CAREFULLY - Word Related Documents




#
Rank
Similarity
Title + Abs.
Year
PMID
012345
664900.9956 The development of antibiotics has provided much success against infectious diseases in animals and humans. But the intensive and extensive use of antibiotics over the years has resulted in the emergence of drug-resistant bacterial pathogens. The existence of a reservoir(s) of antibiotic resistant bacteria and antibiotic resistance genes in an interactive environment of animals, plants, and humans provides the opportunity for further transfer and dissemination of antibiotic resistance. The emergence of antibiotic resistant bacteria has created growing concern about its impact on animal and human health. To specifically address the impact of antibiotic resistance resulting from the use of antibiotics in agriculture, the American Academy of Microbiology convened a colloquium, “Antibiotic Resistance and the Role of Antimicrobials in Agriculture: A Critical Scientific Assessment,” in Santa Fe, New Mexico, November 2–4, 2001. Colloquium participants included academic, industrial, and government researchers with a wide range of expertise, including veterinary medicine, microbiology, food science, pharmacology, and ecology. These scientists were asked to provide their expert opinions on the current status of antibiotic usage and antibiotic resistance, current research information, and provide recommendations for future research needs. The research areas to be addressed were roughly categorized under the following areas: ▪ Origins and reservoirs of resistance; ▪ Transfer of resistance; ▪ Overcoming/modulating resistance by altering usage; and ▪ Interrupting transfer of resistance. The consensus of colloquium participants was that the evaluation of antibiotic usage and its impact were complex and subject to much speculation and polarization. Part of the complexity stems from the diverse array of animals and production practices for food animal production. The overwhelming consensus was that any use of antibiotics creates the possibility for the development of antibiotic resistance, and that there already exist pools of antibiotic resistance genes and antibiotic resistant bacteria. Much discussion revolved around the measurement of antibiotic usage, the measurement of antibiotic resistance, and the ability to evaluate the impact of various types of usage (animal, human) on overall antibiotic resistance. Additionally, many participants identified commensal bacteria as having a possible role in the continuance of antibiotic resistance as reservoirs. Participants agreed that many of the research questions could not be answered completely because of their complexity and the need for better technologies. The concept of the “smoking gun” to indicate that a specific animal source was important in the emergence of certain antibiotic resistant pathogens was discussed, and it was agreed that ascribing ultimate responsibility is likely to be impossible. There was agreement that expanded and more improved surveillance would add to current knowledge. Science-based risk assessments would provide better direction in the future. As far as preventive or intervention activities, colloquium participants reiterated the need for judicious/prudent use guidelines. Yet they also emphasized the need for better dissemination and incorporation by end-users. It is essential that there are studies to measure the impact of educational efforts on antibiotic usage. Other recommendations included alternatives to antibiotics, such as commonly mentioned vaccines and probiotics. There also was an emphasis on management or production practices that might decrease the need for antibiotics. Participants also stressed the need to train new researchers and to interest students in postdoctoral work, through training grants, periodic workshops, and comprehensive conferences. This would provide the expertise needed to address these difficult issues in the future. Finally, the participants noted that scientific societies and professional organizations should play a pivotal role in providing technical advice, distilling and disseminating information to scientists, media, and consumers, and in increasing the visibility and funding for these important issues. The overall conclusion is that antibiotic resistance remains a complex issue with no simple answers. This reinforces the messages from other meetings. The recommendations from this colloquium provide some insightful directions for future research and action.200232687288
665010.9956 Antibiotic resistance is never going to go away. No matter how many drugs we throw at it, no matter how much money and resources are sacrificed to wage a war on resistance, it will always prevail. Humans are forced to coexist with the fact of antibiotic resistance. Public health officials, clinicians, and scientists must find effective ways to cope with antibiotic resistant bacteria harmful to humans and animals and to control the development of new types of resistance. The American Academy of Microbiology convened a colloquium October 12–14, 2008, to discuss antibiotic resistance and the factors that influence the development and spread of resistance. Participants, whose areas of expertise included medicine, microbiology, and public health, made specific recommendations for needed research, policy development, a surveillance network, and treatment guidelines. Antibiotic resistance issues specific to the developing world were discussed and recommendations for improvements were made. Each antibiotic is injurious only to a certain segment of the microbial world, so for a given antibacterial there are some species of bacteria that are susceptible and others not. Bacterial species insusceptible to a particular drug are “naturally resistant.” Species that were once sensitive but eventually became resistant to it are said to have “acquired resistance.” It is important to note that “acquired resistance” affects a subset of strains in the entire species; that is why the prevalence of “acquired resistance” in a species is different according to location. Antibiotic resistance, the acquired ability of a pathogen to withstand an antibiotic that kills off its sensitive counterparts, originally arises from random mutations in existing genes or from intact genes that already serve a similar purpose. Exposure to antibiotics and other antimicrobial products, whether in the human body, in animals, or the environment, applies selective pressure that encourages resistance to emerge favoring both “naturally resistant” strains and strains which have “acquired resistance.” Horizontal gene transfer, in which genetic information is passed between microbes, allows resistance determinants to spread within harmless environmental or commensal microorganisms and pathogens, thus creating a reservoir of resistance. Resistance is also spread by the replication of microbes that carry resistance genes, a process that produces genetically identical (or clonal) progeny. Rapid diagnostic methods and surveillance are some of the most valuable tools in preventing the spread of resistance. Access to more rapid diagnostic tests that could determine the causative agent and antibiotic susceptibility of infections would inform better decision making with respect to antibiotic use, help slow the selection of resistant strains in clinical settings, and enable better disease surveillance. A rigorous surveillance network to track the evolution and spread of resistance is also needed and would probably result in significant savings in healthcare. Developing countries face unique challenges when it comes to antibiotic resistance; chief among them may be the wide availability of antibiotics without a prescription and also counterfeit products of dubious quality. Lack of adequate hygiene, poor water quality, and failure to manage human waste also top the list. Recommendations for addressing the problems of widespread resistance in the developing world include: proposals for training and infrastructure capacity building; surveillance programs; greater access to susceptibility testing; government controls on import, manufacture and use; development and use of vaccines; and incentives for pharmaceutical companies to supply drugs to these countries. Controlling antibiotic resistant bacteria and subsequent infections more efficiently necessitates the prudent and responsible use of antibiotics. It is mandatory to prevent the needless use of antibiotics (e.g., viral infections; unnecessary prolonged treatment) and to improve the rapid prescription of appropriate antibiotics to a patient. Delayed or inadequate prescriptions reduce the efficacy of treatment and favor the spread of the infection. Prudent use also applies to veterinary medicine. For example, antibiotics used as “growth promoters” have been banned in Europe and are subject to review in some other countries. There are proven techniques for limiting the spread of resistance, including hand hygiene, but more rapid screening techniques are needed in order to effectively track and prevent spread in clinical settings. The spread of antibiotic resistance on farms and in veterinary hospitals may also be significant and should not be neglected. Research is needed to pursue alternative approaches, including vaccines, antisense therapy, public health initiatives, and others. The important messages about antibiotic resistance are not getting across from scientists and infectious diseases specialists to prescribers, stakeholders, including the public, healthcare providers, and public officials. Innovative and effective communication initiatives are needed, as are carefully tailored messages for each of the stakeholder groups.200932644325
516820.9955Bacteriophage Resistance Affects Flavobacterium columnare Virulence Partly via Mutations in Genes Related to Gliding Motility and the Type IX Secretion System. Increasing problems with antibiotic resistance have directed interest toward phage therapy in the aquaculture industry. However, phage resistance evolving in target bacteria is considered a challenge. To investigate how phage resistance influences the fish pathogen Flavobacterium columnare, two wild-type bacterial isolates, FCO-F2 and FCO-F9, were exposed to phages (FCO-F2 to FCOV-F2, FCOV-F5, and FCOV-F25, and FCO-F9 to FCL-2, FCOV-F13, and FCOV-F45), and resulting phenotypic and genetic changes in bacteria were analyzed. Bacterial viability first decreased in the exposure cultures but started to increase after 1 to 2 days, along with a change in colony morphology from original rhizoid to rough, leading to 98% prevalence of the rough morphotype. Twenty-four isolates (including four isolates from no-phage treatments) were further characterized for phage resistance, antibiotic susceptibility, motility, adhesion, and biofilm formation, protease activity, whole-genome sequencing, and virulence in rainbow trout fry. The rough isolates arising in phage exposure were phage resistant with low virulence, whereas rhizoid isolates maintained phage susceptibility and high virulence. Gliding motility and protease activity were also related to the phage susceptibility. Observed mutations in phage-resistant isolates were mostly located in genes encoding the type IX secretion system, a component of the Bacteroidetes gliding motility machinery. However, not all phage-resistant isolates had mutations, indicating that phage resistance in F. columnare is a multifactorial process, including both genetic mutations and changes in gene expression. Phage resistance may not, however, be a challenge for development of phage therapy against F. columnare infections since phage resistance is associated with decreases in bacterial virulence. IMPORTANCE Phage resistance of infectious bacteria is a common phenomenon posing challenges for the development of phage therapy. Along with a growing world population and the need for increased food production, constantly intensifying animal farming has to face increasing problems of infectious diseases. Columnaris disease, caused by Flavobacterium columnare, is a worldwide threat for salmonid fry and juvenile farming. Without antibiotic treatments, infections can lead to 100% mortality in a fish stock. Phage therapy of columnaris disease would reduce the development of antibiotic-resistant bacteria and antibiotic loads by the aquaculture industry, but phage-resistant bacterial isolates may become a risk. However, phenotypic and genetic characterization of phage-resistant F. columnare isolates in this study revealed that they are less virulent than phage-susceptible isolates and thus not a challenge for phage therapy against columnaris disease. This is valuable information for the fish farming industry globally when considering phage-based prevention and curing methods for F. columnare infections.202134106011
509830.9955Feature selection and aggregation for antibiotic resistance GWAS in Mycobacterium tuberculosis: a comparative study. INTRODUCTION: Drug resistance (DR) of pathogens remains a global healthcare concern. In contrast to other bacteria, acquiring mutations in the core genome is the main mechanism of drug resistance for Mycobacterium tuberculosis (MTB). For some antibiotics, the resistance of a particular isolate can be reliably predicted by identifying specific mutations, while for other antibiotics the knowledge of resistance mechanisms is limited. Statistical machine learning (ML) methods are used to infer new genes implicated in drug resistance leveraging large collections of isolates with known whole-genome sequences and phenotypic states for different drugs. However, high correlations between the phenotypic states for commonly used drugs complicate the inference of true associations of mutations with drug phenotypes by ML approaches. METHODS: Recently, several new methods have been developed to select a small subset of reliable predictors of the dependent variable, which may help reduce the number of spurious associations identified. In this study, we evaluated several such methods, namely, logistic regression with different regularization penalty functions, a recently introduced algorithm for solving the best-subset selection problem (ABESS) and "Hungry, Hungry SNPos" (HHS) a heuristic algorithm specifically developed to identify resistance-associated genetic variants in the presence of resistance co-occurrence. We assessed their ability to select known causal mutations for resistance to a specific drug while avoiding the selection of mutations in genes associated with resistance to other drugs, thus we compared selected ML models for their applicability for MTB genome wide association studies. RESULTS AND DISCUSSION: In our analysis, ABESS significantly outperformed the other methods, selecting more relevant sets of mutations. Additionally, we demonstrated that aggregating rare mutations within protein-coding genes into markers indicative of changes in PFAM domains improved prediction quality, and these markers were predominantly selected by ABESS, suggesting their high informativeness. However, ABESS yielded lower prediction accuracy compared to logistic regression methods with regularization.202540606161
884640.9953Phage Resistance Accompanies Reduced Fitness of Uropathogenic Escherichia coli in the Urinary Environment. Urinary tract infection (UTI) is among the most common infections treated worldwide each year and is caused primarily by uropathogenic Escherichia coli (UPEC). Rising rates of antibiotic resistance among uropathogens have spurred a consideration of alternative treatment strategies, such as bacteriophage (phage) therapy; however, phage-bacterial interactions within the urinary environment are poorly defined. Here, we assess the activity of two phages, namely, HP3 and ES17, against clinical UPEC isolates using in vitro and in vivo models of UTI. In both bacteriologic medium and pooled human urine, we identified phage resistance arising within the first 6 to 8 h of coincubation. Whole-genome sequencing revealed that UPEC strains resistant to HP3 and ES17 harbored mutations in genes involved in lipopolysaccharide (LPS) biosynthesis. Phage-resistant strains displayed several in vitro phenotypes, including alterations to adherence to and invasion of human bladder epithelial HTB-9 cells and increased biofilm formation in some isolates. Interestingly, these phage-resistant UPEC isolates demonstrated reduced growth in pooled human urine, which could be partially rescued by nutrient supplementation and were more sensitive to several outer membrane-targeting antibiotics than parental strains. Additionally, phage-resistant UPEC isolates were attenuated in bladder colonization in a murine UTI model. In total, our findings suggest that while resistance to phages, such as HP3 and ES17, may arise readily in the urinary environment, phage resistance is accompanied by fitness costs which may render UPEC more susceptible to host immunity or antibiotics. IMPORTANCE UTI is one of the most common causes of outpatient antibiotic use, and rising antibiotic resistance threatens the ability to control UTI unless alternative treatments are developed. Bacteriophage (phage) therapy is gaining renewed interest; however, much like with antibiotics, bacteria can readily become resistant to phages. For successful UTI treatment, we must predict how bacteria will evade killing by phage and identify the downstream consequences of phage resistance during bacterial infection. In our current study, we found that while phage-resistant bacteria quickly emerged in vitro, these bacteria were less capable of growing in human urine and colonizing the murine bladder. These results suggest that phage therapy poses a viable UTI treatment if phage resistance confers fitness costs for the uropathogen. These results have implications for developing cocktails of phage with multiple different bacterial targets, of which each is evaded only at the cost of bacterial fitness.202235920561
840550.9952Mapping Major Disease Resistance Genes in Soybean by Genome-Wide Association Studies. Soybean is one of the most valuable agricultural crops in the world. Besides, this legume is constantly attacked by a wide range of pathogens (fungi, bacteria, viruses, and nematodes) compromising yield and increasing production costs. One of the major disease management strategies is the genetic resistance provided by single genes and quantitative trait loci (QTL). Identifying the genomic regions underlying the resistance against these pathogens on soybean is one of the first steps performed by molecular breeders. In the past, genetic mapping studies have been widely used to discover these genomic regions. However, over the last decade, advances in next-generation sequencing technologies and their subsequent cost decreasing led to the development of cost-effective approaches to high-throughput genotyping. Thus, genome-wide association studies applying thousands of SNPs in large sets composed of diverse soybean accessions have been successfully done. In this chapter, a comprehensive review of the majority of GWAS for soybean diseases published since this approach was developed is provided. Important diseases caused by Heterodera glycines, Phytophthora sojae, and Sclerotinia sclerotiorum have been the focus of the several GWAS. However, other bacterial and fungi diseases also have been targets of GWAS. As such, this GWAS summary can serve as a guide for future studies of these diseases. The protocol begins by describing several considerations about the pathogens and bringing different procedures of molecular characterization of them. Advice to choose the best isolate/race to maximize the discovery of multiple R genes or to directly map an effective R gene is provided. A summary of protocols, methods, and tools to phenotyping the soybean panel is given to several diseases. We also give details of options of DNA extraction protocols and genotyping methods, and we describe parameters of SNP quality to soybean data. Websites and their online tools to obtain genotypic and phenotypic data for thousands of soybean accessions are highlighted. Finally, we report several tricks and tips in Subheading 4, especially related to composing the soybean panel as well as generating and analyzing the phenotype data. We hope this protocol will be helpful to achieve GWAS success in identifying resistance genes on soybean.202235641772
961860.9952Why bacteriophage encode exotoxins and other virulence factors. This study considers gene location within bacteria as a function of genetic element mobility. Our emphasis is on prophage encoding of bacterial virulence factors (VFs). At least four mechanisms potentially contribute to phage encoding of bacterial VFs: (i) Enhanced gene mobility could result in greater VF gene representation within bacterial populations. We question, though, why certain genes but not others might benefit from this mobility. (ii) Epistatic interactions-between VF genes and phage genes that enhance VF utility to bacteria-could maintain phage genes via selection acting on individual, VF-expressing bacteria. However, is this mechanism sufficient to maintain the rest of phage genomes or, without gene co-regulation, even genetic linkage between phage and VF genes? (iii) Phage could amplify VFs during disease progression by carrying them to otherwise commensal bacteria colocated within the same environment. However, lytic phage kill bacteria, thus requiring assumptions of inclusive fitness within bacterial populations to explain retention of phage-mediated VF amplification for the sake of bacterial utility. Finally, (iv) phage-encoded VFs could enhance phage Darwinian fitness, particularly by acting as ecosystem-modifying agents. That is, VF-supplied nutrients could enhance phage growth by increasing the density or by improving the physiology of phage-susceptible bacteria. Alternatively, VF-mediated break down of diffusion-inhibiting spatial structure found within the multicellular bodies of host organisms could augment phage dissemination to new bacteria or to environments. Such phage-fitness enhancing mechanisms could apply particularly given VF expression within microbiologically heterogeneous environments, ie, ones where phage have some reasonable potential to acquire phage-susceptible bacteria.200719325857
962570.9952Water chlorination increases the relative abundance of an antibiotic resistance marker in developing sourdough starters. Multiple factors explain the proper development of sourdough starters. Although the role of raw ingredients and geography, among other things, have been widely studied recently, the possible effect of air quality and water chlorination on the overall bacterial communities associated with sourdough remains to be explored. Here, using 16S rRNA amplicon sequencing, we show that clean, filtered-air severely limited the presence of lactic acid bacteria in sourdough starters, suggesting that surrounding air is an important source of microorganisms necessary for the development of sourdough starters. We also show that water chlorination at levels commonly found in drinking water systems has a limited impact on the overall bacterial communities developing in sourdough starters. However, using targeted sequencing, which offers a higher resolution, we found that the abundance of integron 1, a genetic mechanism responsible for the horizontal exchange of antibiotic-resistance genes in spoilage and pathogenic bacteria, increased significantly with the level of water chlorination. Although our results suggest that water chlorination might not impact sourdough starters at a deep phylogenetic level, they indicate that it can favor the spread of genetic elements associated with spoilage bacteria. IMPORTANCE: Proper development of sourdough starters is critical for making tasty and healthy bread. Although many factors contributing to sourdough development have been studied, the effect of water chlorination on the bacterial communities in sourdough has been largely ignored. Researchers used sequencing techniques to investigate this effect and found that water chlorination at levels commonly found in drinking water systems has a limited impact on the overall bacterial communities developing in sourdough starters. However, they discovered that water chlorination could increase the abundance of integron 1, a genetic mechanism responsible for the horizontal exchange of antibiotic resistance genes in spoilage and pathogenic bacteria. This suggests that water chlorination could favor the growth of key spoilage bacteria and compromise the quality and safety of the bread. These findings emphasize the importance of considering water quality when developing sourdough starters for the best possible bread.202439283274
664880.9951Multi-Drug Resistant Coliform: Water Sanitary Standards and Health Hazards. Water constitutes and sustains life; however, its pollution afflicts its necessity, further worsening its scarcity. Coliform is one of the largest groups of bacteria evident in fecally polluted water, a major public health concern. Coliform thrive as commensals in the gut of warm-blooded animals, and are indefinitely passed through their feces into the environment. They are also called as model organisms as their presence is indicative of the prevalence of other potential pathogens, thus coliform are and unanimously employed as adept indicators of fecal pollution. As only a limited accessible source of fresh water is available on the planet, its contamination severely affects its usability. Coliform densities vary geographically and seasonally which leads to the lack of universally uniform regulatory guidelines regarding water potability often leads to ineffective detection of these model organisms and the misinterpretation of water quality status. Remedial measures such as disinfection, reducing the nutrient concentration or re-population doesn't hold context in huge lotic ecosystems such as freshwater rivers. There is also an escalating concern regarding the prevalence of multi-drug resistance in coliforms which renders antibiotic therapy incompetent. Antimicrobials are increasingly used in household, clinical, veterinary, animal husbandry and agricultural settings. Sub-optimal concentrations of these antimicrobials are unintentionally but regularly dispensed into the environment through seepages, sewages or runoffs from clinical or agricultural settings substantially adding to the ever-increasing pool of antibiotic resistance genes. When present below their minimum inhibitory concentration (MIC), these antimicrobials trigger the transfer of antibiotic-resistant genes that the coliform readily assimilate and further propagate to pathogens, the severity of which is evidenced by the high Multiple Antibiotic Resistance (MAR) index shown by the bacterial isolates procured from the environmental. This review attempts to assiduously anthologize the use of coliforms as water quality standards, their existent methods of detection and the issue of arising multi-drug resistance in them.201829946253
974390.9951Simultaneous Detection of Antibiotic Resistance Genes on Paper-Based Chip Using [Ru(phen)(2)dppz](2+) Turn-on Fluorescence Probe. Antibiotic resistance, the ability of some bacteria to resist antibiotic drugs, has been a major global health burden due to the extensive use of antibiotic agents. Antibiotic resistance is encoded via particular genes; hence the specific detection of these genes is necessary for diagnosis and treatment of antibiotic resistant cases. Conventional methods for monitoring antibiotic resistance genes require the sample to be transported to a central laboratory for tedious and sophisticated tests, which is grueling and time-consuming. We developed a paper-based chip, integrated with loop-mediated isothermal amplification (LAMP) and the "light switch" molecule [Ru(phen)(2)dppz](2+), to conduct turn-on fluorescent detection of antibiotic resistance genes. In this assay, the amplification reagents can be embedded into test spots of the chip in advance, thus simplifying the detection procedure. [Ru(phen)(2)dppz](2+) was applied to intercalate into amplicons for product analysis, enabling this assay to be operated in a wash-free format. The paper-based detection device exhibited a limit of detection (LOD) as few as 100 copies for antibiotic resistance genes. Meanwhile, it could detect antibiotic resistance genes from various bacteria. Noticeably, the approach can be applied to other genes besides antibiotic resistance genes by simply changing the LAMP primers. Therefore, this paper-based chip has the potential for point-of-care (POC) applications to detect various gene samples, especially in resource-limited conditions.201829323478
5099100.9951A machine learning-based strategy to elucidate the identification of antibiotic resistance in bacteria. Microorganisms, crucial for environmental equilibrium, could be destructive, resulting in detrimental pathophysiology to the human host. Moreover, with the emergence of antibiotic resistance (ABR), the microbial communities pose the century's largest public health challenges in terms of effective treatment strategies. Furthermore, given the large diversity and number of known bacterial strains, describing treatment choices for infected patients using experimental methodologies is time-consuming. An alternative technique, gaining popularity as sequencing prices fall and technology advances, is to use bacterial genotype rather than phenotype to determine ABR. Complementing machine learning into clinical practice provides a data-driven platform for categorization and interpretation of bacterial datasets. In the present study, k-mers were generated from nucleotide sequences of pathogenic bacteria resistant to antibiotics. Subsequently, they were clustered into groups of bacteria sharing similar genomic features using the Affinity propagation algorithm with a Silhouette coefficient of 0.82. Thereafter, a prediction model based on Random Forest algorithm was developed to explore the prediction capability of the k-mers. It yielded an overall specificity of 0.99 and a sensitivity of 0.98. Additionally, the genes and ABR drivers related to the k-mers were identified to explore their biological relevance. Furthermore, a multilayer perceptron model with a hamming loss of 0.05 was built to classify the bacterial strains into resistant and non-resistant strains against various antibiotics. Segregating pathogenic bacteria based on genomic similarities could be a valuable approach for assessing the severity of diseases caused by new bacterial strains. Utilization of this strategy could aid in enhancing our understanding of ABR patterns, paving the way for more informed and effective treatment options.202439816256
9610110.9951The evolutionary rate of antibacterial drug targets. BACKGROUND: One of the major issues in the fight against infectious diseases is the notable increase in multiple drug resistance in pathogenic species. For that reason, newly acquired high-throughput data on virulent microbial agents attract the attention of many researchers seeking potential new drug targets. Many approaches have been used to evaluate proteins from infectious pathogens, including, but not limited to, similarity analysis, reverse docking, statistical 3D structure analysis, machine learning, topological properties of interaction networks or a combination of the aforementioned methods. From a biological perspective, most essential proteins (knockout lethal for bacteria) or highly conserved proteins (broad spectrum activity) are potential drug targets. Ribosomal proteins comprise such an example. Many of them are well-known drug targets in bacteria. It is intuitive that we should learn from nature how to design good drugs. Firstly, known antibiotics are mainly originating from natural products of microorganisms targeting other microorganisms. Secondly, paleontological data suggests that antibiotics have been used by microorganisms for million years. Thus, we have hypothesized that good drug targets are evolutionary constrained and are subject of evolutionary selection. This means that mutations in such proteins are deleterious and removed by selection, which makes them less susceptible to random development of resistance. Analysis of the speed of evolution seems to be good approach to test this hypothesis. RESULTS: In this study we show that pN/pS ratio of genes coding for known drug targets is significantly lower than the genome average and also lower than that for essential genes identified by experimental methods. Similar results are observed in the case of dN/dS analysis. Both analyzes suggest that drug targets tend to evolve slowly and that the rate of evolution is a better predictor of drugability than essentiality. CONCLUSIONS: Evolutionary rate can be used to score and find potential drug targets. The results presented here may become a useful addition to a repertoire of drug target prediction methods. As a proof of concept, we analyzed GO enrichment among the slowest evolving genes. These may become the starting point in the search for antibiotics with a novel mechanism.201323374913
4776120.9951Integrate genome-based assessment of safety for probiotic strains: Bacillus coagulans GBI-30, 6086 as a case study. Probiotics are microorganisms that confer beneficial effects on the host; nevertheless, before being allowed for human consumption, their safety must be verified with accurate protocols. In the genomic era, such procedures should take into account the genomic-based approaches. This study aims at assessing the safety traits of Bacillus coagulans GBI-30, 6086 integrating the most updated genomics-based procedures and conventional phenotypic assays. Special attention was paid to putative virulence factors (VF), antibiotic resistance (AR) genes and genes encoding enzymes responsible for harmful metabolites (i.e. biogenic amines, BAs). This probiotic strain was phenotypically resistant to streptomycin and kanamycin, although the genome analysis suggested that the AR-related genes were not easily transferrable to other bacteria, and no other genes with potential safety risks, such as those related to VF or BA production, were retrieved. Furthermore, no unstable elements that could potentially lead to genomic rearrangements were detected. Moreover, a workflow is proposed to allow the proper taxonomic identification of a microbial strain and the accurate evaluation of risk-related gene traits, combining whole genome sequencing analysis with updated bioinformatics tools and standard phenotypic assays. The workflow presented can be generalized as a guideline for the safety investigation of novel probiotic strains to help stakeholders (from scientists to manufacturers and consumers) to meet regulatory requirements and avoid misleading information.201626952108
4272130.9950The hidden impact of antibacterial resistance in respiratory tract infection. Steering an appropriate course: principles to guide antibiotic choice. The prevalence and degree of antibacterial resistance in common respiratory pathogens are increasing worldwide. The health impact of resistance is not yet fully understood. However, once the impact of resistance becomes measurable, it may be too late to apply interventions to reduce resistance levels and regain previous quality and cost of care. We should address resistance now, before patient care is irreversibly compromised. The association between antibiotic consumption and the prevalence of resistance is widely assumed. However, evidence suggests that there is a more complex. multifactorial relationship between antibiotic use and resistance. It is also assumed that there is an adaptive fitness cost for bacterial resistance mutations. However, in some cases, bacteria are able to acquire 'compensatory genes' negating any negative impact of resistance mutations. Mathematical modeling indicates that the timescale for the emergence of resistance is typically shorter than the decay time following a decline in antibiotic consumption. Against this background, a general principle is proposed: to maximize patient outcome whilst minimizing the potential for selection and spread of resistance. This may be achieved through the use of agents that fulfill defined pharmacodynamic and pharmacokinetic parameters and elicit rapid eradication of the bacterial population, including emerging resistant mutants, from the site of infection. The choice of agent may not be the same in all regions, as selection will depend on local resistance patterns and disease etiology; however, the application of this principle may help to preserve the benefits of antibiotic therapy.200111419671
9600140.9950Novel "Superspreader" Bacteriophages Promote Horizontal Gene Transfer by Transformation. Bacteriophages infect an estimated 10(23) to 10(25) bacterial cells each second, many of which carry physiologically relevant plasmids (e.g., those encoding antibiotic resistance). However, even though phage-plasmid interactions occur on a massive scale and have potentially significant evolutionary, ecological, and biomedical implications, plasmid fate upon phage infection and lysis has not been investigated to date. Here we show that a subset of the natural lytic phage population, which we dub "superspreaders," releases substantial amounts of intact, transformable plasmid DNA upon lysis, thereby promoting horizontal gene transfer by transformation. Two novel Escherichia coli phage superspreaders, SUSP1 and SUSP2, liberated four evolutionarily distinct plasmids with equal efficiency, including two close relatives of prominent antibiotic resistance vectors in natural environments. SUSP2 also mediated the extensive lateral transfer of antibiotic resistance in unbiased communities of soil bacteria from Maryland and Wyoming. Furthermore, the addition of SUSP2 to cocultures of kanamycin-resistant E. coli and kanamycin-sensitive Bacillus sp. bacteria resulted in roughly 1,000-fold more kanamycin-resistant Bacillus sp. bacteria than arose in phage-free controls. Unlike many other lytic phages, neither SUSP1 nor SUSP2 encodes homologs to known hydrolytic endonucleases, suggesting a simple potential mechanism underlying the superspreading phenotype. Consistent with this model, the deletion of endonuclease IV and the nucleoid-disrupting protein ndd from coliphage T4, a phage known to extensively degrade chromosomal DNA, significantly increased its ability to promote plasmid transformation. Taken together, our results suggest that phage superspreaders may play key roles in microbial evolution and ecology but should be avoided in phage therapy and other medical applications. IMPORTANCE: Bacteriophages (phages), viruses that infect bacteria, are the planet's most numerous biological entities and kill vast numbers of bacteria in natural environments. Many of these bacteria carry plasmids, extrachromosomal DNA elements that frequently encode antibiotic resistance. However, it is largely unknown whether plasmids are destroyed during phage infection or released intact upon phage lysis, whereupon their encoded resistance could be acquired and manifested by other bacteria (transformation). Because phages are being developed to combat antibiotic-resistant bacteria and because transformation is a principal form of horizontal gene transfer, this question has important implications for biomedicine and microbial evolution alike. Here we report the isolation and characterization of two novel Escherichia coli phages, dubbed "superspreaders," that promote extensive plasmid transformation and efficiently disperse antibiotic resistance genes. Our work suggests that phage superspreaders are not suitable for use in medicine but may help drive bacterial evolution in natural environments.201728096488
9603150.9950Resistance 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
4280160.9950Droplet Microfluidics for High-Throughput Analysis of Antibiotic Susceptibility in Bacterial Cells and Populations. Antibiotic-resistant bacteria are an increasing concern both in everyday life and specialized environments such as healthcare. As the rate of antibiotic-resistant infections rises, so do complications to health and the risk of disability and death. Urgent action is required regarding the discovery of new antibiotics and rapid diagnosis of the resistance profile of an infectious pathogen as well as a better understanding of population and single-cell distribution of the resistance level. High-throughput screening is the major affordance of droplet microfluidics. Droplet screens can be exploited both to look for combinations of drugs that could stop an infection of multidrug-resistant bacteria and to search for the source of resistance via directed-evolution experiments or the analysis of various responses to a drug by genetically identical bacteria. In droplet techniques that have been used in this way for over a decade, aqueous droplets containing antibiotics and bacteria are manipulated both within and outside of the microfluidic devices. The diagnostics problem was approached by producing a series of microfluidic systems with integrated dilution modules for automated preparation of antibiotic concentration gradients, achieving the speed that allowed for high-throughput combinatorial assays. We developed a method for automated emulsification of a series of samples that facilitated measuring the resistance levels of thousands of individual cells encapsulated in droplets and quantifying the inoculum effect, the dependence of resistance level on bacterial cell count. Screening of single cells encapsulated in droplets with varying antibiotic contents has revealed a distribution of resistance levels within populations of clonally identical cells. To be able to screen bacteria from clinical samples, a study of fluorescent dyes in droplets determined that a derivative of a popular viability marker is more suitable for droplet assays. We have developed a detection system that analyzes the growth or death state of bacteria with antibiotics for thousands of droplets per second by measuring the scattering of light hitting the droplets without labeling the cells or droplets. The droplet-based microchemostats enabled long-term evolution of resistance experiments, which will be integrated with high-throughput single-cell assays to better understand the mechanism of resistance acquisition and loss. These techniques underlie automated combinatorial screens of antibiotic resistance in single cells from clinical samples. We hope that this Account will inspire new droplet-based research on the antibiotic susceptibility of bacteria.202235119826
3966170.9950A model of antibiotic resistance genes accumulation through lifetime exposure from food intake and antibiotic treatment. Antimicrobial resistant bacterial infections represent one of the most serious contemporary global healthcare crises. Acquisition and spread of resistant infections can occur through community, hospitals, food, water or endogenous bacteria. Global efforts to reduce resistance have typically focussed on antibiotic use, hygiene and sanitation and drug discovery. However, resistance in endogenous infections, e.g. many urinary tract infections, can result from life-long acquisition and persistence of resistance genes in commensal microbial flora of individual patients, which is not normally considered. Here, using individual based Monte Carlo models calibrated using antibiotic use data and human gut resistomes, we show that the long-term increase in resistance in human gut microbiomes can be substantially lowered by reducing exposure to resistance genes found food and water, alongside reduced medical antibiotic use. Reduced dietary exposure is especially important during patient antibiotic treatment because of increased selection for resistance gene retention; inappropriate use of antibiotics can be directly harmful to the patient being treated for the same reason. We conclude that a holistic approach to antimicrobial resistance that additionally incorporates food production and dietary considerations will be more effective in reducing resistant infections than a purely medical-based approach.202337590256
9744180.9950PARGT: a software tool for predicting antimicrobial resistance in bacteria. With the ever-increasing availability of whole-genome sequences, machine-learning approaches can be used as an alternative to traditional alignment-based methods for identifying new antimicrobial-resistance genes. Such approaches are especially helpful when pathogens cannot be cultured in the lab. In previous work, we proposed a game-theory-based feature evaluation algorithm. When using the protein characteristics identified by this algorithm, called 'features' in machine learning, our model accurately identified antimicrobial resistance (AMR) genes in Gram-negative bacteria. Here we extend our study to Gram-positive bacteria showing that coupling game-theory-identified features with machine learning achieved classification accuracies between 87% and 90% for genes encoding resistance to the antibiotics bacitracin and vancomycin. Importantly, we present a standalone software tool that implements the game-theory algorithm and machine-learning model used in these studies.202032620856
9557190.9950Antimicrobial Resistance Profile by Metagenomic and Metatranscriptomic Approach in Clinical Practice: Opportunity and Challenge. The burden of bacterial resistance to antibiotics affects several key sectors in the world, including healthcare, the government, and the economic sector. Resistant bacterial infection is associated with prolonged hospital stays, direct costs, and costs due to loss of productivity, which will cause policy makers to adjust their policies. Current widely performed procedures for the identification of antibiotic-resistant bacteria rely on culture-based methodology. However, some resistance determinants, such as free-floating DNA of resistance genes, are outside the bacterial genome, which could be potentially transferred under antibiotic exposure. Metagenomic and metatranscriptomic approaches to profiling antibiotic resistance offer several advantages to overcome the limitations of the culture-based approach. These methodologies enhance the probability of detecting resistance determinant genes inside and outside the bacterial genome and novel resistance genes yet pose inherent challenges in availability, validity, expert usability, and cost. Despite these challenges, such molecular-based and bioinformatics technologies offer an exquisite advantage in improving clinicians' diagnoses and the management of resistant infectious diseases in humans. This review provides a comprehensive overview of next-generation sequencing technologies, metagenomics, and metatranscriptomics in assessing antimicrobial resistance profiles.202235625299