ABSTRACT
Single-celled eukaryote genomes predominantly replicate through multiple origins. Although origin usage during the S-phase has been elucidated in some of these organisms, few studies have comparatively approached this dynamic. Here, we developed a user-friendly website able to calculate the length of the cell cycle phases for any organism. Next, using a formula developed by our group, we showed a comparative analysis among the minimum number of replication origins (MO) required to duplicate an entire chromosome within the S-phase duration in trypanosomatids (Trypanosoma cruzi, Leishmania major, and Trypanosoma brucei) and yeasts (Saccharomyces cerevisiae and Schizosaccharomyces pombe). Using the data obtained by our analysis, it was possible to predict the MO required in a situation of replication stress. Also, our findings allow establishing a threshold for the number of origins, which serves as a parameter for genome approaches that map origins. Moreover, our data suggest that when compared to yeasts, trypanosomatids use much more origins than the minimum needed. This is the first time a comparative analysis of the minimum number of origins has been successfully applied. These data may provide new insight into the understanding of the replication mechanism and a new methodological framework for studying single-celled eukaryote genomes.
ABSTRACT
Single-celled eukaryote genomes predominantly replicate through multiple origins. Although origin usage during the S-phase has been elucidated in some of these organisms, few studies have comparatively approached this dynamic. Here, we developed a user-friendly website able to calculate the length of the cell cycle phases for any organism. Next, using a formula developed by our group, we showed a comparative analysis among the minimum number of replication origins (MO) required to duplicate an entire chromosome within the S-phase duration in trypanosomatids (Trypanosoma cruzi, Leishmania major, and Trypanosoma brucei) and yeasts (Saccharomyces cerevisiae and Schizosaccharomyces pombe). Using the data obtained by our analysis, it was possible to predict the MO required in a situation of replication stress. Also, our findings allow establishing a threshold for the number of origins, which serves as a parameter for genome approaches that map origins. Moreover, our data suggest that when compared to yeasts, trypanosomatids use much more origins than the minimum needed. This is the first time a comparative analysis of the minimum number of origins has been successfully applied. These data may provide new insight into the understanding of the replication mechanism and a new methodological framework for studying single-celled eukaryote genomes.
ABSTRACT
Fibroblast growth factor 2 (FGF2) is a well-known cell proliferation promoter; however, it can also induce cell cycle arrest. To gain insight into the molecular mechanisms of this antiproliferative effect, for the first time, the early systemic proteomic differences induced by this growth factor in a K-Ras-driven mouse tumor cell line using a quantitative proteomics approach are investigated. More than 2900 proteins are quantified, indicating that terms associated with metabolism, RNA processing, replication, and transcription are enriched among proteins differentially expressed upon FGF2 stimulation. Proteomic trend dynamics indicate that, for proteins mainly associated with DNA replication and carbohydrate metabolism, an FGF2 stimulus delays their abundance changes, whereas FGF2 stimulation accelerates other metabolic programs. Transcription regulatory network analysis indicates master regulators of FGF2 stimulation, including two critical transcription factors, FOSB and JUNB. Their expression dynamics, both in the Y1 cell line (a murine model of adenocarcinoma cells) and in two other human cell lines (SK-N-MC and UM-UC-3) also susceptible to FGF2 antiproliferative effects, are investigated. Both protein expression levels depend on fibroblast growth factor receptor (FGFR) and src signaling. JUNB and FOSB knockdown do not rescue cells from the growth arrest induced by FGF2; however, FOSB knockdown rescue cells from DNA replication delay, indicating that FOSB expression underlies one of the FGF2 antiproliferative effects, namely, S-phase progression delay.
ABSTRACT
Fibroblast growth factor 2 (FGF2) is a well-known cell proliferation promoter; however, it can also induce cell cycle arrest. To gain insight into the molecular mechanisms of this antiproliferative effect, for the first time, the early systemic proteomic differences induced by this growth factor in a K-Ras-driven mouse tumor cell line using a quantitative proteomics approach are investigated. More than 2900 proteins are quantified, indicating that terms associated with metabolism, RNA processing, replication, and transcription are enriched among proteins differentially expressed upon FGF2 stimulation. Proteomic trend dynamics indicate that, for proteins mainly associated with DNA replication and carbohydrate metabolism, an FGF2 stimulus delays their abundance changes, whereas FGF2 stimulation accelerates other metabolic programs. Transcription regulatory network analysis indicates master regulators of FGF2 stimulation, including two critical transcription factors, FOSB and JUNB. Their expression dynamics, both in the Y1 cell line (a murine model of adenocarcinoma cells) and in two other human cell lines (SK-N-MC and UM-UC-3) also susceptible to FGF2 antiproliferative effects, are investigated. Both protein expression levels depend on fibroblast growth factor receptor (FGFR) and src signaling. JUNB and FOSB knockdown do not rescue cells from the growth arrest induced by FGF2; however, FOSB knockdown rescue cells from DNA replication delay, indicating that FOSB expression underlies one of the FGF2 antiproliferative effects, namely, S-phase progression delay.
