Analysis Of Gene Function Research Articles

Identification and Verification of Key Genes in Colorectal Cancer Liver Metastases Through Analysis of Single-Cell Sequencing Data and TCGA Data

BackgroundColorectal cancer (CRC) is highly prevalent worldwide, with more patients experiencing colorectal cancer liver metastases (CRLM). This study aimed to identify key genes in CRLM through single-cell sequencing data reanalysis and experimental validation.MethodsThe study analyzed single-cell RNA-sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database. Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were used for gene functional enrichment analysis. The Cancer Genome Atlas (TCGA) data enabled bulk-RNA expression and survival prognosis analysis. Real-time polymerase chain reaction (qPCR) detected mRNA expression, whereas Western blot determined protein levels. Cell function experiments assessed SPARC’s impact on CRC cell behavior.ResultsCluster analysis showed 23 classes among 17 CRLM samples, representing six cell types. A GO and KEGG analysis identified interleukin-1 beta (IL1B), CD2 molecule (CD2), and C-X-C motif chemokine ligand 8 (CXCL8) as significant prognostic factors in CRC. Secreted protein acidic and cysteine rich (SPARC) was one of the top differentially expressed genes (DEGs) in tissue stem cells, confirmed in primary and metastatic lesions. Metastatic lesions showed higher expression of SPARC and CRC stem cell marker leucine-rich repeat containing G protein-coupled receptor 5 (LGR5), which was significantly correlated positively with LGR5 expression. Knockdown of SPARC reduced CRC cell sphere- and colony-formation, invasion, and migration abilities. Overexpression of SPARC significantly increased the malignancy of CRC cells.ConclusionsSeveral key genes were identified in the process of CRLM. In CRLM samples and those corresponding to CRC stem cells, SPARC was significantly upregulated. In the therapy of CRLM, SPARC might be a potential target.

Exploiting Brassica rapa L. subsp. pekinensis Genome Research

Chinese cabbage, Brassica rapa L. subsp. pekinensis is a crucial and extensively consumed vegetable in the world, especially Eastern Asia. The market demand for this leafy vegetable increases year by year, resulting in multiple challenges for agricultural researchers worldwide. Multi-omic approaches and the integration of functional genomics helps us understand the relationships between Chinese cabbage genomes and phenotypes under specific physiological and environmental conditions. However, challenges exist in integrating multi-omics for the functional analysis of genes and for developing potential traits for Chinese cabbage improvement. However, the panomics platform allows for the integration of complex omics, enhancing our understanding of molecular regulator networks in Chinese cabbage agricultural traits. In addition, the agronomic features of Chinese cabbage are significantly impacted by the environment. The expression of these agricultural features is tightly regulated by a combination of signals from both the internal regulatory network and the external growth environment. To comprehend the molecular process of these characteristics, it is necessary to have a prior understanding of molecular breeding for the objective of enhancing quality. While the use of various approaches in Chinese cabbage is still in its early stages, recent research has shown that it has the potential to uncover new regulators both rapidly and effectively, leading to updated regulatory networks. In addition, the utilization of the efficient transformation technique in conjunction with gene editing using CRISPR/Cas9 will result in a reduction in time requirements and facilitate a more precise understanding of the role of the regulators. Numerous studies about Chinese cabbage have been conducted in the past two decades, but a comprehensive review about its genome still limited. This review provides a concise summary of the latest discoveries in genomic research related to Brassica and explores the potential future developments for this species.

Arrayed CRISPRi library to suppress genes required for Schizosaccharomyces pombe viability.

The fission yeast, Schizosaccharomyces pombe, is an excellent eukaryote model organism for studying essential biological processes. Its genome contains ∼1,200 genes essential for cell viability, most of which are evolutionarily conserved. To study these essential genes, resources enabling conditional perturbation of target genes are required. Here, we constructed comprehensive arrayed libraries of plasmids and strains to knock down essential genes in S. pombe using dCas9-mediated CRISPRi. These libraries cover ∼98% of all essential genes in fission yeast. We estimate that in ∼60% of these strains, transcription of a target gene was repressed so efficiently that cell proliferation was significantly inhibited. To demonstrate the usefulness of these libraries, we performed metabolic analyses with knockdown strains and revealed flexible interaction among metabolic pathways. Libraries established in this study enable comprehensive functional analyses of essential genes in S. pombe and will facilitate the understanding of essential biological processes in eukaryotes.

Efficient Regeneration of Transgenic Rice from Embryogenic Callus via Agrobacterium-Mediated Transformation: A Case Study Using GFP and Apple MdFT1 Genes

Genetic transformation is a critical tool for gene manipulation and functional analyses in plants, enabling the exploration of key phenotypes and agronomic traits at the genetic level. While dicotyledonous plants offer various tissues for in vitro culture and transformation, monocotyledonous plants, such as rice, have limited options. This study presents an efficient method for genetically transforming rice (Oryza sativa L.) using seed-derived embryogenic calli as explants. Two target genes were utilized to assess regeneration efficiency: green fluorescent protein (eGFP) and the apple FLOWERING LOCUS T (FT)-like gene (MdFT1). Antisense MdFT1 was cloned into a vector controlled by the rice α-amylase 3D (Ramy3D) promoter, while eGFP was fused to Cas9 under the Ubi promoter. These vectors were introduced separately into rice embryogenic calli from two Korean cultivars using Agrobacterium-mediated transformation. Transgenic seedlings were successfully regenerated via hygromycin selection using an in vitro cultivation system. PCR confirmed stable transgene integration in the transgenic calli and their progeny. Fluorescence microscopy revealed eGFP expression, and antisense MdFT1-expressing lines exhibited notable phenotypic changes, including variations in plant height and grain quality. High transformation efficiency and regeneration frequency were achieved for both tested cultivars. This study demonstrated the effective use of seed-derived embryogenic calli for rice transformation, offering a promising approach for developing transgenic plants in monocot species.

The environmental microbial retrieving assessment of cell-processing facilities for cell therapy in a hospital laboratory.

Cell therapy represents a promising treatment modality. A critical component in the production of cell therapy products is maintaining the sterility of cell therapy clean rooms (CTCRs). This study aimed to evaluate the environmental microbial load within CTCRs. We systematically monitored microbial load in CTCRs, following established guidelines. Cultured microbial samples underwent metagenomic sequencing, and alpha and beta diversity analyses, functional annotation, and resistance gene profiling were performed using various bioinformatics tools to assess microbial diversity and function. From November 2023 to January 2024, we collected 42 environmental microbial colony samples from various sources within the CTCR and performed metagenomic sequencing on 39 samples. Alpha diversity analysis revealed no significant differences among surface, settle_plate, and airborne categories, but significant disparities within surface subgroups were revealed. Beta diversity analysis showed notable differences between surface and airborne categories and among surface subgroups. Species distribution analysis identified Bacillus as the predominant genus on surfaces. Functional annotation and resistance gene analysis indicated distinct resistance patterns, with significant variations between subgroups, such as microscopes and transfer windows, and hands and other Grade_B environments. Resistance to hydrogen peroxide was notably higher in the transfer window group. These findings highlight the importance of stringent disinfection protocols and enhanced hand hygiene to maintain sterility in CTCRs. These findings provide valuable insights for implementing effective measures to maintain cleanliness throughout CTCRs. The annotation and study of resistance genes can help rapidly identify methods to control cellular contamination under circumstances of environmental microbial pollution.IMPORTANCEMaintaining the sterility of cell therapy clean rooms (CTCRs) is crucial for the production of safe and effective cell therapy products. Our study systematically evaluated the environmental microbial load within CTCRs, revealing significant microbial diversity and distinct resistance patterns to disinfection methods. These findings underscore the need for stringent disinfection protocols and enhanced hand hygiene practices to ensure CTCR sterility. By identifying key microbial species and their resistance genes, our research provides essential insights into controlling contamination and safeguarding the production environment, ultimately contributing to the reliability and success of cell therapy treatments.

Potential Oncogenic and Immunosuppressive Roles of Multiple EGF-Like Domains 6 (MEGF6) in Colon Cancer: Insights from Bioinformatic Analysis

Multiple epidermal growth factor-like domains protein 6 (MEGF6) is a high molecular weight protein with several EGF-like domains. Although it has been demonstrated to promote metastasis and chemoresistance in colon cancer cells, its specific oncogenic and immunologic functions remain largely unexplored. This study aims to comprehensively analyze publicly available datasets to define the role of MEGF6 in colon cancer development and immune response modulation. The expression of MEGF6 in colon adenocarcinoma (COAD) and normal tissues at both mRNA and protein levels was assessed using the GEPIA2 and HPA databases, respectively. The UALCAN database was employed to examine the association between MEGF6 expression and clinicopathological outcomes in COAD patients, and survival analysis was conducted using the KM plotter database. Functional enrichment analysis of MEGF6-correlated genes was performed using the ShinyGO online tool. Additionally, the correlation of MEGF6 with immune cell infiltration and immunosuppressive molecules was explored through the TIMER and TISIDB databases. Our analysis revealed significantly higher mRNA and protein expressions of MEGF6 in COAD tissues compared to normal tissues, with associations to cancer stage, nodal metastasis status, and histological subtype. High MEGF6 expression was correlated with poorer survival outcomes, and genes correlated with MEGF6 were enriched in biological processes related to cellular component organization, cell adhesion, and extracellular matrix interaction. Furthermore, MEGF6 expression demonstrated a significant correlation with immune cell infiltration and the expression of immunosuppressive molecules, particularly CTLA-4, PD-1, PD-L1, TGF-β, and IL-10. In conclusion, our findings suggest that MEGF6 may play an oncogenic role by influencing cell and extracellular matrix interactions. Its overexpression may indicate immunosuppressive properties within the cancer microenvironment. Therefore, MEGF6 holds promise as a potential biomarker for predicting both prognosis and therapeutic responses in colon cancer. HIGHLIGHTS MEGF6 has been shown to involve colon cancer growth and chemotherapeutic resistance. Bioinformatics confirmed a prognostic significance of MEGF6 in colon cancer. MEGF6 may exert its oncogenic effects by influencing cell-matrix interactions. MEGF6 expression is correlated with immunosuppressive properties of cancers. GRAPHICAL ABSTRACT

Classification and functional analysis of disulfidptosis-associated genes in sepsis.

Sepsis represents a critical condition characterized by multiple-organ dysfunction resulting from inflammatory response to infection. Disulfidptosis is a newly identified type of programmed cell death that is intimately associated with the actin cytoskeleton collapse caused by glucose starvation and disulfide stress, but its role in sepsis is largely unknown. The study was to adopt a diagnostic and prognostic signature for sepsis with disulfidptosis based on the differentially expressed genes (DEGs) between sepsis and healthy people from GEO database. The disulfidptosis hub genes associated with sepsis were identified, and then developed consensus clustering and immune infiltration characteristics. Next, we evaluated disulfidptosis-related risk genes by using LASSO and Random Forest algorithms, and constructed the diagnostic sepsis model by nomogram. Finally, immune infiltration, GSVA analysis and mRNA-miRNA networks based on disulfidptosis-related DEGs were screened. There are five upregulated disulfidptosis-related genes and seven downregulated genes were filtered out. The six intersection disulfidptosis-related genes including LRPPRC, SLC7A11, GLUT, MYH9, NUBPL and GYS1 exhibited higher predictive ability for sepsis with an accuracy of 99.7%. In addition, the expression patterns of the critical genes were validated. The study provided a comprehensive view of disulfidptosis-based signatures to predict the prognosis, biological features and potential treatment directions for sepsis.

Exploring circulating MiRNA signature for osteosarcoma detection: Bioinformatics-based analyzing and validation

Early detection followed by efficient treatment still remain a considerable challenge for osteosarcoma (OS), indicating the importance of emerging innovative diagnostic methods. Circulating miRNAs offer a promising and non-invasive approach to assess the OS molecular landscapes. This study utilized RNAseq data from OS plasma miRNA expression profiles (PRJEB30542) and PCR Array data (GSE65071) from GEO and ENA databases. In total, 43 miRNAs demonstrated significant differential expression in OS samples of training dataset. A diagnostic model, including hsa-miR-30a-5p, hsa-miR-556–3p, hsa-miR-200a-3p, and hsa-miR-582–5p was identified through multivariate logistic regression analysis and demonstrated significant efficacy in differentiating OS patients from healthy controls in the validation group (AUC: 0.917, sensitivity: 1, specificity: 0.85). The result of target gene prediction and functional enrichment analyses revealed significant associations with terms such as epithelial morphogenesis, P53 and Wnt signaling pathways, and neoplasm metastasis. Further bioinformatics-based evaluations showed that the down-regulation of these miRNAs significantly correlates with poor prognosis and lower survival rate in OS patients and propose their tumor suppressor function in pathogenesis of OS. Furthermore, the study developed a miRNA-mRNA subnetwork that connects these miRNAs to the P53 and Wnt signaling pathways, which are critical pathways with oncogenic effects on OS progression. This comprehensive approach not only presents a promising diagnostic model but also proposes potential molecular markers for OS early diagnosis, making prognosis, and targeted therapy. The identified miRNA-mRNA functional axis holds promise as a valuable resource for further research in understanding OS pathogenesis and establishing therapeutic modalities.

Identification and Functional Analysis of Ras-Related Associated with Diabetes Gene (rrad) in Edwardsiella piscicida-Resistant Individuals of Japanese Flounder (Paralichthys olivaceus).

Ras-related associated with diabetes (RRAD) is a member of the Ras GTPase superfamily that plays a role in several cellular functions, such as cell proliferation and differentiation. In particular, the superfamily acts as an NF-κB signaling pathway inhibitor and calcium regulator to participate in the immune response pathway. A recent transcriptome study revealed that rrad was expressed in the spleen of disease-resistant Japanese flounder (Paralichthys olivaceus) individuals compared with disease-susceptible individuals, and the results were also verified by qPCR. Thus, the present study aimed to explore how rrad regulates antimicrobial immunity via the NF-κB pathway. First, the coding sequence of P. olivaceus rrad was identified. The sequence was 1092 bp in length, encoding 364 amino acids. Based on phylogenetic and structural relationship analyses, P. olivaceus rrad appeared to be more closely related to teleosts. Next, rrad expression differences between disease-resistant and disease-susceptible individuals in immune-related tissues were evaluated, and the results revealed that rrad was expressed preferentially in the spleen of disease-resistant individuals. In response to Edwardsiella piscicida infection, rrad expression in the spleen changed. In vitro, co-culture was carried out to assess the hypo-methylated levels of the rrad promoter in the disease-resistant spleen, which was consistent with the high mRNA expression. The siRNA-mediated knockdown of rrad performed with the gill cell line of P. olivaceus affected many rrad-network-related genes, i.e., dcp1b, amagt, rus1, rapgef1, ralbp1, plce1, rasal1, nckipsd, prkab2, cytbc-1, sh3, and others, as well as some inflammation-related genes, such as bal2 and Il-1β. In addition, flow cytometry analysis showed that rrad overexpression was more likely to induce cell apoptosis, with establishing a link between rrad's function and its potential roles in regulating the NF-κB pathway. Thus,. the current study provided some clarity in terms of understanding the immune response about rrad gene differences between disease-resistant and disease-susceptible P. olivaceus individuals. This study provides a molecular basis for fish rrad gene functional analysis and may serve as a reference for in-depth of bacterial disease resistance of teleost.

Brain gene expression reveals pathways underlying nocturnal migratory restlessness

Migration is one of the most extreme and energy demanding life history strategies to have evolved in the animal kingdom. In birds, champions of long-distance migrations, the seasonal emergence of the migratory phenotype is characterised by rapid physiological and metabolic remodelling, including substantial accumulation of fat stores and increases in nocturnality. The molecular underpinnings and brain adaptations to seasonal migrations remain poorly understood. Here, we exposed Common quails (Coturnix coturnix) to controlled changes in day length to simulate southward autumn migration, and then blocked the photoperiod until birds entered the non-migratory wintering phase. We first performed de novo RNA-Sequencing from selected brain samples (hypothalamus) collected from birds at a standardised time at night, either in a migratory state (when restlessness was highest and at their body mass peak), or in a non-migratory state and conducted differential gene expression and functional pathways analyses. We found that the migratory state was associated with up-regulation of a few, yet functionally well defined, gene expression networks implicated in fat trafficking, protein and carbohydrate metabolism. Further analyses that focused on candidate genes (apolipoprotein H or APOH, lysosomal associated membrane protein-2 or LAMP2) from samples collected during the day or night across the entire study population suggested differences in the expression of these genes depending on the time of the day with the largest expression levels being found in the migratory birds sampled at night. We also found that expression of APOH was positively associated with levels of nocturnal activity in the migratory birds; such an association was absent within the non-migratory birds. Our results provide novel experimental evidence revealing that hypothalamic changes in expression of apolipoprotein pathways, which regulate the circulatory transport of lipids, are likely key regulatory activators of nocturnal migratory movements. Our study paves the way for performing deeper functional investigations on seasonal molecular remodelling underlying the development of the migratory phenotype.

Low-dose 60Co-γ-ray irradiation promotes the growth of cucumber seedlings by inducing CsSAUR37 expression.

Cucumber (Cucumis sativus L.) is a major vegetable crop grown globally, with a cultivation history of more than 3000years. The limited genetic diversity, low rate of intraspecific variation, and extended periods of traditional breeding have resulted in slow progress in their genetic research and the development of new varieties. Gamma (γ)-ray irradiation potentially accelerates the breeding progress; however, the biological and molecular effects of γ-ray irradiation on cucumbers are unknown. Exposing cucumber seeds to 0, 50, 100, 150, 200, and 250Gy doses of 60Co-γ-ray irradiation, this study aimed to investigate the resulting phenotype and physiological characteristics of seedling treatment to determine the optimal irradiation dose. The results showed that low irradiation doses (50-100Gy) enhanced root growth, hypocotyl elongation, and lateral root numbers, promoting seedling growth. However, high irradiation doses (150-250Gy) significantly inhibited seed germination and growth, decreasing the survival rate of seedlings. More than 100Gy irradiation significantly decreased the total chlorophyll content while increasing the malondialdehyde (MDA) and H2O2 content in cucumber. Transcriptome sequencing analysis at 0, 50, 100, 150, 200, and 250Gy doses showed that gene expression significantly differed between low and high irradiation doses. Gene Ontology enrichment and functional pathway enrichment analyses revealed that the auxin response pathway played a crucial role in seedling growth under low irradiation doses. Further, gene function analysis revealed that small auxin up-regulated gene CsSAUR37 was a key gene that was overexpressed in response to low irradiation doses, promoting primary root elongation and enhancing lateral root numbers by regulating the expression of protein phosphatase 2Cs (PP2Cs) and auxin synthesis genes.

Changes in Ergosterol Biosynthesis Alter the Response to Cycloheximide, 4-Nitroquinoline-N-Oxide, Weak Organic Acids, and Virulence in Candida glabrata.

The ERG6 gene encodes the sterol C24-methyltransferase converting zymosterol to fecosterol in the ergosterol biosynthetic pathway. Here, we extend the results of functional analysis of the CgERG6 gene, which was previously shown to modulate drug susceptibility in Candida glabrata mutant cells, by demonstrating that its deletion leads to increased susceptibility to cycloheximide, 4-nitroquinoline-N-oxide and weak organic acids, and such effects are associated with attenuated virulence. Together with abrogated efflux of drug substrates by CgCdr1p and CgPdr12p, the Cgerg6Δ mutation leads to reduced cell surface hydrophobicity and decreased virulence of the mutant cells of C. glabrata. The absence of CgErg6p impacts the lipid organization and function of the plasma membrane, resulting in non-specific permeability and abrogation of normal function of membrane-bound proteins accompanied by decreased virulence in Cgerg6Δ cells. Galleria mellonella larvae were used as a non-vertebrate animal host model to determine differences in the virulence potential of C. glabrata strains (parental strain and the Cgerg6Δ deletion mutant). We found that Cgerg6Δ mutant strain attenuated in virulence caused 25-30% survival of larvae compared with parental strain.

Combined Analysis of Human and Experimental Rat Samples Identified Biomarkers for Ischemic Stroke.

The genetic transcription profile and underlying molecular mechanisms of ischemic stroke (IS) remain elusive. To address this issue, four mRNA and one miRNA expression profile of rats with middle cerebral artery occlusion (MCAO) were acquired from the Gene Expression Omnibus (GEO) database. A total of 780 differentially expressed genes (DEGs) and 56 miRNAs (DEMs) were screened. Gene set and functional enrichment analysis revealed that a substantial number of immune-inflammation-related pathways were abnormally activated in IS. Through weighted gene co-expression network analysis, the turquoise module was identified as meaningful. By taking the intersection of the turquoise module genes, DEM-target genes, and all DEGs, 354 genes were subsequently obtained as key IS-related genes. Among them, six characteristic genes were identified using the least absolute shrinkage and selection operator. After validation with three external datasets, transforming growth factor beta 1 (Tgfb1) was selected as the hub gene. This finding was further confirmed by gene expression pattern analysis in both the MCAO model rats and clinical IS patients. Moreover, the expression of the hub genes exhibited a negative correlation with the modified Rankin scale score (P < 0.05). Collectively, these results expand our knowledge of the genetic profile and molecular mechanisms involved in IS and suggest that the Tgfb1 gene is a potential biomarker of this disease.

Identification of the Optimal Quantitative RT-PCR Reference Gene for Paper Mulberry (Broussonetia papyrifera).

Paper Mulberry (Broussonetia papyrifera) possesses medicinal, economic, and ecological significance and is extensively used for feed production, papermaking, and ecological restoration due to its ease of propagation, rapid growth rate, and strong stress resistance. The recent completion of the sequencing of the Paper Mulberry genome has prompted further research into the genetic breeding and molecular biology of this important species. A highly stable reference gene is essential to enhance the quantitative analysis of functional genes in Paper Mulberry; however, none has been identified. Accordingly, in this study, the leaves, stems, roots, petioles, young fruits, and mature fruits of Paper Mulberry plants were selected as experimental materials, and nine candidate reference genes, namely, α-TUB1, α-TUB2, β-TUB, H2A, ACT, DnaJ, UBQ, CDC2, and TIP41, were identified by RT-qPCR. Their stability was assessed using the geNorm, Normfinder, Delta Ct, BestKeeper, and RefFinder algorithms, identifying ACT and UBQ as showing the greatest stability. The expression of BpMYB090, which regulates the production of trichomes, was examined in the leaves of plants of the wild type (which have more trichomes) and mutant (which have fewer trichomes) at various developmental stages to validate the results of this study. As a result, their identification addresses a critical gap in the field of Paper Mulberry research, providing a solid foundation for future research that will concentrate on the characterization of pertinent functional genes in this economically valuable species.

Exploring microbial diversity and biosynthetic potential in zoo and wildlife animal microbiomes

Understanding human, animal, and environmental microbiota is essential for advancing global health and combating antimicrobial resistance (AMR). We investigate the oral and gut microbiota of 48 animal species in captivity, comparing them to those of wildlife animals. Specifically, we characterize the microbiota composition, metabolic pathways, AMR genes, and biosynthetic gene clusters (BGCs) encoding the production of specialized metabolites. Our results reveal a high diversity of microbiota, with 585 novel species-level genome bins (SGBs) and 484 complete BGCs identified. Functional gene analysis of microbiomes shows diet-dependent variations. Furthermore, by comparing our findings to wildlife-derived microbiomes, we observe the impact of captivity on the animal microbiome, including examples of converging microbiome compositions. Importantly, our study identifies AMR genes against commonly used veterinary antibiotics, as well as resistance to vancomycin, a critical antibiotic in human medicine. These findings underscore the importance of the ‘One Health’ approach and the potential for zoonotic transmission of pathogenic bacteria and AMR. Overall, our study contributes to a better understanding of the complexity of the animal microbiome and highlights its BGC diversity relevant to the discovery of novel antimicrobial compounds.

Signature Genes Selection and Functional Analysis of Astrocytoma Phenotypes: A Comparative Study.

Novel cancer biomarkers discoveries are driven by the application of omics technologies. The vast quantity of highly dimensional data necessitates the implementation of feature selection. The mathematical basis of different selection methods varies considerably, which may influence subsequent inferences. In the study, feature selection and classification methods were employed to identify six signature gene sets of grade 2 and 3 astrocytoma samples from the Rembrandt repository. Subsequently, the impact of these variables on classification and further discovery of biological patterns was analysed. Principal component analysis (PCA), uniform manifold approximation and projection (UMAP), and hierarchical clustering revealed that the data set (10,096 genes) exhibited a high degree of noise, feature redundancy, and lack of distinct patterns. The application of feature selection methods resulted in a reduction in the number of genes to between 28 and 128. Notably, no single gene was selected by all of the methods tested. Selection led to an increase in classification accuracy and noise reduction. Significant differences in the Gene Ontology terms were discovered, with only 13 terms overlapping. One selection method did not result in any enriched terms. KEGG pathway analysis revealed only one pathway in common (cell cycle), while the two methods did not yield any enriched pathways. The results demonstrated a significant difference in outcomes when classification-type algorithms were utilised in comparison to mixed types (selection and classification). This may result in the inadvertent omission of biological phenomena, while simultaneously achieving enhanced classification outcomes.

A combined model of six serum microRNAs as diagnostic markers for hepatocellular carcinoma

BackgroundHepatocellular carcinoma (HCC) is associated with high morbidity and mortality, and its poor prognosis is mainly due to the lack of an effective means of early diagnosis. This study aimed to identify a group of serum microRNAs (miRNAs) as potential biomarkers for the diagnosis of HCC. MethodsWe collected 190 HCC cases, 109 benign lesions of the liver, 40 cases of non-HCC tumors, and 130 healthy controls. The 469 participants were divided into training and validation sets. A literature search revealed 12 miRNAs closely associated with HCC. In the training set, significantly differentially expressed miRNAs (DEmiRNAs) were screened using real-time quantitative PCR, and a diagnostic model of HCC was constructed using logistic regression analysis. An independent validation was performed using a validation set. The identified DE miRNAs were subjected to target gene prediction and functional analyses. ResultsCompared to the controls, the levels of miR-21, miR-221, miR-801, and miR-1246 significantly decreased in HCC (P < 0.05), while the levels of miR-26a and miR-122 significantly increased (P < 0.05). A diagnostic model based on the six DE miRNAs was successfully constructed, with AUC values of 0.953 for the training set and 0.952 for the verification set. Finally, 100 target genes of the DE miRNAs were predicted and were significantly enriched in the B cell receptor, neurotrophin, ferroptosis, and EGFR tyrosine kinase inhibitor resistance signaling pathways. ConclusionsThe constructed diagnostic model based on six DE miRNA combinations has important clinical value for the early diagnosis of HCC

Study on the mechanism of SAR1B in sodium acetate promoting milk fat synthesis.

Acetate can promote milk fat synthesis in dairy cow mammary epithelial cells (BMECs). In this study, gene function analysis was used to explore the role of Ras family secretion-related GTP binding protein 1B (SAR1B) in milk fat synthesis of BMECs and its role and molecular mechanism in acetate-promoted milk fat synthesis. We found that the synthesis of lipid droplets and triglycerides was inhibited, and the expression levels of key genes and proteins in milk fat synthesis such as FASN and ACC were decreased in SAR1B knockout, which was reversed by overexpression of SAR1B. Addition of sodium acetate in BMECs can promote the expression of SAR1B, and SAR1B plays an important role in the synthesis of milk fat promoted by sodium acetate. We further investigated the underlying mechanism of SAR1B upregulation by sodium acetate, and found that sodium acetate could affect SAR1B expression through the positive regulation of SAR1B gene promoter activity by C/EBPβ and PPARγ. In conclusion, the results suggest that SAR1B can promote milk fat synthesis in BMECs, while C/EBPβ and PPARγ play important roles in sodium acetate to promote the expression of SAR1B.

Probiotic properties, whole-genome sequence analysis, and safety assessment of BreviBacillus borstelensis S8

In previous studies, BreviBacillus borstelensis S8 exhibited favorable enzyme production characteristics. In this study, the whole genome of Br borstelenensis S8 was sequenced to analyze its genomic sequence information and functions, investigating its genotype and potential probiotic properties. The whole genome sequence of S8 was determined to be 5,559,180 bp with an average GC content of 51.5%. A total of 5406 protein-coding genes were identified and annotated using NCBI Prokaryotic Genome Annotation. By comparing it with the complete genome sequences of Bacillus cereus strains, 1911 orthologous gene families were recognized. Genome analysis revealed the absence of active antibiotic resistance genes, virulence factor genes, and toxin-encoding genes. Safety assessments included hemolytic assays, antibiotic resistance tests, and evaluations of biogenic amine production. Functional gene analysis highlighted S8's metabolic pathways based on its genomic features. The presence of adhesion-related genes, stress response genes (e.g., acid and bile salts), antimicrobial gene clusters, and genes involved in vitamin and essential amino acid synthesis in the genome showcased the probiotic potential of S8. Simultaneously, analysis of hemolytic activity, biogenic amines production ability, acid and bile salt tolerance for the strain S8 also demonstrated its probiotic traits. The genomic exploration and probiotic activity of S8 revealed its potential as a probiotic, offering valuable genomic insights and a foundation for its safe utilization in the food industry.

Identifying cell types by lasso-constraint regularized Gaussian graphical model based on weighted distance penalty.

Single-cell RNA sequencing (scRNA-seq) technology is one of the most cost-effective and efficacious methods for revealing cellular heterogeneity and diversity. Precise identification of cell types is essential for establishing a robust foundation for downstream analyses and is a prerequisite for understanding heterogeneous mechanisms. However, the accuracy of existing methods warrants improvement, and highly accurate methods often impose stringent equipment requirements. Moreover, most unsupervised learning-based approaches are constrained by the need to input the number of cell types a prior, which limits their widespread application. In this paper, we propose a novel algorithm framework named WLGG. Initially, to capture the underlying nonlinear information, we introduce a weighted distance penalty term utilizing the Gaussian kernel function, which maps data from a low-dimensional nonlinear space to a high-dimensional linear space. We subsequently impose a Lasso constraint on the regularized Gaussian graphical model to enhance its ability to capture linear data characteristics. Additionally, we utilize the Eigengap strategy to predict the number of cell types and obtain predicted labels via spectral clustering. The experimental results on 14 test datasets demonstrate the superior clustering accuracy of the WLGG algorithm over 16 alternative methods. Furthermore, downstream analysis, including marker gene identification, pseudotime inference, and functional enrichment analysis based on the similarity matrix and predicted labels from the WLGG algorithm, substantiates the reliability of WLGG and offers valuable insights into biological dynamic biological processes and regulatory mechanisms.