Direct identification of A-to-I editing sites with nanopore native RNA sequencing.

Inosine is a prevalent RNA modification in animals and is formed when an adenosine is deaminated by the ADAR family of enzymes. Traditionally, inosines are identified indirectly as variants from Illumina RNA-sequencing data because they are interpreted as guanosines by cellular machineries. However, this indirect method performs poorly in protein-coding regions where exons are typically short, in non-model organisms with sparsely annotated single-nucleotide polymorphisms, or in disease contexts where unknown DNA mutations are pervasive. Here, we show that Oxford Nanopore direct RNA sequencing can be used to identify inosine-containing sites in native transcriptomes with high accuracy. We trained convolutional neural network models to distinguish inosine from adenosine and guanosine, and to estimate the modification rate at each editing site. Furthermore, we demonstrated their utility on the transcriptomes of human, mouse and Xenopus. Our approach expands the toolkit for studying adenosine-to-inosine editing and can be further extended to investigate other RNA modifications.

Liquid Crystal Monomer: A Potential PPARγ Antagonist.

Liquid crystal monomers (LCMs) are a large family of artificial ingredients that have been widely used in global liquid crystal display (LCD) industries. As a major constituent in LCDs as well as the end products of e-waste dismantling, LCMs are of growing research interest with regard to their environmental occurrences and biochemical consequences. Many studies have analyzed LCMs in multiple environmental matrices, yet limited research has investigated the toxic effects upon exposure to them. In this study, we combined in silico simulation and in vitro assay validation along with omics integration analysis to achieve a comprehensive toxicity elucidation as well as a systematic mechanism interpretation of LCMs for the first time. Briefly, the high-throughput virtual screen and reporter gene assay revealed that peroxisome proliferator-activated receptor gamma (PPARγ) was significantly antagonized by certain LCMs. Besides, LCMs induced global metabolome and transcriptome dysregulation in HK2 cells. Notably, fatty acid ß-oxidation was conspicuously dysregulated, which might be mediated through multiple pathways (IL-17, TNF, and NF-kB), whereas the activation of AMPK and ligand-dependent PPARγ antagonism may play particularly important parts. This study illustrated LCMs as a potential PPARγ antagonist and explored their toxicological mode of action on the trans-omics level, which provided an insightful overview in future chemical risk assessment.

Multiplexed spatial mapping of chromatin features, transcriptome, and proteins in tissues.

The phenotypic and functional states of a cell are modulated by a complex interactive molecular hierarchy of multiple omics layers, involving the genome, epigenome, transcriptome, proteome, and metabolome. Spatial omics approaches have enabled the capture of information from different molecular layers directly in the tissue context. However, current technologies are limited to map one to two modalities at the same time, providing an incomplete representation of cellular identity. Such data is inadequate to fully understand complex biological systems and their underlying regulatory mechanisms. Here we present spatial-Mux-seq, a multi-modal spatial technology that allows simultaneous profiling of five different modalities, including genome-wide profiles of two histone modifications and open chromatin, whole transcriptome, and a panel of proteins at tissue scale and cellular level in a spatially resolved manner. We applied this technology to generate multi-modal tissue maps in mouse embryos and mouse brains, which discriminated more cell types and states than unimodal data. We investigated the spatiotemporal relationship between histone modifications, chromatin accessibility, gene and protein expression in neuron differentiation revealing the relationship between tissue organization, function, and gene regulatory networks. We were able to identify a radial glia spatial niche and revealed spatially changing gradient of epigenetic signals in this region. Moreover, we revealed previously unappreciated involvement of repressive histone marks in the mouse hippocampus. Collectively, the spatial multi-omics approach heralds a new era for characterizing tissue and cellular heterogeneity that single modality studies alone could not reveal.

Kidney organoid models reveal cilium-autophagy metabolic axis as a therapeutic target for PKD both in vitro and in vivo.

Human pluripotent stem cell-derived kidney organoids offer unprecedented opportunities for studying polycystic kidney disease (PKD), which still has no effective cure. Here, we developed both in vitro and in vivo organoid models of PKD that manifested tubular injury and aberrant upregulation of renin-angiotensin aldosterone system. Single-cell analysis revealed that a myriad of metabolic changes occurred during cystogenesis, including defective autophagy. Experimental activation of autophagy via ATG5 overexpression or primary cilia ablation significantly inhibited cystogenesis in PKD kidney organoids. Employing the organoid xenograft model of PKD, which spontaneously developed tubular cysts, we demonstrate that minoxidil, a potent autophagy activator and an FDA-approved drug, effectively attenuated cyst formation in vivo. This in vivo organoid model of PKD will enhance our capability to discover novel disease mechanisms and validate candidate drugs for clinical translation.

Studying Kidney Diseases Using Organoid Models.

The prevalence of chronic kidney disease (CKD) is rapidly increasing over the last few decades, owing to the global increase in diabetes, and cardiovascular diseases. Dialysis greatly compromises the life quality of patients, while demand for transplantable kidney cannot be met, underscoring the need to develop novel therapeutic approaches to stop or reverse CKD progression. Our understanding of kidney disease is primarily derived from studies using animal models and cell culture. While cross-species differences made it challenging to fully translate findings from animal models into clinical practice, primary patient cells quickly lose the original phenotypes during in vitro culture. Over the last decade, remarkable achievements have been made for generating 3-dimensional (3D) miniature organs (organoids) by exposing stem cells to culture conditions that mimic the signaling cues required for the development of a particular organ or tissue. 3D kidney organoids have been successfully generated from different types of source cells, including human pluripotent stem cells (hPSCs), adult/fetal renal tissues, and kidney cancer biopsy. Alongside gene editing tools, hPSC-derived kidney organoids are being harnessed to model genetic kidney diseases. In comparison, adult kidney-derived tubuloids and kidney cancer-derived tumoroids are still in their infancy. Herein, we first summarize the currently available kidney organoid models. Next, we discuss recent advances in kidney disease modelling using organoid models. Finally, we consider the major challenges that have hindered the application of kidney organoids in disease modelling and drug evaluation and propose prospective solutions.