Imaging gene expression in single living cells

AraLeTA: An Arabidopsis leaf expression atlas across diurnal and developmental scales

Mature plant leaves are a composite of distinct cell types, including epidermal, mesophyll, and vascular cells. Notably, the proportion of these cells and the relative transcript concentrations within different cell types may change over time. While gene expression data at a single-cell level can provide cell-type-specific expression values, it is often too expensive to obtain these data for high-resolution time series. Although bulk RNA-seq can be performed in a high-resolution time series, RNA-seq using whole leaves measures average gene expression values across all cell types in each sample. In this study, we combined single-cell RNA-seq data with time-series data from whole leaves to assemble an atlas of cell-type-specific changes in gene expression over time for Arabidopsis (Arabidopsis thaliana). We inferred how the relative transcript concentrations of different cell types vary across diurnal and developmental timescales. Importantly, this analysis revealed 3 subgroups of mesophyll cells with distinct temporal profiles of expression. Finally, we developed tissue-specific gene networks that form a community resource: an Arabidopsis Leaf Time-dependent Atlas (AraLeTa). This allows users to extract gene networks that are confirmed by transcription factor-binding data and specific to certain cell types at certain times of day and at certain developmental stages. AraLeTa is available at https://regulatorynet.shinyapps.io/araleta/.

Kinetics of RNA-LNP delivery and protein expression

Lipid nanoparticles (LNPs) employing ionizable lipids are the most advanced technology for delivery of RNA, most notably mRNA, to cells. LNPs represent well-defined core-shell particles with efficient nucleic acid encapsulation, low immunogenicity and enhanced efficacy. While much is known about the structure and activity of LNPs, less attention is given to the timing of LNP uptake, cytosolic transfer and protein expression. However, LNP kinetics is a key factor determining delivery efficiency. Hence quantitative insight into the multi-cascaded pathway of LNPs is of interest to elucidate the mechanism of delivery. Here, we review experiments as well as theoretical modeling of the timing of LNP uptake, mRNA-release and protein expression. We describe LNP delivery as a sequence of stochastic transfer processes and review a mathematical model of subsequent protein translation from mRNA. We compile probabilities and numbers obtained from time resolved microscopy. Specifically, live-cell imaging on single cell arrays (LISCA) allows for high-throughput acquisition of thousands of individual GFP reporter expression time courses. The traces yield the distribution of mRNA life-times, expression rates and expression onset. Correlation analysis reveals an inverse dependence of gene expression efficiency and transfection onset-times. Finally, we discuss why timing of mRNA release is critical in the context of codelivery of multiple nucleic acid species as in the case of mRNA co-expression or CRISPR/Cas gene editing.

Allele pairing at Sun1-enriched domains at the nuclear periphery via T1A3 tandem DNA repeats

Spatiotemporal gene regulation is fundamental to the biology of diploid cells. Therefore, effective communication between two alleles and their geometry in the nucleus is important. However, the mechanism that fine-tunes the expression from each of the two alleles of an autosome is enigmatic. Establishing an allele-specific gene expression visualization system in living cells, we show that alleles of biallelically expressed Cth and Ttc4 genes are paired prior to acquiring monoallelic expression. We found that active alleles of monoallelic genes are preferentially localized at Sun1-enriched domains at the nuclear periphery. These peripherally localized active DNA loci are enriched with adenine-thymidine-rich tandem repeats that interact with Hnrnpd and reside in a Hi-C-defined A compartment within the B compartment. Our results demonstrate the biological significance of T ₁ A ₃ tandem repeat sequences in genome organization and how the regulation of gene expression, at the level of individual alleles, relates to their spatial arrangement.

Spelling out the roles of individual nucleoporins in nuclear export of mRNA

The Nuclear Pore Complex (NPC) represents a critical passage through the nuclear envelope for nuclear import and export that impacts nearly every cellular process at some level. Recent technological advances in the form of Auxin Inducible Degron (AID) strategies and Single-Point Edge-Excitation sub-Diffraction (SPEED) microscopy have enabled us to provide new insight into the distinct functions and roles of nuclear basket nucleoporins (Nups) upon nuclear docking and export for mRNAs. In this paper, we provide a review of our recent findings as well as an assessment of new techniques, updated models, and future perspectives in the studies of mRNA's nuclear export.

Bromodomains regulate dynamic targeting of the PBAF chromatin-remodeling complex to chromatin hubs

Chromatin remodelers actively target arrays of acetylated nucleosomes at select enhancers and promoters to facilitate or shut down the repeated recruitment of RNA polymerase II during transcriptional bursting. It is poorly understood how chromatin remodelers such as PBAF dynamically target different chromatin states inside a live cell. Our live-cell single-molecule fluorescence microscopy study reveals chromatin hubs throughout the nucleus where PBAF rapidly cycles on and off the genome. Deletion of PBAF's bromodomains impairs targeting and stable engagement of chromatin in hubs. Dual color imaging reveals that PBAF targets both euchromatic and heterochromatic hubs with distinct genome-binding kinetic profiles that mimic chromatin stability. Removal of PBAF's bromodomains stabilizes H3.3 binding within chromatin, indicating that bromodomains may play a direct role in remodeling of the nucleosome. Our data suggests that PBAF's dynamic bromodomain-mediated engagement of a nucleosome may reflect the chromatin-remodeling potential of differentially bound chromatin states.

Imaging Organization of RNA Processing within the Nucleus

Within the nucleus, messenger RNA is generated and processed in a highly organized and regulated manner. Messenger RNA processing begins during transcription initiation and continues until the RNA is translated and degraded. Processes such as 5' capping, alternative splicing, and 3' end processing have been studied extensively with biochemical methods and more recently with single-molecule imaging approaches. In this review, we highlight how imaging has helped understand the highly dynamic process of RNA processing. We conclude with open questions and new technological developments that may further our understanding of RNA processing.

Determining the Biological Mechanisms of Action for Environmental Exposures: Applying CRISPR/Cas9 to Toxicological Assessments

Toxicology is a constantly evolving field, especially in the area of developing alternatives to animal testing. Toxicological research must evolve and utilize adaptive technologies in an effort to improve public, environmental, and occupational health. The most commonly cited mechanisms of toxic action after exposure to a chemical or particle test substance is oxidative stress. However, because oxidative stress involves a plethora of genes and proteins, the exact mechanism(s) are not commonly defined. Exact mechanisms of toxicity can be revealed using an emerging laboratory technique referred to as CRISPR (clustered regularly interspaced short palindromic repeats). This article reviews the most common CRISPR techniques utilized today and how each may be applied in Toxicological Sciences. Specifically, the CRISPR/CRISPR-associated protein complex is used for single gene knock-outs, whereas CRISPR interference/activation is used for silencing or activating (respectively) ribonucleic acid. Finally, CRISPR libraries are used for knocking-out entire gene pathways. This review highlights the application of CRISPR in toxicology to elucidate the exact mechanism through which toxicants perturb normal cellular functions.

How Do Cells Adapt? Stories Told in Landscapes

Cells adapt to changing environments. Perturb a cell and it returns to a point of homeostasis. Perturb a population and it evolves toward a fitness peak. We review quantitative models of the forces of adaptation and their visualizations on landscapes. While some adaptations result from single mutations or few-gene effects, others are more cooperative, more delocalized in the genome, and more universal and physical. For example, homeostasis and evolution depend on protein folding and aggregation, energy and protein production, protein diffusion, molecular motor speeds and efficiencies, and protein expression levels. Models provide a way to learn about the fitness of cells and cell populations by making and testing hypotheses.

A fully-automated, robust, and versatile algorithm for long-term budding yeast segmentation and tracking

Live cell time-lapse microscopy, a widely-used technique to study gene expression and protein dynamics in single cells, relies on segmentation and tracking of individual cells for data generation. The potential of the data that can be extracted from this technique is limited by the inability to accurately segment a large number of cells from such microscopy images and track them over long periods of time. Existing segmentation and tracking algorithms either require additional dyes or markers specific to segmentation or they are highly specific to one imaging condition and cell morphology and/or necessitate manual correction. Here we introduce a fully automated, fast and robust segmentation and tracking algorithm for budding yeast that overcomes these limitations. Full automatization is achieved through a novel automated seeding method, which first generates coarse seeds, then automatically fine-tunes cell boundaries using these seeds and automatically corrects segmentation mistakes. Our algorithm can accurately segment and track individual yeast cells without any specific dye or biomarker. Moreover, we show how existing channels devoted to a biological process of interest can be used to improve the segmentation. The algorithm is versatile in that it accurately segments not only cycling cells with smooth elliptical shapes, but also cells with arbitrary morphologies (e.g. sporulating and pheromone treated cells). In addition, the algorithm is independent of the specific imaging method (bright-field/phase) and objective used (40X/63X/100X). We validate our algorithm's performance on 9 cases each entailing a different imaging condition, objective magnification and/or cell morphology. Taken together, our algorithm presents a powerful segmentation and tracking tool that can be adapted to numerous budding yeast single-cell studies.

Intracellular RNA-tracking methods

RNA tracking allows researchers to visualize RNA molecules in cells and tissues, providing important spatio-temporal information regarding RNA dynamics and function. Methods such as fluorescent in situ hybridization (FISH) and molecular beacons rely on complementary oligonucleotides to label and view endogenous transcripts. Other methods create artificial chimeric transcripts coupled with bacteriophage-derived coat proteins (e.g. MS2, λN) to tag molecules in live cells. In other approaches, endogenous RNAs are recognized by complementary RNAs complexed with noncatalytic Cas proteins. Each technique has its own set of strengths and limitations that must be considered when planning an experiment. Here, we discuss the mechanisms, advantages, and weaknesses of in situ hybridization, molecular beacons, MS2 tagging and Cas-derived systems, as well as how RNA tracking can be employed to study various aspects of molecular biology.

CD-tagging-MS2: detecting allelic expression of endogenous mRNAs and their protein products in single cells

Discriminating between the mRNA and protein outputs of each of the alleles of an endogenous gene in intact cells, is a difficult task. To examine endogenous transcripts originating from a specific allele, we applied Central Dogma tagging (CD-tagging), which is based on a tag insertion into an endogenous gene by creation of a new exon. Previously, CD-tagging was used to tag endogenous proteins. Here we developed a CD-tagging-MS2 approach in which two tags were inserted in tandem; a fluorescent protein tag in conjunction with the mRNA MS2 tag used for tagging mRNAs in cells. A cell clone library of CD-tagged-MS2 genes was generated, and protein and mRNA distributions were examined and characterized in single cells. Taking advantage of having one allele tagged, we demonstrate how the transcriptional activity of all alleles, tagged and untagged, can be identified using single molecule RNA fluorescence in situ hybridization (smFISH). Allele-specific mRNA expression and localization were quantified under normal and stress conditions. The latter generate cytoplasmic stress granules (SGs) that can store mRNAs, and the distribution of the mRNAs within and outside of the SGs was measured. Altogether, CD-tagging-MS2 is a robust and inexpensive approach for direct simultaneous detection of an endogenous mRNA and its translated protein product in the same cell.

Adding energy minimization strategy to peptide-design algorithm enables better search for RNA-binding peptides: Redesigned λ N peptide binds boxB RNA

Our previously developed peptide-design algorithm was improved by adding an energy minimization strategy which allows the amino acid sidechains to move in a broad configuration space during sequence evolution. In this work, the new algorithm was used to generate a library of 21-mer peptides which could substitute for λ N peptide in binding to boxB RNA. Six potential peptides were obtained from the algorithm, all of which exhibited good binding capability with boxB RNA. Atomistic molecular dynamics simulations were then conducted to examine the ability of the λ N peptide and three best evolved peptides, viz. Pept01, Pept26, and Pept28, to bind to boxB RNA. Simulation results demonstrated that our evolved peptides are better at binding to boxB RNA than the λ N peptide. Sequence searches using the old (without energy minimization strategy) and new (with energy minimization strategy) algorithms confirm that the new algorithm is more effective at finding good RNA-binding peptides than the old algorithm. © 2016 Wiley Periodicals, Inc.

From Cells to Virus Particles: Quantitative Methods to Monitor RNA Packaging

In cells, positive strand RNA viruses, such as Retroviridae, must selectively recognize their full-length RNA genome among abundant cellular RNAs to assemble and release particles. How viruses coordinate the intracellular trafficking of both RNA and protein components to the assembly sites of infectious particles at the cell surface remains a long-standing question. The mechanisms ensuring packaging of genomic RNA are essential for viral infectivity. Since RNA packaging impacts on several essential functions of retroviral replication such as RNA dimerization, translation and recombination events, there are many studies that require the determination of RNA packaging efficiency and/or RNA packaging ability. Studies of RNA encapsidation rely upon techniques for the identification and quantification of RNA species packaged by the virus. This review focuses on the different approaches available to monitor RNA packaging: Northern blot analysis, ribonuclease protection assay and quantitative reverse transcriptase-coupled polymerase chain reaction as well as the most recent RNA imaging and sequencing technologies. Advantages, disadvantages and limitations of these approaches will be discussed in order to help the investigator to choose the most appropriate technique. Although the review was written with the prototypic simple murine leukemia virus (MLV) and complex human immunodeficiency virus type 1 (HIV-1) in mind, the techniques were described in order to benefit to a larger community.

The nuts and bolts of the endogenous spliceosome

The complex life of pre-mRNA from transcription to the production of mRNA that can be exported from the nucleus to the cytoplasm to encode for proteins entails intricate coordination and regulation of a network of processing events. Coordination is required between transcription and splicing and between several processing events including 5' and 3' end processing, splicing, alternative splicing and editing that are major contributors to the diversity of the human proteome, and occur within a huge and dynamic macromolecular machine-the endogenous spliceosome. Detailed mechanistic insight of the splicing reaction was gained from studies of the in vitro spliceosome assembled on a single intron. Because most pre-mRNAs are multiintronic that undergo alternative splicing, the in vivo splicing machine requires additional elements to those of the in vitro machine, to account for all these diverse functions. Information about the endogenous spliceosome is emerging from imaging studies in intact and live cells that support the cotranscriptional commitment to splicing model and provide information about splicing kinetics in vivo. Another source comes from studies of the in vivo assembled spliceosome, isolated from cell nuclei under native conditions-the supraspliceosome-that individually package pre-mRNA transcripts of different sizes and number of introns into complexes of a unique structure, indicating their universal nature. Recent years have portrayed new players affecting alternative splicing and novel connections between splicing, transcription and chromatin. The challenge ahead is to elucidate the structure and function of the endogenous spliceosome and decipher the regulation and coordination of its network of processing activities. WIREs RNA 2017, 8:e1377. doi: 10.1002/wrna.1377 For further resources related to this article, please visit the WIREs website.

Bioinformatics approaches to single-cell analysis in developmental biology

Individual cells within the same population show various degrees of heterogeneity, which may be better handled with single-cell analysis to address biological and clinical questions. Single-cell analysis is especially important in developmental biology as subtle spatial and temporal differences in cells have significant associations with cell fate decisions during differentiation and with the description of a particular state of a cell exhibiting an aberrant phenotype. Biotechnological advances, especially in the area of microfluidics, have led to a robust, massively parallel and multi-dimensional capturing, sorting, and lysis of single-cells and amplification of related macromolecules, which have enabled the use of imaging and omics techniques on single cells. There have been improvements in computational single-cell image analysis in developmental biology regarding feature extraction, segmentation, image enhancement and machine learning, handling limitations of optical resolution to gain new perspectives from the raw microscopy images. Omics approaches, such as transcriptomics, genomics and epigenomics, targeting gene and small RNA expression, single nucleotide and structural variations and methylation and histone modifications, rely heavily on high-throughput sequencing technologies. Although there are well-established bioinformatics methods for analysis of sequence data, there are limited bioinformatics approaches which address experimental design, sample size considerations, amplification bias, normalization, differential expression, coverage, clustering and classification issues, specifically applied at the single-cell level. In this review, we summarize biological and technological advancements, discuss challenges faced in the aforementioned data acquisition and analysis issues and present future prospects for application of single-cell analyses to developmental biology.

Chromosome dynamics and folding in eukaryotes: Insights from live cell microscopy

How chromosomes are folded and how this folding relates to function remain fundamental questions. Answering them is rendered difficult by the stochasticity of chromatin fiber motion which inevitably results in heterogeneity of the populations analyzed. Even if single cell analyses are beginning to yield precious insights, how can we determine whether a snapshot of position is related to function of the probed locus or cell-type? Fluorescence labeling of DNA at single or multiple loci allows determination of their position relative to nuclear landmarks and to each other, enabling us to derive physical parameters of the underlying chromatin fiber. Here I review the contribution of quantitative spatial and temporal analysis of labeled DNA to our understanding of chromosome conformation in different cell types, highlighting live cell imaging techniques and large scale geometrical analysis of multiple loci in 3D.

Guidelines for the fitting of anomalous diffusion mean square displacement graphs from single particle tracking experiments

Single particle tracking is an essential tool in the study of complex systems and biophysics and it is commonly analyzed by the time-averaged mean square displacement (MSD) of the diffusive trajectories. However, past work has shown that MSDs are susceptible to significant errors and biases, preventing the comparison and assessment of experimental studies. Here, we attempt to extract practical guidelines for the estimation of anomalous time averaged MSDs through the simulation of multiple scenarios with fractional Brownian motion as a representative of a large class of fractional ergodic processes. We extract the precision and accuracy of the fitted MSD for various anomalous exponents and measurement errors with respect to measurement length and maximum time lags. Based on the calculated precision maps, we present guidelines to improve accuracy in single particle studies. Importantly, we find that in some experimental conditions, the time averaged MSD should not be used as an estimator.

Connecting the dots of RNA-directed DNA methylation in Arabidopsis thaliana

Noncoding RNAs are the rising stars of genome regulation and are crucial to an organism's metabolism, development, and defense. One of their most notable functions is its ability to direct epigenetic modifications through small RNA molecules to specific genomic regions, ensuring transcriptional regulation, proper genome organization, and maintenance of genome integrity. Here, we review the current knowledge of the spatial organization of the Arabidopsis thaliana RNA-directed DNA methylation pathway within the cell nucleus, which, while known to be essential for the proper establishment of epigenetic modifications, remains poorly understood. We will also discuss possible future cytological approaches that have the potential of unveiling functional insights into how small RNA-directed epigenetics is regulated through the spatiotemporal regulation of its major components within the cell.

Single cell correlation fractal dimension of chromatin: a framework to interpret 3D single molecule super-resolution

Chromatin is a major nuclear component, and it is an active matter of debate to understand its different levels of spatial organization, as well as its implication in gene regulation. Measurements of nuclear chromatin compaction were recently used to understand how DNA is folded inside the nucleus and to detect cellular dysfunctions such as cancer. Super-resolution imaging opens new possibilities to measure chromatin organization in situ. Here, we performed a direct measure of chromatin compaction at the single cell level. We used histone H2B, one of the 4 core histone proteins forming the nucleosome, as a chromatin density marker. Using photoactivation localization microscopy (PALM) and adaptive optics, we measured the three-dimensional distribution of H2B with nanometric resolution. We computed the distribution of distances between every two points of the chromatin structure, namely the Ripley K(r) distribution. We found that the K(r) distribution of H2B followed a power law, leading to a precise measurement of the correlation fractal dimension of chromatin of 2.7. Moreover, using photoactivable GFP fused to H2B, we observed dynamic evolution of chromatin sub-regions compaction. As a result, the correlation fractal dimension of chromatin reported here can be interpreted as a dynamically maintained non-equilibrium state.

Electron spectroscopic tomography of specific chromatin domains

The eukaryotic genome is packaged within the nucleus as poly-nucleosome 10 nm chromatin fibres. The nucleosome core particle, the fundamental chromatin subunit, consists of a DNA molecule wrapped around a histone octamer. Biochemical modifications of both the DNA and histone proteins have been characterized that influence chromatin structure and function. These modifications include DNA methylation, histone variants and posttranslational modifications of the core histone protein tails. An outstanding area for investigation in the field of nuclear cell biology is the characterization of the functional relation between these biochemical modifications and the underlying chromatin structure and nuclear sub-compartmentalization. Electron spectroscopic tomography is a high-resolution microscopy technique that facilitates visualization of individual 10 nm chromatin fibres in three dimensions. The method, therefore, has a role to play in exploring the relationships of the epigenome and nuclear organization. Correlating immunofluorescence microscopy with electron spectroscopic tomography provides a powerful approach to relate epigenetic marks with high resolution chromatin organization.

Optical control and study of biological processes at the single-cell level in a live organism

Living organisms are made of cells that are capable of responding to external signals by modifying their internal state and subsequently their external environment. Revealing and understanding the spatio-temporal dynamics of these complex interaction networks is the subject of a field known as systems biology. To investigate these interactions (a necessary step before understanding or modelling them) one needs to develop means to control or interfere spatially and temporally with these processes and to monitor their response on a fast timescale (< minute) and with single-cell resolution. In 2012, an EMBO workshop on 'single-cell physiology' (organized by some of us) was held in Paris to discuss those issues in the light of recent developments that allow for precise spatio-temporal perturbations and observations. This review will be largely based on the investigations reported there. We will first present a non-exhaustive list of examples of cellular interactions and developmental pathways that could benefit from these new approaches. We will review some of the novel tools that have been developed for the observation of cellular activity and then discuss the recent breakthroughs in optical super-resolution microscopy that allow for optical observations beyond the diffraction limit. We will review the various means to photo-control the activity of biomolecules, which allow for local perturbations of physiological processes. We will end up this review with a report on the current status of optogenetics: the use of photo-sensitive DNA-encoded proteins as sensitive reporters and efficient actuators to perturb and monitor physiological processes.

Quantifying the transcriptional output of single alleles in single living mammalian cells

Transcription kinetics of actively transcribing genes in vivo have generally been measured using tandem gene arrays. However, tandem arrays do not reflect the endogenous state of genome organization in which genes appear as single alleles. Here we present a robust technique for the quantification of mRNA synthesis from a single allele in real time in single living mammalian cells. The protocol describes how to generate cell clones harboring an MS2-tagged allele and how to detect in vivo transcription from this tagged allele at high spatial and temporal resolution throughout the cell cycle. Quantification of nascent mRNAs produced from the single tagged allele is performed using RNA fluorescence in situ hybridization (FISH) and live-cell imaging. Subsequent analyses and data modeling detailed in the protocol include measurements of transcription rates of RNA polymerase II, determination of the number of polymerases recruited to the tagged allele and measurement of the spacing between polymerases. Generation of the cells containing the single tagged alleles should take up to 1 month; RNA FISH or live-cell imaging will require an additional week.

Identifying dynamical systems with bifurcations from noisy partial observation

We propose a statistical machine-learning approach to derive low-dimensional models by integrating noisy time-series data from partial observation of high-dimensional systems, aiming to utilize quantitative data on biological phenomena in the cell. In particular, the method estimates a model from data at different values of a bifurcation parameter in order to characterize biological functions as bifurcation types that are insensitive to system details and experimental errors. The method is tested using artificial data generated from two cell-cycle control system models that exhibit different bifurcations and the learned systems are shown to robustly inherit the bifurcation types.

Optical systems for single cell analyses

BACKGROUND

Data extracted from a population of cells represent the average response from all cells within the population. Even when the cells are genetically identical, cell-to-cell variations and genetic noise can make the cells respond in completely different ways. To understand the mechanisms behind the behaviour of a population, the cells must also be analysed on an individual basis.

OBJECTIVE

This review highlights the use of optical manipulation, microfluidics and advanced fluorescence imaging techniques for the acquisition of single cell data.

CONCLUSION

By implementation of these three techniques, it is possible to achieve a deeper insight into the principles underlying cellular functioning and a more thorough understanding of the phenomena often observed in cell populations, thus facilitating research in drug discovery.

Systems biology in animal sciences

Systems biology is a rapidly expanding field of research and is applied in a number of biological disciplines. In animal sciences, omics approaches are increasingly used, yielding vast amounts of data, but systems biology approaches to extract understanding from these data of biological processes and animal traits are not yet frequently used. This paper aims to explain what systems biology is and which areas of animal sciences could benefit from systems biology approaches. Systems biology aims to understand whole biological systems working as a unit, rather than investigating their individual components. Therefore, systems biology can be considered a holistic approach, as opposed to reductionism. The recently developed 'omics' technologies enable biological sciences to characterize the molecular components of life with ever increasing speed, yielding vast amounts of data. However, biological functions do not follow from the simple addition of the properties of system components, but rather arise from the dynamic interactions of these components. Systems biology combines statistics, bioinformatics and mathematical modeling to integrate and analyze large amounts of data in order to extract a better understanding of the biology from these huge data sets and to predict the behavior of biological systems. A 'system' approach and mathematical modeling in biological sciences are not new in itself, as they were used in biochemistry, physiology and genetics long before the name systems biology was coined. However, the present combination of mass biological data and of computational and modeling tools is unprecedented and truly represents a major paradigm shift in biology. Significant advances have been made using systems biology approaches, especially in the field of bacterial and eukaryotic cells and in human medicine. Similarly, progress is being made with 'system approaches' in animal sciences, providing exciting opportunities to predict and modulate animal traits.

Continuous spectroscopic measurements of photo-stimulated release of molecules by nanomachines in a single living cell

The first continuous, real-time spectroscopic monitoring of a photo-driven cargo delivery event from a mesoporous silica-based nanocarrier inside a single living cell is reported. By chemically attaching azobenzene molecules inside the 3 nm pore channels of mesoporous silica nanoparticles (∼70 nm diameter), the escape of the cargo molecule [propidium iodide (PI)] from the pore is prevented in the dark but is facilitated by the light-driven isomerization motion. Real-time spectroscopic measurements of a single cell uncover intermediate processes that occur during this intracellular delivery event, from nanomachine activation to the release of PI into the cytosol and to PI's eventual intercalation with nuclear DNA. Changes in PI's fluorescence intensity and the hypsochromic shift of the band maxima are used to identify the local environment of the fluorophore that is being observed in the cell. The ability to precisely initiate a chemical event inside an individual cell and continuously monitor the subsequent biological responses will enhance our understanding of intracellular process upon drug, protein and nucleic acid delivery.

Live-cell super-resolution imaging with synthetic fluorophores

Super-resolution imaging methods now can provide spatial resolution that is well below the diffraction limit approaching virtually molecular resolution. They can be applied to biological samples and provide new and exciting views on the structural organization of cells and the dynamics of biomolecular assemblies on wide timescales. These revolutionary developments come with novel requirements for fluorescent probes, labeling techniques, and data interpretation strategies. Synthetic fluorophores have a small size, are available in many colors spanning the whole spectrum, and can easily be chemically modified and used for stoichiometric labeling of proteins in live cells. Because of their brightness, their photostability, and their ability to be operated as photoswitchable fluorophores even in living cells under physiological conditions, synthetic fluorophores have the potential to substantially accelerate the broad application of live-cell super-resolution imaging methods.

Proteins on the move: insights gained from fluorescent protein technologies

Proteins are always on the move, and this may occur through diffusion or active transport. The realization that the regulation of signal transduction is highly dynamic in space and time has stimulated intense interest in the movement of proteins. Over the past decade, numerous new technologies using fluorescent proteins have been developed, allowing us to observe the spatiotemporal dynamics of proteins in living cells. These technologies have greatly advanced our understanding of protein dynamics, including protein movement and protein interactions.

Quantitative single cell monitoring of protein synthesis at subcellular resolution using fluorescently labeled tRNA

We have developed a novel technique of using fluorescent tRNA for translation monitoring (FtTM). FtTM enables the identification and monitoring of active protein synthesis sites within live cells at submicron resolution through quantitative microscopy of transfected bulk uncharged tRNA, fluorescently labeled in the D-loop (fl-tRNA). The localization of fl-tRNA to active translation sites was confirmed through its co-localization with cellular factors and its dynamic alterations upon inhibition of protein synthesis. Moreover, fluorescence resonance energy transfer (FRET) signals, generated when fl-tRNAs, separately labeled as a FRET pair occupy adjacent sites on the ribosome, quantitatively reflect levels of protein synthesis in defined cellular regions. In addition, FRET signals enable detection of intra-populational variability in protein synthesis activity. We demonstrate that FtTM allows quantitative comparison of protein synthesis between different cell types, monitoring effects of antibiotics and stress agents, and characterization of changes in spatial compartmentalization of protein synthesis upon viral infection.

Live cell imaging and systems biology

Much of the experimental data used to construct mathematical models of molecular networks are derived from in vitro measurements. However, there is increasing evidence that in vitro measurements fail to capture both the complexity and the individuality found in single, living cells. These limitations can be overcome by live cell microscopy which is evolving to enable in vivo biochemistry. Here, we survey the current capabilities of live cell microscopy and illustrate how a number of different imaging approaches could be applied to analyze a specific molecular network. We argue that incorporation of such quantitative live-cell imaging methods is critical for the progress of systems biology.

Combining SELEX screening and rational design to develop light-up fluorophore-RNA aptamer pairs for RNA tagging

We report here a new small molecule fluorogen and RNA aptamer pair for RNA labeling. The small-molecule fluorogen is designed on the basis of fluorescently quenched sulforhodamine dye. The SELEX (Systematic Evolution of Ligands by EXponential enrichment) procedure and fluorescence screening in E. coli have been applied to discover the aptamer that can specifically activate the fluorogen with micromolar binding affinity. The systematic mutation and truncation study on the aptamer structure determined the minimum binding domain of the aptamer. A series of rationally modified fluorogen analogues have been made to probe the interacting groups of fluorogen with the aptamer. These results led to the design of a much improved fluorogen ASR 7 that displayed a 33-fold increase in the binding affinity for the selected aptamer in comparison to the original ASR 1 and an 88-fold increase in the fluorescence emission after the aptamer binding. This study demonstrates the value of combining in vitro SELEX and E. coli fluorescence screening with rational modifications in discovering and optimizing new fluorogen-RNA aptamer labeling pairs.

Robustness of circadian clocks to daylight fluctuations: hints from the picoeucaryote Ostreococcus tauri

The development of systemic approaches in biology has put emphasis on identifying genetic modules whose behavior can be modeled accurately so as to gain insight into their structure and function. However, most gene circuits in a cell are under control of external signals and thus, quantitative agreement between experimental data and a mathematical model is difficult. Circadian biology has been one notable exception: quantitative models of the internal clock that orchestrates biological processes over the 24-hour diurnal cycle have been constructed for a few organisms, from cyanobacteria to plants and mammals. In most cases, a complex architecture with interlocked feedback loops has been evidenced. Here we present the first modeling results for the circadian clock of the green unicellular alga Ostreococcus tauri. Two plant-like clock genes have been shown to play a central role in the Ostreococcus clock. We find that their expression time profiles can be accurately reproduced by a minimal model of a two-gene transcriptional feedback loop. Remarkably, best adjustment of data recorded under light/dark alternation is obtained when assuming that the oscillator is not coupled to the diurnal cycle. This suggests that coupling to light is confined to specific time intervals and has no dynamical effect when the oscillator is entrained by the diurnal cycle. This intringuing property may reflect a strategy to minimize the impact of fluctuations in daylight intensity on the core circadian oscillator, a type of perturbation that has been rarely considered when assessing the robustness of circadian clocks.

Circadian clocks keep time of day in many living organisms, allowing them to anticipate environmental changes induced by day/night alternation. They consist of networks of genes and proteins interacting so as to generate biochemical oscillations with a period close to 24 hours. Circadian clocks synchronize to the day/night cycle through the year principally by sensing ambient light. Depending on the weather, the perceived light intensity can display large fluctuations within the day and from day to day, potentially inducing unwanted resetting of the clock. Furthermore, marine organisms such as microalgae are subjected to dramatic changes in light intensities in the water column due to streams and wind. We showed, using mathematical modelling, that the green unicellular marine alga Ostreococcus tauri has evolved a simple but effective strategy to shield the circadian clock from daylight fluctuations by localizing coupling to the light during specific time intervals. In our model, as in experiments, coupling is invisible when the clock is in phase with the day/night cycle but resets the clock when it is out of phase. Such a clock architecture is immune to strong daylight fluctuations.

RNA processing and export

Messenger RNAs undergo 5' capping, splicing, 3'-end processing, and export before translation in the cytoplasm. It has become clear that these mRNA processing events are tightly coupled and have a profound effect on the fate of the resulting transcript. This processing is represented by modifications of the pre-mRNA and loading of various protein factors. The sum of protein factors that stay with the mRNA as a result of processing is modified over the life of the transcript, conferring significant regulation to its expression.

Dynamics and kinetics of nucleo-cytoplasmic mRNA export

Activation of the gene expression pathway in eukaryotic cells results in the nuclear transcription of mRNA molecules, many of which are destined for translation into protein by cytoplasmic ribosomes. mRNA transcripts are exported from the nucleus to the cytoplasm via passage through nuclear pore complexes (NPCs), ∼125 MDa supramolecular complexes set in the double-membraned nuclear envelope. Understanding the kinetics of mRNA translocation, from the point of transcription through export, localization, translation, and degradation, is of fundamental interest since gene expression is regulated at all the different levels of this pathway. In this review, we delineate the steps taken by an mRNA molecule in transit to the nuclear envelope and during mRNA export, with specific focus on the dynamic aspects of nucleo-cytoplasmic mRNA transport as revealed by electron microscopy and live-cell imaging.

On the right track: following the nucleo-cytoplasmic path of an mRNA

The transcription machinery in the eukaryotic nucleus generates messenger RNA molecules that translocate through the nucleoplasm, anchor to a nuclear pore, and find their way out into the cytoplasm. The dynamic aspects of these steps in the expression pathway were examined in order to understand the kinetic time-frames of gene activation and message dissemination. Utilizing live-cell imaging and tracking of single mRNPs containing different sized mRNAs and varying numbers of introns and exons, it was possible to quantify the temporal and spatial characteristics of the nucleoplasmic travels of mRNPs as well as the kinetics of translocation through the nuclear pore.

Experimental and computational validation of models of fluorescent and luminescent reporter genes in bacteria

BACKGROUND

Fluorescent and luminescent reporter genes have become popular tools for the real-time monitoring of gene expression in living cells. However, mathematical models are necessary for extracting biologically meaningful quantities from the primary data.

RESULTS

We present a rigorous method for deriving relative protein synthesis rates (mRNA concentrations) and protein concentrations by means of kinetic models of gene expression. We experimentally and computationally validate this approach in the case of the protein Fis, a global regulator of transcription in Escherichia coli. We show that the mRNA and protein concentration profiles predicted from the models agree quite well with direct measurements obtained by Northern and Western blots, respectively. Moreover, we present computational procedures for taking into account systematic biases like the folding time of the fluorescent reporter protein and differences in the half-lives of reporter and host gene products. The results show that large differences in protein half-lives, more than mRNA half-lives, may be critical for the interpretation of reporter gene data in the analysis of the dynamics of regulatory systems.

CONCLUSIONS

The paper contributes to the development of sound methods for the interpretation of reporter gene data, notably in the context of the reconstruction and validation of models of regulatory networks. The results have wide applicability for the analysis of gene expression in bacteria and may be extended to higher organisms.

Noise in biological circuits

Noise biology focuses on the sources, processing, and biological consequences of the inherent stochastic fluctuations in molecular transitions or interactions that control cellular behavior. These fluctuations are especially pronounced in small systems where the magnitudes of the fluctuations approach or exceed the mean value of the molecular population. Noise biology is an essential component of nanomedicine where the communication of information is across a boundary that separates small synthetic and biological systems that are bound by their size to reside in environments of large fluctuations. Here we review the fundamentals of the computational, analytical, and experimental approaches to noise biology. We review results that show that the competition between the benefits of low noise and those of low population has resulted in the evolution of genetic system architectures that produce an uneven distribution of stochasticity across the molecular components of cells and, in some cases, use noise to drive biological function. We review the exact and approximate approaches to gene circuit noise analysis and simulation, and review many of the key experimental results obtained using flow cytometry and time-lapse fluorescent microscopy. In addition, we consider the probative value of noise with a discussion of using measured noise properties to elucidate the structure and function of the underlying gene circuit. We conclude with a discussion of the frontiers of and significant future challenges for noise biology.

In vivo detection of RNA-binding protein interactions with cognate RNA sequences by fluorescence resonance energy transfer

Expression of the nascent RNA transcript is regulated by its interaction with a number of proteins. The misregulation of such interactions can often result in impaired cellular functions that can lead to cancer and a number of diseases. Thus, our understanding of RNA-protein interactions within the cellular context is essential for the development of novel diagnostic and therapeutic tools. While there are many in vitro methods that analyze RNA-protein interactions in vivo approaches are scarce. Here we established a method based on fluorescence resonance energy transfer (FRET), which we term RNA-binding mediated FRET (RB-FRET), which determines RNA-protein interaction inside cells and tested it on hnRNP H protein binding to its cognate RNA. Using two different approaches, we provide evidence that RB-FRET is sensitive enough to detect specific RNA-protein interactions in the cell, providing a powerful tool to study spatial and temporal localization of specific RNA-protein complexes.

Imaging transcription in living cells

The advent of new technologies for the imaging of living cells has made it possible to determine the properties of transcription, the kinetics of polymerase movement, the association of transcription factors, and the progression of the polymerase on the gene. We report here the current state of the field and the progress necessary to achieve a more complete understanding of the various steps in transcription. Our Consortium is dedicated to developing and implementing the technology to further this understanding.

Automated focusing of nuclei for time lapse experiments on single cells using holographic optical tweezers

Experiments on single cells are currently gaining more and more interest. Single cell studies often concerns the spatio-temporal distribution of fluorescent proteins inside living cells, visualized using fluorescence microscopy. In order to extract quantitative information from such experiments it is necessary to image the sample with high spatial and temporal resolution while keeping the photobleaching to a minimum. The analysis of the spatial distribution of proteins often requires stacks of images at each time point, which exposes the sample to unnecessary amounts of excitation light. In this paper we show how holographic optical tweezers combined with image analysis can be used to optimize the axial position of trapped cells in an array in order to bring the nuclei into a single imaging plane, thus eliminating the need for stacks of images and consequently reducing photobleaching. This allows more images to be collected, as well as increasing the time span and/or the time resolution in time lapse studies of single cells.

A relationship between mRNA expression levels and protein solubility in E. coli

Each step in the process of gene expression, from the transcription of DNA into mRNA to the folding and posttranslational modification of proteins, is regulated by complex cellular mechanisms. At the same time, stringent conditions on the physicochemical properties of proteins, and hence on the nature of their amino acids, are imposed by the need to avoid aggregation at the concentrations required for optimal cellular function. A relationship is therefore expected to exist between mRNA expression levels and protein solubility in the cell. By investigating such a relationship, we formulate a method that enables the prediction of the maximal levels of mRNA expression in Escherichia coli with an accuracy of 83% and of the solubility of recombinant human proteins expressed in E. coli with an accuracy of 86%.

Single live-cell imaging for systems biology

Understanding how mammalian cells function requires a dynamic perspective. However, owing to the complexity of signalling networks, these non-linear systems can easily elude human intuition. The central aim of systems biology is to improve our understanding of the temporal complexity of cell signalling pathways, using a combination of experimental and computational approaches. Live-cell imaging and computational modelling are compatible techniques which allow quantitative analysis of cell signalling pathway dynamics. Non-invasive imaging techniques, based on the use of various luciferases and fluorescent proteins, trace cellular events such as gene expression, protein-protein interactions and protein localization in cells. By employing a number of markers in a single assay, multiple parameters can be measured simultaneously in the same cell. Following acquisition using specialized microscopy, analysis of multi-parameter time-lapse images facilitates the identification of important qualitative and quantitative relationships-linking intracellular signalling, gene expression and cell fate.

Living with Irresolute Cell Lines in an Automated World

An automated cell-culture platform becomes the nucleus of an organization performing cell-based research. However, every cell-based project placed on the system brings unique challenges. With each cell line comes millions of years of evolutionary encumbrance and a genetic inclination driving unique phenotypic peculiarities. In vivo, diverse eukaryotic cells rely on their “mammalian host” for survival. An automated system must perform in vitro, the myriad actions needed to sustain multiple cell lines as well, hence becoming an “automated host.” Cells invariably, will endeavor to do as they please. Molding these cells into the operational bounds of a man-made system requires insight into the relationship between cell and machine.

Citing our own experiences, we will describe herein the use of the SelecT automated cell-culture platform (The Automation Partnership, Hertfordshire, England) in our discovery and preclinical profiling programs at Novartis. Achieving the balance between cells and the automated environment, and accommodating variable cell dynamics are discussed.

Interacting RNA polymerase motors on a DNA track: effects of traffic congestion and intrinsic noise on RNA synthesis

RNA polymerase (RNAP) is an enzyme that synthesizes a messenger RNA (mRNA) strand which is complementary to a single-stranded DNA template. From the perspective of physicists, an RNAP is a molecular motor that utilizes chemical energy input to move along the track formed by DNA. In many circumstances, which are described in this paper, a large number of RNAPs move simultaneously along the same track; we refer to such collective movements of the RNAPs as RNAP traffic. Here we develop a theoretical model for RNAP traffic by incorporating the steric interactions between RNAPs as well as the mechanochemical cycle of individual RNAPs during the elongation of the mRNA. By a combination of analytical and numerical techniques, we calculate the rates of mRNA synthesis and the average density profile of the RNAPs on the DNA track. We also introduce, and compute, two different measures of fluctuations in the synthesis of RNA. Analyzing these fluctuations, we show how the level of intrinsic noise in mRNA synthesis depends on the concentrations of the RNAPs as well as on those of some of the reactants and the products of the enzymatic reactions catalyzed by RNAP. We suggest appropriate experimental systems and techniques for testing our theoretical predictions.