TY - DATA AB - 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. AU - Kavcic, Bor ID - 8930 KW - Escherichia coli KW - antibiotic combinations KW - translation KW - growth laws KW - drug interactions KW - bacterial physiology KW - translation inhibitors TI - Analysis scripts and research data for the paper "Minimal biophysical model of combined antibiotic action" ER - TY - DATA AB - 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. AU - Nagy-Staron, Anna A ID - 8951 KW - Gene regulatory networks KW - Gene expression KW - Escherichia coli KW - Synthetic Biology TI - Sequences of gene regulatory network permutations for the article "Local genetic context shapes the function of a gene regulatory network" ER - TY - DATA AB - 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. AU - Grah, Rok ID - 7383 KW - Matlab scripts KW - analysis of microfluidics KW - mathematical model TI - Matlab scripts for the Paper: Gene Amplification as a Form of Population-Level Gene Expression regulation ER - TY - DATA AU - Katsaros, Georgios ID - 9222 TI - Transport data for: Site‐controlled uniform Ge/Si Hut wires with electrically tunable spin–orbit coupling ER - TY - DATA AB - Supplementary movies showing the following sequences for spatio-temporarily programmed shells: input geometry and actuation time landscape; comparison of morphing processes from a camera recording and a simulation; final actuated shape. AU - Guseinov, Ruslan ID - 8375 TI - Supplementary data for "Computational design of curved thin shells: from glass façades to programmable matter" ER -