Abstract

   Previously, we reported changes in the lipid profile of cultured human
   subcutaneous white preadipocytes during their differentiation and
   maturation. Here, using the same cells, we report changes in the
   protein profiles during differentiation and maturation as multi-omics
   data. The three cell lines of Caucasian-derived subcutaneous
   preadipocytes were divided into five stages: stage-1, subcutaneous
   preadipocytes; stage-2, following induction of differentiation into
   adipocytes; stages-3 to -5, from the initiation of lipid droplet
   formation to mature subcutaneous adipocytes (depending on the lipid
   droplet amount and formation). In each stage, proteins were extracted
   from the cells, proteolytically cleaved, and analyzed using untargeted
   liquid chromatography and mass spectrometry. The proteins were then
   identified and statistically analyzed. A total of 1,871 proteins were
   identified with high confidence, of which, 381 were statistically
   significant (P-value < 0.05) between any two stages. The Kyoto
   Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis
   revealed that the proteins significantly altered during the
   differentiation and maturation of preadipocytes were enriched in
   various pathways, including “ribosome,” “Coronavirus disease—COVID-19,”
   and “extracellular matrix (ECM)-receptor interaction” (FDR < 0.05).

   Keywords: Subcutaneous preadipocytes, Subcutaneous adipocytes,
   Proteomics, Mass spectrometry
     __________________________________________________________________

   Specifications Table
   Subject Omics: Proteomics
     __________________________________________________________________

   Specific subject area Changes in protein profiles during subcutaneous
   adipocyte differentiation and maturation
   Type of data Tables
   Figures
   How the data were acquired Peptide samples were separated and
   identified using EASY-nLC 1000 and a Q Exactive Orbitrap mass
   spectrometer. Data were acquired using Xcalibur 4.3.73.11. The Q
   Exactive Orbitrap mass spectrometer is the same instrument that was
   used to measure lipids previously; however, the liquid chromatograph
   differs. MetaboAnalyst 5.0 was used for both lipid and protein
   analyses; whereas, Proteome Discoverer 2.2 and R software ver. 3.6.1
   were used only for protein analysis. The Gene Ontology term and Kyoto
   Encyclopedia of Genes and Genomes pathway enrichment analyses were
   performed exclusively for protein analysis, using DAVID Bioinformatics
   Resources 2021.
   Data format Raw
   Analyzed
   Filtered
   Description of data collection Three Caucasian-derived subcutaneous
   adipocyte cell lines were cultured and divided into five stages. From
   the cell lines, 15 samples were prepared. The cells used were the same
   as those used for lipid profile analysis previously reported. Proteins
   were extracted from the cells, proteolytically cleaved using trypsin,
   and analyzed using untargeted liquid chromatography and mass
   spectrometry.
   Data source location Advanced Research Facilities and Services,
   Hamamatsu University School of Medicine.
   Hamamatsu/Higashi-ku/Handayama
   Japan
   Data accessibility Repository name: ProteomeXchange
   Data identification number: PXD035060
   Direct URL to data:
   [25]http://proteomecentral.proteomexchange.org/cgi/GetDataset?ID=PXD035
   060
   Repository name: jPOST
   Data identification number: JPST001679
   Direct URL to data: [26]https://repository.jpostdb.org/entry/JPST001679
   Related data article Aya Kitamoto, Takuya Kitamoto, Data on changes in
   lipid profiles during the differentiation and maturation of human
   subcutaneous white adipocytes analyzed using chromatographic and
   bioinformatic tools. Data Brief (2022) 108245.
   [27]https://doi.org/10.1016/j.dib.2022.108245
   [28]Open in a new tab

Value of the Data

     * •
       This dataset adds to the previously reported data on the changes in
       lipid profiles that occur during the differentiation and maturation
       of Caucasian-derived subcutaneous adipocytes. The added dataset
       shows the changes in protein profiles that occur during
       differentiation and maturation. The data have been considerably
       expanded as multi-omics data.
     * •
       Multi-omics data allow researchers to better understand the process
       of adipocyte differentiation and maturation than single-omics data.
       In addition, these lipidomics and proteomics data will help
       identify targets for clinical, diagnostic, and therapeutic uses in
       lifestyle-related diseases such as obesity.

1. Data Description

   We used three cell lines of Caucasian-derived subcutaneous
   preadipocytes, designated the as Cell Line-1, Cell Line-2, and Cell
   Line-3. Each cell line was divided into five stages: subcutaneous
   preadipocytes (stage-1), following induction of differentiation into
   adipocytes (stage-2), from initiation of lipid droplet formation to
   mature subcutaneous adipocytes (stage-3 to stage-5 depending on lipid
   droplet amount and formation), for a total of 15 samples [29][1].
   Proteins were extracted from the cells in each stage, proteolytically
   cleaved using trypsin, and subsequently separated and identified using
   EASY-nLC 1000 (Thermo Fisher Scientific, San Jose, CA, USA) and a
   Q-Exactive Orbitrap mass spectrometer (Thermo Fisher Scientific). The
   data were acquired using Xcalibur 4.3.73.11 (Thermo Fisher Scientific).
   Mass spectrometry data were analyzed against the Swiss-Prot human
   database using the Mascot 2.6 search engine (Matrix Science, London,
   UK) and Proteome Discoverer 2.2 (Thermo Fisher Scientific). The
   analysis result from Proteome Discoverer 2.2 was filtered, and 1,871
   proteins identified with a high confidence were exported as an Excel
   file (Supplemental Table S1). A schematic of the cell culture schedule
   and proteomic analysis is shown in [30]Fig. 1. Partial least squares
   discriminant analysis (PLS-DA) and heatmap analysis were performed
   using MetaboAnalyst 5.0 ([31]https://www.metaboanalyst.ca), and stage-1
   to stage-5 cells were clearly separated by PLS-DA ([32]Fig. 2). The
   heatmaps of the top 100 proteins whose expression differed among the
   five stages are shown in [33]Fig. 3. Statistical analysis was performed
   using R software (ver. 3.6.1) using one-way repeated measures ANOVA on
   1,871 protein data, and 803 proteins were determined to be
   significantly differentially expressed (critical value F[0.05] (4,
   8) = 3.84, P-value < 0.05). Furthermore, a paired comparison test using
   Scheffe's post hoc test of these 803 proteins determined that 381
   proteins were statistically significant between any two stages
   (critical value F[0.05] (4, 10) = 3.48, P-value < 0.05). The
   corresponding P-values and mean and standard deviation for normalized
   protein abundances, and log[2] fold change in normalized protein
   abundance are shown in Supplemental Table S2. Protein accession values
   of the 381 statistically significant proteins were converted to Entrez
   gene IDs using the DAVID Bioinformatics Resources 2021
   ([34]https://david.ncifcrf.gov/). Gene Ontology (GO) term enrichment
   analysis [35][2] and Kyoto Encyclopedia of Genes and Genomes (KEGG)
   pathway enrichment analysis were performed using DAVID Bioinformatics
   Resources 2021. In total, 167 GO terms (46 molecular functions, 56
   biological processes, and 65 cellular components) were significantly
   enriched (FDR < 0.05) [36][3] and are listed in [37]Table 1. A total of
   14 KEGG pathways were significantly enriched (FDR < 0.05), namely
   “ribosome,” “Coronavirus disease – COVID-19,” “extracellular matrix
   (ECM)-receptor interaction,” “arginine and proline metabolism,” “fatty
   acid degradation,” “focal adhesion,” “pyruvate metabolism,”
   “spliceosome,” “valine, leucine and isoleucine degradation,” “protein
   digestion and absorption,” “PI3K-Akt signaling,” “proteoglycans in
   cancer,” “citrate cycle (TCA cycle),” and “beta-alanine metabolism”
   pathways. The descriptions of these 14 KEGG pathways are listed in
   [38]Table 2, and a list of the genes involved is provided in
   Supplemental Table S3. Box and whisker plots were added for the
   corresponding proteins in the 14 KEGG pathway maps, and they are shown
   in Supplemental Figure 1-A, -B, and -C. Fifteen raw data files (stages
   1 to 5 for Cell Line-1, Cell Line-2, and Cell Line-3, respectively)
   have been deposited in the ProteomeXchange Consortium via the jPOST
   partner repository with identifier PXD035060.

Fig. 1.

   [39]Fig 1
   [40]Open in a new tab

   Schematic of the experimental procedure. Schedule from cell culture to
   proteomic analysis. Human subcutaneous white preadipocytes were seeded
   in a 12-well plate on day 0. Twenty-four hours after seeding,
   spindle-shaped cells were observed. After approximately seven days, the
   preadipocytes achieved 100% confluence on preadipocyte growth medium
   (Stage-1). The preadipocytes were then differentiated for three
   consecutive days in preadipocyte differentiation medium (Stage-2).
   Three days after replacement with adipocyte nutrition medium, small
   lipid droplets appeared (Stage-3). The number of lipid droplets
   gradually increased (Stage-4) until the cytoplasm was filled with lipid
   droplets (Stage-5). Proteins were then extracted and cleaved with
   trypsin. The peptides were analyzed using liquid chromatography and
   mass spectrometry (LC-MS/MS). Data were analyzed using the Proteome
   Discoverer 2.2 using the Mascot 2.6 search engine.

Fig. 2.

   [41]Fig 2
   [42]Open in a new tab

   Partial Least Squares Discriminant Analysis (PLS-DA) of proteins among
   the five stages. Stage-1: subcutaneous preadipocytes, stage-2: after
   inducing adipocyte differentiation, stages-3 to -5: from initiation of
   lipid droplet formation to appearance of mature subcutaneous adipocytes
   (dependent on lipid droplet amount and formation). The ellipses
   represent the 95% confidence interval. This figure was generated using
   MetaboAnalyst 5.0.

Fig. 3.

   [43]Fig 3
   [44]Open in a new tab

   Hierarchical clustering heatmap analysis among the five stages
   performed using Ward's method with the Euclidean distance. Heatmaps
   showing the top 100 proteins that differed among the five stages (with
   the “do not cluster – samples” setting selected). The red, green, blue,
   light blue, and pink columns indicate stages-1 to -5, respectively. The
   number at the bottom indicates the cell line number. The color scale
   indicates the number of standard deviations from the overall average of
   the proteins. This figure was generated using MetaboAnalyst 5.0.

Table 1.

   Gene Ontology term enrichment analysis.
   Category Term Count % P FDR
   GOTERM_MF_DIRECT GO:0003723∼RNA binding 142 37.17 6.34 × 10^−61
   4.33 × 10^−58
   GOTERM_MF_DIRECT GO:0045296∼cadherin binding 38 9.95 3.92 × 10^−18
   1.34 × 10^−15
   GOTERM_MF_DIRECT GO:0051082∼unfolded protein binding 24 6.28
   9.92 × 10^−16 2.26 × 10^−13
   GOTERM_MF_DIRECT GO:0003735∼structural constituent of ribosome 28 7.33
   2.98 × 10^−15 5.09 × 10^−13
   GOTERM_MF_DIRECT GO:0005515∼protein binding 319 83.51 4.37 × 10^−15
   5.97 × 10^−13
   GOTERM_MF_DIRECT GO:0005201∼extracellular matrix structural constituent
   19 4.97 3.41 × 10^−10 3.51 × 10^−8
   GOTERM_MF_DIRECT GO:0003729∼mRNA binding 24 6.28 3.59 × 10^−10
   3.51 × 10^−8
   GOTERM_MF_DIRECT GO:0016887∼ATPase activity 28 7.33 6.79 × 10^−10
   5.80 × 10^−8
   GOTERM_MF_DIRECT GO:0048027∼mRNA 5′-UTR binding 10 2.62 1.65 × 10^−9
   1.25 × 10^−7
   GOTERM_MF_DIRECT GO:0042802∼identical protein binding 71 18.59
   4.11 × 10^−9 2.79 × 10^−7
   GOTERM_MF_DIRECT GO:0003743∼translation initiation factor activity 13
   3.40 4.66 × 10^−9 2.79 × 10^−7
   GOTERM_MF_DIRECT GO:0003779∼actin binding 27 7.07 4.90 × 10^−9
   2.79 × 10^−7
   GOTERM_MF_DIRECT GO:0044183∼protein binding involved in protein folding
   11 2.88 1.01 × 10^−8 5.31 × 10^−7
   GOTERM_MF_DIRECT GO:0051087∼chaperone binding 14 3.66 3.23 × 10^−7
   1.58 × 10^−5
   GOTERM_MF_DIRECT GO:0005524∼ATP binding 61 15.97 5.01 × 10^−7
   2.28 × 10^−5
   GOTERM_MF_DIRECT GO:0030020∼extracellular matrix structural constituent
   conferring tensile strength 9 2.36 1.32 × 10^−6 5.63 × 10^−5
   GOTERM_MF_DIRECT GO:0051015∼actin filament binding 18 4.71 2.54 × 10^−6
   1.02 × 10^−4
   GOTERM_MF_DIRECT GO:0005178∼integrin binding 15 3.93 4.79 × 10^−6
   1.82 × 10^−4
   GOTERM_MF_DIRECT GO:0042803∼protein homodimerization activity 34 8.90
   6.34 × 10^−6 2.28 × 10^−4
   GOTERM_MF_DIRECT GO:0004029∼aldehyde dehydrogenase (NAD) activity 6
   1.57 8.11 × 10^−6 2.77 × 10^−4
   GOTERM_MF_DIRECT GO:0031625∼ubiquitin protein ligase binding 20 5.24
   1.36 × 10^−5 4.44 × 10^−4
   GOTERM_MF_DIRECT GO:0048407∼platelet-derived growth factor binding 5
   1.31 4.73 × 10^−5 0.0015
   GOTERM_MF_DIRECT GO:0002020∼protease binding 11 2.88 6.41 × 10^−5
   0.0019
   GOTERM_MF_DIRECT GO:0003725∼double-stranded RNA binding 9 2.36
   1.17 × 10^−4 0.0033
   GOTERM_MF_DIRECT GO:0008201∼heparin binding 13 3.40 1.92 × 10^−4 0.0053
   GOTERM_MF_DIRECT GO:0008022∼protein C-terminus binding 14 3.66
   2.82 × 10^−4 0.0074
   GOTERM_MF_DIRECT GO:0005518∼collagen binding 8 2.09 3.86 × 10^−4 0.0098
   GOTERM_MF_DIRECT GO:0003697∼single-stranded DNA binding 10 2.62
   4.32 × 10^−4 0.011
   GOTERM_MF_DIRECT GO:0046332∼SMAD binding 7 1.83 5.31 × 10^−4 0.012
   GOTERM_MF_DIRECT GO:0003676∼nucleic acid binding 17 4.45 6.56 × 10^−4
   0.015
   GOTERM_MF_DIRECT GO:0003724∼RNA helicase activity 8 2.09 8.31 × 10^−4
   0.018
   GOTERM_MF_DIRECT GO:0051287∼NAD binding 6 1.57 0.0010 0.022
   GOTERM_MF_DIRECT GO:0008097∼5S rRNA binding 4 1.05 0.0012 0.024
   GOTERM_MF_DIRECT GO:0016504∼peptidase activator activity 4 1.05 0.0012
   0.024
   GOTERM_MF_DIRECT GO:0008307∼structural constituent of muscle 6 1.57
   0.0016 0.032
   GOTERM_MF_DIRECT GO:0023026∼MHC class II protein complex binding 5 1.31
   0.0020 0.037
   GOTERM_MF_DIRECT GO:0019899∼enzyme binding 18 4.71 0.0020 0.037
   GOTERM_MF_DIRECT GO:0051117∼ATPase binding 8 2.09 0.0022 0.039
   GOTERM_MF_DIRECT GO:0031072∼heat shock protein binding 7 1.83 0.0022
   0.039
   GOTERM_MF_DIRECT GO:0043394∼proteoglycan binding 4 1.05 0.0025 0.041
   GOTERM_MF_DIRECT GO:0044548∼S100 protein binding 4 1.05 0.0025 0.041
   GOTERM_MF_DIRECT GO:0048306∼calcium-dependent protein binding 8 2.09
   0.0025 0.041
   GOTERM_MF_DIRECT GO:0043022∼ribosome binding 7 1.83 0.0028 0.045
   GOTERM_MF_DIRECT GO:1990825∼sequence-specific mRNA binding 4 1.05
   0.0031 0.047
   GOTERM_MF_DIRECT GO:0050840∼extracellular matrix binding 5 1.31 0.0033
   0.050
   GOTERM_BP_DIRECT GO:0002181∼cytoplasmic translation 25 6.54
   2.36 × 10^−21 4.83 × 10^−18
   GOTERM_BP_DIRECT GO:0006412∼translation 33 8.64 5.61 × 10^−19
   5.75 × 10^−16
   GOTERM_BP_DIRECT GO:0006457∼protein folding 29 7.59 8.45 × 10^−19
   5.77 × 10^−16
   GOTERM_BP_DIRECT GO:0006413∼translational initiation 15 3.93
   2.02 × 10^−13 1.03 × 10^−10
   GOTERM_BP_DIRECT GO:0061077∼chaperone-mediated protein folding 14 3.66
   4.41 × 10^−13 1.81 × 10^−10
   GOTERM_BP_DIRECT GO:0050821∼protein stabilization 25 6.54 7.63 × 10^−13
   2.60 × 10^−10
   GOTERM_BP_DIRECT GO:2000767∼positive regulation of cytoplasmic
   translation 10 2.62 3.36 × 10^−12 9.85 × 10^−10
   GOTERM_BP_DIRECT GO:1904874∼positive regulation of telomerase RNA
   localization to Cajal body 9 2.36 1.01 × 10^−10 2.57 × 10^−8
   GOTERM_BP_DIRECT GO:1904851∼positive regulation of establishment of
   protein localization to telomere 7 1.83 9.65 × 10^−9 2.20 × 10^−6
   GOTERM_BP_DIRECT GO:1904871∼positive regulation of protein localization
   to Cajal body 7 1.83 2.09 × 10^−8 4.28 × 10^−6
   GOTERM_BP_DIRECT GO:0032212∼positive regulation of telomere maintenance
   via telomerase 9 2.36 2.06 × 10^−7 3.84 × 10^−5
   GOTERM_BP_DIRECT GO:0000398∼mRNA splicing, via spliceosome 18 4.71
   2.31 × 10^−7 3.94 × 10^−5
   GOTERM_BP_DIRECT GO:0070934∼CRD-mediated mRNA stabilization 6 1.57
   3.05 × 10^−7 4.47 × 10^−5
   GOTERM_BP_DIRECT GO:1900152∼negative regulation of nuclear-transcribed
   mRNA catabolic process, deadenylation-dependent decay 6 1.57
   3.05 × 10^−7 4.47 × 10^−5
   GOTERM_BP_DIRECT GO:0001649∼osteoblast differentiation 14 3.66
   5.04 × 10^−7 6.89 × 10^−5
   GOTERM_BP_DIRECT GO:0035987∼endodermal cell differentiation 8 2.09
   7.76 × 10^−7 9.94 × 10^−5
   GOTERM_BP_DIRECT GO:0071230∼cellular response to amino acid stimulus 10
   2.62 9.64 × 10^−7 1.16 × 10^−4
   GOTERM_BP_DIRECT GO:0006364∼rRNA processing 14 3.66 1.17 × 10^−6
   1.33 × 10^−4
   GOTERM_BP_DIRECT GO:0030199∼collagen fibril organization 10 2.62
   1.78 × 10^−6 1.92 × 10^−4
   GOTERM_BP_DIRECT GO:0006986∼response to unfolded protein 9 2.36
   9.71 × 10^−6 9.94 × 10^−4
   GOTERM_BP_DIRECT GO:1901998∼toxin transport 8 2.09 1.93 × 10^−5 0.0019
   GOTERM_BP_DIRECT GO:0070527∼platelet aggregation 8 2.09 2.25 × 10^−5
   0.0021
   GOTERM_BP_DIRECT GO:0006446∼regulation of translational initiation 7
   1.83 2.40 × 10^−5 0.0021
   GOTERM_BP_DIRECT GO:0045727∼positive regulation of translation 10 2.62
   2.55 × 10^−5 0.0022
   GOTERM_BP_DIRECT GO:0075522∼IRES-dependent viral translational
   initiation 5 1.31 4.02 × 10^−5 0.0033
   GOTERM_BP_DIRECT GO:0007155∼cell adhesion 26 6.81 7.40 × 10^−5 0.0058
   GOTERM_BP_DIRECT GO:0007339∼binding of sperm to zona pellucida 7 1.83
   1.08 × 10^−4 0.0082
   GOTERM_BP_DIRECT GO:0042273∼ribosomal large subunit biogenesis 6 1.57
   2.09 × 10^−4 0.015
   GOTERM_BP_DIRECT GO:0007160∼cell-matrix adhesion 10 2.62 2.10 × 10^−4
   0.015
   GOTERM_BP_DIRECT GO:1903608∼protein localization to cytoplasmic stress
   granule 4 1.05 2.34 × 10^−4 0.016
   GOTERM_BP_DIRECT GO:0007229∼integrin-mediated signaling pathway 10 2.62
   2.42 × 10^−4 0.016
   GOTERM_BP_DIRECT GO:0030198∼extracellular matrix organization 12 3.14
   2.52 × 10^−4 0.016
   GOTERM_BP_DIRECT GO:0001732∼formation of cytoplasmic translation
   initiation complex 5 1.31 2.64 × 10^−4 0.016
   GOTERM_BP_DIRECT GO:0008380∼RNA splicing 13 3.40 3.80 × 10^−4 0.023
   GOTERM_BP_DIRECT GO:0051973∼positive regulation of telomerase activity
   6 1.57 4.53 × 10^−4 0.027
   GOTERM_BP_DIRECT GO:0006739∼NADP metabolic process 4 1.05 5.46 × 10^−4
   0.030
   GOTERM_BP_DIRECT GO:0006177∼GMP biosynthetic process 4 1.05
   5.46 × 10^−4 0.030
   GOTERM_BP_DIRECT GO:0042026∼protein refolding 5 1.31 7.53 × 10^−4 0.041
   GOTERM_BP_DIRECT GO:0043588∼skin development 6 1.57 8.67 × 10^−4 0.046
   GOTERM_BP_DIRECT GO:0000380∼alternative mRNA splicing, via spliceosome
   5 1.31 8.97 × 10^−4 0.046
   GOTERM_CC_DIRECT GO:0070062∼extracellular exosome 168 43.98
   3.26 × 10^−62 1.41 × 10^−59
   GOTERM_CC_DIRECT GO:0005829∼cytosol 223 58.38 3.35 × 10^−40
   7.22 × 10^−38
   GOTERM_CC_DIRECT GO:0016020∼membrane 146 38.22 2.01 × 10^−38
   2.89 × 10^−36
   GOTERM_CC_DIRECT GO:0005925∼focal adhesion 53 13.87 1.27 × 10^−27
   1.36 × 10^−25
   GOTERM_CC_DIRECT GO:1990904∼ribonucleoprotein complex 32 8.38
   1.39 × 10^−22 1.20 × 10^−20
   GOTERM_CC_DIRECT GO:0022626∼cytosolic ribosome 24 6.28 8.49 × 10^−22
   6.10 × 10^−20
   GOTERM_CC_DIRECT GO:0022627∼cytosolic small ribosomal subunit 18 4.71
   1.94 × 10^−18 1.19 × 10^−16
   GOTERM_CC_DIRECT GO:0005737∼cytoplasm 176 46.07 4.98 × 10^−17
   2.68 × 10^−15
   GOTERM_CC_DIRECT GO:0005840∼ribosome 24 6.28 5.29 × 10^−13
   2.53 × 10^−11
   GOTERM_CC_DIRECT GO:1904813∼ficolin-1-rich granule lumen 20 5.24
   1.78 × 10^−12 7.66 × 10^−11
   GOTERM_CC_DIRECT GO:0034774∼secretory granule lumen 19 4.97
   4.74 × 10^−12 1.86 × 10^−10
   GOTERM_CC_DIRECT GO:0015935∼small ribosomal subunit 11 2.88
   6.77 × 10^−11 2.43 × 10^−9
   GOTERM_CC_DIRECT GO:0005739∼mitochondrion 61 15.97 1.68 × 10^−9
   5.56 × 10^−8
   GOTERM_CC_DIRECT GO:0005654∼nucleoplasm 121 31.68 1.86 × 10^−9
   5.72 × 10^−8
   GOTERM_CC_DIRECT GO:0005788∼endoplasmic reticulum lumen 25 6.54
   4.09 × 10^−9 1.17 × 10^−7
   GOTERM_CC_DIRECT GO:0005832∼chaperonin-containing T-complex 7 1.83
   1.75 × 10^−8 4.72 × 10^−7
   GOTERM_CC_DIRECT GO:0005581∼collagen trimer 14 3.66 1.87 × 10^−8
   4.74 × 10^−7
   GOTERM_CC_DIRECT GO:0005634∼nucleus 160 41.88 2.55 × 10^−8 6.11 × 10^−7
   GOTERM_CC_DIRECT GO:0005576∼extracellular region 76 19.90 3.55 × 10^−8
   8.05 × 10^−7
   GOTERM_CC_DIRECT GO:0010494∼cytoplasmic stress granule 13 3.40
   5.91 × 10^−8 1.27 × 10^−6
   GOTERM_CC_DIRECT GO:0005759∼mitochondrial matrix 26 6.81 8.90 × 10^−8
   1.83 × 10^−6
   GOTERM_CC_DIRECT GO:0101031∼chaperone complex 8 2.09 1.01 × 10^−7
   1.98 × 10^−6
   GOTERM_CC_DIRECT GO:0001725∼stress fiber 12 3.14 1.06 × 10^−7
   1.99 × 10^−6
   GOTERM_CC_DIRECT GO:0042788∼polysomal ribosome 9 2.36 1.28 × 10^−7
   2.30 × 10^−6
   GOTERM_CC_DIRECT GO:0042470∼melanosome 13 3.40 5.08 × 10^−7
   8.76 × 10^−6
   GOTERM_CC_DIRECT GO:0071013∼catalytic step 2 spliceosome 12 3.14
   6.63 × 10^−7 1.10 × 10^−5
   GOTERM_CC_DIRECT GO:0005681∼spliceosomal complex 13 3.40 1.39 × 10^−6
   2.22 × 10^−5
   GOTERM_CC_DIRECT GO:0015629∼actin cytoskeleton 19 4.97 1.45 × 10^−6
   2.23 × 10^−5
   GOTERM_CC_DIRECT GO:0043202∼lysosomal lumen 12 3.14 1.80 × 10^−6
   2.67 × 10^−5
   GOTERM_CC_DIRECT GO:0005844∼polysome 8 2.09 3.95 × 10^−6 5.68 × 10^−5
   GOTERM_CC_DIRECT GO:0031012∼extracellular matrix 18 4.71 7.18 × 10^−6
   9.98 × 10^−5
   GOTERM_CC_DIRECT GO:0035578∼azurophil granule lumen 11 2.88
   7.76 × 10^−6 1.04 × 10^−4
   GOTERM_CC_DIRECT GO:0033290∼eukaryotic 48S preinitiation complex 6 1.57
   8.20 × 10^−6 1.07 × 10^−4
   GOTERM_CC_DIRECT GO:0022625∼cytosolic large ribosomal subunit 9 2.36
   1.34 × 10^−5 1.70 × 10^−4
   GOTERM_CC_DIRECT GO:0016282∼eukaryotic 43S preinitiation complex 6 1.57
   1.56 × 10^−5 1.92 × 10^−4
   GOTERM_CC_DIRECT GO:0005764∼lysosome 19 4.97 1.62 × 10^−5 1.94 × 10^−4
   GOTERM_CC_DIRECT GO:0005903∼brush border 9 2.36 1.94 × 10^−5
   2.26 × 10^−4
   GOTERM_CC_DIRECT GO:0044297∼cell body 10 2.62 2.23 × 10^−5 2.53 × 10^−4
   GOTERM_CC_DIRECT GO:0005604∼basement membrane 10 2.62 5.62 × 10^−5
   6.22 × 10^−4
   GOTERM_CC_DIRECT GO:0001726∼ruffle 10 2.62 1.08 × 10^−4 0.0012
   GOTERM_CC_DIRECT GO:0070937∼CRD-mediated mRNA stability complex 4 1.05
   1.24 × 10^−4 0.0013
   GOTERM_CC_DIRECT GO:0005689∼U12-type spliceosomal complex 6 1.57
   1.83 × 10^−4 0.0018
   GOTERM_CC_DIRECT GO:0005852∼eukaryotic translation initiation factor 3
   complex 5 1.31 1.83 × 10^−4 0.0018
   GOTERM_CC_DIRECT GO:0030018∼Z disc 11 2.88 1.92 × 10^−4 0.0019
   GOTERM_CC_DIRECT GO:0031982∼vesicle 12 3.14 3.33 × 10^−4 0.0031
   GOTERM_CC_DIRECT GO:0005730∼nucleolus 44 11.52 3.36 × 10^−4 0.0031
   GOTERM_CC_DIRECT GO:0002199∼zona pellucida receptor complex 4 1.05
   3.39 × 10^−4 0.0031
   GOTERM_CC_DIRECT GO:0005643∼nuclear pore 8 2.09 9.27 × 10^−4 0.0083
   GOTERM_CC_DIRECT GO:0048471∼perinuclear region of cytoplasm 28 7.33
   0.0010 0.0090
   GOTERM_CC_DIRECT GO:0072562∼blood microparticle 10 2.62 0.0016 0.014
   GOTERM_CC_DIRECT GO:0045335∼phagocytic vesicle 7 1.83 0.0017 0.014
   GOTERM_CC_DIRECT GO:0005884∼actin filament 8 2.09 0.0018 0.015
   GOTERM_CC_DIRECT GO:0005783∼endoplasmic reticulum 36 9.42 0.0019 0.015
   GOTERM_CC_DIRECT GO:0070418∼DNA-dependent protein kinase complex 3 0.79
   0.0020 0.016
   GOTERM_CC_DIRECT GO:0005862∼muscle thin filament tropomyosin 3 0.79
   0.0020 0.016
   GOTERM_CC_DIRECT GO:0032991∼macromolecular complex 25 6.54 0.0029 0.022
   GOTERM_CC_DIRECT GO:0005874∼microtubule 15 3.93 0.0033 0.025
   GOTERM_CC_DIRECT GO:0000502∼proteasome complex 6 1.57 0.0042 0.031
   GOTERM_CC_DIRECT GO:0009986∼cell surface 23 6.02 0.0043 0.031
   GOTERM_CC_DIRECT GO:0071682∼endocytic vesicle lumen 4 1.05 0.0043 0.031
   GOTERM_CC_DIRECT GO:0005912∼adherens junction 10 2.62 0.0044 0.031
   GOTERM_CC_DIRECT GO:0005615∼extracellular space 52 13.61 0.0058 0.040
   GOTERM_CC_DIRECT GO:0071011∼precatalytic spliceosome 4 1.05 0.0058
   0.040
   GOTERM_CC_DIRECT GO:0005856∼cytoskeleton 20 5.24 0.0060 0.040
   GOTERM_CC_DIRECT GO:0071541∼eukaryotic translation initiation factor 3
   complex, eIF3m 3 0.79 0.0069 0.046
   GOTERM_CC_DIRECT GO:0030863∼cortical cytoskeleton 4 1.05 0.0077 0.050
   [45]Open in a new tab

   Gene Ontology (GO) comprised of three categories: molecular function
   (MF), biological process (BP), and cellular component (CC). P-values
   were derived using Fisher's exact test. FDR, false discovery rate.

Table 2.

   Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis.
   Category Term Count P FDR
   hsa03010 Ribosome 28 1.84 × 10^−13 4.62 × 10^−11
   hsa05171 Coronavirus disease - COVID-19 28 1.73 × 10^−9 2.17 × 10^−7
   hsa04512 ECM-receptor interaction 15 3.71 × 10^−7 3.11 × 10^−5
   hsa00330 Arginine and proline metabolism 10 2.00 × 10^−5 0.0013
   hsa00071 Fatty acid degradation 9 3.92 × 10^−5 0.0020
   hsa04510 Focal adhesion 18 1.35 × 10^−4 0.0057
   hsa00620 Pyruvate metabolism 8 5.08 × 10^−4 0.016
   hsa03040 Spliceosome 14 5.44 × 10^−4 0.016
   hsa00280 Valine, leucine, and isoleucine degradation 8 5.80 × 10^−4
   0.016
   hsa04974 Protein digestion and absorption 11 0.0012 0.027
   hsa04151 PI3K-Akt signaling pathway 23 0.0012 0.027
   hsa05205 Proteoglycans in cancer 16 0.0015 0.032
   hsa00020 Citrate cycle (TCA cycle) 6 0.0020 0.038
   hsa00410 beta-Alanine metabolism 6 0.0023 0.041
   [46]Open in a new tab

   Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment
   analysis was performed using DAVID Bioinformatics Resources version
   2021. P-values were derived using Fisher's exact test. FDR, false
   discovery rate.

2. Experimental Design, Materials and Methods

2.1. Cell culture, fluorescent staining, and microscopy

   Cell culture, fluorescent staining, and microscopy of the lipid
   droplets and nuclei were previously performed and reported [47][1].
   Cell Line-1 and -2 were purchased from Promocell (GmbH, Heidelberg,
   Germany), and Cell Line-3 was purchased from Zen-Bio (Zen-Bio, Inc.,
   Research Triangle Park, NC, USA). All three cell lines were derived
   from the subcutaneous adipose tissue of the abdomen of Caucasian women
   of mean age 51.3 ± 5 years. The cells were grown according to the
   manufacturers’ recommendations and differentiated into adipocytes in
   vitro. The preadipocytes were cultured in Promocell Preadipocyte Growth
   Medium until 100% confluence (stage-1). The medium was then changed to
   Promocell Preadipocyte Differentiation Medium to induce differentiation
   into adipocytes over 3 days (stage-2). After the differentiation, the
   medium was replaced to promote adipocyte nutrition, the cells were
   cultured for 3 days, and small lipid droplets were observed (stage-3).
   After another 2 days, additional lipid droplets appeared (stage-4), and
   after another 2 days, numerous lipid droplets filled the cytoplasm
   (stage-5). During the culture period, the medium was changed every 2–3
   days. Lipid droplets were stained with boron-dipyrromethene (BODIPY;
   Thermo Fisher Scientific) using the Adipocyte Fluorescent Staining kit
   (PMC, Hokkaido, Japan), and the nuclei were stained with Hoechst 33342
   solution (DOJINDO). Images of cells were obtained using an Olympus
   IX-83 inverted fluorescence microscope (Olympus, Tokyo, Japan). Images
   of the nuclei and lipid droplets in each stage are presented in
   Kitamoto and Kitamoto, 2022 [48][1].

2.2. Protein extraction and sample preparation

   The medium was aspirated from the Caucasian-derived cultured
   subcutaneous adipocytes and the cells were washed with HEPES buffered
   balanced salt solution (Promocell). The cells were treated with
   trypsin/EDTA (0.025%/0.01%) solution at 25°C, and trypsin was
   neutralized with a neutralization solution (Promocell). The cell
   suspension was transferred into a 1.5-mL tube and centrifuged at
   220 × g for 3 min. The supernatant was removed, and the cell
   precipitates were resuspended in 100 µL of Milli-Q water. The collected
   cell samples were lysed with 150 µL of lysis buffer (Mammalian Cell PE
   LB; G-Biosciences, St. Louis, MO, USA) and then agitated gently for 10
   min at room temperature (20–25°C). Protein concentrations were measured
   using the bicinchoninic acid (BCA) assay with a Pierce Micro BCA
   Protein Assay Kit (Pierce, Rockford, IL, USA). Twenty micrograms of
   protein was precipitated with five volumes of ice-cold acetone for 2 h
   at -20°C. The proteins were pelleted via centrifugation at 13,000 × g
   for 15 min at 4°C. The supernatant was removed, and the pellet was
   dried using miVac Duo LV (Genevac, Ipswich, England) and resuspended in
   25.5 µL of 50 mM ammonium bicarbonate (FUJIFILM Wako Pure Chemical,
   Osaka, Japan). The protein lysate was reduced by adding 1.5 µL of 500
   mM dithiothreitol (FUJIFILM Wako Pure Chemical) for 5 min at 95°C and
   alkylated by adding 3 µL of 500 mM iodoacetamide (FUJIFILM Wako Pure
   Chemical) for 20 min at room temperature (20 –25°C) in the dark. The
   proteins were digested with 4 µL of trypsin (100 ng/µL) (Pierce trypsin
   protease, MS-grade; Thermo Fisher Scientific) at 37°C for 4 h, followed
   by incubation with another 4 µL of trypsin (100 ng/µL) overnight at
   30°C, and quenched by adding trifluoroacetic acid (Kanto Kagaku, Tokyo,
   Japan) to a final concentration of 5%. The peptide samples were
   purified using a MonoSpin C18 column (GL Science, Tokyo, Japan), dried
   using miVac Duo LV, and redissolved in 100 µL of 0.1% formic acid
   (Kanto Kagaku).

2.3. Untargeted liquid chromatography and mass spectrometry

   The peptide samples from the cultured Caucasian-derived subcutaneous
   adipocytes were analyzed using EASY-nLC 1000 and a Q-Exactive Orbitrap
   mass spectrometer. One microliter of each peptide sample was separated
   using a C18 column (3 µm, 0.075 mm × 125 mm, NTCC-360/75-3-125; Nikkyo
   Technos). The mobile phases were 0.1% formic acid in water (A) (Kanto
   Kagaku) and 0.1% formic acid in acetonitrile (B) (Kanto Kagaku). The
   flow rate was set at 300 nL/min. The gradient started with 0% mobile
   phase B, which was increased to 35% over 50 min, and to 100% over an
   additional 5 min, where it was maintained for 10 min. Mass spectrometry
   measurements were performed in the positive-ion mode. The full scan was
   performed at a resolution of 70,000 with a mass range of 350–1800 m/z,
   automatic gain control target of 3 × 10^6 ions, and a maximum ion
   injection time of 60 ms. Data-dependent MS/MS (top 10) was performed
   using the following parameters: resolution, 17,500; automatic gain
   control, 1 × 10^5; maximum injection time, 55 ms; isolation window, 1.6
   m/z; normalized collision energy, 27; intensity threshold, 9.1 × 10^3;
   dynamic exclusion time, 20 s; and charge exclusion, unassigned, 1, 5–8,
   and >8. All raw data files have been deposited at the ProteomeXchange
   Consortium via the jPOST partner repository [49][4] with identifier
   PXD035060.

2.4. Data analysis (statistical analysis)

   Mass spectrometric data were analyzed using Proteome Discoverer 2.2
   with the Mascot 2.6 search engine against the human database (20,376
   entries; reviewed) from Swiss-Prot (Version: 2020_04) with the
   following parameters: enzyme name, trypsin; maximum missed cleavage
   sites, 2; precursor mass tolerance, 10 ppm; fragment mass tolerance,
   0.02 Da; dynamic modifications, methionine oxidation; static
   modification, cysteine carbamidomethylation; and peptide confidence,
   high. Normalization of the total peptide amount, scaling on an average,
   was performed. The analysis result from Proteome Discoverer 2.2 was
   filtered, and proteins identified with a high confidence were exported
   as an Excel file (Supplemental Table S1). Further analysis was
   performed with MetaboAnalyst 5.0 using normalized abundance values from
   the analysis results with Proteome Discoverer 2.2. Proteins with >70%
   missing normalized abundance values were excluded, and the remaining
   missing values were set to be replaced with 1/5 of the minimum positive
   value of each variable. The data were log-transformed and autoscaled.
   PLS-DA and heatmap analysis were performed using MetaboAnalyst 5.0
   ([50]Figs. 2 and [51]3). For heatmap analysis, we used the top 100
   proteins and chose the “do not cluster - samples” setting. The data
   processed using MetaboAnalyst 5.0 were exported, and statistical
   analyses were performed using R software (ver. 3.6.1)
   ([52]https://www.r-project.org/). A one-way ANOVA of repeated
   measurements was conducted using anovakun (ver. 4.8.6) [53][5],
   followed by Scheffe's post hoc test using Scheffe. R [54][6] and the
   agricolae package (ver. 1.3-5) [55][7] for comparisons between stages.
   A total of 381 differentially expressed proteins (P-value < 0.05)
   between any two stages were filtered (Supplemental Table S2) and used
   for analysis using DAVID Bioinformatics Resources 2021
   ([56]https://david.ncifcrf.gov/). The GO term enrichment, which
   evaluates molecular functions, biological processes, and cellular
   components ([57]Table 1), and KEGG pathway enrichment analyses
   ([58]Table 2 and Supplemental Table S3) were performed using DAVID
   Bioinformatics Resources 2021. Box and whisker plots were obtained
   using MetaboAnalyst 5.0, and added to the corresponding proteins in the
   KEGG pathway maps; they are shown in Supplemental Figure 1-A, -B, and
   -C.

Ethics Statements

   The authors declare that this work did not involve the use of human
   subjects, social media data, or experimentation with animals.

CRediT authorship contribution statement

   Takuya Kitamoto: Conceptualization, Methodology, Software,
   Investigation, Formal analysis, Writing – original draft. Aya Kitamoto:
   Conceptualization, Validation, Investigation, Formal analysis, Writing
   – review & editing.

Declaration of Competing Interest

   The authors declare that they have no known competing financial
   interests or personal relationships that could have influenced the work
   reported in this paper.

Acknowledgments