@misc{8097,
  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},
  keywords     = {Escherichia coli, antibiotic combinations, translation, growth laws, drug interactions, bacterial physiology, translation inhibitors},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Analysis scripts and research data for the paper "Mechanisms of drug interactions between translation-inhibiting antibiotics"}},
  doi          = {10.15479/AT:ISTA:8097},
  year         = {2020},
}

@phdthesis{8653,
  abstract     = {Mutations are the raw material of evolution and come in many different flavors. Point mutations change a single letter in the DNA sequence, while copy number mutations like duplications or deletions add or remove many letters of the DNA sequence simultaneously.  Each type of mutation exhibits specific properties like its rate of formation and reversal. 
Gene expression is a fundamental phenotype that can be altered by both, point and copy number mutations. The following thesis is concerned with the dynamics of gene expression evolution and how it is affected by the properties exhibited by point and copy number mutations. Specifically, we are considering i) copy number mutations during adaptation to fluctuating environments and ii) the interaction of copy number and point mutations during adaptation to constant environments.  },
  author       = {Tomanek, Isabella},
  issn         = {2663-337X},
  keywords     = {duplication, amplification, promoter, CNV, AMGET, experimental evolution, Escherichia coli},
  pages        = {117},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{The evolution of gene expression by copy number and point mutations}},
  doi          = {10.15479/AT:ISTA:8653},
  year         = {2020},
}

@misc{8930,
  abstract     = {Phenomenological relations such as Ohm’s or Fourier’s law have a venerable history in physics but are still scarce in biology. This situation restrains predictive theory. Here, we build on bacterial “growth laws,” which capture physiological feedback between translation and cell growth, to construct a minimal biophysical model for the combined action of ribosome-targeting antibiotics. Our model predicts drug interactions like antagonism or synergy solely from responses to individual drugs. We provide analytical results for limiting cases, which agree well with numerical results. We systematically refine the model by including direct physical interactions of different antibiotics on the ribosome. In a limiting case, our model provides a mechanistic underpinning for recent predictions of higher-order interactions that were derived using entropy maximization. We further refine the model to include the effects of antibiotics that mimic starvation and the presence of resistance genes. We describe the impact of a starvation-mimicking antibiotic on drug interactions analytically and verify it experimentally. Our extended model suggests a change in the type of drug interaction that depends on the strength of resistance, which challenges established rescaling paradigms. We experimentally show that the presence of unregulated resistance genes can lead to altered drug interaction, which agrees with the prediction of the model. While minimal, the model is readily adaptable and opens the door to predicting interactions of second and higher-order in a broad range of biological systems.},
  author       = {Kavcic, Bor},
  keywords     = {Escherichia coli, antibiotic combinations, translation, growth laws, drug interactions, bacterial physiology, translation inhibitors},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Analysis scripts and research data for the paper "Minimal biophysical model of combined antibiotic action"}},
  doi          = {10.15479/AT:ISTA:8930},
  year         = {2020},
}

@misc{8951,
  abstract     = {Gene expression levels are influenced by multiple coexisting molecular mechanisms. Some of these interactions, such as those of transcription factors and promoters have been studied extensively. However, predicting phenotypes of gene regulatory networks remains a major challenge. Here, we use a well-defined synthetic gene regulatory network to study how network phenotypes depend on local genetic context, i.e. the genetic neighborhood of a transcription factor and its relative position. We show that one gene regulatory network with fixed topology can display not only quantitatively but also qualitatively different phenotypes, depending solely on the local genetic context of its components. Our results demonstrate that changes in local genetic context can place a single transcriptional unit within two separate regulons without the need for complex regulatory sequences. We propose that relative order of individual transcriptional units, with its potential for combinatorial complexity, plays an important role in shaping phenotypes of gene regulatory networks.},
  author       = {Nagy-Staron, Anna A},
  keywords     = {Gene regulatory networks, Gene expression, Escherichia coli, Synthetic Biology},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Sequences of gene regulatory network permutations for the article "Local genetic context shapes the function of a gene regulatory network"}},
  doi          = {10.15479/AT:ISTA:8951},
  year         = {2020},
}

@misc{7016,
  abstract     = {Organisms cope with change by employing transcriptional regulators. However, when faced with rare environments, the evolution of transcriptional regulators and their promoters may be too slow. We ask whether the intrinsic instability of gene duplication and amplification provides a generic alternative to canonical gene regulation. By real-time monitoring of gene copy number mutations in E. coli, we show that gene duplications and amplifications enable adaptation to fluctuating environments by rapidly generating copy number, and hence expression level, polymorphism. This ‘amplification-mediated gene expression tuning’ occurs on timescales similar to canonical gene regulation and can deal with rapid environmental changes. Mathematical modeling shows that amplifications also tune gene expression in stochastic environments where transcription factor-based schemes are hard to evolve or maintain. The fleeting nature of gene amplifications gives rise to a generic population-level mechanism that relies on genetic heterogeneity to rapidly tune expression of any gene, without leaving any genomic signature.},
  author       = {Tomanek, Isabella},
  keywords     = {Escherichia coli, gene amplification, galactose, DOG, experimental evolution, Illumina sequence data, FACS data, microfluidics data},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Data for the paper "Gene amplification as a form of population-level gene expression regulation"}},
  doi          = {10.15479/AT:ISTA:7016},
  year         = {2019},
}

@misc{5560,
  abstract     = {This repository contains the data collected for the manuscript "Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity".
The data is compressed into a single archive. Within the archive, different folders correspond to figures of the main text and the SI of the related publication.
Data is saved as plain text, with each folder containing a separate readme file describing the format. Typically, the data is from fluorescence microscopy measurements of single cells growing in a microfluidic "mother machine" device, and consists of relevant values (primarily arbitrary unit or normalized fluorescence measurements, and division times / growth rates) after raw microscopy images have been processed, segmented, and their features extracted, as described in the methods section of the related publication.},
  author       = {Bergmiller, Tobias and Andersson, Anna M and Tomasek, Kathrin and Balleza, Enrique and Kiviet, Daniel and Hauschild, Robert and Tkacik, Gasper and Guet, Calin C},
  keywords     = {single cell microscopy, mother machine microfluidic device, AcrAB-TolC pump, multi-drug efflux, Escherichia coli},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity}},
  doi          = {10.15479/AT:ISTA:53},
  year         = {2017},
}