Projects & Collaborations 7 foundShow per page10 10 20 50 Bacterial stationary phase: interlacing of variability and active responses Research Project | 3 Project MembersAn organism's evolutionary viability depends on its ability to respond to various environmental challenges. These challenges can range from highly complex ecological rearrangements to seemingly simple changes such as the lack of a particular nutrient. Even for these "simpler" changes, the responses of an organism often involve profound physiological reorganization. In bacteria, for instance, shifting from a nutrient-rich to a nutrient-deprived environment causes dramatic changes in their physiology. In such a shift, machinery that supports exponential growth becomes poorly suited for survival in a non-growing state. Thus, bacteria must reshape their proteome, condense their DNA, etc., to better cope with the new environment. These responses are inherently variable yet reflective of bacterial regulatory programs shaped by evolution. Variability underlies bet-hedging strategies, but it is unclear how it arises and determines the survival of bacteria in a stationary phase. During my postdoc in the van Nimwegen group, I aim to identify quantitative rules governing physiological rearrangements and gene expression variability at the entry into the stationary phase. By combining experimental and modeling work, I will investigate the relative contribution of both passive processes (e.g., exhaustion of intracellular resources) and active regulatory responses (e.g., targeted protein degradation, up- and down-regulation of gene expression) during the transition into the stationary phase. Besides ecology and evolution, the physiology of bacteria in the stationary phase shapes bacterial responses to antibiotics, which makes understanding the mechanisms of growth arrest clinically relevant as well. Drawing the landscape of bacterial stationary phase Research Project | 1 Project MembersNo Description available NCCR AntiResist: New approaches to combat antibiotic-resistant bacteria Umbrella Project | 32 Project MembersAntibiotics are powerful and indispensable drugs to treat life threatening bacterial infections such as sepsis or pneumonia. Antibiotics also play a central role in many other areas of modern medicine, in particular to protect patients with compromised immunity during cancer therapies, transplantations or surgical interventions. These achievements are now at risk, with the fraction of bacterial pathogens that are resistant to one or more antibiotics steadily increasing. In addition, development of novel antimicrobials lags behind, suffering from inherently high attrition rates in particular for drug candidates against the most problematic Gram-negative bacteria. Together, these factors increasingly limit the options clinicians have for treating bacterial infections. The overarching goal of NCCR AntiResist is to elucidate the physiological properties of bacterial pathogens in infected human patients in order to find new ways of combatting superbugs. Among the many societal, economic, and scientific factors that impact on the development of alternative strategies for antibiotic discovery, our limited understanding of the physiology and heterogeneity of bacterial pathogens in patients ranks highly. Bacteria growing in tissues of patients experience environments very different from standard laboratory conditions, resulting in radically different microbial physiology and population heterogeneity compared to conditions generally used for antibacterial discovery. There is currently no systematic strategy to overcome this fundamental problem. This has resulted in: (i) suboptimal screens that identify new antibiotics, which do not target the special properties of bacteria growing within the patient; (ii) an inability to properly evaluate the efficacy of non-conventional antibacterial strategies; (iii) missed opportunities for entirely new treatment strategies. This NCCR utilizes patient samples from ongoing clinical studies and establishes a unique multidisciplinary network of clinicians, biologists, engineers, chemists, computational scientists and drug developers that will overcome this problem. We are excited to merge these disciplines in order to determine the properties of pathogens infecting patients, establish conditions in the lab that reproduce these properties and utilize these in-vitro models for antimicrobial discovery and development. In addition, clinical-trial networks and the pharmaceutical industry have major footprints in antimicrobial R&D. Exploiting synergies between these players has great potential for making transformative progress in this critical field of human health. This NCCR maintains active collaborations with Biotech SMEs and large pharmaceutical companies with the goal to: accelerate antibiotic discovery by providing relevant read-outs for early prioritization of compounds; enable innovative screens for non-canonical strategies such as anti-virulence inhibitors and immunomodulators; identify new antibacterial strategies that effectively combat bacteria either by targeting refractory subpopulations or by synergizing with bacterial stresses imposed by the patients' own immune system. This NCCR proposes a paradigm shift in antibiotic discovery by investigating the physiology of bacterial pathogens in human patients. This knowledge will be used to develop assays for molecular analyses and drug screening under relevant conditions and to accelerate antibacterial discovery, improve treatment regimens, and uncover novel targets for eradicating pathogens. Through this concerted effort, this NCCR will make a crucial and unique contribution to winning the race against superbugs. High-throughput multiplexed microfluidics for antimicrobial drug discovery Research Project | 4 Project MembersThis project ist part of the PhD program of the SNI Swiss Nanoscience Institute. The project is a collaboration between the van Nimwegen research group at the Biozentrum and the Laboratory for Micro- and Nanotechnology at the PSI. The wet lab of the van Nimwegen group, led by Dr. Thomas Julou, is at the forefront of method development for quantitatively tracking bacteria at the single-cell level in dynamically controlled environmental conditions (Kaiser, et al. 2018), whereas the PSI group focuses on microfabrication and prototyping. The main goal of the project is to develop a new method for high-throughput quantification of the effects of antimicrobial compounds on single cells as a function of their physiological state. In the first phase of the project the student will develop new microfluic designs that allow arrays of strains and treatments to be assayed in parallel, building on existing prototypes that have already been developed in the van Nimwegen lab (e.g. the figure shows the response of a lineage of single E. coli cells to a sudden exposure to ceftriaxone). These designs will involve fabrication of channels with sub-micrometer dimensions and thus the use of electron beam lithography. The fabrication will be carried out at the PSI where, besides optical UV lithography, high resolution e-beam direct writing tools are available for defining high aspect ratio micro- and nanometer structures of arbitrary shape (Vila-Comamala, et al. 2011). Measuring single-cell pharmacodynamics with deep learning Research Project | 3 Project MembersThe pharmacodynamics of antibiotics are currently almost exclusively defined at the population level. However, recent studies have highlighted that microbial pathogens diversify into different physiological states within their hosts, and that the action of antibiotics can vary dramatically with the physiological state of single cells. Thus, a comprehensive approach to quantifying pharmacodynamics at the single-cell level, across bacterial strains and growth conditions, will likely have a profound impact on the development of novel antimicrobial therapies. Recently developed microfluidic setups, when used in combination with time-lapse microscopy, allow long-term monitoring of growth and gene expression in single bacterial cells exposed to precisely controlled environments. However, the throughput of such methods is currently highly constrained by the image analysis, which still requires manual curation. We here propose to harness recent progress in deep learning image analysis methods to develop a fully automated image analysis tool for time-lapse microfluidic data. As a proof-of-principle, we will use our tool in combination with downstream Bayesian probabilistic methods to infer detailed single-cell pharmacodynamics of several antibiotics from measurements of growth inhibition and killing of individual bacteria exposed to antibiotics with different growth conditions and treatment protocols. The role of gene expression noise in the evolution of gene regulation Research Project | 12 Project MembersEines der auffälligsten Merkmale, welches uns Lebewesen von den unbelebten Objekten unterscheidet, die die Physik und die Chemie untersucht, ist die Eigenschaft, auf die Umwelt zu reagieren und sich anzupassen. Zellen können Chemikalien in ihrer Umgebung wahrnehmen und darauf reagieren, da sie Mechanismen besitzen, um die Expression ihrer Gene entsprechend anzupassen. Über die molekularen Mechanismen der Genregulierung ist schon viel bekannt; regulatorische Proteine wie z.B. Transkriptionsfaktoren binden in einer sequenz-abhängigen Weise an kurze DNA Stücke, und die Bindungsmuster dieser regulatorischen Proteine sind ziemlich gut erforscht, aber beinahe nichts ist bekannt über die Art und Weise, in der die Genregulation evolutionär entstanden ist. Neuere Arbeit aus unserem Labor hat angedeutet, dass es eine grundlegende, starke Verbindung gibt zwischen der Evolution der Genregulierung und dem Rauschen in dem Prozess der Genexpression. Wie jeder physikalische Prozess hängt auch die Genexpression von thermischen und anderen Fluktuationen ab, welche bewirken, dass sogar identische Zellen in einer homogenen Umgebung Schwankungen in ihrem Verhalten zeigen. Ein Teil dieses Genexpressions-Rauschens wird durch die Ausbreitung des Rauschens der regulatorischen Protein an ihre Zielgene verursacht, und aus unserer jüngsten Arbeit lässt sich schliessen, dass die Weiterleitung des Rauschen eine wichtige Rolle spielt bei der Entwicklung der Genregulation. In diesem Projekt werden wir mit einer Kombination aus experimentellen und theoretischen Ansätzen die Rolle des Rauschens der Genexpression in der Evolution der Genregulierung am Beispiel des Bakteriums Escherichia coli untersuchen. Wir erwarten, dass diese Arbeit neue grundlegende Erkenntnisse liefert, wie Organismen lernen können, sich an ihre Umgebung anzupassen. Diese Erkenntnisse könnten wichtige Auswirkungen auf alle Gebiete der Biotechnologie haben. StoNets - Controlling and exploiting stochasticity in gene regulatory networks Research Project | 30 Project MembersThe precision with which cells undergo differentiation programs or respond to external stimuli is remarkable, especially when considering the inherently "noisy" molecular interactions underlying these processes. StoNets aims to understand how stochasticity is controlled - and even exploited - to allow the development of robust behaviors of genetic networks, cells and cellular systems. Although all cells within an organism carry the same genetic information, regulatory mechanisms that operate at essentially all steps of gene expression lead to a large variety of cell types and behaviors. Progress in measurement technologies has enabled the precise and high-throughput probing of molecules and cells. This in turn has revealed that stochasticity is pervasive in all gene expression regulatory systems. The central question we will address in this StoNets project is how robust and reproducible cellular behaviors can emerge in spite of these noisy molecular interactions. A "slice" across the levels of gene expression organization We will undertake a systematic investigation into the mechanisms that have emerged to control noise at different organizational scales of gene expression regulation, from transcription of individual genes to cell fate switching. Each of the example systems that we selected is interesting in its own right and exhibits important stochastic aspects. Questions motivated by modeling With the continuous progress in understanding the basic mechanisms of gene regulation, many key molecular players have been identified and numerous direct regulatory interactions have been mapped. Theoreticians have started to model the way in which specific behaviors emerge from the underlying interactions. These efforts have led to a large number of new, inherently quantitative questions regarding the biological systems. Through a very tight integration of experimental and computational approaches StoNets aims to answer such questions ultimately contributing to an improved, quantitative understanding and thereby controllability of cellular behaviors. 1 1
Bacterial stationary phase: interlacing of variability and active responses Research Project | 3 Project MembersAn organism's evolutionary viability depends on its ability to respond to various environmental challenges. These challenges can range from highly complex ecological rearrangements to seemingly simple changes such as the lack of a particular nutrient. Even for these "simpler" changes, the responses of an organism often involve profound physiological reorganization. In bacteria, for instance, shifting from a nutrient-rich to a nutrient-deprived environment causes dramatic changes in their physiology. In such a shift, machinery that supports exponential growth becomes poorly suited for survival in a non-growing state. Thus, bacteria must reshape their proteome, condense their DNA, etc., to better cope with the new environment. These responses are inherently variable yet reflective of bacterial regulatory programs shaped by evolution. Variability underlies bet-hedging strategies, but it is unclear how it arises and determines the survival of bacteria in a stationary phase. During my postdoc in the van Nimwegen group, I aim to identify quantitative rules governing physiological rearrangements and gene expression variability at the entry into the stationary phase. By combining experimental and modeling work, I will investigate the relative contribution of both passive processes (e.g., exhaustion of intracellular resources) and active regulatory responses (e.g., targeted protein degradation, up- and down-regulation of gene expression) during the transition into the stationary phase. Besides ecology and evolution, the physiology of bacteria in the stationary phase shapes bacterial responses to antibiotics, which makes understanding the mechanisms of growth arrest clinically relevant as well.
Drawing the landscape of bacterial stationary phase Research Project | 1 Project MembersNo Description available
NCCR AntiResist: New approaches to combat antibiotic-resistant bacteria Umbrella Project | 32 Project MembersAntibiotics are powerful and indispensable drugs to treat life threatening bacterial infections such as sepsis or pneumonia. Antibiotics also play a central role in many other areas of modern medicine, in particular to protect patients with compromised immunity during cancer therapies, transplantations or surgical interventions. These achievements are now at risk, with the fraction of bacterial pathogens that are resistant to one or more antibiotics steadily increasing. In addition, development of novel antimicrobials lags behind, suffering from inherently high attrition rates in particular for drug candidates against the most problematic Gram-negative bacteria. Together, these factors increasingly limit the options clinicians have for treating bacterial infections. The overarching goal of NCCR AntiResist is to elucidate the physiological properties of bacterial pathogens in infected human patients in order to find new ways of combatting superbugs. Among the many societal, economic, and scientific factors that impact on the development of alternative strategies for antibiotic discovery, our limited understanding of the physiology and heterogeneity of bacterial pathogens in patients ranks highly. Bacteria growing in tissues of patients experience environments very different from standard laboratory conditions, resulting in radically different microbial physiology and population heterogeneity compared to conditions generally used for antibacterial discovery. There is currently no systematic strategy to overcome this fundamental problem. This has resulted in: (i) suboptimal screens that identify new antibiotics, which do not target the special properties of bacteria growing within the patient; (ii) an inability to properly evaluate the efficacy of non-conventional antibacterial strategies; (iii) missed opportunities for entirely new treatment strategies. This NCCR utilizes patient samples from ongoing clinical studies and establishes a unique multidisciplinary network of clinicians, biologists, engineers, chemists, computational scientists and drug developers that will overcome this problem. We are excited to merge these disciplines in order to determine the properties of pathogens infecting patients, establish conditions in the lab that reproduce these properties and utilize these in-vitro models for antimicrobial discovery and development. In addition, clinical-trial networks and the pharmaceutical industry have major footprints in antimicrobial R&D. Exploiting synergies between these players has great potential for making transformative progress in this critical field of human health. This NCCR maintains active collaborations with Biotech SMEs and large pharmaceutical companies with the goal to: accelerate antibiotic discovery by providing relevant read-outs for early prioritization of compounds; enable innovative screens for non-canonical strategies such as anti-virulence inhibitors and immunomodulators; identify new antibacterial strategies that effectively combat bacteria either by targeting refractory subpopulations or by synergizing with bacterial stresses imposed by the patients' own immune system. This NCCR proposes a paradigm shift in antibiotic discovery by investigating the physiology of bacterial pathogens in human patients. This knowledge will be used to develop assays for molecular analyses and drug screening under relevant conditions and to accelerate antibacterial discovery, improve treatment regimens, and uncover novel targets for eradicating pathogens. Through this concerted effort, this NCCR will make a crucial and unique contribution to winning the race against superbugs.
High-throughput multiplexed microfluidics for antimicrobial drug discovery Research Project | 4 Project MembersThis project ist part of the PhD program of the SNI Swiss Nanoscience Institute. The project is a collaboration between the van Nimwegen research group at the Biozentrum and the Laboratory for Micro- and Nanotechnology at the PSI. The wet lab of the van Nimwegen group, led by Dr. Thomas Julou, is at the forefront of method development for quantitatively tracking bacteria at the single-cell level in dynamically controlled environmental conditions (Kaiser, et al. 2018), whereas the PSI group focuses on microfabrication and prototyping. The main goal of the project is to develop a new method for high-throughput quantification of the effects of antimicrobial compounds on single cells as a function of their physiological state. In the first phase of the project the student will develop new microfluic designs that allow arrays of strains and treatments to be assayed in parallel, building on existing prototypes that have already been developed in the van Nimwegen lab (e.g. the figure shows the response of a lineage of single E. coli cells to a sudden exposure to ceftriaxone). These designs will involve fabrication of channels with sub-micrometer dimensions and thus the use of electron beam lithography. The fabrication will be carried out at the PSI where, besides optical UV lithography, high resolution e-beam direct writing tools are available for defining high aspect ratio micro- and nanometer structures of arbitrary shape (Vila-Comamala, et al. 2011).
Measuring single-cell pharmacodynamics with deep learning Research Project | 3 Project MembersThe pharmacodynamics of antibiotics are currently almost exclusively defined at the population level. However, recent studies have highlighted that microbial pathogens diversify into different physiological states within their hosts, and that the action of antibiotics can vary dramatically with the physiological state of single cells. Thus, a comprehensive approach to quantifying pharmacodynamics at the single-cell level, across bacterial strains and growth conditions, will likely have a profound impact on the development of novel antimicrobial therapies. Recently developed microfluidic setups, when used in combination with time-lapse microscopy, allow long-term monitoring of growth and gene expression in single bacterial cells exposed to precisely controlled environments. However, the throughput of such methods is currently highly constrained by the image analysis, which still requires manual curation. We here propose to harness recent progress in deep learning image analysis methods to develop a fully automated image analysis tool for time-lapse microfluidic data. As a proof-of-principle, we will use our tool in combination with downstream Bayesian probabilistic methods to infer detailed single-cell pharmacodynamics of several antibiotics from measurements of growth inhibition and killing of individual bacteria exposed to antibiotics with different growth conditions and treatment protocols.
The role of gene expression noise in the evolution of gene regulation Research Project | 12 Project MembersEines der auffälligsten Merkmale, welches uns Lebewesen von den unbelebten Objekten unterscheidet, die die Physik und die Chemie untersucht, ist die Eigenschaft, auf die Umwelt zu reagieren und sich anzupassen. Zellen können Chemikalien in ihrer Umgebung wahrnehmen und darauf reagieren, da sie Mechanismen besitzen, um die Expression ihrer Gene entsprechend anzupassen. Über die molekularen Mechanismen der Genregulierung ist schon viel bekannt; regulatorische Proteine wie z.B. Transkriptionsfaktoren binden in einer sequenz-abhängigen Weise an kurze DNA Stücke, und die Bindungsmuster dieser regulatorischen Proteine sind ziemlich gut erforscht, aber beinahe nichts ist bekannt über die Art und Weise, in der die Genregulation evolutionär entstanden ist. Neuere Arbeit aus unserem Labor hat angedeutet, dass es eine grundlegende, starke Verbindung gibt zwischen der Evolution der Genregulierung und dem Rauschen in dem Prozess der Genexpression. Wie jeder physikalische Prozess hängt auch die Genexpression von thermischen und anderen Fluktuationen ab, welche bewirken, dass sogar identische Zellen in einer homogenen Umgebung Schwankungen in ihrem Verhalten zeigen. Ein Teil dieses Genexpressions-Rauschens wird durch die Ausbreitung des Rauschens der regulatorischen Protein an ihre Zielgene verursacht, und aus unserer jüngsten Arbeit lässt sich schliessen, dass die Weiterleitung des Rauschen eine wichtige Rolle spielt bei der Entwicklung der Genregulation. In diesem Projekt werden wir mit einer Kombination aus experimentellen und theoretischen Ansätzen die Rolle des Rauschens der Genexpression in der Evolution der Genregulierung am Beispiel des Bakteriums Escherichia coli untersuchen. Wir erwarten, dass diese Arbeit neue grundlegende Erkenntnisse liefert, wie Organismen lernen können, sich an ihre Umgebung anzupassen. Diese Erkenntnisse könnten wichtige Auswirkungen auf alle Gebiete der Biotechnologie haben.
StoNets - Controlling and exploiting stochasticity in gene regulatory networks Research Project | 30 Project MembersThe precision with which cells undergo differentiation programs or respond to external stimuli is remarkable, especially when considering the inherently "noisy" molecular interactions underlying these processes. StoNets aims to understand how stochasticity is controlled - and even exploited - to allow the development of robust behaviors of genetic networks, cells and cellular systems. Although all cells within an organism carry the same genetic information, regulatory mechanisms that operate at essentially all steps of gene expression lead to a large variety of cell types and behaviors. Progress in measurement technologies has enabled the precise and high-throughput probing of molecules and cells. This in turn has revealed that stochasticity is pervasive in all gene expression regulatory systems. The central question we will address in this StoNets project is how robust and reproducible cellular behaviors can emerge in spite of these noisy molecular interactions. A "slice" across the levels of gene expression organization We will undertake a systematic investigation into the mechanisms that have emerged to control noise at different organizational scales of gene expression regulation, from transcription of individual genes to cell fate switching. Each of the example systems that we selected is interesting in its own right and exhibits important stochastic aspects. Questions motivated by modeling With the continuous progress in understanding the basic mechanisms of gene regulation, many key molecular players have been identified and numerous direct regulatory interactions have been mapped. Theoreticians have started to model the way in which specific behaviors emerge from the underlying interactions. These efforts have led to a large number of new, inherently quantitative questions regarding the biological systems. Through a very tight integration of experimental and computational approaches StoNets aims to answer such questions ultimately contributing to an improved, quantitative understanding and thereby controllability of cellular behaviors.
