scholarly journals Robust, sensitive, and quantitative single-cell proteomics based on ion mobility filtering

2021 ◽  
Author(s):  
Jongmin Woo ◽  
Geremy C. Clair ◽  
Sarah M. Williams ◽  
Song Feng ◽  
Chia-Feng Tsai ◽  
...  
Keyword(s):  
Single Cell ◽  
Ion Mobility ◽  
Proteome Analysis ◽  
Quantitative Information ◽  
Label Free ◽  
Temporal Response ◽  
Human Organ ◽  
Overall Performance ◽  
Antibody Labeling ◽  
Acquisition Method

AbstractUnbiased single-cell proteomics (scProteomics) promises to advance our understanding of the cellular composition of complex biological systems. However, a major challenge for current methods is their ability to identify and provide accurate quantitative information for low abundance proteins. Herein, we describe an ion mobility-enhanced mass spectrometry acquisition method, TIFF (Transferring Identification based on FAIMS Filtering), designed to improve the sensitivity and accuracy of label-free scProteomics. The TIFF method enabled unbiased proteome analysis to a depth of >1,700 proteins in single HeLa cells with >1,100 proteins consistently quantified, a significant improvement in overall performance. We applied the TIFF method to obtain temporal proteome profiles of >150 single murine macrophage cells during a lipopolysaccharide stimulation experiment and uncovered unanticipated temporal response trajectories. Further, we demonstrated, to our knowledge, the first application of scProteomics to classify cell populations of a human organ (the lung) without prior antibody labeling.

scholarly journals Label-Free and Quantitative Dry Mass Monitoring for Single Cells during In Situ Culture

Cells ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1635
Author(s):  
Ya Su ◽  
Rongxin Fu ◽  
Wenli Du ◽  
Han Yang ◽  
Li Ma ◽  
...  
Keyword(s):  
Cell Growth ◽  
Single Cell ◽  
Hela Cells ◽  
Quantitative Measurement ◽  
Single Cells ◽  
Dry Mass ◽  
Quantitative Detection ◽  
Label Free ◽  
Mass Sensitivity

Quantitative measurement of single cells can provide in-depth information about cell morphology and metabolism. However, current live-cell imaging techniques have a lack of quantitative detection ability. Herein, we proposed a label-free and quantitative multichannel wide-field interferometric imaging (MWII) technique with femtogram dry mass sensitivity to monitor single-cell metabolism long-term in situ culture. We demonstrated that MWII could reveal the intrinsic status of cells despite fluctuating culture conditions with 3.48 nm optical path difference sensitivity, 0.97 fg dry mass sensitivity and 2.4% average maximum relative change (maximum change/average) in dry mass. Utilizing the MWII system, different intrinsic cell growth characteristics of dry mass between HeLa cells and Human Cervical Epithelial Cells (HCerEpiC) were studied. The dry mass of HeLa cells consistently increased before the M phase, whereas that of HCerEpiC increased and then decreased. The maximum growth rate of HeLa cells was 11.7% higher than that of HCerEpiC. Furthermore, HeLa cells were treated with Gemcitabine to reveal the relationship between single-cell heterogeneity and chemotherapeutic efficacy. The results show that cells with higher nuclear dry mass and nuclear density standard deviations were more likely to survive the chemotherapy. In conclusion, MWII was presented as a technique for single-cell dry mass quantitative measurement, which had significant potential applications for cell growth dynamics research, cell subtype analysis, cell health characterization, medication guidance and adjuvant drug development.

scholarly journals 56P Single circulating tumor cells RNA profiling by label-free enrichment and active single cell selection on an integrated fluidic system

2016 ◽  
Vol 27 ◽  
pp. ix15-ix16
Author(s):  
Y.F. Lee ◽  
N. Ramalingam ◽  
L. Szpankowski ◽  
A. Leyrat ◽  
N.D. Angeles ◽  
...  
Keyword(s):  
Single Cell ◽  
Tumor Cells ◽  
Circulating Tumor Cells ◽  
Cell Selection ◽  
Label Free ◽  
Rna Profiling ◽  
Free Enrichment

Non-invasive and label-free identification of human natural killer subclasses by biophysical single-cell features in microfluidic flow

Lab on a Chip ◽  
2021 ◽  
Author(s):  
David Dannhauser ◽  
Domenico Rossi ◽  
Anna T Palatucci ◽  
Valentina Rubino ◽  
Flavia Carriero ◽  
...  
Keyword(s):  
Single Cell ◽  
Natural Killer ◽  
Label Free ◽  
Therapeutic Treatment ◽  
Non Invasive ◽  
Microfluidic Flow

Natural Killer (NK) are indicated as favorite candidates for innovative therapeutic treatment and are divided in two subclasses: immature regulatory NK CD56bright and mature cytotoxic NK CD56dim. Therefore, the ability...

scholarly journals Quantifying single-cell secretion in real time using resonant hyperspectral imaging

2018 ◽  
Vol 115 (52) ◽  
pp. 13204-13209 ◽  
Author(s):  
José Juan-Colás ◽  
Ian S. Hitchcock ◽  
Mark Coles ◽  
Steven Johnson ◽  
Thomas F. Krauss
Keyword(s):  
Single Cell ◽  
Real Time ◽  
Protein Secretion ◽  
Cell Communication ◽  
Label Free ◽  
Cell Secretion ◽  
Physiological Disorder ◽  
Real Time Analysis ◽  
Technology Heterogeneity

Cell communication is primarily regulated by secreted proteins, whose inhomogeneous secretion often indicates physiological disorder. Parallel monitoring of innate protein-secretion kinetics from individual cells is thus crucial to unravel systemic malfunctions. Here, we report a label-free, high-throughput method for parallel, in vitro, and real-time analysis of specific single-cell signaling using hyperspectral photonic crystal resonant technology. Heterogeneity in physiological thrombopoietin expression from individual HepG2 liver cells in response to platelet desialylation was quantified demonstrating how mapping real-time protein secretion can provide a simple, yet powerful approach for studying complex physiological systems regulating protein production at single-cell resolution.

scholarly journals Coarse Raman and optical diffraction tomographic imaging enable label-free phenotyping of isogenic breast cancer cells of varying metastatic potential

2020 ◽  
Author(s):  
Santosh Kumar Paidi ◽  
Vaani Shah ◽  
Piyush Raj ◽  
Kristine Glunde ◽  
Rishikesh Pandey ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Raman Spectroscopy ◽  
Molecular Imaging ◽  
Single Cell ◽  
Cancer Cells ◽  
Breast Cancer Cells ◽  
Metastatic Potential ◽  
Optical Diffraction ◽  
Multivariate Curve Resolution ◽  
Label Free

AbstractIdentification of the metastatic potential represents one of the most important tasks for molecular imaging of cancer. While molecular imaging of metastases has witnessed substantial progress as an area of clinical inquiry, determining precisely what differentiates the metastatic phenotype has proven to be more elusive underscoring the need to marry emerging imaging techniques with tumor biology. In this study, we utilize both the morphological and molecular information provided by 3D optical diffraction tomography and Raman spectroscopy, respectively, to propose a label-free route for optical phenotyping of cancer cells at single-cell resolution. By using an isogenic panel of cell lines derived from MDA-MB-231 breast cancer cells that vary in their metastatic potential, we show that 3D refractive index tomograms can capture subtle morphological differences among the parental, circulating tumor cells, and lung metastatic cells. By leveraging the molecular specificity of Raman spectroscopy, we demonstrate that coarse Raman microscopy is capable of rapidly mapping a sufficient number of cells for training a random forest classifier that can accurately predict the metastatic potential of cells at a single-cell level. We also leverage multivariate curve resolution – alternating least squares decomposition of the spectral dataset to demarcate spectra from cytoplasm and nucleus, and test the feasibility of identifying metastatic phenotypes using the spectra only from the cytoplasmic and nuclear regions. Overall, our study provides a rationale for employing coarse Raman mapping to substantially reduce measurement time thereby enabling the acquisition of reasonably large training datasets that hold the key for label-free single-cell analysis and, consequently, for differentiation of indolent from aggressive phenotypes.

scholarly journals Label-Free Discrimination of Rhizobial Bacteroids and Mutants by Single-Cell Raman Microspectroscopy

2017 ◽  
Vol 89 (12) ◽  
pp. 6336-6340 ◽  
Author(s):  
Jiabao Xu ◽  
Isabel Webb ◽  
Philip Poole ◽  
Wei E. Huang
Keyword(s):  
Single Cell ◽  
Raman Microspectroscopy ◽  
Label Free
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