# | Rank | Similarity | Title + Abs. | Year | PMID |
|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 |
| 9083 | 0 | 0.9633 | ARGNet: using deep neural networks for robust identification and classification of antibiotic resistance genes from sequences. BACKGROUND: Emergence of antibiotic resistance in bacteria is an important threat to global health. Antibiotic resistance genes (ARGs) are some of the key components to define bacterial resistance and their spread in different environments. Identification of ARGs, particularly from high-throughput sequencing data of the specimens, is the state-of-the-art method for comprehensively monitoring their spread and evolution. Current computational methods to identify ARGs mainly rely on alignment-based sequence similarities with known ARGs. Such approaches are limited by choice of reference databases and may potentially miss novel ARGs. The similarity thresholds are usually simple and could not accommodate variations across different gene families and regions. It is also difficult to scale up when sequence data are increasing. RESULTS: In this study, we developed ARGNet, a deep neural network that incorporates an unsupervised learning autoencoder model to identify ARGs and a multiclass classification convolutional neural network to classify ARGs that do not depend on sequence alignment. This approach enables a more efficient discovery of both known and novel ARGs. ARGNet accepts both amino acid and nucleotide sequences of variable lengths, from partial (30-50 aa; 100-150 nt) sequences to full-length protein or genes, allowing its application in both target sequencing and metagenomic sequencing. Our performance evaluation showed that ARGNet outperformed other deep learning models including DeepARG and HMD-ARG in most of the application scenarios especially quasi-negative test and the analysis of prediction consistency with phylogenetic tree. ARGNet has a reduced inference runtime by up to 57% relative to DeepARG. CONCLUSIONS: ARGNet is flexible, efficient, and accurate at predicting a broad range of ARGs from the sequencing data. ARGNet is freely available at https://github.com/id-bioinfo/ARGNet , with an online service provided at https://ARGNet.hku.hk . Video Abstract. | 2024 | 38725076 |
| 9076 | 1 | 0.9632 | ResiDB: An automated database manager for sequence data. The amount of publicly available DNA sequence data is drastically increasing, making it a tedious task to create sequence databases necessary for the design of diagnostic assays. The selection of appropriate sequences is especially challenging in genes affected by frequent point mutations such as antibiotic resistance genes. To overcome this issue, we have designed the webtool resiDB, a rapid and user-friendly sequence database manager for bacteria, fungi, viruses, protozoa, invertebrates, plants, archaea, environmental and whole genome shotgun sequence data. It automatically identifies and curates sequence clusters to create custom sequence databases based on user-defined input sequences. A collection of helpful visualization tools gives the user the opportunity to easily access, evaluate, edit, and download the newly created database. Consequently, researchers do no longer have to manually manage sequence data retrieval, deal with hardware limitations, and run multiple independent software tools, each having its own requirements, input and output formats. Our tool was developed within the H2020 project FAPIC aiming to develop a single diagnostic assay targeting all sepsis-relevant pathogens and antibiotic resistance mechanisms. ResiDB is freely accessible to all users through https://residb.ait.ac.at/. | 2021 | 33495705 |
| 5097 | 2 | 0.9614 | Comparing Graph Sample and Aggregation (SAGE) and Graph Attention Networks in the Prediction of Drug-Gene Associations of Extended-Spectrum Beta-Lactamases in Periodontal Infections and Resistance. INTRODUCTION: Gram-negative bacteria exhibit more antibiotic resistance than gram-positive bacteria due to their cell wall structure and composition differences. Porins, or protein channels in these bacteria, can allow small, hydrophilic antibiotics to diffuse, affecting their susceptibility. Mutations in porin protein genes can also impair antibiotic entry. Predicting drug-gene associations of extended-spectrum beta-lactamases (ESBLs) is crucial as they confer resistance to beta-lactam antibiotics, challenging the treatment of infections. This aids clinicians in selecting suitable treatments, optimizing drug usage, enhancing patient outcomes, and controlling antibiotic resistance in healthcare settings. Graph-based neural networks can predict drug-gene associations in periodontal infections and resistance. The aim of the study was to predict drug-gene associations of ESBLs in periodontal infections and resistance. METHODS: The study focuses on analyzing drug-gene associations using probes and drugs. The data was converted into graph language, assigning nodes and edges for drugs and genes. Graph neural networks (GNNs) and similar algorithms were implemented using Google Colab and Python. Cytoscape and CytoHubba are open-source software platforms used for network analysis and visualization. GNNs were used for tasks like node classification, link prediction, and graph-level prediction. Three graph-based models were used: graph convolutional network (GCN), Graph SAGE, and graph attention network (GAT). Each model was trained for 200 epochs using the Adam optimizer with a learning rate of 0.01 and a weight decay of 5e-4. RESULTS: The drug-gene association network has 57 nodes, 79 edges, and a 2.730 characteristic path length. Its structure, organization, and connectivity are analyzed using the GCN and Graph SAGE, which show high accuracy, precision, recall, and an F1-score of 0.94. GAT's performance metrics are lower, with an accuracy of 0.68, precision of 0.47, recall of 0.68, and F1-score of 0.56, suggesting that it may not be as effective in capturing drug-gene relationships. CONCLUSION: Compared to ESBLs, both GCN and Graph SAGE demonstrate excellent performance with accuracy, precision, recall, and an F1-score of 0.94. These results indicate that GCN and Graph SAGE are highly effective in predicting drug-gene associations related to ESBLs. GCN and Graph SAGE outperform GAT in predicting drug-gene associations for ESBLs. Improvements include data augmentation, regularization, and cross-validation. Ethical considerations, fairness, and open-source implementations are crucial for future research in precision periodontal treatment. | 2024 | 39347119 |
| 8136 | 3 | 0.9606 | Recent progress in CRISPR/Cas9-based genome editing for enhancing plant disease resistance. Nowadays, agricultural production is strongly affected by both climate change and pathogen attacks which seriously threaten global food security. For a long time, researchers have been waiting for a tool allowing DNA/RNA manipulation to tailor genes and their expression. Some earlier genetic manipulation methods such as meganucleases (MNs), zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs) allowed site directed modification but their successful rate was limited due to lack of flexibility when targeting a 'site-specific nucleic acid'. The discovery of clustered regularly interspaced short palindrome repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) system has revolutionized genome editing domain in different living organisms during the past 9 years. Based on RNA-guided DNA/RNA recognition, CRISPR/Cas9 optimizations have offered an unrecorded scientific opportunity to engineer plants resistant to diverse pathogens. In this report, we describe the main characteristics of the primary reported-genome editing tools ((MNs, ZFNs, TALENs) and evaluate the different CRISPR/Cas9 methods and achievements in developing crop plants resistant to viruses, fungi and bacteria. | 2023 | 36871676 |
| 9075 | 4 | 0.9606 | CamPype: an open-source workflow for automated bacterial whole-genome sequencing analysis focused on Campylobacter. BACKGROUND: The rapid expansion of Whole-Genome Sequencing has revolutionized the fields of clinical and food microbiology. However, its implementation as a routine laboratory technique remains challenging due to the growth of data at a faster rate than can be effectively analyzed and critical gaps in bioinformatics knowledge. RESULTS: To address both issues, CamPype was developed as a new bioinformatics workflow for the genomics analysis of sequencing data of bacteria, especially Campylobacter, which is the main cause of gastroenteritis worldwide making a negative impact on the economy of the public health systems. CamPype allows fully customization of stages to run and tools to use, including read quality control filtering, read contamination, reads extension and assembly, bacterial typing, genome annotation, searching for antibiotic resistance genes, virulence genes and plasmids, pangenome construction and identification of nucleotide variants. All results are processed and resumed in an interactive HTML report for best data visualization and interpretation. CONCLUSIONS: The minimal user intervention of CamPype makes of this workflow an attractive resource for microbiology laboratories with no expertise in bioinformatics as a first line method for bacterial typing and epidemiological analyses, that would help to reduce the costs of disease outbreaks, or for comparative genomic analyses. CamPype is publicly available at https://github.com/JoseBarbero/CamPype . | 2023 | 37474912 |
| 8135 | 5 | 0.9605 | Harnessing Genome Editing Techniques to Engineer Disease Resistance in Plants. Modern genome editing (GE) techniques, which include clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein 9 (CRISPR/Cas9) system, transcription activator-like effector nucleases (TALENs), zinc-finger nucleases (ZFNs) and LAGLIDADG homing endonucleases (meganucleases), have so far been used for engineering disease resistance in crops. The use of GE technologies has grown very rapidly in recent years with numerous examples of targeted mutagenesis in crop plants, including gene knockouts, knockdowns, modifications, and the repression and activation of target genes. CRISPR/Cas9 supersedes all other GE techniques including TALENs and ZFNs for editing genes owing to its unprecedented efficiency, relative simplicity and low risk of off-target effects. Broad-spectrum disease resistance has been engineered in crops by GE of either specific host-susceptibility genes (S gene approach), or cleaving DNA of phytopathogens (bacteria, virus or fungi) to inhibit their proliferation. This review focuses on different GE techniques that can potentially be used to boost molecular immunity and resistance against different phytopathogens in crops, ultimately leading to the development of promising disease-resistant crop varieties. | 2019 | 31134108 |
| 34 | 6 | 0.9602 | Silencing of multiple target genes via ingestion of dsRNA and PMRi affects development and survival in Helicoverpa armigera. RNA interference (RNAi) triggered by exogenous double-stranded RNA (dsRNA) is a powerful tool to knockdown genetic targets crucial for the growth and development of agriculturally important insect pests. Helicoverpa armigera is a pest feeding on more than 30 economically important crops worldwide and a major threat. Resistance to insecticides and Bt toxins has been gradually increasing in the field. RNAi-mediated knockdown of H. armigera genes by producing dsRNAs homologous to genetic targets in bacteria and plants has a high potential for insect management to decrease agricultural loss. The acetylcholinesterase (AChE), ecdysone receptor (EcR) and v-ATPase-A (vAA) genes were selected as genetic targets. Fragments comprising a coding sequence of < 500 bp were cloned into the L4440 vector for dsRNA production in bacteria and in a TRV-VIGS vector in antisense orientation for transient expression of dsRNA in Solanum tuberosum leaves. After ingesting bacterial-expressed dsRNA, the mRNA levels of the target genes were significantly reduced, leading to mortality and abnormal development in larva of H. armigera. Furthermore, the S. tuberosum plants transformed with TRV-VIGS expressing AChE exhibited higher mortality > 68% than the control plants 17%, recorded ten days post-feeding and significant resistance in transgenic (transient) plants was observed. Moreover, larval lethality and molting defects were observed in larva fed on potato plants expressing dsRNA specific to EcR. Analysis of transcript levels by quantitative RT-PCR revealed that larval mortality was attributable to the knockdown of genetic targets by RNAi. The results demonstrated that down-regulation of H. armigera genes involved in ATP hydrolysis, transcriptional stimulation of development genes and neural conduction has aptitude as a bioinsecticide to control H. armigera population sizes and therefore decreases crop loss. | 2022 | 35729318 |
| 8263 | 7 | 0.9601 | CRISPR/Cas9: A Novel Weapon in the Arsenal to Combat Plant Diseases. Plant pathogens like virus, bacteria, and fungi incur a huge loss of global productivity. Targeting the dominant R gene resulted in the evolution of resistance in pathogens, which shifted plant pathologists' attention toward host susceptibility factors (or S genes). Herein, the application of sequence-specific nucleases (SSNs) for targeted genome editing are gaining more importance, which utilize the use of meganucleases (MN), zinc finger nucleases (ZFNs), transcription activator-like effector-based nucleases (TALEN) with the latest one namely clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9). The first generation of genome editing technologies, due to their cumbersome nature, is becoming obsolete. Owing to its simple and inexpensive nature the use of CRISPR/Cas9 system has revolutionized targeted genome editing technology. CRISPR/Cas9 system has been exploited for developing resistance against virus, bacteria, and fungi. For resistance to DNA viruses (mainly single-stranded DNA viruses), different parts of the viral genome have been targeted transiently and by the development of transgenic plants. For RNA viruses, mainly the host susceptibility factors and very recently the viral RNA genome itself have been targeted. Fungal and bacterial resistance has been achieved mainly by targeting the host susceptibility genes through the development of transgenics. In spite of these successes CRISPR/Cas9 system suffers from off-targeting. This and other problems associated with this system are being tackled by the continuous discovery/evolution of new variants. Finally, the regulatory standpoint regarding CRISPR/Cas9 will determine the fate of using this versatile tool in developing pathogen resistance in crop plants. | 2018 | 30697226 |
| 8161 | 8 | 0.9598 | Integrative strategies against multidrug-resistant bacteria: Synthesizing novel antimicrobial frontiers for global health. Concerningly, multidrug-resistant bacteria have emerged as a prime worldwide trouble, obstructing the treatment of infectious diseases and causing doubts about the therapeutic accidentalness of presently existing drugs. Novel antimicrobial interventions deserve development as conventional antibiotics are incapable of keeping pace with bacteria evolution. Various promising approaches to combat MDR infections are discussed in this review. Antimicrobial peptides are examined for their broad-spectrum efficacy and reduced ability to develop resistance, while phage therapy may be used under extreme situations when antibiotics fail. In addition, the possibility of CRISPR-Cas systems for specifically targeting and eradicating resistance genes from bacterial populations will be explored. Nanotechnology has opened up the route to improve the delivery system of the drug itself, increasing the efficacy and specificity of antimicrobial action while protecting its host. Discovering potential antimicrobial agents is an exciting prospect through developments in synthetic biology and the rediscovery of natural product-based medicines. Moreover, host-directed therapies are now becoming popular as an adjunct to the main strategies of therapeutics without specifically targeting pathogens. Although these developments appear impressive, questions about production scaling, regulatory approvals, safety, and efficacy for clinical employment still loom large. Thus, tackling the MDR burden requires a multi-pronged plan, integrating newer treatment modalities with existing antibiotic regimens, enforcing robust stewardship initiatives, and effecting policy changes at the global level. The international health community can gird itself against the growing menace of antibiotic resistance if collaboration between interdisciplinary bodies and sustained research endeavours is encouraged. In this study, we evaluate the synergistic potential of combining various medicines in addition to summarizing recent advancements. To rethink antimicrobial stewardship in the future, we provide a multi-tiered paradigm that combines pathogen-focused and host-directed strategies. | 2025 | 40914328 |
| 9182 | 9 | 0.9597 | Harnessing CRISPR/Cas9 in engineering biotic stress immunity in crops. There is significant potential for CRISPR/Cas9 to be used in developing crops that can adapt to biotic stresses such as fungal, bacterial, viral, and pest infections and weeds. The increasing global population and climate change present significant threats to food security by putting stress on plants, making them more vulnerable to diseases and productivity losses caused by pathogens, pests, and weeds. Traditional breeding methods are inadequate for the rapid development of new plant traits needed to counteract this decline in productivity. However, modern advances in genome-editing technologies, particularly CRISPR/Cas9, have transformed crop protection through precise and targeted modifications of plant genomes. This enables the creation of resilient crops with improved resistance to pathogens, pests, and weeds. This review examines various methods by which CRISPR/Cas9 can be utilized for crop protection. These methods include knocking out susceptibility genes, introducing resistance genes, and modulating defense genes. Potential applications of CRISPR/Cas9 in crop protection involve introducing genes that confer resistance to pathogens, disrupting insect genes responsible for survival and reproduction, and engineering crops that are resistant to herbicides. In conclusion, CRISPR/Cas9 holds great promise for advancing crop protection and ensuring food security in the face of environmental challenges and increasing population pressures. The most recent advancements in CRISPR technology for creating resistance to bacteria, fungi, viruses, and pests are covered here. We wrap up by outlining the most pressing issues and technological shortcomings, as well as unanswered questions for further study. | 2025 | 40663257 |
| 8256 | 10 | 0.9589 | Revolutionizing Tomato Cultivation: CRISPR/Cas9 Mediated Biotic Stress Resistance. Tomato (Solanum lycopersicon L.) is one of the most widely consumed and produced vegetable crops worldwide. It offers numerous health benefits due to its rich content of many therapeutic elements such as vitamins, carotenoids, and phenolic compounds. Biotic stressors such as bacteria, viruses, fungi, nematodes, and insects cause severe yield losses as well as decreasing fruit quality. Conventional breeding strategies have succeeded in developing resistant genotypes, but these approaches require significant time and effort. The advent of state-of-the-art genome editing technologies, particularly CRISPR/Cas9, provides a rapid and straightforward method for developing high-quality biotic stress-resistant tomato lines. The advantage of genome editing over other approaches is the ability to make precise, minute adjustments without leaving foreign DNA inside the transformed plant. The tomato genome has been precisely modified via CRISPR/Cas9 to induce resistance genes or knock out susceptibility genes, resulting in lines resistant to common bacterial, fungal, and viral diseases. This review provides the recent advances and application of CRISPR/Cas9 in developing tomato lines with resistance to biotic stress. | 2024 | 39204705 |
| 9077 | 11 | 0.9588 | The PLSDB 2025 update: enhanced annotations and improved functionality for comprehensive plasmid research. Plasmids are extrachromosomal DNA molecules in bacteria and archaea, playing critical roles in horizontal gene transfer, antibiotic resistance, and pathogenicity. Since its first release in 2018, our database on plasmids, PLSDB, has significantly grown and enhanced its content and scope. From 34 513 records contained in the 2021 version, PLSDB now hosts 72 360 entries. Designed to provide life scientists with convenient access to extensive plasmid data and to support computer scientists by offering curated datasets for artificial intelligence (AI) development, this latest update brings more comprehensive and accurate information for plasmid research, with interactive visualization options. We enriched PLSDB by refining the identification and classification of plasmid host ecosystems and host diseases. Additionally, we incorporated annotations for new functional structures, including protein-coding genes and biosynthetic gene clusters. Further, we enhanced existing annotations, such as antimicrobial resistance genes and mobility typing. To accommodate these improvements and to host the increase plasmid sets, the webserver architecture and underlying data structures of PLSDB have been re-reconstructed, resulting in decreased response times and enhanced visualization of features while ensuring that users have access to a more efficient and user-friendly interface. The latest release of PLSDB is freely accessible at https://www.ccb.uni-saarland.de/plsdb2025. | 2025 | 39565221 |
| 8405 | 12 | 0.9588 | Mapping 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. | 2022 | 35641772 |
| 8472 | 13 | 0.9587 | Genetic architecture of resistance to plant secondary metabolites in Photorhabdus entomopathogenic bacteria. BACKGROUND: Entomopathogenic nematodes of the genus Heterorhabditis establish a symbiotic association with Photorhabdus bacteria. Together, they colonize and rapidly kill insects, making them important biological control agents against agricultural pests. Improving their biocontrol traits by engineering resistance to plant secondary metabolites (benzoxazinoids) in Photorhabdus symbiotic bacteria through experimental evolution has been shown to increase their lethality towards benzoxazinoid-defended larvae of the western corn rootworm, a serious crop pest of maize, and it is therefore a promising approach to develop more efficient biocontrol agents to manage this pest. To enhance our understanding of the genetic bases of benzoxazinoid resistance in Photorhabdus bacteria, we conducted an experimental evolution experiment with a phylogenetically diverse collection of Photorhabdus strains from different geographic origins. We cultured 27 different strains in medium containing 6-methoxy-2-benzoxazolinone (MBOA), a highly active benzoxazinoid breakdown product, for 35 24 h-cycles to select for benzoxazinoid-resistant strains. Then, we carried out genome-wide sequence comparisons to uncover the genetic alterations associated with benzoxazinoid resistance. Lastly, we evaluated the resistance of the newly isolated resistant Photorhabdus strains to eight additional bioactive compounds, including 2-benzoxazolinone (BOA), nicotine, caffeine, 6-chloroacetyl-2-benzoxazolinone (CABOA), digitoxin, fenitrothion, ampicillin, and kanamycin. RESULTS: We found that benzoxazinoid resistance evolves rapidly in Photorhabdus in a strain-specific manner. Across the different Photorhabdus strains, a total of nineteen nonsynonymous point mutations, two stop codon gains, and one frameshift were associated with higher benzoxazinoid resistance. The different genetic alterations were polygenic and occurred in genes coding for the EnvZ/OmpR two-component regulatory system, the different subunits of the DNA-directed RNA polymerase, and the AcrABZ-TolC multidrug efflux pump. Apart from increasing MBOA resistance, the different mutations were also associated with cross-resistance to 2-benzoxazolinone (BOA), nicotine, caffeine, and 6-chloroacetyl-2-benzoxazolinone (CABOA) and with collateral sensitivity to fenitrothion, ampicillin, and kanamycin. Targeted mutagenesis will provide a deeper mechanistic understanding, including the relative contribution of the different mutation types. CONCLUSIONS: Our study reveals several genomic features that are associated with resistance to xenobiotics in this important group of biological control agents and enhances the availability of molecular tools to develop better biological control agents, which is essential for more sustainable and ecologically friendly agricultural practices. | 2025 | 41168779 |
| 8765 | 14 | 0.9586 | Pseudomonas chlororaphis IRHB3 assemblies beneficial microbes and activates JA-mediated resistance to promote nutrient utilization and inhibit pathogen attack. INTRODUCTION: The rhizosphere microbiome is critical to plant health and resistance. PGPR are well known as plant-beneficial bacteria and generally regulate nutrient utilization as well as plant responses to environmental stimuli. In our previous work, one typical PGPR strain, Pseudomonas chlororaphis IRHB3, isolated from the soybean rhizosphere, had positive impacts on soil-borne disease suppression and growth promotion in the greenhouse, but its biocontrol mechanism and application in the field are not unclear. METHODS: In the current study, IRHB3 was introduced into field soil, and its effects on the local rhizosphere microbiome, disease resistance, and soybean growth were comprehensively analyzed through high-throughput sequencing and physiological and molecular methods. RESULTS AND DISCUSSION: We found that IRHB3 significantly increased the richness of the bacterial community but not the structure of the soybean rhizosphere. Functional bacteria related to phosphorus solubilization and nitrogen fixation, such as Geobacter, Geomonas, Candidatus Solibacter, Occallatibacter, and Candidatus Koribacter, were recruited in rich abundance by IRHB3 to the soybean rhizosphere as compared to those without IRHB3. In addition, the IRHB3 supplement obviously maintained the homeostasis of the rhizosphere microbiome that was disturbed by F. oxysporum, resulting in a lower disease index of root rot when compared with F. oxysporum. Furthermore, JA-mediated induced resistance was rapidly activated by IRHB3 following PDF1.2 and LOX2 expression, and meanwhile, a set of nodulation genes, GmENOD40b, GmNIN-2b, and GmRIC1, were also considerably induced by IRHB3 to improve nitrogen fixation ability and promote soybean yield, even when plants were infected by F. oxysporum. Thus, IRHB3 tends to synergistically interact with local rhizosphere microbes to promote host growth and induce host resistance in the field. | 2024 | 38380096 |
| 9068 | 15 | 0.9586 | TnCentral: 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. | 2021 | 34517763 |
| 8174 | 16 | 0.9582 | Recent Advances in Understanding the Molecular Mechanisms of Multidrug Resistance and Novel Approaches of CRISPR/Cas9-Based Genome-Editing to Combat This Health Emergency. The rapid spread of multidrug resistance (MDR), due to abusive use of antibiotics has led to global health emergency, causing substantial morbidity and mortality. Bacteria attain MDR by different means such as antibiotic modification/degradation, target protection/modification/bypass, and enhanced efflux mechanisms. The classical approaches of counteracting MDR bacteria are expensive and time-consuming, thus, it is highly significant to understand the molecular mechanisms of this resistance to curb the problem from core level. The revolutionary approach of clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated sequence 9 (CRISPR/Cas9), considered as a next-generation genome-editing tool presents an innovative opportunity to precisely target and edit bacterial genome to alter their MDR strategy. Different bacteria possessing antibiotic resistance genes such as mecA, ermB, ramR, tetA, mqrB and bla(KPC) that have been targeted by CRISPR/Cas9 to re-sensitize these pathogens against antibiotics, such as methicillin, erythromycin, tigecycline, colistin and carbapenem, respectively. The CRISPR/Cas9 from S. pyogenes is the most widely studied genome-editing tool, consisting of a Cas9 DNA endonuclease associated with tracrRNA and crRNA, which can be systematically coupled as sgRNA. The targeting strategies of CRISPR/Cas9 to bacterial cells is mediated through phage, plasmids, vesicles and nanoparticles. However, the targeting approaches of this genome-editing tool to specific bacteria is a challenging task and still remains at a very preliminary stage due to numerous obstacles awaiting to be solved. This review elaborates some recent updates about the molecular mechanisms of antibiotic resistance and the innovative role of CRISPR/Cas9 system in modulating these resistance mechanisms. Furthermore, the delivery approaches of this genome-editing system in bacterial cells are discussed. In addition, some challenges and future prospects are also described. | 2024 | 38344439 |
| 5100 | 17 | 0.9582 | DeepPBI-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. | 2024 | 39344712 |
| 6649 | 18 | 0.9582 | 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. | 2002 | 32687288 |
| 8478 | 19 | 0.9582 | Developing japonica rice introgression lines with multiple resistance genes for brown planthopper, bacterial blight, rice blast, and rice stripe virus using molecular breeding. Yield losses as a result of biotic stresses by fungi, bacteria, viruses, and insects are a key challenge in most rice cultivation areas. The development of resistant cultivars is considered an efficient and sustainable approach to mitigate rice yield reduction. In the present study, we describe the development of japonica rice introgression lines with multiple resistance genes (MR lines), resistant to four different types of biotic stresses, and compare the agronomic performance, yield, and grain quality parameters of these lines with those of the recurrent parent. A total of nine MR lines were developed by marker-assisted backcrossing, which combined five single-R genes in a japonica background with a minimum of linkage drag. All the MR lines harbored the R genes Bph18 and qSTV11(SG) and two Pi genes (Pib + Pik) in common, offering resistance to brown planthopper (BPH), rice stripe virus (RSV), and rice blast disease, respectively. In the case of bacterial blight (BB), Xa40 was detected in only five out of the nine and Xa3 was validated in the others. In particular, the five MR lines pyramiding the R genes (Bph18 + qSTV11SG + Pib + Pik) in combination with Xa40 showed stable resistance to all bioassays for BPH, BB, blast, and RSV. The MR lines did not show any negative effects on the main agronomic traits, including yield production and rice grain quality. The lines have significant potential to stabilize rice yield and minimize production costs in disease and pest-prone areas in Korea, through the pyramiding of five R genes using a marker-assisted backcrossing strategy. | 2018 | 29974251 |