@article{7569, abstract = {Genes differ in the frequency at which they are expressed and in the form of regulation used to control their activity. In particular, positive or negative regulation can lead to activation of a gene in response to an external signal. Previous works proposed that the form of regulation of a gene correlates with its frequency of usage: positive regulation when the gene is frequently expressed and negative regulation when infrequently expressed. Such network design means that, in the absence of their regulators, the genes are found in their least required activity state, hence regulatory intervention is often necessary. Due to the multitude of genes and regulators, spurious binding and unbinding events, called “crosstalk”, could occur. To determine how the form of regulation affects the global crosstalk in the network, we used a mathematical model that includes multiple regulators and multiple target genes. We found that crosstalk depends non-monotonically on the availability of regulators. Our analysis showed that excess use of regulation entailed by the formerly suggested network design caused high crosstalk levels in a large part of the parameter space. We therefore considered the opposite ‘idle’ design, where the default unregulated state of genes is their frequently required activity state. We found, that ‘idle’ design minimized the use of regulation and thus minimized crosstalk. In addition, we estimated global crosstalk of S. cerevisiae using transcription factors binding data. We demonstrated that even partial network data could suffice to estimate its global crosstalk, suggesting its applicability to additional organisms. We found that S. cerevisiae estimated crosstalk is lower than that of a random network, suggesting that natural selection reduces crosstalk. In summary, our study highlights a new type of protein production cost which is typically overlooked: that of regulatory interference caused by the presence of excess regulators in the cell. It demonstrates the importance of whole-network descriptions, which could show effects missed by single-gene models.}, author = {Grah, Rok and Friedlander, Tamar}, issn = {1553-7358}, journal = {PLOS Computational Biology}, number = {2}, publisher = {Public Library of Science}, title = {{The relation between crosstalk and gene regulation form revisited}}, doi = {10.1371/journal.pcbi.1007642}, volume = {16}, year = {2020}, } @misc{9777, author = {Grah, Rok and Friedlander, Tamar}, publisher = {Public Library of Science}, title = {{Maximizing crosstalk}}, doi = {10.1371/journal.pcbi.1007642.s002}, year = {2020}, } @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}, } @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{7383, 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 = {Grah, Rok}, keywords = {Matlab scripts, analysis of microfluidics, mathematical model}, publisher = {Institute of Science and Technology Austria}, title = {{Matlab scripts for the Paper: Gene Amplification as a Form of Population-Level Gene Expression regulation}}, doi = {10.15479/AT:ISTA:7383}, year = {2020}, }