Optimal Decoding of Cellular Identities in a Genetic Network.

In developing organisms, spatially prescribed cell identities are thought to be determined by the expression levels of multiple genes. Quantitative tests of this idea, however, require a theoretical framework capable of exposing the rules and precision of cell specification over developmental time. We use the gap gene network in the early fly embryo as an example to show how expression levels of the four gap genes can be jointly decoded into an optimal specification of position with 1% accuracy. The decoder correctly predicts, with no free parameters, the dynamics of pair-rule expression patterns at different developmental time points and in various mutant backgrounds. Precise cellular identities are thus available at the earliest stages of development, contrasting the prevailing view of positional information being slowly refined across successive layers of the patterning network. Our results suggest that developmental enhancers closely approximate a mathematically optimal decoding strategy.

Diverse Spatial Expression Patterns Emerge from Unified Kinetics of Transcriptional Bursting.

How transcriptional bursting relates to gene regulation is a central question that has persisted for more than a decade. Here, we measure nascent transcriptional activity in early Drosophila embryos and characterize the variability in absolute activity levels across expression boundaries. We demonstrate that boundary formation follows a common transcription principle: a single control parameter determines the distribution of transcriptional activity, regardless of gene identity, boundary position, or enhancer-promoter architecture. We infer the underlying bursting kinetics and identify the key regulatory parameter as the fraction of time a gene is in a transcriptionally active state. Unexpectedly, both the rate of polymerase initiation and the switching rates are tightly constrained across all expression levels, predicting synchronous patterning outcomes at all positions in the embryo. These results point to a shared simplicity underlying the apparently complex transcriptional processes of early embryonic patterning and indicate a path to general rules in transcriptional regulation.

Spatial and temporal organization of the genome: Current state and future aims of the 4D nucleome project.

The four-dimensional nucleome (4DN) consortium studies the architecture of the genome and the nucleus in space and time. We summarize progress by the consortium and highlight the development of technologies for (1) mapping genome folding and identifying roles of nuclear components and bodies, proteins, and RNA, (2) characterizing nuclear organization with time or single-cell resolution, and (3) imaging of nuclear organization. With these tools, the consortium has provided over 2,000 public datasets. Integrative computational models based on these data are starting to reveal connections between genome structure and function. We then present a forward-looking perspective and outline current aims to (1) delineate dynamics of nuclear architecture at different timescales, from minutes to weeks as cells differentiate, in populations and in single cells, (2) characterize cis-determinants and trans-modulators of genome organization, (3) test functional consequences of changes in cis- and trans-regulators, and (4) develop predictive models of genome structure and function.

Physics meets biology: The joining of two forces to further our understanding of cellular function.

Some biological questions are tough to solve through standard molecular and cell biological methods and naturally lend themselves to investigation by physical approaches. Below, a group of formally trained physicists discuss, among other things, how they apply physics to address biological questions and how physical approaches complement conventional biological approaches.

Sorting sloppy Sonic.

In the classic picture of morphogen-mediated patterning, cells acquire the correct spatial arrangement of specified fates by reading a precisely distributed gradient of morphogen. Xiong et al. now provide evidence for an alternate strategy-cells of the zebrafish neural tube actively sort to their correct positions following disordered specification by Sonic hedgehog.

Precise developmental gene expression arises from globally stochastic transcriptional activity.

Early embryonic patterning events are strikingly precise, a fact that appears incompatible with the stochastic gene expression observed across phyla. Using single-molecule mRNA quantification in Drosophila embryos, we determine the magnitude of fluctuations in the expression of four critical patterning genes. The accumulation of mRNAs is identical across genes and fluctuates by only ∼8% between neighboring nuclei, generating precise protein distributions. In contrast, transcribing loci exhibit an intrinsic noise of ∼45% independent of specific promoter-enhancer architecture or fluctuating inputs. Precise transcript distribution in the syncytium is recovered via straightforward spatiotemporal averaging, i.e., accumulation and diffusion of transcripts during nuclear cycles, without regulatory feedback. Common expression characteristics shared between genes suggest that fluctuations in mRNA production are context independent and are a fundamental property of transcription. The findings shed light on how the apparent paradox between stochastic transcription and developmental precision is resolved.

Transcriptional coupling of distant regulatory genes in living embryos.

The prevailing view of metazoan gene regulation is that individual genes are independently regulated by their own dedicated sets of transcriptional enhancers. Past studies have reported long-range gene-gene associations1-3, but their functional importance in regulating transcription remains unclear. Here we used quantitative single-cell live imaging methods to provide a demonstration of co-dependent transcriptional dynamics of genes separated by large genomic distances in living Drosophila embryos. We find extensive physical and functional associations of distant paralogous genes, including co-regulation by shared enhancers and co-transcriptional initiation over distances of nearly 250 kilobases. Regulatory interconnectivity depends on promoter-proximal tethering elements, and perturbations in these elements uncouple transcription and alter the bursting dynamics of distant genes, suggesting a role of genome topology in the formation and stability of co-transcriptional hubs. Transcriptional coupling is detected throughout the fly genome and encompasses a broad spectrum of conserved developmental processes, suggesting a general strategy for long-range integration of gene activity.

Growth produces coordination trade-offs in Trichoplax adhaerens, an animal lacking a central nervous system.

How collectives remain coordinated as they grow in size is a fundamental challenge affecting systems ranging from biofilms to governments. This challenge is particularly apparent in multicellular organisms, where coordination among a vast number of cells is vital for coherent animal behavior. However, the earliest multicellular organisms were decentralized, with indeterminate sizes and morphologies, as exemplified by Trichoplax adhaerens, arguably the earliest-diverged and simplest motile animal. We investigated coordination among cells in T. adhaerens by observing the degree of collective order in locomotion across animals of differing sizes and found that larger individuals exhibit increasingly disordered locomotion. We reproduced this effect of size on order through a simulation model of active elastic cellular sheets and demonstrate that this relationship is best recapitulated across all body sizes when the simulation parameters are tuned to a critical point in the parameter space. We quantify the trade-off between increasing size and coordination in a multicellular animal with a decentralized anatomy that shows evidence of criticality and hypothesize as to the implications of this on the evolution hierarchical structures such as nervous systems in larger organisms.

Structured foraging of soil predators unveils functional responses to bacterial defenses.

Predators and their foraging strategies often determine ecosystem structure and function. Yet, the role of protozoan predators in microbial soil ecosystems remains elusive despite the importance of these ecosystems to global biogeochemical cycles. In particular, amoebae-the most abundant soil protozoan predator of bacteria-remineralize soil nutrients and shape the bacterial community. However, their foraging strategies and their role as microbial ecosystem engineers remain unknown. Here, we present a multiscale approach, connecting microscopic single-cell analysis and macroscopic whole ecosystem dynamics, to expose a phylogenetically widespread foraging strategy, in which an amoeba population spontaneously partitions between cells with fast, polarized movement and cells with slow, unpolarized movement. Such differentiated motion gives rise to efficient colony expansion and consumption of the bacterial substrate. From these insights, we construct a theoretical model that predicts how disturbances to amoeba growth rate and movement disrupt their predation efficiency. These disturbances correspond to distinct classes of bacterial defenses, which allows us to experimentally validate our predictions. All considered, our characterization of amoeba foraging identifies amoeba mobility, and not amoeba growth, as the core determinant of predation efficiency and a key target for bacterial defense systems.

Latent space of a small genetic network: Geometry of dynamics and information.

The high-dimensional character of most biological systems presents genuine challenges for modeling and prediction. Here we propose a neural network-based approach for dimensionality reduction and analysis of biological gene expression data, using, as a case study, a well-known genetic network in the early Drosophila embryo, the gap gene patterning system. We build an autoencoder compressing the dynamics of spatial gap gene expression into a two-dimensional (2D) latent map. The resulting 2D dynamics suggests an almost linear model, with a small bare set of essential interactions. Maternally defined spatial modes control gap genes positioning, without the classically assumed intricate set of repressive gap gene interactions. This, surprisingly, predicts minimal changes of neighboring gap domains when knocking out gap genes, consistent with previous observations. Latent space geometries in maternal mutants are also consistent with the existence of such spatial modes. Finally, we show how positional information is well defined and interpretable as a polar angle in latent space. Our work illustrates how optimization of small neural networks on medium-sized biological datasets is sufficiently informative to capture essential underlying mechanisms of network function.

The many bits of positional information.

Half a century after Lewis Wolpert's seminal conceptual advance on how cellular fates distribute in space, we provide a brief historical perspective on how the concept of positional information emerged and influenced the field of developmental biology and beyond. We focus on a modern interpretation of this concept in terms of information theory, largely centered on its application to cell specification in the early Drosophila embryo. We argue that a true physical variable (position) is encoded in local concentrations of patterning molecules, that this mapping is stochastic, and that the processes by which positions and corresponding cell fates are determined based on these concentrations need to take such stochasticity into account. With this approach, we shift the focus from biological mechanisms, molecules, genes and pathways to quantitative systems-level questions: where does positional information reside, how it is transformed and accessed during development, and what fundamental limits it is subject to?

Trading bits in the readout from a genetic network.

In the regulation of gene expression, information of relevance to the organism is represented by the concentrations of transcription factor molecules. To extract this information the cell must effectively "measure" these concentrations, but there are physical limits to the precision of these measurements. We use the gap gene network in the early fly embryo as an example of the tradeoff between the precision of concentration measurements and the transmission of relevant information. For thresholded measurements we find that lower thresholds are more important, and fine tuning is not required for near-optimal information transmission. We then consider general sensors, constrained only by a limit on their information capacity, and find that thresholded sensors can approach true information theoretic optima. The information theoretic approach allows us to identify the optimal sensor for the entire gap gene network and to argue that the physical limitations of sensing necessitate the observed multiplicity of enhancer elements, with sensitivities to combinations rather than single transcription factors.

Eco-evolutionary significance of "loners".

Loners-individuals out of sync with a coordinated majority-occur frequently in nature. Are loners incidental byproducts of large-scale coordination attempts, or are they part of a mosaic of life-history strategies? Here, we provide empirical evidence of naturally occurring heritable variation in loner behavior in the model social amoeba Dictyostelium discoideum. We propose that Dictyostelium loners-cells that do not join the multicellular life stage-arise from a dynamic population-partitioning process, the result of each cell making a stochastic, signal-based decision. We find evidence that this imperfectly synchronized multicellular development is affected by both abiotic (environmental porosity) and biotic (signaling) factors. Finally, we predict theoretically that when a pair of strains differing in their partitioning behavior coaggregate, cross-signaling impacts slime-mold diversity across spatiotemporal scales. Our findings suggest that loners could be critical to understanding collective and social behaviors, multicellular development, and ecological dynamics in D. discoideum. More broadly, across taxa, imperfect coordination of collective behaviors might be adaptive by enabling diversification of life-history strategies.

Climatic differentiation in polyploid apomictic Ranunculus auricomus complex in Europe.

BACKGROUND: Polyploidy and apomixis are important factors influencing plant distributions often resulting in range shifts, expansions and geographical parthenogenesis. We used the Ranunculus auricomus complex as a model to asses if the past and present distribution and climatic preferences were determined by these phenomena. RESULTS: Ecological differentiation among diploids and polyploids was tested by comparing the sets of climatic variables and distribution modelling using 191 novel ploidy estimations and 561 literature data. Significant differences in relative genome size on the diploid level were recorded between the "auricomus" and "cassubicus" groups and several new diploid occurrences were found in Slovenia and Hungary. The current distribution of diploids overlapped with the modelled paleodistribution (22 kyr BP), except Austria and the Carpathians, which are proposed to be colonized later on from refugia in the Balkans. Current and historical presence of diploids from the R. auricomus complex is suggested also for the foothills of the Caucasus. Based on comparisons of the climatic preferences polyploids from the R. auricomus complex occupy slightly drier and colder habitats than the diploids. CONCLUSIONS: The change of reproductive mode and selection due to competition with the diploid ancestors may have facilitated the establishment of polyploids within the R. auricomus complex in environments slightly cooler and drier, than those tolerated by diploid ancestors. Much broader distribution of polyploid apomicts may have been achieved due to faster colonization mediated by uniparental reproductive system.

The embryo as a laboratory: quantifying transcription in Drosophila.

Transcriptional regulation of gene expression is fundamental to most cellular processes, including determination of cellular fates. Quantitative studies of transcription in cultured cells have led to significant advances in identifying mechanisms underlying transcriptional control. Recent progress allowed implementation of these same quantitative methods in multicellular organisms to ask how transcriptional regulation unfolds both in vivo and at the single molecule level in the context of embryonic development. Here we review some of these advances in early Drosophila development, which bring the embryo on par with its single celled counterparts. In particular, we discuss progress in methods to measure mRNA and protein distributions in fixed and living embryos, and we highlight some initial applications that lead to fundamental new insights about molecular transcription processes. We end with an outlook on how to further exploit the unique advantages that come with investigating transcriptional control in the multicellular context of development.

Morphogenesis at criticality.

Spatial patterns in the early fruit fly embryo emerge from a network of interactions among transcription factors, the gap genes, driven by maternal inputs. Such networks can exhibit many qualitatively different behaviors, separated by critical surfaces. At criticality, we should observe strong correlations in the fluctuations of different genes around their mean expression levels, a slowing of the dynamics along some but not all directions in the space of possible expression levels, correlations of expression fluctuations over long distances in the embryo, and departures from a Gaussian distribution of these fluctuations. Analysis of recent experiments on the gap gene network shows that all these signatures are observed, and that the different signatures are related in ways predicted by theory. Although there might be other explanations for these individual phenomena, the confluence of evidence suggests that this genetic network is tuned to criticality.

Dynamic regulation of eve stripe 2 expression reveals transcriptional bursts in living Drosophila embryos.

We present the use of recently developed live imaging methods to examine the dynamic regulation of even-skipped (eve) stripe 2 expression in the precellular Drosophila embryo. Nascent transcripts were visualized via MS2 RNA stem loops. The eve stripe 2 transgene exhibits a highly dynamic pattern of de novo transcription, beginning with a broad domain of expression during nuclear cycle 12 (nc12), and progressive refinement during nc13 and nc14. The mature stripe 2 pattern is surprisingly transient, constituting just ∼15 min of the ∼90-min period of expression. Nonetheless, this dynamic transcription profile faithfully predicts the limits of the mature stripe visualized by conventional in situ detection methods. Analysis of individual transcription foci reveals intermittent bursts of de novo transcription, with duration cycles of 4-10 min. We discuss a multistate model of transcription regulation and speculate on its role in the dynamic repression of the eve stripe 2 expression pattern during development.

From intracellular signaling to population oscillations: bridging size- and time-scales in collective behavior.

Collective behavior in cellular populations is coordinated by biochemical signaling networks within individual cells. Connecting the dynamics of these intracellular networks to the population phenomena they control poses a considerable challenge because of network complexity and our limited knowledge of kinetic parameters. However, from physical systems, we know that behavioral changes in the individual constituents of a collectively behaving system occur in a limited number of well-defined classes, and these can be described using simple models. Here, we apply such an approach to the emergence of collective oscillations in cellular populations of the social amoeba Dictyostelium discoideum. Through direct tests of our model with quantitative in vivo measurements of single-cell and population signaling dynamics, we show how a simple model can effectively describe a complex molecular signaling network at multiple size and temporal scales. The model predicts novel noise-driven single-cell and population-level signaling phenomena that we then experimentally observe. Our results suggest that like physical systems, collective behavior in biology may be universal and described using simple mathematical models.

Dynamic interpretation of maternal inputs by the Drosophila segmentation gene network.

Patterning of body parts in multicellular organisms relies on the interpretation of transcription factor (TF) concentrations by genetic networks. To determine the extent by which absolute TF concentration dictates gene expression and morphogenesis programs that ultimately lead to patterns in Drosophila embryos, we manipulate maternally supplied patterning determinants and measure readout concentration at the position of various developmental markers. When we increase the overall amount of the maternal TF Bicoid (Bcd) fivefold, Bcd concentrations in cells at positions of the cephalic furrow, an early morphological marker, differ by a factor of 2. This finding apparently contradicts the traditional threshold-dependent readout model, which predicts that the Bcd concentrations at these positions should be identical. In contrast, Bcd concentration at target gene expression boundaries is nearly unchanged early in development but adjusts dynamically toward the same twofold change as development progresses. Thus, the Drosophila segmentation gene network responds faithfully to Bcd concentration during early development, in agreement with the threshold model, but subsequently partially adapts in response to altered Bcd dosage, driving segmentation patterns toward their WT positions. This dynamic response requires other maternal regulators, such as Torso and Nanos, suggesting that integration of maternal input information is not achieved through molecular interactions at the time of readout but through the subsequent collective interplay of the network.

Positional information, in bits.

Cells in a developing embryo have no direct way of "measuring" their physical position. Through a variety of processes, however, the expression levels of multiple genes come to be correlated with position, and these expression levels thus form a code for "positional information." We show how to measure this information, in bits, using the gap genes in the Drosophila embryo as an example. Individual genes carry nearly two bits of information, twice as much as would be expected if the expression patterns consisted only of on/off domains separated by sharp boundaries. Taken together, four gap genes carry enough information to define a cell's location with an error bar of ~1 along the anterior/posterior axis of the embryo. This precision is nearly enough for each cell to have a unique identity, which is the maximum information the system can use, and is nearly constant along the length of the embryo. We argue that this constancy is a signature of optimality in the transmission of information from primary morphogen inputs to the output of the gap gene network.