@article{8586, abstract = {Cryo-electron microscopy (cryo-EM) of cellular specimens provides insights into biological processes and structures within a native context. However, a major challenge still lies in the efficient and reproducible preparation of adherent cells for subsequent cryo-EM analysis. This is due to the sensitivity of many cellular specimens to the varying seeding and culturing conditions required for EM experiments, the often limited amount of cellular material and also the fragility of EM grids and their substrate. Here, we present low-cost and reusable 3D printed grid holders, designed to improve specimen preparation when culturing challenging cellular samples directly on grids. The described grid holders increase cell culture reproducibility and throughput, and reduce the resources required for cell culturing. We show that grid holders can be integrated into various cryo-EM workflows, including micro-patterning approaches to control cell seeding on grids, and for generating samples for cryo-focused ion beam milling and cryo-electron tomography experiments. Their adaptable design allows for the generation of specialized grid holders customized to a large variety of applications.}, author = {Fäßler, Florian and Zens, Bettina and Hauschild, Robert and Schur, Florian KM}, issn = {1047-8477}, journal = {Journal of Structural Biology}, keywords = {electron microscopy, cryo-EM, EM sample preparation, 3D printing, cell culture}, number = {3}, publisher = {Elsevier}, title = {{3D printed cell culture grid holders for improved cellular specimen preparation in cryo-electron microscopy}}, doi = {10.1016/j.jsb.2020.107633}, volume = {212}, year = {2020}, } @phdthesis{8657, abstract = {Synthesis of proteins – translation – is a fundamental process of life. Quantitative studies anchor translation into the context of bacterial physiology and reveal several mathematical relationships, called “growth laws,” which capture physiological feedbacks between protein synthesis and cell growth. Growth laws describe the dependency of the ribosome abundance as a function of growth rate, which can change depending on the growth conditions. Perturbations of translation reveal that bacteria employ a compensatory strategy in which the reduced translation capability results in increased expression of the translation machinery. Perturbations of translation are achieved in various ways; clinically interesting is the application of translation-targeting antibiotics – translation inhibitors. The antibiotic effects on bacterial physiology are often poorly understood. Bacterial responses to two or more simultaneously applied antibiotics are even more puzzling. The combined antibiotic effect determines the type of drug interaction, which ranges from synergy (the effect is stronger than expected) to antagonism (the effect is weaker) and suppression (one of the drugs loses its potency). In the first part of this work, we systematically measure the pairwise interaction network for translation inhibitors that interfere with different steps in translation. We find that the interactions are surprisingly diverse and tend to be more antagonistic. To explore the underlying mechanisms, we begin with a minimal biophysical model of combined antibiotic action. We base this model on the kinetics of antibiotic uptake and binding together with the physiological response described by the growth laws. The biophysical model explains some drug interactions, but not all; it specifically fails to predict suppression. In the second part of this work, we hypothesize that elusive suppressive drug interactions result from the interplay between ribosomes halted in different stages of translation. To elucidate this putative mechanism of drug interactions between translation inhibitors, we generate translation bottlenecks genetically using in- ducible control of translation factors that regulate well-defined translation cycle steps. These perturbations accurately mimic antibiotic action and drug interactions, supporting that the interplay of different translation bottlenecks partially causes these interactions. We extend this approach by varying two translation bottlenecks simultaneously. This approach reveals the suppression of translocation inhibition by inhibited translation. We rationalize this effect by modeling dense traffic of ribosomes that move on transcripts in a translation factor-mediated manner. This model predicts a dissolution of traffic jams caused by inhibited translocation when the density of ribosome traffic is reduced by lowered initiation. We base this model on the growth laws and quantitative relationships between different translation and growth parameters. In the final part of this work, we describe a set of tools aimed at quantification of physiological and translation parameters. We further develop a simple model that directly connects the abundance of a translation factor with the growth rate, which allows us to extract physiological parameters describing initiation. We demonstrate the development of tools for measuring translation rate. This thesis showcases how a combination of high-throughput growth rate mea- surements, genetics, and modeling can reveal mechanisms of drug interactions. Furthermore, by a gradual transition from combinations of antibiotics to precise genetic interventions, we demonstrated the equivalency between genetic and chemi- cal perturbations of translation. These findings tile the path for quantitative studies of antibiotic combinations and illustrate future approaches towards the quantitative description of translation.}, author = {Kavcic, Bor}, isbn = {978-3-99078-011-4}, issn = {2663-337X}, pages = {271}, publisher = {Institute of Science and Technology Austria}, title = {{Perturbations of protein synthesis: from antibiotics to genetics and physiology}}, doi = {10.15479/AT:ISTA:8657}, year = {2020}, } @article{7473, abstract = {How structural and functional properties of synapses relate to each other is a fundamental question in neuroscience. Electrophysiology has elucidated mechanisms of synaptic transmission, and electron microscopy (EM) has provided insight into morphological properties of synapses. Here we describe an enhanced method for functional EM (“flash and freeze”), combining optogenetic stimulation with high-pressure freezing. We demonstrate that the improved method can be applied to intact networks in acute brain slices and organotypic slice cultures from mice. As a proof of concept, we probed vesicle pool changes during synaptic transmission at the hippocampal mossy fiber-CA3 pyramidal neuron synapse. Our findings show overlap of the docked vesicle pool and the functionally defined readily releasable pool and provide evidence of fast endocytosis at this synapse. Functional EM with acute slices and slice cultures has the potential to reveal the structural and functional mechanisms of transmission in intact, genetically perturbed, and disease-affected synapses.}, author = {Borges Merjane, Carolina and Kim, Olena and Jonas, Peter M}, issn = {0896-6273}, journal = {Neuron}, pages = {992--1006}, publisher = {Elsevier}, title = {{Functional electron microscopy (“Flash and Freeze”) of identified cortical synapses in acute brain slices}}, doi = {10.1016/j.neuron.2019.12.022}, volume = {105}, year = {2020}, } @article{8250, abstract = {Antibiotics that interfere with translation, when combined, interact in diverse and difficult-to-predict ways. Here, we explain these interactions by “translation bottlenecks”: points in the translation cycle where antibiotics block ribosomal progression. To elucidate the underlying mechanisms of drug interactions between translation inhibitors, we generate translation bottlenecks genetically using inducible control of translation factors that regulate well-defined translation cycle steps. These perturbations accurately mimic antibiotic action and drug interactions, supporting that the interplay of different translation bottlenecks causes these interactions. We further show that growth laws, combined with drug uptake and binding kinetics, enable the direct prediction of a large fraction of observed interactions, yet fail to predict suppression. However, varying two translation bottlenecks simultaneously supports that dense traffic of ribosomes and competition for translation factors account for the previously unexplained suppression. These results highlight the importance of “continuous epistasis” in bacterial physiology.}, author = {Kavcic, Bor and Tkačik, Gašper and Bollenbach, Tobias}, issn = {2041-1723}, journal = {Nature Communications}, publisher = {Springer Nature}, title = {{Mechanisms of drug interactions between translation-inhibiting antibiotics}}, doi = {10.1038/s41467-020-17734-z}, volume = {11}, year = {2020}, } @unpublished{7673, abstract = {Combining drugs can improve the efficacy of treatments. However, predicting the effect of drug combinations is still challenging. The combined potency of drugs determines the drug interaction, which is classified as synergistic, additive, antagonistic, or suppressive. While probabilistic, non-mechanistic models exist, there is currently no biophysical model that can predict antibiotic interactions. Here, we present a physiologically relevant model of the combined action of antibiotics that inhibit protein synthesis by targeting the ribosome. This model captures the kinetics of antibiotic binding and transport, and uses bacterial growth laws to predict growth in the presence of antibiotic combinations. We find that this biophysical model can produce all drug interaction types except suppression. We show analytically that antibiotics which cannot bind to the ribosome simultaneously generally act as substitutes for one another, leading to additive drug interactions. Previously proposed null expectations for higher-order drug interactions follow as a limiting case of our model. We further extend the model to include the effects of direct physical or allosteric interactions between individual drugs on the ribosome. Notably, such direct interactions profoundly change the combined drug effect, depending on the kinetic parameters of the drugs used. The model makes additional predictions for the effects of resistance genes on drug interactions and for interactions between ribosome-targeting antibiotics and antibiotics with other targets. These findings enhance our understanding of the interplay between drug action and cell physiology and are a key step toward a general framework for predicting drug interactions.}, author = {Kavcic, Bor and Tkačik, Gašper and Bollenbach, Tobias}, booktitle = {bioRxiv}, publisher = {Cold Spring Harbor Laboratory}, title = {{A minimal biophysical model of combined antibiotic action}}, doi = {10.1101/2020.04.18.047886}, year = {2020}, }