A single step three-strain in vivo Gateway reaction

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

Cycling Empirical Antibiotic Therapy in Hospitals: Meta-Analysis and Models

The rise of resistance together with the shortage of new broad-spectrum antibiotics underlines the urgency of optimizing the use of available drugs to minimize disease burden. Theoretical studies suggest that coordinating empirical usage of antibiotics in a hospital ward can contain the spread of resistance. However, theoretical and clinical studies came to different conclusions regarding the usefulness of rotating first-line therapy (cycling). Here, we performed a quantitative pathogen-specific meta-analysis of clinical studies comparing cycling to standard practice. We searched PubMed and Google Scholar and identified 46 clinical studies addressing the effect of cycling on nosocomial infections, of which 11 met our selection criteria. We employed a method for multivariate meta-analysis using incidence rates as endpoints and find that cycling reduced the incidence rate/1000 patient days of both total infections by 4.95 [9.43–0.48] and resistant infections by 7.2 [14.00–0.44]. This positive effect was observed in most pathogens despite a large variance between individual species. Our findings remain robust in uni- and multivariate metaregressions. We used theoretical models that reflect various infections and hospital settings to compare cycling to random assignment to different drugs (mixing). We make the realistic assumption that therapy is changed when first line treatment is ineffective, which we call “adjustable cycling/mixing”. In concordance with earlier theoretical studies, we find that in strict regimens, cycling is detrimental. However, in adjustable regimens single resistance is suppressed and cycling is successful in most settings. Both a meta-regression and our theoretical model indicate that “adjustable cycling” is especially useful to suppress emergence of multiple resistance. While our model predicts that cycling periods of one month perform well, we expect that too long cycling periods are detrimental. Our results suggest that “adjustable cycling” suppresses multiple resistance and warrants further investigations that allow comparing various diseases and hospital settings

Mechanisms of antibiotic action shape the fitness landscapes of resistance mutations

Antibiotic-resistant pathogens are a major public health threat. A deeper understanding of how an antibiotic’s mechanism of action influences the emergence of resistance would aid in the design of new drugs and help to preserve the effectiveness of existing ones. To this end, we developed a model that links bacterial population dynamics with antibiotic-target binding kinetics. Our approach allows us to derive mechanistic insights on drug activity from population-scale experimental data and to quantify the interplay between drug mechanism and resistance selection. We find that both bacteriostatic and bactericidal agents can be equally effective at suppressing the selection of resistant mutants, but that key determinants of resistance selection are the relationships between the number of drug-inactivated targets within a cell and the rates of cellular growth and death. We also show that heterogeneous drug-target binding within a population enables resistant bacteria to evolve fitness-improving secondary mutations even when drug doses remain above the resistant strain’s minimum inhibitory concentration. Our work suggests that antibiotic doses beyond this ‘‘secondary mutation selection window” could safeguard against the emergence of high-fitness resistant strains during treatment

Sequence tag–based analysis of microbial population dynamics

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

ARTIST: High-Resolution Genome-Wide Assessment of Fitness Using Transposon-Insertion Sequencing

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

Analysis of the c-di-GMP mediated cell fate determination in Caulobacter crescentus

Cyclic-di-GMP (c-di-GMP) is a ubiquitous second messenger in bacteria, which has been recognized as a key regulator, antagonistically controlling the transition between motile, planktonic cells and surface attached, multicellular communities. The biosynthesis and degradation of c-di-GMP are mediated by the opposing enzymatic activities of di-guanylate cyclases (DGCs) and phosphodiesterases (PDEs), generally in response to internal and environmental signals. These activities reside in GGDEF and EAL domains respectively, which represent two large families of output domains often found in bacterial one- and twocomponent systems. In this work, the cell cycle-embedded differentiation from a free-living, motile swarmer cell into a sessile stalked cell in the model organism Caulobacter crescentus, and the role of c-di-GMP in this process was investigated. A systematic analysis was used to identify key regulatory enzymes involved in c-di-GMP metabolism that influence this developmental process. The function and regulation of these genes was then examined. One component that has already been implicated in this process, the DGC PleD, was investigated in more detail, with special emphasis on the mechanisms underlying its timed activation and cell cycle specific subcellular localisation. In the first part of this work, a systematic functional analysis of all GGDEF, EAL and GGDEF/EAL composite proteins from C. crescentus with a focus on motility and surface attachment is described. In this screen, the phosphodiesterase PdeA was identified as a gatekeeper that prevents premature paralysis of the flagellum and holdfast synthesis in the C. crescentus swarmer cell. It is shown that PdeA, together with its antagonistic DGCs DgcB and PleD, are components of converging pathways and orchestrate polar development during the swarmer-to-stalked cell transition. Furthermore, evidence is presented for a proteolytic regulation mechanism for PdeA. Secondly, the PleD localisation factor CC1064 is analysed. This transmembrane protein has pleiotropic effects on motility, surface attachment and polar localisation of PleD. It is shown that the motility and PleD localisation phenotypes of a Δcc1064 strain are conditional and depend on environmental factors such as oxygen and temperature stress. Moreover, evidence is presented that the impaired motility of a Δcc1064 mutant is caused by an assembly defect of the motor proteins MotA and MotB, leading to paralysis of the flagellum. A model is suggested that links altered membrane composition under environmental stress conditions to the Δcc1064 phenotypes. In Paul, Abel et al. (2007), insights were gained into the regulation of PleD. In addition to the well characterised non-competitive feedback inhibition, a second independent layer of activity control via dimerisation was investigated. The response regulator PleD is activated by phosphorylation of the N-terminal receiver domain. Here we show that the phospho-mimetic chemical beryllium fluoride specifically activates the enzymatic activity of PleD in vitro and in addition leads to dimerisation. Fractionation experiments showed that the DGC activity exclusively resides within the dimer fraction. Finally, evidence is provided that dimerisation of PleD is not only required for catalytic activity, but also leads to sequestration to the differentiating stalked pole of the C. crescentus cell, thereby providing an elegant way of restricting PleD activity to a subcellular region of the cell. In Paul, Jaeger & Abel et al. (2008), a network of proteins belonging to the two component system that regulates PleD activation and thereby leads to its localisation were investigated in detail. The single domain response regulator DivK is controlled by the phosphatase activity of PleC and the kinase DivJ. It is shown that DivK allosterically activates the kinase activities of PleC and DivJ and thereby switches PleC from a phosphatase into a kinase state. Increased DivJ activity further activates DivK in a feed-forward loop, while PleC and DivJ together stimulate PleD activity and localisation. Evidence is provided that DivJ, PleC, and DivK colocalise in a short time window during the cell cycle, directly prior to PleD activation, suggesting a role for the spatial distribution of these proteins. At last, the wider role of single domain response regulators in the interconnection of two-component signal transduction circuits is discussed. Finally, in Dürig, Folcher, Abel et al. (2008), a role for c-di-GMP in the cell cycle of C. crescentus via regulation of targeted proteolysis of the regulator CtrA is shown. During the swarmer-to-stalked cell transition CtrA is recruited to the incipient stalked pole, where it is degraded by its protease ClpXP. This recruitment and subsequent degradation is dependent on the enzymatically inactive GGDEF domain protein PopA. PopA itself localises to the cell pole and can bind c-di-GMP. It is shown that mutants in the c-di-GMP binding site fail to localise to the developing stalked pole and consequently fail to promote CtrA degradation. Finally, evidence is provided that interconnects PopA with the pathway responsible for substrate inactivation and protease localisation in a cell cycle dependent manner

Selection or drift: The population biology underlying transposon insertion sequencing experiments

Transposon insertion sequencing methods such as Tn-seq revolutionized microbiology by allowing the identification of genomic loci that are critical for viability in a specific environment on a genome-wide scale. While powerful, transposon insertion sequencing suffers from limited reproducibility when different analysis methods are compared. From the perspective of population biology, this may be explained by changes in mutant frequency due to chance (drift) rather than differential fitness (selection). Here, we develop a mathematical model of the population biology of transposon insertion sequencing experiments, i.e. the changes in size and composition of the transposon-mutagenized population during the experiment. We use this model to investigate mutagenesis, the growth of the mutant library, and its passage through bottlenecks. Specifically, we study how these processes can lead to extinction of individual mutants depending on their fitness and the distribution of fitness effects (DFE) of the entire mutant population. We find that in typical in vitro experiments few mutants with high fitness go extinct. However, bottlenecks of a size that is common in animal infection models lead to so much random extinction that a large number of viable mutants would be misclassified. While mutants with low fitness are more likely to be lost during the experiment, mutants with intermediate fitness are expected to be much more abundant and can constitute a large proportion of detected hits, i.e. false positives. Thus, incorporating the DFEs of randomly generated mutations in the analysis may improve the reproducibility of transposon insertion experiments, especially when strong bottlenecks are encountered

Reaction Kinetic Models of Antibiotic Heteroresistance

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’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

The Infectious Dose Shapes Vibrio Cholerae Within-Host Dynamics

During infection, the rates of pathogen replication, death, and migration affect disease progression, dissemination, transmission, and resistance evolution. Here, we follow the population dynamics of Vibrio cholerae in a mouse model by labeling individual bacteria with one of >500 unique, fitness-neutral genomic tags. Using the changes in tag frequencies and CFU numbers, we inform a mathematical model that describes the within-host spatiotemporal bacterial dynamics. This allows us to disentangle growth, death, forward, and retrograde migration rates continuously during infection. Our model has robust predictive power across various experimental setups. The population dynamics of V. cholerae shows substantial spatiotemporal heterogeneity in replication, death, and migration. Importantly, we find that the niche available to V. cholerae in the host increases with inoculum size, suggesting cooperative effects during infection. Therefore, it is not enough to consider just the likelihood of exposure (50% infectious dose) but rather the magnitude of exposure to predict outbreaks