Microsyst Nanoeng. 2023 Nov 24;9:147. doi: 10.1038/s41378-023-00626-9. eCollection 2023.

ABSTRACT

[This corrects the article DOI: 10.1038/s41378-023-00485-4.].

PMID:38025885 | PMC:PMC10673899 | DOI:10.1038/s41378-023-00626-9

iScience. 2023 Oct 18;26(12):108250. doi: 10.1016/j.isci.2023.108250. eCollection 2023 Dec 15.

ABSTRACT

The challenge of drug-resistant bacteria to global public health has led to increased attention on antimicrobial peptides (AMPs) as a targeted therapeutic alternative with a lower risk of resistance. However, high production costs and limitations in functional class prediction have hindered progress in this field. In this study, we used multi-label classifiers with binary relevance and algorithm adaptation techniques to predict different functions of AMPs across a wide range of pathogen categories, including bacteria, mammalian cells, fungi, viruses, and cancer cells. Our classifiers attained promising AUC scores varying from 0.8492 to 0.9126 on independent testing data. Forward feature selection identified sequence order and charge as critical, with specific amino acids (C and E) as discriminative. These findings provide valuable insights for the design of antimicrobial peptides (AMPs) with multiple functionalities, thus contributing to the broader effort to combat drug-resistant pathogens.

PMID:38025779 | PMC:PMC10679894 | DOI:10.1016/j.isci.2023.108250

Physiol Mol Biol Plants. 2023 Sep;29(9):1239-1246. doi: 10.1007/s12298-023-01358-w. Epub 2023 Sep 20.

ABSTRACT

Salinity, low temperature, and drought are major environmental factors in agriculture leading to reduced crop yield. Dehydrins (DHNs) are induced transcriptionally during cellular dehydration and accumulate in different tissues during abiotic stresses. Here we isolated and characterized a bacterial gene BG757 in Arabidopsis, encoding a putative dehydrin type protein. ABA induces the expression of various dehydrins in plants, therefore, to elucidate the potential role, ABA sensitivity was examined in Arabidopsis transgenic lines expressing BG757. Interestingly, BG757-expressing plants showed hypersensitivity towards NaCl and ABA during seed germination. In addition to germination, BG757-expressing plants also showed root growth retardation in the presence of ABA and NaCl when compared with wild type (WT), suggesting that BG757 positively regulate salt stress and ABA response. Furthermore, BG757-expressing plants showed significant drought tolerance compared with WT. Consistent with drought tolerance, expression levels of stress inducible genes (DREB2A, RD22, RD26, LEA7 and SOS1) were strongly upregulated in transgenic plants compared with WT. All together these results suggest that heterologous expression of bacterial gene, BG757 in plants promotes resistance to environmental stresses.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12298-023-01358-w.

PMID:38024953 | PMC:PMC10678877 | DOI:10.1007/s12298-023-01358-w

Biochem Biophys Rep. 2023 Nov 7;36:101574. doi: 10.1016/j.bbrep.2023.101574. eCollection 2023 Dec.

ABSTRACT

Atherosclerosis (ATH) is a chronic cardiovascular disease characterized by plaque formation in arteries, and it is a major cause of illness and death. Although therapeutic advances have significantly improved the prognosis of ATH, missing therapeutic targets pose a significant residual threat. This research used a systems biology approach to identify the molecular biomarkers involved in the onset and progression of ATH, analysing microarray gene expression datasets from ATH and tissues impacted by risk factors such as high cholesterol, adipose tissue, smoking, obesity, sedentary lifestyle, stress, alcohol consumption, hypertension, hyperlipidaemia, high fat, diabetes to find the differentially expressed genes (DEGs). Bioinformatic analyses of Protein-Protein Interaction (PPI), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) were conducted on differentially expressed genes, revealing metabolic and signaling pathways (the chemokine signaling pathway, cytokine-cytokine receptor interaction, the cytosolic DNA-sensing pathway, the peroxisome proliferator-activated receptors signaling pathway, and the nuclear factor-kappa B signaling pathway), ten hubs proteins (CCL5, CCR1, TLR1, CCR2, FCGR2A, IL1B, CD163, AIF1, CXCL-1 and TNF), five transcription factors (YY1, FOXL1, FOXC1, SRF, and GATA2), and five miRNAs (mir-27a-3p, mir-124-3p, mir-16-5p, mir-129-2-3p, mir-1-3p). These findings identify potential biomarkers that may increase knowledge of the mechanisms underlying ATH and their connection to risk factors, aiding in the development of new therapies.

PMID:38024867 | PMC:PMC10652116 | DOI:10.1016/j.bbrep.2023.101574

Front Plant Sci. 2023 Nov 13;14:1286663. doi: 10.3389/fpls.2023.1286663. eCollection 2023.

ABSTRACT

The use of CRISPR/Cas9 is currently the method of choice for precise genome engineering in plants, including in the biomass crop poplar. The most commonly used method for delivering CRISPR/Cas9 and its components in poplar is via Agrobacterium-mediated transformation, that besides the desired gene-editing event also results in stable T-DNA integration. Here we explore the delivery of the gene-editing reagents via DNA-coated microparticle bombardment into the model tree Populus tremula x P. alba to evaluate its potential for developing transgene-free, gene-edited trees, as well as its potential for integrating donor DNA at specific target sites. Using an optimized transformation method, which favors the regeneration of plants that transiently express the genes on the delivered donor DNA, we regenerated gene-edited plants that are free of the Cas9 and the antibiotic resistance-encoding transgenes. In addition, we report the frequent integration of donor DNA fragments at the Cas9-induced double-strand break, opening opportunities toward targeted gene insertions.

PMID:38023888 | PMC:PMC10679337 | DOI:10.3389/fpls.2023.1286663

Front Plant Sci. 2023 Nov 7;14:1324901. doi: 10.3389/fpls.2023.1324901. eCollection 2023.

NO ABSTRACT

PMID:38023871 | PMC:PMC10661230 | DOI:10.3389/fpls.2023.1324901

Front Plant Sci. 2023 Nov 8;14:1272363. doi: 10.3389/fpls.2023.1272363. eCollection 2023.

ABSTRACT

Plants produce a diverse range of specialized metabolites that play pivotal roles in mediating environmental interactions and stress adaptation. These unique chemical compounds also hold significant agricultural, medicinal, and industrial values. Despite the expanding knowledge of their functions in plant stress interactions, understanding the intricate biosynthetic pathways of these natural products remains challenging due to gene and pathway redundancy, multifunctionality of proteins, and the activity of enzymes with broad substrate specificity. In the past decade, substantial progress in genomics, transcriptomics, metabolomics, and proteomics has made the exploration of plant specialized metabolism more feasible than ever before. Notably, recent advances in integrative multi-omics and computational approaches, along with other technologies, are accelerating the discovery of plant specialized metabolism. In this review, we present a summary of the recent progress in the discovery of plant stress-related specialized metabolites. Emphasis is placed on the application of advanced omics-based approaches and other techniques in studying plant stress-related specialized metabolism. Additionally, we discuss the high-throughput methods for gene functional characterization. These advances hold great promise for harnessing the potential of specialized metabolites to enhance plant stress resilience in the future.

PMID:38023861 | PMC:PMC10663375 | DOI:10.3389/fpls.2023.1272363

Front Plant Sci. 2023 Nov 8;14:1257744. doi: 10.3389/fpls.2023.1257744. eCollection 2023.

ABSTRACT

INTRODUCTION: Pine wilt disease (PWD) is responsible for extensive economic and ecological damage to Pinus spp. forests and plantations worldwide. PWD is caused by the pine wood nematode (PWN, Bursaphelenchus xylophilus) and transmitted into pine trees by a vector insect, the Japanese pine sawyer (JPS, Monochamus alternatus). Host infection by PWN will attract JPS to spawn, which leads to the co-existence of PWN and JPS within the host tree, an essential precondition for PWD outbreaks. Through the action of their metabolites, microbes can manipulate the co-existence of PWN and JPS, but our understanding on how key microorganisms engage in this process remains limited, which severely hinders the exploration and utilization of promising microbial resources in the prevention and control of PWD.

METHODS: In this study we investigated how the PWN-associated fungus Aspergillus promotes the co-existence of PWN and JPS in the host trees (Pinus massoniana) via its secondary metabolite, sterigmatocystin (ST), by taking a multi-omics approach (phenomics, transcriptomics, microbiome, and metabolomics).

RESULTS: We found that Aspergillus was able to promote PWN invasion and pathogenicity by increasing ST biosynthesis in the host plant, mainly by suppressing the accumulation of ROS (reactive oxygen species) in plant tissues that could counter PWN. Further, ST accumulation triggered the biosynthesis of VOC (volatile organic compounds) that attracts JPS and drives the coexistence of PWN and JPS in the host plant, thereby encouraging the local transmission of PWD. Meanwhile, we show that application of an Aspergillus inhibitor (chiricanine A treatment) results in the absence of Aspergillus and decreases the in vivo ST amount, thereby sharply restricting the PWN development in host. This further proved that Aspergillus is vital and sufficient for promoting PWD transmission.

DISCUSSION: Altogether, these results document, for the first time, how the function of Aspergillus and its metabolite ST is involved in the entire PWD transmission chain, in addition to providing a novel and long-term effective nematicide for better PWD control in the field.

PMID:38023855 | PMC:PMC10663349 | DOI:10.3389/fpls.2023.1257744

Front Plant Sci. 2023 Nov 8;14:1276472. doi: 10.3389/fpls.2023.1276472. eCollection 2023.

ABSTRACT

Plant microbiome structure affects plant health and productivity. A limited subset of environmental microbes successfully establishes within plant tissues, but the forces underlying this selectivity remain poorly characterized. Transmembrane pattern recognition receptors (PRRs), used by plants to detect microbe-associated molecular patterns (MAMPs), are strong candidates for achieving this selectivity because PRRs can potentially interact with many members of the microbiome. Indeed, MAMPs found in many microbial taxa, including beneficials and commensals, can instigate a robust immune response that affects microbial growth. Surprisingly, we found that MAMP-detecting PRRs have little effect on endophytic bacterial and fungal microbiome structure in the field. We compared the microbiomes of four PRR knockout lines of Arabidopsis thaliana to wild-type plants in multiple tissue types over several developmental stages and detected only subtle shifts in fungal, but not bacterial, β-diversity in one of the four PRR mutants. In one developmental stage, lore mutants had slightly altered fungal β-diversity, indicating that LORE may be involved in plant-fungal interactions in addition to its known role in detecting certain bacterial lipids. No other effects of PRRs on α-diversity, microbiome variability, within-individual homogeneity, or microbial load were found. The general lack of effect suggests that individual MAMP-detecting PRRs are not critical in shaping the endophytic plant microbiome. Rather, we suggest that MAMP-detecting PRRs must either act in concert and/or are individually maintained through pleiotropic effects or interactions with coevolved mutualists or pathogens. Although unexpected, these results offer insights into the role of MAMP-detecting PRRs in plant-microbe interactions and help direct future efforts to uncover host genetic elements that control plant microbiome assembly.

PMID:38023837 | PMC:PMC10663345 | DOI:10.3389/fpls.2023.1276472

Front Plant Sci. 2023 Nov 7;14:1324837. doi: 10.3389/fpls.2023.1324837. eCollection 2023.

NO ABSTRACT

PMID:38023830 | PMC:PMC10660260 | DOI:10.3389/fpls.2023.1324837

Comput Struct Biotechnol J. 2023 Nov 10;21:5530. doi: 10.1016/j.csbj.2023.11.001. eCollection 2023.

ABSTRACT

[This corrects the article DOI: 10.1016/j.csbj.2022.12.006.].

PMID:38022703 | PMC:PMC10665586 | DOI:10.1016/j.csbj.2023.11.001

Comput Struct Biotechnol J. 2023 Oct 21;21:5395-5407. doi: 10.1016/j.csbj.2023.10.031. eCollection 2023.

ABSTRACT

Neurodegenerative diseases (ND) are heterogeneous disorders of the central nervous system that share a chronic and selective process of neuronal cell death. A computational approach to investigate shared genetic and specific loci was applied to 5 different ND: Amyotrophic lateral sclerosis (ALS), Alzheimer's disease (AD), Parkinson's disease (PD), Multiple sclerosis (MS), and Lewy body dementia (LBD). The datasets were analyzed separately, and then we compared the obtained results. For this purpose, we applied a genetic correlation analysis to genome-wide association datasets and revealed different genetic correlations with several human traits and diseases. In addition, a clumping analysis was carried out to identify SNPs genetically associated with each disease. We found 27 SNPs in AD, 6 SNPs in ALS, 10 SNPs in PD, 17 SNPs in MS, and 3 SNPs in LBD. Most of them are located in non-coding regions, with the exception of 5 SNPs on which a protein structure and stability prediction was performed to verify their impact on disease. Furthermore, an analysis of the differentially expressed miRNAs of the 5 examined pathologies was performed to reveal regulatory mechanisms that could involve genes associated with selected SNPs. In conclusion, the results obtained constitute an important step toward the discovery of diagnostic biomarkers and a better understanding of the diseases.

PMID:38022694 | PMC:PMC10651457 | DOI:10.1016/j.csbj.2023.10.031

Front Immunol. 2023 Nov 1;14:1257321. doi: 10.3389/fimmu.2023.1257321. eCollection 2023.

ABSTRACT

Chronic inflammatory diseases (CIDs), including inflammatory bowel disease (IBD), rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) are thought to emerge from an impaired complex network of inter- and intracellular biochemical interactions among several proteins and small chemical compounds under strong influence of genetic and environmental factors. CIDs are characterised by shared and disease-specific processes, which is reflected by partially overlapping genetic risk maps and pathogenic cells (e.g., T cells). Their pathogenesis involves a plethora of intracellular pathways. The translation of the research findings on CIDs molecular mechanisms into effective treatments is challenging and may explain the low remission rates despite modern targeted therapies. Modelling CID-related causal interactions as networks allows us to tackle the complexity at a systems level and improve our understanding of the interplay of key pathways. Here we report the construction, description, and initial applications of the SYSCID map (https://syscid.elixir-luxembourg.org/), a mechanistic causal interaction network covering the molecular crosstalk between IBD, RA and SLE. We demonstrate that the map serves as an interactive, graphical review of IBD, RA and SLE molecular mechanisms, and helps to understand the complexity of omics data. Examples of such application are illustrated using transcriptome data from time-series gene expression profiles following anti-TNF treatment and data from genome-wide associations studies that enable us to suggest potential effects to altered pathways and propose possible mechanistic biomarkers of treatment response.

PMID:38022524 | PMC:PMC10646502 | DOI:10.3389/fimmu.2023.1257321

Front Immunol. 2023 Nov 2;14:1242242. doi: 10.3389/fimmu.2023.1242242. eCollection 2023.

ABSTRACT

The severe and chronic inflammatory bowel diseases (IBD), Crohn disease and ulcerative colitis, are characterized by persistent inflammation and gut damage. There is an increasing recognition that the gut microbiota plays a pivotal role in IBD development and progression. However, studies of the complete microbiota composition (bacteria, fungi, viruses) from precise locations within the gut remain limited. In particular, studies have focused primarily on the bacteriome, with available methods limiting evaluation of the mycobiome (fungi) and virome (virus). Furthermore, while the different segments of the small and large intestine display different functions (e.g., digestion, absorption, fermentation) and varying microenvironment features (e.g., pH, metabolites), little is known about the biogeography of the microbiota in different segments of the intestinal tract or how this differs in IBD. Here, we highlight evidence of the differing microbiota communities of the intestinal sub-organs in healthy and IBD, along with method summaries to improve future studies.

PMID:38022505 | PMC:PMC10654633 | DOI:10.3389/fimmu.2023.1242242

Onco Targets Ther. 2023 Nov 20;16:973-982. doi: 10.2147/OTT.S425723. eCollection 2023.

ABSTRACT

BACKGROUND: Vasopressin gene expression has been demonstrated to be a common feature of all small-cell lung cancer (SCLC) and breast cancer. Provasopressin (ProVP) is a component of the cancer cell membrane and a likely target for treatment. However, a measurable fraction of this cancer provasopressin is also normally processed and products are released into the circulation. Vasopressin (VP) and vasopressin-associated human neurophysin (VP-HNP), two of three products of processing, were earlier shown to be reliable plasma markers for determining the presence of SCLC and monitoring response to treatment.

MATERIAL AND METHODS: In this study, copeptin, the third product of provasopressin processing, was preliminarily evaluated as a plasma marker for SCLC or breast cancer using radioimmunoassay (RIA). Antibodies directed against the 18 residue C-terminal peptide fragment of copeptin were used to avoid interference from the large-carbohydrate component of this endogenous glycopeptide.

RESULTS: The levels of copeptin in 8 male and 6 female patients with SCLC before treatment ranged from 16 to 319 pmol/L, and these levels were elevated (>2.5 times) in 10 of 14 cases (70%) when compared with healthy volunteers (normal mean, 18 ± 6 pmol/L). Volunteer values for males were smaller than for females (15± 4 pmol/L and 20± 9 pmol/L), but numbers were small. Patients with breast cancer had plasma levels ranging from 12 to 68 pmol/L, with only three of the six elevated.

CONCLUSION: While cancer patients displayed a wide range of plasma copeptin levels over 70% with SCLC and 50% with breast cancer had clearly elevated levels. This finding indicates that for such patients, plasma copeptin, like plasma VP and VP-HNP, could be used to detect disease. The control values found for healthy volunteers using our RIA were in a range predictable from established normal plasma levels of both VP and VP-HNP.

PMID:38021449 | PMC:PMC10674625 | DOI:10.2147/OTT.S425723

J Cancer. 2023 Oct 24;14(18):3539-3549. doi: 10.7150/jca.86942. eCollection 2023.

ABSTRACT

Purpose: Cancers often display disorder metabolism, which closely related to the poor outcome of patients. We aimed to establish prognostic models using metabolism-associated genes, and identify the key factor involved in metabolism in lung squamous cell carcinoma (LUSC). Materials and Methods: R package 'TCGA biolinks' was used to download the mRNA sequencing data of LUSC from TCGA. The clusterProfiler package was performed to analyze biological pathways. The online tool GEPIA2 and cox regression method were applied to identify the two gene lists associated with metabolism and prognosis of LUSC. The lasso modeling was conducted to establish prognostic models. The quantiseq method was used to identify the cellular abundance of expression matrix in TCGA-LUSC dataset. Immunohistochemistry and western blotting were done to evaluate the STXBP1 expression in LUSC samples. Lactate assay and ATP detection were performed to assess metabolic effect, and CCK8 assay was done to test cell proliferation in the LUSC cells with overexpression and suppression of STXBP1. Results: Two lists of survival-metabolism-associated genes (11 and 28 genes) were identified and applied in the prognostic model 1 and model 2 construction from TCGA-LUSC dataset. High-risk LUSC patients associated with poor survival in the training cohort and the test cohort of both model 1 and model 2. Higher ROC values for 10- year survival was shown in model 2 than in model 1. In addition, macrophage M1, macrophage M2, neutrophil, and T regulatory cell were enriched in the high-risk group of model 2. STXBP1 was the only optimized gene in both model 1 and model 2, and related to the poor outcome of LUSC patients. Furthermore, STXBP1 associated with infiltrating immune cells, and increased lactate, ATP levels, and cell proliferation. Conclusion: Our finding provides the metabolism-associated models to predict prognosis of LUSC patients. STXBP1, as the key optimized gene in the model, promotes metabolic progress to increase lactate and ATP levels in LUSC cells.

PMID:38021151 | PMC:PMC10647197 | DOI:10.7150/jca.86942

Front Cell Dev Biol. 2023 Nov 1;11:1274127. doi: 10.3389/fcell.2023.1274127. eCollection 2023.

ABSTRACT

Amoeboid cell movement and migration are wide-spread across various cell types and species. Microscopy-based analysis of the model systems Dictyostelium and neutrophils over the years have uncovered generality in their overall cell movement pattern. Under no directional cues, the centroid movement can be quantitatively characterized by their persistence to move in a straight line and the frequency of re-orientation. Mathematically, the cells essentially behave as a persistent random walker with memory of two characteristic time-scale. Such quantitative characterization is important from a cellular-level ethology point of view as it has direct connotation to their exploratory and foraging strategies. Interestingly, outside the amoebozoa and metazoa, there are largely uncharacterized species in the excavate taxon Heterolobosea including amoeboflagellate Naegleria. While classical works have shown that these cells indeed show typical amoeboid locomotion on an attached surface, their quantitative features are so far unexplored. Here, we analyzed the cell movement of Naegleria gruberi by employing long-time phase contrast imaging that automatically tracks individual cells. We show that the cells move as a persistent random walker with two time-scales that are close to those known in Dictyostelium and neutrophils. Similarities were also found in the shape dynamics which are characterized by the appearance, splitting and annihilation of the curvature waves along the cell edge. Our analysis based on the Fourier descriptor and a neural network classifier point to importance of morphology features unique to Naegleria including complex protrusions and the transient bipolar dumbbell morphologies.

PMID:38020930 | PMC:PMC10646312 | DOI:10.3389/fcell.2023.1274127

Front Cell Dev Biol. 2023 Nov 7;11:1260507. doi: 10.3389/fcell.2023.1260507. eCollection 2023.

ABSTRACT

Whole-cell modeling is "the ultimate goal" of computational systems biology and "a grand challenge for 21st century" (Tomita, Trends in Biotechnology, 2001, 19(6), 205-10). These complex, highly detailed models account for the activity of every molecule in a cell and serve as comprehensive knowledgebases for the modeled system. Their scope and utility far surpass those of other systems models. In fact, whole-cell models (WCMs) are an amalgam of several types of "system" models. The models are simulated using a hybrid modeling method where the appropriate mathematical methods for each biological process are used to simulate their behavior. Given the complexity of the models, the process of developing and curating these models is labor-intensive and to date only a handful of these models have been developed. While whole-cell models provide valuable and novel biological insights, and to date have identified some novel biological phenomena, their most important contribution has been to highlight the discrepancy between available data and observations that are used for the parametrization and validation of complex biological models. Another realization has been that current whole-cell modeling simulators are slow and to run models that mimic more complex (e.g., multi-cellular) biosystems, those need to be executed in an accelerated fashion on high-performance computing platforms. In this manuscript, we review the progress of whole-cell modeling to date and discuss some of the ways that they can be improved.

PMID:38020904 | PMC:PMC10661945 | DOI:10.3389/fcell.2023.1260507

Front Cell Dev Biol. 2023 Nov 3;11:1233808. doi: 10.3389/fcell.2023.1233808. eCollection 2023.

ABSTRACT

The linear framework uses finite, directed graphs with labelled edges to model biomolecular systems. Graph vertices represent chemical species or molecular states, edges represent reactions or transitions and edge labels represent rates that also describe how the system is interacting with its environment. The present paper is a sequel to a recent review of the framework that focussed on how graph-theoretic methods give insight into steady states as rational algebraic functions of the edge labels. Here, we focus on the transient regime for systems that correspond to continuous-time Markov processes. In this case, the graph specifies the infinitesimal generator of the process. We show how the moments of the first-passage time distribution, and related quantities, such as splitting probabilities and conditional first-passage times, can also be expressed as rational algebraic functions of the labels. This capability is timely, as new experimental methods are finally giving access to the transient dynamic regime and revealing the computations and information processing that occur before a steady state is reached. We illustrate the concepts, methods and formulas through examples and show how the results may be used to illuminate previous findings in the literature.

PMID:38020901 | PMC:PMC10656611 | DOI:10.3389/fcell.2023.1233808

Curr Res Neurobiol. 2023 Oct 6;5:100112. doi: 10.1016/j.crneur.2023.100112. eCollection 2023.

ABSTRACT

SARS-CoV-2 infection is associated with both acute and post-acute neurological symptoms. Emerging evidence suggests that SARS-CoV-2 can alter mitochondrial metabolism, suggesting that changes in brain metabolism may contribute to the development of acute and post-acute neurological complications. Monoamine oxidase B (MAO-B) is a flavoenzyme located on the outer mitochondrial membrane that catalyzes the oxidative deamination of monoamine neurotransmitters. Computational analyses have revealed high similarity between the SARS-CoV-2 spike glycoprotein receptor binding domain on the ACE2 receptor and MAO-B, leading to the hypothesis that SARS-CoV-2 spike glycoprotein may alter neurotransmitter metabolism by interacting with MAO-B. Our results empirically establish that the SARS-CoV-2 spike glycoprotein interacts with MAO-B, leading to increased MAO-B activity in SH-SY5Y neuron-like cells. Common to neurodegenerative disease pathophysiological mechanisms, we also demonstrate that the spike glycoprotein impairs mitochondrial bioenergetics, induces oxidative stress, and perturbs the degradation of depolarized aberrant mitochondria through mitophagy. Our findings also demonstrate that SH-SY5Y neuron-like cells expressing the SARS-CoV-2 spike protein were more susceptible to MPTP-induced necrosis, likely necroptosis. Together, these results reveal novel mechanisms that may contribute to SARS-CoV-2-induced neurodegeneration.

PMID:38020812 | PMC:PMC10663135 | DOI:10.1016/j.crneur.2023.100112