Proteomics: a tool to investigate of composition and function of HDL in hyperlipidemia
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Tipo de documento: | Tese |
Idioma: | eng |
Título da fonte: | Biblioteca Digital de Teses e Dissertações da USP |
Texto Completo: | https://www.teses.usp.br/teses/disponiveis/46/46131/tde-26082022-123137/ |
Resumo: | The inverse relationship between HDL-C (high-density lipoprotein cholesterol) and cardiovascular disease is well established. However, it is consensus that the cholesterol content present in HDL does not capture its complexity, and other metrics need to be explored. HDL is a heterogeneous, protein-enriched particle with functions going beyond lipid metabolism. In this way, its protein content seems to be attractive to investigate its behavior in the face of pathologies. Many of the proteins with important function in HDL are in low abundance (<1% of total proteins), which makes their detection challenging. Quantitative proteomics allows detecting proteins with high precision and robustness in complex matrix. However, quantitative proteomics is still poorly explored in the context of HDL. In this sense, in the second chapter of this thesis, the analytical performance of two quantitative methodologies was carefully investigated. These methods achieved adequate linearity and high precision using labeled peptides in a pool HDL, in addition to comparable ability to differentiate proteins from HDL subclasses of healthy subjects. Another bottleneck that waits for a solution in proteomics is the lack of standardization in data processing and analysis after mass spectrometry acquisition. In addition, interest in the cardioprotective properties of omega-3 is growing, but little is known about its effects on the HDL proteome. Thus, in the third chapter of this thesis, we compared five protein quantification strategies using Skyline and MaxDIA software platforms in order to investigate the HDL proteome from mice submitted to a high-fat diet supplemented or not with omega-3. MaxDIA with label-free quantification (MaxLFQ) achieved high precision to show that polyunsaturated fatty acids remodel the HDL proteome to a less inflammatory profile. Therefore, the two studies presented in this thesis begin to open new paths for a deeper and more reliable understanding of HDL, both at the level of protein quantification by mass spectrometry and after data acquisition. |
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Proteomics: a tool to investigate of composition and function of HDL in hyperlipidemiaProteômica: uma ferramenta para a investigação da composição e função da HDL em hiperlipidemiaDieta rica em gordura saturadaHDLHDL. Quantitative proteomics. Omega-3. High-fat diet. Hyperlipidemia.HiperlipidemiaÔmega-3Proteômica quantitativaThe inverse relationship between HDL-C (high-density lipoprotein cholesterol) and cardiovascular disease is well established. However, it is consensus that the cholesterol content present in HDL does not capture its complexity, and other metrics need to be explored. HDL is a heterogeneous, protein-enriched particle with functions going beyond lipid metabolism. In this way, its protein content seems to be attractive to investigate its behavior in the face of pathologies. Many of the proteins with important function in HDL are in low abundance (<1% of total proteins), which makes their detection challenging. Quantitative proteomics allows detecting proteins with high precision and robustness in complex matrix. However, quantitative proteomics is still poorly explored in the context of HDL. In this sense, in the second chapter of this thesis, the analytical performance of two quantitative methodologies was carefully investigated. These methods achieved adequate linearity and high precision using labeled peptides in a pool HDL, in addition to comparable ability to differentiate proteins from HDL subclasses of healthy subjects. Another bottleneck that waits for a solution in proteomics is the lack of standardization in data processing and analysis after mass spectrometry acquisition. In addition, interest in the cardioprotective properties of omega-3 is growing, but little is known about its effects on the HDL proteome. Thus, in the third chapter of this thesis, we compared five protein quantification strategies using Skyline and MaxDIA software platforms in order to investigate the HDL proteome from mice submitted to a high-fat diet supplemented or not with omega-3. MaxDIA with label-free quantification (MaxLFQ) achieved high precision to show that polyunsaturated fatty acids remodel the HDL proteome to a less inflammatory profile. Therefore, the two studies presented in this thesis begin to open new paths for a deeper and more reliable understanding of HDL, both at the level of protein quantification by mass spectrometry and after data acquisition.A inversa relação entre HDL-C (do inglês, high-density lipoprotein cholesterol) e doenças cardiovasculares é bem estabelecida. No entanto, é consenso que o conteúdo de colesterol presente na HDL não captura sua complexidade, e outras métricas precisam ser exploradas. A HDL é uma partícula heterogênea, enriquecida em proteínas, com funções que vão além do metabolismo de lipídeos. Dessa forma, seu conteúdo proteico parece ser mais atrativo para exprimir seu comportamento frente às patologias. Muitas das proteínas com função importante estão em baixa abundância (<1% do total de proteínas), o que torna a detecção desafiadora. Métodos quantitativos de proteômica permitem detectar proteínas com alta precisão e robustez em matrizes complexas. No entanto, a proteômica quantitativa ainda é pouco explorada no contexto da HDL. Nesse sentido, no segundo capítulo dessa tese, a performance analítica de dois métodos quantitativos foi criteriosamente investigada, os quais alcançaram adequada linearidade e alta precisão usando peptídeos marcados em um pool de HDL, além de comparável habilidade em diferenciar as proteínas das subclasses da HDL de indivíduos saudáveis. Outro gargalo que aguarda por solução em proteômica é a falta de padronização no processamento e análise de dados após a aquisição por espectrometria de massas. Além disso, é crescente o interesse das propriedades cardioprotetivas do ômega-3, porém pouco se conhece sobre seus efeitos no proteoma da HDL. Então, no terceiro capítulo dessa tese, comparamos cinco estratégias de quantificação de proteínas utilizando os softwares Skyline e MaxDIA com o intuito de comparar o proteoma da HDL de camundongos submetidos a uma dieta hiperlipídica suplementados ou não com ômega-3. MaxDIA com quantificação label-free (MaxLFQ) apresentou alta precisão para mostrar que o ômega-3 remodela o proteoma da HDL para um perfil menos inflamatório. Portanto, os dois estudos apresentados nessa tesa começam a abrir novos caminhos para o entendimento mais profundo e confiável da HDL tanto por meio da quantificação das proteínas por espectrometria de massas quanto após à aquisição dos dados.Biblioteca Digitais de Teses e Dissertações da USPRonsein, Graziella ElizaSilva, Amanda Ribeiro Martins da2022-07-08info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfhttps://www.teses.usp.br/teses/disponiveis/46/46131/tde-26082022-123137/reponame:Biblioteca Digital de Teses e Dissertações da USPinstname:Universidade de São Paulo (USP)instacron:USPLiberar o conteúdo para acesso público.info:eu-repo/semantics/openAccesseng2022-09-01T18:02:11Zoai:teses.usp.br:tde-26082022-123137Biblioteca Digital de Teses e Dissertaçõeshttp://www.teses.usp.br/PUBhttp://www.teses.usp.br/cgi-bin/mtd2br.plvirginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.bropendoar:27212022-09-01T18:02:11Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
Proteomics: a tool to investigate of composition and function of HDL in hyperlipidemia Proteômica: uma ferramenta para a investigação da composição e função da HDL em hiperlipidemia |
title |
Proteomics: a tool to investigate of composition and function of HDL in hyperlipidemia |
spellingShingle |
Proteomics: a tool to investigate of composition and function of HDL in hyperlipidemia Silva, Amanda Ribeiro Martins da Dieta rica em gordura saturada HDL HDL. Quantitative proteomics. Omega-3. High-fat diet. Hyperlipidemia. Hiperlipidemia Ômega-3 Proteômica quantitativa |
title_short |
Proteomics: a tool to investigate of composition and function of HDL in hyperlipidemia |
title_full |
Proteomics: a tool to investigate of composition and function of HDL in hyperlipidemia |
title_fullStr |
Proteomics: a tool to investigate of composition and function of HDL in hyperlipidemia |
title_full_unstemmed |
Proteomics: a tool to investigate of composition and function of HDL in hyperlipidemia |
title_sort |
Proteomics: a tool to investigate of composition and function of HDL in hyperlipidemia |
author |
Silva, Amanda Ribeiro Martins da |
author_facet |
Silva, Amanda Ribeiro Martins da |
author_role |
author |
dc.contributor.none.fl_str_mv |
Ronsein, Graziella Eliza |
dc.contributor.author.fl_str_mv |
Silva, Amanda Ribeiro Martins da |
dc.subject.por.fl_str_mv |
Dieta rica em gordura saturada HDL HDL. Quantitative proteomics. Omega-3. High-fat diet. Hyperlipidemia. Hiperlipidemia Ômega-3 Proteômica quantitativa |
topic |
Dieta rica em gordura saturada HDL HDL. Quantitative proteomics. Omega-3. High-fat diet. Hyperlipidemia. Hiperlipidemia Ômega-3 Proteômica quantitativa |
description |
The inverse relationship between HDL-C (high-density lipoprotein cholesterol) and cardiovascular disease is well established. However, it is consensus that the cholesterol content present in HDL does not capture its complexity, and other metrics need to be explored. HDL is a heterogeneous, protein-enriched particle with functions going beyond lipid metabolism. In this way, its protein content seems to be attractive to investigate its behavior in the face of pathologies. Many of the proteins with important function in HDL are in low abundance (<1% of total proteins), which makes their detection challenging. Quantitative proteomics allows detecting proteins with high precision and robustness in complex matrix. However, quantitative proteomics is still poorly explored in the context of HDL. In this sense, in the second chapter of this thesis, the analytical performance of two quantitative methodologies was carefully investigated. These methods achieved adequate linearity and high precision using labeled peptides in a pool HDL, in addition to comparable ability to differentiate proteins from HDL subclasses of healthy subjects. Another bottleneck that waits for a solution in proteomics is the lack of standardization in data processing and analysis after mass spectrometry acquisition. In addition, interest in the cardioprotective properties of omega-3 is growing, but little is known about its effects on the HDL proteome. Thus, in the third chapter of this thesis, we compared five protein quantification strategies using Skyline and MaxDIA software platforms in order to investigate the HDL proteome from mice submitted to a high-fat diet supplemented or not with omega-3. MaxDIA with label-free quantification (MaxLFQ) achieved high precision to show that polyunsaturated fatty acids remodel the HDL proteome to a less inflammatory profile. Therefore, the two studies presented in this thesis begin to open new paths for a deeper and more reliable understanding of HDL, both at the level of protein quantification by mass spectrometry and after data acquisition. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-07-08 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
format |
doctoralThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://www.teses.usp.br/teses/disponiveis/46/46131/tde-26082022-123137/ |
url |
https://www.teses.usp.br/teses/disponiveis/46/46131/tde-26082022-123137/ |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
|
dc.rights.driver.fl_str_mv |
Liberar o conteúdo para acesso público. info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Liberar o conteúdo para acesso público. |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.coverage.none.fl_str_mv |
|
dc.publisher.none.fl_str_mv |
Biblioteca Digitais de Teses e Dissertações da USP |
publisher.none.fl_str_mv |
Biblioteca Digitais de Teses e Dissertações da USP |
dc.source.none.fl_str_mv |
reponame:Biblioteca Digital de Teses e Dissertações da USP instname:Universidade de São Paulo (USP) instacron:USP |
instname_str |
Universidade de São Paulo (USP) |
instacron_str |
USP |
institution |
USP |
reponame_str |
Biblioteca Digital de Teses e Dissertações da USP |
collection |
Biblioteca Digital de Teses e Dissertações da USP |
repository.name.fl_str_mv |
Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP) |
repository.mail.fl_str_mv |
virginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.br |
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1815257400466210816 |