case study of xenobiotics

Xenobiotics: Sources, Pathways, Degradation, and Risk Associated with Major Emphasis on Pharmaceutical Compounds

• First Online: 01 November 2023

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• Manbir Singh 6 ,
• Ratish Chandra Mishra 6 ,
• Iqbal Shah 6 ,
• Vaishali Wadhwa 7 &
• Vikram Mor 8  

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Xenobiotics are chemical substances which are alien or unnatural to the animal and human life. Xenobiotics include plant components, pharmaceutical drugs, pesticides, cosmetic products, added food flavors, fragrances, etc. At higher concentrations in environmental matrices, naturally occurring substances (endobiotics) may also be considered as xenobiotics. Xenobiotics are categorized as pesticides, pharmaceutical chemicals, personal care products, illicit narcotic drugs/substances, industrial/commercial goods, and nuclear waste and can be present in various environmental matrices. Xenobiotics are used by people and directly or indirectly penetrate in the different environmental matrices generating various metabolites and secondary products (some are even more toxic). Finally, plants, algae, and aquatic organisms take up xenobiotics leading to bioaccumulation, further causing biomagnification. One of the main obstacles to the sustainable water availability in urban systems is the presence of xenobiotics in aquatic ecosystems. In addition to the greater diversity of enzymes present in complex and varied community of microflora, the chemical distinctions between human and microbial transformations of ingested chemicals result from different selection processes that cause these activities. While host metabolism aids in the body’s elimination of xenobiotics, microbial changes to these substances and their human metabolites frequently promote microbial development by supplying nutrients or producing energy.

The amount of xenobiotics found in environmental matrices can be varied from ng/L to g/L. In both humans and animals, long-term chronic exposure to even little doses of xenobiotics may cause toxic, mutagenic, carcinogenic, or teratogenic effects. These compounds may block the enzyme’s active site or affect it in an allosteric way. Some xenobiotics including chlordecone, dichlorodiphenyltrichloroethane (DDT), and dichlorodiphenyldichloroethylene (DDE) show tendency to bioaccumulate, and even their low-level chronic exposures can potentially have an adverse impact on cell signaling pathways. In order to create safer molecules for use in human environment, knowledge of enhanced molecular designs may be useful along with mechanism of xenobiotics’ action. The following chapter explores types and sources of various xenobiotics, the introduction of xenobiotics in the atmosphere and soil, pathways and migration in the soil and aquatic systems (with emphasis on pharmaceutical chemicals), and decomposition of pharmaceutical chemicals in the environment.

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Singh, M., Mishra, R.C., Shah, I., Wadhwa, V., Mor, V. (2023). Xenobiotics: Sources, Pathways, Degradation, and Risk Associated with Major Emphasis on Pharmaceutical Compounds. In: Singh, R., Singh, P., Tripathi, S., Chandra, K.K., Bhadouria, R. (eds) Xenobiotics in Urban Ecosystems. Springer, Cham. https://doi.org/10.1007/978-3-031-35775-6_5

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Article Contents

Key issue no. 1: defining gut microbiomes associated with health, research need no. 1, key issue no. 2: defining causes and effects of altering the gut microbiome, research need no. 2, key issue no. 3: accounting for biotransformation, research need no. 3, key issue no. 4: determining biomarkers of disease and toxicity, research need no. 4, key issue no. 5: optimizing animal models, research need no. 5, recommendations, acknowledgments, the gut microbiome and xenobiotics: identifying knowledge gaps.

Vicki L. Sutherland and Charlene A. McQueen contributed equally to this study.

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Vicki L Sutherland, Charlene A McQueen, Donna Mendrick, Donna Gulezian, Carl Cerniglia, Steven Foley, Sam Forry, Sangeeta Khare, Xue Liang, Jose E Manautou, Donald Tweedie, Howard Young, Alexander V Alekseyenko, Frank Burns, Rod Dietert, Alan Wilson, Connie Chen, The Gut Microbiome and Xenobiotics: Identifying Knowledge Gaps, Toxicological Sciences , Volume 176, Issue 1, July 2020, Pages 1–10, https://doi.org/10.1093/toxsci/kfaa060

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There is an increasing awareness that the gut microbiome plays a critical role in human health and disease, but mechanistic insights are often lacking. In June 2018, the Health and Environmental Sciences Institute (HESI) held a workshop, “The Gut Microbiome: Markers of Human Health, Drug Efficacy and Xenobiotic Toxicity” ( https://hesiglobal.org/event/the-gut-microbiome-workshop ) to identify data gaps in determining how gut microbiome alterations may affect human health. Speakers and stakeholders from academia, government, and industry addressed multiple topics including the current science on the gut microbiome, endogenous and exogenous metabolites, biomarkers, and model systems. The workshop presentations and breakout group discussions formed the basis for identifying data gaps and research needs. Two critical issues that emerged were defining the microbial composition and function related to health and developing standards for models, methods and analysis in order to increase the ability to compare and replicate studies. A series of key recommendations were formulated to focus efforts to further understand host-microbiome interactions and the consequences of exposure to xenobiotics as well as identifying biomarkers of microbiome-associated disease and toxicity.

The gastrointestinal (GI) microbiota play an underlying role in health. Alterations in stability and functional capabilities of microbiota are associated with disease although is unclear whether this is a cause or a result of the disease. Although there is emerging research regarding the physiological functions of intestinal microbes, less is known about the consequences of chemically induced alterations to intestinal microbiome composition and toxicological effects to the host. The interactions of xenobiotics with the microbiota as a result of drug therapy or environmental exposures are of increasing interest to public health.

Health and Environmental Sciences Institute (HESI) assembled a cross-disciplinary group of experts ( Table 1 ) to examine gut microbial-host dynamics in order to better understand what is currently known about the effect of chemical exposures on the microbiome and to identify key knowledge gaps related to such exposures ( Figure 1 ).

Key data gaps in the microbiome research field identified at the 2018 HESI workshop. HESI’s June 2018 workshop identified key data gaps in the gut microbiome research field. The results identify needs for easily accessible biomarkers and improved human and animal experimental model studies for testing and validation of the impact of changes in the gut microbiome on human health outcomes.

Workshop Topics and Presenters

Experts from all sectors addressed state of the science and need for identification of biomarkers to advance understanding and decision making on efficacy and safety of xenobiotics. Presentations can be found on the HESI website here ( https://hesiglobal.org/event/the-gut-microbiome-workshop/ ).

The intestinal microbiome is made up of between 500 and 1000 bacterial species as well as viruses, archaea, and eukaryotic microorganisms, many of which play a role in human health and disease ( Backhed et al. , 2012 ; Gilbert et al. , 2018 ; Hanson and Weinstock, 2016 ; Ogilvie and Jones, 2015 ; Qin et al. , 2010 ; Tuddenham and Sears, 2015 ; Virgin, 2014 ; Ward et al. , 2018 ). There is great variation in species diversity, taxonomic composition, and population density of microbiota in the gut of humans and animal species. For those taxa that contribute to human health little is known about the part that each microbial species is filling, how well they perform that function, their interactions with other microorganisms and with the host, and where in the host they are acting ( Backhed et al. , 2012 ; Barratt et al. , 2017 ; Cho and Blaser, 2012 ; Gilbert et al. , 2018 ). Understanding the functions, features and normal ranges of the microbial communities that support health will be essential in addressing impacts of environmental agents and potentially identifying microbial configurations that result in disease ( Lloyd-Price et al. , 2016 , 2019 ). The inclusion of functional measurements may lead to different interpretations of microbiota diversity, compared with taxonomic classification alone, leading to greater analytical challenges ( Fu et al. , 2016 ; Zhu et al. , 2015 ). However, there is a growing consensus that functional characterizations are necessary for understanding and modeling the physiology of the microbiome ( Heintz-Buschart and Wilmes, 2018 ; Moya and Ferrer, 2016 ; Zhu et al. , 2015 ).

Before beneficial or adverse effects of chemical exposure can be determined, it is necessary to have a baseline for the bacterial species diversity as well as an understanding of the functional capacities associated with health. Given the considerable variation across human populations, among individuals and even within an individual, this will not be a single microbiome but a group of features, capabilities and characteristics of microbial communities that contribute to health. In defining such microbiomes, temporal variability in these communities, such as short-term perturbations associated with diet, lifestyle traits, antibiotic exposure, or acute illness, as well as more long-term impacts that may lead to deleterious chronic health outcomes must be considered ( Kundu et al. , 2017 ). In addition, factors such as geographic location, ethnicity, age, physical activity, genetics and gender, resistance (the ability to withstand stress or perturbations), and resilience (the capacity to return to a healthy state) influence an individual’s microbiome ( Backhed et al , 2012 ). For example, diet is associated with significant differences in microbiota both across populations and with longitudinal studies, yet there may not be apparent adverse impacts to human health ( Clemente et al , 2015 ; Yatsunenko et al , 2012 ). Such observations suggest that there may be functional redundancy in biochemical pathways in the microbiome ( Baumler and Sperandio, 2016 ). Large cohort studies may be needed in defining normal variations within a microbiome, especially if the studies include longitudinal sampling of the microbiome ( Faust et al. , 2015 ; Fettweis et al. 2019 ; Flores et al. , 2014 ; Lloyd-Price et al. , 2019 ; Proctor et al. , 2019 ; Vandeputte et al. , 2017a , b ; Yassour et al. , 2016 ; Zhou et al. , 2019 ). Measurement of blood metabolome is useful in predicting gut α-diversity in such studies ( Price et al. , 2017 ; Wilmanski et al. , 2019 ).

For most healthy adults, there appears to be a window of microbiome normalcy whose bounds are not typically exceeded, even though there may be minor transitory variation in composition observed with dietary changes or exposures to certain xenobiotics ( Kundu et al. , 2017 ; Moya and Ferrer, 2016 ). However, changes in microbial communities can be associated with adverse health consequences. In one model, this may occur if a person’s microbiome leaves their respective window of normalcy reaching a “tipping point” where their health is affected. Alternatively, rather than a distinct shift there can be stochastic changes in the microbiome leading to dispersion of the microbiome composition as well as increased functions that are related to disease ( Armour et al. , 2019 ; Zaneveld et al. 2017 ).

In order to understand, adverse health effects of the microbiome resulting from disease or xenobiotic exposure, there is a need to better understand the essential components, capabilities, and range of microbial variation linked to a person’s health. This requires comprehension of both the structure and the function of the microbial community. Identification of key conserved functional, metabolic, and biochemical pathways present in healthy individuals may provide a strong starting point.

It is evident that multiple factors contribute to the composition, diversity and function of the gut microbiome with regard to health, drug efficacy, and xenobiotic toxicity. The list includes genetics, diet, age, obesity, concomitant diseases, drugs, and gender to name a few. There is a need to not only understand the impact of a single factor on the dynamics between gut microbiome and the host but also to determine contributions of combinations of these factors. However, defining what constitutes microbial diversity and functionally of both healthy and unhealthy individuals will help to elucidate the relative contributions of host factors.

Large cohort studies are valuable sources of data for defining microbiomes associated with health, but comparison and reproducibility across such studies is hindered by differences in experimental design and data analysis. Variation and bias in sampling procedures, stabilization conditions, shipment and storage practices, methods for analyte extraction and purification, sample preparation and analysis, bioinformatic analysis algorithms as well as the reference databases used are contributing factors ( Backhed et al. , 2012 ; Gilbert et al. , 2018 ; Sinha et al. , 2017 ; Stulberg et al. , 2016 ). Standardization of methods and analytical approaches is needed to develop a well-characterized measurement pipeline. However, procedures may need to remain somewhat fluid to account for continuing technological developments and evolving understanding of the biology involved.

GI microbiota are essential in maintaining health and wellness by digesting food nutrients, producing endogenous metabolites and biotransforming xenobiotics ( Dietert and Silbergeld, 2015b ). Furthermore, in a healthy individual the gut microbiome, together with the intestinal mucosa, is necessary to maintain gut homeostasis and provide an epithelial barrier between the lumen and the rest of the body ( Hiippala et al. , 2018 ; Rogers, 2015 ).

Loss, disruption or dispersion of a functional microbiome can be associated with acute adverse health effects or chronic diseases. For example, antibiotics can alter a healthy individual’s microbiome resulting in diarrhea, leaving the body susceptible to the development of Clostridium difficile infection ( Backhed et al. , 2012 ; Schaffler and Breitruck, 2018 ; Schubert et al. , 2014 ). Changes in gut microbiota may be linked to the development of inflammatory bowel disease, colorectal cancer, and fatty liver disease ( Miyoshi et al. , 2017 ; Sharpton et al. , 2019 ; Wang et al. , 2017 ).

Many of these chronic diseases have inflammatory or altered immune system characteristics. Critical immune functions related to epithelial signaling, inflammatory responses, production of antimicrobial factors, and induction of Immunoglobulin A antibodies are propagated locally in the GI tract and associated secondary lymphoid tissues (Peyer’s Patches; Baumler and Sperandio, 2016 ; Dietert and Dietert, 2015a ; Hiippala et al. , 2018 ). The microbiome contributes to the development and maintenance of the immune system ( Agace and McCoy, 2017 ). Early life is characterized by a period of microbial flux and assembly which is affected by multiple factors such as manner of delivery (vaginal or c-section), nutrition (breast milk or formula) and antibiotic exposure. Although dynamic in nature, in adults the majority of the composition and function of the microbiome of a healthy person is fairly stable, but this decreases with age due to the loss of key species and a progressive gain of pathobiotic bacteria ( Buford, 2017 ).

The systemic influence of the GI microbiota on human health can be altered by exogenous compounds during drug therapy or environmental exposures. Antibiotics are used to remove a pathogen from the host, but an unintended consequence can be alteration of the composition and function of the gut microbiota ( Miyoshi et al. , 2017 ). Exposure to nicotine, arsenic, or polybrominated diphenyl ethers change the gut microbiome diversity ( Chi et al. , 2017 , 2018 ; Li et al. , 2018 ).

Exposure to xenobiotics can have effects in multiple ways. These include those that are transitory, established, or developmentally programmed ( Dietert and Dietert, 2015a ; Faust et al. , 2015 ; Fofanova et al. , 2016 ; Moya and Ferrer, 2016 ; Norman et al. , 2015 ; Pascal et al. , 2017 ; Sanz et al. , 2015 ; Stenman et al. , 2016 ). The transitory outcomes, such as changes after eating, are typically easily correctable and the gut microbiome return to the composition and functionality exhibited before the insult. Established outcomes occur when there is the alteration of a keystone species within the microbiota which would require significant host and microbiota changes to recover the original microbiota (eg, after C. difficile infection). The developmentally programmed outcomes are those that occur when the adverse impact is the result of alteration during a critical window of the microbiome development and can lead to later-in-life problems associated with the microbiome (eg, antibiotics during early childhood).

The gut microbiome plays an essential role in maintaining health and modification of the microbial communities can have negative effects in the body. Defining what changes in the microbiota are associated with acute or chronic adverse effects, as well as the magnitude of change necessary, is needed. Adverse effects can range from changes to the intestinal barrier integrity to alterations or dispersion of the normal microbiota of the host population of microbiota leading to a diseased state. Identification of such adverse effects may provide biomarkers of disease progression. To begin to identify causes and effects of changes in the microbial population, 2 approaches are possible. One is to start from a healthy individual’s baseline microbiome then determine deviations associated with a disease state. The second is determining what is a diseased state and ascertaining if there are key nodes, drivers, or contributing factors that move individuals from health to illness.

Despite the improvements in analytical, genomic, and bioinformatic techniques related to structure and function of the microbiome in health and disease, there is still a knowledge gap in the translation of high-throughput data from genotype to phenotype and microbiome composition stability/instability versus core function of the microbial community.

GI microbiota have the capacity to metabolize endogenous and exogenous compounds. The metabolites can have positive, neutral, or negative effects on the host. Endogenous microbial metabolites can exert physiological functions. Gut microbe-derived metabolites can signal via receptors at the epithelium interface and communicate with the host. For example, microbial metabolism of tryptophan generates aryl hydrocarbon receptor (AHR) ligands, such as indole, indirubin, and indigo ( Hubbard et al. , 2015 ). These ligands activate AHR and promote intestinal homeostasis through regulation of innate cytokine or chemokine gene expression, regulation of enterocyte differentiation, as well as regulation and development of intraepithelial lymphocytes and innate lymphoid cells. Gut microbial metabolism can result in products associated with adverse health and disease progression. The microbiome converts dietary lipid phosphatidylcholine to trimethylamine (TMA), which is then metabolized by hepatic flavin monooxygenases to TMA-N-oxide (TMAO). TMAO is a proatherogenic factor associated with cardiovascular disease (CVD; Brown and Hazen, 2015 ). Such findings suggest that endogenous microbial metabolites could be used as potential biomarkers of health or disease.

GI microbiota express biotransformation enzymes that metabolize a variety of therapeutic drugs and environmental compounds that can result in changes in efficacy and toxicity ( Klaassen and Kui, 2015 ; Spanogiannopoulos et al. , 2016 ). Gut bacteria can convert a prodrug to an active drug or detoxify the parent compound leading to modified drug availability, as well as changes in pharmacokinetics-pharmacodynamics (PKPDs). Sulfasalazine, a prodrug for ulcerative colitis, is directly metabolized by the gut bacteria at the azo bond to generate 2 bioactive metabolites, sulfapyridine (antimicrobial) and 5-aminosalicylate (anti-inflammatory; Peppercorn and Goldman, 1972 ). The cardiac drug glycoside digoxin undergoes reduction to an inactive metabolite, dihydrodigoxin, which is significantly decreased if antibiotics are preadministered ( Haiser et al. , 2013 ; Lindenbaum et al. , 1981 ). Microbial metabolites of a drug can also increase toxicity. The chemotherapeutic drug irinotecan is metabolized to SN-38 which is both the active and toxic metabolite. SN-38 is formed and glucuronidated by the liver and then transported to the gut where it undergoes deconjugation by gut bacteria. This results in longer gastrointestinal (GI) exposure, reabsorption, and greater bioavailability of SN-38 ( Wallace et al. , 2010 ). The gut microbiome is also implicated in the interindividual variability in metabolism of the analgesic and antipyretic acetaminophen. The endogenous microbial metabolite p-cresol and acetaminophen are substrates for sulfotransferases. Individuals with high levels of p-cresol generated by bacteria may have decreased acetaminophen metabolism through competition for hepatic sulfonation, which could result in an elevated risk for acetaminophen-induced hepatotoxicity ( Clayton et al. , 2009 ).

Nontherapeutic drugs and environmental xenobiotics can induce compositional changes and functional changes an in gut microbiota. In turn, these compounds may also be biotransformed by the microbiome. Arsenic is metabolized by gut bacteria and also alters the abundance and profile of the gut microbiome ( Chi et al. , 2018 ; Gokulan et al. , 2018 ; Lu et al. , 2014 ). Polychlorinated biphenyl or polybrominated diphenyl ether exposed mice show altered bile acid homeostasis resulting in part from changes in gut microbiota bile acid metabolism ( Cheng et al , 2018 ; Li et al , 2018 ). Gut anaerobes are capable of transforming Hg2 + to highly toxic and permeable methylmercury and significantly contributing to its body burden and poisoning ( Edwards and McBride, 1975 ).

In addition to directly biotransforming chemicals, the gut microbiome can influence the host xenobiotic metabolizing capability. Comparison of hepatic drug metabolizing genes in conventional and germ-free (GF) mice show that 34 genes, including Cyp3a, decrease, whereas 21 genes, including Cyp4a, increase ( Selwyn et al. , 2015 ). A cluster of 112 hepatic genes linked to xenobiotic metabolism and retinoid X receptor-inhibiting pathways are differentially expressed in conventional and GF mice. This results in more efficient pentobarbital metabolism and shorter anesthesia time in GF mice ( Bjorkholm et al. , 2009 ).

Current experimental approaches to evaluate microbe-mediated biotransformation primarily include: (1) in vitro incubation of individual bacterial strains, mixed cultures in bioreactors, or purified enzymes with compounds, (2) ex vivo incubation of a fecal microbiome community (or other GI regions of interest) with compounds, and (3) in vivo administration of compounds into animals such as rodents. These approaches provide evidence in support of microbial metabolism of many approved drugs ( Sousa et al. , 2008 ; Zimmermann et al. , 2019 ). However, more caution is required when extrapolating these results into humans than with traditional PKPD approaches, given the high diversity and interindividual variability of the human gut microbiome. Comprehensive and accurate modeling approaches for analyzing microbial metabolism information and incorporating into host PKPD models are necessary.

As more information on biotransformation of xenobiotics by the microbiome is published, a public database would be valuable. Such a database would be a repository centralizing comprehensive data that identifies compounds, responsible bacteria and/or enzymes, metabolites generated and metabolic pathways. This requires a collaborative effort involving researchers from academia, government and industry, working together with the regulatory agencies to promote a better understanding of microbiome-mediated biotransformation.

Biomarkers of disease and toxicity resulting from perturbations of the gut microbiota composition and function, from changes in microbial metabolites, or as a consequence of microbial biotransformation of xenobiotics would be useful. There are a number of characteristics for an ideal biomarker. It should be able to differentiate between disease progression and/or response to treatment. Stool samples or accessible tissues and/or biofluids should be used and analysis be affordable to facilitate acceptance and use for large scale screening. The biomarker needs to work for high-risk populations and distinguish between the disease and other potentially microbiome-mediated effects.

There are some examples of microbiome biomarkers of disease that are promising. Alterations in gut microbiota are associated with hypertension. Exposure of hypertensive rats to the antibiotic minocycline attenuates blood pressure ( Yang et al. , 2015 ). In animals and humans systolic blood pressure is correlated with microbiota composition and metabolites, as well as alterations in gut structure ( Kim et al. , 2018 ). Zonulin, a bacterial product and a marker of intestinal permeability, is elevated with high systolic blood pressure but is not an ideal biomarker since it is also associated with celiac disease ( Fasano et al. , 2000 ; Kim et al. , 2018 ). A more specific indicator may be the negative correlation of butyrate producing bacteria which alter systolic blood pressure and plasma butyrate levels ( Kim et al. , 2018 ).

TMAO blood levels are of interest as a biomarker for CVD, insulin resistance, and type 2 diabetes ( Miao, 2015 ). The production of TMAO in mammals primarily occurs via gut bacteria. Studies in humans and animals show circulating levels of TMAO are associated with risk and progression of CVD ( Tang et al. , 2014 ). Sensitive assays, particularly those amenable to the clinical setting, are being developed which will facilitate use of TMAO as a biomarker ( Garcia et al , 2017 ). The initial association of TMAO with CVD resulted from using untargeted metabolomics in cardiac patients ( Wang et al. , 2011 ). This approach can be expanded to use multiple data streams (clinical tests, metabolomes, proteomes, genome sequence, and microbiome) to develop correlation networks in order to identify bacterial analytes associated with normal physiology or disease ( Price et al. , 2017 ). For example, there is an association between phenylacetylglutamine and the Coriobacteriaceae and Mogibacteriaceae families. Phenylacetylglutamine is a microbial metabolite and is a risk factor for CVD in those with chronic kidney disease ( Poesen et al. , 2016 ).

Microbial biomarkers may also prove useful for identifying xenobiotic toxicity. Low dose exposure of mice to polychlorinated biphenyls alters microbiota composition leading to a greater abundance of species that generate secondary bile acids causing increases in serum bile acids ( Cheng et al. , 2018 ). At higher doses serum bile acids were not affected due to an increase in hepatic efflux transporters ( Cheng et al. , 2018 ).

Although in vivo studies are useful for discovering biomarkers, there is also a need for in vitro methods. In mice, tempol acts as an antioxidant by detoxifying reactive oxygen species and modulates the gut microbiome host signaling axis resulting in prevention of weight gain ( Cai et al. , 2016 ; Li et al ., 2013 ). Incubation of mouse cecal content with tempol and analysis of samples using flow cytometry as well as high-throughput mass spectrometry and nuclear magnetic resonance-based metabolomics show that tempol disrupted microbiota membrane physiology and metabolic activity consistent with the in vivo data ( Cai et al. , 2016 ). Such a multi-prong in vitro approach holds promise for screening xenobiotics for gut microbial toxicity and identifying potential biomarkers.

Case studies provide examples of potential biomarkers that could serve as the basis for noninvasive diagnostic tests to identify disease and track its progression. When an association between a disease and gut microbiota is recognized, additional work will be needed to distinguish between microbial changes that are a cause or a result of the disease. Biomarkers should also be applicable beyond their discovery cohorts and be able to distinguish between disease states of interest and nontarget diseases, as well as having a reasonable degree of specificity.

Discovery and qualification of biomarkers will also be advanced by the adoption of standard protocols which will generate robust and reproducible data that facilitates comparisons of studies. Detailed methods and procedures for analysis of gut microbiota structure and function that will be useful for toxicologic studies are available ( Nichols et al. , 2018 ).

Although animal species have limitations in completely replicating humans, they provide an opportunity to manipulate host genetics and the environment to allow insight into the relationship between the microbiota, xenobiotics, toxicity, and disease. Although species differences must be recognized in extrapolating animal studies to humans, such data are valuable.

Rodents are widely used in studying the microbiome. The compositions of gut microbiota vary among genetically distinct strains of mice ( Friswell et al. , 2010 ). Differences also occur in laboratory strains compared with genetically similar wild populations ( Rosshart et al. , 2017 ). GF mice and gene-knockout mice are also useful models. GF mice can be colonized with a single (mono-associated) agent, a defined bacterial combination such as altered Schardler flora or human fecal samples ( De Palma et al. , 2017 ; Franklin and Ericsson, 2017 ; Orcutt et al. , 1987 ; Ridaura et al. , 2013 ). Interestingly, introducing microbiota from wild mice into laboratory mouse strains increases resistance to influenza infection, decreases inflammation and increases resistance to certain types of cancer ( Rosshart et al. , 2017 ). The wild mouse microbiome develops as a result of evolutionary pressures due to continuous exposure to natural toxins and pathogens, thus it may offer a better model for human disease ( Rosshart et al. , 2017 ).

Disparities in gut microbiota of the same mouse strain can be attributed to vendor or institutional location ( Friswell et al. , 2010 ). Within a facility, the room, cage housing, food, water, and bedding all have an effect ( Ericsson et al. , 2018 ; Friswell et al. , 2010 ; Hildebrand et al. , 2013 ; Hugenholtz and de Vos, 2018 ; Robertson et al. , 2019 ).

Although rodents are the most commonly used models in microbiome studies, zebrafish are also proving to be useful. Zebrafish develop rapidly and externally to the mother, thereby enabling direct embryo exposures. The GI tract is homologous to that in mammals, although there are differences in the immune system. Zebrafish are kept at a lower temperature than mammals which may compromise the ability to study human-relevant microorganisms. Xenobiotic-microbiome interactions can be evaluated in the zebrafish model. For example, exposure of zebrafish larvae to the antimicrobial compound triclosan results in changes in the community structure of the microbiome. There is an increase in triclosan resistant species which results in a greater ability to biotransform triclosan ( Weitekemp et al. , 2019 ). Gut microbiota in zebrafish also alter metabolism and mediate the neurodevelopmental toxicity of 17-β-estradiol ( Catron et al. , 2019 ).

Study reproducibility in the biosciences is an ongoing concern ( Mullane and Williams, 2017 ). Variations in experimental design, methods, and statistical analysis can contribute to an inability to replicate results and conclusions. Complicating this further is the diversity and function of the gut microbiota ( Franklin and Ericsson, 2017 ; Turner, 2018 ).

Reproducibility in studies of gut microbiome host dynamics can be increased by recognizing the sources of variation, prioritizing them; then, identifying ways to address them ( Ericsson and Franklin, 2015 ; Franklin and Ericsson, 2017 ). To limit variation in mouse models, numerous approaches have been developed to standardize gut microbiota profiles including cohousing, cross fostering, and GF derivation, although each has advantages and disadvantages ( Ericsson and Franklin, 2015 ; Franklin and Ericsson, 2017 ). Maintaining a stable microbiome composition across animals and experiments is a problem that is not easily solved. Banking fecal samples annually and defining the microbiome at the initiation of a study would allow institutional drift to be monitored ( Franklin and Ericsson, 2017 ). In some instances, repeating studies in the second generation addresses the need for exposure to microbiota in early development ( Franklin and Ericsson, 2017 ). For zebrafish, protocols for GF derivation and gnotobiotic husbandry provide useful guidance for standardization ( Melancon et al. , 2017 ).

Often the discrepancies in reported results can be attributed to variations in study design. Unfortunately, key details are often missing from publications. Omissions can be reduced by adoption of Animal Research: Reporting of Experiments guidelines ( Kilkenny et al. , 2012 ). This checklist of 20 items covers species, strain and number of animals, husbandry, experimental design, methods, and statistical analysis.

Determining the optimal microbiota to facilitate translating results from mice to humans depends on the question being asked. The current model of colonizing GF mice with microbiota derived from inbred, wild murine, or human sources has great potential. This approach is currently limited by the availability of the number of defined combinations and characterized mouse or human material. The development of a wider array of standardized samples would be useful.

Several in vitro models of host-microbiome interactions have been described that complement in vivo studies ( Arnold et al. , 2016 ; von Martels et al. , 2017 ). Although there are anaerobic bacteria gut epithelial cell cocultures showing feasibility for experimental use, further refinements and standardization are still necessary ( von Martels et al. , 2017 ). It is also recognized that no one model is perfect, the best one to use will depend on the question being addressed.

The gut microbiome plays a pivotal part in health, but understanding its multiple roles still needs to be fully elucidated. HESI’s gut microbiome workshop was convened to identify research areas critical to determining how gut microbiome alterations may influence human health. Data gaps and research needs to address specific issues have been identified based on workshop presentations and breakout group discussions ( Table 2 ).

Key Issues and Research Needs

Key research areas and needs, as identified by workshop speakers and participants who participated in breakout group discussions.

There are 2 topics that cut across the key issues. The first is the lack of clarity in what constitutes gut microbiomes in healthy individuals. It is recognized that there are many factors that contribute to variation across and within human populations. Consequently, there is not a single microbiome but rather a suite of microbiomes that are associated with health. As yet, these have not yet been adequately defined. Having information on which species comprise such microbiomes and the normal range of variation is critical in order to define disease and adverse effects. The second is the need to adopt standards for methods, models and data analysis. This will facilitate comparisons across studies and reproducibility of data.

Moving forward the key recommendations are to focus efforts on the following important areas:

Defining the range of gut microbiota composition and function gut microbiomes associated with health and/or disease;

Identifying microbiome changes linked to disease and adverse health effects;

Characterizing the formation and function of microbiota metabolism of endogenous products on health and disease;

Determining the effects of xenobiotics on microbiota composition and function;

Increasing understanding of the impact of microbiota biotransformation of xenobiotics on efficacy and toxicity;

Identifying a suite of biomarkers to monitor health, disease and adverse effects resulting from microbiota-host interactions;

Standardizing variables such as husbandry, study design, sample collection, analysis, and statistical methods

Addressing these issues will provide further insight into the role of the microbiome in human health, disease and toxicity.

Health and Environmental Sciences Institute (HESI) is an independent nonprofit that collaboratively identifies and helps to resolve global and environmental challenges by convening experts through multi-sector forums. HESI’s work aims to move scientific principles into tested solutions that can be broadly applied to benefit health and the environment. The authors gratefully acknowledge the contributions of the speakers and the workshop participants, the discussions of which form the basis for this article. The views expressed in this article are those of the authors and do not necessarily reflect the views or policies of the author employers.

This work was provided in-kind by the Health and Environmental Sciences Institute (HESI) Microbiome Subcommittee, which is supported by sponsorships from member companies. HESI’s scientific initiatives are primarily supported by the in-kind contributions (from public and private sector participants) of time, expertise, and experimental effort. These contributions are supplemented by direct funding (that primarily supports program infrastructure and management) provided primarily by HESI’s corporate sponsors.

DECLARATION OF CONFLICTING INTERESTS

The authors of the article volunteered to serve on the HESI Microbiome committee and were involved in the planning and execution of the workshop. The views expressed in this article reflect the discussions from the workshop and do not necessarily reflect the views or policies of their employers.

Disclaimer: This workshop report is for information purposes only and shall not be construed to represent the official position or an obligation on the part of the U.S. Federal Government or any individual organization to provide support for any ideas or recommendations identified in it.

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Author notes

• biological markers
• xenobiotics
• biotransformation
• intestinal bacteria
• toxic effect

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Systematic review article, recent advanced technologies for the characterization of xenobiotic-degrading microorganisms and microbial communities.

• 1 State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangdong Province Key Laboratory of Microbial Signals and Disease Control, Integrative Microbiology Research Centre, South China Agricultural University, Guangzhou, China
• 2 Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, China

Global environmental contamination with a complex mixture of xenobiotics has become a major environmental issue worldwide. Many xenobiotic compounds severely impact the environment due to their high toxicity, prolonged persistence, and limited biodegradability. Microbial-assisted degradation of xenobiotic compounds is considered to be the most effective and beneficial approach. Microorganisms have remarkable catabolic potential, with genes, enzymes, and degradation pathways implicated in the process of biodegradation. A number of microbes, including Alcaligenes, Cellulosimicrobium, Microbacterium, Micrococcus, Methanospirillum, Aeromonas, Sphingobium, Flavobacterium, Rhodococcus, Aspergillus, Penecillium, Trichoderma, Streptomyces, Rhodotorula, Candida , and Aureobasidium , have been isolated and characterized, and have shown exceptional biodegradation potential for a variety of xenobiotic contaminants from soil/water environments. Microorganisms potentially utilize xenobiotic contaminants as carbon or nitrogen sources to sustain their growth and metabolic activities. Diverse microbial populations survive in harsh contaminated environments, exhibiting a significant biodegradation potential to degrade and transform pollutants. However, the study of such microbial populations requires a more advanced and multifaceted approach. Currently, multiple advanced approaches, including metagenomics, proteomics, transcriptomics, and metabolomics, are successfully employed for the characterization of pollutant-degrading microorganisms, their metabolic machinery, novel proteins, and catabolic genes involved in the degradation process. These technologies are highly sophisticated, and efficient for obtaining information about the genetic diversity and community structures of microorganisms. Advanced molecular technologies used for the characterization of complex microbial communities give an in-depth understanding of their structural and functional aspects, and help to resolve issues related to the biodegradation potential of microorganisms. This review article discusses the biodegradation potential of microorganisms and provides insights into recent advances and omics approaches employed for the specific characterization of xenobiotic-degrading microorganisms from contaminated environments.

Introduction

The environment is everything that naturally surrounds us and affects our daily lives on Earth. A safe and healthy environment is essential for the existence of life on this planet. However, in the era of advanced industrialization and urbanization, various anthropogenic activities are largely responsible for the introduction of toxic and hazardous pollutants such as environmental xenobiotics ( Embrandiri et al., 2016 ; Malla et al., 2018 ; Bhatt et al., 2020a ; Rodriguez et al., 2020 ). Xenobiotics are chemical substances not naturally produced or expected to be present within organisms. The term “xenobiotic” is usually used in the context of environmental pollutants to refer to synthetic compounds produced in large volumes for industrial, agricultural, and domestic use ( Embrandiri et al., 2016 ; Atashgahi et al., 2018 ; Dinka, 2018 ). There is growing public concern over the wide range of xenobiotic compounds being introduced, deliberately or accidentally, into the environment, which involves high potential risk to humans and animals ( Jacob and Cherian, 2013 ; Hashmi et al., 2017 ; Zhu et al., 2017 ; Dinka, 2018 ). Environmental xenobiotics include pesticides, polycyclic aromatic hydrocarbons (PAHs), pharmaceutical active compounds (PhACs), personal-care products (PCPs), phenolics, chlorinated compounds, and other industrial chemicals. Their increasing frequency in different environmental compartments has raised concerns about their potential adverse effects ( Crinnion, 2010 ; Kim et al., 2013 ; Embrandiri et al., 2016 ; Tsaboula et al., 2016 ; Dhakal et al., 2017 ). Their toxicity results in unprecedented health hazards and risks to environmental safety and security ( Godheja et al., 2016 ; Dovrak et al., 2017 ; Burgos-Aceves et al., 2018 ; Ravindra and Haq, 2019 ). Once xenobiotics are released into the environment, they can bioaccumulate within the food chain due to their high affinity toward organic substances, and produce toxic adverse effects toward natural ecosystems, humans, and animals ( Pedersen et al., 2003 ; Iovdijova and Bencko, 2010 ; Maurya, 2016 ). Consequently, they can cause severe chronic effects such as respiratory tract infections, damage to the immune system, pulmonary bronchitis, dysfunction of the nervous system, disruption of the endocrine system, behavioral and developmental disorders, and carcinogenic and mutagenic effects ( Sajid et al., 2015 ; Zhu et al., 2017 ; Dinka, 2018 ; Catron et al., 2019 ; Mishra et al., 2019 ; Bertotto et al., 2020 ). Thus, xenobiotic contamination represents a persistent anthropogenic threat and raises serious environmental concerns. Various physical and chemical treatment methods such as coagulation, filtration, adsorption, chemical precipitation, electrolysis ozonation, etc. have been used for the degradation and detoxification of such xenobiotic compounds, but not all these methods are very useful due to their high cost, waste-disposal problem and generation of toxic by-products that are sometimes more hazardous than the parent compound. In contrast, the biological remediation method, “bioremediation,” is a widely accepted clean-up strategy for the degradation of xenobiotics from contaminated environments without producing harmful products ( Paul et al., 2005 ; Perelo, 2010 ). Bioremediation involves the metabolic capabilities of microorganisms in the removal of pollutants and thus, is the most suitable and promising technology these days ( Gilliespie and Philp, 2013 ; Azubuike et al., 2016 ).

Microbial remediation of xenobiotic compounds is regarded as a superficial, proficient, economically feasible approach that uses a wide range of microorganisms to consume organic pollutants as carbon or nitrogen supplements to sustain their developmental activities ( Chen et al., 2013 ; Mahmoud, 2016 ; Arora et al., 2018 ; Ortiz-Hernandez et al., 2018 ; Siles and Margesin, 2018 ; Zhan et al., 2018 ; Bhatt et al., 2020b ). Microorganisms are ubiquitous in nature, and diverse microbial communities thrive in natural and extreme stress environments, including soil, water, the human gut, hydrothermal vents, acid mine runoff, and oil reservoirs ( Cycoń and Piotrowska-Seget, 2016 ; Jalowiecki et al., 2016 ; Ding et al., 2017 ; Aguinga et al., 2018 ; Wang Y. F. et al., 2018 ; Zierer et al., 2018 ; Delegan et al., 2019 ; Arora, 2020 ; Shekhar et al., 2020 ). Microbial populations exhibit potential for the remediation of any contaminated environment because of their genetic diversity and functionality ( Chen et al., 2015 ; Bastida et al., 2016 ; Bhatt and Barh, 2018 ; Dangi et al., 2018 ). Therefore, the study of microbial population existing in contaminated environments provides a significant knowledge of specific microbial characteristics that improve degradation rates. However, effective implementation of microbial remediation strategies needs advanced technical approaches, which provide an in-depth understanding about the dynamics aspects of microbial activity and survival under stressed environment ( Rastogi and Sani, 2011 ; Lima-Morales et al., 2016 ; Mao et al., 2019 ). The development in molecular, biotechnological, bioinformatics and system biology tools pertaining to bio-remedial problems have provided gene level mechanisms of bioremediation ( Ahmad and Ahmad, 2014 ; Aora and Bar, 2014 ; Singh D. P. et al., 2018 ; Jaiswal and Shukla, 2020 ; Nkongolo and Kotha, 2020 ; Wolf et al., 2020 ). Moreover, the direct study of microorganisms in a contaminated environment including the whole microbial population granted a new frontier of the scientific community to share the knowledge of the uncultured microbial world ( Zepeda et al., 2015 ; Zhao Q. et al., 2017 ; Panigrahi et al., 2019 ; Yan et al., 2020 ). The development of advance molecular tools and a better understanding of microbial metabolic and genetic structures and functions have accelerated encroachment in recombinant engineering techniques to enhanced bioremediation for removal of environmental pollutants ( Ram et al., 2005 ; Temperton and Giovannoni, 2012 ; Singh V. et al., 2018 ; Stein et al., 2018 ; Delegan et al., 2019 ; Marco and Abram, 2019 ; Puckett et al., 2020 ). Soil is the most dynamic environment for the enormous microbial population of immense diversity. It has been estimated that one gram of soil approximately contains 10 9 bacterial cells, but only <1% of these may be culturable in the laboratory ( Rossello-Mora and Amann, 2001 ). Culture based identification of diverse microbial population in a contaminated environment, is a challenging task, which is limited to fast-growing microbial diversity ( Gillbride et al., 2006 ). Thus, modern culture-independent molecular techniques represent a feasible approach to unrevealing the diversity and functional dynamics of microbial population in contaminated environments. Moreover, the advanced innovation in molecular tools and techniques provides new insights and changes the traditional research trend in the field of bioremediation ( Malik et al., 2008 ; Shah et al., 2011 ; Devarapalli and Kumavnath, 2015 ; Mahmoud, 2016 ; Biswas and Sarkar, 2018 ; Shakya et al., 2019 ). Omics technologies are the result of advanced molecular techniques, which involved direct characterization of genome structure of microorganisms, devoid of their culture sample ( Segata et al., 2013 ; Biswas and Sarkar, 2018 ; Jaiswal et al., 2019 ; Yu K. et al., 2019 ). Therefore, the applications of modern molecular techniques like metagenomic, transcriptomic, proteomic generates relevant information on genes and proteins expression levels in whole microbial communities under contaminated environments attempted to unravel the mechanism of microbial degradation and successful execution of bioremediation ( Keller and Hettich, 2009 ; Yang, 2013 ; Malla et al., 2018 ; Bharagava et al., 2019 ; Marco and Abram, 2019 ; Rodriguez et al., 2020 ). These methods are comparatively efficient, quicker, and accurate, which overcome the limitations of conventional molecular techniques. It explores the advanced microbial degradation mechanism of xenobiotics, their metabolic activities, genetic regulation and molecular-biology aspects ( Cycoń et al., 2017 ; Gutierrez et al., 2018 ; Gutleben et al., 2018 ; Mishra et al., 2020 ). Hence, this review article highlights the biodegradation potential of microorganisms and provides insights into recent advance methods of “omics” technologies employed in microbial degradation and remediation purpose of xenobiotics and their perspectives in modern biological research.

Bioremediation Potential of Microorganisms for Xenobiotic Compounds

The application of microorganisms in removing xenobiotics from soil, water or sediments through complete transformation or mineralization into harmless end products like CO 2 and H 2 O is a basic concept of bioremediation strategy ( Ortiz et al., 2013 ; Singh et al., 2016 ). Different microorganisms including bacteria ( Pseudomonas, Alcaligenes, Cellulosimicrobium, Microbacterium, Micrococcus, Methanospirillum, Aeromonas, Bacillus, Sphingobium, Flavobacterium , and Rhodococcus ), fungi ( Aspergillus, Penecillium, Trichoderma , and Fusarium ), and yeasts ( Pichia, Rhodotorula, Candida, Aureobasidium , and Exophiala ) have been reported to be involved in the efficient biodegradation of xenobiotic compounds from contaminated soil/water environments, due to their exceptional bioremediation potential ( Sathishkumar et al., 2008 ; Nzila, 2013 ; Sunita et al., 2013 ; Zhao Q. et al., 2017 ; Bharadwaj, 2018 ; Yang J. et al., 2018 ; Yang T. et al., 2018 ; Yu Y. et al., 2019 ; Bhatt et al., 2020c ). The biodegradation ability of microbes is greatly influenced by interactive ecological factors including soil, salinity, temperature, carbon source, moisture content, pH, nitrogen sources, inoculums concentration, etc. ( Megharaj and Naidu, 2010 ; Wu et al., 2014 ; Bhatt et al., 2019 ). Microorganisms harbor remarkable catabolic potential, genes, enzymes, and degradation pathways implicated in the process of bioremediation, which might be responsible in the evolution of novel traits and characters ( Widada et al., 2002 ; Scholer et al., 2017 ; Yan et al., 2018 ; Zhu et al., 2020 ). Moreover, microbial plasmids believed to be responsible for the continuous progression, evolution, and distribution of novel biodegradable genes/enzymes ( Zhang et al., 2016 ; Jeffries et al., 2019 ). These novel genes/enzymes have endowed microorganism's biodegradation capability to remove or detoxify a wide variety of environmental pollutants due to their inheritance horizontal gene transfer property ( Singh V. et al., 2018 ; Jaiswal et al., 2019 ; Li et al., 2019 ; Phale et al., 2019 ; French et al., 2020 ). The microbial remediation process can be further improved via successful application of genome editing and biochemical techniques that modify existing strains and result in the development of a genetically modified organism capable of simultaneously degrading several xenobiotics ( Shanker et al., 2011 ; Zhang et al., 2016 ; Hussain et al., 2018 ; Janssen and Stucki, 2020 ). The advancement of genetic manipulation technology gives more clear information and explores future prospects of bioremediation of xenobiotics through highly proficient microorganisms ( Sayler and Ripp, 2000 ; Shapiro et al., 2018 ; Wong, 2018 ; Liu et al., 2019 ). The chemical structures of several xenobiotic compounds are presented in Figure 1 .

Figure 1 . Chemical structures of several xenobiotic compounds.

Synthetic pesticides are the major example of xenobiotics especially the organochlorine pesticides (OCPs) that used extensively worldwide for a long period of time in agriculture as well as in insect control program. Several OCPs such as aldrin, dieldrin, dichloro diphenyl trichloro ethane (DDT), benzene hexachloride (BHC), and hexachlorocyclohexane are highly toxic in nature due to their stability and bioaccumulative property ( Aktar et al., 2009 ; Jayaraj et al., 2016 ; Awasthi and Awasthi, 2019 ; Pang et al., 2020 ). Lindane (γ-hexachlorocyclohexane) is one of the highly toxic organochlorine xenobiotic compound, which is well-studied for its microbial biodegradation through physical (soil structure, carbon and oxygen gradients, pH, and temperature) and chemical (dechlorination, dehydroxylation, and dehydrogenation) interactions ( Kaur and Kaur, 2016 ; Bashir et al., 2018 ; Zhang et al., 2021 ). The increasing concentration of lindane residues into the environment imposes severe health hazards such as carcinogenicity, mutagenicity, endocrine disruption, and immune-suppression diseases into the humans and other organisms ( Cuozzo et al., 2017 ; Zhang et al., 2020 ). Bacterial strains genera such as Bacillus, Burkholderia, Pseudomonas, Kocuria, Archromobacter, Sphingomonas, Chromohalobacter , demonstrated lindane biodegradation under axenic as well as anoxic conditions via dehydrogenation, dehydrochlorination, and hydroxylation, results in complete degradation or mineralization ( Giri et al., 2014 ; Cuozzo et al., 2017 ; Wang W. et al., 2018 ; Nagata et al., 2019 ; Zhang et al., 2020 ). A simplified catabolic pathway of lindane is presented in Figure 2 .

Figure 2 . Simplified catabolic degradation pathways of organochlorine and polycyclic aromatic hydrocarbon (PAH). Compounds (A) lindane (organochlorine) ( Endo et al., 2005 ; Geueke et al., 2013 ) and (B) naphthalene (PAH) ( Kiyohara et al., 1994 ; Dutta et al., 1998 ; Bamforth and Singleton, 2005 ; Baboshin et al., 2008 ).

Pyrethroids are broad spectrum pesticide mainly used against agricultural and household pests. Cypermethrin, cyhalothrin, deltamethrin, cyfluthrin, bifenthrin are the common example of synthetic pyrethroids ( Chen et al., 2012 , 2014 ; Bhatt et al., 2019 ; Zhan et al., 2020 ). These pesticides are highly toxic and persistent and can cause molecular toxicity, neurotoxicity, and reproductive toxicity ( Sharma et al., 2018 ; Bhatt et al., 2019 ; Gammon et al., 2019 ). One of the pyrethroid i.e., cypermethrin can cross the blood-brain barrier and induces neurotoxicity and motor deficits ( Singh et al., 2012 ). The persistence of these pesticides in the environment poses a severe threat to humans and other non-target terrestrial and aquatic organisms ( Burns and Pastoor, 2018 ; Ullah et al., 2018 ; Lu et al., 2019 ). Microbial strains such as Acinetobacter, Trichoderma, Roultella, Pseudomonas, Cunninghamella , and Bacillus have been reported for their efficient degradation of broad spectrum pesticides like cypermethrin and other pyrethroid pesticides through pyrethroid hydrolases ( Cycoń and Piotrowska-Seget, 2016 ; Zhan et al., 2018 ; Bhatt et al., 2019 ; Chen and Zhan, 2019 ). Co-metabolism exhibiting strains include Flavobacterium, Sphingomonas, Arthrobacter, Azotobacter, Achromobacter, Microbacterium, Brevibacterium, Rhodococcus, Trichoderma , and Aspergillus demonstrated their pollutant degradation capability, exclusive of pollutant consumption as an energy resource ( Nzila, 2013 ).

Polychlorinated bis-phenyles (PCBs) are classified as persistent organic pollutants with high toxicity ( Lallas, 2001 ; Pathiraja et al., 2019 ). They have been linked to chronic effects in humans including immune system damage, decreased pulmonary function, bronchitis, and interference with hormones leading to cancer ( Schecter et al., 2006 ). Microbial degradation of polychlorinated bis-phenyles (PCBs) is a promising remediation technology involving two major pathways: aerobic degradation and anaerobic dehalogination ( Abraham et al., 2002 ; Pathiraja et al., 2019 ). Bacterial strains Pseudomonas, Rhosocossus, Comamonas, Burkholderia , and Bacillus have been characterized for the oxidative degradation of PCBs through ring cleavage resulting into a common by product of chlorbenzoic acid ( Anyasi and Atagana, 2011 ; Jing et al., 2018 ).

Polycyclic aromatic hydrocarbons (PAHs) are potent environmental contaminants and xenobiotics that are widely distributed in the environment due to the incomplete combustion of organic matter. PAHs have moderate to high acute toxicity to aquatic life and birds ( Abdel-Shafy and Mansour, 2016 ; Pandey et al., 2017 ). Some PAHs such as Anthracene, benzo(a)pyrene, phenanthrene, and naphthalene are well-known to produce harmful biological effects such as genotoxicity, mutagenicity, and carcinogenicity and therefore pose a serious threat to the human health ( Kim et al., 2013 ; Lin et al., 2020 ). Microorganisms belonging to Sphingomonas, Sphingobium , and Novosphingobium have been found as efficient degrader of PAHs ( Lee et al., 2016b ; Fida et al., 2017 ; Auti et al., 2019 ). Rhodococcus, Cunninghamella, Pleurotus ostreatus, Oscillatoria, Agmenellum quadriplicatum, Brevibacterium , and Nocardiodes have been widely shown to metabolize particularly naphthalene and phenanthrene ( Ghosal et al., 2016 ; Siles and Margesin, 2018 ). Ortega-Gonzalez et al. (2015) demonstrated that Amycolaptosis sp. Poz14 degraded 100% of naphthalene and 37.87% of anthracene within 45 days. A PAH-degrading marine bacterium Cycloclasticus sp. has been isolated from sea sediments capable to breakdown xenobiotic naphthalene, pyrene, phenanthrene, and other aromatic hydrocarbons into their supplementary products through enzymatic pathways ( Wang W. et al., 2018 ). A simplified catabolic pathway of naphthalene is presented in Figure 2 .

Phthalates or esters of phthalic acids are synthetic xenobiotic chemicals, which are extensively used as plasticizers added to polyvinyl chloride to improve its flexibility and hardness ( Crinnion, 2010 ; Singh and Li, 2011 ; Przybylinska and Wyszkowski, 2016 ). Phthalates are readily released into the environment and create a risk of exposure for humans and other living organisms due their endocrine disrupting behavior ( Przybylinska and Wyszkowski, 2016 ). They cause infertility, reproductive and developmental toxicity in humans and animals ( Singh and Li, 2011 ; Przybylinska and Wyszkowski, 2016 ). Aerobic and anaerobic microbial degradation of xenobiotic phthalic acid, and isophthalaic acid considered as the most effective means of their removal from the environment ( Junghare et al., 2019 ; Boll et al., 2020 ). Di-2(ethyehxyl) phthalate (DEHP) is the most common member of phthalates, which are extensively used as plasticizer in plastics and disposable medical materials ( Singh and Li, 2011 ). DEHP is best known as an endocrine disrupter and can produce neural, heptotoxic, cardiotoxic, and carcinogenic effects on humans and animals ( Rowdhwal and Chen, 2018 ). Arthrobacter, Pseudomonas, Gordonia, Providencia, Acinetobacter, Microbacterium , and Rhodococuus have been identified as efficient DEHP degrading bacteria ( Nahurira et al., 2017 ; Yang T. et al., 2018 ).

In addition, the microbial consortium gained greater attention in bioremediation rather than pure microbial monocultures. The consortia cultures are better equipped in terms of metabolic and pollutant removal capability owing to their constant revelation of contaminant and promising mutual relationship with other available strains ( Patowary et al., 2016 ). Interestingly, microbial consortia can alleviate the metabolic limitations of single microbial culture and enhance biodegradation process by their miscellaneous assemblage of bacterial populations employed with extensive degradation potential ( Zafra et al., 2016 ; Li et al., 2020 ).

Recent Advanced Technologies Employed in Bioremediation for Identification and Characterization of Microorganisms and Microbial Communities

There are several revolutionary advanced molecular practices, including genomics, metagenomics, proteomics, transcriptomics, and metabolomics, which deliver deeper insights into microbial activities with respect to their genes, proteins, mRNA expression levels, enzymes and metabolic pathways with changing environments ( Figure 1 ). The integrated approach of these multiple technologies in the field of bioremediation is termed as the “omics approach,” used for the undeviating characterization of biological macromolecules, and their specific genetic and molecular structures and function mechanisms in a set of microorganisms/microbial communities ( Desai et al., 2009 ; Yang, 2013 ; Godheja et al., 2014 ; Franzosa et al., 2015 ; Chandran et al., 2020 ). The application of omics technologies provides comprehensive insights into microbial populations, their mechanisms of interaction with pollutants, metabolic activities, and genetic-regulation and molecular-biology aspects ( Akinsanya et al., 2015 ; Kaul et al., 2016 ; Misra et al., 2018 ; Marco and Abram, 2019 ; Huang et al., 2021 ). Moreover, these approaches can broaden our knowledge of the so-called “viable but non-culturable (VBNC)” bacteria and their potentially novel pathways for degrading environmental pollutants ( Oliver, 2010 ; Bodor et al., 2020 ). It is believed that these uncultured bacteria may play an important role in the biodegradation of environmental pollutant. However, little is known about the VBNC bacteria as these bacteria cannot be cultivated on conventional media and are very different from cells ( Su et al., 2013 ). VBNC cells exhibit metabolic and respiratory activities and may perform transcription and gene expression, which allows them to recover culturability ( Oliver et al., 2005 ; Zhao X. et al., 2017 ). The VBNC bacteria could be resuscitated in favorable conditions by an autoinducer (AI-2) ( Bari et al., 2013 ) or resuscitated promoting factor (Rpf) ( Li et al., 2015 ). The VBNC bacterial cells are detected on the basis of their viability. Several culture-independent molecular-based methods such as denaturing and temperature gradient gel electrophoresis (DGGE/TGGE), fluorescent in situ hybridization (FISH), terminal restriction fragment length polymorphism (T-RFLP), fatty acid methyl ester (FAME), and next-generation sequencing (NGS) technology are used for obtaining important information about the structural composition and genetic diversity of unculturable microorganisms ( Zhao X. et al., 2017 ; Bodor et al., 2020 ). Selective gene amplification is an emerging approach to detect viable cells. Zhong et al. (2016) developed a real-time fluorescence LAMP technique combined with PMA (propidium monoazide), a high-affinity photolysis DNA nucleic acid dye applied for the detection of VBNC V. parahaemolyticus . Thus, the combined use of these advanced molecular technologies with bioinformatic approaches increases understanding and brings in a new era of unrevealed soil microbial communities, as well as their associated mechanisms of biodegradation for their future applications in bioremediation ( Figure 3 ; Mocalli and Benedetti, 2010 ; Kumar et al., 2016 ; Dangi et al., 2018 ; Pandey et al., 2019 ; Pinu et al., 2019 ).

Figure 3 . Graphical presentation of integrated approach of advanced technologies in biodegradation of xenobiotic compounds.

Genomics and Metagenomics

Genomics and metagenomics are powerful tools for analyzing microbial communities at the genomic level from various contaminated environments. This technology gives a new array to environmental microbiologists for understanding unculturable microbiota with a genetic variability of microbial communities ( Devarapalli and Kumavnath, 2015 ; Zhu et al., 2018 ; Awasthi et al., 2020 ). It gives more details about the particular degradation potential of microbial communities, as it directly entails the whole-genome sequence from environmental samples ( Table 1 ). Metagenomic studies unblock traditional ways of uncultured microorganisms and explore their genetic advantage in the process of bioremediation ( Rahimi et al., 2018 ; Nascimento et al., 2020 ). Complete genome-sequence data of some important microbial strains, including Pseudomonas aeruginosa KT2440, Shewanella oneidensis MR-1, Deinococcus indicus R1, and Dehalococcoides mccartyi WBC-2 have already been given, which is pertinent to successful bioremediation ( http://www.tigr.org ). The new genes can tell too much about the degradation capability and substrate specificity.

Table 1 . Microorganisms and microbial communities using genomic and metagenomic approaches in biodegradation.

Current metagenomic practices allowed for identifying the whole-genome structure of microorganisms and specifying particular genes that are attributed to encode degradative enzymes for the mineralization of xenobiotics ( Zafra et al., 2016 ; Zhu et al., 2020 ). Thus, metagenomics clearly highlights the crucial role of novel genes in connecting the entire microbial population with functional diversity and structural identity. Metagenomics involves the manufacturing of metagenomic libraries that include (I) production of the proper size of DNA fragments, and ligation of these fragments into a suitable cloning vector; (II) further recombinant vectors introduced into an appropriate bacterium cloning host; (III) clones that harbor specific characters, functions, or sequences were screened for libraries ( Figure 3 ). Moreover, the screening of metagenomic libraries can be performed by two processes, i.e., sequence-driven analysis using high-throughput sequencing, and functional analysis using phenotypic expressions ( Handelsman, 2004 ). However, recent sequence-based metagenome analyses (such as SOLiD system of Applied Biosystems, Roche 454 sequencing) are performed without the construction of cloned libraries ( Kumar et al., 2020 ).

Function-driven metagenomics is a potent method for studying the functional aspect of genes. It is widely used for discovering novel genes with desired functions or exploring the sequence diversity of protein families ( Taupp et al., 2011 ; Lam et al., 2015 ). A function-driven analysis involves the construction and screening of metagenomic libraries to identify novel enzymes ( Chakraborthy and Das, 2016 ; Kumar et al., 2020 ). Using functional metagenomics, many novel antibiotic-resistant genes were identified from environmental sources ( Ngara and Zhang, 2018 ). The majority of metagenome-derived hydrolytic enzymes, mainly esterases and glycoside hydrolases, have been characterized biochemically and mainly originated from functional metagenomics ( Steele et al., 2009 ; Taupp et al., 2011 ). A novel functional screening method, a metagenome extract thin layer chromatography (META) system, was developed by Rabausch et al. (2013) for the rapid detection of glycosyltransferase (GT) and other flavonoid-modifying enzymes from metagenomic clone libraries. It involves the screening of 38,000 clones from two different metagenomic libraries and allowed for the identification of two novel UDP glycosyltransferase (UGT) genes. Bouhajja et al. (2017) utilized function-based screening of metagenomic libraries to explore the diversity of genes and microorganisms involved in the monooxygenase-mediated toluene degradation in a hydrocarbon-polluted sediment sample.

Metagenomic approaches offer broad and reliable microbial identification on the species and strain levels, but they are much costlier methods, and the most challenging part is data investigation, which requires all short DNA sequences to pair together to assemble the final genome structure ( Bragg and Tyson, 2014 ). The involvement of indigenous soil microorganisms in the degradation of PAHs was undertaken by Zafra et al. (2016) through a metagenomic approach. This study demonstrated the biodegradation efficiency of microbial consortia with their degradative enzymes and metabolites generated during the remediation process. The microbial-community dynamics of refined- and crude-petroleum-contaminated soil by next-generation sequencing (NGS), and their capability to degrade hydrocarbons and plant-growth-promotion potential through in-silico analysis was investigated by Auti et al. (2019) . In this study, 16S rRNA amplicon sequencing on the Illumina MiSeq platform and PICRUSt revealed that both types of soil contained microbial communities with excellent metabolic potential for petroleum hydrocarbon (PHC) degradation. Using KEGG orthology, the abundance of functional genes involved in hydrocarbon degradation showed the presence of 61 enzyme-encoding genes, such as alkane monooxygenase, alcohol dehydrogenase, and aldehyde dehydrogenase ( Auti et al., 2019 ). 16S rDNA or 16S rRNA gene sequencing has led to evolutionary insights into the phylogenetic and taxonomic identification of microorganisms. The 16S rRNA gene consists of several highly conserved regions interleaved with variable regions in all microorganisms and thus is highly suited as a target gene for sequencing DNA ( Fuks et al., 2018 ; Gursoy and Can, 2019 ). The bacterial 16S rRNA gene generally contains nine “hypervaiable regions” that demonstrate the considerable sequence diversity of bacterial species and can be used for species identification. The 16 S rRNA gene sequence similarity between two strains provides a simple yet robust criterion for the identification of newly isolated strains, whereas phylogenetic analyses can be used to elucidate the overall evolutionary relationship between related taxa ( Johnson et al., 2019 ). Thus, 16S rRNA gene sequencing analysis is a highly recommended cost-effective technique for the phylogenetic resolution and taxonomic profiling of microbial communities ( Auti et al., 2019 ).

The NGS approach has completely changed microbial-community analysis, as it provides comparative details in terms of temporal and spatial data ( Hidalgo et al., 2020 ). There are several NGS technologies, including Illumina, Ion Torrent, SOLiD, and 454 ( Caporaso et al., 2012 ; Liu et al., 2012 ; Knief, 2014 ; Salipante et al., 2014 ; Machado et al., 2019 ). These are high-throughput sequencing techniques of ribosomal genes that quantify community structures and functions at a higher resolution, e.g., 16S rRNA in prokaryotes, and 5S or 18S rRNA genes, or the internal-transcribe-spacer (ITS) region in eukaryotes ( Luo et al., 2012 ). The effectiveness of such NGS technologies in analyzing microbial communities from diverse environments was elucidated, validated, and documented in many studies ( Brown et al., 2013 ; Shokralla et al., 2014 ; Zhou et al., 2015 ; Niu et al., 2016 ; Scholer et al., 2017 ). In addition, PacBio (Pacific Biosciences) and Oxford Nanopore are highly advanced, reliable, and accurate third-generation sequencing platforms applied to microbial community analysis ( Lu et al., 2016 ; Chandran et al., 2020 ). Oxford Nanopore Technologies has launched a portable MinION USB nanopore that does not rely on DNA replication and has the advantage of reading full-length molecules in real time. PacBio RS II, the first commercialized genomic sequencer, developed by Pacific Biosciences, uses single-molecule, real-time (SMRT) technology and is able to sequence single DNA molecules in real time without PCR amplification ( Wagner et al., 2016 ; Nakano et al., 2017 ). The complete genome sequence of atrazine-degrading Arthrobacter sp. ZXY-2 ( Zhao X. et al., 2017 ) and organophosphate-degrading Sphingobium fuliginis ATCC 27552 ( Azam et al., 2019 ) was analyzed using the PacBio RSII sequencing platform to gain more insight into the genetic basis and unravel its degradation potential.

Jeffries et al. (2019) performed functional metagenomic studies in pesticide-contaminated soil to explore the degradation rates of organophosphorus xenobiotic compounds. Their study demonstrated that two distinct soil groups had different functional and taxonomic profiles, and predicted biodegradation potential in rapidly and slowly degrading soil clusters. Burkholderia, Acidomicrobium, Koribacter , and Bradyrhizobium were most abundantly present in rapidly degrading clusters, whereas Singulisphaera, Solibacter , and Desulfomonile were in slowly degrading clusters. The degradation assays of organophosphorus also suggested that slow-degradation clusters had significantly higher abundances of virulence genes and metabolic pathways for fatty acids and carbohydrates. In contrast, rapid-degradation clusters contain more abundant genes related to the transposable elements, membrane transport, and nutrient cycling of nitrogen and phosphorus enzymes potentially involved in phosphorus metabolism. Moreover, rapid-degradation soils also showed a higher abundance of genes encoding phosphodiesterase enzymes, which cleave phosphodiester bonds present in organophosphorus and play a major role in pesticide degradation. Overall, this study gives an overall framework of metagenomic approaches to predict the microbial degradation of xenobiotic organophosphorus compounds.

Metagenomic analysis of a complex community of lindane-contaminated pond sediment was conducted by Negi and Lal (2017) through comparative genomics. The results of this study revealed genomic variation present in pond sediment with degradative enzymes (hydrolases, isomerases, lyases, and oxidoreductases) involved in the biodegradation of hexachlorocyclohexane and chlorobenzene (ko00361), and other xenobiotic compounds. Cellulomonas, Micrococcus, Nocardioides, Kribbella, Isoptericola, Clavibacter, Gutenbergia, Streptomyces, Sanguibacter , and Kineococcus were found to be the most dominating genera present in the aromatic-hydrocarbon-contaminated pond sediment. Genes involved in lindane metabolization, enriched with sequences for linA and linB , were also found in the pond-sediment metagenome.

Whole-metagenome sequencing of e-waste-contaminated microbial populations was conducted by Salam and Verma (2019) , who demonstrated that the functional diversity and structural composition of microorganisms significantly changes due to the detrimental impact of e-waste. Denaturing gel gradient electrophoresis (DGGE) community-profiling results revealed that bacterial groups such as Proteobacteria, Firmicutes, Bacteroidetes , and Chloroflexi were decreased. Zhu et al. (2020) explored microbial assemblage and functional genes potentially involved in upstream and downstream phthalate degradation in soil via a metagenomic approach. Results indicated that bacterial taxon Actinobacteria ( Pimelobacter, Nocardioides, Gordonia, Nocardia, Rhodococcus , and Mycobacterium) was a major degrader under aerobic conditions, and bacterial taxa Proteobacteria ( Ramlibacter and Burkholderia ), Acidobacteria, and Bacteroidetes were involved under anaerobic conditions. The members of Geobacteraceae and Peptococcaceae microbiota present in the jet-fuel-contaminated site could be exploited for their remarkable metabolic potential for the mitigation of toluene and benzene, as exposed by metagenomic analysis ( Hidalgo et al., 2020 ).

Transcriptomics

Transcriptomics is a remarkable tool that addresses the division of genes transcribed in any organism known as the transcriptome. It provides functional insight links involving the genome, proteome, and cellular phenotype by studying their mRNA transcriptional profiles, directly extracted from individual microbes or microbial communities ( Singh and Nagaraj, 2006 ; McGrath et al., 2008 ; Bashiardes et al., 2016 ). Significant changes were seen in gene-expression level and their regulation in microbial communities under stressful environments for their survival. Thus, transcriptomics and metatranscriptomics provide deep analysis of a genome wide range of differently expressed genes, either of the individual cell or the entire microbial community at a specific time ( Table 2 ; Li et al., 2014 ; He et al., 2015 ; Shakya et al., 2019 ). RNA seq and DNA microarrays are significantly powerful technologies to determine the mRNA expression level of every gene ( Diaz, 2004 ). GeoChip uses key enzymes or genes to spot various microbe-mediated mechanisms for biogeochemical cycles, resistance mechanism for heavy metals, and degradation pathways of xenobiotics ( He et al., 2010 ; Xiong et al., 2010 ; Xie et al., 2011 ). Similarly, DNA- and RNA-SIP (Stable Isotope Probing) technologies are also valuable to uncover the microbial taxa and catabolic genes that are important for the bioremediation of polluted environments ( Lueders, 2015 ).

Table 2 . Microorganisms and microbial communities using transcriptomic and metatranscriptomic approaches in biodegradation.

Dual RNA-seq transcriptional profile is a better approach to understand the basic nature and mechanism of differently expressed genes in the host and symbiotic microbes at a time ( Kaul et al., 2016 ). RNA seq allows for the detection of more differently expressed genes than a microarray alone does. Thus, recent advancements and developments in microarrays, RNA seq technology, transcriptomics, and metatranscriptomics revealed unexpected microbial diversity in aquatic and terrestrial environments with their synergistic relationships with humans, animals, plants, and other microorganisms ( Perez-Losada et al., 2015 ; White et al., 2016 ; Moniruzzaman et al., 2017 ; Berg et al., 2018 ; Crump et al., 2018 ).

RNA seq technology is considered more efficient than traditional microarray platforms in gene expression profiling as it provides a wider quantitative range of expression level changes compared to microarrays ( Roh et al., 2010 ; Shakya et al., 2019 ). The microarray technique requires a lot of effort and money to prepare custom-made microarrays. Furthermore, the target genes to be analyzed are limited in number and cannot cover the whole set of genes in the community. In contrast, a number of kits are now commercially available to carry out RNA-seq analysis, whereby a whole set of genes in the community can be quantitatively analyzed. Therefore, many studies are now performed by RNA-seq technology.

Lima-Morales et al. (2016) investigated the microbial organization and catabolic gene diversity of three types of contaminated soil under continuous long-term pollutant stress with benzene and benzene/toluene/ethylene/xylene (BTEX) to identify shifts in community structure and the prevalence of key genes for catabolic pathways. Moreover, de novo transcriptome synthesis gives new insights into and reveals basic information about non-model species without a genome reference. Hydrocarbon-degrading bacterium Achromobacter sp. was isolated from seawater, and indicated that the upregulation of enzymes such as dehydrogenases and monooxygenases, and novel genes associated with fatty acid metabolism is responsible for its enormous capability for hydrocarbon degradation and survival ( Hong et al., 2016 ).

Metatranscriptomic analysis of the wheat rhizosphere identified dominant bacterial communities of diverse taxonomic phyla, including Acidobacteria, Cyanobacteria, Bacteroidetes, Steptophyta, Ascomycota, and Firmicutes, having functional roles in the degradation of various xenobiotic pollutants ( Singh D. P. et al., 2018 ). Multiple enzymes such as isomerases, oxygenases, decarboxylases, reductases, kinases, and inner membrane translocators were identified that were associated with 21 different pathways for benzoates, aromatic amines, phenols, bisphenols, and other xenobiotics ( Singh et al., 2016 ). An et al. (2020) elucidated the study of the transcriptome for the characterization of hexaconazole degrading strain Sphingobacterium multivorum , obtained from activated sludge. This strain was capable of degrading 85.6% hexaconazole in just 6 days and of generating three different metabolites, M1, M2, and M3, recognized as (2-(2,4-dichlorophenyl)-1-(1H-1,2,4-triazol-1-yl)hexane-2,5diol), (2-(2,4-dichlorophenyl) hexane-1,2-diol), and (1H-1,2,4-triazol), respectively. The results of transcriptome sequencing revealed the presence of 864 differential genes in which dehydrogenases, aldehydes, monooxygenases, and RND and AC transporters were upregulated. The M1 metabolite was perhaps generated due to the participation of monooxygenases.

Genomic and transcriptomic approaches were used by Sengupta et al. (2019) for gaining mechanistic insight into 4-nitrophenol (4-NP) degrading bacterium Rhodococcus sp. strain BUPNP1. This study identified a catabolic 43 gene cluster named nph that harbors not only mandatory genes for the breakdown of 4-NP into acetyl co-A and succinate by nitrocatechol, but also for other diverse aromatic compounds. An integrated approach of metagenomics and metatranscriptomics revealed the metabolic capabilities and synergistic relationship between Sphingomonas spp., Pusillimonas sp., and Pseudomonas sp. in the degradation of bisphenol A (BPA) ( Yu K. et al., 2019 ).

Metatranscriptomic analysis of this interaction model demonstrated genes encoding the transcription of 1,2-bis(4-hydroxyphenyl)-2-propanol (1-BP) into 4-hydroxybenzaldehyde (4-HBD) and 4-hydroxy-acetophenone (4-HAP) via 3,4-dihydroxybenzoate (3,4-DHB) and 3-oxoadipate (3-ODP), respectively, to the tricarboxylic acid cycle (TCA)cycle. Marcelino et al. (2019) identified fungal species and subspecies in a mixed community by using metatranscriptomics. This study suggested a strain-level discrepancy between the Cryptococcus fungal species and their in-situ mock communities. Thus, transcriptomic analysis provides a large amount of gene information about the potential function of microbial communities in adaptation and survival in extreme environments ( Singh D. P. et al., 2018 ; Mao et al., 2019 ; Marcelino et al., 2019 ).

Proteins are crucial effectors of biological responses, stabler than RNAs in living organisms, and possibly confer an integral view of biological function expressed in situ ; the term proteomics is put forward to study the entire set of proteins expressed in an organism ( Ram et al., 2005 ; Singh, 2006 ; Hettich et al., 2013 ). Thus, proteomics has emerged as an interesting and fruitful technology to study protein expression (post-translational modifications, protein turnover, proteolysis, and changes in the corresponding gene expression) of the microbial world ( Keller and Hettich, 2009 ; Aslam et al., 2017 ). Proteomics is a promising aspect of omic technologies in the field of microbiology, allowing for investigating the complete protein profile obtained in a straight line from a composite microbial population in a contaminated environment ( Williams et al., 2013 ; Arsene-Ploetze et al., 2015 ; Wang et al., 2016 ). However, metaproteomics is used to decipher crucial information regarding the protein profiling of two diverse ecological units ( Arsene-Ploetze et al., 2015 ). Proteomics has been used to identify microbial communities/microorganisms in various ecosystems including soil and sediment, activated sludge, marine and groundwater sediment, acid mine biofilms, and wastewater plants, as illustrated in Table 3 ( Williams et al., 2013 ; Colatriano et al., 2015 ; Grob et al., 2015 ; Bastida et al., 2016 ; Jagadeesh et al., 2017 ). These studies revealed secret information related to protein synthesis, gene-expression stability, mRNA turnover, and protein–protein interaction networks in microbial communities in stress environments ( Aslam et al., 2017 ).

Table 3 . Microorganisms or microbial communities using proteomic and metaproteomic approaches in biodegradation.

The inclusion of a proteomic approach helps to identify related enzymes and their metabolic pathways in the bioremediation of xenobiotics from various contaminated sites ( Kim et al., 2004 ; Liu et al., 2017 ; Wei et al., 2017 ). Basically, there are four primary steps that involve proteomic analysis: (1) preparation of a biological sample; (2) extraction and separation of proteins by using two-dimensional gel electrophoresis (2D-GE); (3) protein gel images are examined by means of image-analysis software such as ImageMaster 2D or PDQuest; and (4) proteins are identified by using mass spectroscopy (MS)/MALDI-TOF/MS or LC-MS ( Yates et al., 2009 ; Chakka et al., 2015 ; Velmurgan et al., 2017 ).

A combined protein profile of 20 PAH-induced proteins was studied by proteomics in Mycobacterium vanbaalenii PYR-1 grown in a PAH-supplemented culture medium ( Kim et al., 2004 ). PAH exposure of five different compounds, i.e., pyrene, pyerene-4,5-quinone, phenanthrene, anthracene, and fluoranthere causes variation in protein composition, showing upregulation of multiple proteins for PAH treatment compared to an uninduced control sample. Several PAH-induced proteins were identified by LC-MS, including a catalase-peroxidase, a putative monooxygenase, a dioxygenase, a small subunit of naphthalene-inducible dioxygenase, and aldehyde dehydrogenase. The metaproteomic approach was employed by Bastida et al. (2016) to illustrate changes in metabolic activities during compost-treated bioremediation with the help of differential protein expressions in hydrocarbon-polluted soil. Metaproteomic analysis indicated that Sphingomonadales and uncultured bacteria are responsible for the degradation of hydrocarbons in compost-treated soil due to the higher expression of catabolic enzymes such as 2-hydroxymuconic semialdehyde, cis -dihydrodiol dehydrogenase, and catechol 2,3-dioxygenase, dioxygenases involved in the first oxygenation step of aromatic rings. Moreover, biphenyl-2,3-diol 1,2-dioxygenase, estradiol dioxygenase, and naphthalene 1,2-dioxygenase were identified in compost-treated samples. By using metaproteomics, this study explored the functional and phylogenetic relationship of contaminated soil, and the microbial key players involved in compost-assisted bioremediation.

Another study, undertaken by Vandera et al. (2015) demonstrated the comparative proteomic analysis of Arthrobacter phenanivorans Sphe3 on aromatic compounds phenanthrene and phthalates. The proteomic approach confirmed the involvement of several proteins in aromatic-substrate degradation by identifying those mediating the initial ring hydroxylation and ring cleavage of phenanthrene to phthalate. This study also revealed the presence of both the ortho- and the meta- cleavage pathway for the degradation of these aromatic compounds, and it also identified all proteins that take part in these pathways and are highly upregulated upon phthalate growth in comparison to phenanthrene growth.

Proteomic analysis of pyrene-degrading bacterium Achromobacter xylosoxidans PY4 was performed by Nzila et al. (2018) , who identified a total of 1,094 proteins. Among these, 95 proteins were detected in glucose supplementation, and 612 proteins were detected in the presence of pyrene. Furthermore, 25 upregulated proteins were found to be involved in stress response and the progression of genetic information. Two upregulated proteins, 4-hydroxyphenylpyruvate dioxygenase and homogentisate 1,2-dioxygenase, are implicated in the lower degradation pathway of pyrene. Enzyme 4-hydroxyphenylpyruvate dioxygenase may catalyze the conversion of 2-hydroxybenzalpyruvic acid (metabolite of pyrene) to homogentisate. Homogentisate 1,2-dioxygenase is involved in the incorporation of 2 oxygen atoms to produce 4-maleyacetoacetate, which is an intermediate in several metabolic pathways.

Lee et al. (2016b) performed proteomic analysis of PAH-degrading bacterial isolate Sphingobium chungbukense DJ77. This strain exhibited outstanding degradation capability for various aromatic compounds. This study demonstrated the degradation of three xenobiotics compounds, i.e., phenanthrene, naphthalene, and biphenyls (PNB), and their associated proteins was analyzed by 2-DE and MALDI-TOF/MS analysis. During PNB biodegradation by bacterial cells, an alteration was observed in protein expression to cope with the stress condition. Comparative analysis of 2-DE results revealed that the intensity of 10 protein spots changes identically upon exposure to these xenobiotics in strain DJ77 ( Lee et al., 2016b ). Among these ten, five upregulated proteins with multiple functionalities were identified as putative dihydrodiol dehydrogenase (BphB), which catalyzes the NAD + -dependent oxidation of trans- dihydrodiols; 2,3-dihydrobisphenyl 1,2-dioxygenase (PhnQ), which cleaves the aromatic ring; and 2-hydroxy-6-oxo-6-phenylhexa-2,4-dienoate hydrolase (BphD), which degrades biphenyls and polychlorinated biphenyls. A part of the initial diverse catabolism of PNB by BphB, PhnQ, and BphD converged into the same catechol degradation branch. Now, catechol is first transformed into a ring-cleaved product, i.e., 2-hydroxymuconic semialdehyde by catechol 2,3-dioxygenase (PhnE). Moreover, it is assumed that this ring-cleaved product (2-hydroxymuconic semialdehyde) would be further degraded by 2-hydroxymuconic semialdehyde hydrolase (PhnD), and acetaldehyde dehydrogenase (PhnI) into a compound that can enter into the TCA cycle. Hence, these upregulated proteins, dehydrogenase, dioxygenase, and hydrolase, are involved in the catabolic degradation pathway of xenobiotics. The detection of intermediates from 2,3-dihydroxy-biphenyl degradation to pyruvate and acetyl-CoA by LC/MS analysis showed that ring-cleavage products entered the TCA cycle and were mineralized in strain DJ77. It was also suggested that strain DJ77 could completely degrade a wide range of PAHs via multiple catabolic pathways ( Lee et al., 2016b ).

The biodegradation mechanism of tetrabromobis-phenol A (TBBPA) was investigated in Phanerochaete chrysosporium by using a proteomic approach. iTRAQ quantitative analysis identified a total of 2,724 proteins in three biological samples. Compared to control TBBPA, stress caused 148 differentially expressed proteins in P. chrysosporium , among which 90 proteins were upregulated and 58 proteins were downregulated. The upregulation of cytochrome p450 monooxygenase, glutathione- S -transferase, O -methyltransferase, and other oxidoreductases is responsible for the biotransformation of TBBPA via oxidative hydroxylation and reductive debromination ( Chen et al., 2019 ).

A biodegradation study of endocrine-disrupting compound 4- n -nonylphenol (4- n - NP ) by filamentous fungus Metarhizium robertsii was investigated by Szewczyk et al. (2014) with proteomic analysis. This suggested that the main biodegradation mechanism involves the consecutive oxidation of the alkyl chain and benzene, which consequently results in the complete decomposition of the 4- n -NP compound. Proteomic profiling explored the involvement of nitro-reductase-like proteins related to the oxidation–reduction and ROS defense systems, and mainly engaged group of proteins in the removal of 4- n -NP. Proteomic data obtained in this study could not clearly explain the mechanism of 4- n -NP biodegradation in the tested fungal strain, but allowed for the formulation of hypotheses that the over-expressed enzymes in the cultures with 4- n -NP could play a role in xenobiotic removal and the biodegradation process.

Bioremediation of decabromodiphenyl ether (BDE-209) was explored in Microbacterium Y2 in a polluted water-sediment system through proteomics ( Yu Y. et al., 2019 ). Proteomic analysis showed that the overexpression of haloacid dehalogenases, glutathione s-transferase, and ATP-binding cassette (ABC) transporter might occupy important roles in BDE-209 biotransformation. Moreover, heat-shock proteins (HSPs), ribonuclease E, oligoribonuclease (Orn), and ribosomal proteins were activated to counter the BDE-209 toxicity. Thus, it is suggested that these proteins are implicated in microbial degradation, antioxidative stress, and glycolysis ( Yu Y. et al., 2019 ).

Metabolomics

Metabolomics is a well-established recent scientific technology, attributed toward the study of naturally occurring low-molecular weight (<1,000 Da) organic metabolites (organic acids; pyruvate, lactate, malate, formate, fatty acid-like acetate, etc.) inside a tissue, cell, or biofluid ( Johnson et al., 2011 ; Malla et al., 2018 ; Withers et al., 2020 ). Metabolomics explores the relationships between organisms and the environment, such as organismal responses to abiotic stressors, including both natural factors such as temperature, and anthropogenic factors such as pollution, to investigate biotic–biotic interactions such as infections, and metabolic responses ( Lindon et al., 2006 ; Griffiths, 2007 ; Mallick et al., 2019 ).

The combined use of metabolomics with these applications details the authentic collection of chemical outputs and inputs, which arbitrate the exchange of resources between the community and its host ( Table 4 ; Theriot et al., 2014 ; Wang Y. F. et al., 2018 ). Metabolomic studies in environmental sciences have been directed toward understanding changes in the concentration of metabolites associated with exposing model organisms to toxic compounds, such as xenobiotics ( Parisi et al., 2009 ; Seo et al., 2009 ).

Table 4 . Microorganisms or microbial communities using metabolomic approaches in biodegradation.

Metabolomics approach was utilized to investigate the degradation mechanism of carbaryl and other N -methyl carbamates pesticides in Burkholderia sp. strain C3 ( Seo et al., 2013 ). Metabolomes are dynamic and responsive to nutrient and environmental changes. The results of this study showed the metabolic adaptation of Burkholderia sp. C3 to carbaryl in comparison with glucose and nutrient broth. The metabolic changes were notably associated with the biosynthesis and metabolism of amino acids, sugars, PAH lipids, and cofactors. Differential metabolome analysis in response to different substrates identified 196 polar metabolites, 10 fatty acids, and 1 macromolecule (PHA) in this strain, and confirmed up-production metabolites in the pentose phosphate pathway, cysteine metabolism, amino acids, and disaccharides ( Seo et al., 2013 ). Thus, this metabolomic study could provide detailed insights into bacterial adaptation to different metabolic networks, and the metabolism of toxic pesticides and chemicals.

Environmental pollutants cause alterations in microbial communities, which consequently changes biochemical and metabolic functions in soil microorganisms. Microbial degradation of cyfluthrin by Photobacterium ganghwense was investigated via a comparative metabolic approach ( Wang et al., 2019 ). Metabolomics explored the biotransformation pathway of cyfluthrin with the identification of 156 metabolites during the biodegradation process. Recently, on the basis of interactions of indigenous soil microorganisms to PAH-contaminated soil, Li et al. (2018) elucidated that the majority of microbial metabolic functions were adversely affected to cope with PAH pollution. This study includes the combined study of enzyme activity and sequencing analysis with metabolomics, which further exposed the specific inhibition of soil metabolic pathways associated with carbohydrates, amino acids, and fatty acids due to microbial-community shifting under PAH stress.

Soil metabolomics is an effective approach to reveal the complex molecular networks and metabolic pathways operating in the soil microbial community. This approach can also be used to find biomarkers of soil contamination ( Jones et al., 2014 ). High-throughput sequencing and soil metabolomics investigated the differential structures and functions of soil bacterial communities in the pepper rhizosphere and bulk soil under plastic greenhouse vegetable cultivation (PGVC) ( Song et al., 2020 ). A total of 245 metabolites were identified, among which 11 differential metabolites were detected between rhizosphere and bulk soil, including organic acids and sugars that were positively and negatively correlated with the relative abundances of the differential bacteria. A starch and sucrose metabolic pathway was the most differentially expressed pathway in rhizospheric soil. The main functional genes participating in this pathway were predicted to be down regulated in rhizosphere soil. Sugar and organic acids as the main plant-root exudates in the rhizosphere, and they are also the main drivers of the shift in soil microbial community in the rhizosphere. These plant-root exudates act as an energy source to soil microbes, thus benefiting their growth ( Kuzyakov and Blagodatskaya, 2015 ; Shi et al., 2015 ). Linear discriminant analysis (LDA) effect size (LEfSe) analysis showed that bacterial phyla of Proteobacteria and Bacteroidetes were significantly higher in rhizosphere soil, benefitting plant growth. Thus, the relationship between soil metabolites and microbial communities guides the regulation of plant rhizoprocesses through soil amendments to increase plant growth.

Durand et al. (2010) conducted metabolic analysis of Bacillus sp. to characterize the metabolic pathway for the biodegradation of mesotrione, a herbicide. Analysis was carried out by using LC-NMR and LC-MS, and the result of these instrumental analyses was the identification of six metabolites, of which the structures of four metabolites were suggested. Szewczyk et al. (2017) performed metabolic analysis of fungal strain Metarhizium brunneum ARSEF 2017 to predict a biodegradation-pathway metabolic background for the removal of ametryn, an s -triazene herbicide. Qualitative LC-MS/MS metabolomic analysis of ametryn biodegradation resulted in the generation of four metabolites, i.e., 2-hydroxy atrazine, ethyl hydroxylated ametryn, S -demethylated ametryn, and diethyl ametryn.

Wright et al. (2020) evaluated the metabolomic characterization of two potent marine bacterial isolates, Mycobacterium sp. DBP42 and Halomonas sp. ATBC28, capable of the degradation of phthalate and plasticizers such as ATBC, DBP, and DEHP. That study presented the molecular analysis of metabolites generated during biodegradation. A metabolomic study confirmed that DBP and ATBC were degraded through the sequential removal of ester side chains, and generated monobutyl phthalate and phthalate in the case of DBP degradation, and citrate in the case of ATBC degradation in Mycobacterium sp. However, DEHP degradation did not follow the same pathway as that observed for DBP and ATBC. It was suggested that DEHP degradation is initiated through hydroxylation of the ester side chain by monooxygenase, and may occur via the β-oxidation of fatty acid side chains directly on the DEHP molecule. Moreover, in comparison with Mycobacterium sp., Halomonas sp. did not confirm any detectable degradation intermediates for the degradation of plasticizers and phthalate, but it harbored an array of enzymes suggested to be responsible for the degradation of other aromatic compounds. Therefore, metabolomic analyses demonstrated changes that occur in the composition of metabolites, aiding to fully understand the shifts mechanisms of metabolites during the microbial degradation or mineralization of environmental pollutants ( Lindon et al., 2006 ; Keum et al., 2008 ; d'Errico et al., 2020 ).

Bioinformatics

Bioinformatic technology developed a new array of computational technologies that uses both information technology and biological sciences. This modern technology seeks information from multiple high-throughput biological techniques, and keeps all biological data, helping to investigate and decide the relationship among organic molecules, including macromolecular sequences, biochemical and metabolic pathways, protein expressions, metabolites, and structures ( Fulekar and Geetha, 2008 ; Cooper et al., 2018 ; Dangi et al., 2018 ; Greene, 2018 ; Shekhar et al., 2020 ). Enormous amounts of data are generated from DNA, RNA, and protein sequences that need to be accurately executed; thus, bioinformatics has led to finding the best possible way to analyze such huge amounts of biological data via specific computational tools ( Aora and Bar, 2014 ; Bhatt et al., 2021 ). Therefore, bioinformatic-associated tools are very important to understand the bioremediation of toxic pollutants. Bioinformatics provides superior information regarding the cellular, molecular, and genetical bases of xenobiotic degradation and detoxification ( Kumar et al., 2016 ; Huang et al., 2020 ). There are a number of bioinformatic tools and applications that are available to use for biodegradation studies, as listed in Table 5 .

Table 5 . Bioinformatic databases and software tools used in biodegradation studies.

MetaRouter is one of such application that is freely open and a modular architecture to a variety of consumers from any place in a safe and secure manner, just by connecting to an Internet server ( Pazos et al., 2005 ). For the analysis of biodegradation studies, many bioinformatic resources are exclusively available. The University of Minnesota Biocatalysts/Biodegradation Database (UM-BBD) was introduced in 1995 and contains information regarding microbial catabolism and related biotransformation, biodegradation reactions, catabolic enzymes, and pathways for xenobiotics and other hazardous pollutants of various microorganisms. This database is connected to several other databases, such as BRENDA, ENZYME, ExPASy, and NCBI, to collect and store information related to gene structure and enzymes that take part in the biodegradation of environmental contaminants ( Ellis et al., 2006 ). Genomic sequences of microorganisms with competent and efficient degradation abilities could be easily investigated via another widely used database, the National Center for Biotechnology Information (NCBI). It gives a detailed and complete pipeline for annotations, and comprehensive analysis of more than 6,000 microbial genomes ( Brown et al., 2015 ). PRIDE ( Vizcaino et al., 2016 ) is the world's largest data repository of mass-spectroscopy-based proteomic data, and MetaboLights ( Kale et al., 2016 ) is a database for metabolomic experiments and derived information. The GenBank database is freely available in NCBI, and it provides most up-to-date and comprehensive DNA sequence information ( Benson et al., 2013 ). Recently, there have been a number of databases such as CAMERA, MG-RAST, and IMG/M that were developed and employed for the analysis and in-depth understanding of diverse microbial populations, metabolic reconstruction, taxonomic affiliations, and their inter- and intra-relationship networks. Another database, Bionemo, developed by the structural computational-biology group at the Spanish National Cancer Research Center, gives information related to specific genes and proteins that take part in biodegradation reactions and metabolic pathways ( Carbajosa et al., 2009 ). It provides insights into sequences, domains, protein structures, and regulatory elements, and transcription factors for their respective genes. Integrated bioinformatic approaches are employed for the metagenomic characterization of the soil microbial communities of different soil sites by using MetaPhlAn, KEGG, XLSX, and LEfSe bioinformatic databases to reveal the ancestral and functional characterization of diverse soil microbial populations ( Arora et al., 2009 ; Xu et al., 2014 ; Kumar et al., 2016 ). The degradation or detoxification of xenobiotic pollutants through microbial communities is a highly considered and proficient remediation technology, and there is no single resource accessible that provides all the information with reference to environmental contaminants, microorganisms, and their bioremediation potentialities. Thus, these databases coalescing the detailed information about the nature of pollutants, their metabolic pathways, bioremediation microorganisms, catabolic genes, enzymes, and protein-expression profiles would be a significant tool to open up a new vista and enlighten future research science in the field of bioremediation.

Conclusions

Microbial communities have great potential to mediate the successful biodegradation process of xenobiotic-contaminated soil/water environments. However, the greater part of mainstream microorganisms involved in bioremediation are still undefined because not all organisms in nature could be cultured under in vitro environments, but reside in viable-but-non-culturable (VBNC) environments. Thus, to explore the hidden knowledge of these VBNC organisms, recent advanced practices and sophisticated up-to-date technologies are highly desirable to understand the genetic and molecular biology of microorganisms. Newly developed molecular techniques offer promising approaches to address the in-depth characterization of microbial communities from molecule to gene. Recent omics technologies such as metagenomics, transcriptomics, and proteomics are helpful in obtaining information about nucleic acids, enzymes, catabolic genes, plasmids, and metabolic machineries and metabolites generated during the biodegradation process. However, the solitary employment of any individual omics technology is not sufficient to explore or illustrate secret information regarding microbial-remediation practices. Therefore, an interdisciplinary application of multiple omics studies highlights the perspectives of system biology for providing an integrative understanding between genes, proteins, and environmental factors responsible for the whole microbial-degradation process, and gives a new array of novel technologies, such as genome-editing and next-generation-sequencing tools CRISPR-Cas9, TALEN, and ZFNs, which are potent gene-editing tools that design microbes with specific degradation-function genes and provide unique insights into microbial remediation. Moreover, the successful execution of omics technologies could not be possible without the use of bioinformatic tools. The establishment of informative genomic and proteomic databases has been revolutionized by bioinformatics, which facilitates broad information about cellular- and metabolic-mechanism pathways for environmental pollutants. Hence, the involvement of these advanced technologies in the biological sciences shows the way to next-level research in the bioremediation potential of microorganisms, and exploits their capability to remove xenobiotic contamination.

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.

Author Contributions

Conceptualization and writing—original draft preparation: SM. Writing—review and editing: ZL, SP, WZ, PB, and SC. Supervision, funding acquisition, and project administration: SC. All authors contributed to the article and approved the submitted version.

This study was funded by the Key-Area Research and Development Program of Guangdong Province, China (2018B020206001), the National Natural Science Foundation of China (31401763), and the Guangdong Special Branch Plan for Young Talent with Scientific and Technological Innovation, China (2017TQ04N026).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Keywords: bioremediation, microorganisms, xenobiotics, omics, bioinformatics

Citation: Mishra S, Lin Z, Pang S, Zhang W, Bhatt P and Chen S (2021) Recent Advanced Technologies for the Characterization of Xenobiotic-Degrading Microorganisms and Microbial Communities. Front. Bioeng. Biotechnol. 9:632059. doi: 10.3389/fbioe.2021.632059

Received: 22 November 2020; Accepted: 11 January 2021; Published: 10 February 2021.

Reviewed by:

Copyright © 2021 Mishra, Lin, Pang, Zhang, Bhatt and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Shaohua Chen, shchen@scau.edu.cn

This article is part of the Research Topic

Advanced Bioremediation Technologies and Processes for the Treatment of Synthetic Organic Compounds (SOCs)

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• Published: 14 March 2016

The microbial pharmacists within us: a metagenomic view of xenobiotic metabolism

• Peter Spanogiannopoulos 1 ,
• Elizabeth N. Bess 1 ,
• Rachel N. Carmody 1 &
• Peter J. Turnbaugh 1  

Nature Reviews Microbiology volume  14 ,  pages 273–287 ( 2016 ) Cite this article

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• Antimicrobials
• Metagenomics

The gut microbiome is a neglected component of the first-pass metabolism of xenobiotics before reaching the general circulation.

Direct microbial metabolism of xenobiotics and their metabolites often involves reduction or hydrolysis, but most of the enzymes responsible for these reactions remain unknown.

Microbial metabolism influences both efficacy and toxicity, producing bioactive compounds, inactive metabolites and toxins.

Relevant host–microbial interactions include the expression of host genes that are involved in drug transport and metabolism, the interference with host enzymatic activity and the modulation of immune responses.

The translational implications of these studies include the development of novel co-therapies and the identification of new biomarkers and drugs.

Although the importance of human genetic polymorphisms in therapeutic outcomes is well established, the role of our 'second genome' (the microbiome) has been largely overlooked. In this Review, we highlight recent studies that have shed light on the mechanisms that link the human gut microbiome to the efficacy and toxicity of xenobiotics, including drugs, dietary compounds and environmental toxins. Continued progress in this area could enable more precise tools for predicting patient responses and for the development of a new generation of therapeutics based on, or targeted at, the gut microbiome. Indeed, the admirable goal of precision medicine may require us to first understand the microbial pharmacists within.

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Acknowledgements

The authors apologize to all of those colleagues whose work could not be included in this Review owing to space constraints. The authors also thank the reviewers for their comments and suggestions. This work was supported by the US National Institutes of Health (R01AT008618, R01HL122593 and F32DK101154), the Young Investigator Grant for Probiotics Research, the George Williams Hooper Research Foundation and the University of California San Francisco (UCSF) Department of Microbiology & Immunology. P.J.T. is a Nadia's Gift Foundation Innovator supported, in part, by the Damon Runyon Cancer Research Foundation (DRR-42-16).

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Peter Spanogiannopoulos, Elizabeth N. Bess, Rachel N. Carmody & Peter J. Turnbaugh

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Correspondence to Peter J. Turnbaugh .

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P.J.T. is on the Scientific Advisory Board for Seres Therapeutics and Whole Biome, has consulted for Pfizer in the past year and has current research support from MedImmune.

Supplementary information

Comprehensive list of pharmaceuticals and dietary compounds subject to gut microbial metabolism (PDF 591 kb)

PowerPoint slides

Powerpoint slide for fig. 1, powerpoint slide for fig. 2, powerpoint slide for fig. 3, powerpoint slide for fig. 4, powerpoint slide for fig. 5.

The combined genetic material and metabolic activities of the microbiota.

The collection of all microorganisms (archaea, bacteria, microscopic fungi, parasites and viruses) found in a given body habitat.

Compounds that are foreign to a biological system. For humans, these include drugs, dietary bioactive compounds, food additives and environmental toxins.

A chemical bond composed of N=N.

The study of how genetic factors influence therapeutic outcomes.

The use of sequencing-based genomic methods to analyse the links between genetics and therapeutic outcomes.

The proportion of an administered compound that reaches systemic circulation and thus has the potential to influence the intended target.

The metabolism of orally ingested compounds before reaching general circulation.

The transfer of xenobiotics and other compounds from the plasma to bile through hepatocytes, which is followed by the release of the compounds into the gut lumen.

The circulation of xenobiotics and endogenous compounds that are absorbed from the intestines, transported to the liver, and then re-enter the intestine through the bile ducts, where they may be reabsorbed or metabolized by the gut microbiota.

A chemical reaction in which the oxidation state of a chemical bond is reduced. For example, a carbon–carbon bond modified to a carbon–hydrogen bond is a reductive transformation.

A chemical reaction in which a chemical bond is cleaved using a water molecule, which acts as the nucleophile.

(CYPs) A family of enzymes that is responsible for the oxidative biotransformation of xenobiotics and other compounds.

Drugs that are administered in an inactive form and become active when metabolized.

A B vitamin that is essential for DNA synthesis, DNA repair and other biological reactions.

Animals devoid of microorganisms.

The colonization of germ-free animals with individual microorganisms or defined microbial communities.

The addition of glucuronic acid to a substrate. Glucuronidation is used as a mechanism of xenobiotic metabolism by the host.

Steroid acids produced by the liver that emulsify fats during digestion.

The remaining compound after the removal of a glycosyl moiety.

The collection of all metabolites found in serum.

The addition of a chemical unit (for example, glucuronic acid or glutathione) to xenobiotics, increasing the solubility and molecular weight of the parent compound and facilitating elimination from the body.

A collection of physiological and biochemical conditions, defined as a combination of high blood pressure, increased blood sugar levels, excess fat and abnormal cholesterol levels. This syndrome increases the risk of heart disease, stroke and diabetes.

An oral medication used to treat type 2 diabetes.

A manual for the preparation and use of medicinal drugs. The name is derived from the Greek words pharmakon (drug) and - poios (making).

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Spanogiannopoulos, P., Bess, E., Carmody, R. et al. The microbial pharmacists within us: a metagenomic view of xenobiotic metabolism. Nat Rev Microbiol 14 , 273–287 (2016). https://doi.org/10.1038/nrmicro.2016.17

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Published : 14 March 2016

Issue Date : May 2016

DOI : https://doi.org/10.1038/nrmicro.2016.17

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Recent Advanced Technologies for the Characterization of Xenobiotic-Degrading Microorganisms and Microbial Communities

Affiliations.

• 1 State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangdong Province Key Laboratory of Microbial Signals and Disease Control, Integrative Microbiology Research Centre, South China Agricultural University, Guangzhou, China.
• 2 Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, China.
• PMID: 33644024
• PMCID: PMC7902726
• DOI: 10.3389/fbioe.2021.632059

Global environmental contamination with a complex mixture of xenobiotics has become a major environmental issue worldwide. Many xenobiotic compounds severely impact the environment due to their high toxicity, prolonged persistence, and limited biodegradability. Microbial-assisted degradation of xenobiotic compounds is considered to be the most effective and beneficial approach. Microorganisms have remarkable catabolic potential, with genes, enzymes, and degradation pathways implicated in the process of biodegradation. A number of microbes, including Alcaligenes, Cellulosimicrobium, Microbacterium, Micrococcus, Methanospirillum, Aeromonas, Sphingobium, Flavobacterium, Rhodococcus, Aspergillus, Penecillium, Trichoderma, Streptomyces, Rhodotorula, Candida , and Aureobasidium , have been isolated and characterized, and have shown exceptional biodegradation potential for a variety of xenobiotic contaminants from soil/water environments. Microorganisms potentially utilize xenobiotic contaminants as carbon or nitrogen sources to sustain their growth and metabolic activities. Diverse microbial populations survive in harsh contaminated environments, exhibiting a significant biodegradation potential to degrade and transform pollutants. However, the study of such microbial populations requires a more advanced and multifaceted approach. Currently, multiple advanced approaches, including metagenomics, proteomics, transcriptomics, and metabolomics, are successfully employed for the characterization of pollutant-degrading microorganisms, their metabolic machinery, novel proteins, and catabolic genes involved in the degradation process. These technologies are highly sophisticated, and efficient for obtaining information about the genetic diversity and community structures of microorganisms. Advanced molecular technologies used for the characterization of complex microbial communities give an in-depth understanding of their structural and functional aspects, and help to resolve issues related to the biodegradation potential of microorganisms. This review article discusses the biodegradation potential of microorganisms and provides insights into recent advances and omics approaches employed for the specific characterization of xenobiotic-degrading microorganisms from contaminated environments.

Keywords: bioinformatics; bioremediation; microorganisms; omics; xenobiotics.

Copyright © 2021 Mishra, Lin, Pang, Zhang, Bhatt and Chen.

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• Systematic Review

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VDEC is supporting a GBS vaccine to prevent newborn deaths

Antimicrobial resistance to Group B Streptococcus (GBS) antibiotics is growing. This puts newborns at risk. VDEC is supporting a new vaccine to cut antibiotic use

The vaccine development and evaluation centre ( VDEC ) facilitates the development and evaluation of new vaccines and therapeutics.

VDEC ’s work includes vaccine discovery and surveillance . The Vaccine Assay and Immune Response team within  VDEC  provides world class scientific expertise and regulated facilities to enable the classification of diseases, pathogens and their mechanisms of action. They also provide continued national surveillance after the release of vaccines.

They have recently been supporting the creation of a maternal vaccine for Group B Streptococcus ( GBS ).

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GBS is the leading cause of vaccine-preventable infections in newborns in the developed world, and a significant cause of newborn infections and stillbirths worldwide. As such, GBS is a leading driver of antibiotic use in neonatal settings, and antimicrobial resistance is increasing.

To reduce early-onset disease (usually within the first 48 hours of life) many countries have introduced screening for GBS in pregnancy. Culture positive mothers are then given intravenous antibiotics in childbirth to protect both the mother and the infant. This has dramatically increased the use of antibiotics in childbirth. In some countries over 50% of childbirths now involve intravenous antibiotic use.

A maternal vaccine for GBS which protects infants from both early and late onset disease (for which intrapartum antibiotics have no effect) will have a positive impact on infant mortality and morbidity. It will also lead to a sharp reduction in the use of antibiotics in neonatal units worldwide.

Reducing antibiotic use in newborns will allow the development of appropriate commensal gut bacteria. This enables them to digest milk and reduces the risk of antimicrobial resistance.

The UKHSA Pathogen Immunology Group at Porton Down had previously been part of the GASTON consortium. This is an international consortium to develop standardised correlates of protection to allow the evaluation of new GBS vaccines and enable licensure of the leading candidates.

UKHSA Porton successfully developed a ‘Gold Standard’ opsonophagocytic killing assay ( OPKA ) and led a global interlaboratory study of the OPKA in public health, academic and industry labs. The assay was shown to be highly sensitive and reproducible in different laboratories, and standard GBS test strains have been selected by UKHSA and made available worldwide.

What VDEC offers

In 2022 to 2023, follow-on funding was awarded by the Bill and Melinda Gates Foundation ( BMGF ) to develop a higher-throughput version of the OPKA suitable for Phase II/III clinical trials and to provide international reference serum samples with defined units of opsonophagocytic activity. The high throughput OPKA is required as the current assay method is very labour-intensive which limits the number of sera that can be analysed in large vaccine studies.

Expected outcome

Licensure of a GBS vaccine will:

• prevent the deaths of tens of thousands of newborns worldwide
• reduce the need for antibiotic treatment in disease cases
• reduce the need for intrapartum antibiotics during childbirth

Future work

As part of this project, the team has also developed an OPKA for GBS serotype VII, which will be used in a follow-up PATH -funded Phase I/II clinical study of a novel 6-valent GBS vaccine currently being developed.

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Study links talc use to ovarian cancer — a potential boon for thousands suing J&J

New research published this week lends credence to the more than 50,000 lawsuits against Johnson & Johnson that allege its talc-based baby powder caused ovarian cancer.

The analysis , released Wednesday in the Journal of Clinical Oncology, found that applying talc powder to the genitals was associated with ovarian cancer — and that the association was greater for people who used the powder frequently or for long periods of time.

The researchers are from the National Institutes of Health, and their findings were based on data from the Sister Study, which enrolled more than 50,000 women in the U.S. from 2003 to 2009. The participants joined when they were between 35 and 74 years old, and each had a sister who’d been diagnosed with breast cancer, which might put them at increased risk for breast or ovarian cancer.

Lawsuits related to J&J’s talc-based baby powder date back to 1999, when a woman alleged that a lifetime of using it led to her mesothelioma, a rare cancer usually caused by exposure to asbestos — a known carcinogen. In 2009, another woman sued the company, alleging that its talc-based products caused her ovarian cancer. Since then, many thousands of others have filed claims over cases of ovarian cancer or mesothelioma that they say were caused by asbestos in J&J baby powder.

J&J has stood by the safety of its talc products and denies that they ever contained asbestos. The company has also argued that studies have not demonstrated a convincing link between ovarian cancer and talc-based products.

The new research could undermine that line of reasoning as the legal battles continue. Most of the lawsuits against J&J have been consolidated into a single federal case in New Jersey, with trial scheduled for December.

“This study is quite timely. We feel like it completely affirms and confirms the position taken by plaintiffs’ experts,” said Leigh O’Dell, a principal at Beasley Allen Law Firm. O’Dell is the co-lead counsel for the plaintiffs’ steering committee, a group of attorneys appointed to act on behalf of the many people with pending cases against J&J.

However, Erik Haas, J&J’s worldwide vice president of litigation, said the new analysis doesn’t establish causality or implicate a specific cancer-inducing agent.

“This study does not change the overwhelming evidence that talcum powder does not cause ovarian cancer,” he said.

Earlier this month, J&J proposed a payment of around $6.48 billion to resolve the lawsuits, but the deal would involve moving the cases to bankruptcy court and require 75% of claimants to vote in favor.

J&J has tried and failed twice to resolve talc lawsuits in bankruptcy court . The company created a subsidiary in 2021 that could assume liability for talc-related legal claims — a legal maneuver known as a Texas two-step. But thus far, courts have dismissed the bankruptcy filings on the grounds that the subsidiary is not in financial distress.

O’Dell said her team “would like to see these women offered a reasonable and fair resolution outside of bankruptcy.”

“Any effort to file another bankruptcy, we believe, is just yet another abuse of the bankruptcy system,” she said.

The potential harms of talc products

The new study asked women how often they used talc powder on their genitals from ages 10 to 13 and during the year before they enrolled in the study. NIH researchers followed up with surveys from 2017 to 2019 that asked women about their lifetime use of talc powder.

Based on the responses, the researchers estimated that up to 56% of the women used talc powder on their genitals at some point. These women were more likely to be Black, less educated and live in the South compared with people who didn’t use talc powder.

The analysis can’t prove that talc causes ovarian cancer, nor does it identify a brand or chemical driving the association. Dale Sandler, one of the study’s authors and the chief of the epidemiology branch at the National Institute of Environmental Health Sciences, said there probably isn’t a way to prove causality in human studies.

“You can’t do a clinical trial and randomize people to ‘powder’ and ‘no powder.’ So we’re going to need to look to other types of research,” she said.

At the very least, the findings should prompt women to rethink their use of talc products, said Katie O’Brien, the lead author of the analysis and an epidemiologist at the National Institute of Environmental Health Sciences.

“We’re not aware of any medically necessary reasons why someone would need to use talcum,” she said.

Current formulations of J&J baby powder use cornstarch, not talc. The company pulled the talc-based versions from the North American market in 2020, citing waning demand and “misinformation around the safety of the product,” and discontinued the product internationally last year.

Talc and asbestos are found in close proximity in nature, so some raw talc collected via mining may be contaminated with asbestos , according to the Food and Drug Administration.

A 2018 Reuters investigation suggested that J&J knew some of its baby powder was contaminated with small amounts of asbestos as early as the 1970s. But J&J denies asbestos was ever present in its products.

O’Brien said asbestos might not be the only reason for an association between talc and cancer. Some talc products may also contain phthalates — chemicals that disrupt hormones in the body and have been linked to ovarian cancer . Plus, talc itself can be abrasive, she added, so it may cause inflammation in the areas where it’s applied. Inflammation is independently associated with the development of cancer.

A debate over the science

Debates over the research linking talc and ovarian cancer will almost certainly be a focus of upcoming litigation in the J&J case.

The New Jersey federal court ruled in March that the company can contest findings that link ovarian cancer to talc.

To support its position, J&J has pointed to research that O’Brien and Sandler published in 2020 , which did not find a statistically significant association between ovarian cancer and the use of talc powder.

But O’Brien said that older study may not have been set up to detect small changes in risk because it did not ask women about their lifetime use or factor in the chance that people might misremember their past habits. Sandler said the new study accounts for those two variables.

“This newer analysis sort of tips the balance by accounting for all these possible ways that reporting could have been incomplete in the prior literature,” she said.

How talc may have played into body shame

J&J started selling talc-based baby powder in 1894.

Although many women have used it to keep their genitals dry, there’s no need to use powder to get rid of moisture in that area, said Alexandra Scranton, director of science and research at Women’s Voices for the Earth, a nonprofit that aims to eliminate chemicals that negatively affect women’s health.

“Moisture in this part of the body is a very healthy thing,” Scranton said. “This part of the body is covered in mucous membranes. It’s supposed to be moist.”

According to O’Brien’s research, some women in the 2000s — often those in their 20s and 30s — also used talc powder on their genitals to feel clean and reduce odor. That application isn’t advised by health experts, either, since the vagina is self-cleaning and good bacteria inside of it naturally produce a slight odor.

Companies like J&J were “basically creating and promoting this myth that this part of your body — your genitals, your vagina — are inherently dirty and that they’re inherently odorous, and therefore inherently shameful,” Scranton said.

J&J said it disagrees with that characterization.

Some women continue to use baby powder on their genitals or have adopted new products like vaginal washes or scented body deodorants.

“It’s so ingrained and so part of the way they take care of their bodies that they can’t imagine not doing it,” Scranton said. “They’ve got their mom’s voice in their head: ‘This is what you do to be a respectable woman.’”

Aria Bendix is the breaking health reporter for NBC News Digital.

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How One Company Added Carbon Estimates to Its Customer Invoices

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A four-step playbook to help businesses increase transparency and reduce emissions.

Soprema is an international building materials supplier, producing millions of square meters of waterproofing, insulating, and roofing products each year. In 2022, Pierre-Etienne Bindschedler, the company’s president and third-generation owner, committed to reporting the carbon footprint of each product on every customer invoice, and to help customers reduce the embedded GHG emissions in the products they purchased. Paper co-author Melotte, an experienced operations director, was selected to lead a pilot project to measure and subsequently lower the carbon embedded in its products. Melotte decided to follow the E-Liability Pilot Playbook, which divides a pilot project into four stages: Project Design, Data Collection; Data Analysis, and Action. This article describes how the pilot, which focused on the company’s bitumen waterproofing systems, unfolded at Soprema. The company estimates a potential carbon footprint reduction of 34% from the project.

In 2022, Pierre-Etienne Bindschedler, the president and third-generation owner of Soprema, set a goal to develop sustainable solutions for customers. Soprema is a multi-product, family-owned business in the middle of the building materials value chain and produces millions of square meters of waterproofing, insulating, and roofing products each year.  Bindschedler wanted to report the carbon footprint of each product on every customer invoice, and to help customers reduce the embedded GHG emissions in the products they purchased.

• Robert S. Kaplan is a senior fellow and the Marvin Bower Professor of Leadership Development emeritus at Harvard Business School. He coauthored the McKinsey Award–winning HBR article “ Accounting for Climate Change ” (November–December 2021).
• TM Timmy Melotte is an Operational Excellence Director for Soprema International, a building materials supplier based in Limburg, Belgium

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Special Issue: Microbial Degradation of Xenobiotics

Xenobiotics are released into the environment by human activities, and they often cause problems such as environmental pollution, since most such compounds cannot be readily degraded, and have harmful effects on human beings and the natural ecosystem. However, some microorganisms that degrade man-made xenobiotics have been isolated. Most of these aerobic xenobiotics-degrading bacterial strains use xenobiotics as their sole source of carbon and energy, and thus they are excellent models for studying the adaptation and evolution of bacteria in the environment.

Recent genome analyses of bacterial strains that degrade xenobiotics have strongly suggested that they indeed emerged relatively recently by gathering genes for the degradation of xenobiotics, and mobile genetic elements played important roles in the recruitment of the genes [ 1 ]. However, the origin of the genes and the evolutionary processes of such bacterial strains remain largely unknown. Ongoing comprehensive genome and metagenome analyses may provide some insights into these mysteries, and the genes for the degradation of xenobiotics can be used as probes to reveal novel mechanisms for the evolution of microorganisms. In addition, enzymes for the degradation of xenobiotics are good materials for studies on protein evolution, since generally they have promiscuous activities, and their properties change dramatically with a small number of mutations [ 2 ]. On the other hand, the importance of microbial consortia and symbiosis for the degradation of xenobiotics in the environment has also been suggested [ 3 ], and thus studies on xenobiotics degradation may provide some novel concepts in the field of microbial ecology.

This issue gathers 13 articles dealing with various aspects of the microbial degradation of xenobiotics. Four of them deal with the bacterial strains that degrade monocyclic phenolic compounds [ 4 ], polylactic acid [ 5 ], and naphthalene [ 6 ], and those that accumulate perfluorohexane sulfonate [ 7 ]. Two are dedicated to bacterial consortia degrading diesel [ 8 ] and dioxane [ 9 ]. Two focus on the enzymes for degradation of haloalkanes [ 10 ] and bisphenols [ 11 ]. Three articles are related to “indirect” factors that are necessary or important for the microbial degradation of xenobiotics, i.e., transcriptional regulation [ 12 ], transporters that are involved in the transport of xenobiotic compounds across the outer membrane [ 13 ], and mobile genetic elements [ 14 ]. The last two articles address metabolic engineering [ 15 ] and the bioreactors [ 16 ] necessary for practical application.

Acknowledgments

I would like to thank all authors who contributed their excellent papers to this Special Issue. I thank the reviewers for their help in improving the papers to the highest standard of quality. I am also grateful to all members of the Microorganisms Editorial Office for giving me this opportunity, and for their continuous support in managing and organizing this Special Issue.

Conflicts of Interest

The author declares no conflict of interest.