biostudies-literatureUnknownRyu TNINDS NIH HHSNIH HHSSince proteins are essential molecules exerting cellular functions, decoding proteome changes is the key to understanding the normal physiology and pathogenesis mechanism of various diseases. However, conventional proteomic studies are often conducted on tissue lumps, in which multiple cell types are entangled, presenting challenges in interpreting the biological dynamics among diverse cell types. While recent cell-specific proteome analysis techniques, like BONCAT, TurboID, and APEX, have emerged, their necessity for genetic modifications limits their usage. The alternative, laser capture microdissection (LCM), although it does not require genetic alterations, is labor-intensive, time-consuming, and requires specialized expertise, making it less suitable for large-scale studies. In this sbioRxiv : the preprint server for biology2023.06.13.544682https://www.ebi.ac.uk/biostudies/studies/S-EPMC10312661biostudies-literatureDevelopment of an <i>in situ</i> cell-type specific proteome analysis method using antibody-mediated biotinylation.PMC10312661S10 OD021844R01 NS123456Kim SYThuraisamy TNa CHJang YRyu TfalseDevelopment of an <i>in situ</i> cell-type specific proteome analysis method using antibody-mediated biotinylation.Since proteins are essential molecules exerting cellular functions, decoding proteome changes is the key to understanding the normal physiology and pathogenesis mechanism of various diseases. However, conventional proteomic studies are often conducted on tissue lumps, in which multiple cell types are entangled, presenting challenges in interpreting the biological dynamics among diverse cell types. While recent cell-specific proteome analysis techniques, like BONCAT, TurboID, and APEX, have emerged, their necessity for genetic modifications limits their usage. The alternative, laser capture microdissection (LCM), although it does not require genetic alterations, is labor-intensive, time-consuming, and requires specialized expertise, making it less suitable for large-scale studies. In this s2023-01-01T00:00:00Z2023 Jun2025-07-07T03:09:32.651Z2025-07-07T03:09:32.651ZS-EPMC103126613739828610.1101/2023.06.13.544682