Vince Kornél Grolmusz1,2, Eszter Angéla Tóth3, Kornélia Baghy4, István Likó2,5, Ottó Darvasi2,5, Ilona Kovalszky4, János Matkó3, Károly Rácz1,5, Attila Patócs6,7,8. 1. 2nd Department of Medicine, Semmelweis University, Szentkirályi utca 46, 1088, Budapest, Hungary. 2. "Lendület" Hereditary Endocrine Tumours Research Group, Hungarian Academy of Sciences, Semmelweis University, Szentkirályi utca 46, 1088, Budapest, Hungary. 3. Department of Immunology, Eötvös Loránd University, Pázmány Péter sétány 1/C, 1117, Budapest, Hungary. 4. 1st Department of Pathology and Experimental Cancer Research, Semmelweis University, Üllői út 26, 1085, Budapest, Hungary. 5. Molecular Medicine Research Group, Hungarian Academy of Sciences - Semmelweis University, Szentkirályi utca 46, 1088, Budapest, Hungary. 6. "Lendület" Hereditary Endocrine Tumours Research Group, Hungarian Academy of Sciences, Semmelweis University, Szentkirályi utca 46, 1088, Budapest, Hungary. patocs.attila@med.semmelweis-univ.hu. 7. Molecular Medicine Research Group, Hungarian Academy of Sciences - Semmelweis University, Szentkirályi utca 46, 1088, Budapest, Hungary. patocs.attila@med.semmelweis-univ.hu. 8. Department of Laboratory Medicine, Semmelweis University, Nagyvárad tér 4, 1089, Budapest, Hungary. patocs.attila@med.semmelweis-univ.hu.
Abstract
BACKGROUND: Previously, drug-based synchronization procedures were used for characterizing the cell cycle dependent transcriptional program. However, these synchronization methods result in growth imbalance and alteration of the cell cycle machinery. DNA content-based fluorescence activated cell sorting (FACS) is able to sort the different cell cycle phases without perturbing the cell cycle. MiRNAs are key transcriptional regulators of the cell cycle, however, their expression dynamics during cell cycle has not been explored. METHODS: Following an optimized FACS, a complex initiative of high throughput platforms (microarray, Taqman Low Density Array, small RNA sequencing) were performed to study gene and miRNA expression profiles of cell cycle sorted human cells originating from different tissues. Validation of high throughput data was performed using quantitative real time PCR. Protein expression was detected by Western blot. Complex statistics and pathway analysis were also applied. RESULTS: Beyond confirming the previously described cell cycle transcriptional program, cell cycle dependently expressed genes showed a higher expression independently from the cell cycle phase and a lower amplitude of dynamic changes in cancer cells as compared to untransformed fibroblasts. Contrary to mRNA changes, miRNA expression was stable throughout the cell cycle. CONCLUSIONS: Cell cycle sorting is a synchronization-free method for the proper analysis of cell cycle dynamics. Altered dynamic expression of universal cell cycle genes in cancer cells reflects the transformed cell cycle machinery. Stable miRNA expression during cell cycle progression may suggest that dynamical miRNA-dependent regulation may be of less importance in short term regulations during the cell cycle.
BACKGROUND: Previously, drug-based synchronization procedures were used for characterizing the cell cycle dependent transcriptional program. However, these synchronization methods result in growth imbalance and alteration of the cell cycle machinery. DNA content-based fluorescence activated cell sorting (FACS) is able to sort the different cell cycle phases without perturbing the cell cycle. MiRNAs are key transcriptional regulators of the cell cycle, however, their expression dynamics during cell cycle has not been explored. METHODS: Following an optimized FACS, a complex initiative of high throughput platforms (microarray, Taqman Low Density Array, small RNA sequencing) were performed to study gene and miRNA expression profiles of cell cycle sorted human cells originating from different tissues. Validation of high throughput data was performed using quantitative real time PCR. Protein expression was detected by Western blot. Complex statistics and pathway analysis were also applied. RESULTS: Beyond confirming the previously described cell cycle transcriptional program, cell cycle dependently expressed genes showed a higher expression independently from the cell cycle phase and a lower amplitude of dynamic changes in cancer cells as compared to untransformed fibroblasts. Contrary to mRNA changes, miRNA expression was stable throughout the cell cycle. CONCLUSIONS: Cell cycle sorting is a synchronization-free method for the proper analysis of cell cycle dynamics. Altered dynamic expression of universal cell cycle genes in cancer cells reflects the transformed cell cycle machinery. Stable miRNA expression during cell cycle progression may suggest that dynamical miRNA-dependent regulation may be of less importance in short term regulations during the cell cycle.
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