Identification of the stress granule transcriptome via RNA-editing in single cells and in vivo

Stress granules are phase-separated assemblies formed around RNAs. So far, the techniques available to identify these RNAs are not suitable for single cells and small tissues displaying cell heterogeneity. Here, we used TRIBE (target of RNA-binding proteins identified by editing) to profile stress granule RNAs. We used an RNA-binding protein (FMR1) fused to the catalytic domain of an RNA-editing enzyme (ADAR), which coalesces into stress granules upon oxidative stress. RNAs colocalized with this fusion are edited, producing mutations that are detectable by VASA sequencing. Using single-molecule FISH, we validated that this purification-free method can reliably identify stress granule RNAs in bulk and single S2 cells and in Drosophila neurons. Similar to mammalian cells, we find that stress granule mRNAs encode ATP binding, cell cycle, and transcription factors. This method opens the possibility to identify stress granule RNAs and other RNA-based assemblies in other single cells and tissues

The development of single-cell microfluidic technologies for the analysis of microRNA expression

New technologies for single-cell RNA expression profiling have transformed our understanding of cell biology. Despite several variations, the vast majority of available methods are applicable only to messenger RNA expression measurements, leaving microRNAs and other classes of small RNAs largely unexplored. In this dissertation I describe the creation and application of technology that allows for the efficient and precise analysis of microRNA expression in large numbers of single cells. First, the foundational components necessary for microfluidic integration of single-cell RT-qPCR analysis were developed. The resulting device executes and parallelizes all steps of cell capture, cell lysis, reverse transcription, and quantitative PCR on up to 300 cells per run. In comparison to standard benchtop assays, nanolitre-volume processing was found to increase measurement performance on samples with limited template. The core functionality established in this part of the work provides a foundation for further microfluidic single-cell assays. The capabilities of this platform were next expanded to enable highly multiplexed RT-qPCR analysis. By incorporating sophisticated microfluidic fabrication techniques with an extended workflow that included a pre-amplification step, the number of assays per cell was increased from one or two to up to forty, while maintaining the same benefits to measurement performance that were previously observed. Finally, small-volume analysis and carefully optimized molecular biology were combined to develop a method to generate high-quality single-cell microRNA sequencing libraries. This method was then applied to provide a comprehensive look at microRNA expression dynamics across the human hematopoietic cell hierarchy. The results indicated that the population structure derived from miRNA expression profiles supported a model of continuous, linear hematopoietic stem cell differentiation, in contrast to the prevailing model of stepwise, branched lineage commitment. An expanded set of miRNA markers that are highly expressed in HSCs, decrease gradually during differentiation, and are absent in mature cells were also identified. Finally, an analysis of the relative expression of microRNA isoforms was performed, showing that they are a dynamic feature that varies between different microRNAs and cell types. The capabilities conferred by this suite of microfluidic devices will enable the continued, routine analysis of microRNA expression in single cells.Science, Faculty ofGraduat

Single-cell Ribo-seq reveals cell cycle-dependent translational pausing

Single-cell sequencing methods have enabled in-depth analysis of the diversity of cell types and cell states in a wide range of organisms. These tools focus predominantly on sequencing the genomes1, epigenomes2 and transcriptomes3 of single cells. However, despite recent progress in detecting proteins by mass spectrometry with single-cell resolution4, it remains a major challenge to measure translation in individual cells. Here, building on existing protocols5–7, we have substantially increased the sensitivity of these assays to enable ribosome profiling in single cells. Integrated with a machine learning approach, this technology achieves single-codon resolution. We validate this method by demonstrating that limitation for a particular amino acid causes ribosome pausing at a subset of the codons encoding the amino acid. Of note, this pausing is only observed in a sub-population of cells correlating to its cell cycle state. We further expand on this phenomenon in non-limiting conditions and detect pronounced GAA pausing during mitosis. Finally, we demonstrate the applicability of this technique to rare primary enteroendocrine cells. This technology provides a first step towards determining the contribution of the translational process to the remarkable diversity between seemingly identical cells

Methods for Multiplex Template Sampling in Digital PCR Assays

<div><p>The efficient use of digital PCR (dPCR) for precision copy number analysis requires high concentrations of target molecules that may be difficult or impossible to obtain from clinical samples. To solve this problem we present a strategy, called Multiplex Template Sampling (MTS), that effectively increases template concentrations by detecting multiple regions of fragmented target molecules. Three alternative assay approaches are presented for implementing MTS analysis of chromosome 21, providing a 10-fold concentration enhancement while preserving assay precision.</p></div

Highly multiplexed single-cell quantitative PCR

<div><p>We present a microfluidic device for rapid gene expression profiling in single cells using multiplexed quantitative polymerase chain reaction (qPCR). This device integrates all processing steps, including cell isolation and lysis, complementary DNA synthesis, pre-amplification, sample splitting, and measurement in twenty separate qPCR reactions. Each of these steps is performed in parallel on up to 200 single cells per run. Experiments performed on dilutions of purified RNA establish assay linearity over a dynamic range of at least 10⁴, a qPCR precision of 15%, and detection sensitivity down to a single cDNA molecule. We demonstrate the application of our device for rapid profiling of microRNA expression in single cells. Measurements performed on a panel of twenty miRNAs in two types of cells revealed clear cell-to-cell heterogeneity, with evidence of spontaneous differentiation manifested as distinct expression signatures. Highly multiplexed microfluidic RT-qPCR fills a gap in current capabilities for single-cell analysis, providing a rapid and cost-effective approach for profiling panels of marker genes, thereby complementing single-cell genomics methods that are best suited for global analysis and discovery. We expect this approach to enable new studies requiring fast, cost-effective, and precise measurements across hundreds of single cells.</p></div

Multiplex Template Sampling (MTS) strategies.

<p>In the first, “short multiplex”, the sampling rate is raised by ten primer pairs in a multiplexed PCR with a common fluorescent probe for detection. The second method, “long multiplex”, is similar, but loci-specific primers are longer and we append a universal sequence to them. A third method, “repetitive simplex”, uses a single PCR assay designed to target chromosome-specific repetitive sequences.</p

Effect of volume on dPCR reactions.

<p>Performance of same PCR mixes as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0098341#pone-0098341-g001" target="_blank">Figure 1B</a> in 100 pL volumes. Two multiplexing approaches are compared: short primers and long primers plus a pair of universal primers. Multiplexing level in PCR reactions (horizontal axis) increases from 1× to 10×. Asterisks denote data points where difference between the two approaches was not significant (p = 0.05).</p

Single cell mRNA expression.

<p>(A) Heatmap of expression values of six mRNA on 175 single K562 cells and 4 no cell controls (NCC). Each column represents a cell, and each row represents an assay. Replicate measurements are grouped according to assay. As expected, murine <i>Gapdh</i> is not detected, only spuriously generating signal in 4/525 detection chambers. No-cell controls are clearly distinguishable from those from single cells, with an average difference in magnitude greater than 100×. The variability between replicate measurements for each gene is much smaller than the variance in expression seen between different cells. (B) Distribution of the copy number of each gene measured in each single cell, along with the mean expression values obtained from previously published single-cell qPCR measurements [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0191601#pone.0191601.ref010" target="_blank">10</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0191601#pone.0191601.ref012" target="_blank">12</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0191601#pone.0191601.ref014" target="_blank">14</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0191601#pone.0191601.ref030" target="_blank">30</a>]. Error bars represent the mean ± standard deviation.</p

Assessment of chromosome ratio using “short” and “long” multiplexing strategies.

<p>(<b>A</b>) Mean ratio (n = 5) between chromosomes 21 and 6 in normal human adult male DNA as measured by dPCR using ten different primer pairs each specific to one locus on chromosome 21. (<b>B</b>) Mean ratio (n = 5) between chromosome 21 and chromosome 6 as measured by dPCR using multiplexed reactions with one to ten primer pairs in the PCR mix. Reaction volumes are 2 nL, multiplexing level (horizontal axis) increases from 1× to 10×. Two approaches compared: with short primers and long primers plus a pair of universal primers. Upper and lower boundaries of 95% confidence intervals <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0098341#pone.0098341-Dube1" target="_blank">[22]</a> are shown with dashed lines.</p

Multiplex RT-qPCR device schematic and operation.

<p>(A) Two cell-processing units. Components include (i) a reagent injection bus, (ii) a 0.3-nL cell capture chamber, (iii) a 10-nL reverse transcription (RT) chamber, (iv) a 50-nL pre-amplification chamber, (v) twenty 0.15-nL sample-splitting chambers, (vi) twenty shared assay-delivery chambers, and (vii) twenty 6.4-nL detection chambers. The “flow” layer is made up of features of six different heights. Control valves and assay-delivery channels are on the same 25 μm high SU8 “control” layer. Assay delivery from the control layer to the flow layer occurs through laser-ablated interlayer connections. Scale bar 0.5 mm. (B) Optical micrograph of a single K562 cell (indicated by a black arrow) caught in a cell trap. Scale bar 50 μm. (C) Optical micrograph of a subsection of the detection array. Control valves are coloured red. Scale bar 0.5 mm. (D-G) Schematic illustration of device operation. (D) Single cells are first loaded into the device, then washed, isolated, and lysed <i>in situ</i>. (E) Reverse transcription brew is then injected into the RT chamber, mixed with the lysate, and then the device is thermocycled. (F) Similarly, multiplexed pre-amplification mix is injected into the device, mixed with cDNA, and then the device is again thermocycled. (G) Finally, the pre-amplification product is split between detection chambers for qPCR.</p