Exosomal MicroRNA-325 Enhances Trophoblast Migration and Invasion Through Downregulation of Lethal-7b and Upregulation of Forkhead Box Protein O1 Expression in Preeclampsia

We aimed to explore the mechanism by how microRNA (miRNA)-325 derived from marrow mesenchymal stem cell exosomes (MSC-exos) affects the trophoblast progression in preeclampsia (PE). RT-qPCR detected the level of miRNA let-7b and FOXO1 in the placenta tissue of PE patients. Functional experiment was performed to analyze the effect of FOXO1 inhibitor and let-7b mimics on cell migration, invasion and apoptosis through Transwell assay and TUNEL staining. The trophoblast cell was co-cultured with overexpressed-miR-325 MSC-exos to measure gene expression and cell progression. let-7b was highly and FOXO1 was lowly expressed in PE placenta tissue. let-7b directly targeted and inhibited FOXO1 expression. Importantly, as miR-325 was internalized by trophoblast cells through MSC-exos, MSC-exos overexpressing miR-325 inhibited let-7b expression in trophoblasts, up-regulated FOXO1 and activated AKT signaling pathway. Further, MSC-exos treatment promoted invasion and migration of trophoblast cell and inhibited apoptosis. In conclusion, miR-325 derived from MSC-exos promotes the invasion and migration of trophoblast cells in PE through inhibition of let7b and upregulation of FOXO1.

Evaluation of sample preservation and storage methods for metaproteomics analysis of intestinal microbiomes

A critical step in studies of the intestinal microbiome using meta-omics approaches is the preservation of samples before analysis. Preservation is essential for approaches that measure gene expression, such as metaproteomics, which is used to identify and quantify proteins in microbiomes. Intestinal microbiome samples are typically stored by flash freezing and storage at -80 oC, but some experimental set-ups do not allow for immediate freezing of samples. In this study, we evaluated methods to preserve fecal microbiome samples for metaproteomics analyses when flash freezing is not possible. We collected fecal samples from C57BL/6 mice and stored them for 1 and 4 weeks using the following methods: flash-freezing in liquid nitrogen, immersion in RNAlater™, immersion in 95% ethanol, immersion in a RNAlater-like buffer, and combinations of these methods. After storage we extracted protein and prepared peptides for LC-MS/MS analysis to identify and quantify peptides and proteins. All samples produced highly similar metaproteomes, except for ethanol-preserved samples that were distinct from all other samples in terms of protein identifications and protein abundance profiles. Flash-freezing and RNAlater™ (or RNAlater-like treatments) produced metaproteomes that differed only slightly, with less than 0.7% of identified proteins differing in abundance. In contrast, ethanol preservation resulted in an average of 9.5% of the identified proteins differing in abundance between ethanol and the other treatments. Our results suggest that preservation at room temperature in RNAlater™,or an RNAlater-like solution, performs as well as freezing for the preservation of intestinal microbiome samples before metaproteomics analyses.

CRISPR Interference to Inducibly Repress Gene Expression in Chlamydia trachomatis

The ability to inducibly repress gene expression is critical to the study of organisms, like Chlamydia, with reduced genomes wherein the majority of genes are likely to be essential. We recently described the feasibility of a CRISPR interference system to inducibly repress gene expression in Chlamydia trachomatis. However, the initial system suffered from some drawbacks, primarily leaky expression of the anhydrotetracycline (aTc) inducible dCas9 ortholog and plasmid instability, that prevented population-wide studies (e.g. transcript analyses) of the effects of knockdown. Here, we describe various modifications to the original system that have allowed us to measure gene expression changes within a transformed population of C. trachomatis serovar L2. These modifications include (i) a change in the vector backbone, (ii) the introduction of a weaker ribosome binding site driving dCas9 translation, and (iii) the addition of a degradation tag to the dCas9 itself. With these changes, we demonstrate the ability to inducibly repress a target gene sequence as measured by the absence of protein by immunofluorescence analysis and by decreased transcript levels. Importantly, the expression of dCas9 alone (i.e. without a gRNA) had minimal impact on chlamydial growth or development. We also describe complementation of the knockdown effect by introducing a transcriptional fusion of the target gene 3’ to the dCas9. Finally, we demonstrate the functionality of a second CRISPRi system based on a dCas12 system that expands the number of potential chromosomal targets. These tools should provide the ability to study essential gene function in Chlamydia.

Enabling high-throughput single-animal gene-expression studies with molecular and micro-scale technologies

How can microfluidics address the significant limitations to the current tools that measure gene expression in single-animal studies?

NASC-seq monitors RNA synthesis in single cells

Sequencing of newly synthesized RNA can monitor transcriptional dynamics with great sensitivity and high temporal resolution, but is currently restricted to populations of cells. Here, we developed newly synthesized alkylation-dependent single-cell RNA sequencing (NASC-seq), to monitor both newly synthesized and pre-existing RNA in single cells. We validated the method on pre-alkylated exogenous spike-in RNA, and by demonstrating that more newly synthesized RNA was detected for genes with known high mRNA turnover. Importantly, NASC-seq reveals rapidly up- and down-regulated genes during the T-cell activation, and RNA sequenced for induced genes were essentially only newly synthesized. Moreover, the newly synthesized and pre-existing transcriptomes after T-cell activation were distinct confirming that we indeed could simultaneously measure gene expression corresponding to two time points in single cells. Altogether, NASC-seq is a powerful tool to investigate transcriptional dynamics and it will enable the precise monitoring of RNA synthesis at flexible time periods during homeostasis, perturbation responses and cellular differentiation.

Detection and benchmarking of somatic mutations in cancer genomes using RNA-seq data

ABSTRACTTo detect functional somatic mutations in tumor samples, whole-exome sequencing (WES) is often used for its reliability and relative low cost. RNA-seq, while generally used to measure gene expression, can potentially also be used for identification of somatic mutations. However there has been little systematic evaluation of the utility of RNA-seq for identifying somatic mutations. Here, we develop and evaluate a pipeline for processing RNA-seq data from glioblastoma multiforme (GBM) tumors in order to identify somatic mutations. The pipeline entails the use of the STAR aligner 2-pass procedure jointly with MuTect2 from GATK to detect somatic variants. Variants identified from RNA-seq data were evaluated by comparison against the COSMIC and dbSNP databases, and also compared to somatic variants identified by exome sequencing. We also estimated the putative functional impact of coding variants in the most frequently mutated genes in GBM. Interestingly, variants identified by RNA-seq alone showed better representation of GBM-related mutations cataloged by COSMIC. RNA-seq-only data substantially outperformed the ability of WES to reveal potentially new somatic mutations in known GBM-related pathways, and allowed us to build a high-quality set of somatic mutations common to exome and RNA-seq calls. Using RNA-seq data in parallel with WES data to detect somatic mutations in cancer genomes can thus broaden the scope of discoveries and lend additional support to somatic variants identified by exome sequencing alone.

CellView: Interactive exploration of high dimensional single cell RNA-seq data

Advances in high-throughput single cell transcriptomics technologies have revolutionized the study of complex tissues. It is now possible to measure gene expression across thousands of individual cells to define cell types and states. While powerful computational and statistical frameworks are emerging to analyze these complex datasets, a gap exists between this data and a biologist’s insight. The CellView web application fills this gap by providing easy and intuitive exploration of single cell transcriptome data.