Phase Separation and Neuro-degenerative Diseases: A Disturbance in the Force
Many proteins found in pathological aggregations, the hallmark of neuro-degenerative diseases, have been shown to undergo reversible liquid-liquid phase separation under the right conditions. This suggests that aberrant phase separation may trigger the protein aggregation seen in neurodegeneration.
This review addresses similarities and differences among four proteins that are both known to undergo phase separation and are found as aggregations in neuro-degenerative diseases. In addition, future directions in this field are discussed that will contribute to elucidating the molecular mechanisms underlying aggregation and neurodegeneration.
See Zbinden, Pérez-Berlanga et al, Developmental Cell
As coordinator of the ImageTDP43 consortium, the Polymenidou group has been awarded a competitive EU Consortium Grant from the 'EU Joint Programme - Neurodegenerative Disease Research (JPND).
The project 'ImageTDP43: Imaging heterogeneous TDP-43 neuropathologies' aims at developing TDP-43 PET ligands that will allow to accurately detect and monitor TDP-43-related neurodegenerative progression in diseases such as amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration with TDP-43 pathology (FTLD-TDP).
The ImageTDP43 consortium brings together world-class academic partners from Fondazione Santa Lucia (Italy), Skåne University Hospital (Sweden) and Erasmus Medical Center (Netherlands), as well as industry partner AC Immune (Switzerland).
Please also read AC Immune's press release, which can be found here.
We are excited to announce that Bernd Bodenmiller has been appointed as Dual Professor for Quantitative Biomedicine at the UZH and at ETH Zurich, starting from 1 October 2020. Please find the press release here:
Bernd Bodenmiller’s dual affiliation is an important step towards the optimal positioning of DQBM within the Zurich quantitative biomedical community, in order to fulfill our mission to develop next-generation precision medicine in Zurich. We are excited about the new opportunities for scientific synergies between ETHZ and UZH resulting from this dual affiliation and look forward to the journey ahead.
The Kümmerli group shows the potential of combining antivirulence drugs with antibiotics against an opportunistic human pathogen
Combining antibiotics with antivirulence compounds can have synergistic effects and reverse selection for antibiotic resistance in Pseudomonas aeruginosa
This microbiology study reveals that compounds that disarm bacterial pathogens by targeting their virulence factors can be potent adjuvants to antibiotics, as they remain active against - and can reduce the selective advantage of - antibiotic resistant strains.
See Rezzoagli, Archetti et al., PLOS Biology
*Figure 4: Drug interaction heatmaps for antibiotic-antivirulence combination treatments.
The Bodenmiller group receives SNF support to study primary immune response & memory in COVID-19 patients
Together with Prof. Dr. med. Onur Boyman and Dr. med. Jakob Nilsson at the University Hospital Zurich andProf. Dr. Daniel Pinschewer at the University of Basel, the Bodenmiller group has received research project support from SNF NRP78 to contribute to our understanding of COVID-19. The project will focus on primary immune responses and the initial memory phase in mild vs. serious COVID-19 cases.
Please find the official announcement on the SNF website here.
The Bodenmiller group publishes their collaborative work on CD4+ T Helper Cell response heterogeneity
High-Dimensional T Helper Cell Profiling Reveals a Broad Diversity of Stably Committed Effector States and Uncovers Interlineage Relationships
This study resulted from a collaboration with the research group of Prof. Dr. Manfred Kopf at ETH Zurich.
CD4 + T helper (Th) are known to orchestrate immune responses. Based on the expression of signature cytokines and transcription factors, several Th subsets have previously been defined. In this study, CyTOF was used to systematically explore the diversity of Th cell responses generated both in vitro and in animal disease models, revealing a broad diversity in effector states with distinct cytokine footprints.
The DQBM is delighted to announce that Prof. Dr. Bjoern Menze will join the DQBM Faculty as Full Professor for Biomedical Image Analysis and Machine Learning, funded by the Helmut Horten Foundation.
Prof. Menze studied physics in Heidelberg and Uppsala and received his PhD in Heidelberg in 2007. As postdoctoral researcher, he worked at renowned research institutions, including Harvard Medical School in Boston, MIT in Cambridge and ETH Zurich. In 2013, Prof. Menze was appointed a W2 professorship at the Technical University of Munich (TUM), where he has been researching and teaching since. In 2019, Prof. Menze was appointed W3 Professor for Image-Based Biomedical Modelling at the Munich School of BioEngineering and the Zentralinstitut fuer translationale Krebsforschung (TranslaTUM).
The Menze group will be moving to the UZH from the Technical University of Munich (TUM). Please find the UZH's official announcement here.
We look forward to welcoming the Menze Group to our Department later this year!
Photo: © Andreas Heddergott / TU Muenchen
The Kümmerli group shows how biotic and abiotic factors affect competitive dynamics between co-infecting human pathogens
Strain background, species frequency and environmental conditions are important in determining population dynamics and species co-existence between ;Pseudomonas aeruginosa and Staphylococcus aureus
Although bacterial communities in infections are typically diverse, little is known about how ecology affects inter-pathogen competition. Here, ecological theory was applied to understand how biotic and abiotic factors affect interaction patterns between two human pathogens that often co-occur in polymicrobial infections: Pseudomonas aeruginosa and Staphyloccocus aureus. This study revealed that ecological details such as strain background, species frequency and environmental conditions play important roles in the competitive dynamics between these co-infecting pathogens, suggesting that to truly understand polymicrobial infections, an integrative approach combining molecular and ecological aspects is essential.
*Figure 3 shows that the competitive ability of Pseudomonas aeruginosa depends on the Staphylococcus aureus strain genetic background. ;
See Niggli & Kümmerli, Applied & Environmental Microbiology
Antagonistic interactions subdue inter‐species green‐beard cooperation in bacteria
Cooperative behaviour among individuals is common, despite apparent fitness costs for the individual. The green‐beard mechanism can foster such cooperation: When a set of linked genes encodes both a cooperative trait and a phenotypic marker (green beard), carriers of that cooperative trait can selectively direct their cooperative actions to other carriers of this trait. This paper explored an extreme green‐beard scenario between two unrelated bacterial species P. aeruginosa and B. cenocepacia, which both produce the public good pyochelin (the cooperative trait) and an iron-pyochelin uptake receptor (the green beard). Competition experiments between these phylogenetically unrelated species revealed that the green‐beard cooperation effect collapses in this scenario, indicating that selection for competitive traits might overrule selection for cooperation in inter‐species interactions.
See Sathe & Kümmerli, Journal of Evolutionary Biology
The Krauthammer group publishes their work on deep learning-based multimodal fusion techniques to reduce annotation burden
Reducing Annotation Burden Through Multimodal Learning
This study examined deep learning-based multimodal fusion techniques for the combined classification of radiological images and associated text reports, comparing the classification performance of three prototypical multimodal fusion techniques. The experiments demonstrate the potential of multimodal fusion methods to yield competitive results using less training data than their unimodal counterparts. This suggests that the potential of multimodal learning decreases the need for labeled training data, which results in a lower annotation burden for domain experts.
See Lopez et al., Frontiers in Big Data
The Krauthammer Group publishes their work on machine learning models for assessing the quality of online health information.
AutoDiscern: rating the quality of online health information with hierarchical encoder attention-based neural networks
When facing health problems, patients increasingly turn to search engines and online information before or instead of talking to their doctor. However, as online health information is often of poor quality, this practice leads to potential misinformation. In this study, various machine learning models were built to evaluate the quality of online health information using the DISCERN criteria, which were developed at University of Oxford. The results suggest that automating the quality assessment of online health information is feasible, representing an important step towards enabling patients to become informed partners in the health process.
The Kümmerli group publishes their collaborative work on iron-driven phytopathogen control by natural rhizosphere microbiomes
Competition for iron drives phytopathogen control by natural rhizosphere microbiomes
This work results from a collaboration between the Kümmerli group and Alex Jousset, Zhong Wei, Shaohua Gu and others.
Soil-borne pathogenic bacteria are a global threat to food production, but due to the complexity of interactions between plants, their pathogens and the plant microbiome, plant infections are difficult to control. This study combined DNA-based soil microbiome analysis with in vitro and in planta bioassays to show that competition for iron via secreted siderophore molecules is a good predictor of microbe-pathogen interactions and plant protection. The results suggest that pathogen-suppressive microbiome members produce siderophores that the pathogen cannot use, establishing a causal mechanistic link between microbiome-level competition for iron and plant protection. This link provides opportunities to use siderophore-mediated interactions as a tool for microbiome engineering and pathogen control.
See Gu et al, Nature Microbiology
We congratulate Magdalini Polymenidou for being awarded the 2018/2019 Franco Regli Prize (2nd Prize ex æquo) for her work: TDP-43 extracted from frontotemporal lobar degeneration subject brains displays distinct aggregate assemblies and neurotoxic effects reflecting disease progression rates. Nature Neuroscience, Vol. 22, January 2019, 65–77.
Please find the announcement here
The Krauthammer group publishes a data anonymization reference classification merging legal and technical considerations
Lost in Anonymization - A Data Anonymization Reference Classification Merging Legal and Technical Considerations
This work results from a collaboration between Michael Krauthammer, Daniel Stekhoven (Clinical Bioinformatics at the ETH Zurich core facility NEXUS Personalized Health Technologies) and Kerstin Vokinger (UZH).
Technological advances have made it possible to explore the wealth of health data collected in electronic health records (EHR) and other health-related data sources, with the aim of improving innovation and quality in medicine. These advances have led to the concern that the use of health data for publicly-funded research may expose patients personal information. This study i) analysed how different regulations implemented in the US, EU, and Switzerland to protect patient privacy distinguish between different levels of anonymization of health data, and ii) assessed whether and how these levels align with technical advancements.
See K.N. Vokinger et al., 2020, The Journal of Law, Medicine & Ethics
We congratulate Johanna Wagner-Albrecht from the Bodenmiller group for winning the 2020 Annual Thesis Award (Jahrespreis 2020 der Mathematisch-naturwissenschaftlichen Fakultät) for her dissertation: ''Single-Cell Proteomic Characterization of the Tumor and Immune Ecosystem of Human Breast Cancer with Focus on Metastatic Potential''.
Please find the announcement here
Michael Krauthammer shares his vision on using AI to generate medical evidence from real world health data in UZH magazine
Is AI cleverer than us?
Today, Artificial Intelligence (AI) is widely used in the healthcare sector, relieving the burden on doctors and supporting them in taking medical decisions. Michael Krauthammer's vision for healthcare is to create a medical data repository that allows data to be exchanged worldwide, to supplement insights from clinical trials with data from daily medical practice. This would broaden doctors' horizons beyond their own patients to hundreds of thousands of patients worldwide. As the task of building up and maintaining this hypothetical medical data repository with anonymized patient data is highly complex, it will require the help of AI.
Please find the UZH News article here
Image: Zentrale Informatik, Mels
The Bodenmiller group publishes their review on profiling cell signaling networks at single-cell resolution
Profiling cell signaling networks at single-cell resolution
Heterogeneity of signalling networks is at the basis of many biological processes, such as cell differentiation and drug resistance. Recent developments in multiplexed single-cell measurement technologies enabled evaluation of this heterogeneity. This review categorizes single-cell signaling network profiling approaches by their methodology, coverage, and application, and discusses the pros and cons of each technology. Furthermore, computational tools for network characterization using single-cell data are described. Finally, potential confounding factors that need to be considered in single-cell signaling network analyses are discussed.
See Lun & Bodenmiller, Molecular & Cellular Proteomics
Imaging mass cytometry and multiplatform genomics define the phenogenomic landscape of breast cancer
A better understanding of how genomic alterations influence cell phenotypes and the structure of tumor ecosystems will likely allow the identification of biomarkers and the development of new treatments. In this study, Raza Ali, Hartland Jackson and colleagues coupled imaging mass cytometry (IMC) to multi-platform genomics to study how genomic alterations shape breast tumor ecosystems, improving our understanding of how genomic alterations affect tumor cell phenotypes.
Harnessing bacterial interactions to manage infections: a review on the opportunistic pathogen Pseudomonas aeruginosa as a case example
During an infection, bacterial pathogens can interact in a variety of ways, from cooperative sharing of resources to hostile competition. This review focuses on the relevance of these social interactions during opportunistic infections using the human pathogen P. aeruginosa as an example and shows how a deeper understanding of bacterial social dynamics can inspire new treatment approaches and improved, more sustainable infection management strategies.
See Rezzoagli et al., Journal of Medical Microbiology
The Bodenmiller group, in collaboration with the Krishnaswamy group, publishes a method to uncover axes of variation among single-cell cancer specimens
Uncovering axes of variation among single-cell cancer specimens
This work results from a collaboration between the Bodenmiller group and the Krishnaswamy group at Yale School of Medicine.
William S. Chen and Nevena Zivanovic contributed equally to this work.
This work was co-supervised by Bernd Bodenmiller and Smita Krishnaswamy.
See Chen, Zivanovic et al, Nature Methods
DQBM was founded on 1.1.2019. Our joint mission is to foster research and education at the interface of biomedical research, biotechnology, and computational biology, to develop the foundations of next generation precision medicine. Ultimately, our goal is to advance precision medicine for the benefit of patients.
We congratulate Prof. Dr. Bernd Bodenmiller, who has been awarded a prestigious ERC Consolidator Grant worth 2M EUR for his project 'Precision Motifs': Analysis of functional tissue motifs for precision medicine in metastatic breast cancer.
The full list of ERC Consolidator Grantees from UZH can be found here: list
The Kümmerli group publishes their review on bacterial siderophores in community and host interactions
See Kramer et al, Nature Reviews Microbiology
Link to paper: https://www.nature.com/articles/s41579-019-0284-4
We congratulate Prof. Dr. Bernd Bodenmiller, who was selected for the Analytical Scientist's Power List 2019 Top 100.
Please find the Top 100 here:
The Kümmerli group publishes their work on genetic constraints of siderophore cooperation exploitation in Burkholderia cenocepacia
See Sathe et al, Evolution Letters
Link to paper: https://doi.org/10.1002/evl3.144
Magdalini Polymenidou appointed Associate Professor for Biomedicine, in particular Molecular Pathogenesis of Neurodegeneration
We congratulate Prof. Dr. Magdalini Polymenidou on her appointment as Associate Professor for Biomedicine, in particular Molecular Pathogenesis of Neurodegeneration, effective October 1, 2019.
Please see the official announcement here (in German only):
The Krauthammer group publishes their work on neural network-based models versus logistic regression for predicting readmission
See Allam et al, Scientific Reports
Pubmed link to paper: https://www.ncbi.nlm.nih.gov/pubmed/31243311
The Bodenmiller group publishes a human kinome- and phosphatome-wide screen revealing overexpression-induced effects on cancer-related signaling
See Lun et al, Molecular Cell
Pubmed link to paper: https://www.ncbi.nlm.nih.gov/pubmed/31101498
The Kümmerli group publishes their work on the impact of Pseudomonas aeruginosa social interactions on host colonization
See Rezzoagli et al, The ISME Journal
Pubmed link to paper: https://www.ncbi.nlm.nih.gov/pubmed/31123320
The Bodenmiller group finds that breast cancer ecosystems are linked to poor prognosis and immunosuppression.
See Wagner et al, Cell,
TDP-43 extracted from frontotemporal lobar degeneration subject brains displays distinct aggregate assemblies and neurotoxic effects reflecting disease progression rates
See Laferriere et al, Nature Neuroscience
Please also see this accompanied news and views article
and the commentary on Alzforum.
Bernd Bodenmiller has been selected to receive the prestigious Friedrich Miescher Award 2019 for his research at the Institute of Molecular Life Sciences of the University of Zurich. The prize is Switzerland's highest distinction for young scientists performing outstanding research in the field of biochemistry.
Please find the press release here.
We are a new department that will foster research and education at the interface of biomedical research, biotechnology, and computational biology to develop the foundations of next generation precision medicine. Our groups currently cover the topics of cancer, neurodegenerative diseases and infectious diseases. Enjoy browsing our website to learn more about our work.