Biology subjects

Encarnacion-Guevara, S.

Publications and source records attributed to Encarnacion-Guevara, S..

3 recordsLinked to original sources

bioRxiv2025

A proteomic study of the dual oncogenic and tumor- suppressive roles of SIRT3 in lung and breast cancer cell lines

Mitochondria play a crucial role in metabolism and energy production by generating adenosine triphosphate (ATP) through oxidative phosphorylation. They also help maintain intracellular calcium levels, facilitate communication between the nucleus and cytoplasm, detoxify reactive oxygen species (ROS), and regulate apoptosis (programmed cell death). Reversible acetylation of mitochondrial proteins is a key post-translational modification influencing these processes, with the NAD+-dependent deacetylase SIRT3 being a major regulator. While SIRT3 has been described as a tumor suppressor in some contexts and as a tumor promoter in others, its role appears to be tissue- and metabolism-specific. Here, we compared the proteomic and acetylomic responses of lung adenocarcinoma (A549) and breast adenocarcinoma (MCF7) cell lines to SIRT3 inhibition by 3-(1H-1,2,3-triazol-4-yl)pyridine (3-TYP). The two lines were selected based on distinct metabolic phenotypes and reported differences in basal SIRT3 abundance. Total proteome and mitochondrial-enriched fractions were analyzed separately for each cell line to avoid cross-line normalization bias. We identified 6,457 proteins and 4,199 acetylated peptides, revealing divergent pathway enrichments and acetylation patterns following SIRT3 inhibition. A549 cells showed enrichment of oxidative metabolism pathways, whereas MCF7 cells exhibited features consistent with metabolic reprogramming. These findings suggest that the cellular context determines the proteomic consequences of SIRT3 modulation and highlight the importance of metabolism in shaping SIRT3-associated phenotypes. All raw mass spectrometry data are publicly available in [repository accession number]. SignificanceSIRT3s impact on cancer metabolism is context-dependent. By separately profiling lung (A549) and breast (MCF7) cancer cells, we demonstrate that SIRT3 inhibition leads to distinct proteomic and acetylomic outcomes in each cell type. Our findings underscore the need for cell-type-specific strategies when targeting SIRT3 in cancer therapy and provide an open-access proteomic resource for further mechanistic studies.

cancer biology↗

bioRxiv2024

RhizoBindingSites v2.0 is a bioinformatic database of DNA motifs potentially involved in transcriptional regulation deduced from sites of the itself genome

RhizoBindingSites is a de novo depurified database of conserved DNA motifs potentially involved in the transcriptional regulation of the Rhizobium, Sinorhizobium, Bradyrhizobium, Azorhizobium, and Mesorhizobium representative symbiotic species, deduced from the upstream regulatory sequences of orthologous genes (O-matrices) from the Rhizobiales taxon. The sites collected with O-matrices per gene per genome from RhizoBindingSites were used to deduce matrices using the dyad-Regulatory Sequence Analysis Tool (RSAT) method, giving rise to novel S-matrices for the construction of the RizoBindingSites v2.0 database. A comparison of the S-matrix logos showed a greater frequency and/or re-definition of specific-position nucleotides found in the O-matrices. Moreover, S-matrices were better at detecting genes in the genome and there was a greater number of transcription factors (TFs) in the vicinity than O-matrices, corresponding to a more significant genomic coverage for S-matrices. The homology between the matrices of TFs from a genome showed inter-regulation between the clustered TFs. In addition, matrices of AraC, ArsR, GntR, and LysR ortholog TFs showed different motifs, suggesting distinct regulation. Benchmarking showed 72%, 68%, and 81% of common genes per regulon for O-matrices and approximately 14% less common genes with S-matrices of Rhizobium etli CFN42, R. leguminosarum bv. viciae 3841, and Sinorhizobium meliloti 1021. These data were deposited in RhizoBindingSites and the RhizoBindingSites v2.0 database (http://rhizobindingsites.ccg.unam.mx/).

bioinformatics↗

bioRxiv2018

Development of a novel protein identification approach to define mitochondrial proteomic signatures in glioblastoma oncogenesis: T98G vs U87MG cell lines model.

Glioblastoma Multiforme is a cancer type with an important mitochondrial component. Here was used mitochondrial proteome Random Sampling in 2D gels from T98G (oxidative metabolism) and U87MG (glycolytic metabolism) cell lines to obtain and analyze representative spots (regardless of their intensity, size, or difference in abundance between cell lines) by Principal Component Analysis for protein identification. Identified proteins were ordered into specific Protein-Protein Interaction networks, to each cell line, showing mitochondrial processes related to metabolic change, invasion, and metastasis; and other nonmitochondrial processes such as DNA translation, chaperone response, and autophagy in gliomas. T98G and U87MG cell lines were used as glioblastoma transition model; representative proteomic signatures, with the most important biological processes in each cell line, were defined. This pipeline analysis describes the metabolic status of each line and defines clear mitochondria performance differences for distinct glioblastoma stages, introducing a new useful strategy for the understanding of glioblastoma carcinogenesis formation.\n\nBiological significanceThis study defines the mitochondria as an organelle that follows and senses the carcinogenesis process by an original proteomic approach, a random sampling in 2DE gels to obtain a representative spots sample and analyzing their relative abundance by Principal Components Analysis; to faithfully describe glioblastoma cells biology.

systems biology↗