Analysis of the chemical toxicity effects using the enrichment of Gene Ontology terms and KEGG pathways

Microbiological interpretation of weak ultrasound enhanced biological wastewater treatment - using Escherichia coli degrading glucose as model system

The Escherichia coli (E.coli) degrading glucose irradiated by ultrasound irradiation (20 W, 14 min) was investigated as the model system, the glucose degradation increased by 13 % while the E.coli proliferation decreased by 10 % after culture for 18 h. It indicated a tradeoff effect between substrate degradation and cell proliferation, which drove the enhanced contaminants removal and excess sludge reduction in a weak ultrasound enhanced biological wastewater treatment. The enzymatic activities (catalase, superoxide dismutase, adenosine triphosphatases, lactic dehydrogenase, membrane permeability, intracellular reactive oxygen species and calcium ion of E. coli increased immediately by 12 %, 63 %, 124 %, 19 %, 15 %, 4-fold and 38-fold, respectively by ultrasound irradiation power of 20 W for 14 min. Furthermore, the membrane permeability of irradiated E. coli increased by 26 % even though the ultrasound stopped for 10 h. Additionally, pathways associated with glucose degradation and cell proliferation were continuously up-regulated and down-regulated, respectively.

Comparative metabolomics study on areca nut from China and Southeast Asia (Thailand and Indonesia)

INTRODUCTION

Areca nut is an economic crop and an important component in traditional Chinese medicine (TCM) and ethnomedicine. The crop is rich in alkaloids and flavonoids. Most previous studies have focused on the chemical components, especially alkaloids, in crops from certain areca nut-producing areas.

OBJECTIVE

The purpose of this study was to compare the differences in areca nut seeds in two main cultivation areas, identify differential metabolites, and evaluate seed quality in different production areas.

METHODS

A widely targeted metabolomics method based on ultrahigh-performance liquid chromatography coupled with triple quadrupole mass spectrometry (UHPLC-QQQ-MS), combined with the TCM systems pharmacology (TCMSP) database and multivariate statistical analysis, was used in this study to maximise the differentiation between quality characteristics of areca nut seeds from China and Southeast Asian regions.

RESULTS

Altogether, 1031 metabolites were identified in areca nut seeds; by querying the TCMSP database, 375 metabolites were identified as the main active ingredients. Moreover, the research showed that the metabolic profiles of areca nut seeds from China (ASCN) and Southeast Asia (ASSA) exhibit significant differences, and the difference is mainly reflected in 318 compounds. The relative content of 146 metabolites in ASCN was significantly higher than that in ASSA. Through Kyoto Encyclopedia of Genes and Genomes (KEGG) comparative analysis, areca nut seed metabolites in Chinese production areas were determined to have a wider metabolic pathway.

CONCLUSION

The areca nut seeds from cultivation areas possess many metabolites that are beneficial for health, including alkaloids, amino acids, phenolic acids, and lipids. Thus, compared with ASSA, ASCN have a higher medicinal value. This study provides a direction for the subsequent development and utilisation of areca nut seeds.

Identification of core genes associated with different phosphorus levels in quinoa seedlings by weighted gene co-expression network analysis

BACKGROUND

Quinoa is a highly nutritious and novel crop that is resistant to various abiotic stresses. However, its growth and development is restricted due to its limited utilization of soil phosphorus. Studies on the levels of phosphorus in quinoa seedlings are limited; therefore, we analyzed transcriptome data from quinoa seedlings treated with different concentrations of phosphorus.

RESULTS

To identify core genes involved in responding to various phosphorus levels, the weighted gene co-expression network analysis method was applied. From the 12,085 expressed genes, an analysis of the gene co-expression network was done. dividing the expressed genes into a total of twenty-five different modules out of which two modules were strongly correlated with phosphorus levels. Subsequently we identified five core genes that correlated strongly either positively or negatively with the phosphorus levels. Gene ontology and assessments of the Kyoto Encyclopedia of Genes and Genomes have uncovered important biological processes and metabolic pathways that are involved in the phosphorus level response.

CONCLUSIONS

We discovered crucial new core genes that encode proteins from various transcription factor families, such as MYB, WRKY, and ERF, which are crucial for abiotic stress resistance. This new library of candidate genes associated with the phosphorus level responses in quinoa seedlings will help in breeding varieties that are tolerant to phosphorus levels.

Biological activities of drug inactive ingredients

In a drug formulation (DFM), the major components by mass are not Active Pharmaceutical Ingredient (API) but rather Drug Inactive Ingredients (DIGs). DIGs can reach much higher concentrations than that achieved by API, which raises great concerns about their clinical toxicities. Therefore, the biological activities of DIG on physiologically relevant target are widely demanded by both clinical investigation and pharmaceutical industry. However, such activity data are not available in any existing pharmaceutical knowledge base, and their potentials in predicting the DIG-target interaction have not been evaluated yet. In this study, the comprehensive assessment and analysis on the biological activities of DIGs were therefore conducted. First, the largest number of DIGs and DFMs were systematically curated and confirmed based on all drugs approved by US Food and Drug Administration. Second, comprehensive activities for both DIGs and DFMs were provided for the first time to pharmaceutical community. Third, the biological targets of each DIG and formulation were fully referenced to available databases that described their pharmaceutical/biological characteristics. Finally, a variety of popular artificial intelligence techniques were used to assess the predictive potential of DIGs' activity data, which was the first evaluation on the possibility to predict DIG's activity. As the activities of DIGs are critical for current pharmaceutical studies, this work is expected to have significant implications for the future practice of drug discovery and precision medicine.

Mechanism of Action of Novel Pyrazole Carboxamide Containing a Diarylamine Scaffold against Rhizoctonia solani

In the last few decades, Rhizoctonia solani causing rice sheath blight has resulted in a lot of economic losses in the world. Therefore, many novel pyrazole carboxamide fungicides have been intensively researched and employed to fight against it. In this regard, in recent years, our group reported a novel pyrazole carboxamide containing a diarylamine scaffold with good antifungal activity against rice sheath blight in the pot test and field trial. Following this project, the antifungal mechanism of action of the pyrazole carboxamide has been elucidated in this work. The antifungal result showed that compound SCU2028, N-[2-[(3-chlorophenyl)amino]-phenyl]-3-(difluoromethyl)-1-methyl-1H-pyrazole-4-carboxamide, was equivalent to the commercial fungicide thifluzamide and its EC₅₀ value was 0.022 mg/L against R. solani. Also, the observation results by scanning electron microscopy and transmission electron microscopy showed that it could destroy the fungus' cell walls or membranes and result in the leakage of contents and increase of the number of mitochondria and abnormal morphology. Meanwhile, the result on the mitochondrial membrane potential (MMP) showed that it could decrease R. solani's MMP. Furthermore, the results by label-free quantitative proteomic analysis showed that 1153 proteins were found after R. solani was treated with compound SCU2028, including 212 proteins in the control group and 257 proteins in the treatment group. A total of 142 differential proteins were obtained, of which 92 proteins were upregulated and 50 proteins were downregulated. The differentially expressed proteins affected a series of physiological and biochemical pathways in the mitochondria, endoplasmic reticulum, ribosome, and other related GO and KEGG pathways. In particular, the inhibition of the respiratory chain caused by the TCA cycle and oxidative phosphorylation KEGG pathway indicated that complex II (succinate dehydrogenase) and complex IV (cytochrome oxidase) might be compound SCU2028's main action targets. In addition, multiple experiments of qRT-PCR, enzyme activity detection, and molecular docking confirmed complex II and complex IV as targets. It could be seen that these findings provided a theoretical support for further research and development of the pyrazole carboxamide fungicides.

Developmental toxicity and transcriptome analysis of 4-epianhydrotetracycline to zebrafish (Danio rerio) embryos

As a primary degradation by-product of tetracycline (TC), 4-Epianhydrotetracycline (4-EATC) has been detected frequently in the aquatic environment, which may pose a potential environmental risk to aquatic organisms. Up to now, however, the toxicology study on 4-EATC to aquatic organisms is limited. In the present study, in order to better understand the toxic mechanism of 4-EATC, developmental toxicity including lethal and sublethal effects of 4-EATC and TC were investigated. The results showed that the developmental toxicity of 4-EATC to zebrafish embryos was stronger than that of TC. The 96 h LC₅₀ value of 4-EATC to zebrafish embryos was 29.13 mg/L. Malformations seemed to be the most sensitive sublethal endpoint of 4-EATC exposure, and the 96 h EC₅₀ value was 8.57 mg/L. Transcriptome response of 4-EATC to zebrafish embryos was determined. The results showed that 430 different expression genes (DEGs) caused by 4-EATC, and most enriched in tryptophan (TRP) metabolism pathway. Annotation of DEGs in the TRP metabolism demonstrated that expression of 4 gene products in tryptophan metabolized along the kynurenine (KYN) pathway were changed. Disorder of TRP catabolism in KYN pathway was a potential mechanism of 4-EATC toxicity to zebrafish embryos.

Expression Profile Analysis of Differentially Expressed Circular RNAs in Steroid-Induced Osteonecrosis of the Femoral Head

Background

A growing number of studies have suggested that circular RNAs (circRNAs) serve as potential diagnostic biomarkers in many diseases. However, the role of circRNAs in steroid-induced osteonecrosis of the femoral head (SONFH) has not been reported.

Methods

Secondary sequencing was performed to profile circRNA expression in peripheral blood samples from three SONFH patients and three healthy individuals. We confirmed our preliminary findings by qRT-PCR. Bioinformatics analysis was conducted to predict their functions.

Results

The result showed 345 dysregulated circRNAs. qRT-PCR of eight selected circRNAs preliminarily confirmed the results, which were consistent with RNA sequencing. Bioinformatics analyses were performed to predict the functions of circRNAs to target the genes of miRNAs and the networks of circRNA-miRNA-mRNA interactions.

Conclusions

This study provides a new and fundamental circRNA profile of SONFH and a theoretical basis for further studies on the functions of circRNAs in SONFH.

Comparative transcriptomic analysis and endocuticular protein gene expression of alate adults, workers and soldiers of the termite Reticulitermes aculabialis

BACKGROUND

The insect cuticle is mainly composed of exocuticle and endocuticle layers that consist of a large number of structural proteins. The thickness and synthesis of the exocuticle depend on different castes that perform various functions in alates, workers and soldiers. However, it is not clear whether the soft endocuticle is involved in the division of labour in termite colonies. To reveal the structural characteristics of the endocuticle in different castes, we investigated the thickness of endocuticle layers in alates, workers and soldiers of the termite Reticulitermes aculabialis, and then we sequenced their transcriptome and detected the endocuticle protein genes. The differential expression levels of the endocuticular protein genes were confirmed in the three castes.

RESULTS

We found that there was a great difference in the thickness of the endocuticle among the alates, soldiers and workers. The thickest endocuticle layers were found in the heads of the workers 7.88 ± 1.67 μm. The endocuticle layer in the head of the workers was approximately three-fold and nine-fold thicker than that in the heads of soldiers and alates, respectively. The thinnest endocuticle layers occurred in the head, thorax and abdomen of alates, which were 0.86 ± 0.15, 0.76 ± 0.24 and 0.52 ± 0.17 μm thick, respectively, and had no significant differences. A total of 43,531,650 clean sequencing reads was obtained, and 89,475 unigenes were assembled. Of the 70 identified cuticular protein genes, 10 endocuticular genes that belong to the RR-1 family were selected. qRT-PCR analysis of the five endocuticular genes (SgAbd-2, SgAbd-9, Abd-5, SgAbd-2-like and Abd-4-like) revealed that the endocuticle genes were more highly expressed in workers than in soldiers and alates.

CONCLUSION

These results suggest that SgAbd and Abd are the key components of the endocuticle. We infer that the thicker endocuticle in workers is helpful for them to perform their functions against environmental stress.

Analysis of Protein-Protein Functional Associations by Using Gene Ontology and KEGG Pathway

Protein–protein interaction (PPI) plays an extremely remarkable role in the growth, reproduction, and metabolism of all lives. A thorough investigation of PPI can uncover the mechanism of how proteins express their functions. In this study, we used gene ontology (GO) terms and biological pathways to study an extended version of PPI (protein–protein functional associations) and subsequently identify some essential GO terms and pathways that can indicate the difference between two proteins with and without functional associations. The protein–protein functional associations validated by experiments were retrieved from STRING, a well-known database on collected associations between proteins from multiple sources, and they were termed as positive samples. The negative samples were constructed by randomly pairing two proteins. Each sample was represented by several features based on GO and KEGG pathway information of two proteins. Then, the mutual information was adopted to evaluate the importance of all features and some important ones could be accessed, from which a number of essential GO terms or KEGG pathways were identified. The final analysis of some important GO terms and one KEGG pathway can partly uncover the difference between proteins with and without functional associations.

Analysis of Four Types of Leukemia Using Gene Ontology Term and Kyoto Encyclopedia of Genes and Genomes Pathway Enrichment Scores

AIM AND OBJECTIVE

Leukemia is the second common blood cancer after lymphoma, and its incidence rate has an increasing trend in recent years. Leukemia can be classified into four types: acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), chronic lymphocytic leukemia (CLL), and chronic myelogenous leukemia (CML). More than forty drugs are applicable to different types of leukemia based on the discrepant pathogenesis. Therefore, the identification of specific drug-targeted biological processes and pathways is helpful to determinate the underlying pathogenesis among such four types of leukemia.

METHODS

In this study, the gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways that were highly related to drugs for leukemia were investigated for the first time. The enrichment scores for associated GO terms and KEGG pathways were calculated to evaluate the drugs and leukemia. The feature selection method, minimum redundancy maximum relevance (mRMR), was used to analyze and identify important GO terms and KEGG pathways.

RESULTS

Twenty Go terms and two KEGG pathways with high scores have all been confirmed to effectively distinguish four types of leukemia.

CONCLUSION

This analysis may provide a useful tool for the discrepant pathogenesis and drug design of different types of leukemia.

Identification and Analysis of Rice Yield-Related Candidate Genes by Walking on the Functional Network

Rice (Oryza sativa L.) is one of the most important staple foods in the world. It is possible to identify candidate genes associated with rice yield using the model of random walk with restart on a functional similarity network. We demonstrated the high performance of this approach by a five-fold cross-validation experiment, as well as the robustness of the parameter r. We also assessed the strength of associations between known seeds and candidate genes in the light of the results scores. The candidates ranking at the top of the results list were considered to be the most relevant rice yield-related genes. This study provides a valuable alternative for rice breeding and biology research. The relevant dataset and script can be downloaded at the website: http://lab.malab.cn/jj/rice.htm.

Inferring anatomical therapeutic chemical (ATC) class of drugs using shortest path and random walk with restart algorithms

The anatomical therapeutic chemical (ATC) classification system is a widely accepted drug classification scheme. This system comprises five levels and includes several classes in each level. Drugs are classified into classes according to their therapeutic effects and characteristics. The first level includes 14 main classes. In this study, we proposed two network-based models to infer novel potential chemicals deemed to belong in the first level of ATC classification. To build these models, two large chemical networks were constructed using the chemical-chemical interaction information retrieved from the Search Tool for Interactions of Chemicals (STITCH). Two classic network algorithms, shortest path (SP) and random walk with restart (RWR) algorithms, were executed on the corresponding network to mine novel chemicals for each ATC class using the validated drugs in a class as seed nodes. Then, the obtained chemicals yielded by these two algorithms were further evaluated by a permutation test and an association test. The former can exclude chemicals produced by the structure of the network, i.e., false positive discoveries. By contrast, the latter identifies the most important chemicals that have strong associations with the ATC class. Comparisons indicated that the two models can provide quite dissimilar results, suggesting that the results yielded by one model can be essential supplements for those obtained by the other model. In addition, several representative inferred chemicals were analyzed to confirm the reliability of the results generated by the two models. This article is part of a Special Issue entitled: Accelerating Precision Medicine through Genetic and Genomic Big Data Analysis edited by Yudong Cai & Tao Huang.

Circulating microRNA signature of steroid-induced osteonecrosis of the femoral head

OBJECTIVES

Steroid-induced osteonecrosis of the femoral head (ONFH) is a common orthopaedic disease of which early detection remains clinically challenging. Accumulating evidences indicated that circulating microRNAs (miRNAs) plays vital roles in the development of several bone diseases. However, the association between circulating miRNAs and steroid-induced ONFH remains elusive.

MATERIALS AND METHODS

miRNA microarray was performed to identify the differentially abundant miRNAs in the serums of systemic lupus erythematosus (SLE) patients with steroid-induced ONFH as compared with SLE control and healthy control group. We predicted the potential functions of these differentially abundant miRNAs using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses and reconstructed the regulatory networks of miRNA-mRNA interactions.

RESULTS

Our data indicated that there were 11 differentially abundant miRNAs (2 upregulated and 9 downregulated) between SLE-ONFH group and healthy control group and 42 differentially abundant miRNAs (14 upregulated and 28 downregulated) between SLE-ONFH group and SLE control group. We also predicted the potential functions of these differentially abundant miRNAs using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses and reconstructed the regulatory networks of miRNA-mRNA interactions.

CONCLUSIONS

These findings corroborated the idea that circulating miRNAs play significant roles in the development of ONFH and may serve as diagnostic markers and therapeutic targets.

Identification of compound-protein interactions through the analysis of gene ontology, KEGG enrichment for proteins and molecular fragments of compounds

Compound-protein interactions play important roles in every cell via the recognition and regulation of specific functional proteins. The correct identification of compound-protein interactions can lead to a good comprehension of this complicated system and provide useful input for the investigation of various attributes of compounds and proteins. In this study, we attempted to understand this system by extracting properties from both proteins and compounds, in which proteins were represented by gene ontology and KEGG pathway enrichment scores and compounds were represented by molecular fragments. Advanced feature selection methods, including minimum redundancy maximum relevance, incremental feature selection, and the basic machine learning algorithm random forest, were used to analyze these properties and extract core factors for the determination of actual compound-protein interactions. Compound-protein interactions reported in The Binding Databases were used as positive samples. To improve the reliability of the results, the analytic procedure was executed five times using different negative samples. Simultaneously, five optimal prediction methods based on a random forest and yielding maximum MCCs of approximately 77.55 % were constructed and may be useful tools for the prediction of compound-protein interactions. This work provides new clues to understanding the system of compound-protein interactions by analyzing extracted core features. Our results indicate that compound-protein interactions are related to biological processes involving immune, developmental and hormone-associated pathways.