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Single-Cell Proteomics with Spatial Attributes: Tools and Techniques

[Image: see text] Now-a-days, the single-cell proteomics (SCP) concept is attracting interest, especially in clinical research, because it can identify the proteomic signature specific to diseased cells. This information is very essential when dealing with the progression of certain diseases, such a...

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Autores principales: Lohani, Vartika, A.R, Akhiya, Kundu, Soumen, Akhter, MD Quasid, Bag, Swarnendu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2023
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10210017/
https://www.ncbi.nlm.nih.gov/pubmed/37251119
http://dx.doi.org/10.1021/acsomega.3c00795
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author Lohani, Vartika
A.R, Akhiya
Kundu, Soumen
Akhter, MD Quasid
Bag, Swarnendu
author_facet Lohani, Vartika
A.R, Akhiya
Kundu, Soumen
Akhter, MD Quasid
Bag, Swarnendu
author_sort Lohani, Vartika
collection PubMed
description [Image: see text] Now-a-days, the single-cell proteomics (SCP) concept is attracting interest, especially in clinical research, because it can identify the proteomic signature specific to diseased cells. This information is very essential when dealing with the progression of certain diseases, such as cancer, diabetes, Alzheimer’s, etc. One of the major drawbacks of conventional destructive proteomics is that it gives an average idea about the protein expression profile in the disease condition. During the extraction of the protein from a biopsy or blood sample, proteins may come from both diseased cells and adjacent normal cells or any other cells from the disease environment. Again, SCP along with spatial attributes is utilized to learn about the heterogeneous function of a single protein. Before performing SCP, it is necessary to isolate single cells. This can be done by various techniques, including fluorescence-activated cell sorting (FACS), magnetic-activated cell sorting (MACS), laser capture microdissection (LCM), microfluidics, manual cell picking/micromanipulation, etc. Among the different approaches for proteomics, mass spectrometry-based proteomics tools are widely used for their high resolution as well as sensitivity. This Review mainly focuses on the mass spectrometry-based approaches for the study of single-cell proteomics.
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spelling pubmed-102100172023-05-26 Single-Cell Proteomics with Spatial Attributes: Tools and Techniques Lohani, Vartika A.R, Akhiya Kundu, Soumen Akhter, MD Quasid Bag, Swarnendu ACS Omega [Image: see text] Now-a-days, the single-cell proteomics (SCP) concept is attracting interest, especially in clinical research, because it can identify the proteomic signature specific to diseased cells. This information is very essential when dealing with the progression of certain diseases, such as cancer, diabetes, Alzheimer’s, etc. One of the major drawbacks of conventional destructive proteomics is that it gives an average idea about the protein expression profile in the disease condition. During the extraction of the protein from a biopsy or blood sample, proteins may come from both diseased cells and adjacent normal cells or any other cells from the disease environment. Again, SCP along with spatial attributes is utilized to learn about the heterogeneous function of a single protein. Before performing SCP, it is necessary to isolate single cells. This can be done by various techniques, including fluorescence-activated cell sorting (FACS), magnetic-activated cell sorting (MACS), laser capture microdissection (LCM), microfluidics, manual cell picking/micromanipulation, etc. Among the different approaches for proteomics, mass spectrometry-based proteomics tools are widely used for their high resolution as well as sensitivity. This Review mainly focuses on the mass spectrometry-based approaches for the study of single-cell proteomics. American Chemical Society 2023-05-09 /pmc/articles/PMC10210017/ /pubmed/37251119 http://dx.doi.org/10.1021/acsomega.3c00795 Text en © 2023 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Lohani, Vartika
A.R, Akhiya
Kundu, Soumen
Akhter, MD Quasid
Bag, Swarnendu
Single-Cell Proteomics with Spatial Attributes: Tools and Techniques
title Single-Cell Proteomics with Spatial Attributes: Tools and Techniques
title_full Single-Cell Proteomics with Spatial Attributes: Tools and Techniques
title_fullStr Single-Cell Proteomics with Spatial Attributes: Tools and Techniques
title_full_unstemmed Single-Cell Proteomics with Spatial Attributes: Tools and Techniques
title_short Single-Cell Proteomics with Spatial Attributes: Tools and Techniques
title_sort single-cell proteomics with spatial attributes: tools and techniques
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10210017/
https://www.ncbi.nlm.nih.gov/pubmed/37251119
http://dx.doi.org/10.1021/acsomega.3c00795
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