Biology subjects

Becker, T.

Publications and source records attributed to Becker, T..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

Role of the small protein Mco6 in the mitochondrial sorting and assembly machinery

The majority of mitochondrial precursor proteins are imported through the Tom40 {beta}-barrel channel of the translocase of the outer membrane (TOM). The sorting and assembly machinery (SAM) is essential for {beta}-barrel membrane protein insertion into the outer membrane and thus required for the assembly of the TOM complex. Here we demonstrate that the a-helical outer membrane protein Mco6 forms a complex with the mitochondrial distribution and morphology protein Mdm10 as part of the SAM machinery. Moreover, Mco6 also interacts with the subunit Mim1 of the mitochondrial import complex (MIM), which is itself required for the biogenesis of a-helical outer membrane proteins. MCO6 and MDM10 display a negative genetic interaction and a MCO6-MDM10 yeast double mutant contains reduced levels of TOM complex. Cells lacking Mco6 affect the levels of Mdm10 and MIM-subunits associated with assembly defects of the TOM complex. Thus, this work reveals a role of the SAMMco6 complex for the biogenesis of the mitochondrial outer membrane.

cell biology↗

bioRxiv2022

Mitochondrial protein import clogging as a mechanism of disease

Mitochondrial biogenesis requires the import of >1,000 mitochondrial preproteins from the cytosol. Most studies on mitochondrial protein import are focused on the core import machinery. Whether and how the biophysical properties of substrate preproteins affect overall import efficiency is underexplored. Here, we show that protein traffic into mitochondria is disrupted by amino acid substitutions in a single substrate preprotein. Pathogenic missense mutations in adenine nucleotide translocase 1 (Ant1), and its yeast ortholog Aac2, cause the protein to accumulate along the protein import pathway, thereby obstructing general protein translocation into mitochondria. This impairs mitochondrial respiration, cytosolic proteostasis and cell viability independent of Ant1s nucleotide transport activity. The mutations act synergistically, as double mutant Aac2/Ant1 cause severe clogging primarily at the Translocase of the Outer Membrane (TOM) complex. This confers extreme toxicity in yeast. In mice, expression of a super-clogger Ant1 variant led to an age-dependent dominant myopathy that phenocopies Ant1-induced human disease, suggesting clogging as a mechanism of disease. We propose that secondary structures of mitochondrial preproteins play an essential role in preventing clogging and disease.

biochemistry↗

bioRxiv2022

The metabolite-controlled ubiquitin conjugase Ubc8 promotes mitochondrial protein import by enhancing assembly of the TOM complex

Mitochondria are essential organelles that play a key role in cellular energy metabolism. Transitions between glycolytic and respiratory conditions induce considerable adaptations of the cellular proteome. These metabolism-dependent changes are particularly pronounced for the protein composition of mitochondria. Here we show that the yeast cytosolic ubiquitin conjugase Ubc8 plays a crucial role in the remodeling process when cells transition from respiratory to fermentative conditions. Ubc8 is a conserved and well-studied component of the catabolite control system that is known to regulate the stability of gluconeogenesis enzymes. Unexpectedly, we found that Ubc8 also promotes the assembly of the translocase of the outer membrane of mitochondria (TOM) and stabilizes its cytosol-exposed receptor subunit Tom22. Ubc8 deficiency results in a compromised protein import into mitochondria and a subsequent accumulation of mitochondrial precursor proteins in the cytosol. Our observations show that Ubc8, which is controlled by the prevailing metabolic conditions, promotes the switch from glucose synthesis to glucose usage in the cytosol and induces the biogenesis of the mitochondrial TOM machinery in order to improve mitochondrial protein import during phases of metabolic transition.

biochemistry↗

bioRxiv2022

Clearing of ribosome collisions by the ribosome quality control trigger complex RQT

After translational stalls, colliding eukaryotic ribosomes are cleared through dissociation into subunits by the ribosome quality control trigger complex, RQT, by an unknown mechanism. Here we show that RQT requires accessible mRNA and the presence of a neighboring ribosome. Cryo-EM of several RQT-ribosome complexes revealed the structural basis of splitting: RQT engages the 40S subunit of the lead ribosome and can switch between two conformations. We propose a mechanistic model in which the Slh1 helicase subunit of RQT applies a pulling force on the mRNA, causing destabilizing conformational changes of the 40S subunit. The collided ribosome functions as a ram or giant wedge, ultimately resulting in subunit dissociation. Our findings provide a first conceptual framework for a helicase driven ribosomal splitting mechanism. One-Sentence SummaryRQT clears collided ribosomes by pulling mRNA to trigger destabilizing conformational transitions for subunit dissociation.

biochemistry↗

bioRxiv2022

Transforming chemical proteomics enrichment into high throughput method using SP2E workflow.

Protein post-translational modifications (PTMs) play a critical role in the regulation of protein catalytic activity, localization and protein-protein interactions. Attachment of PTMs onto proteins significantly diversifies their structure and function resulting in so-called proteoforms. However, the sole identification of post-translationally modified proteins, which are often cell type and disease specific, is still a highly challenging task. Sub-stoichiometric amounts and modification of low abundant proteins necessitate purification or enrichment of the modified proteins. Although the introduction of the mass spectrometry-based chemical proteomic strategies have enabled to screen protein PTMs with increased throughput, sample preparation has remained highly time consuming and tedious. Here, we report an optimized workflow for enrichment of PTM proteins in 96-well plate format which can be possible extended to robotic automatization. This platform allows to significantly lower the input of total protein, which opens up the opportunity to screen specialized and difficult to culture cell lines in high-throughput manner. The presented SP2E protocol is robust, time- and cost-effective as well as suitable for large-scale screening of proteoforms. Application of the SP2E protocol will thus enable the characterization of proteoforms in various processes such as neurodevelopment, neurodegeneration and cancer and may contribute to an overall acceleration of the recently launched Human Proteoform Project.

biochemistry↗

bioRxiv2021

Recognition and deubiquitination of free 40S for translational reset by Otu2

In actively translating 80S ribosomes the ribosomal protein eS7 of the 40S subunit is monoubiquitinated by the E3 ligase Not41,2 and deubiquitinated by the deubiquitination enzyme Otu2 upon ribosomal subunit recycling3. Despite its importance for general efficiency of translation the exact role and structural basis for this specific translational reset are only poorly understood. Here we present biochemical and structural data showing that Otu2 can engage the recycled 40S subunit together with the recycling factors ABCE1 and Tma64 immediately after 60S dissociation for mRNA recycling, and that it dissociates before 48S initiation complex formation. A combined structural analysis of Otu2 and Otu2-40S complexes by X-ray crystallography, AlphaFold2 prediction4 and cryo-EM revealed how Otu2 can specifically be recruited to the 40S, but not to the 80S ribosome, for removal of the eS7-bound ubiquitin moiety. Here, interactions of the largely helical N-terminal domain of Otu2 to sites that are masked and therefore inaccessible in the 80S ribosome are of crucial importance. Collectively, we provide the structural basis for the Otu2 driven deubiquitination step providing a first mechanistic understanding of this translational reset step during ribosome recycling/(re)initiation.

molecular biology↗

bioRxiv2021

AMPylation is a specific lysosomal protein posttranslational modification in neuronal maturation.

Protein AMPylation is a pervasive posttranslational modification with an emerging role in neurodevelopment. In metazoans the two highly conserved protein AMP-transferases together with a diverse group of AMPylated proteins have been identified using chemical proteomics and biochemical techniques. However, the function of this modification remains largely unknown. Particularly problematic is the localization of thus far identified AMPylated proteins and putative AMP-transferases. Here, we uncover protein AMPylation as a novel posttranslational modification of luminal lysosomal proteins characteristic in differentiating neurons. Through a combination of chemical proteomics, advanced gel-based separation of modified and unmodified proteins and activity assay, we show that an AMPylated, lysosomal soluble form of exonuclease PLD3 increases dramatically during neuronal maturation and that AMPylation inhibits its catalytic activity. Together, our findings unveil so far unknown lysosomal posttranslational modification, its connection to neuronal differentiation and putatively provide a novel molecular rationale to design of therapeutics for lysosomal storage diseases.

biochemistry↗

bioRxiv2020

Predicting compound activity from phenotypic profiles and chemical structures

Recent advances in deep learning enable using chemical structures and phenotypic profiles to accurately predict assay results for compounds virtually, reducing the time and cost of screens in the drug-discovery process. We evaluate the relative strength of three high-throughput data sources--chemical structures, images (Cell Painting), and gene-expression profiles (L1000)--to predict compound activity using a sparse historical collection of 16,170 compounds tested in 270 assays for a total of 585,439 readouts. All three data modalities can predict compound activity with high accuracy in 6-10% of assays tested; replacing million-compound physical screens with computationally prioritized smaller screens throughout the pharmaceutical industry could yield major savings. Furthermore, the three profiling modalities are complementary, and in combination they can predict 21% of assays with high accuracy, and 64% if lower accuracy is acceptable. Our study shows that, for many assays, predicting compound activity from phenotypic profiles and chemical structures might accelerate the early stages of the drug-discovery process.

bioinformatics↗

bioRxiv2020

Structural basis for translational shutdown and immune evasion by the Nsp1 protein of SARS-CoV-2

SARS-CoV-2 is the causative agent of the current COVID-19 pandemic. A major virulence factor of SARS-CoVs is the nonstructural protein 1 (Nsp1) which suppresses host gene expression by ribosome association via an unknown mechanism. Here, we show that Nsp1 from SARS-CoV-2 binds to 40S and 80S ribosomes, resulting in shutdown of capped mRNA translation both in vitro and in cells. Structural analysis by cryo-electron microscopy (cryo-EM) of in vitro reconstituted Nsp1-40S and of native human Nsp1-ribosome complexes revealed that the Nsp1 C-terminus binds to and obstructs the mRNA entry tunnel. Thereby, Nsp1 effectively blocks RIG-I-dependent innate immune responses that would otherwise facilitate clearance of the infection. Thus, the structural characterization of the inhibitory mechanism of Nsp1 may aid structure-based drug design against SARS-CoV-2.

molecular biology↗

bioRxiv2020

Phenotypic screening using synthetic CRISPR gRNAs reveals pro-regenerative genes in spinal cord injury

Acute CRISPR/Cas9 targeting offers the opportunity for scalable phenotypic genetic screening in zebrafish. However, the unpredictable efficiency of CRISPR gRNA (CrRNA) activity is a limiting factor. Here we describe how to resolve this by prescreening CrRNAs for high activity in vivo, using a simple standardised assay based on restriction fragment length polymorphism analysis (RFLP). We targeted 350 genomic sites with synthetic RNA Oligo guide RNAs (sCrRNAs) in zebrafish embryos and found that almost half exhibited > 90% efficiency in our RFLP assay. Having the ability to preselect highly active sCrRNAs (haCRs), we carried out a focussed phenotypic screen of 30 macrophage-related genes in spinal cord regeneration and found 10 genes whose disruption impaired axonal regeneration. Four (tgfb1a, tgfb3, tnfa, sparc) out of 5 stable mutants subsequently analysed retained the acute haCR phenotype, validating the efficiency of this approach. Mechanistically, lack of tgfb1a leads to a prolonged immune response after injury, which inhibits regeneration. Our rapid and scalable screening approach has identified functional regulators of spinal cord regeneration, and can be applied to study any biological function of interest. HIGHLIGHTS- Synthetic CRISPR gRNAs are highly active - in vivo pre-screening allows rapid assessment of CRISPR gRNA activity - Phenotypic CRISPR screen reveals crucial genes for spinal cord regeneration - tgfb1a promotes spinal regeneration by controlling inflammation

neuroscience↗

bioRxiv2020

Marmoset monkeys (Callithrix jacchus) develop eosinophilic airway inflammation after house dust mite exposure

BackgroundExtensive analysis of eosinophilic airway inflammation in human-relevant animal models is required to test novel, human-specific pharmaceuticals. This requires species, which show high genetic homology to humans such as non-human primates. Efficacy assessment of novel human-specific biologicals in eosinophilic airway inflammation is currently performed in the cost-intensive macaque asthma model. ObjectiveThe present study investigated whether marmoset monkeys (Callithrix jacchus), a small-bodied non-human primate species from the New World, develop eosinophilic airway inflammation in response to house dust mite allergen exposure (HDM, Dermatophagoides pteronyssinus). MethodsMarmoset monkeys were sensitized against HDM by subcutaneous (s.c.) injection and subsequent intratracheal (i.t.) HDM aerosol challenges. Airway and systemic immunologic reactions were monitored and sensitivity towards glucocorticoid therapy was assessed. The pulmonary immunologic response was analyzed by repetitive bronchoalveolar lavage (BAL). ResultsBronchoalveolar lavage fluid (BALF) exhibited increased levels of eosinophils, mast cells, and lymphocytes, as well as interleukin (IL)-13 after HDM challenges, compared to negative controls. The systemic immunologic response was assessed in peripheral blood mononuclear cells derived from sensitized animals, which secreted increased IL-13 and IFN-{gamma} upon allergen stimulation in contrast to non-sensitized negative control animals. Although IgE was not detectable, HDM-specific serum IgG was elevated in sensitized animals. Both airway and systemic responses were reduced by treatment with glucocorticoids. However, lung function and pathological analyses did not reveal significant differences between groups. ConclusionIn conclusion, marmoset monkeys developed a mild HDM-induced eosinophilic airway inflammation useful for efficacy testing of novel human-specific biologicals.

immunology↗

bioRxiv2020

Structure and function of yeast Lso2 and human CCDC124 bound to hibernating ribosomes.

Cells adjust to nutrient deprivation by reversible translational shut down. This is accompanied by maintaining inactive ribosomes in a hibernation state, where they are bound by proteins with inhibitory and protective functions. In eukaryotes, such a function was attributed to Stm1 (SERBP1 in mammals), and recently Lso2 (CCDC124 in mammals) was found to be involved in translational recovery after starvation from stationary phase. Here, we present cryo-electron microscopy (cryo-EM) structures of translationally inactive yeast and human ribosomes. We found Lso2/CCDC124 accumulating on idle ribosomes in the non-unrotated state, in contrast to Stm1/SERBP1-bound ribosomes, which display a rotated state. Lso2/CCDC124 bridges the decoding sites of the small with the GTPase-activating center of the large subunit. This position allows accommodation of the Dom34-dependent ribosome recycling system, which splits Lso2-containing but not Stm1-containing ribosomes. We propose a model in which Lso2 facilitates rapid translation reactivation by stabilizing the recycling-competent state of inactive ribosomes.

molecular biology↗

bioRxiv2019

The Ccr4-Not complex monitors the translating ribosome for codon optimality

Control of mRNA decay rate is intimately connected to translation elongation but the spatial coordination of these events is poorly understood. The Ccr4-Not complex initiates mRNA decay through deadenylation and activation of decapping. Using a combination of cryo-electron microscopy, ribosome profiling and mRNA stability assays we show recruitment of Ccr4-Not to the ribosome via specific interaction of the Not5 subunit with the ribosomal E-site. This interaction only occurs when the ribosome lacks accommodated A-site tRNA, indicative of low codon optimality. Loss of Not5 results in the inability of the mRNA degradation machinery to sense codon optimality. Our analysis elucidates a physical link between the Ccr4-Not complex and the ribosome providing mechanistic insight into the coupling of decoding efficiency with mRNA stability.

molecular biology↗

bioRxiv2019

Machine Learning Analysis of Motor Evoked Potential Time Series to Predict Disability Progression in Multiple Sclerosis

BackgroundEvoked potentials (EPs) are a measure of the conductivity of the central nervous system. They are used to monitor disease progression of multiple sclerosis patients. Previous studies only extracted a few variables from the EPs, which are often further condensed into a single variable: the EP score. We perform a machine learning analysis of motor EP that uses the whole time series, instead of a few variables, to predict disability progression after two years. Obtaining realistic performance estimates of this task has been difficult because of small data set sizes. We recently extracted a dataset of EPs from the Rehabiliation & MS Center in Overpelt, Belgium. Our data set is large enough to obtain, for the first time, a performance estimate on an independent test set containing different patients.\n\nMethodsWe extracted a large number of time series features from the motor EPs with the highly comparative time series analysis software package. Mutual information with the target and the Boruta method are used to find features which contain information not included in the features studied in the literature. We use random forests (RF) and logistic regression (LR) classifiers to predict disability progression after two years. Statistical significance of the performance increase when adding extra features is checked with the DeLong hypothesis test.\n\nResultsIncluding extra time series features in motor EPs leads to a statistically significant improvement compared to using only the known features, although the effect is limited in magnitude ({triangleup}AUC = 0.02 for RF and {triangleup}AUC = 0.05 for LR). RF with extra time series features obtains the best performance (AUC = 0.75 {+/-} 0.07), which is good considering the limited number of biomarkers in the model. RF (a nonlinear classifier) outperforms LR (a linear classifier).\n\nConclusionsUsing machine learning methods on EPs shows promising predictive performance. Using additional EP time series features beyond those already in use leads to a modest increase in performance. Larger datasets, preferably multi-center, are needed for further research. Given a large enough dataset, these models may be used to support clinicians in their decision making process regarding future treatment.

immunology↗

bioRxiv2019

Molecular mechanism of translational stalling by inhibitory codon combinations and poly(A) tracts

Inhibitory codon pairs and poly(A) tracts within the translated mRNA cause ribosome stalling and reduce protein output. The molecular mechanisms that drive these stalling events, however, are still unknown. Here, we use a combination of in vitro biochemistry, ribosome profiling, and cryo-EM to define molecular mechanisms that lead to these ribosome stalls. First, we use an in vitro reconstituted yeast translation system to demonstrate that inhibitory codon pairs slow elongation rates which are partially rescued by increased tRNA concentration or by an artificial tRNA not dependent on wobble base pairing. Ribosome profiling data extend these observations by revealing that paused ribosomes with empty A sites are enriched on these sequences. Cryo-EM structures of stalled ribosomes provide a structural explanation for the observed effects by showing decoding-incompatible conformations of mRNA in the A sites of all studied stall-inducing sequences. Interestingly, in the case of poly(A) tracts, the inhibitory conformation of the mRNA in the A site involves a nucleotide stacking array. Together, these data demonstrate novel mRNA-induced mechanisms of translational stalling in eukaryotic ribosomes.

biochemistry↗

bioRxiv2019

The exhaustive genomic scan approach, with an application to rare-variant association analysis

Region-based genome-wide scans are usually performed by use of a priori chosen analysis regions. Such an approach will likely miss the region comprising the strongest signal and, thus, may result in increased type II error rates and decreased power. Here, we propose a genomic exhaustive scan approach that analyzes all possible subsequences and does not rely on a prior definition of the analysis regions. As a prime instance, we present a computationally ultra-efficient implementation using the rare-variant collapsing test for phenotypic association, the genomic exhaustive collapsing scan (GECS). Our implementation allows for the identification of regions comprising the strongest signals in large, genome-wide rare-variant association studies while controlling the family-wise error rate via permutation. Application of GECS to two genomic data sets revealed several novel significantly associated regions for age-related macular degeneration and for schizophrenia. Our approach also offers a high potential for genome-wide scans for selection, methylation and other analyses.

genetics↗

bioRxiv2018

Regeneration of dopaminergic neurons in adult zebrafish depends on immune system activation and differs for distinct populations

Adult zebrafish regenerate neurons in their brain, but the extent and variability of this capacity is unclear. Here we ask whether loss of various dopaminergic neuron populations is sufficient to trigger their functional regeneration. Genetic lineage tracing shows that specific diencephalic ependymo-radial glial progenitor cells (ERGs) give rise to new dopaminergic (Th+) neurons. Ablation elicits an immune response, increased proliferation of ERGs and increased addition of new Th+ neurons in populations that constitutively add new neurons, e.g. diencephalic population 5/6. Inhibiting the immune response attenuates neurogenesis to control levels. Boosting the immune response enhances ERG proliferation, but not addition of Th+ neurons. In contrast, in populations in which constitutive neurogenesis is undetectable, e.g. the posterior tuberculum and locus coeruleus, cell replacement and tissue integration are incomplete and transient. This is associated with loss of spinal Th+ axons, as well as permanent deficits in shoaling and reproductive behaviour. Hence, dopaminergic neuron populations in the adult zebrafish brain show vast differences in regenerative capacity that correlate with constitutive addition of neurons and depend on immune system activation.

neuroscience↗

bioRxiv2018

Evaluation of Deep Learning Strategies for Nucleus Segmentation in Fluorescence Images

Identifying nuclei is often a critical first step in analyzing microscopy images of cells, and classical image processing algorithms are most commonly used for this task. Recent developments in deep learning can yield superior accuracy, but typical evaluation metrics for nucleus segmentation do not satisfactorily capture error modes that are relevant in cellular images. Besides, large image data sets with ground truth for evaluation have been limiting. We present an evaluation framework to measure accuracy, types of errors, and computational efficiency; and use it to compare two deep learning strategies (U-Net and DeepCell) alongside a classical approach implemented in CellProfiler. We publicly release a set of 23,165 manually annotated nuclei and source code to reproduce experiments. Our results show that U-Net outperforms both pixel-wise classification networks and classical algorithms. Also, our evaluation framework shows that deep learning improves accuracy and reduces the number of biologically relevant errors by half.

bioinformatics↗