Search Results (42)

Wound healing is a complex and dynamic process involving several stages of tissue repair. This study has shown that extracellular vesicles (EVs) derived from the callus of Camellia japonica L. and their associated microRNAs (miRNAs) possess significant wound healing activities. In human fibroblasts, EVs from C. japonica L. stimulated wound healing and upregulated collagen gene expression. The EVs also decreased inflammation levels in human keratinocytes, supporting wound healing. Among the miRNAs identified, miR408, one of the abundant miRNAs in the EVs, also showed similar wound healing efficacy. These findings suggest that both EVs and miR408 from the callus of C. japonica L. play a pivotal role in promoting wound healing. Additionally, this study shows that the regulation of miRNAs between different kingdoms can be achieved and suggests a new direction for the utilization of plant-derived components. Full article

Berberis kaschgarica Rupr.-derived exosome-like nanovesicles (BELNs), a type of plant-derived extracellular vesicle, consist of proteins, lipids, and nucleic acids. In this research, we employed differential centrifugation and ultracentrifugation techniques to isolate and purify BELNs. Subsequently, we conducted a comprehensive multi-omics analysis to systematically determine their physicochemical properties. Experiments were conducted in vitro with Human Umbilical Vein Endothelial Cells (HUVECs) to verify the therapeutic impact of BELNSs on atherosclerosis. The isolated BELNs exhibited a distinctive teacup-shaped exosome morphology. The extraction yield was approximately 2.1 × 10¹³ particles per milliliter, and the average particle size was measured to be 179.1 nm. These nanovesicles were lipid-rich. The protein content predominantly comprised cytoplasmic proteins. In-depth analysis revealed the presence of five highly conserved plant microRNAs: miR166, miR156, miR399, miR171, and miR395. These miRNAs are involved in regulating plant growth and responses to both biotic and abiotic stresses. Functional assays demonstrated that Berberis kaschgarica Rupr.-derived exosome-like nanovesicles substantially decreased the lipid deposition in HUVECs that was triggered by Palmitic Acid (PA). This research establishes the inaugural utilization of multi-omics platforms to systematically elucidate the bioactivity profile of BELNs from Berberis kaschgarica Rupr., thereby laying the groundwork for advancing its therapeutic potential. Full article

Tea (Camellia sinensis L.) holds agricultural economic value and forestry carbon sequestration potential, with Taiwan’s annual tea production exceeding TWD 7 billion. However, climate change-induced stressors threaten tea plant growth, photosynthesis, yield, and quality, necessitating an accurate real-time monitoring system to enhance plantation management and production stability. This study surveys tea plantations at low, mid-, and high elevations in Nantou County, central Taiwan, collecting data from 21 fields using conventional farming methods (CFMs), which emphasize intensive management, and agroecological farming methods (AFMs), which prioritize environmental sustainability. This study integrates leaf area index (LAI), photochemical reflectance index (PRI), and quantum yield of photosystem II (ΦPSII) data with unmanned aerial vehicles (UAV)-derived visible-light and multispectral imagery to compute color indices (CIs) and multispectral indices (MIs). Using feature ranking methods, an optimized dataset was developed, and the predictive performance of eight regression algorithms was assessed for estimating tea plant physiological parameters. The results indicate that LAI was generally lower in AFMs, suggesting reduced leaf growth density and potential yield differences. However, PRI and ΦPSII values revealed greater environmental adaptability and potential long-term ecological benefits in AFMs compared to CFMs. Among regression models, MIs provided greater stability for tea plant physiological parameters, whereas feature ranking methods had minimal impact on accuracy. XGBoost outperformed all models in predicting parameters, achieving optimal results for (1) LAI: R² = 0.716, RMSE = 1.01, MAE = 0.683, (2) PRI: R² = 0.643, RMSE = 0.013, MAE = 0.009, and (3) ΦPSII: R² = 0.920, RMSE = 0.048, MAE = 0.013. Overall, we highlight the effectiveness of integrating gradient boosting models with multispectral data to capture tea plant physiological characteristics. This study develops generalizable predictive models for tea plant physiological parameter estimation and advances non-contact crop physiological monitoring for tea plantation management, providing a scientific foundation for precision agriculture applications. Full article

Background/Objectives: microRNAs are small non-coding RNAs that regulate gene expression by inducing mRNA degradation or inhibiting translation. A growing body of evidence suggests that miRNAs may be utilized as anti-cancer therapeutics by targeting expression of key genes involved in cancerous transformation and progression. Renal cell cancer (RCC) is the most common kidney malignancy. The most efficient RCC treatments involve blockers of immune checkpoints, including antibodies targeting PD-L1 (Programmed Death Ligand 1). Interestingly, recent studies revealed the cross-kingdom horizontal transfer of plant miRNAs into mammalian cells, contributing to the modulation of gene expression by food ingestion. Here, we hypothesized that PD-L1 expression may be modulated by miRNAs originating from edible plants. Methods: To verify this hypothesis, we performed bioinformatic analysis to identify mes-miR395e from Manihot esculenta (cassava) as a promising candidate miRNA that could target PD-L1. To verify PD-L1 regulation mediated by the predicted plant miRNA, synthetic mes-miR395 mimics were transfected into cell lines derived from RCC tumors, followed by evaluation of PD-L1 expression using qPCR and Western blot. Results: Transfection of mes-miR395e mimics into RCC-derived cell lines confirmed that this miRNA decreases expression of PD-L1 in RCC cells at both mRNA and protein levels. Conclusions: This preliminary study shows the promise of plant miRNA as potential adjuvants supporting RCC treatment. Full article

Early detection of nitrogen deficiency in cotton requires timely identification of stress symptoms like leaf chlorosis (yellowing) and canopy stunting. Chlorosis initially appears in older, lower-canopy leaves, which are often not visible in conventional nadir-looking imaging. This study investigates oblique ground-based multispectral imaging to estimate plant height and capture spectral details from the upper (UC) and lower (LC) cotton canopy layers. Images were collected from four camera pitch and height configurations: set 1 (30°, 2 m), set 2 (55°, 2 m), set 3 (68°, 3 m), and set 4 (70°, 1.5 m). A pre-trained monocular depth estimation model (MiDaS) was used to estimate plant height from aligned RGB images and an empirically derived tangential model corrected for perspective distortion. Further, the lower and upper vertical halves of the plants were categorized as LC and UC, with vegetation indices (CI_green, CI_rededge) calculated for each. The aligned images in set 1 had the best sharpness and quality. The plant height estimates from set 1 had the highest correlation (r = 0.64) and lowest root mean squared error (RMSE = 0.13 m). As the images became more oblique, alignment and monocular depth/height accuracy decreased. Also, the effects of perspective and object-scale ambiguity in monocular depth estimation were prominent in the high oblique and relatively low altitude images. The spectral vegetation indices (VIs) were affected by band misalignment and shadows. VIs from the different canopy layers demonstrated moderate correlation with leaf nitrogen concentration, and sets 2 and 3 specifically showed high and low differences in VIs from the UC and LC layers for the no and high-nitrogen treatments, respectively. However, improvements in the multispectral alignment process, extensive data collection, and ground-truthing are needed to conclude whether the LC spectra are useful for early nitrogen stress detection in field cotton. Full article

Banana streak GF virus (BSGFV) is the extremely dangerous monopartite badnavirus (genus, Badnavirus; family, Caulimoviridae) of banana (Musa acuminata AAA Group) that imposes a serious threat to global banana production. The BSGFV causes a devastating pandemic in banana crops, transmitted by deadly insect pest mealybug vectors and replicated through an RNA intermediate. The BSGFV is a reverse-transcribing DNA virus that has a monopartite open circular double-stranded DNA (dsDNA) genome with a length of 7325 bp. RNA interference (RNAi) is a natural mechanism that has revolutionized the target gene regulation of various organisms to combat virus infection. The current study aims to locate the potential target binding sites of banana-encoded microRNAs (mac-miRNAs) on the BSGFV-dsDNA-encoded mRNAs based on three algorithms, RNA22, RNAhybrid and TAPIR. Mature banana (2n = 3x = 33) miRNAs (n = 32) were selected and hybridized to the BSGFV genome (MN296502). Among the 32 targeted mature locus-derived mac-miRNAs investigated, two banana mac-miRNA homologs (mac-miR162a and mac-miR172b) were identified as promising naturally occurring biomolecules to have binding affinity at nucleotide positions 5502 and 9 of the BSGFV genome. The in silico banana-genome-encoded mac-miRNA/mbg-miRNA-regulatory network was developed with the BSGFV—ORFs using Circos software (version 0.69-9) to identify potential therapeutic target proteins. Therefore, the current work provides useful biological material and opens a new range of opportunities for generating BSGFV-resistant banana plants through the genetic manipulation of the selected miRNAs. Full article

Background: Edible plants have been linked to the mitigation of metabolic disturbances in liver and adipose tissue, including the decrease of lipogenesis and the enhancement of lipolysis and adipocyte browning. In this context, plant microRNAs could be key bioactive molecules underlying the cross-kingdom beneficial effects of plants. This study sought to explore the impact of plant-derived microRNAs on the modulation of adipocyte and hepatocyte genes involved in metabolism and thermogenesis. Methods: Plant miR6262 was selected as a candidate from miRBase for the predicted effect on the regulation of human metabolic genes. Functional validation was conducted after transfection with plant miRNA mimics in HepG2 hepatocytes exposed to free fatty acids to mimic liver steatosis and hMADs cells differentiated into brown-like adipocytes. Results: miR6262 decreases the expression of the predicted target RXRA in the fatty acids-treated hepatocytes and in brown-like adipocytes and affects the expression profile of critical genes involved in metabolism and thermogenesis, including PPARA, G6PC, SREBF1 (hepatocytes) and CIDEA, CPT1M and PLIN1 (adipocytes). Nevertheless, plant miR6262 mimic transfections did not decrease hepatocyte lipid accumulation or stimulate adipocyte browning. Conclusions: these findings suggest that plant miR6262 could have a cross-kingdom regulation relevance through the modulation of human genes involved in lipid and glucose metabolism and thermogenesis in adipocytes and hepatocytes. Full article

Crop monitoring with unmanned aerial vehicles (UAVs) has the potential to reduce field monitoring costs while increasing monitoring frequency and improving efficiency. However, the utilization of RGB-based UAV imagery for crop-specific monitoring, especially for sugarcane, remains limited. This work proposes a UAV platform with an RGB camera as a low-cost solution to monitor sugarcane fields, complementing the commonly used multi-spectral methods. This new approach optimizes the RGB vegetation indices for accurate prediction of sugarcane growth, providing many improvements in scalable crop-management methods. The images were captured by a DJI Mavic Pro drone. Four RGB vegetation indices (VIs) (GLI, VARI, GRVI, and MGRVI) and the crop surface model plant height (CSM_PH) were derived from the images. The fractional vegetation cover (FVC) values were compared by image classification. Sugarcane plant height predictions were generated using two machine learning (ML) algorithms—multiple linear regression (MLR) and random forest (RF)—which were compared across five predictor combinations (CSM_PH and four VIs). At the early stage, all VIs showed significantly lower values than later stages (p < 0.05), indicating an initial slow progression of crop growth. MGRVI achieved a classification accuracy of over 94% across all growth phases, outperforming traditional indices. Based on the feature rankings, VARI was the least sensitive parameter, showing the lowest correlation (r < 0.5) and mutual information (MI < 0.4). The results showed that the RF and MLR models provided better predictions for plant height. The best estimation results were observed withthe combination of CSM_PH and GLI utilizing RF model (R² = 0.90, RMSE = 0.37 m, MAE = 0.27 m, and AIC = 21.93). This study revealed that VIs and the CSM_PH derived from RGB images captured by UAVs could be useful in monitoring sugarcane growth to boost crop productivity. Full article

Colorectal cancer (CRC) ranks as the third most prevalent global malignancy, marked by significant metastasis and post-surgical recurrence, posing formidable challenges to treatment efficacy. The integration of oligonucleotides with chemotherapeutic drugs emerges as a promising strategy for synergistic CRC therapy. The nanoformulation, lipid nanoparticle (LNP), presents the capability to achieve co-delivery of oligonucleotides and chemotherapeutic drugs for cancer therapy. In this study, we constructed lipid nanoparticles, termed as LNP-I-V by microfluidics to co-deliver oligonucleotides miR159 mimics (VDX05001SI) and irinotecan (IRT), demonstrating effective treatment of CRC both in vitro and in vivo. The LNP-I-V exhibited a particle size of 118.67 ± 1.27 nm, ensuring excellent stability and targeting delivery to tumor tissues, where it was internalized and escaped from the endosome with a pH-sensitive profile. Ultimately, LNP-I-V significantly inhibited CRC growth, extended the survival of tumor-bearing mice, and displayed favorable safety profiles. Thus, LNP-I-V held promise as an innovative platform to combine gene therapy and chemotherapy for improving CRC treatment. Full article

Plant-parasitic nematodes (PPNs) are among the most serious phytopathogens and cause widespread and serious damage in major crops. In this study, using a genome mining method, we identified nonribosomal peptide synthetase (NRPS)-like enzymes in genomes of plant-parasitic nematodes, which are conserved with two consecutive reducing domains at the N-terminus (A-T-R₁-R₂) and homologous to fungal NRPS-like ATRR. We experimentally investigated the roles of the NRPS-like enzyme (MiATRR) in nematode (Meloidogyne incognita) parasitism. Heterologous expression of Miatrr in Saccharomyces cerevisiae can overcome the growth inhibition caused by high concentrations of glycine betaine. RT-qPCR detection shows that Miatrr is significantly upregulated at the early parasitic life stage (J2s in plants) of M. incognita. Host-derived Miatrr RNA interference (RNAi) in Arabidopsis thaliana can significantly decrease the number of galls and egg masses of M. incognita, as well as retard development and reduce the body size of the nematode. Although exogenous glycine betaine and choline have no obvious impact on the survival of free-living M. incognita J2s (pre-parasitic J2s), they impact the performance of the nematode in planta, especially in Miatrr-RNAi plants. Following application of exogenous glycine betaine and choline in the rhizosphere soil of A. thaliana, the numbers of galls and egg masses were obviously reduced by glycine betaine but increased by choline. Based on the knowledge about the function of fungal NRPS-like ATRR and the roles of glycine betaine in host plants and nematodes, we suggest that MiATRR is involved in nematode–plant interaction by acting as a glycine betaine reductase, converting glycine betaine to choline. This may be a universal strategy in plant-parasitic nematodes utilizing NRPS-like ATRR to promote their parasitism on host plants. Full article

Sugarcane mosaic virus (SCMV) (genus, Potyvirus; family, Potyviridae) is widespread, deleterious, and the most damaging pathogen of sugarcane (Saccharum officinarum L. and Saccharum spp.) that causes a substantial barrier to producing high sugarcane earnings. Sugarcane mosaic disease (SCMD) is caused by a single or compound infection of SCMV disseminated by several aphid vectors in a non-persistent manner. SCMV has flexuous filamentous particle of 700–750 nm long, which encapsidated in a positive-sense, single-stranded RNA molecule of 9575 nucleotides. RNA interference (RNAi)-mediated antiviral innate immunity is an evolutionarily conserved key biological process in eukaryotes and has evolved as an antiviral defense system to interfere with viral genomes for controlling infections in plants. The current study aims to analyze sugarcane (Saccharum officinarum L. and Saccharum spp.) locus-derived microRNAs (sof-miRNAs/ssp-miRNAs) with predicted potential for targeting the SCMV +ssRNA-encoded mRNAs, using a predictive approach that involves five algorithms. The ultimate goal of this research is to mobilize the in silico- predicted endogenous sof-miRNAs/ssp-miRNAs to experimentally trigger the catalytic RNAi pathway and generate sugarcane cultivars to evaluate the potential antiviral resistance surveillance ability and capacity for SCMV. Experimentally validated mature sugarcane (S. officinarum, 2n = 8X = 80) and (S. spp., 2n = 100–120) sof-miRNA/ssp-miRNA sequences (n = 28) were downloaded from the miRBase database and aligned with the SCMV genome (KY548506). Among the 28 targeted mature locus-derived sof-miRNAs/ssp-miRNAs evaluated, one sugarcane miRNA homolog, sof-miR159c, was identified to have a predicted miRNA binding site, at nucleotide position 3847 of the SCMV genome targeting CI ORF. To verify the accuracy of the target prediction accuracy and to determine whether the sugarcane sof-miRNA/ssp-miRNA could bind the predicted SCMV mRNA target(s), we constructed an integrated Circos plot. A genome-wide in silico-predicted miRNA-mediated target gene regulatory network was implicated to validate interactions necessary to warrant in vivo analysis. The current work provides valuable computational evidence for the generation of SCMV-resistant sugarcane cultivars. Full article

Melanoma is a type of skin cancer known for its high mortality rate. Cancer stem cells (CSCs) are a subpopulation of cancer cells that significantly contribute to tumour recurrence and differentiation. Epigenetic-specific changes involving miRNAs maintain CSCs. Plant polyphenols have been reported to be involved in cancer chemoprevention and chemotherapy, with miRNAs being the novel effectors in their biological activities. A polyphenol-enriched blueberry preparation (PEBP) derived from fermented blueberries has demonstrated promising chemopreventative properties on breast cancer stem cells by influencing inflammatory pathways and miRNAs. In our current investigation, we seek to unveil the impact of PEBP on inhibiting melanoma development and to elucidate the underlying mechanisms. Our study employs various human cell lines, including an ex vivo cell line derived from a patient’s metastatic tumour. We found that it elevates miR-200c, increasing E-cadherin expression and inhibiting miR-210-3p through NF-κB signalling, impacting Epithelial-to-Mesenchymal Transition (EMT), a critical process in cancer progression. PEBP increases the SOCS1 expression, potentially contributing to miR-210-3p inhibition. Experiments involving miRNA manipulation confirm their functional roles. The study suggests that PEBP’s anti-inflammatory effects involve regulating miR-200c and miR-210 expression and their targets in EMT-related pathways. The overall aim is to provide evidence-based supportive care and preclinical evaluation of PEBP, offering a promising strategy for skin cancer chemoprevention. Full article

UVB significantly impacts the occurrence of cutaneous disorders, ranging from inflammatory to neoplastic diseases. Polyphenols derived from plants have been found to exhibit photoprotective effects against various factors that contribute to skin cancer. During the fermentation of the polyphenol-enriched blueberry preparation (PEBP), small oligomers of polyphenols were released, thus enhancing their photoprotective effects. This study aimed to investigate the protective effects of PEBP on UVB-induced skin inflammation. Topical preparations of polyphenols were applied to the skin of dorsally shaved mice. Mice were subsequently exposed to UVB and were sacrificed 90 min after UVB exposure. This study revealed that pretreatment with PEBP significantly inhibited UVB-induced recruitment of mast and neutrophil cells and prevented the loss of skin thickness. Furthermore, the findings show that PEBP treatment resulted in the downregulation of miR-210, 146a, and 155 and the upregulation of miR-200c and miR-205 compared to the UVB-irradiated mice. Additionally, PEBP was found to reduce the expression of IL-6, IL-1β, and TNFα, inhibiting COX-2 and increasing IL-10 after UVB exposure. Moreover, DNA methylation analysis indicated that PEBP might potentially reduce the activation of inflammation-related pathways such as MAPK, Wnt, Notch, and PI3K-AKT signaling. Our finding suggests that topical application of PEBP treatment may effectively prevent UVB-induced skin damage by inhibiting inflammation. Full article

Cotton leaf curl Kokhran virus (CLCuKoV) (genus, Begomovirus; family, Geminiviridae) is one of several plant virus pathogens of cotton (Gossypium hirsutum L.) that cause cotton leaf curl disease in Pakistan. Begomoviruses are transmitted by the whitefly Bemisia tabaci cryptic species group and cause economic losses in cotton and other crops worldwide. The CLCuKoV strain, referred to as CLCuKoV-Bur, emerged in the vicinity of Burewala, Pakistan, and was the primary causal virus associated with the second CLCuD epidemic in Pakistan. The monopartite ssDNA genome of (2.7 Kb) contains six open reading frames that encode four predicted proteins. RNA interference (RNAi)-mediated antiviral immunity is a sequence-specific biological process in plants and animals that has evolved to combat virus infection. The objective of this study was to design cotton locus-derived microRNA (ghr-miRNA) molecules to target strains of CLCuKoV, with CLCuKoV-Lu, as a typical CLCuD-begomovirus genome, predicted by four algorithms, miRanda, RNA22, psRNATarget, and RNA hybrid. Mature ghr-miRNA sequences (n = 80) from upland cotton (2n = 4x = 52) were selected from miRBase and aligned with available CLCuKoV-Lu genome sequences. Among the 80 cotton locus-derived ghr-miRNAs analyzed, ghr-miR2950 was identified as the most optimal, effective ghr-miRNA for targeting the CLCuKoV-Lu genome (nucleotide 82 onward), respectively, based on stringent criteria. The miRNA targeting relies on the base pairing of miRNA–mRNA targets. Conservation and potential base pairing of binding sites with the ghr-miR2950 were validated by multiple sequence alignment with all available CLCuKoV sequences. A regulatory interaction network was constructed to evaluate potential miRNA–mRNA interactions with the predicted targets. The efficacy of miRNA targeting of CLCuKoV was evaluated in silico by RNAi-mediated mRNA cleavage. This predicted targets for the development of CLCuD-resistant cotton plants. Full article

Biofertilizer as an amendment has growing awareness. Little attention has been paid to bioremediation potential of indigenous heavy-metal-resistant microbes, especially when isolated from long-term polluted soil, as a bioinoculant in biofertilizers. Biofertilizers are a type of versatile nutrient provider and soil conditioner that is cost-competitive and highly efficient with nondisruptive detoxifying capability. Herein, we investigated the effect of biofertilizers containing indigenous cadmium (Cd)-resistant microbial consortia on rice growth and physiological response. The Thai rice cultivar PSL2 (Oryza sativa L.) was grown in Cd-enriched soils amended with 3% biofertilizer. The composition of the biofertilizers’ bacterial community at different taxonomic levels was explored using 16S rRNA gene Illumina MiSeq sequencing. Upon Cd stress, the test biofertilizer had maximum mitigating effects as shown by modulating photosynthetic pigment, MDA and proline content and enzymatic antioxidants, thereby allowing increased shoot and root biomass (46% and 53%, respectively) and reduced grain Cd content, as compared to the control. These phenomena might be attributed to increased soil pH and organic matter, as well as enriched beneficial detoxifiers, i.e., Bacteroidetes, Firmicutes and Proteobacteria, in the biofertilizers. The test biofertilizer was effective in alleviating Cd stress by improving soil biophysicochemical traits to limit Cd bioavailability, along with adjusting physiological traits such as antioxidative defense. This study first demonstrated that incorporating biofertilizer derived from indigenous Cd-resistant microbes could restrict Cd contents and consequently enhance plant growth and tolerance in polluted soil. Full article