Siwicki, R. A. | Search bioRxiv

bioRxiv2023

Cell type-focused compound screen in human organoids reveals molecules and pathways controlling cone photoreceptor death

Human organoids that mirror their corresponding organs in cell-type diversity present an opportunity to perform large-scale screens for compounds that protect disease-affected or damage healthy cell types. However, such screens have not yet been performed. Here, we generated 20,000 human retinal organoids with GFP-labeled cone photoreceptors. Since degeneration of cones is a leading cause of blindness, we induced cone death and screened 2,707 compounds with known targets, for those that saved cones or those that further damaged cones. We identified inhibitors of CK1 or MAPK11 that protected cones, HSP90 inhibitors that saved cones in the short term but damaged them in the longer term, and broad HDAC inhibition by many compounds that significantly damaged cones. This work provides a database for cone-damaging compounds and describes compounds that can be starting points to develop neuroprotection for cones in diseases such as macular degeneration.

neuroscience↗

bioRxiv2022

Combined single-sample metabolomics and RNAseq reveals a hepatic pyrimidine metabolic response to acute viral infection

ObjectiveMetabolomics and RNA sequencing (RNAseq) each provide powerful readouts of phenotype, and integration of these data can provide information greater than the sum of their parts. The ability to conduct such analysis on a single sample has many practical advantages, especially when dealing with rare or difficult-to-obtain samples. While methods exist to isolate multiple biomolecular subclasses from the same sample, in-depth analysis of the suitability of these approaches for multi- omics readouts is lacking. MethodsMice were injected with lymphocytic choriomeningitis virus (LCMV) or vehicle (Veh) control and liver tissue was harvested 2.5-days later. RNA was isolated from aliquots of pulverized liver tissue either following metabolite extraction using 80% methanol (MetRNA) or directly from frozen tissue (RNA). RNA sequencing data was evaluated by differential expression analysis via edgeR and dispersion using Ginis mean differences. Differential metabolite abundance was assessed using LIMMA. Pathway enrichment analysis was conducted on metabolomics and RNAseq data using MetaboAnalysts joint-integration tools. ResultsPrior metabolite extraction had no deleterious effects on quality or quantity of isolated RNA. RNA and MetRNA generated from the same sample clustered together by principal component analysis, indicating that inter-individual differences were the largest source of variance. Of the 2,169 genes that were differentially expressed between LCMV and Veh, the vast majority (n=1,848) were shared between extraction method, with the remainder evenly divided between RNA (n=165) and MetRNA (n=156). These differentially expressed genes unique to extraction method were attributed to randomness around the false discovery rate (FDR) = 0.05 cutoff and stochastic changes in variance estimation. Gini analysis further revealed that extraction method had no effect on the dispersion of detected transcripts across the entire dataset. To demonstrate the power of multi-omics integration on interrogated metabolic phenotypes, we next performed integrated pathway enrichment analysis on RNAseq data and metabolomics data. Our analysis revealed pyrimidine metabolism as the most impacted pathway by LCMV infection. Plotting up- and down-regulated genes and metabolites on the Kyoto Encyclopedia of Genes and Genomes (KEGG) pyrimidine pathway exposed a pattern enzymatic degradation of pyrimidine nucleotides to generate the nucleobase uracil. Further, uracil was among the most differentially abundant metabolite in serum of LCMV infected mice, suggesting a novel mechanism of hepatic uracil export in acute infection response. ConclusionsWe demonstrate that prior metabolite extraction does not have a deleterious effect on RNAseq quality, which enables investigators to confidently perform metabolomics and RNAseq on the same sample. Implementation of this approach revealed a novel involvement of the hepatic pyrimidine metabolism during acute viral infection.

molecular biology↗

bioRxiv2022

STORM-seq Reveals Differentiation Trajectories of Primary Human Fallopian Tube Epithelium

Despite significant advances, current single-cell RNA sequencing (scRNA-seq) technologies often struggle with accurately detecting non-coding transcripts, achieving full-length RNA coverage, and/or resolving transcript-level complexity. Many are also difficult to implement or inaccessible without specialized liquid handlers, further limiting their utility. We present Single-cell TOtal RNA-seq Miniaturized (STORM-seq), a random- hexamer primed, ribo-reduced single-cell total RNA sequencing (sc-total-RNA-seq) protocol using standard laboratory equipment. Adapted as a kit, STORM-seq constructs sequence-ready libraries in one working day, producing the highest complexity scRNA- seq libraries to-date, robustly measuring transcript isoforms and clinically relevant gene fusions in single cells. STORM-seq faithfully reconstructs expression profiles of locus- level transposable elements (TEs), and provides high-resolution profiling of transient, low- abundance enhancer RNAs (eRNAs), offering a powerful tool to dissect single-cell gene regulatory networks in unprecedented detail. Applied to human fallopian tube epithelium, the improved transcriptional resolution reveals a putative progenitor-like population and intermediate cell states, shaped by TEs and non-coding RNAs.

molecular biology↗