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      Global monitoring of antimicrobial resistance based on metagenomics analyses of urban sewage

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      1 , 1 , 1 , 2 , 3 , 1 , 1 , 4 , 1 , 1 , 1 , 1 , 1 , 1 , 5 , 5 , 6 , 7 , 7 , The Global Sewage Surveillance project consortium, 8 , 8 , 9 , 6 , 10 , 10 , 1 , 7 , 1 , 2 , 4 , 1 , 1 , 1 ,
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          Abstract

          Antimicrobial resistance (AMR) is a serious threat to global public health, but obtaining representative data on AMR for healthy human populations is difficult. Here, we use metagenomic analysis of untreated sewage to characterize the bacterial resistome from 79 sites in 60 countries. We find systematic differences in abundance and diversity of AMR genes between Europe/North-America/Oceania and Africa/Asia/South-America. Antimicrobial use data and bacterial taxonomy only explains a minor part of the AMR variation that we observe. We find no evidence for cross-selection between antimicrobial classes, or for effect of air travel between sites. However, AMR gene abundance strongly correlates with socio-economic, health and environmental factors, which we use to predict AMR gene abundances in all countries in the world. Our findings suggest that global AMR gene diversity and abundance vary by region, and that improving sanitation and health could potentially limit the global burden of AMR. We propose metagenomic analysis of sewage as an ethically acceptable and economically feasible approach for continuous global surveillance and prediction of AMR.

          Abstract

          Obtaining data on antimicrobial resistance (AMR) from healthy human populations is difficult. Here, Hendriksen et al. use metagenomic analysis to obtain AMR data from untreated sewage from 79 sites in 60 countries, finding correlations with socio-economic, health and environmental factors.

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          Most cited references34

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          Global increase and geographic convergence in antibiotic consumption between 2000 and 2015

          Significance Antibiotic resistance, driven by antibiotic consumption, is a growing global health threat. Our report on antibiotic use in 76 countries over 16 years provides an up-to-date comprehensive assessment of global trends in antibiotic consumption. We find that the antibiotic consumption rate in low- and middle-income countries (LMICs) has been converging to (and in some countries surpassing) levels typically observed in high-income countries. However, inequities in drug access persist, as many LMICs continue to be burdened with high rates of infectious disease-related mortality and low rates of antibiotic consumption. Our findings emphasize the need for global surveillance of antibiotic consumption to support policies to reduce antibiotic consumption and resistance while providing access to these lifesaving drugs.
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            Using observation-level random effects to model overdispersion in count data in ecology and evolution

            Overdispersion is common in models of count data in ecology and evolutionary biology, and can occur due to missing covariates, non-independent (aggregated) data, or an excess frequency of zeroes (zero-inflation). Accounting for overdispersion in such models is vital, as failing to do so can lead to biased parameter estimates, and false conclusions regarding hypotheses of interest. Observation-level random effects (OLRE), where each data point receives a unique level of a random effect that models the extra-Poisson variation present in the data, are commonly employed to cope with overdispersion in count data. However studies investigating the efficacy of observation-level random effects as a means to deal with overdispersion are scarce. Here I use simulations to show that in cases where overdispersion is caused by random extra-Poisson noise, or aggregation in the count data, observation-level random effects yield more accurate parameter estimates compared to when overdispersion is simply ignored. Conversely, OLRE fail to reduce bias in zero-inflated data, and in some cases increase bias at high levels of overdispersion. There was a positive relationship between the magnitude of overdispersion and the degree of bias in parameter estimates. Critically, the simulations reveal that failing to account for overdispersion in mixed models can erroneously inflate measures of explained variance (r 2), which may lead to researchers overestimating the predictive power of variables of interest. This work suggests use of observation-level random effects provides a simple and robust means to account for overdispersion in count data, but also that their ability to minimise bias is not uniform across all types of overdispersion and must be applied judiciously.
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              What is a resistance gene? Ranking risk in resistomes.

              Metagenomic studies have shown that antibiotic resistance genes are ubiquitous in the environment, which has led to the suggestion that there is a high risk that these genes will spread to bacteria that cause human infections. If this is true, estimating the real risk of dissemination of resistance genes from environmental reservoirs to human pathogens is therefore very difficult. In this Opinion article, we analyse the current definitions of antibiotic resistance and antibiotic resistance genes, and we describe the bottlenecks that affect the transfer of antibiotic resistance genes to human pathogens. We propose rules for estimating the risks associated with genes that are present in environmental resistomes by evaluating the likelihood of their introduction into human pathogens, and the consequences of such events for the treatment of infections.
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                Author and article information

                Contributors
                fmaa@food.dtu.dk
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                8 March 2019
                8 March 2019
                2019
                : 10
                : 1124
                Affiliations
                [1 ]ISNI 0000 0001 2181 8870, GRID grid.5170.3, National Food Institute, , Technical University of Denmark, ; Kgs. Lyngby, 2800 Denmark
                [2 ]ISNI 0000 0004 1936 7988, GRID grid.4305.2, Usher Institute, , University of Edinburgh, ; Edinburgh, EH8 9AG UK
                [3 ]ISNI 0000 0004 1936 7988, GRID grid.4305.2, Centre for Synthetic and Systems Biology, School of Biological Sciences, , University of Edinburgh, ; Edinburgh, EH9 3JD UK
                [4 ]ISNI 000000040459992X, GRID grid.5645.2, Viroscience, Erasmus Medical Center, ; Rotterdam, 3015 The Netherlands
                [5 ]ISNI 0000 0001 0791 5666, GRID grid.4818.5, RIKILT Wageningen University and Research, ; Wageningen, 6708 The Netherlands
                [6 ]ISNI 0000 0001 2208 0118, GRID grid.31147.30, National Institute for Public Health and the Environment (RIVM), ; Bilthoven, 3721 The Netherlands
                [7 ]ISNI 0000 0001 2181 8870, GRID grid.5170.3, Department of Bio and Health Informatics, , Technical University of Denmark, ; Kgs. Lyngby, 2800 Denmark
                [8 ]ISNI 0000 0000 9709 7726, GRID grid.225360.0, European Molecular Biology Laboratory, , European Bioinformatics Institute, ; Hinxton, CB10 1SD UK
                [9 ]ISNI 0000 0004 0627 9137, GRID grid.444449.d, Centre of Excellence for Omics-Driven Computational Biodiscovery, , AIMST University, ; Kedah, 08100 Malaysia
                [10 ]ISNI 0000000121633745, GRID grid.3575.4, World Health Organization, ; Geneva, 1202 Switzerland
                [11 ]ISNI 0000 0004 4688 1528, GRID grid.414773.2, Institute of Public Health, ; Tirana, 1000 Albania
                [12 ]ISNI 0000 0004 0407 4680, GRID grid.468069.5, Melbourne Water Corporation, ; Melbourne, 3008 VIC Australia
                [13 ]ISNI 0000 0000 9984 5644, GRID grid.413314.0, Canberra Hospital, ; Canberra, 2605 ACT Australia
                [14 ]ISNI 0000 0001 2224 6253, GRID grid.414107.7, Austrian Agency for Health and Food Safety (AGES), ; Vienna, 1220 Austria
                [15 ]ISNI 0000 0004 1785 2090, GRID grid.448573.9, Botswana International University of Science and Technology, ; Private Bag 16, Papapye, Botswana
                [16 ]Vale Institute of Technology, Sustainable Development, Belém, 66055-090 Brazil
                [17 ]ISNI 0000 0004 0469 0184, GRID grid.419273.a, National Center of Infectious and Parasitic Diseases, ; Sofia, 1504 Bulgaria
                [18 ]GRID grid.418537.c, Institut Pasteur du Cambodge, ; Phnom Penh, 855 Cambodia
                [19 ]ISNI 0000 0004 1936 9131, GRID grid.57926.3f, University of Regina, ; Regina, S4S0A2 Canada
                [20 ]ISNI 0000 0000 8803 2373, GRID grid.198530.6, Guangdong Provincial Center for Disease Control and Prevention, No. 160, ; Guangzhou, 511430 China
                [21 ]ISNI 0000 0004 0605 3373, GRID grid.411679.c, Shantou University Medical College, ; Shantou, 515041 China
                [22 ]ISNI 0000 0001 1703 2808, GRID grid.466621.1, Corporacion Colombiana de Investigacion Agropecuaria (AGROSAVIA), ; Mosquera, 250040 Colombia
                [23 ]ISNI 0000 0004 0475 3667, GRID grid.418523.9, Institut Pasteur de Côte d’Ivoire, ; Abidjan, 01 BP 490 Abidjan 01 Côte d’Ivoire
                [24 ]Andrija Stampar Teaching Institute of Public Health, Zagreb, 10000 Croatia
                [25 ]ISNI 0000 0001 0657 4636, GRID grid.4808.4, University of Zagreb, ; Zagreb, 10000 Croatia
                [26 ]ISNI 0000 0001 2285 286X, GRID grid.426567.4, Veterinary Research Institute, ; Brno, 621 00 Czech Republic
                [27 ]Instituto Nacional de Investigación en Salud Pública-INSPI (CRNRAM), Quito, 170136 Ecuador
                [28 ]ISNI 0000 0001 1250 5688, GRID grid.7123.7, Addis Ababa University, ; Addis Ababa, P.O. Box 1176 Ethiopia
                [29 ]ISNI 0000 0004 0410 2071, GRID grid.7737.4, University of Helsinki, ; Helsinki, FI00014 Finland
                [30 ]ISNI 0000 0004 5345 9480, GRID grid.429654.8, National Center for Disease Control and Public Health, ; Tbilisi, 177 Georgia
                [31 ]ISNI 0000 0001 0940 3744, GRID grid.13652.33, Robert Koch Institute, ; Berlin, 13353 Germany
                [32 ]GRID grid.442305.4, University for Development Studies, ; Tamale, 233 Ghana
                [33 ]ISNI 0000 0001 0942 9821, GRID grid.11804.3c, Semmelweis University, Institute of Medical Microbiology, ; Budapest, 1089 Hungary
                [34 ]ISNI 0000 0001 2226 5083, GRID grid.483037.b, University of Veterinary Medicine, ; Budapest, 1078 Hungary
                [35 ]ISNI 0000 0004 0640 0021, GRID grid.14013.37, Institute for Experimental Pathology, , University of Iceland, ; Keldur, 112 Iceland
                [36 ]ISNI 0000 0001 2189 9308, GRID grid.411771.5, Cochin University of Science and Technology, ; Cochin, 682016 India
                [37 ]GRID grid.411600.2, Foodborne and Waterborne Diseases Research center, Research Institute for Gastroenterology and Liver Diseases, , Shahid Beheshti University of Medical Sciences, ; Tehran, 1985717413 Iran
                [38 ]ISNI 0000 0004 0488 0789, GRID grid.6142.1, National University of Ireland Galway, ; Galway, H91 TK33 Ireland
                [39 ]ISNI 0000 0004 1937 0511, GRID grid.7489.2, School of Public Health, , Ben Gurion University of the Negev and Ministry of Health, ; Beer Sheva, 8410501 Israel
                [40 ]Istituto Zooprofilattico Sperimentale del Lazio e della Toscana, Rome, 178 Italy
                [41 ]National Center of Expertise, Taldykorgan, 40000 Kazakhstan
                [42 ]GRID grid.449177.8, Mount Kenya University, ; Thika, P. O. Box 342-01000 Kenya
                [43 ]ISNI 0000 0001 0155 5938, GRID grid.33058.3d, Kenya Medical Research Institute, ; Nairobi, 254 Kenya
                [44 ]GRID grid.449627.a, University of Prishtina “Hasan Prishtina” & National Institute of Public Health of Kosovo, ; Prishtina, 10000 Kosovo
                [45 ]ISNI 0000 0004 0452 6958, GRID grid.493428.0, Institute of Food Safety, ; Riga, LV-1076 Latvia
                [46 ]GRID grid.423669.c, Luxembourg Institute of Science and Technology, ; Belvaux, L-4422 Luxembourg
                [47 ]Environmental Health Directorate, St. Venera, SVR 9018 Malta
                [48 ]GRID grid.460993.1, Agriculture and Forestry University, ; Kathmandu, 44200 Nepal
                [49 ]ISNI 0000 0004 1936 7830, GRID grid.29980.3a, University of Otago, ; Dunedin, 9016 New Zealand
                [50 ]ISNI 0000 0004 1794 5983, GRID grid.9582.6, University of Ibadan, ; Ibadan, 200284 Nigeria
                [51 ]VEAS, Slemmestad, NO-3470 Norway
                [52 ]ISNI 0000 0001 0633 6224, GRID grid.7147.5, Aga Khan University, ; Karachi, 74800 Pakistan
                [53 ]National Institute of Health, Lima, 15072 Peru
                [54 ]GRID grid.419811.4, National Veterinary Research Institute, ; Pulawy, 24-100 Poland
                [55 ]GRID grid.493421.9, Institute of Public Health of the Republic of Macedonia, ; Skopje, 1000 Republic of Macedonia
                [56 ]ISNI 0000 0004 0401 2738, GRID grid.28224.3e, State Medical and Pharmaceutical University, ; Chişinău, MD-2004 Republic of Moldova
                [57 ]ISNI 0000 0001 1956 9596, GRID grid.418508.0, Institut Pasteur de Dakar, ; Dakar, BP 220 Senegal
                [58 ]Institute of Veterinary Medicine of Serbia, Belgrade, 11000 Serbia
                [59 ]ISNI 0000 0001 2224 0361, GRID grid.59025.3b, Nanyang Technological University, Singapore, Singapore Centre for Environmental Life Sciences Engineering (SCELSE), ; Singapore, 637551 Singapore
                [60 ]ISNI 0000 0001 2224 0361, GRID grid.59025.3b, Nanyang Technological University Food Technology Centre (NAFTEC), Nanyang Technological University (NTU), ; Singapore, 637551 Singapore
                [61 ]GRID grid.437898.9, Public Health Authority of the Slovak Republic, ; Bratislava, 826 45 Slovakia
                [62 ]National Laboratory of Health, Environment and Food, Ljubjana, 1000 Slovenia
                [63 ]Daspoort Waste Water Treatment Works, Pretoria, 1 South Africa
                [64 ]ISNI 0000 0004 1937 1135, GRID grid.11951.3d, University of the Witwatersrand, ; Johannesburg, 1485 South Africa
                [65 ]ISNI 0000 0001 1943 6646, GRID grid.8581.4, IRTA, Centre de Recerca en Sanitat Animal (CReSA, IRTA-UAB), ; Bellaterra, 8193 Spain
                [66 ]ISNI 0000 0000 8530 3182, GRID grid.415115.5, Medical Research Institute, ; Colombo, 800 Sri Lanka
                [67 ]ISNI 0000 0000 8578 2742, GRID grid.6341.0, Swedish University of Agricultural Sciences, ; Uppsala, 75007 Sweden
                [68 ]ISNI 0000 0000 9919 9582, GRID grid.8761.8, The Sahlgrenska Academy at the University of Gothenburg, ; Gothenburg, SE-413 46 Sweden
                [69 ]Ara Region Bern Ag, Herrenschwanden, 3037 Switzerland
                [70 ]ISNI 0000 0004 0648 0439, GRID grid.412898.e, Kilimanjaro Clinical Research Institute, ; Moshi, 255 Tanzania
                [71 ]GRID grid.463484.9, National Public Health Laboratories, , Ministry of Health and Social Welfare, Kotu Layout, ; Kotu Layout, Kotu, 1863 The Gambia
                [72 ]National Institute of Hygiene, Lome, 228 Togo
                [73 ]Agence de Médecine Préventive, Dapaong, Togo
                [74 ]Division of Integrated Surveillance of Health Emergencies and Response, Lome, Togo
                [75 ]Public Health Institution of Turkey, Ankara, 6100 Turkey
                [76 ]ISNI 0000000122986657, GRID grid.34477.33, University of Washington, ; Seattle, 98105-6099 WA USA
                [77 ]Institute of Public Health in Ho Chi Minh City, Ho Chi Minh City, 700000 Vietnam
                [78 ]ISNI 0000 0000 8914 5257, GRID grid.12984.36, University of Zambia, ; Lusaka, 15101 Zambia
                [79 ]GRID grid.440616.1, University of N’Djamena, ; N’Djamena, 1117 Chad
                [80 ]ISNI 0000 0001 1541 4204, GRID grid.418193.6, Norwegian Institute of Public Health, ; Oslo, 0456 Norway
                [81 ]ISNI 0000 0001 2224 0804, GRID grid.411964.f, Universidad Católica del Maule, ; Av. San Miguel 3605, Talca, Chile
                [82 ]ISNI 0000 0001 2224 0804, GRID grid.411964.f, Centro de Biotecnología de los Recursos Naturales, Facultad de Ciencias Agrárias y Forestales, , Universidad Católica del Maule, ; Av. San Miguel 3605, Talca, Chile
                Author information
                http://orcid.org/0000-0001-8813-4019
                http://orcid.org/0000-0003-2177-7073
                http://orcid.org/0000-0001-6323-9041
                http://orcid.org/0000-0002-7116-2723
                Article
                8853
                10.1038/s41467-019-08853-3
                6408512
                30850636
                20eb777d-a017-46f7-b3aa-543191398f9e
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 16 November 2018
                : 31 January 2019
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