Stress-free cell aggregation by using the CEPT cocktail enhances embryoid body and organoid fitness.

Embryoid bodies (EBs) and self-organizing organoids derived from human pluripotent stem cells (hPSCs) recapitulate tissue development in a dish and hold great promise for disease modeling and drug development. However, current protocols are hampered by cellular stress and apoptosis during cell aggregation, resulting in variability and impaired cell differentiation. Here, we demonstrate that EBs and various organoid models (e.g., brain, gut, kidney) can be optimized by using the small molecule cocktail named CEPT (chroman 1, emricasan, polyamines, trans-ISRIB), a polypharmacological approach that ensures cytoprotection and cell survival. Application of CEPT for just 24 h during cell aggregation has long-lasting consequences affecting morphogenesis, gene expression, cellular differentiation, and organoid function. Various qualification methods confirmed that CEPT treatment enhanced experimental reproducibility and consistently improved EB and organoid fitness as compared to the widely used ROCK inhibitor Y-27632. Collectively, we discovered that stress-free cell aggregation and superior cell survival in the presence of CEPT are critical quality control determinants that establish a robust foundation for bioengineering complex tissue and organ models.

SEQUIN is an R/Shiny framework for rapid and reproducible analysis of RNA-seq data.

SEQUIN is a web-based application (app) that allows fast and intuitive analysis of RNA sequencing data derived for model organisms, tissues, and single cells. Integrated app functions enable uploading datasets, quality control, gene set enrichment, data visualization, and differential gene expression analysis. We also developed the iPSC Profiler, a practical gene module scoring tool that helps measure and compare pluripotent and differentiated cell types. Benchmarking to other commercial and non-commercial products underscored several advantages of SEQUIN. Freely available to the public, SEQUIN empowers scientists using interdisciplinary methods to investigate and present transcriptome data firsthand with state-of-the-art statistical methods. Hence, SEQUIN helps democratize and increase the throughput of interrogating biological questions using next-generation sequencing data with single-cell resolution.

A multicenter study benchmarking single-cell RNA sequencing technologies using reference samples.

Comparing diverse single-cell RNA sequencing (scRNA-seq) datasets generated by different technologies and in different laboratories remains a major challenge. Here we address the need for guidance in choosing algorithms leading to accurate biological interpretations of varied data types acquired with different platforms. Using two well-characterized cellular reference samples (breast cancer cells and B cells), captured either separately or in mixtures, we compared different scRNA-seq platforms and several preprocessing, normalization and batch-effect correction methods at multiple centers. Although preprocessing and normalization contributed to variability in gene detection and cell classification, batch-effect correction was by far the most important factor in correctly classifying the cells. Moreover, scRNA-seq dataset characteristics (for example, sample and cellular heterogeneity and platform used) were critical in determining the optimal bioinformatic method. However, reproducibility across centers and platforms was high when appropriate bioinformatic methods were applied. Our findings offer practical guidance for optimizing platform and software selection when designing an scRNA-seq study.

The essential chloroplast ribosomal protein uL15c interacts with the chloroplast RNA helicase ISE2 and affects intercellular trafficking through plasmodesmata.

Chloroplasts retain part of their ancestral genomes and the machinery for expression of those genomes. The nucleus-encoded chloroplast RNA helicase INCREASED SIZE EXCLUSION LIMIT2 (ISE2) is required for chloroplast ribosomal RNA processing and chloro-ribosome assembly. To further elucidate ISE2's role in chloroplast translation, two independent approaches were used to identify its potential protein partners. Both a yeast two-hybrid screen and a pull-down assay identified plastid ribosomal protein L15, uL15c (formerly RPL15), as interacting with ISE2. The interaction was confirmed in vivo by co-immunoprecipitation. Interestingly, we found that rpl15 null mutants do not complete embryogenesis, indicating that RPL15 is an essential gene for autotrophic growth of Arabidopsis thaliana. Arabidopsis and Nicotiana benthamiana plants with reduced expression of RPL15 developed chlorotic leaves, had reduced photosynthetic capacity and exhibited defective chloroplast development. Processing of chloroplast ribosomal RNAs and assembly of ribosomal subunits were disrupted by reduced expression of RPL15. Chloroplast translation was also decreased, reducing accumulation of chloroplast-encoded proteins, in such plants compared to wild-type plants. Notably, knockdown of RPL15 expression increased intercellular trafficking, a phenotype also observed in plants with reduced ISE2 expression. This finding provides further evidence for chloroplast function in modulating intercellular trafficking via plasmodesmata.

The chloroplast RNA helicase ISE2 is required for multiple chloroplast RNA processing steps in Arabidopsis thaliana.

INCREASED SIZE EXCLUSION LIMIT2 (ISE2) is a chloroplast-localized RNA helicase that is indispensable for proper plant development. Chloroplasts in leaves with reduced ISE2 expression have previously been shown to exhibit reduced thylakoid contents and increased stromal volume, indicative of defective development. It has recently been reported that ISE2 is required for the splicing of group II introns from chloroplast transcripts. The current study extends these findings, and presents evidence for ISE2's role in multiple aspects of chloroplast RNA processing beyond group II intron splicing. Loss of ISE2 from Arabidopsis thaliana leaves resulted in defects in C-to-U RNA editing, altered accumulation of chloroplast transcripts and chloroplast-encoded proteins, and defective processing of chloroplast ribosomal RNAs. Potential ISE2 substrates were identified by RNA immunoprecipitation followed by next-generation sequencing (RIP-seq), and the diversity of RNA species identified supports ISE2's involvement in multiple aspects of chloroplast RNA metabolism. Comprehensive phylogenetic analyses revealed that ISE2 is a non-canonical Ski2-like RNA helicase that represents a separate sub-clade unique to green photosynthetic organisms, consistent with its function as an essential protein. Thus ISE2's evolutionary conservation may be explained by its numerous roles in regulating chloroplast gene expression.

The Circadian Clock Modulates Global Daily Cycles of mRNA Ribosome Loading.

Circadian control of gene expression is well characterized at the transcriptional level, but little is known about diel or circadian control of translation. Genome-wide translation state profiling of mRNAs in Arabidopsis thaliana seedlings grown in long day was performed to estimate ribosome loading per mRNA. The experiments revealed extensive translational regulation of key biological processes. Notably, translation of mRNAs for ribosomal proteins and mitochondrial respiration peaked at night. Central clock mRNAs are among those subject to fluctuations in ribosome loading. There was no consistent phase relationship between peak translation states and peak transcript levels. The overlay of distinct transcriptional and translational cycles can be expected to alter the waveform of the protein synthesis rate. Plants that constitutively overexpress the clock gene CCA1 showed phase shifts in peak translation, with a 6-h delay from midnight to dawn or from noon to evening being particularly common. Moreover, cycles of ribosome loading that were detected under continuous light in the wild type collapsed in the CCA1 overexpressor. Finally, at the transcript level, the CCA1-ox strain adopted a global pattern of transcript abundance that was broadly correlated with the light-dark environment. Altogether, these data demonstrate that gene-specific diel cycles of ribosome loading are controlled in part by the circadian clock.

The insulator protein Suppressor of Hairy wing is required for proper ring canal development during oogenesis in Drosophila.

Chromatin insulators orchestrate gene transcription during embryo development and cell differentiation by stabilizing interactions between distant genomic sites. Mutations in genes encoding insulator proteins are generally lethal, making in vivo functional analyses of insulator proteins difficult. In Drosophila, however, mutations in the gene encoding the Suppressor of Hairy wing insulator protein [Su(Hw)] are viable and female sterile, providing an opportunity to study insulator function during oocyte development. Whereas previous reports suggest that the function of Su(Hw) in oogenesis is independent of its insulator activity, many aspects of the role of Su(Hw) in Drosophila oogenesis remain unexplored. Here we show that mutations in su(Hw) result in smaller ring canal lumens and smaller outer ring diameters, which likely obstruct molecular and vesicle passage from nurse cells to the oocyte. Fluorescence microscopy reveals that lack of Su(Hw) leads to excess accumulation of Kelch (Kel) and Filament-actin (F-actin) proteins in the ring canal structures of developing egg chambers. Furthermore, we found that misexpression of the Src oncogene at 64B (Src64B) may cause ring canal development defects as microarray analysis and real-time RT-PCR revealed there is a three fold decrease in Src64B expression in su(Hw) mutant ovaries. Restoration of Src64B expression in su(Hw) mutant female germ cells rescued the ring phenotype but did not restore fertility. We conclude that loss of su(Hw) affects expression of many oogenesis related genes and down-regulates Src64B, resulting in ring canal defects potentially contributing to obstruction of molecular flow and an eventual failure of egg chamber organization.

Molecular and metabolic profiles suggest that increased lipid catabolism in adipose tissue contributes to leanness in domestic chickens.

Domestic broiler chickens rapidly accumulate fat and are naturally hyperglycemic and insulin resistant, making them an attractive model for studies of human obesity. We previously demonstrated that short-term (5 h) fasting rapidly upregulates pathways of fatty acid oxidation in broiler chickens and proposed that activation of these pathways may promote leanness. The objective of the current study was to characterize adipose tissue from relatively lean and fatty lines of chickens and determine if heritable leanness in chickens is associated with activation of some of the same pathways induced by fasting. We compared adipose gene expression and metabolite profiles in white adipose tissue of lean Leghorn and Fayoumi breeds to those of fattier commercial broiler chickens. Both lipolysis and expression of genes involved in fatty acid oxidation were upregulated in lean chickens compared with broilers. Although there were strong similarities between the lean lines compared with broilers, distinct expression signatures were also found between Fayoumi and Leghorn, including differences in adipogenic genes. Similarities between genetically lean and fasted chickens suggest that fatty acid oxidation in white adipose tissue is adaptively coupled to lipolysis and plays a role in heritable differences in fatness. Unique signatures of leanness in Fayoumi and Leghorn lines highlight distinct pathways that may provide insight into the basis for leanness in humans. Collectively, our results provide a number of future directions through which to fully exploit chickens as unique models for the study of human obesity and adipose metabolism.

MetabR: an R script for linear model analysis of quantitative metabolomic data.

BACKGROUND: Metabolomics is an emerging high-throughput approach to systems biology, but data analysis tools are lacking compared to other systems level disciplines such as transcriptomics and proteomics. Metabolomic data analysis requires a normalization step to remove systematic effects of confounding variables on metabolite measurements. Current tools may not correctly normalize every metabolite when the relationships between each metabolite quantity and fixed-effect confounding variables are different, or for the effects of random-effect confounding variables. Linear mixed models, an established methodology in the microarray literature, offer a standardized and flexible approach for removing the effects of fixed- and random-effect confounding variables from metabolomic data. FINDINGS: Here we present a simple menu-driven program, "MetabR", designed to aid researchers with no programming background in statistical analysis of metabolomic data. Written in the open-source statistical programming language R, MetabR implements linear mixed models to normalize metabolomic data and analysis of variance (ANOVA) to test treatment differences. MetabR exports normalized data, checks statistical model assumptions, identifies differentially abundant metabolites, and produces output files to help with data interpretation. Example data are provided to illustrate normalization for common confounding variables and to demonstrate the utility of the MetabR program. CONCLUSIONS: We developed MetabR as a simple and user-friendly tool for implementing linear mixed model-based normalization and statistical analysis of targeted metabolomic data, which helps to fill a lack of available data analysis tools in this field. The program, user guide, example data, and any future news or updates related to the program may be found at http://metabr.r-forge.r-project.org/.

Transcriptomic and metabolomic profiling of chicken adipose tissue in response to insulin neutralization and fasting.

BACKGROUND: Domestic broiler chickens rapidly accumulate adipose tissue due to intensive genetic selection for rapid growth and are naturally hyperglycemic and insulin resistant, making them an attractive addition to the suite of rodent models used for studies of obesity and type 2 diabetes in humans. Furthermore, chicken adipose tissue is considered as poorly sensitive to insulin and lipolysis is under glucagon control. Excessive fat accumulation is also an economic and environmental concern for the broiler industry due to the loss of feed efficiency and excessive nitrogen wasting, as well as a negative trait for consumers who are increasingly conscious of dietary fat intake. Understanding the control of avian adipose tissue metabolism would both enhance the utility of chicken as a model organism for human obesity and insulin resistance and highlight new approaches to reduce fat deposition in commercial chickens. RESULTS: We combined transcriptomics and metabolomics to characterize the response of chicken adipose tissue to two energy manipulations, fasting and insulin deprivation in the fed state. Sixteen to 17 day-old commercial broiler chickens (ISA915) were fed ad libitum, fasted for five hours, or fed but deprived of insulin by injections of anti-insulin serum. Pair-wise contrasts of expression data identified a total of 2016 genes that were differentially expressed after correction for multiple testing, with the vast majority of differences due to fasting (1780 genes). Gene Ontology and KEGG pathway analyses indicated that a short term fast impacted expression of genes in a broad selection of pathways related to metabolism, signaling and adipogenesis. The effects of insulin neutralization largely overlapped with the response to fasting, but with more modest effects on adipose tissue metabolism. Tissue metabolomics indicated unique effects of insulin on amino acid metabolism. CONCLUSIONS: Collectively, these data provide a foundation for further study into the molecular basis for adipose expansion in commercial poultry and identify potential pathways through which fat accretion may be attenuated in the future through genetic selection or management practices. They also highlight chicken as a useful model organism in which to study the dynamic relationship between food intake, metabolism, and adipose tissue biology.