Evaluation of the Indazole Analogs of 5-MeO-DMT and Related Tryptamines as Serotonin Receptor 2 Agonists.

Herein, we report the synthesis and characterization of a novel set of substituted indazole-ethanamines and indazole-tetrahydropyridines as potent serotonin receptor subtype 2 (5-HT2) agonists. Specifically, we examine the 5-HT2 pharmacology of the direct indazole analogs of 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT) and related serotonergic tryptamines, and highlight the need for rigorous characterization of 5-HT2 subtype selectivity for these analogs, particularly for the 5-HT2B receptor subtype. Within this series, the potent analog VU6067416 (19d) was optimized to have suitable preclinical pharmacokinetic properties for in vivo dosing, although potent 5-HT2B agonist activity precluded further characterization for this series. Additionally, in silico docking studies suggest that the high potency of 19d may be a consequence of a halogen-bonding interaction with Phe2345.38 in the 5-HT2A orthosteric pocket.

Dynamical model of antibiotic responses linking expression of resistance genes to metabolism explains emergence of heterogeneity during drug exposures.

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 resistancetetoperon inE. 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.

Quantifying forms and functions of intestinal bile acid pools in mice.

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.

Short-term evolution of antibiotic responses in highly dynamic environments favors loss of regulation.

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.

Fatal iatrogenic cerebral ß-amyloid-related arteritis in a woman treated with lecanemab for Alzheimer's disease.

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 ß-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.

Dynamical model of antibiotic responses linking expression of resistance to metabolism explains emergence of heterogeneity during drug exposures.

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.

Community composition and the environment modulate the population dynamics of type VI secretion in human gut bacteria.

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.

Chemical Reactions of Indole Alkaloids That Enable Rapid Access to New Scaffolds for Discovery.

This graphical review provides a concise overview of indole alkaloids and chemical reactions that have been reported to transform both these natural products and derivatives to rapidly access new molecular scaffolds. Select biologically active compounds from these synthetic efforts are reported herein.

Alkylation of NH-sulfoximines under Mitsunobu-type conditions.

Previously described approaches for the alkylation of NH-sulfoximines typically rely either on transition metal catalysis, or the use of traditional alkylation reagents and strong bases. Herein, we report a straightforward alkylation of diverse NH-sulfoximines under simple Mitsunobu-type conditions, despite the unusually high pKa of the NH center.

Community composition and the environment modulate the population dynamics of type VI secretion in human gut bacteria.

Understanding the relationship between the composition of the human gut microbiota and the ecological forces shaping it is of high importance as progress towards therapeutic modulation of the microbiota advances. However, given the inaccessibility of the gastrointestinal tract, our knowledge of the biogeographical and ecological relationships between physically interacting taxa has been limited to date. It has been suggested that interbacterial antagonism plays an important role in gut community dynamics, but in practice the conditions under which antagonistic behavior is favored or disfavored by selection in the gut environment are not well known. Here, using phylogenomics of bacterial isolate genomes and analysis of infant and adult fecal metagenomes, we show that the contact-dependent type VI secretion system (T6SS) is repeatedly lost from the genomes of Bacteroides fragilis in adults compare to infants. Although this result implies a significant fitness cost to the T6SS, but we could not identify in vitro conditions under which such a cost manifests. Strikingly, however, experiments in mice illustrated that the B. fragilis T6SS can be favored or disfavored in the gut environment, depending on the strains and species in the surrounding community and their susceptibility to T6SS antagonism. We use a variety of ecological modeling techniques to explore the possible local community structuring conditions that could underlie the results of our larger scale phylogenomic and mouse gut experimental approaches. The models illustrate robustly that the pattern of local community structuring in space can modulate the extent of interactions between T6SS-producing, sensitive, and resistant bacteria, which in turn control the balance of fitness costs and benefits of performing contact-dependent antagonistic behavior. Taken together, our genomic analyses, in vivo studies, and ecological theory point toward new integrative models for interrogating the evolutionary dynamics of type VI secretion and other predominant modes of antagonistic interaction in diverse microbiomes.

Oral IRAK-4 Inhibitor CA-4948 Is Blood-Brain Barrier Penetrant and Has Single-Agent Activity against CNS Lymphoma and Melanoma Brain Metastases.

PURPOSE: An ongoing challenge in cancer is the management of primary and metastatic brain malignancies. This is partly due to restrictions of the blood-brain barrier and their unique microenvironment. These challenges are most evident in cancers such as lymphoma and melanoma, which are typically responsive to treatment in systemic locations but resistant when established in the brain. We propose interleukin-1 receptor-associated kinase-4 (IRAK-4) as a potential target across these diseases and describe the activity and mechanism of oral IRAK-4 inhibitor CA-4948. EXPERIMENTAL DESIGN: Human primary central nervous system lymphoma (PCNSL) and melanoma brain metastases (MBM) samples were analyzed for expression of IRAK-4 and downstream transcription pathways. We next determined the central nervous system (CNS) applicability of CA-4948 in naïve and tumor-bearing mice using models of PCNSL and MBM. The mechanistic effect on tumors and the tumor microenvironment was then analyzed. RESULTS: Human PCNSL and MBM have high expression of IRAK-4, IRAK-1, and nuclear factor kappa B (NF-κB). This increase in inflammation results in reflexive inhibitory signaling. Similar profiles are observed in immunocompetent murine models. Treatment of tumor-bearing animals with CA-4948 results in the downregulation of mitogen-activated protein kinase (MAPK) signaling in addition to decreased NF-κB. These intracellular changes are associated with a survival advantage. CONCLUSIONS: IRAK-4 is an attractive target in PCNSL and MBM. The inhibition of IRAK-4 with CA-4948 downregulates the expression of important transcription factors involved in tumor growth and proliferation. CA-4948 is currently being investigated in clinical trials for relapsed and refractory lymphoma and warrants further translation into PCNSL and MBM.

mSphere of Influence: Learning Biology from the Radio.

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.

Community composition shapes microbial-specific phenotypes in a cystic fibrosis polymicrobial model system.

Interspecies interactions can drive the emergence of unexpected microbial phenotypes that are not observed when studying monocultures. The cystic fibrosis (CF) lung consists of a complex environment where microbes, living as polymicrobial biofilm-like communities, are associated with negative clinical outcomes for persons with CF (pwCF). However, the current lack of in vitro models integrating the microbial diversity observed in the CF airway hampers our understanding of why polymicrobial communities are recalcitrant to therapy in this disease. Here, integrating computational approaches informed by clinical data, we built a mixed community of clinical relevance to the CF lung composed of Pseudomonas aeruginosa, Staphylococcus aureus, Streptococcus sanguinis, and Prevotella melaninogenica. We developed and validated this model biofilm community with multiple isolates of these four genera. When challenged with tobramycin, a front-line antimicrobial used to treat pwCF, the microorganisms in the polymicrobial community show altered sensitivity to this antibiotic compared to monospecies biofilms. We observed that wild-type P. aeruginosa is sensitized to tobramycin in a mixed community versus monoculture, and this observation holds across a range of community relative abundances. We also report that LasR loss-of-function, a variant frequently detected in the CF airway, drives tolerance of P. aeruginosa to tobramycin specifically in the mixed community. Our data suggest that the molecular basis of this community-specific recalcitrance to tobramycin for the P. aeruginosa lasR mutant is increased production of phenazines. Our work supports the importance of studying a clinically relevant model of polymicrobial biofilms to understand community-specific traits relevant to infections.

Carbohydrate-Small Molecule Hybrids as Lead Compounds Targeting IL-6 Signaling.

In the past 25 years, a number of efforts have been made toward the development of small molecule interleukin-6 (IL-6) signaling inhibitors, but none have been approved to date. Monosaccharides are a diverse class of bioactive compounds, but thus far have been unexplored as a scaffold for small molecule IL-6-signaling inhibitor design. Therefore, in this present communication, we combined a structure-based drug design approach with carbohydrate building blocks to design and synthesize novel IL-6-signaling inhibitors targeting glycoprotein 130 (gp130). Of this series of compounds, LS-TG-2P and LS-TF-3P were the top lead compounds, displaying IC50 values of 6.9 and 16 µM against SUM159 cell lines, respectively, while still retaining preferential activity against the IL-6-signaling pathway. The carbohydrate moiety was found to improve activity, as N-unsubstituted triazole analogues of these compounds were found to be less active in vitro compared to the leads themselves. Thus, LS-TG-2P and LS-TF-3P are promising scaffolds for further development and study as IL-6-signaling inhibitors.

Influenza A Virus Exacerbates Group A Streptococcus Infection and Thwarts Anti-Bacterial Inflammatory Responses in Murine Macrophages.

Seasonal influenza epidemics pose a considerable hazard for global health. In the past decades, accumulating evidence revealed that influenza A virus (IAV) renders the host vulnerable to bacterial superinfections which in turn are a major cause for morbidity and mortality. However, whether the impact of influenza on anti-bacterial innate immunity is restricted to the vicinity of the lung or systemically extends to remote sites is underexplored. We therefore sought to investigate intranasal infection of adult C57BL/6J mice with IAV H1N1 in combination with bacteremia elicited by intravenous application of Group A Streptococcus (GAS). Co-infection in vivo was supplemented in vitro by challenging murine bone marrow derived macrophages and exploring gene expression and cytokine secretion. Our results show that viral infection of mice caused mild disease and induced the depletion of CCL2 in the periphery. Influenza preceding GAS infection promoted the occurrence of paw edemas and was accompanied by exacerbated disease scores. In vitro co-infection of macrophages led to significantly elevated expression of TLR2 and CD80 compared to bacterial mono-infection, whereas CD163 and CD206 were downregulated. The GAS-inducible upregulation of inflammatory genes, such as Nos2, as well as the secretion of TNFα and IL-1ß were notably reduced or even abrogated following co-infection. Our results indicate that IAV primes an innate immune layout that is inadequately equipped for bacterial clearance.

Design and evaluation of novel analogs of 2-amino-4-boronobutanoic acid (ABBA) as inhibitors of human gamma-glutamyl transpeptidase.

Inhibitors of gamma-glutamyl transpeptidase (GGT1, aka gamma-glutamyl transferase) are needed for the treatment of cancer, cardiovascular illness and other diseases. Compounds that inhibit GGT1 have been evaluated in the clinic, but no inhibitor has successfully demonstrated specific and systemic GGT1 inhibition. All have severe side effects. L-2-amino-4­boronobutanoic acid (l-ABBA), a glutamate analog, is the most potent GGT1 inhibitor in vitro. In this study, we have solved the crystal structure of human GGT1 (hGGT1) with ABBA bound in the active site. The structure was interrogated to identify interactions between the enzyme and the inhibitor. Based on these data, a series of novel ABBA analogs were designed and synthesized. Their inhibitory activity against the hydrolysis and transpeptidation activities of hGGT1 were determined. The lead compounds were crystalized with hGGT1 and the structures solved. The kinetic data and structures of the complexes provide new insights into the critical role of protein structure dynamics in developing compounds for inhibition of hGGT1.

Optimal transcriptional regulation of dynamic bacterial responses to sudden drug exposures.

Cellular responses to the presence of toxic compounds in their environment require prompt expression of the correct levels of the appropriate enzymes, which are typically regulated by transcription factors that control gene expression for the duration of the response. The characteristics of each response dictate the choice of regulatory parameters such as the affinity of the transcription factor to its binding sites and the strength of the promoters it regulates. Although much is known about the dynamics of cellular responses, we still lack a framework to understand how different regulatory strategies evolved in natural systems relate to the selective pressures acting in each particular case. Here, we analyze a dynamical model of a typical antibiotic response in bacteria, where a transcriptionally repressed enzyme is induced by a sudden exposure to the drug that it processes. We identify strategies of gene regulation that optimize this response for different types of selective pressures, which we define as a set of costs associated with the drug, enzyme, and repressor concentrations during the response. We find that regulation happens in a limited region of the regulatory parameter space. While responses to more costly (toxic) drugs favor the usage of strongly self-regulated repressors, responses where expression of enzyme is more costly favor the usage of constitutively expressed repressors. Only a very narrow range of selective pressures favor weakly self-regulated repressors. We use this framework to determine which costs and benefits are most critical for the evolution of a variety of natural cellular responses that satisfy the approximations in our model and to analyze how regulation is optimized in new environments with different demands.

Bioactive lipid screening during respiratory tract infections with bacterial and viral pathogens in mice.

INTRODUCTION: Respiratory tract infections are a worldwide health problem for humans and animals. Different cell types produce lipid mediators in response to infections, which consist of eicosanoids like hydroxyeicosatetraenoic acids (HETEs) or oxylipins like hydroxydocosahexaenoic acids (HDHAs). Both substance classes possess immunomodulatory functions. However, little is known about their role in respiratory infections. OBJECTIVES: Here, we aimed to analyze the lipid mediator imprint of different organs of C57BL/6J mice after intranasal mono-infections with Streptococcus pneumoniae (pneumococcus), Staphylococcus aureus or Influenza A virus (IAV) as wells as pneumococcal-IAV co-infection. METHODS: C57BL/6J mice were infected with different pathogens and lungs, spleen, and plasma were collected. Lipid mediators were analyzed using HPLC-MS/MS. In addition, spatial-distribution of sphingosine 1-phosphate (S1P) and ceramide 1-phosphates (C1P) in tissue samples was examined using MALDI-MS-Imaging. The presence of bacterial pathogens in the lung was confirmed via immunofluorescence staining. RESULTS: We found IAV specific changes for different HDHAs and HETEs in mouse lungs as well as enhanced levels of 20-HETE in severe S. aureus infection. Moreover, MALDI-MS-Imaging analysis showed an accumulation of C1P and a decrease of S1P during co-infection in lung and spleen. Long chain C1P was enriched in the red and not in the white pulp of the spleen. CONCLUSIONS: Lipid mediator analysis showed that host synthesis of bioactive lipids is in part specific for a certain pathogen, in particular for IAV infection. Furthermore, MS-Imaging displayed great potential to study infections and revealed changes of S1P and C1P in lungs and spleen of co-infected animals, which was not described before.

Nutrient Gradients Mediate Complex Colony-Level Antibiotic Responses in Structured Microbial Populations.

Antibiotic treatments often fail to eliminate bacterial populations due to heterogeneity in how individual cells respond to the drug. In structured bacterial populations such as biofilms, bacterial metabolism and environmental transport processes lead to an emergent phenotypic structure and self-generated nutrient gradients toward the interior of the colony, which can affect cell growth, gene expression and susceptibility to the drug. Even in single cells, survival depends on a dynamic interplay between the drug's action and the expression of resistance genes. How expression of resistance is coordinated across populations in the presence of such spatiotemporal environmental coupling remains elusive. Using a custom microfluidic device, we observe the response of spatially extended microcolonies of tetracycline-resistant E. coli to precisely defined dynamic drug regimens. We find an intricate interplay between drug-induced changes in cell growth and growth-dependent expression of resistance genes, resulting in the redistribution of metabolites and the reorganization of growth patterns. This dynamic environmental feedback affects the regulation of drug resistance differently across the colony, generating dynamic phenotypic structures that maintain colony growth during exposure to high drug concentrations and increase population-level resistance to subsequent exposures. A mathematical model linking metabolism and the regulation of gene expression is able to capture the main features of spatiotemporal colony dynamics. Uncovering the fundamental principles that govern collective mechanisms of antibiotic resistance in spatially extended populations will allow the design of optimal drug regimens to counteract them.

Metabolic basis for the evolution of a common pathogenic Pseudomonas aeruginosa variant.

Microbes frequently evolve in reproducible ways. Here, we show that differences in specific metabolic regulation rather than inter-strain interactions explain the frequent presence of lasR loss-of-function (LOF) mutations in the bacterial pathogen Pseudomonas aeruginosa. While LasR contributes to virulence through its role in quorum sensing, lasR mutants have been associated with more severe disease. A model based on the intrinsic growth kinetics for a wild type strain and its LasR- derivative, in combination with an experimental evolution based genetic screen and further genetics analyses, indicated that differences in metabolism were sufficient to explain the rise of these common mutant types. The evolution of LasR- lineages in laboratory and clinical isolates depended on activity of the two-component system CbrAB, which modulates substrate prioritization through the catabolite repression control pathway. LasR- lineages frequently arise in cystic fibrosis lung infections and their detection correlates with disease severity. Our analysis of bronchoalveolar lavage fluid metabolomes identified compounds that negatively correlate with lung function, and we show that these compounds support enhanced growth of LasR- cells in a CbrB-controlled manner. We propose that in vivo metabolomes contribute to pathogen evolution, which may influence the progression of disease and its treatment.

Bacteria can evolve quickly, a skill that proves useful in ever-changing environments. For example, individuals in many bacterial species can start to work together under certain circumstances; this ability is underpinned by a system called quorum sensing, which allows cells to detect nearby conspecifics. However, species of harmful bacteria often lose their quorum sensing abilities when they infect humans. This is the case for Pseudomonas aeruginosa, which normally lives in the soil but can also cause deadly conditions, especially in hospital settings. Patients often carry P. aeruginosa with mutations that disable the quorum-sensing signal receptor LasR, a molecular actor that can switch on many other genes in a cell. People who are infected with P. aeruginosa strains carrying a damaged version of the lasR gene are typically more ill and less likely to recover. Why this is the case ­ and in fact, why genes associated with quorum sensing often lose function during infection ­ is still unclear. To investigate this question, Mould et al. used laboratory evolution experiments and computer models of P. aeruginosa growth to understand how lasR mutant cells evolve. Differences in growth rates and ways to use resources (rather than changes in cell-to-cell interactions) best explained why lasR mutants become more successful. Further experiments narrowed down the molecular cascade required for the rise of lasR mutants, identifying a pathway that regulates how P. aeruginosa switches between different nutrient sources. This work reveals a new connection between quorum sensing genes and nutrient regulation in bacterial cells. Loss of functional LasR changes the way that cells use nutrients, and thus will reshape how they interact with host cells and other bacteria. This insight could lead to better ways to predict the outcomes of bacterial infections and how to best treat them.