NucTools: analysis of chromatin feature occupancy profiles from high-throughput sequencing data

Background: Biomedical applications of high-throughput sequencing methods generate a vast amount of data in which numerous chromatin features are mapped along the genome. The results are frequently analysed by creating binary data sets that link the presence/absence of a given feature to specific genomic loci. However, the nucleosome occupancy or chromatin accessibility landscape is essentially continuous. It is currently a challenge in the field to cope with continuous distributions of deep sequencing chromatin readouts and to integrate the different types of discrete chromatin features to reveal linkages between them. Results: Here we introduce the NucTools suite of Perl scripts as well as MATLAB- and R-based visualization programs for a nucleosome-centred downstream analysis of deep sequencing data. NucTools accounts for the continuous distribution of nucleosome occupancy. It allows calculations of nucleosome occupancy profiles averaged over several replicates, comparisons of nucleosome occupancy landscapes between different experimental conditions, and the estimation of the changes of integral chromatin properties such as the nucleosome repeat length. Furthermore, NucTools facilitates the annotation of nucleosome occupancy with other chromatin features like binding of transcription factors or architectural proteins, and epigenetic marks like histone modifications or DNA methylation. The applications of NucTools are demonstrated for the comparison of several datasets for nucleosome occupancy in mouse embryonic stem cells (ESCs) and mouse embryonic fibroblasts (MEFs). Conclusions: The typical workflows of data processing and integrative analysis with NucTools reveal information on the interplay of nucleosome positioning with other features such as for example binding of a transcription factor CTCF, regions with stable and unstable nucleosomes, and domains of large organized chromatin K9me2 modifications (LOCKs). As potential limitations and problems we discuss how inter-replicate variability of MNase-seq experiments can be addressed

Tumorigenesis and peritoneal colonization from fallopian tube epithelium.

Ovarian cancer is the most lethal gynecological malignancy, primarily because its origin and initiation factors are unknown. A secretory murine oviductal epithelial (MOE) model was generated to address the hypothesis that the fallopian tube is an origin for high-grade serous cancer. MOE cells were stably altered to express mutation in p53, silence PTEN, activate AKT, and amplify KRAS alone and in combination, to define if this cell type gives rise to tumors and what genetic alterations are required to drive malignancy. Cell lines were characterized in vitro and allografted into mice. Silencing PTEN formed high-grade carcinoma with wide spread tumor explants including metastasis into the ovary. Addition of p53 mutation to PTEN silencing did not enhance this phenotype, whereas addition of KRAS mutation reduced survival. Interestingly, PTEN silencing and KRAS mutation originating from ovarian surface epithelium generated endometrioid carcinoma, suggesting that different cellular origins with identical genetic manipulations can give rise to distinct cancer histotypes. Defining the roles of specific signaling modifications in tumorigenesis from the fallopian tube/oviduct is essential for early detection and development of targeted therapeutics. Further, syngeneic MOE allografts provide an ideal model for pre-clinical testing in an in vivo environment with an intact immune system

Identification and super-resolution imaging of ligand-activated receptor dimers in live cells

Molecular interactions are key to many chemical and biological processes like protein function. In many signaling processes they occur in sub-cellular areas displaying nanoscale organizations and involving molecular assemblies. The nanometric dimensions and the dynamic nature of the interactions make their investigations complex in live cells. While super-resolution fluorescence microscopies offer live-cell molecular imaging with sub-wavelength resolutions, they lack specificity for distinguishing interacting molecule populations. Here we combine super-resolution microscopy and single-molecule Förster Resonance Energy Transfer (FRET) to identify dimers of receptors induced by ligand binding and provide super-resolved images of their membrane distribution in live cells. By developing a two-color universal-Point-Accumulation-In-the-Nanoscale-Topography (uPAINT) method, dimers of epidermal growth factor receptors (EGFR) activated by EGF are studied at ultra-high densities, revealing preferential cell-edge sub-localization. This methodology which is specifically devoted to the study of molecules in interaction, may find other applications in biological systems where understanding of molecular organization is crucial