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907600.9903ResiDB: 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/.202133495705
813610.9894Recent 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.202336871676
826320.9893CRISPR/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.201830697226
816130.9891Integrative 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.202540914328
974140.9891ARGai 1.0: A GAN augmented in silico approach for identifying resistant genes and strains in E. coli using vision transformer. The emergence of infectious disease and antibiotic resistance in bacteria like Escherichia coli (E. coli) shows the necessity for novel computational techniques for identifying essential genes that contribute to resistance. The task of identifying resistant strains and multi-drug patterns in E. coli is a major challenge with whole genome sequencing (WGS) and next-generation sequencing (NGS) data. To address this issue, we suggest ARGai 1.0 a deep learning architecture enhanced with generative adversarial networks (GANs). We mitigate data scarcity difficulties by augmenting limited experimental datasets with synthetic data generated by GANs. Our in-silico method (augmentation with feature selection) improves the identification of resistance genes in E. coli by using feature extraction techniques to identify valuable features from actual and GAN-generated data. Employing comprehensive validation, we exhibit the effectiveness of our ARGai 1.0 in precisely identifying the informative and resistant genes. In addition, our ARGai 1.0 identifies the resistant strains with a classification accuracy of 98.96 % on Deep Convolutional Generative Adversarial Network (DCGAN) augmented data. Additionally, ARGai 1.0 achieves more than 98 % of sensitivity and specificity. We also benchmark our ARGai 1.0 with several state-of-the-art AI models for resistant strain classification. In the fight against antibiotic resistance, ARGai 1.0 offers a promising avenue for computational genomics. With implications for research and clinical practice, this work shows the potential of deep networks with GAN augmentation as a practical and successful method for gene identification in E. coli.202539813877
918250.9890Harnessing 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.202540663257
825960.9889Secondary Metabolite Transcriptomic Pipeline (SeMa-Trap), an expression-based exploration tool for increased secondary metabolite production in bacteria. For decades, natural products have been used as a primary resource in drug discovery pipelines to find new antibiotics, which are mainly produced as secondary metabolites by bacteria. The biosynthesis of these compounds is encoded in co-localized genes termed biosynthetic gene clusters (BGCs). However, BGCs are often not expressed under laboratory conditions. Several genetic manipulation strategies have been developed in order to activate or overexpress silent BGCs. Significant increases in production levels of secondary metabolites were indeed achieved by modifying the expression of genes encoding regulators and transporters, as well as genes involved in resistance or precursor biosynthesis. However, the abundance of genes encoding such functions within bacterial genomes requires prioritization of the most promising ones for genetic manipulation strategies. Here, we introduce the 'Secondary Metabolite Transcriptomic Pipeline' (SeMa-Trap), a user-friendly web-server, available at https://sema-trap.ziemertlab.com. SeMa-Trap facilitates RNA-Seq based transcriptome analyses, finds co-expression patterns between certain genes and BGCs of interest, and helps optimize the design of comparative transcriptomic analyses. Finally, SeMa-Trap provides interactive result pages for each BGC, allowing the easy exploration and comparison of expression patterns. In summary, SeMa-Trap allows a straightforward prioritization of genes that could be targeted via genetic engineering approaches to (over)express BGCs of interest.202235580059
918470.9888Unlocking 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
817280.9888From resistance to remedy: the role of clustered regularly interspaced short palindromic repeats system in combating antimicrobial resistance-a review. The growing challenge of antimicrobial resistance (AMR) poses a significant and increasing risk to public health worldwide, necessitating innovative strategies to restore the efficacy of antibiotics. The precise genome-editing abilities of the CRISPR-Cas system have made it a potent instrument for directly targeting and eliminating antibiotic resistance genes. This review explored the mechanisms and applications of CRISPR-Cas systems in combating AMR. The latest developments in CRISPR technology have broadened its potential use, encompassing programmable antibacterial agents and improved diagnostic methods for antibiotic-resistant infections. Nevertheless, several challenges must be overcome for clinical success, including the survival of resistant bacteria, generation of anti-CRISPR proteins that reduce effectiveness, and genetic modifications that change target sequences. Additionally, the efficacy of CRISPR-Cas systems differs across bacterial species, making their universal application challenging. After overcoming these challenges, CRISPR-Cas has the potential to revolutionize AMR treatment, restore antibiotic efficacy, and reshape infection control.202539404843
826290.9887Advances in CRISPR-Cas systems for human bacterial disease. Prokaryotic adaptive immune systems called CRISPR-Cas systems have transformed genome editing by allowing for precise genetic alterations through targeted DNA cleavage. This system comprises CRISPR-associated genes and repeat-spacer arrays, which generate RNA molecules that guide the cleavage of invading genetic material. CRISPR-Cas is classified into Class 1 (multi-subunit effectors) and Class 2 (single multi-domain effectors). Its applications span combating antimicrobial resistance (AMR), targeting antibiotic resistance genes (ARGs), resensitizing bacteria to antibiotics, and preventing horizontal gene transfer (HGT). CRISPR-Cas3, for example, effectively degrades plasmids carrying resistance genes, providing a precise method to disarm bacteria. In the context of ESKAPE pathogens, CRISPR technology can resensitize bacteria to antibiotics by targeting specific resistance genes. Furthermore, in tuberculosis (TB) research, CRISPR-based tools enhance diagnostic accuracy and facilitate precise genetic modifications for studying Mycobacterium tuberculosis. CRISPR-based diagnostics, leveraging Cas endonucleases' collateral cleavage activity, offer highly sensitive pathogen detection. These advancements underscore CRISPR's transformative potential in addressing AMR and enhancing infectious disease management.202439266183
9077100.9887The 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/plsdb2025.202539565221
8256110.9886Revolutionizing 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.202439204705
8171120.9886Advancements in CRISPR-Cas-based strategies for combating antimicrobial resistance. Multidrug resistance (MDR) in bacteria presents a significant global health threat, driven by the widespread dissemination of antibiotic-resistant genes (ARGs). The CRISPR-Cas system, known for its precision and adaptability, holds promise as a tool to combat antimicrobial resistance (AMR). Although previous studies have explored the use of CRISPR-Cas to target bacterial genomes or plasmids harboring resistance genes, the application of CRISPR-Cas-based antimicrobial therapies is still in its early stages. Challenges such as low efficiency and difficulties in delivering CRISPR to bacterial cells remain. This review provides an overview of the CRISPR-Cas system, highlights recent advancements in CRISPR-Cas-based antimicrobials and delivery strategies for combating AMR. The review also discusses potential challenges for the future development of CRISPR-Cas-based antimicrobials. Addressing these challenges would enable CRISPR therapies to become a practical solution for treating AMR infections in the future.202540440869
9448130.9886Fresh Ideas Bloom in Gut Healthcare to Cross-Fertilize Lake Management. Harmful bacteria may be the most significant threat to human gut and lake ecosystem health, and they are often managed using similar tools, like poisoning with antibiotics or algicides. Out-of-the-box thinking in human microbiome engineering is leading to novel methods, like engineering bacteria to kill pathogens, "persuade" them not to produce toxins, or "mop up" their toxins. The bacterial agent can be given a competitive edge via an exclusive nutrient, and they can be engineered to commit suicide once their work is done. Viruses can kill pathogens with specific DNA sequences or knock out their antibiotic resistance genes using CRISPR technology. Some of these ideas may work for lakes. We critically review novel methods for managing harmful bacteria in the gut from the perspective of managing toxic cyanobacteria in lakes, and discuss practical aspects such as modifying bacteria using genetic engineering or directed evolution, mass culturing and controlling the agents. A key knowledge gap is in the ecology of strains, like toxigenic vs nontoxigenic Microcystis, including allelopathic and Black Queen interactions. Some of the "gut methods" may have future potential for lakes, but there presently is no substitute for established management approaches, including reducing N and P nutrient inputs, and mitigating climate change.201931647664
9179140.9886A detailed landscape of CRISPR-Cas-mediated plant disease and pest management. Genome editing technology has rapidly evolved to knock-out genes, create targeted genetic variation, install precise insertion/deletion and single nucleotide changes, and perform large-scale alteration. The flexible and multipurpose editing technologies have started playing a substantial role in the field of plant disease management. CRISPR-Cas has reduced many limitations of earlier technologies and emerged as a versatile toolbox for genome manipulation. This review summarizes the phenomenal progress of the use of the CRISPR toolkit in the field of plant pathology. CRISPR-Cas toolbox aids in the basic studies on host-pathogen interaction, in identifying virulence genes in pathogens, deciphering resistance and susceptibility factors in host plants, and engineering host genome for developing resistance. We extensively reviewed the successful genome editing applications for host plant resistance against a wide range of biotic factors, including viruses, fungi, oomycetes, bacteria, nematodes, insect pests, and parasitic plants. Recent use of CRISPR-Cas gene drive to suppress the population of pathogens and pests has also been discussed. Furthermore, we highlight exciting new uses of the CRISPR-Cas system as diagnostic tools, which rapidly detect pathogenic microorganism. This comprehensive yet concise review discusses innumerable strategies to reduce the burden of crop protection.202235835393
9191150.9886Blunted blades: new CRISPR-derived technologies to dissect microbial multi-drug resistance and biofilm formation. The spread of multi-drug-resistant (MDR) pathogens has rapidly outpaced the development of effective treatments. Diverse resistance mechanisms further limit the effectiveness of our best treatments, including multi-drug regimens and last line-of-defense antimicrobials. Biofilm formation is a powerful component of microbial pathogenesis, providing a scaffold for efficient colonization and shielding against anti-microbials, which further complicates drug resistance studies. Early genetic knockout tools didn't allow the study of essential genes, but clustered regularly interspaced palindromic repeat inference (CRISPRi) technologies have overcome this challenge via genetic silencing. These tools rapidly evolved to meet new demands and exploit native CRISPR systems. Modern tools range from the creation of massive CRISPRi libraries to tunable modulation of gene expression with CRISPR activation (CRISPRa). This review discusses the rapid expansion of CRISPRi/a-based technologies, their use in investigating MDR and biofilm formation, and how this drives further development of a potent tool to comprehensively examine multi-drug resistance.202438511958
9078160.9886MetaCherchant: analyzing genomic context of antibiotic resistance genes in gut microbiota. MOTIVATION: Antibiotic resistance is an important global public health problem. Human gut microbiota is an accumulator of resistance genes potentially providing them to pathogens. It is important to develop tools for identifying the mechanisms of how resistance is transmitted between gut microbial species and pathogens. RESULTS: We developed MetaCherchant-an algorithm for extracting the genomic environment of antibiotic resistance genes from metagenomic data in the form of a graph. The algorithm was validated on a number of simulated and published datasets, as well as applied to new 'shotgun' metagenomes of gut microbiota from patients with Helicobacter pylori who underwent antibiotic therapy. Genomic context was reconstructed for several major resistance genes. Taxonomic annotation of the context suggests that within a single metagenome, the resistance genes can be contained in genomes of multiple species. MetaCherchant allows reconstruction of mobile elements with resistance genes within the genomes of bacteria using metagenomic data. Application of MetaCherchant in differential mode produced specific graph structures suggesting the evidence of possible resistance gene transmission within a mobile element that occurred as a result of the antibiotic therapy. MetaCherchant is a promising tool giving researchers an opportunity to get an insight into dynamics of resistance transmission in vivo basing on metagenomic data. AVAILABILITY AND IMPLEMENTATION: Source code and binaries are freely available for download at https://github.com/ctlab/metacherchant. The code is written in Java and is platform-independent. COTANCT: ulyantsev@rain.ifmo.ru. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.201829092015
9108170.9885Learning from losers. Bacteria can overcome environmental challenges by killing nearby bacteria and incorporating their DNA.201729148975
8135180.9885Harnessing 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.201931134108
9083190.9885ARGNet: 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.202438725076