ABSTRACT: The in silico single gene deletion step was adapted to simulate the knock-out of all targets of a drug on an objective function such as growth or energy balance. Based on publicly available and in-house large scale transcriptomic data, metabolic models for melanoma were reconstructed, enabling the prediction of 28 candidate drugs and estimating their respective efficacy.
Project description:31 samples transcriptomics to simulate the knock-out of all targets of a drug on an objective function such as growth or energy balance.
Project description:Aberrant activity of type II topoisomerases (TOP2) often causes blocked double-strand breaks (DSBs), whose inefficient repair can seriously compromise genomic stability. One of the two TOP2 paralogs encoded in vertebrates is TOP2B, which has been linked to essential processes such as transcription or genome organization. Few TOP2B genome-wide maps have been profiled, and a comprehensive study of the mechanisms involved in TOP2B-DNA binding is still lacking. Here, we conduct an in silico approach for the prediction of TOP2B binding sites using publicly available sequencing data. We achieve highly accurate predictions and find that open chromatin and architectural factors are the most informative features. We also validate our predictions on experimental data and generate predicted TOP2B tracks that mirror experimental ones with high precision.
Project description:Micro RNAs (miRNAs) are a class of small, non-coding RNAs that post-transcriptionally control the translation and stability of mRNAs. In our study, we found a higher level of miR-92a in PMBL versus DLBCL. A bioinformatics approach combining in silico prediction and transcriptomic analyses on patient samples and transduced cell lines, enabled us to identify miR-92a target genes in PMBL.
Project description:The accurate identification and prioritization of antigenic peptides presented by class-I and -II human leukocyte antigens (HLA-I and -II) recognized by autologous T cells is crucial for the development of cancer immunotherapies. While several clinical neoantigen prediction pipelines are now publicly available, none of them allows the direct integration of mass spectrometry immunopeptidomics data that can uncover antigenic peptides derived from various canonical and non-canonical sources. Therefore, we have developed and shared a unique ‘end-to-end’ clinical proteo-genomic pipeline, called NeoDisc. NeoDisc is a fast and modular computational pipeline that combines state-of-the-art publicly available and in-house software for genomics, transcriptomics, mass-spectrometry-based immunopeptidomics, and in silico tools for the identification, prediction, and prioritization of tumor-specific and immunogenic antigens from multiple sources. We demonstrated the application of NeoDisc for personalized antigen discovery, in the context of heterogenic antigenic landscape and defective cellular antigen presentation machineries, and we highlighted its clinical implementation.
Project description:Granulosa cells of dominant follicles originating from dairy cows with severe negative energy balance (BHBH) or mild negative energy balance (BHBL) were compared. Mild negative energy balance (BHBL) is the reference.
Project description:Granulosa cells of dominant follicles originating from dairy cows with severe negative energy balance (BHBH) or mild negative energy balance (BHBL) were compared. Mild negative energy balance (BHBL) is the reference. Two conditions experiment (BHBH and BHBL); Four pools of 3 biological replicates for each group (total = 12 cows for each group); Two technical replicates per pool (dye-swap).
Project description:Transcriptional profiling of CHO-K1 cells comparing to in-house serum-free and suspension adapted CHO-K1 cells in the exponential phase. Goal was to determine the effects of serum on CHO-K1 cells.
Project description:Most dairy cows suffer uterine microbial contamination postpartum. Persistent endometritis often develops, associated with reduced fertility. We used a model of differential feeding and milking regimes to produce cows in differing negative energy balance (NEB) status in early lactation. We used Affymetrix GeneChipM-CM-^R Bovine Genome Array to investigate the global gene expression underlying negative energy balance and to identify the significantly differentially expressed genes during this process. We investigate the differences of gene expression profiles in uterine endometrial tissues between the cows with mild and severe negative energy balance.
Project description:Pyrococcus yayanosii CH1 is the first and only obligate piezophilic hyperthermophilic microorganism discovered so far, that extends the physical and chemical limits of life on Earth and strengthens the idea of the existence of a hyperthermophilic biosphere in the depth of our planet. It was isolated from the Ashadze hydrothermal vent at 4,100 m depth. Multi-omics analyses where performed in order to study the mechanisms implemented by the cell to face high hydrostatic pressure variations. In silico analyses showed that P. yayanosii genome is highly adapted to its harsh environment with precisely a loss of aromatic amino acid biosynthesis and the high constitutive expression of the energy metabolism compared to others non obligate piezophilic Pyrococus. Differential proteomics and transcriptomics analyses identified key hydrostatic pressure responsive genes involved in translation, chemotaxis, energy metabolism (hydrogenases and formate metabolism) and CRISPR-cas. Cells were grown at different hydrostatic pressures (20, 52 and 80 Mpa for P. yayanosii and 0.1 and 45 Mpa for P. furiosus) until they reached the middle of the exponential phase. Each culture was done 3 times independantly.