Discovering untapped microbial communities through metagenomics for microplastic remediation: recent advances, challenges, and way forward

Abstract

Microplastics (MPs) are ubiquitous pollutants persisting almost everywhere in the environment. With the increase in anthropogenic activities, MP accumulation is increasing enormously in aquatic, marine, and terrestrial ecosystems. Owing to the slow degradation of plastics, MPs show an increased biomagnification probability of persistent, bioaccumulative, and toxic substances thereby creating a threat to environmental biota. Thus, remediation of MP-pollutants requires efficient strategies to circumvent the mobilization of contaminants leaching into the water, soil, and ultimately to human beings. Over the years, several microorganisms have been characterized by the potential to degrade different plastic polymers through enzymatic actions. Metagenomics (MGs) is an effective way to discover novel microbial communities and access their functional genetics for the exploration and characterization of plastic-degrading microbial consortia and enzymes. MGs in combination with metatranscriptomics and metabolomics approaches are a powerful tool to identify and select remediation-efficient microbes in situ. Advancement in bioinformatics and sequencing tools allows rapid screening, mining, and prediction of genes that are capable of polymer degradation. This review comprehensively summarizes the growing threat of microplastics around the world and highlights the role of MGs and computational biology in building effective response strategies for MP remediation.

Introduction

The use of plastic has escalated tremendously over the last 50 years due to industrialization. Plastic rise from 1.5 million metric tons (MMTs) in 1950 to 367 MMTs in 2020 is a testament to the global plastic surge (Peng et al. 2021). Even though there has been a decrease of 0.3% in plastic production, the shoot-up in the usage of masks, gloves, sanitizer bottles, and medical equipment during the ongoing COVID-19 pandemic has contributed to unforeseen environmental crisis (Patrício Silva et al. 2021). Microplastics (MPs), the plastic fragments with less than 5 mm in size, are insoluble, biodegradable, and non-biodegradable waste particles having a half-life of about 100–1000 years. Based on the occurrence, MPs are classified into primary and secondary types. Primary MPs exist in nature in standard MP-size such as microbeads and plastic pellets, whereas secondary MPs arise from the breakdown of larger plastic materials like fishing nets, soda bottles, microwave containers, and other plastic products. Chemically, MPs are synthetic or semi-synthetic polymers composed of carbon, nitrogen, oxygen, hydrogen, chloride, silicon, etc. Depending on the nature of side chains, polymer backbone, physical properties, tensile strength, density, and thermal resistant plastics are classified into seven types each numbered according to their recycling codes as (1) polyethylene terephthalate/PET (beverage bottles, polyester clothing, rope), (2) high-density polyethylene/HDPE (detergent bottles, toys, buckets, rigid pipes), (3) polyvinyl chloride/PVC (credit cards, medical tubing, rain gutters), (4) low-density polyethylene/LDPE (grocery bags, beverage cups, bread bags), (5) polypropylene/PP (straws, packaging tape, disposable diapers), (6) polystyrene/styrofoam/PS (insulations, takeout food containers, cutlery), and (7) others/O (bisphenol A, polyamimide, polycarbonate) (Verla et al. 2019; Henderson and Green 2020; Veerasingam et al. 2020; Frias et al. 2021).

The top countries in the generation plastic waste per year in million tons in 2020 include the USA (58.02) (Law et al. 2020), India (55.06) (Shams et al. 2021), the UK (39.7) (Burgess et al. 2021), South Korea (38.1) (Shin et al. 2020), Germany (36) (Nelles et al. 2016), Thailand (32.4) (Parashar and Hait 2021), Malaysia (29.8) (Fauziah et al. 2021), Argentina (29.7) (Ronda et al. 2021), Russia (28) (Filiciotto and Rothenberg 2021), Italy (24.5) (Geyer et al. 2017), and Brazil (23.2) (Almeida et al. 2021). Most ecosystems are under threat of plastic pollution because of the properties like non-biodegradability, limited recovery, toxicity, higher ingestion, accumulation, and incorporation associated with MPs (Campanale et al. 2020; Issac and Kandasubramanian 2021). Since MP particles bear a resemblance with the food of marine biota, fishes, mammals, and plankton easily engulf it and accumulate in the body leading to blockage of the digestive system (Walkinshaw et al. 2020). Wang et al. (2019a) studied the effect of ingested PS-MPs on Artemia parthenogenetica (microcrustacean) and reported the occurrence of several abnormal epithelial cells in the digestive tract. Exposure of zooplankton crustacean Daphnia magna to PET textile microfibers resulted in increased mortality of daphnids (Jemec et al. 2016). MPs not only affect the ecosystem directly, but they also act as carriers for other environmental contaminants like heavy metals such as zinc and copper (Brennecke et al. 2016), polychlorinated biphenyl (Gerdes et al. 2019), and polyaromatic hydrocarbons (Sørensen et al. 2020) (Ye et al. 2020a). Humans may suffer chronic effects by ingestion, inhalation, and dermal contact of MPs leading to cell damage, inflammation, and hypersensitive reactions (Visalli et al. 2021; Domenech and Marcos 2021; Blackburn and Green 2021). A 2016–2017 UN report documented about 800 animal species contaminated with plastic via entanglement and ingestion, which is almost 70% greater than that of 1977 UN report. This makes humans prone to harmful effects of plastic in the upcoming decades (Smith et al. 2018).

Hwang et al. (2019) assessed the PP toxicity in human-derived cells and found that PP-MPs induce pro-inflammatory cytokines in a size-dependent manner. Likewise, Wu et al. (2019) studied the size-dependent effects of PS-MPs on cytotoxicity and efflux pump inhibition in human colon adenocarcinoma Caco-2 cells. They reported higher mitochondrial depolarization through 5 μm PS-MPs while 0.1 μm PS-MPs induced higher inhibition of adenosine triphosphate-binding cassette transporter. The traditional disposal methods like recycling, incineration, and landfill have been reported to show negative effects by generating secondary pollutants that cause disastrous effects on the environment (Rhodes 2018). Therefore, microbial degradation has emerged as a method of choice for expunging plastic and other pollutants. Several studies have been carried out in studying the biodegradation of MPs such as PE (Restrepo-Flórez et al. 2014), PS (Kim et al. 2021), PP (Jeon et al. 2021), and PET (Farzi et al. 2019). Kim et al. (2020) reported that the Pseudomonas aeruginosa DSM 50,071 strain, isolated from the gut of Zophobas atratus larvae, mediates the degradation of PS-MPs through enzymatic action. Zalerion maritimum (Paço et al. 2017), Aspergillus versicolor (Akhtar and Mannan 2020), Vibrio parahemolyticus (Kesy et al. 2020), and Psychrobacter sp. (Chattopadhyay 2022) have been also reported to exhibit the MP-remediation potential. A challenge in using microbial degradation on large scale is the slow rate of plastic degradation. Moreover, most of the reports published on the biodegradation of MPs have been performed in the laboratory set-ups.

Many microbes cannot be cultured in the laboratory conditions; hence, culture-based approaches have proved to be insufficient for the exploration and characterization of microorganisms. Besides, plastic biodegradation is also an outcome of the microbial consortia acting synergistically, which is difficult to study through culture-based approach. Metagenomics offers a gateway to overcome this problem (Handelsman 2004; Wani et al. 2022a). MGs in association with other meta-omics approaches are proving to be the standout approach for the identification of novel uncultivable microorganisms capable of MP-remediation (Bharagava et al. 2018; Wani et al. 2022b). This review offers a comprehensive outlook of the MP threat around the globe besides highlighting the fundamental MP remediation studies mediated by microorganisms isolated through culture-dependent and culture-independent approaches.

Microplastics (MPs): generation and escalation

Millions of tons of plastics are released into the environment every year. As a result, the quantity and distribution of MPs have escalated in the atmosphere, aquatic, and terrestrial ecosystems (Fig. 1). It is estimated that by 2060 plastic accumulation can reach up to 155–265 million tons, and it is believed that about 13.2% of this weight could be MPs (Eriksen et al. 2014; Geyer et al. 2017; Bergmann et al. 2019). The presence of MPs in different environments was revealed during the early 1970s (Buchanan 1971; Carpenter and Smith 1972). However, in recent times, scientists have started to investigate MP spread, accumulation, and ecological implications (Huang et al. 2021; Chen et al. 2021a; Vaid et al. 2021; Kallenbach et al. 2022). MP pollution in terrestrial and freshwater ecosystems has been less extensively studied in comparison to marine ecosystems (Chen et al. 2021a). Afrin et al. (2020) investigated MP presence in landfill sites of Dhaka, Bangladesh, and reported the presence of LDPE, HDPE, and cellulose acetate. Liu et al. (2018) also reported PP (50.51%) and PE (43.43%) in the suburbs of Shanghai, China. In total, 10% of the plastic ends up in the ocean and about 7–8 million plastic pieces escape into the oceans from land terrestrial sources. At present, most of the world’s seas and oceans are MP-contaminated. The Mediterranean Sea, with a 1500 m average depth, is recognized as a plastic contamination hotspot because its MP-concentration is fourfold greater than the North Pacific Ocean. This is attributed to the distinguishing semi-enclosed morphology of the Mediterranean Sea, and surrounding plastic waste-generating countries (Sharma et al. 2021). Table 1 gives insight about the growing MP contamination in different parts of the world. Lacerda et al. (2019) evaluated and characterized plastics in sea surface waters of the Antarctic Peninsula and did not find any statistical difference between the amount of MPs (54%) and mesoplastics (46%). They found smaller fragments composed of polyamide, PET, and polyurethane (PU).

Fig. 1.

Escalation of plastic waste around the world from 1950 to 2050 (Ritchie and Roser 2018; Zhang et al. 2021; Jankowska et al. 2022; Luan et al. 2022)

Table 1.

Amount and type of microplastic contamination reported in different marine and terrestrial sites of the world

Country/region	Sampling site	Sample type	Microplastic (MP) types/shapes	MP-amount	References
Atlantic Ocean	South-North transect	Surface	PE and PP	1723 ± 1793 particles m3 and 822 ± 1250 particles/ m3	Pabortsava and Lampitt (2020)
Australia	Gardens	Soil	PE and PP	NA	Sobhani et al. (2021)
Brazil	Guanabara bay sublittoral sites	Sediment	Polyester	160–1000 items/kg	Alves and Figueiredo (2019)
	Patos Lagoon (Laranjal beach)	Water	LDPE, HDPE, and PFTE	0.00021 g/L	Silva and de Sousa (2021)
China	Laizhou Bay	Water and Sediment	PET, Cellophane (CP), PE and PP	1.7 ± 1.5 particles/m3 and 461.6 ± 167.0 particles/kg	Teng et al. (2020)
	Maowei Sea	Water	Polyester and Rayon	1.2–10.1 particles/L	Zhu et al. (2019)
	North Yellow Sea	Surface water and Sediment	PE and PP	545 ± 282 items/m3 and 37.1 ± 42.7 items/kg	Zhu et al. (2018)
	Jiaozhou Bay	Water and Sediment	PET, PP, and PE	20–120 items/m3 and 7–25 items/kg	Zheng et al. (2019)
French Polynesia	Tropical lagoons	Surface water and Pearl oyster	PE, and PP	0.2–8.4 items/m3 and 2.1–125.0 items/g	Gardon et al. (2021)
India	Coastal stretch of the Bay of Bengal	Water, sediment, and dry sand	PP, PE, polyesters, and fluoro-polymers	60–820 items/m3, 60–1620 items/kg, and 20–1540 items/kg	Sunitha et al. (2021)
	River shoreline Brahmaputra river	Sediment	PP, PE, and PVC	20–240 MP/Kg (particles larger than 150 μm) and 531–3485 MP/kg (MP particles size range 20–150 μm)	Tsering et al. (2021)
	Calicut beach, Kerela	Sediment	PE, PE + PP, PP, PS, PCU, PET, and PVC	80.56 items/Kg	Kumar and Varghese (2021)
Indonesia	Jakarta bay (Sunda Kelapa Port)	Sediment	PP, PE, PS, and PA	45,066.67 ± 2444.04 particles/kg	Azizi et al. (2021)
	Banten Bay	Sediment	Foam and PS	267 ± 98 particles/kg	Falahudin et al. (2020)
Malaysia	Klang River, estuary	Surface water	PE, PA, fibers, and pellets	2.47 particles/L	Zaki et al. (2021)
Mediterranean Sea	Calabrian coasts	Surface water	PE	0.13 ± 0.19 particles/ m2	Marrone et al. (2021)
Nepal	Mount Everest	Stream water and Snow	Polyester fibers	1 item/L and 30 items/L	Napper et al. (2020)
Pacific Ocean	Western part	Sediment	PP, PE, and PET	240 items per kg dry weight	Zhang et al. (2020)
	Mid North	Surface water	PP and irregular fragments	0.51 ± 0.36 items/m3	Pan et al. (2022)
Portugal	Beaches of Portuguese coast	Sediment	Resin pellets, and PS	358–1679 items m−2, and 63–169 items m−2	Antunes et al. (2018)
South America	Two Tributaries of Cuiaba River	Water	Microfibers	9.6 ± 8.3 × 100/L	Faria et al. (2021)
Taiwan	Taiwan Strait	Sediment and surface seawater	Films, fragment, fibers, and granules	28–208 items/kg and 0.004–0.0058 items/m3	Wu et al. (2021)
Tropical Eastern Pacific and Galapagos	Coast	Water and specimens	Fibers	NA	Alfaro-Núñez et al. (2021)
United States	Northwest Panhandle Florida and Central Florida	Water and snails	Microbeads, microfragments, and microfibers	8.375 items/L and 4.26 MPs/snail	Kleinschmidt and Janosik (2021)

Bioaccumulation and Ecotoxicological repercussions of MPs

The resistance (Sharma and Chatterjee 2017), high durability (Lim 2021), high consumption (Chen et al. 2021b), and low recycling (Muncke et al. 2020) of plastic polymers contribute to the escalation of plastic in the environment. Oceans are the largest known sinks for MPs (Kvale et al. 2020). The plastic debris from sewage treatment plants, transport and cosmetic industries, manufacturing, fishing, packaging, and shipping industries reaches the marine environment and is estimated to be 5–12 million metric tons per annum (Thushari and Senevirathna 2020; Vriend et al. 2021; Lim 2021; Peng et al. 2021). MP accumulation in terrestrial and aquatic biota through absorption, ingestion, or respiration has been widely recognized (Duis and Coors 2016; Souza Machado et al. 2018; Amobonye et al. 2021). Arenicola marina, an annelid species, has been reported to have MPs embedded in its gastrointestinal tracts (Besseling et al. 2013). Some crustaceans like Carcinus maenas have also been reported with the presence of MPs in the digestive and respiratory tracts (McGoran et al. 2020). These plastic particles are mistaken for food, leading to the blockade of essential body tracts which results in the generation of incorrect signals (Smith et al. 2018; Ugwu et al. 2021). Several studies have shown that MP accumulation or continuous exposure in aquatic organisms leads to the deterioration of inflammatory and oxidative intestinal balance, and permeability disruption of gut epithelial cells besides promoting the growth of pathogens on cell surfaces (Viršek et al. 2017; Limonta et al. 2019; Yang et al. 2020). Red tilapia when exposed to 0.3, 5, and 70 μm PS fragments for 14 days induced oxidative stress, neurotoxicity, and inhibition of cytochrome P450 enzyme activity (Ding et al. 2020). The accumulation of PS in Oryzias melastigmas (Ye et al. 2021) and PE in Dicentrachus labrax (Barboza et al. 2020) has been reported to cause negative effects on histology, immunity, and metabolism. Barboza et al. (2020) reported that PE and polyester in wild fish cause oxidative damage in muscles and gills besides increasing acetylcholinesterase activity in the brain. Bisphenol A and petroleum hydrocarbon aggravate immunotoxicity in blood clams and increase the toxicity of cadmium in fishes (Prüst et al. 2020). Benthic sea cucumbers, a non-selective bottom feeder, feed on the ocean floor debris and engulf a large amount of sediment (Sfriso et al. 2020). A study reported that Holothuria floridana, Thyonella gemmate, and Cucumaria frondose ingested 2–20 times more filter feeders have been reported to ingest MPs which decreases their filtration ability leading to effects like neurotoxicity and immunotoxicity (Mohsen et al. 2019; Bulleri et al. 2021). In 2019, marine biologists reported that seagrass beds in Makassar Strait, Indonesia, contain MP contaminants in the form of beads, pellets, fragments, and fibers (Tahir et al. 2019). Zooplankton also ingests MP beads which upon excretion can stick to the exoskeleton and appendages (Hasegawa and Nakaoka 2021).

The bioaccumulation of MPs in humans largely remains obscure, yet the MP consumption by crustaceans and fishes which are subsequently eaten by humans is still a matter of concern. There has been no study that evaluates the direct effect of plastic polymers on humans. A major concern in determining the negative effects of MPs on humans is the lack of information on human exposure. Thus, a better understanding of the MP-ability to cross epithelial barriers, skin, and gastrointestinal tract is needed to alleviate the uncertainty in human risk assessment of MPs (Prata et al. 2020; Vethaak and Legler 2021). However, several laboratory studies involving human cells and tissues and model organisms like rats and mice have shown negative implications of MPs. Researchers have started to investigate the presence of MPs in human tissues to extrapolate the effects of MPs that are directly human-oriented rather than in vitro. Ragusa et al. gave the first evidence of PPMP presence in the human placenta (Ragusa et al. 2021). Even though the presence and implications of MP in human tissues are obscure, there is a need to track and monitor MP pollution continuously. Exposure of mice to PE showed inflammation (Li et al. 2020) and smaller pups (Park et al. 2020), and exposure to PS reduced sperm count in mice (Jin et al. 2021). In mice gut, MPs increased intestinal permeability, altered gut microbiota composition, and enhanced intestinal inflammation (Deng et al. 2020a, b). One of the sub-chronic studies reported the accumulation of methacrylate polymer beads only in the gastrointestinal tract of mice (Groborz et al. 2020). Rodriguez-Seijo et al. (2017) reported the accumulation of PE-MPs in the earthworm gut causing damage to the epithelium of the gut wall. Seabirds also feed on marine debris and several studies have reported the presence of MPs in samples targeted for dietary studies, regurgitated cadavers, and feces. After engulfing, seabirds likely get rid of MPs through excretion or regurgitation (Blight and Burger 1997; Gil-Delgado et al. 2017; Hamilton et al. 2021). However, there is a risk of exposing offspring to the MPs at the time of feeding. Kühn and van Franeker (2012) found plastic in the intestine of juveniles rather than in adult birds.

Table 2 gives insight into the effect of different MPs on aquatic and terrestrial living systems of the earth. Figure 2 illustrates the potential threat of MPs on the biotic components of the earth.

Table 2.

Effect of different MPs on the biota of aquatic and terrestrial ecosystems

Microplastic type/shape	Organism	Effect	Reference
Aquatic organisms
HDPE	Heliopora, Porites, Acropora, and Pocillopora (Hermatypic corals)	Increase of coral susceptibility to stressors and increase in energy demand	Reichert et al. (2019)
Microspheres	Aiptasia sp. and Favites chinensis	Disturbs anthozoan-algae symbiosis	Okubo et al. (2018)
PE	Sparus aurata	Intestinal distension, liquid accumulation, inflammation, epithelial desquamation	Varó et al. (2021)
	Pagurus bernhardus (Hermit crabs)	Impairs shell selection and cognition that disrupts essential survival behavior	Crump et al. (2020)
	Clarias gariepinus (Catfish)	Reduction in swimming speed and increased opercular beat frequency	Tongo and Erhunmwunse (2022)
Polyester	Amphibians (Host) and Trematodes (parasite)	Reduces infection success when both are exposed to polyester contamination simultaneously	Buss et al. (2021)
PP	Dicentrarchus labrax (Sea bass)	Upregulation of tumor necrosis factor- α and perturbations in gut microbiota	Montero et al. (2022)
	Daphnia magna	Acute toxicity	Jemec Kokalj et al. (2022)
PS/PS-microbeads	Pelteobagrus fulvidraco (Yellow catfish)	Expression Inhibition of interleukin-8 and tumor necrosis factor-α	Li et al. (2021)
	Mytilus coruscus (Mussel)	Depletion of cellular energy stores like proteins, carbohydrates, and lipids	Shang et al. (2021)
	Danio rerio (Zebrafish)	Inflammation, increased permeability, microbiota dysbiosis and mucosal damage	Qiao et al. (2019)
	Poecilia reticulata (Juvenile guppy)	Impairs digestive performance, induces microbiota dysbiosis, and stimulates immune response	Huang et al. (2020)
	Paracentrotus lividus (sea urchin)	Increase in reactive oxygen and nitrogen species thus inducing stress on immune cells	Murano et al. (2020)
PVC	Carassius auratus (Goldfish)	Liver inflammation, oxidative damage in the brain, and histomorphological changes in the intestine	Romano et al. (2020)
	Cyprinus carpio var. larvae	Inhibition of weight gain and reduction in malondialdehyde level	Xia et al. (2020)
Terrestrial organisms
BPA	Sprague–Dawley rats	Perturbations in butanoate, alanine and aspartate metabolism	Mao et al. (2021)
PE	Mice	Increase in gut microbiota species and increase of interleukin-1α in serum	Li et al. (2020)
	Mice	Increase in globulin and albumin levels	Sun et al. (2021)
PE and PVC	Drosophila melanogaster	Changes in fertility and sex ratio	Jimenez-Guri et al. (2021)
PET	Achatina fulica (Snail)	Villi damage in gastrointestinal walls and elevation in malondialdehyde levels	Song et al. (2019)
	Human	Alteration in colonic microbial community	Tamargo et al. (2022)
PP, PVC, PET, and PE	Cucurbita pepo	Root and shoot growth impairment, leaf size, and chlorophyll reduction	Colzi et al. (2022)
PS	D. melanogaster	Negative effect on locomotion and intestinal damage	Matthews et al. (2021)
	Rats	Apoptosis and pyroptosis of granulosa cells	Hou et al. (2021)
	Triticum aestivum (Wheat)	Inhibition of wheat root and stem elongation	Liao et al. (2019)

Fig. 2.

Impact of MPs on marine and terrestrial biota, and its potential threat to human beings

Microplastic remediation mediated by microorganisms

MPs degrade mechanically (Schyns and Shaver 2021), chemically (Zhou et al. 2021), and biologically (Arpia et al. 2021) in the environment. Degradation rates mainly depend on structure, chemical composition, temperature, humidity, and deposition environment (Soil, water, sand). Mechanical degradation of MPs occurs through particle contact with anthropogenic (littered trash, boats, vehicles, groynes) and natural items (sediment, woody debris, shells) (Strayer and Findlay 2010; Qiao et al. 2019). Mechanical abrasion of MPs produces items that are similar in morphology to sediment grains. Song et al. (2017) examined the effect of UV exposure on MPs in the replicated beach environment and reported that the degradation rate varies with plastic type. PE and PP showed low degradation possibility through mechanical abrasion, but PS was found to fragment into more pieces. The exposure of floating plastic to UV light leads to the polymer degradation and the generation of chain scission products (Gewert et al. 2018). Enfrin et al. (2020) investigated weathering of MPs when exposed to stress using pumping, ultrasonic irradiation, and stirring. They reported that MP break down into nanoplastics (NPs) under low stress thus introducing more plastic debris to the environment. The weathering process of MPs is initiated or sometimes enhanced by chemical degradation through thermal oxidation, hydrolysis, and photooxidation. Plastics upon degradation produce different hydrocarbon gases such as methane, ethane, propylene, and ethylene when exposed to the solar radiation. Thus, climate-relevant trace gases are expected to increase with the accumulation of more plastic in the environment (Royer et al. 2018).

Besides, chemical degradation in seawater or replicated seawater has been reported to advance at a higher rate as compared to freshwater because of the variations in pH, and biotic community (Weinstein et al. 2016; Da Costa et al. 2018). Multiple chemical processes that are involved in the chemical degradation of MPs have been extensively reported and reviewed in great detail by different authors (Min et al. 2020; Ye et al. 2020b; Miao et al. 2020; Venkataramana et al. 2021; Zhou et al. 2021; Akhtar et al. 2022). Both natural and synthetic plastics are degraded by microbial action (Zeenat et al. 2021). Microorganisms degrade MPs using oxygen as an electron acceptor in the case of aerobic biodegradation (Yoshikawa et al. 2016). MPs are not transported directly into microorganisms because of their large size and water-insoluble nature (Cavicchioli et al. 2019). The degradation of MPs occurs through a series of events including, microbial attachment forming biofilms (Oberbeckmann and Labrenz 2020), and utilization of MPs as a carbon source (Lear et al. 2021). The microbial attachment to the MPs leads to the secretion of enzymes changing large MPs into monomers and oligomers having a low molecular weight (Lin et al. 2022). The microorganisms can change the surface properties of MPs followed by their bio-fragmentation through enzymatic action (Pathak and Navneet 2017). Hou and Majumder (2021) identified cytochrome 4500 s, monooxygenases, and hydrolases from microbial sources with PS-degrading potential. Several other microorganisms have been reported to have MP-degradation potential with varying biodegradation efficiency. Pseudomonas fluorescens, Bacillus sp., and Paenibacillus sp. degrade PE (Kathiresan 2003; Park and Kim 2019), B. vallismortis, Aspergillus oryzae, B. cereus, Trichoderma viride, A. nomius, and B. siamensis degrade LDPE (Skariyachan et al. 2017; Montazer et al. 2018; Nourollahi et al. 2019), and Klebsiella pneumoniae, and A. flavus degrade HDPE (Awasthi et al. 2017; Taghavi et al. 2021). The bio-fragmented MPs enter microorganisms through the cell membrane. The large monomers stay outside the microbial cells whereas small monomers move inside. Within the microbial cells, the monomers undergo oxidation which leads to energy generation used for biomass production (Lucas et al. 2008; Ru et al. 2020). MP biodegradability is largely affected by the factors like structural complexity, functional groups, morphology, polymer toughness, and bond strength (Klein et al. 2018). Biodegradability of MPs can be enhanced by combining MPs with several additives like nitric acid or pre-treating MPs with heat or UV (Montazer et al. 2018; Falkenstein et al. 2020). B. amyloliquefaciens degrades LDPE upon preliminary heat treatment by depolymerization reaction (Das and Kumar 2015). Similarly, B. safensis and B. mycoides degrades LDPE and HDPE upon pretreatment with 0.1% mercuric acid and sunlight respectively (Ibiene et al. 2013; Das and Kumar 2015). Microorganisms are known to adapt to varying environmental conditions including the pollution sites through a cascade of cellular and genetic pathways (Wani et al. 2022c). Microorganisms colonize surface of MPs which causes changes in mechanical properties like roughness, strength, and reduction in molecular weight (McGivney et al. 2020). The attachment changes hydrophobic MP surfaces into hydrophilic which makes them prone to degradation through the action of enzymes like tyrosinase, laccase, lipase, and peroxidase. For example, K. pneumoniae releases certain surfactants that mediate hydrophobic and hydrophilic phase exchange assisting in easy microbial penetration into PE for its degradation (Awasthi et al. 2017). Table 3 highlights the MP-degrading potential of microorganisms.

Table 3.

Microorganisms with MP-degrading potential isolated from different sites

Microorganisms	Sample	MP-type	MP- initial concentration (grams)	Weight loss (%)	Incubation period in days
Massilia sp. FS1903	Galleria mellonella gut	PS	0.15	12.97 ± 1.05	30 (Jiang et al. 2021)
B. siamensis	Waste disposal	LDPE	100	8.46 ± 0.3	90 (Maroof et al. 2021)
B. cereus	Landfill area	LDPE	0.13	1.53	120 (Zerhouni et al. 2018)
Pseudomonas sp.	Soil	Bisphenol-A	0.0001	54.6 ± 3.7	60 (Matsumura et al. 2009)
Lysinibacillus sp.	Soil grove	PE and PP	0.3 and 0.39	7.5 and 3	28 (Jeon et al. 2021)
Microbacterium paraaoxydans and P. aeruginosa	Pure cultures used	LDPE	0.25	61 and 50.5	60 (Rajandas et al. 2012)
Pseudomonas sp. and Rhodococcus sp.	Antarctic soil	PP	0.100	17.3 and 7.3	40 (Habib et al. 2020)
Rhodococcu sp.	Mangrove sediment	PP	0.500	6.4	40 (Auta et al. 2018)
Aspergillus tubingensis and A. flavus	Coastal area soil	HDPE	0.200	6.02 ± 0.1 and 9.34 ± 0.2	30(Sangeetha Devi et al. 2015)
Paenibacillus sp.	Landfill	PE	0.0147	11.6	90 (Bardají et al. 2019)
Lysinibacillus xylanilyticus and Aspergillus niger	Landfill	LDPE	0.300	8.9 and 17.4	63 and 126(Esmaeili et al. 2013)
Stenotrophomonas sp. and Fusarium sp.	Compost soil	Nylon	0.03	16 and 14	28 (Tachibana et al. 2010)
P. aeruginosa	Surface water	PE	0.80	6.25	30 (Mouafo Tamnou et al. 2021)
Dethiosulfovibrio sp.; Sporobacter sp., and Cupriavidus sp.	Marine litter and water	PVC	10	3.51 ± 0.81,3.71 ± 0.28, and 3.91 ± 0.2,	90 (Giacomucci et al. 2020)
Mycobacterium neoaurum	Soil	Dimethyl phenol	0.5	6.7	60 (Ji et al. 2020)

Enzymatic degradation of MPs

Owing to the presence of the homoatomic and heteroatomic backbone in plastics, MP degradation by microorganisms is an arduous process (Edmondson and Gilbert 2017). There is considerable weight loss in the plastic polymer with the action microorganisms but the process is significantly slower than chemically mediated biodegradation processes (Jaiswal et al. 2020). The polymer chains of MPs are broken by enzymes secreted by microbes (Mohanan et al. 2020; Lv et al. 2022; Kaur et al. 2022; Gaur et al. 2022). ATP-binding cassette transporters couple hydrolysis process to mediate the uptake and efflux of small fragments across the cell membrane in prokaryotic and eukaryotic cells. These transporters also play role in the secretion of toxins (Giuliani et al. 2011). Enzymatic actions like oxidation, hydrolysis, and hydroxylation cleave the MPs into monomers (Rana et al. 2022). The high molecular weight MPs are degraded first by extracellular enzymes and then incorporate into microbial cells (Urbanek et al. 2018). Within the microorganisms, the degraded MPs are catabolically channeled to yield energy for intracellular polymerization and integration into cellular structures (Müller et al. 2019; Rogers et al. 2020). Cutinase, an esterase sub-class, isolated from F. solani, Thermobifida fusca, T. alba, and T. cellulosilytica is effective in hydrolyzing polyester MPs (Ribitsch et al. 2012; Dong et al. 2020). Several studies have reported that PET degradation is mediated by PET hydrolases belonging to cutinases (Kawai et al. 2019; Furukawa et al. 2019; Carr et al. 2020). The enzymatic degradation of PET occurs either by surface modification of polyester fibers or polymer hydrolysis (Bååth et al. 2020). Several hydrolases have been reported to cause PET surface hydrophilization, such as lipases from Thermomyces sp., Candida antartica (Carniel et al. 2017), cutinases from Penicillium citrinum, Humicola insolens, and Saccharomonospora viridis (Liebminger et al. 2007), and carboxylesterases from T. halotolerans (Samak et al. 2020). PU degradation by membrane-associated (PudA) and extracellular (PueA, PueB) esterases isolated from Comamonas acidovorans, P.fluorescens, and P. chlororaphis has been characterized (Stern and Howard 2000). The blending of certain natural polymers like starch with synthetic MPs has been shown to increase the rate of MP-biodegradation (Vroman and Tighzert 2009). This is attributed to the rapid hydrolysis of starch making the MPs susceptible to microbial degradations. Karimi and Biria (2019) have reported LDPE degradation by the action of amylase when blended with starch. Currently, the least information on the enzymes acting on MPs with high molecular weight like PVC, PP, PS and polyamide is available. Even though mixed microbial communities have been reported to cause the weight loss of these MPs, the effectiveness of gene products is yet to be ascertained completely. Extreme environments are rich reservoirs of hydrolytic enzymes stable at fluctuating environmental conditions like temperature, pH, salinity, and pressure. The search for MP-degrading microorganisms and enzymes is already gaining research attention through metagenomic strategies. Table 4 gives an overview of the enzymes isolated and characterized from microbial sources with MP-degrading potential.

Table 4.

Enzymes derived from different microorganisms and their MP-degrading potential

MP-type	Enzyme	Microorganism	References
Biodegradable plastic	Esterase	Pseudozyma antartica	Sameshima-Yamashita et al. (2019)
HDPE	Peroxidase	Citrobacter sp.	Ojha et al. (2017)
LDPE	Laccase	Lysinibacillus sp.	Ghatge et al. (2020)
PE	Laccase	Rhodococcus ruber	Santo et al. (2013)
	Alkane hydroxylase	Pseudomonas sp.	Jeon and Kim (2015)
PET	PETase	Ideonella sakaiensis	Webb et al. (2013)
	Cutinase	Thermobifida fusca	Müller et al. (2005)
	Cutinase	Fusarium sp., and Humicola sp.	O’Neill et al. (2007); Ronkvist et al. (2009)
	MHETase	Ideonella sakaiensis	Yoshida et al. (2016)
	Oxidoreducase	Klebsiella pneumoniae	Peter Guengerich and Yoshimoto (2018); Kawai et al. (2019)
Polycaprolactone	Lipase	Alcaligenes faecalis	Oda et al. (1997)
Polycaprolactone and Polyhydroxybutyrate	Manganese peroxidase	Amycolaptosis sp. and Tremetes versicolor	Deguchi et al. (1998); Fujisawa et al. (2001)
Polyester	Polyesterase	Cyanobacteria sp.	Hajighasemi et al. (2018); Wani et al. (2021)
	Protease	P. fluorescens	Howard and Blake (1998)
	Serine hydrolase	Pestalotiopsis microspore	Russell et al. (2011)
Polylactic acid	Cutinase like enzyme	Cryptococcus sp.	Masaki et al. (2005)
PP	Monooxygenase	Rhodococcus sp.	Toda et al. (2012)
	Hydrolases	Rhodococcus sp. and Bacillus sp.	Auta et al. (2018)
PS	Hydrolases	Rhodococcus ruber	Mor and Sivan (2008)
	Styrene monooxygenase	Nocordia sp.	Jacquin et al. (2019)
	Isomerase, dehydrogenase, and monooxygenase	Micrococcus, Nocordia, and Bacillus	Jacquin et al. (2019); Danso et al. (2019)
	Cytochrome P4500s	Enterococcus sp.	Hou and Majumder (2021)
	Peroxidase, esterase, dioxygenase, and monooxygenase	B. paralicheniformis	Ganesh Kumar et al. (2021)
	Oxygenase	Exiguobacterium sp. RIT 594	Parthasarathy et al. (2022)
PU	Esterase	Alicycliphilus sp.	Oceguera-Cervantes et al. (2007)
	Lipase	Candida rugosa	Gautam et al. (2007)

Metagenomics (MGs): gateway to microbial and enzyme mining

Even though microorganisms are present everywhere in the environment, limitations in traditional culture techniques have crippled the exploration of vast microbial flora (Lewis et al. 2021). Microbiologists estimate that only 1–2% of the total microbial flora is culturable, which leaves the majority of the microorganisms unexplored. MGs offer an efficient lens to reveal the hidden microbial diversity in a culture-independent manner (Handelsman 2004; Wani et al. 2022d). Figure 3 highlights the fundamental methodology of the sequence- and function-based metagenomic approach for the exploration of microorganisms and gene products. The taxonomic profiling and functional gene annotation of microbial communities of river Ganga (sediment) using whole-genome MGs have also been done (Rout et al. 2022). Several other research groups have identified novel bacteria from different sites including extreme environments like hot springs, deserts, and deep-sea sediments for bioprospecting using a MG approach (Tang et al. 2018; Najar et al. 2020; Alotaibi et al. 2020; Zhu et al. 2022; Wani et al. 2022b). Global ocean sampling revealed about 40 million non-redundant novel genes from more than 30,000 species, whereas over 97% of the 150 million genes reported in topsoil globally cannot be found in the existing gene catalogue. This is a strong indicator that microbiomes carry huge functional potential, with unculturable microorganisms as acting enzyme reservoir (Sunagawa et al. 2015; Bahram et al. 2018). In a study, hidden Markov models were constructed from experimentally verified enzymes and mined soil and ocean metagenomes to assess the ability of microorganisms in degrading plastics. They compiled almost 30,000 non-redundant enzymes that were homologues with known enzymes having plastic degrading potential (Zrimec et al. 2021). Chow et al. (2023) present a sequence-based in silico strategy for screening and characterization of PETases from MG datasets. The MG screening of a novel PET esterase through in vitro expression system has also been developed using next-generation sequencing (Han et al. 2023). In a recent study, distinct microbial communities have been unveiled through MGs that degrade hydrocarbon chains, which are units of plastic polymers (Hauptfeld et al. 2022). Using 16S rRNA datasets obtained through MGs, the taxonomic and functional characteristics of PE-degrading microorganisms have been analyzed from one of the waste recycling sites in Tehran, Iran (Hesami Zokaei et al. 2021).

Fig. 3.

Metagenomic (MG)-driven search operation for MP-degrading microorganisms through function and sequence-based metagenomic approaches. The function-based approach is followed by random screening for different enzymes while the sequence-based approach ensures the prediction of several genes that are effective in producing MP-degrading enzymes

Integrated microbial genome (IMG) helps to identify candidate genes from different metagenomes (Zaidi et al. 2021). In a MG study, two heat-stable enzymes with application in plastic degradation were partially characterized (Danso et al. 2018). Shotgun MGs have revealed the microbial community response to plastic contamination in coastal environments (Pinnell and Turner 2019). Shotgun MGs generated 3,314,688 contigs (DNA sequences that overlap providing a contiguous representation of a genomic region) and 120 microbial genomes. This was followed by the functional gene annotation to identify microbiomes that harbor genes encoding esterases, lipases, and monooxygenases that are known to degrade different types of plastics (Radwan et al. 2020). Hu et al. (2021) reported hydrolysis of PET by a metalloprotease and a serine protease. The study provided intrinsic insight into PET degradation and opened a gateway for hunting more plastic-degrading enzymes. Bollinger et al. (2020), also characterized a novel polyester hydrolase from P. aestusingri for the degradation of synthetic PET. Table 5 highlights some of the abundant microbes and enzymes isolated and characterized from microorganisms through culture-based and sequence- and function-based MG approaches having MP-degrading potential. Even though the MP degradation by microorganisms and their gene products is effective, the rate of degradation has always been a matter of concern. MG investigation allows upscaling the degradation rate by modifying the microbial composition and genome engineering.

Table 5.

Sequence-based (SB) and function-based (FB) metagenomic approaches for the identification of abundant microbes and /or enzymes useful in targeting different plastic substrates

Microbes/enzymes	Metagenome source	Metagenome sequencing approach	Metagenome strategy	Target plastic substrate	References
Bryozoa, Cyanobacteria, Alphaproteobacteria, and Bacteroidetes	Sea water	Shotgun metagenomics	SB	Mixed plastic debris	Bryant et al. (2016)
Flavobacteriaceae, Methylophilaceae, Rhodobacteraceae, Planctomycetaceae, Nocardiaceae, and Verrucomicrobiaceae	Surface sea water	16S metagenomics (V4-V6 and V9)	SB	PS	Sekiguchi et al. (2009); Kirstein et al. (2019)
Rhodococcus sp. (YC-SY1, YC-BJ1, and YC-GZ1)	Soil	Illumina HiSeq 16S metagenomics (V3 + V4)	SB	Triphenyl phosphate (Plasticizer)	Wang et al. (2019b)
PET hydrolase	Marine water	Next-generation metagenome sequencing	FB	PET	Danso et al. (2018)
Thalassospiracea, Alteromonadaceae, Alcanivoraceae, and Vibrionaceae	Beach sediment	Meta-omics (16S metagenomic approach)	SB and FB	PET	Wright et al. (2021)
Proteobacteria, Firmicutes, Actinobacteria, and Firmicutes	Landfill soil	High throughput metagenomics	SB	PE and PS	Kumar et al. (2021)
Polyurethane esterase	Landfill	Shotgun metagenomics	FB	PU	Gaytán et al. (2019)
Cutinase	Compost	Shotgun metagenomics	FB	PET	Sulaiman et al. (2012)
Esterase	Seawater	Illumina Hiseq	FB	Polyhydroxybutyrate, and polylactic acid	Tchigvintsev et al. (2015)
Esterase	Compost	Shotgun metagenomics	SB and FB	PU	Kang et al. (2011)
Protease	Marine sediment	Bidirectional end sequencing	FB	Polyester	Lim et al. (2005); Sun et al. (2020)

Microbial manipulation

The manipulation of human, animal, soil, plant, and water microbiome is the contemporary strategy followed for increasing the benefits offered by them (Huynh et al. 2016; Hussain et al. 2018; Jochum et al. 2019). It includes several cellular, molecular, and chemical methods for extensive manipulation with higher specificity and magnitude. The prebiotic (chemical) approach enables modification in microbial communities to increase their adaptability and functionality in a particular environment (Gianoulis et al. 2009; Raes et al. 2021). Polysaccharides and oligosaccharides affect microbiome composition and support the growth of MP-degrading microorganisms (Grondin et al. 2017). Chitin, starch, lipopeptides, glycolipids, etc. help in biofilm formation by acting as surfactants on MP-surfaces (Shilpa et al. 2022). Similarly, probiotic cultures are applied for the better performance of MP-degraders through bioaugmentation (Kamilya and Devi 2022). The microorganisms like Pseudomonas, Micrococcus, Moraxella, Streptomyces, Thermoactinomyces, Penicillium, and Aspergillus are preferred over the native microorganism (Spini et al. 2018). Microbiome transplantation and probiotic bioaugmentation remain unsuccessful owing to the slow microbial growth, low cell viability, limited distribution, and reduced functionality. These issues are likely to be solved by metagenome engineering followed by bioaugmentation.

Microorganisms are genetically modified to produce novel strains that express unique and well-defined genetic determinants or to introduce genetic variants that cause phenotypic changes. The process is used to investigate the biotechnological potential linked to environmentally useful microorganisms and to make use of functional genes when put into the right host (Zeaiter et al. 2018). There have also been attempts to chemically alter marine microbes. Besides natural competence, wild-type and DNase-negative Vibrio cholerae strains are effectively electroporated and transformed by the researchers for biotechnological applications (Marcus et al. 1990; Jaskólska et al. 2018). Although the outcome of the electroporation can also be influenced by other parameters, including growth conditions, the pulse used, and the type of exogenous DNA, the electroporation efficiency is strain-dependent. Several marine strains from various genera, including Roseobacter, Vibrio, Pseudoalteromonas, Caulobacter, Cyanobacteria, and Halomona, have been successfully modified for the expression of environment-useful genes (Kivelä et al. 2008; Borg et al. 2016; Laurenceau et al. 2020).

Genetic engineering

With the progress in molecular biology and genetic engineering, the development of genetically modified microorganisms as potent MP degraders has advanced significantly. The construction of metagenomic libraries makes it likely to create genetic circuits with novel and precise functionalities (Bacha et al. 2021). The synthetic microbial cells created through genome editing, protein engineering, or genetic engineering can be employed for metagenome engineering in the plastisphere (Austin et al. 2018; Jaiswal et al. 2019). Since the biodegradation of MPs involves a cascade of oxidation processes which is difficult and slow by the action of single species (Klein et al. 2018). Metagenome engineering can be applied for complementing multiple genes involved in MP-degrading metabolic pathways. This will ensure the production of multiple enzymes that regulate biofilm formation and quorum sensing. Genome modification of B. subtilis and E. coli for the expression of PETase enzyme for the degradation of PET is a common example. PETase and MHETase have been identified in Ideonella sakaiensis 201-F6 and cloned in a suitable PUCIDT vector for the creation of recombinants with higher PET-degrading potential (Janatunaim and Fibriani 2020). Puspitasari et al. (2021) showed that the rate of PETase hydrolysis increases significantly in the presence of hydrophobin. Since the core metagenome of any site is constant, therefore, rather than modifying a single genome, it is possible to engineer the entire metagenome. The direct in situ metagenome engineering of microbial population is achievable through horizontal gene transfer of plasmid construct through genetic augmentation. The applicability of bacteriophages as gene-delivery agents is advancing. The strategy can very well be applied to the gene delivery with having MP-degrading potential. However, there is a growing concern about the release of genetically engineered microorganisms into the environment owing to their adverse effects. There are chances that engineered microorganisms may affect the biodiversity by creating more infectious pathogens, harm non-target species, and disrupt ecological balance (Lenski 1993; Clark 2006).

Metagenome analysis through computational tools

The development in computational tools and advancement of computational power has enormously aided in metagenome refinement and analysis. The sequencing of metagenome samples with the potential to degrade contaminants is a method of choice for identifying novel microorganisms and predicting genes. Shotgun MGs give insight into the microbial community members and the possible metabolic pathways mediated by them. Since metagenome collection from environments is largely uncontrolled, the organisms present in abundance are highly represented in sequence data. To achieve equal coverage of all the microbial members, the random shotgun sequencing resolves genomes uniformly and ensures the identification of lesser-presented organisms. The metagenome data is often enormous containing fragmented and raw data (Wooley et al. 2010). The metagenome sequencing of cow rumen generated more than 250 gigabases, while the gut microbiome of human-generated more than 550 gigabases of sequence data (Qin et al. 2010; Hess et al. 2011). Thus, the identification, collection, and curation of useful data from huge metagenome datasets are challenging for many researchers. Almeida et al. employed in silico screening method for the identification of potential PETase-like enzymes. They identified the PETase-like gene SM14est in streptomyces after analyzing more than 50 genomes (Almeida et al. 2019). Figure 4 represents the basic methodology of metagenome data analysis useful for understanding microbial diversity and predicting useful genes. One of the standalone metagenome analyzing tools is meta genome analyzer (MEGAN). It was initially used for studying metagenomes obtained from mammoth bone (Poinar et al. 2006). The tool is used to perform functional and taxonomic binning using the lowest common ancestor algorithm. More efficient, accurate, and faster computational tools are being developed to keep up the face with high-throughput sequencing. Metagenomic rapid annotations using subsystems technology (MG-RAST) is one of the biggest metagenome repositories developed for automatic phylogenic and functional analysis of metagenomes. Wani et al. (2022e) have comprehensively reviewed the maximum number of computational tools used in the analysis of metagenome data sets.

Fig. 4.

Basic methodology of the metagenome analysis through computational tools. The generated metagenome sequences are prefiltered for the removal of low-quality and redundant sequences using Eu-detect and DeConseq. To increase the analytical efficiency of computational tools, the metagenome assemblies are developed using Phrap or Celera or MEGAHIT assembler. This is followed by the prediction of genes using the MEGAN or Gene Mark or Gene Locator and Interpolated Markov Modeler (GLIMMER) program. Function-based annotation and taxonomic profiling are carried out MetaPhlan or Automatic phylogenomic inference application (AMPHORA) or Metaphyler followed by integration into MG-RAST, Integrated Microbial Genomes and Metagenomes (IMG/M) and Genomic Encyclopedia of Bacteria and Archaea (GEBA) like tools

Limitations and way forward

MG-based studies allow the exploration of microbial diversity, genetic evolution, species composition, and bioprospecting. However, bottlenecks in MGs right from sample collection until the analysis have always been challenging (Scholz et al. 2012). Sample collection is one of the confounding factors that affect the sequencing outcomes owing to concerns like contamination, transportation, storage, and safety. The developments in sequencing technology have significantly advanced computational tools for functional annotations and analysis (Bharti and Grimm 2021). However, multiple challenges still exist owing to the complexity of metagenomic data. While analyzing the complex metagenome data sets, challenges like multiple genomes and inter- and intra-genomic repeats lead to uneven sequencing with a higher degree of sequencing errors. Although the gene prediction tools have an efficiency of about 90%, the small number of genes escaping detection can be novel and more useful (Coleman and Korem 2021). Downstream processing of MG data is also much crucial for understanding microbiome structures and metabolic pathways, but due to multivariate metagenomic data, the downstream analysis is difficult (Lindgreen et al. 2016). The discovery of enzymes is prevented by other limitations like limited thermostability, low stereoselectivity, and insufficient expression. Ribosome engineering can be useful in retrieving all possible candidate genes for synthesis and testing the activities (Uchiyama and Miyazaki 2009). Fungi despite their affinity for plastics have been largely neglected. MG findings provide evidence that the plastisphere is a suitable niche for various fungal organisms, including pathogenic species (Gkoutselis et al. 2021).

The technical glitches and problems in data evaluation and interpretation confronted during metagenome studies can be overcome by the combination of MGs and machine learning tools like artificial intelligence (Rhoads 2020; Wani et al. 2022f). This will help in the accurate and timely characterization of microorganisms and microbial products useful in remediation processes. Artificial intelligence can be utilized in developing new models to design effective bioremediation tools and evaluate the performance and functionality of microorganisms. The development of smart biomarkers as indicators of pollution is an efficient way to track environmental fluctuations (Krishna Kumar et al. 2011). Moreover, gene engineering within genomes and metagenomes using gene-editing tools like clustered regular interspaced short palindromic repeats-associated protein (CRISPR-Cas) system can revolutionize the microbe-mediated degradation processes owing to its specific nature (Jaiswal et al. 2019; Wani et al. 2022g; Mir et al. 2022). This will help to upregulate contaminant-degrading genes and pave way for understanding the molecular pathway involved in it. The applicability of artificial intelligence environmental and genome editing for microbial simulation will continue to be the method of choice in combatting plastic and other pollution.

Conclusion

The emergence of MP-contamination has become a serious concern for the biota owing to the small size and their ability to reach into the human body through secondary sources like food. Moreover, research investigations and evidence based on the ecological toxicity of microplastics to aquatic biota revealed numerous toxic effects on organisms, posing serious ecological risks. The hazardous effect of microplastic is outlined as single and combined toxicity of various pollutants, which has reportedly impacted mortality rates, development, food intake capacity, reproductive capability, and gene expression in aquatic organisms. Considering the degradation potential of microbes and enzymes, it is possible to detoxify and degrade MPs into non-toxic end products. Thus, it is necessary to explore microorganisms that can mediate the bioremediation process of these MPs. MGs is a powerful genome-centric culture-independent technique to identify novel microorganisms and their products for bioprospecting including the degradation of environmental contaminants. MGs with other meta-omics strategies can be useful in building a timely response strategy for combatting the growing plastic threat and its associated concerns. Overall, MGs have enabled scientific studies of complex microbiomes, which have assisted to explain certain metabolic processes of polymer degradation. As a result, extensive research in this area is required, which may significantly reduce global plastic pollution while also ensuring the health of future generations.

Author contribution

Atif Khurshid Wani: conceptualization, methodology, visualization, data curation, writing—original draft, writing—review & editing. Nahid Akhtar: methodology, visualization, data curation, writing—original draft, writing—review & editing. Nafiaah Naqash: visualization, data curation, writing—original draft, writing—review & editing. Farida Rahayu: data curation, writing—original draft, writing—review & editing. Djajadi Djajadi: data curation, writing—original draft, writing—review & editing. Chirag Chopra: data curation, writing—original draft, writing – review & editing. Reena Singh: visualization, data curation, writing—original draft, writing—review & editing. Sikandar I. Mulla: writing—original draft, writing—review & editing. Farooq Sher: writing—original draft, writing—review & editing. Juliana Heloisa Pinê Américo-Pinheiro: conceptualization, methodology, visualization, data curation, writing—original draft, visualization, writing—review & editing, supervision, project administration.

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Competing interests

The authors declare no competing interests.