# | Rank | Similarity | Title + Abs. | Year | PMID |
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| 0 | 1 | 2 | 3 | 4 | 5 |
| 5117 | 0 | 1.0000 | 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 |
| 5002 | 1 | 0.9994 | Genomic Diversity of Hospital-Acquired Infections Revealed through Prospective Whole-Genome Sequencing-Based Surveillance. Healthcare-associated infections (HAIs) cause mortality, morbidity, and waste of health care resources. HAIs are also an important driver of antimicrobial resistance, which is increasing around the world. Beginning in November 2016, we instituted an initiative to detect outbreaks of HAIs using prospective whole-genome sequencing-based surveillance of bacterial pathogens collected from hospitalized patients. Here, we describe the diversity of bacteria sampled from hospitalized patients at a single center, as revealed through systematic analysis of bacterial isolate genomes. We sequenced the genomes of 3,004 bacterial isolates from hospitalized patients collected over a 25-month period. We identified bacteria belonging to 97 distinct species, which were distributed among 14 groups of related species. Within these groups, isolates could be distinguished from one another by both average nucleotide identity (ANI) and principal-component analysis of accessory genes (PCA-A). Core genome genetic distances and rates of evolution varied among species, which has practical implications for defining shared ancestry during outbreaks and for our broader understanding of the origins of bacterial strains and species. Finally, antimicrobial resistance genes and putative mobile genetic elements were frequently observed, and our systematic analysis revealed patterns of occurrence across the different species sampled from our hospital. Overall, this study shows how understanding the population structure of diverse pathogens circulating in a single health care setting can improve the discriminatory power of genomic epidemiology studies and can help define the processes leading to strain and species differentiation. IMPORTANCE Hospitalized patients are at increased risk of becoming infected with antibiotic-resistant organisms. We used whole-genome sequencing to survey and compare over 3,000 clinical bacterial isolates collected from hospitalized patients at a large medical center over a 2-year period. We identified nearly 100 different bacterial species, which we divided into 14 different groups of related species. When we examined how genetic relatedness differed between species, we found that different species were likely evolving at different rates within our hospital. This is significant because the identification of bacterial outbreaks in the hospital currently relies on genetic similarity cutoffs, which are often applied uniformly across organisms. Finally, we found that antibiotic resistance genes and mobile genetic elements were abundant and were shared among the bacterial isolates we sampled. Overall, this study provides an in-depth view of the genomic diversity and evolutionary processes of bacteria sampled from hospitalized patients, as well as genetic similarity estimates that can inform hospital outbreak detection and prevention efforts. | 2022 | 35695507 |
| 4940 | 2 | 0.9994 | Predicting Phenotypic Polymyxin Resistance in Klebsiella pneumoniae through Machine Learning Analysis of Genomic Data. Polymyxins are used as treatments of last resort for Gram-negative bacterial infections. Their increased use has led to concerns about emerging polymyxin resistance (PR). Phenotypic polymyxin susceptibility testing is resource intensive and difficult to perform accurately. The complex polygenic nature of PR and our incomplete understanding of its genetic basis make it difficult to predict PR using detection of resistance determinants. We therefore applied machine learning (ML) to whole-genome sequencing data from >600 Klebsiella pneumoniae clonal group 258 (CG258) genomes to predict phenotypic PR. Using a reference-based representation of genomic data with ML outperformed a rule-based approach that detected variants in known PR genes (area under receiver-operator curve [AUROC], 0.894 versus 0.791, P = 0.006). We noted modest increases in performance by using a bacterial genome-wide association study to filter relevant genomic features and by integrating clinical data in the form of prior polymyxin exposure. Conversely, reference-free representation of genomic data as k-mers was associated with decreased performance (AUROC, 0.692 versus 0.894, P = 0.015). When ML models were interpreted to extract genomic features, six of seven known PR genes were correctly identified by models without prior programming and several genes involved in stress responses and maintenance of the cell membrane were identified as potential novel determinants of PR. These findings are a proof of concept that whole-genome sequencing data can accurately predict PR in K. pneumoniae CG258 and may be applicable to other forms of complex antimicrobial resistance.IMPORTANCE Polymyxins are last-resort antibiotics used to treat highly resistant Gram-negative bacteria. There are increasing reports of polymyxin resistance emerging, raising concerns of a postantibiotic era. Polymyxin resistance is therefore a significant public health threat, but current phenotypic methods for detection are difficult and time-consuming to perform. There have been increasing efforts to use whole-genome sequencing for detection of antibiotic resistance, but this has been difficult to apply to polymyxin resistance because of its complex polygenic nature. The significance of our research is that we successfully applied machine learning methods to predict polymyxin resistance in Klebsiella pneumoniae clonal group 258, a common health care-associated and multidrug-resistant pathogen. Our findings highlight that machine learning can be successfully applied even in complex forms of antibiotic resistance and represent a significant contribution to the literature that could be used to predict resistance in other bacteria and to other antibiotics. | 2020 | 32457240 |
| 4894 | 3 | 0.9994 | Do we need new antibiotics? For several years, alarmist articles both in mass media and in the scientific community have reported an increase in antibiotic resistance, even citing an inability to treat patients infected with multidrug-resistant bacteria (MDR) responsible for high mortality worldwide. In this review we summarize and discuss the key points associated with the reality of (i) the existence of pandrug-resistant bacteria, (ii) the increase of resistance worldwide, (iii) the link between resistance and death, and (iv) the need to develop new antibiotics. Data on antibiotic resistance in Europe for the main bacteria associated with invasive infections apparently demonstrate that apart from Klebsiella pneumoniae, which is resistant to carbapenems in three countries (Romania, Italy and Greece), the level of resistance to three or more classes of antibiotics (defined as MDR phenotype) has remained low and stable over the last 5 years and that therapeutic options exist both for reference antibiotics and for old antibiotics. The clinical outcome of patients infected by MDR bacteria remains controversial and death rates attributable to MDR bacteria versus non-MDR bacteria are still debated. The arsenal of antibiotics currently available (including 'old antibiotics') suffices for facing the waves of emergence of new bacterial resistance and should be considered as a World Heritage. This heritage should be managed in a non-profit model with international regulatory approval. | 2016 | 27021418 |
| 4999 | 4 | 0.9994 | Dissemination Routes of Carbapenem and Pan-Aminoglycoside Resistance Mechanisms in Hospital and Urban Wastewater Canalizations of Ghana. Wastewater has a major role in antimicrobial resistance (AMR) dynamics and public health. The impact on AMR of wastewater flux at the community-hospital interface in low- and middle-income countries (LMICs) is poorly understood. Therefore, the present study analyzed the epidemiological scenario of resistance genes, mobile genetic elements (MGEs), and bacterial populations in wastewater around the Tamale metropolitan area (Ghana). Wastewater samples were collected from the drainage and canalizations before and after three hospitals and one urban waste treatment plant (UWTP). From all carbapenem/pan-aminoglycoside-resistant bacteria, 36 isolates were selected to determine bacterial species and phenotypical resistance profiles. Nanopore sequencing was used to screen resistance genes and plasmids, whereas, sequence types, resistome and plasmidome contents, pan-genome structures, and resistance gene variants were analyzed with Illumina sequencing. The combination of these sequencing data allowed for the resolution of the resistance gene-carrying platforms. Hospitals and the UWTP collected genetic and bacterial elements from community wastewater and amplified successful resistance gene-bacterium associations, which reached the community canalizations. Uncommon carbapenemase/β-lactamase gene variants, like bla(DIM-1), and novel variants, including bla(VIM-71), bla(CARB-53), and bla(CMY-172), were identified and seem to spread via clonal expansion of environmental Pseudomonas spp. However, bla(NDM-1), bla(CTX-M-15), and armA genes, among others, were associated with MGEs that allowed for their dissemination between environmental and clinical bacterial hosts. In conclusion, untreated hospital wastewater in Ghana is a hot spot for the emergence and spread of genes and gene-plasmid-bacterium associations that accelerate AMR, including to last-resort antibiotics. Urgent actions must be taken in wastewater management in LMICs in order to delay AMR expansion. IMPORTANCE Antimicrobial resistance (AMR) is one the major threats to public health today, especially resistance to last-resort compounds for the treatment of critical infections, such as carbapenems and aminoglycosides. Innumerable works have focused on the clinical ambit of AMR, but studies addressing the impact of wastewater cycles on the emergence and dissemination of resistant bacteria are still limited. The lack of knowledge is even greater when referring to low- and middle-income countries, where there is an absence of accurate sanitary systems. Furthermore, the combination of short- and long-read sequencing has surpassed former technical limitations, allowing the complete characterization of resistance genes, mobile genetic platforms, plasmids, and bacteria. The present study deciphered the multiple elements and routes involved in AMR dynamics in wastewater canalizations and, therefore, in the local population of Tamale, providing the basis to adopt accurate control measures to preserve and promote public health. | 2022 | 35103490 |
| 4851 | 5 | 0.9993 | A global view on carbapenem-resistant Acinetobacter baumannii. Carbapenem-resistant Acinetobacter baumannii are of increasing public health importance, as they are resistant to last-line antibiotics. International clones with well-characterized resistance genes dominate globally; however, locally, other lineages with different properties may be of importance to consider. This study investigated isolates from a broad geographic origin from 114 hospitals in 47 countries and from five world regions ensuring the greatest possible diversity in an organism known for its propensity for clonal epidemic spread and reflecting the current global epidemiology of carbapenem-resistant A. baumannii. In Latin America, a lineage different from other geographic regions circulates, with a different resistance gene profile. This knowledge is important to adjust local infection prevention measures. In a global world with migration and increasing use of antimicrobials, multidrug-resistant bacteria will continue to adapt and challenge our healthcare systems worldwide. | 2023 | 37882512 |
| 4856 | 6 | 0.9993 | An Overview on Phenotypic and Genotypic Characterisation of Carbapenem-Resistant Enterobacterales. Improper use of antimicrobials has resulted in the emergence of antimicrobial resistance (AMR), including multi-drug resistance (MDR) among bacteria. Recently, a sudden increase in Carbapenem-resistant Enterobacterales (CRE) has been observed. This presents a substantial challenge in the treatment of CRE-infected individuals. Bacterial plasmids include the genes for carbapenem resistance, which can also spread to other bacteria to make them resistant. The incidence of CRE is rising significantly despite the efforts of health authorities, clinicians, and scientists. Many genotypic and phenotypic techniques are available to identify CRE. However, effective identification requires the integration of two or more methods. Whole genome sequencing (WGS), an advanced molecular approach, helps identify new strains of CRE and screening of the patient population; however, WGS is challenging to apply in clinical settings due to the complexity and high expense involved with this technique. The current review highlights the molecular mechanism of development of Carbapenem resistance, the epidemiology of CRE infections, spread of CRE, treatment options, and the phenotypic/genotypic characterisation of CRE. The potential of microorganisms to acquire resistance against Carbapenems remains high, which can lead to even more susceptible drugs such as colistin and polymyxins. Hence, the current study recommends running the antibiotic stewardship programs at an institutional level to control the use of antibiotics and to reduce the spread of CRE worldwide. | 2022 | 36422214 |
| 5118 | 7 | 0.9993 | 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 |
| 5110 | 8 | 0.9993 | Surveillance of carbapenem-resistant organisms using next-generation sequencing. The genomic data generated from next-generation sequencing (NGS) provides nucleotide-level resolution of bacterial genomes which is critical for disease surveillance and the implementation of prevention strategies to interrupt the spread of antimicrobial resistance (AMR) bacteria. Infection with AMR bacteria, including Gram-negative Carbapenem-Resistant Organisms (CRO), may be acute and recurrent-once they have colonized a patient, they are notoriously difficult to eradicate. Through phylogenetic tools that assess the single nucleotide polymorphisms (SNPs) within a pathogen genome dataset, public health scientists can estimate the genetic identity between isolates. This information is used as an epidemiologic proxy of a putative outbreak. Pathogens with minimal to no differences in SNPs are likely to be the same strain attributable to a common source or transmission between cases. These genomic comparisons enhance public health response by prompting targeted intervention and infection control measures. This methodology overview demonstrates the utility of phenotypic and molecular assays, antimicrobial susceptibility testing (AST), NGS, publicly available genomics databases, and open-source bioinformatics pipelines for a tiered workflow to detect resistance genes and potential clusters of illness. These methods, when used in combination, facilitate a genomic surveillance workflow for detecting potential AMR bacterial outbreaks to inform epidemiologic investigations. Use of this workflow helps to target and focus epidemiologic resources to the cases with the highest likelihood of being related. | 2023 | 37255756 |
| 6624 | 9 | 0.9993 | Water as a Source of Antimicrobial Resistance and Healthcare-Associated Infections. Healthcare-associated infections (HAIs) are one of the most common patient complications, affecting 7% of patients in developed countries each year. The rise of antimicrobial resistant (AMR) bacteria has been identified as one of the biggest global health challenges, resulting in an estimated 23,000 deaths in the US annually. Environmental reservoirs for AMR bacteria such as bed rails, light switches and doorknobs have been identified in the past and addressed with infection prevention guidelines. However, water and water-related devices are often overlooked as potential sources of HAI outbreaks. This systematic review examines the role of water and water-related devices in the transmission of AMR bacteria responsible for HAIs, discussing common waterborne devices, pathogens, and surveillance strategies. AMR strains of previously described waterborne pathogens including Pseudomonas aeruginosa, Mycobacterium spp., and Legionella spp. were commonly isolated. However, methicillin-resistant Staphylococcus aureus and carbapenem-resistant Enterobacteriaceae that are not typically associated with water were also isolated. Biofilms were identified as a hot spot for the dissemination of genes responsible for survival functions. A limitation identified was a lack of consistency between environmental screening scope, isolation methodology, and antimicrobial resistance characterization. Broad universal environmental surveillance guidelines must be developed and adopted to monitor AMR pathogens, allowing prediction of future threats before waterborne infection outbreaks occur. | 2020 | 32824770 |
| 4759 | 10 | 0.9993 | Recent advances in rapid antimicrobial susceptibility testing systems. INTRODUCTION: Until recently antimicrobial susceptibility testing (AST) methods based on the demonstration of phenotypic susceptibility in 16-24 h remained largely unchanged. AREAS COVERED: Advances in rapid phenotypic and molecular-based AST systems. EXPERT OPINION: AST has changed over the past decade, with many rapid phenotypic and molecular methods developed to demonstrate phenotypic or genotypic resistance, or biochemical markers of resistance such as β-lactamases associated with carbapenem resistance. Most methods still require isolation of bacteria from specimens before both legacy and newer methods can be used. Bacterial identification by MALDI-TOF mass spectroscopy is now widely used and is often key to the interpretation of rapid AST results. Several PCR arrays are available to detect the most frequent pathogens associated with bloodstream infections and their major antimicrobial resistance genes. Many advances in whole-genome sequencing of bacteria and fungi isolated by culture as well as directly from clinical specimens have been made but are not yet widely available. High cost and limited throughput are the major obstacles to uptake of rapid methods, but targeted use, continued development and decreasing costs are expected to result in more extensive use of these increasingly useful methods. | 2021 | 33926351 |
| 4297 | 11 | 0.9993 | Predicting clinical resistance prevalence using sewage metagenomic data. Antibiotic resistance surveillance through regional and up-to-date testing of clinical isolates is a foundation for implementing effective empirical treatment. Surveillance data also provides an overview of geographical and temporal changes that are invaluable for guiding interventions. Still, due to limited infrastructure and resources, clinical surveillance data is lacking in many parts of the world. Given that sewage is largely made up of human fecal bacteria from many people, sewage epidemiology could provide a cost-efficient strategy to partly fill the current gap in clinical surveillance of antibiotic resistance. Here we explored the potential of sewage metagenomic data to assess clinical antibiotic resistance prevalence using environmental and clinical surveillance data from across the world. The sewage resistome correlated to clinical surveillance data of invasive Escherichia coli isolates, but none of several tested approaches provided a sufficient resolution for clear discrimination between resistance towards different classes of antibiotics. However, in combination with socioeconomic data, the overall clinical resistance situation could be predicted with good precision. We conclude that analyses of bacterial genes in sewage could contribute to informing management of antibiotic resistance. | 2020 | 33244050 |
| 4886 | 12 | 0.9993 | 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 |
| 4943 | 13 | 0.9993 | Targeted sequencing of Enterobacterales bacteria using CRISPR-Cas9 enrichment and Oxford Nanopore Technologies. Sequencing DNA directly from patient samples enables faster pathogen characterization compared to traditional culture-based approaches, but often yields insufficient sequence data for effective downstream analysis. CRISPR-Cas9 enrichment is designed to improve the yield of low abundance sequences but has not been thoroughly explored with Oxford Nanopore Technologies (ONT) for use in clinical bacterial epidemiology. We designed CRISPR-Cas9 guide RNAs to enrich the human pathogen Klebsiella pneumoniae, by targeting multi-locus sequence type (MLST) and transfer RNA (tRNA) genes, as well as common antimicrobial resistance (AMR) genes and the resistance-associated integron gene intI1. We validated enrichment performance in 20 K. pneumoniae isolates, finding that guides generated successful enrichment across all conserved sites except for one AMR gene in two isolates. Enrichment of MLST genes led to a correct allele call in all seven loci for 8 out of 10 isolates that had depth of 30× or more in these regions. We then compared enriched and unenriched sequencing of three human fecal samples spiked with K. pneumoniae at varying abundance. Enriched sequencing generated 56× and 11.3× the number of AMR and MLST reads, respectively, compared to unenriched sequencing, and required approximately one-third of the computational storage space. Targeting the intI1 gene often led to detection of 10-20 proximal resistance genes due to the long reads produced by ONT sequencing. We demonstrated that CRISPR-Cas9 enrichment combined with ONT sequencing enabled improved genomic characterization outcomes over unenriched sequencing of patient samples. This method could be used to inform infection control strategies by identifying patients colonized with high-risk strains. IMPORTANCE: Understanding bacteria in complex samples can be challenging due to their low abundance, which often results in insufficient data for analysis. To improve the detection of harmful bacteria, we implemented a technique aimed at increasing the amount of data from target pathogens when combined with modern DNA sequencing technologies. Our technique uses CRISPR-Cas9 to target specific gene sequences in the bacterial pathogen Klebsiella pneumoniae and improve recovery from human stool samples. We found our enrichment method to significantly outperform traditional methods, generating far more data originating from our target genes. Additionally, we developed new computational techniques to further enhance the analysis, providing a thorough method for characterizing pathogens from complex biological samples. | 2025 | 39772804 |
| 4893 | 14 | 0.9993 | Molecular Characterization of Multidrug-Resistant Shigella flexneri. Due to their propensity for causing diarrheal illnesses and their rising susceptibility to antimicrobials, Shigella infections constitute a serious threat to global public health. This extensive study explores the frequency, antibiotic resistance, genetic evolution, and effects of Shigella infections on vulnerable groups. The research covers a wide range of geographical areas and sheds information on how the prevalence of Shigella species is evolving. Shigella strain antimicrobial resistance patterns are thoroughly examined. Multidrug resistance (MDR) has been found to often occur in investigations, especially when older antimicrobials are used. The improper use of antibiotics in China is blamed for the quick emergence of resistance, and variations in resistance rates have been seen across different geographical areas. Shigella strains' genetic makeup can be used to identify emerging trends and horizontal gene transfer's acquisition of resistance genes. Notably, S. sonnei exhibits the capacity to obtain resistance genes from nearby bacteria, increasing its capacity for infection. The study also emphasizes the difficulties in accurately serotyping Shigella strains due to inconsistencies between molecular and conventional serology. These results highlight the necessity of reliable diagnostic methods for monitoring Shigella infections. In conclusion, this study emphasizes how dynamic Shigella infections are, with varying patterns of occurrence, changing resistance landscapes, and genetic adaptability. In addition to tackling the rising problem of antibiotic resistance in Shigella infections, these findings are essential for guiding efforts for disease surveillance, prevention, and treatment. | 2024 | 38435906 |
| 5008 | 15 | 0.9993 | Genetic diversity and risk factors for the transmission of antimicrobial resistance across human, animals and environmental compartments in East Africa: a review. BACKGROUND: The emergence and spread of antimicrobial resistance (AMR) present a challenge to disease control in East Africa. Resistance to beta-lactams, which are by far the most used antibiotics worldwide and include the penicillins, cephalosporins, monobactams and carbapenems, is reducing options for effective control of both Gram-positive and Gram-negative bacteria. The World Health Organization, Food and Agricultural Organization and the World Organization for Animal Health have all advocated surveillance of AMR using an integrated One Health approach. Regional consortia also have strengthened collaboration to address the AMR problem through surveillance, training and research in a holistic and multisectoral approach. This review paper contains collective information on risk factors for transmission, clinical relevance and diversity of resistance genes relating to extended-spectrum beta-lactamase-producing (ESBL) and carbapenemase-producing Enterobacteriaceae, and Methicillin-resistant Staphylococcus aureus (MRSA) across the human, animal and environmental compartments in East Africa. MAIN BODY: The review of the AMR literature (years 2001 to 2019) was performed using search engines such as PubMed, Scopus, Science Direct, Google and Web of Science. The search terms included 'antimicrobial resistance and human-animal-environment', 'antimicrobial resistance, risk factors, genetic diversity, and human-animal-environment' combined with respective countries of East Africa. In general, the risk factors identified were associated with the transmission of AMR. The marked genetic diversity due to multiple sequence types among drug-resistant bacteria and their replicon plasmid types sourced from the animal, human and environment were reported. The main ESBL, MRSA and carbapenem related genes/plasmids were the (bla)CTX-Ms (45.7%), SCCmec type III (27.3%) and IMP types (23.8%), respectively. CONCLUSION: The high diversity of the AMR genes suggests there may be multiple sources of resistance bacteria, or the possible exchange of strains or a flow of genes amongst different strains due to transfer by mobile genetic elements. Therefore, there should be harmonized One Health guidelines for the use of antibiotics, as well as regulations governing their importation and sale. Moreover, the trend of ESBLs, MRSA and carbapenem resistant (CAR) carriage rates is dynamic and are on rise over time period, posing a public health concern in East Africa. Collaborative surveillance of AMR in partnership with regional and external institutions using an integrated One Health approach is required for expert knowledge and technology transfer to facilitate information sharing for informed decision-making. | 2020 | 32762743 |
| 4991 | 16 | 0.9993 | Genomic and metagenomic analysis reveals shared resistance genes and mobile genetic elements in E. coli and Klebsiella spp. isolated from hospital patients and hospital wastewater at intra- and inter-genus level. Antimicrobial resistance (AMR) is a global problem that gives serious cause for concern. Hospital wastewater (HWW) is an important link between the clinical setting and the natural environment, and an escape route for pathogens that cause hospital infections, including urinary tract infections (UTI). Bacteria of the genera Escherichia and Klebsiella are common etiological factors of UTI, especially in children, and they can cause short-term infections, as well as chronic conditions. ESBL-producing Escherichia and Klebsiella have also emerged as potential indicators for estimating the burden of antimicrobial resistance under environmental conditions and the spread of AMR between clinical settings and the natural environment. In this study, whole-genome sequencing and the nanopore technology were used to analyze the complete genomes of ESBL-producing E.coli and Klebsiella spp. and the HWW metagenome, and to characterize the mechanisms of AMR. The similarities and differences in the encoded mechanisms of AMR in clinical isolates (causing UTI) and environmental strains (isolated from HWW and the HWW metagenome) were analyzed. Special attention was paid to the genetic context and the mobility of antibiotic resistance genes (ARGs) to determine the common sources and potential transmission of these genes. The results of this study suggest that the spread of drug resistance from healthcare facilities via HWW is not limited to the direct transmission of resistant clonal lines that are typically found in the clinical setting, but it also involves the indirect transfer of mobile elements carrying ARGs between bacteria colonizing various environments. Hospital wastewater could offer a supportive environment for plasmid evolution through the insertion of new ARGs, including typical chromosomal regions. These results indicate that interlined environments (hospital patients - HWW) should be closely monitored to evaluate the potential transmission routes of drug resistance in bacteria. | 2024 | 39038407 |
| 5112 | 17 | 0.9993 | Genome-Based Prediction of Bacterial Antibiotic Resistance. Clinical microbiology has long relied on growing bacteria in culture to determine antimicrobial susceptibility profiles, but the use of whole-genome sequencing for antibiotic susceptibility testing (WGS-AST) is now a powerful alternative. This review discusses the technologies that made this possible and presents results from recent studies to predict resistance based on genome sequences. We examine differences between calling antibiotic resistance profiles by the simple presence or absence of previously known genes and single-nucleotide polymorphisms (SNPs) against approaches that deploy machine learning and statistical models. Often, the limitations to genome-based prediction arise from limitations of accuracy of culture-based AST in addition to an incomplete knowledge of the genetic basis of resistance. However, we need to maintain phenotypic testing even as genome-based prediction becomes more widespread to ensure that the results do not diverge over time. We argue that standardization of WGS-AST by challenge with consistently phenotyped strain sets of defined genetic diversity is necessary to compare the efficacy of methods of prediction of antibiotic resistance based on genome sequences. | 2019 | 30381421 |
| 6613 | 18 | 0.9993 | Approaches for characterizing and tracking hospital-associated multidrug-resistant bacteria. Hospital-associated infections are a major concern for global public health. Infections with antibiotic-resistant pathogens can cause empiric treatment failure, and for infections with multidrug-resistant bacteria which can overcome antibiotics of "last resort" there exists no alternative treatments. Despite extensive sanitization protocols, the hospital environment is a potent reservoir and vector of antibiotic-resistant organisms. Pathogens can persist on hospital surfaces and plumbing for months to years, acquire new antibiotic resistance genes by horizontal gene transfer, and initiate outbreaks of hospital-associated infections by spreading to patients via healthcare workers and visitors. Advancements in next-generation sequencing of bacterial genomes and metagenomes have expanded our ability to (1) identify species and track distinct strains, (2) comprehensively profile antibiotic resistance genes, and (3) resolve the mobile elements that facilitate intra- and intercellular gene transfer. This information can, in turn, be used to characterize the population dynamics of hospital-associated microbiota, track outbreaks to their environmental reservoirs, and inform future interventions. This review provides a detailed overview of the approaches and bioinformatic tools available to study isolates and metagenomes of hospital-associated bacteria, and their multi-layered networks of transmission. | 2021 | 33582841 |
| 6602 | 19 | 0.9992 | Environmental Risk Factors Contributing to the Spread of Antibiotic Resistance in West Africa. Antibiotic resistance is a well-documented global health challenge that disproportionately impacts low- and middle-income countries. In 2019, the number of deaths attributed to and associated with antibiotic resistance in Western Sub-Saharan Africa was approximately 27 and 115 per 100,000, respectively, higher than in other regions worldwide. Extensive research has consistently confirmed the persistent presence and spread of antibiotic resistance in hospitals, among livestock, within food supply chains, and across various environmental contexts. This review documents the environmental risk factors contributing to the spread of antibiotic resistance in West Africa. We collected studies from multiple West African countries using the Web of Science and PubMed databases. We screened them for factors associated with antibiotic-resistant bacteria and resistance genes between 2018 and 2024. Our findings indicate that antibiotic resistance remains a significant concern in West Africa, with environmental pollution and waste management identified as major factors in the proliferation of antibiotic-resistant bacteria and resistance genes between 2018 and 2024. Additional contributing factors include poor hygiene, the use of antibiotics in agriculture, aquaculture, and animal farming, and the transmission of antibiotic resistance within hospital settings. Unfortunately, the lack of comprehensive genetic characterization of antibiotic-resistant bacteria and resistance genes hinders a thorough understanding of this critical issue in the region. Since antibiotic resistance transcends national borders and can spread within and between countries, it is essential to understand the environmental risk factors driving its dissemination in West African countries. Such understanding will be instrumental in developing and recommending effective strategies nationally and internationally to combat antibiotic resistance. | 2025 | 40284787 |