Microproteomic sample preparation
Multiple applications of proteomics in life and health science, pathology and pharmacology, require handling size‐limited cell and tissue samples. During proteomic sample preparation, analyte loss in these samples arises when standard procedures are used. Thus, specific considerations have to be tak...
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Veröffentlicht in: | Proteomics (Weinheim) 2021-05, Vol.21 (9), p.e2000318-n/a |
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description | Multiple applications of proteomics in life and health science, pathology and pharmacology, require handling size‐limited cell and tissue samples. During proteomic sample preparation, analyte loss in these samples arises when standard procedures are used. Thus, specific considerations have to be taken into account for processing, that are summarised under the term microproteomics (μPs). Microproteomic workflows include: sampling (e.g., flow cytometry, laser capture microdissection), sample preparation (possible disruption of cells or tissue pieces via lysis, protein extraction, digestion in bottom‐up approaches, and sample clean‐up) and analysis (chromatographic or electrophoretic separation, mass spectrometric measurements and statistical/bioinformatic evaluation). All these steps must be optimised to reach wide protein dynamic ranges and high numbers of identifications. Under optimal conditions, sampling is adapted to the studied sample types and nature, sample preparation isolates and enriches the whole protein content, clean‐up removes salts and other interferences such as detergents or chaotropes, and analysis identifies as many analytes as the instrumental throughput and sensitivity allow. In the suggested review, we present and discuss the current state in μP applications for processing of small number of cells (cell μPs) and microscopic tissue regions (tissue μPs). |
doi_str_mv | 10.1002/pmic.202000318 |
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During proteomic sample preparation, analyte loss in these samples arises when standard procedures are used. Thus, specific considerations have to be taken into account for processing, that are summarised under the term microproteomics (μPs). Microproteomic workflows include: sampling (e.g., flow cytometry, laser capture microdissection), sample preparation (possible disruption of cells or tissue pieces via lysis, protein extraction, digestion in bottom‐up approaches, and sample clean‐up) and analysis (chromatographic or electrophoretic separation, mass spectrometric measurements and statistical/bioinformatic evaluation). All these steps must be optimised to reach wide protein dynamic ranges and high numbers of identifications. Under optimal conditions, sampling is adapted to the studied sample types and nature, sample preparation isolates and enriches the whole protein content, clean‐up removes salts and other interferences such as detergents or chaotropes, and analysis identifies as many analytes as the instrumental throughput and sensitivity allow. 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During proteomic sample preparation, analyte loss in these samples arises when standard procedures are used. Thus, specific considerations have to be taken into account for processing, that are summarised under the term microproteomics (μPs). Microproteomic workflows include: sampling (e.g., flow cytometry, laser capture microdissection), sample preparation (possible disruption of cells or tissue pieces via lysis, protein extraction, digestion in bottom‐up approaches, and sample clean‐up) and analysis (chromatographic or electrophoretic separation, mass spectrometric measurements and statistical/bioinformatic evaluation). All these steps must be optimised to reach wide protein dynamic ranges and high numbers of identifications. Under optimal conditions, sampling is adapted to the studied sample types and nature, sample preparation isolates and enriches the whole protein content, clean‐up removes salts and other interferences such as detergents or chaotropes, and analysis identifies as many analytes as the instrumental throughput and sensitivity allow. In the suggested review, we present and discuss the current state in μP applications for processing of small number of cells (cell μPs) and microscopic tissue regions (tissue μPs).</description><subject>bottom‐up approach</subject><subject>cell microproteomics</subject><subject>Cell size</subject><subject>Detergents</subject><subject>Flow cytometry</subject><subject>Lysis</subject><subject>mass spectrometry</subject><subject>microproteomics</subject><subject>Pharmacology</subject><subject>protein analysis</subject><subject>Proteins</subject><subject>Proteomics</subject><subject>Salts</subject><subject>Sample preparation</subject><subject>Sampling</subject><subject>Spectrometry</subject><subject>Statistical methods</subject><subject>tissue microproteomics</subject><subject>top‐down approach</subject><issn>1615-9853</issn><issn>1615-9861</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNqFkD1PwzAQhi0EoqWwMqIiFpaUsx1_ZEQVH5VawQCzdXFtKVXSBLsR6r_HVUsHFqa74blH772EXFOYUAD20DWVnTBgAMCpPiFDKqnICi3p6XEXfEAuYlwBUKULdU4GnItcaaGG5HZR2dB2od24NqnGEZuuduMuuA4Dbqp2fUnOPNbRXR3miHw-P31MX7P528ts-jjPLJcFZCi9yx0tc-cpSrDMM-1R88IBLhFyXCrrbSl1yTkClpYKjqVUuS41CO_5iNzvvSnMV-_ixjRVtK6uce3aPhqWa0WFAAkJvfuDrto-rFM6wwSjlBVcqERN9lR6MMbgvOlC1WDYGgpmV57ZlWeO5aWDm4O2Lxu3POK_bSVA7IHvqnbbf3TmfTGbUs418B8rg3np</recordid><startdate>202105</startdate><enddate>202105</enddate><creator>Alexovič, Michal</creator><creator>Sabo, Ján</creator><creator>Longuespée, Rémi</creator><general>Wiley Subscription Services, Inc</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>7QP</scope><scope>7TK</scope><scope>7TM</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>M7N</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-1618-1059</orcidid></search><sort><creationdate>202105</creationdate><title>Microproteomic sample preparation</title><author>Alexovič, Michal ; Sabo, Ján ; Longuespée, Rémi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3690-a6fe4e1b4ef1a60c2f28fa839e0ada04ad7cfcb68b33a0abc153ab6748b805ff3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>bottom‐up approach</topic><topic>cell microproteomics</topic><topic>Cell size</topic><topic>Detergents</topic><topic>Flow cytometry</topic><topic>Lysis</topic><topic>mass spectrometry</topic><topic>microproteomics</topic><topic>Pharmacology</topic><topic>protein analysis</topic><topic>Proteins</topic><topic>Proteomics</topic><topic>Salts</topic><topic>Sample preparation</topic><topic>Sampling</topic><topic>Spectrometry</topic><topic>Statistical methods</topic><topic>tissue microproteomics</topic><topic>top‐down approach</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Alexovič, Michal</creatorcontrib><creatorcontrib>Sabo, Ján</creatorcontrib><creatorcontrib>Longuespée, Rémi</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Proteomics (Weinheim)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Alexovič, Michal</au><au>Sabo, Ján</au><au>Longuespée, Rémi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Microproteomic sample preparation</atitle><jtitle>Proteomics (Weinheim)</jtitle><addtitle>Proteomics</addtitle><date>2021-05</date><risdate>2021</risdate><volume>21</volume><issue>9</issue><spage>e2000318</spage><epage>n/a</epage><pages>e2000318-n/a</pages><issn>1615-9853</issn><eissn>1615-9861</eissn><abstract>Multiple applications of proteomics in life and health science, pathology and pharmacology, require handling size‐limited cell and tissue samples. During proteomic sample preparation, analyte loss in these samples arises when standard procedures are used. Thus, specific considerations have to be taken into account for processing, that are summarised under the term microproteomics (μPs). Microproteomic workflows include: sampling (e.g., flow cytometry, laser capture microdissection), sample preparation (possible disruption of cells or tissue pieces via lysis, protein extraction, digestion in bottom‐up approaches, and sample clean‐up) and analysis (chromatographic or electrophoretic separation, mass spectrometric measurements and statistical/bioinformatic evaluation). All these steps must be optimised to reach wide protein dynamic ranges and high numbers of identifications. Under optimal conditions, sampling is adapted to the studied sample types and nature, sample preparation isolates and enriches the whole protein content, clean‐up removes salts and other interferences such as detergents or chaotropes, and analysis identifies as many analytes as the instrumental throughput and sensitivity allow. In the suggested review, we present and discuss the current state in μP applications for processing of small number of cells (cell μPs) and microscopic tissue regions (tissue μPs).</abstract><cop>Germany</cop><pub>Wiley Subscription Services, Inc</pub><pmid>33547857</pmid><doi>10.1002/pmic.202000318</doi><tpages>16</tpages><orcidid>https://orcid.org/0000-0002-1618-1059</orcidid></addata></record> |
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subjects | bottom‐up approach cell microproteomics Cell size Detergents Flow cytometry Lysis mass spectrometry microproteomics Pharmacology protein analysis Proteins Proteomics Salts Sample preparation Sampling Spectrometry Statistical methods tissue microproteomics top‐down approach |
title | Microproteomic sample preparation |
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