Descripció del projecte
Improvements in nanoscale (i.e single molecule localization) bio-imaging instrumentation hardware, like more sensitive and faster cameras, better optics, even adaptive, more selective filters and more coherent and faster laser beams, that even allow structured or lattice illumination at different wavelengths, are allowing that nowadays’ state-of-the-art advanced light microscopes, provide Super-resolution 3D localization, in large volumes (even full specimen), at kinematic speeds (25 volumes/second and beyond) and in many channels (that is 5D imaging). This instruments and many others that are also improving their limitations (for instance offering physiological conditions) by the use of new technologies, and can be crucial in studies tackling the singularity (epigenetics) of some diseases (cancer, dementia, etc.).
The large amounts of data that these instruments provide, is something not trivial to handle and most of the processing algorithms relay in offline post-processing algorithms and analysis tools, that require either high computational power or large computation times. The ultimate goal of all these instruments is to obtain all of the aforementioned benefits in real-time (on-the-flight), in physiological conditions (this means in vitro/ in vivo) and even improve them further and simultaneously get more insights (i.e. spectroscopy/multiplexed information). The hypothesis is that by using massive GPU parallelization, and new algorithms, for instance applying Artificial Intelligence, the systems will be faster, cheaper and what it is more important, they will be able to sense different nanoscale (or molecular scale) single cell properties that were previously undercover.
Recent articles are pointing into these directions; for instance, they suggest that 60% of acute type T cell leukaemia, T lymphocytes present a loss of activity in a gene called NUDT16, whose encoded protein promotes degradation of potentially oncogenic proteins. The lack of NUDT16 monitoring in these T lymphocytes allows a widely recognized cancer-causing gene, called C-MYC, to act freely and transforms these healthy cells into cancer cells. The NUDT16 gene is not genetically damaged, so it could be reactivated with epigenetic drugs already used in other types of leukaemia and lymphoma. It would also be worthwhile to test whether this leukaemia, being so dependent on the C-MYC oncogene, would also be more sensitive to drugs targeting this protein. This and other studies for instance in SARS-CoV-2 (Covid-19) suggest, that the use of nanoscopy would bring new insights on the real pathway of such proteins to recognize other possible targeting proteins and hence discover new epigenetic drugs more efficient and with a wider use (i.e. different cancer types, or SARS mutations).
The aim of the project is that the PhD student could benefit from a highly multidisciplinary and inter-sectorial environment, reaching both the private sector, through the recently created company ViRe Instruments S.L; and the public sector in one of the top European Cancer Research Institutes, the Josep Carreras Leukaemia Research Institute (IJC). The student will also be eligible for a possible secondment in the University of Cambridge (where the CEO of the company is developing his Postdoctoral research in super-resolution microscopy – TheLeeLab) and the Institute of Photonic Sciences (ICFO – Team Loza). The project frames in between the basic and the applied science, giving it translational dimension.
The PhD student tasks will include but are not be limited to:
1) Get training in the basic instrumentation for genetic analysis in IJC, both indirect and mainly direct (microscopy) and getting documented with the state-of-the-art processing, visualization and analysis tools having access to top journal articles. A deeper knowledge in advanced nanoscopy instruments through optional secondments in the Cambridge University and ICFO.
2) Getting transversal skills of technology transfer that will be provided by the fellowship management and by the company (for instance innovation proposal writing, patent managing, company regulations, etc.).
3) The core of the project will be to work on a programming toolchain for processing, visualization and analysis of 3D molecular bio-images applied to cancer epigenetics on the cloud (using mainly IBM POWER9, Intel x86 and Tesla (CUDA) architectures).
4) Obtain cutting edge experimental epigenetics data and process it, building an application with the help of the programming toolchain, to tackle a relevant cancer epigenetic and/or SARS-Cov-2 problem (with optional secondments in the University of Cambridge and ICFO).
5) The final stage will be to write and defend the Phd Thesis with all the research results.
