Proteomics applications in next generation induced pluripotent stem cell models

References

• Takahashi K, Yamanaka S. Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell. 2006;126(4):663–676. doi: 10.1016/j.cell.2006.07.024
   PubMed Web of Science ®Google Scholar
• Takahashi K, Yamanaka S. A decade of transcription factor-mediated reprogramming to pluripotency. Nat Rev Mol Cell Biol. 2016;17(3):183–193. doi: 10.1038/nrm.2016.8
   PubMed Web of Science ®Google Scholar
• Sekine K, Tsuzuki S, Yasui R, et al. Robust detection of undifferentiated iPSC among differentiated cells. Sci Rep. 2020;10(1):10293. doi: 10.1038/s41598-020-66845-6
   PubMed Web of Science ®Google Scholar
• Zhou Y, Wang L, Liu Z, et al. Comparative gene expression analyses reveal distinct molecular signatures between differentially reprogrammed cardiomyocytes. Cell Rep. 2017;20(13):3014–3024. doi: 10.1016/j.celrep.2017.09.005
   PubMed Web of Science ®Google Scholar
• Müller F-J, Schuldt BM, Williams R, et al. A bioinformatic assay for pluripotency in human cells. Nat Methods. 2011;8(4):315–317. doi: 10.1038/nmeth.1580
   PubMed Web of Science ®Google Scholar
• Cho S, Discher DE, Leong KW, et al. Challenges and opportunities for the next generation of cardiovascular tissue engineering. Nat Methods. 2022;19(9):1064–1071. doi: 10.1038/s41592-022-01591-3
   PubMed Web of Science ®Google Scholar
• Sharma A, Sances S, Workman MJ, et al. Multi-lineage human iPSC-derived platforms for disease modeling and drug discovery. Cell Stem Cell. 2020;26(3):309–329. doi: 10.1016/j.stem.2020.02.011
   PubMed Web of Science ®Google Scholar
• Clark DJ, Dhanasekaran SM, Petralia F, et al. Integrated proteogenomic characterization of clear cell renal cell carcinoma. Cell. 2019;179(4):964–983.e31. doi: 10.1016/j.cell.2019.10.007
   PubMed Web of Science ®Google Scholar
• Srivastava H, Lippincott MJ, Currie J, et al. Protein prediction models support widespread post-transcriptional regulation of protein abundance by interacting partners. In: Käll L, editor PLoS Comput Biol. Vol. 18, 2022. p. e1010702. doi:10.1371/journal.pcbi.1010702
   Google Scholar
• Franks A, Airoldi E, Slavov N, et al. Post-transcriptional regulation across human tissues. PLoS Comput Biol. 2017;13(5):e1005535. doi: 10.1371/journal.pcbi.1005535
   PubMed Web of Science ®Google Scholar
• Mann M, Kumar C, Zeng W-F, et al. Artificial intelligence for proteomics and biomarker discovery. Cell Syst. 2021;12(8):759–770. doi: 10.1016/j.cels.2021.06.006
   PubMed Web of Science ®Google Scholar
• Macklin A, Khan S, Kislinger T. Recent advances in mass spectrometry based clinical proteomics: applications to cancer research. Clin Proteomics. 2020;17(1):17. doi: 10.1186/s12014-020-09283-w
   PubMed Web of Science ®Google Scholar
• Shuken SR. An introduction to mass spectrometry-based proteomics. J Proteome Res. 2023;22(7):2151–2171. doi: 10.1021/acs.jproteome.2c00838
   PubMed Web of Science ®Google Scholar
• Jiang Y, Rex DAB, Schuster D, et al. Comprehensive Overview of Bottom-Up Proteomics using Mass spectrometry. ArXiv. 2023;arXiv:2311.07791v1.
   Google Scholar
• Wiśniewski JR, Zougman A, Nagaraj N, et al. Universal sample preparation method for proteome analysis. Nat Methods. 2009;6(5):359–362. doi: 10.1038/nmeth.1322
   PubMed Web of Science ®Google Scholar
• Hughes CS, Moggridge S, Müller T, et al. Single-pot, solid-phase-enhanced sample preparation for proteomics experiments. Nat Protoc. 2019;14(1):68–85. doi: 10.1038/s41596-018-0082-x
   PubMed Web of Science ®Google Scholar
• Johnston SM, Webber KGI, Xie X, et al. Rapid, one-step sample processing for label-free single-cell proteomics. J Am Soc Mass Spectrom. 2023;34(8):1701–1707. doi: 10.1021/jasms.3c00159
   PubMed Web of Science ®Google Scholar
• Bennett HM, Stephenson W, Rose CM, et al. Single-cell proteomics enabled by next-generation sequencing or mass spectrometry. Nat Methods. 2023;20(3):363–374. doi: 10.1038/s41592-023-01791-5
   PubMed Web of Science ®Google Scholar
• Han Y, Thomas CT, Wennersten SA, et al. 2021. Shotgun proteomics sample processing automated by an open-source lab robot. J Vis Exp JoVE. (176). doi: 10.3791/63092-v
   Web of Science ®Google Scholar
• Ctortecka C, Hartlmayr D, Seth A, et al. An automated nanowell-array workflow for quantitative multiplexed single-cell proteomics sample preparation at high sensitivity. Mol & Cell Proteomics. 2023;22(12):100665. doi: 10.1016/j.mcpro.2023.100665
   PubMed Web of Science ®Google Scholar
• Müller T, Kalxdorf M, Longuespée R, et al. Automated sample preparation with SP 3 for low‐input clinical proteomics. Mol Syst Biol. 2020;16(1):e9111. doi: 10.15252/msb.20199111
   PubMed Web of Science ®Google Scholar
• Borteçen T, Müller T, Krijgsveld J. An integrated workflow for quantitative analysis of the newly synthesized proteome. Nat Commun. 2023;14(1):8237. doi: 10.1038/s41467-023-43919-3
   PubMed Web of Science ®Google Scholar
• Vargas-Diaz D, Altelaar M. Automated high-throughput method for the fast, robust, and reproducible enrichment of newly synthesized proteins. J Proteome Res. 2022;21(1):189–199. doi: 10.1021/acs.jproteome.1c00743
   PubMed Web of Science ®Google Scholar
• Van Oostrum M, Campbell B, Seng C, et al. Surfaceome dynamics reveal proteostasis-independent reorganization of neuronal surface proteins during development and synaptic plasticity. Nat Commun. 2020;11(1):4990. doi: 10.1038/s41467-020-18494-6
   PubMed Web of Science ®Google Scholar
• Rajczewski AT, Jagtap PD, Griffin TJ. An overview of technologies for MS-based proteomics-centric multi-omics. Expert Rev Proteomics. 2022;19(3):165–181. doi: 10.1080/14789450.2022.2070476
   PubMed Web of Science ®Google Scholar
• Ludwig C, Gillet L, Rosenberger G, et al. Data‐independent acquisition‐based SWATH ‐ MS for quantitative proteomics: a tutorial. Mol Syst Biol. 2018;14(8):e8126. doi: 10.15252/msb.20178126
   PubMed Web of Science ®Google Scholar
• Demichev V, Messner CB, Vernardis SI, et al. DIA-NN: neural networks and interference correction enable deep proteome coverage in high throughput. Nat Methods. 2020;17(1):41–44. doi: 10.1038/s41592-019-0638-x
   PubMed Web of Science ®Google Scholar
• Yu F, Teo GC, Kong AT, et al. Analysis of DIA proteomics data using MSFragger-DIA and FragPipe computational platform. Nat Commun. 2023;14(1):4154. doi: 10.1038/s41467-023-39869-5
   PubMed Web of Science ®Google Scholar
• Kohler D, Staniak M, Tsai T-H, et al. Msstats version 4.0: statistical analyses of quantitative mass spectrometry-based proteomic experiments with chromatography-based quantification at scale. J Proteome Res. 2023;22(5):1466–1482. doi: 10.1021/acs.jproteome.2c00834
   PubMed Web of Science ®Google Scholar
• Munoz J, Low TY, Kok YJ, et al. The quantitative proteomes of human-induced pluripotent stem cells and embryonic stem cells. Mol Syst Biol. 2011;7(1):550. doi: 10.1038/msb.2011.84
   PubMedGoogle Scholar
• Phanstiel DH, Brumbaugh J, Wenger CD, et al. Proteomic and phosphoproteomic comparison of human ES and iPS cells. Nat Methods. 2011;8(10):821–827. doi: 10.1038/nmeth.1699
   PubMed Web of Science ®Google Scholar
• Hao J, Li W, Dan J, et al. Reprogramming- and pluripotency-associated membrane proteins in mouse stem cells revealed by label-free quantitative proteomics. J Proteomics. 2013;86:70–84. doi: 10.1016/j.jprot.2013.04.018
   PubMed Web of Science ®Google Scholar
• Tien W-S, Chen P-M, Chuang C-Y, et al. Combining membrane proteomics and computational three-way pathway analysis revealed signalling pathways preferentially regulated in human iPscs and human ESCs. Sci Rep. 2017;7(1):15055. doi: 10.1038/s41598-017-15347-z
   PubMedGoogle Scholar
• Ohi Y, Qin H, Hong C, et al. Incomplete DNA methylation underlies a transcriptional memory of somatic cells in human iPS cells. Nat Cell Biol. 2011;13(5):541–549. doi: 10.1038/ncb2239
   PubMed Web of Science ®Google Scholar
• Wang Y, Zhao C, Hou Z, et al. Unique molecular events during reprogramming of human somatic cells to induced pluripotent stem cells (iPscs) at naïve state. Elife. 2018;7:e29518. doi: 10.7554/eLife.29518
   PubMed Web of Science ®Google Scholar
• Apostolou E, Stadtfeld M. Cellular trajectories and molecular mechanisms of iPSC reprogramming. Curr Opin Genet Dev. 2018;52:77–85. doi: 10.1016/j.gde.2018.06.002
   PubMed Web of Science ®Google Scholar
• Hansson J, Rafiee MR, Reiland S, et al. Highly coordinated proteome dynamics during reprogramming of somatic cells to pluripotency. Cell Rep. 2012;2(6):1579–1592. doi: 10.1016/j.celrep.2012.10.014
   PubMed Web of Science ®Google Scholar
• Sabatier P, Beusch CM, Saei AA, et al. An integrative proteomics method identifies a regulator of translation during stem cell maintenance and differentiation. Nat Commun. 2021;12(1):6558. doi: 10.1038/s41467-021-26879-4
   PubMed Web of Science ®Google Scholar
• Sridharan R, Gonzales-Cope M, Chronis C, et al. Proteomic and genomic approaches reveal critical functions of H3K9 methylation and heterochromatin protein-1γ in reprogramming to pluripotency. Nat Cell Biol. 2013;15(7):872–882. doi: 10.1038/ncb2768
   PubMed Web of Science ®Google Scholar
• Brenes AJ, Yoshikawa H, Bensaddek D, et al. Erosion of human X chromosome inactivation causes major remodeling of the iPSC proteome. Cell Rep. 2021;35(4):109032. doi: 10.1016/j.celrep.2021.109032
   PubMed Web of Science ®Google Scholar
• Pripuzova NS, Getie-Kebtie M, Grunseich C, et al. Development of a protein marker panel for characterization of human induced pluripotent stem cells (hiPscs) using global quantitative proteome analysis. Stem Cell Res. 2015;14(3):323–338. doi: 10.1016/j.scr.2015.01.009
   PubMed Web of Science ®Google Scholar
• Beekhuis-Hoekstra SD, Watanabe K, Werme J, et al. Systematic assessment of variability in the proteome of iPSC derivatives. Stem Cell Res. 2021;56:102512. doi: 10.1016/j.scr.2021.102512
   PubMed Web of Science ®Google Scholar
• Brenes A, Bensaddek D, Hukelmann J, et al. The iPSC proteomic compendium. Biochemistry. 2018 Nov. doi: 10.1101/469916
   Google Scholar
• Kilpinen H, Goncalves A, Leha A, et al. Common genetic variation drives molecular heterogeneity in human iPscs. Nature. 2017;546(7658):370–375. doi: 10.1038/nature22403
   PubMed Web of Science ®Google Scholar
• Mirauta BA, Seaton DD, Bensaddek D, et al. Population-scale proteome variation in human induced pluripotent stem cells. Elife. 2020;9:e57390. doi: 10.7554/eLife.57390
   PubMed Web of Science ®Google Scholar
• Matlock AD, Vaibhav V, Holewinski R, et al. NeuroLINCS proteomics: defining human-derived iPSC proteomes and protein signatures of pluripotency. Sci Data. 2023;10(1):24. doi: 10.1038/s41597-022-01687-7
   PubMed Web of Science ®Google Scholar
• Mallanna SK, Waas M, Duncan SA, et al. N-glycoprotein surfaceome of human induced pluripotent stem cell derived hepatic endoderm. Proteomics. 2017;17(5):17. doi: 10.1002/pmic.201600397
   Web of Science ®Google Scholar
• Cui M, Wu W, Li Q, et al. Unlocking the potential of human-induced pluripotent stem cells: cellular responses and secretome profiles in peptide hydrogel 3D culture. Cells. 2024;13(2):143. doi: 10.3390/cells13020143
   PubMed Web of Science ®Google Scholar
• Gundry RL, Riordon DR, Tarasova Y, et al. A cell surfaceome map for immunophenotyping and sorting pluripotent stem cells. Mol & Cell Proteomics. 2012;11(8):303–316. doi: 10.1074/mcp.M112.018135
   PubMed Web of Science ®Google Scholar
• Boheler KR, Bhattacharya S, Kropp EM, et al. A human pluripotent stem Cell surface N-Glycoproteome resource reveals markers, extracellular epitopes, and drug targets. Stem Cell Rep. 2014;3(1):185–203. doi: 10.1016/j.stemcr.2014.05.002
   PubMed Web of Science ®Google Scholar
• Hayashi Y, Ohnuma K, Furue MK. Pluripotent Stem Cell Heterogeneity. Adv Exp Med Biol. 2019;1123:71–94. doi: 10.1007/978-3-030-11096-3_6
   PubMed Web of Science ®Google Scholar
• Volpato V, Webber C. Addressing variability in iPSC-derived models of human disease: guidelines to promote reproducibility. Dis Model Mech. 2020;13(1):dmm042317. doi: 10.1242/dmm.042317
   PubMed Web of Science ®Google Scholar
• Berg Luecke L, Waas M, Littrell J, et al. Surfaceome mapping of primary human heart cells with CellSurfer uncovers cardiomyocyte surface protein LSMEM2 and proteome dynamics in failing hearts. Nat Cardiovasc Res. 2023;2(1):76–95. doi: 10.1038/s44161-022-00200-y
   PubMedGoogle Scholar
• Varderidou-Minasian S, Verheijen BM, Schätzle P, et al. Deciphering the proteome dynamics during development of neurons derived from induced pluripotent stem cells. J Proteome Res. 2020;19(6):2391–2403. doi: 10.1021/acs.jproteome.0c00070
   PubMed Web of Science ®Google Scholar
• Reilly L, Lara E, Ramos D, et al. A fully automated FAIMS-DIA mass spectrometry-based proteomic pipeline. Cell Rep Methods. 2023;3(10):100593. doi: 10.1016/j.crmeth.2023.100593
   PubMedGoogle Scholar
• Vethe H, Bjørlykke Y, Ghila LM, et al. Probing the missing mature β-cell proteomic landscape in differentiating patient iPSC-derived cells. Sci Rep. 2017;7(1):4780. doi: 10.1038/s41598-017-04979-w
   PubMedGoogle Scholar
• Urasawa T, Koizumi T, Kimura K, et al. Quantitative proteomics for the development and manufacturing of human-induced pluripotent stem Cell-derived neural stem cells using Data-independent acquisition mass spectrometry. J Proteome Res. 2023;22(6):1843–1854. doi: 10.1021/acs.jproteome.2c00841
   PubMed Web of Science ®Google Scholar
• Djuric U, Rodrigues DC, Batruch I, et al. Spatiotemporal proteomic profiling of human cerebral development. Mol & Cell Proteomics. 2017;16(9):1548–1562. doi: 10.1074/mcp.M116.066274
   PubMed Web of Science ®Google Scholar
• Tyleckova J, Valekova I, Zizkova M, et al. Surface N-glycoproteome patterns reveal key proteins of neuronal differentiation. J Proteomics. 2016;132:13–20. doi: 10.1016/j.jprot.2015.11.008
   PubMed Web of Science ®Google Scholar
• Van Hoof D, Dormeyer W, Braam SR, et al. Identification of cell surface proteins for antibody-based selection of human embryonic stem cell-derived cardiomyocytes. J Proteome Res. 2010;9(3):1610–1618. doi: 10.1021/pr901138a
   PubMed Web of Science ®Google Scholar
• Dubois NC, Craft AM, Sharma P, et al. SIRPA is a specific cell-surface marker for isolating cardiomyocytes derived from human pluripotent stem cells. Nat Biotechnol. 2011;29(11):1011–1018. doi: 10.1038/nbt.2005
   PubMed Web of Science ®Google Scholar
• Protze SI, Liu J, Nussinovitch U, et al. Sinoatrial node cardiomyocytes derived from human pluripotent cells function as a biological pacemaker. Nat Biotechnol. 2017;35(1):56–68. doi: 10.1038/nbt.3745
   PubMed Web of Science ®Google Scholar
• Funakoshi S, Miki K, Takaki T, et al. Enhanced engraftment, proliferation and therapeutic potential in heart using optimized human iPSC-derived cardiomyocytes. Sci Rep. 2016;6(1):19111. doi: 10.1038/srep19111
   PubMedGoogle Scholar
• Veevers J, Farah EN, Corselli M, et al. Cell-surface marker signature for enrichment of ventricular cardiomyocytes derived from human embryonic stem cells. Stem Cell Rep. 2018;11(3):828–841. doi: 10.1016/j.stemcr.2018.07.007
   PubMed Web of Science ®Google Scholar
• Cyganek L, Tiburcy M, Sekeres K, et al. Deep phenotyping of human induced pluripotent stem cell–derived atrial and ventricular cardiomyocytes. JCI Insight. 2018;3(12):e99941. doi: 10.1172/jci.insight.99941
   PubMed Web of Science ®Google Scholar
• Karbassi E, Fenix A, Marchiano S, et al. Cardiomyocyte maturation: advances in knowledge and implications for regenerative medicine. Nat Rev Cardiol. 2020;17(6):341–359. doi: 10.1038/s41569-019-0331-x
   PubMed Web of Science ®Google Scholar
• Krumm J, Sekine K, Samaras P, et al. High temporal resolution proteome and phosphoproteome profiling of stem cell-derived hepatocyte development. Cell Rep. 2022;38(13):110604. doi: 10.1016/j.celrep.2022.110604
   PubMed Web of Science ®Google Scholar
• Mallanna SK, Cayo MA, Twaroski K, et al. Mapping the Cell-surface N-Glycoproteome of human hepatocytes reveals markers for selecting a homogeneous population of iPSC-derived hepatocytes. Stem Cell Rep. 2016;7(3):543–556. doi: 10.1016/j.stemcr.2016.07.016
   PubMed Web of Science ®Google Scholar
• Hurrell T, Segeritz C-P, Vallier L, et al. A proteomic time course through the differentiation of human induced pluripotent stem cells into hepatocyte-like cells. Sci Rep. 2019;9(1):3270. doi: 10.1038/s41598-019-39400-1
   PubMedGoogle Scholar
• Hellen N, Pinto Ricardo C, Vauchez K, et al. Proteomic analysis reveals temporal changes in protein expression in human induced pluripotent stem Cell-derived cardiomyocytes in vitro. Stem Cells Dev. 2019;28(9):565–578. doi: 10.1089/scd.2018.0210
   PubMed Web of Science ®Google Scholar
• Cai W, Zhang J, de Lange WJ, et al. An unbiased proteomics method to assess the maturation of human pluripotent stem cell–derived cardiomyocytes. Circ Res. 2019;125(11):936–953. doi: 10.1161/CIRCRESAHA.119.315305
   PubMed Web of Science ®Google Scholar
• Poon EN-Y, Luo X, Webb SE, et al. The cell surface marker CD36 selectively identifies matured, mitochondria-rich hPSC-cardiomyocytes. Cell Res. 2020;30(7):626–629. doi: 10.1038/s41422-020-0292-y
   PubMed Web of Science ®Google Scholar
• Haller C, Chaskar P, Piccand J, et al. Insights into islet differentiation and maturation through proteomic characterization of a human iPSC-derived pancreatic endocrine model. Proteomics - Clin Appl. 2018;12(5):1600173. doi: 10.1002/prca.201600173
   Web of Science ®Google Scholar
• Trakarnsanga K, Wilson MC, Griffiths RE, et al. Qualitative and quantitative comparison of the proteome of erythroid cells differentiated from human iPscs and adult erythroid cells by multiplex TMT labelling and NanoLC-MS/MS. In: Pant A, editor. PLoS ONE. Vol. 9, 2014. p. e100874. doi: 10.1371/journal.pone.0100874
   Google Scholar
• Soontararak S, Chow L, Johnson V, et al. Mesenchymal stem cells (MSC) derived from induced pluripotent stem cells (iPSC) equivalent to adipose-derived MSC in promoting intestinal healing and microbiome normalization in mouse inflammatory bowel disease model. Stem Cells Transl Med. 2018;7(6):456–467. doi: 10.1002/sctm.17-0305
   PubMed Web of Science ®Google Scholar
• Dominici M, Le Blanc K, Mueller I, et al. Minimal criteria for defining multipotent mesenchymal stromal cells. Cytotherapy. 2006;8(4):315–317. doi: 10.1080/14653240600855905
   PubMed Web of Science ®Google Scholar
• Sarantopoulos CN, Banyard DA, Ziegler ME, et al. Elucidating the preadipocyte and its role in adipocyte formation: a Comprehensive Review. Stem Cell Rev and Rep. 2018;14(1):27–42. doi: 10.1007/s12015-017-9774-9
   PubMed Web of Science ®Google Scholar
• Pogodziński D, Ostrowska L, Smarkusz-Zarzecka J, et al. Secretome of adipose tissue as the key to understanding the endocrine function of adipose tissue. Int J Mol Sci. 2022;23(4):2309. doi: 10.3390/ijms23042309
   PubMed Web of Science ®Google Scholar
• Deshmukh AS, Peijs L, Beaudry JL, et al. Proteomics-based comparative mapping of the secretomes of human Brown and white adipocytes reveals EPDR1 as a novel batokine. Cell Metab. 2019;30(5):963–975.e7. doi: 10.1016/j.cmet.2019.10.001
   PubMed Web of Science ®Google Scholar
• Gupta S, Krishnakumar V, Soni N, et al. Comparative proteomic profiling of small extracellular vesicles derived from iPscs and tissue specific mesenchymal stem cells. Exp Cell Res. 2022;420(2):113354. doi: 10.1016/j.yexcr.2022.113354
   PubMed Web of Science ®Google Scholar
• Park DS, Kozaki T, Tiwari SK, et al. iPS-cell-derived microglia promote brain organoid maturation via cholesterol transfer. Nature. 2023;623(7986):397–405. doi: 10.1038/s41586-023-06713-1
   PubMed Web of Science ®Google Scholar
• Takasato M, Er PX, Chiu HS, et al. Kidney organoids from human iPS cells contain multiple lineages and model human nephrogenesis. Nature. 2015;526(7574):564–568. doi: 10.1038/nature15695
   PubMed Web of Science ®Google Scholar
• de Lange WJ, Farrell ET, Kreitzer CR, et al. Human iPSC-engineered cardiac tissue platform faithfully models important cardiac physiology. Am J Physiol Heart Circ Physiol. 2021;320(4):H1670–H1686. doi: 10.1152/ajpheart.00941.2020
   PubMed Web of Science ®Google Scholar
• Rossler KJ, De Lange WJ, Mann MW, et al. Lactate- and immunomagnetic-purified hiPSC–derived cardiomyocytes generate comparable engineered cardiac tissue constructs. JCI Insight. 2024;9(1):e172168. doi: 10.1172/jci.insight.172168
   PubMed Web of Science ®Google Scholar
• Nascimento JM, Saia-Cereda VM, Sartore RC, et al. Human cerebral organoids and fetal brain tissue share proteomic similarities. Front Cell Dev Biol. 2019;7:303. doi: 10.3389/fcell.2019.00303
   PubMed Web of Science ®Google Scholar
• Notaras M, Lodhi A, Fang H, et al. The proteomic architecture of schizophrenia iPSC-derived cerebral organoids reveals alterations in GWAS and neuronal development factors. Transl Psychiatry. 2021;11(1):541. doi: 10.1038/s41398-021-01664-5
   PubMed Web of Science ®Google Scholar
• Ilieva M, Aldana BI, Vinten KT, et al. Proteomic phenotype of cerebral organoids derived from autism spectrum disorder patients reveal disrupted energy metabolism, cellular components, and biological processes. Mol Psychiatry. 2022;27(9):3749–3759. doi: 10.1038/s41380-022-01627-2
   PubMed Web of Science ®Google Scholar
• McClure-Begley TD, Ebmeier CC, Ball KE, et al. Cerebral organoid proteomics reveals signatures of dysregulated cortical development associated with human trisomy 21. Systems Biology. 2018 May. doi:10.1101/315317
   Google Scholar
• Pellegrini L, Bonfio C, Chadwick J, et al. Human CNS barrier-forming organoids with cerebrospinal fluid production. Science. 2020;369(6500):eaaz5626. doi: 10.1126/science.aaz5626
   PubMed Web of Science ®Google Scholar
• Hale LJ, Howden SE, Phipson B, et al. 3D organoid-derived human glomeruli for personalised podocyte disease modelling and drug screening. Nat Commun. 2018;9(1):5167. doi: 10.1038/s41467-018-07594-z
   PubMedGoogle Scholar
• Gatto L, Aebersold R, Cox J, et al. Initial recommendations for performing, benchmarking and reporting single-cell proteomics experiments. Nat Methods. 2023;20(3):375–386. doi: 10.1038/s41592-023-01785-3
   PubMed Web of Science ®Google Scholar
• Petelski AA, Emmott E, Leduc A, et al. Multiplexed single-cell proteomics using SCoPE2. Nat Protoc. 2021;16(12):5398–5425. doi: 10.1038/s41596-021-00616-z
   PubMed Web of Science ®Google Scholar
• Wang M, Yu H, Zhang T, et al. In-depth comparison of matrigel dissolving methods on proteomic profiling of organoids. Mol & Cell Proteomics. 2022;21(1):100181. doi: 10.1016/j.mcpro.2021.100181
   PubMed Web of Science ®Google Scholar
• Kelly MI, Albahrani M, Castro C, et al. Importance of evaluating protein glycosylation in pluripotent stem cell-derived cardiomyocytes for research and clinical applications. Pflugers Arch - Eur J Physiol. 2021;473(7):1041–1059. doi: 10.1007/s00424-021-02554-x
   PubMed Web of Science ®Google Scholar
• Lau E, Han Y, Williams DR, et al. Splice-junction-based mapping of alternative isoforms in the human proteome. Cell Rep. 2019;29(11):3751–3765.e5. doi: 10.1016/j.celrep.2019.11.026
   PubMed Web of Science ®Google Scholar
• Laflamme C, McKeever PM, Kumar R, et al. Implementation of an antibody characterization procedure and application to the major ALS/FTD disease gene C9ORF72. Elife. 2019;8:e48363. doi: 10.7554/eLife.48363
   PubMed Web of Science ®Google Scholar
• Baker M. Reproducibility crisis: blame it on the antibodies. Nature. 2015;521(7552):274–276. doi: 10.1038/521274a
   PubMed Web of Science ®Google Scholar
• Bradbury A, Plückthun A. Reproducibility: standardize antibodies used in research. Nature. 2015;518(7537):27–29. doi: 10.1038/518027a
   PubMed Web of Science ®Google Scholar
• Lund-Johansen F. A strong case for third-party testing. Elife. 2023;12:e93329. doi: 10.7554/eLife.93329
   PubMed Web of Science ®Google Scholar
• Connor-Robson N, Booth H, Martin JG, et al. An integrated transcriptomics and proteomics analysis reveals functional endocytic dysregulation caused by mutations in LRRK2. Neurobiol Dis. 2019;127:512–526. doi: 10.1016/j.nbd.2019.04.005
   PubMed Web of Science ®Google Scholar
• Iannotti MJ, MacArthur R, Jones R, et al. Detecting secretory proteins by acoustic droplet ejection in multiplexed high-throughput applications. ACS Chem Biol. 2019;14(3):497–505. doi: 10.1021/acschembio.9b00001
   PubMed Web of Science ®Google Scholar
• Oh H-H, Rutledge J, Nachun D, et al. Organ aging signatures in the plasma proteome track health and disease. Nature. 2023;624(7990):164–172. doi: 10.1038/s41586-023-06802-1
   PubMed Web of Science ®Google Scholar
• Eldjarn GH, Ferkingstad E, Lund SH, et al. Large-scale plasma proteomics comparisons through genetics and disease associations. Nature. 2023;622(7982):348–358. doi: 10.1038/s41586-023-06563-x
   PubMed Web of Science ®Google Scholar
• Pietzner M, Wheeler E, Carrasco-Zanini J, et al. Synergistic insights into human health from aptamer- and antibody-based proteomic profiling. Nat Commun. 2021;12(1):6822. doi: 10.1038/s41467-021-27164-0
   PubMed Web of Science ®Google Scholar
• Joshi A, Mayr M. In aptamers they trust: caveats of the SOMAscan biomarker discovery platform from SomaLogic. Circulation. 2018;138(22):2482–2485. doi: 10.1161/CIRCULATIONAHA.118.036823
   PubMed Web of Science ®Google Scholar
• Wollscheid B, Bausch-Fluck D, Henderson C, et al. Mass-spectrometric identification and relative quantification of N-linked cell surface glycoproteins. Nat Biotechnol. 2009;27(4):378–386. doi: 10.1038/nbt.1532
   PubMed Web of Science ®Google Scholar
• Bausch-Fluck D, Hofmann A, Bock T, et al. A Mass spectrometric-derived cell surface protein atlas. In: Wanjin H, editor. PLOS ONE. Vol. 10, 2015. p. e0121314. doi: 10.1371/journal.pone.0121314
   Google Scholar
• Spitzer MH, Nolan GP. Mass cytometry: single cells, many features. Cell. 2016;165(4):780–791. doi: 10.1016/j.cell.2016.04.019
   PubMed Web of Science ®Google Scholar
• Im I, Son YS, Jung KB, et al. Mass cytometry–based single-cell analysis of human stem cell reprogramming uncovers differential regulation of specific pluripotency markers. J Biol Chem. 2019;294(49):18547–18556. doi: 10.1074/jbc.RA119.009061
   PubMed Web of Science ®Google Scholar
• Zunder ER, Lujan E, Goltsev Y, et al. A continuous molecular roadmap to iPSC reprogramming through progression analysis of single-cell mass cytometry. Cell Stem Cell. 2015;16(3):323–337. doi: 10.1016/j.stem.2015.01.015
   PubMed Web of Science ®Google Scholar
• Tran C, Damaser MS. Stem cells as drug delivery methods: application of stem cell secretome for regeneration. Adv Drug Deliv Rev. 2015;82–83:1–11. doi: 10.1016/j.addr.2014.10.007
   PubMed Web of Science ®Google Scholar
• Jennbacken K, Wågberg F, Karlsson U, et al. Phenotypic screen with the human secretome identifies FGF16 as inducing proliferation of iPSC-derived cardiac progenitor cells. Int J Mol Sci. 2019;20(23):6037. doi: 10.3390/ijms20236037
   PubMed Web of Science ®Google Scholar
• Knecht S, Eberl HC, Kreisz N, et al. An introduction to analytical challenges, approaches, and applications in mass spectrometry–based secretomics. Mol & Cell Proteomics. 2023;22(9):100636. doi: 10.1016/j.mcpro.2023.100636
   PubMed Web of Science ®Google Scholar
• Tüshaus J, Müller SA, Kataka ES, et al. An optimized quantitative proteomics method establishes the cell type-resolved mouse brain secretome. EMBO J. 2020;39(20):e105693. doi: 10.15252/embj.2020105693
   PubMed Web of Science ®Google Scholar
• Hammond DE, Kumar JD, Raymond L, et al. Stable isotope dynamic labeling of secretomes (SIDLS) identifies authentic secretory proteins released by cancer and stromal cells. Mol Cell Proteomics Mcp. 2018;17:1837–1849. doi: 10.1074/mcp.TIR117.000516
   PubMed Web of Science ®Google Scholar