Immunopeptidomics in the Era of Single-Cell Proteomics DOI Creative Commons
Rupert L. Mayer, Karl Mechtler

Biology, Год журнала: 2023, Номер 12(12), С. 1514 - 1514

Опубликована: Дек. 12, 2023

Immunopeptidomics, as the analysis of antigen peptides being presented to immune system via major histocompatibility complexes (MHC), is seen an imperative tool for identifying epitopes vaccine development treat cancer and viral bacterial infections well parasites. The field has made tremendous strides over last 25 years but currently still faces challenges in sensitivity throughput widespread applications personalized medicine large studies. Cutting-edge technological advancements sample preparation, liquid chromatography mass spectrometry, data analysis, however, are transforming field. This perspective showcases how advent single-cell proteomics accelerated this transformation immunopeptidomics recent will pave way even more sensitive higher-throughput analyses.

Язык: Английский

One-Tip enables comprehensive proteome coverage in minimal cells and single zygotes DOI Creative Commons
Zilu Ye, Pierre Sabatier, Javier Martín‐González

и другие.

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

Процитировано

37
Automated single-cell proteomics providing sufficient proteome depth to study complex biology beyond cell type classifications DOI Creative Commons
Claudia Ctortecka, Natalie M. Clark, Brian Boyle

и другие.

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

Процитировано

32
From Genotype to Phenotype: Raman Spectroscopy and Machine Learning for Label-Free Single-Cell Analysis DOI
Yirui Zhang, Kai Chang, Babatunde Ogunlade

и другие.

ACS Nano, Год журнала: 2024, Номер 18(28), С. 18101 - 18117

Опубликована: Июль 1, 2024

Raman spectroscopy has made significant progress in biosensing and clinical research. Here, we describe how surface-enhanced (SERS) assisted with machine learning (ML) can expand its capabilities to enable interpretable insights into the transcriptome, proteome, metabolome at single-cell level. We first review advances nanophotonics-including plasmonics, metamaterials, metasurfaces-enhance scattering for rapid, strong label-free spectroscopy. then discuss ML approaches precise spectral analysis, including neural networks, perturbation gradient algorithms, transfer learning. provide illustrative examples of phenotyping using nanophotonics ML, bacterial antibiotic susceptibility predictions, stem cell expression profiles, cancer diagnostics, immunotherapy efficacy toxicity predictions. Lastly, exciting prospects future spectroscopy, instrumentation, self-driving laboratories, data banks, uncovering biological insights.

Язык: Английский

Процитировано

22
Enhanced sensitivity and scalability with a Chip-Tip workflow enables deep single-cell proteomics DOI Creative Commons
Zilu Ye, Pierre Sabatier, Leander van der Hoeven

и другие.

Nature Methods, Год журнала: 2025, Номер unknown

Опубликована: Янв. 16, 2025

Single-cell proteomics (SCP) promises to revolutionize biomedicine by providing an unparalleled view of the proteome in individual cells. Here, we present a high-sensitivity SCP workflow named Chip-Tip, identifying >5,000 proteins HeLa It also facilitated direct detection post-translational modifications single cells, making need for specific modification-enrichment unnecessary. Our study demonstrates feasibility processing up 120 label-free samples per day. An optimized tissue dissociation buffer enabled effective single-cell disaggregation drug-treated cancer cell spheroids, refining overall analysis. Analyzing nondirected human-induced pluripotent stem differentiation, consistently quantified markers OCT4 and SOX2 cells lineage such as GATA4 (endoderm), HAND1 (mesoderm) MAP2 (ectoderm) different embryoid body sets benchmark sensitivity throughput, with broad applications basic biology identification type-specific therapeutic targets.

Язык: Английский

Процитировано

9
Easy and Accessible Workflow for Label-Free Single-Cell Proteomics DOI

Ximena Sanchez-Avila,

Thy Truong, Xiaofeng Xie

и другие.

Journal of the American Society for Mass Spectrometry, Год журнала: 2023, Номер 34(10), С. 2374 - 2380

Опубликована: Авг. 18, 2023

Single-cell proteomics (SCP) can provide information that is unattainable through either bulk-scale protein measurements or single-cell profiling of other omes. Maximizing proteome coverage often requires custom instrumentation, consumables, and reagents for sample processing separations, which has limited the accessibility SCP to a small number specialized laboratories. Commercial platforms have become available cell isolation preparation, but high cost these technical expertise required their operation place them out reach many interested Here, we assessed new HP D100 Single Cell Dispenser label-free SCP. The low-cost instrument proved highly accurate reproducible dispensing in range from 200 nL 2 μL. We used isolate prepare single cells within 384-well PCR plates. When well plates were immediately centrifuged following again after reagent dispensing, found ∼97% wells identified software as containing indeed provided expected cell. This commercial dispenser combined with one-step provides very rapid easy-to-use workflow no reduction relative nanowell-based workflow, also facilitate autosampling unmodified instrumentation. samples analyzed using home-packed 30 μm i.d. nanoLC columns commercially 50 columns. resulted ∼35% fewer proteins. However, plate-based preparation platform, presented fully relatively alternative separation, should greatly broaden

Язык: Английский

Процитировано

31
What’s new in single-cell proteomics DOI
Thy Truong, Ryan Kelly

Current Opinion in Biotechnology, Год журнала: 2024, Номер 86, С. 103077 - 103077

Опубликована: Фев. 14, 2024

Язык: Английский

Процитировано

13
Automated single-cell proteomics providing sufficient proteome depth to study complex biology beyond cell type classifications DOI Creative Commons
Claudia Ctortecka, Natalie M. Clark, Brian Boyle

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Янв. 22, 2024

Abstract Mass spectrometry (MS)-based single-cell proteomics (SCP) has gained massive attention as a viable complement to other single cell approaches. The rapid technological and computational advances in the field have pushed boundaries of sensitivity throughput. However, reproducible quantification thousands proteins within at reasonable proteome depth characterize biological phenomena remains challenge. To address some those limitations we present combination fully automated sample preparation utilizing dedicated chip picolitre dispensing robot, cellenONE. proteoCHIP EVO 96 can be directly interfaced with Evosep One chromatographic system for in-line desalting highly separation throughput 80 samples per day. This, Bruker timsTOF MS instruments, demonstrates double identifications without manual handling. Moreover, relative standard high-performance liquid chromatography, provides further 2-fold improvement protein identifications. implementation newest generation Ultra our 96-based workflow reproducibly identifies up 4,000 HEK-293T carrier or match-between runs. Our current SCP spans over 4 orders magnitude 50 biologically relevant ubiquitin ligases. We profile hundreds lipopolysaccharide (LPS)-perturbed THP-1 cells identified key regulatory involved interleukin interferon signaling. This study that sufficient complex biology beyond cell-type classifications.

Язык: Английский

Процитировано

12
AM-DMF-SCP: Integrated Single-Cell Proteomics Analysis on an Active Matrix Digital Microfluidic Chip DOI Creative Commons
Zhicheng Yang, Kai Jin,

Yi‐Min Chen

и другие.

JACS Au, Год журнала: 2024, Номер 4(5), С. 1811 - 1823

Опубликована: Март 26, 2024

Single-cell proteomics offers unparalleled insights into cellular diversity and molecular mechanisms, enabling a deeper understanding of complex biological processes at the individual cell level. Here, we develop an integrated sample processing on active-matrix digital microfluidic chip for single-cell (AM-DMF-SCP). Employing AM-DMF-SCP approach data-independent acquisition (DIA), identify average 2258 protein groups in single HeLa cells within 15 min liquid chromatography gradient. We performed comparative analyses three tumor lines: HeLa, A549, HepG2, machine learning was utilized to unique features these lines. Applying characterize proteomes third-generation EGFR inhibitor, ASK120067-resistant (67R) their parental NCI-H1975 cells, observed potential correlation between elevated VIM expression 67R resistance, which is consistent with findings from bulk analyses. These results suggest that automated, robust, sensitive platform demonstrate providing valuable mechanisms.

Язык: Английский

Процитировано

11
Massively parallel sample preparation for multiplexed single-cell proteomics using nPOP DOI
Andrew Leduc, Luke Khoury, Joshua Cantlon

и другие.

Nature Protocols, Год журнала: 2024, Номер 19(12), С. 3750 - 3776

Опубликована: Авг. 8, 2024

Язык: Английский

Процитировано

11
Cell Storage Conditions Impact Single-Cell Proteomic Landscapes DOI Creative Commons
Bora Onat, Amanda Momenzadeh,

Ali Haghani

и другие.

Journal of Proteome Research, Год журнала: 2025, Номер unknown

Опубликована: Янв. 24, 2025

Single cell transcriptomics (SCT) has revolutionized our understanding of cellular heterogeneity, yet the emergence single proteomics (SCP) promises a more functional view dynamics. A challenge is that not all mass spectrometry facilities can perform SCP, and laboratories have access to sorting equipment required for which together motivate an interest in sending bulk samples through mail SCP analysis. Shipping requires storage, unknown effect on results. This study investigates impact storage conditions proteomic landscape at level, utilizing Data-Independent Acquisition (DIA) coupled with Parallel Accumulation Serial Fragmentation (diaPASEF). Three were compared 293T cells: (1) 37 °C (control), (2) 4 overnight, (3) −196 followed by liquid nitrogen preservation. Both cold frozen induced significant alterations diameter, elongation, proteome composition. By elucidating how alter morphology profiles, this contributes foundational technical information about sample preparation data quality.

Язык: Английский

Процитировано

1