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<p><strong>Sample preparation for proteomic analysis</strong></p>
<p>Proteins were extracted from adipose tissue samples in lysis buffer containing 12 mM sodium deoxycholate, 12 mM sodium N-dodecanoylsarcosinate, and 100 mM Tris.Cl pH 9.0, with cOmplete, mini, EDTA-free Protease Inhibitor Cocktail (Roche, Switzerland), using homogenization with a glass dounce followed by sonication for 15 minutes using a Bioruptor water bath sonicator on high power, with cycles of one min sonication followed by one min rest (Cosmo Bio Co. Ltd., Japan). The samples were centrifuged at 18,000 x <em>g</em>, for 20 min at 4 <sup>o</sup>C and the supernatant fractions were taken. Protein concentrations were determined using a Pierce BCA Assay Kit (Thermo Fisher Scientific, USA), according to manufacturer’s instructions. Samples were prepared for liquid chromatography tandem mass spectrometry (LC-M/MS) using the Phase Transfer Surfactant Method (Masuda <em>et al</em>., 2008; Masuda <em>et al</em>., 2009), with minor modifications as previously described (Mostafa <em>et al</em>., 2020). Afterwards, dried Lys-C/tryptic peptides were dissolved in 0.1% TFA and desalted using MonoSpin C18 columns (GL Sciences Inc., Japan). Peptides were eluted from C18 columns in 0.1% (v/v) TFA in 50% (v/v) acetonitrile and dried in a centrifugal vacuum concentrator. Tryptic peptides were dissolved in 0.1% (v/v) formic acid, 3% (v/v) acetonitrile in water for MS analysis and the peptide concentrations were determined using a Pierce Quantitative Colorimetric Peptide Assay Kit (Thermo Fisher). A portion of the peptides from the samples were pooled and fractionated using a Pierce High pH Reversed-Phase (HPRP) Peptide Fractionation Kit (Thermo Fisher) to generate a spectral library.</p>
<p><strong>MS measurement</strong></p>
<p>Samples were measured using a Q Exactive Plus Orbitrap LC–MS/MS System (Thermo Fisher), equipped with a Nanospray Flex ion source. Peptides were separated on 3-µm particle, 75-µm inner diameter, 12-cm filling length C18 columns (Nikkyo Technos Co., Ltd., Japan). For each sample, 600 ng was injected and the samples were measured with data-independent acquisition (DIA). For HPRP fractions, 450 ng was injected and the samples were measured with data-dependent acquisition (DDA). LC-MS/MS conditions were as previously described (Mostafa <em>et al</em>., 2020), except for DDA the first mass for MS2 scans was not fixed and for DIA the AGC target of DIA segments was 3e<sup>6</sup>.</p>
<p><strong>Protein identification and quantification</strong></p>
<p>Raw files from DDA measurements were searched against a mouse-specific database (uniprot-reviewed_Mus_musculus_10090_.fasta) using Proteome Discoverer v2.4 software (Thermo Fisher). Filtered output was used to generate a sample-specific spectral library using Spectronaut software (Biognosys, Switzerland). Raw files from DIA measurements were used for quantitative data extraction with the generated spectral library, as previously described (Mostafa <em>et al</em>., 2020). FDR was estimated with the mProphet approach (Reiter <em>et al</em>., 2011) and set to 0.01 at both peptide precursor level and protein level (Rosenberger <em>et al</em>., 2017). </p>
<p><strong>References</strong></p>
<p>Masuda, T., Tomita, M., and Ishihama, Y. (2008) Phase transfer surfactant-aided trypsin digestion for membrane proteome analysis. <em>J. Proteome Res</em>. <strong>7</strong>, 731-740.</p>
<p>Masuda, T., Saito, N., Tomita, M., and Ishihama, Y. (2009) Unbiased quantification of <em>Escherichia coli </em>membrane proteome using phase transfer surfactants. <em>Mol. Cell. Proteomics</em> <strong>8</strong>, 2770-2777.</p>
<p>Mostafa, D., Yanagiya, A., Georgiadou, E., Wu, Y., Stylianides, T., Rutter, G. A., Suzuki, T., & Yamamoto, T. (2020). Loss of β-cell identity and diabetic phenotype in mice caused by disruption of CNOT3-dependent mRNA deadenylation. <em>Commun. Biol.</em> <strong>3</strong>, 476.</p>
<p>Reiter, L., Rinner, O., Picotti, P., Hüttenhain, R., Beck, M., Hengartner, M. O., and Aebersold, R. (2011) mProphet: automated data processing and statistical validation for large scale SRM experiments. <em>Nat. Methods</em> <strong>8</strong>, 430–435.</p>
<p>Rosenberger, G., Bludau, I., Schmitt, U., Heusel, M., Hunter, C. L., Liu, Y., MacCoss, M. J., MacLean, B. X., Nesvizhskii, A. I., Pedrioli, P. G. A., Reiter, L., Röst, H. L., Tate, S., Ting, Y. S., Collins, B. C., and Aebersold, R. (2017) Statistical control of peptide and protein error rates in large-scale targeted data-independent acquisition analyses. <em>Nat. Methods</em> <strong>14</strong>, 921–927.</p>
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