Strategies for consistent and automated quantification of HDL proteome using data-independent acquisition

Author(s)

Souza Junior, Douglas Ricardo ; Silva, Amanda Ribeiro Martins ; Ronsein, Graziella Eliza

• Document type: Journal article
• Source: Journal of Lipid Research; v. 64, n. 7, p. 14-pg., 2023-07-03.

Abstract

The introduction of mass spectrometrybased 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, 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. (AU)

• FAPESP's process: 17/07725-1 - Proteomics: a tool to investigate the composition and function of HDL in hyperlipidemia
• Grantee: Amanda Ribeiro Martins da Silva
• Support Opportunities: Scholarships in Brazil - Doctorate
• FAPESP's process: 16/00696-3 - Proteomic as a tool to understand HDL function and composition
• Grantee: Graziella Eliza Ronsein
• Support Opportunities: Research Grants - Young Investigators Grants
• FAPESP's process: 13/07937-8 - Redoxome - Redox Processes in Biomedicine
• Grantee: Ohara Augusto
• Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC
• FAPESP's process: 19/25702-4 - Understanding the effects of high density lipoprotein on human macrophages
• Grantee: Douglas Ricardo de Souza Junior
• Support Opportunities: Scholarships in Brazil - Doctorate (Direct)