@article{570, abstract = {Most phenotypes are determined by molecular systems composed of specifically interacting molecules. However, unlike for individual components, little is known about the distributions of mutational effects of molecular systems as a whole. We ask how the distribution of mutational effects of a transcriptional regulatory system differs from the distributions of its components, by first independently, and then simultaneously, mutating a transcription factor and the associated promoter it represses. We find that the system distribution exhibits increased phenotypic variation compared to individual component distributions - an effect arising from intermolecular epistasis between the transcription factor and its DNA-binding site. In large part, this epistasis can be qualitatively attributed to the structure of the transcriptional regulatory system and could therefore be a common feature in prokaryotes. Counter-intuitively, intermolecular epistasis can alleviate the constraints of individual components, thereby increasing phenotypic variation that selection could act on and facilitating adaptive evolution. }, author = {Lagator, Mato and Sarikas, Srdjan and Acar, Hande and Bollback, Jonathan P and Guet, Calin C}, issn = {2050084X}, journal = {eLife}, publisher = {eLife Sciences Publications}, title = {{Regulatory network structure determines patterns of intermolecular epistasis}}, doi = {10.7554/eLife.28921}, volume = {6}, year = {2017}, } @article{613, abstract = {Bacteria in groups vary individually, and interact with other bacteria and the environment to produce population-level patterns of gene expression. Investigating such behavior in detail requires measuring and controlling populations at the single-cell level alongside precisely specified interactions and environmental characteristics. Here we present an automated, programmable platform that combines image-based gene expression and growth measurements with on-line optogenetic expression control for hundreds of individual Escherichia coli cells over days, in a dynamically adjustable environment. This integrated platform broadly enables experiments that bridge individual and population behaviors. We demonstrate: (i) population structuring by independent closed-loop control of gene expression in many individual cells, (ii) cell-cell variation control during antibiotic perturbation, (iii) hybrid bio-digital circuits in single cells, and freely specifiable digital communication between individual bacteria. These examples showcase the potential for real-time integration of theoretical models with measurement and control of many individual cells to investigate and engineer microbial population behavior.}, author = {Chait, Remy P and Ruess, Jakob and Bergmiller, Tobias and Tkacik, Gasper and Guet, Calin C}, issn = {20411723}, journal = {Nature Communications}, number = {1}, publisher = {Nature Publishing Group}, title = {{Shaping bacterial population behavior through computer interfaced control of individual cells}}, doi = {10.1038/s41467-017-01683-1}, volume = {8}, year = {2017}, } @article{624, abstract = {Bacteria adapt to adverse environmental conditions by altering gene expression patterns. Recently, a novel stress adaptation mechanism has been described that allows Escherichia coli to alter gene expression at the post-transcriptional level. The key player in this regulatory pathway is the endoribonuclease MazF, the toxin component of the toxin-antitoxin module mazEF that is triggered by various stressful conditions. In general, MazF degrades the majority of transcripts by cleaving at ACA sites, which results in the retardation of bacterial growth. Furthermore, MazF can process a small subset of mRNAs and render them leaderless by removing their ribosome binding site. MazF concomitantly modifies ribosomes, making them selective for the translation of leaderless mRNAs. In this study, we employed fluorescent reporter-systems to investigate mazEF expression during stressful conditions, and to infer consequences of the mRNA processing mediated by MazF on gene expression at the single-cell level. Our results suggest that mazEF transcription is maintained at low levels in single cells encountering adverse conditions, such as antibiotic stress or amino acid starvation. Moreover, using the grcA mRNA as a model for MazF-mediated mRNA processing, we found that MazF activation promotes heterogeneity in the grcA reporter expression, resulting in a subpopulation of cells with increased levels of GrcA reporter protein.}, author = {Nikolic, Nela and Didara, Zrinka and Moll, Isabella}, issn = {21678359}, journal = {PeerJ}, number = {9}, publisher = {PeerJ}, title = {{MazF activation promotes translational heterogeneity of the grcA mRNA in Escherichia coli populations}}, doi = {10.7717/peerj.3830}, volume = {2017}, year = {2017}, } @article{655, abstract = {The bacterial flagellum is a self-assembling nanomachine. The external flagellar filament, several times longer than a bacterial cell body, is made of a few tens of thousands subunits of a single protein: flagellin. A fundamental problem concerns the molecular mechanism of how the flagellum grows outside the cell, where no discernible energy source is available. Here, we monitored the dynamic assembly of individual flagella using in situ labelling and real-time immunostaining of elongating flagellar filaments. We report that the rate of flagellum growth, initially ~1,700 amino acids per second, decreases with length and that the previously proposed chain mechanism does not contribute to the filament elongation dynamics. Inhibition of the proton motive force-dependent export apparatus revealed a major contribution of substrate injection in driving filament elongation. The combination of experimental and mathematical evidence demonstrates that a simple, injection-diffusion mechanism controls bacterial flagella growth outside the cell.}, author = {Renault, Thibaud and Abraham, Anthony and Bergmiller, Tobias and Paradis, Guillaume and Rainville, Simon and Charpentier, Emmanuelle and Guet, Calin C and Tu, Yuhai and Namba, Keiichi and Keener, James and Minamino, Tohru and Erhardt, Marc}, issn = {2050084X}, journal = {eLife}, publisher = {eLife Sciences Publications}, title = {{Bacterial flagella grow through an injection diffusion mechanism}}, doi = {10.7554/eLife.23136}, volume = {6}, year = {2017}, } @article{541, abstract = {While we have good understanding of bacterial metabolism at the population level, we know little about the metabolic behavior of individual cells: do single cells in clonal populations sometimes specialize on different metabolic pathways? Such metabolic specialization could be driven by stochastic gene expression and could provide individual cells with growth benefits of specialization. We measured the degree of phenotypic specialization in two parallel metabolic pathways, the assimilation of glucose and arabinose. We grew Escherichia coli in chemostats, and used isotope-labeled sugars in combination with nanometer-scale secondary ion mass spectrometry and mathematical modeling to quantify sugar assimilation at the single-cell level. We found large variation in metabolic activities between single cells, both in absolute assimilation and in the degree to which individual cells specialize in the assimilation of different sugars. Analysis of transcriptional reporters indicated that this variation was at least partially based on cell-to-cell variation in gene expression. Metabolic differences between cells in clonal populations could potentially reduce metabolic incompatibilities between different pathways, and increase the rate at which parallel reactions can be performed.}, author = {Nikolic, Nela and Schreiber, Frank and Dal Co, Alma and Kiviet, Daniel and Bergmiller, Tobias and Littmann, Sten and Kuypers, Marcel and Ackermann, Martin}, issn = {15537390}, journal = {PLoS Genetics}, number = {12}, publisher = {Public Library of Science}, title = {{Cell-to-cell variation and specialization in sugar metabolism in clonal bacterial populations}}, doi = {10.1371/journal.pgen.1007122}, volume = {13}, year = {2017}, } @misc{9847, abstract = {information on culture conditions, phage mutagenesis, verification and lysate preparation; Raw data}, author = {Pleska, Maros and Guet, Calin C}, publisher = {The Royal Society}, title = {{Supplementary materials and methods; Full data set from effects of mutations in phage restriction sites during escape from restriction–modification}}, doi = {10.6084/m9.figshare.5633917.v1}, year = {2017}, } @misc{9845, abstract = {Estimates of 13 C-arabinose and 2 H-glucose uptake from the fractions of heavy isotopes measured in single cells}, author = {Nikolic, Nela and Schreiber, Frank and Dal Co, Alma and Kiviet, Daniel and Bergmiller, Tobias and Littmann, Sten and Kuypers, Marcel and Ackermann, Martin}, publisher = {Public Library of Science}, title = {{Mathematical model}}, doi = {10.1371/journal.pgen.1007122.s017}, year = {2017}, } @misc{9849, abstract = {This text provides additional information about the model, a derivation of the analytic results in Eq (4), and details about simulations of an additional parameter set.}, author = {Lukacisinova, Marta and Novak, Sebastian and Paixao, Tiago}, publisher = {Public Library of Science}, title = {{Modelling and simulation details}}, doi = {10.1371/journal.pcbi.1005609.s001}, year = {2017}, } @misc{9850, abstract = {In this text, we discuss how a cost of resistance and the possibility of lethal mutations impact our model.}, author = {Lukacisinova, Marta and Novak, Sebastian and Paixao, Tiago}, publisher = {Public Library of Science}, title = {{Extensions of the model}}, doi = {10.1371/journal.pcbi.1005609.s002}, year = {2017}, } @misc{9846, author = {Nikolic, Nela and Schreiber, Frank and Dal Co, Alma and Kiviet, Daniel and Bergmiller, Tobias and Littmann, Sten and Kuypers, Marcel and Ackermann, Martin}, publisher = {Public Library of Science}, title = {{Supplementary methods}}, doi = {10.1371/journal.pgen.1007122.s016}, year = {2017}, }