Rat deconvolution as knowledge miner for immune cell trafficking from toxicogenomics databases
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PROVIDER: PRJNA1001893 | ENA |
REPOSITORIES: ENA
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Project description:Toxicogenomics databases are useful for understanding biological responses in individuals because they are derived from well-controlled experiments and include a diverse spectrum of biological responses. Although these databases contain no information regarding immune cells in the liver, which are important in the progression of liver injury, deconvolution that estimates cell-type proportions from bulk transcriptome could add information regarding immune cell trafficking to the database. However, deconvolution has been mainly applied to humans and mice and less often to rats, which are the main target of toxicogenomics databases. Here, we developed a deconvolution method for rats and established a methodology to obtain information regarding immune cells from toxicogenomics databases. The contributions of this work are three-fold. First, we obtained the gene expression profiles of various rat immune cells necessary for deconvolution and constructed a dataset; second, we compared the accuracy of models based on human and mouse datasets and showed the impact of species differences on deconvolution; third, we showed that rat deconvolution could retrieve information regarding immune cell trafficking from toxicogenomics databases. Correspondence: Tadahaya Mizuno
2023-08-15 | GSE239996 | GEO
Project description:Toxicogenomics databases are useful for understanding biological responses in individuals because they include a diverse spectrum of biological responses. Although these databases contain no information regarding immune cells in the liver, which are important in the progression of liver injury, deconvolution that estimates cell-type proportions from bulk transcriptome could extend immune information. However, deconvolution has been mainly applied to humans and mice and less often to rats, which are the main target of toxicogenomics databases. Here, we developed a deconvolution method for rats to retrieve information regarding immune cells from toxicogenomics databases. The rat-specific deconvolution showed high correlations for several types of immune cells between spleen and blood, and between liver treated with toxicants compared with those based on human and mouse data. Additionally, we found 4 clusters of compounds in Open TG-GATEs database based on estimated immune cell trafficking, which are different from those based on transcriptome data itself. The contributions of this work are three-fold. First, we obtained the gene expression profiles of 6 rat immune cells necessary for deconvolution. Second, we clarified the importance of species differences on deconvolution. Third, we retrieved immune cell trafficking from toxicogenomics databases. Accumulated and comparable immune cell profiles of massive data of immune cell trafficking in rats could deepen our understanding of enable us to clarify the relationship between the order and the contribution rate of immune cells, chemokines and cytokines, and pathologies. Ultimately, these findings will lead to the evaluation of organ responses in Adverse Outcome Pathway.
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2010-06-09 | E-GEOD-2045 | biostudies-arrayexpress
Project description:Coffee leaf miner is an important plague in coffee crops. Using subtracted cDNA libraries and nylon filter arrays, we analyzed the expression profile of 1536 expressed sequence tags (ESTs) of coffee plants from an hybrid progeny (C. arabica x C. racemosa), containg resistant (R) and susceptible plants (S) to the infestation of coffee leaf miner. Leaf discs were collected from non-infested plants (R control - RC; S control - SC), infested plants after moth oviposition (R oviposition - Ro; S oviposition - So) and infested after larvar eclosion (R eclosion - Re; S eclosion - Se). Isolation and characterization of Coffea genes induced during coffee leaf miner (Leucoptera coffeella) infestation. Plant Science 169(2):351-360 Keywords: ordered
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Project description:Due to its high throughput nature, toxicogenomics can provide a broad picture of a toxic response, offering the ideal functional platform for grouping chemicals according to mechanistic similarity. In this way, toxicogenomics has found its way into predictive toxicology. However, so far, the predictive potential of toxicogenomics in an endocrine disruptive screening context has not been extensively examined. The aim of this study was to combine a toxicogenomics approach with an estrogen-sensitive MCF-7 cell system. In total, 18 compounds with endocrine disruptive potential were selected, of which 11 are listed as ICCVAM reference compounds for validation of estrogen receptor (ER) binding and transactivation assays. In this way, the grouping and classification potential of the gene expression profiles could be directly compared to the more classical estrogenicity screens, such as ER binding, ER transactivation and MCF-7 cell proliferation assays. Results indicated that this toxicogenomics approach was clearly capable of grouping compounds into strong, weak and non estrogenic groups. This demonstrates the value of toxicogenomics for evaluating gradual differences in related modes of action, in addition to the more common search for opposite modes of action. The chemical groups were represented by interesting marker genes such as PGR, ERBB2, CXCL12, AREG and EGR3, including some early-responsive (4h) potential biomarkers. These results open the discussion on the added value of a broader endpoint evaluation in estrogenicity screens provided by omics-techniques compared to the classical single endpoint based assays.
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