Cellular Functions Research Articles

Optimizing the leaf-to-bunch ratio in ‘Mazafati’ date trees by considering source-sink limitation and physiological-molecular responses

The balance between carbon production and consumption is regulated by source and sink, which can limit plant performance. When there is an imbalance between source and sink, the plant's performance is affected. Thus, source and sink are interdependent. We conducted a two-year study (220–221) to investigate how different leaf-to–bunch ratios (LBR) (7–12) affect source–sink balance and yield in ’Mazafati’ date trees. We also determined the optimal number of bunches per tree as the main carbon sinks competing with other organs. Trehalose is a non-reducing sugar that protects cellular structure and function under stress. We found that 9–10 LBR-trees had no biotic stress due to carbon deficiency or excess, as indicated by minimal expression of the trehalose-6-phosphate synthase (TPS) gene and synthesis of trehalose. This alleviated source-sink limitation and resulted in the highest yield, bunch weight, fruit weight and flavor, water use efficiency, and reduced abscised fruit. Hormones gibberellic acid (GA3) and abscisic acid (ABA), gene expression of sucrose phosphate synthase 1 (SPS1), enzyme activities of sucrose phosphate synthase (SPS) and sucrose synthase (SuSy) related to sucrose synthesis, reducing and non-reducing sugars, and starch increased with increasing LBR in date palm fruit. Based on our findings, we concluded that a LBR of 9–10 optimizes fruit quality in date palm.

LexA, an SOS response repressor, activates TGase synthesis in Streptomyces mobaraensis

Transglutaminase (EC 2.3.2.13, TGase), an enzyme that catalyzes the formation of covalent cross-links between protein or peptide molecules, plays a critical role in commercial food processing, medicine, and textiles. TGase from Streptomyces is the sole commercial enzyme preparation for cross-linking proteins. In this study, we revealed that the SOS response repressor protein LexA in Streptomyces mobaraensis not only triggers morphological development but also enhances TGase synthesis. The absence of lexA significantly diminished TGase production and sporulation. Although LexA does not bind directly to the promoter region of the TGase gene, it indirectly stimulates transcription of the tga gene, which encodes TGase. Furthermore, LexA directly enhances the expression of genes associated with protein synthesis and transcription factors, thus favorably influencing TGase synthesis at both the transcriptional and posttranscriptional levels. Moreover, LexA activates four crucial genes involved in morphological differentiation, promoting spore maturation. Overall, our findings suggest that LexA plays a dual role as a master regulator of the SOS response and a significant contributor to TGase regulation and certain aspects of secondary metabolism, offering insights into the cellular functions of LexA and facilitating the strategic engineering of TGase overproducers.

Oleic acid stimulates proliferation of RMG-1 ovarian cancer cells by activating the pentose phosphate pathway and glutamine metabolism

Extracellular fatty acids (FAs) play an important role in regulating cellular functions such as cell proliferation, survival, and migration. The effects of oleic acid (OA) on cancer cells vary depending on the cell type. Our prior study showed that two distinct ovarian cancer cell lines, RMG-1 and HNOA, proliferate in response to OA, but they differ with respect to glucose utilization. Here, we aimed to elucidate the mechanism(s) by which OA stimulates proliferation of RMG-1 cells. We found that OA stimulates RMG-1 proliferation by activating the FA transporter CD36. OA also increases uptake of glucose and glutamine, which subsequently activate the pentose phosphate pathway (PPP) and glutamine metabolism, respectively. Given that ribose 5-phosphate derived from the PPP is utilized for glutamine metabolism and the subsequent de novo nucleotide synthesis, our findings suggest that OA affects the PPP associated with Gln metabolism, rather than glycolysis associated with glutaminolysis; this leads ultimately to activation of DNA synthesis, which is required for cell proliferation. This selective activation by OA contrasts with the mechanisms observed in HNOA cells, in which OA-induced cell proliferation is driven by transcriptional regulation of the GLUT gene. The diverse responses of cancer cells to OA may be attributed to distinct mechanisms of OA reception and/or different metabolic pathways activated by OA.

Additive aluminum as a cause of induced immunoexcitoxicity resulting in neurodevelopmental and neurodegenerative disorders: A biochemical, pathophysiological, and pharmacological analysis.

Much has been learned about the neurotoxicity of aluminum over the past several decades in terms of its ability to disrupt cellular function, result in slow accumulation, and the difficulty of its removal from cells. Newer evidence suggests a central pathophysiological mechanism may be responsible for much of the toxicity of aluminum and aluminofluoride compounds on the brain and spinal cord. This mechanism involves activation of the brain's innate immune system, primarily the microglia, astrocytes, and macrophages, with a release of neurotoxic concentrations of excitotoxins and proinflammatory cytokines, chemokines, and immune mediators. Many studies suggest that excitotoxicity plays a significant role in the neurotoxic action of several metals, including aluminum. Recently, researchers have found that while most of the chronic pathology involved in the observed neurodegenerative effects of these metals are secondary to prolonged inflammation, it is the enhancement of excitotoxicity by the immune mediators that are responsible for most of the metal's toxicity. This enhancement occurs through a crosstalk between cytokines and glutamate-related mechanisms. The author coined the name immunoexcitotoxicity to describe this process. This paper reviews the evidence linking immunoexcitotoxicity to aluminum's neurotoxic effects and that a slow accumulation of aluminum may be the cause of neurodevelopmental defects as well as neurodegeneration in the adult.

DDMut-PPI: predicting effects of mutations on protein-protein interactions using graph-based deep learning.

Protein-protein interactions (PPIs) play a vital role in cellular functions and are essential for therapeutic development and understanding diseases. However, current predictive tools often struggle to balance efficiency and precision in predicting the effects of mutations on these complex interactions. To address this, we present DDMut-PPI, a deep learning model that efficiently and accurately predicts changes in PPI binding free energy upon single and multiple point mutations. Building on the robust Siamese network architecture with graph-based signatures from our prior work, DDMut, the DDMut-PPI model was enhanced with a graph convolutional network operated on the protein interaction interface. We used residue-specific embeddings from ProtT5 protein language model as node features, and a variety of molecular interactions as edge features. By integrating evolutionary context with spatial information, this framework enables DDMut-PPI to achieve a robust Pearson correlation of up to 0.75 (root mean squared error: 1.33 kcal/mol) in our evaluations, outperforming most existing methods. Importantly, the model demonstrated consistent performance across mutations that increase or decrease binding affinity. DDMut-PPI offers a significant advancement in the field and will serve as a valuable tool for researchers probing the complexities of protein interactions. DDMut-PPI is freely available as a web server and an application programming interface at https://biosig.lab.uq.edu.au/ddmut_ppi.

Histone deacetylase Hos2 regulates protein expression noise by potentially modulating the protein translation machinery.

Non-genetic variations derived from expression noise at transcript or protein levels can result in cell-to-cell heterogeneity within an isogenic population. Although cells have developed strategies to reduce noise in some cellular functions, this heterogeneity can also facilitate varying levels of regulation and provide evolutionary benefits in specific environments. Despite several general characteristics of cellular noise having been revealed, the detailed molecular pathways underlying noise regulation remain elusive. Here, we established a dual-fluorescent reporter system in Saccharomyces cerevisiae and performed experimental evolution to search for mutations that increase expression noise. By analyzing evolved cells using bulk segregant analysis coupled with whole-genome sequencing, we identified the histone deacetylase Hos2 as a negative noise regulator. A hos2 mutant down-regulated multiple ribosomal protein genes and exhibited partially compromised protein translation, indicating that Hos2 may regulate protein expression noise by modulating the translation machinery. Treating cells with translation inhibitors or introducing mutations into several Hos2-regulated ribosomal protein genes-RPS9A, RPS28B and RPL42A-enhanced protein expression noise. Our study provides an effective strategy for identifying noise regulators and also sheds light on how cells regulate non-genetic variation through protein translation.

MetalinksDB: a flexible and contextualizable resource of metabolite-protein interactions.

From the catalytic breakdown of nutrients to signaling, interactions between metabolites and proteins play an essential role in cellular function. An important case is cell-cell communication, where metabolites, secreted into the microenvironment, initiate signaling cascades by binding to intra- or extracellular receptors of neighboring cells. Protein-protein cell-cell communication interactions are routinely predicted from transcriptomic data. However, inferring metabolite-mediated intercellular signaling remains challenging, partially due to the limited size of intercellular prior knowledge resources focused on metabolites. Here, we leverage knowledge-graph infrastructure to integrate generalistic metabolite-protein with curated metabolite-receptor resources to create MetalinksDB. MetalinksDB is an order of magnitude larger than existing metabolite-receptor resources and can be tailored to specific biological contexts, such as diseases, pathways, or tissue/cellular locations. We demonstrate MetalinksDB's utility in identifying deregulated processes in renal cancer using multi-omics bulk data. Furthermore, we infer metabolite-driven intercellular signaling in acute kidney injury using spatial transcriptomics data. MetalinksDB is a comprehensive and customizable database of intercellular metabolite-protein interactions, accessible via a web interface (https://metalinks.omnipathdb.org/) and programmatically as a knowledge graph (https://github.com/biocypher/metalinks). We anticipate that by enabling diverse analyses tailored to specific biological contexts, MetalinksDB will facilitate the discovery of disease-relevant metabolite-mediated intercellular signaling processes.

Novel Dihydropteridinone Derivatives As Potent Inhibitors of the Understudied Human Kinases Vaccinia-Related Kinase 1 and Casein Kinase 1δ/ε.

Vaccinia-related kinase 1 (VRK1) and the δ and ε isoforms of casein kinase 1 (CK1) are linked to various disease-relevant pathways. However, the lack of tool compounds for these kinases has significantly hampered our understanding of their cellular functions and therapeutic potential. Here, we describe the structure-based development of potent inhibitors of VRK1, a kinase highly expressed in various tumor types and crucial for cell proliferation and genome integrity. Kinome-wide profiling revealed that our compounds also inhibit CK1δ and CK1ε. We demonstrate that dihydropteridinones 35 and 36 mimic the cellular outcomes of VRK1 depletion. Complementary studies with existing CK1δ and CK1ε inhibitors suggest that these kinases may play overlapping roles in cell proliferation and genome instability. Together, our findings highlight the potential of VRK1 inhibition in treating p53-deficient tumors and possibly enhancing the efficacy of existing cancer therapies that target DNA stability or cell division.

The axes of biology: a novel axes-based network embedding paradigm to decipher the functional mechanisms of the cell.

Common approaches for deciphering biological networks involve network embedding algorithms. These approaches strictly focus on clustering the genes' embedding vectors and interpreting such clusters to reveal the hidden information of the networks. However, the difficulty in interpreting the genes' clusters and the limitations of the functional annotations' resources hinder the identification of the currently unknown cell's functioning mechanisms. We propose a new approach that shifts this functional exploration from the embedding vectors of genes in space to the axes of the space itself. Our methodology better disentangles biological information from the embedding space than the classic gene-centric approach. Moreover, it uncovers new data-driven functional interactions that are unregistered in the functional ontologies, but biologically coherent. Furthermore, we exploit these interactions to define new higher-level annotations that we term Axes-Specific Functional Annotations and validate them through literature curation. Finally, we leverage our methodology to discover evolutionary connections between cellular functions and the evolution of species. Data and source code can be accessed at https://gitlab.bsc.es/sdoria/axes-of-biology.git.

Modification of extracellular matrix proteins by oxidants and electrophiles.

The extracellular matrix (ECM) is critical to biological architecture and determines cellular properties, function and activity. In many situations it is highly abundant, with collagens and elastin being some of the most abundant proteins in mammals. The ECM comprises of multiple different protein species and sugar polymers, with both different isoforms and post-translational modifications (PTMs) providing a large variety of microenvironments that play a key role in determining tissue structure and health. A number of the PTMs (e.g. cross-links) present in the ECM are critical to integrity and function, whereas others are deleterious to both ECM structure and associated cells. Modifications induced by reactive oxidants and electrophiles have been reported to accumulate in some ECM with increasing age. This accumulation can be exacerbated by disease, and in particular those associated with acute or chronic inflammation, obesity and diabetes. This is likely to be due to higher fluxes of modifying agents in these conditions. In this focused review, the role and effects of oxidants and other electrophiles on ECM are discussed, with a particular focus on the artery wall and atherosclerotic cardiovascular disease. Modifications generated on ECM components are reviewed, together with the effects of these species on cellular properties including adhesion, proliferation, migration, viability, metabolic activity, gene expression and phenotype. Increasing data indicates that ECM modifications are both prevalent in human and mammalian tissues and play an important role in disease development and progression.

Molecular regulation of PPARγ/RXRα signaling by the novel cofactor ZFP407.

Cofactors interacting with PPARγ can regulate adipogenesis and adipocyte metabolism by modulating the transcriptional activity and selectivity of PPARγ signaling. ZFP407 was previously demonstrated to regulate PPARγ target genes such as GLUT4, and its overexpression improved glucose homeostasis in mice. Here, using a series of molecular assays, including protein-interaction studies, mutagenesis, and ChIP-seq, ZFP407 was found to interact with the PPARγ/RXRα protein complex in the nucleus of adipocytes. Consistent with this observation, ZFP407 ChIP-seq peaks significantly overlapped with PPARγ ChIP-seq peaks, with more than half of ZFP407 peaks overlapping with PPARγ peaks. Transcription factor binding motifs enriched in these overlapping sites included CTCF, RARα/RXRγ, TP73, and ELK1, which regulate cellular development and function within adipocytes. Site-directed mutagenesis of frequent PPARγ phosphorylation or SUMOylation sites did not prevent its regulation by ZFP407, while mutagenesis of ZFP407 domains potentially necessary for RXR and PPARγ binding abrogated any impact of ZFP407 on PPARγ activity. These data suggest that ZFP407 controls the activity of PPARγ, but does so independently of post-translational modifications, likely by direct binding, establishing ZFP407 as a newly identified PPARγ cofactor. In addition, ZFP407 ChIP-seq analyses identified regions that did not overlap with PPARγ peaks. These non-overlapping peaks were significantly enriched for the transcription factor binding motifs of TBX19, PAX8, HSF4, and ZKSCAN3, which may contribute to the PPARγ-independent functions of ZFP407 in adipocytes and other cell types.

#1118 Direct delivery of novel gene therapy to podocytes enables pathway to clinical translation for the treatment of glomerular diseases

Abstract Background and Aims Adeno associated vector (AAV) gene therapy has the potential to treat a wide range of kidney diseases via the targeted delivery of genes to kidney cells to repair cellular and renal function. Despite the potential to impact many kidney conditions, kidney AAV gene therapy has proven challenging due to technical and physiological hurdles limiting the ability of AAV to be effectively delivered to podocytes. We have developed a novel AAV gene therapy, PS-001, and local method of administration, to effectively and safely deliver the podocin gene NPHS2 to podocytes. Biallelic NPHS2 mutations are the most common cause of monogenic childhood nephrotic syndrome. Curative efficacy and resolution of disease phenotype was demonstrated in transgenic murine models following PS-001 gene therapy treatment. The potential for translation of this approach to NPHS2 nephropathy patients in the clinic was also demonstrated in pre-clinical studies in Gottingen Minipigs. Method Transgenic murine models representative of NPHS2-driven nephropathy were treated with an AAV gene therapy encoding NPHS2, including a knock in mouse model (Nphs2R140Q/−) which introduces a R140Q mutation in the podocin gene. Mice were assessed for improvement in disease phenotype via analysis of proteinuria, serum albumin, renal histopathology and survival. Mice were treated with an analogue of PS-001, as the PS-001 capsid is not permissive in rodents. Gottingen minipigs were treated with PS-001 and followed for 4 weeks. Clinically relevant doses and a procedure for local administration specifically to the kidney were established. In-life safety assessments from blood and urine were monitored and at study end pig tissues were assessed for podocin biodistribution using multiple assays (qPCR, RT-qPCR, ELISA, RNAScope and IF) and for toxicological effects via histopathological analysis. Results Using our AAV gene therapy platform, which includes a capsid that is highly effective at transducing human podocytes and promoter that drives gene expression specifically in the podocyte, the gene therapy product PS-001 encoding NPHS2 was generated. Using a murine analogue of PS-001, in vivo proof of concept studies in a translationally relevant murine disease model (Nphs2R140Q/−) showed NPHS2 delivery and podocin expression in glomeruli and efficacy in terms of renal function rescue. This was demonstrated by resolution of severe proteinuria (mean ACR ug/mg 6049 ± 2803 vs 192 ± 51 in PS-001 treated animals, n = 11), improved serum albumin (g/L 27.50 ± 3.33 g/L vs 30.75 ± 2.46 in PS-001 treated animals, P = .021) and reduction in glomerulosclerosis (mean sclerosed glomeruli 81% ± 19 vs 18.75% ± 12 in PS-001 treated animals, P < .0001). The methods to translate the approach to the clinical setting using a local administration were established in pigs. Administration of PS-001 resulted in transgene mRNA expression across 89% ± 11% of kidney glomeruli as assessed by RNAScope (n = 3 pigs), and transgene derived podocin could be specifically detected in podocytes as assessed by IF analysis. Using qPCR, RT-PCR and ELISA it was shown that using local administration, podocin gene expression was restricted exclusively to the kidney glomerulus, with gene expression undetectable in off-target organs including the liver. Additional toxicological assessments of renal and other organ function from urine and blood, and post-study histopathological assessments revealed no pre-clinical treatment-related safety concerns. Conclusion We present data showing development of an AAV gene therapy and method of administration for the delivery of transgenes specifically to podocytes. We have shown transgenes can be efficiently targeted to podocytes to replace defective genes or to use the podocyte as a protein factory to modulate glomerular biology. This technology therefore provides an important novel modality for potentially treating a broad range of glomerular disease. PS-001 is being developed as a novel approach to treat steroid resistant nephrotic syndrome caused by mutated NPHS2, and may become the first podocyte targeted gene therapy to enter clinical development.

DeepGRNCS: deep learning-based framework for jointly inferring gene regulatory networks across cell subpopulations.

Inferring gene regulatory networks (GRNs) allows us to obtain a deeper understanding of cellular function and disease pathogenesis. Recent advances in single-cell RNA sequencing (scRNA-seq) technology have improved the accuracy of GRN inference. However, many methods for inferring individual GRNs from scRNA-seq data are limited because they overlook intercellular heterogeneity and similarities between different cell subpopulations, which are often present in the data. Here, we propose a deep learning-based framework, DeepGRNCS, for jointly inferring GRNs across cell subpopulations. We follow the commonly accepted hypothesis that the expression of a target gene can be predicted based on the expression of transcription factors (TFs) due to underlying regulatory relationships. We initially processed scRNA-seq data by discretizing data scattering using the equal-width method. Then, we trained deep learning models to predict target gene expression from TFs. By individually removing each TF from the expression matrix, we used pre-trained deep model predictions to infer regulatory relationships between TFs and genes, thereby constructing the GRN. Our method outperforms existing GRN inference methods for various simulated and real scRNA-seq datasets. Finally, we applied DeepGRNCS to non-small cell lung cancer scRNA-seq data to identify key genes in each cell subpopulation and analyzed their biological relevance. In conclusion, DeepGRNCS effectively predicts cell subpopulation-specific GRNs. The source code is available at https://github.com/Nastume777/DeepGRNCS.

Mitochondria-ER-PM contacts regulate mitochondrial division and PI(4)P distribution.

The mitochondria-ER-cortex anchor (MECA) forms a tripartite membrane contact site between mitochondria, the endoplasmic reticulum (ER), and the plasma membrane (PM). The core component of MECA, Num1, interacts with the PM and mitochondria via two distinct lipid-binding domains; however, the molecular mechanism by which Num1 interacts with the ER is unclear. Here, we demonstrate that Num1 contains a FFAT motif in its C-terminus that interacts with the integral ER membrane protein Scs2. While dispensable for Num1's functions in mitochondrial tethering and dynein anchoring, the FFAT motif is required for Num1's role in promoting mitochondrial division. Unexpectedly, we also reveal a novel function of MECA in regulating the distribution of phosphatidylinositol-4-phosphate (PI(4)P). Breaking Num1 association with any of the three membranes it tethers results in an accumulation of PI(4)P on the PM, likely via disrupting Sac1-mediated PI(4)P turnover. This work establishes MECA as an important regulatory hub that spatially organizes mitochondria, ER, and PM to coordinate crucial cellular functions.

Structural and functional mechanisms of actin isoforms.

Actin is a highly conserved and fundamental protein in eukaryotes and participates in a broad spectrum of cellular functions. Cells maintain a conserved ratio of actin isoforms, with muscle and non-muscle actins representing the main actin isoforms in muscle and non-muscle cells, respectively. Actin isoforms have specific and redundant functional roles and display different biochemistries, cellular localization, and interactions with myosins and actin-binding proteins. Understanding the specific roles of actin isoforms from the structural and functional perspective is crucial for elucidating the intricacies of cytoskeletal dynamics and regulation and their implications in health and disease. Here, we review how the structure contributes to the functional mechanisms of actin isoforms with a special emphasis on the questions of how post-translational modifications and disease-linked mutations affect actin isoforms biochemistry, function, and interaction with actin-binding proteins and myosin motors.

Association of c.+677 C>T (rs1801133) and c.+1298 A>C (rs1801131) MTHFR genetic variants with cardiometabolic and disease risk in systemic lupus erythematosus patients: A cross-sectional study.

Systemic lupus erythematosus (SLE) patients present a high prevalence of cardiometabolic risk, associated with worse clinical manifestations and mortality. Folate, an essential micronutrient that participates in vital immune cellular functions, could positively affect the cardiometabolic and disease risk in SLE, through the methylenetetrahydrofolate reductase (MTHFR) enzyme, which participates in the folate metabolism, where single nucleotide variants (SNVs) have been described as a potential genetic risk factor for SLE. The aim of this study was to determine the association of the c.+677C>T (rs1801133) and c.+1298 A>C (rs1801131) MTHFR genetic variants with cardiometabolic risk and clinical disease variables in SLE patients. A case-control study was conducted on 394 unrelated Mexican-mestizo women: 199 with SLE according to the 1997 SLE-ACR criteria and 196 control subjects (CS). Folic acid and homocysteine levels were evaluated by immunoassays. Genotyping of MTHFR genetic variants was carried out by allelic discrimination. No significant differences were found for folic acid (p = .15) and homocysteine serum levels (p = .59) between groups. According to the CC c.+677 MTHFR genotype, this was associated with low cardiovascular disease (CVD) risk by the Castelli index (OR = 0.42; p = .03) in SLE patients. The TC (OR = 1.3; p = .03) and the TA (OR = 1.6; p < .01) haplotypes from c.+677C>T plus c.+1298 MTHFR were associated with SLE risk, while the CC MTHFR haplotype (OR = 0.5; p = .01) was found as a non-risk factor for the disease. In conclusion, the TC and the TA MTHFR haplotypes are associated with disease risk; meanwhile, the CC c.+677 MTHFR genotype confers lower cardiometabolic risk in Mexican-mestizo SLE patients.

GAPS: a geometric attention-based network for peptide binding site identification by the transfer learning approach.

Protein-peptide interactions (PPepIs) are vital to understanding cellular functions, which can facilitate the design of novel drugs. As an essential component in forming a PPepI, protein-peptide binding sites are the basis for understanding the mechanisms involved in PPepIs. Therefore, accurately identifying protein-peptide binding sites becomes a critical task. The traditional experimental methods for researching these binding sites are labor-intensive and time-consuming, and some computational tools have been invented to supplement it. However, these computational tools have limitations in generality or accuracy due to the need for ligand information, complex feature construction, or their reliance on modeling based on amino acid residues. To deal with the drawbacks of these computational algorithms, we describe a geometric attention-based network for peptide binding site identification (GAPS) in this work. The proposed model utilizes geometric feature engineering to construct atom representations and incorporates multiple attention mechanisms to update relevant biological features. In addition, the transfer learning strategy is implemented for leveraging the protein-protein binding sites information to enhance the protein-peptide binding sites recognition capability, taking into account the common structure and biological bias between proteins and peptides. Consequently, GAPS demonstrates the state-of-the-art performance and excellent robustness in this task. Moreover, our model exhibits exceptional performance across several extended experiments including predicting the apo protein-peptide, protein-cyclic peptide and the AlphaFold-predicted protein-peptide binding sites. These results confirm that the GAPS model is a powerful, versatile, stable method suitable for diverse binding site predictions.

Targeting GLUT1 degradation with assembling glycopeptide for cancer inhibition

The upregulation of GLUT1 expression is closely associated with poor patient survival rates, highlighting its significance as a therapeutic target in tumor therapy. While efforts have predominantly focus on developing GLUT1 inhibitors, the crucial role of GLUT1 has been largely overlooked. Herein, we introduce a straightforward strategy involving the integration of mannose moiety into self-assembling peptides to exploit GLUT1 for enhanced cellular internalization. Additionally, the accumulation of glycosylated peptides prompts the self-assembly into nanofibers within lysosomes, initiating GLUT1 degradation and inducing lysosomal dysfunction, ultimately leading to cell death. Notably, peptides lacking mannose exhibit minimal cytosolic internalization, resulting in insignificant effects on GLUT1 expression and cellular functionality. Furthermore, in vivo studies demonstrated this assembling glycopeptide shows comparable efficacy to the chemotherapeutic drug Taxol. By simple incorporating mannose into self-assembling peptides and leveraging GLUT1′s role in modulating the cellular uptake of amphiphile peptides, this facile approach not only offers valuable insights for designing cell-permeable therapeutic peptide drugs, also holds promise for targeting the degradation of disease-associated proteins.

Cellular memory function from 3D to 2D: Three-dimensional high density collagen microfiber cultures induce their resistance to reactive oxygen species

Cell properties generally change when the culture condition is changed. However, mesenchymal stem cells cultured on a hard material surface maintain their differentiation characteristics even after being cultured on a soft material surface. This phenomenon suggests the possibility of a cell culture material to memorize stem cell function even in changing cell culture conditions. However, there are no reports about cell memory function in three-dimensional (3D) culture. In this study, colon cancer cells were cultured with collagen microfibers (CMF) in 3D to evaluate their resistance to reactive oxygen species (ROS) in comparison with a monolayer (2D) culture condition and to understand the effect of 3D-culture on cell memory function. The ratio of ROS-negative cancer cells in 3D culture increased with increasing amounts of CMF and the highest amount of CMF was revealed to be 35-fold higher than that of the 2D condition. The ROS-negative cells ratio was maintained for 7 days after re-seeding in a 2D culture condition, suggesting a 3D-memory function of ROS resistance. The findings of this study will open up new opportunities for 3D culture to induce cell memory function.

Recent Advances in the Inhibition of Membrane Lipid Peroxidation by Food-Borne Plant Polyphenols via the Nrf2/GPx4 Pathway.

Lipid peroxidation (LP) leads to changes in the fluidity and permeability of cell membranes, affecting normal cellular function and potentially triggering apoptosis or necrosis. This process is closely correlated with the onset of many diseases. Evidence suggests that the phenolic hydroxyl groups in food-borne plant polyphenols (FPPs) make them effective antioxidants capable of preventing diseases triggered by cell membrane LP. Proper dietary intake of FPPs can attenuate cellular oxidative stress, especially damage to cell membrane phospholipids, by activating the Nrf2/GPx4 pathway. Nuclear factor E2-related factor 2 (Nrf2) is an oxidative stress antagonist. The signaling pathway regulated by Nrf2 is a defense transduction pathway of the organism against external stimuli such as reactive oxygen species and exogenous chemicals. Glutathione peroxidase 4 (GPx4), under the regulation of Nrf2, is the only enzyme that reduces cell membrane lipid peroxides with specificity, thus playing a pivotal role in regulating cellular ferroptosis and counteracting oxidative stress. This study explored the Nrf2/GPx4 pathway mechanism, antioxidant activity of FPPs, and mechanism of LP. It also highlighted the bioprotective properties of FPPs against LP and its associated mechanisms, including (i) activation of the Nrf2/GPx4 pathway, with GPx4 potentially serving as a central target protein, (ii) regulation of antioxidant enzyme activities, leading to a reduction in the production of ROS and other peroxides, and (iii) antioxidant effects on LP and downstream phospholipid structure. In conclusion, FPPs play a crucial role as natural antioxidants in preventing LP. However, further in-depth analysis of FPPs coregulation of multiple signaling pathways is required, and the combined effects of these mechanisms need further evaluation in experimental models. Human trials could provide valuable insights into new directions for research and application.