Context

In this project, you will learn how to fit a model for predicting resistance in bacteria, and see how different forms of cross-validation impact the interpretation of your performance results.

We will be focussing on a species called Neisseria gonorrhoeae, bacteria which cause gonorrhoea. Gonorrhoea is the second most common sexually transmitted infection (STI) in Europe, after chlamydia. Rates of gonorrhoea infection are on the rise, with a 26% increase reported from 2017-2018 in the UK.

Many people who are infected (especially women) experience no symptoms, helping its spread. However if the infection is left untreated, it can lead to infertility in women, and can occasionally spread to other parts of the body such as your joints, heart valves, brain or spinal cord.

Resistance of these bacteria to antibiotics is rising over time, making infections hard to treat. Below, you can see rates of resistance to different antibiotics. Image is from this paper: https://www.mdpi.com/2079-6382/7/3/60.

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In the past, patients were treated with an antibiotic called ciprofloxacin. Doctors had to stop using this antibiotic because resistance to the drug became too common, causing treatments if infections to fail. Until very recently, the recommended treatment was two drugs - ceftriaxone and azithromycin. Azithromycin was removed from recommendations because of concern over rising resistance to the antibiotic. Currently, in the UK, patients are only treated with ceftriaxone. In February 2018, the first ever reported case of resistance to treatment with ceftriaxone and azithromycin, as well as resistance to the last-resort treatment spectinomycin, was reported.

We will look at machine learning algorithms for predicting resistance to both ciprofloxacin and azithromycin.

Content

For this project, we will be working with "unitigs", which are segments of DNA shared by a subset of the strains in our collection. This dataset contains unitigs that are statistically associated with resistance to three different antibiotics.

There are three unitig files ('[code]_gwas_filtered_unitigs'), corresponding to trimmed versions of the full unitig files. Each contains the unitigs that have the lowest P-values in a genome-wide association study for resistance to a given antibiotic (azm = azithromycin, cfx = cefixime, cip = ciprofloxacin). Each column corresponds to a unitig, or sequence found in samples in the dataset. 1 means the unitig is present in a given sample, 0 means it is absent.

The metadata file contains the phenotype data we will be trying to predict. For this work, focus on predicting azm_sr, cfx_sr and cip_sr with the corresponding unitig data. sr refers to sensitive and resistant isolates, with 1 corresponding to resistance and 0 corresponding to sensitivity to the antibiotic.

Acknowledgements

The strains for this project have been gathered from the following sources:

Chisholm et al. (2016). An outbreak of high-level azithromycin resistant Neisseria gonorrhoeae in England. Sexually Transmitted Infections. Demczuk et al. (2015). Whole-Genome Phylogenomic Heterogeneity of Neisseria gonorrhoeae Isolates with Decreased Cephalosporin Susceptibility Collected in Canada between 1989 and 2013. Journal of Clinical Microbiology. Demczuk et al. (2016). Genomic Epidemiology and Molecular Resistance Mechanisms of Azithromycin-Resistant Neisseria gonorrhoeae in Canada from 1997 to 2014. Journal of Clinical Microbiology. Eyre et al. (2017). WGS to predict antibiotic MICs for Neisseria gonorrhoeae. The Journal of Antimicrobial Chemotherapy. Fifer et al. (2018). Sustained transmission of high-level azithromycin-resistant Neisseria gonorrhoeae in England: an observational study. The Lancet Infectious Diseases. Grad et al. (2014). Genomic epidemiology of Neisseria gonorrhoeae with reduced susceptibility to cefixime in the USA: a retrospective observational study. The Lancet Infectious Diseases. Grad et al. (2016). Genomic Epidemiology of Gonococcal Resistance to Extended-Spectrum Cephalosporins, Macrolides, and Fluoroquinolones in the United States, 2000-2013. The Journal of Infectious Diseases. Harris et al. (2018). Public health surveillance of multidrug-resistant clones of Neisseria gonorrhoeae in Europe: a genomic survey. The Lancet Infectious Diseases. Jacobsson et al. (2016). WGS analysis and molecular resistance mechanisms of azithromycin-resistant (MIC >2 mg/L) Neisseria gonorrhoeae isolates in Europe from 2009 to 2014. The Journal of Antimicrobial Chemotherapy. Lee et al. (2018). Genomic epidemiology and antimicrobial resistance of Neisseria gonorrhoeae in New Zealand. The Journal of Antimicrobial Chemotherapy. Sánche...

In this study, the abundance and distribution of antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs), as well as the concentrations of antibiotics present in a mixed-use watershed in Athens, GA, USA were examined, in order to enhance understanding of the existing state of AR in the freshwater environment. The current study has shown that antibiotic-related contaminants are prevalent in the freshwater environment, including commensal and pathogenic bacteria that are resistant to antibiotics used for human and veterinary purposes, medically important antibiotics, as well as the genes associated with resistance to these antibiotics. This dataset is not publicly accessible because: Data belong to coauthor at USDA ARS. It can be accessed through the following means: The data presented in this study are available on request from the corresponding author, Jonathan Frye at USDA. Format: Statistical analysis of data from surface water samples, see the journal article's Supplementary Materials for additional information: https://www.mdpi.com/article/10.3390/antibiotics12111586/s1. This dataset is associated with the following publication: Cho, S., L. Hiott, Q. Read, J. Damashek, J. Westrich, M. Edwards, R. Seim, D. Glinski, J. Bateman McDonald, E. Ottesen, E. Lipp, M. Henderson, C. Jackson, and J. Frye. Distribution of Antibiotic Resistance in a Mixed-Use Watershed and the Impact of Wastewater Treatment Plants on Antibiotic Resistance in Surface Water. The Journal of Antibiotics. Springer Nature, New York, NY, USA, 12(11): 1586, (2023).

An Environmental Component of a "One Health" approach, the mission of the Agricultural Antibiotic Resistance (AgAR) project is to develop practical tools and protocols to measure antibiotic drugs, resistant bacteria and resistance genes in agriculturally-impacted soil, water, air, and food; design and evaluate agricultural best management practices to limit the persistence and spread of antibiotic resistance from agroecosystems; facilitate sharing of ideas and resources among ARS scientists by establishing an agency-wide network of researchers with the common goal of conducting science-based research on AgAR topics. ANTIBIOTIC DRUGS: Which drugs are the most relevant for each type of ag production system? At what level do excreted drugs continue to provide selective pressure in the environment? RESISTANT BACTERIA: What is the relative contribution of specific bacteria to resistance in human clinical settings? Are some bacteria more likely than others to donate or receive resistance genes? What is the relative contribution of clonal spread of pathogens versus horizontal gene transfer? RESISTANT GENES: How long do specific types of genes persist in agricultural samples? What conditions increase or decrease the likelihood of a successful transfer in manure, soil, water, and air? What is the role of the natural soil "resistome"? AgAR Network Goals: Connect ARS researchers at multiple locations in order to develop and assess methods for measuring resistance that are robust, and that are validated across production systems and geographical areas. Identify which types of resistance are relevant to measure, based on an understanding of individual production systems and prioritized human health threats as identified by WHO and CDC Encourage the collection of baseline data and control samples so that the impact of agricultural best management practices can be accurately determined. Assess persistence of antibiotic drugs, resistant bacteria and resistance genes in environmental and pre-harvest settings. Long term goal: Discover the details of how, and at what rate bacteria and genes move back and forth between animals and humans through agricultural systems (soil, water, air wildlife, insects, and food). The AgAR network is composed of ARS scientists with an interest in understanding the ecology of antibiotic resistance in soil, water, air, insects, wildlife, and food. The network currently represents 4 national programs at 10 ARS locations across the United States, with over 200 peer-reviewed publications on AgAR topics, authored and co-authored by over 70 current and former ARS employees. Activities: Facilitate routine communication between AgAR members to address priority research areas, encourage agency and location wide collaboration and minimize research overlap. Establish a framework for the cross-laboratory validation of AgAR methods. Serve as a resource to scientists, stakeholders and administrators on current and past projects that address AgAR. Provide a point of contact for agency coordinators to solicit information and transmit agency goals to relevant research groups. Importance: While there is broad agreement the use of antibiotics in food animals has the potential to adversely impact human clinical outcomes, the details of how this happens are unknown, and there is a critical need for information on antibiotic resistance (AR) in agricultural settings (AgAR). U.S. and international health organizations have taken the lead on identifying specific antibiotic drugs and resistant infections that are critical to human health. ARS is uniquely positioned to provide information on the "farm" side of the "farm to fork continuum". ARS scientists are able to address these questions in a practical way, by combining their experience (over 200 peer-reviewed ARS publications on antibiotic resistance) with their applied understanding of agricultural production systems. ORGANIZATION: Scientists work on their own, individual research projects. The AgAR network provides resources to participants to encourage collaboration across program areas and geographical location. MANAGEMENT: The AgAR network is operated using a wiki community approach. All participating scientists are encouraged to contribute to and share in the community resources. Currently, the group resources will be curated by the group coordinator, with input and guidance from a five person advisory panel. RESOURCES: Bibliography of peer-reviewed AgAR papers by ARS authors • AgAR topic reference lists • information on meetings and conferences • "AR_in_environment" listserve • Community webinars Resources in this dataset:Resource Title: AgAR Data Search. File Name: Web Page, url: https://agcros-usdaars.opendata.arcgis.com/pages/ag-ar

Antibiotic-resistant infections kill approximately 23,000 people and cost $20,000,000,000 each year in the United States alone despite the widespread use of small-molecule antimicrobial combination therapy. Antibiotic combinations typically have an additive effect: the efficacy of the combination matches the sum of the efficacies of each antibiotic when used alone. Small molecules can also act synergistically when the efficacy of the combination is greater than the additive efficacy. However, synergistic combinations are rare and have been historically difficult to identify. High-throughput identification of synergistic pairs is limited by the scale of potential combinations: a modest collection of 1,000 small molecules involves 1 million pairwise combinations. Here, we describe a high-throughput method for rapid identification of synergistic small-molecule pairs, the overlap2 method (O2M). O2M extracts patterns from chemical-genetic datasets, which are created when a collection of mutants is grown in the presence of hundreds of different small molecules, producing a precise set of phenotypes induced by each small molecule across the mutant set. The identification of mutants that show the same phenotype when treated with known synergistic molecules allows us to pinpoint additional molecule combinations that also act synergistically. As a proof of concept, we focus on combinations with the antibiotics trimethoprim and sulfamethizole, which had been standard treatment against urinary tract infections until widespread resistance decreased efficacy. Using O2M, we screened a library of 2,000 small molecules and identified several that synergize with the antibiotic trimethoprim and/or sulfamethizole. The most potent of these synergistic interactions is with the antiviral drug azidothymidine (AZT). We then demonstrate that understanding the molecular mechanism underlying small-molecule synergistic interactions allows the rational design of additional combinations that bypass drug resistance. Trimethoprim and sulfamethizole are both folate biosynthesis inhibitors. We find that this activity disrupts nucleotide homeostasis, which blocks DNA replication in the presence of AZT. Building on these data, we show that other small molecules that disrupt nucleotide homeostasis through other mechanisms (hydroxyurea and floxuridine) also act synergistically with AZT. These novel combinations inhibit the growth and virulence of trimethoprim-resistant clinical Escherichia coli and Klebsiella pneumoniae isolates, suggesting that they may be able to be rapidly advanced into clinical use. In sum, we present a generalizable method to screen for novel synergistic combinations, to identify particular mechanisms resulting in synergy, and to use the mechanistic knowledge to rationally design new combinations that bypass drug resistance.

Non-typhoidal Salmonella (NTS) are important enteric pathogens causing over 1 million foodborne illnesses in the U.S. annually. The widespread emergence of antibiotic resistance in NTS isolates has limited the availability of antibiotics that can be used for therapy. Since Michigan is not part of the FoodNet surveillance system, few studies have quantified antibiotic resistance frequencies and identified risk factors for NTS infections in the state. We obtained 198 clinical NTS isolates via active surveillance at four Michigan hospitals from 2011 to 2014 for classification of serovars and susceptibility to 24 antibiotics using broth microdilution. The 198 isolates belonged to 35 different serovars with Enteritidis (36.9%) predominating followed by Typhimurium (19.5%) and Newport (9.7%), though the proportion of each varied by year, residence, and season. The number of Enteritidis and Typhimurium cases was higher in the summer, while Enteritidis cases were significantly more common among urban vs. rural residents. A total of 30 (15.2%) NTS isolates were resistant to ≥1 antibiotic and 15 (7.5%) were resistant to ≥3 antimicrobial classes; a significantly greater proportion of Typhimurium isolates were resistant compared to Enteritidis isolates and an increasing trend in the frequency of tetracycline resistance and multidrug resistance was observed over the 4-year period. Resistant infections were associated with longer hospital stays as the mean stay was 5.9 days for patients with resistant isolates relative to 4.0 days for patients infected with susceptible isolates. Multinomial logistic regression indicated that infection with serovars other than Enteritidis [Odds ratio (OR): 3.8, 95% confidence interval (CI): 1.23–11.82] as well as infection during the fall (OR: 3.0; 95% CI: 1.22–7.60) were independently associated with resistance. Together, these findings demonstrate the importance of surveillance, monitoring resistance frequencies, and identifying risk factors that can aid in the development of new prevention strategies.

Nebraska Prairie Study for Agricultural Antibiotic Resistance in Lincoln, Nebraska The inherent spatial heterogeneity and complexity of antibiotic resistant bacteria and antibiotic resistance (AR) genes in manureaffected soils makes it difficult to sort out resistance that can be attributed to human antibiotic use from resistance that occurs naturally in the soil. This study characterizes native Nebraska prairie soils that have not been affected by human or food-animal waste products to provide data on background levels of resistance in southeastern Nebraskan soils. Soil samples were collected from 20 sites enumerated on tetracycline and cefotaxime media; screened for tetracycline-, sulfonamide-, b-lactamase–, and macrolide-resistance genes; and characterized for soil physical and chemical parameters. All prairies contained tetracyclineand cefotaxime-resistant bacteria, and 48% of isolates collected were resistant to two or more antibiotics. Most (98%) of the soil samples and all 20 prairies had at least one tetracycline gene. Most frequently detected were tet(D), tet(A) tet(O), tet(L), and tet(B). Sulfonamide genes, which are considered a marker of human or animal activity, were detected in 91% of the samples, despite the lack of human inputs at these sites. No correlations were found between either phenotypic or genotypic resistance and soil physical or chemical parameters. Heterogeneity was observed in AR within and between prairies. Therefore, multiple samples are necessary to overcome heterogeneity and to accurately assess AR. Conclusions regarding AR depend on the gene target measured. To determine the impacts of food-animal antibiotic use on resistance, it is essential that background and/or baseline levels be considered, and where appropriate subtracted out, when evaluating AR in agroecosystems.

This is the dataset for the study of "Social dilemma in the excess use of antimicrobials incurring antimicrobial resistance". The emergence of antimicrobial resistance (AMR) caused by the excess use of antimicrobials has come to be recognized as a global threat to public health. There is a ‘tragedy of the commons’ type social dilemma behind this excessive use of antimicrobials, which should be recognized by all stakeholders. To address this global threat, we thus surveyed eight countries/areas to determine whether people recognize this dilemma and showed that although more than half of the population pays little, if any, attention to it, almost 20% recognize this social dilemma, and 15–30% of those have a positive attitude toward solving that dilemma. We suspect that increasing individual awareness of this social dilemma contributes to decreasing the frequency of AMR emergencies. Methods We designed a questionnaire to observe a social dilemma in the excess use of antimicrobials incurring antimicrobial resistance by placing two types of imaginary artificial-intelligence (AI) physicians who perform medical practice from either an individual or societal perspective. We assume two AI medical diagnosis systems: “Individual precedence AI” (abbreviated Individual-AI) and “World precedence AI” (abbreviated World-AI). Both AIs diagnose and prescribe medicine automatically. The Individual-AI system diagnoses patients and prescribes medicine to prevent infections based on an individual perspective, including all prophylactic prescriptions against rare accidental infections (not yet present and unlikely to occur). It does not consider the global risk of AMR in the decision. The World-AI system, instead, takes into account the global mortality rate of AMR, aiming to reduce the total number of all AMR-related deaths. Because of this, this AI system does not prescribe antimicrobials against rare and not-yet-present infections. This questionnaire design allows us to observe the social dilemma. For example, it shows a typical social dilemma caused by preferring the use of Individual-AI for diagnosing oneself but preferring the use of World-AI for diagnosing strangers.

The survey entitled “Survey on Medical Advancement” was administered to 8 countries/areas. The survey was conducted 4 times. For the two surveys in Japan, an internet survey company, Cross Marketing Inc. (https://www.cross-m.co.jp/en/), created the questionnaire webpages based on our study design. The company also collected the data. As of April 2020, Cross Marketing Inc. has 4.79 million people in an active panel (survey participants who registered in advance). Here, the definition of an active panel is a survey respondent who has been active within the last year. For the panels, the questionnaire and response column were displayed on the website through which the respondents could complete and submit their responses. We extracted 500 submissions for each gender and each age group by random sampling from all samples collected during the survey periods. The surveys in the 7 countries/areas (i.e., the United States, the United Kingdom, Sweden, Taiwan, Australia, Brazil, and Russia) are conducted by Cint (https://www.cint.com/). Cint is the world’s largest consumer network for digital survey-based research. The headquarters of the company is in Sweden. Cint maintains a survey platform that contained more than 100 million consumer monitors in over 80 countries as of May 2020. For surveys in the US, UK, Sweden, Taiwan, Australia, Brazil, and Russia, Cint Japan (https://jp.cint.com/), which is the Japanese distributor of Cint, created translated questionnaire webpages based on our study design. The company also collected the data. We extracted at least 500 (US, UK, SWE, BRA, RUS) or 250 (TWN, AUS) submissions for each gender (male and female) and each age group (20 s, 30 s, 40 s, 50 s, and 60 s) by random sampling from all samples collected between survey periods. Note that both companies eliminated inconsistent or apathetic respondents. For example, respondents with inconsistent responses (e.g., the registered age of the respondent differed from the reported age at the time of the survey.) were eliminated before reaching the authors. In addition, respondents with significantly short response times (i.e., shorter than 1 min) were eliminated because they may not have read the questions carefully.

Antibiotic-resistant pathogens cause over 35,000 preventable deaths in the United States every year, and multiple strategies could decrease morbidity and mortality. As antibiotic stewardship requirements are being deployed for the outpatient setting, community providers are facing systematic challenges in implementing stewardship programs. Given that the vast majority of antibiotics are prescribed in the outpatient setting, there are endless opportunities to make a smart and informed choice when prescribing and to move the needle on antibiotic stewardship. Antibiotic stewardship in the community, or “smart prescribing” as we suggest, should factor in antibiotic efficacy, safety, local resistance rates, and overall cost, in addition to patient-specific factors and disease presentation, to arrive at an appropriate therapy. Here, we discuss some of the challenges, such as patient/parent pressure to prescribe, lack of data or resources for implementation, and a disconnect between guidelines and real-world practice, among others. We have assembled an easy-to-use best practice guide for providers in the outpatient setting who lack the time or resources to develop a plan or consult lengthy guidelines. We provide specific suggestions for antibiotic prescribing that align real-world clinical practice with best practices for antibiotic stewardship for two of the most common bacterial infections seen in the outpatient setting: community-acquired pneumonia and skin and soft-tissue infection. In addition, we discuss many ways that community providers, payors, and regulatory bodies can make antibiotic stewardship easier to implement and more streamlined in the outpatient setting.

2014 Naive Broiler CAFO Study for Agricultural Antibiotic Resistance in Mississippi State, Mississippi Conventional commercial broiler production involves the rearing of more than 20,000 broilers in a single confined space, atop bedding material such as pine shavings or rice hulls, for approximately 6.5 weeks. This environment is known for harboring pathogens and antibiotic resistant bacteria, but studies have focused on previously established houses. A concerted effort by the broiler industry has involved the scaling back of antibiotic use on-farm, but this has only been a recent occurrence. In the current study, a set of three naïve houses were followed from inception through 11 broiler flocks and monitored for ambient climatic conditions, bacterial pathogens, and antibiotic resistance. Within the first 3 weeks of the first flock cycle, 100% of litter samples were positive for Salmonella and Listeria while Campylobacter was culture negative. In all likelihood, given that pre flock bedding and soil levels were negative for pathogens and 4-5 orders of magnitude lower for other indicators, chicks most likely provided the colonizing bacteria. The influence of intra-house location was minor with only watering lines and side walls influencing some pathogen and indicator levels. Most bacterial groups experienced the typical cyclical pattern of litter contamination seen in other studies. This study represents a first of its kind view into the time required for bacterial pathogens and antibiotic resistance to colonize and establish in naïve broiler houses. Resources in this dataset:Resource Title: GeoData catalog record. File Name: Web Page, url: https://geodata.nal.usda.gov/geonetwork/srv/eng/catalog.search#/metadata/83c91004-f234-441f-9616-2bd33149f42b

Antimicrobial resistance (AMR) is one of the most alarming global public health challenges of the 21st century. Over 3 million antimicrobial-resistant infections occur in the United States annually, with nearly 50,000 cases being fatal. Innovations in drug discovery methods and platforms are crucial to identify novel antibiotics to combat AMR. We present the isolation and characterization of potentially novel antibiotic lead compounds produced by the cross-feeding of two rhizosphere bacteria, Acinetobacter sp. RIT 592 and Exiguobacterium sp. RIT 594. We used solid-phase extraction (SPE) followed by liquid chromatography (LC) to enrich antibiotic extracts and subsequently mass spectrometry (MS) analysis of collected fractions for compound structure identification and characterization. The MS data were processed through the Global Natural Product Social Molecular Networking (GNPS) database. The supernatant from RIT 592 induced RIT 594 to produce a cocktail of antimicrobial compounds active against Gram-positive and negative bacteria. The GNPS analysis indicated compounds with known antimicrobial activity in the bioactive samples, including oligopeptides and their derivatives. This work emphasizes the utility of microbial community-based platforms to discover novel clinically relevant secondary metabolites. Future work includes further structural characterization and antibiotic activity evaluation of the individual compounds against pathogenic multidrug-resistant (MDR) bacteria.

BackgroundInfections by drug-resistant bacteria are a significant threat to human health worldwide although many drug-resistant bacteria are sensitive to aminoglycosides (AGs), an older class of antibiotics. AGs have played a significant role in clinical practice in recent years.MethodsPublications from 1 January 2013 to 31 December 2023 that described clinical research of AGs were identified by searching the Web of Science Core Collection Database. Visual presentations of different bibliometric networks were prepared using VOSviewer and CiteSpace.ResultsThere were 915 eligible publications and the annual number of publications increased over time. The United States had the most publications and was at the core of the cooperative network. Italy and Belgium had the highest quality publications, and many of the institutions with high yield and high research quality were in Australia. JA Roberts (University of Queensland, Australia) was the most productive author and was the author of many high-quality studies in cooperation with various other researchers. The majority of publications were in journals that focused on antibacterials, chemotherapy, and pharmacokinetics. Analysis of the most highly cited publications, references, and keywords, indicated that this research mainly focused on infections by drug-resistant bacteria, drug administration in vulnerable populations, safety, pharmacokinetics, combination therapy, and new methods of administration.ConclusionAGs have an increasingly important role in the treatment of infections by multidrug-resistant bacteria. Therapeutic drug monitoring should be performed in vulnerable populations, such as the elderly, children, and infants, to improve efficacy and reduce toxicity. Avoiding prolonged dosing cycles and refraining from using AGs in patients with the m.1555 A > G gene variant can significantly mitigate the risk of ototoxicity. Future studies should examine the pharmacokinetic and pharmacodynamic targets of AGs and assess the efficacy and safety of administration by inhalation to improve efficacy and decrease risk.

2014 Swine CAFO Study SE for Agricultural Antibiotic Resistance in Mississippi State, Mississippi The environmental influence of farm management in concentrated animal feeding operations (CAFO) can yield vast changes to the microbial biota and ecological structure of both the pig and waste manure lagoon wastewater. While some of these changes may not be negative, it is possible that CAFOs can enrich antibiotic resistant bacteria or pathogens based on farm type, thereby influencing the impact imparted by the land application of its respective wastewater. The purpose of this study was to measure the microbial constituents of swine-sow, -nursery, and -finisher farm manure lagoon wastewater and determine the changes induced by farm management. A total of 37 farms were visited in the Mid-South USA and analyzed for the genes 16S rRNA, spaQ (Salmonella spp.), Camp-16S (Campylobacter spp.), tetA, tetB, ermF, ermA, mecA, and intI using quantitative PCR. Additionally, 16S rRNA sequence libraries were created. Overall, it appeared that finisher farms were significantly different from nursery and sow farms in nearly all genes measured and in 16S rRNA clone libraries. Nearly all antibiotic resistance genes were detected in all farms. Interestingly, the mecA resistance gene (e.g. methicillin resistant Staphylococcus aureus) was below detection limits on most farms, and decreased as the pigs aged. Finisher farms generally had fewer antibiotic resistance genes, which corroborated previous phenotypic data; additionally, finisher farms produced a less diverse 16S rRNA sequence library. Comparisons of Camp-16S and spaQ GU (genomic unit) values to previous culture data demonstrated ratios from 10 to 10,000:1 depending on farm type, indicating viable but not cultivatable bacteria were dominant. The current study indicated that swine farm management schemes positively and negatively affect microbial and antibiotic resistant populations in CAFO wastewater which has future “downstream” implications from both an environmental and public health perspective.

Antimicrobial resistance (AMR) is a world-wide public health threat that is projected to lead to 10 million annual deaths globally by 2050. The AMR public health issue has led to the development of action plans to combat AMR, including improved antimicrobial stewardship, development of new antimicrobials, and advanced monitoring. The National Antimicrobial Resistance Monitoring System (NARMS) led by the United States (U.S) Food and Drug Administration along with the U.S. Centers for Disease Control and U.S. Department of Agriculture has monitored antimicrobial resistant bacteria in retail meats, humans, and food animals since the mid 1990’s. NARMS is currently exploring an integrated One Health monitoring model recognizing that human, animal, plant, and environmental systems are linked to public health. Since 2020, the U.S. Environmental Protection Agency has led an interagency NARMS environmental working group (EWG) to implement a surface water AMR monitoring program (SWAM) at watershed and national scales. The NARMS EWG divided the development of the environmental monitoring effort into five areas: (i) defining objectives and questions, (ii) designing study/sampling design, (iii) selecting AMR indicators, (iv) establishing analytical methods, and (v) developing data management/analytics/metadata plans. For each of these areas, the consensus among the scientific community and literature was reviewed and carefully considered prior to the development of this environmental monitoring program. The data produced from the SWAM effort will help develop robust surface water monitoring programs with the goal of assessing public health risks associated with AMR pathogens in surface water (e.g., recreational water exposures), provide a comprehensive picture of how resistant strains are related spatially and temporally within a watershed, and help assess how anthropogenic drivers and intervention strategies impact the transmission of AMR within human, animal, and environmental systems.

The healthcare-associated infection component of CDC’s EIP engages a network of state health departments and their academic medical center partners to help answer critical questions about emerging HAI threats, advanced infection tracking methods, and antibiotic resistance in the United States. Information gathered through this activity will play a key role in shaping future policies and recommendations targeting HAI prevention. Click here to learn more about Invasive Staphylococcus aureus infections

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• Data presented in HAICViz may differ from other HAIC publications since different datasets or methods may be used.
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Poultry litter (PL) is a by-product of broiler production. Most PL is land applied. Land-applied PL is a valuable nutrient source for crop production but can also be a route of environmental contamination with manure-borne bacteria. The objective of this study was to characterize the fate of pathogens, fecal indicator bacteria (FIB), and bacteria containing antibiotic resistance genes (ARGs) after application of PL to soils under conventional till or no-till management. This 2-yr study was conducted in accordance with normal agricultural practices, and microbial populations were quantified using a combination of culture and quantitative, real-time polymerase chain reaction analysis. Initial concentrations of Campylobacter jejuni in PL were 5.4 ± 3.2 × 106 cells g-1 PL; Salmonella sp. was not detected in the PL but was enriched periodically from PL-amended soils. Escherichia coli was detected in PL (1.5 ± 1.3 × 102 culturable or 1.5 ± 0.3 × 107 genes g-1) but was rarely detected in field soils, whereas enterococci (1.5 ± 0.5 × 108 cells g-1 PL) were detected throughout the study. These results suggest that enterococci may be better FIB for field-applied PL. Concentrations of ARGs for sulfonamide, streptomycin, and tetracycline resistance increased up to 3.0 orders of magnitude after PL application and remained above background for up to 148 d. These data provide new knowledge about important microbial FIB, pathogens, and ARGs associated with PL application under realistic field-based conditions. Resources in this dataset:Resource Title: GeoData catalog record. File Name: Web Page, url: https://geodata.nal.usda.gov/geonetwork/srv/eng/catalog.search#/metadata/07bc5fb2-462e-40bc-bee6-d24e735ea9b1

Data set includes total aerobic bacterial counts of Raw, Digested, and Treated sewage sludge materials from a single wastewater treatment plant. Data set contains results from multiple sample events from the same wastewater treatment plant. Total aerobic bacterial counts for the same 3 categories that are resistant to Ciprofloxacin, and Azithromycin and different levels of antibiotics. This dataset is associated with the following publication: Niang, M., J. Reichard, A. Maier, G. Talaska, J. Ying, J. Santo Domingo, E. Varughese, L. Boczek, E. Huff, and T. Reponen. Ciprofloxacin and azithromycin resistant bacteria in a wastewater treatment plant. JOURNAL OF OCCUPATIONAL AND ENVIRONMENTAL HYGIENE. Taylor & Francis, Inc., Philadelphia, PA, USA, 20(5-6): 219-225, (2023).

This record contains raw data related to article “High prevalence of multidrug-resistant bacteria in patients with pyogenic liver abscess following liver cancer loco-regional treatments"

Liver abscess is a rare condition, associated with significant in-hospital mortality. Because of improved diagnostic yield and standardized treatment strategies, mortality has been reduced from 70% to 6% in the last decades.1, 2

The aetiology of pyogenic liver abscess (PLA) varies according to geographical areas and is relevant to tailor treatment strategies; in Western countries, 80% of PLA are bacterial with Escherichia coli, other Enterobacteriaceae and anaerobes being the most common microorganisms. In Asia, Klebsiella pneumoniae has emerged as the most common pathogen in the last two decades, with up to 81.1% of cases reported in Taiwan.3, 4 Interestingly, increasing frequencies of PLA from K. pneumonia have also been observed in Europe and the United States.5

The most common risk factors for PLA include primary liver tumour and metastases, loco-regional liver procedures and liver cysts.

The treatment of PLA with antibiotic therapy, percutaneous drainage and management of the underlying cause is the current standard of care; however, the recommended antibiotic regimen and the optimal duration of treatment remain uncertain.

Yin et al6 reported in a retrospective study the management of 1572 patients with PLA in China. The most identified microorganism was K. pneumoniae (85.6%), with an overall mortality of 4.5% following abscess drainage and antibiotic therapy. Prognosis was associated with length of hospitalization, fever, pleural effusion and development of multiple organ dysfunction.

Given the increase in incidence of multi-drug resistant (MDR) infections in the western world and the differences in aetiology of PLA between geographical areas, we analysed the aetiology and mortality of PLA in our centre, focusing on the prevalence and factors associated with MDR bacterial infections

Every year millions of people die due to fatal waterborne diseases around the world especially in developing countries like India. Sikkim, a northeastern state of India, greatly depends on natural water sources. About 80% of the population of Sikkim depends on natural spring water for domestic as well as agricultural use. Recent waterborne disease outbreaks in the state raises a concerning question on water quality. In this study, we analyzed water quality especially for the detection of Enterobacteriaceae members from four districts of the state. Isolation with selective culture media techniques and taxonomic characterization of Enterobacteriaceae bacteria with 16S rRNA gene showed the prevalence of Escherichia coli (37.50%), Escherichia fergusonii (29.41%), Klebsiella oxytoca (36.93%), Citrobacter freundii (37.92%), Citrobacter amalonaticus (43.82%), Enterobacter sp. (43.82%), Morganella morganii (43.82%), Hafnia alvei (32.42%), Hafnia paralvei (38.74%), and Shigella flexneri (30.47%) in the spring water of Sikkim. Antibiotic susceptibility test (AST) showed resistance of the isolates to common antibiotics like ampicillin, amoxicillin as well as to third generation antibiotics like ceftazidime and carbapenem. None of the isolates showed resistance to chloramphenicol. E. coli isolated from spring water of Sikkim showed presence of different virulence genes such as stx1 (81.81%), elt (86.66%), and eae (66.66%) along with resistance gene for ampicillin (CITM) (80%), quinolones (qnrB) (44.44%), tetracycline (tetO) (66.66%), and streptomycin (aadA1) (66.66%). The data indicates a high incidence rate of multiple antibiotic resistant enteric bacteria in the spring water of Sikkim. Additionally, the presence of enteric bacteria in the water samples indicates widespread fecal contamination of the spring water.

Antimicrobial use in beef cattle can increase antimicrobial resistance prevalence in their enteric bacteria, including potential pathogens such as Escherichia coli. These bacteria can contaminate animal products at slaughterhouses and cause food-borne illness, which can be difficult to treat if it is due to antimicrobial resistant bacteria. One potential intervention to reduce the dissemination of resistant bacteria from feedlot to consumer is to impose a withdrawal period after antimicrobial use, similar to the current withdrawal period designed to prevent drug residues in edible animal meat. We investigated tetracycline resistance in generic E. coli in the bovine large intestine during and after antimicrobial treatment by building a mathematical model of oral chlortetracycline pharmacokinetics-pharmacodynamics and E. coli population dynamics. We tracked three E. coli subpopulations (susceptible, intermediate, and resistant) during and after treatment with each of three United States chlortetracycline indications (liver abscess reduction, disease control, disease treatment). We compared the proportion of resistant E. coli before antimicrobial use to that at several time points after treatment and found a greater proportion of resistant enteric E. coli after the current withdrawal periods than prior to treatment. In order for the proportion of resistant E. coli in the median beef steer to return to the pre-treatment level, withdrawal periods of 15 days after liver abscess reduction dosing (70 mg daily), 31 days after disease control dosing (350 mg daily), and 36 days after disease treatment dosing (22 mg/kg bodyweight for 5 days) are required in this model. These antimicrobial resistance withdrawal periods would be substantially longer than the current U.S. withdrawals of 0–2 days or Canadian withdrawals of 5–10 days. One published field study found similar time periods necessary to reduce the proportion of resistant E. coli following chlortetracycline disease treatment to those suggested by this model, but additional carefully designed field studies are necessary to confirm the model results. This model is limited to biological processes within the cattle and does not include resistance selection in the feedlot environment or co-selection of chlortetracycline resistance following other antimicrobial use.

Klebsiella pneumoniae is a primary culprit of antibiotic-resistant nosocomial infections worldwide, and infections caused by NDM-producing strains are a major threat due to limited therapeutic options. The majority of blaNDM cases occur on plasmids; therefore, we explored the relationships between plasmids and blaNDM genes in K. pneumoniae by analyzing the variants of blaNDM, replicon types, conjugative transfer regions of 171 blaNDM-harboring plasmids from 4,451 K. pneumoniae plasmids. Of the nine identified blaNDM variants, blaNDM-1 (73.68%) and blaNDM-5 (16.37%) were the most dominant. Over half of the blaNDM-harboring plasmids of K. pneumoniae were classified into IncF plasmids. IncX3 single-replicon plasmids (46–57 kb) carried genes encoding relaxases of the MOBP family, T4CP genes of the VirD4/TraG subfamily, and VirB-like T4SS gene clusters, which were mainly geographically distributed in China. We found 10 blaNDM-harboring IncN plasmids (38.38–63.05 kb) carrying the NW-type origin of transfer (oriT) regions, genes coding for relaxases of MOBF family, genes encoding T4CPs of the TrwB/TraD subfamily, and Trw-like T4SS gene clusters, which were also mainly geographically distributed in China. Moreover, we identified 21 IncC plasmids carrying blaNDM-1 (140.1–329.2 kb), containing the A/C-type oriTs, genes encoding relaxases of MOBH family, genes encoding T4CPs belonging to TrwB/TraD subfamily, and Tra_F-like T4SS gene clusters. The blaNDM-harboring IncC plasmids were widely geographically distributed all over the world, mainly in the United States, China and Viet Nam. These findings enhance our understanding of the diversity of blaNDM-harboring plasmids in K. pneumoniae.