Project description:The microbiome plays a significant role in gut brain communication and is linked to several animal and human diseases. Hypertension is characterized by gut dysbiosis, and this study aimed to determine how the gut microbiome differed between male and female normotensive and hypertensive rodents. WKY is a genetic control for spontaneous hypertensive rats or SHR which is well documented to have elevated blood pressure at approximately 8 to 10 weeks. We compared the microbiome of normotensive and hypertensive rodents using a meta-genomics approach.
Project description:The purpose of this study is to explore the effects of cooked navy bean powder or rice bran consumption on the stool microbiome and metabolome of colorectal cancer survivors and healthy adults.
| 2150580 | ecrin-mdr-crc
Project description:meta-transcriptomics sequencing data
Project description:In this study, integrated transcriptomics and proteomics approaches were applied to investigate the molecular responses of JA in the shoots of 7-days old rice (cv. Nipponbare) seedlings exposed to 5 micromolar JA for a period of 7 days. Based on the morphological alteration of JA-exposed rice seedlings, transcript profiling of rice genes was performed in seedlings using rice DNA microarray chip, and proteomics by 2-DGE. This systematic survey showed that JA triggers a chain reaction of altered gene and protein expressions involved in multiple cellular processes in rice growth and development and defense. Keywords: JA exposure response
Project description:Today, swine is regarded as promising biomedical model, however, its gastrointestinal microbiome dynamics have been less investigated than that of humans or murine models . The aim of this study was to establish a high-throughput multi-omics pipeline to investigate the healthy fecal microbiome of swine and its temporal dynamics as basis for future infection studies. To this end, a homogenization protocol based on deep-frozen feces followed by integrated sample preparation for different meta-omics analyses was developed. Subsequent data integration linked microbiome composition with function, i.e. expressed proteins and secreted metabolites.
