Bile acids repress the transcription of cytochrome P450 7A1 (CYP7A1), which catalyzes the rate-limiting step in bile acid biosynthesis. Although bile acids activate the farnesoid X receptor (FXR), the mechanism underlying bile acid-mediated repression of CYP7A1 remained unclear. We have used a potent, nonsteroidal FXR ligand to show that FXR induces expression of small heterodimer partner 1 (SHP-1), an atypical member of the nuclear receptor family that lacks a DNA-binding domain. SHP-1 represses expression of CYP7A1 by inhibiting the activity of liver receptor homolog 1 (LRH-1), an orphan nuclear receptor that is known to regulate CYP7A1 expression positively. This bile acid-activated regulatory cascade provides a molecular basis for the coordinate suppression of CYP7A1 and other genes involved in bile acid biosynthesis.
GATA-3 is one member of a growing family of related transcription factors which share a strongly conserved expression pattern in all vertebrate organisms. In order to elucidate GATA-3 function using a direct genetic approach, we have disrupted the murine gene by homologous recombination in embryonic stem cells. Mice heterozygous for the GATA3 mutation are fertile and appear in all respects to be normal, whereas homozygous mutant embryos die between days 11 and 12 postcoitum (p.c.) and display massive internal bleeding, marked growth retardation, severe deformities of the brain and spinal cord, and gross aberrations in fetal liver haematopoiesis.
Graphical Abstract Highlights d The exRNA Atlas provides access to human exRNA profiles and web-accessible tools d Atlas analysis reveals six exRNA cargo types present across five human biofluids d Five of the cargo types associate with specific vesicular and non-vesicular carriers d These findings and resources empower studies of extracellular RNA communication An extracellular RNA atlas from five human biofluids (serum, plasma, cerebrospinal fluid, saliva, and urine) reveals six extracellular RNA cargo types, including both vesicular and nonvesicular carriers. SUMMARY To develop a map of cell-cell communication mediated by extracellular RNA (exRNA), the NIH Extracellular RNA Communication Consortium created the exRNA Atlas resource (https://exrna-atlas.org). The Atlas version 4P1 hosts 5,309 exRNA-seq and exRNA qPCR profiles from 19 studies and a suite of analysis and visualization tools. To analyze variation between profiles, we apply computational deconvolution. The analysis leads to a model with six exRNA cargo types (CT1, CT2, CT3A, CT3B, CT3C, CT4), each detectable in multiple biofluids (serum, plasma, CSF, saliva, urine). Five of the cargo types associate with known vesicular and non-vesicular (lipoprotein and ribonucleoprotein) exRNA carriers. To validate utility of this model, we re-analyze an exercise response study by deconvolution to identify physiologically relevant response pathways that were not detected previously.To enable wide application of this model, as part of the exRNA Atlas resource, we provide tools for deconvolution and analysis of user-provided case-control studies.
We describe an mRNA profiling technique for determining differential gene expression that utilizes, but does not require, prior knowledge of gene sequences. This method permits high-throughput reproducible detection of most expressed sequences with a sensitivity of greater than 1 part in 100,000. Gene identification by database query of a restriction endonuclease fingerprint, confirmed by competitive PCR using gene-specific oligonucleotides, facilitates gene discovery by minimizing isolation procedures. This process, called GeneCalling, was validated by analysis of the gene expression profiles of normal and hypertrophic rat hearts following in vivo pressure overload.
The Extracellular RNA Communication Consortium (ERCC) was launched to accelerate progress in the new field of extracellular RNA (exRNA) biology and to establish whether exRNAs and their carriers, including extracellular vesicles (EVs), can mediate intercellular communication and be utilized for clinical applications. Phase 1 of the ERCC focused on exRNA/EV biogenesis and function, discovery of exRNA biomarkers, development of exRNA/EV-based therapeutics, and construction of a robust set of reference exRNA profiles for a variety of biofluids. Here, we present progress by ERCC investigators in these areas, and we discuss collaborative projects directed at development of robust methods for EV/exRNA isolation and analysis and tools for sharing and computational analysis of exRNA profiling data. The Origin of the ERCC1 ProgramThe discovery that extracellular vesicles (EVs) can transport RNAs between cells (Skog et al., 2008;Valadi et al., 2007) suggested that RNAs carried by EVs may play a previously unrecognized role in intercellular communication and launched the field of extracellular RNA (exRNA) biology. It was quickly recognized that exRNAs might also have utility as biomarkers of disease and as therapeutic agents. There were, however, many gaps in knowledge and technical challenges to overcome. The mechanisms of EV biogenesis and uptake, exRNA cargo selection, and exRNA function were largely unknown. Moreover, efficient and reproducible methods for isolation and analysis of exRNAs were not available, further complicated by early findings that suggesting that exRNAs can associate with multiple subtypes
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