Visualization and analysis of mRNA molecules using fluorescence in situ hybridization in Saccharomyces cerevisiae

Strain-dependent differences in coordination of yeast signalling networks

The yeast mitogen-activated protein kinase pathways serve as a model system for understanding how network interactions affect the way in which cells coordinate the response to multiple signals. We have quantitatively compared two yeast strain backgrounds YPH499 and ∑1278b (both of which have previously been used to study these pathways) and found several important differences in how they coordinate the interaction between the high osmolarity glycerol (HOG) and mating pathways. In the ∑1278b background, in response to simultaneous stimulus, mating pathway activation is dampened and delayed in a dose-dependent manner. In the YPH499 background, only dampening is dose-dependent. Furthermore, leakage from the HOG pathway into the mating pathway (crosstalk) occurs during osmostress alone in the ∑1278b background only. The mitogen-activated protein kinase Hog1p suppresses crosstalk late in an induction time course in both strains but does not affect the early crosstalk seen in the ∑1278b background. Finally, the kinase Rck2p plays a greater role suppressing late crosstalk in the ∑1278b background than in the YPH499 background. Our results demonstrate that comparisons between laboratory yeast strains provide an important resource for understanding how signalling network interactions are tuned by genetic variation without significant alteration to network structure.

European Society of Toxicologic Pathology (Pathology 2.0 Molecular Pathology Special Interest Group): Review of In Situ Hybridization Techniques for Drug Research and Development

In situ hybridization (ISH) is used for the localization of specific nucleic acid sequences in cells or tissues by complementary binding of a nucleotide probe to a specific target nucleic acid sequence. In the last years, the specificity and sensitivity of ISH assays were improved by innovative techniques like synthetic nucleic acids and tandem oligonucleotide probes combined with signal amplification methods like branched DNA, hybridization chain reaction and tyramide signal amplification. These improvements increased the application spectrum for ISH on formalin-fixed paraffin-embedded tissues. ISH is a powerful tool to investigate DNA, mRNA transcripts, regulatory noncoding RNA, and therapeutic oligonucleotides. ISH can be used to obtain spatial information of a cell type, subcellular localization, or expression levels of targets. Since immunohistochemistry and ISH share similar workflows, their combination can address simultaneous transcriptomics and proteomics questions. The goal of this review paper is to revisit the current state of the scientific approaches in ISH and its application in drug research and development.

An Optogenetic Platform for Real-Time, Single-Cell Interrogation of Stochastic Transcriptional Regulation

Transcription is a highly regulated and inherently stochastic process. The complexity of signal transduction and gene regulation makes it challenging to analyze how the dynamic activity of transcriptional regulators affects stochastic transcription. By combining a fast-acting, photo-regulatable transcription factor with nascent RNA quantification in live cells and an experimental setup for precise spatiotemporal delivery of light inputs, we constructed a platform for the real-time, single-cell interrogation of transcription in Saccharomyces cerevisiae. We show that transcriptional activation and deactivation are fast and memoryless. By analyzing the temporal activity of individual cells, we found that transcription occurs in bursts, whose duration and timing are modulated by transcription factor activity. Using our platform, we regulated transcription via light-driven feedback loops at the single-cell level. Feedback markedly reduced cell-to-cell variability and led to qualitative differences in cellular transcriptional dynamics. Our platform establishes a flexible method for studying transcriptional dynamics in single cells.

Pulsatile inputs achieve tunable attenuation of gene expression variability and graded multi-gene regulation

Many natural transcription factors are regulated in a pulsatile fashion, but it remains unknown whether synthetic gene expression systems can benefit from such dynamic regulation. Here we find, using a fast-acting, optogenetic transcription factor in Saccharomyces cerevisiae, that dynamic pulsatile signals reduce cell-to-cell variability in gene expression. We then show that by encoding such signals into a single input, expression mean and variability can be independently tuned. Further, we construct a light-responsive promoter library and demonstrate how pulsatile signaling also enables graded multi-gene regulation at fixed expression ratios, despite differences in promoter dose-response characteristics. Pulsatile regulation can thus lead to beneficial functional behaviors in synthetic biological systems, which previously required laborious optimization of genetic parts or the construction of synthetic gene networks.

Systematic identification of factors mediating accelerated mRNA degradation in response to changes in environmental nitrogen

Cellular responses to changing environments frequently involve rapid reprogramming of the transcriptome. Regulated changes in mRNA degradation rates can accelerate reprogramming by clearing or stabilizing extant transcripts. Here, we measured mRNA stability using 4-thiouracil labeling in the budding yeast Saccharomyces cerevisiae during a nitrogen upshift and found that 78 mRNAs are subject to destabilization. These transcripts include Nitrogen Catabolite Repression (NCR) and carbon metabolism mRNAs, suggesting that mRNA destabilization is a mechanism for targeted reprogramming of the transcriptome. To explore the molecular basis of destabilization we implemented a SortSeq approach to screen the pooled deletion collection library for trans factors that mediate rapid GAP1 mRNA repression. We combined low-input multiplexed Barcode sequencing with branched-DNA single-molecule mRNA FISH and Fluorescence-activated cell sorting (BFF) to identify the Lsm1-7p/Pat1p complex and general mRNA decay machinery as important for GAP1 mRNA clearance. We also find that the decapping modulators EDC3 and SCD6, translation factor eIF4G2, and the 5' UTR of GAP1 are factors that mediate rapid repression of GAP1 mRNA, suggesting that translational control may impact the post-transcriptional fate of mRNAs in response to environmental changes.

Single-cell RNA sequencing reveals intrinsic and extrinsic regulatory heterogeneity in yeast responding to stress

From bacteria to humans, individual cells within isogenic populations can show significant variation in stress tolerance, but the nature of this heterogeneity is not clear. To investigate this, we used single-cell RNA sequencing to quantify transcript heterogeneity in single Saccharomyces cerevisiae cells treated with and without salt stress to explore population variation and identify cellular covariates that influence the stress-responsive transcriptome. Leveraging the extensive knowledge of yeast transcriptional regulation, we uncovered significant regulatory variation in individual yeast cells, both before and after stress. We also discovered that a subset of cells appears to decouple expression of ribosomal protein genes from the environmental stress response in a manner partly correlated with the cell cycle but unrelated to the yeast ultradian metabolic cycle. Live-cell imaging of cells expressing pairs of fluorescent regulators, including the transcription factor Msn2 with Dot6, Sfp1, or MAP kinase Hog1, revealed both coordinated and decoupled nucleocytoplasmic shuttling. Together with transcriptomic analysis, our results suggest that cells maintain a cellular filter against decoupled bursts of transcription factor activation but mount a stress response upon coordinated regulation, even in a subset of unstressed cells.

Genetically identical cells growing in the same environment can vary in their cellular state and behavior. Such heterogeneity may explain why some cells in an isogenic population can survive sudden severe environmental stress whereas other cells succumb. Cell-to-cell variation in gene expression has been linked to variable stress survival, but how and why transcript levels vary across the transcriptome in single cells is only beginning to emerge. Here, we used single-cell RNA sequencing (scRNA-seq) to measure cell-to-cell heterogeneity in the transcriptome of budding yeast (Saccharomyces cerevisiae). We find surprising patterns of variation across known sets of transcription factor targets, indicating that cells vary in their transcriptome profile both before and after stress exposure. scRNA-seq analysis combined with live-cell imaging of transcription factor activation dynamics revealed some cells in which the stress response was coordinately activated and other cells in which the traditional response was decoupled, suggesting unrecognized regulatory nuances that expand our understanding of stress response and survival.

Translation initiation events on structured eukaryotic mRNAs generate gene expression noise

Gene expression stochasticity plays a major role in biology, creating non-genetic cellular individuality and influencing multiple processes, including differentiation and stress responses. We have addressed the lack of knowledge about posttranscriptional contributions to noise by determining cell-to-cell variations in the abundance of mRNA and reporter protein in yeast. Two types of structural element, a stem–loop and a poly(G) motif, not only inhibit translation initiation when inserted into an mRNA 5΄ untranslated region, but also generate noise. The noise-enhancing effect of the stem–loop structure also remains operational when combined with an upstream open reading frame. This has broad significance, since these elements are known to modulate the expression of a diversity of eukaryotic genes. Our findings suggest a mechanism for posttranscriptional noise generation that will contribute to understanding of the generally poor correlation between protein-level stochasticity and transcriptional bursting. We propose that posttranscriptional stochasticity can be linked to cycles of folding/unfolding of a stem–loop structure, or to interconversion between higher-order structural conformations of a G-rich motif, and have created a correspondingly configured computational model that generates fits to the experimental data. Stochastic events occurring during the ribosomal scanning process can therefore feature alongside transcriptional bursting as a source of noise.

The lncRNA RZE1 Controls Cryptococcal Morphological Transition

In the fungal pathogen Cryptococcus neoformans, the switch from yeast to hypha is an important morphological process preceding the meiotic events during sexual development. Morphotype is also known to be associated with cryptococcal virulence potential. Previous studies identified the regulator Znf2 as a key decision maker for hypha formation and as an anti-virulence factor. By a forward genetic screen, we discovered that a long non-coding RNA (lncRNA) RZE1 functions upstream of ZNF2 in regulating yeast-to-hypha transition. We demonstrate that RZE1 functions primarily in cis and less effectively in trans. Interestingly, RZE1's function is restricted to its native nucleus. Accordingly, RZE1 does not appear to directly affect Znf2 translation or the subcellular localization of Znf2 protein. Transcriptome analysis indicates that the loss of RZE1 reduces the transcript level of ZNF2 and Znf2's prominent downstream targets. In addition, microscopic examination using single molecule fluorescent in situ hybridization (smFISH) indicates that the loss of RZE1 increases the ratio of ZNF2 transcripts in the nucleus versus those in the cytoplasm. Taken together, this lncRNA controls Cryptococcus yeast-to-hypha transition through regulating the key morphogenesis regulator Znf2. This is the first functional characterization of a lncRNA in a human fungal pathogen. Given the potential large number of lncRNAs in the genomes of Cryptococcus and other fungal pathogens, the findings implicate lncRNAs as an additional layer of genetic regulation during fungal development that may well contribute to the complexity in these "simple" eukaryotes.

Neuronal expression of CB2 cannabinoid receptor mRNAs in the mouse hippocampus

In the brain, CB1 cannabinoid receptors primarily mediate the effects of cannabinoids, but CB2 cannabinoid receptors (CB2Rs) have recently been discovered in the nervous system and also implicated in neuromodulatory roles. To understand the mechanisms of CB2R functions in the brain, it is essential to localize CB2Rs, but the types of cells expressing CB2Rs have been controversial. Unequivocal localization of CB2Rs in the brain has been impeded in part by the low expression levels of CB2Rs and poor specificity of detection methods. Here, we used an ultrasensitive and specific in situ hybridization method called the RNAscope to determine the spatial pattern of CB2R mRNA expression in the mouse hippocampus. CB2R mRNAs were mostly expressed in a subset of excitatory and inhibitory neurons in the CA1, CA3 and dentate gyrus areas, but rarely in microglia. CB2R knock-out mice were used as a negative control. Using the quantitative real-time polymerase chain reaction, we also found that the temporal pattern of CB2R mRNA expression was stable during postnatal development. Consistent with previous reports, the immunological detection of CB2Rs was not reliable, implying extremely low levels of the protein expression and/or insufficient specificity of the current anti-CB2R antibodies. Our findings of the expression patterns of CB2R mRNAs may help determine the cell types involved in, and hence the mechanisms of, the CB2R-mediated neuromodulation.

Quantitative measurement of cancer tissue biomarkers in the lab and in the clinic

Detection of biomolecules in tissues provides contextual information and the possibility to assess the interaction of different cell types and markers. Routine qualitative assessment of immune- and oligonucleotide-based methods in research and the clinic has been associated with assay variability because of lack of stringent validation and subjective interpretation of results. As a result, the vast majority of in situ assays in clinical usage are nonquantitative and, although useful, often of questionable scientific validity. Here, we revisit the reporters and methods used for single- and multiplexed in situ visualization of protein and RNA. Then we examine methods for the use of quantitative platforms for in situ measurement of protein and mRNA levels. Finally, we discuss the challenges of the transition of these methods to the clinic and their potential role as tools for development of companion diagnostic tests.

Aro: a machine learning approach to identifying single molecules and estimating classification error in fluorescence microscopy images

Background

Recent techniques for tagging and visualizing single molecules in fixed or living organisms and cell lines have been revolutionizing our understanding of the spatial and temporal dynamics of fundamental biological processes. However, fluorescence microscopy images are often noisy, and it can be difficult to distinguish a fluorescently labeled single molecule from background speckle.

Results

We present a computational pipeline to distinguish the true signal of fluorescently labeled molecules from background fluorescence and noise. We test our technique using the challenging case of wide-field, epifluorescence microscope image stacks from single molecule fluorescence in situ experiments on nematode embryos where there can be substantial out-of-focus light and structured noise. The software recognizes and classifies individual mRNA spots by measuring several features of local intensity maxima and classifying them with a supervised random forest classifier. A key innovation of this software is that, by estimating the probability that each local maximum is a true spot in a statistically principled way, it makes it possible to estimate the error introduced by image classification. This can be used to assess the quality of the data and to estimate a confidence interval for the molecule count estimate, all of which are important for quantitative interpretations of the results of single-molecule experiments.

Conclusions

The software classifies spots in these images well, with >95% AUROC on realistic artificial data and outperforms other commonly used techniques on challenging real data. Its interval estimates provide a unique measure of the quality of an image and confidence in the classification.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0534-z) contains supplementary material, which is available to authorized users.

Genetic basis for Saccharomyces cerevisiae biofilm in liquid medium

Biofilm-forming microorganisms switch between two forms: free-living planktonic and sessile multicellular. Sessile communities of yeast biofilms in liquid medium provide a primitive example of multicellularity and are clinically important because biofilms tend to have other growth characteristics than free-living cells. We investigated the genetic basis for yeast, Saccharomyces cerevisiae, biofilm on solid surfaces in liquid medium by screening a comprehensive deletion mutant collection in the Σ1278b background and found 71 genes that were essential for biofilm development. Quantitative northern blots further revealed that AIM1, ASG1, AVT1, DRN1, ELP4, FLO8, FMP10, HMT1, KAR5, MIT1, MRPL32, MSS11, NCP1, NPR1, PEP5, PEX25, RIM8, RIM101, RGT1, SNF8, SPC2, STB6, STP22, TEC1, VID24, VPS20, VTC3, YBL029W, YBL029C-A, YFL054C, YGR161W-C, YIL014C-A, YIR024C, YKL151C, YNL200C, YOR034C-A, and YOR223W controlled biofilm through FLO11 induction. Almost all deletion mutants that were unable to form biofilms in liquid medium also lost the ability to form surface-spreading biofilm colonies (mats) on agar and 69% also lost the ability to grow invasively. The protein kinase A isoform Tpk3p functioned specifically in biofilm and mat formation. In a tpk3 mutant, transcription of FLO11 was induced three-fold compared with wild-type, but biofilm development and cell-cell adhesion was absent, suggesting that Tpk3p regulates FLO11 positive posttranscriptionally and negative transcriptionally.The study provides a resource of biofilm-influencing genes for additional research on biofilm development and suggests that the regulation of FLO11 is more complex than previously anticipated.

Rapid synthesis and screening of chemically activated transcription factors with GFP-based reporters

Synthetic biology aims to rationally design and build synthetic circuits with desired quantitative properties, as well as provide tools to interrogate the structure of native control circuits. In both cases, the ability to program gene expression in a rapid and tunable fashion, with no off-target effects, can be useful. We have constructed yeast strains containing the ACT1 promoter upstream of a URA3 cassette followed by the ligand-binding domain of the human estrogen receptor and VP16. By transforming this strain with a linear PCR product containing a DNA binding domain and selecting against the presence of URA3, a constitutively expressed artificial transcription factor (ATF) can be generated by homologous recombination. ATFs engineered in this fashion can activate a unique target gene in the presence of inducer, thereby eliminating both the off-target activation and nonphysiological growth conditions found with commonly used conditional gene expression systems. A simple method for the rapid construction of GFP reporter plasmids that respond specifically to a native or artificial transcription factor of interest is also provided.