Biology subjects

Hornburg, D.

Publications and source records attributed to Hornburg, D..

14 recordsLinked to original sources

bioRxiv2026

Expanded Proteome Coverage Powered by Advanced Ion Processing Enables Deep Single-Cell Drug Response Subtyping in Human Stem Cell Derived Cardiomyocytes

Single-cell proteomics (SCP) enables the study of cellular heterogeneity at the functional level but remains limited by incomplete proteome coverage and high data missingness. Here, we present an enhanced label-free SCP workflow that leverages the timsUltra AIP mass spectrometry platform equipped with the Athena Ion Processor (AIP). Across a controlled dilution series of human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs), AIP-enabled acquisition consistently increased proteome depth and detection consistency across cells at all input levels. In single iPSC-CMs, the timsUltra AIP quantified up to 3,858 protein groups, averaging [~]1,300 proteins per cell, enabling robust proteome-level classification of cardiomyocyte subtypes. Using a reference-based protein classifier, cells were stratified into mature cardiomyocytes and less differentiated cell states, revealing substantial baseline heterogeneity. Importantly, increased single-cell sensitivity translated directly into biological insight, as approximately 30% of differentially expressed proteins associated with subtype-specific drug responses were detected exclusively by timsUltra AIP. Application of this workflow to PR-364 (a mitophagy boosting drug) dose-response experiment uncovered distinct, subtype-dependent pathway adaptations. Mature cardiomyocytes exhibited dose-dependent increases in mitochondrial and metabolic pathway activity, while immature cells showed enrichment of cytoskeletal and developmental programs. These effects were partially obscured in simulated bulk analyses, highlighting the value of single-cell resolution. Together, these results demonstrate that improved fragment ion transmission and utilization translate directly into enhanced biological insight, enabling more comprehensive and functionally relevant single-cell proteomics.

molecular biology↗

bioRxiv2025

An ultrasensitive spatial tissue proteomics workflow exceeding 100 proteomes per day

Achieving high-resolution spatial tissue proteomes requires careful balancing and integration of optimized sample processing, chromatography, and MS acquisition. Here, we present an advanced cellenONE protocol for loss-reduced tissue processing and compare all Evosep ONE Whisper Zoom gradients (20, 40, 80, and 120 samples per day), along with three common DIA acquisition schemes on a timsUltra AIP mass spectrometer. We found that tissue type was as important as gradient length and sample amount in determining proteome coverage. Moreover, the benefit of increased tissue sampling was gradient- and dynamic range-dependent. Analyzing mouse liver, a high dynamic range tissue, over tenfold more tissue sampling led to only ~30% gain in protein identification for short gradients (120 SPD and 80 SPD). However, even the lowest tested tissue amount (0.04 nL, 40,000 {micro}m3) yielded 3,200 reproducibly quantified proteins for the 120 SPD method. Longer gradients (40 SPD and 20 SPD) instead significantly benefited from more tissue sampling, quantifying over 7,500 proteins from 0.5 nL of tonsil T-cell niches. Finally, we applied our workflow to a rare squamous cell carcinoma of the oral cavity, uncovering disease-associated pathways and region-specific protein level changes. Our study demonstrates that more than 100 high-quality spatial tissue proteomes can be prepared and acquired daily, laying a strong foundation for cohort-size spatial tissue proteomics in translational research.

systems biology↗

bioRxiv2024

High-throughput proteome profiling with low variation in a multi-center study using dia-PASEF

High throughput proteomics is gaining increasing traction as it facilitates screening of large sample cohorts required in clinical research and systems biology studies. Recent developments in mass spectrometry-based proteomics resulted in improved hardware and software providing deep proteome coverage, robustness, and scale accessible to a wide range of laboratories. Here, we benchmark dia-PASEF, a data-independent acquisition scheme that integrates trapped ion mobility with high scan speed, with a high-resolution time-of-flight mass analyzer (timsTOF HT) for the deep proteome analysis of a human cell line applying short 5-minute gradients. To show intra-and interlaboratory reproducibility, we performed a multi-laboratory study including 11 sites. We demonstrate that on average 7,072 protein groups and 99,835 peptides were identified in human chronic myelogenous leukemia cells on the timsTOF HT with low variation. Our results underline that dia-PASEF data acquisition combined with reproducible chromatography enables high robustness and data consistency across instruments and laboratories, which is a prerequisite for translational biomedical insights.

systems biology↗

bioRxiv2024

Deep, unbiased and quantitative mass spectrometry-based plasma proteome analysis of individual responses to mRNA COVID-19 vaccine

Global campaign against COVID-19 have vaccinated a significant portion of the world population in recent years. Combating the COVID-19 pandemic with mRNA vaccines played a pivotal role in the global immunization effort. However, individual responses to a vaccine are diverse and lead to varying vaccination efficacy. Despite significant progress, a complete understanding of the molecular mechanisms driving the individual immune response to the COVID-19 vaccine remains elusive. To address this gap, we combined a novel nanoparticle-based proteomic workflow with tandem mass tag (TMT) labeling, to quantitatively assess the proteomic changes in a cohort of 12 volunteers following two doses of the Pfizer-BioNTech mRNA COVID-19 vaccine. This optimized protocol seamlessly integrates comprehensive proteome analysis with enhanced throughput by leveraging the enrichment of low-abundant plasma proteins by engineered nanoparticles. Our data demonstrate the ability of this nanoparticle-based workflow to quantify over 3,000 proteins from 48 human plasma samples, providing the deepest view into COVID-19 vaccine-related plasma proteome study. We identified 69 proteins exhibiting a boosted response to the vaccine after the second dose. Additionally, 74 proteins were differentially regulated between seven volunteers, who contracted COVID-19 despite receiving two doses of the vaccine, and the ones who did not contract COVID-19. These findings offer valuable insights into individual variability in response to vaccination, demonstrating the potential of personalized medicine approaches in vaccine development.

immunology↗

bioRxiv2024

Longitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease

To understand dynamic interplay between the human microbiome and host during health and disease, we analyzed the microbial composition, temporal dynamics, and associations with host multi-omics, immune and clinical markers of microbiomes from four body sites in 86 participants over six years. We found that microbiome stability and individuality are body-site-specific and heavily influenced by the host. The stool and oral microbiome were more stable than the skin and nasal microbiomes, possibly due to their interaction with the host and environment. Also, we identified individual-specific and commonly shared bacterial taxa, with individualized taxa showing greater stability. Interestingly, microbiome dynamics correlated across body sites, suggesting systemic coordination influenced by host-microbial-environment interactions. Notably, insulin-resistant individuals showed altered microbial stability and associations between microbiome, molecular markers, and clinical features, suggesting their disrupted interaction in metabolic disease. Our study offers comprehensive views of multi-site microbial dynamics and their relationship with host health and disease. Study HighlightsO_LIThe stability of the human microbiome varies among individuals and body sites. C_LIO_LIHighly individualized microbial genera are more stable over time. C_LIO_LIAt each of the four body sites, systematic interactions between the environment, the host and bacteria can be detected. C_LIO_LIIndividuals with insulin resistance have lower microbiome stability, a more diversified skin microbiome, and significantly altered host-microbiome interactions. C_LI

microbiology↗

bioRxiv2023

Longitudinal Deep Multi-Omics Profiling in a CLN3Δex7/8 Minipig Model Reveals Novel Biomarker Signatures for Batten Disease

Development of therapies for CLN3 Batten disease, a rare pediatric lysosomal storage disorder, has been hindered by the lack of etiological insights and translatable biomarkers to clinics. Here, we used a deep multi-omics approach to discover new biomarkers using longitudinal serum samples from a porcine model of CLN3 disease. Comprehensive metabolomics was combined with a nanoparticle-based LC-MS-based proteomic profiling coupled with TMTpro 18-plex to generate quantitative data on 769 metabolites and 2,634 proteins, collectively the most exhaustive multi-omics profile conducted on serum from a porcine model, which was previously impossible due a to lack of efficient deep serum proteome profiling technologies compatible with model organisms. The presymptomatic disease state was characterized by elevations in glycerophosphodiester species and lysosomal proteases, while later timepoints were enriched with species involved in immune cell activation and sphingolipid metabolism. Cathepsin S, Cathepsin B, glycerophosphoinositol, and glycerophosphoethanolamine captured a large portion of the genotype-correlated variation between healthy and diseased animals, suggesting that an index score based on these analytes could have great utility in the clinic.

neuroscience↗

bioRxiv2023

Protein Coronas on Functionalized Nanoparticles Enable Quantitative and Precise Large-Scale Deep Plasma Proteomics

BackgroundThe wide dynamic range of circulating proteins coupled with the diversity of proteoforms present in plasma has historically impeded comprehensive and quantitative characterization of the plasma proteome at scale. Automated nanoparticle (NP) protein corona-based proteomics workflows can efficiently compress the dynamic range of protein abundances into a mass spectrometry (MS)-accessible detection range. This enhances the depth and scalability of quantitative MS-based methods, which can elucidate the molecular mechanisms of biological processes, discover new protein biomarkers, and improve comprehensiveness of MS-based diagnostics. MethodsInvestigating multi-species spike-in experiments and a cohort, we investigated fold-change accuracy, linearity, precision, and statistical power for the using the Proteograph Product Suite, a deep plasma proteomics workflow, in conjunction with multiple MS instruments. ResultsWe show that NP-based workflows enable accurate identification (false discovery rate of 1%) of more than 6,000 proteins from plasma (Orbitrap Astral) and, compared to a gold standard neat plasma workflow that is limited to the detection of hundreds of plasma proteins, facilitate quantification of more proteins with accurate fold-changes, high linearity, and precision. Furthermore, we demonstrate high statistical power for the discovery of biomarkers in small- and large-scale cohorts. ConclusionsThe automated NP workflow enables high-throughput, deep, and quantitative plasma proteomics investigation with sufficient power to discover new biomarker signatures with a peptide level resolution.

biochemistry↗

bioRxiv2022

Lipidomic profiling reveals age-dependent changes in complex plasma membrane lipids that regulate neural stem cell aging

The aging brain exhibits a decline in the regenerative populations of neural stem cells (NSCs), which may underlie age-associated defects in sensory and cognitive functions1-6. While mechanisms that restore old NSC function have started to be identified7-23, the role of lipids - especially complex lipids - in NSC aging remains largely unclear. Using lipidomic profiling by mass spectrometry, we identify age-related lipidomic signatures in young and old quiescent NSCs in vitro and in vivo. These analyses reveal drastic changes in several complex membrane lipid classes, including phospholipids and sphingolipids in old NSCs. Moreover, poly-unsaturated fatty acids (PUFAs) strikingly increase across complex lipid classes in quiescent NSCs during aging. Age-related changes in complex lipid levels and side chain composition are largely occurring in plasma membrane lipids, as revealed by lipidomic profiling of isolated plasma membrane vesicles. Experimentally, we find that aging is accompanied by modifications in plasma membrane biophysical properties, with a decrease in plasma membrane order in old quiescent NSCs in vitro and in vivo. To determine the functional role of plasma membrane lipids in aging NSCs, we performed genetic and supplementation studies. Knockout of Mboat2, which encodes a phospholipid acyltransferase, exacerbates age-related lipidomic changes in old quiescent NSCs and impedes their ability to activate. As Mboat2 expression declines with age, Mboat2 deficiency may drive NSC decline during aging. Interestingly, supplementation of plasma membrane lipids derived from young NSCs boosts the ability of old quiescent NSCs to activate. Our work could lead to lipid-based strategies for restoring the regenerative potential of NSCs in old individuals, which has important implications for countering brain decline during aging.

molecular biology↗

bioRxiv2022

Enhanced competitive protein exchange at the nano-bio interface enables ultra-deep coverage of the human plasma proteome

We have developed a scalable system that leverages protein-nano interactions to overcome current limitations of deep plasma proteomics in large cohorts. Introducing proprietary engineered nanoparticles (NPs) into a biofluid such as blood plasma leads to the formation of a selective and reproducible protein corona at the particle-protein interface, driven by the relationship between protein-NP affinity and protein abundance. Here we demonstrate the importance of tuning the protein to NP-surface ratio (P/NP), which determines the competition between proteins for binding. We demonstrate how optimized P/NP ratio affects protein corona composition, ultimately enhancing performance of a fully automated NP-based deep proteomic workflow (Proteograph). By limiting the available binding surface of NPs and increasing the binding competition, we identify 1.2 - 1.7x more proteins with only 1% false discovery rate on the surface of each NP, and up to 3x compared to a standard neat plasma proteomics workflow. Moreover, increased competition means proteins are more consistently identified and quantified across replicates, yielding precise quantification and improved coverage of the plasma proteome when using multiple physicochemically distinct NPs. In summary, by optimizing NPs and assay conditions, we capture a larger and more diverse set of proteins, enabling deep proteomic studies at scale.

biophysics↗

bioRxiv2021

Integration and comparison of multi-omics profiles of NGLY1 deficiency plasma and cellular models to identify clinically relevant molecular phenotypes

NGLY1 (N-glycanase 1) deficiency is a rare congenital recessive disorder of protein deglycosylation unaddressed by the current standard of care. Using combined metabolomics and proteomics profiling, we show that NGLY1 deficiency activates the immune response and disturbs lipid metabolism, biogenic amine synthesis, and glutathione metabolism. These alterations were also observed in NGLY1 deficient patient-derived induced pluripotent stem cells (iPSCs) and differentiated neural progenitor cells (NPCs), which serve as personalized cellular models of the disease. These findings provide molecular insight into the pathophysiology of NGLY1 deficiency and suggest potential therapeutic strategies.

systems biology↗

bioRxiv2020

Identification of Covalent Modifications Regulating Immune Signaling Complex Composition and Phenotype

Cells signal through rearrangements of protein communities governed by covalent modifications and reversible interactions of distinct sets of proteins. A method that identifies those post-transcriptional modifications regulating signaling complex composition and functional phenotypes in one experimental setup would facilitate an efficient identification of novel molecular signaling checkpoints. Here we devised Modifications, Interactions and Phenotypes by Affinity Purification Mass Spectrometry (MIP-APMS), comprising the streamlined cloning and transduction of tagged proteins into functionalized reporter cells as well as affinity chromatography, followed by MS-based quantification. We report the time-resolved interplay of more than 50 previously undescribed modification and hundreds of protein-protein interactions of 19 immune protein complexes in monocytes. Validation of interdependecies between covalent, reversible and functional protein complex regulations by knock-out or site-specific mutation, revealed isgylation and phosphorylation of TRAF2 as well as ARHGEF18 interaction in Toll-like receptor 2 signaling. Moreover, we identify distinct mechanisms of action for small molecule inhibitors of p-38 (MAPK14). Our method provides a fast and cost-effective pipeline for the molecular interrogation of protein communities in diverse biological systems and primary cells. HighlightsO_LIExperimental framework to reveal dynamic signaling checkpoints in primary cells C_LIO_LIIdentification of crosstalk between protein modifications and interactions in signaling complexes C_LIO_LIDiscovery of TRAF2 isgylation, phosphorylation and ARHGEF18 interaction in monocytes C_LIO_LIDifferential drug mode of action for p-38 (MAPK14) kinase inhibitors C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=131 SRC="FIGDIR/small/384750v1_ufig1.gif" ALT="Figure 1"> View larger version (55K): org.highwire.dtl.DTLVardef@1e833d3org.highwire.dtl.DTLVardef@1a2805forg.highwire.dtl.DTLVardef@199e1eaorg.highwire.dtl.DTLVardef@1becf99_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2020

Molecular Choreography of Acute Exercise

Exercise testing is routinely used in clinical practice to assess fitness - a strong predictor of survival - as well as causes of exercise limitations. While these studies often focus on cardiopulmonary response and selected molecular pathways, the dynamic system-wide molecular response to exercise has not been fully characterized. We performed a longitudinal multi-omic profiling of plasma and peripheral blood mononuclear cells including transcriptome, immunome, proteome, metabolome and lipidome in 36 well-characterized volunteers before and after a controlled bout of acute exercise (2, 15, 30 min and 1 hour in recovery). Integrative analysis revealed an orchestrated choreography of biological processes across key tissues. Most of these processes were dampened in insulin resistant participants. Finally, we discovered biological pathways involved in exercise capacity and developed prediction models revealing potential resting blood-based biomarkers of fitness.

systems biology↗

bioRxiv2019

Amyloid-like aggregates cause lysosomal defects in neurons via gain-of-function toxicity

The autophagy-lysosomal pathway is impaired in many neurodegenerative diseases characterized by protein aggregation, but the link between aggregation and lysosomal dysfunction remains poorly understood. Here, we combine cryo-electron tomography, proteomics and cell biology studies to investigate the effects of protein aggregates in primary neurons. We use artificial amyloid-like {beta}-sheet proteins ({beta} proteins) to focus on the gain-of-function aspect of aggregation. These proteins form fibrillar aggregates and cause neurotoxicity. We show that late stages of autophagy are impaired by the aggregates, resulting in lysosomal alterations reminiscent of lysosomal storage disorders. Mechanistically, {beta} proteins interact with and sequester AP-31, a subunit of the AP-3 adaptor complex involved in protein trafficking to lysosomal organelles. This leads to destabilization of the AP-3 complex, missorting of AP-3 cargo, and lysosomal defects. Restoring AP-31 expression ameliorates neurotoxicity caused by {beta} proteins. Altogether, our results highlight the link between protein aggregation and neurotoxicity, pointing to lysosomes as particularly vulnerable organelles.

cell biology↗

bioRxiv2019

A genome-wide almanac of co-essential modules assigns function to uncharacterized genes

A central remaining question in the post-genomic era is how genes interact to form biological pathways. Measurements of gene dependency across hundreds of cell lines have been used to cluster genes into co-essential pathways, but this approach has been limited by ubiquitous false positives. Here, we develop a statistical method that enables robust identification of gene co-essentiality and yields a genome-wide set of functional modules. This almanac recapitulates diverse pathways and protein complexes and predicts the functions of 102 uncharacterized genes. Validating top predictions, we show that TMEM189 encodes plasmanylethanolamine desaturase, the long-sought key enzyme for plasmalogen synthesis. We also show that C15orf57 binds the AP2 complex, localizes to clathrin-coated pits, and enables efficient transferrin uptake. Finally, we provide an interactive web tool for the community to explore the results (coessentiality.net). Our results establish co-essentiality profiling as a powerful resource for biological pathway identification and discovery of novel gene functions.

genomics↗