Biology subjects

Muelleder, M.

Publications and source records attributed to Muelleder, M..

16 recordsLinked to original sources

bioRxiv2026

Reverse engineering Lewy bodies suggests alpha-synuclein pathology as condensatopathy

Understanding how soluble monomeric alpha-synuclein transitions into pathological alpha-synuclein (Lewy bodies) has remained a central challenge in neurodegeneration. Existing models, largely based on treating cells and animals with pre-formed alpha-synuclein fibrils cannot account for the emergence of the first inclusion without pre-existing seeds. Here, we combine in vitro reconstitutions, computational modeling and a minimal cellular system to show that phase separation of alpha-synuclein with an interacting scaffold can recapitulate Lewy body-like structures. An unbiased proteomics screen, live-cell imaging, correlative light-electron microscopy, and soft X-ray tomography show that Lewy body-like structures are associated with redistribution of actin and membrane-bound organelles, with mitochondria accumulating at their periphery in an actin-dependent manner. Structural analyses further indicate that alpha-synuclein condensates provide local environments in which the insoluble beta-sheets can form. Together, these findings support a seed-independent trajectory from soluble alpha-synuclein through condensation and progressive immobilization to Lewy body-like assemblies and, subsequently, insoluble beta-sheet fibrils. This framework offers a new mechanistic route for understanding the disease progression and promises to guide the design of innovative therapeutic interventions.

neuroscience↗

bioRxiv2025

Liver Viscosity Decreases Before the Onset of Fibrosis in Metabolic Dysfunction-Associated 1 Steatohepatitis (MASH)

Background and AimMetabolic dysfunction-associated steatohepatitis (MASH) is an increasingly prevalent condition worldwide, associated with biomechanical liver changes and detectable by magnetic resonance elastography (MRE). This study explored the pathophysiological features and their biomechanical manifestations at different stages of MASH in a mouse dietary model. MethodsUsing MRE on a clinical 3 Tesla MRI scanner, we measured liver stiffness, viscosity, fat fraction and water diffusion in 45 male mice. These values were correlated with histopathology and proteomics analyses to further characterize the liver microstructural and metabolic changes during MASH progression. ResultsWe found in a high-fat, low amino-acid model that early MASH was marked by fat accumulation and increasing inflammatory activity, while later stages showed a reduction in fat despite persistent inflammation. These changes in microstructure were associated with biomechanical adaptations, including a progressive decrease in hepatic viscosity and the water diffusion. Notably, viscosity was inversely correlated with lobular inflammation, cell adhesion, antioxidant activity, and metabolic adaptations such as enhanced ketone body synthesis. These findings, which precede the onset of fibrosis and tissue stiffening, show that tissue viscosity is highly sensitive to early microstructural and metabolic alterations in MASH. ConclusionSteatosis and inflammation significantly alter liver biophysical properties, particularly viscosity, in a mouse dietary model of MASH, even in the absence of fibrosis. These findings suggest that viscosity is a potential early and clinically translatable biomarker for the development and progression of MASH.

biophysics↗

bioRxiv2025

Interspecies interactions drive bacterial proteome reorganisation and emergent metabolism

Species in microbial communities must respond to the presence of others to stave off resource competition or to capitalise on new resources that may become available due to additional metabolic activities. Such metabolic interactions manifest in growth effects such as competitive exclusion or cooperative growth boost. However, intra-cellular molecular changes that underpin these responses are very sparsely studied, preventing mechanistic insights into community function and dynamics. Here, we analyse meta-proteomics and metabolomic responses in 104 pairwise co-cultures of 15 diverse gut bacteria in a nutrient-rich medium. These co-cultures span a diversity of ecological interactions with competition, amensalism and exploitation being prominent, and with around one in five positive interactions. The species in co-cultures feature substantial molecular responses, with typically more than 60% of the proteome changing in response to at least one partner. Even closely related species and ortholog proteins show different expression profiles in response to the same partner indicating functional diversification at both protein and species level. We show that the magnitude of these responses is determined by genome size, species abundance, and pH. Small-molecule transport and carbon metabolism are among the most responsive processes indicating pervasive metabolic interactions. Using metabolomics, we identify likely cross-fed metabolites, emergent polyamine metabolism, and niche partitioning in amino acid utilisation. Overall, our study shows how bacteria respond to the presence of other species through extensive remodelling of their proteome and metabolome.

microbiology↗

bioRxiv2024

A genome-to-proteome atlas charts natural variants controlling proteome diversity and forecasts their fitness effects

Despite abundant genomic and phenotypic data across individuals and environments, the functional impact of most mutations on phenotype remains unclear. Here, we bridge this gap by linking genome to proteome in 800 meiotic progeny from an intercross between two closely related Saccharomyces cerevisiae isolates adapted to distinct niches. Modest genetic distance between the parents generated remarkable proteomic diversity that was amplified in the progeny and captured by 6,476 genotype-protein associations, over 1,600 of which we resolved to single variants. Proteomic adaptation emerged through the combined action of numerous cis- and trans-regulatory mutations, a regulatory architecture that was conserved across the species. Notably, trans-regulatory variants often arose in proteins not traditionally associated with gene regulation, such as enzymes. Moreover, the proteomic consequences of mutations predicted fitness under various stresses. Our study demonstrates that the collective action of natural genetic variants drives dramatic proteome diversification, with molecular consequences that forecast phenotypic outcomes. Highlights- Proteome diversity arises from natural genetic variants, with divergent proteomes in closely related parents and progeny. - Cis-regulatory elements had strong individual impacts, but coherent trans effects combined to dominate protein expression. - Directional selection and frequent transgression suggest much of the proteome is under selective pressure. - Many trans-regulators are enzymes or transporters, with fewer than 4% of pQTLs linking known interactors. - Genome-to-proteome connections predicted the fitness impact of mutations under various stresses, including a strong but hidden causal variant in IRA2/NF1.

systems biology↗

bioRxiv2024

An INS-1 beta-cell proteome highlights the role of fatty acid biosynthesis in glucose-stimulated insulin secretion

Pancreatic beta cells secrete insulin as a response to rising glucose level, a process known as glucose-stimulated insulin secretion (GSIS). In this study, we used liquid chromatography tandem mass spectrometry and data-independent acquisition to acquire proteomes of rat pancreatic INS-1 832/13 beta cells that were short-term stimulated with glucose concentrations ranging from 0 to 20 mM, quantifying the behavior of 3703 proteins across 11 concentrations. Ensemble clustering of proteome profiles revealed unique response patterns of proteins expressed by INS-1 cells. 237 proteins, amongst them proteins associated with vesicular SNARE interactions, protein export, and pancreatic secretion showed an increase in abundance upon glucose stimulation, whilst the majority of proteins, including those associated with metabolic pathways such as glycolysis, the TCA cycle and the respiratory chain, did not respond to rising glucose concentrations. Interestingly, we observe that enzymes participating in fatty acid metabolism, responded distinctly, showing a "switch-on" response upon release of glucose starvation with no further changes in abundance upon increasing glucose levels. We speculate that increased activity of fatty acid metabolic activity might either be part of GSIS by replenishing membrane lipids required for vesicle-mediated exocytosis and/or by providing an electron sink to compensate for the increase in glucose catabolism. Significance of the StudyWe used high-throughput proteomics to capture comprehensive proteome changes 30 minutes post stimulation in the INS-1 832/13 beta cell line. Our study provides insights into the metabolic regulation of glucose-stimulated insulin secretion in pancreatic beta cells, specifically highlighting the early role of fatty acid biosynthesis. These findings suggest a necessary shift in focus from electrochemical to metabolic mechanisms in understanding GSIS, paving the way for future research. As the first to document proteome alterations in the initial phase of GSIS, our study furthermore documents the extent of protein abundance variability when obtaining data after short stimulation times, and therefore highlights the necessity of well-controlled study design and biological replicates. The recorded data set complements existing metabolomic and transcriptomic studies, providing a valuable resource for subsequent investigations.

cell biology↗

bioRxiv2024

The Molecular Landscape of Cellular Metal Ion Biology

Metal ions play crucial roles in cells, yet the broader impact of metal availability on biological networks remains underexplored. We generated genome-wide resources, systematically quantifying yeast cell growth, metallomic, proteomic, and genetic responses upon varying each of its essential metal ions (Ca, Cu, Fe, K, Mg, Mn, Mo, Na, Zn), over several orders of magnitude. We find that metal ions deeply impact cellular networks, with 57.6% of the proteome, including most signalling pathways, responding. While the biological response to each metal is distinct, our data reveals common properties of metal responsiveness, such as concentration interdependencies and metal homeostasis. We describe a compendium of metal-dependent cellular processes and reveal that several understudied genes can be functionally annotated based on their metal responses. Furthermore, we report that metalloenzymes occupy central nodes in the metabolic network and are more likely to be encoded by isozymes, resulting in system-wide responsiveness to metal availability.

systems biology↗

bioRxiv2023

Myeloperoxidase-dependent tyrosine halogenation potentiates alpha-defensins functions

Neutrophils are immune cells that eliminate microbes using a powerful arsenal of reactive oxygen species, hypohalous acids, proteases, and antimicrobial peptides -- yet how these cytotoxic effectors act in concert remains poorly understood. Here, we identify an unrecognized synergy between oxidative and non-oxidative neutrophil defenses. We show that myeloperoxidase-derived hypohalous acids selectively halogenate -defensins (HNP1-3) at conserved tyrosine residues. This post-translational modification occurs in both human and rat neutrophils and is prominent in diseases marked by neutrophil-rich inflammation, including cystic fibrosis, bacterial pneumonia, and Staphylococcus aureus abscesses. Halogenation increases HNP1 hydrophobicity without altering its structure, reprogramming these peptides into potent immunomodulatory mediators. Using single-cell transcriptomics and a in vivo peritonitis model, we demonstrate that halogenated HNP1s amplify immune signaling. Our analysis of the human haloproteome reveals a novel oxidative mechanism by which hypohalous acids rewire immune protein functions, uncovering an unexpected layer of cooperation between neutrophil effector systems. The discovery of halogenated HNP1s represents, to our knowledge, the first characterization of a protein halogenation that has biologically significance in human immunity.

biochemistry↗

bioRxiv2023

The amino acid sequence determines protein abundance through its conformational stability and reduced synthesis cost.

Understanding what drives protein abundance is essential to biology, medicine, and biotechnology. Driven by evolutionary selection, the amino acid sequence is tailored to meet the required abundance of proteomes, underscoring the intricate relationship between sequence and functional demand. Yet, the specific role of amino acid sequences in determining proteome abundance remains elusive. Here, we demonstrate that the amino acid sequence predicts abundance by shaping a proteins conformational stability. We show that increasing the abundance provides metabolic cost benefits, underscoring the evolutionary advantage of maintaining a highly abundant and stable proteome. Specifically, using a deep learning model (BERT), we predict 56% of protein abundance variation in Saccharomyces cerevisiae solely based on amino acid sequence. The model reveals latent factors linking sequence features to protein stability. To probe these relationships, we introduce MGEM (Mutation Guided by an Embedded Manifold), a methodology for guiding protein abundance through sequence modifications. We find that mutations increasing abundance significantly alter protein polarity and hydrophobicity, underscoring a connection between protein stability and abundance. Through molecular dynamics simulations and in vivo experiments in yeast, we confirm that abundance-enhancing mutations result in longer-lasting and more stable protein expression. Importantly, these sequence changes also reduce metabolic costs of protein synthesis, elucidating the evolutionary advantage of cost-effective, high-abundance, stable proteomes. Our findings support the role of amino acid sequence as a pivotal determinant of protein abundance and stability, revealing an evolutionary optimization for metabolic efficiency.

evolutionary biology↗

bioRxiv2023

Speedy-PASEF: Analytical flow rate chromatography and trapped ion mobility for deep high-throughput proteomics

Increased throughput in proteomic experiments can improve accessibility of proteomic platforms, reduce costs and facilitate new approaches in systems biology and biomedical research. Here we propose Speedy-PASEF, a combination of analytical flow rate chromatography with ion mobility separation of peptide ions, data-independent acquisition and data analysis with the DIA-NN software suite, for conducting fast, high-quality proteomic experiments that require only moderate sample amounts. For instance, using a 500-l/min flow rate and a 3-minute chromatographic gradient, Speedy-PASEF quantified 5,211 proteins from 2 g of a mammalian cell-line standard at high quantitative accuracy and precision. We further used Speedy-PASEF to analyze blood plasma samples from a cohort of COVID-19 inpatients, using a 3-minute chromatographic gradient and alternating column regeneration on a dual pump system, for processing 398 samples per day. Speedy-PASEF delivered a comprehensive view of the COVID-19 plasma proteome, allowing classification of the patients according to disease severity and revealing plasma biomarker candidates. Speedy-PASEF thus facilitates acquisition of high-quality proteomes in large numbers.

biochemistry↗

bioRxiv2023

Sema7A and Sema4D Heterodimerization is Essential for Membrane Targeting and Neocortical Wiring

Disruption of neocortical circuitry and architecture in humans causes numerous neurodevelopmental disorders. Neocortical cytoarchitecture is orchestrated by various transcription factors such as Satb2 that control target genes during strict time windows. In humans, mutations of SATB2 cause SATB2 Associated Syndrome (SAS), a multisymptomatic syndrome involving intellectual disability, speech delay, epilepsy and craniofacial defects. We show that Satb2 controls neuronal migration and axonal outgrowth by inducing the expression of the GPI-anchored protein, Sema7A. We find that heterodimerization with Sema4D increases targeting of Sema4D to the membrane and is required for Sema7A function. Finally, we report that membrane localization and pos- translational modification of the Sema7A-Sema4D complex is disrupted by a novel de novo mutation in Sema4D (Q497P) that is associated with epilepsy in humans. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=197 HEIGHT=200 SRC="FIGDIR/small/527998v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@db698org.highwire.dtl.DTLVardef@4ee980org.highwire.dtl.DTLVardef@c3d9d6org.highwire.dtl.DTLVardef@12a135_HPS_FORMAT_FIGEXP M_FIG C_FIG HIGHLIGHTSO_LISema7A is a direct Satb2 target that drives neuronal migration and axon outgrowth C_LIO_LISema7A exerts its effect by heterodimerizing with Sema4D at neurites and growth cones C_LIO_LISema7A increases cell surface localization of Sema4D C_LIO_LIDe novo human Sema4D-Q497P mutation causes epilepsy, inhibits post-translational processing & surface localization C_LI eTOCSema7A is a direct target of the transcription factor Satb2. Sema7A promotes normal migration and axon outgrowth in cortical neurons by modulating reverse signaling via Sema4D. These processes are dependent on Sema7A-Sema4D heterodimerization and membrane localization; insufficient transcription of Sema7A or incomplete glycosylation of Sema4D inhibit this progression.

neuroscience↗

bioRxiv2022

High-throughput proteomics of nanogram-scale samples with Zeno SWATH DIA

The ability to conduct high-quality proteomic experiments in high throughput has opened new avenues in clinical research, drug discovery, and systems biology. Next to an increase in quantitative precision, recent developments in high-throughput proteomics have also gained proteomic depth, to the extent that earlier gaps between classic and high-throughput experiments have significantly narrowed. Here we introduce and benchmark Zeno SWATH, a data-independent acquisition technique that employs a linear ion trap pulsing (Zeno trap pulsing) in order to increase proteomic depth and dynamic range in proteomic experiments. Combined with the high acquisition speed, these gains in sensitivity are particularly attractive for conducting high-throughput proteomics experiments with high chromatographic flow rates and fast gradients. We demonstrate that when combined with either micro-flow- or analytical-flow-rate chromatography, Zeno SWATH increases protein identification in complex samples 5- to 10-fold when compared to current SWATH acquisition methods on the same instrument. Using 20-min micro-flow chromatography, Zeno SWATH identified > 6,000 proteins from a 62.5 ng load of human cell lysate with more than 5,000 proteins consistently quantified in triplicate injections with a median CV of 6%. Using 5-min analytical-flow-rate chromatography (800 {micro}l/min), Zeno SWATH identified 4,907 proteins from a triplicate injection of 2 {micro}g of a human cell lysate; or more than 3,000 proteins from 250 ng tryptic digest. Zeno SWATH hence facilitates precise proteomic experiments with small sample amounts using a fast and robust high flow-rate chromatographic method, broadening the application space that requires precise proteomic experiments on a large scale.

biochemistry↗

bioRxiv2022

The natural diversity of the yeast proteome reveals chromosome-wide dosage compensation in aneuploids

Aneuploidy, an imbalance in chromosome copy numbers, causes genetic disorders, and drives cancer progression, drug tolerance, and antimicrobial resistance. While aneuploidy can confer stress resistance, it is not well understood how cells overcome the fitness burden caused by aberrant chromosomal copy numbers. Studies using both systematically generated 1-5 and natural aneuploid yeasts 6-8 triggered an intense debate about the role of dosage compensation, concluding that aneuploidy is transmitted to the transcriptome and proteome without significant buffering at the chromosome-wide level, and is, at least in lab strains, associated with significant fitness costs. Conversely, systematic sequencing and phenotyping of large collections of natural isolates revealed that aneuploidy is frequent and has few - if any - fitness costs in nature 9. To address these discrepant findings at the proteomic level, we developed a platform that yields highly precise proteomic measurements across large numbers of genetically diverse samples, and applied it to natural isolates collected as part of the 1011 genomes project 9. For 613 of the isolates, we were able to match the proteomes to their corresponding transcriptomes and genomes, subsequently quantifying the effect of aneuploidy on gene expression by comparing 95 aneuploid with 518 euploid strains. We find, as in previous studies, that aneuploid gene dosage is not buffered chromosome-wide at the transcriptome level. Importantly, in the proteome, we detect an attenuation of aneuploidy by about 25% below the aneuploid gene dosage in natural yeast isolates. Furthermore, this chromosome-wide dosage compensation is associated with the ubiquitin-proteasome system (UPS), which is expressed at higher levels and has increased activity across natural aneuploid strains. Thus, through systematic exploration of the species-wide diversity of the yeast proteome, we shed light on a long-standing debate about the biology of aneuploids, revealing that aneuploidy tolerance is mediated through chromosome-wide dosage compensation at the proteome level.

systems biology↗

bioRxiv2022

Occurrence and quantities of DNA modifications across the tree of life

Enzymatic DNA modifications like methylcytosine (5mdC), methyladenine (N6mdA), or hydroxymethylcytosine (5hmdC) are key for chromatin function, gene expression regulation, and antiviral defense, but they remain understudied in non-model organisms. We established a mass spectrometric method for the sensitive and accurate quantification of enzymatic DNA modifications, and analyzed 85 bacterial genomes, 19 plant samples, 41 tissues from 12 animal species, 6 yeast species, and two archaeal species. We report no or only very low concentrations of DNA modifications in yeast and insects, but find DNA modifications universal to both bacteria and higher eukaryotes. Specifically for prokaryotes, our dataset indicates that evolutionary relationships and host-pathogen interactions, but not the ecological niche in general, select for a similar degree of DNA modification. In higher eukaryotes, largest concentration differences between tissues are detected for 5hmdC. Our dataset further reveals unique biological cases that warrant attention in the study of DNA modifications. For instance, while our data shows that most species contain just one dominating DNA modification, we detect all dominianting DNA modifications (5mdC, N6mdA, and 5hmdC) to exist in parallel in Raphanus sativus. Other plant species, like onion, sunflower, or the grass big bluestem, can have more than 35% of cytosines methylated. Finally, 5hmdC, so far mostly studied in the vertebrate central nervous system, was identified to reach a concentration of up to 8% of all cytosines in the Oman garra brain, and was also detected in several plants, like Lepidium sativum. The present study underscores the exploitation of biological diversity for studying DNA modifications.

genomics↗

bioRxiv2022

Cell-cell metabolite exchange creates a pro-survival metabolic environment that extends lifespan

Metabolism is fundamentally intertwined with the ageing process. We here report that a key determinant of cellular lifespan is not only nutrient supply and intracellular metabolism, but also metabolite exchange interactions that occur between cells. Studying chronological ageing in yeast, we observed that metabolites exported by young, exponentially growing, cells are re- imported during the stationary phase when cells age chronologically, indicating the existence of cross-generational metabolic interactions. We then used self-establishing metabolically cooperating communities (SeMeCos) to boost cell-cell metabolic interactions and observed a significant lifespan extension. A search for the underlying mechanisms, coupling SeMeCos, metabolic profiling, proteomics and genome-scale metabolic modelling, attributed a specific role to methionine consumer cells. These cells were enriched over time, adopted glycolytic metabolism and increased export of protective metabolites. Glycerol, in particular, accumulated in the communal metabolic environment and extended the lifespan of all cells in the community in a paracrine fashion. Our results hence establish metabolite exchange interactions as a determinant of the ageing process and show that metabolically cooperating cells shape their metabolic environment to achieve lifespan extension.

biochemistry↗

bioRxiv2021

High sensitivity dia-PASEF proteomics with DIA-NN and FragPipe

The dia-PASEF technology exploits ion mobility separation for high-sensitivity analysis of complex proteomes. Here, we demonstrate neural network-based processing of the ion mobility data, which we implement in the DIA-NN software suite. Using spectral libraries generated with the MSFragger-based FragPipe computational platform, the DIA-NN analysis of dia-PASEF raw data increases the proteomic depth by up to 69% compared to the originally published dia-PASEF workflow. For example, we quantify over 5200 proteins from 10ng of HeLa peptides separated with a 95-minute nanoflow gradient, and over 5000 proteins from 200ng using a 4.8-minute separation with an Evosep One system. In complex samples, featuring a mix of human and yeast lysates, the workflow detects over 11700 proteins in single runs acquired with a 100-minute nanoflow gradient, while demonstrating quantitative precision. Hence, the combination of FragPipe and DIA-NN provides a simple-to-use software platform for dia-PASEF data analysis, yielding significant gains in high-sensitivity proteomics.

bioinformatics↗

bioRxiv2019

A multi-omic analysis of optineurin proteinopathy in a yeast model suggests the involvement of lipid metabolism in Amyotrophic Lateral Sclerosis

Amyotrophic Lateral Sclerosis (ALS) is an incurable fatal neurodegenerative disease for which the precise mechanisms of toxicity remain unclear despite some significant advances in our understanding of the underlying genetic basis. A holistic, integrated view of cellular changes will be critical to understanding the processes of neurodegeneration and the development of effective treatments. Mutant forms of optineurin (a ubiquitin-binding protein involved in autophagy, membrane trafficking, and NF-{kappa}B activation) are found associated with cytoplasmic inclusions containing TDP43 or SOD1 in some ALS patients. We have taken a multi-omics approach to understand the cellular response to OPTN overexpression in a yeast model of ALS. We found that genetic interaction screens and metabolomics provided parallel, highly complementary data on OPTN toxicity. Genetic enhancers of OPTN toxicity in yeast relate directly to the native function of OPTN in vesicular trafficking and intracellular transport, suggesting the human OPTN protein is functional when expressed in yeast even though there is no yeast ortholog. Crucially, we find that the genetic modifiers and the metabolic response are distinct for different ALS-linked genes expressed in yeast. This lends strong support to the use of yeast as a model system and omics platform to study ALS.

systems biology↗