Exploring functional protein covariation across single cells using nPOP

Genome biology, Год журнала: 2022, Номер 23(1)

Опубликована: Дек. 16, 2022

Many biological processes, such as cell division cycle and drug resistance, are reflected in protein covariation across single cells. This can be quantified interpreted by single-cell mass spectrometry with sufficiently high throughput accuracy.

Язык: Английский

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Prioritized mass spectrometry increases the depth, sensitivity and data completeness of single-cell proteomics

Nature Methods, Год журнала: 2023, Номер 20(5), С. 714 - 722

Опубликована: Апрель 3, 2023

Major aims of single-cell proteomics include increasing the consistency, sensitivity and depth protein quantification, especially for proteins modifications biological interest. Here, to simultaneously advance all these aims, we developed prioritized Single-Cell ProtEomics (pSCoPE). pSCoPE consistently analyzes thousands peptides across single cells (thus data completeness) while maximizing instrument time spent analyzing identifiable peptides, thus proteome depth. These strategies increased sensitivity, completeness coverage over twofold. The gains enabled quantifying variation in untreated lipopolysaccharide-treated primary macrophages. Within each condition, covaried within functional sets, including phagosome maturation proton transport, similarly both treatment conditions. This covariation is coupled phenotypic variability endocytic activity. also proteolytic products, suggesting a gradient cathepsin activities condition. freely available widely applicable, interest without sacrificing coverage. Support at http://scp.slavovlab.net/pSCoPE .

Язык: Английский

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scPerturb: harmonized single-cell perturbation data

Nature Methods, Год журнала: 2024, Номер 21(3), С. 531 - 540

Опубликована: Янв. 26, 2024

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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Challenges and best practices in omics benchmarking

Nature Reviews Genetics, Год журнала: 2024, Номер 25(5), С. 326 - 339

Опубликована: Янв. 12, 2024

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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Evaluating the capabilities of the Astral mass analyzer for single-cell proteomics

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2023, Номер unknown

Опубликована: Июнь 8, 2023

Abstract The complexity of human physiology arises from well-orchestrated interactions between trillions single cells in the body. While single-cell RNA sequencing (scRNA-seq) has enhanced our understanding cell diversity, gene expression alone does not fully characterize phenotypes. Additional molecular dimensions, such as proteins, are needed to define cellular states accurately. Mass spectrometry (MS)-based proteomics emerged a powerful tool for comprehensive protein analysis, including applications. However, challenges remain terms throughput and proteomic depth, order maximize biological impact by Spectrometry (scp-MS) workflows. This study leverages novel high-resolution, accurate mass (HRAM) instrument platform, consisting both an Orbitrap innovative HRAM Asymmetric Track Lossless (Astral) analyzer. Astral analyzer offers high sensitivity resolution through lossless ion transfer unique flight track design. We evaluate performance Thermo Scientific MS using Data-Independent Acquisition (DIA) assess proteome depth quantitative precision ultra-low input samples. Optimal DIA method parameters identified, we demonstrate ability cycle dynamics Human Embryonic Kidney (HEK293) cells, cancer heterogeneity primary Acute Myeloid Leukemia (AML) culture model.

Язык: Английский

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HyperSCP: Combining Isotopic and Isobaric Labeling for Higher Throughput Single-Cell Proteomics

Analytical Chemistry, Год журнала: 2023, Номер 95(20), С. 8020 - 8027

Опубликована: Май 11, 2023

Recent developments in mass spectrometry-based single-cell proteomics (SCP) have resulted dramatically improved sensitivity, yet the relatively low measurement throughput remains a limitation. Isobaric and isotopic labeling methods been separately applied to SCP increase through multiplexing. Here we combined both forms of achieve multiplicative scaling for higher throughput. Two-plex stable isotope amino acids cell culture (SILAC) isobaric tandem tag (TMT) enabled up 28 single cells be analyzed liquid chromatography–mass spectrometry (LC–MS) analysis, addition carrier, reference, negative control channels. A custom nested nanowell chip was used nanoliter sample processing minimize losses. Using 145-min total LC–MS cycle time, ∼280 were per day. This could increased ∼700 samples day with high-duty-cycle multicolumn LC system producing same active gradient. The efficiency achievable proteome coverage characterized multiple analysis conditions.

Язык: Английский

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MS²Rescore 3.0 Is a Modular, Flexible, and User-Friendly Platform to Boost Peptide Identifications, as Showcased with MS Amanda 3.0

Journal of Proteome Research, Год журнала: 2024, Номер 23(8), С. 3200 - 3207

Опубликована: Март 16, 2024

Rescoring of peptide-spectrum matches (PSMs) has emerged as a standard procedure for the analysis tandem mass spectrometry data. This emphasizes need software maintenance and continuous improvement such algorithms. We introduce MS

Язык: Английский

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scPROTEIN: a versatile deep graph contrastive learning framework for single-cell proteomics embedding

Nature Methods, Год журнала: 2024, Номер 21(4), С. 623 - 634

Опубликована: Март 19, 2024

Язык: Английский

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