An Automated Nanowell-Array Workflow for Quantitative Multiplexed Single-Cell Proteomics Sample Preparation at High Sensitivity

Molecular & Cellular Proteomics, Год журнала: 2023, Номер 22(12), С. 100665 - 100665

Опубликована: Окт. 14, 2023

Multiplexed and label-free mass spectrometry-based approaches with single-cell resolution have attributed surprising heterogeneity to presumed homogenous cell populations. Even though specialized experimental designs instrumentation demonstrated remarkable advances, the efficient sample preparation of single cells still lags. Here, we introduce proteoCHIP, a universal option for proteomics including multiplexed labeling up 16-plex high sensitivity throughput. The automated processing using commercial system combining isolation picoliter dispensing, cellenONE®, reduces final volumes low nanoliters submerged in hexadecane layer simultaneously eliminating error-prone manual handling overcoming evaporation. proteoCHIP design allows direct injection via standard autosampler resulting around 1,500 protein groups per TMT10-plex reduced or eliminated need carrier proteome. We evaluated effect wider precursor windows at input levels found that 2 Da increased overall without significantly impacting interference. Using dedicated MS acquisition strategies detailed here, identified on average close 2,000 proteins across 170 readily distinguished human types. Overall, our workflow combines highly preparation, chromatographic ion mobility-based filtering, rapid wide-window DDA analysis intelligent data optimal proteomics. This versatile proteoCHIP-based approach is sufficiently sensitive drive biological applications can be adopted by laboratories.

Язык: Английский

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

Molecular Systems Biology, Год журнала: 2023, Номер 19(9)

Опубликована: Авг. 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.

Язык: Английский

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Exploration of cell state heterogeneity using single-cell proteomics through sensitivity-tailored data-independent acquisition

Nature Communications, Год журнала: 2023, Номер 14(1)

Опубликована: Сен. 22, 2023

Single-cell resolution analysis of complex biological tissues is fundamental to capture cell-state heterogeneity and distinct cellular signaling patterns that remain obscured with population-based techniques. The limited amount material encapsulated in a single cell however, raises significant technical challenges molecular profiling. Due extensive optimization efforts, single-cell proteomics by Mass Spectrometry (scp-MS) has emerged as powerful tool facilitate proteome profiling from ultra-low amounts input, although further development needed realize its full potential. To this end, we carry out comprehensive orbitrap-based data-independent acquisition (DIA) for proteomics. Notably, find difference between optimal DIA methods high- low-load samples. We improve our low-input method relying on high-resolution MS1 quantification, thus enhancing sensitivity more efficiently utilizing available mass analyzer time. With input tailored method, are able accommodate long injection times high resolution, while keeping the scan cycle time low enough ensure robust quantification. Finally, demonstrate capability approach mouse embryonic stem culture conditions, showcasing global proteomes highlighting differences key metabolic enzyme expression subclusters.

Язык: Английский

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A review of the current state of single-cell proteomics and future perspective

Analytical and Bioanalytical Chemistry, Год журнала: 2023, Номер 415(28), С. 6889 - 6899

Опубликована: Июнь 7, 2023

Abstract Single-cell methodologies and technologies have started a revolution in biology which until recently has primarily been limited to deep sequencing imaging modalities. With the advent subsequent torrid development of single-cell proteomics over last 5 years, despite fact that proteins cannot be amplified like transcripts, it now become abundantly clear is worthy complement transcriptomics. In this review, we engage an assessment current state art including workflow, sample preparation techniques, instrumentation, biological applications. We investigate challenges associated with working very small volumes acute need for robust statistical methods data interpretation. delve into what believe promising future research at resolution highlight some exciting discoveries already made using proteomics, identification rare cell types, characterization cellular heterogeneity, investigation signaling pathways disease mechanisms. Finally, acknowledge there are number outstanding pressing problems scientific community vested advancing technology needs resolve. Of prime importance set standards so becomes widely accessible allowing novel easily verifiable. conclude plea solve these rapidly can part robust, high-throughput, scalable multi-omics platform ubiquitously applied elucidating insights diagnosis treatment all diseases afflict us.

Язык: Английский

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Nanopore DNA sequencing technologies and their applications towards single-molecule proteomics

Nature Chemistry, Год журнала: 2024, Номер 16(3), С. 314 - 334

Опубликована: Март 1, 2024

Язык: Английский

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One-Tip enables comprehensive proteome coverage in minimal cells and single zygotes

Nature Communications, Год журнала: 2024, Номер 15(1)

Опубликована: Март 20, 2024

Mass spectrometry (MS)-based proteomics workflows typically involve complex, multi-step processes, presenting challenges with sample losses, reproducibility, requiring substantial time and financial investments, specialized skills. Here we introduce One-Tip, a methodology that seamlessly integrates efficient, one-pot preparation precise, narrow-window data-independent acquisition (nDIA) analysis. One-Tip substantially simplifies processing, enabling the reproducible identification of >9000 proteins from ~1000 HeLa cells. The versatility is highlighted by nDIA ~6000 in single cells early mouse embryos. Additionally, study incorporates Uno Single Cell Dispenser™, demonstrating capability single-cell >3000 identified per cell. We also extend workflow to analysis extracellular vesicles (EVs) extracted blood plasma, its high sensitivity identifying 16 ng EV preparation. expands capabilities proteomics, offering greater depth throughput across range types.

Язык: Английский

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Automated single-cell proteomics providing sufficient proteome depth to study complex biology beyond cell type classifications

Nature Communications, Год журнала: 2024, Номер 15(1)

Опубликована: Июль 8, 2024

Abstract The recent technological and computational advances in mass spectrometry-based single-cell proteomics have pushed the boundaries of sensitivity throughput. However, reproducible quantification thousands proteins within a single cell remains challenging. To address some those limitations, we present dedicated sample preparation chip, proteoCHIP EVO 96 that directly interfaces with Evosep One. This, combination Bruker timsTOF demonstrates double identifications without manual handling newest generation Ultra identifies up to 4000 an average 3500 protein groups per HEK-293T carrier or match-between runs. Our workflow spans 4 orders magnitude, over 50 E3 ubiquitin-protein ligases, profiles key regulatory upon small molecule stimulation. This study 96-based provides sufficient proteome depth complex biology beyond cell-type classifications.

Язык: Английский

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Pick-up single-cell proteomic analysis for quantifying up to 3000 proteins in a Mammalian cell

Nature Communications, Год журнала: 2024, Номер 15(1)

Опубликована: Фев. 10, 2024

Abstract The shotgun proteomic analysis is currently the most promising single-cell protein sequencing technology, however its identification level of ~1000 proteins per cell still insufficient for practical applications. Here, we develop a pick-up (PiSPA) workflow to achieve deep capable quantifying up 3000 groups in mammalian using label-free quantitative method. PiSPA specially established samples mainly based on nanoliter-scale microfluidic liquid handling robot, achieving capture, pretreatment and injection under operation strategy. Using this customized with remarkable improvement identification, 2449–3500, 2278–3257 1621–2904 are quantified single A549 cells ( n = 37), HeLa 44) U2OS 27) DIA (MBR) mode, respectively. Benefiting from flexible picking-up ability, study migration at proteome level, demonstrating potential biological research insight.

Язык: Английский

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Micropillar arrays, wide window acquisition and AI-based data analysis improve comprehensiveness in multiple proteomic applications

Nature Communications, Год журнала: 2024, Номер 15(1)

Опубликована: Фев. 3, 2024

Comprehensive proteomic analysis is essential to elucidate molecular pathways and protein functions. Despite tremendous progress in proteomics, current studies still suffer from limited coverage dynamic range. Here, we utilize micropillar array columns (µPACs) together with wide-window acquisition the AI-based CHIMERYS search engine achieve excellent comprehensiveness for bulk affinity purification mass spectrometry single cell proteomics. Our data show that µPACs identify ≤50% more peptides ≤24% proteins, while offering improved throughput, which critical large (clinical) proteomics studies. Combining wide precursor isolation widths of m/z 4-12 identified +51-74% +59-150% proteins peptides, respectively, cell, co-immunoprecipitation, multi-species samples over a conventional workflow at well-controlled false discovery rates. The further offers precision, CVs <7% low input samples, accuracy, deviations <10% expected fold changes regular abundance two-proteome mixes. Compared workflow, our entire optimized platform discovered 92% potential interactors protein-protein interaction study on chromatin remodeler Smarca5/Snf2h. These include previously described Smarca5 binding partners undescribed ones including Arid1a, another key roles neurodevelopmental malignant disorders.

Язык: Английский

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The 2023 Report on the Proteome from the HUPO Human Proteome Project

Journal of Proteome Research, Год журнала: 2024, Номер 23(2), С. 532 - 549

Опубликована: Янв. 17, 2024

Since 2010, the Human Proteome Project (HPP), flagship initiative of Organization (HUPO), has pursued two goals: (1) to credibly identify protein parts list and (2) make proteomics an integral part multiomics studies human health disease. The HPP relies on international collaboration, data sharing, standardized reanalysis MS sets by PeptideAtlas MassIVE-KB using Guidelines for quality assurance, integration curation non-MS neXtProt, plus extensive use antibody profiling carried out Protein Atlas. According neXtProt release 2023-04-18, expression now been detected (PE1) 18,397 19,778 predicted proteins coded in genome (93%). Of these PE1 proteins, 17,453 were with mass spectrometry (MS) accordance 944 a variety methods. number PE2, PE3, PE4 missing stands at 1381. Achieving unambiguous identification 93% encoded from across all chromosomes represents remarkable experimental progress list. Meanwhile, there are several categories that have proved resistant detection regardless protein-based methods used. Additionally some PE1–4 probably should be reclassified PE5, specifically 21 LINC entries ∼30 HERV entries; being addressed present year. Applying wide array biological clinical ensures other omics platforms as reported Biology Disease-driven teams pathology resource pillars. Current positioned transition its Grand Challenge focused determining primary function(s) every itself networks pathways within context

Язык: Английский

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