Promoter-mediated diversification of transcriptional bursting dynamics following gene duplication.

During the evolution of gene families, functional diversification of proteins often follows gene duplication. However, many gene families expand while preserving protein sequence. Why do cells maintain multiple copies of the same gene? Here we have addressed this question for an actin family with 17 genes encoding an identical protein. The genes have divergent flanking regions and are scattered throughout the genome. Surprisingly, almost the entire family showed similar developmental expression profiles, with their expression also strongly coupled in single cells. Using live cell imaging, we show that differences in gene expression were apparent over shorter timescales, with family members displaying different transcriptional bursting dynamics. Strong "bursty" behaviors contrasted steady, more continuous activity, indicating different regulatory inputs to individual actin genes. To determine the sources of these different dynamic behaviors, we reciprocally exchanged the upstream regulatory regions of gene family members. This revealed that dynamic transcriptional behavior is directly instructed by upstream sequence, rather than features specific to genomic context. A residual minor contribution of genomic context modulates the gene OFF rate. Our data suggest promoter diversification following gene duplication could expand the range of stimuli that regulate the expression of essential genes. These observations contextualize the significance of transcriptional bursting.

Multiple cell and population-level interactions with mouse embryonic stem cell heterogeneity.

Much of development and disease concerns the generation of gene expression differences between related cells sharing similar niches. However, most analyses of gene expression only assess population and time-averaged levels of steady-state transcription. The mechanisms driving differentiation are buried within snapshots of the average cell, lacking dynamic information and the diverse regulatory history experienced by individual cells. Here, we use a quantitative imaging platform with large time series data sets to determine the regulation of developmental gene expression by cell cycle, lineage, motility and environment. We apply this technology to the regulation of the pluripotency gene Nanog in mouse embryonic stem cells. Our data reveal the diversity of cell and population-level interactions with Nanog dynamics and heterogeneity, and how this regulation responds to triggers of pluripotency. Cell cycles are highly heterogeneous and cycle time increases with Nanog reporter expression, with longer, more variable cycle times as cells approach ground-state pluripotency. Nanog reporter expression is highly stable over multiple cell generations, with fluctuations within cycles confined by an attractor state. Modelling reveals an environmental component to expression stability, in addition to any cell-autonomous behaviour, and we identify interactions of cell density with both cycle behaviour and Nanog. Rex1 expression dynamics showed shared and distinct regulatory effects. Overall, our observations of multiple partially overlapping dynamic heterogeneities imply complex cell and environmental regulation of pluripotent cell behaviour, and suggest simple deterministic views of stem cell states are inappropriate.

Modeling of Noisy Spindle Dynamics Reveals Separable Contributions to Achieving Correct Orientation.

The mechanisms by which the mammalian mitotic spindle is guided to a predefined orientation through microtubule-cortex interactions have recently received considerable interest, but there has been no dynamic model that describes spindle movements toward the preferred axis in human cells. Here, we develop a dynamic model based on stochastic activity of cues anisotropically positioned around the cortex of the mitotic cell and we show that the mitotic spindle does not reach equilibrium before chromosome segregation. Our model successfully captures the characteristic experimental behavior of noisy spindle rotation dynamics in human epithelial cells, including a weak underlying bias in the direction of rotation, suppression of motion close to the alignment axis, and the effect of the aspect ratio of the interphase cell shape in defining the final alignment axis. We predict that the force exerted per cue has a value that minimizes the deviation of the spindle from the predefined axis. The model has allowed us to systematically explore the parameter space around experimentally relevant configurations, and predict the mechanistic function of a number of established regulators of spindle orientation, highlighting how physical modeling of a noisy system can lead to functional biological understanding. We provide key insights into measurable parameters in live cells that can help distinguish between mechanisms of microtubule and cortical-cue interactions that jointly control the final orientation of the spindle.

Passive microrheology of solvent-induced fibrillar protein networks.

Particle tracking microrheology (PTM) has been used to study the sol-gel transition in solvent-induced fibrillar beta-lactoglobulin gels at room temperature and pH 7. The passive nature of microrheology allowed measurements to be made around and below the critical gelation concentration. The method of superposition introduced by Larsen and Furst (Larsen, T. H.; Furst, E. M. Phys. Rev. Lett. 2008, 100, 146001) was applied to the one-particle mean square displacement (MSD), yielding a critical relaxation exponent of n = 0.58 at concentrations close to the measured critical concentration of 4% (w/v). At a higher concentration of 12% (w/v), n was observed to decrease. The pregel and gel master curves were used to find the viscoelastic moduli over 8 decades of frequency. Combined with the measured shift factors, this allowed cure curves at 1 Hz to be constructed for direct comparison with results from bulk rheology. Time-independent modulus superposition was found for all concentrations. Good agreement for concentration scaling was found between the traditional methods for characterizing gels and the recently described microrheological determination of the gel time and critical behavior.

IA-Lab: A MATLAB framework for efficient microscopy image analysis development, applied to quantifying intracellular transport of internalized peptide-drug conjugate.

This work presents a MATLAB-based software package for high-throughput microscopy image analysis development, making such development more accessible for a large user community. The toolbox provides a GUI and a number of analysis workflows, and can serve as a general framework designed to allow for easy extension. For a new application, only a minor part of the object-oriented code needs to be replaced by new components, making development efficient. This makes it possible to quickly develop solutions for analysis not available in existing tools. We show its use in making a tool for quantifying intracellular transport of internalized peptide-drug conjugates. The code is freely available as open source on GitHub (https://github.com/amcorrigan/ia-lab).

Introducing an automated high content confocal imaging approach for Organs-on-Chips.

Organ-Chips are micro-engineered systems that aim to recapitulate the organ microenvironment. Implementation of Organ-Chips within the pharmaceutical industry aims to improve the probability of success of drugs reaching late stage clinical trial by generating models for drug discovery that are of human origin and have disease relevance. We are adopting the use of Organ-Chips for enhancing pre-clinical efficacy and toxicity evaluation and prediction. Whilst capturing cellular phenotype via imaging in response to drug exposure is a useful readout in these models, application has been limited due to difficulties in imaging the chips at scale. Here we created an end-to-end, automated workflow to capture and analyse confocal images of multicellular Organ-Chips to assess detailed cellular phenotype across large batches of chips. By automating this process, we not only reduced acquisition time, but we also minimised process variability and user bias. This enabled us to establish, for the first time, a framework of statistical best practice for Organ-Chip imaging, creating the capability of using Organ-Chips and imaging for routine testing in drug discovery applications that rely on quantitative image data for decision making. We tested our approach using benzbromarone, whose mechanism of toxicity has been linked to mitochondrial damage with subsequent induction of apoptosis and necrosis, and staurosporine, a tool inducer of apoptosis. We also applied this workflow to assess the hepatotoxic effect of an active AstraZeneca drug candidate illustrating its applicability in drug safety assessment beyond testing tool compounds. Finally, we have demonstrated that this approach could be adapted to Organ-Chips of different shapes and sizes through application to a Kidney-Chip.

Generation of Single-Cell Transcript Variability by Repression.

Gene expression levels vary greatly within similar cells, even within clonal cell populations [1]. These spontaneous expression differences underlie cell fate diversity in both differentiation and disease [2]. The mechanisms responsible for generating expression variability are poorly understood. Using single-cell transcriptomics, we show that transcript variability emerging during Dictyostelium differentiation is driven predominantly by repression rather than activation. The increased variability of repressed genes was observed over a broad range of expression levels, indicating that variability is actively imposed and not a passive statistical effect of the reduced numbers of molecules accompanying repression. These findings can be explained by a simple model of transcript production, with expression controlled by the frequency, rather than the magnitude, of transcriptional firing events. Our study reveals that the generation of differences between cells can be a direct consequence of the basic mechanisms of transcriptional regulation.

A continuum model of transcriptional bursting.

Transcription occurs in stochastic bursts. Early models based upon RNA hybridisation studies suggest bursting dynamics arise from alternating inactive and permissive states. Here we investigate bursting mechanism in live cells by quantitative imaging of actin gene transcription, combined with molecular genetics, stochastic simulation and probabilistic modelling. In contrast to early models, our data indicate a continuum of transcriptional states, with a slowly fluctuating initiation rate converting the gene between different levels of activity, interspersed with extended periods of inactivity. We place an upper limit of 40 s on the lifetime of fluctuations in elongation rate, with initiation rate variations persisting an order of magnitude longer. TATA mutations reduce the accessibility of high activity states, leaving the lifetime of on- and off-states unchanged. A continuum or spectrum of gene states potentially enables a wide dynamic range for cell responses to stimuli.

Quantitative measurement of transcription dynamics in living cells.

In a wide range of organisms the kinetics of transcription have been found to be noisy, with "bursts" or "pulses" of transcription interspersed with irregular periods of inactivity. The in vivo analysis of transcription dynamics can be most directly monitored using RNA stem loop motifs derived from MS2 and other bacteriophages. Here we describe the implementation of the MS2 RNA detection system and the steps required for precise measurement of transcription dynamics in highly motile cells. Automated image processing techniques are used to track large numbers of cells and measure transcription in a systematic and unbiased manner. We discuss popular methods for automatic image segmentation and frame-to-frame tracking of cells, and the considerations required to make measurements as quantitatively as possible.

Regulation of transcriptional bursting by a naturally oscillating signal.

Transcription is highly stochastic, occurring in irregular bursts. For temporal and spatial precision of gene expression, cells must somehow deal with this noisy behavior. To address how this is achieved, we investigated how transcriptional bursting is entrained by a naturally oscillating signal, by direct measurement of transcription together with signal dynamics in living cells. We identify a Dictyostelium gene showing rapid transcriptional oscillations with the same period as extracellular cAMP signaling waves. Bursting approaches antiphase to cAMP waves, with accelerating transcription cycles during differentiation. Although coupling between signal and transcription oscillations was clear at the population level, single-cell transcriptional bursts retained considerable heterogeneity, indicating that transcription is not governed solely by signaling frequency. Previous studies implied that burst heterogeneity reflects distinct chromatin states. Here we show that heterogeneity is determined by multiple intrinsic and extrinsic cues and is maintained by a transcriptional persistence. Unusually for a persistent transcriptional behavior, the lifetime was only 20 min, with rapid randomization of transcriptional state by the response to oscillatory signaling. Linking transcription to rapid signaling oscillations allows reduction of gene expression heterogeneity by temporal averaging, providing a mechanism to generate precision in cell choices during development.

Imaging nascent RNA dynamics in Dictyostelium.

Dictyostelium cells have great utility for live imaging of single gene transcriptional dynamics. The cells allow efficient molecular genetics, for targeting of RNA reporters and fluorescent proteins to individual, defined loci. Dictyostelium cells share many signalling, chromatin and nuclear characteristics of larger eukaryotes, yet the cells have a relatively simple scattered differentiation programme, allowing imaging of transcriptional events in the context of stochastic developmental choices. This review will detail the methods and considerations for imaging nascent RNA dynamics at single genes in living Dictyostelium cells.

Automated tracking of mitotic spindle pole positions shows that LGN is required for spindle rotation but not orientation maintenance.

Spindle orientation defines the plane of cell division and, thereby, the spatial position of all daughter cells. Here, we develop a live cell microscopy-based methodology to extract spindle movements in human epithelial cell lines and study how spindles are brought to a pre-defined orientation. We show that spindles undergo two distinct regimes of movements. Spindles are first actively rotated toward the cells' long-axis and then maintained along this pre-defined axis. By quantifying spindle movements in cells depleted of LGN, we show that the first regime of rotational movements requires LGN that recruits cortical dynein. In contrast, the second regime of movements that maintains spindle orientation does not require LGN, but is sensitive to 2ME2 that suppresses microtubule dynamics. Our study sheds first insight into spatially defined spindle movement regimes in human cells, and supports the presence of LGN and dynein independent cortical anchors for astral microtubules.

The formation of nematic liquid crystal phases by hen lysozyme amyloid fibrils.

Amyloid fibrils are a polymeric aggregate of protein. The fibrils are typically on the order of micrometers long, with widths of 10-20 nm. They are generally regarded as stiff, and nonbranching. It is well-known that similar synthetic polymers and biopolymers such as DNA and polysaccharides, have a tendency to form liquid crystalline phases when incubated under appropriate conditions. Here we show that amyloid fibrils from the protein hen lysozyme can similarly form liquid crystal phases. The most common phase observed is the nematic. Alignment can persist for several centimeters. When the fibrils are freeze-thawed to shorten them, similar phases form but at higher concentrations, confirming the importance of the aspect ratio of the fibrils. Freeze-thawed fibrils are also seen to form "tactoids", discrete liquid crystalline structures. The addition of NaCl to the solutions appears to only have a minor effect, while the effect of pH appears much more significant. We propose that the consideration of amyloid fibrils as polymer analogues should open new routes to explore in the burgeoning field of biomaterials.