establish context-dependent miRNA targeting rules.
Key Points:
* Deep profiling identifies novel targets of miR-181 associated with global gene regulation.
* miR-181 MREs in repeat elements in the coding sequence act through translational inhibition.
* High-resolution analysis reveals an alternative seed match in functional MREs.
Cryo-electron tomography combined with subtomogram averaging (StA) has yielded high-resolution structures of macromolecules in their native context. However, high-resolution StA is not commonplace due to beam-induced sample drift, images with poor signal-to-noise ratios (SNR), challenges in CTF correction, and limited particle number. Here we address these issues by collecting tilt series with a higher electron dose at the zero-degree tilt. Particles of interest are then located within reconstructed tomograms, processed by conventional StA, and then re-extracted from the high-dose images in 2D. Single particle analysis tools are then applied to refine the 2D particle alignment and generate a reconstruction. Use of our hybrid StA (hStA) workflow improved the resolution for tobacco mosaic virus from 7.2 to 4.4 Å and for the ion channel RyR1 in crowded native membranes from 12.9 to 9.1 Å. These resolution gains make hStA a promising approach for other StA projects aimed at achieving subnanometer resolution.
Cryo electron tomography (cryo-ET) combined with subtomogram averaging (StA) enables structural determination of macromolecules in their native context. A few structures were reported by StA at resolution higher than 4.5 Å, however all of these are from viral structural proteins or vesicle coats. Reaching high resolution for a broader range of samples is uncommon due to beam-induced sample drift, poor signal-to-noise ratio (SNR) of images, challenges in CTF correction, limited number of particles. Here we propose a strategy to address these issues, which consists of a tomographic data collection scheme and a processing workflow. Tilt series are collected with higher electron dose at zero-degree tilt in order to increase SNR. Next, after performing StA conventionally, we extract 2D projections of the particles of interest from the higher SNR images and use the single particle analysis tools to refine the particle alignment and generate a reconstruction. We benchmarked our proposed hybrid StA (hStA) workflow and improved the resolution for tobacco mosaic virus from 7.2 to 5.2 Å and the resolution for the ion channel RyR1 in crowded native membranes from 12.9 to 9.1 Å. We demonstrate that hStA can improve the resolution obtained by conventional StA and promises to be a useful tool for StA projects aiming at subnanometer resolution or higher.
The Kinase Chemogenomic Set (KCGS): An open science resource for kinase vulnerability identification
(2019)
We describe the assembly and annotation of a chemogenomic set of protein kinase inhibitors as an open science resource for studying kinase biology. The set only includes inhibitors that show potent kinase inhibition and a narrow spectrum of activity when screened across a large panel of kinase biochemical assays. Currently, the set contains 187 inhibitors that cover 215 human kinases. The kinase chemogenomic set (KCGS) is the most highly annotated set of selective kinase inhibitors available to researchers for use in cell-based screens.
RNA-binding proteins (RBPs) control every RNA metabolic process by multiple protein-RNA and protein-protein interactions. Their roles have largely been analyzed by crude mutations, which abrogate multiple functions at once and likely impact the structural integrity of the large ribonucleoprotein particles (RNPs) these proteins function in. Using UV-induced RNA-protein crosslinking of entire cells, protein complex purification and mass spectrometric analysis, we identified >100 in vivo RNA crosslinks in 16 nuclear mRNP components in Saccharomyces cerevisiae. For functional analysis, we chose Npl3, which displayed crosslinks in its two RNA recognition motifs (RRMs) and in the connecting flexible linker region. Both RRM domains and the linker uniquely contribute to RNA recognition as revealed by NMR and structural analyses. Interestingly, mutations in these regions cause different phenotypes, indicating distinct functions of the different RNA-binding domains. Notably, an npl3-Linker mutation strongly impairs recruitment of several mRNP components to chromatin and incorporation of other mRNP components into nuclear mRNPs, establishing a so far unknown function of Npl3 in nuclear mRNP assembly. Taken together, our integrative analysis uncovers a specific function of the RNA-binding activity of the nuclear mRNP component Npl3. This approach can be readily applied to RBPs in any RNA metabolic process.