# | Rank | Similarity | Title + Abs. | Year | PMID |
|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 |
| 8923 | 0 | 1.0000 | The 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. | 2016 | 27879333 |
| 8922 | 1 | 0.9999 | Transitioning from Soil to Host: Comparative Transcriptome Analysis Reveals the Burkholderia pseudomallei Response to Different Niches. Burkholderia pseudomallei, a soil and water saprophyte, is responsible for the tropical human disease melioidosis. A hundred years since its discovery, there is still much to learn about B. pseudomallei proteins that are essential for the bacterium's survival in and interaction with the infected host, as well as their roles within the bacterium's natural soil habitat. To address this gap, bacteria grown under conditions mimicking the soil environment were subjected to transcriptome sequencing (RNA-seq) analysis. A dual RNA-seq approach was used on total RNA from spleens isolated from a B. pseudomallei mouse infection model at 5 days postinfection. Under these conditions, a total of 1,434 bacterial genes were induced, with 959 induced in the soil environment and 475 induced in bacteria residing within the host. Genes encoding metabolism and transporter proteins were induced when the bacteria were present in soil, while virulence factors, metabolism, and bacterial defense mechanisms were upregulated during active infection of mice. On the other hand, capsular polysaccharide and quorum-sensing pathways were inhibited during infection. In addition to virulence factors, reactive oxygen species, heat shock proteins, siderophores, and secondary metabolites were also induced to assist bacterial adaptation and survival in the host. Overall, this study provides crucial insights into the transcriptome-level adaptations which facilitate infection by soil-dwelling B. pseudomallei. Targeting novel therapeutics toward B. pseudomallei proteins required for adaptation provides an alternative treatment strategy given its intrinsic antimicrobial resistance and the absence of a vaccine. IMPORTANCE Burkholderia pseudomallei, a soil-dwelling bacterium, is the causative agent of melioidosis, a fatal infectious disease of humans and animals. The bacterium has a large genome consisting of two chromosomes carrying genes that encode proteins with important roles for survival in diverse environments as well as in the infected host. While a general mechanism of pathogenesis has been proposed, it is not clear which proteins have major roles when the bacteria are in the soil and whether the same proteins are key to successful infection and spread. To address this question, we grew the bacteria in soil medium and then in infected mice. At 5 days postinfection, bacteria were recovered from infected mouse organs and their gene expression was compared against that of bacteria grown in soil medium. The analysis revealed a list of genes expressed under soil growth conditions and a different set of genes encoding proteins which may be important for survival, replication, and dissemination in an infected host. These proteins are a potential resource for understanding the full adaptation mechanism of this pathogen. In the absence of a vaccine for melioidosis and with treatment being reliant on combinatorial antibiotic therapy, these proteins may be ideal targets for designing antimicrobials to treat melioidosis. | 2023 | 36856434 |
| 8920 | 2 | 0.9999 | A 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. | 2012 | 22523548 |
| 9005 | 3 | 0.9999 | Insights into the Vibrio Genus: A One Health Perspective from Host Adaptability and Antibiotic Resistance to In Silico Identification of Drug Targets. The genus Vibrio comprises an important group of ubiquitous bacteria of marine systems with a high infectious capacity for humans and fish, which can lead to death or cause economic losses in aquaculture. However, little is known about the evolutionary process that led to the adaptation and colonization of humans and also about the consequences of the uncontrollable use of antibiotics in aquaculture. Here, comparative genomics analysis and functional gene annotation showed that the species more related to humans presented a significantly higher amount of proteins associated with colonization processes, such as transcriptional factors, signal transduction mechanisms, and iron uptake. In comparison, those aquaculture-associated species possess a much higher amount of resistance-associated genes, as with those of the tetracycline class. Finally, through subtractive genomics, we propose seven new drug targets such as: UMP Kinase, required to catalyze the phosphorylation of UMP into UDP, essential for the survival of bacteria of this genus; and, new natural molecules, which have demonstrated high affinity for the active sites of these targets. These data also suggest that the species most adaptable to fish and humans have a distinct natural evolution and probably undergo changes due to anthropogenic action in aquaculture or indiscriminate/irregular use of antibiotics. | 2022 | 36290057 |
| 8921 | 4 | 0.9999 | Multivariate approach to comparing whole-cell proteomes of Bacillus cereus indicates a biofilm-specific proteome. Biofilm bacteria are widely held to exhibit a unique phenotype, typified by their increased resistance to antimicrobial agents. Numerous studies have been devoted to the identification of biofilm-specific genes, but surprisingly few have been reported to date. We compared the whole cell proteomes of 24 h old Bacillus cereus biofilms and the associated suspended population to exponential, transient and stationary phase planktonic cultures using the unbiased approach of principal component analysis, comparing the quantity variations of the 823 detected spots. The analyses support the hypothesis that biofilms of Gram positive bacteria have a unique pattern of gene expression. The data provides proteomic evidence for a new biofilm and surface influenced planktonic population which is distinct to both planktonic and biofilm cells. | 2006 | 16889414 |
| 9288 | 5 | 0.9999 | Understanding cellular responses to toxic agents: a model for mechanism-choice in bacterial metal resistance. Bacterial resistances to metals are heterogeneous in both their genetic and biochemical bases. Metal resistance may be chromosomally-, plasmid- or transposon-encoded, and one or more genes may be involved: at the biochemical level at least six different mechanisms are responsible for resistance. Various types of resistance mechanisms can occur singly or in combination and for a particular metal different mechanisms of resistance can occur in the same species. To understand better the diverse responses of bacteria to metal ion challenge we have constructed a qualitative model for the selection of metal resistance in bacteria. How a bacterium becomes resistant to a particular metal depends on the number and location of cellular components sensitive to the specific metal ion. Other important selective factors include the nature of the uptake systems for the metal, the role and interactions of the metal in the normal metabolism of the cell and the availability of plasmid (or transposon) encoded resistance mechanisms. The selection model presented is based on the interaction of these factors and allows predictions to be made about the evolution of metal resistance in bacterial populations. It also allows prediction of the genetic basis and of mechanisms of resistance which are in substantial agreement with those in well-documented populations. The interaction of, and selection for resistance to, toxic substances in addition to metals, such as antibiotics and toxic analogues, involve similar principles to those concerning metals. Potentially, models for selection of resistance to any substance can be derived using this approach. | 1995 | 7766205 |
| 9381 | 6 | 0.9999 | Cross-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. | 2018 | 30281587 |
| 9615 | 7 | 0.9999 | Persistence 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. | 2016 | 26999656 |
| 9289 | 8 | 0.9999 | Artificial Gene Amplification in Escherichia coli Reveals Numerous Determinants for Resistance to Metal Toxicity. When organisms are subjected to environmental challenges, including growth inhibitors and toxins, evolution often selects for the duplication of endogenous genes, whose overexpression can provide a selective advantage. Such events occur both in natural environments and in clinical settings. Microbial cells-with their large populations and short generation times-frequently evolve resistance to a range of antimicrobials. While microbial resistance to antibiotic drugs is well documented, less attention has been given to the genetic elements responsible for resistance to metal toxicity. To assess which overexpressed genes can endow gram-negative bacteria with resistance to metal toxicity, we transformed a collection of plasmids overexpressing all E. coli open reading frames (ORFs) into naive cells, and selected for survival in toxic concentrations of six transition metals: Cd, Co, Cu, Ni, Ag, Zn. These selections identified 48 hits. In each of these hits, the overexpression of an endogenous E. coli gene provided a selective advantage in the presence of at least one of the toxic metals. Surprisingly, the majority of these cases (28/48) were not previously known to function in metal resistance or homeostasis. These findings highlight the diverse mechanisms that biological systems can deploy to adapt to environments containing toxic concentrations of metals. | 2018 | 29356848 |
| 9612 | 9 | 0.9999 | Using 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. | 2011 | 21509046 |
| 9607 | 10 | 0.9999 | Transcriptome-Level Signatures in Gene Expression and Gene Expression Variability during Bacterial Adaptive Evolution. Antibiotic-resistant bacteria are an increasingly serious public health concern, as strains emerge that demonstrate resistance to almost all available treatments. One factor that contributes to the crisis is the adaptive ability of bacteria, which exhibit remarkable phenotypic and gene expression heterogeneity in order to gain a survival advantage in damaging environments. This high degree of variability in gene expression across biological populations makes it a challenging task to identify key regulators of bacterial adaptation. Here, we research the regulation of adaptive resistance by investigating transcriptome profiles of Escherichia coli upon adaptation to disparate toxins, including antibiotics and biofuels. We locate potential target genes via conventional gene expression analysis as well as using a new analysis technique examining differential gene expression variability. By investigating trends across the diverse adaptation conditions, we identify a focused set of genes with conserved behavior, including those involved in cell motility, metabolism, membrane structure, and transport, and several genes of unknown function. To validate the biological relevance of the observed changes, we synthetically perturb gene expression using clustered regularly interspaced short palindromic repeat (CRISPR)-dCas9. Manipulation of select genes in combination with antibiotic treatment promotes adaptive resistance as demonstrated by an increased degree of antibiotic tolerance and heterogeneity in MICs. We study the mechanisms by which identified genes influence adaptation and find that select differentially variable genes have the potential to impact metabolic rates, mutation rates, and motility. Overall, this work provides evidence for a complex nongenetic response, encompassing shifts in gene expression and gene expression variability, which underlies adaptive resistance. IMPORTANCE Even initially sensitive bacteria can rapidly thwart antibiotic treatment through stress response processes known as adaptive resistance. Adaptive resistance fosters transient tolerance increases and the emergence of mutations conferring heritable drug resistance. In order to extend the applicable lifetime of new antibiotics, we must seek to hinder the occurrence of bacterial adaptive resistance; however, the regulation of adaptation is difficult to identify due to immense heterogeneity emerging during evolution. This study specifically seeks to generate heterogeneity by adapting bacteria to different stresses and then examines gene expression trends across the disparate populations in order to pinpoint key genes and pathways associated with adaptive resistance. The targets identified here may eventually inform strategies for impeding adaptive resistance and prolonging the effectiveness of antibiotic treatment. | 2017 | 28217741 |
| 9608 | 11 | 0.9998 | A genome-wide atlas of antibiotic susceptibility targets and pathways to tolerance. Detailed knowledge on how bacteria evade antibiotics and eventually develop resistance could open avenues for novel therapeutics and diagnostics. It is thereby key to develop a comprehensive genome-wide understanding of how bacteria process antibiotic stress, and how modulation of the involved processes affects their ability to overcome said stress. Here we undertake a comprehensive genetic analysis of how the human pathogen Streptococcus pneumoniae responds to 20 antibiotics. We build a genome-wide atlas of drug susceptibility determinants and generated a genetic interaction network that connects cellular processes and genes of unknown function, which we show can be used as therapeutic targets. Pathway analysis reveals a genome-wide atlas of cellular processes that can make a bacterium less susceptible, and often tolerant, in an antibiotic specific manner. Importantly, modulation of these processes confers fitness benefits during active infections under antibiotic selection. Moreover, screening of sequenced clinical isolates demonstrates that mutations in genes that decrease antibiotic sensitivity and increase tolerance readily evolve and are frequently associated with resistant strains, indicating such mutations could be harbingers for the emergence of antibiotic resistance. | 2022 | 35672367 |
| 8990 | 12 | 0.9998 | Enhanced virulence of Salmonella enterica serovar typhimurium after passage through mice. The interaction between Salmonella enterica and the host immune system is complex. The outcome of an infection is the result of a balance between the in vivo environment where the bacteria survive and grow and the regulation of fitness genes at a level sufficient for the bacteria to retain their characteristic rate of growth in a given host. Using bacteriological counts from tissue homogenates and fluorescence microscopy to determine the spread, localization, and distribution of S. enterica in the tissues, we show that, during a systemic infection, S. enterica adapts to the in vivo environment. The adaptation becomes a measurable phenotype when bacteria that have resided in a donor animal are introduced into a recipient naïve animal. This adaptation does not confer increased resistance to early host killing mechanisms but can be detected as an enhancement in the bacterial net growth rate later in the infection. The enhanced growth rate is lost upon a single passage in vitro, and it is therefore transient and not due to selection of mutants. The adapted bacteria on average reach higher intracellular numbers in individual infected cells and therefore have patterns of organ spread different from those of nonadapted bacteria. These experiments help in developing an understanding of the influence of passage in a host on the fitness and virulence of S. enterica. | 2011 | 21098099 |
| 6340 | 13 | 0.9998 | Identification and functional analysis of novel protein-encoding sequences related to stress-resistance. Currently, industrial bioproducts are less competitive than chemically produced goods due to the shortcomings of conventional microbial hosts. Thus, is essential developing robust bacteria for improved cell tolerance to process-specific parameters. In this context, metagenomic approaches from extreme environments can provide useful biological parts to improve bacterial robustness. Here, in order to build genetic constructs that increase bacterial resistance to diverse stress conditions, we recovered novel protein-encoding sequences related to stress-resistance from metagenomic databases using an in silico approach based on Hidden-Markov-Model profiles. For this purpose, we used metagenomic shotgun sequencing data from microbial communities of extreme environments to identify genes encoding chaperones and other proteins that confer resistance to stress conditions. We identified and characterized 10 novel protein-encoding sequences related to the DNA-binding protein HU, the ATP-dependent protease ClpP, and the chaperone protein DnaJ. By expressing these genes in Escherichia coli under several stress conditions (including high temperature, acidity, oxidative and osmotic stress, and UV radiation), we identified five genes conferring resistance to at least two stress conditions when expressed in E. coli. Moreover, one of the identified HU coding-genes which was retrieved from an acidic soil metagenome increased E. coli tolerance to four different stress conditions, implying its suitability for the construction of a synthetic circuit directed to expand broad bacterial resistance. | 2023 | 37840709 |
| 9606 | 14 | 0.9998 | Rapid identification of key antibiotic resistance genes in E. coli using high-resolution genome-scale CRISPRi screening. Bacteria possess a vast repertoire of genes to adapt to environmental challenges. Understanding the gene fitness landscape under antibiotic stress is crucial for elucidating bacterial resistance mechanisms and antibiotic action. To explore this, we conducted a genome-scale CRISPRi screen using a high-density sgRNA library in Escherichia coli exposed to various antibiotics. This screen identified essential genes under antibiotic-induced stress and offered insights into the molecular mechanisms underlying bacterial responses. We uncovered previously unrecognized genes involved in antibiotic resistance, including essential membrane proteins. The screen also underscored the importance of transcriptional modulation of essential genes in antibiotic tolerance. Our findings emphasize the utility of genome-wide CRISPRi screening in mapping the genetic landscape of antibiotic resistance. This study provides a valuable resource for identifying potential targets for antibiotics or antimicrobial strategies. Moreover, it offers a framework for exploring transcriptional regulatory networks and resistance mechanisms in E. coli and other bacterial pathogens. | 2025 | 40352728 |
| 9001 | 15 | 0.9998 | Bacterial 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. | 2018 | 29934334 |
| 9613 | 16 | 0.9998 | Using Selection by Nonantibiotic Stressors to Sensitize Bacteria to Antibiotics. Evolutionary adaptation of bacteria to nonantibiotic selective forces, such as osmotic stress, has been previously associated with increased antibiotic resistance, but much less is known about potentially sensitizing effects of nonantibiotic stressors. In this study, we use laboratory evolution to investigate adaptation of Enterococcus faecalis, an opportunistic bacterial pathogen, to a broad collection of environmental agents, ranging from antibiotics and biocides to extreme pH and osmotic stress. We find that nonantibiotic selection frequently leads to increased sensitivity to other conditions, including multiple antibiotics. Using population sequencing and whole-genome sequencing of single isolates from the evolved populations, we identify multiple mutations in genes previously linked with resistance to the selecting conditions, including genes corresponding to known drug targets or multidrug efflux systems previously tied to collateral sensitivity. Finally, we hypothesized based on the measured sensitivity profiles that sequential rounds of antibiotic and nonantibiotic selection may lead to hypersensitive populations by harnessing the orthogonal collateral effects of particular pairs of selective forces. To test this hypothesis, we show experimentally that populations evolved to a sequence of linezolid (an oxazolidinone antibiotic) and sodium benzoate (a common preservative) exhibit increased sensitivity to more stressors than adaptation to either condition alone. The results demonstrate how sequential adaptation to drug and nondrug environments can be used to sensitize bacteria to antibiotics and highlight new potential strategies for exploiting shared constraints governing adaptation to diverse environmental challenges. | 2020 | 31851309 |
| 9002 | 17 | 0.9998 | Bacterial strategies to inhabit acidic environments. Bacteria can inhabit a wide range of environmental conditions, including extremes in pH ranging from 1 to 11. The primary strategy employed by bacteria in acidic environments is to maintain a constant cytoplasmic pH value. However, many data demonstrate that bacteria can grow under conditions in which pH values are out of the range in which cytoplasmic pH is kept constant. Based on these observations, a novel notion was proposed that bacteria have strategies to survive even if the cytoplasm is acidified by low external pH. Under these conditions, bacteria are obliged to use acid-resistant systems, implying that multiple systems having the same physiological role are operating at different cytoplasmic pH values. If this is true, it is quite likely that bacteria have genes that are induced by environmental stimuli under different pH conditions. In fact, acid-inducible genes often respond to another factor(s) besides pH. Furthermore, distinct genes might be required for growth or survival at acid pH under different environmental conditions because functions of many systems are dependent on external conditions. Systems operating at acid pH have been described to date, but numerous genes remain to be identified that function to protect bacteria from an acid challenge. Identification and analysis of these genes is critical, not only to elucidate bacterial physiology, but also to increase the understanding of bacterial pathogenesis. | 2000 | 12483574 |
| 9614 | 18 | 0.9998 | Antibiotic-Independent Adaptive Effects of Antibiotic Resistance Mutations. Antibiotic usage selects for the accumulation and spread of antibiotic-resistant bacteria. However, resistance can also accumulate in the absence of antibiotic exposure. Antibiotics are often designed to target widely distributed regulatory housekeeping genes. The targeting of such genes enables these antibiotics to be useful against a wider variety of pathogens. This review highlights work suggesting that regulatory housekeeping genes of the type targeted by many antibiotics function as hubs of adaptation to conditions unrelated to antibiotic exposure. As a result of this, some mutations to the regulatory housekeeping gene targets of antibiotics confer both antibiotic resistance and an adaptive effect unrelated to antibiotic exposure. Such antibiotic-independent adaptive effects of resistance mutations may substantially affect the dynamics of antibiotic resistance accumulation and spread. | 2017 | 28629950 |
| 9605 | 19 | 0.9998 | Gene Expression Variability Underlies Adaptive Resistance in Phenotypically Heterogeneous Bacterial Populations. The root cause of the antibiotic resistance crisis is the ability of bacteria to evolve resistance to a multitude of antibiotics and other environmental toxins. The regulation of adaptation is difficult to pinpoint due to extensive phenotypic heterogeneity arising during evolution. Here, we investigate the mechanisms underlying general bacterial adaptation by evolving wild-type Escherichia coli populations to dissimilar chemical toxins. We demonstrate the presence of extensive inter- and intrapopulation phenotypic heterogeneity across adapted populations in multiple traits, including minimum inhibitory concentration, growth rate, and lag time. To search for a common response across the heterogeneous adapted populations, we measured gene expression in three stress-response networks: the mar regulon, the general stress response, and the SOS response. While few genes were differentially expressed, clustering revealed that interpopulation gene expression variability in adapted populations was distinct from that of unadapted populations. Notably, we observed both increases and decreases in gene expression variability upon adaptation. Sequencing select genes revealed that the observed gene expression trends are not necessarily attributable to genetic changes. To further explore the connection between gene expression variability and adaptation, we propagated single-gene knockout and CRISPR (clustered regularly interspaced short palindromic repeats) interference strains and quantified impact on adaptation to antibiotics. We identified significant correlations that suggest genes with low expression variability have greater impact on adaptation. This study provides evidence that gene expression variability can be used as an indicator of bacterial adaptive resistance, even in the face of the pervasive phenotypic heterogeneity underlying adaptation. | 2015 | 27623410 |