Bioinformatic analysis of the molecular targets of curcumin in colorectal cancer.

Colorectal cancer (CRC) is a major global health concern, with rising incidence and mortality rates. Conventional treatments often come with significant complications, prompting the exploration of natural compounds like curcumin as potential therapeutic agents. Using bioinformatic tools, this study investigated the role of curcumin in CRC treatment. Significant protein interactions between curcumin and target proteins were identified in the STITCH database. Differentially expressed genes (DEGs) associated with CRC were then analyzed from GEO databases. Comparing curcumin targets and CRC-related DEGs, nine significant common targets were identified: DNMT1, PCNA, CCND1, PLAU, MMP3, SOX9, FOXM1, CXCL2, and SERPINB5. Pathway enrichment analyses revealed that curcumin-targeted pathways were primarily related to p53, IL-17, NF-kappa B, TNF, and cell cycle signaling, all crucial in CRC development and progression. Further analyses using DAID and EnrichR algorithms showed that the curcumin targets exhibited greater specificity to bronchial epithelial cells and colorectal adenocarcinoma than other diseases. Analyses via the DSigDB database indicated that curcumin ranks highly among other drugs targeting the identified CRC-related genes. Docking studies revealed favorable binding interactions between curcumin and the key CRC-related proteins, suggesting potential molecular mechanisms by which curcumin may exert its effects. In summary, this study provides bioinformatic and docking evidence that curcumin may exert beneficial effects on CRC by modulating the expression or activity of multiple CRC-susceptibility genes involved in critical signaling pathways. These findings warrant further experimental validation and support the potential of curcumin as a therapeutic agent for CRC.

Investigation of Fructus Ligustri Lucidi for Premature Ovarian Insufficiency based on a Network Pharmacology and Experiment Verifications.

INTRODUCTION: Premature ovarian insufficiency [POI] is a disease characterized by a premature decline in ovarian function before the age of 40. In China, Ligustrum lucidum [FLL] has long been used to improve ovarian function and treat POI. METHODS: This study aims to verify the effect of FLL on POI through network pharmacology, molecular docking, and in-vitro cell experiments. RESULTS: A total of 13 active substances were screened in FLL, including including quercetin, taxifolin, luteolin, kaempferol, and beta-sitosterol. Then, network analysis found that FLL may exert effects on POI through 10 targets, including AR, ESR1, ESR2, KDR, CYP19A1, CLPP, GC, MMP3, PPARG, and STS. According to GO and KEGG enrichment analysis, FLL is associated with mechanisms related to estrogen, including steroid hormone biosynthesis, ovarian steroidogenesis, and the estrogen signaling pathway. Molecular docking confirms the interaction between the active ingredients of FLL and CYP19A1, which encodes aromatase. CCK8 experiment confirmed that quercetin and taxifolin can enhance the proliferation of KGN granulosa cells, while quercetin, taxifolin, and kaempferol can inhibit the apoptosis of KGN granulosa cells. ELISA experiments have confirmed that quercetin, taxifolin, luteolin, and kaempferol can increase the synthesis of estradiol in KGN granulosa cells. WB confirms that quercetin can increase the expression level of CYP19A1 in KGN cells. CONCLUSION: FLL can improve the proliferation, apoptosis, and synthesis of estradiol in ovarian granulosa cells, and has the potential to treat POI.

Identification of chemoresistance targets in doxorubicin-resistant lung adenocarcinoma cells using LC-MS/MS-based proteomics.

Acquired chemoresistance remains a significant challenge in the clinics as most of the treated cancers eventually emerge as hard-to-treat phenotypes. Therefore, identifying chemoresistance targets is highly warranted to manage the disease better. In this study, we employed a label-free LC-MS/MS-based quantitative proteomics analysis to identify potential targets and signaling pathways underlying acquired chemoresistance in a sub-cell line (A549DR) derived from the parental lung adenocarcinoma cells (A549) treated with gradually increasing doses of doxorubicin (DOX). Our proteomics analysis identified 146 upregulated and 129 downregulated targets in A549DR cells. The KEGG pathway and Gene ontology (GO) analysis of differentially expressed upregulated and downregulated proteins showed that most abundant upregulated pathways were related to metabolic pathways, cellular senescence, cell cycle, and p53 signaling. Meanwhile, the downregulated pathways were related to spliceosome, nucleotide metabolism, DNA replication, nucleotide excision repair, and nuclear-cytoplasmic transport. Further, STRING analysis of upregulated biological processes showed a protein-protein interaction (PPI) between CDK1, AKT2, SRC, STAT1, HDAC1, FDXR, FDX1, NPC1, ALDH2, GPx1, CDK4, and B2M, proteins. The identified proteins in this study might be the potential therapeutic targets for mitigating DOX resistance.

Insights into the effects of anilofos on direct-seeded rice production system through untargeted metabolomics.

Weed infestation is the major biological threat in direct-seeded rice production and can cause significant yield losses. The effective use of herbicides is particularly important in direct-seeded rice production. Anilofos, a pre-emergence herbicide, has been shown to be effective against the weed barnyardgrass. However, its impacts on crop yield and the direct-seeded rice production ecosystem remain underexplored. In this study, we conducted field trials and used untargeted metabolomics to investigate systemic effects of two different treatments (40 g/acre and 60 g/acre) on rice shoot and root as well as the rhizosphere soil during the critical tillering stage. Here, a total of 400 metabolites were determined in the crop and soil, with differential metabolites primarily comprising lipids and lipid-like molecules as well as phenylpropanoids and polyketides. Spearman correlation network analysis and a Zi-Pi plot revealed 7 key differential metabolites with significant topological roles, including succinic acid semialdehyde and riboflavin. KEGG pathway analysis showed that anilofos downregulated the amino acid metabolism while mainly promoted carbohydrate metabolism and secondary metabolites biosynthesis of the crop, which made minimal disruption on soil metabolism. Notably, we found 40 g/acre anilofos application could significantly improve the rice yield, potentially linked to the improved activity of flavonoid biosynthesis and starch and sucrose metabolism. This research provides a comprehensive evaluation of anilofos effects in the direct-seeded rice production system, offering new insights into optimizing herbicide use to improve agricultural sustainability and productivity.

Uncovering chikungunya virus-encoded miRNAs and host-specific targeted genes associated with antiviral immune responses: an integrated bioinformatics approach.

Chikungunya virus (CHIKV) is a single-stranded RNA virus belonging to the genus Alphavirus and is responsible for causing Chikungunya fever, a type of arboviral fever. Despite extensive research, the pathogenic mechanism of CHIKV within host cells remains unclear. In this study, an in-silico approach was used to predict that CHIKV produces micro-RNAs that target host-specific genes associated with host cellular regulatory pathways. Putative micro-RNAs of CHIKV were predicted using the miRNAFold and Vmir RNA structure web servers, and secondary structure prediction was performed using RNAfold. Host-specific target genes were then predicted, and hub genes were identified using CytoHubba and module selection through MCODE. Functional annotations of hub genes revealed their association with various pathways, including osteoclast differentiation, neuroactive ligand-receptor interaction, and mRNA surveillance. We used the freely available dataset GSE49985 to determine the level of expression of host-specific target genes and found that two genes, F-box and leucine-rich repeat protein 16 (FBXL16) and retinoic acid receptor alpha (RARA), were down-regulated, while four genes, RNA binding protein with serine-rich domain 1 (RNPS1), RNA helicase and ATPase (UPF1), neuropeptide S receptor 1 (NPSR1), and vasoactive intestinal peptide receptor 1 (VIPR1), were up-regulated. These findings provide insight into novel miRNAs and hub genes associated with CHIKV infection and suggest potential targets for therapeutic intervention. Further experimental validation of these targets could lead to the development of effective treatments for CHIKV-mediated diseases.

Novel analysis of functional relationship linking moyamoya disease to moyamoya syndrome.

Objective: The aim of this study was to elucidate the genetic pathways associated with Moyamoya disease (MMD) and Moyamoya syndrome (MMS), compare the functional activities, and validate relevant related genes in an independent dataset. Methods: We conducted a comprehensive search for genetic studies on MMD and MMS across multiple databases and identified related genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments analyses were performed for these genes. Commonly shared genes were selected for further validation in the independent dataset, GSE189993. The Sangerbox platform was used to perform statistical analysis and visualize the results. P＜0.05 indicated a statistically significant result. Results: We included 52 MMD and 51 MMS-related publications and identified 126 and 51 relevant genes, respectively. GO analysis for MMD showed significant enrichment in cytokine activity, cell membrane receptors, enzyme binding, and immune activity. A broader range of terms was enriched for MMS. KEGG pathway analysis for MMD highlighted immune and cellular activities and pathways related to MMS prominently featured inflammation and metabolic disorders. Notably, nine overlapping genes were identified and validated. The expressions of RNF213, PTPN11, and MTHFR demonstrated significant differences in GSE189993. A combined receiver operating characteristic curve showed high diagnostic accuracy (AUC = 0.918). Conclusions: The findings indicate a close relationship of MMD with immune activity and MMS with inflammation, metabolic processes and other environmental factors in a given genetic background. Differentiating between MMD and MMS can enhance the understanding of their pathophysiology and inform the strategies for their diagnoses and treatment.

Bioinformatics reveals the potential mechanisms and biomarkers of necroptosis in neuroblastoma.

Background: Neuroblastoma (NB) is a malignant tumor primarily found in children, presenting significant challenges in its development and prognosis. The role of necroptosis in the pathogenesis of NB has been acknowledged as crucial for treatment. This study aimed to investigate the key genes and functional pathways associated with necroptosis, as well as immune infiltration analysis, in NB. Furthermore, we aimed to evaluate the diagnostic significance of these genes for prognostic assessment and explore their potential immunological characteristics. Methods: The NB dataset (GSE19274, GSE73517, and GSE85047) was obtained from the Gene Expression Omnibus (GEO) database, and genes associated with necroptosis were collected from GeneCards and previous literature. First, we conducted differential expression analysis and performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). We employed gene set enrichment analysis (GSEA) to identify overlapping enriched functional pathways from the NB dataset. In addition, we constructed a protein-protein interaction (PPI) network, predicting relevant microRNAs (miRNAs) and transcription factors (TFs), as well as their corresponding drug predictions. Furthermore, the diagnostic value was assessed using receiver operating characteristic (ROC) curves. Finally, an immune infiltration analysis was performed. Results: We identified six necroptosis-related differentially expressed genes (NRDEGs) closely associated with necroptosis in NB. They were enriched in Tuberculosis, Apoptosis-multiple species, Salmonella infection, legionellosis, and platinum drug resistance. GSEA and PPI network analyses, along with mRNA-drug interaction network, revealed 38 potential drugs corresponding to BIRC2, CAMK2G, CASP3, and IL8. ROC curve analysis showed that in GSE19274, FLOT2 with area under the ROC curve (AUC) of 0.850 and DAPK1 with AUC of 0.789. Conclusions: Our study elucidates the key genes and functional pathways associated with necroptosis in NB, offering valuable insights to enhance our comprehension of the pathogenesis of NB, and improve prognosis assessment.

The network interactions between the porcine deltacoronavirus nucleocapsid protein and host cellular proteins.

Porcine deltacoronavirus (PDCoV) is an emerging swine coronavirus that can cause diarrhea in pigs of all ages with varying severity. Host-virus protein interactions are critical for intracellular viral replication. Elucidating the interactions between cellular and viral proteins can help us to design antiviral strategies. PDCoV N protein is the most abundant and vital regulator in virus replication. In this study, 604 host proteins were identified to interact with PDCoV N protein by Co-IP combined with LC-MS, of which 243 proteins were specifically bound to N protein. PPI analysis revealed that the N-interacting host proteins are categorized into three groups: ribonucleoprotein complex biogenesis modulation, cellular nitrogen compound metabolism, and nucleic acid binding. GO and KEGG analyses showed that the host proteins are primarily involved in mRNA splicing, stress granule assembly, spliceosomal snRNP assembly. Additionally, four host proteins-TRIM25, HNRNPUL1, RPS27A, and SLC3A2-were selected to validate the interactome data through Co-IP and Confocal assays. This study can help in designing anti-PDCoV strategies and understanding the replication mechanism of PDCoV.

Normalization of gene counts affects principal components-based exploratory analysis of RNA-sequencing data.

Normalization of count data is an essential step of in the analysis of RNA-sequencing data. Its statistical analysis has been mostly addressed in the context of differential expression analysis, that is in the univariate setting. However, relationships between genes and samples are better explored and quantified using multivariate exploratory data analysis tools like Principal Component Analysis (PCA). In this study we investigate how normalization impacts PCA models and interpretation, considering twelve different widely used normalization methods that were applied on simulated and experimental data. Correlation patterns in the normalized data were explored using both summary statistics and Covariance Simultaneous Component Analysis. The impact of normalization on the PCA solutions was assessed by exploring the model complexity, the quality of sample clustering in the low-dimensional PCA space and gene ranking in the model fit to normalized data. PCA models upon normalization were interpreted in the context gene enrichment pathway analysis. We found that although PCA score plots are often similar independently form the normalization used, biological interpretation of the models can depend heavily on the normalization method applied.

In silico exploration of 4(α-l-rhamnosyloxy)-benzyl isothiocyanate: A promising phytochemical-based drug discovery approach for combating multi-drug resistant Staphylococcus aureus.

Multidrug-resistant (MDR) Staphylococcus aureus infections significantly threaten global health. With rising resistance to current antibiotics and limited solutions, the urgent discovery of new, effective, and affordable antibacterials with low toxicity is imperative to combat diverse MDR S. aureus strains. Hence, in this study, we introduce an in silico phytochemical-based approach for discovering novel antibacterial agents, underscoring the potential of computational approaches in therapeutic discovery. Glucomoringin Isothiocyanate (GMG-ITC) from Moringa oleifera Lam. is one of the phytochemical compounds with several biological activities, including antimicrobial, anti-inflammatory, and antioxidant activities, and is also effective against S. aureus. This study focuses on screening GMG-ITC as a potential drug candidate to combat MDR S. aureus infections through a molecular docking approach. Moreover, interaction amino acid analysis, in silico pharmacokinetics, compound target prediction, pathway enrichment analysis and molecular dynamics (MD) simulations were conducted for further investigation. Molecular docking and interaction analysis showed strong binding affinity towards S. aureus lipase, dihydrofolate reductase, and other MDR S. aureus proteins, including penicillin-binding protein 2a, MepR, D-Ala:D-Ala ligase, and RPP TetM, through hydrophilic and hydrophobic interactions. GMG-ITC also showed a strong binding affinity to cyclooxygenase-2 and FAD-dependent NAD(P)H oxidase, suggesting that it is a potential anti-inflammatory and antioxidant candidate that may eliminate inflammation and oxidative stress associated with S. aureus infections. MD simulations validated the stability of the GMG-ITC molecular interactions determined by molecular docking. In silico pharmacokinetic analysis highlights its potency as a drug candidate, showing strong absorption, distribution, and excretion properties in combination with low toxicity. It acts as an active protease and enzyme inhibitor with moderate activity against GPCR ligands, ion channels, nuclear receptor ligands, and kinases. Enrichment analysis further elucidated its involvement in important biological, molecular, and cellular functions with potential therapeutic applications in diseases like cancer, hepatitis B, and influenza. Results suggest that GMG-ITC is an effective antibacterial agent that could treat MDR S. aureus-associated infections.

Ileum Proteomics Identifies Distinct Pathways Associated with Different Dietary Doses of Copper-Fructose Interactions: Implications for the Gut-Liver Axis and MASLD.

The interactions of different dietary doses of copper with fructose contribute to the development of metabolic dysfunction-associated steatotic liver disease (MASLD) via the gut-liver axis. The underlying mechanisms remain elusive. The aim of this study was to identify the specific pathways leading to gut barrier dysfunction in the ileum using a proteomics approach in a rat model. Male weanling Sprague Dawley rats were fed diets with adequate copper (CuA), marginal copper (CuM), or supplemented copper (CuS) in the absence or presence of fructose supplementation (CuAF, CuMF, and CuSF) for 4 weeks. Ileum protein was extracted and analyzed with an LC-MS. A total of 2847 differentially expressed proteins (DEPs) were identified and submitted to functional enrichment analysis. As a result, the ileum proteome and signaling pathways that were differentially altered were revealed. Of note, the CuAF is characterized by the enrichment of oxidative phosphorylation and ribosome as analyzed with the KEGG; the CuMF is characterized by an enriched arachidonic acid metabolism pathway; and focal adhesion, the regulation of the actin cytoskeleton, and tight junction were significantly enriched by the CuSF. In conclusion, our proteomics analysis identified the specific pathways in the ileum related to the different dietary doses of copper-fructose interactions, suggesting that distinct mechanisms in the gut are involved in the development of MASLD.

Qualitative and Untargeted Volatilome Fingerprinting of Aspergillus sp. and Bulbithecium sp. by HS-SPME-GCMS and Functional Interactions.

Research on fungal volatile organic compounds (VOCs) has increased worldwide in the last 10 years, but marine fungal volatilomes remain underexplored. Similarly, the hormone-signaling pathways, agronomic significance, and biocontrol potential of VOCs in plant-associated fungi make the area of research extremely promising. In the current investigation, VOCs of the isolates-Aspergillus sp. GSBT S13 and GSBT S14 from marine sediments, and Bulbithecium sp. GSBT E3 from Eucalyptus foliage were extracted using Head Space solid phase microextraction, followed by gas chromatography-mass spectrometry, identification, statistical analyses, and prediction of functions by KEGG COMPOUND and STITCH 5.0 databases. The significance of this research is fingerprinting VOCs of the isolates from distinct origins, identification of compounds using three libraries (NIST02, NIST14, and W9N11), and using bioinformatic tools to perform functional analysis. The most important findings include the identification of previously unreported compounds in fungi-1-methoxy naphthalene, diethyl phthalate, pentadecane, pristane, and nonanal; the prediction of the involvement of small molecules in the degradation of aromatic compound pathways and activation, inhibition, binding, and catalysis of metabolites with predicted protein partners. This study has ample opportunity to validate the findings and understand the mechanism or mode of action, the interspecies interactions, and the role of the metabolites in geochemical cycles.

Thanos: An R Package for the Gene-Centric Analysis of Functional Potential in Metagenomic Samples.

As the amount of metagenomic sequencing continues to increase, there is a growing need for tools that help biologists make sense of the data. Specifically, researchers are often interested in the potential of a microbial community to carry out a metabolic reaction, but this analysis requires knitting together multiple software tools into a complex pipeline. Thanos offers a user-friendly R package designed for the pathway-centric analysis and visualization of the functions encoded within metagenomic samples. It allows researchers to go beyond taxonomic profiles and find out, quantitatively, which pathways are prevalent in an environment, as well as comparing different environments in terms of their functional potential. The analysis is based on the sequencing depth of the genes of interest, either in the metagenome-assembled genomes (MAGs) or in the assembled reads (contigs), using a normalization strategy that enables comparison across samples. The package can import the data from multiple formats and offers functions for the visualization of the results as bar plots of the functional profile, box plots of compare functions across samples, and annotated pathway graphs. By streamlining the analysis of the functional potential encoded in microbial communities, Thanos can enable impactful discoveries in all the fields touched by metagenomics, from human health to the environmental sciences.

Macrophages and pulmonary fibrosis: a bibliometric and visual analysis of publications from 1990 to 2023.

Background: The role of macrophages in the symptomatic and structural progression of pulmonary fibrosis (PF) has garnered significant scholarly attention in recent years. This study employs a bibliometric approach to examine the present research status and areas of focus regarding the correlation between macrophages and PF, aiming to provide a comprehensive understanding of their relationship. Methodology: The present study employed VOSviewer, CiteSpace, and Microsoft Excel software to visualize and analyze various aspects such as countries, institutions, authors, journals, co-cited literature, keywords, related genes, and diseases. These analyses were conducted using the Web of Science core collection database. Results: A comprehensive collection of 3,479 records pertaining to macrophages and PF from the period of 1990 to 2023 was obtained. Over the years, there has been a consistent increase in research literature on this topic. Notably, the United States and China exhibited the highest level of collaboration in this field. Through careful analysis, the institutions, authors, and prominent journals that hold significant influence within this particular field have been identified as having the highest publication output. The pertinent research primarily concentrates on the domains of Biology and Medicine. The prevailing keywords encompass pulmonary fibrosis, acute lung injury, idiopathic pulmonary fibrosis, and others. Notably, TGFß1, TNF, and CXCL8 emerge as the most frequently studied targets, primarily associated with signaling pathways such as cytokine-cytokine receptor interaction. Additionally, cluster analysis of related diseases reveals their interconnectedness with ailments such as cancer. Conclusion: The present study employed bibliometric methods to investigate the knowledge structure and developmental trends in the realm of macrophage and PF research. The findings shed light on the introduction and research hotspots that facilitate a more comprehensive understanding of macrophages and PF.

Genome-wide analysis of the cytochrome P450 gene family in Pacific oyster Crassostrea gigas and their expression profiles during gonad development.

The cytochrome P450 (CYP) gene superfamily plays a significant role in various physiological processes, producing different compounds such as hormones, fatty acids, and biomolecules. However, little information is known their roles during gonad development in Pacific oyster (Crassostrea gigas). In this study, total of 116 CgCYP (Crassostrea gigas cytochrome P450) genes were identified and their expression pattern was analyzed for the first time. The relative molecular weights of these CgCYP genes ranged from 63.52 to 113.41 kDa, and the length of encoded amino acids ranged from 103 to 993. And total 26 cis-acting elements of these CgCYP genes were identified. GO and KEGG enrichment analysis showed some CgCYP genes are essential for the metabolism of male and female sex hormones. Additionally, expression anslysis showed 69 CgCYP genes were over-expressed in early gonad development and triploid infertile individuals. More importantly, expression levels of CgCYP1, CgCYP15, CgCYP34, CgCYP46, CgCYP69, CgCYP87, CgCYP88, and CgCYP103, were found to be significantly higher in female gonad, suggesting their important roles in female gonad development. The results of this study will provide a better understanding of the CgCYP genes in the gonad development of Pacific oyster.

Placenta-derived mesenchymal stem cells promote diabetic wound healing via exosomal protein interaction networks.

There is a lack of effective treatment options for diabetic refractory wounds, which presents a critical clinical issue that needs to be addressed urgently. Our research has demonstrated that human placenta-derived mesenchymal stem cells (plaMSCs) facilitate the migration and proliferation of HaCat cells, thereby enhancing diabetic wound healing primarily via the exosomes derived from plaMSCs (plaMSCs-Ex). Using label-free proteomics, plaMSCs and their exosomes were analysed for proteome taxonomic content in order to explore the underlying effective components mechanism of plaMSCs-Ex in diabetic wound healing. Differentially expressed proteins enriched in plaMSCs-Ex were identified and underwent bioinformatics analysis including GO annotation, KEGG pathway enrichment, gene set enrichment analysis (GSEA) and protein-protein interaction analysis (PPI). Results showed that the proteins enriched in plaMSCs-Ex are significantly involved in extracellular matrix organisation, epithelium morphogenesis, cell growth, adhesion, proliferation and angiogenesis. PPI analysis filtered 2 wound healing-related clusters characterised by hub proteins such as POSTN, FN1, SPARC, TIMP1, SERPINE1, LRP1 and multiple collagens. In brief, the exosomal proteins derived from plaMSCs reveal diverse functions of regeneration and tissue remodelling based on proteomics analysis and potentially play a role in diabetic wound healing.

Whole proteome analysis of germinating and outgrowing Bacillus subtilis 168.

In this study, we present a high-resolution dataset and bioinformatic analysis of the proteome of Bacillus subtilis 168 trp+ (BSB1) during germination and spore outgrowth. Samples were collected at 14 different time points (ranging from 0 to 130 min) in three biological replicates after spore inoculation into germination medium. A total of 2191 proteins were identified and categorized based on their expression kinetics. We observed four distinct clusters that were analyzed for functional categories and KEGG pathways annotations. The examination of newly synthesized proteins between successive time points revealed significant changes, particularly within the first 50 min. The dataset provides an information base that can be used for modeling purposes and inspire the design of new experiments.

Transcriptome Reveals the Key Genes Related to the Metabolism of Volatile Sulfur-Containing Compounds in Lentinula edodes Mycelium.

Lentinula edodes (L. edodes) is a globally popular edible mushroom because of its characteristic sulfur-containing flavor compounds. However, the formation of the volatile sulfur-containing compounds in the mycelium of L. edodes has not been studied. We found that there were also sulfur-containing aroma compounds in the mycelium of L. edodes, and the content and composition varied at different stages of mycelial growth and development. The γ-glutamyl-transpeptidase (GGT) and cysteine sulfoxide lyase (C-S lyase) related to the generation of sulfur compounds showed the highest activities in the 15-day sample. Candidate genes for the metabolism of volatile sulfur compounds in mycelium were screened using transcriptome analysis, including encoding the GGT enzyme, C-S lyase, fatty acid oxidase, HSP20, and P450 genes. The expression patterns of Leggt3 and Leccsl3 genes were consistent with the measured activities of GGT and C-S lyase during the cultivation of mycelium and molecular dynamics simulations showed that they could stably bind to the substrate. Our findings provide insights into the formation of sulfur-containing flavor compounds in L. edodes. The mycelium of L. edodes is suggested for use as material for the production of sulfur-containing flavor compounds.

Comparative genome analysis of the genus Marivirga and proposal of two novel marine species: Marivirga arenosa sp. nov., and Marivirga salinae sp. nov.

BACKGROUND: The phylum Bacteroidota represents a significant proportion of heterotrophic bacteria found in marine ecosystems. Members of the phylum Bacteroidota are actively involved in the degradation of biopolymers such as polysaccharides and proteins. Bacteroidota genomes exhibit a significant enrichment of various enzymes, including carbohydrate-active enzymes (CAZymes), carboxypeptidases, esterases, isomerases, peptidases, phosphatases, and sulfatases. The genus Marivirga, a member of the family Marivirgaceae within the phylum Bacteroidota, comprises six documented species. During a microbial diversity study, three novel Marivirga strains (BKB1-2 T, ABR2-2, and BDSF4-3 T) were isolated from the West Sea, Republic of Korea. RESULTS: To explore the taxonomic status and genomic characteristics of the novel isolates, we employed a polyphasic taxonomic approach, which included phylogenetic, chemotaxonomic and comprehensive genome analysis. The three isolates were Gram-stain-negative, aerobic, rod-shaped, moderately halophilic, and had a gliding motility. The average nucleotide identity (ANI) and digital DNA-DNA hybridization (dDDH) values among the two isolates, BKB1-2 T and BDSF4-3 T, and the six reference strains were 70.5-76.5% for ANI and 18.1-25.7% for dDDH. Interestingly, the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that the strains harbor genes for a comprehensive pathway for dissimilatory nitrate reduction to ammonium (DNRA), as well as other nitrogen pathways for the reduction of nitrite, nitric oxide, and nitrous oxide. Additionally, the antiSMASH analysis indicated that the strains contained three to eight biosynthetic gene clusters (BGCs) associated with the synthesis of secondary metabolites. Furthermore, the strains carried a high number of CAZyme ranging from 53 to 152, which was also demonstrated by an in vitro analysis of degradation of the polysaccharide cellulose, chitin, laminarin, starch, and xylan. Additionally, all the strains carried genes for the metabolism of heavy metals, and exhibited tolerance to heavy metals, with minimum inhibitory concentrations (MICs) in millimoles (mM) in ranges of Co2+ (3-6), Cu2+ (0.2-0.4), Ni2+ (3-5), Zn2+ (2-4), Mn2+ (20-50), and Hg2+ (0.3). CONCLUSIONS: Based on polyphasic taxonomic approach, the three isolated strains represent two novel species names Marivirga arenosa sp. nov. (BKB1-2 T = KCTC 82989 T = InaCC B1618T), and Marivirga salinae sp. nov. (BDSF4-3 T = KCTC 82973 T = InaCC B1619T).

Comparative Analysis of Hulless Barley Transcriptomes to Regulatory Effects of Phosphorous Deficiency.

Hulless barley is a cold-resistant crop widely planted in the northwest plateau of China. It is also the main food crop in this region. Phosphorus (P), as one of the important essential nutrient elements, regulates plant growth and defense. This study aimed to analyze the development and related molecular mechanisms of hulless barley under P deficiency and explore the regulatory genes so as to provide a basis for subsequent molecular breeding research. Transcriptome analysis was performed on the root and leaf samples of hulless barley cultured with different concentrations of KH2PO4 (1 mM and 10 µM) Hoagland solution. A total of 46,439 genes were finally obtained by the combined analysis of leaf and root samples. Among them, 325 and 453 genes had more than twofold differences in expression. These differentially expressed genes (DEGs) mainly participated in the abiotic stress biosynthetic process through Gene Ontology prediction. Moreover, the Kyoto Encyclopedia of Genes and Genomes showed that DEGs were mainly involved in photosynthesis, plant hormone signal transduction, glycolysis, phenylpropanoid biosynthesis, and synthesis of metabolites. These pathways also appeared in other abiotic stresses. Plants initiated multiple hormone synergistic regulatory mechanisms to maintain growth under P-deficient conditions. Transcription factors (TFs) also proved these predictions. The enrichment of ARR-B TFs, which positively regulated the phosphorelay-mediated cytokinin signal transduction, and some other TFs (AP2, GRAS, and ARF) was related to plant hormone regulation. Some DEGs showed different values in their FPKM (fragment per kilobase of transcript per million mapped reads), but the expression trends of genes responding to stress and phosphorylation remained highly consistent. Therefore, in the case of P deficiency, the first response of plants was the expression of stress-related genes. The effects of this stress on plant metabolites need to be further studied to improve the relevant regulatory mechanisms so as to further understand the importance of P in the development and stress resistance of hulless barley.