Single-Cell Mass Spectrometry Analysis of Metabolites Facilitated by Cell Electro-Migration and Electroporation

Li, Zishuai; Wang, Zhengmao; Pan, Junmin; Ma, Xiaoxiao; Zhang, Wenpeng; Ouyang, Zheng

doi:10.1021/acs.analchem.0c02147

Cited by 40 publications

(29 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Cell fixation, cell manipulation, and collective derivatization. An efficient method for cell manipulation and subsequent MS analysis based on electro-migration and electroporation was previously developed for analyzing cells with cell walls, including fungus, algae, and protozoa 48 . However, to extend this method for mammalian cells, isotonic buffer (e.g., phosphate-buffered saline, PBS) needs to be used to prevent the lysis of the cell membrane, which is incompatible with electrospray ionization.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Single-cell lipidomics with high structural specificity by mass spectrometry

et al. 2021

Self Cite

View full text Add to dashboard Cite

Single-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.

show abstract

Section: Resultsmentioning

confidence: 99%

“…Single-cell MS analysis. Previously, we have developed method for manipulating and analyzing single cells using electromigration 48 . Using a modified method, individual cell could be sent to a capillary tip and multi-round sampling of the cell could be performed for MS or MS/MS data acquisition.…”

Section: Resultsmentioning

confidence: 99%

Single-cell lipidomics with high structural specificity by mass spectrometry

et al. 2021

Self Cite

View full text Add to dashboard Cite

show abstract

“…Methods for label-free, single-cell analysis of proteins, and metabolites from microbes are limited. Singlecell MS has been used to measure in the region of 25 intracellular metabolites from up to a thousand single cells from microbial cultures (Ibanez et al, 2013;Walker et al, 2013;Krismer et al, 2017;Li Z. et al, 2020). To our knowledge, only few methods for unlabeled single-cell proteomics of microorganisms exist in literature.…”

Section: Discussion Of Single-cell Technologies For the Study Of Adapmentioning

confidence: 99%

Single-Cell Technologies to Understand the Mechanisms of Cellular Adaptation in Chemostats

Wright

Rønnest

Sonnenschein

2020

Front. Bioeng. Biotechnol.

View full text Add to dashboard Cite

There is a growing interest in continuous manufacturing within the bioprocessing community. In this context, the chemostat process is an important unit operation. The current application of chemostat processes in industry is limited although many high yielding processes are reported in literature. In order to reach the full potential of the chemostat in continuous manufacture, the output should be constant. However, adaptation is often observed resulting in changed productivities over time. The observed adaptation can be coupled to the selective pressure of the nutrient-limited environment in the chemostat. We argue that population heterogeneity should be taken into account when studying adaptation in the chemostat. We propose to investigate adaptation at the single-cell level and discuss the potential of different single-cell technologies, which could be used to increase the understanding of the phenomena. Currently, none of the discussed single-cell technologies fulfill all our criteria but in combination they may reveal important information, which can be used to understand and potentially control the adaptation.

show abstract

“…However, refinements in the current single cell isolation techniques, mass spectrometry (MS) and high-throughput microfluidic-based methods have led to the detection of a limited number of metabolites present in the cell ( Comi et al, 2017 ; Zhang and Vertes, 2018 ; Duncan et al, 2019 ; He et al, 2020 ). These methods include electrospray ionization mass spectrometry (ESI-MS) ( Huang et al, 2020 ; Li et al, 2020 ), matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) ( Shanta et al, 2020 )and secondary ion mass spectrometry (SIMS) ( Leo et al, 2019 ). Coupled with separation-based methods, MS is the most sensitive method for detecting a wide range of metabolites in a single cell.…”

Section: An Overview Of Single-cell Omics Technologiesmentioning

confidence: 99%

Computational Methods for Single-Cell Imaging and Omics Data Integration

Watson

Fard

Mar

2022

Front. Mol. Biosci.

View full text Add to dashboard Cite

Integrating single cell omics and single cell imaging allows for a more effective characterisation of the underlying mechanisms that drive a phenotype at the tissue level, creating a comprehensive profile at the cellular level. Although the use of imaging data is well established in biomedical research, its primary application has been to observe phenotypes at the tissue or organ level, often using medical imaging techniques such as MRI, CT, and PET. These imaging technologies complement omics-based data in biomedical research because they are helpful for identifying associations between genotype and phenotype, along with functional changes occurring at the tissue level. Single cell imaging can act as an intermediary between these levels. Meanwhile new technologies continue to arrive that can be used to interrogate the genome of single cells and its related omics datasets. As these two areas, single cell imaging and single cell omics, each advance independently with the development of novel techniques, the opportunity to integrate these data types becomes more and more attractive. This review outlines some of the technologies and methods currently available for generating, processing, and analysing single-cell omics- and imaging data, and how they could be integrated to further our understanding of complex biological phenomena like ageing. We include an emphasis on machine learning algorithms because of their ability to identify complex patterns in large multidimensional data.

show abstract

Single-Cell Mass Spectrometry Analysis of Metabolites Facilitated by Cell Electro-Migration and Electroporation

Cited by 40 publications

References 50 publications

Single-cell lipidomics with high structural specificity by mass spectrometry

Single-cell lipidomics with high structural specificity by mass spectrometry

Single-Cell Technologies to Understand the Mechanisms of Cellular Adaptation in Chemostats

Computational Methods for Single-Cell Imaging and Omics Data Integration

Contact Info

Product

Resources

About