# | Rank | Similarity | Title + Abs. | Year | PMID |
|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 |
| 9076 | 0 | 0.9949 | 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 |
| 9184 | 1 | 0.9945 | Unlocking 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. | 2023 | 37770168 |
| 9174 | 2 | 0.9944 | Developing Phage Therapy That Overcomes the Evolution of Bacterial Resistance. The global rise of antibiotic resistance in bacterial pathogens and the waning efficacy of antibiotics urge consideration of alternative antimicrobial strategies. Phage therapy is a classic approach where bacteriophages (bacteria-specific viruses) are used against bacterial infections, with many recent successes in personalized medicine treatment of intractable infections. However, a perpetual challenge for developing generalized phage therapy is the expectation that viruses will exert selection for target bacteria to deploy defenses against virus attack, causing evolution of phage resistance during patient treatment. Here we review the two main complementary strategies for mitigating bacterial resistance in phage therapy: minimizing the ability for bacterial populations to evolve phage resistance and driving (steering) evolution of phage-resistant bacteria toward clinically favorable outcomes. We discuss future research directions that might further address the phage-resistance problem, to foster widespread development and deployment of therapeutic phage strategies that outsmart evolved bacterial resistance in clinical settings. | 2023 | 37268007 |
| 6508 | 3 | 0.9943 | Synergizing Ecotoxicology and Microbiome Data Is Key for Developing Global Indicators of Environmental Antimicrobial Resistance. The One Health concept recognises the interconnectedness of humans, plants, animals and the environment. Recent research strongly supports the idea that the environment serves as a significant reservoir for antimicrobial resistance (AMR). However, the complexity of natural environments makes efforts at AMR public health risk assessment difficult. We lack sufficient data on key ecological parameters that influence AMR, as well as the primary proxies necessary for evaluating risks to human health. Developing environmental AMR 'early warning systems' requires models with well-defined parameters. This is necessary to support the implementation of clear and targeted interventions. In this review, we provide a comprehensive overview of the current tools used globally for environmental AMR human health risk assessment and the underlying knowledge gaps. We highlight the urgent need for standardised, cost-effective risk assessment frameworks that are adaptable across different environments and regions to enhance comparability and reliability. These frameworks must also account for previously understudied AMR sources, such as horticulture, and emerging threats like climate change. In addition, integrating traditional ecotoxicology with modern 'omics' approaches will be essential for developing more comprehensive risk models and informing targeted AMR mitigation strategies. | 2024 | 39611949 |
| 8171 | 4 | 0.9943 | Advancements 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. | 2025 | 40440869 |
| 9172 | 5 | 0.9943 | These Are the Genes You're Looking For: Finding Host Resistance Genes. Humanity's ongoing struggle with new, re-emerging and endemic infectious diseases serves as a frequent reminder of the need to understand host-pathogen interactions. Recent advances in genomics have dramatically advanced our understanding of how genetics contributes to host resistance or susceptibility to bacterial infection. Here we discuss current trends in defining host-bacterial interactions at the genome-wide level, including screens that harness CRISPR/Cas9 genome editing, natural genetic variation, proteomics, and transcriptomics. We report on the merits, limitations, and findings of these innovative screens and discuss their complementary nature. Finally, we speculate on future innovation as we continue to progress through the postgenomic era and towards deeper mechanistic insight and clinical applications. | 2021 | 33004258 |
| 9552 | 6 | 0.9940 | Addressing antibiotic resistance: computational answers to a biological problem? The increasing prevalence of infections caused by antibiotic-resistant bacteria is a global healthcare crisis. Understanding the spread of resistance is predicated on the surveillance of antibiotic resistance genes within an environment. Bioinformatics and artificial intelligence (AI) methods applied to metagenomic sequencing data offer the capacity to detect known and infer yet-unknown resistance mechanisms, and predict future outbreaks of antibiotic-resistant infections. Machine learning methods, in particular, could revive the waning antibiotic discovery pipeline by helping to predict the molecular structure and function of antibiotic resistance compounds, and optimising their interactions with target proteins. Consequently, AI has the capacity to play a central role in guiding antibiotic stewardship and future clinical decision-making around antibiotic resistance. | 2023 | 37031568 |
| 8185 | 7 | 0.9940 | RNA-cleaving DNAzymes as a diagnostic and therapeutic agent against antimicrobial resistant bacteria. The development of nucleic-acid-based antimicrobials such as RNA-cleaving DNAzyme (RCD), a short catalytically active nucleic acid, is a promising alternative to the current antibiotics. The current rapid spread of antimicrobial resistance (AMR) in bacteria renders some antibiotics useless against bacterial infection, thus creating the need for alternative antimicrobials such as DNAzymes. This review summarizes recent advances in the use of RCD as a diagnostic and therapeutic agent against AMR. Firstly, the recent diagnostic application of RCD for the detection of bacterial cells and the associated resistant gene(s) is discussed. The next section summarises the therapeutic application of RCD in AMR bacterial infections which includes direct targeting of the resistant genes and indirect targeting of AMR-associated genes. Finally, this review extends the discussion to challenges of utilizing RCD in real-life applications, and the potential of combining both diagnostic and therapeutic applications of RCD into a single agent as a theranostic agent. | 2022 | 34505182 |
| 9219 | 8 | 0.9940 | Knowing 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. | 2023 | 37932119 |
| 9744 | 9 | 0.9940 | PARGT: a software tool for predicting antimicrobial resistance in bacteria. With the ever-increasing availability of whole-genome sequences, machine-learning approaches can be used as an alternative to traditional alignment-based methods for identifying new antimicrobial-resistance genes. Such approaches are especially helpful when pathogens cannot be cultured in the lab. In previous work, we proposed a game-theory-based feature evaluation algorithm. When using the protein characteristics identified by this algorithm, called 'features' in machine learning, our model accurately identified antimicrobial resistance (AMR) genes in Gram-negative bacteria. Here we extend our study to Gram-positive bacteria showing that coupling game-theory-identified features with machine learning achieved classification accuracies between 87% and 90% for genes encoding resistance to the antibiotics bacitracin and vancomycin. Importantly, we present a standalone software tool that implements the game-theory algorithm and machine-learning model used in these studies. | 2020 | 32620856 |
| 9483 | 10 | 0.9939 | Ecological and evolutionary mechanisms driving within-patient emergence of antimicrobial resistance. The ecological and evolutionary mechanisms of antimicrobial resistance (AMR) emergence within patients and how these vary across bacterial infections are poorly understood. Increasingly widespread use of pathogen genome sequencing in the clinic enables a deeper understanding of these processes. In this Review, we explore the clinical evidence to support four major mechanisms of within-patient AMR emergence in bacteria: spontaneous resistance mutations; in situ horizontal gene transfer of resistance genes; selection of pre-existing resistance; and immigration of resistant lineages. Within-patient AMR emergence occurs across a wide range of host niches and bacterial species, but the importance of each mechanism varies between bacterial species and infection sites within the body. We identify potential drivers of such differences and discuss how ecological and evolutionary analysis could be embedded within clinical trials of antimicrobials, which are powerful but underused tools for understanding why these mechanisms vary between pathogens, infections and individuals. Ultimately, improving understanding of how host niche, bacterial species and antibiotic mode of action combine to govern the ecological and evolutionary mechanism of AMR emergence in patients will enable more predictive and personalized diagnosis and antimicrobial therapies. | 2024 | 38689039 |
| 9083 | 11 | 0.9939 | 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 |
| 9187 | 12 | 0.9939 | Recent advances in gene-editing approaches for tackling antibiotic resistance threats: a review. Antibiotic resistance, a known global health challenge, involves the flow of bacteria and their genes among animals, humans, and their surrounding environment. It occurs when bacteria evolve and become less responsive to the drugs designated to kill them, making infections harder to treat. Despite several obstacles preventing the spread of genes and bacteria, pathogens regularly acquire novel resistance factors from other species, which reduces their ability to prevent and treat such bacterial infections. This issue requires coordinated efforts in healthcare, research, and public awareness to address its impact on human health worldwide. This review outlines how recent advances in gene editing technology, especially CRISPR/Cas9, unveil a breakthrough in combating antibiotic resistance. Our focus will remain on the relationship between CRISPR/cas9 and its impact on antibiotic resistance and its related infections. Moreover, the prospects of this new advanced research and the challenges of adopting these technologies against infections will be outlined by exploring its different derivatives and discussing their advantages and limitations over others, thereby providing a corresponding reference for the control and prevention of the spread of antibiotic resistance. | 2024 | 38994001 |
| 9557 | 13 | 0.9939 | Antimicrobial 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. | 2022 | 35625299 |
| 9216 | 14 | 0.9939 | Mitigating Antibiotic Resistance: The Utilization of CRISPR Technology in Detection. Antibiotics, celebrated as some of the most significant pharmaceutical breakthroughs in medical history, are capable of eliminating or inhibiting bacterial growth, offering a primary defense against a wide array of bacterial infections. However, the rise in antimicrobial resistance (AMR), driven by the widespread use of antibiotics, has evolved into a widespread and ominous threat to global public health. Thus, the creation of efficient methods for detecting resistance genes and antibiotics is imperative for ensuring food safety and safeguarding human health. The clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated proteins (Cas) systems, initially recognized as an adaptive immune defense mechanism in bacteria and archaea, have unveiled their profound potential in sensor detection, transcending their notable gene-editing applications. CRISPR/Cas technology employs Cas enzymes and guides RNA to selectively target and cleave specific DNA or RNA sequences. This review offers an extensive examination of CRISPR/Cas systems, highlighting their unique attributes and applications in antibiotic detection. It outlines the current utilization and progress of the CRISPR/Cas toolkit for identifying both nucleic acid (resistance genes) and non-nucleic acid (antibiotic micromolecules) targets within the field of antibiotic detection. In addition, it examines the current challenges, such as sensitivity and specificity, and future opportunities, including the development of point-of-care diagnostics, providing strategic insights to facilitate the curbing and oversight of antibiotic-resistance proliferation. | 2024 | 39727898 |
| 6689 | 15 | 0.9939 | Wastewater-Based Epidemiology as a Complementary Tool for Antimicrobial Resistance Surveillance: Overcoming Barriers to Integration. This commentary highlights the potential of wastewater-based epidemiology (WBE) as a complementary tool for antimicrobial resistance (AMR) surveillance. WBE can support the early detection of resistance trends at the population level, including in underserved communities. However, several challenges remain, including technical variability, complexities in data interpretation, and regulatory gaps. An additional limitation is the uncertainty surrounding the origin of resistant bacteria and their genes in wastewater, which may derive not only from human sources but also from industrial, agricultural, or infrastructural contributors. Therefore, effective integration of WBE into public health systems will require standardized methods, sustained investment, and cross-sector collaboration. This could be achieved through joint monitoring initiatives that combine hospital wastewater data with agricultural and municipal surveillance to inform antibiotic stewardship policies. Overcoming these barriers could position WBE as an innovative tool for AMR monitoring, enhancing early warning systems and supporting more responsive, equitable, and preventive public health strategies. | 2025 | 40522150 |
| 8172 | 16 | 0.9939 | From 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. | 2025 | 39404843 |
| 9182 | 17 | 0.9939 | 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 |
| 8162 | 18 | 0.9939 | Nanotechnology for Targeted Detection and Removal of Bacteria: Opportunities and Challenges. The emergence of nanotechnology has created unprecedented hopes for addressing several unmet industrial and clinical issues, including the growing threat so-termed "antibiotic resistance" in medicine. Over the last decade, nanotechnologies have demonstrated promising applications in the identification, discrimination, and removal of a wide range of pathogens. Here, recent insights into the field of bacterial nanotechnology are examined that can substantially improve the fundamental understanding of nanoparticle and bacteria interactions. A wide range of developed nanotechnology-based approaches for bacterial detection and removal together with biofilm eradication are summarized. The challenging effects of nanotechnologies on beneficial bacteria in the human body and environment and the mechanisms of bacterial resistance to nanotherapeutics are also reviewed. | 2021 | 34558234 |
| 9179 | 19 | 0.9938 | A 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. | 2022 | 35835393 |