Circadian rhythms are pervasive among eukaryotes, and the underlying clocks share a common regulatory architecture-a negative feedback loop. A wealth of genetic and biochemical data underpin current perceptions of circadian oscillators but aspects of their cell biology remain cryptic, especially in syncytial systems like Neurospora crassa. We employed novel microfluidic systems and a light-blind mutant that retains circadian function to simultaneously track multiple clock components in vivo across circadian cycles in Neurospora. Despite heterogeneity of clock gene (frq) expression, we find robust, synchronous cycles in FRQ nuclear localization among all nuclei and document free diffusion of multiple clock components among nuclei. Within nuclei, clock components form small, highly dynamic nuclear bodies that persist throughout the cycle and exhibit time-dependent changes in composition, including transient colocalization between the positive and negative components for circadian regulatory functions. This rich context of in vivo spatiotemporal information illustrates how dynamic subnuclear organization and internuclear exchange of clock proteins ensure synchronous regulation of cellular activities across a macroscopic, multinucleated syncytium.

Pseudomonas aeruginosa infections in adults with cystic fibrosis (CF) are comprised of heterogeneous populations, most often tracing ancestry back to a single recent common ancestor. What is not clear is the physical spatial structure within the lung infection population, its stability over time, and whether this physical structure leads to different evolutionary trajectories in different adaptive environments. To compare the P. aeruginosa populations across a single lung, we performed whole genome sequence analyses of 450 isolates recovered from lavage samples of the three different lobes of the right lung from a person with mild-to-moderate CF lung disease at three time points over the course of ~1.5 years. We found that isolates fell into five distinct phylogenetic lineages with evidence for repeated translocation of isolates from different lineages across lobes and loss-of-function mutations in lasR and mucA were present in all 450 isolates. The well-resolved phylogenetic analyses revealed a structured population in which we find the coexistence of a slowly evolving lineage and more rapidly evolving lineages. There is also support for numerous migration events. Furthermore, strong evidence for parallel adaptive mutations in multiple genes revealed distinct evolutionary paths affecting mucoid phenotypes and genetic variation in antibiotic resistance-associated pathways across coexisting populations within a single individual over time. These results provide an example of within-host evolution leading to microheterogeneity that may be useful to consider in future study of infection metapopulations dynamics over the course of chronic infection.IMPORTANCEIndividuals with cystic fibrosis (CF) commonly have chronic lung infections that contain clonally derived Pseudomonas aeruginosa populations with genotypic and phenotypic diversity. This study describes a substantial data set containing 450 isolates from different lobes of the right lung across three time points from an individual with mild-to-moderate CF lung disease. Some regional enrichment for specific lineages with parallel mutations among individual lobes of the lung was observed, but longitudinal analysis also demonstrated that compartmentalization is not strictly maintained and that isolates migrate between lobes of the lung over time. Perspectives on within lung evolution will be important for understanding the pathogen populations in chronic respiratory infections in CF and other diseases.

Antibiotics are known to induce new persister cells during treatment, yet the inability to distinguish and quantify pre-existing versus drug-induced persisters has long obscured how antibiotics and genes shape persistence. Here, we develop a quantitative framework integrating kinetic modeling with serial-dilution time-kill (SDTK) assays to resolve persister population dynamics and accurately quantify both persister types. We show that antibiotic exposure dynamically generates a substantial number of persisters that are heterogeneous and distributed along a persistence spectrum. Across antibiotics, we uncover pronounced differences in rates of persister induction and elimination, with ampicillin inducing persisters at the highest rate and kanamycin at the lowest. Depending on dilution history, drug-induced persisters can dominate the persister pool. Our framework enables identification of genetic determinants specific to pre-existing and/or drug-induced persistence and reveals drug-dependent pre-existing persister fractions. Systematic sequential-drug treatments demonstrate that kanamycin persisters form the most tolerant subset, embedded within ciprofloxacin persisters that in turn are nested within the broader ampicillin persister subpopulation. Together, we propose a Drug-Induced Persistence-Spectrum (DIPS) model in which antibiotics differentially induce and select for persister subsets along a tolerance continuum. ### Competing Interest Statement The authors have declared no competing interest. U.S. National Science Foundation, CCF-2240264, PHY-2412766, DMS-2527337 United States Department of Energy, DE-SC0026232

In this issue of Cell Host & Microbe, Nishimoto et al. evolve S. pneumoniae under antibiotics and immune pressure, uncovering drug tolerance mutations, instead of resistance. Increased RNase activity depletes the RNA pool to avert lethal transcriptional collapse, preserving transcript fidelity and enabling a transcriptome reboot when drug subsides.

Using combinations of existing antibiotics is a promising strategy to treat bacterial infections. Although some drugs act synergistically, other drug combinations inhibit microbial growth less than what is expected from their individual effects. Ciprofloxacin and tetracycline display such antagonistic interaction. In a new study, Broughton and colleagues (Broughton et al, 2025) used single-cell microfluidics to show that exposing E. coli cells to a combination of ciprofloxacin and tetracycline results in highly heterogeneous outcomes. The survival of single cells is linked to the expression of moderate levels of the SOS response, which fixes the double-strand DNA breaks caused by ciprofloxacin. High expression of the SOS response was found only among dying cells. Tetracycline then counteracts ciprofloxacin by increasing the proportion of cells that survive treatment within the low-SOS subpopulation. These findings highlight the importance of single-cell studies in understanding the phenotypic heterogeneity that emerges during antibiotic responses, which decide the success of treatments. J. Carvalho and D. Schultz discuss the study by Broughton et al, in this issue of Molecular Systems Biology, on the heterogeneous responses of individual E. coli to a combination of antibiotics, contributing to their antagonistic interaction.

Microbes inhabit natural environments that are remarkably dynamic. Therefore, microbes harbor regulated genetic mechanisms to sense shifts in conditions and induce the appropriate responses. Recent studies suggest that the initial evolution of microbes occupying new niches favors mutations in regulatory pathways. However, it is not clear how this evolution is affected by how quickly conditions change (i.e. dynamics), or which mechanisms are commonly used to implement new regulation. Here, we perform experimental evolution on continuous cultures of Escherichia coli carrying the tetracycline resistance tet operon to identify specific mutations that adapt drug responses to different dynamic regimens of drug administration. We find that cultures evolved under gradually increasing tetracycline concentrations show no mutations in the tet operon, but instead a predominance of fine-tuning mutations increasing the affinity of an alternative efflux pump AcrB to tetracycline. When cultures are instead periodically exposed to large drug doses, all populations evolved transposon insertions in repressor TetR, resulting in loss of regulation and constitutive expression of efflux pump TetA. We use a mathematical model of the dynamics of antibiotic responses to show that sudden exposure to large drug concentrations overwhelm regulated responses, which cannot induce resistance fast enough, resulting in selection for constitutive expression of resistance. These results help explain the frequent loss of regulation of antibiotic resistance by pathogens evolved in clinical environments. Our experiment supports the notion that initial evolution in new ecological niches proceeds largely through regulatory mutations and suggests that transposon insertions are the main mechanism driving this process.

Single-cell microfluidic experiments have shown that upon abrupt exposures to antibiotics, genetically homogeneous microbial populations undergo divergent cell fates. The mechanism underlying this divergence is not clear and in particular, the emergence of a range of distinct slow-growing phenotypes cannot be explained by models relying on bistability alone. Here, we propose a model for gene expression and growth dynamics during antibiotic exposures, which is informed by well-known scaling relations connecting proteome allocation and cell growth. In our model, resources available for transcription and translation of resistance genes act like generalized momenta and their initial variation is predictive of cell fate. Our model reproduces key experimental observations, including the prediction of specific phenotypes and a critical threshold in initial resource allocation that predicts cell survival. These results offer an alternative mechanism for the emergence of phenotypic diversity where slow cell growth effectively stabilizes cellular states along the trajectory that are far from the final stable states predicted by fixed points. ### Competing Interest Statement The authors have declared no competing interest. NSF, DMS-2527337, PHY-2412766

Microbes inhabit natural environments that are remarkably dynamic, with sudden environmental shifts that require immediate action by the cell. To cope with changing environments, microbes are equipped with regulated response mechanisms that are only activated when needed. However, when exposed to extreme environments such as clinical antibiotic treatments, complete loss of regulation is frequently observed. Although recent studies suggest that the initial evolution of microbes in new environments tends to favor mutations in regulatory pathways, it is not clear how this evolution is affected by how quickly conditions change (i.e. dynamics), or which mechanisms are commonly used to implement new regulation. Here, we perform experimental evolution on continuous cultures of E. coli carrying the tetracycline resistance tet operon to identify specific types of mutations that adapt drug responses to different dynamical regimens of drug administration. When cultures are evolved under gradually increasing tetracycline concentrations, we observe no mutations in the tet operon, but a predominance of fine-tuning mutations increasing the affinity of alternative efflux pump AcrB to tetracycline. When cultures are instead periodically exposed to large drug doses, all populations developed transposon insertions in repressor TetR, resulting in loss of regulation of efflux pump TetA. We use a mathematical model of the dynamics of antibiotic responses to show that sudden exposure to large drug concentrations can overwhelm regulated responses, which cannot induce resistance fast enough, resulting in fitness advantage for constitutive expression of resistance. These results help explain the loss of regulation of antibiotic resistance by opportunistic pathogens evolving in clinical environments. Our experiment supports the notion that initial evolution in new ecological niches proceeds largely through regulatory mutations and suggests that transposon insertions are a main mechanism driving this process.

Despite competition for both space and nutrients, bacterial species often coexist within structured, surface-attached communities termed biofilms. While these communities play important, widespread roles in ecosystems and are agents of human infection, understanding how multiple bacterial species assemble to form these communities and what physical processes underpin the composition of multispecies biofilms remains an active area of research. Using a model three-species community composed of Pseudomonas aeruginosa, Escherichia coli, and Enterococcus faecalis, we show with cellular-scale resolution that biased dispersal of the dominant community member, P. aeruginosa, prevents competitive exclusion from occurring, leading to the coexistence of the three species. A P. aeruginosa bqsS deletion mutant no longer undergoes periodic mass dispersal, leading to the local competitive exclusion of E. coli. Introducing periodic, asymmetric dispersal behavior into minimal models, parameterized by only maximal growth rate and local density, supports the intuition that biased dispersal of an otherwise dominant competitor can permit coexistence generally. Colonization experiments show that WT P. aeruginosa is superior at colonizing new areas, in comparison to ΔbqsS P. aeruginosa, but at the cost of decreased local competitive ability against E. coli and E. faecalis. Overall, our experiments document how one species’ modulation of a competition-dispersal-colonization trade-off can go on to influence the stability of multispecies coexistence in spatially structured ecosystems.

Antibiotic responses in bacteria are highly dynamic and heterogeneous, with sudden exposure of bacterial colonies to high drug doses resulting in the coexistence of recovered and arrested cells. The dynamics of the response is determined by regulatory circuits controlling the expression of resistance genes, which are in turn modulated by the drug's action on cell growth and metabolism. Despite advances in understanding gene regulation at the molecular level, we still lack a framework to describe how feedback mechanisms resulting from the interdependence between expression of resistance and cell metabolism can amplify naturally occurring noise and create heterogeneity at the population level. To understand how this interplay affects cell survival upon exposure, we constructed a mathematical model of the dynamics of antibiotic responses that links metabolism and regulation of gene expression, based on the tetracycline resistance tet operon in E. coli. We use this model to interpret measurements of growth and expression of resistance in microfluidic experiments, both in single cells and in biofilms. We also implemented a stochastic model of the drug response, to show that exposure to high drug levels results in large variations of recovery times and heterogeneity at the population level. We show that stochasticity is important to determine how nutrient quality affects cell survival during exposure to high drug concentrations. A quantitative description of how microbes respond to antibiotics in dynamical environments is crucial to understand population-level behaviors such as biofilms and pathogenesis.

Typical antibiotic susceptibility testing (AST) of microbial samples is performed in homogeneous cultures in steady environments, which does not account for the highly heterogeneous and dynamic nature of antibiotic responses. The most common mutation found in P. aeruginosa lineages evolved in the human lung, a loss of function of repressor MexZ, increases basal levels of multidrug efflux MexXY, but does not increase resistance by traditional MIC measures. Here, we use single cell microfluidics to show that P. aeruginosa response to aminoglycosides is highly heterogeneous, with only a subpopulation of cells surviving exposure. mexZ mutations then bypass the lengthy process of MexXY activation, increasing survival to sudden drug exposures and conferring a fitness advantage in fluctuating environments. We propose a simple "Response Dynamics" assay to quantify the speed of population-level recovery to drug exposures. This assay can be used alongside MIC for resistance profiling to better predict clinical outcomes.

Bile acids (BAs) are gastrointestinal metabolites that serve dual functions in lipid absorption and cell signaling. BAs circulate actively between the liver and distal small intestine (i.e., ileum), yet the dynamics through which complex BA pools are absorbed in the ileum and interact with intestinal cells in vivo remain ill-defined. Through multi-site sampling of nearly 100 BA species in individual wild type mice, as well as mice lacking the ileal BA transporter, Asbt/Slc10a2, we calculate the ileal BA pool in fasting C57BL/6J mice to be ~0.3 μmoles/g. Asbt-mediated transport accounts for ~80% of this pool and amplifies size, whereas passive absorption explains the remaining ~20%, and generates diversity. Accordingly, ileal BA pools in mice lacking Asbt are ~5-fold smaller than in wild type controls, enriched in secondary BA species normally found in the colon, and elicit unique transcriptional responses in cultured ileal explants. This work quantitatively defines ileal BA pools in mice and reveals how BA dysmetabolism can impinge on intestinal physiology.

AbstractWe report the case of an elderly woman in good general health aside from early-stage Alzheimer’s disease who was enrolled in a randomized controlled trial of the novel therapeutic monoclonal antibody lecanemab where she was treated with the placebo, and subsequently in the open label extension study where she received lecanemab infusions every two weeks. After the third infusion, she suffered a seizure followed by aphasia and progressively worsening encephalopathy. Magnetic resonance imaging revealed multifocal cerebral edema and an increased burden of cerebral microhemorrhages compared to pre-trial imaging, consistent with Amyloid Related Imaging Abnormality (ARIA). She was treated with an antiepileptic regimen and high-dose intravenous corticosteroids but continued to worsen and expired after five days in the hospital. The family requested an autopsy and consented to evaluation of her brain for research. Post-mortem MRI confirmed extensive microhemorrhagic changes in the temporal, parietal and occipital lobes, some of which were visible on gross inspection of the brain. Autopsy confirmed APOE genotype of E4/E4 and the presence of typical neuropathological features of Alzheimer’s disease along with severe cerebral amyloid angiopathy with inflammatory features, including perivascular lymphocytic infiltrates, reactive macrophages and fibrinoid degeneration of vessel walls. There were deposits of β-amyloid in meningeal vessels and penetrating arterioles with numerous microaneurysms. Cerebral microhemorrhages were associated with arterioles harboring β-amyloid deposits and having degenerative morphologies. We conclude from these results that the patient likely died as a result of severe cerebral amyloid angiopathy with marked microvascular degeneration and meningoencephalitis. Further study of the mechanism of ARIA and the neuropathological changes associated with plaque clearance are needed.

We report the case of a 79-year-old woman with Alzheimer’s disease who participated in a Phase III randomized controlled trial called CLARITY-AD testing the experimental drug lecanemab. She was randomized to the placebo group and subsequently enrolled in an open-label extension which guaranteed she received the active drug. After the third biweekly infusion, she suffered a seizure characterized by speech arrest and a generalized convulsion. Magnetic resonance imaging revealed she had multifocal swelling and a marked increase in the number of cerebral microhemorrhages. She was treated with an antiepileptic regimen and high-dose intravenous corticosteroids but continued to worsen and died after 5 days. Post-mortem MRI confirmed extensive microhemorrhages in the temporal, parietal and occipital lobes. The autopsy confirmed the presence of two copies of APOE4, a gene associated with a higher risk of Alzheimer’s disease, and neuropathological features of moderate severity Alzheimer’s disease and severe cerebral amyloid angiopathy with perivascular lymphocytic infiltrates, reactive macrophages and fibrinoid degeneration of vessel walls. There were deposits of β-amyloid in meningeal vessels and penetrating arterioles with numerous microaneurysms. We conclude that the patient likely died as a result of severe cerebral amyloid-related inflammation.

Daniel Schultz works at the intersection of microbiology and biological physics. In this mSphere of Influence article, he reflects on how two papers concerning the radio, "Can a biologist fix a radio? Or, what I learned while studying apoptosis" by Yuri Lazebnik and "The evolved radio and its implications for modeling the evolution of novel sensors" by Jon Bird and Paul Layzell, offered him complementary perspectives on how to bridge the gap between engineering and biology in the study of cellular circuits.

Understanding the relationship between the composition of the human gut microbiota and the ecological forces shaping it is of great importance; however, knowledge of the biogeographical and ecological relationships between physically interacting taxa is limited. Interbacterial antagonism may play an important role in gut community dynamics, yet the conditions under which antagonistic behaviour is favoured or disfavoured by selection in the gut are not well understood. Here, using genomics, we show that a species-specific type VI secretion system (T6SS) repeatedly acquires inactivating mutations in Bacteroides fragilis in the human gut. This result implies a fitness cost to the T6SS, but we could not identify laboratory conditions under which such a cost manifests. Strikingly, experiments in mice illustrate that the T6SS can be favoured or disfavoured in the gut depending on the strains and species in the surrounding community and their susceptibility to T6SS antagonism. We use ecological modelling to explore the conditions that could underlie these results and find that community spatial structure modulates interaction patterns among bacteria, thereby modulating the costs and benefits of T6SS activity. Our findings point towards new integrative models for interrogating the evolutionary dynamics of type VI secretion and other modes of antagonistic interaction in microbiomes.