Endogenous CRISPR/Cas9 arrays for scalable whole-organism lineage tracing.

The past decade has seen a renewed appreciation of the central importance of cellular lineages to many questions in biology (especially organogenesis, stem cells and tumor biology). This has been driven in part by a renaissance in genetic clonal-labeling techniques. Recent approaches are based on accelerated mutation of DNA sequences, which can then be sequenced from individual cells to re-create a 'phylogenetic' tree of cell lineage. However, current approaches depend on making transgenic alterations to the genome in question, which limit their application. Here, we introduce a new method that completely avoids the need for prior genetic engineering, by identifying endogenous CRISPR/Cas9 target arrays suitable for lineage analysis. In both mouse and zebrafish, we identify the highest quality compact arrays as judged by equal base composition, 5' G sequence, minimal likelihood of residing in the functional genome, minimal off targets and ease of amplification. We validate multiple high-quality endogenous CRISPR/Cas9 arrays, demonstrating their utility for lineage tracing. Our pragmatically scalable technique thus can produce deep and broad lineages in vivo, while removing the dependence on genetic engineering.

A spectrum of modularity in multi-functional gene circuits.

A major challenge in systems biology is to understand the relationship between a circuit's structure and its function, but how is this relationship affected if the circuit must perform multiple distinct functions within the same organism? In particular, to what extent do multi-functional circuits contain modules which reflect the different functions? Here, we computationally survey a range of bi-functional circuits which show no simple structural modularity: They can switch between two qualitatively distinct functions, while both functions depend on all genes of the circuit. Our analysis reveals two distinct classes: hybrid circuits which overlay two simpler mono-functional sub-circuits within their circuitry, and emergent circuits, which do not. In this second class, the bi-functionality emerges from more complex designs which are not fully decomposable into distinct modules and are consequently less intuitive to predict or understand. These non-intuitive emergent circuits are just as robust as their hybrid counterparts, and we therefore suggest that the common bias toward studying modular systems may hinder our understanding of real biological circuits.

Dynamics of gene circuits shapes evolvability.

To what extent does the dynamical mechanism producing a specific biological phenotype bias the ability to evolve into novel phenotypes? We use the interpretation of a morphogen gradient into a single stripe of gene expression as a model phenotype. Although there are thousands of three-gene circuit topologies that can robustly develop a stripe of gene expression, the vast majority of these circuits use one of just six fundamentally different dynamical mechanisms. Here we explore the potential for gene circuits that use each of these six mechanisms to evolve novel phenotypes such as multiple stripes, inverted stripes, and gradients of gene expression. Through a comprehensive and systematic analysis, we find that circuits that use alternative mechanisms differ in the likelihood of reaching novel phenotypes through mutation. We characterize the phenotypic transitions and identify key ingredients of the evolutionary potential, such as sensitive interactions and phenotypic hubs. Finally, we provide an intuitive understanding on how the modular design of a particular mechanism favors the access to novel phenotypes. Our work illustrates how the dynamical mechanism by which an organism develops constrains how it can evolve. It is striking that these dynamical mechanisms and their impact on evolvability can be observed even for such an apparently simple patterning task, performed by just three-node circuits.

The role of spatially controlled cell proliferation in limb bud morphogenesis.

Although the vertebrate limb bud has been studied for decades as a model system for spatial pattern formation and cell specification, the cellular basis of its distally oriented elongation has been a relatively neglected topic by comparison. The conventional view is that a gradient of isotropic proliferation exists along the limb, with high proliferation rates at the distal tip and lower rates towards the body, and that this gradient is the driving force behind outgrowth. Here we test this hypothesis by combining quantitative empirical data sets with computer modelling to assess the potential role of spatially controlled proliferation rates in the process of directional limb bud outgrowth. In particular, we generate two new empirical data sets for the mouse hind limb--a numerical description of shape change and a quantitative 3D map of cell cycle times--and combine these with a new 3D finite element model of tissue growth. By developing a parameter optimization approach (which explores spatial patterns of tissue growth) our computer simulations reveal that the observed distribution of proliferation rates plays no significant role in controlling the distally extending limb shape, and suggests that directional cell activities are likely to be the driving force behind limb bud outgrowth. This theoretical prediction prompted us to search for evidence of directional cell orientations in the limb bud mesenchyme, and we thus discovered a striking highly branched and extended cell shape composed of dynamically extending and retracting filopodia, a distally oriented bias in Golgi position, and also a bias in the orientation of cell division. We therefore provide both theoretical and empirical evidence that limb bud elongation is achieved by directional cell activities, rather than a PD gradient of proliferation rates.

Transfecting RNA quadruplexes results in few transcriptome perturbations.

Guanine-rich nucleic acid sequences can form four-stranded structures called G-quadruplexes. Previous studies showed that transfecting G-quadruplex DNA oligonucleotides inhibits proliferation in many cancer cell lines and can induce apoptosis. However, little is known about the effects of transfecting RNA quadruplexes. In this study, we transfected a G-quadruplex RNA oligonucleotide (GqRNA) into HEK293T cells and observed that it did not alter cell viability. Subsequent transcriptome expression profiling revealed that only two genes, EGR1 and FOS, were significantly altered in the presence of GqRNA (upregulated 2- to 4-fold). Sequence analysis showed that both genes contained putative quadruplex sequences (PQS) in their 3'-UTRs, immediately adjacent to the stop codons. Transfection of the EGR1 PQS as an RNA oligonucleotide also caused an increase in EGR1 expression. Similar motifs are found in a variety of genomes, but are relatively rare and have been missed by previous annotations. A bioinformatic analysis revealed stop codon-proximal enrichment of such motifs compared with the rest of the 3'-UTR, although these genes were not affected by RNA quadruplex transfection, and their function remains unknown. Overall, transfecting RNA quadruplexes results in relatively few alterations in gene expression.

In vitro whole-organ imaging: 4D quantification of growing mouse limb buds.

Quantitative mapping of the normal tissue dynamics of an entire developing mammalian organ has not been achieved so far but is essential to understand developmental processes and to provide quantitative data for computational modeling. We developed a four-dimensional (4D) imaging technique that can be used to quantitatively image tissue movements and dynamic GFP expression domains in a growing transgenic mouse limb by time-lapse optical projection tomography (OPT).

An atlas of gene regulatory networks reveals multiple three-gene mechanisms for interpreting morphogen gradients.

The interpretation of morphogen gradients is a pivotal concept in developmental biology, and several mechanisms have been proposed to explain how gene regulatory networks (GRNs) achieve concentration-dependent responses. However, the number of different mechanisms that may exist for cells to interpret morphogens, and the importance of design features such as feedback or local cell-cell communication, is unclear. A complete understanding of such systems will require going beyond a case-by-case analysis of real morphogen interpretation mechanisms and mapping out a complete GRN 'design space.' Here, we generate a first atlas of design space for GRNs capable of patterning a homogeneous field of cells into discrete gene expression domains by interpreting a fixed morphogen gradient. We uncover multiple very distinct mechanisms distributed discretely across the atlas, thereby expanding the repertoire of morphogen interpretation network motifs. Analyzing this diverse collection of mechanisms also allows us to predict that local cell-cell communication will rarely be responsible for the basic dose-dependent response of morphogen interpretation networks.

Author Correction: A strategy for effective latent HIV reactivation using subtherapeutic drug doses.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

A strategy for effective latent HIV reactivation using subtherapeutic drug doses.

Cell state switches underlie a plethora of biological phenomena and disease treatment strategies. Hence the ability to efficiently switch states in a chosen direction is of central importance in a number of scenarios. Increasing the concentration of an effector that results in a given switch is often limited by side effects. Approaches are thus increasingly sought to bypass these constraints, increasing the frequency of state switching without increasing the frequency of the side effect. Here, we employ dynamical systems theory to uncover a simple strategy as to how to maximize the probability of reactivating latent Human immunodeficiency virus (HIV) whilst maintaining minimal side effects. We demonstrate that continuous supply of an effector is significantly more likely to result in a switch with minimal side effects than the same effector supplied in temporally discrete doses. Importantly this continual dosage is likely to occur far below the Minimum effective dose at a concentration that has classically been thought subtherapeutic. We therefore suggest that in many interventional settings there exists potential to reduce drug dose much further than has previously been thought possible yet still maintaining efficacy.

A simple high throughput assay to evaluate water consumption in the fruit fly.

Water intake is essential for survival and thus under strong regulation. Here, we describe a simple high throughput system to monitor water intake over time in Drosophila. The design of the assay involves dehydrating fly food and then adding water back separately so flies either eat or drink. Water consumption is then evaluated by weighing the water vessel and comparing this back to an evaporation control. Our system is high throughput, does not require animals to be artificially dehydrated, and is simple both in design and implementation. Initial characterisation of homeostatic water consumption shows high reproducibility between biological replicates in a variety of experimental conditions. Water consumption was dependent on ambient temperature and humidity and was equal between sexes when corrected for mass. By combining this system with the Drosophila genetics tools, we could confirm a role for ppk28 and DopR1 in promoting water consumption, and through functional investigation of RNAseq data from dehydrated animals, we found DopR1 expression in the mushroom body was sufficient to drive consumption and enhance water taste sensitivity. Together, we provide a simple high throughput water consumption assay that can be used to dissect the cellular and molecular machinery regulating water homeostasis in Drosophila.

Sucralose Promotes Food Intake through NPY and a Neuronal Fasting Response.

Non-nutritive sweeteners like sucralose are consumed by billions of people. While animal and human studies have demonstrated a link between synthetic sweetener consumption and metabolic dysregulation, the mechanisms responsible remain unknown. Here we use a diet supplemented with sucralose to investigate the long-term effects of sweet/energy imbalance. In flies, chronic sweet/energy imbalance promoted hyperactivity, insomnia, glucose intolerance, enhanced sweet taste perception, and a sustained increase in food and calories consumed, effects that are reversed upon sucralose removal. Mechanistically, this response was mapped to the ancient insulin, catecholamine, and NPF/NPY systems and the energy sensor AMPK, which together comprise a novel neuronal starvation response pathway. Interestingly, chronic sweet/energy imbalance promoted increased food intake in mammals as well, and this also occurs through an NPY-dependent mechanism. Together, our data show that chronic consumption of a sweet/energy imbalanced diet triggers a conserved neuronal fasting response and increases the motivation to eat.

A Local, Self-Organizing Reaction-Diffusion Model Can Explain Somite Patterning in Embryos.

During somitogenesis in embryos, a posteriorly moving differentiation front arrests the oscillations of "segmentation clock" genes, leaving behind a frozen, periodic pattern of expression stripes. Both mathematical theories and experimental observations have invoked a "clock and wavefront" model to explain this phenomenon, in which long-range molecular gradients control the movement of the front and therefore the placement of the stripes in the embryo. Here, we develop a fundamentally different model-a progressive oscillatory reaction-diffusion (PORD) system driven by short-range interactions. In this model, posterior movement of the front is a local, emergent phenomenon that, in contrast to the clock and wavefront model, is not controlled by global positional information. The PORD model explains important features of somitogenesis, such as size regulation, that previous reaction-diffusion models could not explain. Moreover, the PORD and clock and wavefront models make different predictions about the results of FGF-inhibition and tissue-cutting experiments, and we demonstrate that the results of these experiments favor the PORD model.

Exome sequencing reveals a potential mutational trajectory and treatments for a specific pancreatic cancer patient.

Pancreatic cancer is the fourth biggest killer, and has one of the worst prognoses, of any cancer type. Approximately 95% of patients diagnosed with pancreatic cancer will not survive beyond 5 years post diagnosis, and these statistics have barely improved in over 40 years. Here, genomic changes in one particular patient with stage IV metastatic pancreatic cancer were explored to suggest a potential personalized treatment. In particular, exome sequencing of genomic DNA extracted from blood and the cancer biopsy was utilized with the aim of identifying mutational drivers of the cancer. This analysis revealed a splice site mutation in RBCK1 as the most promising driver of the cancer and a therapy based on a pan-cyclin-dependent kinase (pan-CDK) inhibitor, flavopiridol. This study suggests that drugs whose effectiveness is unclear for general populations of cancer sufferers should possibly be reconsidered for specific patients where the drug could be rationally argued to improve outcome.

Design principles of stripe-forming motifs: the role of positive feedback.

Interpreting a morphogen gradient into a single stripe of gene-expression is a fundamental unit of patterning in early embryogenesis. From both experimental data and computational studies the feed-forward motifs stand out as minimal networks capable of this patterning function. Positive feedback within gene networks has been hypothesised to enhance the sharpness and precision of gene-expression borders, however a systematic analysis has not yet been reported. Here we set out to assess this hypothesis, and find an unexpected result. The addition of positive-feedback can have different effects on two different designs of feed-forward motif- it increases the parametric robustness of one design, while being neutral or detrimental to the other. These results shed light on the abundance of the former motif and especially of mutual-inhibition positive feedback in developmental networks.

A unified design space of synthetic stripe-forming networks.

Synthetic biology is a promising tool to study the function and properties of gene regulatory networks. Gene circuits with predefined behaviours have been successfully built and modelled, but largely on a case-by-case basis. Here we go beyond individual networks and explore both computationally and synthetically the design space of possible dynamical mechanisms for 3-node stripe-forming networks. First, we computationally test every possible 3-node network for stripe formation in a morphogen gradient. We discover four different dynamical mechanisms to form a stripe and identify the minimal network of each group. Next, with the help of newly established engineering criteria we build these four networks synthetically and show that they indeed operate with four fundamentally distinct mechanisms. Finally, this close match between theory and experiment allows us to infer and subsequently build a 2-node network that represents the archetype of the explored design space.

Mechanistic explanations for restricted evolutionary paths that emerge from gene regulatory networks.

The extent and the nature of the constraints to evolutionary trajectories are central issues in biology. Constraints can be the result of systems dynamics causing a non-linear mapping between genotype and phenotype. How prevalent are these developmental constraints and what is their mechanistic basis? Although this has been extensively explored at the level of epistatic interactions between nucleotides within a gene, or amino acids within a protein, selection acts at the level of the whole organism, and therefore epistasis between disparate genes in the genome is expected due to their functional interactions within gene regulatory networks (GRNs) which are responsible for many aspects of organismal phenotype. Here we explore epistasis within GRNs capable of performing a common developmental function--converting a continuous morphogen input into discrete spatial domains. By exploring the full complement of GRN wiring designs that are able to perform this function, we analyzed all possible mutational routes between functional GRNs. Through this study we demonstrate that mechanistic constraints are common for GRNs that perform even a simple function. We demonstrate a common mechanistic cause for such a constraint involving complementation between counter-balanced gene-gene interactions. Furthermore we show how such constraints can be bypassed by means of "permissive" mutations that buffer changes in a direct route between two GRN topologies that would normally be unviable. We show that such bypasses are common and thus we suggest that unlike what was observed in protein sequence-function relationships, the "tape of life" is less reproducible when one considers higher levels of biological organization.

p53 Gene repair with zinc finger nucleases optimised by yeast 1-hybrid and validated by Solexa sequencing.

The tumor suppressor gene p53 is mutated or deleted in over 50% of human tumors. As functional p53 plays a pivotal role in protecting against cancer development, several strategies for restoring wild-type (wt) p53 function have been investigated. In this study, we applied an approach using gene repair with zinc finger nucleases (ZFNs). We adapted a commercially-available yeast one-hybrid (Y1H) selection kit to allow rapid building and optimization of 4-finger constructs from randomized PCR libraries. We thus generated novel functional zinc finger nucleases against two DNA sites in the human p53 gene, near cancer mutation 'hotspots'. The ZFNs were first validated using in vitro cleavage assays and in vivo episomal gene repair assays in HEK293T cells. Subsequently, the ZFNs were used to restore wt-p53 status in the SF268 human cancer cell line, via ZFN-induced homologous recombination. The frequency of gene repair and mutation by non-homologous end-joining was then ascertained in several cancer cell lines, using a deep sequencing strategy. Our Y1H system facilitates the generation and optimisation of novel, sequence-specific four- to six-finger peptides, and the p53-specific ZFN described here can be used to mutate or repair p53 in genomic loci.