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Research Article

Proteomic analysis of monolayer-integrated proteins on lipid droplets identifies amphipathic interfacial α-helical membrane anchors

Camille I. Pataki, João Rodrigues, Lichao Zhang, Junyang Qian, Bradley Efron, View ORCID ProfileTrevor Hastie, Joshua E. Elias, Michael Levitt, and Ron R. Kopito
PNAS August 28, 2018 115 (35) E8172-E8180; first published August 13, 2018; https://doi.org/10.1073/pnas.1807981115
Camille I. Pataki
aDepartment of Biochemistry, Stanford University, Stanford, CA 94305;
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João Rodrigues
bDepartment of Structural Biology, Stanford University, Stanford, CA 94305;
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Lichao Zhang
cDepartment of Chemical and Systems Biology, Stanford University, Stanford, CA 94305;
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Junyang Qian
dDepartment of Statistics, Stanford University, Stanford, CA 94305;
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Bradley Efron
dDepartment of Statistics, Stanford University, Stanford, CA 94305;
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Trevor Hastie
dDepartment of Statistics, Stanford University, Stanford, CA 94305;
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  • ORCID record for Trevor Hastie
Joshua E. Elias
cDepartment of Chemical and Systems Biology, Stanford University, Stanford, CA 94305;
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Michael Levitt
bDepartment of Structural Biology, Stanford University, Stanford, CA 94305;
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Ron R. Kopito
eDepartment of Biology, Stanford University, Stanford, CA 94305
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  • For correspondence: kopito@stanford.edu
  1. Edited by Jennifer Lippincott-Schwartz, Howard Hughes Medical Institute, Ashburn, VA, and approved July 23, 2018 (received for review May 9, 2018)

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    Fig. 1.

    Chaotrope extraction and TMT proteomics used to distinguish MIPs from peripheral proteins. (A) Chaotrope treatment workflow. Purified LDs were incubated with chaotrope or detergent and repurified sucrose gradient centrifugation. Proteins extracted from the LD monolayer membrane remain in the heavy fractions while proteins anchored to the monolayer membrane float with repurified LDs. (B) MIPs are retained on LD membranes after chaotrope-treatment. Repurified LDs were analyzed by SDS/PAGE and immunoblotting with the indicated antibodies. Immunoblots from a single experiment, representative of n = 5 replicates (VCP, UBXD8, ATGL, CGI-58) or n = 2 (AUP1, PLIN2), are shown. Individual lanes were loaded based on equivalent triacylglycerol content. (C) Proteomic and data-processing workflow. Chaotrope-treated repurified LDs were subjected to TMT–based quantitative proteomics. The signals derived from the TMTs were normalized to the signals from reference MIPs characterized in B. Subsequent mixture modeling and Bayesian-based calculations were used to determine FDR values for every protein identified in all three biological replicates. (D) Nonnormalized relative abundances distinguish MIPs from peripheral proteins. Average of nonnormalized relative abundances from one biological replicate of all peptides for each indicated protein are shown. Technical duplicates were summed. (E) MIP relative abundances are at approximately equal proportions following normalization. Average of normalized relative abundances of all peptides for each indicated protein is shown. Technical duplicates were summed. (F) Ternary plot data visualization. Ternary plots have axes representing each of the three conditions. Shown is data from a single TMT experiment. Each protein is represented by a single point (gray dot) associated with three abundance values. The four validated reference MIPs have the same relative abundance in all conditions and are in the center of the plot (red symbols). VCP (blue square) is highly abundant in buffer and scarce following alkaline carbonate or high-salt extraction. CGI-58 (black dot) is abundant following buffer and high-salt extraction but at very low abundance after alkaline carbonate treatment.

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    Fig. 2.

    Bioinformatics analysis of candidate MIPs. (A) Proteins that fall below 1% FDR cut-off are candidate MIPs. The 87 proteins below 1% FDR are classified into one of four indicated groups that describe features that confer chaotrope-resistance. Classifications are based on annotations from Uniprot consortium and SPOCTOPUS (Dataset S1). (B) Pie chart representing proportions of MIPs classified as having lipid anchors, predicted HMDs, a combination of both, or neither (other). (C) Pie chart representing proportions of HMD-containing MIPs classified as TMD, reentrant loops (RL), signal peptides, or a combination of signal peptides with TMDs or RLs. SPOCTOPUS was used to distinguish between TMDs, RLs, and signal peptides.

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    Fig. 3.

    N-terminal predicted TMD of DHRS3 is necessary and sufficient for targeting to LD. (A) Schematic diagram of DHRS3-GFP deletion constructs. The location of the two predicted TMDs (pTMD) is indicated. (B) Oleate-treated HEK cells expressing the indicated DHRS3 fusion constructs (A) were separated into LD, cytosol (C), and membrane (M) fractions. Representative immunoblots of these fractions probed with the indicated antibodies are shown. Blot shown is representative of at least two replicates for each construct. (C) Chaotrope-resistant integration of DHRS3(1–60) and DHRS3(1–28) fusions into LD. Purified LDs (input) were treated with alkaline carbonate and repurified on a second sucrose gradient and analyzed by immunoblotting, as in Fig. 1. Representative immunoblots (n = 3) with the indicated antibodies are shown.

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    Fig. 4.

    The N-terminal predicted TMD of DHRS3 forms a partially buried amphipathic α-helix. (A) Relative mPEG reactivity of systematic single cysteine-mutants of DHRS3(1–60) GFP. Each point represents mean ± SD from n = 3 independent experiments. Green and orange labels identify exposed and buried residues, respectively. “Periodic,” “gradual increase,” and “max reactivity” describe the reactivity pattern of the indicated region. (B) DHRS3(1–26) modeled onto a helical wheel and color-coded green for exposed residues and orange for buried, as in A. (C) DHRS3(1–35) modeled onto a peptide with green and orange spheres indicating exposed and buried residues, respectively. Residues 27–35 are shown in gray ribbon.

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    Fig. 5.

    MD simulations predict DHRS3 N terminus to be at membrane-solvent interface. (A) Schematic of the steered simulation for calculating the PMF of a peptide at various depths of a bilayer membrane. An α-helical peptide was placed in the middle of a bilayer membrane and a force (F) applied in the positive (Z) direction. During the simulation, the peptide was not allowed to tilt, but was allowed to rotate. (B) Graph of the PMF measurements for DHRS3(1–26) as it is pulled from the middle of the membrane toward bulk solvent. The black vertical line denotes the minimum PMF force, and thus, the most stable location of the peptide in the membrane. The gray vertical dashed line denotes the top of the membrane. (C) Cross-sectional view of DHRS3(1–26) during an unrestrained simulation in the membrane at the location indicated by the black vertical line in B. (D) Side-chain solvent accessibility measurements from MD simulations corroborate solvent accessibility measurements from biochemical assay. DHRS3(1–26) wild-type and individual cysteine mutants were placed in the membrane position corresponding to the PMF minimum in B and allowed to run without any restraints. The calculated accessibilities of each amino acid in wild-type and individual cysteine mutants are shown in a line plot together with data from the PEGylation experiment (Fig. 4A), normalized to values between 0 and 1. Calculated accessibilities of wild-type DHRS3(1–25) is also rendered as a heatmap.

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Proteomic analysis of monolayer-integrated proteins on lipid droplets identifies amphipathic interfacial α-helical membrane anchors
Camille I. Pataki, João Rodrigues, Lichao Zhang, Junyang Qian, Bradley Efron, Trevor Hastie, Joshua E. Elias, Michael Levitt, Ron R. Kopito
Proceedings of the National Academy of Sciences Aug 2018, 115 (35) E8172-E8180; DOI: 10.1073/pnas.1807981115

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Proteomic analysis of monolayer-integrated proteins on lipid droplets identifies amphipathic interfacial α-helical membrane anchors
Camille I. Pataki, João Rodrigues, Lichao Zhang, Junyang Qian, Bradley Efron, Trevor Hastie, Joshua E. Elias, Michael Levitt, Ron R. Kopito
Proceedings of the National Academy of Sciences Aug 2018, 115 (35) E8172-E8180; DOI: 10.1073/pnas.1807981115
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