# | Rank | Similarity | Title + Abs. | Year | PMID |
|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 |
| 9004 | 0 | 1.0000 | Shedding light on the bacterial resistance to toxic UV filters: a comparative genomic study. UV filters are toxic to marine bacteria that dominate the marine biomass. Ecotoxicology often studies the organism response but rarely integrates the toxicity mechanisms at the molecular level. In this study, in silico comparative genomics between UV filters sensitive and resistant bacteria were conducted in order to unravel the genes responsible for a resistance phenotype. The genomes of two environmentally relevant Bacteroidetes and three Firmicutes species were compared through pairwise comparison. Larger genomes were carried by bacteria exhibiting a resistant phenotype, favoring their ability to adapt to environmental stresses. While the antitoxin and CRISPR systems were the only distinctive features in resistant Bacteroidetes, Firmicutes displayed multiple unique genes that could support the difference between sensitive and resistant phenotypes. Several genes involved in ROS response, vitamin biosynthesis, xenobiotic degradation, multidrug resistance, and lipophilic compound permeability were shown to be exclusive to resistant species. Our investigation contributes to a better understanding of UV filters resistance phenotypes, by identifying pivotal genes involved in key pathways. | 2021 | 34760358 |
| 8920 | 1 | 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 |
| 9615 | 2 | 0.9998 | 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 |
| 9005 | 3 | 0.9998 | 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 |
| 9289 | 4 | 0.9998 | 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 |
| 4373 | 5 | 0.9998 | Plasmids of psychrophilic and psychrotolerant bacteria and their role in adaptation to cold environments. Extremely cold environments are a challenge for all organisms. They are mostly inhabited by psychrophilic and psychrotolerant bacteria, which employ various strategies to cope with the cold. Such harsh environments are often highly vulnerable to the influence of external factors and may undergo frequent dynamic changes. The rapid adjustment of bacteria to changing environmental conditions is crucial for their survival. Such "short-term" evolution is often enabled by plasmids-extrachromosomal replicons that represent major players in horizontal gene transfer. The genomic sequences of thousands of microorganisms, including those of many cold-active bacteria have been obtained over the last decade, but the collected data have yet to be thoroughly analyzed. This report describes the results of a meta-analysis of the NCBI sequence databases to identify and characterize plasmids of psychrophilic and psychrotolerant bacteria. We have performed in-depth analyses of 66 plasmids, almost half of which are cryptic replicons not exceeding 10 kb in size. Our analyses of the larger plasmids revealed the presence of numerous genes, which may increase the phenotypic flexibility of their host strains. These genes encode enzymes possibly involved in (i) protection against cold and ultraviolet radiation, (ii) scavenging of reactive oxygen species, (iii) metabolism of amino acids, carbohydrates, nucleotides and lipids, (iv) energy production and conversion, (v) utilization of toxic organic compounds (e.g., naphthalene), and (vi) resistance to heavy metals, metalloids and antibiotics. Some of the plasmids also contain type II restriction-modification systems, which are involved in both plasmid stabilization and protection against foreign DNA. Moreover, approx. 50% of the analyzed plasmids carry genetic modules responsible for conjugal transfer or mobilization for transfer, which may facilitate the spread of these replicons among various bacteria, including across species boundaries. | 2014 | 25426110 |
| 9657 | 6 | 0.9998 | Machine Learning Leveraging Genomes from Metagenomes Identifies Influential Antibiotic Resistance Genes in the Infant Gut Microbiome. Antibiotic resistance in pathogens is extensively studied, and yet little is known about how antibiotic resistance genes of typical gut bacteria influence microbiome dynamics. Here, we leveraged genomes from metagenomes to investigate how genes of the premature infant gut resistome correspond to the ability of bacteria to survive under certain environmental and clinical conditions. We found that formula feeding impacts the resistome. Random forest models corroborated by statistical tests revealed that the gut resistome of formula-fed infants is enriched in class D beta-lactamase genes. Interestingly, Clostridium difficile strains harboring this gene are at higher abundance in formula-fed infants than C. difficile strains lacking this gene. Organisms with genes for major facilitator superfamily drug efflux pumps have higher replication rates under all conditions, even in the absence of antibiotic therapy. Using a machine learning approach, we identified genes that are predictive of an organism's direction of change in relative abundance after administration of vancomycin and cephalosporin antibiotics. The most accurate results were obtained by reducing annotated genomic data to five principal components classified by boosted decision trees. Among the genes involved in predicting whether an organism increased in relative abundance after treatment are those that encode subclass B2 beta-lactamases and transcriptional regulators of vancomycin resistance. This demonstrates that machine learning applied to genome-resolved metagenomics data can identify key genes for survival after antibiotics treatment and predict how organisms in the gut microbiome will respond to antibiotic administration. IMPORTANCE The process of reconstructing genomes from environmental sequence data (genome-resolved metagenomics) allows unique insight into microbial systems. We apply this technique to investigate how the antibiotic resistance genes of bacteria affect their ability to flourish in the gut under various conditions. Our analysis reveals that strain-level selection in formula-fed infants drives enrichment of beta-lactamase genes in the gut resistome. Using genomes from metagenomes, we built a machine learning model to predict how organisms in the gut microbial community respond to perturbation by antibiotics. This may eventually have clinical applications. | 2018 | 29359195 |
| 9003 | 7 | 0.9998 | Extreme Environments and High-Level Bacterial Tellurite Resistance. Bacteria have long been known to possess resistance to the highly toxic oxyanion tellurite, most commonly though reduction to elemental tellurium. However, the majority of research has focused on the impact of this compound on microbes, namely E. coli, which have a very low level of resistance. Very little has been done regarding bacteria on the other end of the spectrum, with three to four orders of magnitude greater resistance than E. coli. With more focus on ecologically-friendly methods of pollutant removal, the use of bacteria for tellurite remediation, and possibly recovery, further highlights the importance of better understanding the effect on microbes, and approaches for resistance/reduction. The goal of this review is to compile current research on bacterial tellurite resistance, with a focus on high-level resistance by bacteria inhabiting extreme environments. | 2019 | 31766694 |
| 9658 | 8 | 0.9998 | Functional metagenomic libraries generated from anthropogenically impacted environments reveal importance of metabolic genes in biocide and antibiotic resistance. Anthropogenic activities result in the release of antimicrobial resistant bacteria and a cocktail of antimicrobial compounds into the environment that may directly select or indirectly co-select for antimicrobial resistance (AMR). Many studies use metagenome sequencing or qPCR-based approaches to study the environmental resistome but these methods are limited by a priori knowledge. In this study, a functional metagenomic approach was used to explore biocide resistance mechanisms in two contaminated environments and a pristine site, and to identify whether potentially novel genes conferring biocide resistance also conferred resistance or reduced susceptibility to antibiotics. Resistance was predominately mediated through novel mechanisms exclusive of the well-known qac efflux genes. UDP-galactose 4-epimerase (galE) -like genes were identified in both contaminated environments and were shown to confer cross-resistance to biocides and clinically important antibiotics for the first time (to our knowledge), compared to knockout mutants. GalE -like genes were also co-located with transposons, suggesting mobilisation potential. These results show that housekeeping genes may play a significant yet underappreciated role in AMR in environmental microbiomes. | 2023 | 36908773 |
| 8923 | 9 | 0.9998 | 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 |
| 9288 | 10 | 0.9998 | 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 |
| 8384 | 11 | 0.9998 | In vivo function and comparative genomic analyses of the Drosophila gut microbiota identify candidate symbiosis factors. Symbiosis is often characterized by co-evolutionary changes in the genomes of the partners involved. An understanding of these changes can provide insight into the nature of the relationship, including the mechanisms that initiate and maintain an association between organisms. In this study we examined the genome sequences of bacteria isolated from the Drosophila melanogaster gut with the objective of identifying genes that are important for function in the host. We compared microbiota isolates with con-specific or closely related bacterial species isolated from non-fly environments. First the phenotype of germ-free Drosophila (axenic flies) was compared to that of flies colonized with specific bacteria (gnotobiotic flies) as a measure of symbiotic function. Non-fly isolates were functionally distinct from bacteria isolated from flies, conferring slower development and an altered nutrient profile in the host, traits known to be microbiota-dependent. Comparative genomic methods were next employed to identify putative symbiosis factors: genes found in bacteria that restore microbiota-dependent traits to gnotobiotic flies, but absent from those that do not. Factors identified include riboflavin synthesis and stress resistance. We also used a phylogenomic approach to identify protein coding genes for which fly-isolate sequences were more similar to each other than to other sequences, reasoning that these genes may have a shared function unique to the fly environment. This method identified genes in Acetobacter species that cluster in two distinct genomic loci: one predicted to be involved in oxidative stress detoxification and another encoding an efflux pump. In summary, we leveraged genomic and in vivo functional comparisons to identify candidate traits that distinguish symbiotic bacteria. These candidates can serve as the basis for further work investigating the genetic requirements of bacteria for function and persistence in the Drosophila gut. | 2014 | 25408687 |
| 9326 | 12 | 0.9998 | Genes that enhance the ecological fitness of Shewanella oneidensis MR-1 in sediments reveal the value of antibiotic resistance. Environmental bacteria persist in various habitats, yet little is known about the genes that contribute to growth and survival in their respective ecological niches. Signature-tagged mutagenesis (STM) of Shewanella oneidensis MR-1 coupled with a screen involving incubations of mutant strains in anoxic aquifer sediments allowed us to identify 47 genes that enhance fitness in sediments. Gene functions inferred from annotations provide us with insight into physiological and ecological processes that environmental bacteria use while growing in sediment ecosystems. Identification of the mexF gene and other potential membrane efflux components by STM demonstrated that homologues of multidrug resistance genes present in pathogens are required for sediment fitness of nonpathogenic bacteria. Further studies with a mexF deletion mutant demonstrated that the multidrug resistance pump encoded by mexF is required for resistance to antibiotics, including chloramphenicol and tetracycline. Chloramphenicol-adapted cultures exhibited mutations in the gene encoding a TetR family regulatory protein, indicating a role for this protein in regulating expression of the mexEF operon. The relative importance of mexF for sediment fitness suggests that antibiotic efflux may be a required process for bacteria living in sediment systems. | 2007 | 17114320 |
| 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 |
| 9001 | 14 | 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 |
| 9406 | 15 | 0.9998 | Proteomics as the final step in the functional metagenomics study of antimicrobial resistance. The majority of clinically applied antimicrobial agents are derived from natural products generated by soil microorganisms and therefore resistance is likely to be ubiquitous in such environments. This is supported by the fact that numerous clinically important resistance mechanisms are encoded within the genomes of such bacteria. Advances in genomic sequencing have enabled the in silico identification of putative resistance genes present in these microorganisms. However, it is not sufficient to rely on the identification of putative resistance genes, we must also determine if the resultant proteins confer a resistant phenotype. This will require an analysis pipeline that extends from the extraction of environmental DNA, to the identification and analysis of potential resistance genes and their resultant proteins and phenotypes. This review focuses on the application of functional metagenomics and proteomics to study antimicrobial resistance in diverse environments. | 2015 | 25784907 |
| 3809 | 16 | 0.9998 | High abundance of virulence gene homologues in marine bacteria. Marine bacteria can cause harm to single-celled and multicellular eukaryotes. However, relatively little is known about the underlying genetic basis for marine bacterial interactions with higher organisms. We examined whole-genome sequences from a large number of marine bacteria for the prevalence of homologues to virulence genes and pathogenicity islands known from bacteria that are pathogenic to terrestrial animals and plants. As many as 60 out of 119 genomes of marine bacteria, with no known association to infectious disease, harboured genes of virulence-associated types III, IV, V and VI protein secretion systems. Type III secretion was relatively uncommon, while type IV was widespread among alphaproteobacteria (particularly among roseobacters) and type VI was primarily found among gammaproteobacteria. Other examples included homologues of the Yersinia murine toxin and a phage-related 'antifeeding' island. Analysis of the Global Ocean Sampling metagenomic data indicated that virulence genes were present in up to 8% of the planktonic bacteria, with highest values in productive waters. From a marine ecology perspective, expression of these widely distributed genes would indicate that some bacteria infect or even consume live cells, that is, generate a previously unrecognized flow of organic matter and nutrients directly from eukaryotes to bacteria. | 2009 | 19207573 |
| 8953 | 17 | 0.9998 | Evolution 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. | 2022 | 36070219 |
| 9670 | 18 | 0.9998 | An Approach to In Silico Dissection of Bacterial Intelligence Through Selective Genomic Tools. All the genetic potential and the intelligence a bacteria can showcase in a given environment are embedded in its genome. In this study, we have presented systematic guidelines to understand a bacterial genome with the relevant set of in silico tools using a novel bacteria as an example. This study presents a multi-dimensional approach from genome annotation to tracing genes and their network of metabolism operating in an organism. It also shows how the sequence can be used to mine the enzymes and construction of its 3-dimensional structure so that its functional behavior can be predicted and compared. The discriminating algorithm allows analysis of the promoter region and provides the insight in the regulation of genes in spite of the similarity in its sequences. The ecological niche specific bacterial behavior and adapted altered physiology can be understood through the presence of secondary metabolite, antibiotic resistance genes, and viral genes; and it helps in the valorization of genetic information for developing new biological application/processes. This study provides an in silico work plan and necessary steps for genome analysis of novel bacteria without any rigorous wet lab experiments. | 2018 | 30013271 |
| 3830 | 19 | 0.9998 | Resistance Gene Carriage Predicts Growth of Natural and Clinical Escherichia coli Isolates in the Absence of Antibiotics. Bacterial pathogens that carry antibiotic resistance alleles sometimes pay a cost in the form of impaired growth in antibiotic-free conditions. This cost of resistance is expected to be a key parameter for understanding how resistance spreads and persists in pathogen populations. Analysis of individual resistance alleles from laboratory evolution and natural isolates has shown they are typically costly, but these costs are highly variable and influenced by genetic variation at other loci. It therefore remains unclear how strongly resistance is linked to impaired antibiotic-free growth in bacteria from natural and clinical scenarios, where resistance alleles are likely to coincide with other types of genetic variation. To investigate this, we measured the growth of 92 natural and clinical Escherichia coli isolates across three antibiotic-free environments. We then tested whether variation of antibiotic-free growth among isolates was predicted by their resistance to 10 antibiotics, while accounting for the phylogenetic structure of the data. We found that isolates with similar resistance profiles had similar antibiotic-free growth profiles, but it was not simply that higher average resistance was associated with impaired growth. Next, we used whole-genome sequences to identify antibiotic resistance genes and found that isolates carrying a greater number of resistance gene types grew relatively poorly in antibiotic-free conditions, even when the resistance genes they carried were different. This suggests that the resistance of bacterial pathogens is linked to growth costs in nature, but it is the total genetic burden and multivariate resistance phenotype that predict these costs, rather than individual alleles or mean resistance across antibiotics.IMPORTANCE Managing the spread of antibiotic resistance in bacterial pathogens is a major challenge for global public health. Central to this challenge is understanding whether resistance is linked to impaired bacterial growth in the absence of antibiotics, because this determines whether resistance declines when bacteria are no longer exposed to antibiotics. We studied 92 isolates of the key bacterial pathogen Escherichia coli; these isolates varied in both their antibiotic resistance genes and other parts of the genome. Taking this approach, rather than focusing on individual genetic changes associated with resistance as in much previous work, revealed that growth without antibiotics was linked to the number of specialized resistance genes carried and the combination of antibiotics to which isolates were resistant but was not linked to average antibiotic resistance. This approach provides new insights into the genetic factors driving the long-term persistence of antibiotic-resistant bacteria, which is important for future efforts to predict and manage resistance. | 2019 | 30530714 |