Background
Autophagy is a housekeeping process that preserves a functional cell state by balancing cell material degradation and recycling, with nutrient availability, metabolism, and growth. For this, cells target damaged organelles and proteins to the lysosomes for degradation into smaller constituents that are then reincorporated back into the cell circuitry. Furthermore, cells use this mechanism to get rid of intracellular pathogens or to counter cancer development.
Misregulation of autophagy relates to several human pathologies including cancer, inflammatory diseases, neurodegeneration, and aging. These associations raise the importance of the study of autophagy. A critical aspect for cell health is that autophagic activity must be balanced. Too much or too little autophagy can be harmful for the cell. Therefore, the nature of autophagy regulation is highly dynamic. Autophagy is tightly controlled by the nutritional status within an organism going through cycles of feeding and fasting, as well as variations in the metabolic status of a given cell. For these reasons, the development of therapies that manipulate the balance of autophagy for the treatment of human diseases has been challenging.
The first breakthrough in autophagy research was made using yeast as the biological study system. From there, the field grew in popularity and the research on autophagy has moved to more complex model organisms. However, current models for autophagy regulation has remained too simplistic, and they lack understanding of the dynamical regulation on a systems-level. Autophagy has predominantly been studied in the form of single endpoint measures that do not capture the temporal progression of its activity. To do better, autophagy must be studied as a dynamical system that switches between states, by tracking changes along a temporal axis. Furthermore, the complete mapping of the metabolic circuitry in yeast makes it a perfect model organism for a metabolic systems-level study of adaptive autophagy regulation in response to nutritional perturbations.
Goal
In our laboratory, we performed a high-content screening with confocal imaging of a collection of single deletion mutants that comprises the whole genome of yeast. To monitor autophagy response under nutritional perturbations, we tracked the signal distribution changes of autophagy-related fluorescent proteins across multiple time-points. We used machine-learning approaches for the phenotype classification, and we used network theory for the identification of genes and biological circuits that control autophagy. As a result, we identified a cluster of genes related to metabolic circuits that affect autophagy-response kinetics.
Our goal is to identify the temporal dynamics of metabolic networks that control autophagy. For that, the student will map the whole metabolic network in yeast and integrate these data with the results from screening in order to predict the key metabolites that alter autophagy dynamics. As a first step, we will use machine learning algorithms for time-series analysis to determine metabolic pathways that cause changes in autophagy kinetics. The student will then compare changes in autophagy dynamics caused by perturbation of either intrinsic or extrinsic metabolite sources, and use different tools to monitor and measure autophagy, such as confocal imaging, tracking of autophagy selective markers by western blotting and enzymatic assays to monitor degradation.
What we offer the student
The student in this project will get wet lab experience with budding yeast handling, molecular biology and biochemistry methods such as PCR, cloning, western blotting and confocal microscopy. The student will also get experience in systems biology research and advanced computational analysis of biological screening data. In addition, the student will get training in transferrable skills such as scientific oral communication, writing and project planning.
Our group
The Cancer Molecular Medicine group is led by Professor Jorrit Enserink and consists of 21 members from 9 different countries. One of our research areas is the study of dynamic behaviours of autophagy control together with the development of computational strategies. The group has extensive experience in the supervision of master and PhD students and offers an excellent international and dynamic research environment. Our group is located at the Department for Molecular Cell Biology at Radiumhospitalet, where we share facilities, reagents, and expertise with other groups working on a variety of research topics. We are also part of the CanCell Centre of Excellence.