Strategies for consistent and automated quantification of HDL proteome using data-independent acquisition
The introduction of mass spectrometry-based proteomics has revolutionized the high-density lipoprotein (HDL) field, with the description, characterization, and implication of HDL-associated proteins in an array of pathologies. However, acquiring robust, reproducible data is still a challenge in the...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-07-01
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| Series: | Journal of Lipid Research |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0022227523000706 |
| _version_ | 1797776271665528832 |
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| author | Douglas Ricardo Souza Junior Amanda Ribeiro Martins Silva Graziella Eliza Ronsein |
| author_facet | Douglas Ricardo Souza Junior Amanda Ribeiro Martins Silva Graziella Eliza Ronsein |
| author_sort | Douglas Ricardo Souza Junior |
| collection | DOAJ |
| description | The introduction of mass spectrometry-based proteomics has revolutionized the high-density lipoprotein (HDL) field, with the description, characterization, and implication of HDL-associated proteins in an array of pathologies. However, acquiring robust, reproducible data is still a challenge in the quantitative assessment of HDL proteome. Data-independent acquisition (DIA) is a mass spectrometry methodology that allows the acquisition of reproducible data, but data analysis remains a challenge in the field. To date, there is no consensus on how to process DIA-derived data for HDL proteomics. Here, we developed a pipeline aiming to standardize HDL proteome quantification. We optimized instrument parameters and compared the performance of four freely available, user-friendly software tools (DIA-NN, EncyclopeDIA, MaxDIA, and Skyline) in processing DIA data. Importantly, pooled samples were used as quality controls throughout our experimental setup. A careful evaluation of precision, linearity, and detection limits, first using E. coli background for HDL proteomics and second using HDL proteome and synthetic peptides, was undertaken. Finally, as a proof of concept, we employed our optimized and automated pipeline to quantify the proteome of HDL and apolipoprotein B–containing lipoproteins. Our results show that determination of precision is key to confidently and consistently quantifying HDL proteins. Taking this precaution, any of the available software tested here would be appropriate for quantification of HDL proteome, although their performance varied considerably. |
| first_indexed | 2024-03-12T22:47:24Z |
| format | Article |
| id | doaj.art-a0eb0caff1244db0b1ec7374d2accadc |
| institution | Directory Open Access Journal |
| issn | 0022-2275 |
| language | English |
| last_indexed | 2024-03-12T22:47:24Z |
| publishDate | 2023-07-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Lipid Research |
| spelling | doaj.art-a0eb0caff1244db0b1ec7374d2accadc2023-07-21T04:57:38ZengElsevierJournal of Lipid Research0022-22752023-07-01647100397Strategies for consistent and automated quantification of HDL proteome using data-independent acquisitionDouglas Ricardo Souza Junior0Amanda Ribeiro Martins Silva1Graziella Eliza Ronsein2Department of Biochemistry, Institute of Chemistry, University of São Paulo, São Paulo, BrazilDepartment of Biochemistry, Institute of Chemistry, University of São Paulo, São Paulo, BrazilFor correspondence: Graziella Eliza Ronsein; Department of Biochemistry, Institute of Chemistry, University of São Paulo, São Paulo, BrazilThe introduction of mass spectrometry-based proteomics has revolutionized the high-density lipoprotein (HDL) field, with the description, characterization, and implication of HDL-associated proteins in an array of pathologies. However, acquiring robust, reproducible data is still a challenge in the quantitative assessment of HDL proteome. Data-independent acquisition (DIA) is a mass spectrometry methodology that allows the acquisition of reproducible data, but data analysis remains a challenge in the field. To date, there is no consensus on how to process DIA-derived data for HDL proteomics. Here, we developed a pipeline aiming to standardize HDL proteome quantification. We optimized instrument parameters and compared the performance of four freely available, user-friendly software tools (DIA-NN, EncyclopeDIA, MaxDIA, and Skyline) in processing DIA data. Importantly, pooled samples were used as quality controls throughout our experimental setup. A careful evaluation of precision, linearity, and detection limits, first using E. coli background for HDL proteomics and second using HDL proteome and synthetic peptides, was undertaken. Finally, as a proof of concept, we employed our optimized and automated pipeline to quantify the proteome of HDL and apolipoprotein B–containing lipoproteins. Our results show that determination of precision is key to confidently and consistently quantifying HDL proteins. Taking this precaution, any of the available software tested here would be appropriate for quantification of HDL proteome, although their performance varied considerably.http://www.sciencedirect.com/science/article/pii/S0022227523000706apolipoproteinsdata-independent acquisitionhigh-density lipoproteinHDLlipoproteinsproteomics |
| spellingShingle | Douglas Ricardo Souza Junior Amanda Ribeiro Martins Silva Graziella Eliza Ronsein Strategies for consistent and automated quantification of HDL proteome using data-independent acquisition Journal of Lipid Research apolipoproteins data-independent acquisition high-density lipoprotein HDL lipoproteins proteomics |
| title | Strategies for consistent and automated quantification of HDL proteome using data-independent acquisition |
| title_full | Strategies for consistent and automated quantification of HDL proteome using data-independent acquisition |
| title_fullStr | Strategies for consistent and automated quantification of HDL proteome using data-independent acquisition |
| title_full_unstemmed | Strategies for consistent and automated quantification of HDL proteome using data-independent acquisition |
| title_short | Strategies for consistent and automated quantification of HDL proteome using data-independent acquisition |
| title_sort | strategies for consistent and automated quantification of hdl proteome using data independent acquisition |
| topic | apolipoproteins data-independent acquisition high-density lipoprotein HDL lipoproteins proteomics |
| url | http://www.sciencedirect.com/science/article/pii/S0022227523000706 |
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