Single-particle imaging of nanomedicine entering the brain.

Nanomedicine has emerged as a revolutionary strategy of drug delivery. However, fundamentals of the nano-neuro interaction are elusive. In particular, whether nanocarriers can cross the blood-brain barrier (BBB) and release the drug cargo inside the brain, a basic process depicted in numerous books and reviews, remains controversial. Here, we develop an optical method, based on stimulated Raman scattering, for imaging nanocarriers in tissues. Our method achieves a suite of capabilities-single-particle sensitivity, chemical specificity, and particle counting capability. With this method, we visualize individual intact nanocarriers crossing the BBB of mouse brains and quantify the absolute number by particle counting. The fate of nanocarriers after crossing the BBB shows remarkable heterogeneity across multiple scales. With a mouse model of aging, we find that blood-brain transport of nanocarriers decreases with age substantially. This technology would facilitate development of effective therapeutics for brain diseases and clinical translation of nanocarrier-based treatment in general.

Harnessing non-Watson-Crick's base pairing to enhance CRISPR effectors cleavage activities and enable gene editing in mammalian cells.

Genomic DNA of the cyanophage S-2L virus is composed of 2-aminoadenine (Z), thymine (T), guanine (G), and cytosine (C), forming the genetic alphabet ZTGC, which violates Watson-Crick base pairing rules. The Z-base has an extra amino group on the two position that allows the formation of a third hydrogen bond with thymine in DNA strands. Here, we explored and expanded applications of this non-Watson-Crick base pairing in protein expression and gene editing. Both ZTGC-DNA (Z-DNA) and ZUGC-RNA (Z-RNA) produced in vitro show detectable compatibility and can be decoded in mammalian cells, including Homo sapiens cells. Z-crRNA can guide CRISPR-effectors SpCas9 and LbCas12a to cleave specific DNA through non-Watson-Crick base pairing and boost cleavage activities compared to A-crRNA. Z-crRNA can also allow for efficient gene and base editing in human cells. Together, our results help pave the way for potential strategies for optimizing DNA or RNA payloads for gene editing therapeutics and give insights to understanding the natural Z-DNA genome.

Monovalent SARS-COV-2 mRNA vaccine using optimal UTRs and LNPs is highly immunogenic and broadly protective against Omicron variants.

The emergence of highly transmissible severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) that are resistant to the current COVID-19 vaccines highlights the need for continued development of broadly protective vaccines for the future. Here, we developed two messenger RNA (mRNA)-lipid nanoparticle (LNP) vaccines, TU88mCSA and ALCmCSA, using the ancestral SARS-CoV-2 spike sequence, optimized 5' and 3' untranslated regions (UTRs), and LNP combinations. Our data showed that these nanocomplexes effectively activate CD4+ and CD8+ T cell responses and humoral immune response and provide complete protection against WA1/2020, Omicron BA.1 and BQ.1 infection in hamsters. Critically, in Omicron BQ.1 challenge hamster models, TU88mCSA and ALCmCSA not only induced robust control of virus load in the lungs but also enhanced protective efficacy in the upper respiratory airways. Antigen-specific immune analysis in mice revealed that the observed cross-protection is associated with superior UTRs [Carboxylesterase 1d (Ces1d)/adaptor protein-3ß (AP3B1)] and LNP formulations that elicit robust lung tissue-resident memory T cells. Strong protective effects of TU88mCSA or ALCmCSA against both WA1/2020 and VOCs suggest that this mRNA-LNP combination can be a broadly protective vaccine platform in which mRNA cargo uses the ancestral antigen sequence regardless of the antigenic drift. This approach could be rapidly adapted for clinical use and timely deployment of vaccines against emerging and reemerging VOCs.

Lipid nanoparticle-mediated lymph node-targeting delivery of mRNA cancer vaccine elicits robust CD8+ T cell response.

The targeted delivery of messenger RNA (mRNA) to desired organs remains a great challenge for in vivo applications of mRNA technology. For mRNA vaccines, the targeted delivery to the lymph node (LN) is predicted to reduce side effects and increase the immune response. In this study, we explored an endogenously LN-targeting lipid nanoparticle (LNP) without the modification of any active targeting ligands for developing an mRNA cancer vaccine. The LNP named 113-O12B showed increased and specific expression in the LN compared with LNP formulated with ALC-0315, a synthetic lipid used in the COVID-19 vaccine Comirnaty. The targeted delivery of mRNA to the LN increased the CD8+ T cell response to the encoded full-length ovalbumin (OVA) model antigen. As a result, the protective and therapeutic effect of the OVA-encoding mRNA vaccine on the OVA-antigen-bearing B16F10 melanoma model was also improved. Moreover, 113-O12B encapsulated with TRP-2 peptide (TRP2180-188)-encoding mRNA also exhibited excellent tumor inhibition, with the complete response of 40% in the regular B16F10 tumor model when combined with anti-programmed death-1 (PD-1) therapy, revealing broad application of 113-O12B from protein to peptide antigens. All the treated mice showed long-term immune memory, hindering the occurrence of tumor metastatic nodules in the lung in the rechallenging experiments that followed. The enhanced antitumor efficacy of the LN-targeting LNP system shows great potential as a universal platform for the next generation of mRNA vaccines.

Lipidoid Artificial Compartments for Bidirectional Regulation of Enzyme Activity through Nanomechanical Action.

Photoresponsive inhibitor and noninhibitor systems have been developed to achieve on-demand enzyme activity control. However, inhibitors are only effective for a specific and narrow range of enzymes. Noninhibitor systems usually require mutation and modification of the enzymes, leading to irreversible loss of enzymatic activities. Inspired by biological membranes, we herein report a lipidoid-based artificial compartment composed of azobenzene (Azo) lipidoids and helper lipids, which can bidirectionally regulate the activity of the encapsulated enzymes by light. In this system, the reversible photoisomerization of Azo lipidoids triggered by UV/vis light creates a continuous rotation-inversion movement, thereby enhancing the permeability of the compartment membrane and allowing substrates to pass through. Moreover, the membrane can revert to its impermeable state when light is removed. Thus, enzyme activity can be switched on and off when encapsulating enzymes in the compartments. Importantly, since neither mutation nor modification is required, negligible loss of activity is observed for the encapsulated enzymes after repeated activation and inhibition. Furthermore, this approach provides a generic strategy for controlling multiple enzymes by forgoing the use of inhibitors and may broaden the applications of enzymes in biological mechanism research and precision medicine.

Alzheimer's-Associated Upregulation of Mitochondria-Associated ER Membranes After Traumatic Brain Injury.

Traumatic brain injury (TBI) can lead to neurodegenerative diseases such as Alzheimer's disease (AD) through mechanisms that remain incompletely characterized. Similar to AD, TBI models present with cellular metabolic alterations and modulated cleavage of amyloid precursor protein (APP). Specifically, AD and TBI tissues display increases in amyloid-ß as well as its precursor, the APP C-terminal fragment of 99 a.a. (C99). Our recent data in cell models of AD indicate that C99, due to its affinity for cholesterol, induces the formation of transient lipid raft domains in the ER known as mitochondria-associated endoplasmic reticulum (ER) membranes ("MAM" domains). The formation of these domains recruits and activates specific lipid metabolic enzymes that regulate cellular cholesterol trafficking and sphingolipid turnover. Increased C99 levels in AD cell models promote MAM formation and significantly modulate cellular lipid homeostasis. Here, these phenotypes were recapitulated in the controlled cortical impact (CCI) model of TBI in adult mice. Specifically, the injured cortex and hippocampus displayed significant increases in C99 and MAM activity, as measured by phospholipid synthesis, sphingomyelinase activity and cholesterol turnover. In addition, our cell type-specific lipidomics analyses revealed significant changes in microglial lipid composition that are consistent with the observed alterations in MAM-resident enzymes. Altogether, we propose that alterations in the regulation of MAM and relevant lipid metabolic pathways could contribute to the epidemiological connection between TBI and AD.

Lower resting brain entropy is associated with stronger task activation and deactivation.

Brain entropy (BEN) calculated from resting state fMRI has been the subject of increasing research interest in recent years. Previous studies have shown the correlations between rest BEN and neurocognition and task performance, but how this relates to task-evoked brain activations and deactivations remains unknown. The purpose of this study is to address this open question using large data (n = 862). Voxel wise correlations were calculated between rest BEN and task activations/deactivations of five different tasks. For most of the assessed tasks, lower rest BEN was found to be associated with stronger activations (negative correlations) and stronger deactivations (positive correlations) only in brain regions activated or deactivated by the tasks. Higher workload evoked spatially more extended negative correlations between rest BEN and task activations. These results not only confirm that resting brain activity can predict brain activity during task performance but also for the first time show that resting brain activity may facilitate both task activations and deactivations. In addition, the results provide a clue to understanding the individual differences of task performance and brain activations.

Improving Sensitivity of Arterial Spin Labeling Perfusion MRI in Alzheimer's Disease Using Transfer Learning of Deep Learning-Based ASL Denoising.

BACKGROUND: Arterial spin labeling (ASL) perfusion magnetic resonance imaging (MRI) denoising through deep learning (DL) often faces insufficient training data from patients. One solution is to train DL models using healthy subjects' data which are more widely available and transfer them to patients' data. PURPOSE: To evaluate the transferability of a DL-based ASL MRI denoising method (DLASL). STUDY TYPE: Retrospective. SUBJECTS: Four hundred and twenty-eight subjects (189 females) from three cohorts. FIELD STRENGTH/SEQUENCE: 3 T two-dimensional (2D) echo-planar imaging (EPI)-based pseudo-continuous ASL (PCASL) and 2D EPI-based pulsed ASL (PASL) sequences. ASSESSMENT: DLASL was trained using young healthy adults' PCASL data (Dataset 1: 250/30 subjects as training/validation set) and was directly transferred (DTF) to PCASL data from Dataset 2 (45 subjects test set) of normal controls (NC) and Alzheimer's disease (AD) groups. DLASL was fine-tuned (DLASLFT) and tested on PASL data from Dataset 3 (103 subjects test set) of NC and AD. An existing non-DL method (NonDL) was used for comparison. Cerebral blood flow (CBF) images from ASL MRI were compared between NC and AD to assess characteristic hypoperfusion (lower CBF) patterns in AD. CBF image quality and CBF map sensitivity for detecting hypoperfusion using peak t-value and suprathreshold cluster size are outcome measures. STATISTICAL TESTS: Paired t-test, two-sample t-test, one-way analysis of variance, and Tukey honestly significant difference, and linear mixed-effects models were used. P < 0.05 was considered statistically significant. RESULTS: Mean contrast-to-noise ratio (CNR) of Dataset 2 showed that DTF outperformed NonDL (AD: 3.38 vs. 2.64, NC: 3.80 vs. 3.36). On Dataset 3, DLASLFT outperformed NonDL measured by mean CNR (AD: 2.45 vs. 1.87, NC: 2.54 vs. 2.17) and mean radiologic score (2.86 vs. 2.44). Image quality improvement was significant on both test sets. DTF and DLASLFT improved sensitivity for detecting AD-related hypoperfusion patterns compared with NonDL. DATA CONCLUSION: We demonstrated the DLASL's transferability across different ASL sequences and different populations. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Engineering a Nano/Biointerface for Cell and Organ-Selective Drug Delivery.

The field of nanomedicine has rapidly grown in the past decades. Although a few nanomedicines are available in the market for clinical use, it is still challenging to develop nanomedicine targeting tissues beyond the liver. It has been recognized that even though the nanoparticles are modified with targeting ligands, the formation of a protein corona on the surface of nanoparticles in the biological fluids results in limited progress in nanoparticle-based drug delivery to specific cells or tissues. In this Perspective, we will discuss the role of surface properties in determining the formation of the protein corona and summarize the recent progress in engineering the nano/bio interface for protein-corona-mediated cell- and organ-selective drug delivery. Moreover, current challenges in the field and insights into designing new strategies for targeting drug delivery with a better understanding of the protein corona will be discussed.

An efficient differential sensing strategy for phenolic pollutants based on a nanozyme with polyphenol oxidase activity.

To realize the efficient differential sensing of phenolic pollutants in sewage, a novel sensing strategy was successfully developed based on a nanozyme (GMP-Cu) with polyphenol oxidase activity. Phenolic pollutants can be oxidized using GMP-Cu, and the oxidation products reacts subsequently with 4-aminoantipyrine to produce a quinone-imine compound. The absorption spectra of final quinone-imine products that resulted from different phenolic pollutants showed obvious differences, which were due to the interaction difference between GMP-Cu and phenolic pollutants, as well as the different molecular structures of the quinone-imine products from different phenolic pollutants. Based on the difference in the absorption spectra, a novel differential sensing strategy was developed. A genetic algorithm was used to select the characteristic wavelengths at different enzymatic reaction times. Hierarchical cluster analysis and PLS-DA algorithms were utilized for the discriminant sensing of seven representative phenolic pollutants, including hydroquinone, resorcinol, catechol, resorcinol, phenol, p-chlorophenol, and 2,4-dichlorophenol. A scientific wavelength selection algorithm and a recognition algorithm resulted in the successful identification of phenolic pollutants in sewage with a discriminant accuracy of 100%, and differentiation of the phenolic pollutants regardless of their concentration. These results indicated that a sensing strategy can be used as an effective tool for the efficient identification and differentiation of phenolic pollutants in sewage.

Determination of catechin and glutathione using copper aspartate nanofibers with multiple enzyme-like activities.

Copper aspartate nanofibers were facilely prepared based on aspartic acid and copper (CuAsp nanofibers). It is found that the prepared CuAsp nanofibers have catalytic activities of five enzymes, including peroxidase, laccase, catalase, ascorbate oxidase, and superoxide dismutase mimetic activities. The kinetic and catalytic properties of CuAsp nanofibers were systematically investigated, showing their high catalytic activity, excellent stability, and reusability. The laccase mimetic activity of nanofibers could be used to detect catechin in the range 20-1200 µM with a detection limit of 5.88 µM. In addition, a sensing platform for glutathione with a detection limit of 0.25 µM and a detection range of 1-50 µM was established based on CuAsp nanofibers which have the peroxidase-mimicking activity. The sensor had good selectivity and could detect glutathione in actual samples of human serum. Therefore, CuAsp nanofibers with multi-enzyme activity have broad application prospects such as biosensing, environmental management, and disease diagnosis.

Resting-state brain entropy in schizophrenia.

BACKGROUND: The human brain presents ongoing temporal fluctuations whose dynamic range indicates the capacity of information processing and can be approximately quantified with entropy. Using functional magnetic resonance imaging (fMRI), recent studies have shown a stable distribution pattern of temporal brain entropy (tBEN) in healthy subjects, which may be affected by neuropsychiatric diseases such as schizophrenia. Assessing tBEN may reciprocally provide a new tool to characterize those disorders. METHODS: The current study aimed to identify tBEN changes in schizophrenia patients using publicly available data from the Centers of Biomedical Research Excellence (COBRE) project. Forty-three schizophrenia patients and 59 sex- and age-matched healthy control subjects were included, and tBEN was calculated from their resting-state fMRI scans. RESULTS: Compared with healthy controls, patients showed decreased tBEN in the right middle prefrontal cortex, bilateral thalamus, right hippocampus and bilateral caudate and increased tBEN in the left lingual gyrus, left precuneus, right fusiform face area and right superior occipital gyrus. In schizophrenia patients, tBEN in the left cuneus and middle occipital gyrus was negatively correlated with the positive and negative syndrome scores (PANSS). Age of onset was inversely correlated with tBEN in the right fusiform gyrus and left insula. CONCLUSION: Our findings demonstrate a detrimental tBEN reduction in schizophrenia that is related to clinical characteristics. The tBEN increase in a few regions might be a result of tBEN redistribution across the whole brain in schizophrenia.

Whole Slide Imaging for High-Throughput Sensing Antibiotic Resistance at Single-Bacterium Level and Its Application to Rapid Antibiotic Susceptibility Testing.

Since conventional culture-based antibiotic susceptibility testing (AST) methods are too time-consuming (typically 24-72 h), rapid AST is urgently needed for preventing the increasing emergence and spread of antibiotic resistant infections. Although several phenotypic antibiotic resistance sensing modalities are able to reduce the AST time to a few hours or less, concerning the biological heterogeneity, their accuracy or limit of detection are limited by low throughput. Here, we present a rapid AST method based on whole slide imaging (WSI)-enabled high-throughput sensing antibiotic resistance at single-bacterium level. The time for determining the minimum inhibitory concentration (MIC) was theoretically shortest, which ensures that the growth of each individual cell present in a large population is inhibited. As a demonstration, our technique was able to sense the growth of at least several thousand bacteria at single-cell level. Reliable MIC of Enterobacter cloacae against gentamicin was obtained within 1 h, while the gold standard broth dilution method required at least 16 h for the same result. In addition, the application of our method prevails over other imaging-based AST approaches in allowing rapid and accurate determination of antibiotic susceptibility for phenotypically heterogeneous samples, in which the number of antibiotic resistant cells was negligible compared to that of the susceptible cells. Hence, our method shows great promise for both rapid AST determination and point-of-care testing of complex clinical bacteria isolates.

Digital, Rapid, Accurate, and Label-Free Enumeration of Viable Microorganisms Enabled by Custom-Built On-Glass-Slide Culturing Device and Microscopic Scanning.

Accurately measuring the number of viable microorganisms plays an essential role in microbiological studies. Since the conventional agar method of enumerating visible colonies is time-consuming and not accurate, efforts have been made towards overcoming these limitations by counting the invisible micro-colonies. However, none of studies on micro-colony counting was able to save significant time or provide accurate results. Herein, we developed an on-glass-slide cell culture device that enables rapid formation of micro-colonies on a 0.38 mm-thick gel film without suffering from nutrient and oxygen deprivation during bacteria culturing. Employing a phase contrast imaging setup, we achieved rapid microscopic scanning of micro-colonies within a large sample area on the thin film without the need of fluorescent staining. Using Escherichia coli (E. coli) as a demonstration, our technique was able to shorten the culturing time to within 5 h and automatically enumerate the micro-colonies from the phase contrast images. Moreover, this method delivered more accurate counts than the conventional visible colony counting methods. Due to these advantages, this imaging-based micro-colony enumeration technique provides a new platform for the quantification of viable microorganisms.

Runx2 modified dental pulp stem cells (DPSCs) enhance new bone formation during rapid distraction osteogenesis (DO).

Distraction osteogenesis (DO) remains a major challenge in orthopedic and craniofacial surgery. The transplantion of mesenchymal stem cells (MSCs) could reduce the treatment period and the associated complications by increasing new bone formation during long-bone DO. Runt-related transcription factor 2 (Runx2) encodes a nuclear protein that is a pivotal regulator of osteoblast differentiation. It significantly stimulates calcium accumulation and alkaline phosphatase (ALP) activity in dental pulp stem cells (DPSCs). In this study, we investigated the effects of gene therapy using Runx2 on new bone formation during tibia DO of rabbits. The distraction gap of the rabbits was injected with adenovirus (Adv)-Runx2-green fluorescent protein (GFP)-transfected DPSCs (overexpression group, Group OE) or Adv-GFP-transfected DPSCs (negative control group, Group NC). Rabbits in the control group (Groups CON) were injected with physiologic saline. The generation of new bone tissue in the distraction gap was studied by radiographic examination, micro-computed tomography (CT) evaluation, histological analyze, and Mechanical testing at weeks 8 in the consolidation period. Excellent bone formation in the distracted callus was observed in Group OE and Group NC. Moreover, the OE group showed better bone formation and the highest bone mineral density (BMD) and bone mineral content (BMC). Group CON animals showed inadequate bone formation in the distracted callus compared to the other groups. The results suggest that gene therapy using Runx2-modified DPSCs was more effective during bone deposition and new bone formation in tibia DO.

Systemic administration of lithium improves distracted bone regeneration in rats.

Lithium, popular in psychology field, has been recognized as an activator component of the canonical Wnt signaling pathway. The effect of lithium on osteogenesis or on the human fracture risk has been widely reported. However, little is known on its role in distraction osteogenesis to date. In this study, the effect of systematic administrated lithium on distraction osteogenesis in a rat model was investigated. The osteotomy was performed on the right tibia in 40 adult male Sprague-Dawley rats. Then they were randomly assigned into two equal groups (n = 20/group), which underwent Lithium or saline treatment through gastric gavage until the day they were killed. One week after the osteotomy, the tibias were distracted for 14 days (rate 0.6 mm/day). Following 8 weeks consolidation period, the distracted tibias in both groups were harvested and examined by X-ray plain radiography, histology, dual-energy X-ray absorptiometry, Micro-CT, and biomechanical tests. The results showed that lithium group possessed higher bone mineral density, more mature new bone tissue, and better regenerated bone mass continuity in the distraction gaps without any local or systemic adverse effects was encountered. This study suggested lithium could increase bony callus ossification volume and accelerate distracted tissue mineralization to facilitate bone regeneration in distraction gap.

Long circulating self-assembled nanoparticles from cholesterol-containing brush-like block copolymers for improved drug delivery to tumors.

Amphiphilic brush-like block copolymers composed of polynorbonene-cholesterol/poly(ethylene glycol) (P(NBCh9-b-NBPEG)) self-assembled to form a long circulating nanostructure capable of encapsulating the anticancer drug doxorubicin (DOX) with high drug loading (22.1% w/w). The release of DOX from the DOX-loaded P(NBCh9-b-NBPEG) nanoparticles (DOX-NPs) was steady at less than 2% per day in PBS. DOX-NPs were effectively internalized by human cervical cancer cells (HeLa) and showed dose-dependent cytotoxicity, whereas blank nanoparticles were noncytotoxic. The DOX-NPs demonstrated a superior in vivo circulation time relative to that of free DOX. Tissue distribution and in vivo imaging studies showed that DOX-NPs preferentially accumulated in tumor tissue with markedly reduced accumulation in the heart and other vital organs. The DOX-NPs greatly improved survival and significantly inhibited tumor growth in tumor-bearing SCID mice compared to that for the untreated and free DOX-treated groups. The results indicated that self-assembled P(NBCh9-b-NBPEG) may be a useful carrier for improving tumor delivery of hydrophobic anticancer drugs.

Tuning Lipid Nanoparticles for RNA Delivery to Extrahepatic Organs.

RNA therapeutics have been successfully transitioned into clinical applications. Lipid nanoparticles (LNPs) are widely employed as nonviral delivery vehicles for RNA therapeutics in commercial vaccine and gene therapy products. However, the bottleneck in expanding the clinical applications of LNP-based RNA therapeutics lies in the tendency of these nanoparticles to preferentially accumulate in the liver. This challenge underscores the need to design LNPs capable of delivering RNA to organs beyond the liver. In this perspective, recent progress is discussed in developing strategies for designing LNPs to deliver RNA to extrahepatic organs. Organ-selective targeting capability is achieved by either altering the composition of the LNP formulation or chemically modifying the ionizable lipid component. Both approaches result in changes in the physicochemical properties of the LNPs, which subsequently alters the composition of the biomolecular corona that adsorbs onto its surface following administration. The biomolecular corona is a known mechanism that mediates organ-selective LNP delivery. Furthermore, this perspective aims to provide an outlook on shaping the next-generation LNP delivery platforms. Potential efforts include targeting specific cell types, improving the safety profile of LNPs, and developing strategies to overcome physiological barriers against organ-specific delivery.

Machine learning-assisted melamine-Cu nanozyme and cholinesterase integrated array for multi-category pesticide intelligent recognition.

Expanding target pesticide species and intelligent pesticide recognition were formidable challenges for existing cholinesterase inhibition methods. To improve this status, multi-active Mel-Cu nanozyme with mimetic Cu-N sites was prepared for the first time. It exhibited excellent laccase-like and peroxidase-like activities, and can respond to some pesticides beyond the detected range of enzyme inhibition methods, such as glyphosate, carbendazim, fumonisulfuron, etc., through coordination and hydrogen bonding. Inspired by the signal complementarity of Mel-Cu and cholinesterase, an integrated sensor array based on the Mel-Cu laccase-like activity, Mel-Cu peroxidase-like activity, acetylcholinesterase, and butyrylcholinesterase was creatively constructed. And it could successfully discriminate 12 pesticides at 0.5-50 µg/mL, which was significantly superior to traditional enzyme inhibition methods. Moreover, on the basis of above array, a unified stepwise prediction model was built using classification and regression algorithms in machine learning, which enabled concentration-independent qualitative identification as well as precise quantitative determination of multiple pesticide targets, simultaneously. The sensing accuracy was verified by blind sample analysis, in which the species was correctly identified and the concentration was predicted within 10% error, suggesting great intelligent recognition ability. Further, the proposed method also demonstrated significant immunity to interference and practical application feasibility, providing powerful means for pesticide residue analysis.

Elucidating polyethylene microplastic degradation mechanisms and metabolic pathways via iron-enhanced microbiota dynamics in marine sediments.

The extensive use of plastics has given rise to microplastics, a novel environmental contaminant that has sparked considerable ecological and environmental concerns. Biodegradation offers a more environmentally friendly approach to eliminating microplastics, but their degradation by marine microbial communities has received little attention. In this study, we used iron-enhanced marine sediment to augment the natural bacterial community and facilitate the decomposition of polyethylene (PE) microplastics. The introduction of iron-enhanced sediment engendered an augmented bacterial biofilm formation on the surface of polyethylene (PE), thereby leading to a more pronounced degradation effect. This novel observation has been ascribed to the oxidative stress-induced generation of a variety of oxygenated functional groups, including hydroxyl (-OH), carbonyl (-CO), and ether (-C-O) moieties, within the microplastic substrate. The analysis of succession in the community structure of sediment bacteria during the degradation phase disclosed that Acinetobacter and Pseudomonas emerged as the principal bacterial players in PE degradation. These taxa were directly implicated in oxidative metabolic pathways facilitated by diverse oxidase enzymes under iron-facilitated conditions. The present study highlights bacterial community succession as a new pivotal factor influencing the complex biodegradation dynamics of polyethylene (PE) microplastics. This investigation also reveals, for the first time, a unique degradation pathway for PE microplastics orchestrated by the multifaceted marine sediment microbiota. These novel insights shed light on the unique functional capabilities and internal biochemical mechanisms employed by the marine sediment microbiota in effectively degrading polyethylene microplastics.