Community-Driven Data Analysis Training for Biology

The primary problem with the explosion of biomedical datasets is not the data, not computational resources, and not the required storage space, but the general lack of trained and skilled researchers to manipulate and analyze these data. Eliminating this problem requires development of comprehensive educational resources. Here we present a community-driven framework that enables modern, interactive teaching of data analytics in life sciences and facilitates the development of training materials. The key feature of our system is that it is not a static but a continuously improved collection of tutorials. By coupling tutorials with a web-based analysis framework, biomedical researchers can learn by performing computation themselves through a web browser without the need to install software or search for example datasets. Our ultimate goal is to expand the breadth of training materials to include fundamental statistical and data science topics and to precipitate a complete re-engineering of undergraduate and graduate curricula in life sciences. This project is accessible at https://training.galaxyproject.org.

Proteomic analysis of lung metastases in a murine breast cancer model reveals divergent influence of CTSB and CTSL overexpression

Studies in the MMTV-PyMT (PyMT) breast cancer mouse model have shown a strong influence of the lysosomal cysteine cathepsins B or L on lung metastasis formation. Transgenic expression of human CTSB (tgCTSB) or CTSL (tgCTSL) both led to similar metastatic phenotypes with increased metastatic burden in the PyMT mice. However, recent studies in other tumor models proved marked differences in effects of either cathepsin on the proteome composition. We sought to analyze and compare proteome changes in the metastatic proteome of PyMT mice expressing either tgCTSB or tgCTSL to evaluate similarities and differences in those models.

Performing an explorative, quantitative proteome comparison based on LC-MS/MS, we identified up to 3,000 proteins from murine lung metastases in three independent biological replicates per genotype. In both cases, when compared to wild-type (WT) mice, we noticed a pronounced impact of transgene cathepsin expression on the metastasis proteome. Highlights include increased moesin, integrin beta 1 and vinexin levels in the tgCTSB dataset and increased saposin and granulin levels in the tgCTSL dataset. Importantly, non-supervised hierarchical clustering clearly separated tgCTSB vs. tgCTSL induced proteome changes.

In summary, tgCTSB and tgCTSL both display a strong and distinct impact on proteome composition of lung macrometastases in the PyMT model. Our observations suggest that they impact malignant behavior in distinct ways, thus further emphasizing interest into their tumor-contextual functionality.

miR-200c dampens cancer cell migration via regulation of protein kinase A subunits

Expression of miR-200c is a molecular switch to determine cellular fate towards a mesenchymal or epithelial phenotype. miR-200c suppresses the early steps of tumor progression by preventing epithelial-mesenchymal transition (EMT) and intravasation of tumor cells. Unraveling the underlying molecular mechanisms might pinpoint to novel therapeutic options. To better understand these mechanisms it is crucial to identify targets of miR-200c. Here, we employ a combination of quantitative proteomic and bioinformatic strategies to identify novel miR-200c targets. We identify and confirm two subunits of the central cellular kinase protein kinase A (PKA), namely PRKAR1A and PRKACB, to be directly regulated by miR-200c. Notably, siRNA-mediated downregulation of both proteins phenocopies the migratory behavior of breast cancer cells after miR-200c overexpression. Patient data from publicly accessible databases supports a miR-200c-PKA axis. Thus, our study identifies the PKA heteroprotein as an important mediator of miR-200c induced repression of migration in breast cancer cells. By bioinformatics, we define a miRNA target cluster consisting of PRKAR1A, PRKAR2B, PRKACB, and COF2, which is targeted by a group of 14 miRNAs.

Transmembrane collagen XVII modulates integrin dependent keratinocyte migration via PI3K/Rac1 signaling

The hemidesmosomal transmembrane component collagen XVII (ColXVII) plays an important role in the anchorage of the epidermis to the underlying basement membrane. However, this adhesion protein seems to be also involved in the regulation of keratinocyte migration, since its expression in these cells is strongly elevated during reepithelialization of acute wounds and in the invasive front of squamous cell carcinoma, while its absence in ColXVII-deficient keratinocytes leads to altered cell motility. Using a genetic model of murine Col17a1⁻/⁻ keratinocytes we elucidated ColXVII mediated signaling pathways in cell adhesion and migration. Col17a1⁻/⁻ keratinocytes exhibited increased spreading on laminin 332 and accelerated, but less directed cell motility. These effects were accompanied by increased expression of the integrin subunits β4 and β1. The migratory phenotype, as evidenced by formation of multiple unstable lamellipodia, was associated with enhanced phosphoinositide 3-kinase (PI3K) activity. Dissection of the signaling pathway uncovered enhanced phosphorylation of the β4 integrin subunit and the focal adhesion kinase (FAK) as activators of PI3K. This resulted in elevated Rac1 activity as a downstream consequence. These results provide mechanistic evidence that ColXVII coordinates keratinocyte adhesion and directed motility by interfering integrin dependent PI3K activation and by stabilizing lamellipodia at the leading edge of reepithelializing wounds and in invasive squamous cell carcinoma.