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We developed a simplified, highly efficient Gateway reaction that recombines target DNA to expression (destination) plasmids in vivo and subsequently conjugates the final vector into a recipient strain, all in a single step. This recipient strain does not need to contain any selective marker and can be freely chosen as long as it is sensitive to ccdB counterselection and can be targeted by the RP4α conjugation system. Our protocol is simple, robust, and cost effective. It works in 96-well plate format and performs across a range of temperatures. We designed modular, minimal destination vectors containing a modified Gateway insert to ease vector design by providing locations for insertion of tags, promoters, or conjugations. To demonstrate the utility of our system, we created destination vectors with split adenylate cyclase tags for bacterial two-hybrid (B2H) studies and screened a library of diguanylate cyclases for protein-protein interactions in a single step.

A significant challenge today within protein lipidology is to understand the relationship between cell structure, lipid membrane integrity, ion homeostasis and the embedded membrane proteins. The bacterial magnesium transporter A (MgtA) is a specialized P-type ATPase important for Mg2+ import into the cytoplasm; disrupted magnesium homeostasis is linked to intrinsic ribosome instability and nitro-oxidative stress in Salmonella strains. MgtA’s function is highly dependent on anionic lipids, particularly cardiolipin, and further co-localization of cardiolipin with MgtA at the E. coli cell poles has been revealed. Here, we show that MgtA has functional specificity for cardiolipin 18:1, but it reaches maximum activity only in combination with cardiolipin 16:0, equivalent to the major components of native cardiolipin found in E. coli membranes. This is the first time it has been shown experimentally that two different lipid species from the same class, individually promoting low activity, can enhance activity in combination. Native mass spectrometry verifies the presence of two binding sites for cardiolipin and kinetic studies reveal that a cooperative relationship likely exists between the two different cardiolipin variants (cardiolipin 16:0 and cardiolipin 18:1). This is the first experimental evidence of cooperative effects between lipids of the same class, with only minor variations in their acyl chain composition, acting on a membrane protein. In summary, our results reveal that MgtA exhibits a highly complex interaction with one cardiolipin 18:1 and one cardiolipin 16:0, affecting protein activity and stability, and contributing to our understanding of the particular interactions between lipid environment and membrane proteins. Further, a better understanding of Mg2+ homeostasis in bacteria, due to its role as a virulence regulator, will provide further insights into the regulation and mechanism of bacterial infections.

Microbial division rates determine the speed of mutation accumulation and thus the emergence of antimicrobial resistance. Microbial death rates are affected by antibiotic action and the immune system. Therefore, measuring these rates has advanced our understanding of host-pathogen interactions and antibiotic action. Several methods based on marker-loss or few inheritable neutral markers exist that allow estimating microbial division and death rates, each of which has advantages and limitations. Technical bottlenecks, i.e., experimental sampling events, during the experiment can distort the rate estimates and are typically unaccounted for or require additional calibration experiments. In this work, we introduce RESTAMP (Rate Estimates by Sequence Tag Analysis of Microbial Populations) as a method for determining bacterial division and death rates. This method uses hundreds of fitness neutral sequence barcodes to measure the rates and account for experimental bottlenecks at the same time. We experimentally validate RESTAMP and compare it to established plasmid loss methods. We find that RESTAMP has a number of advantages over plasmid loss or previous marker based techniques. (i) It enables to correct the distortion of rate estimates by technical bottlenecks. (ii) Rate estimates are independent of the sequence tag distribution in the starting culture allowing the use of an arbitrary number of tags. (iii) It introduces a bottleneck sensitivity measure that can be used to maximize the accuracy of the experiment. RESTAMP allows studying microbial population dynamics with great resolution over a wide dynamic range and can thus advance our understanding of host-pathogen interactions or the mechanisms of antibiotic action.

Antibiotic resistance is rising and we urgently need to gain a better quantitative understanding of how antibiotics act, which in turn would also speed up the development of new antibiotics. Here, we describe a computational model (COMBAT-COmputational Model of Bacterial Antibiotic Target-binding) that can quantitatively predict antibiotic dose-response relationships. Our goal is dual: We address a fundamental biological question and investigate how drug-target binding shapes antibiotic action. We also create a tool that can predict antibiotic efficacy a priori. COMBAT requires measurable biochemical parameters of drug-target interaction and can be directly fitted to time-kill curves. As a proof-of-concept, we first investigate the utility of COMBAT with antibiotics belonging to the widely used quinolone class. COMBAT can predict antibiotic efficacy in clinical isolates for quinolones from drug affinity (R2>0.9). To further challenge our approach, we also do the reverse: estimate the magnitude of changes in drug-target binding based on antibiotic dose-response curves. We overexpress target molecules to infer changes in antibiotic-target binding from changes in antimicrobial efficacy of ciprofloxacin with 92–94% accuracy. To test the generality of our approach, we use the beta-lactam ampicillin to predict target molecule occupancy at MIC from antimicrobial action with 90% accuracy. Finally, we apply COMBAT to predict antibiotic concentrations that can select for resistance due to novel resistance mutations. Using ciprofloxacin and ampicillin as well defined test cases, our work demonstrates that drug-target binding is a major predictor of bacterial responses to antibiotics. This is surprising because antibiotic action involves many additional effects downstream of drug-target binding. In addition, COMBAT provides a framework to inform optimal antibiotic dose levels that maximize efficacy and minimize the rise of resistant mutants., Author summary Antibiotic efficacy is traditionally assessed with a single value, the minimal inhibitory concentration, despite its limited predictive power. Dose-response curves that assess efficacy over a range of antibiotic concentrations are promising, but extremely work intensive. Using the well-characterized antibiotics ciprofloxacin and ampicillin as proof-of-concept, we provide a mathematical framework that allows predicting optimal dosing of antibiotics based on drug-target binding parameters. These could be measured early in drug development and can also change when bacteria become resistant. Thus, we can predict the probability that resistant strains are selected at a given dosing regimen without isolating and testing a multitude of resistant strains. Predicting optimal dosing with early accessible experimental data can reduce the prevalent trial-and-error approaches and thereby the number of antibiotic candidates that fail late in drug development.

Das Controlling hat an kritischen Stellen des Budgetierungsprozesses sehr wirkungsvolle Möglichkeiten, die Auswirkungen des House Money Effekts und des Break-Even Effekts einzudämmen. Durch Controllinginstrumente können deren Auslöser erkannt und eliminiert werden, um die risikovorgebende und zielgerichtete Steuerungsfunktion von Budgets aufrechtzuerhalten. Dieses Potenzial wird jedoch bislang oftmals nicht ausgeschöpft.

Ein ‚digitalisiertes Controlling‘ wird im Allgemeinen als erstrebenswert angesehen, da sich neue Möglichkeiten für eine bessere Nutzung der Informationen (z.B. mobiler Datenzugriff) für das Management eröffnen. Allerdings entstehen ebenfalls neue Herausforderungen im Umgang mit diesen Informationen, welche eine mediierende Funktion des Controllers zwischen Daten und Management auch weiterhin unverzichtbar machen.

Bacterial heteroresistance (i.e., the co-existence of several subpopulations with different antibiotic susceptibilities) can delay the clearance of bacteria even with long antibiotic exposure. Some proposed mechanisms have been successfully described with mathematical models of drug-target binding where the mechanism&rsquo, s downstream of drug-target binding are not explicitly modeled and subsumed in an empirical function, connecting target occupancy to antibiotic action. However, with current approaches it is difficult to model mechanisms that involve multi-step reactions that lead to bacterial killing. Here, we have a dual aim: first, to establish pharmacodynamic models that include multi-step reaction pathways, and second, to model heteroresistance and investigate which molecular heterogeneities can lead to delayed bacterial killing. We show that simulations based on Gillespie algorithms, which have been employed to model reaction kinetics for decades, can be useful tools to model antibiotic action via multi-step reactions. We highlight the strengths and weaknesses of current models and Gillespie simulations. Finally, we show that in our models, slight normally distributed variances in the rates of any event leading to bacterial death can (depending on parameter choices) lead to delayed bacterial killing (i.e., heteroresistance). This means that a slowly declining residual bacterial population due to heteroresistance is most likely the default scenario and should be taken into account when planning treatment length.

Enterohemorrhagic Escherichia coli O157:H7 (EHEC) is an important food-borne pathogen that colonizes the colon. Transposon-insertion sequencing (TIS) was used to identify genes required for EHEC and E. coli K-12 growth in vitro and for EHEC growth in vivo in the infant rabbit colon. Surprisingly, many conserved loci contribute to EHEC’s but not to K-12’s growth in vitro. There was a restrictive bottleneck for EHEC colonization of the rabbit colon, which complicated identification of EHEC genes facilitating growth in vivo. Both a refined version of an existing analytic framework as well as PCA-based analysis were used to compensate for the effects of the infection bottleneck. These analyses confirmed that the EHEC LEE-encoded type III secretion apparatus is required for growth in vivo and revealed that only a few effectors are critical for in vivo fitness. Over 200 mutants not previously associated with EHEC survival/growth in vivo also appeared attenuated in vivo, and a subset of these putative in vivo fitness factors were validated. Some were found to contribute to efficient type-three secretion while others, including tatABC, oxyR, envC, acrAB, and cvpA, promote EHEC resistance to host-derived stresses. cvpA is also required for intestinal growth of several other enteric pathogens, and proved to be required for EHEC, Vibrio cholerae and Vibrio parahaemolyticus resistance to the bile salt deoxycholate, highlighting the important role of this previously uncharacterized protein in pathogen survival. Collectively, our findings provide a comprehensive framework for understanding EHEC growth in the intestine., Author summary Enterohemorrhagic E. coli (EHEC) is an important food-borne pathogen that infects the colon. We created a dense EHEC transposon library and used transposon-insertion sequencing to identify the genes required for EHEC growth in vitro and in vivo in the infant rabbit colon. We found that there is a large infection bottleneck in the rabbit model of intestinal colonization and refined two analytic approaches to facilitate rigorous identification of new EHEC genes that promote fitness in vivo. Besides the known type III secretion system, more than 200 additional genes were found to contribute to EHEC survival and/or growth within the intestine. The requirement for some of these new in vivo fitness factors was confirmed, and their contributions to infection were investigated. This set of genes should be of considerable value for future studies elucidating the processes that enable the pathogen to proliferate in vivo and for design of new therapeutics.

Combatting antibiotic resistance will require both new antibiotics and strategies to preserve the effectiveness of existing drugs. Both approaches would benefit from predicting optimal dosing of antibiotics based on drug-target binding parameters that can be measured early in drug development and that can change when bacteria become resistant. This would avoid the currently frequently employed trial-and-error approaches and might reduce the number of antibiotic candidates that fail late in drug development.Here, we describe a computational model (COMBAT-COmputational Model of Bacterial Antibiotic Target-binding) that leverages accessible biochemical parameters to quantitatively predict antibiotic dose-response relationships. We validate our model with MICs of a range of quinolone antibiotics in clinical isolates demonstrating that antibiotic efficacy can be predicted from drug-target binding (R2 > 0.9). To further challenge our approach, we do not only predict antibiotic efficacy from biochemical parameters, but also do the reverse: estimate the magnitude of changes in drug-target binding based on antibiotic dose-response curves. We experimentally demonstrate that changes in drug-target binding can be predicted from antibiotic dose-response curves with 92-94 % accuracy by exposing bacteria overexpressing target molecules to ciprofloxacin. To test the generality of COMBAT, we apply it to a different antibiotic class, the beta-lactam ampicillin, and can again predict binding parameters from dose-response curves with 90 % accuracy. We then apply COMBAT to predict antibiotic concentrations that can select for resistance due to novel resistance mutations.Our goal here is dual: First, we address a fundamental biological question and demonstrate that drug-target binding determines bacterial response to antibiotics, although antibiotic action involves many additional effects downstream of drug-target binding. Second, we create a tool that can help accelerate drug development by predicting optimal dosing and preserve the efficacy of existing antibiotics by predicting optimal treatment for possible resistant mutants.

Transposon insertion sequencing (TIS) is a powerful approach that can be extensively applied to the genome-wide definition of loci that are required for bacterial growth under diverse conditions. However, experimental design choices and stochastic biological processes can heavily influence the results of TIS experiments and affect downstream statistical analysis. In this Opinion article, we discuss TIS experimental parameters and how these factors relate to the benefits and limitations of the various statistical frameworks that can be applied to the computational analysis of TIS data.

Source at https://doi.org/10.1073/pnas.1702077114. Supporting information at http://www.pnas.org/lookup/suppl/doi:10.1073/pnas.1702077114/-/DCSupplemental Listeria monocytogenes is a common food-borne pathogen that can disseminate from the intestine and infect multiple organs. Here, we used sequence tag-based analysis of microbial populations (STAMP) to investigate L. monocytogenes population dynamics during infection. We created a genetically barcoded library of murinized L. monocytogenes and then used deep sequencing to track the pathogen’s dissemination routes and quantify its founding population (Nb) sizes in different organs. We found that the pathogen disseminates from the gastrointestinal tract to distal sites through multiple independent routes and that Nb sizes vary greatly among tissues, indicative of diverse host barriers to infection. Unexpectedly, comparative analyses of sequence tags revealed that fecally excreted organisms are largely derived from the very small number of L. monocytogenes cells that colonize the gallbladder. Immune depletion studies suggest that distinct innate immune cells restrict the pathogen’s capacity to establish replicative niches in the spleen and liver. Finally, studies in germ-free mice suggest that the microbiota plays a critical role in the development of the splenic, but not the hepatic, barriers that prevent L. monocytogenes from seeding these organs. Collectively, these observations illustrate the potency of the STAMP approach to decipher the impact of host factors on population dynamics of pathogens during infection.

Vibrio parahaemolyticus is the most common cause of seafood-borne gastroenteritis worldwide and a blight on global aquaculture. This organism requires a horizontally acquired type III secretion system (T3SS2) to infect the small intestine, but knowledge of additional factors that underlie V. parahaemolyticus pathogenicity is limited. We used transposon-insertion sequencing to screen for genes that contribute to viability of V. parahaemolyticus in vitro and in the mammalian intestine. Our analysis enumerated and controlled for the host infection bottleneck, enabling robust assessment of genetic contributions to in vivo fitness. We identified genes that contribute to V. parahaemolyticus colonization of the intestine independent of known virulence mechanisms in addition to uncharacterized components of T3SS2. Our study revealed that toxR, an ancestral locus in Vibrio species, is required for V. parahaemolyticus fitness in vivo and for induction of T3SS2 gene expression. The regulatory mechanism by which V. parahaemolyticus ToxR activates expression of T3SS2 resembles Vibrio cholerae ToxR regulation of distinct virulence elements acquired via lateral gene transfer. Thus, disparate horizontally acquired virulence systems have been placed under the control of this ancestral transcription factor across independently evolved human pathogens.

In Caulobacter crescentus, phosphorylation of key regulators is coordinated with the second messenger cyclic di-GMP to drive cell-cycle progression and differentiation. The diguanylate cyclase PleD directs pole morphogenesis, while the c-di-GMP effector PopA initiates degradation of the replication inhibitor CtrA by the AAA+ protease ClpXP to license S phase entry. Here, we establish a direct link between PleD and PopA reliant on the phosphodiesterase PdeA and the diguanylate cyclase DgcB. PdeA antagonizes DgcB activity until the G1-S transition, when PdeA is degraded by the ClpXP protease. The unopposed DgcB activity, together with PleD activation, upshifts c-di-GMP to drive PopA-dependent CtrA degradation and S phase entry. PdeA degradation requires CpdR, a response regulator that delivers PdeA to the ClpXP protease in a phosphorylation-dependent manner. Thus, CpdR serves as a crucial link between phosphorylation pathways and c-di-GMP metabolism to mediate protein degradation events that irreversibly and coordinately drive bacterial cell-cycle progression and development.

Second messengers control a wide range of important cellular functions in eukaryotes and prokaryotes. Here we show that cyclic di-GMP, a global bacterial second messenger, promotes cell cycle progression in Caulobacter crescentus by mediating the specific degradation of the replication initiation inhibitor CtrA. During the G1-to-S-phase transition, both CtrA and its cognate protease ClpXP dynamically localize to the old cell pole, where CtrA is rapidly degraded. Sequestration of CtrA to the cell pole depends on PopA, a newly identified cyclic di-GMP effector protein. PopA itself localizes to the cell pole and directs CtrA to this subcellular site via the direct interaction with a mediator protein, RcdA. We present evidence that c-di-GMP regulates CtrA degradation during the cell cycle by controlling the dynamic sequestration of the PopA recruitment factor to the cell pole. Furthermore, we show that cell cycle timing of CtrA degradation relies on converging pathways responsible for substrate and protease localization to the old cell pole. This is the first report that links cyclic di-GMP to protein dynamics and cell cycle control in bacteria.

Activity-based protein profiling (ABPP) is a chemoproteomic tool for detecting active enzymes in complex biological systems. We used ABPP to identify secreted bacterial and host serine hydrolases that are active in animals infected with the cholera pathogen Vibrio cholerae. Four V. cholerae proteases were consistently active in infected rabbits, and one, VC0157 (renamed IvaP), was also active in human choleric stool. Inactivation of IvaP influenced the activity of other secreted V. cholerae and rabbit enzymes in vivo, and genetic disruption of all four proteases increased the abundance of intelectin, an intestinal lectin, and its binding to V. cholerae in infected rabbits. Intelectin also bound to other enteric bacterial pathogens, suggesting that it may constitute a previously unrecognized mechanism of bacterial surveillance in the intestine that is inhibited by pathogen-secreted proteases. Our work demonstrates the power of activity-based proteomics to reveal host-pathogen enzymatic dialog in an animal model of infection.

Finding optimal dosing strategies for treating bacterial infections is extremely difficult, and improving therapy requires costly and time-intensive experiments. To date, an incomplete mechanistic understanding of drug effects has limited our ability to make accurate quantitative predictions of drug-mediated bacterial killing and impeded the rational design of antibiotic treatment strategies. Three poorly understood phenomena complicate predictions of antibiotic activity: post-antibiotic growth suppression, density-dependent antibiotic effects, and persister cell formation. We show that chemical binding kinetics alone are sufficient to explain these three phenomena, using single-cell data and time-kill curves of Escherichia coli and Vibrio cholerae exposed to a variety of antibiotics in combination with a theoretical model that links chemical reaction kinetics to bacterial population biology. Our model reproduces existing observations, has a high predictive power across different experimental setups ( R 2 = 0.86), and makes several testable predictions, which we verified in new experiments and by analyzing published data from a clinical trial on tuberculosis therapy. Although a variety of biological mechanisms have previously been invoked to explain post-antibiotic growth suppression, density-dependent antibiotic effects, and especially persister cell formation, our findings reveal that a simple model that considers only binding kinetics provides a parsimonious and unifying explanation for these three complex, phenotypically distinct behaviours. Current antibiotic and other chemotherapeutic regimens are often based on trial and error or expert opinion. Our “chemical reaction kinetics”–based approach may inform new strategies, which are based on rational design.

Fundamental to all living organisms is the capacity to coordinate cell division and cell differentiation to generate appropriate numbers of specialized cells. Whereas eukaryotes use cyclins and cyclin depend ent kinases to balance division with cell fate decisions1 equivalent regulatory systems have not been described in bacteria. Moreover the mechanisms used by bacteria to tune division in line with devel opmental programs are poorly understood. Here we show that Caulobacter crescentus a bacterium with an asymmetric division cycle uses oscillating levels of the second messenger cyclic diguany late (c di GMP) to drive its cell cycle. We demonstrate that c di GMP directly binds to the essential cell cycle kinase CckA to inhibit kinase activity and stimulate phosphatase activity. An upshift of c di GMP during the G1–S transition switches CckA from the kinase to the phosphatase mode thereby allowing replication initiation and cell cycle progression. Finally we show that during division c di GMP imposes spatial control on CckA to install the replication asymmetry of future daughter cells. These studies reveal c di GMP to be a cyclin like molecule in bacteria that coordinates chromosome replication with cell morphogenesis in Caulobacter. The observation that c di GMP mediated control is conserved in the plant pathogen Agrobacterium tumefaciens suggests a general mechanism through which this global regulator of bacterial virulence and persistence coordinates behaviour and cell proliferation.

We describe sequence tag-based analysis of microbial populations (STAMP) for characterization of pathogen population dynamics during infection. STAMP analyzes the frequency changes of genetically 'barcoded' organisms to quantify population bottlenecks and infer the founding population size. Analyses of intraintestinal Vibrio cholerae revealed infection-stage and region-specific host barriers to infection and showed unexpected V. cholerae migration counter to intestinal flow. STAMP provides a robust, widely applicable analytical framework for high-confidence characterization of in vivo microbial dissemination.

This chapter summarizes the current knowledge of cyclic di-GMP (c-di-GMP)-mediated control in Caulobacter crescentus. Several members of this family dynamically position to distinct polar sites during the C. crescentus cell cycle, where they contribute to the temporal and spatial regulation of pole morphogenesis and cell cycle progression. The finding that C. crescentus pole development is regulated by c-di-GMP raised several important questions. Recent in vitro and in vivo studies provided convincing evidence that DivK acts as an allosteric regulator of PleC kinase activity. The primary function of the complex regulatory mechanism responsible for cell cycle-dependent PleD phosphorylation is to limit PleD diguanylate cyclase (DGC) activity to the sessile stalked (ST) cell and exclude it from the motile swarmer (SW) cell. The wide range of different cellular processes and molecular targets that are regulated by c-di-GMP reflects its remarkable versatility as a signaling device. Recently, cell cycle control and regulated proteolysis have been added to this growing list of cellular functions controlled by c-di-GMP. The C. crescentus cell cycle is controlled by a cascade of four master regulators that are activated sequentially and in a hierarchical manner. The molecular and cellular mechanisms that underlie the characteristic behavior of Caulobacter cells and its regulation by c-di-GMP might thus be of general relevance for the understanding of processes involved in the motile-sessile transition in many other bacteria.

Zinc-finger domain transcriptional regulators regulate a myriad of functions in eukaryotes. Interestingly, ancestral versions (MucR) from Alpha-proteobacteria control bacterial virulence/symbiosis. Whether virulence regulators can also control cell cycle transcription is unknown. Here we report that MucR proteins implement a hitherto elusive primordial S→G1 transcriptional switch. After charting G1-specific promoters in the cell cycle model Caulobacter crescentus by comparative ChIP-seq, we use one such promoter as genetic proxy to unearth two MucR paralogs, MucR1/2, as constituents of a quadripartite and homeostatic regulatory module directing the S→G1 transcriptional switch. Surprisingly, MucR orthologues that regulate virulence and symbiosis gene transcription in Brucella, Agrobacterium or Sinorhizobium support this S→G1 switch in Caulobacter. Pan-genomic ChIP-seq analyses in Sinorhizobium and Caulobacter show that this module indeed targets orthologous genes. We propose that MucR proteins and possibly other virulence regulators primarily control bacterial cell cycle (G1-phase) transcription, rendering expression of target (virulence) genes periodic and in tune with the cell cycle., The bacterium Caulobacter crescentus divides asymmetrically to generate a replicative stalk cell and a quiescent swarmer cell. Fumeaux et al. show that MucR zinc-finger transcription factors, which regulate virulence in other species, also control re-entry into quiescence in Caulobacter.

Nat. Chem. Biol. 12, 268–274 (2016); published online 22 February 2016; corrected after print 23 March 2016 Within the Discussion section, one instance referring to the published crystal structure of trimeric human intelectin-1 was attributed to reference 47 instead of the correct reference 44. The error has been corrected in the HTML and PDF versions of the article.

SummaryThe two-component phosphorylation network is of critical importance for bacterial growth and physiology. Here, we address plasticity and interconnection of distinct signal transduction pathways within this network. In Caulobacter crescentus antagonistic activities of the PleC phosphatase and DivJ kinase localized at opposite cell poles control the phosphorylation state and subcellular localization of the cell fate determinator protein DivK. We show that DivK functions as an allosteric regulator that switches PleC from a phosphatase into an autokinase state and thereby mediates a cyclic di-GMP-dependent morphogenetic program. Through allosteric activation of the DivJ autokinase, DivK also stimulates its own phosphorylation and polar localization. These data suggest that DivK is the central effector of an integrated circuit that operates via spatially organized feedback loops to control asymmetry and cell fate determination in C. crescentus. Thus, single domain response regulators can facilitate crosstalk, feedback control, and long-range communication among members of the two-component network.

Diguanylate cyclases (DGCs) are key enzymes of second messenger signaling in bacteria. Their activity is responsible for the condensation of two GTP molecules into the signaling compound cyclic di-GMP. Despite their importance and abundance in bacteria, catalytic and regulatory mechanisms of this class of enzymes are poorly understood. In particular, it is not clear if oligomerization is required for catalysis and if it represents a level for activity control. To address this question we perform in vitro and in vivo analysis of the Caulobacter crescentus diguanylate cyclase PleD. PleD is a member of the response regulator family with two N-terminal receiver domains and a C-terminal diguanylate cyclase output domain. PleD is activated by phosphorylation but the structural changes inflicted upon activation of PleD are unknown. We show that PleD can be specifically activated by beryllium fluoride in vitro, resulting in dimerization and c-di-GMP synthesis. Cross-linking and fractionation experiments demonstrated that the DGC activity of PleD is contained entirely within the dimer fraction, confirming that the dimer represents the enzymatically active state of PleD. In contrast to the catalytic activity, allosteric feedback regulation of PleD is not affected by the activation status of the protein, indicating that activation by dimerization and product inhibition represent independent layers of DGC control. Finally, we present evidence that dimerization also serves to sequester activated PleD to the differentiating Caulobacter cell pole, implicating protein oligomerization in spatial control and providing a molecular explanation for the coupling of PleD activation and subcellular localization.

Vibrio cholerae is the agent of cholera, a potentially lethal diarrheal disease that remains a significant threat to populations in developing nations. The infant rabbit model of cholera is the only non-surgical small animal model system that closely mimics human cholera. Following oro-gastric inoculation, V. cholerae colonizes the intestines of infant rabbits, and the animals develop severe cholera-like diarrhea. In this unit, we provide a detailed description of the preparation of the V. cholerae inoculum, the inoculation process and the collection and processing of tissue samples. This infection model is useful for studies of V. cholerae factors and mechanisms that promote its intestinal colonization and enterotoxicity, as well as the host response to infection. The infant rabbit model of cholera enables investigations that will further our understanding of the pathophysiology of cholera and provides a platform for testing new therapeutics.

Transposon-insertion sequencing (TIS) is a powerful approach for deciphering genetic requirements for bacterial growth in different conditions, as it enables simultaneous genome-wide analysis of the fitness of thousands of mutants. However, current methods for comparative analysis of TIS data do not adjust for stochastic experimental variation between datasets and are limited to interrogation of annotated genomic elements. Here, we present ARTIST, an accessible TIS analysis pipeline for identifying essential regions that are required for growth under optimal conditions as well as conditionally essential loci that participate in survival only under specific conditions. ARTIST uses simulation-based normalization to model and compensate for experimental noise, and thereby enhances the statistical power in conditional TIS analyses. ARTIST also employs a novel adaptation of the hidden Markov model to generate statistically robust, high-resolution, annotation-independent maps of fitness-linked loci across the entire genome. Using ARTIST, we sensitively and comprehensively define Mycobacterium tuberculosis and Vibrio cholerae loci required for host infection while limiting inclusion of false positive loci. ARTIST is applicable to a broad range of organisms and will facilitate TIS-based dissection of pathways required for microbial growth and survival under a multitude of conditions., Author Summary Transposon insertion sequencing (TIS) is a powerful method that couples high-density transposon mutagenesis with next-generation sequencing to comprehensively assess the fitness of thousands of transposon mutants across a genome. TIS is an extremely flexible technique that has been used to define genomic loci required for bacterial growth and survival in a variety of species and in many different growth conditions, including during host infection. However, there remain several important limitations to current TIS analysis methods. First, TIS data are not routinely normalized for the impact of experimental variability; second, most analyses are restricted to annotated loci and do not completely exploit the richness of TIS datasets; finally, TIS analysis methods are not easily accessible to most biologists. Here we present a pipeline—ARTIST—that addresses these issues and will transform TIS-based studies. We used ARTIST to conduct robust analyses of Mycobacterium tuberculosis and Vibrio cholerae in vivo TIS datasets and comprehensively defined the genetic requirements of these pathogens for host infection. The ARTIST pipeline will make TIS analysis accessible to many researchers and greatly enhance the rigor of and insights gained from TIS studies in a wide range of microorganisms.