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907200.9951PanGeT: Pan-genomics tool. A decade after the concept of Pan-genome was first introduced; research in this field has spread its tentacles to areas such as pathogenesis of diseases, bacterial evolutionary studies and drug resistance. Gene content-based differentiation of virulent and a virulent strains of bacteria and identification of pathogen specific genes is imperative to understand their physiology and gain insights into the mechanism of genome evolution. Subsequently, this will aid in identifying diagnostic targets and in developing and selecting vaccines. The root of pan-genomic studies, however, is to identify the core genes, dispensable genes and strain specific genes across the genomes belonging to a clade. To this end, we have developed a tool, "PanGeT - Pan-genomics Tool" to compute the 'pan-genome' based on comparisons at the genome as well as the proteome levels. This automated tool is implemented using LaTeX libraries for effective visualization of overall pan-genome through graphical plots. Links to retrieve sequence information and functional annotations have also been provided. PanGeT can be downloaded from http://pranag.physics.iisc.ernet.in/PanGeT/ or https://github.com/PanGeTv1/PanGeT.201727851981
510310.9951Revolutionising bacteriology to improve treatment outcomes and antibiotic stewardship. LABORATORY INVESTIGATION OF BACTERIAL INFECTIONS GENERALLY TAKES TWO DAYS: one to grow the bacteria and another to identify them and to test their susceptibility. Meanwhile the patient is treated empirically, based on likely pathogens and local resistance rates. Many patients are over-treated to prevent under-treatment of a few, compromising antibiotic stewardship. Molecular diagnostics have potential to improve this situation by accelerating precise diagnoses and the early refinement of antibiotic therapy. They include: (i) the use of 'biomarkers' to swiftly distinguish patients with bacterial infection, and (ii) molecular bacteriology to identify pathogens and their resistance genes in clinical specimens, without culture. Biomarker interest centres on procalcitonin, which has given good results particularly for pneumonias, though broader biomarker arrays may prove superior in the future. PCRs already are widely used to diagnose a few infections (e.g. tuberculosis) whilst multiplexes are becoming available for bacteraemia, pneumonia and gastrointestinal infection. These detect likely pathogens, but are not comprehensive, particularly for resistance genes; there is also the challenge of linking pathogens and resistance genes when multiple organisms are present in a sample. Next-generation sequencing offers more comprehensive profiling, but obstacles include sensitivity when the bacterial load is low, as in bacteraemia, and the imperfect correlation of genotype and phenotype. In short, rapid molecular bacteriology presents great potential to improve patient treatments and antibiotic stewardship but faces many technical challenges; moreover it runs counter to the current nostrum of defining resistance in pharmacodynamic terms, rather than by the presence of a mechanism, and the policy of centralising bacteriology services.201324265945
960120.9951Phage steering in the presence of a competing bacterial pathogen. The rise of antibiotic-resistant bacteria has necessitated the development of alternative therapeutic strategies, such as bacteriophage therapy, where viruses infect bacteria, reducing bacterial burden. However, rapid bacterial resistance to phage treatment remains a critical challenge, potentially leading to failure. Phage steering, which leverages the evolutionary dynamics between phage and bacteria, offers a novel solution by driving bacteria to evolve away from virulence factors or resistance mechanisms. In this study, we examined whether phage steering using bacteriophage Luz19 could function in the presence of a competing pathogen, Staphylococcus aureus (SA) (USA300), while targeting Pseudomonas aeruginosa (PAO1). Through in vitro co-evolution experiments with and without the competitor, we observed that Luz19 consistently steered P. aeruginosa away from the Type IV pilus (T4P), a key virulence factor, without interference from SA. Genomic analyses revealed mutations in T4P-associated genes, including pilR and pilZ, which conferred phage resistance. Our findings suggest that phage steering remains effective even in polymicrobial environments, providing a promising avenue for enhancing bacteriophage therapy efficacy in complex infections.IMPORTANCEPhage steering-using phages that bind essential virulence or resistance-associated structures-offers a promising solution by selecting for resistance mutations that attenuate pathogenic traits. However, it remains unclear whether this strategy remains effective in polymicrobial contexts, where interspecies interactions may alter selective pressures. Here, we demonstrate that Pseudomonas aeruginosa evolves phage resistance via loss-of-function mutations in Type IV pilus (T4P) when challenged with the T4P-binding phage Luz19 and that this evolutionary trajectory is preserved even in the presence of a competing pathogen, Staphylococcus aureus. Phage resistance was phenotypically confirmed via twitching motility assays and genotypically via whole-genome sequencing. These findings support the robustness of phage steering under interspecies competition, underscoring its translational potential for managing complex infections-such as those seen in cystic fibrosis-where microbial diversity is the norm.202540492711
840530.9950Mapping 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
837640.9949BBSdb, an open resource for bacterial biofilm-associated proteins. Bacterial biofilms are organized heterogeneous assemblages of microbial cells encased within a self-produced matrix of exopolysaccharides, extracellular DNA and proteins. Over the last decade, more and more biofilm-associated proteins have been discovered and investigated. Furthermore, omics techniques such as transcriptomes, proteomes also play important roles in identifying new biofilm-associated genes or proteins. However, those important data have been uploaded separately to various databases, which creates obstacles for biofilm researchers to have a comprehensive access to these data. In this work, we constructed BBSdb, a state-of-the-art open resource of bacterial biofilm-associated protein. It includes 48 different bacteria species, 105 transcriptome datasets, 21 proteome datasets, 1205 experimental samples, 57,823 differentially expressed genes (DEGs), 13,605 differentially expressed proteins (DEPs), 1,930 'Top 5% differentially expressed genes', 444 'Threshold-based DEGs' and a predictor for prediction of biofilm-associated protein. In addition, 1,781 biofilm-associated proteins, including annotation and sequences, were extracted from 942 articles and public databases via text-mining analysis. We used E. coli as an example to represent how to explore potential biofilm-associated proteins in bacteria. We believe that this study will be of broad interest to researchers in field of bacteria, especially biofilms, which are involved in bacterial growth, pathogenicity, and drug resistance. Availability and implementation: The BBSdb is freely available at http://124.222.145.44/#!/.202439149420
955750.9948Antimicrobial 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
665060.9948 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
509870.9948Feature 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
953080.9948The role of biofilms in otolaryngologic infections. PURPOSE OF REVIEW: Bacterial biofilms have recently been shown to be important in diseases of the head and neck. Because the concept of biofilms is novel to most practitioners, it is important to gain a basic understanding of biofilms and to recognize that strategies developed to treat planktonic bacteria are ineffective against bacteria in a biofilm. RECENT FINDINGS: Bacteria preferentially exist in complex, surface-attached organizations known as biofilms. Bacteria in biofilms express a different set of genes than their planktonic counterparts and have markedly different phenotypes. Biofilm bacteria communicate with each other, and have mechanisms to diffuse nutrients and dispose of waste. Biofilms provide bacteria with distinct advantages, including antimicrobial resistance and protection from host defenses. Thus, bacteria exist in a far more complex fashion than previously thought and can best be thought of as "self-assembling multicellular communities." Although a focus on the planktonic form of bacteria has been useful in understanding acute infections, chronic infections are much better understood as biofilm illnesses. Biofilms have been shown to be involved in chronic otitis media, chronic tonsillitis, cholesteatoma, and device-associated infections. SUMMARY: Now that basic research has demonstrated that the vast majority of bacteria exist in biofilms, the biofilm concept of disease is beginning to spread throughout the clinical world. Understanding that many of the infections that affect structures of the head and neck are actually biofilm related is fundamental to developing rational strategies for treatment and prevention.200415167027
664990.9948 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
8397100.9947Application of combined CRISPR screening for genetic and chemical-genetic interaction profiling in Mycobacterium tuberculosis. CRISPR screening, including CRISPR interference (CRISPRi) and CRISPR-knockout (CRISPR-KO) screening, has become a powerful technology in the genetic screening of eukaryotes. In contrast with eukaryotes, CRISPR-KO screening has not yet been applied to functional genomics studies in bacteria. Here, we constructed genome-scale CRISPR-KO and also CRISPRi libraries in Mycobacterium tuberculosis (Mtb). We first examined these libraries to identify genes essential for Mtb viability. Subsequent screening identified dozens of genes associated with resistance/susceptibility to the antitubercular drug bedaquiline (BDQ). Genetic and chemical validation of the screening results suggested that it provided a valuable resource to investigate mechanisms of action underlying the effects of BDQ and to identify chemical-genetic synergies that can be used to optimize tuberculosis therapy. In summary, our results demonstrate the potential for efficient genome-wide CRISPR-KO screening in bacteria and establish a combined CRISPR screening approach for high-throughput investigation of genetic and chemical-genetic interactions in Mtb.202236417506
9213110.9947Emergence of antibiotic-resistant extremophiles (AREs). Excessive use of antibiotics in recent years has produced bacteria that are resistant to a wide array of antibiotics. Several genetic and non-genetic elements allow microorganisms to adapt and thrive under harsh environmental conditions such as lethal doses of antibiotics. We attempt to classify these microorganisms as antibiotic-resistant extremophiles (AREs). AREs develop strategies to gain greater resistance to antibiotics via accumulation of multiple genes or plasmids that harbor genes for multiple drug resistance (MDR). In addition to their altered expression of multiple genes, AREs also survive by producing enzymes such as penicillinase that inactivate antibiotics. It is of interest to identify the underlying molecular mechanisms by which the AREs are able to survive in the presence of wide arrays of high-dosage antibiotics. Technologically, "omics"-based approaches such as genomics have revealed a wide array of genes differentially expressed in AREs. Proteomics studies with 2DE, MALDI-TOF, and MS/MS have identified specific proteins, enzymes, and pumps that function in the adaptation mechanisms of AREs. This article discusses the molecular mechanisms by which microorganisms develop into AREs and how "omics" approaches can identify the genetic elements of these adaptation mechanisms. These objectives will assist the development of strategies and potential therapeutics to treat outbreaks of pathogenic microorganisms in the future.201222907125
9068120.9947TnCentral: a Prokaryotic Transposable Element Database and Web Portal for Transposon Analysis. We describe here the structure and organization of TnCentral (https://tncentral.proteininformationresource.org/ [or the mirror link at https://tncentral.ncc.unesp.br/]), a web resource for prokaryotic transposable elements (TE). TnCentral currently contains ∼400 carefully annotated TE, including transposons from the Tn3, Tn7, Tn402, and Tn554 families; compound transposons; integrons; and associated insertion sequences (IS). These TE carry passenger genes, including genes conferring resistance to over 25 classes of antibiotics and nine types of heavy metal, as well as genes responsible for pathogenesis in plants, toxin/antitoxin gene pairs, transcription factors, and genes involved in metabolism. Each TE has its own entry page, providing details about its transposition genes, passenger genes, and other sequence features required for transposition, as well as a graphical map of all features. TnCentral content can be browsed and queried through text- and sequence-based searches with a graphic output. We describe three use cases, which illustrate how the search interface, results tables, and entry pages can be used to explore and compare TE. TnCentral also includes downloadable software to facilitate user-driven identification, with manual annotation, of certain types of TE in genomic sequences. Through the TnCentral homepage, users can also access TnPedia, which provides comprehensive reviews of the major TE families, including an extensive general section and specialized sections with descriptions of insertion sequence and transposon families. TnCentral and TnPedia are intuitive resources that can be used by clinicians and scientists to assess TE diversity in clinical, veterinary, and environmental samples. IMPORTANCE The ability of bacteria to undergo rapid evolution and adapt to changing environmental circumstances drives the public health crisis of multiple antibiotic resistance, as well as outbreaks of disease in economically important agricultural crops and animal husbandry. Prokaryotic transposable elements (TE) play a critical role in this. Many carry "passenger genes" (not required for the transposition process) conferring resistance to antibiotics or heavy metals or causing disease in plants and animals. Passenger genes are spread by normal TE transposition activities and by insertion into plasmids, which then spread via conjugation within and across bacterial populations. Thus, an understanding of TE composition and transposition mechanisms is key to developing strategies to combat bacterial pathogenesis. Toward this end, we have developed TnCentral, a bioinformatics resource dedicated to describing and exploring the structural and functional features of prokaryotic TE whose use is intuitive and accessible to users with or without bioinformatics expertise.202134517763
5100130.9947DeepPBI-KG: a deep learning method for the prediction of phage-bacteria interactions based on key genes. Phages, the natural predators of bacteria, were discovered more than 100 years ago. However, increasing antimicrobial resistance rates have revitalized phage research. Methods that are more time-consuming and efficient than wet-laboratory experiments are needed to help screen phages quickly for therapeutic use. Traditional computational methods usually ignore the fact that phage-bacteria interactions are achieved by key genes and proteins. Methods for intraspecific prediction are rare since almost all existing methods consider only interactions at the species and genus levels. Moreover, most strains in existing databases contain only partial genome information because whole-genome information for species is difficult to obtain. Here, we propose a new approach for interaction prediction by constructing new features from key genes and proteins via the application of K-means sampling to select high-quality negative samples for prediction. Finally, we develop DeepPBI-KG, a corresponding prediction tool based on feature selection and a deep neural network. The results show that the average area under the curve for prediction reached 0.93 for each strain, and the overall AUC and area under the precision-recall curve reached 0.89 and 0.92, respectively, on the independent test set; these values are greater than those of other existing prediction tools. The forward and reverse validation results indicate that key genes and key proteins regulate and influence the interaction, which supports the reliability of the model. In addition, intraspecific prediction experiments based on Klebsiella pneumoniae data demonstrate the potential applicability of DeepPBI-KG for intraspecific prediction. In summary, the feature engineering and interaction prediction approaches proposed in this study can effectively improve the robustness and stability of interaction prediction, can achieve high generalizability, and may provide new directions and insights for rapid phage screening for therapy.202439344712
8177140.9947Antibiotic action and resistance: updated review of mechanisms, spread, influencing factors, and alternative approaches for combating resistance. Antibiotics represent a frequently employed therapeutic modality for the management of bacterial infections across diverse domains, including human health, agriculture, livestock breeding, and fish farming. The efficacy of antibiotics relies on four distinct mechanisms of action, which are discussed in detail in this review, along with accompanying diagrammatic illustrations. Despite their effectiveness, antibiotic resistance has emerged as a significant challenge to treating bacterial infections. Bacteria have developed defense mechanisms against antibiotics, rendering them ineffective. This review delves into the specific mechanisms that bacteria have developed to resist antibiotics, with the help of diagrammatic illustrations. Antibiotic resistance can spread among bacteria through various routes, resulting in previously susceptible bacteria becoming antibiotic-resistant. Multiple factors contribute to the worsening crisis of antibiotic resistance, including human misuse of antibiotics. This review also emphasizes alternative solutions proposed to mitigate the exacerbation of antibiotic resistance.202338283841
9184150.9947Unlocking the potential of phages: Innovative approaches to harnessing bacteriophages as diagnostic tools for human diseases. Phages, viruses that infect bacteria, have been explored as promising tools for the detection of human disease. By leveraging the specificity of phages for their bacterial hosts, phage-based diagnostic tools can rapidly and accurately detect bacterial infections in clinical samples. In recent years, advances in genetic engineering and biotechnology have enabled the development of more sophisticated phage-based diagnostic tools, including those that express reporter genes or enzymes, or target specific virulence factors or antibiotic resistance genes. However, despite these advancements, there are still challenges and limitations to the use of phage-based diagnostic tools, including concerns over phage safety and efficacy. This review aims to provide a comprehensive overview of the current state of phage-based diagnostic tools, including their advantages, limitations, and potential for future development. By addressing these issues, we hope to contribute to the ongoing efforts to develop safe and effective phage-based diagnostic tools for the detection of human disease.202337770168
9219160.9947Knowing and Naming: Phage Annotation and Nomenclature for Phage Therapy. Bacteriophages, or phages, are viruses that infect bacteria shaping microbial communities and ecosystems. They have gained attention as potential agents against antibiotic resistance. In phage therapy, lytic phages are preferred for their bacteria killing ability, while temperate phages, which can transfer antibiotic resistance or toxin genes, are avoided. Selection relies on plaque morphology and genome sequencing. This review outlines annotating genomes, identifying critical genomic features, and assigning functional labels to protein-coding sequences. These annotations prevent the transfer of unwanted genes, such as antimicrobial resistance or toxin genes, during phage therapy. Additionally, it covers International Committee on Taxonomy of Viruses (ICTV)-an established phage nomenclature system for simplified classification and communication. Accurate phage genome annotation and nomenclature provide insights into phage-host interactions, replication strategies, and evolution, accelerating our understanding of the diversity and evolution of phages and facilitating the development of phage-based therapies.202337932119
5099170.9946A 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
8278180.9946Siderophore cheating and cheating resistance shape competition for iron in soil and freshwater Pseudomonas communities. All social organisms experience dilemmas between cooperators performing group-beneficial actions and cheats selfishly exploiting these actions. Although bacteria have become model organisms to study social dilemmas in laboratory systems, we know little about their relevance in natural communities. Here, we show that social interactions mediated by a single shareable compound necessary for growth (the iron-scavenging pyoverdine) have important consequences for competitive dynamics in soil and pond communities of Pseudomonas bacteria. We find that pyoverdine non- and low-producers co-occur in many natural communities. While non-producers have genes coding for multiple pyoverdine receptors and are able to exploit compatible heterologous pyoverdines from other community members, producers differ in the pyoverdine types they secrete, offering protection against exploitation from non-producers with incompatible receptors. Our findings indicate that there is both selection for cheating and cheating resistance, which could drive antagonistic co-evolution and diversification in natural bacterial communities.Lab strains of Pseudomonas are model systems for the evolution of cooperation over public goods (iron-scavenging siderophores). Here, Butaitė et al. add ecological and evolutionary insight into this system by showing that cheating and resistance to cheating both shape competition for iron in natural Pseudomonas communities.201728871205
8360190.9946Genome mining of Streptomyces scabrisporus NF3 reveals symbiotic features including genes related to plant interactions. Endophytic bacteria are wide-spread and associated with plant physiological benefits, yet their genomes and secondary metabolites remain largely unidentified. In this study, we explored the genome of the endophyte Streptomyces scabrisporus NF3 for discovery of potential novel molecules as well as genes and metabolites involved in host interactions. The complete genomes of seven Streptomyces and three other more distantly related bacteria were used to define the functional landscape of this unique microbe. The S. scabrisporus NF3 genome is larger than the average Streptomyces genome and not structured for an obligate endosymbiotic lifestyle; this and the fact that can grow in R2YE media implies that it could include a soil-living stage. The genome displays an enrichment of genes associated with amino acid production, protein secretion, secondary metabolite and antioxidants production and xenobiotic degradation, indicating that S. scabrisporus NF3 could contribute to the metabolic enrichment of soil microbial communities and of its hosts. Importantly, besides its metabolic advantages, the genome showed evidence for differential functional specificity and diversification of plant interaction molecules, including genes for the production of plant hormones, stress resistance molecules, chitinases, antibiotics and siderophores. Given the diversity of S. scabrisporus mechanisms for host upkeep, we propose that these strategies were necessary for its adaptation to plant hosts and to face changes in environmental conditions.201829447216