Biology subjects

Sinn, L. R.

Publications and source records attributed to Sinn, L. R..

13 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↗

bioRxiv2026

A draft atlas of the human plasma proteome at isoform resolution

Key plasma protein, including albumin, complement system proteins, and coagulation factors circulate in biochemically and functionally distinct isoforms, or proteoforms. Despite the importance of these proteoforms being widely accepted, they are challenging to resolve systematically, and as a consequence, we still lack a more complete picture of the total proteoform diversity of the human plasma proteome. Here, we generated 3,114 intact protein fractions by extensively separating plasma according to isoelectric point and molecular weight. We then analysed these fractions by liquid chromatography data-independent acquisition mass spectrometry (DIA-MS) upon tryptic digestions, and combined the resultant data into a multidimensional, proteoform resolved atlas of the human plasma proteome. We report that 5,077 unequivocally detected plasma proteins circulate at least 179,049 distinct proteoforms, of which we detect 44,083, with a median of 11 proteoforms per protein, at high confidence. Substantially increasing the number of experimentally confirmed proteoforms, our atlas implies that the canonical protein forms account for less than half of the total protein mass in plasma. We detect the greatest proteoform diversity among the most abundant plasma proteins and those functioning in nutrient transport, complement and coagulation. Finally, our data clarifies discrepancies between the Olink and SomaScan proteomic platforms, as according to our atlas, these techniques provide correlated values for relatively abundant proteins with low to medium proteoform diversity, but struggle in the quantification of low-abundant proteins and on those which exist in many proteoforms. In sum, our data reveals extensive proteoform diversity of the human plasma proteome, and implies that proteoform diversity represents an enormous untapped reservoir for biomedical research and biomarker discovery.

biochemistry↗

bioRxiv2026

SILAC-Site: A streamlined workflow for determining phosphopeptide stoichiometries

Mass spectrometry-based proteomics enables in-depth investigation of protein phosphorylation, quantifying tens of thousands of phosphosites per sample following phosphopeptide enrichment. However, critical information on phosphosite occupancy (stoichiometry) is typically lost during the phospho-enrichment process. Here, we introduce SILAC-Site, a SILAC-based fractionation-free and chemical labelling-free workflow for direct phosphosite stoichiometry evaluation using stable isotope labeling and phosphatase treatment. By acquiring treated or untreated peptides together with their heavy-labelled dephosphorylated counterparts within the same LC-MS runs, this approach provides internally controlled stoichiometry estimates compatible with high-throughput data-independent acquisition proteomics. Applying SILAC-Site to S. cerevisiae, we show that the majority of phosphopeptides identified only after enrichment possess low stoichiometries, and that inferred stoichiometry strongly correlates with the direct detection of phosphopeptides in samples without enrichment. Based on these findings, we propose the analysis of samples without enrichment as a simple complementary addition to a typical phosphoproteomics workflow, facilitating recovery of phosphorylation stoichiometry information.

biochemistry↗

bioRxiv2025

Large-scale quantitative benchmark reveals accuracy limits of proteomics

Quantitative proteomics has become a streamlined method for high-throughput interrogation of biological samples, with a wide range of applications in both basic and clinical research. We present a benchmark data set and methodology for evaluating the accuracy of proteomics in a high-throughput setting. We build upon previous works by incorporating the variation of sample amounts and the background proteome into the experiment design. This approach allows us to comprehensively map the factors that determine the accuracy of proteomic measurements, revealing significant systematic errors missed by previous works. We envision these data to assist in future method optimisation as well as provide a comprehensive benchmark for data analysis software algorithms.

biochemistry↗

bioRxiv2025

Tolerance to the antifungal drug fluconazole is mediated by tuning cytoplasmic fluidity

Treatment failure rates for fungal infections cannot be explained simply by increased rates of drug resistance. Antifungal drug tolerance, the ability of a susceptible isolate to grow in the presence of inhibitory drug concentrations, relies upon a broad set of stress response pathways and can contribute to antifungal drug treatment failures. As the physical properties of the cytoplasm are critical for diverse cellular processes, we investigated whether cytoplasmic mesoscale fluidity is linked to antifungal tolerance, taking advantage of a fluorescent microrheological probe. Here, we show either using fluconazole, a common drug that inhibits ergosterol biosynthesis, or mutants in the ergosterol biosynthesis pathway, that cytoplasmic fluidity decreased and could be reversed upon drug removal. Reducing ribosome concentration decreased drug tolerance and restored cytoplasmic fluidity, highlighting a link between tolerance and cytoplasmic crowding and/or viscosity. However, growth in fluconazole did not increase ribosome concentrations; rather growth in fluconazole increased the number of dormant, hibernating ribosomes, cytoplasmic protein concentration, viscosity and condensate formation. Specifically, growth in fluconazole resulted in a substantial increase in processing bodies (P-bodies), whose presence correlated with azole tolerance. Furthermore, we found a substantial increase in cell-cell heterogeneity in all biophysical, biochemical and molecular outputs analyzed. Together, our results reveal that changes in the physical properties of the cytoplasm occur in response to antifungal drug and suggest that these changes, as well as increased cell-cell heterogeneity, are crucial for survival in fungistatic drugs.

microbiology↗

bioRxiv2025

Pho-Tip: one-pot dephosphorylation for rapid and sensitive analysis of DIA phosphoproteomics data

Recent advances in instrumentation and data processing have transformed data-independent acquisition (DIA) proteomics into a reliable technology for quantitative profiling of post-translational modifications. However, analysis of DIA phosphoproteomics data is challenging due to the large search space, wherein all combinations of phosphosites on a peptide need to be considered. Current approaches therefore face significant hurdles in detecting low-abundant phosphorylated peptides, in particular when working with low sample amounts. Here we introduce Pho-Tip, a lossless one-pot dephosphorylation strategy. We show that Pho-Tip enables comprehensive mapping of phosphorylated peptide sequences, facilitating streamlined creation of experiment-focused in silico predicted spectral libraries and thus rapid and sensitive analysis of DIA phosphoproteomics experiments.

biochemistry↗

bioRxiv2025

Performance Characteristics of Zeno Trap Scanning DIA for Sensitive and Quantitative Proteomics at High Throughput

Proteomic experiments, particularly those addressing dynamic proteome properties, time series, or genetic diversity, require the analysis of large sample numbers. Despite significant advancements in proteomic technologies in recent years, further improvements are needed to accelerate measurement and enhance proteome coverage and quantitative performance. Previously, we demonstrated that incorporating a scanning MS2 dimension into data-independent acquisition methods (Scanning SWATH, or more generally scanning DIA) but also ion trapping, improves analytical depth and quantitative performance, especially in proteomic methods using fast chromatography. Here, we evaluate the scanning DIA approach combined with ion trapping via the Zeno trap in a method termed ZT Scan DIA, using a prototype Zeno trap Q-TOF instrument (SCIEX). Applying this method to established proteome standards across various analytical setups, enabling intermediate to high sample throughput, we observed a 30-40% increase in identified precursors. This enhancement extended to overall protein identification and precise quantification. Furthermore, ZT Scan DIA effectively eliminated quantitative bias, as demonstrated by its ability to deconvolute proteomes in multi-species mixtures. We propose that ZT Scan DIA can be used for a broad range of applications in proteomics, particularly in studies requiring high quantitative precision with low sample input and high-throughput workflows. Significance StatementThe advent of faster DIA proteomics methods paved the way for investigating increasingly large sample series, including patient cohorts and strain collections containing thousands of samples. Yet, recent improvements in DIA methods still entailed compromises between analytical sensitivity and selectivity. The presented combination of a scanning quadrupole with fast ion trapping in a Zeno Trap, coined ZT Scan DIA increases quantitative precision and accuracy in fast proteomics experiments. These features of ZT Scan DIA may benefit applications that deal with low input samples and high-throughput proteomic workflows in biomedical cohort studies and systems biology.

systems biology↗

bioRxiv2024

Dynamic cytoplasmic fluidity during morphogenesis in a human fungal pathogen

The molecular crowding of the cytoplasm impacts a range of cellular processes. Using a fluorescent microrheological probe (GEMs), we observed a striking decrease in molecular crowding during the yeast to filamentous growth transition in the human fungal pathogen Candida albicans. This decrease in crowding is due to a decrease in ribosome concentration that results in part from an inhibition of ribosome biogenesis, combined with an increase in cytoplasmic volume; leading to a dilution of the major cytoplasmic crowder. Moreover, our results suggest that inhibition of ribosome biogenesis is a trigger for C. albicans morphogenesis.

cell biology↗

bioRxiv2024

Molecular insights into dynamic protein structures by high-contrast crosslinking mass spectrometry

Proteins are comprised of structured domains and dynamic regions, and both are essential for biological function. However, studying dynamic regions is challenging using most structural biology methods, including crosslinking mass spectrometry. Here, we dramatically improve the usefulness of distance restraints from crosslinking MS by taking advantage of short-lived reactive species generated from diazirine-based photo-crosslinking. This leads to a clear view of complex topologies and conformational changes, including in dynamic regions. We demonstrate that photo-crosslinking MS data can be used to model flexible regions and conformational changes in the DNA repair complexes; Fanconi Anemia core complex and FANCD2-FANCI. In addition, we obtain new insights into the architecture and arrangement of the highly flexible CCR4-NOT mRNA deadenylation complex. The improved contrast of photo-crosslinking empowers structural biology by providing clearer structural insights into dynamic biological systems that have eluded other structural biology approaches.

molecular biology↗

bioRxiv2023

QuantUMS: uncertainty minimisation enables confident quantification in proteomics

Mass spectrometry-based proteomics has been rapidly gaining traction as a powerful analytical method both in basic research and translation. While the problem of error control in peptide and protein identification has been addressed extensively, the quality of the resulting quantities remains challenging to evaluate. Here we introduce QuantUMS (Quantification using an Uncertainty Minimising Solution), a machine learning-based method which minimises errors and eliminates bias in peptide and protein quantification by integrating multiple sources of quantitative information. In combination with data-independent acquisition proteomics, QuantUMS boosts accuracy and precision of quantities, as well as reports an uncertainty metric, enabling effective filtering of data for downstream analysis. The algorithm has linear complexity with respect to the number of mass spectrometry acquisitions in the experiment and is thus scalable to infinitely large proteomic experiments. For an easy implementation in a proteomics laboratory, we integrate QuantUMS in our automated DIA-NN software suite.

bioinformatics↗

bioRxiv2021

Improved peptide backbone fragmentation is the primary advantage of MS-cleavable crosslinkers

Proteome-wide crosslinking mass spectrometry studies have coincided with the advent of MS-cleavable crosslinkers that can reveal the individual masses of the two crosslinked peptides. However, recently such studies have also been published with non-cleavable crosslinkers suggesting that MS-cleavability is not essential. We therefore examined in detail the advantages and disadvantages of using the most popular MS-cleavable crosslinker, DSSO. Indeed, DSSO gave rise to signature peptide fragments with a distinct mass difference (doublet) for nearly all identified crosslinked peptides. Surprisingly, we could show that it was not these peptide masses that proved the main advantage of MS-cleavability of the crosslinker, but improved peptide backbone fragmentation that allowed for more confident peptide identification. We also show that the more intricate MS3-based data acquisition approaches lack sensitivity and specificity, causing them to be outperformed by the simpler and faster stepped HCD method. This understanding will guide future developments and applications of proteome-wide crosslinking mass spectrometry.

systems biology↗

bioRxiv2021

Retention Time Prediction Using Neural Networks Increases Identifications in Crosslinking Mass Spectrometry

Crosslinking mass spectrometry (Crosslinking MS) has developed into a robust technique that is increasingly used to investigate the interactomes of organelles and cells. However, the incomplete and noisy information in the spectra limits the numbers of protein-protein interactions (PPIs) that can be confidently identified. Here, we successfully leveraged chromatographic retention time (RT) information to aid the identification of crosslinked peptides from spectra. Our Siamese machine learning model xiRT achieved highly accurate RT predictions of crosslinked peptides in a multi-dimensional separation of crosslinked E. coli lysate. We combined strong cation exchange (SCX), hydrophilic strong anion exchange (hSAX) and reversed-phase (RP) chromatography and reached R2 0.94 in RP and a margin of error of 1 fraction for hSAX in 94%, and SCX in 85% of the predictions. Importantly, supplementing the search engine score with retention time features led to a 1.4-fold increase in PPIs at a 1% false discovery rate. We also demonstrate the value of this approach for the more routine analysis of a crosslinked multiprotein complexes. An increase of 1.7-fold in heteromeric crosslinked residue-pairs was achieved at 1% residue-pair FDR for Fanconi anaemia monoubiquitin ligase complex, solely using reversed-phase RT. Retention times are a powerful complement to mass spectrometric information to increase the sensitivity of Crosslinking MS analyses.

bioinformatics↗

bioRxiv2020

Reliable identification of protein-protein interactions by crosslinking mass spectrometry

Crosslinking mass spectrometry is widening its scope from structural analyzes of purified multi-protein complexes towards systems-wide analyzes of protein-protein interactions. Assessing the error in these large datasets is currently a challenge. Using a controlled large-scale analysis of Escherichia coli cell lysate, we demonstrate a reliable false-discovery rate estimation procedure for protein-protein interactions identified by crosslinking mass spectrometry.

systems biology↗