Biology subjects

wang, g.

Publications and source records attributed to wang, g..

3 recordsLinked to original sources

bioRxiv2022

Revealing the molecular mechanisms underlying neural transmission of female pheromone signals in the male antennae of Antheraea pernyi by integrative proteomics and metabolomics analysis

Detection of sex pheromones of insects relies on the antennae. The female pheromone signal transmission in the male antennae ultimately initiates the courtship and mating behaviors of males. To investigate the proteins and metabolites involved in this neural transduction, the study adopted integrative proteomics and metabolomics analysis including tandem mass tag (TMT) proteomic quantification and liquid chromatography tandem mass spectrometry (LC/MS)-based metabolomics for comparing proteomic and metabolic changes between the antennae of male moths following stimulation by females and the non-stimulated males of A. pernyi. A total of 92 differentially expressed proteins (DEPs) containing 52 up-regulated and 40 down-regulated proteins and 545 differentially expressed metabolites (DEMs) including 218 up- and 327 down-regulated metabolites were identified from the antennae of female-stimulated male moths based on the proteome and metabolome data, respectively. GO enrichment analysis showed that 45 DEPs could be enriched into different GO terms on different levels. COG analysis indicated that 61 DEPs were assigned to 20 functional categories. The 160 DEMs respectively fell into 11 and 44 classes at SuperClass and Class levels based on HMDB annotation. KEGG pathway enrichment analysis indicated that totally 43 DEMs were enriched into 6, 27, and 87 pathways on level 1, 2, and 3, respectively. A number of DEPs and DEMs related to neural transmission of female pheromone signals in the male antennae of A. pernyi were screened, including tyrosine hydroxylase, cryptochrome-1, tachykinin, arylalkylamine N-acetyltransferase, cadherin-23, glutathione S-transferase delta 3, tyramine, tryptamine, n-oleoyl dopamine, n-stearoyl dopamine, and n-stearoyl tyrosine. We concluded that the altered expression levels of those proteins or metabolites were involved in regulating the neuron activity for enhanced transmission of neural impulses and continuous perception, reception, and transduction of female pheromone signals. Our findings yielded novel insights into the potential molecular mechanisms in the antennae of male A. pernyi responding to female attraction.

molecular biology↗

bioRxiv2022

PlantCADB: A comprehensive plant chromatin accessibility database

Chromatin accessibility landscapes are essential for detecting regulatory elements, illustrating the corresponding regulatory networks, and, ultimately, understanding the molecular bases underlying key biological processes. With the advancement of sequencing technologies, a large volume of chromatin accessibility data has been accumulated and integrated in humans and other mammals. These data have greatly advanced the study of disease pathogenesis, cancer survival prognosis, and tissue development. To advance the understanding of molecular mechanisms regulating plant key traits and biological processes, we developed a comprehensive plant chromatin accessibility database (PlantCADB, https://bioinfor.nefu.edu.cn/PlantCADB/) from 649 samples of 37 species. Among these samples, 159 are abiotic stress-related (including heat, cold, drought, salt, etc.), 232 are development-related and 376 are tissue-specific. Overall, 18,339,426 accessible chromatin regions (ACRs) were compiled. These ACRs were annotated with genomic information, associated genes, transcription factors footprint, motif, and SNPs. Additionally, PlantCADB provides various tools to visualize ACRs and corresponding annotations. It thus forms an integrated, annotated, and analyzed plant-related chromatin accessibility information which can aid to better understand genetic regulatory networks underlying development, important traits, stress adaptions, and evolution.

genomics↗

bioRxiv2019

INeo-Epp: T-cell HLA class I immunogenic or neoantigenic epitope prediction via random forest algorithm based on sequence related amino acid features

In silico T-cell epitope prediction plays an important role in immunization experimental design and vaccine preparation. Currently, most epitope prediction research focuses on peptide processing and presentation, e.g. proteasomal cleavage, transporter associated with antigen processing (TAP) and major histocompatibility complex (MHC) combination. To date, however, the mechanism for immunogenicity of epitopes remains unclear. It is generally agreed upon that T-cell immunogenicity may be influenced by the foreignness, accessibility, molecular weight, molecular structure, molecular conformation, chemical properties and physical properties of target peptides to different degrees. In this work, we tried to combine these factors. Firstly, we collected significant experimental HLA-I T-cell immunogenic peptide data, as well as the potential immunogenic amino acid properties. Several characteristics were extracted, including amino acid physicochemical property of epitope sequence, peptide entropy, eluted ligand likelihood percentile rank (EL rank(%)) score and frequency score for immunogenic peptide. Subsequently, a random forest classifier for T cell immunogenic HLA-I presenting antigen epitopes and neoantigens was constructed. The classification results for the antigen epitopes outperformed the previous research (the optimal AUC=0.81, external validation data set AUC=0.77). As mutational epitopes generated by the coding region contain only the alterations of one or two amino acids, we assume that these characteristics might also be applied to the classification of the endogenic mutational neoepitopes also called neoantigens. Based on mutation information and sequence related amino acid characteristics, a prediction model of neoantigen was established as well (the optimal AUC=0.78). Further, an easy-to-use web-based tool INeo-Epp was developed (available at http://www.biostatistics.online/INeo-Epp/neoantigen.php)for the prediction of human immunogenic antigen epitopes and neoantigen epitopes.

immunology↗