# | Rank | Similarity | Title + Abs. | Year | PMID |
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| 0 | 1 | 2 | 3 | 4 | 5 |
| 6649 | 0 | 0.9956 | The development of antibiotics has provided much success against infectious diseases in animals and humans. But the intensive and extensive use of antibiotics over the years has resulted in the emergence of drug-resistant bacterial pathogens. The existence of a reservoir(s) of antibiotic resistant bacteria and antibiotic resistance genes in an interactive environment of animals, plants, and humans provides the opportunity for further transfer and dissemination of antibiotic resistance. The emergence of antibiotic resistant bacteria has created growing concern about its impact on animal and human health. To specifically address the impact of antibiotic resistance resulting from the use of antibiotics in agriculture, the American Academy of Microbiology convened a colloquium, “Antibiotic Resistance and the Role of Antimicrobials in Agriculture: A Critical Scientific Assessment,” in Santa Fe, New Mexico, November 2–4, 2001. Colloquium participants included academic, industrial, and government researchers with a wide range of expertise, including veterinary medicine, microbiology, food science, pharmacology, and ecology. These scientists were asked to provide their expert opinions on the current status of antibiotic usage and antibiotic resistance, current research information, and provide recommendations for future research needs. The research areas to be addressed were roughly categorized under the following areas: ▪ Origins and reservoirs of resistance; ▪ Transfer of resistance; ▪ Overcoming/modulating resistance by altering usage; and ▪ Interrupting transfer of resistance. The consensus of colloquium participants was that the evaluation of antibiotic usage and its impact were complex and subject to much speculation and polarization. Part of the complexity stems from the diverse array of animals and production practices for food animal production. The overwhelming consensus was that any use of antibiotics creates the possibility for the development of antibiotic resistance, and that there already exist pools of antibiotic resistance genes and antibiotic resistant bacteria. Much discussion revolved around the measurement of antibiotic usage, the measurement of antibiotic resistance, and the ability to evaluate the impact of various types of usage (animal, human) on overall antibiotic resistance. Additionally, many participants identified commensal bacteria as having a possible role in the continuance of antibiotic resistance as reservoirs. Participants agreed that many of the research questions could not be answered completely because of their complexity and the need for better technologies. The concept of the “smoking gun” to indicate that a specific animal source was important in the emergence of certain antibiotic resistant pathogens was discussed, and it was agreed that ascribing ultimate responsibility is likely to be impossible. There was agreement that expanded and more improved surveillance would add to current knowledge. Science-based risk assessments would provide better direction in the future. As far as preventive or intervention activities, colloquium participants reiterated the need for judicious/prudent use guidelines. Yet they also emphasized the need for better dissemination and incorporation by end-users. It is essential that there are studies to measure the impact of educational efforts on antibiotic usage. Other recommendations included alternatives to antibiotics, such as commonly mentioned vaccines and probiotics. There also was an emphasis on management or production practices that might decrease the need for antibiotics. Participants also stressed the need to train new researchers and to interest students in postdoctoral work, through training grants, periodic workshops, and comprehensive conferences. This would provide the expertise needed to address these difficult issues in the future. Finally, the participants noted that scientific societies and professional organizations should play a pivotal role in providing technical advice, distilling and disseminating information to scientists, media, and consumers, and in increasing the visibility and funding for these important issues. The overall conclusion is that antibiotic resistance remains a complex issue with no simple answers. This reinforces the messages from other meetings. The recommendations from this colloquium provide some insightful directions for future research and action. | 2002 | 32687288 |
| 4761 | 1 | 0.9954 | Antimicrobial resistance and biofilm formation of penile prosthesis isolates: insights from in-vitro analysis. BACKGROUND: Inflatable penile prostheses (IPPs) have been shown to harbor biofilms in the presence and absence of infection despite exposure to various antimicrobials. Microbes persisting on IPPs following antibiotic exposure have not been adequately studied to assess biofilm formation capacity and antibiotic resistance. AIM: In this study, we aimed to assess these properties of microbes obtained from explanted infected and non-infected IPPS using an in vitro model. METHODS: 35 bacterial isolates were grown and tested against various single-agent or multiple agent antibiotic regimens including: bacitracin, cefaclor, cefazolin, gentamicin, levofloxacin, trimethoprim-sulfamethoxazole, tobramycin, vancomycin, piperacillin/tazobactam, gentamicin + piperacillin/tazobactam, gentamicin + cefazolin, and gentamicin + vancomycin. Zones of inhibition were averaged for each sample site and species. Statistics were analyzed with Holm's corrected, one-sample t-tests against a null hypothesis of 0. Isolates were also allowed to form biofilms in a 96-well polyvinyl plate and absorbance was tested at 570 nm using a microplate reader. OUTCOMES: Resistance was determined via clinical guidelines or previously established literature, and the mean and standard deviation of biofilm absorbance values were calculated and normalized to the optical density600 of the bacterial inoculum. RESULTS: Every species tested was able to form robust biofilms with the exception of Staphylococcus warneri. As expected, most bacteria were resistant to common perioperative antimicrobial prophylaxis. Gentamicin dual therapy demonstrated somewhat greater efficacy. STRENGTHS AND LIMITATIONS: This study examines a broad range of antimicrobials against clinically obtained bacterial isolates. However, not all species and antibiotics tested had standardized breakpoints, requiring the use of surrogate values from the literature. The microbes included in this study and their resistance genes are expectedly biased towards those that survived antibiotic exposure, and thus reflect the types of microbes which might "survive" in vivo exposure following revisional surgery. CLINICAL TRANSLATION: Despite exposure to antimicrobials, bacteria isolated during penile prosthesis revision for both infected and non-infected cases exhibit biofilm forming capacity and extensive antibiotic resistance patterns in vitro. These microbes merit further investigation to understand when simple colonization vs re-infection might occur. CONCLUSIONS: Although increasing evidence supports the concept that all IPPs harbor biofilms, even in the absence of infection, a deeper understanding of the characteristics of bacteria that survive revisional surgery is warranted. This study demonstrated extensive biofilm forming capabilities, and resistance patterns among bacteria isolated from both non-infected and infected IPP revision surgeries. Further investigation is warranted to determine why some devices become infected while others remain colonized but non-infected. | 2025 | 40062463 |
| 6650 | 2 | 0.9953 | Antibiotic resistance is never going to go away. No matter how many drugs we throw at it, no matter how much money and resources are sacrificed to wage a war on resistance, it will always prevail. Humans are forced to coexist with the fact of antibiotic resistance. Public health officials, clinicians, and scientists must find effective ways to cope with antibiotic resistant bacteria harmful to humans and animals and to control the development of new types of resistance. The American Academy of Microbiology convened a colloquium October 12–14, 2008, to discuss antibiotic resistance and the factors that influence the development and spread of resistance. Participants, whose areas of expertise included medicine, microbiology, and public health, made specific recommendations for needed research, policy development, a surveillance network, and treatment guidelines. Antibiotic resistance issues specific to the developing world were discussed and recommendations for improvements were made. Each antibiotic is injurious only to a certain segment of the microbial world, so for a given antibacterial there are some species of bacteria that are susceptible and others not. Bacterial species insusceptible to a particular drug are “naturally resistant.” Species that were once sensitive but eventually became resistant to it are said to have “acquired resistance.” It is important to note that “acquired resistance” affects a subset of strains in the entire species; that is why the prevalence of “acquired resistance” in a species is different according to location. Antibiotic resistance, the acquired ability of a pathogen to withstand an antibiotic that kills off its sensitive counterparts, originally arises from random mutations in existing genes or from intact genes that already serve a similar purpose. Exposure to antibiotics and other antimicrobial products, whether in the human body, in animals, or the environment, applies selective pressure that encourages resistance to emerge favoring both “naturally resistant” strains and strains which have “acquired resistance.” Horizontal gene transfer, in which genetic information is passed between microbes, allows resistance determinants to spread within harmless environmental or commensal microorganisms and pathogens, thus creating a reservoir of resistance. Resistance is also spread by the replication of microbes that carry resistance genes, a process that produces genetically identical (or clonal) progeny. Rapid diagnostic methods and surveillance are some of the most valuable tools in preventing the spread of resistance. Access to more rapid diagnostic tests that could determine the causative agent and antibiotic susceptibility of infections would inform better decision making with respect to antibiotic use, help slow the selection of resistant strains in clinical settings, and enable better disease surveillance. A rigorous surveillance network to track the evolution and spread of resistance is also needed and would probably result in significant savings in healthcare. Developing countries face unique challenges when it comes to antibiotic resistance; chief among them may be the wide availability of antibiotics without a prescription and also counterfeit products of dubious quality. Lack of adequate hygiene, poor water quality, and failure to manage human waste also top the list. Recommendations for addressing the problems of widespread resistance in the developing world include: proposals for training and infrastructure capacity building; surveillance programs; greater access to susceptibility testing; government controls on import, manufacture and use; development and use of vaccines; and incentives for pharmaceutical companies to supply drugs to these countries. Controlling antibiotic resistant bacteria and subsequent infections more efficiently necessitates the prudent and responsible use of antibiotics. It is mandatory to prevent the needless use of antibiotics (e.g., viral infections; unnecessary prolonged treatment) and to improve the rapid prescription of appropriate antibiotics to a patient. Delayed or inadequate prescriptions reduce the efficacy of treatment and favor the spread of the infection. Prudent use also applies to veterinary medicine. For example, antibiotics used as “growth promoters” have been banned in Europe and are subject to review in some other countries. There are proven techniques for limiting the spread of resistance, including hand hygiene, but more rapid screening techniques are needed in order to effectively track and prevent spread in clinical settings. The spread of antibiotic resistance on farms and in veterinary hospitals may also be significant and should not be neglected. Research is needed to pursue alternative approaches, including vaccines, antisense therapy, public health initiatives, and others. The important messages about antibiotic resistance are not getting across from scientists and infectious diseases specialists to prescribers, stakeholders, including the public, healthcare providers, and public officials. Innovative and effective communication initiatives are needed, as are carefully tailored messages for each of the stakeholder groups. | 2009 | 32644325 |
| 4776 | 3 | 0.9952 | Integrate genome-based assessment of safety for probiotic strains: Bacillus coagulans GBI-30, 6086 as a case study. Probiotics are microorganisms that confer beneficial effects on the host; nevertheless, before being allowed for human consumption, their safety must be verified with accurate protocols. In the genomic era, such procedures should take into account the genomic-based approaches. This study aims at assessing the safety traits of Bacillus coagulans GBI-30, 6086 integrating the most updated genomics-based procedures and conventional phenotypic assays. Special attention was paid to putative virulence factors (VF), antibiotic resistance (AR) genes and genes encoding enzymes responsible for harmful metabolites (i.e. biogenic amines, BAs). This probiotic strain was phenotypically resistant to streptomycin and kanamycin, although the genome analysis suggested that the AR-related genes were not easily transferrable to other bacteria, and no other genes with potential safety risks, such as those related to VF or BA production, were retrieved. Furthermore, no unstable elements that could potentially lead to genomic rearrangements were detected. Moreover, a workflow is proposed to allow the proper taxonomic identification of a microbial strain and the accurate evaluation of risk-related gene traits, combining whole genome sequencing analysis with updated bioinformatics tools and standard phenotypic assays. The workflow presented can be generalized as a guideline for the safety investigation of novel probiotic strains to help stakeholders (from scientists to manufacturers and consumers) to meet regulatory requirements and avoid misleading information. | 2016 | 26952108 |
| 5819 | 4 | 0.9951 | Application of mNGS in the Etiological Analysis of Lower Respiratory Tract Infections and the Prediction of Drug Resistance. Lower respiratory tract infections (LRTIs) have high morbidity and mortality rates. However, traditional etiological detection methods have not been able to meet the needs for the clinical diagnosis and prognosis of LRTIs. The rapid development of metagenomic next-generation sequencing (mNGS) provides new insights for the diagnosis and treatment of LRTIs; however, little is known about how to interpret the application of mNGS results in LRTIs. In this study, lower respiratory tract specimens from 46 patients with suspected LRTIs were tested simultaneously using conventional microbiological detection methods and mNGS. Receiver operating characteristic (ROC) curves were used to evaluate the performance of the logarithm of reads per kilobase per million mapped reads [lg(RPKM)], genomic coverage, and relative abundance of the organism in predicting the true-positive pathogenic bacteria. True-positive viruses were identified according to the lg(RPKM) threshold of bacteria. We also evaluated the ability to predict drug resistance genes using mNGS. Compared to that using conventional detection methods, the false-positive detection rate of pathogenic bacteria was significantly higher using mNGS. It was concluded from the ROC curves that the lg(RPKM) and genomic coverage contributed to the identification of pathogenic bacteria, with the performance of lg(RPKM) being the best (area under the curve [AUC] = 0.99). The corresponding lg(RPKM) threshold for identifying the pathogenic bacteria was -1.35. Thirty-five strains of true-positive virus were identified based on the lg(RPKM) threshold of bacteria, with the detection of human gammaherpesvirus 4 being the highest and prone to coinfection with Pseudomonas aeruginosa, Acinetobacter baumannii, and Stenotrophomonas maltophilia. Antimicrobial susceptibility tests (AST) revealed the resistance of bacteria containing drug resistance genes (detected by mNGS). However, the drug resistance genes of some multidrug-resistant bacteria were not detected. As an emerging technology, mNGS has shown many advantages for the unbiased etiological detection and the prediction of antibiotic resistance. However, a correct understanding of mNGS results is a prerequisite for its clinical application, especially for LRTIs. IMPORTANCE LRTIs are caused by hundreds of pathogens, and they have become a great threat to human health due to the limitations of traditional etiological detection methods. As an unbiased approach to detect pathogens, mNGS overcomes such etiological diagnostic challenges. However, there is no unified standard on how to use mNGS indicators (the sequencing reads, genomic coverage, and relative abundance of each organism) to distinguish between pathogens and colonizing microorganisms or contaminant microorganisms. Here, we selected the mNGS indicator with the best identification performance and established a cutoff value for the identification of pathogens in LRTIs using ROC curves. In addition, we also evaluated the accuracy of antibiotic resistance prediction using mNGS. | 2022 | 35171007 |
| 2554 | 5 | 0.9951 | Development of an antibiotic resistance monitoring system in Hungary. Because of the rapid development and spread of antimicrobial resistance it is important that a system be established to monitor antimicrobial resistance in pathogenic zoonotic and commensal bacteria of animal origin. Susceptibility testing of bacteria from carcasses and different samples of animal origin has been carried out in veterinary institutes for a long time but by an inconsistent methodology. The disc diffusion method proposed by the National Committee for Clinical Laboratory Standards (NCCLS) was introduced in all institutes in 1997. In order to obtain a coherent view of the antimicrobial resistance of bacteria a computer system was consulted, consisting of a central computer to store all data and some local computers attached to it through the network. At these local measuring stations computers are connected to a video camera, which displays the picture of Petri dishes on the monitor, and inhibition zone diameters of bacteria can be drawn with the mouse by the inspector. The software measures the diameters, evaluates whether or not the bacteria are sensitive, and stores the data. The evaluation is based upon the data of the NCCLS. The central computer can be connected to as many local computers with measuring stations as we wish, so it is suitable for an integrated system for monitoring trends in antimicrobial resistance of bacteria from animals, food and humans, facilitating comparison of the occurrence of resistance for each circumstance in the chain. It depends on the examiners which antibiotics they want to examine. Thirty-two different antibiotic panels were compiled, taking into consideration the active ingredients of medicinal products permitted for veterinary use in Hungary, natural resistance and cross-resistance, the mechanism of resistance and the animal species, i.e. which drugs were recommended for treatment in the given animal species, and the recommendations of the OIE Expert Group on Antimicrobial Resistance. The members of the panels can be changed any time, even during the measuring process. In addition to the inhibition zone diameters of bacteria the database also includes information about bacterial and animal species, the age of animals and the sample or organ where the bacteria are from. Since January 2001 the antibiotic susceptibility of E. coli, Salmonella, Campylobacter and Enterococcus strains isolated from the colons of slaughter cows, pigs and broiler chickens has also been examined. Each of the 19 counties of Hungary submits to the laboratory three tied colon samples from a herd of the above-mentioned animals every month. | 2002 | 12113174 |
| 5117 | 6 | 0.9951 | Metagenomic sequencing of mpox virus clade Ib lesions identifies possible bacterial and viral co-infections in hospitalized patients in eastern DRC. Mpox is an emerging zoonotic disease that caused two public health emergencies of international concern within two years. Less is known about the interplay of microbial organisms in mpox lesions which could result in superinfections that exacerbate outcomes or delay recovery. We utilized a unified metagenomic sequencing approach involving slow-speed centrifugation and differential lysis on 19 mpox lesion swabs of hospitalized patients in South Kivu province (eastern DRC) to characterize bacteria, antimicrobial resistance genes, mpox virus (MPXV), and viral co-infections. High-quality MPXV whole-genome sequences were obtained until a Ct value of 27. Furthermore, co-infections with other clinically relevant viruses, such as varicella zoster virus and herpes simplex virus-2, were detected and confirmed by real-time PCR. In addition, metagenomic sequence analysis of the bacterial content showed the presence of bacteria associated with skin and soft tissue infection in 10 of the 19 samples analyzed. These bacteria had a high abundance of resistance genes, with possible implications for antimicrobial treatment based on the predicted antimicrobial resistance. In conclusion, we report the presence of bacterial and viral pathogens in mpox lesions and detection of widespread resistance genes to the standard antibiotic treatment. The possibility of a co-infection, including antimicrobial resistance, should be considered when discussing treatment options, along with the determination of the case-fatality ratio.IMPORTANCEThe mpox virus clade Ib lineage emerged in the eastern Democratic Republic of the Congo owing to continuous human-to-human transmission in a vulnerable patient population. A major challenge of this ongoing outbreak is its occurrence in regions with severely limited healthcare infrastructure. As a result, less is known about co-infections in affected patients. Identifying and characterizing pathogens, including their antimicrobial resistance, is crucial for reducing infection-related complications and improving antimicrobial stewardship. In this study, we applied a unified metagenomics approach to detect and characterize bacterial and viral co-infections in mpox lesions of hospitalized mpox patients in the eastern DRC. | 2025 | 40445195 |
| 5118 | 7 | 0.9951 | Automated extraction of genes associated with antibiotic resistance from the biomedical literature. The detection of bacterial antibiotic resistance phenotypes is important when carrying out clinical decisions for patient treatment. Conventional phenotypic testing involves culturing bacteria which requires a significant amount of time and work. Whole-genome sequencing is emerging as a fast alternative to resistance prediction, by considering the presence/absence of certain genes. A lot of research has focused on determining which bacterial genes cause antibiotic resistance and efforts are being made to consolidate these facts in knowledge bases (KBs). KBs are usually manually curated by domain experts to be of the highest quality. However, this limits the pace at which new facts are added. Automated relation extraction of gene-antibiotic resistance relations from the biomedical literature is one solution that can simplify the curation process. This paper reports on the development of a text mining pipeline that takes in English biomedical abstracts and outputs genes that are predicted to cause resistance to antibiotics. To test the generalisability of this pipeline it was then applied to predict genes associated with Helicobacter pylori antibiotic resistance, that are not present in common antibiotic resistance KBs or publications studying H. pylori. These genes would be candidates for further lab-based antibiotic research and inclusion in these KBs. For relation extraction, state-of-the-art deep learning models were used. These models were trained on a newly developed silver corpus which was generated by distant supervision of abstracts using the facts obtained from KBs. The top performing model was superior to a co-occurrence model, achieving a recall of 95%, a precision of 60% and F1-score of 74% on a manually annotated holdout dataset. To our knowledge, this project was the first attempt at developing a complete text mining pipeline that incorporates deep learning models to extract gene-antibiotic resistance relations from the literature. Additional related data can be found at https://github.com/AndreBrincat/Gene-Antibiotic-Resistance-Relation-Extraction. | 2022 | 35134132 |
| 5103 | 8 | 0.9951 | Revolutionising bacteriology to improve treatment outcomes and antibiotic stewardship. LABORATORY INVESTIGATION OF BACTERIAL INFECTIONS GENERALLY TAKES TWO DAYS: one to grow the bacteria and another to identify them and to test their susceptibility. Meanwhile the patient is treated empirically, based on likely pathogens and local resistance rates. Many patients are over-treated to prevent under-treatment of a few, compromising antibiotic stewardship. Molecular diagnostics have potential to improve this situation by accelerating precise diagnoses and the early refinement of antibiotic therapy. They include: (i) the use of 'biomarkers' to swiftly distinguish patients with bacterial infection, and (ii) molecular bacteriology to identify pathogens and their resistance genes in clinical specimens, without culture. Biomarker interest centres on procalcitonin, which has given good results particularly for pneumonias, though broader biomarker arrays may prove superior in the future. PCRs already are widely used to diagnose a few infections (e.g. tuberculosis) whilst multiplexes are becoming available for bacteraemia, pneumonia and gastrointestinal infection. These detect likely pathogens, but are not comprehensive, particularly for resistance genes; there is also the challenge of linking pathogens and resistance genes when multiple organisms are present in a sample. Next-generation sequencing offers more comprehensive profiling, but obstacles include sensitivity when the bacterial load is low, as in bacteraemia, and the imperfect correlation of genotype and phenotype. In short, rapid molecular bacteriology presents great potential to improve patient treatments and antibiotic stewardship but faces many technical challenges; moreover it runs counter to the current nostrum of defining resistance in pharmacodynamic terms, rather than by the presence of a mechanism, and the policy of centralising bacteriology services. | 2013 | 24265945 |
| 5168 | 9 | 0.9951 | Bacteriophage Resistance Affects Flavobacterium columnare Virulence Partly via Mutations in Genes Related to Gliding Motility and the Type IX Secretion System. Increasing problems with antibiotic resistance have directed interest toward phage therapy in the aquaculture industry. However, phage resistance evolving in target bacteria is considered a challenge. To investigate how phage resistance influences the fish pathogen Flavobacterium columnare, two wild-type bacterial isolates, FCO-F2 and FCO-F9, were exposed to phages (FCO-F2 to FCOV-F2, FCOV-F5, and FCOV-F25, and FCO-F9 to FCL-2, FCOV-F13, and FCOV-F45), and resulting phenotypic and genetic changes in bacteria were analyzed. Bacterial viability first decreased in the exposure cultures but started to increase after 1 to 2 days, along with a change in colony morphology from original rhizoid to rough, leading to 98% prevalence of the rough morphotype. Twenty-four isolates (including four isolates from no-phage treatments) were further characterized for phage resistance, antibiotic susceptibility, motility, adhesion, and biofilm formation, protease activity, whole-genome sequencing, and virulence in rainbow trout fry. The rough isolates arising in phage exposure were phage resistant with low virulence, whereas rhizoid isolates maintained phage susceptibility and high virulence. Gliding motility and protease activity were also related to the phage susceptibility. Observed mutations in phage-resistant isolates were mostly located in genes encoding the type IX secretion system, a component of the Bacteroidetes gliding motility machinery. However, not all phage-resistant isolates had mutations, indicating that phage resistance in F. columnare is a multifactorial process, including both genetic mutations and changes in gene expression. Phage resistance may not, however, be a challenge for development of phage therapy against F. columnare infections since phage resistance is associated with decreases in bacterial virulence. IMPORTANCE Phage resistance of infectious bacteria is a common phenomenon posing challenges for the development of phage therapy. Along with a growing world population and the need for increased food production, constantly intensifying animal farming has to face increasing problems of infectious diseases. Columnaris disease, caused by Flavobacterium columnare, is a worldwide threat for salmonid fry and juvenile farming. Without antibiotic treatments, infections can lead to 100% mortality in a fish stock. Phage therapy of columnaris disease would reduce the development of antibiotic-resistant bacteria and antibiotic loads by the aquaculture industry, but phage-resistant bacterial isolates may become a risk. However, phenotypic and genetic characterization of phage-resistant F. columnare isolates in this study revealed that they are less virulent than phage-susceptible isolates and thus not a challenge for phage therapy against columnaris disease. This is valuable information for the fish farming industry globally when considering phage-based prevention and curing methods for F. columnare infections. | 2021 | 34106011 |
| 5826 | 10 | 0.9950 | Rapid and accurate sepsis diagnostics via a novel probe-based multiplex real-time PCR system. Sepsis is a critical clinical emergency that requires prompt diagnosis and intervention. Its prevalence has increased due to the aging population and increased antibiotic resistance. Early identification and the use of innovative technologies are crucial for improving patient outcomes. Modern methodologies are needed to minimize the turnaround time for diagnosis and improve outcomes. Rapid diagnostic tests and multiplex PCR are effective but have limitations in identifying a range of pathogens and target genes. Our study evaluated two novel probe-based multiplex real-time PCR systems: the SEPSI ID and SEPSI DR panels. These systems can quickly identify bacterial and fungal pathogens, alongside antibiotic resistance genes. The assays cover 29 microorganisms (gram-negative bacteria, gram-positive bacteria, yeast, and mold species), alongside 23 resistance genes and four virulence factors. A streamlined workflow uses 2 µL of broth from positive blood cultures (BCs) without nucleic acid extraction and provides results in approximately 1 h. We present the results from an evaluation of 228 BCs and 22 isolates previously characterized by whole-genome sequencing. In comparison to the reference methods, the SEPSI ID panel demonstrated a sensitivity of 96.88%, a specificity of 100%, and a PPV of 100%, whereas the SEPSI DR panel showed a sensitivity of 97.8%, a PPV of 89.7%, and a specificity of 96.7%. Both panels also identified additional pathogens and resistance-related targets not detected by conventional methods. This assay shows promise for rapidly and accurately diagnosing sepsis. Future studies should validate its performance in various clinical settings to enhance sepsis management and improve patient outcomes.IMPORTANCEWe present a new diagnostic method that enables the quick and precise identification of pathogens and resistance genes from positive blood cultures, eliminating the need for nucleic acid extraction. This technique can also be used on fresh pathogen cultures. It has the potential to greatly improve treatment protocols, leading to better patient outcomes, more responsible antibiotic use, and more efficient management of healthcare resources. | 2025 | 41025980 |
| 2522 | 11 | 0.9950 | Identification and specificity validation of unique and antimicrobial resistance genes to trace suspected pathogenic AMR bacteria and to monitor the development of AMR in non-AMR strains in the environment and clinical settings. The detection of developing antimicrobial resistance (AMR) has become a global issue. The detection of developing antimicrobial resistance has become a global issue. The growing number of AMR bacteria poses a new threat to public health. Therefore, a less laborious and quick confirmatory test becomes important for further investigations into developing AMR in the environment and in clinical settings. This study aims to present a comprehensive analysis and validation of unique and antimicrobial-resistant strains from the WHO priority list of antimicrobial-resistant bacteria and previously reported AMR strains such as Acinetobacter baumannii, Aeromonas spp., Anaeromonas frigoriresistens, Anaeromonas gelatinfytica, Bacillus spp., Campylobacter jejuni subsp. jejuni, Enterococcus faecalis, Escherichia coli, Haemophilus influenzae, Helicobacter pylori, Klebsiella pneumonia subsp. pneumoniae, Pseudomonas aeruginosa, Salmonella enterica subsp. enterica serovar Typhimurium, Thermanaeromonas toyohensis, and Vibrio proteolyticus. Using in-house designed gene-specific primers, 18 different antibiotic resistance genes (algJ, alpB, AQU-1, CEPH-A3, ciaB, CMY-1-MOX-7, CMY-1-MOX-9, CMY-1/MOX, cphA2, cphA5, cphA7, ebpA, ECP_4655, fliC, OXA-51, RfbU, ThiU2, and tolB) from 46 strains were selected and validated. Hence, this study provides insight into the identification of strain-specific, unique antimicrobial resistance genes. Targeted amplification and verification using selected unique marker genes have been reported. Thus, the present detection and validation use a robust method for the entire experiment. Results also highlight the presence of another set of 18 antibiotic-resistant and unique genes (Aqu1, cphA2, cphA3, cphA5, cphA7, cmy1/mox7, cmy1/mox9, asaI, ascV, asoB, oxa-12, acr-2, pepA, uo65, pliI, dr0274, tapY2, and cpeT). Of these sets of genes, 15 were found to be suitable for the detection of pathogenic strains belonging to the genera Aeromonas, Pseudomonas, Helicobacter, Campylobacter, Enterococcus, Klebsiella, Acinetobacter, Salmonella, Haemophilus, and Bacillus. Thus, we have detected and verified sets of unique and antimicrobial resistance genes in bacteria on the WHO Priority List and from published reports on AMR bacteria. This study offers advantages for confirming antimicrobial resistance in all suspected AMR bacteria and monitoring the development of AMR in non-AMR bacteria, in the environment, and in clinical settings. | 2023 | 38058762 |
| 4779 | 12 | 0.9950 | First Molecular Characterization of Siphoviridae-Like Bacteriophages Infecting Staphylococcus hyicus in a Case of Exudative Epidermitis. Exudative epidermitis (EE), also known as greasy pig disease, is one of the most frequent skin diseases affecting piglets. Zoonotic infections in human occur. EE is primarily caused by virulent strains of Staphylococcus (S.) hyicus. Generally, antibiotic treatment of this pathogen is prone to decreasing success, due to the incremental development of multiple resistances of bacteria against antibiotics. Once approved, bacteriophages might offer interesting alternatives for environmental sanitation or individualized treatment, subject to the absence of virulence and antimicrobial resistance genes. However, genetic characterization of bacteriophages for S. hyicus has, so far, been missing. Therefore, we investigated a piglet raising farm with a stock problem due to EE. We isolated eleven phages from the environment and wash water of piglets diagnosed with the causative agent of EE, i.e., S. hyicus. The phages were morphologically characterized by electron microscopy, where they appeared Siphoviridae-like. The genomes of two phages were sequenced on a MiSeq instrument (Illumina), resulting in the identification of a new virulent phage, PITT-1 (PMBT8), and a temperate phage, PITT-5 (PMBT9). Sequencing of three host bacteria (S. hyicus) from one single farm revealed the presence of two different strains with genes coding for two different exfoliative toxin genes, i.e., exhA (2 strains) and exhC (1 strain). The exhC-positive S. hyicus strain was only weakly lysed by most lytic phages. The occurrence of different virulent S. hyicus strains in the same outbreak limits the prospects for successful phage treatment and argues for the simultaneous use of multiple and different phages attacking the same host. | 2021 | 34305825 |
| 9760 | 13 | 0.9950 | Mutations leading to ceftolozane/tazobactam and imipenem/cilastatin/relebactam resistance during in vivo exposure to ceftazidime/avibactam in Pseudomonas aeruginosa. Identifying resistance mechanisms to novel antimicrobials informs treatment strategies during infection and antimicrobial development. Studying resistance that develops during the treatment of an infection can provide the most clinically relevant mutations conferring resistance, but cross-sectional studies frequently identify multiple candidate resistance mutations without resolving the driver mutation. We performed whole-genome sequencing of longitudinal Pseudomonas aeruginosa from a patient whose P. aeruginosa developed imipenem/cilastatin/relebactam and ceftolozane/tazobactam resistance during ceftazidime/avibactam treatment. This analysis determined new mutations that arose in isolates resistant to both imipenem/cilastatin/relebactam and ceftolozane/tazobactam. Mutations in penicillin-binding protein 3 ftsI, the MexAB-OprM repressor nalD, and a virulence regulator pvdS were found in resistant isolates. Importantly, drug efflux was not increased in the resistant isolate compared to the most closely related susceptible isolates. We conclude that mutations in peptidoglycan synthesis genes can alter the efficacy of multiple antimicrobials. IMPORTANCE: Antibiotic resistance is a significant challenge for physicians trying to treat infections. The development of novel antibiotics to treat resistant infections has not been prioritized for decades, limiting treatment options for infections caused by many high-priority pathogens. Cross-resistance, when one mutation provides resistance to multiple antibiotics, is most problematic. Mutations that cause cross-resistance need to be considered when developing new antibiotics to guide developers toward drugs with different targets, and thus a better likelihood of efficacy. This work was undertaken to determine the mutation that caused resistance to three antibiotics for highly resistant Pseudomonas aeruginosa infection treatment while the bacteria were exposed to only one of these agents. The findings provide evidence that drug developers should endeavor to find effective antibiotics with new targets and that medical providers should utilize medications with different mechanisms of action in bacteria that have become resistant to even one of these three agents. | 2025 | 39932323 |
| 4886 | 14 | 0.9950 | Molecular diagnostics for genotypic detection of antibiotic resistance: current landscape and future directions. Antimicrobial resistance (AMR) among bacteria is an escalating public health emergency that has worsened during the COVID-19 pandemic. When making antibiotic treatment decisions, clinicians rely heavily on determination of antibiotic susceptibility or resistance by the microbiology laboratory, but conventional methods often take several days to identify AMR. There are now several commercially available molecular methods that detect antibiotic resistance genes within hours rather than days. While these methods have limitations, they offer promise for optimizing treatment and patient outcomes, and reducing further emergence of AMR. This review provides an overview of commercially available genotypic assays that detect individual resistance genes and/or resistance-associated mutations in a variety of specimen types and discusses how clinical outcomes studies may be used to demonstrate clinical utility of such diagnostics. | 2023 | 36816746 |
| 5099 | 15 | 0.9950 | A machine learning-based strategy to elucidate the identification of antibiotic resistance in bacteria. Microorganisms, crucial for environmental equilibrium, could be destructive, resulting in detrimental pathophysiology to the human host. Moreover, with the emergence of antibiotic resistance (ABR), the microbial communities pose the century's largest public health challenges in terms of effective treatment strategies. Furthermore, given the large diversity and number of known bacterial strains, describing treatment choices for infected patients using experimental methodologies is time-consuming. An alternative technique, gaining popularity as sequencing prices fall and technology advances, is to use bacterial genotype rather than phenotype to determine ABR. Complementing machine learning into clinical practice provides a data-driven platform for categorization and interpretation of bacterial datasets. In the present study, k-mers were generated from nucleotide sequences of pathogenic bacteria resistant to antibiotics. Subsequently, they were clustered into groups of bacteria sharing similar genomic features using the Affinity propagation algorithm with a Silhouette coefficient of 0.82. Thereafter, a prediction model based on Random Forest algorithm was developed to explore the prediction capability of the k-mers. It yielded an overall specificity of 0.99 and a sensitivity of 0.98. Additionally, the genes and ABR drivers related to the k-mers were identified to explore their biological relevance. Furthermore, a multilayer perceptron model with a hamming loss of 0.05 was built to classify the bacterial strains into resistant and non-resistant strains against various antibiotics. Segregating pathogenic bacteria based on genomic similarities could be a valuable approach for assessing the severity of diseases caused by new bacterial strains. Utilization of this strategy could aid in enhancing our understanding of ABR patterns, paving the way for more informed and effective treatment options. | 2024 | 39816256 |
| 8403 | 16 | 0.9949 | Uncovering virulence factors in Cronobacter sakazakii: insights from genetic screening and proteomic profiling. The increasing problem of antibiotic resistance has driven the search for virulence factors in pathogenic bacteria, which can serve as targets for the development of new antibiotics. Although whole-genome Tn5 transposon mutagenesis combined with phenotypic assays has been a widely used approach, its efficiency remains low due to labor-intensive processes. In this study, we aimed to identify specific genes and proteins associated with the virulence of Cronobacter sakazakii, a pathogenic bacterium known for causing severe infections, particularly in infants and immunocompromised individuals. By employing a combination of genetic screening, comparative proteomics, and in vivo validation using zebrafish and rat models, we rapidly screened highly virulent strains and identified two genes, rcsA and treR, as potential regulators of C. sakazakii toxicity toward zebrafish and rats. Proteomic profiling revealed upregulated proteins upon knockout of rcsA and treR, including FabH, GshA, GppA, GcvH, IhfB, RfaC, MsyB, and three unknown proteins. Knockout of their genes significantly weakened bacterial virulence, confirming their role as potential virulence factors. Our findings contribute to understanding the pathogenicity of C. sakazakii and provide insights into the development of targeted interventions and therapies against this bacterium.IMPORTANCEThe emergence of antibiotic resistance in pathogenic bacteria has become a critical global health concern, necessitating the identification of virulence factors as potential targets for the development of new antibiotics. This study addresses the limitations of conventional approaches by employing a combination of genetic screening, comparative proteomics, and in vivo validation to rapidly identify specific genes and proteins associated with the virulence of Cronobacter sakazakii, a highly pathogenic bacterium responsible for severe infections in vulnerable populations. The identification of two genes, rcsA and treR, as potential regulators of C. sakazakii toxicity toward zebrafish and rats and the proteomic profiling upon knockout of rcsA and treR provides novel insights into the mechanisms underlying bacterial virulence. The findings contribute to our understanding of C. sakazakii's pathogenicity, shed light on the regulatory pathways involved in bacterial virulence, and offer potential targets for the development of novel interventions against this highly virulent bacterium. | 2023 | 37750707 |
| 2587 | 17 | 0.9949 | Prevalence of multi-drug resistant bacteria associated with foods and drinks in Nigeria (2015-2020): A systematic review. Foods are essential vehicles in human exposure to antibiotic resistant bacteria which serve as reservoirs for resistance genes and a rising food safety concern. Antimicrobial resistance, including multidrug resistance (MDR), is an increasing problem globally and poses a serious concern to human health. This study was designed to synthesize data regarding the prevalence of MDR bacteria associated with foods and drinks sold within Nigeria in order to contribute to the existing findings in this area. A comprehensive literature search on the prevalence of multi-drug resistant bacteria associated with foods and drinks in Nigeria from 2015 to 2020 was conducted using three databases; PubMed, Science Direct and Scopus. After screening and selection, 26 out of 82 articles were used for the qualitative data synthesis. Of the total of one thousand three hundred and twenty-six MDR bacteria reportedly isolated in all twenty-six articles, the highest prevalence (660) was observed in drinks, including water, while the lowest (20) was observed in the article which combined results for both protein and vegetable-based foods. Escherichia sp. had the most frequency of occurrence, appearing as MDR bacteria in ten out of the twenty-six articles. Salmonella sp. appeared as MDR in seven out of the twenty-six articles included in this study, in all seven articles where it was reported, it had the highest percentage (85.4%) prevalence as MDR bacteria. Public health personnel need to ensure critical control during the production and handling of foods and drinks, as well as create more awareness on proper hygienic practices to combat the spread of MDR bacteria becoming a growing food safety issue (Zurfluh et al., 2019; Mesbah et al., 2017; Campos et al., 2019). Foods can be contaminated by different means, including exposure to irrigation water, manure, feces or soil with pathogenic bacteria. Foods can also become contaminated as they are harvested, handled after harvest or during processing if food safety standards are not correctly applied (Meshbah et al., 2017). Food-borne diseases caused by resistant organisms are one of the most important public health problems as they contribute to the risk of development of antibiotic resistance in the food production chain (Hehempour-Baltork et al., 2019). Apart from pathogenic bacteria causing foodborne diseases, foods that are raw or not processed following standard procedures can introduce several antibiotic-resistant bacteria (ARB) to consumers (Gekemidis et al., 2018). Antibiotic resistance, though harbored in non-pathogenic bacteria, can potentially be spread through horizontal gene transfer to other species including opportunistic pathogens that are present in the environment or after consumption of ARB-contaminated foods. When ARB-contaminated foods are consumed, the spread of antibiotic resistant genes may affect the gut microbiome thereby contributing to the pool of antibiotic-resistance genes (ARG) in the human gut (Gekemidis et al, 2018). MDR bacteria have been defined as bacteria that are resistant to at least one antimicrobial agent present in three or more antimicrobial classes (Sweeny et al., 2018). There has been an increase in drug resistance in pathogens isolated from food for human consumption with species of Escherichia coli and Salmonella enterica being considered among the most important pathogens due to their ability to effect zoonotic transfer of resistant genes (Canton et al., 2018; Maneilla-Becerra et al., 2019). However, other pathogens, such as Vibrio spp., some species of Aeromonas, spores of Clostridium botulinum type F, and Campylobacter, have been linked to food-borne diseases in humans who have consumed seafood or other animal foods (Maneilla-Becerra et al., 2019). Some other resistant bacteria associated with foods include Staphylococcus aureus, Listeria spp., and Shigella spp. (Maneilla-Becerra et al., 2019) This study was therefore designed to synthesize data (2015-2020) regarding the prevalence of MDR bacteria associated with foods and drinks sold within Nigeria in order to contribute to the existing findings in this area. | 2021 | 35018289 |
| 5098 | 18 | 0.9949 | Feature selection and aggregation for antibiotic resistance GWAS in Mycobacterium tuberculosis: a comparative study. INTRODUCTION: Drug resistance (DR) of pathogens remains a global healthcare concern. In contrast to other bacteria, acquiring mutations in the core genome is the main mechanism of drug resistance for Mycobacterium tuberculosis (MTB). For some antibiotics, the resistance of a particular isolate can be reliably predicted by identifying specific mutations, while for other antibiotics the knowledge of resistance mechanisms is limited. Statistical machine learning (ML) methods are used to infer new genes implicated in drug resistance leveraging large collections of isolates with known whole-genome sequences and phenotypic states for different drugs. However, high correlations between the phenotypic states for commonly used drugs complicate the inference of true associations of mutations with drug phenotypes by ML approaches. METHODS: Recently, several new methods have been developed to select a small subset of reliable predictors of the dependent variable, which may help reduce the number of spurious associations identified. In this study, we evaluated several such methods, namely, logistic regression with different regularization penalty functions, a recently introduced algorithm for solving the best-subset selection problem (ABESS) and "Hungry, Hungry SNPos" (HHS) a heuristic algorithm specifically developed to identify resistance-associated genetic variants in the presence of resistance co-occurrence. We assessed their ability to select known causal mutations for resistance to a specific drug while avoiding the selection of mutations in genes associated with resistance to other drugs, thus we compared selected ML models for their applicability for MTB genome wide association studies. RESULTS AND DISCUSSION: In our analysis, ABESS significantly outperformed the other methods, selecting more relevant sets of mutations. Additionally, we demonstrated that aggregating rare mutations within protein-coding genes into markers indicative of changes in PFAM domains improved prediction quality, and these markers were predominantly selected by ABESS, suggesting their high informativeness. However, ABESS yielded lower prediction accuracy compared to logistic regression methods with regularization. | 2025 | 40606161 |
| 5116 | 19 | 0.9949 | Prediction of Antimicrobial Resistance in Gram-Negative Bacteria From Whole-Genome Sequencing Data. BACKGROUND: Early detection of antimicrobial resistance in pathogens and prescription of more effective antibiotics is a fast-emerging need in clinical practice. High-throughput sequencing technology, such as whole genome sequencing (WGS), may have the capacity to rapidly guide the clinical decision-making process. The prediction of antimicrobial resistance in Gram-negative bacteria, often the cause of serious systemic infections, is more challenging as genotype-to-phenotype (drug resistance) relationship is more complex than for most Gram-positive organisms. METHODS AND FINDINGS: We have used NCBI BioSample database to train and cross-validate eight XGBoost-based machine learning models to predict drug resistance to cefepime, cefotaxime, ceftriaxone, ciprofloxacin, gentamicin, levofloxacin, meropenem, and tobramycin tested in Acinetobacter baumannii, Escherichia coli, Enterobacter cloacae, Klebsiella aerogenes, and Klebsiella pneumoniae. The input is the WGS data in terms of the coverage of known antibiotic resistance genes by shotgun sequencing reads. Models demonstrate high performance and robustness to class imbalanced datasets. CONCLUSION: Whole genome sequencing enables the prediction of antimicrobial resistance in Gram-negative bacteria. We present a tool that provides an in silico antibiogram for eight drugs. Predictions are accompanied with a reliability index that may further facilitate the decision making process. The demo version of the tool with pre-processed samples is available at https://vancampn.shinyapps.io/wgs2amr/. The stand-alone version of the predictor is available at https://github.com/pieterjanvc/wgs2amr/. | 2020 | 32528441 |