Biochemical Genetics最新文献

Sepsis, a life-threatening condition characterized by a systemic inflammatory response, leads to organ dysfunction and high mortality rates. Honeysuckle, a traditional herbal remedy, has shown promise in attenuating organ damage and inhibiting pro-inflammatory factors in sepsis. However, the underlying molecular mechanisms remain unclear. We employed a multi-omics approach to elucidate honeysuckle's potential therapeutic effects in sepsis. RNA sequencing was performed on blood samples from 22 sepsis patients and 10 healthy controls to identify differentially expressed genes. Network pharmacology was utilized to predict effective ingredients and therapeutic targets of honeysuckle in sepsis. Meta-analysis compared gene expression between sepsis survivors and non-survivors. Single-cell RNA sequencing was employed to localize target gene expression at the cellular level. We identified 1328 differentially expressed genes in sepsis, with 221 upregulated and 1107 downregulated. Network analysis revealed 15 genes linked to 12 honeysuckle components. Four genes-DPP4, CD40LG, BCL2, and TP53-emerged as core therapeutic targets, showing decreased expression in non-survivors but upregulation in survivors. Single-cell analysis demonstrated that these genes were primarily expressed in T cells and other immune cells, suggesting their role in regulating immune response and inflammation. This study uses single-cell RNA sequencing and network analysis to identify DPP4, CD40LG, BCL2, and TP53 as key regulatory targets in sepsis, providing insights into disease mechanisms and potential therapeutic interventions. Network pharmacology analysis suggests possible interactions with honeysuckle compounds, though experimental validation is needed.

Atherosclerosis is the main cause of coronary artery disease (CAD), and it is not easy to be detected at the early stage. To mine biomarkers for early diagnosis of CAD. Potential molecular mechanism was mined using the biological databases. The qPCR and western blotting were used to detect the expression of LINC01220, hsa-miR- 6727 - 5p, and FBLN5. Dual-luciferase report assay and overexpression experiment were used to explore the regulation among LINC01220, hsa-miR- 6727 - 5p, and FBLN5. The cell viability, migration, apoptosis, and senescence were evaluated by CCK- 8, transwell, Annexin V/PI staining, and detection of aging markers. The differentiation of human bone marrow monocytes (HBMMs) was evaluated by detecting the expression of CD68, CD86, and iNOS. The clinical analysis was performed based on the blood samples from healthy individuals and asymptomatic CAD patients. The receiver operating characteristic (ROC) curve and logistic regression analysis were used to evaluate the diagnostic value of LINC01220/hsa-miR- 6727 - 5p/FBLN5 in CAD. Overexpression of LINC01220 promoted FBLN5 expression by down-regulating hsa-miR- 6727 - 5p. LINC01220 rescued human aortic endothelial cell (HAEC) viability injury, apoptosis, and senescence induced by oxidized low-density lipoprotein (ox-LDL), and inhibited HBMM migration and differentiation, by regulating hsa-miR- 6727 - 5p/FBLN5. The area under curve (AUC) of the LINC01220/hsa-miR- 6727 - 5p/FBLN5 axis in diagnosing CAD was 0.954 (0.919-0.990), with sensitivity of 91.9% and specificity of 91.7%. LINC01220 may hinder CAD progression by negatively regulating hsa-miR- 6727 - 5p which targeted FBLN5, and they were potential biomarkers of CAD.

NASH poses a significant threat to human health and is recognized as the leading contributor to HCC. In this study, we leveraged publicly accessible datasets to identify novel differentially expressed genes that may serve as potential targets in NASH or potentially NASH-induced HCC. The publicly available datasets were obtained from the GEO. Differential gene expression analysis and enrichment analysis was performed. Subsequently, WGCNA and PPI network were constructed. Lastly, machine learning was employed to identify key feature genes. Utilizing the integrated GEO database, we identified 446 genes exhibiting differential expression. Enrichment analysis indicated that these genes are predominantly associated with glucose and lipid metabolism and inflammatory processes. Through WGCNA, three modules were identified that demonstrated a significant correlation with NASH. Furthermore, core genes among the differentially expressed genes were extracted via protein and protein interaction analysis. Ultimately, machine learning techniques were employed, leading to the identification of three genes: FosB, Fos, and SOCS3. Notably, FosB exhibited consistent expression across various datasets, demonstrated strong predictive capabilities for NASH, and was associated with improved prognostic outcomes in hepatocellular carcinoma by data from TCGA. Additionally, in vitro immunohistochemistry experiments revealed significant reduction of FosB expression in NASH. Bioinformatics analyses conducted on various datasets, along with in vitro immunohistochemistry experiments, revealed significant downregulation of FosB in NASH. It indicates that FosB plays a critical role in the pathogenesis of NASH, and its expression is associated with the prognosis of patients with HCC. Further experimental studies are required to investigate the potential targeting of FosB in NASH and NASH-induced HCC.

Common bean (Phaseolus vulgaris) anthracnose, caused by Colletotrichum lindemuthianum affects and decreases its yield substantially. Fifty Simple Sequence Repeat (SSR) markers were used to analyze the genetic and genotypic variation among 36 C. lindemuthianum isolates. Among the 50 SSRs, 24 were polymorphic and amplified 66 alleles. Most of the SSRs had polymorphic information content (PIC) values > 0.30, indicating their strong discriminative competence. Distance based dendrogram analysis and population structure analysis divided 36 C. lindemuthianum isolates into three clusters. Analysis of molecular variance at spatiotemporal levels showed high genetic variation among the populations. The six C. lindemuthianum subpopulations had high Shannon-Wiener indices. The multilocus genotype and genetic diversity indices show that C. lindemuthianum populations in Kashmir are diverse. The three geographic subpopulations of C. lindemuthianum rejected the null hypothesis of linkage equilibrium (p = 0.001). Before this study, all PCR based genetic diversity studies on C. lindemuthianum relied on dominant markers. This study is the first to identify 24 robust SSRs, which can be utilized to elucidate the population structure of the common bean anthracnose pathogen.

SATB2-associated syndrome (SAS) is a multisystemic disorder characterized by developmental delay, moderate to profound intellectual disability, speech delay and/or absent speech, behavioral issues such as autistic tendencies, agitation or aggressive outbursts, self-injury, impulsivity, hyperactivity, anxiety and sleeping difficulties. Alterations in the SATB2 gene have been identified as pathogenic causes of SAS. No formal clinical diagnostic criteria have been established for SAS, and molecular disruption of SATB2 is necessary to confirm the diagnosis. To investigate the molecular pathogenesis of five sporadic patients with intellectual disability, and to delineate the comprehensive clinical characteristics of SAS patients. Whole-exome sequencing analysis was performed in five unrelated patients, and RNA analysis was employed to validate the impact of genetic variation on aberrant splicing. Five SATB2 variants were identified, three of which were novel, including three frameshift variants, one nonsense variant, and a missense variant resulting in aberrant splicing was verified by RNA analysis. A comparative analysis was conducted between the clinical features of our patients and those reported in the literature. In addition to intellectual disability and impaired speech, abnormalities in palmar creases and postnatal growth delay were highlighted as clinically significant features for the diagnosis of SAS. Language regression, as well as joints and fingers abnormalities were also observed in our cohort. Our findings demonstrate that effective mRNA analysis is helpful for understanding the pathogenic mechanisms of novel variants. This study broadens the genetic and phenotypic spectrum of SAS and enhances our knowledge to facilitate accurate genetic counseling and appropriate treatment options.

Tall fescue (Festuca arundinacea Schreb.), taxonomically synonymous with Lolium arundinaceum (Schreb.) Darbysh., is a cool-season perennial grass valued for adaptability, forage quality, and stress tolerance. This study evaluated the genetic diversity and population structure of 32 Tunisian spontaneous populations and 3 local varieties using CAAT-box Derived Polymorphism (CBDP) and Conserved DNA-Derived Polymorphism (CDDP) markers. Out of 16 tested primers (8 CBDP and 8 CDDP), 12 (7 CBDP and 5 CDDP) generated reproducible and polymorphic banding patterns, producing a total of 124 bands for CBDP and 121 bands for CDDP. High polymorphism was observed (86.29% for CBDP; 74.38% for CDDP), with a mean polymorphism information content (PIC) of 0.378, confirming the informativeness of both marker systems. Clustering analyses based on CBDP, CDDP, and combined data revealed some grouping tendencies among populations, but these groupings were not strictly associated with geographic origin, bioclimatic stage, or whether populations were spontaneous or cultivated. STRUCTURE analysis suggested two clusters for each marker system, but accessions showed overlapping membership, indicating weak population structure. The combined dataset detected four admixed groups, yet all populations displayed high admixture, reflecting high genetic diversity and extensive gene flow in this outcrossing species. Analysis of molecular variance (AMOVA) indicated that over 97% of the total genetic variation occurred within regions, while PhiPT values were low but significant (P = 0.004). No isolation by distance was detected with the Mantel test (CBDP: r = 0.011, p = 0.419; CDDP: r = 0.087, p = 0.078). This study is the first to apply CBDP and CDDP markers in Tunisian tall fescue populations, demonstrating their efficiency in revealing genetic diversity. The findings highlight substantial genetic diversity among populations within regions and underscore the value of this germplasm for breeding and conservation efforts.

Breast cancer (BC) is the leading cause of cancer mortality in women. The emergence of resistance to radiotherapy (RT) is a great challenge for BC treatment. Discoidin domain receptor 1 (DDR1) can modulate the proliferation, migration, and apoptosis of cancer cells, but its role in RT of BC has not been illuminated. This project evaluated the expression of DDR1 in BC based on single-cell RNA sequencing data. We established RT-resistant strains through radiation and detected the expression of DDR1 using qPCR. The proliferation and apoptosis abilities of BC cells were evaluated using CCK-8, colony formation assay, and flow cytometry. Western blot and IHC were applied to detect the levels of proteins related to the AMPK/SIRT1/PGC-1α pathway. The effect of the DDR1-mediated pathway on resistance to RT in BC was explored in combination with an AMPK inhibitor. DDR1 was highly expressed in BC. In vitro experiments demonstrated that knocking down DDR1 repressed the viability of BC cells during RT, curbed cell proliferation, facilitated apoptosis, and elevated the levels of p-AMPK, SIRT1, and PGC-1α proteins. The addition of an AMPK inhibitor reversed the effects of DDR1 knockdown on cell proliferation and apoptosis. In vivo experiments showed that knocking down DDR1 inhibited tumor growth, and the inhibitory effect was stronger when combined with radiation therapy. This study revealed that the upregulation of DDR1 in BC may reinforce RT resistance by modulating the AMPK/SIRT1/PGC-1α pathway, thus providing a new therapeutic target for improving the sensitivity of BC to RT.

With the increasing complexity of genomic data, traditional classification methods face dual challenges of the "curse of dimensionality" and class imbalance when processing multiple single nucleotide polymorphism (SNP) markers. To address these challenges, this study proposes an innovative approach integrating the Boruta dimensionality reduction algorithm with the Synthetic Minority Over-sampling Technique (SMOTE). The methodology involves two key steps: Feature optimization using the Boruta algorithm to identify the most representative genetic markers, thereby significantly reducing the complexity of high-dimensional data. Application of SMOTE technology to generate synthetic samples, balancing minority class distributions and alleviating data imbalance issues. Experimental results demonstrate that the proposed method outperforms traditional classifiers (Random Forest [RF], K-Nearest Neighbors [KNN], Extreme Gradient Boosting [XGBoost] and Convolutional Neural Network [CNN]) without Boruta-SMOTE integration across multiple metrics including accuracy, precision, recall, and F1-score. This study provides new insights for the conservation of donkey genetic resources, breed improvement, and commercial applications, while offering an effective solution for genomic data classification challenges.

The genetic etiology of hearing loss (HL) in Ecuador remains largely unexplored. This study investigates the spectrum of genetic variants associated with HL in a cohort of 66 Ecuadorian families using Exome or Genome sequencing (ES/GS). We identified pathogenic and likely pathogenic variants underlying HL in 27 families (41%). While variants were detected in 15 different genes, only GJB2 (in 12 families) and TMC1 (in 3 families) variants were identified in more than one family. The NM_004004.6 (GJB2):c.19 C > T (p.Gln7*) and NM_004004.6 (GJB2):c.35delG (p.Gly12Valfs*2) variants were more common than other alleles in GJB2. In some families, we detected variants of uncertain significance (VUS) in well-established HL genes and classified them as "possibly solved" due to their rarity and equivocal functional predictions. This study provides valuable insights into the genetic basis of HL in Ecuador and lays the groundwork for improved regional genetic diagnostics and management.

Streptomyces spp. is a crucial source for the drug discovery and development, especially those from extreme environments. The complete genome was sequenced to uncover the biosynthetic potential of the strain Qhu-M197 producing mithramycin isolated from the alpine meadow of the Qinghai-Tibetan Plateau. The results revealed that the genome consists of one linear chromosome and two plasmids with the size of 9.12 megabases (Mb) and the guanine-cytosine (G + C) content of 71.52%. The phylogenetic analyses of 16S rRNA gene and genome of strain Qhu-M197 suggested the strain belonged to Streptomyces genus, and the closest phylogenetic relationship between the strain Qhu-M197 and S. phaeoluteigriseus DSM 41896^T. The average nucleotide identity (ANI) and digital DNA-DNA hybridization (dDDH) values between Qhu-M197 and S. phaeoluteigriseus DSM 41896^T are 97.47% and 84.1%, respectively, indicating that they likely belong to the same species. However, comparative genomic analysis with closely related species reveals that Qhu-M197 may represent a novel strain of S. phaeoluteigriseus, highlighting its potential distinction at the strain level. The biosynthetic gene clusters (BGCs) analyzed by antiSMASH v7.0 revealed that Qhu-M197 had 33 BGCs encoding secondary metabolites. Interestingly, about 64% BGCs show less than 50% similarity to those annotated, which provides new opportunities for the discovery of novel natural products.