Work Package 4.

Regulation of endo-lysosomal processes by metabolic challenges.

Helmholtz Institute, Munich, Germany

Anja Zeigerer

Metabolic mouse models of diet-induced obesity have indicated a regulatory role for glucose and lipid metabolism on the dynamics of endo-lysosomal processes at a transcriptional and post-transcriptional level. This work package will identify which endo-lysosomal processes are shaped by metabolic changes (fasting/feeding), aging, disease conditions of the metabolic syndrome, including NAFLD/NASH and cholesterol storage disorders.

PhD projects in this Work Package:

PhD student 7 – The importance of the fasting-feeding transition for endosomal transport in the liver 

 Helmholtz Center Munich, DE

Anja Zeigerer, anja.zeigerer[at]helmholtz-muenchen.de

The PhD student will investigate whether metabolic changes and disease conditions influences endosomal activity and function, by using sub-cellular fractionation of endosomes from fasted and refed liver tissues followed by organelle proteomics. The most promising candidates will be genetically manipulated (using antisense oligonucleotides) to alleviate disease progression in animal models of NAFLD and type-2 diabetes. One of the candidates, Vps33b will be functionally exploited. Using these models, we will assess how the fasting-refeeding transition influences endosomal transport in the liver and will elucidate the importance of endosomal proteins in metabolic diseases, such as NAFLD & NASH.

PhD student 8 – High-throughput screening of endosomes in different metabolic/genetic backgrounds (position open)

Institut d’Investigacions Biomèdiques August Pi i Sunyer, University of Barcelona, ES

Albert Pol, apols[at]ub.edu

The PhD student will implement improved methods to purify endosomes from rat liver during different metabolic stresses (obesity and starvation) and genetic backgrounds (CRISPR/Cas9 loss-of-function). High-throughput quantitative proteomics and systems biology will be used to identify and characterize the protein complexes organized on endosomes in response to metabolic stresses and genetic backgrounds. Using genetic or pharmacological manipulation of selected endosomal candidates will be used to reproduce or alleviate disease progression in animal models.

PhD student 9 – Transcriptional regulation and functional validation of endo-lysosomal genes in metabolic diseases

Nebion, Zurich, CH

Philip Zimmermann, phz[at]nebion.com

You are employed and the research is done at Nebion. In addition, you are registered at the Helmholtz Institute, Munich, Germany, where you will do the thesis defence

The PhD student will scout and curate public transcriptomic datasets of healthy, diseased and treated patient samples and mouse models of NAFLD/NASH with focus on liver and adipose tissue. The student will be involved in the integration of the datasets and meta-analysis to gather insights for follow-up experimental planning with emphasis on endo-lysosomal processes. Perturbation analysis will be performed to formulate the potential role of top candidates in metabolic disease. After prioritization, several candidates will be further studied in cellular and mouse models.

PhD student 10 – Identifying the molecular pathology and the role of endo-lysosomal components in fatty livers progressing to cancer

Utrecht University, NL

Alain de Bruin, A.deBruin[at]uu.nl

The PhD student will determine the transcriptomic & proteomic profile of endo-lysosomal components in human/murine fatty livers by analysing public databases as well as performing RNA sequencing (single cell) and mass spectrometry. These results will be validated at the cellular and subcellular levels in diseased livers. Next, the impact of inhibiting endo-lysosomal gene expression on proliferation, viability, lipid metabolism in 3D- fatty liver models and cancer cells will be studied. The student will dissect the role of endo-lysosomal proteins in the progression of fatty liver disease by utilizing an established mouse model in combination with a direct in vivo editing approaches to delete candidates.

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