Biology subjects

Albrecht, V.

Publications and source records attributed to Albrecht, V..

8 recordsLinked to original sources

bioRxiv2026

Deep axonal proteomics of human iPSC-derived neurons by microfluidic separation and DIA-MS

One of the defining features of neurons is their compartmentalisation into soma, dendrites and axon. Axons are highly specialised for the transmission of signals over long distances but also exhibit unique vulnerabilities in the context of neurodegeneration, implying a specialised axonal proteome. However, in-depth proteomic characterisation of axons has been limited by the difficulty of isolating pure axonal material in sufficient quantities for conventional mass spectrometry analysis. Here, we combine microfluidic-based axon-soma separation with data-independent acquisition mass spectrometry (DIA-MS) on an Orbitrap Astral mass spectrometer for deep profiling of compartment-resolved proteomes of human induced pluripotent stem cell (iPSC)-derived cortical neurons. We quantify over 9,000 proteins in the somatodendritic compartment and [~]6,000 proteins in the axonal compartment, to our knowledge, representing the deepest human axonal proteome reported to date. Differential abundance analysis identifies 1,250 axon-enriched proteins with strong enrichment of axon-related pathways including vesicle-mediated transport, synaptic vesicle dynamics, and cytoskeletal organisation. Extending this workflow to iPSC-derived lower motor neurons, we reveal a core set of 417 axon-enriched proteins shared between cortical and lower motor neurons, alongside subtype-specific axonal signatures whose functional differences become evident only through compartment-restricted analysis. We show broad coverage of genes for the neurodegenerative diseases hereditary spastic paraplegia and amyotrophic lateral sclerosis, establishing a quantitative reference for interpreting how disease-linked mutations may differentially affect axonal versus somatodendritic proteostasis. This workflow and resource are readily applicable to other neuronal subtypes and disease models, paving the way for studying axonal proteome dynamics in health and disease. HighlightsO_LIDeepest human axonal proteome with [~]6,000 proteins from iPSC-derived neurons C_LIO_LIMicrofluidic separation paired with DIA mass spectrometry C_LIO_LIAxon-specific signatures masked in whole-cell analyses are revealed C_LIO_LICore set of 417 axon-enriched proteins shared across neuron subtypes C_LIO_LIFramework for studying axon-selective vulnerability in neurodegeneration C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=74 SRC="FIGDIR/small/739061v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@191493dorg.highwire.dtl.DTLVardef@15f459forg.highwire.dtl.DTLVardef@1d3e61forg.highwire.dtl.DTLVardef@a9262a_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2026

In situ polymerized monolith tips for reproducible, format-flexible proteomic sample preparation applied to biofluids

Sample preparation increasingly sets the throughput and reproducibility of mass spectrometry (MS)-based proteomics. StageTips (stop-and-go extraction tips) and variants thereof have long been common implements to purify samples, and we recently extended the concept to solid-phase extraction capture (SPEC) tips, in which the entire digestion takes place in sub-microliter volumes. Here we replace the hand-packed bed with a strong anion-exchange (SAX) monolith photopolymerized directly inside the pipette tip from a defined recipe (pSPEC). A liquid-handling robot casts 384 tunable tips in minutes, at low cost and in any format, adding negligibly to the workflows variance. Across biofluids, pSPEC added [~]20% more identifications than in-solution plasma and reached 3,500 protein groups from a single injection of healthy urine and 4,800 from saliva at 100 samples per day, depths usually requiring depletion or fractionation. The same light-cast chemistry should extend to single cells, affinity capture, and population-scale studies.

biochemistry↗

bioRxiv2026

Multi-platform plasma proteomics reveals orthogonal metabolic signatures distinguishing elite athletic phenotypes

Exercise confers profound health benefits, yet the molecular mechanisms linking physical activity to health and longevity are incompletely known. Here we applied three mass spectrometry (MS)-based and one aptamer-based proteomics workflows to elite athletes with contrasting metabolic phenotypes, sampled before and after maximal exhaustive exercise. MS detected larger effect sizes and resolved isoforms; aptamers extended proteome coverage but with unannotated proteoform biases. Acute exercise induced coordinated platelet degranulation, neutrophil activation, and extracellular matrix turnover, with peptide topology analysis providing direct evidence for vesicular release. Chronic adaptations organized along two orthogonal axes: a muscle mass gradient marked by hypertrophy signaling and attenuated systemic inflammation, and an oxidative capacity gradient characterized by metabolic health-associated proteins (APOA4, IGFBP2, ITLN1) and dampened IGF-I signaling. Exploratory biological age analysis suggested younger adipose age in athletes. The plasma proteome provides an integrated readout of exercise adaptation, linking cardiorespiratory fitness to metabolic health and healthy aging.

biochemistry↗

bioRxiv2025

Exploring chromatographic dimensions for state-of-the-art proteomics applications

The evolution of mass spectrometry (MS)-based proteomics has been driven by continuous technological advances in sample preparation, instrumentation, and data acquisition. While chromatographic separation has historically been considered a critical bottleneck in achieving comprehensive proteome coverage, recent developments in ultra-fast data acquisition fundamentally challenge this paradigm. We investigated whether the traditional paradigm that chromatographic performance directly correlates with proteome depth still holds true. Spanning a matrix of experiments with five distinct stationary phases, including C18 chemistries, C8, and Phenyl-Hexyl, across eight column lengths (40-140 mm), we evaluate protein identification performance using data-independent acquisition (DIA) on the Orbitrap Astral mass spectrometer. Despite substantial chromatographic differences, we observed remarkably convergent proteome coverage metrics. All C18 and C8 phases consistently achieved over 150,000 precursor- and approximately 9,000 protein group identifications, regardless of column length variations. While distinct selectivity fingerprints persisted across chemistries, these chromatographic differences did not translate into meaningful variations in proteome coverage under high-speed acquisition conditions at 200 Hz. We conclude that the analytical bottleneck has fundamentally shifted from chromatographic resolution to mass spectrometric sampling efficiency, where comprehensive peptide identification is now gained through advanced spectral deconvolution rather than physical separation alone. This paradigmatic shift is reflected in modern proteomics by method development priorities being directed beyond traditional separation optimization, with greater emphasis placed on operational robustness, analytical throughput, and reproducibility.

biochemistry↗

bioRxiv2025

Pre-Analytical Drivers of Bias in Bead-Enriched Plasma Proteomics

Bead-based enrichment has emerged as a promising strategy to improve depth in plasma proteomics by overcoming the dynamic range barrier. However, its robustness against pre-analytical variation has not been sufficiently characterized. Here, we systematically evaluate five plasma proteomics workflows--including three bead-based methods and two conventional protocols--using controlled spike-ins of low-abundance proteins and defined cellular contaminants. We find that bead-based approaches enhance detection of low-abundance proteins but can be highly susceptible to systematic bias from platelet and PBMC contamination, even at low levels. This can easily inflate results by thousands of proteins, likely accounting for some of the very high literature-reported numbers. In contrast, a perchloric acid-based workflow shows notable resistance to erythrocyte and platelet-derived contamination. We further investigate how centrifugation conditions, anticoagulant choice, and buffer-bead combinations modulate contamination profiles and demonstrate that bias can partially be mitigated by optimized sample handling. In total, we identify more than 13,000 different protein groups from various conditions, including cellular components from the circulating proteome. Our results provide a quantitative framework for assessing workflow performance under variable sample quality and offer guidance for both biomarker discovery and quality control in clinical proteomics studies.

biochemistry↗

bioRxiv2025

A simplified perchloric acid workflow with neutralization (PCA-N) for democratizing deep plasma proteomics at population scale

Large scale plasma proteomics studies offer tremendous potential for biomarker discovery but face significant challenges in balancing analytical depth, throughput and cost-effectiveness. We present an optimized perchloric acid-based workflow with neutralization - PCA-N - that addresses these limitations. By introducing a neutralization step following protein precipitation, PCA-N enables direct enzymatic digestion without additional purification steps, reducing sample volume requirements to only 5 {micro}L of plasma while maintaining deep plasma proteome coverage. The streamlined protocol allows preparation of over 10,000 samples per day using 384-well formats at costs comparable to undepleted plasma analysis (NEAT). Rigorous validation according to the recently introduced CLSI C64 guideline demonstrated that despite somewhat higher technical variability compared to NEAT, PCA-N maintained excellent biological resolution and reproducibility. We confirmed the workflows exceptional stability through analysis of 1,500 quality control samples systematically interspersed among 36,000 plasma samples measured continuously over 311 days. Technical performance remained consistent across multiple instruments, sample preparation batches and nearly a year of measurements. Compared to NEAT plasma proteomics, PCA-N doubled the proteomic depth while maintaining comparable reagent costs and throughput. The minimal sample reequipments, operational simplicity while using only common laboratory chemical and exceptional scalability positions PCA-N as an attractive approach for population-level plasma proteomics, democratizing access to deep plasma proteome analysis. HighlightsO_LIPerchloric acid with neutralization (PCA-N) allows drastic upscaling of plasma proteomics C_LIO_LIMinimal sample input (5 {micro}L) in 384-well format enables thousands of samples processed daily C_LIO_LIPCA-N democratizes deep plasma proteomics using only common chemicals C_LIO_LIValidation per CLSI C64 demonstrates excellent repeatability and reproducibility C_LIO_LIPCA-N showed exceptional stability across 311 days of continuous MS acquisition C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=106 HEIGHT=200 SRC="FIGDIR/small/645089v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@11eb315org.highwire.dtl.DTLVardef@7f4f41org.highwire.dtl.DTLVardef@2c41feorg.highwire.dtl.DTLVardef@1a09925_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2024

A novel hybrid high speed mass spectrometer allows rapid translation from biomarker candidates to targeted clinical tests using 15N labeled proteins

Recent developments in affinity binder or mass spectrometry (MS)-based plasma proteomics are now producing panels of potential biomarker candidates for diagnosis or prognosis. However, clinical validation and implementation of these biomarkers remain limited by the reliance on dated triple quadrupole MS technology. Here, we evaluate a novel hybrid high-speed mass spectrometer, Stellar MS, which integrates the robustness of triple quadrupoles with the enhanced capabilities of an advanced linear ion trap analyzer. This instrument allows for extremely rapid and sensitive parallel reaction monitoring (PRM) and MS3 targeting. The Stellar MS allowed targeting thousands of peptides originally measured on Orbitrap Astral MS, achieving high reproducibility and low coefficients of variation (CV) as well as sensitivity and specificity sufficient for more than the top 1000 plasma proteins. Furthermore, we developed targeted assays for alcohol-related liver disease (ALD) biomarkers, showcasing the potential of Stellar MS in clinical applications. Absolute quantification is typically a requirement for clinical assays and we explore the use of 15 N labeled protein standards in a rapid, streamlined and generic manner. Our results indicate that Stellar MS can bridge the gap between proteomics discovery and routine clinical testing, enhancing the diagnostic and prognostic utility of protein biomarkers.

biochemistry↗

bioRxiv2021

Data independent acquisition enables deep and fast label-free dynamic organellar mapping

The Dynamic Organellar Maps (DOMs) approach combines cell fractionation and shotgun-proteomics for global profiling analysis of protein subcellular localization. Here, we have drastically enhanced the performance of DOMs through data-independent acquisition (DIA) mass spectrometry (MS). DIA-DOMs achieve twice the depth of our previous workflow in the same MS runtime, and substantially improve profiling precision and reproducibility. We leveraged this gain to establish flexible map formats scaling from rapid analyses to ultra-deep coverage. Our fastest format takes only [~]2.5h/map and enables high-throughput experimental designs. Furthermore, we introduce DOM-QC, an open-source software tool for in-depth standardized analysis of DOMs and other profiling data. We then applied DIA-DOMs to capture subcellular localization changes in response to starvation and disruption of lysosomal pH in HeLa cells, which revealed a subset of Golgi proteins that cycle through endosomes. DIA-DOMs offer a superior workflow for label-free spatial proteomics as a systematic phenotype discovery tool.

biochemistry↗