Single-Cell Proteomic and Transcriptomic Characterization of Drug-Resistant Prostate Cancer Cells Reveals Molecular Signatures Associated with Morphological Changes DOI
Jongmin Jacob Woo,

Michael Loycano,

Md Amanullah

et al.

Published: Oct. 28, 2024

Abstract This study delves into the proteomic intricacies of drug-resistant cells (DRCs) within prostate cancer, which are known for their pivotal roles in therapeutic resistance, relapse, and metastasis. Utilizing single-cell proteomics (SCP) with an optimized high-throughput Data Independent Acquisition (DIA) approach throughput 60 sample per day, we characterized landscape DRCs comparison to parental PC3 cells. DIA method allowed robust reproducible protein quantification at level, enabling identification over 1,300 proteins cell on average. Distinct sub-clusters DRC population were identified, closely linked variations size. The uncovered novel signatures, including regulation critical adhesion metabolic processes, as well upregulation surface transcription factors cancer progression. Furthermore, by integrating SCP RNA-seq (scRNA-seq) data, identified six upregulated ten downregulated genes consistently altered drug-treated across both scRNA-seq platforms. These findings underscore heterogeneity unique molecular providing valuable insights biological behavior potential targets.

Language: Английский

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

et al.

Nature Protocols, Journal Year: 2024, Volume and Issue: 19(12), P. 3750 - 3776

Published: Aug. 8, 2024

Language: Английский

Citations

11
Single-Cell Proteomic Characterization of Drug-Resistant Prostate Cancer Cells Reveals Molecular Signatures Associated with Morphological Changes DOI Creative Commons
Jongmin Jacob Woo, Michael A. Loycano,

Md Amanullah

et al.

Molecular & Cellular Proteomics, Journal Year: 2025, Volume and Issue: unknown, P. 100949 - 100949

Published: March 1, 2025

This study delves into the proteomic intricacies of drug-resistant cells (DRCs) within prostate cancer, which are known for their pivotal roles in therapeutic resistance, relapse, and metastasis. Utilizing single-cell proteomics (SCP) with an optimized high-throughput Data Independent Acquisition (DIA) approach throughput 60 sample per day, we characterized landscape DRCs comparison to parental PC3 cells. DIA method allowed robust reproducible protein quantification at level, enabling identification over 1,300 proteins cell on average. Distinct sub-clusters DRC population were identified, closely linked variations size. The uncovered novel signatures, including regulation critical adhesion metabolic processes, as well upregulation surface transcription factors cancer progression. Furthermore, by conducting RNA-seq (scRNA-seq) analysis, identified six upregulated ten downregulated genes consistently altered drug-treated across both SCP scRNA-seq platforms. These findings underscore heterogeneity unique molecular providing valuable insights biological behavior potential targets.

Language: Английский

Citations

1
Data-Independent Acquisition Shortens the Analytical Window of Single-Cell Proteomics to Fifteen Minutes in Capillary Electrophoresis Mass Spectrometry DOI
Bo‐Wen Shen, Leena R. Pade, Péter Nemes

et al.

Journal of Proteome Research, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 26, 2024

Separation in single-cell mass spectrometry (MS) improves molecular coverage and quantification; however, it also elongates measurements, thus limiting analytical throughput to study large populations of cells. Here, we advance the speed bottom-up proteomics by capillary electrophoresis (CE) high-resolution for proteomics. We adjust applied potential readily control duration electrophoresis. On HeLa proteome standard, shorter separation times curbed detection using data-dependent acquisition (DDA) but not data-independent (DIA) on an Orbitrap analyzer. This DIA method identified 1161 proteins vs 401 reference DDA within a 15 min effective from single HeLa-cell-equivalent (∼200 pg) digests. Label-free quantification found these exclusively DIA-identified lower domain concentration range, revealing sensitivity improvement. The approach significantly advanced reproducibility quantification, where ∼76% DIA-quantified had <20% coefficient variation ∼43% DDA. As proof principle, allowed us quantify 1242 subcellular niches single, neural-tissue fated cell live

Language: Английский

Citations

5
Trends in Mass Spectrometry-Based Single-Cell Proteomics DOI

Ximena Sanchez-Avila,

Raphaela Menezes de Oliveira, Siqi Huang

et al.

Analytical Chemistry, Journal Year: 2025, Volume and Issue: unknown

Published: March 16, 2025

InfoMetrics Analytical ChemistryASAPArticle CiteCitationCitation and abstractCitation referencesMore citation options ShareShare onFacebookXWeChatLinkedInRedditEmailBlueskyJump toExpandCollapse ReviewMarch 16, 2025Trends in Mass Spectrometry-Based Single-Cell ProteomicsClick to copy article linkArticle link copied!Ximena Sanchez-AvilaXimena Sanchez-AvilaDepartment of Chemistry Biochemistry, Brigham Young University, Provo, Utah 84602, United StatesMore by Ximena Sanchez-AvilaView BiographyRaphaela M. de OliveiraRaphaela OliveiraDepartment Raphaela OliveiraView BiographySiqi HuangSiqi HuangDepartment Siqi HuangView BiographyChao WangChao WangDepartment Chao WangView Biographyhttps://orcid.org/0009-0008-6197-2985Ryan T. Kelly*Ryan KellyDepartment States*Email: [email protected]More Ryan KellyView Biographyhttps://orcid.org/0000-0002-3339-4443Other Access OptionsAnalytical ChemistryCite this: Anal. Chem. 2025, XXXX, XXX, XXX-XXXClick citationCitation copied!https://pubs.acs.org/doi/10.1021/acs.analchem.5c00661https://doi.org/10.1021/acs.analchem.5c00661Published March 2025 Publication History Received 28 January 2025Accepted February 2025Revised 23 2025Published online 16 2025review-article© American Chemical SocietyRequest reuse permissionsACS Publications© SocietySubjectswhat are subjects Article automatically applied from the ACS Subject Taxonomy describe scientific concepts themes article. Cells Isolation spectrometry Peptides proteins Sample preparation Note: In lieu an abstract, this is article's first page. Read To access article, please review available below. Get instant Purchase for 48 hours. Check out below using your ID or as a guest. Restore my guest Recommended through Your Institution You may have institution. institution does not content. Add change let them know you'd like include access. Through Recommend Name Loading Institutional Login Options... Change Explore subscriptions institutions Log with if you previously purchased it member benefits. hours $48.00 cart Checkout Cited By Click section linkSection copied!This has yet been cited other publications.Download PDF e-AlertsGet e-AlertsAnalytical copied!https://doi.org/10.1021/acs.analchem.5c00661Published 2025© permissionsArticle Views6Altmetric-Citations-Learn about these metrics closeArticle Views COUNTER-compliant sum full text downloads since November 2008 (both HTML) across all individuals. These regularly updated reflect usage leading up last few days.Citations number articles citing calculated Crossref daily. Find more information counts.The Altmetric Attention Score quantitative measure attention that research received online. Clicking on donut icon will load page at altmetric.com additional details score social media presence given how calculated.Recommended Articles

Language: Английский

Citations

0
Single-cell proteomics of Arabidopsis leaf mesophyll identifies drought stress-related proteins DOI
James Fulcher, Pranav Dawar,

Vimal Kumar Balasubramanian

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: July 3, 2024

Abstract The application of single-cell omics tools to biological systems can provide unique insights into diverse cellular populations and their heterogeneous responses internal external perturbations. Thus far, most studies in plant have been limited RNA-sequencing approaches, which only indirect readouts functions. Here, we present a proteomics workflow for cells that integrates tape-sandwich protoplasting, piezoelectric cell sorting, nanoPOTS sample preparation, FAIMS-based MS data acquisition method label-free analysis Arabidopsis leaf mesophyll cells. From single protoplast, over 3,000 proteins were quantified with high precision. is demonstrated identify stress associated changes protein abundance by analyzing >80 protoplasts from well-watered water-deficit stressed plants. Additionally, describe new approach constructing covarying networks at the level demonstrate how covariation reveal previously unrecognized functions while also capturing stress-induced protein-protein dynamics. Highlights This study describes first scProteomics abiotic proteome regulation ∼2800 on average precision using label free leaves revealed known novel involved drought response Single-protoplast water deficit-induced independent

Language: Английский

Citations

3
The current economics and throughput of single cell proteomics by liquid chromatography mass spectrometry DOI Creative Commons
Amanda L. Smythers, Benjamin C. Orsburn

Published: June 11, 2024

Single cell proteomics by mass spectrometry (SCP) is an emerging field of study that has captured the interest and imagination biologists in a wide array disciplines. In pursuit this new dizzying technologies techniques have demonstrated ability to quantify hundreds few thousand proteins single mammalian cells typical size. One striking characteristic these methods range relative costs associated with analysis each cell. We attempted estimate cost per across 17 different studies based on quotes we obtained for hardware, reagents instrument support plans relation number can be analyzed day. Before including labor or facilities, find analyze size from less than <$2 over $50 The increase appears directly related decrease throughput as measured theoretical maximum Perhaps most surprising observation average year. This when compared emergence RNA sequencing where increased, cost/cell decreased exponentially first 7 years field’s emergence. While made many assumptions obtain estimates, hope will informative scientists interested obtaining SCP data spectrometrists who are considering entering field. provided spreadsheet simple calculator supplemental allow others adjust our calculations other variables which inevitably described future.

Language: Английский

Citations

2
DESP demixes cell-state profiles from dynamic bulk molecular measurements DOI Creative Commons
Ahmed Youssef, Indranil Paul, Mark Crovella

et al.

Cell Reports Methods, Journal Year: 2024, Volume and Issue: 4(3), P. 100729 - 100729

Published: March 1, 2024

Understanding the dynamic expression of proteins and other key molecules driving phenotypic remodeling in development pathobiology has garnered widespread interest, yet exploration these systems at foundational resolution underlying cell states been significantly limited by technical constraints. Here, we present DESP, an algorithm designed to leverage independent estimates cell-state proportions, such as from single-cell RNA sequencing, resolve relative contributions bulk molecular measurements, most notably quantitative proteomics, recorded parallel. We applied DESP vitro model epithelial-to-mesenchymal transition demonstrated its ability accurately reconstruct signatures bulk-level measurements both proteome transcriptome, providing insights into transient regulatory mechanisms. provides a generalizable computational framework for modeling relationship between enabling study proteomes profiles level using established workflows.

Language: Английский

Citations

0
Single-Cell Proteomic and Transcriptomic Characterization of Drug-Resistant Prostate Cancer Cells Reveals Molecular Signatures Associated with Morphological Changes DOI
Jongmin Jacob Woo,

Michael Loycano,

Md Amanullah

et al.

Published: Oct. 28, 2024

Abstract This study delves into the proteomic intricacies of drug-resistant cells (DRCs) within prostate cancer, which are known for their pivotal roles in therapeutic resistance, relapse, and metastasis. Utilizing single-cell proteomics (SCP) with an optimized high-throughput Data Independent Acquisition (DIA) approach throughput 60 sample per day, we characterized landscape DRCs comparison to parental PC3 cells. DIA method allowed robust reproducible protein quantification at level, enabling identification over 1,300 proteins cell on average. Distinct sub-clusters DRC population were identified, closely linked variations size. The uncovered novel signatures, including regulation critical adhesion metabolic processes, as well upregulation surface transcription factors cancer progression. Furthermore, by integrating SCP RNA-seq (scRNA-seq) data, identified six upregulated ten downregulated genes consistently altered drug-treated across both scRNA-seq platforms. These findings underscore heterogeneity unique molecular providing valuable insights biological behavior potential targets.

Language: Английский

Citations

0