The widespread utilization and inadequate management of plastic products have contributed to a significant increase of microplastics (MPs) in natural environments. MPs persist in the environment and are resistant to degradation. However, certain microorganisms possess the ability to degrade them. This study focuses on the in silico identification and molecular docking analysis of different lipases found in various fungal species, specifically aiming to assess their catalytic potential for microplastic degradation. In addition to observing enzyme-substrate interactions at the active site, hydrophobic interactions, highest binding affinity and hydrogen bonds were also examined. A total of 71 lipases were identified from 13 fungal species on the basis of presence of the lipase 3 domain. Most of the proteins were predicted to be extracellularly localized. Based on the results of molecular dockings, in terms of binding affinities, polycarbonate (PC) was found to have the highest binding affinities with all the docked proteins which suggests that it is the most biodegradable plastic type. However, polyvinyl chloride (PVC) exhibited low binding energies with all the lipases indicating its resistance against degradation via fungal lipases. Key amino acids involved in binding interactions of PC were found to be glycine, alanine and valine. The binding interactions encompass hydrogen bonding, Van der Waals forces and Pi-interactions. These findings highlighted the potential of enzymes sourced from fungal species for microplastic degradation purposes. The role of lipase in the germination of A. oryzae was also predicted under soy sauce koji fermentation. It was found that 4 proteins were upregulated whereas 4 proteins were downregulated.
Research Article
Genome-Wide Identification and Characterization of Lipases from Ascomycetes, and Molecular Docking Analysis with Various Plastics
https://doi.org/10.21203/rs.3.rs-3951591/v1
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Microplastics
Lipase
Degradation
Enzyme
Binding Interactions
Extracellular
Microplastics (MPs) are small, solid, synthetic plastic particles with a size between 1 µm and 5 mm. Both regular and atypical forms are possible for these water-insoluble particles (Frias & Nash, 2019). These are categorized as primary and secondary MPs. Primary MPs are produced intentionally for using in personal care products, cleansing agents, cosmetics and drug vectors (Xiang et al., 2022), whereas secondary MPs are generated as a result of the degradation of larger plastic pieces due to environmental effects including temperature and UV rays (Hernández Fernández et al., 2022). Extensive use and poor management of plastic products have resulted in an increased amount of MPs in natural habitats (Xiang et al., 2022). Microplastic contamination is found in freshwater, terrestrial, atmospheric, marine ecosystems and this continuous accumulation of MPs in diverse ecosystems is posing a global threat (Miri et al., 2022).
MPs, due to their negative impact on the environment have attracted increasing interest from the scientific community (Lin et al., 2022). Polyethylene (PE), polyurethane (PU), polyamide (PA), polypropylene (PP), polystyrene (PS), and polyethylene terephthalate (PET) are the most common types of MPs found in the ecosystem (Fan et al., 2022). The presence of these MPs causes a significant change in the structure, activity, functioning and size of the soil microbiome and has a negative impact on the growth of plants (Zang et al., 2020). MPs have been found to directly interfere with plant chlorophyll a / chlorophyll b ratio balance, modify water holding capacity and soil bulk density and negatively impact plant rooting potential. Blockage of root pores and seed capsules by MPs hinder plant growth. By the modification of dominant microflora present in the soil, or by alteration of genes and enzymes linked to N/C/P cycles, MPs may also disrupt the soil nutrient cycling (Huang et al., 2022). Since MPs are persistent in nature, they are not easily degraded, but some microorganisms are capable of degrading them using enzymes (Yuan et al., 2020).
Microbes are the best candidates for plastic waste minimization in the environment as they produce specialized enzymes, allowing them to consume plastic as a source of energy (De Jesus & Alkendi, 2022). Extracellular enzymes like lipases, laccases, lignin peroxidases, esterases and manganese peroxidases, are crucial for plastic degradation, as they contribute to the increased hydrophobicity of the polymer via conversion of functional groups such as carbonyl and alcohol groups, which facilitates the attachment of the microbes to the plastic surface and promote further degradation of the polymer (Shahnawaz et al., 2019). Lipases are a class of hydrolase enzyme family that act on the surface of plastic and break it down into smaller molecules (Sol et al., 2020). In chemical groups or the side chains of plastic polymers, there are specific bonds where these enzymes attach and enhance cleavage during the process of biodegradation. Due to their size, their diffusion in the polymer structure does not occur and the degradation only occurs on the surface of the polymer (Miri et al., 2022).
Fungi are particularly interesting candidates for plastic degradation as they offer a wide variety of enzymes with a focus on the breakdown of recalcitrant substances (Temporiti et al., 2022). Species belonging Genus Aspergillus, Alternaria, Candida, Geotrichum, Penicillium, Humicola, Acremonium, Fusarium, Rhizopus and Mucor are the main fungi that produce lipase (Chandra et al., 2020). Lipases produced by fungi have a striking ability to degrade PET by acting on the ester bonds of the polymer (Carr et al., 2020). Lipases produced by Candida antarctica (CALB) (de Castro et al., 2017) and Aspergillus oryzae CCUG 33812 (Wang et al., 2008) are the well-studied lipases that are involved in PET degradation. Yeasts belonging to the Candida species are the principal producers of lipases that are involved in the hydrolytic breakdown of PU (Temporiti et al., 2022). It has been reported that Aspergillus tubingensis is capable of PU degradation via the production of lipase and esterase (Khan et al., 2020).
Natural enzymes have been demonstrated to have the capacity to catalyze the hydrolysis of MPs as an eco-friendly substitute for chemical recycling techniques (Wei Zimmermann, 2017, Xiang et al. 2023). These enzymes are found in a variety of saprotrophic organisms, such as bacteria and fungi (Dimarogona et al. 2015; Fecker et al. 2018). Microbial species frequently live in environments that are rich in plant-based organic matter or plastic waste, which, when necessary, can be used as the primary carbon source for cell growth activities. The synthesis of these enzymes, which break down the MPs into simpler molecules, enables the breakdown of MPs by these microbes. In this study, an in silico examination of several MP compounds' binding affinities to the lipase enzyme of diverse fungal strains were carried out. The binding free energy values of the compounds were used to assess the enzyme selectivity of the MPs. The results of this investigation would considerably improve our understanding of how the enzyme lipase affects the selected MPs.
Overall methodology has been described in Fig. 1.
2.1. Identification of Lipase genes in Fungal species
A total of 17 different fungal species were included in this study, with 8 of these species having genome assembly data available up to the chromosome level, while remaining species had genome assembly data available at the scaffold level. The protein FASTA files of the fungi were retrieved from the latest genome assembly accessible on NCBI (http://https://www.ncbi.nlm.nih.gov/), to serve as a local database for performing protein BLAST (BLASTp). The species along with corresponding genome assembly level and assembly accessions are provided in Table 1. Additionally, 5 already reported protein FASTA sequences of lipase were also retrieved from NCBI, from Aspergillus flavus, Aspergillus oryzae, Talaromyces marneffei, Paeciloyces variotii, Rasamsonia emersonii, to be further used as query sequences for the identification of lipase genes in the selected fungal species. BLASTp was done using BioEdit tool, utilizing BLOSUM62 matrix and setting the E-value threshold to 10. All the BLAST hits (not previously reported) were checked for the presence of lipase 3 domain (Pfam: PF01764) using the Pfam server (https://pfam.xfam.org/).
| Genus | Species | Genome Assembly Accession | Genome Assembly Level |
|---|---|---|---|
| Botrytis | Botrytis cinerea | GCF_000143535.2 | Chromosome |
| Fusarium | Fusarium oxysporum | GCF_000149955.1 | Chromosome |
| Fusarium fujikuroi | GCF_900079805.1 | Chromosome | |
| Fusarium mangiferae | GCF_900044065.1 | Scaffold | |
| Aspergillus | Aspergillus oryzae | GCF_000184455.2 | Chromosome |
| Aspergillus flavus | GCF_014117465.1 | Chromosome | |
| Aspergillus terrus | GCF_000149615.1 | Scaffold | |
| Aspergillus tubingensis | GCF_013340325.1 | Scaffold | |
| Aspergillus fumigatus | GCF_000002655.1 | Chromosome | |
| Aspergillus niger | GCF_000002855.3 | Scaffold | |
| Penicillium | Penicillium oxalicum | GCF_001723175.1 | Scaffold |
| Chaetomium | Chaetomium globosum | GCF_000143365.1 | Scaffold |
| Trichoderma | Trichoderma harzianum | GCF_003025095.1 | Scaffold |
| Cryphonectria | Cryphonectria parasitica | GCF_011745365.1 | Scaffold |
| Geotrichum | Geotrichum candidum | GCA_013365045.1 | Scaffold |
| Nefusicoccum | Nefusicoccum parvum | GCF_000385595.1 | Chromosome |
| Alternaria | Alternaria alternata | GCF_001642055.1 | Chromosome |
2.2. Multiple Sequence Alignment and Phylogenetic Analysis of Fungal Lipases
Multiple Sequence alignment of protein sequences of the 2 identified lipases per fungal specie was done using ClustalW in MEGA11 (Tamura et al., 2021). Results of multiple sequence alignment were then visualized via Jalview (version 2.11.2.7; (Waterhouse et al., 2009). The alignment results were then used for the generation of phylogenetic tree using the Neighboring method (NJ) with 10000 as bootstrap value in MEGA11. The phylogenetic tree was visualized and further optimized using the iTOL webserver (https://itol.embl.de/).
2.3. Motif Analysis of Fungal lipases
Motif identification in the proteins sequences of identified lipases was done using MEME (Multiple Em for Motif Eliciation) web server (https://meme-suite.ord/meme/).
2.4. Physiochemical Properties and Subcellular Localization of Identified Lipases
The physiochemical properties of the identified lipases, including molecular weight, isoelectric point (pI), instability and aliphatic index were assessed using the ProtParam-ExPASy webserver (https://web.expasy.org/protparam/). For the prediction of the subcellular localization of enzymes, WoLF PSORT (https://wolfpsort.hgc.jp/) was used.
2.5. Structure Prediction of Lipase Enzyme
Tertiary structure prediction was limited to the lipases that were predicted to have extracellular localization. Structure Prediction was done using SWISS-MODEL (https://https://swissmodel.expasy.org/interactive/). All the predicted models for each enzyme sequence, were evaluated for selection of the best model based on the Qmean score using QMEAN SWISS-MODEL server (https://swissmodel.expasy.org/qmean/) and ERRAT value and Ramachandran plots via PROCHECK using the SAVES v6.0 UCLA server (https://saves.mbi.ucla.edu/). The PDB structures of the enzymes were then used for docking analysis.
2.6. Retrieval of Plastic Compounds Structures
In this study, 5 different types of plastics were used including polyethylene terephthalate (PET), polycarbonate (PC), polypropylene (PP), polystyrene (PS), polyvinyl chloride (PVC). Structures of the plastic compounds were obtained from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/). The 3D structure data files were downloaded in the SDF format and then converted into MOL2 using Open Babel version 3.1.1. The MOL2 files were then used for molecular docking.
2.7. Molecular Docking of Fungal Lipase with Plastics Compounds
Docking of the enzymes with all five plastic compounds was done using AutoDock Vina in PyRx version 0.8. Blind docking of the plastic compound with the enzyme was done to allow the ligand to freely explore and interact with potential binding sites where the binding energy is minimum.
2.8. Visualization of docking results
Binding interactions between the enzyme and plastic compounds were visualized using Biovia Discovery Studio 2021. The highest binding affinity according to each plastic type with enzymes from each specie were visually analyzed and for each specie, the plastic with best binding affinity was visually represented.
2.9. Differential expression analysis of lipase genes of A. oryzae
RNA sequencing data for A. oryzae (Illumina HiSeq 2500) from the public database NCBI GEO (https://www.ncbi.nlm.nih.gov/geo/query), were collected. The A. oryzae strain was cultured at 30°C for 3–4 days on potato dextrose agar (PDA) plates. Subsequently, spores were harvested and suspended in autoclaved water to create an aqueous conidia suspension (ACS) at a concentration of 108 spores/ml, which was stored at 4°C. For koji production, soybeans were soaked, steamed, mixed with wheat flour, and inoculated with the prepared ACS. Koji fermentation occurred at 30°C for approximately 72 h at ≥ 85% humidity, encompassing three distinct stages: mycelia expansion (ME), early sporulation (ES), and mature sporulation (MS).
In terms of data analysis, we utilized RStudio 3.5.1 (Team, 2010) for differential expression analysis. Sequence read archive (SRA) files were imported and converted into FASTA format. Quality assessment was performed using FASTQC, followed by sequence preprocessing using Cutadapt, with a minimum length and quality cut-off set at 20 nucleotides. RNA STAR was employed for normalization and differential gene expression analysis. Genes lacking significance were filtered out based on an adjusted p-value threshold of 0.05 and an absolute fold change (FC) threshold of > 2. Differential expression patterns were visually represented through volcano plots generated in RStudio 3.5.1 (Team, 2010), with a specific focus on highlighting differentially expressed catalase genes.
3.1. Identification of Lipase in Fugal Species
Based on the presence of enzyme specific domain i.e., the lipase 3 domain, a total of 71 genes were identified in only 13 from a total of 17 fungal species. All of the identified proteins were not reported previously. No lipase genes were identified from the following four species: Neofusicoccum parvum, Alternaria alternata, Aspergillus fumigatus and Aspergillus niger. The identified genes were renamed using a custom naming convention, utilizing the species name (2 letters, initial of genus and initial of specie), followed by protein name (2 letters) and a sequential number (last digit). This approach enhances convenience and allows easy identification as well as organization of the genes. The identified lipase genes, along with their respective attributes are presented in Supplementary Table S1.
3.2. Multiple Sequence Alignment and Phylogenetic Analysis
The results of multiple sequence alignment demonstrated consistent domain patterns and conserved amino acid residues. The active site, characterized by a conserved sequence of catalytic residue (G-X-S-X-G), was observed across all fungal lipases except Foli6, FfLi2, CgLi1 and CgLi7. Alignment showing the catalytic residue is represented in Fig. 2. The phylogenetic tree, represented in Fig. 3, resulted in the formation of 7 distinct groups, highlighting their distribution and evolutionary relationships.
3.3. Motif Analysis in Fungal Lipases
Conserved motifs in the identified lipases were detected through the MEME web server and are represented in Fig. 4. A collective of 5 motifs were identified across all proteins. From the results it can be observed that Motif 1 which is part of the lipase domain, is present in all proteins except CgLi1 and CgLi7. Whereas motif 2, 3 and 5 exhibited a prominent presence in a significant proportion of proteins. Motif 4 was present only a few sequences.
3.4. Physiochemical Properties and Subcellular Localization
The physiochemical properties of lipases identified from all 13 species were assessed. Supplementary Table S2, provides a comprehensive overview of the physiochemical properties of the identified fungal lipases. The results revealed significant variation in the molecular weight of lipase across different fungal species, ranging from 27.58 kDa (kilodaltons) to 129.00 kDa. Among a set of 71 lipases analyzed, the isoelectric points (pI) of 54 lipases were predominantly observed in the acidic range, signifying acidic nature of these proteins. Additionally, 11 proteins demonstrated pI values in the basic range, suggesting a basic character for these enzymes. Furthermore, a subset of six proteins exhibited slight alkalinity, with pI values ranging between 7.15 to 7.69. Out of a total of 71 proteins analyzed, 37 proteins demonstrated stability, as evidenced by an instability index of less than 40. In contrast, 34 proteins had an instability index higher than 40 implying a higher likelihood of instability. An indicator of protein stability is the instability index, with values above 40 indicating a higher probability of instability. The thermal stability of proteins can be inferred from a high aliphatic index (> 40%). All identified proteins demonstrated high thermal stability based on the aliphatic index, however, AteLi3 and FoLi4 were found to be most stable.
The subcellular localization analysis was conducted to predict the cellular distribution of all identified lipases from 13 fungal species, illustrated in Fig. 5. While most of the enzymes were predicted to be localized extracellularly, some exhibited a distant localization within the mitochondria and the cytosol. Extracellular localization of these proteins facilitates there in vitro extraction, eliminating complexities associated with the extraction method of intracellularly localized proteins.
3.5. Structure Prediction
The best model among the predicted ones was selected, based on the Qmean score, ERRAT value and Ramachandran plots, for each enzyme. The protein model files are given in Supplementary file S3 the ERRAT values for each model and Ramachandran plots are given in Supplementary file S4.
3.6. Results of Molecular Docking
The potential for microorganisms to break down the plastic that pollutes our environment has raised interest in the fundamental process by which microbes can break down this extremely durable polymer. Due to the presence of various enzymes in these microbes, including fungi and bacteria, have been found to possess pathways for degrading polyester. The development of these enzymes as bioremediations for environmental plastic debris depends on the validation of these enzymes. In this work, 45 lipase enzymes from 12 fungal species, that have been known to break down plastics and are predicted to be extracellular, were docked against 5 plastic compounds in an effort to foretell the likelihood that the plastic compounds would biodegrade. Since the active site pocket between the polymeric compounds and the enzymes was unknown. Therefore, blind docking was used. The highest binding affinity, hydrophobic interactions and hydrogen bonds were all examined in addition to looking for active site contact between the enzyme-substance complexes. This is done to compare and provide a clearer understanding of how the examined enzymes degrade. Figures 6 and 7 shows the docking visualization results of only one enzyme per specie with the plastic with which it has highest binding affinity. Table 2 shows the best binding affinities of enzymes from all species and plastic compounds. The binding energies of all the enzymes against all plastic compounds are given in Supplementary Table S5. Notably, PVC has the least score (Table 2), indicating that the enzymes have a lower affinity to bind with this compound. Whilst polyethylene and polycarbonate showed the maximum affinity to bind the lipase (Table 2). This is in line with the findings of (Enyoh et al. (2022), who also discovered that plasticized PVC composites had a low biodegradation yield. This behavior might be explained by a minor cross-linking reaction that takes place during the extrusion process, which makes it extremely unlikely for aqueous enzymes to access the polymers (Baldera-Moreno et al., 2022).
Table 2 Binding Affinity of Plastic Compounds with Lipase from Fungal Species
The 2D and 3D docking visualization results of Aspergillus flavus lipase against PC are illustrated in Fig. 6 (A). The binding affinity of enzyme with each plastic compound is shown in Table 2. Binding Affinity scores were observed to be in the following order, PC (-7.2) > PET (-7) > PS (-5.9) > PP (-4.8) > PVC (-2.7). The more negative binding affinity score, the stronger the binding is between the protein and ligand. This indicates a greater probability of degradation of the plastic compound. Results indicate that among all plastic compounds, PC had the highest binding affinity score including 5 Van der Waals interactions, 2 Pi-Sigma and Pi-Alkyl interactions. Whereas PVC had the least binding affinity.
Docking results of PET against lipase from Aspergillus oryzae are visually represented in both 2D and 3D formats in Fig. 6 (B). The binding affinity of enzyme with each plastic compound is shown in Table 2. The binding affinity scores were observed in the following order PET (-7.8) > PS (-6.3) > PC (-6.9) > PP (-4.8) > PVC (-2.4). From the results it was observed that, PET showed the highest binding affinity score with 3 conventional hydrogen bond interactions, 9 Van der Waals interactions, 1 Pi-Pi Stacked and 1 carbon-hydrogen bond.
The docking outcomes of lipase from Aspergillus terreus and PC through 2D and 3D visualization representations are shown in Fig. 6 (C). The binding affinity of enzyme with each plastic compound is shown in Table 2. The binding affinity scores follow the order: PC (-7.8) > PET (-6.5) > PS (-5.5) > PP (-4.4) > PVC (-2.4). Based on the results obtained, it was observed that PC has the highest binding affinity score and the binding interaction between PC and lipase is characterized by 2 conventional hydrogen bonds, 4 Pi-Alkyl interactions, 1 Pi-Pi stacked interaction and 4 Van der Waals interactions.
Both the 2D and 3D visualizations were used to represent the docking outcomes of PC against lipase from Aspergillus tubingensis as illustrated in Fig. 6 (D). The binding affinity between the enzyme and the plastic compounds is represented in Table 2. By comparing the binding affinity scores, observed order is PC (-6.4) > PET (-6.2) > PS (-5.1) > PP (-4.7) > PVC (-2.4). It was evident that PC demonstrates the most favourable binding affinity score compared to other plastic compounds. Whereas PVC demonstrated the least favourable binding affinity score. The interaction between PC and lipase revealed intriguing findings including 4 polar interactions (conventional hydrogen bonds), 2 hydrophilic Van der Waals interactions and 1 Pi-Alkyl and 1 Alkyl interaction.
The 2D and 3D visual representation, illustrating the docking results between lipase identified in Botyrtis cinerea and PC are shown in Fig. 6 (E). Table 2 provides information on the binding affinity of the enzyme with each plastic compound. The binding affinities listed from highest to lowest are: PC (-6.4) > PET (-6.1) > PS (-5.6) > PP (-4.3) > PVC (-2.4). These computational results suggested that PC exhibited a strong propensity to bind to the enzyme and thus has a greater probability of being degraded by it. Additionally, the docking analysis identifies specific molecular interactions that characterize this binding phenomenon. Notably, PC was found to be engaged in 2 polar conventional hydrogen bond interactions, 1 Pi-Alkyl, and 9 can der Waals with the enzyme. These anticipated interactions provide valuable insights into the potential binding strategies and intermolecular forces that govern the formation of plastic-enzyme complex.
A comprehensive 2D and 3D visualization of the docking results between lipase identified in Chaetomium globosum and PC are presented in Fig. 6 (F). The binding affinities between the enzyme and plastic compounds are presented in Table 2. The relative binding affinity scores follow the order: PC (-7.1) > PET (-6.3) > PS (-5.5) > PP (-4.3) > PVC (-2.5). These results indicate that PC, having the highest binding affinity score, has a greater likelihood of being recognized and degraded by the enzyme. Specific molecular interactions identified in the PC-enzyme complex include: 9 Van der Waals interactions 3 Pi-Alkyl and 2 Pi-Sigma interactions.
Comprehensive 2D and 3D visualization are employed to effectively represent the docking outcomes of the plastic compounds against the lipase identified in Cryphonectria parasitica, Fig. 7 (A). The binding affinity of enzyme with each plastic compound. In terms of binding affinity, compounds can be arranged in the following order PC (-6.6) > PET (-5.8) > PS (-4.8) > PP (-4) > PVC (-2.3), Table 2. The results demonstrate that PC have the highest binding affinity score, indicating its strong potential for effective binding with lipase and hence greater probability of degradation. The PC-lipase complex is characterized by the presence of 4 Van der Waals interactions, 3 conventional hydrogen bond interactions and Pi-interactions including 2 Pi-Sigma and 1 Pi-Alkyl. These diverse intermolecular forces significantly enhance the stability as well as the strength of the binding between PC and lipase.
Visualization of the docking results of PC against lipase identified in Fusarium fujikuroi are represented in Fig. 7 (B). Table 2 presents the binding affinities of the enzyme with the plastic compounds. The descending order of binding affinity scores is: PC (-6.6) > PET (-6.3) > PS (-5.7) > PP (-4.2) > PVC (-2.6). It is evident from the docking results that PC has the highest binding affinity with lipase compared to other plastics, indicating a greater driving force for the formation of stable binding with it. PC displays the presence of 1 conventional hydrogen bond, 4 Van der Waals interactions, 2 Pi-Alkyl and 1 Pi-Sigma interactions.
The 2D and 3D visualizations are employed to effectively represent the docking outcomes of PC against lipase identified in Fusarium mangiferae, Fig. 7 (C) the binding affinities of the enzyme with plastic compounds are presented in Table 2. In terms of decreasing binding affinity, the plastic compounds can be arranged in the following order: PC (-6.7) > PET (-5.6) > PS (-5.5) PP (-4.6) > PVC (-2.5). The observed outcomes highlight PC as the compound with the highest binding affinity towards the enzyme suggesting a greater likelihood of it being degraded effectively by the enzyme owing to the more stable and stronger binding interaction. The binding is characterized by the presence of 8 Van der Waals interactions and 1 Alkyl interaction.
The results of docking of PC against lipase identified in Fusarium oxysporum are represented in 2D and 3D visualization in Fig. 7 (D). Binding affinities of lipase with each plastic compound are given in Table 2. Binding affinities, listed from highest to lowest, are: PC (-6.8) > PET (-5.9) > PS (-5.1) > PP (-4.5) > PVC (-2.6). Based on the observed outcomes, PC emerges as the plastic compounds with highest binding affinity towards the enzyme, implying a higher probability of effective degradation by the enzyme. The key interactions involved in this binding are 1 conventional hydrogen bond, 11 Van der Waals interactions, 3 Pi-Alkyl and Alkyl interactions.
Detailed 2D and 3D visualization of docking results of PC against lipase identified in Geotrichum candidum are illustrated in Fig. (E). The binding affinity values of enzyme with each plastic are provided in Table 2. In terms of binding affinities, the compounds can be arranged in the following order: PC (-6.8) > PET (-6.4) > PS (-5.7) > PP (-4.7) > PVC (-2.4). From the results, it can be observed that PC has the highest binding affinity, suggesting a greater likelihood of effective degradation by the enzyme. Notably interactions involved in this binding include 6 Van der Waals interactions, 3 Pi-Alkyl and Alkyl interactions and 1 Pi-Sigma interaction.
The docking results of PC against lipase identified in Trichoderma harzianum are illustrated through 2D and 3D visualizations as can be seen in Fig. 7 (F). The value for binding affinities of enzyme with each plastic is given in Table 2. PC has the highest binding affinity with the enzyme among all the plastic compounds. PC demonstrates presence of 1 conventional hydrogen bond, 6 Van der Waals interactions and 1 Pi-Sigma, and 1 Alkyl interaction.
3.7. Differential expression analysis of lipase genes of A. oryzae on soy sauce koji fermentation
RNA-sequencing analysis of A. oryzae under soy sauce koji fermentation was performed using the RStudio 3.5.1 (Team, 2010) to have insights about the possible role of lipase in the germination of A. oryzae. RStudio 3.5.1 (Team, 2010) was used to analyze up-regulated, down-regulated and no-regulated lipase genes in soy sauce koji fermentation, given in Supplementary File S6. Volcano plot showed the differential gene expression as shown in Fig. 8. Among the 270 proteins of A. oryzae genes, four hypothetical proteins i.e., AORIB40019695, AORIB40019223, AORIB40019694, and AORIB40002623, were found down regulated in soy sauce koji fermentation. Similarly, four hypothetical proteins (AORIB40015147, AORIB40015148, AORIB40015149, AORIB40031096, and AORIB40027858) were found up-regulated in soy sauce koji fermentation.
Microplastic pollution poses a significant threat as these small, solid plastic particles, are increasingly accumulating in agricultural environments, leading to a wide range of detrimental effects on both the agricultural ecosystem and the well-being of individuals relying on agricultural products (Gondal et al., 2023; Leed & Smithson, 2019). The presence of microplastics (MPs) in agroecosystems raises urgent concerns that demand attention and sustainable solutions to mitigate the potential long-term consequences on agricultural sustainability and human welfare (Mihai et al., 2021).
Harnessing the enzymatic prowess of microbes, particularly fungi, emerges as a promising strategy to counter the mounting threat of MP pollution. Fungi's capacity to produce a diverse range of enzymes, lipases, in particular, play a crucial role in breaking down the surface of plastics into smaller molecules, facilitating further degradation (Bacha et al., 2021), positions them as valuable agents in breaking down plastic polymers effectively (Cai et al., 2023) (Amobonye et al., 2021). This eco-friendly approach not only showcases the adaptability and efficiency of fungi but also underscores their potential in safeguarding the ecological balance by mitigating the detrimental effects of MPs on the environment. Integrating microbial solutions into environmental restoration initiatives offers a sustainable path forward in addressing this pressing issue.
In this study, we harnessed the power of computational analysis, specifically employing an in-silico approach. Our primary objective was to discern and characterize lipase genes within a selection of 13 diverse fungal species, employing the presence of the Lipase3 domain as our key criterion. Through this meticulous computational screening, we unveiled a total of 71 novel lipase genes, a discovery that significantly enriches our comprehension of the wide-ranging diversity inherent in fungal lipases. The significance of our in-silico methodology lies in its ability to offer a swift and cost-effective means of sifting through vast and complex genomic datasets. By sifting through the genetic data of multiple fungal species, this approach enabled us to efficiently pinpoint lipases that exhibit promising attributes for the biodegradation of MPs. This analytical strategy capitalizes on the vast information encoded within genomes, allowing us to make highly targeted selections of candidate enzymes. These enzymes are specifically chosen for their potential to fulfill the desired characteristics required for the effective degradation of MP pollutants, thereby advancing the field of environmental biotechnology in the quest to address the pressing issue of MP pollution.
To unravel the functional intricacies and potential substrate preferences of the lipases we identified, a comprehensive suite of analytical techniques was employed. Our investigative arsenal included multiple sequence alignment, phylogenetic analysis, and motif analysis, collectively shedding light on the molecular attributes of these enzymes. Multiple sequence alignment, a foundational element of our analysis, disclosed an intriguing revelation: the prevalence of a highly conserved catalytic triad, typically denoted as G-X-S-X-G, across the majority of fungal lipases. This remarkable conservation underscores a shared mechanism intrinsic to their catalytic activity, a mechanism with promising implications for plastic degradation. The catalytic triad's well-established role in facilitating hydrolysis reactions within lipases further bolsters our confidence in these identified fungal lipases' potential contributions to MPs degradation, aligning with prior research findings by (Villeneuve et al., 2000).
Our foray into phylogenetic analysis bore fruit by providing invaluable insights into the evolutionary relationships governing these lipases. This analytical endeavor not only illuminated the evolutionary history of these enzymes but also unveiled their functional diversification. The evolutionary context afforded by the phylogenetic analysis enhances our comprehension of these lipases' roles in plastic degradation, enabling us to infer potential links between their evolutionary heritage and their proclivity for specific plastic substrates (Tucker et al., 2017). Such insights are pivotal in understanding the precise mechanisms governing their plastic-degrading prowess. Additionally, the motif analysis conducted in this study allowed us to identify specific structural motifs in these lipases, shedding light on their potential binding affinities and substrate interactions, further deepening our understanding of their plastic-degrading capabilities.
Furthermore, the motif analysis played a pivotal role in our study. This analytical approach unveiled conserved motifs within the lipases we examined, offering essential insights into their substrate specificity and catalytic mechanisms. These identified motifs serve as crucial indicators, providing potential clues about the enzymes' structural and functional properties. In the context of our investigation, the identification of these specific motifs assumes particular significance. It equips us with valuable tools for predicting the potential preferences of these lipases for binding to specific plastic compounds. This predictive capacity is instrumental in understanding how these enzymes interact with plastic substrates, offering a glimpse into the molecular basis of their plastic-degrading capabilities. By deciphering the structural elements that facilitate these interactions, we advance our comprehension of the intricate mechanisms underlying their efficacy in MP degradation, thus contributing to the development of targeted and sustainable solutions for addressing plastic pollution.
To delve deeper into the potential of these lipases in the context of plastic degradation, a critical phase of our study involved conducting molecular docking analyses. Specifically, we subjected these enzymes to rigorous computational assessments by engaging them with five prevalent plastic compounds commonly encountered in environmental settings—namely, polycarbonate (PC), polyethylene terephthalate (PET), polypropylene (PP), polyvinyl chloride (PVC), and polystyrene (PS), as documented in prior research (Fischer & Scholz-Böttcher, 2017). Molecular docking, a well-established computational methodology, played a pivotal role in our investigative framework. This approach serves as a powerful tool for forecasting the preferred spatial orientation of a ligand—in this instance, the plastic compounds—when they interact with a receptor, represented by the lipase enzymes (Agarwal & Mehrotra, 2016). By simulating and scrutinizing these interactions at the molecular level, we gained invaluable insights into the affinity and binding characteristics of these lipases towards various plastic substrates. Such insights hold the key to unraveling the intricate dynamics of plastic degradation, guiding us toward a more comprehensive understanding of these enzymes' efficacy in the breakdown of MP pollutants.
The outcomes of our docking analyses yielded a wealth of valuable insights into the intricate interactions between fungal lipases and various plastic compounds. Notably, among the array of plastic compounds scrutinized, polycarbonate (PC) consistently emerged as a standout candidate, showcasing the highest binding affinity scores when paired with fungal lipases, across multiple fungal species. This remarkable consistency in binding affinity underscores PC's promise as a prime contender for efficient plastic degradation in the dynamic interplay between the plastic compound and the enzymatic catalyst. Such results instill confidence in the potential success of PC-driven degradation, a prospect with profound implications for addressing the persistent issue of MP pollution.
Remarkably, our findings align closely with a parallel study conducted by Duru et al. (2021). In their research, they assessed the degradation potential of PET hydrolase derived from Ideonella sakaiensis through a similar docking approach. Intriguingly, they observed that the binding free energy of PET hydrolase with PC exhibited the highest score, registering at -5.7 kcal/mol, indicative of strong binding interactions. In contrast, PVC demonstrated a notably lower binding free energy score of -2.2 kcal/mol, suggesting comparatively weaker interactions. In comparison, all fungal lipases, as elucidated in our study, consistently displayed superior binding free energy scores within the range of -5.6 to -7.8 kcal/mol. This convergence in findings across diverse studies underscores the robustness of PC as a potential substrate for enzymatic degradation, reinforcing the premise that fungal lipases hold promise as versatile agents for combating MP pollution. These insights not only enhance our understanding of the underlying mechanisms governing plastic degradation but also pave the way for targeted and sustainable solutions to address the environmental challenges posed by MPs.
The robust binding affinity observed between polycarbonate (PC) and fungal lipases can be ascribed to the distinctive structural attributes and chemical properties inherent to PC. This phenomenon finds support in prior research conducted by (Hsieh et al., 2001), who elucidated the molecular structure of PC. Central to PC's exceptional binding affinity is its linear and rigid molecular configuration. This structural rigidity equips PC with the capacity to establish steadfast interactions with pivotal amino acid residues situated within the active sites of the lipase enzymes. Such interactions form the foundation of the binding process, anchoring PC securely within the enzyme's catalytic domain and facilitating the catalytic degradation of the plastic compound. Moreover, the binding stability of the PC-enzyme complex is further fortified by a complex network of intermolecular forces. Van der Waals interactions, known for their contribution to molecular cohesion, feature prominently in the PC-enzyme binding interface. These non-covalent forces foster a strong attraction between PC and the lipase, bolstering the overall stability of the complex. Additionally, hydrogen bonds, characterized by their capacity to form strong intermolecular connections, come into play in the PC-enzyme interaction. These hydrogen bonds serve as pivotal bridges, further fortifying the binding affinity and ensuring a robust attachment between PC and the lipase.
Further enhancing the binding stability are pi interactions, encompassing various types such as Pi-Alkyl, Pi-Sigma, Pi-Stacked, and Pi-Anion interactions. These diverse pi interactions play a multifaceted role in reinforcing the PC-enzyme complex's cohesion, establishing a web of attractive forces that secure PC within the enzyme's active site. The exceptional binding affinity between PC and fungal lipases arises from a confluence of factors, including PC's linear and rigid molecular structure, as well as a rich tapestry of intermolecular interactions, including Van der Waals forces, hydrogen bonds, and various pi interactions. These structural and chemical attributes collectively contribute to the overall stability of the PC-enzyme complex, elucidating the basis of PC's efficacy as a substrate for enzymatic plastic degradation.
In contrast, our docking analyses revealed that other plastic compounds, including PET, PS, PP, and PVC, exhibited notably lower binding affinity scores in comparison to polycarbonate (PC). These variations in binding affinity can be attributed to the distinct chemical compositions and molecular arrangements inherent to each of these plastic substrates, resulting in weaker interactions with the active site residues of the fungal lipase enzymes.
Polyethylene terephthalate (PET), while displaying relatively higher binding affinity scores, represented by a score of -7.8, may not undergo as efficient degradation as PC. This relative inefficiency in degradation is likely due to the fewer interactions PET forms with the enzyme, resulting in a less robust binding configuration.
On the other hand, polystyrene (PS), polypropylene (PP), and polyvinyl chloride (PVC), with even lower binding affinity scores, are expected to exhibit even less potential for effective degradation by fungal lipases. These plastic compounds possess chemical structures that inherently hinder their interactions with the lipase's active site, thus diminishing the binding affinity and subsequently impeding efficient degradation.
Furthermore, the specific molecular interactions identified within the PC-enzyme complexes, including multiple Van der Waals interactions, hydrogen bonds, and various pi interactions, are instrumental in enhancing the stability and strength of the binding. These interactions collectively contribute to the robustness of the PC-enzyme interaction, offering valuable insights into the potential binding strategies and intermolecular forces governing the formation of plastic-enzyme complexes. This in-depth understanding of the molecular basis of binding provides critical guidance for the rational design and optimization of enzymatic strategies aimed at plastic degradation, ultimately advancing our capabilities in addressing MP pollution.
The RNA-sequencing analysis conducted during soy sauce koji fermentation has unveiled a trove of captivating molecular insights, shedding light on the remarkable adaptability of Aspergillus oryzae (A. oryzae) in response to complex and challenging environments. The up-regulation of lipase genes observed in this context offers a striking revelation, hinting at A. oryzae's capacity to thrive even in conditions contaminated with MPs. Lipases, recognized for their pivotal role in the breakdown of intricate organic compounds, emerge as key players in A. oryzae's adaptive strategy. This up-regulation implies that lipases contribute significantly to the fungus's ability to navigate and prosper within environments tainted by MPs. Furthermore, the dynamic expression patterns observed in hypothetical proteins during soy sauce koji fermentation underscore the fungus's inherent flexibility in metabolic regulation. These proteins, whose functions may not be fully characterized, play a pivotal role in the fungus's ability to fine-tune its metabolic pathways in response to environmental cues. This adaptability represents a remarkable evolutionary advantage, allowing A. oryzae to optimize its resource utilization and thrive in diverse and ever-changing ecological niches. The RNA-sequencing analysis not only deepens our understanding of the molecular underpinnings of A. oryzae's adaptability but also highlights the pivotal role of lipases in its response to challenging environments contaminated with MPs. Additionally, the dynamic expression of hypothetical proteins underscores the fungus's remarkable capacity to adjust its metabolic machinery in a dynamic and context-dependent manner. These insights have broader implications not only in the realm of MP pollution but also in understanding the adaptive strategies of microorganisms in complex ecosystems.
Harnessing the remarkable biodegradative capabilities of these microbial agents represents a pivotal stride towards mitigating the pernicious impact of MPs on the soil, plants, and the broader agricultural ecosystem. This ecological approach carries profound implications, not only for preserving the health and sustainability of agroecosystems but also for safeguarding human well-being by preempting the infiltration of MPs into the food chain. Nevertheless, it is imperative to acknowledge that the actual process of degradation is likely to be a multifaceted and dynamic interplay, subject to an array of influential factors. Environmental conditions, such as temperature, humidity, and microbial nutrient availability, may significantly modulate the efficacy and efficiency of microbial plastic degradation. Furthermore, the intricate composition and diversity of microbial communities within the environment can exert a pronounced influence on the biodegradation process. Given the intricate web of variables at play, further empirical studies are not only warranted but indeed indispensable. These investigations will serve as a crucible for validating the predictions advanced through this study and, crucially, for refining the development of effective and tailored strategies for the biodegradation of MPs within agroecosystems and beyond. By reconciling theoretical insights with empirical observations, we stand to unlock the full potential of microbial-driven plastic degradation, fostering both environmental restoration and human welfare.
In conclusion, this study has emphasized the growing concern posed by microplastic pollution in agricultural environments. Fungi, known for their enzymatic capabilities, especially lipases, show promise in addressing this issue. The study employed an in-silico approach to identify 71 novel lipase genes in 13 fungal species, expanding our knowledge of their diversity and potential applications. Lipases from various fungal species were identified and subjected to computational investigation in order to evaluate their potential for hydrolysis of specific plastic compounds including, polycarbonate (PC), polyethylene terephthalate (PET), polypropylene (PP), polystyrene (PS), and polyvinyl chloride (PVC). This research not only highlights the adaptability of fungi, like A. oryzae, to challenging environments but also suggests their potential in mitigating MP pollution. Leveraging fungal enzymes offers a sustainable strategy for safeguarding agroecosystems and preventing MP entry into the food chain. Nonetheless, further empirical investigations are imperative to validate these findings and refine the development of effective biotechnological strategies for MP waste management and environmental restoration. This scientific inquiry serves as a crucial stepping stone toward mitigating the adverse impacts of MPs in agricultural settings and beyond.
Competing Interests
The authors have no relevant financial or non-financial interests to disclose.
Funding
The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.
Author Contributions
All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Khadija Amjad, Zeeshan Khan and Tariq Shah. The first draft of the manuscript was written by Khadija Amjad, Tariq Shah, Zeeshan khan and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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