@article{12478, abstract = {In Gram negative bacteria, the multiple antibiotic resistance or mar operon, is known to control the expression of multi-drug efflux genes that protect bacteria from a wide range of drugs. As many different chemical compounds can induce this operon, identifying the parameters that govern the dynamics of its induction is crucial to better characterize the processes of tolerance and resistance. Most experiments have assumed that the properties of the mar transcriptional network can be inferred from population measurements. However, measurements from an asynchronous population of cells can mask underlying phenotypic variations of single cells. We monitored the activity of the mar promoter in single Escherichia coli cells in linear micro-colonies and established that the response to a steady level of inducer was most heterogeneous within individual colonies for an intermediate value of inducer. Specifically, sub-lineages defined by contiguous daughter-cells exhibited similar promoter activity, whereas activity was greatly variable between different sub-lineages. Specific sub-trees of uniform promoter activity persisted over several generations. Statistical analyses of the lineages suggest that the presence of these sub-trees is the signature of an inducible memory of the promoter state that is transmitted from mother to daughter cells. This single-cell study reveals that the degree of epigenetic inheritance changes as a function of inducer concentration, suggesting that phenotypic inheritance may be an inducible phenotype.}, author = {Guet, Calin C and Bruneaux, L and Oikonomou, P and Aldana, M and Cluzel, P}, issn = {1664-302X}, journal = {Frontiers in Microbiology}, publisher = {Frontiers}, title = {{Monitoring lineages of growing and dividing bacteria reveals an inducible memory of mar operon expression}}, doi = {10.3389/fmicb.2023.1049255}, volume = {14}, year = {2023}, } @article{10939, abstract = {Understanding and characterising biochemical processes inside single cells requires experimental platforms that allow one to perturb and observe the dynamics of such processes as well as computational methods to build and parameterise models from the collected data. Recent progress with experimental platforms and optogenetics has made it possible to expose each cell in an experiment to an individualised input and automatically record cellular responses over days with fine time resolution. However, methods to infer parameters of stochastic kinetic models from single-cell longitudinal data have generally been developed under the assumption that experimental data is sparse and that responses of cells to at most a few different input perturbations can be observed. Here, we investigate and compare different approaches for calculating parameter likelihoods of single-cell longitudinal data based on approximations of the chemical master equation (CME) with a particular focus on coupling the linear noise approximation (LNA) or moment closure methods to a Kalman filter. We show that, as long as cells are measured sufficiently frequently, coupling the LNA to a Kalman filter allows one to accurately approximate likelihoods and to infer model parameters from data even in cases where the LNA provides poor approximations of the CME. Furthermore, the computational cost of filtering-based iterative likelihood evaluation scales advantageously in the number of measurement times and different input perturbations and is thus ideally suited for data obtained from modern experimental platforms. To demonstrate the practical usefulness of these results, we perform an experiment in which single cells, equipped with an optogenetic gene expression system, are exposed to various different light-input sequences and measured at several hundred time points and use parameter inference based on iterative likelihood evaluation to parameterise a stochastic model of the system.}, author = {Davidović, Anđela and Chait, Remy P and Batt, Gregory and Ruess, Jakob}, issn = {1553-7358}, journal = {PLoS Computational Biology}, number = {3}, publisher = {Public Library of Science}, title = {{Parameter inference for stochastic biochemical models from perturbation experiments parallelised at the single cell level}}, doi = {10.1371/journal.pcbi.1009950}, volume = {18}, year = {2022}, } @article{11713, abstract = {Objective: MazF is a sequence-specific endoribonuclease-toxin of the MazEF toxin–antitoxin system. MazF cleaves single-stranded ribonucleic acid (RNA) regions at adenine–cytosine–adenine (ACA) sequences in the bacterium Escherichia coli. The MazEF system has been used in various biotechnology and synthetic biology applications. In this study, we infer how ectopic mazF overexpression affects production of heterologous proteins. To this end, we quantified the levels of fluorescent proteins expressed in E. coli from reporters translated from the ACA-containing or ACA-less messenger RNAs (mRNAs). Additionally, we addressed the impact of the 5′-untranslated region of these reporter mRNAs under the same conditions by comparing expression from mRNAs that comprise (canonical mRNA) or lack this region (leaderless mRNA). Results: Flow cytometry analysis indicates that during mazF overexpression, fluorescent proteins are translated from the canonical as well as leaderless mRNAs. Our analysis further indicates that longer mazF overexpression generally increases the concentration of fluorescent proteins translated from ACA-less mRNAs, however it also substantially increases bacterial population heterogeneity. Finally, our results suggest that the strength and duration of mazF overexpression should be optimized for each experimental setup, to maximize the heterologous protein production and minimize the amount of phenotypic heterogeneity in bacterial populations, which is unfavorable in biotechnological processes.}, author = {Nikolic, Nela and Sauert, Martina and Albanese, Tanino G. and Moll, Isabella}, issn = {1756-0500}, journal = {BMC Research Notes}, keywords = {General Biochemistry, Genetics and Molecular Biology, General Medicine}, publisher = {Springer Nature}, title = {{Quantifying heterologous gene expression during ectopic MazF production in Escherichia coli}}, doi = {10.1186/s13104-022-06061-9}, volume = {15}, year = {2022}, } @article{10736, abstract = {Predicting function from sequence is a central problem of biology. Currently, this is possible only locally in a narrow mutational neighborhood around a wildtype sequence rather than globally from any sequence. Using random mutant libraries, we developed a biophysical model that accounts for multiple features of σ70 binding bacterial promoters to predict constitutive gene expression levels from any sequence. We experimentally and theoretically estimated that 10–20% of random sequences lead to expression and ~80% of non-expressing sequences are one mutation away from a functional promoter. The potential for generating expression from random sequences is so pervasive that selection acts against σ70-RNA polymerase binding sites even within inter-genic, promoter-containing regions. This pervasiveness of σ70-binding sites implies that emergence of promoters is not the limiting step in gene regulatory evolution. Ultimately, the inclusion of novel features of promoter function into a mechanistic model enabled not only more accurate predictions of gene expression levels, but also identified that promoters evolve more rapidly than previously thought.}, author = {Lagator, Mato and Sarikas, Srdjan and Steinrueck, Magdalena and Toledo-Aparicio, David and Bollback, Jonathan P and Guet, Calin C and Tkačik, Gašper}, issn = {2050-084X}, journal = {eLife}, publisher = {eLife Sciences Publications}, title = {{Predicting bacterial promoter function and evolution from random sequences}}, doi = {10.7554/eLife.64543}, volume = {11}, year = {2022}, } @article{10812, abstract = {Several promising strategies based on combining or cycling different antibiotics have been proposed to increase efficacy and counteract resistance evolution, but we still lack a deep understanding of the physiological responses and genetic mechanisms that underlie antibiotic interactions and the clinical applicability of these strategies. In antibiotic-exposed bacteria, the combined effects of physiological stress responses and emerging resistance mutations (occurring at different time scales) generate complex and often unpredictable dynamics. In this Review, we present our current understanding of bacterial cell physiology and genetics of responses to antibiotics. We emphasize recently discovered mechanisms of synergistic and antagonistic drug interactions, hysteresis in temporal interactions between antibiotics that arise from microbial physiology and interactions between antibiotics and resistance mutations that can cause collateral sensitivity or cross-resistance. We discuss possible connections between the different phenomena and indicate relevant research directions. A better and more unified understanding of drug and genetic interactions is likely to advance antibiotic therapy.}, author = {Römhild, Roderich and Bollenbach, Mark Tobias and Andersson, Dan I.}, issn = {1740-1534}, journal = {Nature Reviews Microbiology}, keywords = {General Immunology and Microbiology, Microbiology, Infectious Diseases}, pages = {478--490}, publisher = {Springer Nature}, title = {{The physiology and genetics of bacterial responses to antibiotic combinations}}, doi = {10.1038/s41579-022-00700-5}, volume = {20}, year = {2022}, } @article{11339, abstract = {The interaction between a cell and its environment shapes fundamental intracellular processes such as cellular metabolism. In most cases growth rate is treated as a proximal metric for understanding the cellular metabolic status. However, changes in growth rate might not reflect metabolic variations in individuals responding to environmental fluctuations. Here we use single-cell microfluidics-microscopy combined with transcriptomics, proteomics and mathematical modelling to quantify the accumulation of glucose within Escherichia coli cells. In contrast to the current consensus, we reveal that environmental conditions which are comparatively unfavourable for growth, where both nutrients and salinity are depleted, increase glucose accumulation rates in individual bacteria and population subsets. We find that these changes in metabolic function are underpinned by variations at the translational and posttranslational level but not at the transcriptional level and are not dictated by changes in cell size. The metabolic response-characteristics identified greatly advance our fundamental understanding of the interactions between bacteria and their environment and have important ramifications when investigating cellular processes where salinity plays an important role.}, author = {Glover, Georgina and Voliotis, Margaritis and Łapińska, Urszula and Invergo, Brandon M. and Soanes, Darren and O’Neill, Paul and Moore, Karen and Nikolic, Nela and Petrov, Peter and Milner, David S. and Roy, Sumita and Heesom, Kate and Richards, Thomas A. and Tsaneva-Atanasova, Krasimira and Pagliara, Stefano}, issn = {2399-3642}, journal = {Communications Biology}, publisher = {Springer Nature}, title = {{Nutrient and salt depletion synergistically boosts glucose metabolism in individual Escherichia coli cells}}, doi = {10.1038/s42003-022-03336-6}, volume = {5}, year = {2022}, } @article{11843, abstract = {A key attribute of persistent or recurring bacterial infections is the ability of the pathogen to evade the host’s immune response. Many Enterobacteriaceae express type 1 pili, a pre-adapted virulence trait, to invade host epithelial cells and establish persistent infections. However, the molecular mechanisms and strategies by which bacteria actively circumvent the immune response of the host remain poorly understood. Here, we identified CD14, the major co-receptor for lipopolysaccharide detection, on mouse dendritic cells (DCs) as a binding partner of FimH, the protein located at the tip of the type 1 pilus of Escherichia coli. The FimH amino acids involved in CD14 binding are highly conserved across pathogenic and non-pathogenic strains. Binding of the pathogenic strain CFT073 to CD14 reduced DC migration by overactivation of integrins and blunted expression of co-stimulatory molecules by overactivating the NFAT (nuclear factor of activated T-cells) pathway, both rate-limiting factors of T cell activation. This response was binary at the single-cell level, but averaged in larger populations exposed to both piliated and non-piliated pathogens, presumably via the exchange of immunomodulatory cytokines. While defining an active molecular mechanism of immune evasion by pathogens, the interaction between FimH and CD14 represents a potential target to interfere with persistent and recurrent infections, such as urinary tract infections or Crohn’s disease.}, author = {Tomasek, Kathrin and Leithner, Alexander F and Glatzová, Ivana and Lukesch, Michael S. and Guet, Calin C and Sixt, Michael K}, issn = {2050-084X}, journal = {eLife}, publisher = {eLife Sciences Publications}, title = {{Type 1 piliated uropathogenic Escherichia coli hijack the host immune response by binding to CD14}}, doi = {10.7554/eLife.78995}, volume = {11}, year = {2022}, } @article{12333, abstract = {Together, copy-number and point mutations form the basis for most evolutionary novelty, through the process of gene duplication and divergence. While a plethora of genomic data reveals the long-term fate of diverging coding sequences and their cis-regulatory elements, little is known about the early dynamics around the duplication event itself. In microorganisms, selection for increased gene expression often drives the expansion of gene copy-number mutations, which serves as a crude adaptation, prior to divergence through refining point mutations. Using a simple synthetic genetic reporter system that can distinguish between copy-number and point mutations, we study their early and transient adaptive dynamics in real time in Escherichia coli. We find two qualitatively different routes of adaptation, depending on the level of functional improvement needed. In conditions of high gene expression demand, the two mutation types occur as a combination. However, under low gene expression demand, copy-number and point mutations are mutually exclusive; here, owing to their higher frequency, adaptation is dominated by copy-number mutations, in a process we term amplification hindrance. Ultimately, due to high reversal rates and pleiotropic cost, copy-number mutations may not only serve as a crude and transient adaptation, but also constrain sequence divergence over evolutionary time scales.}, author = {Tomanek, Isabella and Guet, Calin C}, issn = {2050-084X}, journal = {eLife}, publisher = {eLife Sciences Publications}, title = {{Adaptation dynamics between copynumber and point mutations}}, doi = {10.7554/ELIFE.82240}, volume = {11}, year = {2022}, } @misc{12339, abstract = {Copy-number and point mutations form the basis for most evolutionary novelty through the process of gene duplication and divergence. While a plethora of genomic sequence data reveals the long-term fate of diverging coding sequences and their cis-regulatory elements, little is known about the early dynamics around the duplication event itself. In microorganisms, selection for increased gene expression often drives the expansion of gene copy-number mutations, which serves as a crude adaptation, prior to divergence through refining point mutations. Using a simple synthetic genetic system that allows us to distinguish copy-number and point mutations, we study their early and transient adaptive dynamics in real-time in Escherichia coli. We find two qualitatively different routes of adaptation depending on the level of functional improvement selected for: In conditions of high gene expression demand, the two types of mutations occur as a combination. Under low gene expression demand, negative epistasis between the two types of mutations renders them mutually exclusive. Thus, owing to their higher frequency, adaptation is dominated by copy-number mutations. Ultimately, due to high rates of reversal and pleiotropic cost, copy-number mutations may not only serve as a crude and transient adaptation but also constrain sequence divergence over evolutionary time scales.}, author = {Tomanek, Isabella and Guet, Calin C}, publisher = {Dryad}, title = {{Flow cytometry YFP and CFP data and deep sequencing data of populations evolving in galactose}}, doi = {10.5061/dryad.rfj6q57ds}, year = {2022}, } @article{9046, author = {Römhild, Roderich and Andersson, Dan I.}, issn = {15537374}, journal = {PLoS Pathogens}, number = {1}, publisher = {Public Library of Science}, title = {{Mechanisms and therapeutic potential of collateral sensitivity to antibiotics}}, doi = {10.1371/journal.ppat.1009172}, volume = {17}, year = {2021}, }