Enhancing Microbial Pollutant Degradation by Integrating Eco-Evolutionary Principles with Environmental Biotechnology

Abstract

We advocate to shift research efforts in environmental biotechnology from searching for desired traits of monocultures to that of microbial communities. As these traits will be hard to identify with classical genome mining approaches, we recommend using artificial community selection as a tool to identify and to select for novel and/or enhanced functions.Bioremediation and biodegradation with artificially selected microbial communities harbors great potential to become a fast, cost-effective, eco-friendly, and socially acceptable way to remove pollutants without prior knowledge of the involved species and degradation pathways needed.The use of highly integrated multispecies microbial communities instead of monocultures in biodegradation processes will result in more stable and more productive cultures.The novelty of our proposed approach lies in the combination of eco-evolutionary principles with applied biotechnology. This will stimulate new advancements in environmental biotechnology, and will likely result in the discovery of novel metabolic degradation pathways. Environmental accumulation of anthropogenic pollutants is a pressing global issue. The biodegradation of these pollutants by microbes is an emerging field but is hampered by inefficient degradation rates and a limited knowledge of potential enzymes and pathways. Here, we advocate the view that significant progress can be achieved by harnessing artificial community selection for a desired biological process, an approach that makes use of eco-evolutionary principles. The selected communities can either be directly used in bioremediation applications or further be analyzed and modified, for instance through a combination of systems biology, synthetic biology, and genetic engineering. This knowledge can then inform machine learning and enhance the discovery of novel biodegradation pathways. Environmental accumulation of anthropogenic pollutants is a pressing global issue. The biodegradation of these pollutants by microbes is an emerging field but is hampered by inefficient degradation rates and a limited knowledge of potential enzymes and pathways. Here, we advocate the view that significant progress can be achieved by harnessing artificial community selection for a desired biological process, an approach that makes use of eco-evolutionary principles. The selected communities can either be directly used in bioremediation applications or further be analyzed and modified, for instance through a combination of systems biology, synthetic biology, and genetic engineering. This knowledge can then inform machine learning and enhance the discovery of novel biodegradation pathways. Pollution, in the atmosphere, soil, or water, is a serious challenge of the 21st century. Deleterious impacts on aquatic ecosystems are triggered by different sources of anthropogenic pollution including sewage, nutrients and terrigenous materials, crude oil, heavy metals, and plastics [1.Häder D.-P. et al.Anthropogenic pollution of aquatic ecosystems: emerging problems with global implications.Sci. Total Environ. 2020; 713: 136586Crossref PubMed Scopus (138) Google Scholar]. Importantly, oceans comprise the largest biome on the planet and operate as a sink for many pollutants, such as plastics. It is estimated that 80% of the plastic pollution in the ocean comes from land-based sources and reaches the ocean via rivers and wastewater treatment facilities [2.Amaral-Zettler L.A. et al.Ecology of the plastisphere.Nat. Rev. Microbiol. 2020; 18: 139-151Crossref PubMed Scopus (242) Google Scholar]. In 2010, it was estimated that 5–13 million tons of plastic entered the ocean [3.Jambeck J.R. et al.Plastic waste inputs from land into the ocean.Science. 2015; 347: 768-771Crossref PubMed Scopus (4638) Google Scholar], where they accumulate in various habitats, such as marine sediments, and via ingestion at different trophic levels in the marine food web. Many of the pollutants are of global concern because they significantly affect human and ecosystem health around the world, for instance, contaminants of emerging concern (CECs) [4.Nilsen E. et al.Critical review: grand challenges in assessing the adverse effects of contaminants of emerging concern on aquatic food webs.Environ. Toxicol. Chem. 2018; 38: 46-60Crossref PubMed Scopus (70) Google Scholar], persistent organic pollutants (POPs) [5.Jamieson A.J. et al.Bioaccumulation of persistent organic pollutants in the deepest ocean fauna.Nat. Ecol. Evol. 2017; 1: 51Crossref PubMed Scopus (168) Google Scholar], and endocrine disrupting chemicals (EDCs) [6.Zhou X. et al.Endocrine disrupting chemicals in wild freshwater fishes: species, tissues, sizes, and human health risks.Environ. Pollut. 2018; 244: 462-468Crossref PubMed Scopus (46) Google Scholar]. Therefore, restoration and conservation of our ecosystems for future generations should be of utmost priority. To date, different remediation techniques, such as physical, chemical, and biological, have been used for the removal of contaminants. Despite the fact that physical and chemical approaches have been practiced for decades, they still suffer from several drawbacks. These include high processing costs, increased requirements of reagents, and the undesirable generation of secondary pollutants [7.Dangi A.K. et al.Bioremediation through microbes: systems biology and metabolic engineering approach.Crit. Rev. Biotechnol. 2018; 39: 79-98Crossref PubMed Scopus (90) Google Scholar]. By contrast, biological remediation (bioremediation, see Glossary) in the form of microbe-based treatments, is a cost-effective, eco-friendly, and socially acceptable way to remove pollutants such as heavy metals [8.Iravani S. Varma R.S. Bacteria in heavy metal remediation and nanoparticle biosynthesis.ACS Sustain. Chem. Eng. 2020; 8: 5395-5409Crossref Scopus (42) Google Scholar], pesticides [9.Rodríguez A. et al.Omics approaches to pesticide biodegradation.Curr. Microbiol. 2020; 77: 545-563Crossref PubMed Scopus (34) Google Scholar], and hydrocarbons [10.Ławniczak Ł. et al.Microbial degradation of hydrocarbons - basic principles for bioremediation: a review.Molecules. 2020; 25: 856Crossref Scopus (77) Google Scholar] from the environment. Nevertheless, while culturable bacteria were isolated from contaminated sites already 45 years ago [11.Raymond R.L. et al.Final Report on Beneficial Stimulation of Bacterial Activity in Ground Waters Containing Petroleum Products. American Petroleum Institute (API), Committee on Environmental Affairs, Sun Ventures Inc., 1975Google Scholar], the approach of bioremediation has so far failed to provide convincible solutions in pollutant management. Classically, the majority of the studies performed in the field of bioremediation have aimed to isolate, culture, and characterize the organisms that are responsible for the remediation process [12.Head I.M. et al.Bioremediation: a critical review. Horizon Scientific Press, 2003Google Scholar]. While using such culture-based techniques has resulted in the identification of a number of microbes carrying out the biodegradation of specific environmental contaminants (Malla et al. [13.Malla M.A. et al.Understanding and designing the strategies for the microbe-mediated remediation of environmental contaminants using omics approaches.Front. Microbiol. 2018; 9: 1132Crossref PubMed Scopus (101) Google Scholar] for examples), it suffers from important drawbacks. One is that more than 99% of the microorganisms that exist in the environment cannot be cultivated (easily) under laboratory conditions. This, known as the ‘great plate count anomaly’ [14.Staley J.T. Konopka A. Measurement of in situ activities of nonphotosynthetic microorganisms in aquatic and terrestrial habitats.Annu. Rev. Microbiol. 1985; 39: 321-346Crossref PubMed Scopus (920) Google Scholar], has made the recovery of specific isolates that are responsible for, or participate in, a given biodegradation process challenging. The biodegradation process for the so-called recalcitrant pollutants, such as microplastics and POPs, is particularly problematic as it is slow due to the lack of efficient microbial metabolic traits [15.Janssen D.B. et al.Bacterial degradation of xenobiotic compounds: evolution and distribution of novel enzyme activities.Environ. Microbiol. 2005; 7: 1868-1882Crossref PubMed Scopus (171) Google Scholar]. This can be exemplified by research on the degradation of the non-native polymer polyethylene terephthalate (PET), the sixth most produced plastic in degradation is of the plastic degradation to date, a of enzymes that have been in and S. et that and PubMed Scopus Google et degradation of using a from 2005; Scopus Google et environmental and on microbial Environ. Microbiol. Scopus Google Scholar]. The of these enzymes is hampered by rates that for research is the for novel as as the of already for through engineering et engineering of from for highly efficient 9: Scopus Google Scholar], or et to and plastic 2020; PubMed Scopus Google Scholar]. the of such the field of bioremediation has been as it for the of microbes and microbial communities novel and enzymes with increased Nevertheless, it is problematic to on We effects on the they with microbial communities the bioremediation process and to the environment. This in either or for applications in the in approaches and that have our of the genetic and in microbial communities X. et and research using 7: PubMed Scopus Google Scholar], we still lack knowledge of potential degradation pathways and new approach for to microbial community has been by et al. et of genetic to microbial community 2020; PubMed Scopus Google Scholar]. Here, genetic were to microbial communities under a environmental selection under the of the selection the and of important were involved in the be the communities by in engineering the of microbes with metabolic [7.Dangi A.K. et al.Bioremediation through microbes: systems biology and metabolic engineering approach.Crit. Rev. Biotechnol. 2018; 39: 79-98Crossref PubMed Scopus (90) Google et to and plastic 2020; PubMed Scopus Google S. et through and systems a for Biotechnol. 2018; PubMed Scopus Google Scholar]. and in Press, Scholar] and evolution et evolution of enzymes for PubMed Scopus Google Scholar] are that have machine learning et machine learning evolution of Scholar] for different in to or enzyme enzyme engineering can be used to sites to novel and artificial enzymes S. et with sites for enhanced and 2020; Scopus (46) Google Scholar]. can further be applied to enzyme of different to of enzyme 2017; 7: Scopus (101) Google Scholar]. of approaches of genetic engineering for bioremediation is [7.Dangi A.K. et al.Bioremediation through microbes: systems biology and metabolic engineering approach.Crit. Rev. Biotechnol. 2018; 39: 79-98Crossref PubMed Scopus (90) Google et bacteria for of Google approach at to microbial communities is the new field of in situ engineering et communities by in situ PubMed Scopus Google Scholar], is by the et systems from discovery to 2020; PubMed Scopus Google Scholar]. This has been applied to microbial communities in the et engineering of the in PubMed Scopus Google Scholar]. It was that can be used to genetic to the community in a The to genetic so that traits can a Importantly, genetic can be and into without the for or such as The of systems biology and genetic engineering into an has been proposed for by et al. S. et through and systems a for Biotechnol. 2018; PubMed Scopus Google Scholar] and for engineering by et al. et principles and for engineering Rev. Microbiol. PubMed Scopus Google Scholar]. It is an and approach as it discovery and into bioremediation engineering the of microbes with metabolic [7.Dangi A.K. et al.Bioremediation through microbes: systems biology and metabolic engineering approach.Crit. Rev. Biotechnol. 2018; 39: 79-98Crossref PubMed Scopus (90) Google et to and plastic 2020; PubMed Scopus Google S. et through and systems a for Biotechnol. 2018; PubMed Scopus Google Scholar]. and in Press, Scholar] and evolution et evolution of enzymes for PubMed Scopus Google Scholar] are that have machine learning et machine learning evolution of Scholar] for different in to or enzyme enzyme engineering can be used to sites to novel and artificial enzymes S. et with sites for enhanced and 2020; Scopus (46) Google Scholar]. can further be applied to enzyme of different to of enzyme 2017; 7: Scopus (101) Google Scholar]. of approaches of genetic engineering for bioremediation is [7.Dangi A.K. et al.Bioremediation through microbes: systems biology and metabolic engineering approach.Crit. Rev. Biotechnol. 2018; 39: 79-98Crossref PubMed Scopus (90) Google et bacteria for of Google Scholar]. approach at to microbial communities is the new field of in situ engineering et communities by in situ PubMed Scopus Google Scholar], is by the et systems from discovery to 2020; PubMed Scopus Google Scholar]. This has been applied to microbial communities in the et engineering of the in PubMed Scopus Google Scholar]. It was that can be used to genetic to the community in a The to genetic so that traits can a Importantly, genetic can be and into without the for or such as The of systems biology and genetic engineering into an has been proposed for by et al. S. et through and systems a for Biotechnol. 2018; PubMed Scopus Google Scholar] and for engineering by et al. et principles and for engineering Rev. Microbiol. PubMed Scopus Google Scholar]. 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