Project description:A comparison between a human placental cell line (3A sub E placental, aka, PLC), human choriocarcinoma methotrexate-sensitive JEG3, and methotrexate-resistant JEG3R. This comparison focused on genomic 'hot spot' regions that are frequently mutated in human cancer genes.
Project description:In vertebrates, DNA methylation-mediated repression of retrotransposons is essential for the maintenance of genomic integrity. In the current study, we developed a technique termed HT-TREBS (High-Throughput Targeted Repeat Element Bisulfite Sequencing). This technique is designed to measure the DNA methylation levels of individual loci of any repeat families with next-generation sequencing approaches. To test the feasibility of HT-TREBS, we analyzed the DNA methylation levels of the IAPLTR family using a set of 12 different genomic DNA isolated from the brain, liver and kidney of 4 one-week-old littermates of the mouse strain C57BL/6N. This technique has successfully generated the CpG methylation data of 5,233 loci common in all the samples, representing more than 80% of the individual loci of the five targeted subtypes of the IAPLTR family. According to the results, approximately 5% of the IAPLTR loci have less than 80% average CpG methylation levels with no genomic position preference. Further analyses of the IAPLTR loci also revealed the presence of extensive DNA methylation variations between different tissues and individuals. Overall, these data demonstrate the efficiency and robustness of the new technique, HT-TREBS, and also provide new insights regarding the genome-wide DNA methylation patterns of the IAPLTR repeat elements. High-throughput, single-base resolution, singlicate DNA methylation profiles of IAPLTR retrotransposons in the brain, liver , and kidney of four 1-week-old mouse littemates using the developed technique, HT-TREBS.
Project description:MicroRNAs are important negative regulators of protein coding gene expression, and have been studied intensively over the last few years. To this purpose, different measurement platforms to determine their RNA abundance levels in biological samples have been developed. In this study, we have systematically compared 12 commercially available microRNA expression platforms by measuring an identical set of 20 standardized positive and negative control samples, including human universal reference RNA, human brain RNA and titrations thereof, human serum samples, and synthetic spikes from homologous microRNA family members. We developed novel quality metrics in order to objectively assess platform performance of very different technologies such as small RNA sequencing, RT-qPCR and (microarray) hybridization. We assessed reproducibility, sensitivity, quantitative performance, and specificity. The results indicate that each method has its strengths and weaknesses, which helps guiding informed selection of a quantitative microRNA gene expression platform in function of particular study goals.
Project description:We evaluated whether targeted next-generation sequencing (NGS) using the Ion Torrent Personal Genome Sequencer of cfDNA could identify prognostic or predictive factors for overall survival (OS) or progression free survival (PFS) within a large cohort of patients with advanced lung adenocarcinoma enrolled in the GALAXY-1 trial.
Project description:To better understand proteostasis in health and disease, determination of protein half-lives is essential. We improved the precision and accuracy of peptide-ion intensity based quantification in order to enable accurate determination of protein turnover in non-dividing cells using dynamic-SILAC. This enabled precise and accurate protein half-life determination ranging from 10 to more than 1000 hours. We achieve good proteomic coverage ranging from four to six thousand proteins in several types of non-dividing cells, corresponding to a total of 9699 unique proteins over the entire dataset. Good agreement was observed in half-lives between B-cells, natural killer cells and monocytes, while hepatocytes and mouse embryonic neurons showed substantial differences. Our comprehensive dataset enabled extension and statistical validation of the previous observation that subunits of protein complexes tend to have coherent turnover. Furthermore, we observed complex architecture dependent turnover within complexes of the proteasome and the nuclear pore complex. Our method is broadly applicable and might be used to investigate protein turnover in various cell types.
Project description:To better understand proteostasis in health and disease, determination of protein half-lives is essential. We improved the precision and accuracy of peptide-ion intensity based quantification in order to enable accurate determination of protein turnover in non-dividing cells using dynamic-SILAC. This enabled precise and accurate protein half-life determination ranging from 10 to more than 1000 hours. We achieve good proteomic coverage ranging from four to six thousand proteins in several types of non-dividing cells, corresponding to a total of 9699 unique proteins over the entire dataset. Good agreement was observed in half-lives between B-cells, natural killer cells and monocytes, while hepatocytes and mouse embryonic neurons showed substantial differences. Our comprehensive dataset enabled extension and statistical validation of the previous observation that subunits of protein complexes tend to have coherent turnover. Furthermore, we observed complex architecture dependent turnover within complexes of the proteasome and the nuclear pore complex. Our method is broadly applicable and might be used to investigate protein turnover in various cell types.
Project description:To better understand proteostasis in health and disease, determination of protein half-lives is essential. We improved the precision and accuracy of peptide-ion intensity based quantification in order to enable accurate determination of protein turnover in non-dividing cells using dynamic-SILAC. This enabled precise and accurate protein half-life determination ranging from 10 to more than 1000 hours. We achieve good proteomic coverage ranging from four to six thousand proteins in several types of non-dividing cells, corresponding to a total of 9699 unique proteins over the entire dataset. Good agreement was observed in half-lives between B-cells, natural killer cells and monocytes, while hepatocytes and mouse embryonic neurons showed substantial differences. Our comprehensive dataset enabled extension and statistical validation of the previous observation that subunits of protein complexes tend to have coherent turnover. Furthermore, we observed complex architecture dependent turnover within complexes of the proteasome and the nuclear pore complex. Our method is broadly applicable and might be used to investigate protein turnover in various cell types.
Project description:The American lobster, Homarus americanus, is not only of considerable economic importance but has also emerged as a pivotal model in neuroscience research. Neuropeptides, an important class of cell-to-cell signaling molecules, play crucial roles in a wide array of physiological and psychological processes. In light of the recently sequenced high-quality draft genome of the American lobster, our study sought to profile the neuropeptidome in this model organism. Employing advanced mass spectrometry techniques alongside functional genomic analysis, we identified 24 neuropeptide precursors and 101 unique mature neuropeptides in Homarus americanus. Intriguingly, 67 of these neuropeptides were discovered for the first time. Our findings offer a comprehensive overview of the peptidomic attributes of the lobster's nervous system and highlight the tissue-specific distribution of these neuropeptides. Collectively, this research not only enriches our understanding of the neural complexities of the American lobster but also sets a foundational basis for future investigations into the functional roles that these peptides play in crustacean species.