Tag: Antibiotic pollution

UNEP last week published their report on one health responses to antimicrobial resistance (1), which I have taken part in writing (well, I think I ultimately only contributed a few sentences here and there, but apparently that counts to be listed among the report’s contributors). The report, named “Bracing for Superbugs: Strengthening environmental action in the One Health response to antimicrobial resistance” showcases the evidence for that the environment plays a key role in the development, transmission and spread of AMR.

The report tries to unpack the different aspects of environmental AMR, and offers a fairly comprehensive picture of where the science stands on the subject. We also conclude that a systems effort – “One Health” – recognizing that the health of people, animals, plants and the environment are closely connected, is needed to tackle AMR.

This report analyzes the three economic sectors and their value chains that are key drivers of AMR development and spread in the environment: pharmaceuticals and other chemicals, agriculture including the food chain, and healthcare, together with pollutants from poor sanitation, sewage and waste effluent in municipal systems.

I am very happy to have been part of this report writing team and I hope that this will spur future action on AMR from a one-health perspective. You can read the entire report here.

Reference

1. United Nations Environment Programme (2023). Bracing for Superbugs: Strengthening environmental action in the One Health response to antimicrobial resistance. Geneva

Last week, I published 13 (!!) papers in the EFSA Journal on how to assess concentrations of antibiotics that could select for antibiotic resistance in animal feed (1-13). Or, well, you could also look at it as that the EFSA Biohaz panel that I have been a part of for more than two years published our final 13-part report.

Regardless of how you view it, this set of papers have two main takeaways:

1. We present a method to establish Predicted Minimal Selective Concentrations (PMSCs) for antibiotics. This method uses a combination of Dan Andersson’s approach to MSCs (14) and the method I published with Joakim Larsson around five years ago to establish predicted no-effect concentrations (PNECs) for antibiotics based on MIC data (15). The combination is a powerful (but very cautious) tool to estimate minimal selective concentrations for antibiotics (1), and we have subsequently applied this method to animal feed contamination with antibiotics, but…
2. There is way too little data to establish PMSCs for most antibiotics with any certainty. Really, the lack of data is so bad that for many of the antibiotic classes we could not make a reasonable assessment. Thus the main conclusion might be that we need a lot more data on how low concentrations of antibiotics that select for antibiotic resistance, both in laboratory systems and in more realistic settings.

References

1. EFSA Panel on Biological Hazards (BIOHAZ)*, Allende A, Koutsoumanis K, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Ru G, Simmons M, Skandamis P, Suffredini E, Andersson DI, Bampidis V, Bengtsson-Palme J, Bouchard D, Ferran A, Kouba M, López Puente S, López-Alonso M, Saxmose Nielsen S, Pechová A, Petkova M, Girault S, Broglia A, Guerra B, Lorenzo Innocenti M, Liébana E, López-Gálvez G, Manini P, Stella P, Peixe L: Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 1: Methodology, general data gaps and uncertainties. EFSA Journal, 19, 10 (2021). doi: 10.2903/j.efsa.2021.6852 [Paper link]
2. EFSA Panel on Biological Hazards (BIOHAZ)*, Allende A, Koutsoumanis K, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Ru G, Simmons M, Skandamis P, Suffredini E, Andersson DI, Bampidis V, Bengtsson-Palme J, Bouchard D, Ferran A, Kouba M, López Puente S, López-Alonso M, Saxmose Nielsen S, Pechová A, Petkova M, Girault S, Broglia A, Guerra B, Lorenzo Innocenti M, Liébana E, López-Gálvez G, Manini P, Stella P, Peixe L: Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 2: Aminoglycosides/aminocyclitols: apramycin, paromomycin, neomycin and spectinomycin. EFSA Journal, 19, 10 (2021). doi: 10.2903/j.efsa.2021.6853 [Paper link]
3. EFSA Panel on Biological Hazards (BIOHAZ)*, Allende A, Koutsoumanis K, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Ru G, Simmons M, Skandamis P, Suffredini E, Andersson DI, Bampidis V, Bengtsson-Palme J, Bouchard D, Ferran A, Kouba M, López Puente S, López-Alonso M, Saxmose Nielsen S, Pechová A, Petkova M, Girault S, Broglia A, Guerra B, Lorenzo Innocenti M, Liébana E, López-Gálvez G, Manini P, Stella P, Peixe L: Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 3: Amprolium. EFSA Journal, 19, 10 (2021). doi: 10.2903/j.efsa.2021.6854 [Paper link]
4. EFSA Panel on Biological Hazards (BIOHAZ)*, Allende A, Koutsoumanis K, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Ru G, Simmons M, Skandamis P, Suffredini E, Andersson DI, Bampidis V, Bengtsson-Palme J, Bouchard D, Ferran A, Kouba M, López Puente S, López-Alonso M, Saxmose Nielsen S, Pechová A, Petkova M, Girault S, Broglia A, Guerra B, Lorenzo Innocenti M, Liébana E, López-Gálvez G, Manini P, Stella P, Peixe L: Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 4: ß-Lactams: amoxicillin and penicillin. EFSA Journal, 19, 10 (2021). doi: 10.2903/j.efsa.2021.6855 [Paper link]
5. EFSA Panel on Biological Hazards (BIOHAZ)*, Allende A, Koutsoumanis K, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Ru G, Simmons M, Skandamis P, Suffredini E, Andersson DI, Bampidis V, Bengtsson-Palme J, Bouchard D, Ferran A, Kouba M, López Puente S, López-Alonso M, Saxmose Nielsen S, Pechová A, Petkova M, Girault S, Broglia A, Guerra B, Lorenzo Innocenti M, Liébana E, López-Gálvez G, Manini P, Stella P, Peixe L: Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 5: Lincosamides: lincomycin. EFSA Journal, 19, 10 (2021). doi: 10.2903/j.efsa.2021.6856 [Paper link]
6. EFSA Panel on Biological Hazards (BIOHAZ)*, Allende A, Koutsoumanis K, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Ru G, Simmons M, Skandamis P, Suffredini E, Andersson DI, Bampidis V, Bengtsson-Palme J, Bouchard D, Ferran A, Kouba M, López Puente S, López-Alonso M, Saxmose Nielsen S, Pechová A, Petkova M, Girault S, Broglia A, Guerra B, Lorenzo Innocenti M, Liébana E, López-Gálvez G, Manini P, Stella P, Peixe L: Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 6: Macrolides: tilmicosin, tylosin and tylvalosin. EFSA Journal, 19, 10 (2021). doi: 10.2903/j.efsa.2021.6858 [Paper link]
7. EFSA Panel on Biological Hazards (BIOHAZ)*, Allende A, Koutsoumanis K, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Ru G, Simmons M, Skandamis P, Suffredini E, Andersson DI, Bampidis V, Bengtsson-Palme J, Bouchard D, Ferran A, Kouba M, López Puente S, López-Alonso M, Saxmose Nielsen S, Pechová A, Petkova M, Girault S, Broglia A, Guerra B, Lorenzo Innocenti M, Liébana E, López-Gálvez G, Manini P, Stella P, Peixe L: Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 7: Amphenicols: florfenicol and thiamphenicol. EFSA Journal, 19, 10 (2021). doi: 10.2903/j.efsa.2021.6859 [Paper link]
8. EFSA Panel on Biological Hazards (BIOHAZ)*, Allende A, Koutsoumanis K, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Ru G, Simmons M, Skandamis P, Suffredini E, Andersson DI, Bampidis V, Bengtsson-Palme J, Bouchard D, Ferran A, Kouba M, López Puente S, López-Alonso M, Saxmose Nielsen S, Pechová A, Petkova M, Girault S, Broglia A, Guerra B, Lorenzo Innocenti M, Liébana E, López-Gálvez G, Manini P, Stella P, Peixe L: Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 8: Pleuromutilins: tiamulin and valnemulin. EFSA Journal, 19, 10 (2021). doi: 10.2903/j.efsa.2021.6860 [Paper link]
9. EFSA Panel on Biological Hazards (BIOHAZ)*, Allende A, Koutsoumanis K, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Ru G, Simmons M, Skandamis P, Suffredini E, Andersson DI, Bampidis V, Bengtsson-Palme J, Bouchard D, Ferran A, Kouba M, López Puente S, López-Alonso M, Saxmose Nielsen S, Pechová A, Petkova M, Girault S, Broglia A, Guerra B, Lorenzo Innocenti M, Liébana E, López-Gálvez G, Manini P, Stella P, Peixe L: Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 9: Polymyxins: colistin. EFSA Journal, 19, 10 (2021). doi: 10.2903/j.efsa.2021.6861 [Paper link]
10. EFSA Panel on Biological Hazards (BIOHAZ)*, Allende A, Koutsoumanis K, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Ru G, Simmons M, Skandamis P, Suffredini E, Andersson DI, Bampidis V, Bengtsson-Palme J, Bouchard D, Ferran A, Kouba M, López Puente S, López-Alonso M, Saxmose Nielsen S, Pechová A, Petkova M, Girault S, Broglia A, Guerra B, Lorenzo Innocenti M, Liébana E, López-Gálvez G, Manini P, Stella P, Peixe L: Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 10: Quinolones: flumequine and oxolinic acid. EFSA Journal, 19, 10 (2021). doi: 10.2903/j.efsa.2021.6862 [Paper link]
11. EFSA Panel on Biological Hazards (BIOHAZ)*, Allende A, Koutsoumanis K, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Ru G, Simmons M, Skandamis P, Suffredini E, Andersson DI, Bampidis V, Bengtsson-Palme J, Bouchard D, Ferran A, Kouba M, López Puente S, López-Alonso M, Saxmose Nielsen S, Pechová A, Petkova M, Girault S, Broglia A, Guerra B, Lorenzo Innocenti M, Liébana E, López-Gálvez G, Manini P, Stella P, Peixe L: Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 11: Sulfonamides. EFSA Journal, 19, 10 (2021). doi: 10.2903/j.efsa.2021.6863 [Paper link]
12. EFSA Panel on Biological Hazards (BIOHAZ)*, Allende A, Koutsoumanis K, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Ru G, Simmons M, Skandamis P, Suffredini E, Andersson DI, Bampidis V, Bengtsson-Palme J, Bouchard D, Ferran A, Kouba M, López Puente S, López-Alonso M, Saxmose Nielsen S, Pechová A, Petkova M, Girault S, Broglia A, Guerra B, Lorenzo Innocenti M, Liébana E, López-Gálvez G, Manini P, Stella P, Peixe L: Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 12: Tetracycline, chlortetracycline, oxytetracycline, and doxycycline. EFSA Journal, 19, 10 (2021). doi: 10.2903/j.efsa.2021.6864[Paper link]
13. EFSA Panel on Biological Hazards (BIOHAZ)*, Allende A, Koutsoumanis K, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Ru G, Simmons M, Skandamis P, Suffredini E, Andersson DI, Bampidis V, Bengtsson-Palme J, Bouchard D, Ferran A, Kouba M, López Puente S, López-Alonso M, Saxmose Nielsen S, Pechová A, Petkova M, Girault S, Broglia A, Guerra B, Lorenzo Innocenti M, Liébana E, López-Gálvez G, Manini P, Stella P, Peixe L: Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 13: Trimethoprim. EFSA Journal, 19, 10 (2021). doi: 10.2903/j.efsa.2021.6865 [Paper link]
14. Gullberg E, Cao S, Berg OG, Ilbäck C, Sandegren L, Hughes D, et al.: Selection of resistant bacteria at very low antibiotic concentrations. PLoS Pathogens 7, e1002158 (2011). doi: 10.1371/journal.ppat.1002158
15. Bengtsson-Palme J, Larsson DGJ: Concentrations of antibiotics predicted to select for resistant bacteria: Proposed limits for environmental regulation. Environment International, 86, 140-149 (2016). doi: 10.1016/j.envint.2015.10.015 [Paper link]

Here’s some updates on my Spring schedule.

On March 19, I will be presenting the EMBARK program and what we aim to achieve at a conference organised by the Swedish Medical Products Agency called NordicMappingAMR. The event will feature an overview of existing monitoring of antibiotics and antibiotic resistant bacteria in the environment. The conference aims to present the results from this survey, to listen to experts in the field and to discuss possible progress. It takes place in Uppsala. For any further questions, contact Kia Salin at NordicMappingAMR@lakemedelsverket.se

Then on May 18 to 20 I will participate in the 7th Microbiome & Probiotics R&D and Business Collaboration Forum in Rotterdam. This industry/academia cross-over event focuses on cutting-edge microbiome and probiotics research, and challenges and opportunities in moving research towards commercialisation. I will talk on the work we do on deciphering genetic mechanisms behind microbial interactions in microbiomes on May 20.

And finally, I also want to bring the attention to that my collaborator Erik Kristiansson has an open PhD position in his lab. The position is funded by the Environmental Dimensions of Antibiotic Resistance (EDAR) research project, aiming to describe the environmental role in the development and promotion of antibiotic resistance. The focus of the PhD position will be on analysis of large-scale data, with special emphasis on the identification of new forms of resistance genes. The project also includes phylogenetic analysis and development of methods for assessment of gene evolution. More info can be found here.

I have been slow at picking this ball up, but the book chapter that I coauthored with Stefanie Hess is now available online (and has been for almost a month). It is part of the book Antibiotic Drug Resistance, edited by José-Luis Capelo-Martínez and Gilberto Igrejas and was available in print on September 9th.

Our chapter deals with sources of resistant bacteria to the environment, and in particular the roles of sewage, wastewater and agriculture in resistance dissemination. Furthermore, the chapter discusses de novo selection of resistance and defines relevant risk scenarios. Finally, we outline the different management options available and discuss their feasibility.

The chapter boils down to that the available strategies for limiting antibiotic resistance dissemination and selection in the environment are overall quite clear. Larger problems that remain to be solved are how to prioritize between different strategies, which technologies that would provide the largest benefits and to achieve the political willingness to pursue these strategies. We note that several of the most efficient resistance prevention options involve high costs, investments in technology and infrastructure in other countries or proposals that are likely to be rather unpopular with the general public. For example, investing in sewage treatment and water infrastructure in low-income countries would likely be among the most effective means to reduce releases of resistant bacteria into the environment and reduced meat consumption would contribute to lower the use of antibiotics in animal husbandry, but neither is a very popular proposal for tax payers in high-income countries.

I have not yet read the entire book myself, but the table of content shows a very wide-reaching and comprehensive picture of the antibiotic resistance field, with a range of prominent authors. The editors have made a good job collecting this many interesting book chapters in the same volume!

Reference

Bengtsson-Palme J, Heß S: Strategies to reduce or eliminate resistant pathogens in the environment. In: Capelo Martinez JL, Igrejas G (Eds.) Antibiotic Drug Resistance, 637–673. Wiley, NJ, USA (2020). doi: 10.1002/9781119282549.ch24[Link]

I celebrate the fourth of July with the coincidental publishing of my most recent paper, in collaboration with the lab of Nikolina Udikovic-Kolic. The study used shotgun metagenomics to investigate the taxonomic structure and resistance gene composition of sludge communities in a treatment plant in Croatia receiving wastewater from production of the macrolide antibiotic azithromycin (1). We compared the levels of antibiotic resistance genes in sludge from this treatment plant and municipal sludge from a sewage treatment plant in Zagreb, and found that the total abundance of resistance genes was three times higher in sludge from the treatment plant receiving wastewater from pharmaceutical production. To our great surprise, this was not true for macrolide resistance genes, however. Instead, those genes had overall slightly lower abundances in the industrial sludge. At the same time, the genes that are associated with mobile genetic elements (such as integrons) had higher abundances in the industrial sludge.

This leads us to think that at high concentrations of antibiotics (such as in the industrial wastewater treatment plant), selection may favor taxonomic shifts towards intrinsically resistant species or strains harboring chromosomal resistance mutations rather than acquisition of mobile resistance genes. Unfortunately, the results regarding resistance mutation – obtained using our recent software tool Mumame (2) – were uninformative due to low number of reads mapping to the resistance regions of the 23S rRNA target gene for azithromycin.

Often, the problem of environmental pollution with pharmaceuticals is perceived as primarily being a concern in countries with poor pollution control, since price pressure has led to outsourcing of global antibiotics production to locations with lax environmental regulation (3). If this was the case, there would be much less incentive for improving legislation regarding emissions from pharmaceutical manufacturing at the EU level, as this would not move the needle in a significant way. However, the results of the paper (and other work by Nikolina’s group (4,5)) underscore the need for regulatory action also within Europe to avoid release of antibiotics into the environment.

References

1. Bengtsson-Palme J, Milakovic M, Švecová H, Ganjto M, Jonsson V, Grabic R, Udiković Kolić N: Pharmaceutical wastewater treatment plant enriches resistance genes and alter the structure of microbial communities. Water Research, accepted manuscript (2019). doi: 10.1016/j.watres.2019.06.073
2. Magesh S, Jonsson V, Bengtsson-Palme J: Quantifying point-mutations in metagenomic data. bioRxiv, 438572 (2018). doi: 10.1101/438572
3. Bengtsson-Palme J, Gunnarsson L, Larsson DGJ: Can branding and price of pharmaceuticals guide informed choices towards improved pollution control during manufacturing? Journal of Cleaner Production, 171, 137–146 (2018). doi: 10.1016/j.jclepro.2017.09.247
4. Bielen A, Šimatović A, Kosić-Vukšić J, Senta I, Ahel M, Babić S, Jurina T, González-Plaza JJ, Milaković M, Udiković-Kolić N: Negative environmental impacts of antibiotic-contaminated effluents from pharmaceutical industries. Water Research, 126, 79–87 (2017). doi: 10.1016/j.watres.2017.09.019
5. González-Plaza JJ, Šimatović A, Milaković M, Bielen A, Wichmann F, Udikovic-Kolic N: Functional repertoire of antibiotic resistance genes in antibiotic manufacturing effluents and receiving freshwater sediments. Frontiers in Microbiology, 8, 2675 (2017). doi: 10.3389/fmicb.2017.02675

I am happy to announce that Cancer- och Allergifonden [the Cancer and Allergy Foundation] have awarded me with the first Lennart Sparell prize. The prize was instated in memory of the foundations founder – Lennart Sparell, who passed away last year – and is awarded to researchers (or other persons) who have thought outside-of-the-box or challenged the current paradigms. A particular emphasis is given to research on environmental pollutants that affect human health through food or environmental exposure.

Naturally, I am honored to be the recipient of this prize. The award was motivated by the research I have done on the role of ecological and evolutionary processes in the external environment in driving antibiotic resistance development, and how that can have consequences for human health. Particularly, I am happy that the research that I, Joakim Larsson, Erik Kristiansson and a few others on the role of environmental processes in the development of antibiotic resistance and the recruitment of novel resistance genes are given attention. This view, which perhaps do not challenge the paradigm but at the very least points to an alternative risk scenario, has often been neglected when environmental antibiotic resistance has been discussed.

The prize will be awarded on a ceremony on June 10 in Stockholm, but I would already now take the opportunity to thank everyone who has been involved in the research being recognized, particularly Joakim Larsson and Erik Kristiansson – this award is to a very very large extent to your merit.

The outcomes from a workshop arranged by JPIAMR, the Swedish Research Council (VR) and CARe were just published as a short review paper in Environment International. In the paper, which was mostly moved forward by Prof. Joakim Larsson at CARe, we describe four major areas of knowledge gaps in the realm of environmental antibiotic resistance (1). We then highlight several important sub-questions within these areas. The broad areas we define are:

• What are the relative contributions of different sources of antibiotics and antibiotic resistant bacteria into the environment?
• What is the role of the environment as affected by anthropogenic inputs (e.g. pollution and other activities) on the evolution (mobilization, selection, transfer, persistence etc.) of antibiotic resistance?
• How significant is the exposure of humans to antibiotic resistant bacteria via different environmental routes, and what is the impact on human health?
• What technological, social, economic and behavioral interventions are effective to mitigate the emergence and spread of antibiotic resistance via the environment?

Although much has been written on the topic before (e.g. 2-12), I think it is unique that we collect and explicitly point out areas in which we are lacking important knowledge to build accurate risk models and devise appropriate intervention strategies. The workshop was held in Gothenburg on the 27–28th of September 2017. The workshop leaders Joakim Larsson, Ana-Maria de Roda Husman and Ramanan Laxminarayan were each responsible for moderating a breakout group, and every breakout group was tasked to deal with knowledge gaps related to either evolution, transmission or interventions. The reports of the breakout groups were then discussed among all participants to clarify and structure the areas where more research is needed, which boiled down to the four overarching critical knowledge gaps described in the paper (1).

This is a short paper, and I think everyone with an interest in environmental antibiotic resistance should read it and reflect over its content (because, we may of course have overlooked some important aspect). You can find the paper here.

References

1. Larsson DGJ, Andremont A, Bengtsson-Palme J, Brandt KK, de Roda Husman AM, Fagerstedt P, Fick J, Flach C-F, Gaze WH, Kuroda M, Kvint K, Laxminarayan R, Manaia CM, Nielsen KM, Ploy M-C, Segovia C, Simonet P, Smalla K, Snape J, Topp E, van Hengel A, Verner-Jeffreys DW, Virta MPJ, Wellington EM, Wernersson A-S: Critical knowledge gaps and research needs related to the environmental dimensions of antibiotic resistance. Environment International, 117, 132–138 (2018). doi: 10.1016/j.envint.2018.04.041
2. Bengtsson-Palme J, Kristiansson E, Larsson DGJ: Environmental factors influencing the development and spread of antibiotic resistance. FEMS Microbiology Reviews, 42, 1, 68–80 (2018). doi: 10.1093/femsre/fux053
3. Martinez JL, Coque TM, Baquero F: What is a resistance gene? Ranking risk in resistomes. Nature Reviews Microbiology 2015, 13:116–123. doi:10.1038/nrmicro3399
4. Bengtsson-Palme J, Larsson DGJ: Antibiotic resistance genes in the environment: prioritizing risks. Nature Reviews Microbiology, 13, 369 (2015). doi: 10.1038/nrmicro3399-c1
5. Ashbolt NJ, Amézquita A, Backhaus T, Borriello P, Brandt KK, Collignon P, et al.: Human Health Risk Assessment (HHRA) for Environmental Development and Transfer of Antibiotic Resistance. Environmental Health Perspectives, 121, 993–1001 (2013)
6. Pruden A, Larsson DGJ, Amézquita A, Collignon P, Brandt KK, Graham DW, et al.: Management options for reducing the release of antibiotics and antibiotic resistance genes to the environment. Environmental Health Perspectives, 121, 878–85 (2013).
7. Gillings MR: Evolutionary consequences of antibiotic use for the resistome, mobilome and microbial pangenome. Frontiers in Microbiology, 4, 4 (2013).
8. Baquero F, Alvarez-Ortega C, Martinez JL: Ecology and evolution of antibiotic resistance. Environmental Microbiology Reports, 1, 469–476 (2009).
9. Baquero F, Tedim AP, Coque TM: Antibiotic resistance shaping multi-level population biology of bacteria. Frontiers in Microbiology, 4, 15 (2013).
10. Berendonk TU, Manaia CM, Merlin C et al.: Tackling antibiotic resistance: the environmental framework. Nature Reviews Microbiology, 13, 310–317 (2015).
11. Hiltunen T, Virta M, Laine A-L: Antibiotic resistance in the wild: an eco-evolutionary perspective. Philosophical Transactions of the Royal Society B: Biological Sciences, 372 (2017) doi: 10.1098/rstb.2016.0039.
12. Martinez JL: Bottlenecks in the transferability of antibiotic resistance from natural ecosystems to human bacterial pathogens. Frontiers in Microbiology, 2, 265 (2011).

My colleagues in Gothenburg have published a new paper in Environment International, in which I was involved in the bioinformatics analyses. In the paper, for which Nadine Kraupner did the lion’s share of the work, we establish minimal selective concentrations (MSCs) for resistance to the antibiotic ciprofloxacin in Escherichia coli grown in complex microbial communities (1). We also determine the community responses at the taxonomic and resistance gene levels. Nadine has made use of Sara Lundström’s aquarium system (2) to grow biofilms in the exposure of sublethal levels of antibiotics. Using the system, we find that 1 μg/L ciprofloxacin selects for the resistance gene qnrD, while 10 μg/L ciprofloxacin is required to detect changes of phenotypic resistance. In short, the different endpoints studied (and their corresponding MSCs) were:

• CFU counts from test tubes, grown on R2A plates with 2 mg/L ciprofloxain – MSC = 5 μg/L
• CFU counts from aquaria, grown on R2A plates with 0.25 or 2 mg/L ciprofloxain – MSC = 10 μg/L
• Chromosomal resistance mutations – MSC ~ 10 μg/L
• Increased resistance gene abundances, metagenomics – MSC range: 1 μg/L
• Changes to taxonomic diversity – 1 µg/L
• Changes to taxonomic community composition – MSC ~ 1-10 μg/L

We have previously reported a predicted no-effect concentration for resistance of 0.064 µg/L for ciprofloxacin (3), which corresponds fairly well with the MSCs determined experimentally here, being around a factor of ten off. However, we cannot exclude that in other experimental systems, the selective effects of ciprofloxacin could be even lower and thus the predicted PNEC may still be relevant. The selective concentrations we report for ciprofloxacin are close to those that have been reported in sewage treatment plants (3-5), suggesting the possibility for weak selection of resistance. Several recent reports have underscored the need to populate the this far conceptual models for resistance development in the environment with actual numbers (6-10). Determining selective concentrations for different antibiotics in actual community settings is an important step on the road towards building accurate quantitative models for resistance emergence and propagation.

References

1. Kraupner N, Ebmeyer S, Bengtsson-Palme J, Fick J, Kristiansson E, Flach C-F, Larsson DGJ: Selective concentration for ciprofloxacin in Escherichia coli grown in complex aquatic bacterial biofilms. Environment International, 116, 255–268 (2018). doi: 10.1016/j.envint.2018.04.029 [Paper link]
2. Lundström SV, Östman M, Bengtsson-Palme J, Rutgersson C, Thoudal M, Sircar T, Blanck H, Eriksson KM, Tysklind M, Flach C-F, Larsson DGJ: Minimal selective concentrations of tetracycline in complex aquatic bacterial biofilms. Science of the Total Environment, 553, 587–595 (2016). doi: 10.1016/j.scitotenv.2016.02.103 [Paper link]
3. Bengtsson-Palme J, Larsson DGJ: Concentrations of antibiotics predicted to select for resistant bacteria: Proposed limits for environmental regulation. Environment International, 86, 140-149 (2016). doi: 10.1016/j.envint.2015.10.015
4. Michael I, Rizzo L, McArdell CS, Manaia CM, Merlin C, Schwartz T, Dagot C, Fatta-Kassinos D: Urban wastewater treatment plants as hotspots for the release of antibiotics in the environment: a review. Water Research, 47, 957–995 (2013). doi:10.1016/j.watres.2012.11.027
5. Bengtsson-Palme J, Hammarén R, Pal C, Östman M, Björlenius B, Flach C-F, Kristiansson E, Fick J, Tysklind M, Larsson DGJ: Elucidating selection processes for antibiotic resistance in sewage treatment plants using metagenomics. Science of the Total Environment, 572, 697–712 (2016). doi: 10.1016/j.scitotenv.2016.06.228
6. Ågerstrand M, Berg C, Björlenius B, Breitholtz M, Brunstrom B, Fick J, Gunnarsson L, Larsson DGJ, Sumpter JP, Tysklind M, Rudén C: Improving environmental risk assessment of human pharmaceuticals. Environmental Science and Technology (2015). doi:10.1021/acs.est.5b00302
7. Bengtsson-Palme J, Kristiansson E, Larsson DGJ: Environmental factors influencing the development and spread of antibiotic resistance. FEMS Microbiology Reviews, 42, 1, 68–80 (2018). doi: 10.1093/femsre/fux053
8. Joint Programming Initiative on Antimicrobial Resistance: JPIAMR Workshop on Environmental Dimensions of AMR: Summary and recommendations. JPIAMR (2017). [Link]
9. Angers A, Petrillo P, Patak, A, Querci M, Van den Eede G: The Role and Implementation of Next-Generation Sequencing Technologies in the Coordinated Action Plan against Antimicrobial Resistance. JRC Conference and Workshop Report, EUR 28619 (2017). doi: 10.2760/745099
10. Larsson DGJ, Andremont A, Bengtsson-Palme J, Brandt KK, de Roda Husman AM, Fagerstedt P, Fick J, Flach C-F, Gaze WH, Kuroda M, Kvint K, Laxminarayan R, Manaia CM, Nielsen KM, Ploy M-C, Segovia C, Simonet P, Smalla K, Snape J, Topp E, van Hengel A, Verner-Jeffreys DW, Virta MPJ, Wellington EM, Wernersson A-S: Critical knowledge gaps and research needs related to the environmental dimensions of antibiotic resistance. Environment International, in press (2018). doi: 10.1016/j.envint.2018.04.041

Recently, Le Page et al. published a paper in Environmental International (1), partially building on the predicted no-effect concentrations for resistance selection for 111 antibiotics that me and Joakim Larsson published around two years ago (2). In their paper, the authors stress that discharge limits for antibiotics need to consider their potency to affect both environmental and human health, which we believe is a very reasonable standpoint, and to which we agree. However, we do not agree on the authors’ claim that cyanobacteria would often be more sensitive to antibiotics than the most sensitive human-associated bacteria (1). Importantly, we also think that it is a bit unclear from the paper which protection goals are considered. Are the authors mainly concerned with protecting microbial diversity in ecosystems, protecting ecosystem functions and services, or protecting from risks for resistance selection? This is important because it influence why one would want to mitigate, and therefore who would perform which actions. To elaborate a little on our standpoints, we wrote a short correspondence piece to Environment International, which is now published (3). (It has been online for a few days, but without a few last-minute changes we did to the proof, and hence I’m only posting about it now when the final version is online.) There is indeed an urgent need for discharge limits for antibiotics, particularly for industrial sources (4) and such limits would have tremendous value in regulation efforts, and in development of environmental criteria within public procurement and generic exchange programs (5). Importantly, while we are all for taking ecotoxicological data into account when doing risk assessment, we think that there should be solid scientific ground for mitigations and that regulations need to consider the benefits versus the costs, which is what we want to convey in our response to Le Page et al.

References

1. Le Page G, Gunnarsson L, Snape J, Tyler CR: Integrating human and environmental health in antibiotic risk assessment: a critical analysis of protection goals, species sensitivity and antimicrobial resistance. Environment International, in press (2017). doi: 10.1016/j.envint.2017.09.013
2. Bengtsson-Palme J, Larsson DGJ: Concentrations of antibiotics predicted to select for resistant bacteria: Proposed limits for environmental regulation. Environment International, 86, 140–149 (2016). doi: 10.1016/j.envint.2015.10.015
3. Bengtsson-Palme J, Larsson DGJ: Protection goals must guide risk assessment for antibiotics. Environment International, in press (2017). doi: 10.1016/j.envint.2017.10.019
4. Bengtsson-Palme J, Larsson DGJ: Time to limit antibiotic pollution. The Medicine Maker, 0416, 302, 17–18 (2016). [Paper link]
5. Bengtsson-Palme J, Gunnarsson L, Larsson DGJ: Can branding and price of pharmaceuticals guide informed choices towards improved pollution control during manufacturing? Journal of Cleaner Production, 171, 137–146 (2018). doi: 10.1016/j.jclepro.2017.09.247

Yesterday, Swedish television channel TV4 highlighted a recent publication by myself, Lina Gunnarsson and Joakim Larsson, in which we show that the price of pharmaceuticals is linked to the environmental standards of production countries. Surprisingly, however, this link seems to be mostly driven by whether the product is generic or original (branded), which in turns affect the prices.

In the study (1), published in Journal of Cleaner Production, we have used an exclusive set of Swedish sales data for pharmaceuticals combined with data on the origin of the active ingredients, obtained under an agreement to not identify individual manufacturers or products. We used this data to determine if price pressure and generic substitution could be linked to the general environmental performance and the corruption levels of the production countries, as measured by the Environmental Performance Index (2) and the Corruption Perception Index (3). In line with what we believed, India was the largest producer of generics, while Europe and the USA dominated the market for branded products (1). Importantly, we found that the price and environmental performance index of the production countries were linked, but that this relationship was largely explained by whether the product was original or generic.

To some extent, this relationship would allow buyers to select products that likely originate from countries that, in general terms, have better pollution control, which was also highlighted in the news clip that TV4 produced. However, what was lacking from that clip was the fact that this approach lacks resolution, because it does not say anything about the environmental footprint of individual products. We therefore conclude that to better allow consumers, hospitals and pharmacies to influence the environmental impact of their product choices, there is need for regulation and, importantly, transparency in the production chain, as has also been pointed out earlier (4,5). To this end, emissions from manufacturing need to be measured, allowing for control and follow-up on industry commitments towards sustainable manufacturing of pharmaceuticals (6). Since the discharges from pharmaceutical manufacturing not only leads to consequences to the local environment (7,8), but also in the case of antibiotics has potentially global consequences in terms of increasing risks for resistance development (9), limiting discharges is an urgent need to avoid a looming antibiotic resistance crisis (10).

The paper was also highlighted by the Centre for Antibiotic Resistance Research, and can be read here or here.

References

1. Bengtsson-Palme J, Gunnarsson L, Larsson DGJ: Can branding and price of pharmaceuticals guide informed choices towards improved pollution control during manufacturing? Journal of Cleaner Production, 171, 137–146 (2018). doi: 10.1016/j.jclepro.2017.09.247
2. Hsu A, Alexandre N, Cohen S, Jao P, Khusainova E: 2016 Environmental Performance Index. Yale University, New Haven, CT, USA (2016). http://epi.yale.edu/reports/2016-report
3. Transparency International: Corruption Perceptions Index 2014. Transparency International, Berlin, Germany (2014). http://www.transparency.org/cpi2014/in_detail
4. Larsson DGJ, Fick J: Transparency throughout the production chain–a way to reduce pollution from the manufacturing of pharmaceuticals? Regulatory Toxicology and Pharmacology, 53, 161–163 (2009). doi:10.1016/j.yrtph.2009.01.008
5. Ågerstrand M, Berg C, Björlenius B, Breitholtz M, Brunström B, Fick J, Gunnarsson L, Larsson DGJ, Sumpter JP, Tysklind M, Rudén C: Improving environmental risk assessment of human pharmaceuticals. Environmental Science & Technology, 49, 5336–5345 (2015). doi:10.1021/acs.est.5b00302
6. Industry Roadmap for Progress on Combating Antimicrobial Resistance: Industry Roadmap for Progress on Combating Antimicrobial Resistance – September 2016. (2016). http://www.ifpma.org/wp-content/uploads/2016/09/Roadmap-for-Progress-on-AMR-FINAL.pdf
7. Larsson DGJ, de Pedro C, Paxeus N: Effluent from drug manufactures contains extremely high levels of pharmaceuticals. Journal of Hazardous Materials, 148, 751–755 (2007). doi:10.1016/j.jhazmat.2007.07.008
8. aus der Beek T, Weber FA, Bergmann A, Hickmann S, Ebert I, Hein A, Küster A: Pharmaceuticals in the environment–Global occurrences and perspectives. Environmental Toxicology and Chemistry, 35, 823–835 (2016). doi:10.1002/etc.3339
9. Bengtsson-Palme J, Larsson DGJ: Concentrations of antibiotics predicted to select for resistant bacteria: Proposed limits for environmental regulation. Environment International, 86, 140–149 (2016). doi: 10.1016/j.envint.2015.10.015
10. Bengtsson-Palme J, Larsson DGJ: Time to limit antibiotic pollution. The Medicine Maker, 0416, 302, 17–18 (2016). [Paper link]