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Coacervation of Lipid Bilayer in Natural Cell Membranes for Extraction, Fractionation, and Enrichment of Proteins in Proteomics Studies Amir Koolivand, Mohammadmehdi Azizi, Ariel O'Brien, and Morteza G. Khaledi J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.8b00857 • Publication Date (Web): 27 Feb 2019 Downloaded from http://pubs.acs.org on February 28, 2019
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Journal of Proteome Research
Coacervation of Lipid Bilayer in Natural Cell Membranes for Extraction, Fractionation, and Enrichment of Proteins in Proteomics Studies Amir Koolivand 1; Mohammadmehdi Azizi 1; Ariel O’Brien 1, Morteza G. Khaledi 1*; 1The
University of Texas at Arlington, Department of Chemistry and Biochemistry, Arlington, TX, 76019
Corresponding author:
[email protected] ABSTRACT
This is the first report where Hexafluoroisopropanol (HFIP) was used to induce the coacervation of lipid components in natural cell membranes that would concomitantly result in solubilization, extraction, and enrichment of hydrophobic proteins (e.g. Integral Membrane Proteins, IMP) into the coacervate phase; and extraction of hydrophilic proteins in a separate aqueous phase. The incorporation of this innovative approach in the proteomics workflow would allow the fractionation of proteins in separate aqueous and coacervate phases and would also eliminate the need for using surfactants. Subsequently, proteins can be identified by the bottom-up proteomics approach where samples were digested in solution after phase separation. Yeast cell wall proteins, anchored membrane proteins, and proteins related to some regulatory activities were mostly found in the aqueous-rich phase. On the other hand, most integral membrane proteins, proteins involved in metabolic processes, and proteins responsible for ions or drug binding were identified in the coacervate phase. The detergent-free, facile and rapid process of natural lipid coacervation increased the number of identified proteins by 8% (vs. no-phase separation experiment). The identification of all IMPs and organelle IMPs was improved by 13 and 29% respectively. In addition, 25% more low-abundance proteins (less than 20 ppm) were identified. Keywords: natural lipid coacervates, protein separation and enrichment, membrane proteomics, low abundance and hydrophobic proteins 1 ACS Paragon Plus Environment
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INTRODUCTION
Coacervates are a type of self-assembly of amphiphilic molecules that form a separate, amphiphilerich phase in aqueous media. In fluorinated alcohol-induced coacervate (FAIC) systems, the addition of a small concentration of a water-miscible fluoroalcohol (e.g. trifluoroethanol (TFE) or hexafluoroisopropanol (HFIP)) to the aqueous solution of an amphiphile (e.g. surfactants, polyelectrolytes, bile salts, or phospholipids) would facilitate coacervation and subsequent phase separation1–5. The coacervate phase in FAIC system is highly concentrated in amphiphile and fluoroalcohol and has the capacity to extract and solubilize compounds with a wide range of hydrophobicity. In the earlier work, we utilized FAIC systems prepared from HFIP and surfactants (sodium
dodecyl
sulfate
(SDS),
cetrimonium
bromide
(CTAB),
3-(N,
N
dimethylmyristylammonio) propanesulfonate (DMAPS)) in proteomic analysis of yeast sample1. We have also reported the use of novel FAIC systems for protein separation2 where the unique behavior of FAIC composed of tetra-butyl ammonium bromide (TBAB) for the selective extraction and enrichment of hydrophobic proteins (including membrane proteins) was shown. However, such a methodology requires the removal of the surfactant prior to digestion and LCMS/MS analysis. This communication is the first report of the incorporation of a novel form of coacervation of lipid bilayers of the natural cell membrane in the proteomics workflow that would obviate the need for surfactant removal. Due to the hydrophobic nature of coacervates, they can extract hydrophobic proteins such as integral membrane proteins (IMPs). IMPs are associated with a cell or organelle membrane, serve as receptors, and participate in many vital cell functions including but not limited to cell-cell interactions, cell signaling, channeling, and many others6. More than half of approved drugs are designed to target membrane proteins7; and many gene mutation diseases, such as cancer, are 2 ACS Paragon Plus Environment
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linked to membrane proteins8. Therefore, studies of the membrane proteome (such as protein identification, quantification, modification, and their localization) have rapidly emerged in recent years. Membrane protein solubilization, separation, and identification pose significant challenges in proteomic studies due to their hydrophobic nature and low abundance in cells6,9. Many sample preparation methods have been developed to overcome these obstacles; for instance, the use of detergents such as sodium deoxycholate (SDC) or sodium dodecyl sulfate was investigated to enhance the solubility of membrane proteins and subsequently improve their separation and identification10–13. However, detergent removal methods such as filter-aided sample preparation (FASP)14,15 requires long centrifugation steps where sample loss is inevitable. Other detergents such as SDC can be removed by precipitation in an acidic environment prior to LC-MS/MS analysis
12
which may cause sample loss. Enrichments methods such as methanol/chloroform or
acetone precipitation are commonly used in proteomic studies, however due to multiple steps in sample preparation and protein precipitation, it was shown that those methods were not ideal in membrane proteomics, and the number of identified proteins decreased when these precipitation methods were used12. Here we describe a novel method based on coacervation of the natural lipids in the cell membranes for extraction, fractionation of the complex mixture, and enrichment of proteins in separate phases that resulted in improved protein identification. In our first publication on the FAIC systems, we reported that HFIP can induce coacervation in aqueous suspensions of phospholipids such as phosphatidylcholine (PC) and phosphatidylglycerol (PG)3. The focus of this report is to take advantage of this capability to induce the coacervation of lipid components in natural cell membranes that would concomitantly result in solubilization, extraction, and enrichment of hydrophobic proteins (e.g. IMPs) into the coacervate phase. The incorporation of this innovative approach in the proteomics workflow would allow the 3 ACS Paragon Plus Environment
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fractionation of proteins in separate phases based on their subcellular location, molecular function, and biological properties and would also eliminate the need for using surfactants. Subsequently, proteins can be identified by bottom-up proteomics approach where samples were digested in solution after phase separation. MATERIALS AND METHODS
Cell Lysate Preparation Saccharomyces cerevisiae (Ward’s Science, USA) was grown on YPD broth (Fisher, USA) for 16 to 20 h in a shaker incubator at 30 °C until the optical density at 600 nm (O.D. 600) reached 2 to 5, where the stationary phase was achieved. The autoclaved media was kept as a blank in O.D. measurement and cell mixture was diluted enough to obtain O.D less than 0.8 and then multiplied by the dilution factor to calculate O.D. for the cell mixture. Cells were harvested by centrifugation at 1000×g for 5 min at 4 °C and then washed two times with cold autoclaved D.I water and centrifuged at 1000×g for 5 min. The harvested cells later were resuspended with a volume ratio 1:1 in a lysis buffer (50 mM ammonium bicarbonate (pH =7.8), Pierce™ Protease and Phosphatase Inhibitor Mini Tablets (1 tablet per 10 mL lysis buffer), and 100 mM NaCl). The mixture of cell pellets and cell lysis buffer were placed in a clean mortar and pestle and liquid nitrogen was added to freeze the mixture. The frozen mixture was ground until a fine powder formed. Liquid nitrogen was added during grinding to keep the mixture frozen. The powder was transferred to a vial and allowed to melt. For additional lysing, the semi- lysed cells were mixed with pre-washed glass beads. Acid (HCl) washed glass beads (0.5 mm, Scientific Industries, Inc.) were rinsed with enough deionized water to remove any remaining acid, cooked in an oven at 150 °C for 2 h and then cooled in a refrigerator at 4 °C. One volume of semi-lysed cell mixture with lysis buffer was mixed with one volume of chilled glass beads in 2 mL microcentrifuge vials and placed in a 4 ACS Paragon Plus Environment
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TissueLyser II system (Qiagen). The mixture was then shaken at a frequency of 30 Hz for 4 min. The glass bead beating was repeated 8-10 times; vials were placed on ice for 1 min between each run. After the glass beads settled, the crude cell lysate was collected by micropipette. The glass beads were washed with one volume of lysis buffer and pooled with collected cell lysate. The crude cell lysate was centrifuged at 500×g for 5 min at 4 °C to pellet unbroken cells and remove any remaining glass beads. The supernatant was collected, and protein concentration was measured using a protein assay kit (Coomassie Protein Assay Kit, Thermo Scientific). Coacervate Formation Two approaches were used to form lipid-coacervate in the sample preparation step for the proteomic analysis. The first approach involved the coacervation of an aqueous suspension of the yeast cell membrane in ammonium bicarbonate (ABC) buffer, while in the second approach, the yeast cell lysate was first solubilized in urea solution prior to HFIP-induced coacervation. Sixteen percent (v/v) HFIP was then added to each sample to induce two-phase formation. The phase diagram was created to determine the composition at which HFIP-induced yeast lipid coacervation occurs (Fig. S1 in the supplementary information). Although aqueous/coacervate two-phase system can be formed in a wide range of HFIP concentrations (5-20%, v/v), 16% (v/v) HFIP was selected for this study because the volume of coacervate phase at this concentration was large enough for facile sample handling. In addition, 16% (v/v) HFIP was far enough from phase transition lines to ensure a stable and reproducible two-phase formation. The lipid concentration was measured using a developed mass spectrometry method (unpublished result) and was found to be 15 mg/mL prior to two-phase formation. In order to incorporate coacervation, the protein digestion protocol for this work was modified from urea-based digestion protocols in previous reports 12,16. The step
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by step coacervate formation protocol with protein digestion can be found in the supplementary information. Fig. 1 shows a schematic of lipid coacervation workflow and subsequent proteomics analysis. After two-phase formation, the top aqueous-rich and bottom lipid-coacervate phases were separated and bottom-up proteomic analysis was performed on both samples. Proteins in the aqueous-rich phase, coacervate phase, and a sample without phase separation in urea (control sample) were digested and identified from LC-MS/MS analysis.
a
b
16% (v/v)
c
d
HFIP
Fig 1. Top) Proteomics workflow incorporated with HFIP-induced coacervation of natural lipids in yeast cell lysate with lipid concentration of 15 mg/mL. Bottom) a: The cell lysate dissolved in urea (6.5 M), b: The cell lysate
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suspension in ABC buffer (50 mM), c: The coacervation of cell lysate dissolved in urea after adding 16% (v/v) HFIP, d: The Coacervation of cell lysate in ABC buffer after adding 16% (v/v) HFIP.
LC-MS/MS After protein digestion, 2 uL of each peptide sample was analyzed using an Orbitrap Fusion Lumos mass spectrometer (Thermo Electron) coupled to an Ultimate 3000 RSLC-Nano liquid chromatography system (Dionex). Samples were injected into a 75 μm i.d., 50-cm long EasySpray® C18 Reversed Phase (RP) column (Thermo), and eluted with a gradient program performed as follows: load at 0% B for 30 minutes (flow rate 350 nL/min), 0-28% B in 60 min (flow rate 250 nL/min), 28-99% B in 10 min, hold at 99% B for 5 min, and then re-equilibrate the column at 0% B for 15 minutes (flow rate 250 nL/min). Mobile phase A contained 2% (v/v) ACN (Acetonitrile) and 0.1% (v/v) formic acid in water, and mobile phase B contained 80% (v/v) ACN, 10% (v/v) TFE (trifluoroethanol), and 0.1% formic acid in water. The mass spectrometer operated in positive ion mode with a source voltage of 2.2 kV and an ion transfer tube temperature of 275 °C. MS scans were acquired at 120,000 resolutions in the Orbitrap and up to 10 MS/MS spectra were obtained in the ion trap for each full spectrum acquired using higher-energy collisional dissociation (HCD) for ions with charges 2-7. Dynamic exclusion was set for 25 s after an ion was selected for fragmentation. Data Analysis Four biological replicates of all samples were prepared, and each replicate was subjected to one run of LC-MS/MS. The RAW data were analyzed using MaxQuant (Ver. 1.6.1.0)17 incorporated with Andromeda search engine18. Proteins identified in at least three out of four replicates were considered in further data analysis. MaxQuant software was developed by Mann et al. at MaxPlanck Institute for Biochemistry19. The reviewed yeast database was downloaded from UniProt 7 ACS Paragon Plus Environment
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and configured into the software. The search parameters were set to be as follows: oxidation of methionine and N-terminal acetylation as variable modifications (maximum 5 oxidation/acetyl modifications per peptides), carbamidomethyl as a fixed modification, 2 missed cleavages, labelfree quantification with iBAQ, minimum 1 unique peptide for protein identification, PSM FDR (peptide-spectrum match- false discovery rate) 1%, and protein FDR 1%. iBAQ quantification is defined as a protein's total intensity (the sum of identified peptides for a protein) divided by number of tryptic peptides with 6 to 30 amino acids in length20 and used as the intensity of each identified protein. Venn diagrams were created using an online tool21. Gene ontology analysis was performed using Yeast Database22 and Gene Ontology Consortium23. RESULTS AND DISCUSSION
Yeast (Saccharomyces cerevisiae) cell membrane is composed of three main lipid structures; glycerophospholipids, sphingolipids, and ergosterol24. Yeast lipidome contains 20.3% phosphatidylinositol (PI), 14.9% phosphatidylethanolamine (PE), 14.3% phosphatidylcholine (PC), 8.3% phosphatidic acid (PA), and 1.8% phosphatidylserine (PS) lipid types25. Addition of 16% (v/v) HFIP into the cell lysate resulted into a two-phase formation. The natural lipids in cell lysate interact with HFIP and form coacervate as a separate phase. The number of proteins identified in each phase were determined and are listed below: 1. Aqueous/Coacervate two-phase system in the presence of urea: Coacervate phase in the presence of urea (CoU) =1992 Aqueous phase in the presence of urea (AqU) = 1554 CoU + AqU = 2332 (sum of the common and unique proteins in both phases) 2. Aqueous/Coacervate two-phase system without urea: Coacervate phase without urea (Co) = 1986 Aqueous phase without urea (Aq) = 1061 8 ACS Paragon Plus Environment
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Co + Aq =2231 (sum of the common and unique proteins in both phases) 3. Control system: sample prepared in urea: Control sample with no phase separation (NP) = 2153 As it is shown, the implementation of simple coacervation in proteomics workflow improved the protein identification in yeast. The addition of urea before coacervation enhanced the effect of coacervation and the highest number of identified proteins were in the coacervation system in the presence of urea. However, the selectivity of these phases could expand their application in proteomics studies, therefore, the types of proteins and selectivity of each phase toward different types of proteins were investigated and explained in the following sections. Gene ontology To investigate gene ontology (GO) annotation for identified proteins, yeast database gene code for each
protein
was
extracted
(https://www.yeastgenome.org).
from
The
Saccharomyces
same
gene
IDs
Genome can
also
Database be
retrieved
(SGD) from
http://www.uniprot.org26. The gene list for proteins in each sample was analyzed using a GO enrichment analysis tool available at http://www.geneontology.org23. GOs in terms of cellular component, biological process and molecular function were annotated and selected GOs in each sample are listed in Table 1. As shown, most membrane-related proteins were enriched in the coacervate phase, except the anchored component of a membrane which mostly stayed in the aqueous phase. Anchored membrane proteins are covalently bound to the membrane by an attached anchor, therefore these proteins are hydrophilic membrane-related proteins. The majority of proteins located in the mitochondrial ribosomes were in the coacervate phases. However, proteins located in the cell wall or extracellular region were separated into the aqueous phase in the presence of urea (AqU). The cell wall in yeast or fungal cells is an essential component for their survival and proteins in the cell wall might be involved in adhesion to host cells, virulence, 9 ACS Paragon Plus Environment
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or even biofilm formation which results from adhering of multicellular structures to the surfaces27,28. The top aqueous phase in lipid coacervate two-phase system can be valuable in separating and enriching the cell wall or extracellular region proteins in yeast. In the biological process GO, proteins related to lipid and protein metabolic process were enriched into the coacervate phases however, proteins involved in the regulation of metabolic process remained in the aqueous phase. Proteins related to the molecular function of binding to molecules, such as ions or drugs, favored the coacervate phase, while proteins involved in the transcription regulator activity were enriched into the aqueous phase. To better understand the differences in each GOs, the Venn diagrams for some of the GOs in Table 1 were created and further explained in the following sections (Figs 2-4). Table 1.
Identified proteins with different gene ontology. NP: No phase separation, Aq: Aqueous phase
without urea, Co: Coacervate phase without urea, AqU: Aqueous phase in the presence of urea, CoU: coacervate phase in the presence of urea. CoU+AqU and Co+Aq are the sums of unique and common proteins in coacervate and aqueous phases.
1-
Cellular component
Membrane Intrinsic component of membrane Integral component of membrane Integral component of organelle membrane Integral component of golgi membrane Integral component of mitochondrial membrane
NP
CoU
AqU
CoU+ AqU
Co
Aq
Co + Aq
741
697
495
818
699
326
784
404
391
242
460
392
143
439
394
388
226
444
388
129
425
45
52
25
58
54
11
58
14
18
8
19
17
3
17
23
26
13
29
28
5
31
32
33
17
36
33
9
34
Integral component of endoplasmic reticulum membrane
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Integral component of plasma membrane
20
16
15
24
16
10
23
33
20
39
42
26
26
36
170
171
93
191
167
54
180
62
55
51
68
51
46
68
13
5
19
19
7
17
17
33
20
40
43
27
29
39
32
26
6
27
25
1
25
3
1
6
6
1
5
5
NP
CoU
AqU
CoU+ AqU
Co
Aq
Co + Aq
Lipid metabolic process
124
135
62
141
128
40
134
Lipid biosynthetic process
81
89
45
92
84
29
88
Protein metabolic process
596
571
416
623
556
281
586
Organic acid metabolic process
257
254
185
262
251
129
257
Metabolic process
1613
1526
1122
1718
1500
755
1631
Regulation of transcription by RNA polymerase II
144
124
138
180
121
76
149
Response to abiotic stimulus
91
72
78
93
19
55
67
Positive regulation of RNA metabolic process
121
103
118
147
104
77
127
Positive regulation of metabolic process
193
167
177
225
170
123
203
17
10
19
19
12
12
17
56
41
46
66
46
33
64
NP
CoU
AqU
CoU+ AqU
Co
Aq
Co + Aq
Cell wall Mitochondrial membrane RNA polymerase complex Anchored component of membrane Extracellular region Mitochondrial ribosome Unknown cellular component
2-
Biological process
Regulation of DNA-templated transcription in response to stress Unknown biological process
3-
Molecular function
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Transcription regulator activity Phosphatase regulator activity Regulatory region nucleic acid binding Transcription cofactor activity DNA binding transcription factor activity DNA binding Sequence-specific DNA binding Drug binding Nucleic acid binding Small molecule binding Nucleotide binding Ion binding Cation binding Anion binding Coenzyme binding Transferase activity Catalytic activity Transferase activity, transferring hexosyl groups Transferase activity, transferring acyl groups Oxidoreductase activity Unknown molecular function
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67
53
78
79
54
60
88
9
8
16
17
6
11
14
25
19
35
38
18
25
31
23
15
28
32
19
22
29
27
20
33
37
19
25
33
162
145
141
191
140
114
177
44
40
51
61
41
42
59
357
341
247
360
316
193
341
523
492
409
566
471
319
540
494
477
347
500
438
260
476
448
435
320
458
399
240
434
749
715
540
783
667
379
741
336
323
254
369
302
159
345
498
475
347
500
439
262
478
99
95
68
97
85
45
92
408
397
244
433
366
176
397
1159
1119
764
1216
1053
505
1146
39
43
14
44
40
11
42
54
59
29
62
52
20
53
203
195
136
204
183
81
195
217
187
171
269
203
109
256
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a) Cellular component Membrane proteins showed a significant difference in protein distribution between the coacervate and aqueous phases. The total number of proteins and membrane-related proteins in each phase and the control experiment are summarized in Table 2. The results of two coacervation approaches were compared with that of the control experiment (i.e. no coacervation). The number of proteins identified in all subcellular locations was improved using coacervate systems. The total number proteins in both the membrane and the integral component of the membrane were increased by 77 and 50 respectively, when a coacervation system in the presence of urea was used.
The
identification of protein located in the integral component of an organelle membrane improved by almost 30%. Golgi, mitochondrial and endoplasmic reticulum proteins were compared and in each subcategory the number of proteins increased when a two-phase lipid coacervation was used. Identification of proteins in the integral component of membrane and the anchored component of a membrane was improved by 13% and 46% respectively with the help of lipid coacervation however, as mentioned earlier, the enrichment trend was different as proteins related to anchored component of a membrane stayed in aqueous phases, and proteins in the integral component of a membrane enriched in coacervate phases. The identification improvement of proteins is due to the selective separation and extraction of proteins which resulted in the simplification of a complex mixture. The results of this study showed how a simple two-phase coacervation step in proteomics can provide a significant improvement in membrane-related protein identification. Table 2.
Identification improvement in membrane-related proteins due to phase separation when compared
to the control sample; control sample is the typical digestion of yeast cell lysate without any phase separations. The percentage of protein numbers in “coacervate+aqueous system” that increased compared to a no phase separation (NP) sample is shown as “% increase”.
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Gene Ontology (Cellular Component) Membrane Intrinsic Component of Membrane Integral Component of Membrane Integral Component of Organelle Membrane Integral Component of Golgi Membrane Integral Component of Mitochondrial Membrane Integral Component of Endoplasmic Reticulum Membrane Integral Component of Plasma Membrane Anchored Component of Membrane
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Coacervate System in The Presence of Urea
Coacervate System Without Urea
Number of Proteins
% Increase (vs. Control)
Number of Proteins
% Increase (vs. Control)
818
10%
784
6%
460
14%
439
9%
444
13%
425
8%
58
29%
58
29%
19
36%
17
21%
29
26%
31
35%
36
13%
34
6%
24
20%
23
15%
19
46%
17
30%
Solubilization with urea enhanced the identification of membrane and integral membrane proteins by almost 4% and 5%, respectively compared to a coacervation system without urea (See Table 2 for identification improvement in samples with and without urea). Only proteins located in the mitochondrial membrane showed a slightly better result without urea addition. Adding urea before coacervate formation improved membrane protein solubilization into the aqueous phase which led to the fractionation increase between two phases, allowing a higher number of proteins to be identified. The results showed how using a chaotropic agent, such as urea, before coacervation could significantly improve membrane protein identification coverage however, it is worthwhile to mention that both coacervate systems, with or without urea, improved the membrane protein identification when compared to the sample without phase separation.
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The Venn diagrams of proteins in different cellular components are shown in Fig. 2. As shown, almost all proteins located in mitochondrial ribosomes were found in the coacervate phase. Mitochondrial ribosomes (mitoribosomes) are responsible for protein synthesis inside the mitochondria, and mitoribosomes have been specialized to synthesize mitochondria membrane proteins29. Almost all cell wall proteins can be identified in the aqueous phase with urea, which shows the selectivity of the aqueous phase to these kinds of proteins.
Fig 2. Venn diagrams of proteins located in different cellular components. AqU, CoU stand for the aqueous phase and the coacervate phase in the presence of urea. Aq and Co stand for the aqueous phase and the coacervate phase without urea.
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b) Biological process Protein distribution between aqueous and coacervate phases was examined in terms of the corresponding biological processes and are illustrated in Venn diagrams in Fig. 3. In general, coacervates tend to extract more proteins involved in metabolic processes (e.g. lipid, organic acid, and protein metabolic processes). However, proteins responsible for the regulation of metabolic process (e.g. proteins involved in positive regulation of RNA metabolic processes) can be mostly found in the aqueous phase. Specifically, proteins participating in the regulation of DNAtemplated transcription in response to stress were selectively separated into the aqueous phase in the presence of urea. The fractionation by lipid coacervation is not limited to the cellular component analysis but is also an effective separation based on the biological processes. Proteins responsible for defense mechanism (e.g. response to abiotic stimulus) were mostly in the aqueous phases. It is interesting that the addition of urea allows these kinds of proteins to be partitioned more into coacervate phase rather than aqueous phase, therefore if the goal was separating proteins involved in abiotic stimulus, the aqueous phase of the lipid coacervate system without urea should be considered.
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Fig 3. Venn diagrams of proteins involved in different biological processes in coacervate and aqueous phases with or without urea. AqU, CoU stand for the aqueous phase and the coacervate phase in the presence of urea. Aq and Co stand for the aqueous phase and the coacervate phase without urea.
c) Molecular function Protein activities such as binding and catalysis at the molecular level can be described by molecular function gene ontology. Most proteins related to some binding molecular functions (e.g. cation, anion, coenzyme, and drug bindings) and catalytic and oxidoreductase activity tend to have an affinity for coacervate phases. However, proteins related to DNA binding, DNA binding transcription factor activity, transcription cofactor activity, transcription regulator activity, and phosphatase regulator activity were mostly identified in aqueous phases. Transcription regulation 17 ACS Paragon Plus Environment
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controls the transcription of genetic information which involves binding to DNA; proteins related to this process preferred the aqueous-rich phase (see transcription regulatory activity in Fig. 4).
Fig 4. Venn diagrams of proteins with different molecular functions in coacervate and aqueous phases with or without urea. AqU, CoU stand for the aqueous phase and the coacervate phase in the presence of urea. Aq and Co stand for the aqueous phase and the coacervate phase without urea.
Protein Abundance The yeast proteins have been quantified using various tagging methods, including tandem affinity purification (TAP) and green fluorescent protein (GFP)30–32. Ghaemmaghami et al determined the first global protein abundance in yeast by high-affinity epitope tagging followed by a chemiluminescence approach30. Recently, a method was reported using multiplexed tandem mass tag strategy to quantify 5,000 proteins in yeast33. The protein abundance database for different species is available online34, where the abundance for each protein was retrieved from reported 18 ACS Paragon Plus Environment
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values in the literature and then integrated across an organism proteome. The yeast proteome abundance database was downloaded and was used to identify the low abundance proteins in our samples and the effect of coacervation on the identification of proteins with lower abundance was investigated. The unit for abundance is in part per million (ppm) across the whole proteome, which is the abundance of each protein respect to the whole expressed proteome. We compared all proteins identified in aqueous and coacervate phases with the control (a sample in urea without a phase separation, NP) (Fig. 5). The average abundance for common and unique proteins was calculated and is presented in Fig. 5. The majority of uniquely identified proteins in each phase and control sample had an abundance less than 100 ppm (Fig. 5 c and f) however, the average abundances of common proteins were higher than 500 ppm (Fig. 5 a, and d). The proteins with abundance less than 20 ppm were examined in each phase and compared in Fig. 5 g and i. The total numbers of proteins with abundance less than 20 ppm were 296, 270 and 236 for coacervation in the presence of urea (AqU+CoU), coacervation without urea (Aq+Co), and no phase separation, respectively. Although some proteins cannot be identified in either coacervate or aqueous phases because of their partitioning, coacervation improved the identification of whole proteins and the low abundance proteins (less than 20 ppm) by 8% and 25% respectively, due to simplifying the sample complexity and protein enrichment. Low abundance integral membrane proteins tend to enrich into the coacervate phase which should facilitate their identification in membrane proteomics (Fig. 5 h, and j).
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Fig 5. a) Venn diagram comparing identified proteins in Aq, Co, and NP, b) The abundance distribution of proteins uniquely found in Aq, Co and NP, c) The zoom in graph of (b) (proteins with the abundance less than 400 ppm), d) Venn diagram comparing identified proteins in AqU, CoU, and NP, e) The abundance distribution of proteins uniquely found in Aq, Co and NP, f) The zoom-in graph of (e)(proteins with the abundance less than 400 ppm). The average abundances of unique proteins are shown for each sample in graphs (b) and (e). The average abundances of common proteins are shown in diagrams (a) and (d) which were much higher than the one for unique proteins, therefore they can be identified in both phases as well as control sample. g) All proteins with the abundance less than 20 ppm in Aq and Co, h) Integral membrane proteins with the abundance less than 20 ppm in Aq and Co, i) All proteins with the abundance less than 20 ppm in AqU and CoU, j) Integral membrane proteins with the abundance less than 20 ppm in AqU and CoU.
GRAVY Score and Isoelectric Points To evaluate the hydrophobicity of identified proteins, GRAVY scores were calculated using YeastMine (http://yeastmine.yeastgenome.org) which has a retrieval tool to calculate protein properties such as pI or GRAVY scores from yeast genome database 22,35. The most hydrophobic protein identified in a sample without phase separation had a GRAVY score of 0.68 however, when coacervation was employed, hydrophobic proteins with GRAVY scores greater than 0.68 were also identified (Fig 6 a, and b). The identification of proteins with GRAVY scores higher than 1.0 only occurred in samples with lipid coacervation, because of hydrophobic selectivity in the coacervate phase. Protein V-type proton ATPase subunit c (P25515VATL1_YEAST) with GRAVY score 1.2 was the most hydrophobic protein identified in this study and was only detected in coacervate phases. This protein is an integral membrane protein and acts as a proton pump in the vacuolar membrane vesicles. It also has 4 transmembrane domains which are predicted to be helical based on sequence analysis available at Uniprot.org. It has an abundance of 423 ppm, which is high enough to be detected but it was not identified in the control
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sample without phase separation most likely due to its high hydrophobicity. The coacervate phase extracted and solubilized this protein allowing it to be identified. The hydrophobicity of integral membrane proteins is another challenge for their identification. These results showed that the coacervate phase was able to improve the identification of hydrophobic integral membrane proteins. On the other hand, the average value and GRAVY score distribution also showed that the most hydrophilic proteins stayed in aqueous phases (Fig. 6).
a)
b)
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c)
Fig 6.
a) GRAVY score distribution of all proteins in the control, coacervate and aqueous phases, b) GRAVY score
distribution of uniquely identified proteins in coacervate and aqueous phases. The values shown in the graphs are maximum, mean and minimum values for each sample from top to bottom, c) Data distribution and box plot of pI values of identified proteins in control sample, coacervate and aqueous phases. The box shows the middle 50% of the pI distribution. The values next to each box represent the mean pI. The line in the box shows the median values.
Unique proteins identified in coacervate and aqueous phases contained the most hydrophobic and hydrophilic proteins, respectively. When comparing uniquely identified proteins in the aqueous and coacervate phases (Fig. 6 b), the average GRAVY value for proteins in coacervate phases (0.3) was much higher than the one in the aqueous phase (-0.7). The addition of urea did not change the trend of hydrophobic selectivity of coacervates. Isoelectric point (pI) is another protein characteristic that was compared for proteins in each phase. The average isoelectric point of proteins identified in the aqueous phases (pI = 6.5-6.6) was slightly lower than the one in the coacervate phase (pI = 6.9-7), meaning the coacervate phase extracted proteins with more basic pI values (Fig. 6 c). This could be due to lipid charges mostly involved 23 ACS Paragon Plus Environment
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in coacervation, therefore further investigation on lipid coacervation and characterization is underway in a separate study. Partition Coefficient for Common Proteins The partition coefficient of common proteins for both phases can be calculated from “intensitybased absolute quantification” (iBAQ) which is directly related to the protein concentration. The partition coefficient was calculated using the following equation (Eq.1): 𝑃𝑎𝑟𝑡𝑖𝑡𝑖𝑜𝑛 𝑐𝑜𝑒𝑓𝑓𝑖𝑐𝑒𝑖𝑛𝑡 (𝑘) =
[𝑝𝑟𝑜𝑡𝑒𝑖𝑛]𝑐𝑜
𝑖𝐵𝐴𝑄 ― 𝑀𝑆 𝐼𝑛𝑡𝑒𝑛𝑠𝑖𝑡𝑦𝑐𝑜
[𝑝𝑟𝑜𝑡𝑒𝑖𝑛]𝑎𝑞 = 𝑖𝐵𝐴𝑄 ― 𝑀𝑆 𝐼𝑛𝑡𝑒𝑛𝑠𝑖𝑡𝑦𝑎𝑞 × 𝑑𝑖𝑙𝑢𝑡𝑖𝑜𝑛 𝑓𝑎𝑐𝑡𝑜𝑟 𝑟𝑎𝑡𝑖𝑜
(Eq. 1)
where the “dilution factor ratio” is a dilution factor of coacervate phase divided by dilution factor of the aqueous phase before protein digestion and LC-MS/MS analysis. The dilution factor ratio was around 95 prior to LC-MS/MS. These values were calculated for common proteins and their log (k) distributions were plotted in Fig. 7. Almost all common proteins were enriched in a coacervate phase. Most proteins showed a partition coefficient higher than 100, meaning those proteins were concentrated in the coacervate phase 100 times than in aqueous phase. Partition coefficient distribution shifted to higher values for coacervate systems without urea compared to the one with urea. We speculated that urea addition improved protein solubilization in the aqueous phase which resulted in a higher concentration (i.e. higher iBAQ-MS intensity) of proteins in the aqueous phase.
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Fig 7. The log of partition coefficient (k) of proteins in lipid-coacervation two-phase systems with and without urea addition. The partition coefficient was calculated using Eq.1.
CONCLUSION
Complex biological samples contain thousands of proteins, making the protein separation and identification a difficult task. Advanced analytical techniques such as LC-MS/MS provide the opportunity to analyze a complex sample, however a pre-fractionation or extraction method could improve protein identification. Low abundance proteins, such as integral membrane proteins, are often under-represented in proteomics studies. Because of their hydrophobic nature and low abundance in cells; solubilization, separation, and enrichment of membrane proteins are
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challenging. The facile HFIP-induced coacervation of the natural lipids in yeast improved protein identification coverage. Coacervates were formed by adding 16% HFIP (v/v) into a yeast cell lysate with a total lipid concentration of 15 mg/mL (in the presence or absence of urea). HFIPinduced coacervation of natural lipids in the presence of urea improved whole, membrane and intrinsic membrane identification by 8, 10 and 14% respectively. Urea solubilized more proteins in the aqueous phase, which improved the protein separation and partitioning between two phases. Proteins were separated based on their subcellular location, molecular function, and biological process involvement.
Anchored membrane proteins and integral membrane proteins were
separated into aqueous and coacervate phases respectively. Not only did coacervation improve membrane related protein identification but it also increased the number of proteins identified in other cellular components, such as mitochondrial ribosomes (in the coacervate phase) and cell wall (in the aqueous phase). Most proteins related to positive regulation of metabolic process or positive regulation of RNA metabolic process were in aqueous phases while proteins in lipid, organic acid, and protein metabolic process preferred coacervate phases. Proteins with molecular function involving cation, anion, coenzyme, drug bindings and catalytic and oxidoreductase activity were extracted into coacervate phases. However, most proteins participating in DNA binding and its transcription factor activity, transcription cofactor activity, transcription regulator activity, and phosphatase regulator activity were identified in aqueous phases. The coacervate phase contained a higher percentage of low abundance integral membrane proteins (less than 20 ppm) than the aqueous phase (35% vs. 20% in coacervate and aqueous phases respectively). Proteins in coacervate phases were more hydrophobic (higher GRAVY score) and had a higher average isoelectric point. The most hydrophobic integral membrane protein in this study, V-type proton ATPase subunit c, was 26 ACS Paragon Plus Environment
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only identified in coacervate phases. The hydrophobic nature of lipid-HFIP coacervate and its enrichment capability allow such a separation selectivity in proteins. Therefore, HFIP-induced coacervation of natural lipids improved the low abundance and hydrophobic protein identification, which can facilitate membrane protein identification in proteomic studies. SUPPORTING INFORMATION The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE 36partner repository with the dataset identifier PXD012349. The following information is available free of charge at ACS website. Protocols file includes lipid coacervate phase diagram (Fig. S1), protein digestion protocol, the coacervate formation. Excel file contains the list of identified proteins and their gene ontology (Table S1-S8). ACKNOWLEDGMENTS This research was funded by NSF Grant (1632221). REFERENCES (1) (2) (3) (4) (5) (6)
McCord, J. P.; Muddiman, D. C.; Khaledi, M. G. Perfluorinated Alcohol Induced Coacervates as Extraction Media for Proteomic Analysis. J. Chromatogr. A 2017, 1523, 293–299. Koolivand, A.; Clayton, S.; Rion, H.; Oloumi, A.; O’Brien, A.; Khaledi, M. G. Fluoroalcohol – Induced Coacervates for Selective Enrichment and Extraction of Hydrophobic Proteins. J. Chromatogr. B 2018, 1083, 180–188. Khaledi, M. G.; Jenkins, S. I.; Liang, S. Perfluorinated Alcohols and Acids Induce Coacervation in Aqueous Solutions of Amphiphiles. Langmuir 2013, 29 (8), 2458–2464. Jenkins, S. I.; Collins, C. M.; Khaledi, M. G. Perfluorinated Alcohols Induce Complex Coacervation in Mixed Surfactants. Langmuir 2016, 32 (10), 2321–2330. Nejati, M. M.; Khaledi, M. G. Perfluoro-Alcohol-Induced Complex Coacervates of Polyelectrolyte–Surfactant Mixtures: Phase Behavior and Analysis. Langmuir 2015, 31 (20), 5580–5589. Vit, O.; Petrak, J. Integral Membrane Proteins in Proteomics. How to Break Open the Black Box? J. Proteomics 2017, 153, 8–20.
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(7) (8) (9) (10) (11) (12) (13) (14) (15) (16) (17) (18) (19) (20) (21) (22)
(23)
Yıldırım, M. A.; Goh, K.-I.; Cusick, M. E.; Barabási, A.-L.; Vidal, M. Drug—Target Network. Nat. Biotechnol. 2007, 25 (10), 1119–1126. Kampen, K. R. Membrane Proteins: The Key Players of a Cancer Cell. J. Membr. Biol. 2011, 242 (2), 69–74. Arnold, T.; Linke, D. Phase Separation in the Isolation and Purification of Membrane Proteins. BioTechniques 2007, 43 (4), 427–440. DI Girolamo, F.; Ponzi, M.; Crescenzi, M.; Alessandroni, J.; Guadagni, F. A Simple and Effective Method to Analyze Membrane Proteins by SDS-PAGE and MALDI Mass Spectrometry. Anticancer Res. 2010, 30 (4), 1121–1129. Masuda, T.; Tomita, M.; Ishihama, Y. Phase Transfer Surfactant-Aided Trypsin Digestion for Membrane Proteome Analysis. J. Proteome Res. 2008, 7 (2), 731–740. Moore, S. M.; Hess, S. M.; Jorgenson, J. W. Extraction, Enrichment, Solubilization, and Digestion Techniques for Membrane Proteomics. J. Proteome Res. 2016, 15 (4), 1243– 1252. Wang, M.; Heo, G.-Y.; Omarova, S.; Pikuleva, I. A.; Turko, I. V. Sample Prefractionation for Mass Spectrometry Quantification of Low-Abundance Membrane Proteins. Anal. Chem. 2012, 84 (12), 5186–5191. Erde, J.; Loo, R. R. O.; Loo, J. A. Enhanced FASP (EFASP) to Increase Proteome Coverage and Sample Recovery for Quantitative Proteomic Experiments. J. Proteome Res. 2014, 13 (4), 1885–1895. Wiśniewski, J. R.; Zougman, A.; Nagaraj, N.; Mann, M. Universal Sample Preparation Method for Proteome Analysis. Nat. Methods 2009, 6 (5), 359–362. Richards, A. L.; Hebert, A. S.; Ulbrich, A.; Bailey, D. J.; Coughlin, E. E.; Westphall, M. S.; Coon, J. J. One-Hour Proteome Analysis in Yeast. Nat. Protoc. 2015, 10 (5), 701–714. Tyanova, S.; Temu, T.; Cox, J. The MaxQuant Computational Platform for Mass Spectrometry-Based Shotgun Proteomics. Nat. Protoc. 2016, 11 (12), 2301–2319. Cox, J.; Neuhauser, N.; Michalski, A.; Scheltema, R. A.; Olsen, J. V.; Mann, M. Andromeda: A Peptide Search Engine Integrated into the MaxQuant Environment. J. Proteome Res. 2011, 10 (4), 1794–1805. Cox, J.; Mann, M. MaxQuant Enables High Peptide Identification Rates, Individualized p.p.b.-Range Mass Accuracies and Proteome-Wide Protein Quantification. Nat. Biotechnol. 2008, 26 (12), 1367–1372. Schwanhäusser, B.; Busse, D.; Li, N.; Dittmar, G.; Schuchhardt, J.; Wolf, J.; Chen, W.; Selbach, M. Global Quantification of Mammalian Gene Expression Control. Nature 2011, 473 (7347), 337–342. Hulsen, T.; de Vlieg, J.; Alkema, W. BioVenn – a Web Application for the Comparison and Visualization of Biological Lists Using Area-Proportional Venn Diagrams. BMC Genomics 2008, 9, 488. Balakrishnan, R.; Park, J.; Karra, K.; Hitz, B. C.; Binkley, G.; Hong, E. L.; Sullivan, J.; Micklem, G.; Michael Cherry, J. YeastMine—an Integrated Data Warehouse for Saccharomyces Cerevisiae Data as a Multipurpose Tool-Kit. Database J. Biol. Databases Curation 2012, 2012, bar062. Ashburner, M.; Ball, C. A.; Blake, J. A.; Botstein, D.; Butler, H.; Cherry, J. M.; Davis, A. P.; Dolinski, K.; Dwight, S. S.; Eppig, J. T.; et al. Gene Ontology: Tool for the Unification of Biology. Nat. Genet. 2000, 25 (1), 25–29.
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(24) Guan, X. L.; Riezman, I.; Wenk, M. R.; Riezman, H. Chapter 15 - Yeast Lipid Analysis and Quantification by Mass Spectrometry; Enzymology, B.-M. in, Ed.; Guide to Yeast Genetics: Functional Genomics, Proteomics, and Other Systems Analysis; Academic Press, 2010; Vol. 470, pp 369–391. (25) Ejsing, C. S.; Sampaio, J. L.; Surendranath, V.; Duchoslav, E.; Ekroos, K.; Klemm, R. W.; Simons, K.; Shevchenko, A. Global Analysis of the Yeast Lipidome by Quantitative Shotgun Mass Spectrometry. Proc. Natl. Acad. Sci. 2009, 106 (7), 2136–2141. (26) Apweiler, R.; Bairoch, A.; Wu, C. H.; Barker, W. C.; Boeckmann, B.; Ferro, S.; Gasteiger, E.; Huang, H.; Lopez, R.; Magrane, M.; et al. UniProt: The Universal Protein Knowledgebase. Nucleic Acids Res. 2004, 32 (Database issue), D115–D119. (27) Reynolds, T. B.; Fink, G. R. Bakers’ Yeast, a Model for Fungal Biofilm Formation. Science 2001, 291 (5505), 878–881. (28) Hsu, P.-H.; Chiang, P.-C.; Liu, C.-H.; Chang, Y.-W. Characterization of Cell Wall Proteins in Saccharomyces Cerevisiae Clinical Isolates Elucidates Hsp150p in Virulence. PLOS ONE 2015, 10 (8), e0135174. (29) Greber, B. J.; Ban, N. Structure and Function of the Mitochondrial Ribosome. Annu. Rev. Biochem. 2016, 85 (1), 103–132. (30) Ghaemmaghami, S.; Huh, W.-K.; Bower, K.; Howson, R. W.; Belle, A.; Dephoure, N.; O’Shea, E. K.; Weissman, J. S. Global Analysis of Protein Expression in Yeast. Nature 2003, 425 (6959), 737–741. (31) Ho, B.; Baryshnikova, A.; Brown, G. W. Comparative Analysis of Protein Abundance Studies to Quantify the Saccharomyces Cerevisiae Proteome. bioRxiv 2017, 104919. (32) Huh, W.-K.; Falvo, J. V.; Gerke, L. C.; Carroll, A. S.; Howson, R. W.; Weissman, J. S.; O’Shea, E. K. Global Analysis of Protein Localization in Budding Yeast. Nature 2003, 425 (6959), 686–691. (33) Paulo, J. A.; O’Connell, J. D.; Everley, R. A.; O’Brien, J.; Gygi, M. A.; Gygi, S. P. Quantitative Mass Spectrometry-Based Multiplexing Compares the Abundance of 5000 S. Cerevisiae Proteins across 10 Carbon Sources. J. Proteomics 2016, 148, 85–93. (34) Wang, M.; Herrmann, C. J.; Simonovic, M.; Szklarczyk, D.; von Mering, C. Version 4.0 of PaxDb: Protein Abundance Data, Integrated across Model Organisms, Tissues, and CellLines. Proteomics 2015, 15 (18), 3163–3168. (35) Cherry, J. M.; Hong, E. L.; Amundsen, C.; Balakrishnan, R.; Binkley, G.; Chan, E. T.; Christie, K. R.; Costanzo, M. C.; Dwight, S. S.; Engel, S. R.; et al. Saccharomyces Genome Database: The Genomics Resource of Budding Yeast. Nucleic Acids Res. 2012, 40 (Database issue), D700–D705. (36) Vizcaíno, J. A.; Csordas, A.; del-Toro, N.; Dianes, J. A.; Griss, J.; Lavidas, I.; Mayer, G.; Perez-Riverol, Y.; Reisinger, F.; Ternent, T.; et al. 2016 Update of the PRIDE Database and Its Related Tools. Nucleic Acids Res. 2016, 44 (Database issue), D447–D456.
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