@article{457, abstract = {Temperate bacteriophages integrate in bacterial genomes as prophages and represent an important source of genetic variation for bacterial evolution, frequently transmitting fitness-augmenting genes such as toxins responsible for virulence of major pathogens. However, only a fraction of bacteriophage infections are lysogenic and lead to prophage acquisition, whereas the majority are lytic and kill the infected bacteria. Unless able to discriminate lytic from lysogenic infections, mechanisms of immunity to bacteriophages are expected to act as a double-edged sword and increase the odds of survival at the cost of depriving bacteria of potentially beneficial prophages. We show that although restriction-modification systems as mechanisms of innate immunity prevent both lytic and lysogenic infections indiscriminately in individual bacteria, they increase the number of prophage-acquiring individuals at the population level. We find that this counterintuitive result is a consequence of phage-host population dynamics, in which restriction-modification systems delay infection onset until bacteria reach densities at which the probability of lysogeny increases. These results underscore the importance of population-level dynamics as a key factor modulating costs and benefits of immunity to temperate bacteriophages}, author = {Pleska, Maros and Lang, Moritz and Refardt, Dominik and Levin, Bruce and Guet, Calin C}, journal = {Nature Ecology and Evolution}, number = {2}, pages = {359 -- 366}, publisher = {Springer Nature}, title = {{Phage-host population dynamics promotes prophage acquisition in bacteria with innate immunity}}, doi = {10.1038/s41559-017-0424-z}, volume = {2}, year = {2018}, } @article{5984, abstract = {G-protein-coupled receptors (GPCRs) form the largest receptor family, relay environmental stimuli to changes in cell behavior and represent prime drug targets. Many GPCRs are classified as orphan receptors because of the limited knowledge on their ligands and coupling to cellular signaling machineries. Here, we engineer a library of 63 chimeric receptors that contain the signaling domains of human orphan and understudied GPCRs functionally linked to the light-sensing domain of rhodopsin. Upon stimulation with visible light, we identify activation of canonical cell signaling pathways, including cAMP-, Ca2+-, MAPK/ERK-, and Rho-dependent pathways, downstream of the engineered receptors. For the human pseudogene GPR33, we resurrect a signaling function that supports its hypothesized role as a pathogen entry site. These results demonstrate that substituting unknown chemical activators with a light switch can reveal information about protein function and provide an optically controlled protein library for exploring the physiology and therapeutic potential of understudied GPCRs.}, author = {Morri, Maurizio and Sanchez-Romero, Inmaculada and Tichy, Alexandra-Madelaine and Kainrath, Stephanie and Gerrard, Elliot J. and Hirschfeld, Priscila and Schwarz, Jan and Janovjak, Harald L}, issn = {2041-1723}, journal = {Nature Communications}, number = {1}, publisher = {Springer Nature}, title = {{Optical functionalization of human class A orphan G-protein-coupled receptors}}, doi = {10.1038/s41467-018-04342-1}, volume = {9}, year = {2018}, } @article{19, abstract = {Bacteria regulate genes to survive antibiotic stress, but regulation can be far from perfect. When regulation is not optimal, mutations that change gene expression can contribute to antibiotic resistance. It is not systematically understood to what extent natural gene regulation is or is not optimal for distinct antibiotics, and how changes in expression of specific genes quantitatively affect antibiotic resistance. Here we discover a simple quantitative relation between fitness, gene expression, and antibiotic potency, which rationalizes our observation that a multitude of genes and even innate antibiotic defense mechanisms have expression that is critically nonoptimal under antibiotic treatment. First, we developed a pooled-strain drug-diffusion assay and screened Escherichia coli overexpression and knockout libraries, finding that resistance to a range of 31 antibiotics could result from changing expression of a large and functionally diverse set of genes, in a primarily but not exclusively drug-specific manner. Second, by synthetically controlling the expression of single-drug and multidrug resistance genes, we observed that their fitness-expression functions changed dramatically under antibiotic treatment in accordance with a log-sensitivity relation. Thus, because many genes are nonoptimally expressed under antibiotic treatment, many regulatory mutations can contribute to resistance by altering expression and by activating latent defenses.}, author = {Palmer, Adam and Chait, Remy P and Kishony, Roy}, issn = {0737-4038}, journal = {Molecular Biology and Evolution}, number = {11}, pages = {2669 -- 2684}, publisher = {Oxford University Press}, title = {{Nonoptimal gene expression creates latent potential for antibiotic resistance}}, doi = {10.1093/molbev/msy163}, volume = {35}, year = {2018}, } @article{438, abstract = {The MazF toxin sequence-specifically cleaves single-stranded RNA upon various stressful conditions, and it is activated as a part of the mazEF toxin–antitoxin module in Escherichia coli. Although autoregulation of mazEF expression through the MazE antitoxin-dependent transcriptional repression has been biochemically characterized, less is known about post-transcriptional autoregulation, as well as how both of these autoregulatory features affect growth of single cells during conditions that promote MazF production. Here, we demonstrate post-transcriptional autoregulation of mazF expression dynamics by MazF cleaving its own transcript. Single-cell analyses of bacterial populations during ectopic MazF production indicated that two-level autoregulation of mazEF expression influences cell-to-cell growth rate heterogeneity. The increase in growth rate heterogeneity is governed by the MazE antitoxin, and tuned by the MazF-dependent mazF mRNA cleavage. Also, both autoregulatory features grant rapid exit from the stress caused by mazF overexpression. Time-lapse microscopy revealed that MazF-mediated cleavage of mazF mRNA leads to increased temporal variability in length of individual cells during ectopic mazF overexpression, as explained by a stochastic model indicating that mazEF mRNA cleavage underlies temporal fluctuations in MazF levels during stress.}, author = {Nikolic, Nela and Bergmiller, Tobias and Vandervelde, Alexandra and Albanese, Tanino and Gelens, Lendert and Moll, Isabella}, journal = {Nucleic Acids Research}, number = {6}, pages = {2918--2931}, publisher = {Oxford University Press}, title = {{Autoregulation of mazEF expression underlies growth heterogeneity in bacterial populations}}, doi = {10.1093/nar/gky079}, volume = {46}, year = {2018}, } @misc{5569, abstract = {Nela Nikolic, Tobias Bergmiller, Alexandra Vandervelde, Tanino G. Albanese, Lendert Gelens, and Isabella Moll (2018) “Autoregulation of mazEF expression underlies growth heterogeneity in bacterial populations” Nucleic Acids Research, doi: 10.15479/AT:ISTA:74; microscopy experiments by Tobias Bergmiller; image and data analysis by Nela Nikolic.}, author = {Bergmiller, Tobias and Nikolic, Nela}, keywords = {microscopy, microfluidics}, publisher = {Institute of Science and Technology Austria}, title = {{Time-lapse microscopy data}}, doi = {10.15479/AT:ISTA:74}, year = {2018}, } @article{161, abstract = {Which properties of metabolic networks can be derived solely from stoichiometry? Predictive results have been obtained by flux balance analysis (FBA), by postulating that cells set metabolic fluxes to maximize growth rate. Here we consider a generalization of FBA to single-cell level using maximum entropy modeling, which we extend and test experimentally. Specifically, we define for Escherichia coli metabolism a flux distribution that yields the experimental growth rate: the model, containing FBA as a limit, provides a better match to measured fluxes and it makes a wide range of predictions: on flux variability, regulation, and correlations; on the relative importance of stoichiometry vs. optimization; on scaling relations for growth rate distributions. We validate the latter here with single-cell data at different sub-inhibitory antibiotic concentrations. The model quantifies growth optimization as emerging from the interplay of competitive dynamics in the population and regulation of metabolism at the level of single cells.}, author = {De Martino, Daniele and Mc, Andersson Anna and Bergmiller, Tobias and Guet, Calin C and Tkacik, Gasper}, journal = {Nature Communications}, number = {1}, publisher = {Springer Nature}, title = {{Statistical mechanics for metabolic networks during steady state growth}}, doi = {10.1038/s41467-018-05417-9}, volume = {9}, year = {2018}, } @phdthesis{26, abstract = {Expression of genes is a fundamental molecular phenotype that is subject to evolution by different types of mutations. Both the rate and the effect of mutations may depend on the DNA sequence context of a particular gene or a particular promoter sequence. In this thesis I investigate the nature of this dependence using simple genetic systems in Escherichia coli. With these systems I explore the evolution of constitutive gene expression from random starting sequences at different loci on the chromosome and at different locations in sequence space. First, I dissect chromosomal neighborhood effects that underlie locus-dependent differences in the potential of a gene under selection to become more highly expressed. Next, I find that the effects of point mutations in promoter sequences are dependent on sequence context, and that an existing energy matrix model performs poorly in predicting relative expression of unrelated sequences. Finally, I show that a substantial fraction of random sequences contain functional promoters and I present an extended thermodynamic model that predicts promoter strength in full sequence space. Taken together, these results provide new insights and guides on how to integrate information on sequence context to improve our qualitative and quantitative understanding of bacterial gene expression, with implications for rapid evolution of drug resistance, de novo evolution of genes, and horizontal gene transfer.}, author = {Steinrück, Magdalena}, issn = {2663-337X}, pages = {109}, publisher = {Institute of Science and Technology Austria}, title = {{The influence of sequence context on the evolution of bacterial gene expression}}, doi = {10.15479/AT:ISTA:th1059}, year = {2018}, } @article{67, abstract = {Gene regulatory networks evolve through rewiring of individual components—that is, through changes in regulatory connections. However, the mechanistic basis of regulatory rewiring is poorly understood. Using a canonical gene regulatory system, we quantify the properties of transcription factors that determine the evolutionary potential for rewiring of regulatory connections: robustness, tunability and evolvability. In vivo repression measurements of two repressors at mutated operator sites reveal their contrasting evolutionary potential: while robustness and evolvability were positively correlated, both were in trade-off with tunability. Epistatic interactions between adjacent operators alleviated this trade-off. A thermodynamic model explains how the differences in robustness, tunability and evolvability arise from biophysical characteristics of repressor–DNA binding. The model also uncovers that the energy matrix, which describes how mutations affect repressor–DNA binding, encodes crucial information about the evolutionary potential of a repressor. The biophysical determinants of evolutionary potential for regulatory rewiring constitute a mechanistic framework for understanding network evolution.}, author = {Igler, Claudia and Lagator, Mato and Tkacik, Gasper and Bollback, Jonathan P and Guet, Calin C}, journal = {Nature Ecology and Evolution}, number = {10}, pages = {1633 -- 1643}, publisher = {Nature Publishing Group}, title = {{Evolutionary potential of transcription factors for gene regulatory rewiring}}, doi = {10.1038/s41559-018-0651-y}, volume = {2}, year = {2018}, } @misc{5585, abstract = {Mean repression values and standard error of the mean are given for all operator mutant libraries.}, author = {Igler, Claudia and Lagator, Mato and Tkacik, Gasper and Bollback, Jonathan P and Guet, Calin C}, publisher = {Institute of Science and Technology Austria}, title = {{Data for the paper Evolutionary potential of transcription factors for gene regulatory rewiring}}, doi = {10.15479/AT:ISTA:108}, year = {2018}, } @article{538, abstract = {Optogenetik und Photopharmakologie ermöglichen präzise räumliche und zeitliche Kontrolle von Proteinwechselwirkung und -funktion in Zellen und Tieren. Optogenetische Methoden, die auf grünes Licht ansprechen und zum Trennen von Proteinkomplexen geeignet sind, sind nichtweitläufig verfügbar, würden jedoch mehrfarbige Experimente zur Beantwortung von biologischen Fragestellungen ermöglichen. Hier demonstrieren wir die Verwendung von Cobalamin(Vitamin B12)-bindenden Domänen von bakteriellen CarH-Transkriptionsfaktoren zur Grünlicht-induzierten Dissoziation von Rezeptoren. Fusioniert mit dem Fibroblasten-W achstumsfaktor-Rezeptor 1 führten diese im Dunkeln in kultivierten Zellen zu Signalaktivität durch Oligomerisierung, welche durch Beleuchten umgehend aufgehoben wurde. In Zebrafischembryonen, die einen derartigen Rezeptor exprimieren, ermöglichte grünes Licht die Kontrolle über abnormale Signalaktivität während der Embryonalentwicklung. }, author = {Kainrath, Stephanie and Stadler, Manuela and Gschaider-Reichhart, Eva and Distel, Martin and Janovjak, Harald L}, journal = {Angewandte Chemie}, number = {16}, pages = {4679 -- 4682}, publisher = {Wiley}, title = {{Grünlicht-induzierte Rezeptorinaktivierung durch Cobalamin-bindende Domänen}}, doi = {10.1002/ange.201611998}, volume = {129}, year = {2017}, }