Mutations in pre-mRNA processing factors (PRPFs) cause autosomal-dominant retinitis pigmentosa (RP), but it is unclear why mutations in ubiquitously expressed genes cause non-syndromic retinal disease. Here, we generate transcriptome profiles from RP11 (PRPF31-mutated) patient-derived retinal organoids and retinal pigment epithelium (RPE), as well as Prpf31+/− mouse tissues, which revealed that disrupted alternative splicing occurred for specific splicing programmes. Mis-splicing of genes encoding pre-mRNA splicing proteins was limited to patient-specific retinal cells and Prpf31+/− mouse retinae and RPE. Mis-splicing of genes implicated in ciliogenesis and cellular adhesion was associated with severe RPE defects that include disrupted apical – basal polarity, reduced trans-epithelial resistance and phagocytic capacity, and decreased cilia length and incidence. Disrupted cilia morphology also occurred in patient-derived photoreceptors, associated with progressive degeneration and cellular stress. In situ gene editing of a pathogenic mutation rescued protein expression and key cellular phenotypes in RPE and photoreceptors, providing proof of concept for future therapeutic strategies.

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Microglia activation has emerged as a potential key factor in the pathogenesis of Alzheimer’s disease. Metabolite levels assessed by magnetic resonance spectroscopy (MRS) are used as markers of neuroinflammation in neurodegenerative diseases, but how they relate to microglial activation in health and chronic disease is incompletely understood. Using MRS, we monitored the brain metabolic response to lipopolysaccharides (LPS)-induced microglia activation in vivo in a transgenic mouse model of Alzheimer’s disease (APP/PS1) and healthy controls (wild-type (WT) littermates) over 4 hours. We assessed reactive gliosis by immunohistochemistry and correlated metabolic and histological measures. In WT mice, LPS induced a microglial phenotype consistent with activation, associated with a sustained increase in macromolecule and lipid levels (ML9). This effect was not seen in APP/PS1 mice, where LPS did not lead to a microglial response measured by histology, but induced a late increase in the putative inflammation marker myoinositol (mI) and metabolic changes in total creatine and taurine previously reported to be associated with amyloid load. We argue that ML9 and mI distinguish the response of WT and APP/PS1 mice to immune mediators. Lipid and macromolecule levels may represent a biomarker of activation of healthy microglia, while mI may not be a glial marker.

Cell replacement therapy is a promising treatment for irreversible retinal cell death in diverse diseases such as Stargardt's disease, age-related macular degeneration, and retinitis pigmentosa. The final impact of all retinal dystrophies is the loss of photoreceptors; hence, there is a pressing need for research into replacement. Seminal work has

Porcine diarrhea is a global problem that leads to large economic losses of the porcine industry. There are numerous factors related to piglet diarrhea, and compelling evidence suggests that gut microbiota is vital to host health. However, the key bacterial differences between non-diarrheic and diarrheic piglets are not well understood. In the present study, a total of 85 commercial piglets at three pig farms in Sichuan Province and Chongqing Municipality, China were investigated. To accomplish this, anal swab samples were collected from piglets during the lactation (0–19 days old in this study), weaning (20–21 days old), and post-weaning periods (22–40 days), and fecal microbiota were assessed by 16S rRNA gene V4 region sequencing using the Illumina Miseq platform. We found age-related biomarker microbes in the fecal microbiota of diarrheic piglets. Specifically, the family Enterobacteriaceae was a biomarker of diarrheic piglets during lactation (cluster A, 7–12 days old), whereas the Bacteroidales family S24–7 group was found to be a biomarker of diarrheic pigs during weaning (cluster B, 20–21 days old). Co-correlation network analysis revealed that the genus Escherichia-Shigella was the core component of diarrheic microbiota, while the genus Prevotellacea UCG-003 was the key bacterium in non-diarrheic microbiota of piglets in Southwest China. Furthermore, changes in bacterial metabolic function between diarrheic piglets and non-diarrheic piglets were estimated by PICRUSt analysis, which revealed that the dominant functions of fecal microbes were membrane transport, carbohydrate metabolism, amino acid metabolism, and energy metabolism. Remarkably, genes related to transporters, DNA repair and recombination proteins, purine metabolism, ribosome, secretion systems, transcription factors, and pyrimidine metabolism were decreased in diarrheic piglets, but no significant biomarkers were found between groups using LEfSe analysis.