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Max Planck Society
Country: Germany
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1,043 Projects, page 1 of 209
  • Funder: EC Project Code: 101041331
    Overall Budget: 1,500,000 EURFunder Contribution: 1,500,000 EUR

    Advancing age is the major risk factor for many serious illnesses, including cancer, cardiovascular disease, and dementia. The rising number of older individuals is thus causing a major burden of ill health. However, individuals that reach an exceptional old age often seem to escape or delay age-related diseases, and part of this trait seems to be encoded in their genome. Hence, by studying the genome of long-lived individuals, we may be able to identify mechanisms that could be targeted for healthy ageing in the general population. My previous work suggests that large genome-wide association studies (GWAS) of long-lived individuals can be used to identify genetic variants involved in longevity. However, the common genetic variants thus far identified using GWAS only explain a minor part of the genetic component of longevity. This trait, therefore, may well be mainly determined by rare genetic variants, which can be detected using whole-genome or exome sequencing of long-lived families or exceptionally long-lived individuals. The aim of the proposed project is to establish the effect of genetic variants identified in genetic studies of long-lived individuals on general health and lifespan using cellular models and, subsequently, model organisms. To this end, I will use CRISPR/Cas9 gene editing to generate transgenic cell lines and mice that harbour genetic variants in candidate genes and pathways identified through GWAS and sequencing studies of long-lived families and individuals. I will subsequently use this information to create a high-throughput screening assay to identify compounds that can pharmacologically recapitulate the observed in vitro effects. As a proof-of-principle, I will start with functional characterisation of rare variants in genes involved in insulin/insulin-like growth factor 1 (IIS) and mammalian target of rapamycin (mTOR) signalling, given the well-known role of these networks in ageing in pre-clinical model organisms.

  • Funder: EC Project Code: 101086182
    Overall Budget: 2,000,000 EURFunder Contribution: 2,000,000 EUR

    The ability to infer information about hidden degrees of freedom from time series would revolutionize experiments on single molecules, mesoscale assemblies, and tissues, as well as financial and climate systems. Hidden dynamics are often essential, as they reflect the approaching of a critical transition or describe its mechanism, e.g. the folding of a protein or RNA, or an abrupt shift in climate. With the project proposed here I plan to push our quantitative understanding of experiments, ranging from single-molecule spectroscopy to observations of migrating cells and developing tissues, to a new level, by exploiting how the properties of a high-dimensional landscape and current imprint onto the time ordering of projected states along individual trajectories. I will introduce functionals of projected paths that are easily inferred from data, and analyze their statistics and measure concentration by combining the theory of functionals of stochastic paths, concentration inequalities, and semiclassical analysis, and apply these to single-molecule force spectroscopy and plasmon ruler experiments, cell tracking, and Molecular Dynamics simulations. A distinctive characteristic of the project is the focus on non-asymptotic measure concentration, i.e. on “occurs with high probability” results that will be addressed for the first time in the context of non-equilibrium physics. Providing a new framework for interpreting experiments—using the information readily encoded in the data but inaccessible to existing approaches—the project will generate new knowledge that will resolve the long-standing debate about intermediates in DNA, RNA and protein folding, controversies about non converging dynamics of folded proteins, and shed new light on the operation of nanomachines and self-assembly far from equilibrium, as well as cell movements during tissue regeneration. It will lead to a paradigm-shift in soft matter and biophysics and may reshape actuarial and climate science.

  • Funder: EC Project Code: 101111457
    Funder Contribution: 189,687 EUR

    Metagenome-assembled genomes (MAGs) obtained from metagenomics are of fundamental value to understanding diverse ecological niches of microbes such as the human gut, with applications in medicine, biotechnology, and climate science. However, the quality of MAGs constructed with state-of-the-art tools is often unsatisfactory and worse than the self-reported quality. The main source of error is binning, a computational step that groups sequences assembled from short sequencing reads (contigs) into species-wise bins. The two chief challenges are accurately binning (1) genomes with low abundance and (2) highly conserved regions. Due to cross-mapping of reads, the contigs from conserved regions appear to have abundances equal to the sum of the abundances of the related species or strains. As conventional binning tools all rely on clustering contigs according to their abundances across samples, conserved regions end up forming separate bins. Besides, most existing methods optimise quality measures (purity and completeness based on conserved marker genes) and assess the final quality on these very measures, leading to highly optimistic results. I aim to solve these problems by developing a binning algorithm that applies i) linear mixture models using non-negative matrix factorization to account for cross-mapping, ii) Poisson statistics to accurately model low abundance, and iii) Bayesian statistics-based multinomial clustering to calculate bin numbers. Importantly, it does not require marker gene-based quality measures for binning. By improving the binning of low-abundance and highly conserved contigs, this approach should yield more high-quality MAGs, thereby enhancing a multitude of downstream metagenomic analyses for all areas of microbiome research.

  • Funder: EC Project Code: 101054447
    Overall Budget: 2,171,250 EURFunder Contribution: 2,171,250 EUR

    Eukaryotic messenger ribonucleoprotein (mRNP) particles are the functional entities that carry genetic information to the protein synthesizing machinery. These ribonucleoprotein complexes are dynamic and diverse, as highlighted by the copious number of proteins and transcripts identified in global proteomic and transcriptomic studies. However, little is known about the composition and architecture of individual mRNPs, and how changes in mRNP structure relate to their function or to dysfunction. The GOVERNA project will address this gap in knowledge by purifying specific mRNPs and delving into their molecular and structural arrangement. With our preliminary data serving as a springboard, the project combines genomic tagging engineered to maintain the most physiologically relevant conditions, biochemical methods developed to preserve the integrity of transient ribonucleoprotein assemblies, and mass spectrometry and cryo-electron microscopy to identify the composition and architecture of mRNPs. We will zoom-in on a set of paradigms in RNA biology that not only sample the breadth of mRNP diversity, but are also powerful model systems for linking structural information and biological function. We will investigate the molecular features in the three-dimensional organization of nuclear mRNPs from S. cerevisiae and of translationally repressed mRNPs in early developmental stages in D. melanogaster and X. laevis. For mRNPs undergoing active translation, we will investigate the transitions of human beta-globin mRNPs in the course of a surveillance process connected to disease. By studying these examples, we will glean fundamental insights into global principles governing the packaging of mRNPs and the remodeling of their three-dimensional features throughout a transcript’s life-cycle. The cumulative output will illuminate a central node of eukaryotic gene expression that is also particularly timely and relevant given recent developments in mRNA-based therapeutics.

  • Funder: EC Project Code: 757957
    Overall Budget: 1,618,120 EURFunder Contribution: 1,618,120 EUR

    With each newly detected exoplanet system, the planet formation theory is constantly gaining weight in the astrophysical research. The planets origin is a mystery which can only be solved by understanding the protoplanetary disks evolution. Recent disk observations by the new class of interferometer telescopes are challenging the existing theory of planet formation. They reveal astonishing detailed structures of spirals and rings in the dust emission which have never been seen before. Those structures are often claimed to be caused by embedded planets, which is difficult to explain with current models. This growing discrepancy between observation and theory forces us to realize: a novel disk modeling is essential to move on. Separate gas or dust evolution models have reached their limit and the gap between those has to be closed. With the UFOS project, I propose an unique and ambitious approach to unite gas and dust evolution models for protoplanetary disks. For the first time, a single global model will mutually link self-consistently: a) the transport of gaseous disk material, b) the radiative transfer, c) magnetic fields and their dissipation and d) the transport and growth of the solid material in form of dust grains. The development, performing and post-analysis of the models will initiate a new age for the planet formation research. The project results will achieve 1) unprecedented self-consistent precision to answer the question if those novel observed structures are caused by embedded planets or by the gas dynamics itself; 2) to find the locations of dust concentration and growth to unveil the birth places of planets and 3) to close the gap and finally unify self-consistent models of the disk evolution with the new class of observations. Only such advanced models combined with multi-wavelength observations, can show us the process of planet formation, and so explain the origin of the various of planets and exoplanets in our solar neighborhood and beyond.

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