Tag: Book chapter

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]

Time flies, and my first 2019 publication (wait what?) is now out! It’s a chapter in the book “Management of Emerging Public Health Issues and Risks: Multidisciplinary Approaches to the Changing Environment” (1), edited by Benoit Roig, Karine Weiss and Véronique Thireau. I have to confess to not having read the other chapters in the book yet, but I think the subject is exciting and hope for a lot of good reading over Christmas here!

My chapter deals with assessment and management of risks associated with antibiotic resistance in the environment (2), and particularly I make an attempt at clarifying the different types of risks and how to deal with them. In short, I partition resistance risks into two categories: dissemination risks and risks for acquisition of new types of resistance (see also 3). While the former category largely encompasses quantifiable risks, the latter is to a large extent impossible (or at least extremely hard) to quantify with current means. This means that we need to be a bit more creative in assessing, prioritizing and managing these risks. Some lessons can be learnt from other fields dealing with very uncertain (and rare) risks, such as asteroid impact assessment, nuclear energy accidents and ecosystem destabilization (4,5). Incorporating elements from such risk management schemes will be necessary to understand and delay emergence of novel resistance in the future.

All these aspects are further discussed in the book chapter (2), which I encourage everyone working with environmental antibiotic resistance risks to read!

References

1. Roig B, Weiss K, Thoreau V (Eds.) Management of Emerging Public Health Issues and Risks: Multidisciplinary Approaches to the Changing Environment. Academic Press/Elsevier, UK (2019). doi: 10.1016/C2016-0-00995-6
2. Bengtsson-Palme J: Assessment and management of risks associated with antibiotic resistance in the environment. In: Roig B, Weiss K, Thoreau V (Eds.) Management of Emerging Public Health Issues and Risks: Multidisciplinary Approaches to the Changing Environment, 243–263. Elsevier, UK (2019). doi: 10.1016/B978-0-12-813290-6.00010-X
3. 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
4. WBGU GACOGC: World in Transition: Strategies for Managing Global Environmental Risks. Springer
   Berlin Heidelberg, Berlin, Heidelberg (2000).
5. Government Office for Science: Blackett Review of High Impact Low Probability Events. Department for
   Business, Innovation and Skills, London (2011).

Last summer, I was approached by Muniyandi Nagarajan to write a book chapter for a book on metagenomics. The book was published earlier this month, and is now available online (1). I have to admit that I have not yet read the entire book, but my own chapter deals with selecting the right tools for metagenomic analysis, and discusses different strategies to perform taxonomic classification, functional analysis, metagenomic assembly, and statistical comparisons between metagenomes (2). The chapter also considers the pros and cons of automated computational “pipelines” for analysis of metagenomic data. While I do not point to a specific set of software that obviously perform better in all situations, I do highlight some analysis strategies that clearly should be avoided. The chapter also suggests a few among the set of robust and well-functioning software tools that, in my opinion, should be used for metagenomic analyses. To some degree, this paper overlaps with the review paper we wrote on using metagenomics to analyze antibiotic resistance genes in various environments, published earlier this year (3), but the discussion in the book chapter is far more general. I imagine that the book chapter could be used, for example, in teaching metagenomics to students in bioinformatics (that’s at least a use I envision myself). Finally, apart from my own chapter, I can also highly recommend the chapter by Boulund et al. on statistical considerations for metagenomic data analysis (4). The book is available to buy from here, and the chapter can be read here.

References

1. Nagarajan M (Ed.) Metagenomics: Perspectives, Methods, and Applications. ISBN: 9780081022689. Academic Press, Elsevier, USA (2018). doi: 10.1016/B978-0-08-102268-9 [Link]
2. Bengtsson-Palme J: Strategies for Taxonomic and Functional Annotation of Metagenomes. In: Nagarajan M (Ed.) Metagenomics: Perspectives, Methods, and Applications, 55–79. Academic Press, Elsevier, USA (2018). doi: 10.1016/B978-0-08-102268-9.00003-3 [Link]
3. Bengtsson-Palme J, Larsson DGJ, Kristiansson E: Using metagenomics to investigate human and environmental resistomes. Journal of Antimicrobial Chemotherapy, 72, 2690–2703 (2017). doi: 10.1093/jac/dkx199 [Paper link]
4. Boulund F, Pereira MB, Jonsson V, Kristiansson E: Computational and Statistical Considerations in the Analysis of Metagenomic Data. In: Nagarajan M (Ed.) Metagenomics: Perspectives, Methods, and Applications, 81–102. Academic Press,, Elsevier, USA (2018). doi: 10.1016/B978-0-08-102268-9.00004-5 [Link]

A long time ago, we (Martin Eriksson, Martin Hartmann, Henrik Nilsson and me) were invited to write an overview on Metaxa for the Encyclopedia of Metagenomics. I guess the workload for pulling such a project off is huge, so there’s no surprise that it has taken a while for it to be accepted, but now it is available for consumption.

Meanwhile, Metaxa have been getting regular updates, and I hope to soon be able to show you a new major update to the software, bringing it up to the next generation of metagenomics. More on that soon.

• Bengtsson-Palme J, Hartmann M, Eriksson KM, Nilsson RH: Metaxa, overview. In:Nelson K. (Ed.) Encyclopedia of Metagenomics: SpringerReference (www.springerreference.com). Springer-Verlag Berlin Heidelberg (2013). [Link]