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Assessing the Microbiome—Current and Future Technologies and Applications
Published in David Perlmutter, The Microbiome and the Brain, 2019
Thomas Gurry, Shrish Budree, Alim Ladha, Bharat Ramakrishna, Zain Kassam
As the field of microbiome sequencing progresses, investigators are striving to unearth the mechanisms underlying host–microbiome interactions. This requires researchers to study the function of a host’s microbiome and not just its identity. Using both 16S and, more reliably, shotgun metagenomics, researchers can now determine the functional capacity of a microbial community. This type of analysis is facilitated by a computational software package like PICRUSt. Metagenomic data can be mapped against a reference database called the Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology (KO) to determine representative metabolic pathways present in a given sample. With 16S data, OTUs must be mapped to phylogenetic trees and reference databases containing information on their broader genetic code, a method which is only moderately reliable (Langille et al. 2013). Therefore, shotgun metagenomics provides a significantly more reliable method for determining functional profiles of the microbiome.
The Development of Improved Therapeutics through a Glycan- “Designer” Approach
Published in Peter Grunwald, Pharmaceutical Biocatalysis, 2019
For a more specific investigation of cancer-associated carbohydrates and their pathways in cancer research, the free database KEGG Cancer can be explored (https://www.genome.jp/kegg/glycan/). KEGG mapping allows one to view the glycan biosynthesis pathway, obtaining additional information of the genetics underlying certain diseases including references. The KEGG glycan structure database relies on the previously mentioned CarBank database. KEGG database is one of the first databases that implement cross-disciplinary data (genes, disease pathways, structures, glycan structures).
Computational characterization and integrative analysis of proteins involved in spermatogenesis
Published in C. Yan Cheng, Spermatogenesis, 2018
Pranitha Jenardhanan, Manivel Panneerselvam, Premendu P. Mathur
With the identification of differentially expressed genes/proteins, it becomes necessary to understand their biological significance. Application of bioinformatics finds its place in this step, where several integrated bioinformatics tools are employed. The basic understanding of biological significance aims at understanding different aspects of gene products such as their cellular location, functional classification, structural classification, and analysis of their domain, structures, relationship to biological pathways, and diseases. Several integrated bioinformatics tools like the Database for Annotation, Visualization and Integrated Discovery (DAVID), gene ontology, and Kyoto Encyclopedia of Genes and Genomes (KEGG) are being used for this purpose. DAVID tool performs gene-list-based annotations15,16 that takes gene list as the input and identifies data related to gene ontology17 and metabolic pathway analysis from KEGG.18 With identification of protein targets it becomes essential to understand their interaction partners, which can be achieved using web-based protein-protein interaction databases such as String.19 Later, structural analysis of predicted targets is achieved by three-dimensional structure prediction of proteins by the MODELLER suite20 and the Rosetta suite.21 With analysis of individual protein structures it becomes essential to understand how selected protein interacts with its targets using protein-protein docking software such as HADDOCK22 and protein-ligand docking such as Schrodinger Glide.23 Finally, the conformational changes induced by complex formation are evaluated using molecular dynamics simulation studies that use software such as the Gromacs suite.24
Comparative transcriptome analysis reveals the effects of different feeding times on the hepatopancreas of Chinese mitten crabs
Published in Chronobiology International, 2023
Yingkai Xu, Baoli Zhang, Changyue Yu, Ziwei Hung, Nan Hu, Yuqiao Cai, Yingdong Li
After obtaining the gene expression results, the R-based DESeq software package was used to identify DEGs between samples. Based on expression differences, a |log2fold-change| > 1 and a significant p value < .05 were used as the screening conditions for DEGs. GO and KEGG enrichment analyses were performed on the DEGs. The software used for GO analysis was topGO. During the analysis, the differential genes annotated based on GO terms were used to count the number of genes and gene lists associated with each term; the p value was calculated using the hypergeometric distribution method. KEGG is a database that integrates genomic, chemical, and systemic functional information. One of the features of the KEGG database is the association between gene catalogs from fully sequenced genomes and system functions at higher levels for cells, species, and ecosystems.
Dual transcriptome of Streptococcus mutans and Candida albicans interplay in biofilms
Published in Journal of Oral Microbiology, 2023
Yan Zeng, Elena Rustchenko, Xinyan Huang, Tong Tong Wu, Megan L. Falsetta, Jin Xiao
We further performed KEGG pathway analyses to understand the functional association with gene expression. KEGG PATHWAY is a collection of pathway maps representing the knowledge of the molecular interaction, reaction and relation networks for metabolism, genetic information processing, environmental information processing, cellular processes, organismal systems, human diseases and drug development. mutans DEGs [> (-) 1 Log2 fold change] and 92 C. albicans DEGs [> (-) 3 Log2 fold change] were input into KEGG mapper for analysis. 17 pathways for S. mutans and 36 pathways for C. albicans were mapped in Figure 4 and Figure 5. KEGG pathway analyses showed that nearly all the S. mutans and C. albicans DEGs that related to metabolism pathways were up-regulated.
Alysicarpus vaginalis Bio-Actives as ESR Signaling Pathway Inhibitor for Breast Cancer Treatment: A Network Pharmacology Approach
Published in Nutrition and Cancer, 2022
Nikhil S. Sakle, Shweta A. More, Santosh N. Mokale
Gene Ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis is carried on ClueGO v_2.5.5, a Cytoscape plug-in which provides biological interpretation of large lists of genes outcome from pathway enrichment analysis. It gives the information and complete knowledge of pathways and its significance. GO enrichment analysis methods helps to determine whether GO terms about specific biological processes, molecular functions, or cellular components (26). The GO describes the biological domain with respect to three aspects i.e., biological processes (BPs), molecular functions (MFs) and cellular components (CCs). KEGG pathway is used to study the gene functions and metabolic pathway to discover the contributing pathway of the target linked with the disease. Then, top 10 GO terms and KEGG pathway of each was selected for further analysis (27).