Single-Probe Mass Spectrometry Analysis of Metabolites in Single Cells

2019 ◽  
pp. 61-71 ◽  
Author(s):  
Ning Pan ◽  
Wei Rao ◽  
Zhibo Yang
Keyword(s):  
Mass Spectrometry ◽  
Single Cells ◽  
Mass Spectrometry Analysis ◽  
Spectrometry Analysis ◽  
Single Probe

scholarly journals Single-cell lipidomics with high structural specificity by mass spectrometry

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Zishuai Li ◽  
Simin Cheng ◽  
Qiaohong Lin ◽  
Wenbo Cao ◽  
Jing Yang ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Single Cell ◽  
Cancer Cells ◽  
Single Cell Analysis ◽  
Single Cells ◽  
Mass Spectrometry Analysis ◽  
Human Lung Cancer ◽  
Cell Analysis ◽  
Structural Specificity ◽  
Spectrometry Analysis

AbstractSingle-cell analysis is critical to revealing cell-to-cell heterogeneity that would otherwise be lost in ensemble analysis. Detailed lipidome characterization for single cells is still far from mature, especially when considering the highly complex structural diversity of lipids and the limited sample amounts available from a single cell. We report the development of a general strategy enabling single-cell lipidomic analysis with high structural specificity. Cell fixation is applied to retain lipids in the cell during batch treatments prior to single-cell analysis. In addition to tandem mass spectrometry analysis revealing the class and fatty acyl-chain for lipids, batch photochemical derivatization and single-cell droplet treatment are performed to identify the C=C locations and sn-positions of lipids, respectively. Electro-migration combined with droplet-assisted electrospray ionization enables single-cell mass spectrometry analysis with easy operation but high efficiency in sample usage. Four subtypes of human breast cancer cells are correctly classified through quantitative analysis of lipid C=C location or sn-position isomers in ~160 cells. Most importantly, the single-cell deep lipidomics strategy successfully discriminates gefitinib-resistant cells from a population of wild-type human lung cancer cells (HCC827), highlighting its unique capability to promote precision medicine.

scholarly journals Tip Enhanced Laser Ablation Sample Transfer for Mass Spectrometry

2015 ◽  
Vol 1754 ◽  
pp. 87-95 ◽  
Author(s):  
Kermit K. Murray ◽  
Suman Ghorai ◽  
Chinthaka A. Seneviratne
Keyword(s):  
Mass Spectrometry ◽  
Laser Ablation ◽  
Spatial Resolution ◽  
Single Cells ◽  
Sample Surface ◽  
Mass Spectrometry Analysis ◽  
Full Potential ◽  
Primary Analysis ◽  
Spectrometry Analysis ◽  
Sample Transfer

ABSTRACTMass spectrometry is one of the primary analysis techniques for biological analysis but there are technological barriers in sampling scale that must be overcome for it to be used to its full potential on the size scale of single cells. Current mass spectrometry imaging methods are limited in spatial resolution when analyzing large biomolecules. The goal of this project is to use atomic force microscope (AFM) tip enhanced laser ablation to remove material from cells and tissue and capture it for subsequent mass spectrometry analysis. The laser ablation sample transfer system uses an AFM stage to hold the metal-coated tip at a distance of approximately 10 nm from a sample surface. The metal tip acts as an antenna for the electromagnetic radiation and enables the ablation of the sample with a spot size much smaller than a laser focused with a conventional lens system. A pulsed nanosecond UV or visible wavelength laser is focused onto the gold-coated silicon tip at an angle nearly parallel with the surface, which results in the removal of material from a spot between 500 nm and 1 µm in diameter and 200 and 500 nm deep. This corresponds to a few picograms of ablated material, which can be captured on a metal surface for MALDI analysis. We have used this approach to transfer small peptides and proteins from a thin film for analysis by mass spectrometry as a first step toward high spatial resolution imaging.

The Single-Probe: A Miniaturized Multifunctional Device for Single Cell Mass Spectrometry Analysis

2014 ◽  
Vol 86 (19) ◽  
pp. 9376-9380 ◽  
Author(s):  
Ning Pan ◽  
Wei Rao ◽  
Naga Rama Kothapalli ◽  
Renmeng Liu ◽  
Anthony W. G. Burgett ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Single Cell ◽  
Cell Mass ◽  
Mass Spectrometry Analysis ◽  
Spectrometry Analysis ◽  
Single Probe ◽  
Multifunctional Device ◽  
Cell Mass Spectrometry

scholarly journals DART-ID increases single-cell proteome coverage

2018 ◽  
Author(s):  
Albert T. Chen ◽  
Alexander Franks ◽  
Nikolai Slavov
Keyword(s):  
Mass Spectrometry ◽  
Liquid Chromatography ◽  
Single Cell ◽  
Retention Time ◽  
Mammalian Cells ◽  
Statistical Power ◽  
Single Cells ◽  
Peptide Sequence ◽  
Mass Spectrometry Analysis ◽  
Spectrometry Analysis

AbstractAnalysis by liquid chromatography and tandem mass spectrometry (LC-MS/MS) can identify and quantify thousands of proteins in microgram-level samples, such as those comprised of thousands of cells. This process, however, remains challenging for smaller samples, such as the proteomes of single mammalian cells, because reduced protein levels reduce the number of confidently sequenced peptides. To alleviate this reduction, we developed Data-driven Alignment of Retention Times for IDentification (DART-ID). DART-ID implements principled Bayesian frameworks for global retention time (RT) alignment and for incorporating RT estimates towards improved confidence estimates of peptide-spectrum-matches. When applied to bulk or to single-cell samples, DART-ID increased the number of data points by 30 – 50% at 1% FDR, and thus decreased missing data. Benchmarks indicate excellent quantification of peptides upgraded by DART-ID and support their utility for quantitative analysis, such as identifying cell types and cell-type specific proteins. The additional datapoints provided by DART-ID boost the statistical power and double the number of proteins identified as differentially abundant in monocytes and T-cells. DART-ID can be applied to diverse experimental designs and is freely available at http://github.com/SlavovLab/DART-ID.Author SummaryIdentifying and quantifying proteins in single cells gives researchers the ability to tackle complex biological problems that involve single cell heterogeneity, such as the treatment of solid tumors. Mass spectrometry analysis of peptides can identify their sequence from their masses and the masses of their fragment ion, but often times these pieces of evidence are insufficient for a confident peptide identification. This problem is exacerbated when analyzing lowly abundant samples such as single cells. To identify even peptides with weak mass spectra, DART-ID incorporates their retention time – the time when they elute from the liquid chromatography used to physically separate them. We present both a novel method of aligning the retention times of peptides across experiments, as well as a rigorous framework for using the estimated retention times to enhance peptide sequence identification. Incorporating the retention time as additional evidence leads to a substantial increase in the number of samples in which proteins are confidently identified and quantified.

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