Projects
Here you can find an overview of the team's research projects; please stay tuned for more information on international and industrial collaborations.
Squiggle Data
Metagenomics allows us to study whole microbial communities found in environmental samples. One of the disadvantages of metagenomics is that we cannot differentiate between living and dead microorganisms.
Nanopore sequencing enables real-time DNA sequencing by measuring the fluctuation in ionic current in signal traces (“squiggle”) while single-strand nucleotides move through a membrane-embedded nanopore. As this squiggle signal can detect atomic changes in nucleotides through the fluctuations in the nanopores’ ionic current, this raw nanopore signal can be leveraged to infer functionally important characteristics of the genomic material, such as epigenetic modifications.
In this project, we aim to leverage nanopore sequencing and deep neural networks to develop an entirely computer-based framework that can predict the viability of microorganisms from squiggle data.
This project is led by Harika Urel in collaboration with FZ Jülich (Stefan Kesselheim, Sabrina Benassou, Anoop Chandran) and the Technical University of Munich (Michael Schloter).
Special feature: Our Real-time Genomics for One Health Workshop in the Alps in September 2023
We have invited an international and interdisciplinary group of researchers to the Schneefernerhaus high up in the Alps to discuss Real-time Genomics for One Health in-depth, and to provide a platform to discuss a long-term consortium framework for our future collaborations. We are excited to welcome renowned nanopore users such as Olga Francino, Reindert Nijland, Martin Hölzer, Ebenezer Foster-Nyarko, and more. Our schedule will be:
September 3rd: Arrival in Munich and discussions over dinner
September 4th: Arrival at Schneefernerhaus and workshops
1300-1500: Squiggle data workshop
1530-1700: Biodiversity workshop (plus adaptive sampling)
1730-1900: Clinical application workshop
September 5th: Workshops, "nanothon", and consortium discussions
800-1000: Computational metagenomics workshop
1000-1200: Start of hackathon in small groups to lay out realistic One Health problems and solutions through real-time genomics
1200-1330: Lunch
1400-1600: Hike to Zugspitze Glacier
1600-1900: Continuation of hackathon and preparation of presentations; in parallel: One Health Genomics consortium discussions
September 6th: Nanothon wrap-up
800-930: nanothon presentations
from 10:00: Return to Munich and afternoon presentations at Helmholtz Munich
Real-time Metagenomics
We develop and apply laboratory and computational tools to assess microbial communities from metagenomic long-read data. We apply this to better understand ecosystem functions of freshwater, glacier ice, and air ecosystems, the impact of anthropogenic pressures, and potential repercussions for human health.
This research is led by Anastasia Grekova, Tim Reska, and Amit Fenn in collaboration with ISGlobal Barcelona, the University of Cambridge, Universidade de São Paulo, Kromek, the Technical University of Munich, and many more.
Biodiversity Monitoring
Non-invasive methods are a key element to monitor endangered wildlife without disturbing their welfare and inducing unnecessary stress to them. We monitor pathogen spread in wildlife through environmental samples.
For example, we develop techniques for non-invasive avian influenza virus (AIV) monitoring. The Western world is currently suffering from one of the most devastating AIV epidemics, with unprecedented mortality in wild birds and millions of poultry birds culled. Even if the zoonotic risk is low at present, many AIV outbreaks have been detected in mammals, and transmission between mammal species has been suspected in some cases. Therefore, the need for fast and accessible surveillance methods to detect smaller outbreaks in wild populations before they spread to areas with a high density of poultry farms is more evident than ever.
We are developing portable, non-invasive, and easy-to-use workflow that will be accessible to non-experts for efficient AIV detection and classification in the field – a first step to establish AIV surveillance platforms in wild and remote areas to detect AIV circulation before it arrives at high-density agricultural areas
We further apply non-invasive conservation genomic approaches to a wide array of species, including the takahē (Porphyrio hochstetteri), the kākāpō (Strigops habroptilus), and the rock ptarmigan (Lagopus muta).
This research is led by Albert Perlas Puente, Linus Hoelzel, and Daniel Gygax, in collaboration with the New Zealand Department of Conservation, C4C, Rifcon, IRTA-CReSA Barcelona, and many other international conservation organizations.
Clinical Applications
Multidrug-resistant bacteria represent a major challenge for tackling bloodstream infections due to higher rates of treatment failure. A rapid and accurate identification of phenotypic resistance patterns would facilitate the early administration of appropriate therapy. Yet, bloodstream infection diagnosis is mainly culture-based, which is time- and resource-consuming. In this study, we use long-read assemblies from patient blood cultures for real-time resistance prediction to overcome the limitations of a culture-based approach. For this, we are developing a machine learning-based framework to make fast and accurate predictions of phenotypic resistances in bloodstream infections. By using long-read sequencing combined with phenotypic resistance data, we will be able to better understand the genomic predictors of resistance beyond gene detection, such as gene clusters and polygenic interactions. This framework bears the potential to improve the prognosis of resistant bloodstream infections by reducing the turnover time from sample collection to resistance diagnosis.
This project is led by Ela Sauerborn, in collaboration with the Health Research Unit Zimbabwe (THRU-ZIM), the Technical University of Munich, the London School of Hygiene & Tropical Medicine, and others.
