scholarly journals High-throughput quantitation of inorganic nanoparticle biodistribution at the single-cell level using mass cytometry

2017 ◽  
Vol 8 (1) ◽  
Author(s):  
Yu-Sang Sabrina Yang ◽  
Prabhani U. Atukorale ◽  
Kelly D. Moynihan ◽  
Ahmet Bekdemir ◽  
Kavya Rakhra ◽  
...  
Keyword(s):  
Single Cell ◽  
Drug Carriers ◽  
Inorganic Nanoparticles ◽  
Single Cell Level ◽  
Label Free ◽  
Mass Cytometry ◽  
Cell Level ◽  
Myeloid Dendritic Cells ◽  
Inorganic Nanoparticle

Abstract Inorganic nanoparticles (NPs) are studied as drug carriers, radiosensitizers and imaging agents, and characterizing nanoparticle biodistribution is essential for evaluating their efficacy and safety. Tracking NPs at the single-cell level with current technologies is complicated by the lack of reliable methods to stably label particles over extended durations in vivo. Here we demonstrate that mass cytometry by time-of-flight provides a label-free approach for inorganic nanoparticle quantitation in cells. Furthermore, mass cytometry can enumerate AuNPs with a lower detection limit of ∼10 AuNPs (3 nm core size) in a single cell with tandem multiparameter cellular phenotyping. Using the cellular distribution insights, we selected an amphiphilic surface ligand-coated AuNP that targeted myeloid dendritic cells in lymph nodes as a peptide antigen carrier, substantially increasing the efficacy of a model vaccine in a B16-OVA melanoma mouse model. This technology provides a powerful new level of insight into nanoparticle fate in vivo.

scholarly journals Erratum: High-throughput quantitation of inorganic nanoparticle biodistribution at the single-cell level using mass cytometry

2017 ◽  
Vol 8 (1) ◽  
Author(s):  
Yu-Sang Sabrina Yang ◽  
Prabhani U Atukorale ◽  
Kelly D. Moynihan ◽  
Ahmet Bekdemir ◽  
Kavya Rakhra ◽  
...  
Keyword(s):  
Single Cell ◽  
High Throughput ◽  
Single Cell Level ◽  
Mass Cytometry ◽  
Cell Level ◽  
Inorganic Nanoparticle

Label-Free Cancer Stem-like Cell Assay Conducted at a Single Cell Level Using Microfluidic Mechanotyping Devices

2021 ◽  
Author(s):  
Miyu Terada ◽  
Sachiko Ide ◽  
Toyohiro Naito ◽  
Niko Kimura ◽  
Michiya Matsusaki ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Cell Level ◽  
Label Free ◽  
Cell Level ◽  
Cell Assay

scholarly journals CyTOFmerge: integrating mass cytometry data across multiple panels

2019 ◽  
Vol 35 (20) ◽  
pp. 4063-4071 ◽  
Author(s):  
Tamim Abdelaal ◽  
Thomas Höllt ◽  
Vincent van Unen ◽  
Boudewijn P F Lelieveldt ◽  
Frits Koning ◽  
...  
Keyword(s):  
Single Cell ◽  
Biological Sample ◽  
Supplementary Information ◽  
High Dimensional ◽  
Single Cell Level ◽  
Supplementary Data ◽  
Mass Cytometry ◽  
Cell Level ◽  
Cellular Markers

Abstract Motivation High-dimensional mass cytometry (CyTOF) allows the simultaneous measurement of multiple cellular markers at single-cell level, providing a comprehensive view of cell compositions. However, the power of CyTOF to explore the full heterogeneity of a biological sample at the single-cell level is currently limited by the number of markers measured simultaneously on a single panel. Results To extend the number of markers per cell, we propose an in silico method to integrate CyTOF datasets measured using multiple panels that share a set of markers. Additionally, we present an approach to select the most informative markers from an existing CyTOF dataset to be used as a shared marker set between panels. We demonstrate the feasibility of our methods by evaluating the quality of clustering and neighborhood preservation of the integrated dataset, on two public CyTOF datasets. We illustrate that by computationally extending the number of markers we can further untangle the heterogeneity of mass cytometry data, including rare cell-population detection. Availability and implementation Implementation is available on GitHub (https://github.com/tabdelaal/CyTOFmerge). Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals High-resolution label-free 3D mapping of extracellular pH of single living cells

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Yanjun Zhang ◽  
Yasufumi Takahashi ◽  
Sung Pil Hong ◽  
Fengjie Liu ◽  
Joanna Bednarska ◽  
...  
Keyword(s):  
Single Cell ◽  
Cancer Cells ◽  
Extracellular Ph ◽  
Single Cell Level ◽  
Ph Sensing ◽  
Label Free ◽  
Cell Level ◽  
Spatiotemporal Resolution ◽  
Ion Conductance ◽  
Scanning Ion Conductance Microscopy

AbstractDynamic mapping of extracellular pH (pHe) at the single-cell level is critical for understanding the role of H+ in cellular and subcellular processes, with particular importance in cancer. While several pHe sensing techniques have been developed, accessing this information at the single-cell level requires improvement in sensitivity, spatial and temporal resolution. We report on a zwitterionic label-free pH nanoprobe that addresses these long-standing challenges. The probe has a sensitivity > 0.01 units, 2 ms response time, and 50 nm spatial resolution. The platform was integrated into a double-barrel nanoprobe combining pH sensing with feedback-controlled distance dependance via Scanning Ion Conductance Microscopy. This allows for the simultaneous 3D topographical imaging and pHe monitoring of living cancer cells. These classes of nanoprobes were used for real-time high spatiotemporal resolution pHe mapping at the subcellular level and revealed tumour heterogeneity of the peri-cellular environments of melanoma and breast cancer cells.

scholarly journals A Mass-Ratiometry-Based CD45 Barcoding Method for Mass Cytometry Detection

2019 ◽  
Vol 24 (4) ◽  
pp. 408-419
Author(s):  
Hongu Meng ◽  
Antony Warden ◽  
Lulu Zhang ◽  
Ting Zhang ◽  
Yiyang Li ◽  
...  
Keyword(s):  
Data Acquisition ◽  
Sample Size ◽  
Single Cell ◽  
Large Sample Size ◽  
Single Cell Level ◽  
Mass Cytometry ◽  
Cell Level ◽  
Large Sample ◽  
Antibody Staining ◽  
Instrument Sensitivity

Mass cytometry (CyTOF) is a critical cell profiling tool in acquiring multiparameter proteome data at the single-cell level. A major challenge in CyTOF analysis is sample-to-sample variance arising from the pipetting process, staining variation, and instrument sensitivity. To reduce such variations, cell barcoding strategies that enable the combination of individual samples prior to antibody staining and data acquisition on CyTOF are often utilized. The most prevalent barcoding strategy is based on a binary scheme that cross-examines the existence or nonexistence of certain mass signals; however, it is limited by low barcoding efficiency and high cost, especially for large sample size. Herein, we present a novel barcoding method for CyTOF application based on mass ratiometry. Different mass tags with specific fixed ratios are used to label CD45 antibody to achieve sample barcoding. The presented method exponentially increases the number of possible barcoded samples with the same amount of mass tags compared with conventional methods. It also reduces the overall time for the labeling process to 40 min and avoids the need for expensive commercial barcoding buffer reagents. Moreover, unlike the conventional barcoding process, this strategy does not pre-permeabilize cells before the barcoding procedure, which offers additional benefits in preserving surface biomarker signals.

Alterations of Raman profiles of nasopharyngeal carcinoma cells after treated with chemodrugs detected by laser tweezer Raman spectroscopy.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e15513-e15513
Author(s):  
Miaomiao Li ◽  
Xiaochuan Chen ◽  
Ting Lin ◽  
Zongwei Huang ◽  
Shihong Wu ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Nasopharyngeal Carcinoma ◽  
Single Cell ◽  
Control Group ◽  
Single Cell Level ◽  
Label Free ◽  
Cell Level ◽  
Analytical Strategy ◽  
Linear Discriminant ◽  
Laser Tweezer

e15513 Background: To explore the metabolic alterations of nasopharyngeal carcinoma (NPC) cells after treated with chemodrugs, the Raman profiles were characterized with laser tweezer Raman spectroscopy. Methods: Two NPC cell lines (CNE2 and C666-1) were treated with gemcitabine, cisplatin, and paclitaxel, respectively. The high-quality Raman spectra of cells without or with treatments were recorded at the single-cell level with label-free laser tweezers Raman spectroscopy (LTRS) and analyzed for the differences of alterations of Raman profiles. Results: Tentative assignments of Raman peaks indicated that the cellular specific biomolecular changes associated with drug treatment, including changes in protein structure (e.g. 1655 cm−1), changes in DNA content and structure (e.g. 830 cm−1), destruction of DNA base pairs (e.g. 785 cm−1), and reduction in lipids (e.g. 970 cm−1). Besides, both principal components analysis (PCA) combined with linear discriminant analysis (LDA) and the classification and regression trees (CRT) algorithms were employed to further analyze and classify the spectral data between control group and treated group, with the best discriminant accuracy of 96.7% and 90.0% for CNE2 and C666-1 group treated with paclitaxel, respectively. Conclusions: This exploratory work demonstrated that LTRS technology combined with multivariate statistical analysis has promising potential to be a novel analytical strategy at the single-cell level for the evaluation of NPC-related chemotherapeutic drugs.

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