Pedro Henrique Thimotheu Chaves^1,2, Mauricio Quiñones Vega^1,2, Bruno Andrade Paranhos¹, Luis Ariel Espinosa Rodríguez^1,2, Gilberto Barbosa Domont^1,2, Fábio César Sousa Nogueira^1,2

The cellular composition of a tissue has a profound impact on biology, biochemistry, and medicine, influencing fields such as cancer research, immunology, embryonic development, and personalized medicine. Traditional proteomics employs techniques for analyzing tissues or cell populations, which may obscure variations between individual cells. Scientific advances in microfluidics and mass spectrometry have enabled the development of single-cell proteomics (SCP), an innovative approach with sufficient sensitivity to analyze individual cells and distinguish them based on their proteome. Automation in SCP is essential for managing the complexity and scale of analyses, allowing for efficient, reproducible, and highly sensitive processing of numerous samples.

In this context, the objective of this study is to develop an efficient protocol for performing automated SCP using the HepG2 cell model (a human hepatocyte cell line). The cells were cultured in DMEM High medium supplemented with 10% fetal bovine serum, 2 mM glutamine, and 1% penicillin-streptomycin antibiotic. For a pilot experiment, the Uno Single-Cell Dispenser Tecan™ was used to dispense isolated cells into 96-well plates containing PBS buffer at pH 7.4 (137 mM NaCl, 2.7 mM KCl, 10 mM Na₂HPO₄, and 1.8 mM KH₂PO₄) and lysis solution at pH 8.5 (1 ng/uL Trypsin/Lys-C, 5% DMSO, and Promega™ commercial buffer). After dispensing, the plate was incubated in an Eppendorf™ Thermocycler™ at 50 °C for 2 hours. Subsequently, the resulting peptides were injected into a Vanquish Neo™ UHPLC system (Thermo Scientific™) coupled to an Exploris 480 mass spectrometer (Thermo Scientific™). Chromatographic separation was performed using a 5-minute gradient run, with mobile phase A consisting of water with 0.1% formic acid and mobile phase B consisting of 80% acetonitrile with 0.1% formic acid.

Mass spectrometry data were acquired in DIA mode using 50 m/z windows across a 400–800 m/z range. These data were then cross-referenced with a spectral library derived from the UniProt human database (20,497 canonical protein entries). In the initial analysis, a total of 2,145 proteins were identified, including 1,260 in the HeLa standard, 1,018 total proteins from single HepG2 cells, and 243 proteins per individual HepG2 cell. As a future direction, additional experiments will be conducted to increase the number of identified proteins. To this end, the protocol will be optimized through the use of improved reagents, different cell types, an experimental spectral library, and alternative equipment for cell dispensing into 96-well plates.

Agradecimentos: Brazilian Proteomics Society (BRPROT); Institutional Scientific Initiation Scholarship Program (PIBIC) of UFRJ; Proteomics Laboratory (LADETEC and Proteomics Unit), Institute of Chemistry, UFRJ; Research Center for Precision Medicine (CPMP), Carlos Chagas Filho Institute of Biophysics, UFRJ