@article{12261, abstract = {Dose–response relationships are a general concept for quantitatively describing biological systems across multiple scales, from the molecular to the whole-cell level. A clinically relevant example is the bacterial growth response to antibiotics, which is routinely characterized by dose–response curves. The shape of the dose–response curve varies drastically between antibiotics and plays a key role in treatment, drug interactions, and resistance evolution. However, the mechanisms shaping the dose–response curve remain largely unclear. Here, we show in Escherichia coli that the distinctively shallow dose–response curve of the antibiotic trimethoprim is caused by a negative growth-mediated feedback loop: Trimethoprim slows growth, which in turn weakens the effect of this antibiotic. At the molecular level, this feedback is caused by the upregulation of the drug target dihydrofolate reductase (FolA/DHFR). We show that this upregulation is not a specific response to trimethoprim but follows a universal trend line that depends primarily on the growth rate, irrespective of its cause. Rewiring the feedback loop alters the dose–response curve in a predictable manner, which we corroborate using a mathematical model of cellular resource allocation and growth. Our results indicate that growth-mediated feedback loops may shape drug responses more generally and could be exploited to design evolutionary traps that enable selection against drug resistance.}, author = {Angermayr, Andreas and Pang, Tin Yau and Chevereau, Guillaume and Mitosch, Karin and Lercher, Martin J and Bollenbach, Mark Tobias}, issn = {1744-4292}, journal = {Molecular Systems Biology}, keywords = {Applied Mathematics, Computational Theory and Mathematics, General Agricultural and Biological Sciences, General Immunology and Microbiology, General Biochemistry, Genetics and Molecular Biology, Information Systems}, number = {9}, publisher = {Embo Press}, title = {{Growth‐mediated negative feedback shapes quantitative antibiotic response}}, doi = {10.15252/msb.202110490}, volume = {18}, year = {2022}, } @article{7026, abstract = {Effective design of combination therapies requires understanding the changes in cell physiology that result from drug interactions. Here, we show that the genome-wide transcriptional response to combinations of two drugs, measured at a rigorously controlled growth rate, can predict higher-order antagonism with a third drug in Saccharomyces cerevisiae. Using isogrowth profiling, over 90% of the variation in cellular response can be decomposed into three principal components (PCs) that have clear biological interpretations. We demonstrate that the third PC captures emergent transcriptional programs that are dependent on both drugs and can predict antagonism with a third drug targeting the emergent pathway. We further show that emergent gene expression patterns are most pronounced at a drug ratio where the drug interaction is strongest, providing a guideline for future measurements. Our results provide a readily applicable recipe for uncovering emergent responses in other systems and for higher-order drug combinations. A record of this paper’s transparent peer review process is included in the Supplemental Information.}, author = {Lukacisin, Martin and Bollenbach, Tobias}, issn = {2405-4712}, journal = {Cell Systems}, number = {5}, pages = {423--433.e1--e3}, publisher = {Cell Press}, title = {{Emergent gene expression responses to drug combinations predict higher-order drug interactions}}, doi = {10.1016/j.cels.2019.10.004}, volume = {9}, year = {2019}, } @phdthesis{6392, abstract = {The regulation of gene expression is one of the most fundamental processes in living systems. In recent years, thanks to advances in sequencing technology and automation, it has become possible to study gene expression quantitatively, genome-wide and in high-throughput. This leads to the possibility of exploring changes in gene expression in the context of many external perturbations and their combinations, and thus of characterising the basic principles governing gene regulation. In this thesis, I present quantitative experimental approaches to studying transcriptional and protein level changes in response to combinatorial drug treatment, as well as a theoretical data-driven approach to analysing thermodynamic principles guiding transcription of protein coding genes. In the first part of this work, I present a novel methodological framework for quantifying gene expression changes in drug combinations, termed isogrowth profiling. External perturbations through small molecule drugs influence the growth rate of the cell, leading to wide-ranging changes in cellular physiology and gene expression. This confounds the gene expression changes specifically elicited by the particular drug. Combinatorial perturbations, owing to the increased stress they exert, influence the growth rate even more strongly and hence suffer the convolution problem to a greater extent when measuring gene expression changes. Isogrowth profiling is a way to experimentally abstract non-specific, growth rate related changes, by performing the measurement using varying ratios of two drugs at such concentrations that the overall inhibition rate is constant. Using a robotic setup for automated high-throughput re-dilution culture of Saccharomyces cerevisiae, the budding yeast, I investigate all pairwise interactions of four small molecule drugs through sequencing RNA along a growth isobole. Through principal component analysis, I demonstrate here that isogrowth profiling can uncover drug-specific as well as drug-interaction-specific gene expression changes. I show that drug-interaction-specific gene expression changes can be used for prediction of higher-order drug interactions. I propose a simplified generalised framework of isogrowth profiling, with few measurements needed for each drug pair, enabling the broad application of isogrowth profiling to high-throughput screening of inhibitors of cellular growth and beyond. Such high-throughput screenings of gene expression changes specific to pairwise drug interactions will be instrumental for predicting the higher-order interactions of the drugs. In the second part of this work, I extend isogrowth profiling to single-cell measurements of gene expression, characterising population heterogeneity in the budding yeast in response to combinatorial drug perturbation while controlling for non-specific growth rate effects. Through flow cytometry of strains with protein products fused to green fluorescent protein, I discover multiple proteins with bi-modally distributed expression levels in the population in response to drug treatment. I characterize more closely the effect of an ionic stressor, lithium chloride, and find that it inhibits the splicing of mRNA, most strongly affecting ribosomal protein transcripts and leading to a bi-stable behaviour of a small ribosomal subunit protein Rps22B. Time-lapse microscopy of a microfluidic culture system revealed that the induced Rps22B heterogeneity leads to preferential survival of Rps22B-low cells after long starvation, but to preferential proliferation of Rps22B-high cells after short starvation. Overall, this suggests that yeast cells might use splicing of ribosomal genes for bet-hedging in fluctuating environments. I give specific examples of how further exploration of cellular heterogeneity in yeast in response to external perturbation has the potential to reveal yet-undiscovered gene regulation circuitry. In the last part of this thesis, a re-analysis of a published sequencing dataset of nascent elongating transcripts is used to characterise the thermodynamic constraints for RNA polymerase II (RNAP) elongation. Population-level data on RNAP position throughout the transcribed genome with single nucleotide resolution are used to infer the sequence specific thermodynamic determinants of RNAP pausing and backtracking. This analysis reveals that the basepairing strength of the eight nucleotide-long RNA:DNA duplex relative to the basepairing strength of the same sequence when in DNA:DNA duplex, and the change in this quantity during RNA polymerase movement, is the key determinant of RNAP pausing. This is true for RNAP pausing while elongating, but also of RNAP pausing while backtracking and of the backtracking length. The quantitative dependence of RNAP pausing on basepairing energetics is used to infer the increase in pausing due to transcriptional mismatches, leading to a hypothesis that pervasive RNA polymerase II pausing is due to basepairing energetics, as an evolutionary cost for increased RNA polymerase II fidelity. This work advances our understanding of the general principles governing gene expression, with the goal of making computational predictions of single-cell gene expression responses to combinatorial perturbations based on the individual perturbations possible. This ability would substantially facilitate the design of drug combination treatments and, in the long term, lead to our increased ability to more generally design targeted manipulations to any biological system. }, author = {Lukacisin, Martin}, isbn = {978-3-99078-001-5}, issn = {2663-337X}, pages = {103}, publisher = {IST Austria}, title = {{Quantitative investigation of gene expression principles through combinatorial drug perturbation and theory}}, doi = {10.15479/AT:ISTA:6392}, year = {2019}, } @phdthesis{6263, abstract = {Antibiotic resistance can emerge spontaneously through genomic mutation and render treatment ineffective. To counteract this process, in addition to the discovery and description of resistance mechanisms,a deeper understanding of resistanceevolvabilityand its determinantsis needed. To address this challenge, this thesisuncoversnew genetic determinants of resistance evolvability using a customized robotic setup, exploressystematic ways in which resistance evolution is perturbed due to dose-responsecharacteristics of drugs and mutation rate differences,and mathematically investigates the evolutionary fate of one specific type of evolvability modifier -a stress-induced mutagenesis allele.We find severalgenes which strongly inhibit or potentiate resistance evolution. In order to identify them, we first developedan automated high-throughput feedback-controlled protocol whichkeeps the population size and selection pressure approximately constant for hundreds of cultures by dynamically re-diluting the cultures and adjusting the antibiotic concentration. We implementedthis protocol on a customized liquid handling robot and propagated 100 different gene deletion strains of Escherichia coliin triplicate for over 100 generations in tetracycline and in chloramphenicol, and comparedtheir adaptation rates.We find a diminishing returns pattern, where initially sensitive strains adapted more compared to less sensitive ones. Our data uncover that deletions of certain genes which do not affect mutation rate,including efflux pump components, a chaperone and severalstructural and regulatory genes can strongly and reproducibly alterresistance evolution. Sequencing analysis of evolved populations indicates that epistasis with resistance mutations is the most likelyexplanation. This work could inspire treatment strategies in which targeted inhibitors of evolvability mechanisms will be given alongside antibiotics to slow down resistance evolution and extend theefficacy of antibiotics.We implemented astochasticpopulation genetics model, toverifyways in which general properties, namely, dose-response characteristics of drugs and mutation rates, influence evolutionary dynamics. In particular, under the exposure to antibiotics with shallow dose-response curves,bacteria have narrower distributions of fitness effects of new mutations. We show that in silicothis also leads to slower resistance evolution. We see and confirm with experiments that increased mutation rates, apart from speeding up evolution, also leadto high reproducibility of phenotypic adaptation in a context of continually strong selection pressure.Knowledge of these patterns can aid in predicting the dynamics of antibiotic resistance evolutionand adapting treatment schemes accordingly.Focusing on a previously described type of evolvability modifier –a stress-induced mutagenesis allele –we find conditions under which it can persist in a population under periodic selectionakin to clinical treatment. We set up a deterministic infinite populationcontinuous time model tracking the frequencies of a mutator and resistance allele and evaluate various treatment schemes in how well they maintain a stress-induced mutator allele. In particular,a high diversity of stresses is crucial for the persistence of the mutator allele. This leads to a general trade-off where exactly those diversifying treatment schemes which are likely to decrease levels of resistance could lead to stronger selection of highly evolvable genotypes.In the long run, this work will lead to a deeper understanding of the genetic and cellular mechanisms involved in antibiotic resistance evolution and could inspire new strategies for slowing down its rate. }, author = {Lukacisinova, Marta}, issn = {2663-337X}, pages = {91}, publisher = {Institute of Science and Technology Austria}, title = {{Genetic determinants of antibiotic resistance evolution}}, doi = {10.15479/AT:ISTA:th1072}, year = {2018}, } @article{520, abstract = {Cyanobacteria are mostly engineered to be sustainable cell-factories by genetic manipulations alone. Here, by modulating the concentration of allosteric effectors, we focus on increasing product formation without further burdening the cells with increased expression of enzymes. Resorting to a novel 96-well microplate cultivation system for cyanobacteria, and using lactate-producing strains of Synechocystis PCC6803 expressing different l-lactate dehydrogenases (LDH), we titrated the effect of 2,5-anhydro-mannitol supplementation. The latter acts in cells as a nonmetabolizable analogue of fructose 1,6-bisphosphate, a known allosteric regulator of one of the tested LDHs. In this strain (SAA023), we achieved over 2-fold increase of lactate productivity. Furthermore, we observed that as carbon is increasingly deviated during growth toward product formation, there is an increased fixation rate in the population of spontaneous mutants harboring an impaired production pathway. This is a challenge in the development of green cell factories, which may be countered by the incorporation in biotechnological processes of strategies such as the one pioneered here.}, author = {Du, Wei and Angermayr, Andreas and Jongbloets, Joeri and Molenaar, Douwe and Bachmann, Herwig and Hellingwerf, Klaas and Branco Dos Santos, Filipe}, issn = {21615063}, journal = {ACS Synthetic Biology}, number = {3}, pages = {395 -- 401}, publisher = {American Chemical Society}, title = {{Nonhierarchical flux regulation exposes the fitness burden associated with lactate production in Synechocystis sp. PCC6803}}, doi = {10.1021/acssynbio.6b00235}, volume = {6}, 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{9851, abstract = {Based on the intuitive derivation of the dynamics of SIM allele frequency pM in the main text, we present a heuristic prediction for the long-term SIM allele frequencies with χ > 1 stresses and compare it to numerical simulations.}, author = {Lukacisinova, Marta and Novak, Sebastian and Paixao, Tiago}, publisher = {Public Library of Science}, title = {{Heuristic prediction for multiple stresses}}, doi = {10.1371/journal.pcbi.1005609.s003}, year = {2017}, } @misc{9852, abstract = {We show how different combination strategies affect the fraction of individuals that are multi-resistant.}, author = {Lukacisinova, Marta and Novak, Sebastian and Paixao, Tiago}, publisher = {Public Library of Science}, title = {{Resistance frequencies for different combination strategies}}, doi = {10.1371/journal.pcbi.1005609.s004}, year = {2017}, } @phdthesis{818, abstract = {Antibiotics have diverse effects on bacteria, including massive changes in bacterial gene expression. Whereas the gene expression changes under many antibiotics have been measured, the temporal organization of these responses and their dependence on the bacterial growth rate are unclear. As described in Chapter 1, we quantified the temporal gene expression changes in the bacterium Escherichia coli in response to the sudden exposure to antibiotics using a fluorescent reporter library and a robotic system. Our data show temporally structured gene expression responses, with response times for individual genes ranging from tens of minutes to several hours. We observed that many stress response genes were activated in response to antibiotics. As certain stress responses cross-protect bacteria from other stressors, we then asked whether cellular responses to antibiotics have a similar protective role in Chapter 2. Indeed, we found that the trimethoprim-induced acid stress response protects bacteria from subsequent acid stress. We combined microfluidics with time-lapse imaging to monitor survival, intracellular pH, and acid stress response in single cells. This approach revealed that the variable expression of the acid resistance operon gadBC strongly correlates with single-cell survival time. Cells with higher gadBC expression following trimethoprim maintain higher intracellular pH and survive the acid stress longer. Overall, we provide a way to identify single-cell cross-protection between antibiotics and environmental stressors from temporal gene expression data, and show how antibiotics can increase bacterial fitness in changing environments. While gene expression changes to antibiotics show a clear temporal structure at the population-level, it is unclear whether this clear temporal order is followed by every single cell. Using dual-reporter strains described in Chapter 3, we measured gene expression dynamics of promoter pairs in the same cells using microfluidics and microscopy. Chapter 4 shows that the oxidative stress response and the DNA stress response showed little timing variability and a clear temporal order under the antibiotic nitrofurantoin. In contrast, the acid stress response under trimethoprim ran independently from all other activated response programs including the DNA stress response, which showed particularly high timing variability in this stress condition. In summary, this approach provides insight into the temporal organization of gene expression programs at the single-cell level and suggests dependencies between response programs and the underlying variability-introducing mechanisms. Altogether, this work advances our understanding of the diverse effects that antibiotics have on bacteria. These results were obtained by taking into account gene expression dynamics, which allowed us to identify general principles, molecular mechanisms, and dependencies between genes. Our findings may have implications for infectious disease treatments, and microbial communities in the human body and in nature. }, author = {Mitosch, Karin}, issn = {2663-337X}, pages = {113}, publisher = {Institute of Science and Technology Austria}, title = {{Timing, variability and cross-protection in bacteria – insights from dynamic gene expression responses to antibiotics}}, doi = {10.15479/AT:ISTA:th_862}, year = {2017}, } @article{666, abstract = {Antibiotics elicit drastic changes in microbial gene expression, including the induction of stress response genes. While certain stress responses are known to “cross-protect” bacteria from other stressors, it is unclear whether cellular responses to antibiotics have a similar protective role. By measuring the genome-wide transcriptional response dynamics of Escherichia coli to four antibiotics, we found that trimethoprim induces a rapid acid stress response that protects bacteria from subsequent exposure to acid. Combining microfluidics with time-lapse imaging to monitor survival and acid stress response in single cells revealed that the noisy expression of the acid resistance operon gadBC correlates with single-cell survival. Cells with higher gadBC expression following trimethoprim maintain higher intracellular pH and survive the acid stress longer. The seemingly random single-cell survival under acid stress can therefore be predicted from gadBC expression and rationalized in terms of GadB/C molecular function. Overall, we provide a roadmap for identifying the molecular mechanisms of single-cell cross-protection between antibiotics and other stressors.}, author = {Mitosch, Karin and Rieckh, Georg and Bollenbach, Tobias}, issn = {24054712}, journal = {Cell Systems}, number = {4}, pages = {393 -- 403}, publisher = {Cell Press}, title = {{Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment}}, doi = {10.1016/j.cels.2017.03.001}, volume = {4}, year = {2017}, } @article{822, abstract = {Polymicrobial infections constitute small ecosystems that accommodate several bacterial species. Commonly, these bacteria are investigated in isolation. However, it is unknown to what extent the isolates interact and whether their interactions alter bacterial growth and ecosystem resilience in the presence and absence of antibiotics. We quantified the complete ecological interaction network for 72 bacterial isolates collected from 23 individuals diagnosed with polymicrobial urinary tract infections and found that most interactions cluster based on evolutionary relatedness. Statistical network analysis revealed that competitive and cooperative reciprocal interactions are enriched in the global network, while cooperative interactions are depleted in the individual host community networks. A population dynamics model parameterized by our measurements suggests that interactions restrict community stability, explaining the observed species diversity of these communities. We further show that the clinical isolates frequently protect each other from clinically relevant antibiotics. Together, these results highlight that ecological interactions are crucial for the growth and survival of bacteria in polymicrobial infection communities and affect their assembly and resilience. }, author = {De Vos, Marjon and Zagórski, Marcin P and Mcnally, Alan and Bollenbach, Mark Tobias}, issn = {00278424}, journal = {PNAS}, number = {40}, pages = {10666 -- 10671}, publisher = {National Academy of Sciences}, title = {{Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections}}, doi = {10.1073/pnas.1713372114}, volume = {114}, year = {2017}, } @article{1029, abstract = {RNA Polymerase II pauses and backtracks during transcription, with many consequences for gene expression and cellular physiology. Here, we show that the energy required to melt double-stranded nucleic acids in the transcription bubble predicts pausing in Saccharomyces cerevisiae far more accurately than nucleosome roadblocks do. In addition, the same energy difference also determines when the RNA polymerase backtracks instead of continuing to move forward. This data-driven model corroborates—in a genome wide and quantitative manner—previous evidence that sequence-dependent thermodynamic features of nucleic acids influence both transcriptional pausing and backtracking.}, author = {Lukacisin, Martin and Landon, Matthieu and Jajoo, Rishi}, issn = {19326203}, journal = {PLoS One}, number = {3}, publisher = {Public Library of Science}, title = {{Sequence-specific thermodynamic properties of nucleic acids influence both transcriptional pausing and backtracking in yeast}}, doi = {10.1371/journal.pone.0174066}, volume = {12}, year = {2017}, } @article{696, abstract = {Mutator strains are expected to evolve when the availability and effect of beneficial mutations are high enough to counteract the disadvantage from deleterious mutations that will inevitably accumulate. As the population becomes more adapted to its environment, both availability and effect of beneficial mutations necessarily decrease and mutation rates are predicted to decrease. It has been shown that certain molecular mechanisms can lead to increased mutation rates when the organism finds itself in a stressful environment. While this may be a correlated response to other functions, it could also be an adaptive mechanism, raising mutation rates only when it is most advantageous. Here, we use a mathematical model to investigate the plausibility of the adaptive hypothesis. We show that such a mechanism can be mantained if the population is subjected to diverse stresses. By simulating various antibiotic treatment schemes, we find that combination treatments can reduce the effectiveness of second-order selection on stress-induced mutagenesis. We discuss the implications of our results to strategies of antibiotic therapy.}, author = {Lukacisinova, Marta and Novak, Sebastian and Paixao, Tiago}, issn = {1553734X}, journal = {PLoS Computational Biology}, number = {7}, publisher = {Public Library of Science}, title = {{Stress induced mutagenesis: Stress diversity facilitates the persistence of mutator genes}}, doi = {10.1371/journal.pcbi.1005609}, volume = {13}, year = {2017}, } @article{1027, abstract = {The rising prevalence of antibiotic resistant bacteria is an increasingly serious public health challenge. To address this problem, recent work ranging from clinical studies to theoretical modeling has provided valuable insights into the mechanisms of resistance, its emergence and spread, and ways to counteract it. A deeper understanding of the underlying dynamics of resistance evolution will require a combination of experimental and theoretical expertise from different disciplines and new technology for studying evolution in the laboratory. Here, we review recent advances in the quantitative understanding of the mechanisms and evolution of antibiotic resistance. We focus on key theoretical concepts and new technology that enables well-controlled experiments. We further highlight key challenges that can be met in the near future to ultimately develop effective strategies for combating resistance.}, author = {Lukacisinova, Marta and Bollenbach, Mark Tobias}, journal = {Current Opinion in Biotechnology}, pages = {90 -- 97}, publisher = {Elsevier}, title = {{Toward a quantitative understanding of antibiotic resistance evolution}}, doi = {10.1016/j.copbio.2017.02.013}, volume = {46}, year = {2017}, } @article{1154, abstract = {Cellular locomotion is a central hallmark of eukaryotic life. It is governed by cell-extrinsic molecular factors, which can either emerge in the soluble phase or as immobilized, often adhesive ligands. To encode for direction, every cue must be present as a spatial or temporal gradient. Here, we developed a microfluidic chamber that allows measurement of cell migration in combined response to surface immobilized and soluble molecular gradients. As a proof of principle we study the response of dendritic cells to their major guidance cues, chemokines. The majority of data on chemokine gradient sensing is based on in vitro studies employing soluble gradients. Despite evidence suggesting that in vivo chemokines are often immobilized to sugar residues, limited information is available how cells respond to immobilized chemokines. We tracked migration of dendritic cells towards immobilized gradients of the chemokine CCL21 and varying superimposed soluble gradients of CCL19. Differential migratory patterns illustrate the potential of our setup to quantitatively study the competitive response to both types of gradients. Beyond chemokines our approach is broadly applicable to alternative systems of chemo- and haptotaxis such as cells migrating along gradients of adhesion receptor ligands vs. any soluble cue. }, author = {Schwarz, Jan and Bierbaum, Veronika and Merrin, Jack and Frank, Tino and Hauschild, Robert and Bollenbach, Mark Tobias and Tay, Savaş and Sixt, Michael K and Mehling, Matthias}, journal = {Scientific Reports}, publisher = {Nature Publishing Group}, title = {{A microfluidic device for measuring cell migration towards substrate bound and soluble chemokine gradients}}, doi = {10.1038/srep36440}, volume = {6}, year = {2016}, } @article{1218, abstract = {Investigating the physiology of cyanobacteria cultured under a diel light regime is relevant for a better understanding of the resulting growth characteristics and for specific biotechnological applications that are foreseen for these photosynthetic organisms. Here, we present the results of a multiomics study of the model cyanobacterium Synechocystis sp. strain PCC 6803, cultured in a lab-scale photobioreactor in physiological conditions relevant for large-scale culturing. The culture was sparged withN2 andCO2, leading to an anoxic environment during the dark period. Growth followed the availability of light. Metabolite analysis performed with 1Hnuclear magnetic resonance analysis showed that amino acids involved in nitrogen and sulfur assimilation showed elevated levels in the light. Most protein levels, analyzed through mass spectrometry, remained rather stable. However, several high-light-response proteins and stress-response proteins showed distinct changes at the onset of the light period. Microarray-based transcript analysis found common patterns of~56% of the transcriptome following the diel regime. These oscillating transcripts could be grouped coarsely into genes that were upregulated and downregulated in the dark period. The accumulated glycogen was degraded in the anaerobic environment in the dark. A small part was degraded gradually, reflecting basic maintenance requirements of the cells in darkness. Surprisingly, the largest part was degraded rapidly in a short time span at the end of the dark period. This degradation could allow rapid formation of metabolic intermediates at the end of the dark period, preparing the cells for the resumption of growth at the start of the light period.}, author = {Angermayr, Andreas and Van Alphen, Pascal and Hasdemir, Dicle and Kramer, Gertjan and Iqbal, Muzamal and Van Grondelle, Wilmar and Hoefsloot, Huub and Choi, Younghae and Hellingwerf, Klaas}, journal = {Applied and Environmental Microbiology}, number = {14}, pages = {4180 -- 4189}, publisher = {American Society for Microbiology}, title = {{Culturing synechocystis sp. Strain pcc 6803 with N2 and CO2 in a diel regime reveals multiphase glycogen dynamics with low maintenance costs}}, doi = {10.1128/AEM.00256-16}, volume = {82}, year = {2016}, } @article{1552, abstract = {Antibiotic resistance carries a fitness cost that must be overcome in order for resistance to persist over the long term. Compensatory mutations that recover the functional defects associated with resistance mutations have been argued to play a key role in overcoming the cost of resistance, but compensatory mutations are expected to be rare relative to generally beneficial mutations that increase fitness, irrespective of antibiotic resistance. Given this asymmetry, population genetics theory predicts that populations should adapt by compensatory mutations when the cost of resistance is large, whereas generally beneficial mutations should drive adaptation when the cost of resistance is small. We tested this prediction by determining the genomic mechanisms underpinning adaptation to antibiotic-free conditions in populations of the pathogenic bacterium Pseudomonas aeruginosa that carry costly antibiotic resistance mutations. Whole-genome sequencing revealed that populations founded by high-cost rifampicin-resistant mutants adapted via compensatory mutations in three genes of the RNA polymerase core enzyme, whereas populations founded by low-cost mutants adapted by generally beneficial mutations, predominantly in the quorum-sensing transcriptional regulator gene lasR. Even though the importance of compensatory evolution in maintaining resistance has been widely recognized, our study shows that the roles of general adaptation in maintaining resistance should not be underestimated and highlights the need to understand how selection at other sites in the genome influences the dynamics of resistance alleles in clinical settings.}, author = {Qi, Qin and Toll Riera, Macarena and Heilbron, Karl and Preston, Gail and Maclean, R Craig}, journal = {Proceedings of the Royal Society of London Series B Biological Sciences}, number = {1822}, publisher = {Royal Society, The}, title = {{The genomic basis of adaptation to the fitness cost of rifampicin resistance in Pseudomonas aeruginosa}}, doi = {10.1098/rspb.2015.2452}, volume = {283}, year = {2016}, } @article{1571, abstract = {Epistatic interactions can frustrate and shape evolutionary change. Indeed, phenotypes may fail to evolve when essential mutations are only accessible through positive selection if they are fixed simultaneously. How environmental variability affects such constraints is poorly understood. Here, we studied genetic constraints in fixed and fluctuating environments using the Escherichia coli lac operon as a model system for genotype-environment interactions. We found that, in different fixed environments, all trajectories that were reconstructed by applying point mutations within the transcription factor-operator interface became trapped at suboptima, where no additional improvements were possible. Paradoxically, repeated switching between these same environments allows unconstrained adaptation by continuous improvements. This evolutionary mode is explained by pervasive cross-environmental tradeoffs that reposition the peaks in such a way that trapped genotypes can repeatedly climb ascending slopes and hence, escape adaptive stasis. Using a Markov approach, we developed a mathematical framework to quantify the landscape-crossing rates and show that this ratchet-like adaptive mechanism is robust in a wide spectrum of fluctuating environments. Overall, this study shows that genetic constraints can be overcome by environmental change and that crossenvironmental tradeoffs do not necessarily impede but also, can facilitate adaptive evolution. Because tradeoffs and environmental variability are ubiquitous in nature, we speculate this evolutionary mode to be of general relevance.}, author = {De Vos, Marjon and Dawid, Alexandre and Šunderlíková, Vanda and Tans, Sander}, journal = {PNAS}, number = {48}, pages = {14906 -- 14911}, publisher = {National Academy of Sciences}, title = {{Breaking evolutionary constraint with a tradeoff ratchet}}, doi = {10.1073/pnas.1510282112}, volume = {112}, year = {2015}, } @article{1581, abstract = {In animal embryos, morphogen gradients determine tissue patterning and morphogenesis. Shyer et al. provide evidence that, during vertebrate gut formation, tissue folding generates graded activity of signals required for subsequent steps of gut growth and differentiation, thereby revealing an intriguing link between tissue morphogenesis and morphogen gradient formation.}, author = {Bollenbach, Mark Tobias and Heisenberg, Carl-Philipp J}, journal = {Cell}, number = {3}, pages = {431 -- 432}, publisher = {Cell Press}, title = {{Gradients are shaping up}}, doi = {10.1016/j.cell.2015.04.009}, volume = {161}, year = {2015}, }