Kyoto Encyclopedia Of Genes And Genomes Database Research Articles

Unveiling FRG1’s DNA repair role in breast cancer

The FRG1(FSHD region gene 1) gene has emerged as a pivotal tumor suppressor in both breast and prostate cancer. HPF1 (Histone PARylation Factor 1), a gene crucial in the base excision repair (BER) mechanism for single-stranded DNA (ssDNA) lesions, showcases a robust correlation with FRG1. This implies that FRG1 might have the capacity to influence BER via HPF1, potentially playing a role in tumorigenesis. Using a comprehensive approach that integrates in-silico analyses involving differential gene expression, KEGG (Kyoto Encyclopedia of Genes and Genomes), GO (Gene Ontology), and STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) databases, we unravelled the intricate network of genes and pathways influenced by FRG1, which includes BER. Our linear regression analysis unveiled a positive relationship between FRG1 and key genes crucial for BER. Notably, breast cancer patients with low FRG1 expression exhibited a significantly higher frequency of mutation in TP53. To enhance the accuracy of our analysis, we conducted qRT-PCR assays, which demonstrated that FRG1 affects the transcription of DNA base excision repair genes, showing differential expression in breast cancer cells. Moreover, through the Alkaline Comet Assay, a technique that quantifies DNA damage at the single-cell level, we observed diminished DNA repair capabilities when FRG1 levels are low. Risk scores were calculated using the Cox regression coefficients, and we found notable differences in Overall Survival (OS) and mRNA expression of DEGs in the low and high-risk groups. In summary, our findings shed light on the pivotal role of FRG1 in maintaining DNA repair efficiency within breast cancer cells.

Uncovering the protective mechanism of baicalin in treatment of fatty liver based on network pharmacology and cell model of NAFLD

Excessive nonesterified fatty acids (NEFA) impair cellular metabolism and will induce fatty liver formation in dairy cows during the periparturient. Baicalin, an active flavonoid, has great potential efficacy in alleviating lipid accumulation and ameliorating the development of fatty liver disease. Nevertheless, its mechanism remains unclear. Here, the potential mechanism of baicalin on system levels was explored using network pharmacology and in vitro experiments. Firstly, the target of baicalin and fatty liver disease was predicted, and then the protein–protein interaction (PPI) network was constructed. In addition, the Kyoto Encyclopedia of Genes and Genomes (KEGG) (q-value) pathway enrichment is performed through the Database for Annotation, Visualization, and Integrated Discovery (DAVID) server. Finally, the results of the network analysis of the in vitro treatment of bovine hepatocytes by NEFA were confirmed. The results showed that 33 relevant targets of baicalin in the treatment of liver fatty were predicted by network pharmacology, and the top 20 relevant pathways were extracted by KEGG database. Baicalin treatment can reduce triglyceride (TAG) content and lipid droplet accumulation in NEFA-treated bovine hepatocytes, and the mechanism is related to inhibiting lipid synthesis and promoting lipid oxidation. The alleviating effect of baicalin on fatty liver may be related to the up-regulation of solute vector family member 4 (SLC2A4), Down-regulated AKT serine/threonine kinase 1 (AKT1), Peroxisome proliferator-activated receptor gamma (PPARG), Epidermal growth factor receptor (EGFR), tumor necrosis factor (TNF), Interleukin 6 (IL-6) were associated. These results suggested that baicalin may modulate key inflammatory markers, and lipogenesis processes to prevent fatty liver development in dairy cows.

KEGG orthology prediction of bacterial proteins using natural language processing

BackgroundThe advent of high-throughput technologies has led to an exponential increase in uncharacterized bacterial protein sequences, surpassing the capacity of manual curation. A large number of bacterial protein sequences remain unannotated by Kyoto Encyclopedia of Genes and Genomes (KEGG) orthology, making it necessary to use auto annotation tools. These tools are now indispensable in the biological research landscape, bridging the gap between the vastness of unannotated sequences and meaningful biological insights.ResultsIn this work, we propose a novel pipeline for KEGG orthology annotation of bacterial protein sequences that uses natural language processing and deep learning. To assess the effectiveness of our pipeline, we conducted evaluations using the genomes of two randomly selected species from the KEGG database. In our evaluation, we obtain competitive results on precision, recall, and F1 score, with values of 0.948, 0.947, and 0.947, respectively.ConclusionsOur experimental results suggest that our pipeline demonstrates performance comparable to traditional methods and excels in identifying distant relatives with low sequence identity. This demonstrates the potential of our pipeline to significantly improve the accuracy and comprehensiveness of KEGG orthology annotation, thereby advancing our understanding of functional relationships within biological systems.

Immune Gene Networks from Lung Cancer Patients Treated with Immune Checkpoint Inhibitors.

The association between immune checkpoint inhibitors (ICIs) and immune gene networks in squamous lung cancer (LUSC) and lung adenocarcinoma (LUAD) was studied. Immune gene networks were constructed using RNA-seq data from the gene expression omnibus (GEO) database. Datasets with more than 10 samples of normal control and tumor tissues were selected; of these, GSE87340, GSE120622, and GSE111907 were suitable for analysis. Gene set enrichment for pathway analysis was performed. For immune gene network construction, 998 unique immune genes were selected from 21 pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG). Gene function annotation was performed based on the KEGG, Gene Ontology, and Reactome databases. Tumor tissues showed decreased coagulation, hematopoiesis, and innate immune pathways, whereas complement- and coagulation-related genes were prominent in the tumor immune gene network. The average numbers of neighbors, clustering coefficients, network diameters, path lengths, densities, and heterogeneities were highest for normal tissue, followed by LUAD and LUSC. Decreased coagulation genes, which were prominent in tumor immune networks, imply functional attenuation. LUAD was deviated from normal tissue, based on network parameters. Tumor tissues showed decreased immune function, and the deviation of LUSC from normal tissue might explain LUSC's better therapeutic response to ICI treatment.

Genome sequencing and analysis of penicillin V producing Penicillium rubens strain BIONCL P45 isolated from India.

A filamentous fungus Penicillium rubens is widely recognized for producing industrially important antibiotic, penicillin at industrial scale. To better comprehend, the genetic blueprint of the wild-type P. rubens was isolated from India to identify the genetic/biosynthetic pathways for phenoxymethylpenicillin (penicillin V, PenV) and other secondary metabolites. Genomic DNA (gDNA) was isolated, and library was prepared as per Illumina platform. Whole genome sequencing (WGS) was performed according to Illumina NovoSeq platform. Further, SOAPdenovo was used to assemble the short reads validated by Bowtie-2 and SAMtools packages. Glimmer and GeneMark were used to dig out total genes in genome. Functional annotation of predicted proteins was performed by NCBI non-redundant (NR), UniProt, Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Ontology (GO) databases. Moreover, secretome analysis was performed by SignalP 4.1 and TargetP v1.1 and carbohydrate-active enzymes (CAZymes) and protease families by CAZy database. Comparative genome analysis was performed by Mauve 2.4.0. software to find genomic correlation between P. rubens BIONCL P45 and Penicillium chrysogenum Wisconsin 54-1255; also phylogeny was prepared with known penicillin producing strains by ParSNP tool. Penicillium rubens BIONCL P45 strain was isolated from India and is producing excess PenV. The 31.09Mb genome was assembled with 95.6% coverage of the reference genome P. chrysogenum Wis 54-1255 with 10687 protein coding genes, 3502 genes had homologs in NR, UniProt, KEGG, and GO databases. Additionally, 358 CAZymes and 911 transporter coding genes were found in genome. Genome contains complete pathways for penicillin, homogentisate pathway of phenyl acetic acid (PAA) catabolism, Andrastin A, Sorbicillin, Roquefortine C, and Meleagrin. Comparative genome analysis of BIONCL P45 and Wis 54-1255 revealed 99.89% coverage with 2952 common KEGG orthologous protein-coding genes. Phylogenetic analysis revealed that BIONCL P45 was clustered with Fleming's original isolate P. rubens IMI 15378. This genome can be a helpful resource for further research in developing fermentation processes and strain engineering approaches for high titer penicillin production.

Optimization of nitrogen removal and microbial mechanism of a hydrogen-based membrane biofilm reactor

ABSTRACT The hydrogen-based membrane biofilm reactor (H2-MBfR) is an emerging biological nitrogen removal technology characterized by high efficiency, energy-saving capability, and environmental friendliness. The technology achieves denitrification and denitrogenation of microorganisms by passing hydrogen as an electron donor from inside to outside through the hollow fibre membrane module, and eventually the hydrogen reachs the biofilm attached to the surface of the fibre membrane. H2-MBfR has obtained favourable outcomes in the treatment of secondary biochemical effluent and low concentration nitrogen polluted water source. The experiment was optimized by s single-factor testing and response surface methodology-based optimization (RSM), and the optimal operational conditions were obtained as follows: an influent flow rate of 2 mL/min, hydrogen pressure of 0.04 MPa, and influent nitrate concentration of 24.29 mg/L. Under these conditions, a high nitrate removal rate of 98.25% was achieved. In addition, Proteobacteria and Bacteroidetes were the dominant bacteria in all stages, and the genus Hydrogenophaga was sufficiently enriched, occurring at 13.0%–49.0% throughout the reactor operation. Furthermore, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway for nitrate reduction and inorganic carbon utilization by microorganisms in the H2-MBfR was explored through comparison with the KEGG database. The results provided a mechanistic explanation for the denitrification and carbon sequestration capacity of the H2-MBfR.

KEGGSum: Summarizing Genomic Pathways

Over time, the renowned Kyoto Encyclopedia of Genes and Genomes (KEGG) has grown to become one of the most comprehensive online databases for biological procedures. The majority of the data are stored in the form of pathways, which are graphs that depict the relationships between the diverse items participating in biological procedures, such as genes and chemical compounds. However, the size, complexity, and diversity of these graphs make them difficult to explore and understand, as well as making it difficult to extract a clear conclusion regarding their most important components. In this regard, we present KEGGSum, a system enabling the efficient and effective summarization of KEGG pathways. KEGGSum receives a KEGG identifier (Kid) as an input, connects to the KEGG database, downloads a specialized form of the pathway, and determines the most important nodes in the graph. To identify the most important nodes in the KEGG graphs, we explore multiple centrality measures that have been proposed for generic graphs, showing their applicability to KEGG graphs as well. Then, we link the selected nodes in order to produce a summary graph out of the initial KEGG graph. Finally, our system visualizes the generated summary, enabling an understanding of the most important parts of the initial graph. We experimentally evaluate our system, and we show its advantages and benefits.

Bioinformatics-Based Identification of Key Prognostic Genes in Neuroblastoma with a Focus on Immune Cell Infiltration and Diagnostic Potential of VGF.

This study aims to identify differentially expressed genes (DEGs) in neuroblastoma (NB) through comprehensive bioinformatics analysis and machine learning techniques. We seek to elucidate these DEGs' biological functions and associated signaling pathways. Furthermore, our objective extends to predicting upstream microRNAs (miRNAs) and relevant transcription factors of pivotal genes, with the ultimate goal of guiding clinical diagnostics and informing future treatment strategies for Neuroblastoma. In this study, we sourced datasets GSE49710 and TARGET from the GEO and UCSC-XENA databases, respectively. Differentially expressed genes (DEGs) were identified using the R language "limma" package. Subsequent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of these DEGs were conducted using the "clusterProfiler" package. We employed Weighted Gene Co-expression Network Analysis (WGCNA) to isolate the most significant modules associated with death and MYCN amplification, specifically MEpink and MEbrown modules. These modules were then cross-referenced with the DEGs for further GO and KEGG pathway analyses. LASSO regression analysis, facilitated by the "glmnet" package, was utilized to pinpoint three hub genes. We performed differential analysis on these genes and constructed Receiver Operating Characteristic (ROC) curves for disease diagnosis purposes. Immune infiltration analysis was conducted using the "GSVA" package's ssGSEA function. Additionally, single-gene Gene Set Enrichment Analysis (GSEA) on the hub gene was carried out based on Reactome and KEGG databases. Upstream miRNA and transcription factors associated with the hub gene were predicted using RegNetwork, with visual representations created in Cytoscape. Furthermore, to validate the three identified markers in neuroblastoma tissues, quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) analysis was conducted. We identified 483 differentially expressed genes (DEGs) in neuroblastoma. These genes predominantly function in protein translation, membrane composition, and RNA transcription regulation, and are implicated in multiple signaling pathways relevant to neurodegenerative diseases. Utilizing LASSO regression analysis, we pinpointed three hub genes: VGF, DGKD, and C19orf52. The Receiver Operating Characteristic (ROC) curve analysis yielded Area Under Curve (AUC) values of 0.751 and 0.722 for VGF, 0.79 and 0.656 for DGKD, and 0.8 and 0.753 for C19orf52, respectively. Our immune infiltration analysis revealed significant correlations among monocytes, follicular helper T cells, and CD4+ T cells. Notably, in the death group, we observed heightened infiltration levels of activated CD4+ T cells, macrophages, and Th2 cells. C19orf52 exhibited a close association with the infiltration of monocytes, CD4+ T cells, and Th2 cells, with P-values less than 0.05. Furthermore, qRT-PCR analysis corroborated the upregulation of VGF in neuroblastoma tissues, further validating our findings. The hub genes (VGF, DGKD, and C19orf52) of neuroblastoma are screened. VGF, one of the hub genes, may have a high diagnostic value and is involved in the immune cell infiltration in neuroblastoma tissue, which may be used as a biomarker for the diagnosis of neuroblastoma and provides a new direction for clinical prognosis prediction and management improvement.

RESISTÊNCIA INSULINICA MIOCÁRDICA E HIPERTENSÃO ARTERIAL SISTÊMICA

Background: Low availability of Glut-4 transporters in the sarcolemma of cardiac cells characterizes myocardial insulin resistance (MIR), which is triggered separately from generalized insulin resistance. Insulin receptors are quite evident in the heart muscle and vessels, and mitochondrial activity performs a significant role in MIR preserving cellular homeostasis through cell reproduction, cells livelihoods, and energy generation. Objective: To evaluate the MIR mechanism and its association with hypertension by signaling pathways design. Methods: PubMed database was employed to search for reviews publications with MIR. The referenced data of the signaling pathway was chosen by aggregating references from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. A signaling pathway was designed based on MIR research manuscripts, where we show several mechanisms included in the MIR. The KEGG server was employed to exploit the interrelationship protein-protein, and elaborate signaling pathway diagram. The signaling pathway mapping was carried out with PathVisio software. Results: We selected 42 articles from a total of 450 articles in the PubMed database that presented a significant association between the terms “insulin resistance myocardial” AND “signaling pathway” AND “systemic arterial hypertension”. Founded on database-validated research papers, we chose well-founded pathways and we succeeded in representative description of these pathways. The reproduction contigs taken from the KEGG database designed the signaling pathway of the bio-molecules that lead to MIR. Thus, the acting among multiple mechanisms releases factors that participate in the development of MIR. Conclusion: The interaction among various mechanisms and molecular interactions are important factors in developing MIR.

In Vivo Regulation of Signal Transduction Pathways by Vitamin D Stabilizes Homeostasis of Human Immune Cells and Counteracts Molecular Stress.

Vitamin D3 is a pre-hormone that regulates hundreds of target genes and dozens of physiological functions, including calcium homeostasis and the activity of the immune system, via its metabolite 1,25-dihydroxyvitamin D3, which is a high-affinity ligand for the transcription factor vitamin D receptor. In this study, we took advantage of data from the VitDHiD vitamin D3 intervention trial (25 healthy individuals) indicating that 442 protein-coding genes were significantly (false discovery rate < 0.05) up- or downregulated in peripheral blood mononuclear cells one day after taking a vitamin D3 bolus. Since more than half of the encoded proteins had "signaling" assigned as a primary biological function, we evaluated their involvement in signal transduction cascades included in the KEGG (Kyoto Encyclopedia of Genes and Genomes) database and found 88 of the vitamin D targets contributing to 16 different pathways. Eight of the pathways show an approximately even contribution of up- and downregulated genes, suggesting that the actions of vitamin D stabilize homeostasis of the physiological processes driven by the respective signaling cascades. Interestingly, vitamin D target genes involved in the signaling pathways of hypoxia-inducible factor 1 (HIF1), tumor necrosis factor (TNF), mitogen-activated protein kinases (MAPKs) and nuclear factor κB (NFκB) are primarily downregulated. This supports the observation that the physiological role of vitamin D in healthy individuals is to tone down certain processes rather than activate them. In conclusion, under in vivo conditions, vitamin D either alleviates the homeostasis of immune cells in healthy individuals or counteracts molecular responses to oxygen deprivation (HIF1), microbe infection (TNF), growth stimulation (MAPKs) and inflammation (NFκB).

Analysis of the mechanism of action of Euphorbia fischeriana Steud on cirrhosis based on network pharmacology.

This study aimed to employ network pharmacology to elucidate the mechanism by which Euphorbia fischeriana Steud (EFS) exhibits the efficacy on cirrhosis. The compounds and targets of EFS were retrieved from Traditional Chinese Medicine Integrated Database and Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Next, these compounds and targets were analyzed based on protein-protein interaction (PPI) network. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling network was established based on KEGG database. We constructed a compound-compound target-intersection target-pathway PPI network, including 20 compounds, 19 intersection targets between compound targets and EFS targets. Among the 20 compounds, 8-Isopentenyl-kaempferol has the most targets, with 27 targets, followed by 3,4',5-Trihydroxy-7-methoxy-8-isopentenylflavone, Formononetin, Isoxanthohumol, and Isokurarinone with potential targets of 26, 22, 18, and 14, respectively. Top 5 targets are HSP90AA1, PTGS2, NOS2, MAPK14, and PPARG. KEGG pathway enrichment analysis showed that pathways such as Hepatitis B, Hepatitis C, Lipid and atherosclerosis, and AGE-RAGE signaling pathway in diabetic complications were closely related to the infection and abnormal metabolism of the liver. The application of network pharmacology could identify potential targets of EFS with a low false-positive rate and provide novel insight into the mechanism of action of EFS on cirrhosis.

Screening and genome-wide analysis of lignocellulose-degrading bacteria from humic soil.

Crop straw contains huge amounts of exploitable energy, and efficient biomass degradation measures have attracted worldwide attention. Mining strains with high yields of cellulose-degrading enzymes is of great significance for developing clean energy and industrial production of related enzymes. In this study, we reported a high-quality genome sequence of Bacillus velezensis SSF6 strain using high-throughput sequencing technology (Illumina PE150 and PacBio) and assessed its lignocellulose degradation potential. The results demonstrated that the genome of B. velezensis SSF6 was 3.89 Mb and contained 4,015 genes, of which 2,972, 3,831 and 158 genes were annotated in the COGs (Clusters of Orthologous Groups), KEGG (Kyoto Encyclopedia of Genes and Genomes) and CAZyme (Carbohydrate-Active enZymes) databases, respectively, and contained a large number of genes related to carbohydrate metabolism. Furthermore, B. velezensis SSF6 has a high cellulose degradation capacity, with a filter paper assay (FPA) and an exoglucanase activity of 64.48 ± 0.28 and 78.59 ± 0.42 U/mL, respectively. Comparative genomic analysis depicted that B. velezensis SSF6 was richer in carbohydrate hydrolase gene. In conclusion, the cellulose-degrading ability of B. velezensis SSF6 was revealed by genome sequencing and the determination of cellulase activity, which laid a foundation for further cellulose degradation and bioconversion.

Comparative analysis of differentially expressed genes for biosynthesis of active ingredients in fruits of different cultivars of Lycium barbarum L. based on transcriptome sequencing

To explore the differentially expressed genes (DEGs) related to biosynthesis of active ingredients in wolfberry fruits of different varieties of Lycium barbarum L. and reveal the molecular mechanism of the differences of active ingredients, we utilized Illumina NovaSeq 6000 high-throughput sequencing technology to conduct transcriptome sequencing on the fruits of 'Ningqi No.1' and 'Ningqi No.7' during the green fruit stage, color turning stage and maturity stage. Subsequently, we compared the profiles of related gene expression in the fruits of the two varieties at different development stages. The results showed that a total of 811 818 178 clean reads were obtained, resulting in 121.76 Gb of valid data. There were 2 827, 2 552 and 2 311 DEGs obtained during the green fruit stage, color turning stage and maturity stage of 'Ningqi No. 1' and 'Ningqi No. 7', respectively, among which 2 153, 2 050 and 1 825 genes were annotated in six databases, including gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG) and clusters of orthologous groups of proteins (KOG). In GO database, 1 307, 865 and 624 DEGs of green fruit stage, color turning stage and maturity stage were found to be enriched in biological processes, cell components and molecular functions, respectively. In the KEGG database, the DEGs at three developmental stages were mainly concentrated in metabolic pathways, biosynthesis of secondary metabolites and plant-pathogen interaction. In KOG database, 1 775, 1 751 and 1 541 DEGs were annotated at three developmental stages, respectively. Searching the annotated genes against the PubMed database revealed 18, 26 and 24 DEGs related to the synthesis of active ingredients were mined at the green fruit stage, color turning stage and maturity stage, respectively. These genes are involved in carotenoid, flavonoid, terpenoid, alkaloid, vitamin metabolic pathways, etc. Seven DEGs were verified by RT-qPCR, which showed consistent results with transcriptome sequencing. This study provides preliminary evidences for the differences in the content of active ingredients in different Lycium barbarum L. varieties from the transcriptional level. These evidences may facilitate further exploring the key genes for active ingredients biosynthesis in Lycium barbarum L. and analyzing their expression regulation mechanism.

Molecular and biochemical investigations of the anti-fatigue effects of tea polyphenols and fruit extracts of Lycium ruthenicum Murr. on mice with exercise-induced fatigue.

Background: The molecular mechanisms regulating the therapeutic effects of plant-based ingredients on the exercise-induced fatigue (EIF) remain unclear. The therapeutic effects of both tea polyphenols (TP) and fruit extracts of Lycium ruthenicum (LR) on mouse model of EIF were investigated. Methods: The variations in the fatigue-related biochemical factors, i.e., lactate dehydrogenase (LDH), superoxide dismutase (SOD), tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), interleukin-2 (IL-2), and interleukin-6 (IL-6), in mouse models of EIF treated with TP and LR were determined. The microRNAs involved in the therapeutic effects of TP and LR on the treatment of mice with EIF were identified using the next-generation sequencing technology. Results: Our results revealed that both TP and LR showed evident anti-inflammatory effect and reduced oxidative stress. In comparison with the control groups, the contents of LDH, TNF-α, IL-6, IL-1β, and IL-2 were significantly decreased and the contents of SOD were significantly increased in the experimental groups treated with either TP or LR. A total of 23 microRNAs (21 upregulated and 2 downregulated) identified for the first time by the high-throughput RNA sequencing were involved in the molecular response to EIF in mice treated with TP and LR. The regulatory functions of these microRNAs in the pathogenesis of EIF in mice were further explored based on Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses with a total of over 20,000-30,000 target genes annotated and 44 metabolic pathways enriched in the experimental groups based on GO and KEGG databases, respectively. Conclusion: Our study revealed the therapeutic effects of TP and LR and identified the microRNAs involved in the molecular mechanisms regulating the EIF in mice, providing strong experimental evidence to support further agricultural development of LR as well as the investigations and applications of TP and LR in the treatment of EIF in humans, including the professional athletes.

Genome sequencing, assembly, and characterization of Pichia fermentans Z9Y-3 as a non-Saccharomyces yeast with aroma enhancing potential

Pichia fermentans is an important non-Saccharomyces yeast applied in mixed fermentation to enhance fruity and floral traits of wine aroma. In this study, genome sequencing of P. fermentans Z9Y-3 was performed using the PacBio single-molecule real-time sequencing platform, and was further assembled using MECAT. The sequenced genes are annotated by non-redundant protein (Nr), Gene Ontology (GO), Cluster of Orthologous Groups of proteins (COG), Kyoto Encyclopedia of Genes and Genomes (KEGG) and carbohydrate-active enzymes (CAZymes) database. Results indicated that the genome size was about 13.5 Mb with 42.09% GC content and 4730 protein coding genes. The 95.90% genes were annotated to the non-redundant protein (Nr) database, and then annotated to GO database. The 62.64% genes annotated to the COG database revealed 25 functional groups. The 58.22% genes annotated to the KEGG database revealed 5 groups. The 586 genes were annotated to CAZymes, in which two genes bglH and bglC encoding beta-glucosidase were found and further analyzed its motifs. A terpene and a nonribosomal peptides like secondary metabolic gene clusters were predicted using antiSMASH 7.0.0. This study benefits us to understand physiological and biochemical behavior of P. fermentans Z9Y-3 at a molecular level to better use P. fermentans Z9Y-3 in aroma enhancing winemaking.

Full-length transcriptome combined with RNA sequence analysis of Fraxinus chinensis.

The dry root or stem bark of Fraxinus chinensis is a famous herb Qin Pi which is known for its anti-inflammatory, analgesic, anti-tumor, liver protective and diuretic pharmacological effects, the fundamental chemical components are coumarin, phenylethanol glycosides and flavonoids. However, it is difficult to clarify the secondary metabolite synthesis pathway and key genes involved in the pathway because of lack genome information of Fraxinus chinensis. To generate a complete transcriptome of Fraxinus chinensis and to clarify the differentially expressed genes (DEGs) in leaves and stem barks. In this study, full-length transcriptome analysis and RNA-Seq were combined to characterize Fraxinus chinensis transcriptome. A total of 69,145 transcripts were acquired and regarded as reference transcriptome, 67,441 transcripts (97.47%) were annotated to NCBI non-redundant protein (Nr), SwissProt, the Kyoto Encyclopedia of Genes and Genomes (KEGG) and eukaryotic orthologous groups (KOG) databases. A total of 18,917 isoforms were annotated to KEGG database and classified to 138 biological pathways. In total, 10,822 simple sequence repeat (SSRs) and 11,319 resistance (R) gene were classified to 18 types, and 3947 transcription factors (TFs) were identified in full-length transcriptome analysis. Additionally, 15,095 DEGs were detected by RNA-seq in leaves and barks, including 4696 significantly up-regulated and 10,399 significantly down-regulated genes. And 254 transcripts were annotated into phenylpropane metabolism pathway containing 86 DEGs and ten of these enzyme genes were verified by qRT-PCR. It laid the foundation for further exploration of the biosynthetic pathway of phenylpropanoids and related key enzyme genes.

Kegg_pull: a software package for the RESTful access and pulling from the Kyoto Encyclopedia of Gene and Genomes

BackgroundThe Kyoto Encyclopedia of Genes and Genomes (KEGG) provides organized genomic, biomolecular, and metabolic information and knowledge that is reasonably current and highly useful for a wide range of analyses and modeling. KEGG follows the principles of data stewardship to be findable, accessible, interoperable, and reusable (FAIR) by providing RESTful access to their database entries via their web-accessible KEGG API. However, the overall FAIRness of KEGG is often limited by the library and software package support available in a given programming language. While R library support for KEGG is fairly strong, Python library support has been lacking. Moreover, there is no software that provides extensive command line level support for KEGG access and utilization.ResultsWe present kegg_pull, a package implemented in the Python programming language that provides better KEGG access and utilization functionality than previous libraries and software packages. Not only does kegg_pull include an application programming interface (API) for Python programming, it also provides a command line interface (CLI) that enables utilization of KEGG for a wide range of shell scripting and data analysis pipeline use-cases. As kegg_pull’s name implies, both the API and CLI provide versatile options for pulling (downloading and saving) an arbitrary (user defined) number of database entries from the KEGG API. Moreover, this functionality is implemented to efficiently utilize multiple central processing unit cores as demonstrated in several performance tests. Many options are provided to optimize fault-tolerant performance across a single or multiple processes, with recommendations provided based on extensive testing and practical network considerations.ConclusionsThe new kegg_pull package enables new flexible KEGG retrieval use cases not available in previous software packages. The most notable new feature that kegg_pull provides is its ability to robustly pull an arbitrary number of KEGG entries with a single API method or CLI command, including pulling an entire KEGG database. We provide recommendations to users for the most effective use of kegg_pull according to their network and computational circumstances.

Urinary protein biomarkers based on LC-MS/MS analysis to discriminate vascular dementia from Alzheimer's disease in Han Chinese population.

This study aimed to identify the potential urine biomarkers of vascular dementia (VD) and unravel the disease-associated mechanisms by applying Liquid chromatography tandem-mass spectrometry (LC-MS/MS). LC-MS/MS proteomic analysis was applied to urine samples from 3 groups, including 14 patients with VD, 9 patients with AD, and 21 normal controls (NC). By searching the MS data by Proteome Discoverer software, analyzing the protein abundances qualitatively and quantitatively, comparing between groups, combining bioinformatics analysis using Gene Ontology (GO) and pathway crosstalk analysis using Kyoto Encyclopedia of Genes and Genomes (KEGG), and literature searching, the differentially expressed proteins (DEPs) of VD can be comprehensively determined at last and were further quantified by receiver operating characteristic (ROC) curve methods. The proteomic findings showed quantitative changes in patients with VD compared to patients with NC and AD groups; among 4,699 identified urine proteins, 939 and 1,147 proteins displayed quantitative changes unique to VD vs. NC and AD, respectively, including 484 overlapped common DEPs. Then, 10 unique proteins named in KEGG database (including PLOD3, SDCBP, SRC, GPRC5B, TSG101/STP22/VPS23, THY1/CD90, PLCD, CDH16, NARS/asnS, AGRN) were confirmed by a ROC curve method. Our results suggested that urine proteins enable detection of VD from AD and VC, which may provide an opportunity for intervention.

Network Pharmacology Research Indicates that Wu-Mei-Wan Treats Obesity by Inhibiting Th17 Cell Differentiation and Alleviating Metabolic Inflammation.

Wu-Mei-Wan (WMW), a traditional Chinese medicine (TCM) formula, has a good effect on the treatment of obesity and has been proven helpful to promote the metabolism of adipose tissue. However, its underlying mechanism remains to be studied. This study aims to explore the potential pharmacological mechanism of WMW in the treatment of obesity. Network pharmacology was used to sort out the relationship between WMW putative targets and obesity-related drug targets or disease targets, which indicated the mechanism of WMW in treating obesity from two aspects of clinical drugs approved by the Food and Drug Administration (FDA) and obesity-related diseases. Databases such as Traditional Chinese Medicine Systems Pharmacology (TCMSP), PubChem, DrugBank, DisGeNET, and Genecards were used to collect information about targets. String platform was used to convert the data into gene symbol of "homo sapiens", and perform gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. With the Human Protein Reference Database (HPRD) as background data, Cytoscape 3.6.0 software was used to construct a new protein-protein interaction (PPI) network. Mechanism diagrams of key pathways were obtained from the KEGG database. AutoDock Vina software was used to conduct molecular docking verification. The number of targets in the overlap between WMW putative targets and obesity-related drug targets accounted for more than 50% of the latter, and HTR3A, SLC6A4, and CYP3A4 were core targets. In obesity-related disease targets-WMW putative targets PPI network, the Th17 cell differentiation pathway, and the IL-17 signaling pathway were key pathways, and the 1st module and the 7th module were central function modules that were highly associated with immunity and inflammation. Molecular docking verified that STAT3, TGFB1, MMP9, AHR, IL1B, and CCL2 were core targets in the treatment of WMW on obesity. WMW has similar effects on lipid and drug metabolism as the current obesity-related drugs, and is likely to treat obesity by inhibiting Th17 cell differentiation and alleviating metabolic inflammation.

Comparative Genomics Analysis Provides New Insights into High Ethanol Tolerance of Lactiplantibacillus pentosus LTJ12, a Novel Strain Isolated from Chinese Baijiu.

Lactic acid bacteria have received a significant amount of attention due to their probiotic characteristics. The species Lactiplantibacillus plantarum and Lactiplantibacillus pentosus are genotypically closely related, and their phenotypes are so similar that they are easily confused and mistaken. In the previous study, an ethanol-resistant strain, LTJ12, isolated from the fermented grains of soy sauce aroma type baijiu in North China, was originally identified as L. plantarum through a 16S rRNA sequence analysis. Here, the genome of strain LTJ12 was further sequenced using PacBio and Illumina sequencing technology to obtain a better understanding of the metabolic pathway underlying its resistance to ethanol stress. The results showed that the genome of strain LTJ12 was composed of one circular chromosome and three circular plasmids. The genome size is 3,512,307 bp with a GC content of 46.37%, and the number of predicted coding genes is 3248. Moreover, by comparing the coding genes with the GO (Gene Ontology), COG (Cluster of Orthologous Groups) and KEGG (Kyoto Encyclopedia of Genes and Genomes) databases, the functional annotation of the genome and an assessment of the metabolic pathways were performed, with the results showing that strain LTJ12 has multiple genes that may be related to alcohol metabolism and probiotic-related genes. Antibiotic resistance gene analysis showed that there were few potential safety hazards. Further, after conducting the comparative genomics analysis, it was found that strain LTJ12 is L. pentosus but not L. plantarum, but it has more functional genes than other L. pentosus strains that are mainly related to carbohydrate transport and metabolism, transcription, replication, recombination and repair, signal transduction mechanisms, defense mechanisms and cell wall/membrane/envelope biogenesis. These unique functional genes, such as gene 2754 (encodes alcohol dehydrogenase), gene 3093 (encodes gamma-D-glutamyl-meso-diaminopimelate peptidase) and some others may enhance the ethanol tolerance and alcohol metabolism of the strain. Taken together, L. pentosus LTJ12 might be a potentially safe probiotic with a high ethanol tolerance and alcohol metabolism. The findings of this study will also shed light on the accurate identification and rational application of the Lactiplantibacillus species.