Transcriptome and Gene Ontology (GO) Enrichment Analysis Reveals Genes Involved in Biotin Metabolism That Affect L-Lysine Production in Corynebacterium glutamicum

LC-qTOF-MS analysis of fish immune organs reveals the distribution of amino acids in response to metabolic adaptation of the survival phenotype in grouper against Vibrio infection

Epinephelus fuscoguttatus is economically crucial to various Southeast Asia countries where they are reared in fish farms to meet the demand for supply. However, a systemic infectious disease known as vibriosis has steadily and extensively affected the fish farming industry. The disease is caused by Vibrio spp., which are pathogenic gram-negative bacteria. This study focused on understanding the host's metabolic adaptation against Vibrio vulnificus infection, which features a survival phenotype, by profiling the metabolites in grouper fingerlings that survived the experimental infection. Mapping of the pathways is crucial to explain the roles of metabolites in fish immunity. A solvent extraction method was used on the grouper's immune organs (gills, liver and spleen) prior to Liquid Chromatography-Quadrupole Time-of-Flight Mass Spectrometry (LC-qTOF-MS) analysis. The metabolites identified in fingerlings that survived experimental infections were mostly amino acids (primary metabolites). Glutamine (0.44%), alanine (0.68%), phenylalanine (2.63%) and tyrosine (2.60%) were highly abundant in survived-infected gills. Aspartic acid (13.57%) and leucine (4.01%) were highly abundant in the livers of the survived-infected fish and lysine was highly abundant in both gills (2.94%) and liver (3.64%) of the survived-infected fish. Subsequent bioinformatics analysis revealed the involvement of the identified functional amino acids in various immune-related pathways. The current findings facilitate the comprehension of the metabolic adaptation of grouper fingerlings that exhibited a survival phenotype against Vibrio infection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-022-03269-1.

Robust prognostic model based on immune infiltration-related genes and clinical information in ovarian cancer

Immune infiltration of ovarian cancer (OV) is a critical factor in determining patient's prognosis. Using data from TCGA and GTEx database combined with WGCNA and ESTIMATE methods, 46 genes related to OV occurrence and immune infiltration were identified. Lasso and multivariate Cox regression were applied to define a prognostic score (IGCI score) based on 3 immune genes and 3 types of clinical information. The IGCI score has been verified by K‐M curves, ROC curves and C‐index on test set. In test set, IGCI score (C‐index = 0.630) is significantly better than AJCC stage (C‐index = 0.541, p < 0.05) and CIN25 (C‐index = 0.571, p < 0.05). In addition, we identified key mutations to analyse prognosis of patients and the process related to immunity. Chi‐squared tests revealed that 6 mutations are significantly (p < 0.05) related to immune infiltration: BRCA1, ZNF462, VWF, RBAK, RB1 and ADGRV1. According to mutation survival analysis, we found 5 key mutations significantly related to patient prognosis (p < 0.05): CSMD3, FLG2, HMCN1, TOP2A and TRRAP. RB1 and CSMD3 mutations had small p‐value (p < 0.1) in both chi‐squared tests and survival analysis. The drug sensitivity analysis of key mutation showed when RB1 mutation occurs, the efficacy of six anti‐tumour drugs has changed significantly (p < 0.05).

Genome Instability-Associated Long Non-Coding RNAs Reveal Biomarkers for Glioma Immunotherapy and Prognosis

Genome instability is a hallmark of tumors and is involved in proliferation, invasion, migration, and treatment resistance of many tumors. However, the relationship of genome instability with gliomas remains unclear. Here, we constructed genome instability-derived long non-coding RNA (lncRNA)-based gene signatures (GILncSig) using genome instability-related lncRNAs derived from somatic mutations. Multiple platforms were used to confirm that the GILncSig were closely related to patient prognosis and clinical characteristics. We found that GILncSig, the glioma microenvironment, and glioma cell DNA methylation-based stemness index (mDNAsi) interacted with each other to form a complex regulatory network. In summary, this study confirmed that GILncSig was an independent prognostic indicator for patients, distinguished high-risk and low-risk groups, and affected immune-cell infiltration and tumor-cell stemness indicators (mDNAsi) in the tumor microenvironment, resulting in tumor heterogeneity and immunotherapy resistance. GILncSig are expected to provide new molecular targets for the clinical treatment of patients with gliomas.

A systematic bioinformatics approach for large-scale identification and characterization of host-pathogen shared sequences

Background

Biology has entered the era of big data with the advent of high-throughput omics technologies. Biological databases provide public access to petabytes of data and information facilitating knowledge discovery. Over the years, sequence data of pathogens has seen a large increase in the number of records, given the relatively small genome size and their important role as infectious and symbiotic agents. Humans are host to numerous pathogenic diseases, such as that by viruses, many of which are responsible for high mortality and morbidity. The interaction between pathogens and humans over the evolutionary history has resulted in sharing of sequences, with important biological and evolutionary implications.

Results

This study describes a large-scale, systematic bioinformatics approach for identification and characterization of shared sequences between the host and pathogen. An application of the approach is demonstrated through identification and characterization of the Flaviviridae-human share-ome. A total of 2430 nonamers represented the Flaviviridae-human share-ome with 100% identity. Although the share-ome represented a small fraction of the repertoire of Flaviviridae (~ 0.12%) and human (~ 0.013%) non-redundant nonamers, the 2430 shared nonamers mapped to 16,946 Flaviviridae and 7506 human non-redundant protein sequences. The shared nonamer sequences mapped to 125 species of Flaviviridae, including several with unclassified genus. The majority (~ 68%) of the shared sequences mapped to Hepacivirus C species; West Nile, dengue and Zika viruses of the Flavivirus genus accounted for ~ 11%, ~ 7%, and ~ 3%, respectively, of the Flaviviridae protein sequences (16,946) mapped by the share-ome. Further characterization of the share-ome provided important structural-functional insights to Flaviviridae-human interactions.

Conclusion

Mapping of the host-pathogen share-ome has important implications for the design of vaccines and drugs, diagnostics, disease surveillance and the discovery of unknown, potential host-pathogen interactions. The generic workflow presented herein is potentially applicable to a variety of pathogens, such as of viral, bacterial or parasitic origin.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07657-4.

Predicting miRNA-lncRNA interactions and recognizing their regulatory roles in stress response of plants

It has been found that each non-coding RNA (ncRNA) can act not only through its target gene, but also interact with each other to act on biological traits, and this interaction is more common. Many studies focus mainly on the analysis of microRNA(miRNA) and message RNA (mRNA) interactions. In this study, we investigated miRNA and long non-coding RNA (lncRNA) interactions using support vector regression (SVR) for prediction of new target genes in Arabidopsis thaliana and identify some regulatory roles in stress response. The networks of miRNA-mRNA, miRNA-lncRNA and miRNA-mRNA-lncRNA were constructed. They were further analyzed and interpreted in R. We showed that miRNA with low sequence number, targeted lncRNA with high sequence number and miRNA with high sequence number targeted lncRNA with low sequence number. The experimental results showed that there is a regulatory relationship between miRNA-lncRNA. New RNA targets were predicted using SVR with new gene expression mechanism and the stress related functions were annotated.

Identification of potential drugs for diffuse large b-cell lymphoma based on bioinformatics and Connectivity Map database

Diffuse large B-cell lymphoma (DLBCL) is the most main subtype in non-Hodgkin lymphoma. After chemotherapy, about 30% of patients with DLBCL develop resistance and relapse. This study was to identify potential therapeutic drugs for DLBCL using the bioinformatics method. The differentially expressed genes (DEGs) between DLBCL and non-cancer samples were downloaded from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). Gene ontology enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of DEGs were analyzed using the Database for Annotation, Visualization, and Integrated Discovery. The R software package (SubpathwayMiner) was used to perform pathway analysis on DEGs affected by drugs found in the Connectivity Map (CMap) database. Protein-protein interaction (PPI) networks of DEGs were constructed using the Search Tool for the Retrieval of Interacting Genes online database and Cytoscape software. In order to identify potential novel drugs for DLBCL, the DLBCL-related pathways and drug-affected pathways were integrated. The results showed that 1927 DEGs were identified from TCGA and GEO. We found 54 significant pathways of DLBCL using KEGG pathway analysis. By integrating pathways, we identified five overlapping pathways and 47 drugs that affected these pathways. The PPI network analysis results showed that the CDK2 is closely associated with three overlapping pathways (cell cycle, p53 signaling pathway, and small cell lung cancer). The further literature verification results showed that etoposide, rinotecan, methotrexate, resveratrol, and irinotecan have been used as classic clinical drugs for DLBCL. Anisomycin, naproxen, gossypol, vorinostat, emetine, mycophenolic acid and daunorubicin also act on DLBCL. It was found through bioinformatics analysis that paclitaxel in the drug-pathway network can be used as a potential novel drug for DLBCL.

Understanding the high L-valine production in Corynebacterium glutamicum VWB-1 using transcriptomics and proteomics

Toward the elucidation of the advanced mechanism of l-valine production by Corynebacterium glutamicum, a highly developed industrial strain VWB-1 was analyzed, employing the combination of transcriptomics and proteomics methods. The transcriptional level of 1155 genes and expression abundance of 96 proteins were changed significantly by the transcriptome and proteome comparison of VWB-1 and ATCC 13869. It was indicated that the key genes involved in the biosynthesis of l-valine, ilvBN, ilvC, ilvD, ilvE were up-regulated in VWB-1, which together made prominent contributions in improving the carbon flow towards l-valine. The l-leucine and l-isoleucine synthesis ability were weakened according to the down-regulation of leuB and ilvA. The up-regulation of the branched chain amino acid transporter genes brnFE promoted the l-valine secretion capability of VWB-1. The NADPH and ATP generation ability of VWB-1 were strengthened through the up-regulation of the genes involved in phosphate pentose pathway and TCA pathway. Pyruvate accumulation was achieved through the weakening of the l-lactate, acetate and l-alanine pathways. The up-regulation of the genes coding for elongation factors and ribosomal proteins were beneficial for l-valine synthesis in C. glutamicum. All information acquired were useful for the genome breeding of better industrial l-valine producing strains.

Metabolic Design of Corynebacterium glutamicum for Production of l-Cysteine with Consideration of Sulfur-Supplemented Animal Feed

l-Cysteine is a valuable sulfur-containing amino acid widely used as a nutrition supplement in industrial food production, agriculture, and animal feed. However, this amino acid is mostly produced by acid hydrolysis and extraction from human or animal hairs. In this study, we constructed recombinant Corynebacterium glutamicum strains that overexpress combinatorial genes for l-cysteine production. The aims of this work were to investigate the effect of the combined overexpression of serine acetyltransferase (CysE), O-acetylserine sulfhydrylase (CysK), and the transcriptional regulator CysR on l-cysteine production. The CysR-overexpressing strain accumulated approximately 2.7-fold more intracellular sulfide than the control strain (empty pMT-tac vector). Moreover, in the resulting CysEKR recombinant strain, combinatorial overexpression of genes involved in l-cysteine production successfully enhanced its production by approximately 3.0-fold relative to that in the control strain. This study demonstrates a biotechnological model for the production of animal feed supplements such as l-cysteine using metabolically engineered C. glutamicum.