High Wolbachia density correlates with cost of infection for insecticide resistant Culex pipiens mosquitoes. - Related Documents




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898501.0000High Wolbachia density correlates with cost of infection for insecticide resistant Culex pipiens mosquitoes. In the mosquito Culex pipiens, insecticide resistance genes alter many life-history traits and incur a fitness cost. Resistance to organophosphate insecticides involves two loci, with each locus coding for a different mechanism of resistance (degradation vs. insensitivity to insecticides). The density of intracellular Wolbachia bacteria has been found to be higher in resistant mosquitoes, regardless of the mechanism involved. To discriminate between costs of resistance due to resistance genes from those associated with elevated Wolbachia densities, we compared strains of mosquito sharing the same genetic background but differing in their resistance alleles and Wolbachia infection status. Life-history traits measured included strength of insecticide resistance, larval mortality, adult female size, fecundity, predation avoidance, mating competition, and strength of cytoplasmic incompatibility (CI). We found that: (1) when Wolbachia are removed, insecticide resistance genes still affect some life-history traits; (2) Wolbachia are capable of modifying the cost of resistance; (3) the cost of Wolbachia infections increases with their density; (4) different interactions occurred depending on the resistance alleles involved; and (5) high densities of Wolbachia do not increase the strength of CI or maternal transmission efficiency relative to low Wolbachia densities. Insecticide resistance genes generated variation in the costs of Wolbachia infections and provided an interesting opportunity to study how these costs evolve, a process generally operating when Wolbachia colonizes a new host.200616610322
961210.9994Using experimental evolution to explore natural patterns between bacterial motility and resistance to bacteriophages. Resistance of bacteria to phages may be gained by alteration of surface proteins to which phages bind, a mechanism that is likely to be costly as these molecules typically have critical functions such as movement or nutrient uptake. To address this potential trade-off, we combine a systematic study of natural bacteria and phage populations with an experimental evolution approach. We compare motility, growth rate and susceptibility to local phages for 80 bacteria isolated from horse chestnut leaves and, contrary to expectation, find no negative association between resistance to phages and bacterial motility or growth rate. However, because correlational patterns (and their absence) are open to numerous interpretations, we test for any causal association between resistance to phages and bacterial motility using experimental evolution of a subset of bacteria in both the presence and absence of naturally associated phages. Again, we find no clear link between the acquisition of resistance and bacterial motility, suggesting that for these natural bacterial populations, phage-mediated selection is unlikely to shape bacterial motility, a key fitness trait for many bacteria in the phyllosphere. The agreement between the observed natural pattern and the experimental evolution results presented here demonstrates the power of this combined approach for testing evolutionary trade-offs.201121509046
898620.9994Gene expression in Lucilia sericata (Diptera: Calliphoridae) larvae exposed to Pseudomonas aeruginosa and Acinetobacter baumannii identifies shared and microbe-specific induction of immune genes. Antibiotic resistance is a continuing challenge in medicine. There are various strategies for expanding antibiotic therapeutic repertoires, including the use of blow flies. Their larvae exhibit strong antibiotic and antibiofilm properties that alter microbiome communities. One species, Lucilia sericata, is used to treat problematic wounds due to its debridement capabilities and its excretions and secretions that kill some pathogenic bacteria. There is much to be learned about how L. sericata interacts with microbiomes at the molecular level. To address this deficiency, gene expression was assessed after feeding exposure (1 h or 4 h) to two clinically problematic pathogens: Pseudomonas aeruginosa and Acinetobacter baumannii. The results identified immunity-related genes that were differentially expressed when exposed to these pathogens, as well as non-immune genes possibly involved in gut responses to bacterial infection. There was a greater response to P. aeruginosa that increased over time, while few genes responded to A. baumannii exposure, and expression was not time-dependent. The response to feeding on pathogens indicates a few common responses and features distinct to each pathogen, which is useful in improving the wound debridement therapy and helps to develop biomimetic alternatives.202234613655
938130.9994Cross-resistance is modular in bacteria-phage interactions. Phages shape the structure of natural bacterial communities and can be effective therapeutic agents. Bacterial resistance to phage infection, however, limits the usefulness of phage therapies and could destabilise community structures, especially if individual resistance mutations provide cross-resistance against multiple phages. We currently understand very little about the evolution of cross-resistance in bacteria-phage interactions. Here we show that the network structure of cross-resistance among spontaneous resistance mutants of Pseudomonas aeruginosa evolved against each of 27 phages is highly modular. The cross-resistance network contained both symmetric (reciprocal) and asymmetric (nonreciprocal) cross-resistance, forming two cross-resistance modules defined by high within- but low between-module cross-resistance. Mutations conferring cross-resistance within modules targeted either lipopolysaccharide or type IV pilus biosynthesis, suggesting that the modularity of cross-resistance was structured by distinct phage receptors. In contrast, between-module cross-resistance was provided by mutations affecting the alternative sigma factor, RpoN, which controls many lifestyle-associated functions, including motility, biofilm formation, and quorum sensing. Broader cross-resistance range was not associated with higher fitness costs or weaker resistance against the focal phage used to select resistance. However, mutations in rpoN, providing between-module cross-resistance, were associated with higher fitness costs than mutations associated with within-module cross-resistance, i.e., in genes encoding either lipopolysaccharide or type IV pilus biosynthesis. The observed structure of cross-resistance predicted both the frequency of resistance mutations and the ability of phage combinations to suppress bacterial growth. These findings suggest that the evolution of cross-resistance is common, is likely to play an important role in the dynamic structure of bacteria-phage communities, and could inform the design principles for phage therapy treatments.201830281587
938040.9994Coevolution between marine Aeromonas and phages reveals temporal trade-off patterns of phage resistance and host population fitness. Coevolution of bacteria and phages is an important host and parasite dynamic in marine ecosystems, contributing to the understanding of bacterial community diversity. On the time scale, questions remain concerning what is the difference between phage resistance patterns in marine bacteria and how advantageous mutations gradually accumulate during coevolution. In this study, marine Aeromonas was co-cultured with its phage for 180 days and their genetic and phenotypic dynamics were measured every 30 days. We identified 11 phage resistance genes and classified them into three categories: lipopolysaccharide (LPS), outer membrane protein (OMP), and two-component system (TCS). LPS shortening and OMP mutations are two distinct modes of complete phage resistance, while TCS mutants mediate incomplete resistance by repressing the transcription of phage genes. The co-mutation of LPS and OMP was a major mode for bacterial resistance at a low cost. The mutations led to significant reductions in the growth and virulence of bacterial populations during the first 60 days of coevolution, with subsequent leveling off. Our findings reveal the marine bacterial community dynamics and evolutionary trade-offs of phage resistance during coevolution, thus granting further understanding of the interaction of marine microbes.202337814126
892750.9994Changes in Intrinsic Antibiotic Susceptibility during a Long-Term Evolution Experiment with Escherichia coli. High-level resistance often evolves when populations of bacteria are exposed to antibiotics, by either mutations or horizontally acquired genes. There is also variation in the intrinsic resistance levels of different bacterial strains and species that is not associated with any known history of exposure. In many cases, evolved resistance is costly to the bacteria, such that resistant types have lower fitness than their progenitors in the absence of antibiotics. Some longer-term studies have shown that bacteria often evolve compensatory changes that overcome these tradeoffs, but even those studies have typically lasted only a few hundred generations. In this study, we examine changes in the susceptibilities of 12 populations of Escherichia coli to 15 antibiotics after 2,000 and 50,000 generations without exposure to any antibiotic. On average, the evolved bacteria were more susceptible to most antibiotics than was their ancestor. The bacteria at 50,000 generations tended to be even more susceptible than after 2,000 generations, although most of the change occurred during the first 2,000 generations. Despite the general trend toward increased susceptibility, we saw diverse outcomes with different antibiotics. For streptomycin, which was the only drug to which the ancestral strain was highly resistant, none of the evolved lines showed any increased susceptibility. The independently evolved lineages often exhibited correlated responses to the antibiotics, with correlations usually corresponding to their modes of action. On balance, our study shows that bacteria with low levels of intrinsic resistance often evolve to become even more susceptible to antibiotics in the absence of corresponding selection.IMPORTANCE Resistance to antibiotics often evolves when bacteria encounter antibiotics. However, bacterial strains and species without any known exposure to these drugs also vary in their intrinsic susceptibility. In many cases, evolved resistance has been shown to be costly to the bacteria, such that resistant types have reduced competitiveness relative to their sensitive progenitors in the absence of antibiotics. In this study, we examined changes in the susceptibilities of 12 populations of Escherichia coli to 15 antibiotics after 2,000 and 50,000 generations without exposure to any drug. The evolved bacteria tended to become more susceptible to most antibiotics, with most of the change occurring during the first 2,000 generations, when the bacteria were undergoing rapid adaptation to their experimental conditions. On balance, our findings indicate that bacteria with low levels of intrinsic resistance can, in the absence of relevant selection, become even more susceptible to antibiotics.201930837336
841460.9994Patterns of Piscirickettsia salmonis load in susceptible and resistant families of Salmo salar. The pathogen Piscirickettsia salmonis produces a systemic aggressive infection that involves several organs and tissues in salmonids. In spite of the great economic losses caused by this pathogen in the Atlantic salmon (Salmo salar) industry, very little is known about the resistance mechanisms of the host to this pathogen. In this paper, for the first time, we aimed to identify the bacterial load in head kidney and muscle of Atlantic salmon exhibiting differential familiar mortality. Furthermore, in order to assess the patterns of gene expression of immune related genes in susceptible and resistant families, a set of candidate genes was evaluated using deep sequencing of the transcriptome. The results showed that the bacterial load was significantly lower in resistant fish, when compared with the susceptible individuals. Based on the candidate genes analysis, we infer that the resistant hosts triggered up-regulation of specific genes (such as for example the LysC), which may explain a decrease in the bacterial load in head kidney, while the susceptible fish presented an exacerbated innate response, which is unable to exert an effective response against the bacteria. Interestingly, we found a higher bacterial load in muscle when compared with head kidney. We argue that this is possible due to the availability of an additional source of iron in muscle. Besides, the results show that the resistant fish could not be a likely reservoir of the bacteria.201525862974
892370.9994The Genome-Wide Interaction Network of Nutrient Stress Genes in Escherichia coli. Conventional efforts to describe essential genes in bacteria have typically emphasized nutrient-rich growth conditions. Of note, however, are the set of genes that become essential when bacteria are grown under nutrient stress. For example, more than 100 genes become indispensable when the model bacterium Escherichia coli is grown on nutrient-limited media, and many of these nutrient stress genes have also been shown to be important for the growth of various bacterial pathogens in vivo To better understand the genetic network that underpins nutrient stress in E. coli, we performed a genome-scale cross of strains harboring deletions in some 82 nutrient stress genes with the entire E. coli gene deletion collection (Keio) to create 315,400 double deletion mutants. An analysis of the growth of the resulting strains on rich microbiological media revealed an average of 23 synthetic sick or lethal genetic interactions for each nutrient stress gene, suggesting that the network defining nutrient stress is surprisingly complex. A vast majority of these interactions involved genes of unknown function or genes of unrelated pathways. The most profound synthetic lethal interactions were between nutrient acquisition and biosynthesis. Further, the interaction map reveals remarkable metabolic robustness in E. coli through pathway redundancies. In all, the genetic interaction network provides a powerful tool to mine and identify missing links in nutrient synthesis and to further characterize genes of unknown function in E. coli Moreover, understanding of bacterial growth under nutrient stress could aid in the development of novel antibiotic discovery platforms. IMPORTANCE: With the rise of antibiotic drug resistance, there is an urgent need for new antibacterial drugs. Here, we studied a group of genes that are essential for the growth of Escherichia coli under nutrient limitation, culture conditions that arguably better represent nutrient availability during an infection than rich microbiological media. Indeed, many such nutrient stress genes are essential for infection in a variety of pathogens. Thus, the respective proteins represent a pool of potential new targets for antibacterial drugs that have been largely unexplored. We have created all possible double deletion mutants through a genetic cross of nutrient stress genes and the E. coli deletion collection. An analysis of the growth of the resulting clones on rich media revealed a robust, dense, and complex network for nutrient acquisition and biosynthesis. Importantly, our data reveal new genetic connections to guide innovative approaches for the development of new antibacterial compounds targeting bacteria under nutrient stress.201627879333
900180.9994Bacterial Methionine Metabolism Genes Influence Drosophila melanogaster Starvation Resistance. Animal-associated microorganisms (microbiota) dramatically influence the nutritional and physiological traits of their hosts. To expand our understanding of such influences, we predicted bacterial genes that influence a quantitative animal trait by a comparative genomic approach, and we extended these predictions via mutant analysis. We focused on Drosophila melanogaster starvation resistance (SR). We first confirmed that D. melanogaster SR responds to the microbiota by demonstrating that bacterium-free flies have greater SR than flies bearing a standard 5-species microbial community, and we extended this analysis by revealing the species-specific influences of 38 genome-sequenced bacterial species on D. melanogaster SR. A subsequent metagenome-wide association analysis predicted bacterial genes with potential influence on D. melanogaster SR, among which were significant enrichments in bacterial genes for the metabolism of sulfur-containing amino acids and B vitamins. Dietary supplementation experiments established that the addition of methionine, but not B vitamins, to the diets significantly lowered D. melanogaster SR in a way that was additive, but not interactive, with the microbiota. A direct role for bacterial methionine metabolism genes in D. melanogaster SR was subsequently confirmed by analysis of flies that were reared individually with distinct methionine cycle Escherichia coli mutants. The correlated responses of D. melanogaster SR to bacterial methionine metabolism mutants and dietary modification are consistent with the established finding that bacteria can influence fly phenotypes through dietary modification, although we do not provide explicit evidence of this conclusion. Taken together, this work reveals that D. melanogaster SR is a microbiota-responsive trait, and specific bacterial genes underlie these influences.IMPORTANCE Extending descriptive studies of animal-associated microorganisms (microbiota) to define causal mechanistic bases for their influence on animal traits is an emerging imperative. In this study, we reveal that D. melanogaster starvation resistance (SR), a model quantitative trait in animal genetics, responds to the presence and identity of the microbiota. Using a predictive analysis, we reveal that the amino acid methionine has a key influence on D. melanogaster SR and show that bacterial methionine metabolism mutants alter normal patterns of SR in flies bearing the bacteria. Our data further suggest that these effects are additive, and we propose the untested hypothesis that, similar to bacterial effects on fruit fly triacylglyceride deposition, the bacterial influence may be through dietary modification. Together, these findings expand our understanding of the bacterial genetic basis for influence on a nutritionally relevant trait of a model animal host.201829934334
900790.9994Genes involved in copper resistance influence survival of Pseudomonas aeruginosa on copper surfaces. AIMS: To evaluate the killing of Pseudomonas aeruginosa PAO1 on copper cast alloys and the influence of genes on survival on copper containing medium and surfaces. METHODS AND RESULTS: Different strains of P. aeruginosa were inoculated on copper containing medium or different copper cast alloys and the survival rate determined. The survival rates were compared with rates on copper-free medium and stainless steel as control. In addition, the effect of temperature on survival was examined. CONCLUSIONS: Copper cast alloys had been previously shown to be bactericidal to various bacteria, but the mechanism of copper-mediated killing is still not known. In this report, we demonstrate that P. aeruginosa PAO1 is rapidly killed on different copper cast alloys and that genes involved in conferring copper resistance in copper-containing medium also influenced survival on copper cast alloys. We also show that the rate of killing is influenced by temperature. SIGNIFICANCE AND IMPACT OF THE STUDY: To use copper surfaces more widely as bactericidal agents in various settings, it is important to understand how genes influence survival on these surfaces. Here we show that genes shown to be involved in copper resistance in P. aeruginosa PAO1 can have an impact on the length of survival time on copper cast alloys under certain conditions. This is an important first step for evaluation of future use of copper surfaces as bactericidal agents.200919239551
9603100.9994Resistance signatures manifested in early drug response across cancer types and species. Aim: Growing evidence points to non-genetic mechanisms underlying long-term resistance to cancer therapies. These mechanisms involve pre-existing or therapy-induced transcriptional cell states that confer resistance. However, the relationship between early transcriptional responses to treatment and the eventual emergence of resistant states remains poorly understood. Furthermore, it is unclear whether such early resistance-associated transcriptional responses are evolutionarily conserved. In this study, we examine the similarity between early transcriptional responses and long-term resistant states, assess their clinical relevance, and explore their evolutionary conservation across species. Methods: We integrated datasets on early drug responses and long-term resistance from multiple cancer cell lines, bacteria, and yeast to identify early transcriptional changes predictive of long-term resistance and assess their evolutionary conservation. Using genome-wide CRISPR-Cas9 knockout screens, we evaluated the impact of genes associated with resistant transcriptional states on drug sensitivity. Clinical datasets were analyzed to explore the prognostic value of the identified resistance-associated gene signatures. Results: We found that transcriptional states observed in drug-naive cells and shortly after treatment overlapped with those seen in fully resistant populations. Some of these shared features appear to be evolutionarily conserved. Knockout of genes marking resistant states sensitized ovarian cancer cells to Prexasertib. Moreover, early resistance gene signatures effectively distinguished therapy responders from non-responders in multiple clinical cancer trials and differentiated premalignant breast lesions that progressed to malignancy from those that remained benign. Conclusion: Early cellular transcriptional responses to therapy exhibit key similarities to fully resistant states across different drugs, cancer types, and species. Gene signatures defining these early resistance states have prognostic value in clinical settings.202541019980
8919110.9994Gene expression in Pseudomonas aeruginosa biofilms. Bacteria often adopt a sessile biofilm lifestyle that is resistant to antimicrobial treatment. Opportunistic pathogenic bacteria like Pseudomonas aeruginosa can develop persistent infections. To gain insights into the differences between free-living P. aeruginosa cells and those in biofilms, and into the mechanisms underlying the resistance of biofilms to antibiotics, we used DNA microarrays. Here we show that, despite the striking differences in lifestyles, only about 1% of genes showed differential expression in the two growth modes; about 0.5% of genes were activated and about 0.5% were repressed in biofilms. Some of the regulated genes are known to affect antibiotic sensitivity of free-living P. aeruginosa. Exposure of biofilms to high levels of the antibiotic tobramycin caused differential expression of 20 genes. We propose that this response is critical for the development of biofilm resistance to tobramycin. Our results show that gene expression in biofilm cells is similar to that in free-living cells but there are a small number of significant differences. Our identification of biofilm-regulated genes points to mechanisms of biofilm resistance to antibiotics.200111677611
3810120.9994The Effect of the Presence and Absence of DNA Repair Genes on the Rate and Pattern of Mutation in Bacteria. Bacteria lose and gain repair genes as they evolve. Here, we investigate the consequences of gain and loss of 11 DNA repair genes across a broad range of bacteria. Using synonymous polymorphisms from bacteria and a set of 50 phylogenetically independent contrasts, we find no evidence that the presence or absence of these 11 genes affects either the overall level of diversity or the pattern of mutation. Using phylogenetic generalized linear squares yields a similar conclusion. It seems likely that the lack of an effect is due to variation in the genetic background and the environment which obscures any effects that the presence or absence of individual genes might have.202439376054
9378130.9994Inferring strain-level mutational drivers of phage-bacteria interaction phenotypes arising during coevolutionary dynamics. The enormous diversity of bacteriophages and their bacterial hosts presents a significant challenge to predict which phages infect a focal set of bacteria. Infection is largely determined by complementary - and largely uncharacterized - genetics of adsorption, injection, cell take-over and lysis. Here we present a machine learning approach to predict phage-bacteria interactions trained on genome sequences of and phenotypic interactions amongst 51 Escherichia coli strains and 45 phage λ strains that coevolved in laboratory conditions for 37 days. Leveraging multiple inference strategies and without a priori knowledge of driver mutations, this framework predicts both who infects whom and the quantitative levels of infections across a suite of 2,295 potential interactions. We found that the most effective approach inferred interaction phenotypes from independent contributions from phage and bacteria mutations, accurately predicting 86% of interactions while reducing the relative error in the estimated strength of the infection phenotype by 40% . Feature selection revealed key phage λ and E. coli mutations that have a significant influence on the outcome of phage-bacteria interactions, corroborating sites previously known to affect phage λ infections, as well as identifying mutations in genes of unknown function not previously shown to influence bacterial resistance. The method's success in recapitulating strain-level infection outcomes arising during coevolutionary dynamics may also help inform generalized approaches for imputing genetic drivers of interaction phenotypes in complex communities of phage and bacteria.202438260415
8926140.9994Evolution of honey resistance in experimental populations of bacteria depends on the type of honey and has no major side effects for antibiotic susceptibility. With rising antibiotic resistance, alternative treatments for communicable diseases are increasingly relevant. One possible alternative for some types of infections is honey, used in wound care since before 2000 BCE and more recently in licensed, medical-grade products. However, it is unclear whether medical application of honey results in the evolution of bacterial honey resistance and whether this has collateral effects on other bacterial traits such as antibiotic resistance. Here, we used single-step screening assays and serial transfer at increasing concentrations to isolate honey-resistant mutants of Escherichia coli. We only detected bacteria with consistently increased resistance to the honey they evolved in for two of the four tested honey products, and the observed increases were small (maximum twofold increase in IC(90)). Genomic sequencing and experiments with single-gene knockouts showed a key mechanism by which bacteria increased their honey resistance was by mutating genes involved in detoxifying methylglyoxal, which contributes to the antibacterial activity of Leptospermum honeys. Crucially, we found no evidence that honey adaptation conferred cross-resistance or collateral sensitivity against nine antibiotics from six different classes. These results reveal constraints on bacterial adaptation to different types of honey, improving our ability to predict downstream consequences of wider honey application in medicine.202134025770
8953150.9994Evolution of antibiotic resistance impacts optimal temperature and growth rate in Escherichia coli and Staphylococcus epidermidis. AIMS: Bacterial response to temperature changes can influence their pathogenicity to plants and humans. Changes in temperature can affect cellular and physiological responses in bacteria that can in turn affect the evolution and prevalence of antibiotic-resistance genes. Yet, how antibiotic-resistance genes influence microbial temperature response is poorly understood. METHODS AND RESULTS: We examined growth rates and physiological responses to temperature in two species-E. coli and Staph. epidermidis-after evolved resistance to 13 antibiotics. We found that evolved resistance results in species-, strain- and antibiotic-specific shifts in optimal temperature. When E. coli evolves resistance to nucleic acid and cell wall inhibitors, their optimal growth temperature decreases, and when Staph. epidermidis and E. coli evolve resistance to protein synthesis and their optimal temperature increases. Intriguingly, when Staph. epidermidis evolves resistance to Teicoplanin, fitness also increases in drug-free environments, independent of temperature response. CONCLUSION: Our results highlight how the complexity of antibiotic resistance is amplified when considering physiological responses to temperature. SIGNIFICANCE: Bacteria continuously respond to changing temperatures-whether through increased body temperature during fever, climate change or other factors. It is crucial to understand the interactions between antibiotic resistance and temperature.202236070219
8920160.9994A systems biology approach to drug targets in Pseudomonas aeruginosa biofilm. Antibiotic resistance is an increasing problem in the health care system and we are in a constant race with evolving bacteria. Biofilm-associated growth is thought to play a key role in bacterial adaptability and antibiotic resistance. We employed a systems biology approach to identify candidate drug targets for biofilm-associated bacteria by imitating specific microenvironments found in microbial communities associated with biofilm formation. A previously reconstructed metabolic model of Pseudomonas aeruginosa (PA) was used to study the effect of gene deletion on bacterial growth in planktonic and biofilm-like environmental conditions. A set of 26 genes essential in both conditions was identified. Moreover, these genes have no homology with any human gene. While none of these genes were essential in only one of the conditions, we found condition-dependent genes, which could be used to slow growth specifically in biofilm-associated PA. Furthermore, we performed a double gene deletion study and obtained 17 combinations consisting of 21 different genes, which were conditionally essential. While most of the difference in double essential gene sets could be explained by different medium composition found in biofilm-like and planktonic conditions, we observed a clear effect of changes in oxygen availability on the growth performance. Eight gene pairs were found to be synthetic lethal in oxygen-limited conditions. These gene sets may serve as novel metabolic drug targets to combat particularly biofilm-associated PA. Taken together, this study demonstrates that metabolic modeling of human pathogens can be used to identify oxygen-sensitive drug targets and thus, that this systems biology approach represents a powerful tool to identify novel candidate antibiotic targets.201222523548
8918170.9994Antibiotic resistance alters the ability of Pseudomonas aeruginosa to invade bacteria from the respiratory microbiome. The emergence and spread of antibiotic resistance in bacterial pathogens is a global health threat. One important unanswered question is how antibiotic resistance influences the ability of a pathogen to invade the host-associated microbiome. Here we investigate how antibiotic resistance impacts the ability of a bacterial pathogen to invade bacteria from the microbiome, using the opportunistic bacterial pathogen Pseudomonas aeruginosa and the respiratory microbiome as our model system. We measure the ability of P. aeruginosa spontaneous antibiotic-resistant mutants to invade pre-established cultures of commensal respiratory microbes in an assay that allows us to link specific resistance mutations with changes in invasion ability. While commensal respiratory microbes tend to provide some degree of resistance to P. aeruginosa invasion, antibiotic resistance is a double-edged sword that can either help or hinder the ability of P. aeruginosa to invade. The directionality of this help or hindrance depends on both P. aeruginosa genotype and respiratory microbe identity. Specific resistance mutations in genes involved in multidrug efflux pump regulation are shown to facilitate the invasion of P. aeruginosa into Staphylococcus lugdunensis, yet impair invasion into Rothia mucilaginosa and Staphylococcus epidermidis. Streptococcus species provide the strongest resistance to P. aeruginosa invasion, and this is maintained regardless of antibiotic resistance genotype. Our study demonstrates how the cost of mutations that provide enhanced antibiotic resistance in P. aeruginosa can crucially depend on community context. We suggest that attempts to manipulate the microbiome should focus on promoting the growth of commensals that can increase the fitness costs associated with antibiotic resistance and provide robust inhibition of both wildtype and antibiotic-resistant pathogen strains.202439328287
9615180.9994Persistence and resistance as complementary bacterial adaptations to antibiotics. Bacterial persistence represents a simple of phenotypic heterogeneity, whereby a proportion of cells in an isogenic bacterial population can survive exposure to lethal stresses such as antibiotics. In contrast, genetically based antibiotic resistance allows for continued growth in the presence of antibiotics. It is unclear, however, whether resistance and persistence are complementary or alternative evolutionary adaptations to antibiotics. Here, we investigate the co-evolution of resistance and persistence across the genus Pseudomonas using comparative methods that correct for phylogenetic nonindependence. We find that strains of Pseudomonas vary extensively in both their intrinsic resistance to antibiotics (ciprofloxacin and rifampicin) and persistence following exposure to these antibiotics. Crucially, we find that persistence correlates positively to antibiotic resistance across strains. However, we find that different genes control resistance and persistence implying that they are independent traits. Specifically, we find that the number of type II toxin-antitoxin systems (TAs) in the genome of a strain is correlated to persistence, but not resistance. Our study shows that persistence and antibiotic resistance are complementary, but independent, evolutionary adaptations to stress and it highlights the key role played by TAs in the evolution of persistence.201626999656
8377190.9994Genome-Wide Association Analyses in the Model Rhizobium Ensifer meliloti. Genome-wide association studies (GWAS) can identify genetic variants responsible for naturally occurring and quantitative phenotypic variation. Association studies therefore provide a powerful complement to approaches that rely on de novo mutations for characterizing gene function. Although bacteria should be amenable to GWAS, few GWAS have been conducted on bacteria, and the extent to which nonindependence among genomic variants (e.g., linkage disequilibrium [LD]) and the genetic architecture of phenotypic traits will affect GWAS performance is unclear. We apply association analyses to identify candidate genes underlying variation in 20 biochemical, growth, and symbiotic phenotypes among 153 strains of Ensifer meliloti For 11 traits, we find genotype-phenotype associations that are stronger than expected by chance, with the candidates in relatively small linkage groups, indicating that LD does not preclude resolving association candidates to relatively small genomic regions. The significant candidates show an enrichment for nucleotide polymorphisms (SNPs) over gene presence-absence variation (PAV), and for five traits, candidates are enriched in large linkage groups, a possible signature of epistasis. Many of the variants most strongly associated with symbiosis phenotypes were in genes previously identified as being involved in nitrogen fixation or nodulation. For other traits, apparently strong associations were not stronger than the range of associations detected in permuted data. In sum, our data show that GWAS in bacteria may be a powerful tool for characterizing genetic architecture and identifying genes responsible for phenotypic variation. However, careful evaluation of candidates is necessary to avoid false signals of association.IMPORTANCE Genome-wide association analyses are a powerful approach for identifying gene function. These analyses are becoming commonplace in studies of humans, domesticated animals, and crop plants but have rarely been conducted in bacteria. We applied association analyses to 20 traits measured in Ensifer meliloti, an agriculturally and ecologically important bacterium because it fixes nitrogen when in symbiosis with leguminous plants. We identified candidate alleles and gene presence-absence variants underlying variation in symbiosis traits, antibiotic resistance, and use of various carbon sources; some of these candidates are in genes previously known to affect these traits whereas others were in genes that have not been well characterized. Our results point to the potential power of association analyses in bacteria, but also to the need to carefully evaluate the potential for false associations.201830355664