Search Results (308)

Ziziphus lotus (L.) Lam. (Rhamnaceae), a key shrub species native to North Africa, is commonly found in arid and semi-arid regions. Renowned for its resilience under harsh conditions, it forms vegetation clusters that influence the surrounding environment. These clusters create microhabitats that promote biodiversity, reduce soil erosion, and improve soil fertility. However, in agricultural fields, Z. lotus is often regarded as an undesirable species. This study investigated the bacterial diversity and community composition along spatial gradients around Z. lotus patches in barley-planted and non-planted fields. Using 16S rRNA gene sequencing, 84 soil samples were analyzed from distances of 0, 3, and 6 m from Z. lotus patches. MiSeq sequencing generated 143,424 reads, representing 505 bacterial ASVs across 22 phyla. Alpha-diversity was highest at intermediate distances (3 m), while beta-diversity analyses revealed significant differences in community composition across distances (p = 0.035). Pseudomonadota dominated close to the shrub (44% at 0 m) but decreased at greater distances, whereas Bacillota and Actinobacteriota displayed distinct spatial patterns. A core microbiome comprising 44 ASVs (8.7%) was shared across all distances, with the greatest number of unique ASVs identified at 3 m. Random forest analysis highlighted Skermanella and Rubrobacter as key discriminatory taxa. These findings emphasize the spatial structuring of bacterial communities around Z. lotus patches, demonstrating the shrub’s substantial influence on bacterial dynamics in arid ecosystems. Full article

Acute respiratory distress syndrome (ARDS) is an inflammatory pulmonary condition that remains at alarming rates of fatality, with neutrophils playing a vital role in its pathogenesis. Beyond their classical antimicrobial functions, neutrophils contribute to pulmonary injury via the release of reactive oxygen species, proteolytic enzymes, and neutrophil extracellular traps (NETs). To identify targets for treatment, it was found that epigenetic mechanisms, including histone modifications, hypomethylation, hypermethylation, and non-coding RNAs, regulate neutrophil phenotypic plasticity, survival, and inflammatory potential. It has been identified that neutrophils in ARDS patients exhibit abnormal methylation patterns and are associated with altered gene expression and prolonged neutrophil activation, thereby contributing to sustained inflammation. Histone citrullination, particularly via PAD4, facilitates NETosis, while histone acetylation status modulates chromatin accessibility and inflammatory gene expression. MicroRNAs have also been shown to regulate neutrophil activity, with miR-223 and miR-146a potentially being biomarkers and therapeutic targets. Neutrophil heterogeneity, as evidenced by distinct subsets such as low-density neutrophils (LDNs), varies across ARDS etiologies, including COVID-19. Single-cell RNA sequencing analyses, including the use of trajectory analysis, have revealed transcriptionally distinct neutrophil clusters with differential activation states. These studies support the use of epigenetic inhibitors, including PAD4, HDAC, and DNMT modulators, in therapeutic intervention. While the field has been enlightened with new findings, challenges in translational application remain an issue due to species differences, lack of stratification tools, and heterogeneity in ARDS presentation. This review describes how targeting neutrophil epigenetic regulators could help regulate hyperinflammation, making epigenetic modulation a promising area for precision therapeutics in ARDS. Full article

Noise-induced hearing loss (NIHL) is a significant occupational health issue, characterized by permanent damage to the cochlea due to prolonged exposure to high-intensity noise. Circulating microRNAs (c-miRNAs) have emerged as promising non-invasive indicators of inner ear pathology and potential modulators of cellular stress responses. Nevertheless, their specific roles in NIHL remain inadequately characterized. This study evaluated miRNA expression in the peripheral blood of individuals with bilateral NIHL (n = 12) and matched healthy controls (n = 6) using GeneChip^® miRNA 4.0 arrays. The Transcriptome Analysis Console software was used for differential expression analysis, and bioinformatic predictions of gene targets and pathway enrichment were performed using TargetScan (version 8.0) and the Enrichr tool. Among the 72 differentially expressed miRNAs (FDR < 0.05), hsa-miR-486-2, hsa-miR-664b-3p, hsa-miR-4485, hsa-miR-501, and hsa-miR-663b were notably upregulated, while hsa-miR-6723, hsa-miR-194-2, hsa-miR-668-5p, hsa-miR-4722-3p, and hsa-miR-4716 showed significant downregulation. Enrichment analyses indicated involvement in apoptosis regulation, mitochondrial stability, and cell cycle control. Principal component analysis (PCA) and clustering methods revealed clear molecular distinctions between the patient and control groups. The observed alterations in c-miRNA profiles highlight their relevance to NIHL-related cellular stress and degeneration. These findings support their utility as candidate biomarkers for diagnosis and prognosis, warranting further validation in functional and longitudinal studies. Full article

Recent findings have identified high-density lipoprotein (HDL) as a carrier of microRNAs, small non-coding RNAs that regulate gene expression, suggesting a potential novel functional and biochemical role for HDL-microRNA cargo. Here, we conduct an in-depth bioinformatics analysis of unique HDL-microRNA cargo to uncover their molecular mechanisms and potential applications as clinical biomarkers. First, using the Gene Expression Omnibus (GEO), we performed computational analysis on public human microRNA array datasets (GSE 25425; platform GPL11162) obtained from highly purified fractions of HDL in human plasma in order to identify their unique miRNA cargo. This led to the identification of eleven miRNAs present only in HDL, herein listed: hsa-miR-210, hsa-miR-26a-1, hsa-miR-628-3p, hsa-miR-31, hsa-miR-501-5p, hsa-miR-100-3p, hsa-miR-571, hsa-miR-100-5p, hsa-miR-23a, hsa-miR-550, and hsa-miR-432. Then, these unique miRNAs present in HDL were analyzed using a bioinformatics approach to recognize their validated target genes. The ClusterProfiler R package applied gene ontology and KEGG enrichment analysis. The key genes mainly enriched in the biological process of cellular regulation were identified and linked to neurodegeneration. Finally, the protein–protein interaction and co-expression network were analyzed using the STRING and GeneMANIA Cytoscape plugins. Full article

Stroke is a leading cause of morbidity and mortality worldwide, with ischemic stroke (IS) accounting for approximately 85% of cases. Recent research has highlighted the critical role of microRNAs (miRNAs), a class of small non-coding RNA molecules, in the pathogenesis of stroke. Among these, the miR-17-92 cluster and its paralogs have emerged as key regulators in the development of stroke pathology and the subsequent recovery processes. We emphasize their regulatory roles in key pathological processes, including inflammation, apoptosis, neuroprotection, and tissue repair. We provide an overview of these mechanisms to support the identification of novel miRNA-based therapeutic targets and to improve stroke diagnosis, treatment, and recovery strategies. Specific miRNAs, such as miR-19a, miR-18a, and miR-92a, contribute to processes including neurogenesis, axonal growth, and a reduction in neuronal apoptosis. The miR-17-92 cluster also offers potential therapeutic applications by targeting injury-induced pathways, such as modulating apoptosis, promoting axonal elongation, or inhibiting neurodegeneration. Preclinical studies have suggested their potential to enhance neural regeneration and promote functional recovery. Future research should further elucidate the regulatory mechanisms of the miR-17-92 members and their therapeutic potential to enhance stroke treatment strategies. Full article

This article focuses on the creation of a monitoring tool using routinely collected data from milk payment analyses. Milk samples were analyzed through Fourier Transform mid-infrared spectrometry every 1 to 3 days, and their compositions were predicted using machine learning models. Among the predicted parameters, fatty acid profiles appear to be effective indicators of animal status and management practices. In this research, these profiles were summarized using 31 fatty acids or groups of fatty acids. The methodology consists of four steps: hierarchical clustering to detect patterns in a Belgian spectral dataset (N = 774,781), interpretation of the identified seven clusters, development of predictive models applied to a Canadian dataset (N = 670,165), and validation using management information collected from Canadian farms. The identified clusters revealed significant relationships with feeding management strategies and temporal evolutions, highlighting the potential to develop automated alert systems that assist farmers and advisors in herd monitoring. Full article

Background: In Staphylococcus aureus, antimicrobial resistance (AMR) imposes significant fitness costs (FCs), including reduced growth rate, interbacterial competitiveness, and virulence. However, the FC molecular basis remains poorly understood. This study investigated the FC omic basis and compensatory adaptations in high-risk HA-, LA-, and CA-MRSA, acquiring mono- or cross-resistance to second-line daptomycin (DAP) and dalbavancin (DAL), as well as reduced susceptibility (RS) to first-line glycopeptides, i.e., vancomycin and teicoplanin (GLYs, i.e., VAN, TEC), related to the specific mechanism of action (MOA)-related AMR-mechanisms and genomic backgrounds, paying increasing FCs. Methods: The FC omic basis associated with mono- or cross- DAP-/DAL-R and GLY-RS were investigated by integrated omics. This study focused on core-genome essential (EG) and accessory virulence gene (VG) SNPomics and transcriptomics by Illumina MiSeq whole-genome sequencing, RNA-seq, and bioinformatic analysis. Results: Moderate impact nsSNPs were identified in EGs related to vital cellular functions and VGs. Comparative EG transcriptomics revealed differential expressions and key dysregulations—via asRNAs—prevalently affecting the protein synthesis and cell-envelope EG clusters, as well as the VG cluster. Conclusions: Our data, firstly, underlined the EG and VG mutation- and transcription-driven omic-based FC burden and the compensatory adaptations associated with the emergence of mono-DAP-R, cross-DAP-R/hGISA, and DAP-R/DAL-R/GISA, linked to specific MOA-related AMR-mechanisms and genomic backgrounds in high-risk HA-, LA-, and CA-MRSA. Full article

Background/Objectives: Salivary gland tumors (SGTs) are a rare and histologically heterogeneous group of neoplasms that are challenging to diagnose due to phenotypic heterogeneity and overlapping histomorphological markers. Accurate diagnosis is required for clinical management, particularly in unusual subtypes. The objective of this study was to ascertain whether attenuated total reflectance–Fourier transform infrared (ATR-FTIR) spectroscopy, in combination with enzymatic deglycosylation, would be useful in SGT classification by detecting glycosylation-related metabolic variations. Methods: 155 tissue sections, consisting of 80 SGTs and 75 controls, were analyzed. ATR-FTIR spectroscopy was used to record the mid-infrared (MIR) spectra (4000–400 cm⁻¹) of enzymatically untreated and deglycosylated samples. Spectral data were preprocessed and analyzed by principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA). Enzymatic deglycosylation focused on sialic acid and fucose residues with α2-3,6,8 neuraminidase, α1-2,4,6 fucosidase O, and α1-3,4 fucosidase. Results: Tumor and control samples were discriminated with an OPLS-DA model, achieving an accuracy of 81.9% (78.7% for controls and 85.0% for tumors), especially in the glycosylation-relevant spectral range (850–1250 cm⁻¹). Classification between benign and malignant tumors was more challenging, with an accuracy of 70.0% (72.5% for benign and 67.5% for malignant cases). Enzymatic deglycosylation resulted in detectable changes in the MIR spectra, confirming the contribution of glycosylation to tumor-specific signatures. Benign vs. malignant tumor discrimination was still poor and was not much enhanced in the sense of incorporating glycosylation-specific regions. Conclusions: ATR-FTIR spectroscopy coupled with enzymatic deglycosylation can distinguish tumor and control tissues based on glycan-associated spectral differences. Application of the technique to benign/malignant SGT discrimination is hampered by spectral overlap and tumor heterogeneity. Further research will be necessary to explore other clustering algorithms and larger and more homogeneous datasets for improved diagnostic accuracy. Full article

Background: Colubridae, known to be one of the most species-rich snake families, remains relatively understudied in termshe context of complete mitochondrial genome research. This study provide the first systematic characterization of the mitochondrial genomes of six colubrid species: Lycodon subcinctus, Lycodon rosozonatus, Lycodon fasciatus, Lycodon gongshan, Lycodon futsingensis, and Lycodon aulicus. Method: In this study, mitochondrial genomes were sequenced using Sanger sequencing. The raw data were subjected to quality- filtered withing using Fastp and subsequently assembled into complete mitochondrial genomes via SPAdes. Gene annotation was performed by Tblastn, Genewise (for CDS coding sequences), MiTFi (for transfer RNAs), and Rfam (for ribosomal RNAs). Sequence analyses were conducted with various tools, including MEGA, tRNAscan-SE, DnaSP, MISA, and REPuter. Finally, phylogenetic trees were reconstructed based on 13 protein-coding genes from 14 species. Results:The mitogenomes of these six species ranged from 17,143 to 17,298 bp in length and con-sisted of 13 protein-coding genes (PCGs), 22 transfer RNA genes (tRNAs), 2 ribosomal RNA genes (rRNAs), and 2 control regions. The nucleotide composition of the Colu-bridae mitogenomes was comparable with an A + T composition ranging from 52.1% to 58.8% except for the trnS1 and trnC. All the tRNAs could fold into a stable secondary structure. The Pi and Ka/Ks values suggested that atp8 was the fastest-evolving gene, while cox1 was the most conserved gene. Bayesian inference and maximum likelihood phylogenetic analyses yielded consistent results, with the six sequenced species clus-tering together with their congeneric species. These findings will provide valuable references for further research on the phylogeny of Colubridae. Full article

Cotton fiber length is an important measurement for application in the textile industry, and researchers are seeking to cultivate cotton plants with longer fibers. In this study, cotton fiber genes were systematically reviewed through meta-analysis in terms of extending and shortening fiber and the use of different research technologies for the first time. PubMed, Web of Science, China National Knowledge Infrastructure (CNKI), and Baidu Xueshu databases were included as literature retrieval sources. A total of 21,467 articles were retrieved, and 45 articles were used in the final analysis. Data analysis was performed using RevMan 5.4 software. To shorten cotton fiber length, clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 technology was superior to virus-induced gene silencing (VIGS) technology and RNA interference (RNAi) technology [p = 0.002, MD = −1.05, 95% CI (−1.73, −0.37), Chi² = 39.89]. To increase cotton fiber length, CRISPR-Cas9 technology had a similar effect as VIGS technology [p = 0.12, MD = −0.59, 95% CI (−1.33, −0.15), Chi² = 0.17]. When some genes (GhLAC15, GhALDH7B4, GhMDHAR1A/GhDHAR2A, STTM-miR396b, GhMYB44, GhFP2, GhMYB7, GhKNL1, GhTCP4, GhHDA5, GhGalT1, GhKNOX6, GhXB38D, and GhBZR3) were damaged, cotton fiber length increased. Furthermore, we found that after gene interference, the fiber-shortening genes occurred more frequently than the fiber-elongating genes. Synergistic research on these genes may better promote cotton fiber elongation. Full article

MicroRNAs (miRNAs) are crucial in physiological and pathological processes and serve as biomarkers for various diseases. We previously validated seven miRNA biomarkers and nine in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). In this study, we observed distinct clustering patterns of LUAD or LUSC tissues compared to paired normal tissues based on miRNA expression levels, suggesting the potential involvement of circulating miRNAs in non-small-cell lung cancer (NSCLC) progression. To elucidate their biological function, we identified the most significant differentially expressed miRNAs (DE-miRNAs)—hsa-miR-451a, hsa-miR-139-5p and hsa-miR-126-5p—using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. We then performed protein–protein interaction (PPI) analysis and constructed a miRNA-hub gene regulatory network based on targets predicted by several miRNA-target prediction tools. Additionally, we evaluated the biological functions of these miRNA biomarkers through EdU and wound healing assays in A549 cells. Our study identifies three miRNAs that may contribute to lung cancer progression by modulating cancer-related targets and highlights their potential as biomarkers. Future mechanistic investigations may provide novel insights into NSCLC pathogenesis and open new therapeutic avenues. Full article

The Fragile X mental retardation type 1 gene (FMR1) contains a CGG triplet cluster of varied length (30 repeats on average) located in its 5′ UTR. In its premutated state (54–200 repeats), FMR1 contributes to the pathogenesis of premature ovarian insufficiency (POI). Its gray zone alleles (41–54 repeats) are supposed to impair the ovarian function as well. In the case of a CGG repeat length > 200, Fragile X syndrome occurs. Post-transcriptional expression of FMR1 is regulated by microRNAs. Although miR-323a-3p overexpression suppresses FMR1 in various tissues, this relationship has not been evaluated in the human ovary. Additionally, this microRNA targets SMADs, which are suggested regulators of ovarian cell proliferation, growth, and function. This study investigated how FMR1 allele lengths with CGG repeat numbers n < 55 (normal and gray zone genotypes) relate to miR-323a-3p expression and how they may impact associated SMAD expression in human granulosa cells. COV434 cells and patient-derived GCs were used to evaluate FMR1, miR-323a-3p, and BMP/SMAD-pathway member expression levels. Briefly, miR-323a-3p was significantly upregulated in GCs of the gray zone group compared to the normal allele group (p < 0.0001), while the FMR1 level did not vary. Furthermore, the gray zone group showed a significant upregulation of BMPR2, SMAD1, SMAD4, and SMAD9. In contrast, the miR-323a-3p transfection of COV434 cells significantly downregulated SMAD3, SMAD4, SMAD5, and SMAD9, while the FMR1 and SMAD1 levels remained stable. Our findings highlight a CGG repeat number-dependent upregulation of miR-323a-3p and an alteration of the BMP/SMAD pathway, suggesting that these changes happen and contribute to impaired ovarian function independently. Full article

Major depressive disorder (MDD) is a complex psychiatric illness, with synaptic plasticity playing a key role in its pathology. Our study aims to investigate the molecular basis of MDD by analyzing synaptic plasticity-related gene expression at the single-cell level. Utilizing a published snRNA-seq dataset (GSE144136), we identified Excitatory.neurons_1 as the cell cluster most associated with MDD and synaptic plasticity through cell clustering, gene set enrichment analysis (GSEA), and pseudotime analysis. Integrating the bulk RNA-seq data (GSE38206), we identified CASKIN1 and CSTB as hub genes via differential expression analysis and machine learning methods. Further exploration of the relevant mechanisms was performed via cell–cell communication and ligand-receptor interaction analysis, functional enrichment analysis, and the construction of molecular regulatory networks, highlighting miR-21-5p as a key biomarker. We propose that elevated miR-21-5p in MDD downregulates CASKIN1 in Excitatory.neurons_1 cells, resulting in decreased neural connectivity and altered synaptic plasticity. As our analyzed snRNA-seq dataset consists solely of male samples, these findings may be male-specific. Our findings shed light on potential mechanisms underlying synaptic plasticity in MDD, offering novel insights into the disorder’s cellular and molecular dynamics. Full article

Background: Preeclampsia (PE) is a critical complication of pregnancy that affects 3% to 5% of all pregnancies and has been linked to aberrant placentation, causing severe maternal and fetal illness and death. Objectives: This systematic review aims to elucidate the association of in-utero endocrine-disrupting chemical (EDC) exposure and microRNAs and their imprinted genes from prenatal and maternal circulation of PE patients. Methods: Databases such as PubMed, PubMed Central, ScienceDirect, the Comparative Toxicogenomics Database (CTD), ProQuest, EBSCOhost, and Google Scholar were utilized to search for articles that investigate the relationships between selected EDCs and epigenetic events such as DNA methylation and microRNAs that are associated with PE. Results: A total of 29 studies were included in the database search. Altered expression of microRNAs (miR-15a-5p, miR-142-3p, and miR-185) in the placenta of PE patients was positively associated with the urinary concentration of phthalates and phenols in the development of the disease in the first trimester. EDCs such as phenols, phthalates, perfluoroalkyl substances (PFOAs), polybrominated diphenyl ethers (PBDEs), and organochlorine phosphates (OCPs) have been reported to be associated with hypertensive disorders in pregnancy. miRNA-31, miRNA-144, miRNA-145, miRNA-210, placental specific clusters (C14MC, and C19MC) may be used as possible targets for PE because of their potential roles in the onset and progression of PE. Conclusions: Prenatal EDC exposure, including exposure to BPA, showed association with signaling pathways including estrogen, sFlt-1/PlGF, ErbB, MAPK/ERK, and cholesterol mechanisms with placental hemodynamics. Even low EDC exposures leave altered epigenetic marks throughout gestation, which might cause PE complications. Full article

Transcription factors (TFs) and microRNAs (miRNAs) are fundamental regulators of gene expression, cell state, and biological processes. This study investigated whether a small subset of TFs and miRNAs could accurately predict genome-wide gene expression. We analyzed 8895 samples across 31 cancer types from The Cancer Genome Atlas and identified 28 miRNA and 28 TF clusters using unsupervised learning. Medoids of these clusters could differentiate tissues of origin with 92.8% accuracy, demonstrating their biological relevance. We developed Tissue-Agnostic and Tissue-Aware models to predict 20,000 gene expressions using the 56 selected medoid miRNAs and TFs. The Tissue-Aware model attained an $R^2$ of 0.70 by incorporating tissue-specific information. Despite measuring only 1/400th of the transcriptome, the prediction accuracy was comparable to that achieved by the 1000 landmark genes. This suggests the transcriptome has an intrinsically low-dimensional structure that can be captured by a few regulatory molecules. Our approach could enable cheaper transcriptome assays and analysis of low-quality samples. It also provides insights into genes that are heavily regulated by miRNAs/TFs versus alternative mechanisms. However, model transportability was impacted by dataset discrepancies, especially in miRNA distribution. Overall, this study demonstrates the potential of a biology-guided approach for robust transcriptome representation. Full article