Leishmania infantum (JPCM5) subcellular fractions, proteomics raw data and identified proteins

Project description.- Promastigotes of L. infantum JPCM5 strain were grown at 26 ◦C in Roswell Park Memorial Institute (RPMI) medium supplemented with 15% of heat-inactivated fetal bovine serum (FBS), hemin (10 μg/mL) and an antibiotic mix (streptomycin 10 μg/mL and penicillin 105 U/mL). Cultures (50 mL) were started at 5 × 105 cells/mL and the parasites were harvested in the middle logarithmic growth phase (107 promastigotes/mL). After washing twice with phosphate buffer saline (PBS), the pellets (5 × 108 cells) were processed using the Subcellular Protein Fractionation Kit for Cultured Cells (Cat. Number 78840; Thermofisher Scintific). As a result, four fractions were obtained and processed for proteomic analysis: F1, cytoplasmic fraction; F2, membranous fraction; F3, nuclear soluble fraction; F4, chromatin-bound fraction. The project aimed to analyze the subcellular distribution of L. infantum proteins in the promastigote stage. Sample processing protocol.- Each fraction was submitted to in-gel digestion using sequencing-grade trypsin (Promega, Madison, WI, USA) following the procedure described elsewhere (Adán-Jiménez et al., 2024). Peptide samples were analyzed by reverse phase-liquid chromatography (RP-LC)-MS/MS analysis (Dynamic Exclusion Mode) in an Easy-nLC 1200 system coupled to an ion trap LTQ-Orbitrap Velos Pro hybrid mass spectrometer (Thermo Scientific, Waltham, MA, USA). Data processing protocol.- Peptide identification from raw data was carried out using the PEAKS Studio XPro search engine (Bioinformatics Solutions Inc.,Waterloo, ON, Canada) (Tran et al., 2019). Searches were performed against the most recent L. infantum proteome dataset available at Mendeley Data server (https://data.mendeley.com/datasets/dtmstvb2j5/2). The file protein.html contains the proteins identified from the four fractions. The proteomic analysis was carried out in the CBM PROTEIN CHEMISTRY FACILITY, which belongs to ProteoRed. References. Adán-Jiménez, J., Sánchez-Salvador, A., Morato, E., Solana, J. C., Aguado, B. and Requena, J. M. (2024). A Proteogenomic Approach to Unravel New Proteins Encoded in the Leishmania donovani (HU3) Genome. Genes 15, 775. doi: 10.3390/GENES15060775. Tran, N. H., Qiao, R., Xin, L., Chen, X., Liu, C., Zhang, X., Shan, B., Ghodsi, A. and Li, M. (2019). Deep learning enables de novo peptide sequencing from data-independent-acquisition mass spectrometry. Nature methods 16, 63–66. doi: 10.1038/S41592-018-0260-3.