Robust dimethyl‐based multiplex‐DIA doubles single‐cell proteome depth via a reference channel

Molecular Systems Biology, Journal Year: 2023, Volume and Issue: 19(9)

Published: Aug. 21, 2023

Single-cell proteomics aims to characterize biological function and heterogeneity at the level of proteins in an unbiased manner. It is currently limited proteomic depth, throughput, robustness, which we address here by a streamlined multiplexed workflow using data-independent acquisition (mDIA). We demonstrate automated complete dimethyl labeling bulk or single-cell samples, without losing depth. Lys-N digestion enables five-plex quantification MS1 MS2 level. Because channels are quantitatively isolated from each other, mDIA accommodates reference channel that does not interfere with target channels. Our algorithm RefQuant takes advantage this confidently quantifies twice as many per single cell compared our previous work (Brunner et al, PMID 35226415), while allows routine analysis 80 cells day. Finally, combined spatial increase throughput Deep Visual Proteomics seven-fold for microdissection four-fold MS analysis. Applying primary cutaneous melanoma, discovered signatures within distinct tumor microenvironments, showcasing its potential precision oncology.

Language: Английский

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Plasma proteomics identify biomarkers predicting Parkinson’s disease up to 7 years before symptom onset

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: June 18, 2024

Abstract Parkinson’s disease is increasingly prevalent. It progresses from the pre-motor stage (characterised by non-motor symptoms like REM sleep behaviour disorder), to disabling motor stage. We need objective biomarkers for early/pre-motor stages be able intervene and slow underlying neurodegenerative process. Here, we validate a targeted multiplexed mass spectrometry assay blood samples recently diagnosed patients ( n = 99), individuals with isolated disorder (two cohorts: 18 54 longitudinally), healthy controls 36). Our machine-learning model accurately identifies all Parkinson classifies 79% of up 7 years before onset analysing expression eight proteins—Granulin precursor, Mannan-binding-lectin-serine-peptidase-2, Endoplasmatic-reticulum-chaperone-BiP, Prostaglaindin-H2-D-isomaerase, Interceullular-adhesion-molecule-1, Complement C3, Dickkopf-WNT-signalling pathway-inhibitor-3, Plasma-protease-C1-inhibitor. Many these correlate symptom severity. This specific panel indicates molecular events in early could help identify at-risk participants clinical trials aimed at slowing/preventing disease.

Language: Английский

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Opportunities and barriers in omics-based biomarker discovery for steatotic liver diseases

Journal of Hepatology, Journal Year: 2024, Volume and Issue: 81(2), P. 345 - 359

Published: March 28, 2024

The rising prevalence of liver diseases related to obesity and excessive use alcohol is fuelling an increasing demand for accurate biomarkers aimed at community screening, diagnosis steatohepatitis significant fibrosis, monitoring, prognostication prediction treatment efficacy. Breakthroughs in omics methodologies the power bioinformatics have created excellent opportunity apply technological advances clinical needs, instance development precision personalised medicine. Via technologies, biological processes from genes circulating protein, as well microbiome - including bacteria, viruses fungi, can be investigated on axis. However, there are important barriers omics-based biomarker discovery validation, semi-quantitative measurements untargeted platforms, which may exhibit high analytical, inter- intra-individual variance. Standardising methods need validate them across diverse populations presents a challenge, partly due disease complexity dynamic nature expression different stages. Lack validity causes lost opportunities when studies fail provide knowledge needed regulatory approvals, all contributes delayed translation these discoveries into practice. While no matured implementation, extent data generated has enabled hypothesis-free plethora candidate that warrant further validation. To explore many hepatologists detailed commonalities differences between various layers, both advantages approaches.

Language: Английский

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Mass-spectrometry-based proteomics: from single cells to clinical applications

Nature, Journal Year: 2025, Volume and Issue: 638(8052), P. 901 - 911

Published: Feb. 26, 2025

Language: Английский

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Integrating Artificial Intelligence for Advancing Multiple-Cancer Early Detection via Serum Biomarkers: A Narrative Review

Cancers, Journal Year: 2024, Volume and Issue: 16(5), P. 862 - 862

Published: Feb. 21, 2024

The concept and policies of multicancer early detection (MCED) have gained significant attention from governments worldwide in recent years. In the era burgeoning artificial intelligence (AI) technology, integration MCED with AI has become a prevailing trend, giving rise to plethora products. However, due heterogeneity both targets technologies, overall diversity products remains considerable. types encompass protein biomarkers, cell-free DNA, or combinations these biomarkers. development models, different model training approaches are employed, including datasets case-control studies real-world cancer screening datasets. Various validation techniques, such as cross-validation, location-wise validation, time-wise used. All factors show impacts on predictive efficacy AIs. After completion development, deploying AIs clinical practice presents numerous challenges, presenting reports, identifying potential locations tumors, addressing cancer-related information, follow-up treatment. This study reviews several mature currently available market, detecting their composing serum biomarker detection, training/validation, application. review illuminates challenges encountered by existing across stages, offering insights into continued obstacles within field AI.

Language: Английский

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Lanthanide Metal–Organic Framework Flowers for Proteome Profiling and Biomarker Identification in Ultratrace Biofluid Samples

ACS Nano, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 22, 2025

Identifying effective biomarkers has long been a persistent need for early diagnosis and targeted therapy of disease. While mass spectrometry-based label-free proteomics with trace cell demonstrated, deep ultratrace human biofluid remains challenging due to low protein concentration, extremely limited patient sample volume, substantial contact losses during preprocessing. Herein, we proposed validated lanthanide metal–organic framework flowers (MOF-flowers), as materials, trap enrich in jointly through cation−π interaction O–Ln coordination. We further developed MOF-flower assisted simplified single-pot Sample Preparation (Mass-SP) workflow that incorporates capture, digest, peptide elute into one single PCR tube maximally avoid adsorptive loss. adopted Mass-SP decipher aqueous humor (AH) proteome signatures from cataract retinal vein occlusion (RVO) patients quantified ∼3900 proteins merely 1 μL AH. Combined machine learning, identified PFKL prioritization biomarker RVO disease the areas under curves 0.95 ± 0.04. presents strategy identify de novo explore potential therapeutic targets clinical body fluid resources.

Language: Английский

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Neat plasma proteomics: getting the best out of the worst

Clinical Proteomics, Journal Year: 2024, Volume and Issue: 21(1)

Published: March 12, 2024

Plasma proteomics holds immense potential for clinical research and biomarker discovery, serving as a non-invasive "liquid biopsy" tissue sampling. Mass spectrometry (MS)-based proteomics, thanks to improvement in speed robustness, emerges an ideal technology exploring the plasma proteome its unbiased highly specific protein identification quantification. Despite potential, is still challenge due vast dynamic range of abundance, hindering detection less abundant proteins. Different approaches can help overcome this challenge. Conventional depletion methods face limitations cost, throughput, accuracy, off-target depletion. Nanoparticle-based enrichment shows promise compressing range, but cost remains constraint. Enrichment strategies extracellular vesicles (EVs) enhance coverage dramatically, current are too laborious large series. Neat popular cost-effectiveness, time efficiency, low volume requirement. We used test set 33 samples all evaluations. Samples were digested using S-Trap analyzed on Evosep One nanoElute coupled timsTOF Pro different elution gradients ion mobility ranges. Data mainly library-free searches DIA-NN. This study explores ways improve neat both MS data acquisition analysis. demonstrate value sampling smaller hydrophilic peptides, increasing chromatographic separation, searches. Additionally, we introduce EV boost approach, that leverages vesicle fraction samples. Globally, our optimized analysis workflow allows quantification over 1000 proteins with 24SPD throughput. believe these considerations be independently LC-MS platform used.

Language: Английский

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Harnessing the power of proteomics in precision diabetes medicine

Diabetologia, Journal Year: 2024, Volume and Issue: 67(5), P. 783 - 797

Published: Feb. 12, 2024

Language: Английский

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Longitudinal proteomics of leptin treatment in humans with acute and chronic energy deficiency-induced hypoleptinemia reveal novel, mainly immune-related, pleiotropic effects

Metabolism, Journal Year: 2024, Volume and Issue: 159, P. 155984 - 155984

Published: Aug. 2, 2024

Language: Английский

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Secretome analysis using Affinity Proteomics and Immunoassays: a focus on Tumor Biology

Molecular & Cellular Proteomics, Journal Year: 2024, Volume and Issue: 23(9), P. 100830 - 100830

Published: Aug. 14, 2024

The study of the cellular secretome using proteomic techniques continues to capture attention research community across a broad range topics in biomedical research. Due their untargeted nature, independence from model system used, historically superior depth analysis, as well comparative affordability, mass spectrometry-based approaches traditionally dominate such analyses. More recently, however, affinity-based assays have massively gained analytical depth, which together with high sensitivity, dynamic coverage throughput capabilities render them exquisitely suited analysis. In this review, we revisit challenges implied by secretomics and provide an overview platforms currently available for analyses, tumor example basic translational

Language: Английский

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