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. 2019 Jun:24:101222.
doi: 10.1016/j.redox.2019.101222. Epub 2019 May 17.

HDL subclass proteomic analysis and functional implication of protein dynamic change during HDL maturation

Yuling Zhang  1 , Scott M Gordon  2 , Hang Xi  3 , Seungbum Choi  3 , Merlin Abner Paz  3 , Runlu Sun  4 , William Yang  3 , Jason Saredy  3 , Mohsin Khan  3 , Alan Thomas Remaley  5 , Jing-Feng Wang  4 , Xiaofeng Yang  3 , Hong Wang  6
Affiliations

HDL subclass proteomic analysis and functional implication of protein dynamic change during HDL maturation

Yuling Zhang et al. Redox Biol. 2019 Jun.

Abstract

Recent clinical trials reported that increasing high-density lipoprotein-cholesterol (HDL-C) levels does not improve cardiovascular outcomes. We hypothesize that HDL proteome dynamics determine HDL cardioprotective functions. In this study, we characterized proteome profiles in HDL subclasses and established their functional connection. Mouse plasma was fractionized by fast protein liquid chromatography, examined for protein, cholesterial, phospholipid and trigliceride content. Small, medium and large (S/M/L)-HDL subclasseses were collected for proteomic analysis by mass spectrometry. Fifty-one HDL proteins (39 in S-HDL, 27 in M-HDL and 29 in L-HDL) were identified and grouped into 4 functional categories (lipid metabolism, immune response, coagulation, and others). Eleven HDL common proteins were identified in all HDL subclasses. Sixteen, 3 and 7 proteins were found only in S-HDL, M-HDL and L-HDL, respectively. We established HDL protein dynamic distribution in S/M/L-HDL and developed a model of protein composition change during HDL maturation. We found that cholesterol efflux and immune response are essential functions for all HDL particles, and amino acid metabolism is a special function of S-HDL, whereas anti-coagulation is special for M-HDL. Pon1 is recruited into M/L-HDL to provide its antioxidative function. ApoE is incorporated into L-HDL to optimize its cholesterial clearance function. Next, we acquired HDL proteome data from Pubmed and identified 12 replicated proteins in human and mouse HDL particle. Finally, we extracted 3 shared top moleccular pathways (LXR/RXR, FXR/RXR and acute phase response) for all HDL particles and 5 top disease/bio-functions differentially related to S/M/L-HDL subclasses, and presented one top net works for each HDL subclass. We conclude that beside their essencial functions of cholesterol efflux and immune response, HDL aquired antioxidative and cholesterol clearance functions by recruiting Pon1 and ApoE during HDL maturation.

Keywords: Cardiovascular disease; Lipids and cholesterol; Metabolism; Proteomics; Risk factors.

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Figures

Fig. 1
Fig. 1
Lipoprotein profile and L/M/S-HDL subclass characterization of mouse plasma. Blood was collected from male C57BL/6J mice at 14–16 weeks of age. Pooled plasma from 3 mice was applied to a ÄKTA FPLC system for lipoprotein fractionation. Forty-eight fractions were collected and further assessed for phospholipid, cholesterol, and triglyceride concentrations using biochemical kits from Wako. Protein content was quantified by the absorbance at OD280. Fractions 10 to 15 were determined as VLDL by the peak of triglyceride, 16 to 22 as LDL by the peak of protein, 25 to 36 as HDL by the peak of phospholipid, 37 to 45 as albumin. Fractions 25 to 28 were pooled as large-HDL particles (L-HDL), 29 to 32 as medium-HDL (M-HDL), and 33 to 36 as small-HDL (S-HDL). (A) Model of lipoprotein fractionation and lipid/protein analysis (FPLC-MS). (B) Protein. (C) Phospholipid. (D) Total cholesterol. (E) Triglyceride. Protein, phospholipid, total cholesterol and triglyceride profiles were established by biochemical assessment in 48 fractions. (F) HDL protein. Protein concentrations of pooled L/M/S-HDL fractions were assessed by BCA assay. (G) HDL phospholipid. (H) HDL total cholesterol. (I) HDL triglyceride. Phospholipid, total cholesterol and triglyceride content of pooled L/M/S-HDL fractions were assessed and normalized by HDL protein concentration. HDL, high density lipoprotein; LDL, low density lipoprotein; VLDL, very low density lipoprotein. BCA, bicinchoninic acid. *p < 0.05 compared with L-HDL, #p < 0.05 compared with M-HDL.
Fig. 2
Fig. 2
Identification of protein overlaps in mouse HDL subclasses. Pooled mouse plasma was fractionated using an ÄKTA FPLC system. Large, medium, small HDL subclasses were collected as described in Fig. 1 and subjected to proteomic analysis using a Qstar XL-MS system. 51 proteins were identified in HDL particles and abbreviated according to Genecards website. (A) Heat map of relative protein abundance in HDL particles. Relative abundance of each identified protein in HDL particles were described by peptide count, determined by MS. A value of 1.0 was assigned to the highest peptide count of the specific protein in three S/M/L-HDL subclasses. Peptide counts for other proteins were scaled accordingly. The highest values are colored red and gradually changed to yellow for the lower values. Green indicates no peptide was identified in that particular HDL fraction. (B) Protein overlaps in HDL particle; Venn-diagram describes the presence of identified protein in HDL particles (39 in S-HDL, 27 in M-HDL, and 29 in L-HDL). 11 proteins overlap in all S/M/L-HDL fractions and are listed as common HDL proteins. (C) Fold-change of protein peptide counts in L-HDL; Fold change of each protein in L-HDL was calculated with dividing its peptide count in L-HDL by that in S-HDL. Positive numbers describe the fold changes of increased proteins in L-HDL. Negative numbers describe the fold changes of decreased proteins derived from dividing negative one (−1) by the fold value. Infinity symbol “∞” indicates protein present in L-HDL but absent in S-HDL., whereas, “-∞” indicates protein absent in L-HDL but present in S-HDL. Protein name abbreviation are explained in Table 1A. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 3
Fig. 3
Dynamic protein distribution in mouse HDL subclasses by biological function groups and model of protein composition change during HDL biosynthesis/maturation. HDL fractions (S/M/L) were collected from FPLC purification as described in Fig. 1. Proteins in each HDL fraction were identified by Qstar XL-MS analysis as describing in Fig. 2. Relative abundance of each identified protein in HDL particles were described by peptide count, determined by MS. A value of 1.0 was assigned to the highest peptide count of the specific protein in three S/M/L-HDL fractions. Identified HDL proteins were grouped by the biological function as describing in Table 1 and classified as increased and decreased groups. Protein dynamic changes are presented as relative peptide count curves. (A) Lipid metabolism. (B) Immune response; B1, Complement proteins, B2, Inflammatory protein, B3, Immunoglobin proteins. (C) Coagulation proteins. (D) Other types. (E) Model of protein composition change during HDL biosynthesis/maturation. Flow chat describes transition points when HDL proteins join or departure from HDL subgroups during HDL biosynthesis/maturation. Protein names highlighted in red are those emphasized in the session of discussion. Protein name abbreviation are explained in Table 1A. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 4
Fig. 4
Identification of replicated proteins in human and mouse HDL. Reported HDL proteomics data was acquired from PubMed database. 14 human and 2 mouse HDL proteomics data were reported (from 2010 to 2015, details in Supplement Table 2), which were compared to our mouse HDL proteome. (A) Identification of replicated HDL protein. HDL proteins were presented by number of reported/publication times. 94 replicated human HDL proteins (published ≥ 2 times among 275 reported human HDL proteins), 72 replicated mouse HDL proteins (published ≥ 2 times among 111 reported mouse HDL proteins or replicated with our data) are presented. 12 replicated HDL proteins are identified (replicated ≥ 3 times in human and mouse proteomics) and framed in dash line. (B) Strategy for the identification of 12 replicated HDL proteins. (C) Dynamic distribution of 12 replicated HDL proteins; Relative abundance of each identified protein in HDL particles were described by relative peptide count determined by MS. A value of 1.0 was assigned to the highest peptide count in three S/M/L-HDL subclasses. Protein dynamic changes are expressed as peptide count curves. Identified HDL proteins were classified as increased, decreased and steadily expressed groups. Protein name abbreviation are explained in Table 1A. Standard abbreviations of HDL proteins were obtained from public databases (Genecards and Uniprot).
Fig. 5
Fig. 5
Identification of Ingenuity pathways & disease/bio-functions of HDL proteins and significance comparison (IPA software). 51 HDL proteins were identified by FPLC purification and MS analysis as described in Fig. 1 and Table 1. The abbreviation and Uniprot ID of these HDL proteins were obtained from public databases (Genecards and Uniprot) and used for the identification of Ingenuity pathways and disease/bio-functions (www.ingenuity.com). (A) Strategy for pathway & function analysis of HDL proteins. (B) Top 3 ingenuity pathways of S/M/L-HDL proteins. (C) Top 5 disease/bio-functions of S/M/L HDL proteins. The top 3 Ingenuity canonical pathways and top 5 disease/bio-functions of L/M/S-HDL particles were identified. The significance of identified pathways and disease/bio-functions were evaluated by p-value which describes the significance of individual pathway over others in each HDL fraction. Overlaps describe the numbers and percentage of identified HDL proteins in the previously identified pathway proteins. (D) Heat map of significance comparison of ingenuity pathways. (E) Heat map of significance comparison of disease/bio-functions. The significance comparison of Ingenuity pathways and disease/bio-functions between three HDL fractions was calculated as P value using IPA software and presented in the heat map. Blue color represents the highest significance (the smallest p value) of the identified pathway among three HDL fractions. White color represents the lowest significance (the largest p value) among three fractions. Abbreviations: AD, Alzheimer's disease; defi., deficiency; HSC, hematopoiesis; MΦ, macrophage; NO, nitric oxide; R, Receptor; ROS, reactive oxygen species; SC, stem cell; TC, targeted cell, T1DM, type 1 diabetes mellitus. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 6
Fig. 6
Network identification of HDL proteins (IPA software). (A) Strategy of network identification. 51 HDL proteins (39 in S-HDL, 27 in M-HDL, and 29 in L-HDL) were identified in mouse plasma by FPLC purification and MS analysis as describing in Fig. 1 and Table 1 and used for network analyzing by IPA software (www.ingenuity.com). Predicted networks and score are calculated using IPA algorithm. Each connection represents known relationships between the molecules found in the Ingenuity knowledge base. (B) Top 3 networks for each HDL population. The top 3 scored networks and their associated diseases/bio-functions of L/M/S-HDL are presented. (C) Molecular property of network proteins. (D) S-HDL top network. (E) M-HDL top network. (F). L-HDL top network. The highest scored networks for S/M/L-HDL subclasses are presented. Blue lines indicate direct interactions of 2 molecules. Green lines indicate indirect interactions. The symbols describe the property of the molecules and explained in C. Abbreviations for identified HDL proteins are explained in Table 1A. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
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