Mechanical coordination is sufficient to promote tissue replacement during metamorphosis in Drosophila.

During development, cells coordinate to organize in coherent structures. Although it is now well established that physical forces are essential for implementing this coordination, the instructive roles of mechanical inputs are not clear. Here, we show that the replacement of the larval epithelia by the adult one in Drosophila demands the coordinated exchange of mechanical signals between two cell types, the histoblasts (adult precursors) organized in nests and the surrounding larval epidermal cells (LECs). An increasing stress gradient develops from the center of the nests toward the LECs as a result of the forces generated by histoblasts as they proliferate and by the LECs as they delaminate (push/pull coordination). This asymmetric radial coordination of expansive and contractile activities contributes to epithelial replacement. Our analyses support a model in which cell-cell mechanical communication is sufficient for the rearrangements that implement epithelial morphogenesis.

The complex three-dimensional organization of epithelial tissues.

Understanding the cellular organization of tissues is key to developmental biology. In order to deal with this complex problem, researchers have taken advantage of reductionist approaches to reveal fundamental morphogenetic mechanisms and quantitative laws. For epithelia, their two-dimensional representation as polygonal tessellations has proved successful for understanding tissue organization. Yet, epithelial tissues bend and fold to shape organs in three dimensions. In this context, epithelial cells are too often simplified as prismatic blocks with a limited plasticity. However, there is increasing evidence that a realistic approach, even from a reductionist perspective, must include apico-basal intercalations (i.e. scutoidal cell shapes) for explaining epithelial organization convincingly. Here, we present an historical perspective about the tissue organization problem. Specifically, we analyze past and recent breakthroughs, and discuss how and why simplified, but realistic, in silico models require scutoidal features to address key morphogenetic events.

Mechanics and self-organization in tissue development.

Self-organization is an all-important feature of living systems that provides the means to achieve specialization and functionality at distinct spatio-temporal scales. Herein, we review this concept by addressing the packing organization of cells, the sorting/compartmentalization phenomenon of cell populations, and the propagation of organizing cues at the tissue level through traveling waves. We elaborate on how different theoretical models and tools from Topology, Physics, and Dynamical Systems have improved the understanding of self-organization by shedding light on the role played by mechanics as a driver of morphogenesis. Altogether, by providing a historical perspective, we show how ideas and hypotheses in the field have been revisited, developed, and/or rejected and what are the open questions that need to be tackled by future research.

ANISE: an application to design mechanobiology simulations of planar epithelia.

SUMMARY: TiFoSi (Tissues Forces & Signaling) is an efficient computational tool for performing mechanobiology simulations of planar epithelia. A drawback of this tool is that it relies on an XML configuration file (input data) that can be cumbersome to set up and/or decode due to the endless possibilities of the software. Moreover, some modeling know-how is needed in order to provide equations that describe gene regulatory interactions. These factors limit the usability of this tool for users with a weak computational and/or mathematical background. Here, we introduce ANISE (grAphical coNfigurator of TiFoSi In Silico Experiments), a web-app that allows to easily setup the configuration of mechanobiology simulations using TiFoSi. The application covers all the configuration modules in TiFoSi comprehensively (from basic to advanced editing options) and uses a graphical approach (e.g. to build the modeling equations of gene regulatory networks). AVAILABILITY AND IMPLEMENTATION: http://github.com/lsym-uveg/anise (server: http://lsymserver.uv.es/lsym/ANISE).

TiFoSi: an efficient tool for mechanobiology simulations of epithelia.

MOTIVATION: Emerging phenomena in developmental biology and tissue engineering are the result of feedbacks between gene expression and cell biomechanics. In that context, in silico experiments are a powerful tool to understand fundamental mechanisms and to formulate and test hypotheses. RESULTS: Here, we present TiFoSi, a computational tool to simulate the cellular dynamics of planar epithelia. TiFoSi allows to model feedbacks between cellular mechanics and gene expression (either in a deterministic or a stochastic way), the interaction between different cell populations, the custom design of the cell cycle and cleavage properties, the protein number partitioning upon cell division, and the modeling of cell communication (juxtacrine and paracrine signaling). AVAILABILITY AND IMPLEMENTATION: http://tifosi.thesimbiosys.com. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Direct mapping of nanoscale compositional connectivity on intact cell membranes.

Lateral segregation of cell membranes is accepted as a primary mechanism for cells to regulate a diversity of cellular functions. In this context, lipid rafts have been conceptualized as organizing principle of biological membranes where underlying cholesterol-mediated selective connectivity must exist even at the resting state. However, such a level of nanoscale compositional connectivity has been challenging to prove. Here we used single-molecule near-field scanning optical microscopy to visualize the nanolandscape of raft ganglioside GM1 after tightening by its ligand cholera toxin (CTxB) on intact cell membranes. We show that CTxB tightening of GM1 is sufficient to initiate a minimal raft coalescence unit, resulting in the formation of cholesterol-dependent GM1 nanodomains < 120 nm in size. This particular arrangement appeared independent of cell type and GM1 expression level on the membrane. Simultaneous dual color high-resolution images revealed that GPI anchored and certain transmembrane proteins were recruited to regions proximal (< 150 nm) to CTxB-GM1 nanodomains without physical intermixing. Together with in silico experiments, our high-resolution data conclusively demonstrate the existence of raft-based interconnectivity at the nanoscale. Such a linked state on resting cell membranes constitutes thus an obligatory step toward the hierarchical evolution of large-scale raft coalescence upon cell activation.

Comprehensive profiling of neutralizing polyclonal sera targeting coxsackievirus B3.

Despite their fundamental role in resolving viral infections, our understanding of how polyclonal neutralizing antibody responses target non-enveloped viruses remains limited. To define these responses, we obtained the full antigenic profile of multiple human and mouse polyclonal sera targeting the capsid of a prototypical picornavirus, coxsackievirus B3. Our results uncover significant variation in the breadth and strength of neutralization sites targeted by individual human polyclonal responses, which contrasted with homogenous responses observed in experimentally infected mice. We further use these comprehensive antigenic profiles to define key structural and evolutionary parameters that are predictive of escape, assess epitope dominance at the population level, and reveal a need for at least two mutations to achieve significant escape from multiple sera. Overall, our data provide a comprehensive analysis of how polyclonal sera target a non-enveloped viral capsid and help define both immune dominance and escape at the population level.

Random field calibration with data on irregular grid for regional analyses: A case study on the bare carrying capacity of bats in Africa.

Many applications in science and engineering involve data defined at specific geospatial locations, which are often modeled as random fields. The modeling of a proper correlation function is essential for the probabilistic calibration of the random fields, but traditional methods were developed with the assumption to have observations with evenly spaced data. Available methods dealing with irregularly spaced data generally require either interpolation or computationally expensive solutions. Instead, we propose a simple approach based on least square regression to estimate the autocorrelation function. We first tested our methodology on an artificially produced dataset to assess the performance of our method. The accuracy of the method and its robustness to the level of noise in the data indicate that it is suitable for use in realistic problems. In addition, the methodology was used on a major application, the modeling of animal species connected with zoonotic diseases. Understanding the population dynamics of reservoirs of zoonotic diseases, such as bats, is a crucial first step to predict and prevent potential spillover of deadly viruses like Ebola. Due to the limited data on bats across Africa, their density and migrations can only be studied with probabilistic numerical models based on samples of the ecological bare carrying capacity (K0). For this purpose, the bare carrying capacity was modeled as a random field and its statistics calibrated with the available data. The bare carrying capacity of bats was found to be denser in central Africa. This is because climatic and environmental conditions are more suitable for the survival of bats. The proposed methodology for random field calibration was shown to be a promising approach, which can cope with large gaps in data and with complex applications involving large geographical areas and high resolution.

Dynamics and mechanical stability of the developing dorsoventral organizer of the wing imaginal disc.

Shaping the primordia during development relies on forces and mechanisms able to control cell segregation. In the imaginal discs of Drosophila the cellular populations that will give rise to the dorsal and ventral parts on the wing blade are segregated and do not intermingle. A cellular population that becomes specified by the boundary of the dorsal and ventral cellular domains, the so-called organizer, controls this process. In this paper we study the dynamics and stability of the dorsal-ventral organizer of the wing imaginal disc of Drosophila as cell proliferation advances. Our approach is based on a vertex model to perform in silico experiments that are fully dynamical and take into account the available experimental data such as: cell packing properties, orientation of the cellular divisions, response upon membrane ablation, and robustness to mechanical perturbations induced by fast growing clones. Our results shed light on the complex interplay between the cytoskeleton mechanics, the cell cycle, the cell growth, and the cellular interactions in order to shape the dorsal-ventral organizer as a robust source of positional information and a lineage controller. Specifically, we elucidate the necessary and sufficient ingredients that enforce its functionality: distinctive mechanical properties, including increased tension, longer cell cycle duration, and a cleavage criterion that satisfies the Hertwig rule. Our results provide novel insights into the developmental mechanisms that drive the dynamics of the DV organizer and set a definition of the so-called Notch fence model in quantitative terms.

Bacterial degrons in synthetic circuits.

Bacterial proteases are a promising post-translational regulation strategy in synthetic circuits because they recognize specific amino acid degradation tags (degrons) that can be fine-tuned to modulate the degradation levels of tagged proteins. For this reason, recent efforts have been made in the search for new degrons. Here we review the up-to-date applications of degradation tags for circuit engineering in bacteria. In particular, we pay special attention to the effects of degradation bottlenecks in synthetic oscillators and introduce mathematical approaches to study queueing that enable the quantitative modelling of proteolytic queues.

Estimation of Ebola's spillover infection exposure in Sierra Leone based on sociodemographic and economic factors.

Zoonotic diseases spread through pathogens-infected animal carriers. In the case of Ebola Virus Disease (EVD), evidence supports that the main carriers are fruit bats and non-human primates. Further, EVD spread is a multi-factorial problem that depends on sociodemographic and economic (SDE) factors. Here we inquire into this phenomenon and aim at determining, quantitatively, the Ebola spillover infection exposure map and try to link it to SDE factors. To that end, we designed and conducted a survey in Sierra Leone and implement a pipeline to analyze data using regression and machine learning techniques. Our methodology is able (1) to identify the features that are best predictors of an individual's tendency to partake in behaviors that can expose them to Ebola infection, (2) to develop a predictive model about the spillover risk statistics that can be calibrated for different regions and future times, and (3) to compute a spillover exposure map for Sierra Leone. Our results and conclusions are relevant to identify the regions in Sierra Leone at risk of EVD spillover and, consequently, to design and implement policies for an effective deployment of resources (e.g., drug supplies) and other preventative measures (e.g., educational campaigns).

A quantitative biophysical principle to explain the 3D cellular connectivity in curved epithelia.

Epithelial cell organization and the mechanical stability of tissues are closely related. In this context, it has been recently shown that packing optimization in bended or folded epithelia is achieved by an energy minimization mechanism that leads to a complex cellular shape: the "scutoid". Here, we focus on the relationship between this shape and the connectivity between cells. We use a combination of computational, experimental, and biophysical approaches to examine how energy drivers affect the three-dimensional (3D) packing of tubular epithelia. We propose an energy-based stochastic model that explains the 3D cellular connectivity. Then, we challenge it by experimentally reducing the cell adhesion. As a result, we observed an increment in the appearance of scutoids that correlated with a decrease in the energy barrier necessary to connect with new cells. We conclude that tubular epithelia satisfy a quantitative biophysical principle that links tissue geometry and energetics with the average cellular connectivity.

Interplay between intrinsic noise and the stochasticity of the cell cycle in bacterial colonies.

Herein we report on the effects that different stochastic contributions induce in bacterial colonies in terms of protein concentration and production. In particular, we consider for what we believe to be the first time cell-to-cell diversity due to the unavoidable randomness of the cell-cycle duration and its interplay with other noise sources. To that end, we model a recent experimental setup that implements a protein dilution protocol by means of division events to characterize the gene regulatory function at the single cell level. This approach allows us to investigate the effect of different stochastic terms upon the total randomness experimentally reported for the gene regulatory function. In addition, we show that the interplay between intrinsic fluctuations and the stochasticity of the cell-cycle duration leads to different constructive roles. On the one hand, we show that there is an optimal value of protein concentration (alternatively an optimal value of the cell cycle phase) such that the noise in protein concentration attains a minimum. On the other hand, we reveal that there is an optimal value of the stochasticity of the cell cycle duration such that the coherence of the protein production with respect to the colony average production is maximized. The latter can be considered as a novel example of the recently reported phenomenon of diversity induced resonance.

Self-sustained planar intercalations due to mechanosignaling feedbacks lead to robust axis extension during morphogenesis.

Tissue elongation is a necessary process in metazoans to implement their body plans that is not fully understood. Here we propose a mechanism based on the interplay between cellular mechanics and primordia patterning that results in self-sustained planar intercalations. Thus, we show that a location-dependent modulation of the mechanical properties of cells leads to robust axis extension. To illustrate the plausibility of this mechanism, we test it against different patterning models by means of computer simulations of tissues where we implemented mechano-signaling feedbacks. Our results suggest that robust elongation relies on a trade-off between cellular and tissue strains that is orchestrated through the cleavage orientation. In the particular context of axis extension in Turing-patterned tissues, we report that different directional cell activities cooperate synergetically to achieve elongation. Altogether, our findings help to understand how the axis extension phenomenon emerges from the dynamics of individual cells.

Mycobacterium Phage Butters-Encoded Proteins Contribute to Host Defense against Viral Attack.

A diverse set of prophage-mediated mechanisms protecting bacterial hosts from infection has been recently uncovered within cluster N mycobacteriophages isolated on the host, Mycobacterium smegmatis mc2155. In that context, we unveil a novel defense mechanism in cluster N prophage Butters. By using bioinformatics analyses, phage plating efficiency experiments, microscopy, and immunoprecipitation assays, we show that Butters genes located in the central region of the genome play a key role in the defense against heterotypic viral attack. Our study suggests that a two-component system, articulated by interactions between protein products of genes 30 and 31, confers defense against heterotypic phage infection by PurpleHaze (cluster A/subcluster A3) or Alma (cluster A/subcluster A9) but is insufficient to confer defense against attack by the heterotypic phage Island3 (cluster I/subcluster I1). Therefore, based on heterotypic phage plating efficiencies on the Butters lysogen, additional prophage genes required for defense are implicated and further show specificity of prophage-encoded defense systems.IMPORTANCE Many sequenced bacterial genomes, including those of pathogenic bacteria, contain prophages. Some prophages encode defense systems that protect their bacterial host against heterotypic viral attack. Understanding the mechanisms undergirding these defense systems is crucial to appreciate the scope of bacterial immunity against viral infections and will be critical for better implementation of phage therapy that would require evasion of these defenses. Furthermore, such knowledge of prophage-encoded defense mechanisms may be useful for developing novel genetic tools for engineering phage-resistant bacteria of industrial importance.

Noise-induced coherence in multicellular circadian clocks.

In higher organisms, circadian rhythms are generated by a multicellular genetic clock that is entrained very efficiently to the 24-h light-dark cycle. Most studies done so far of these circadian oscillators have considered a perfectly periodic driving by light, in the form of either a square wave or a sinusoidal modulation. However, in natural conditions, organisms are subject to nonnegligible fluctuations in the light level all through the daily cycle. In this article, we investigate how the interplay between light fluctuations and intercellular coupling affects the dynamics of the collective rhythm in a large ensemble of nonidentical, globally coupled cellular clocks modeled as Goodwin oscillators. On the basis of experimental considerations, we assume an inverse dependence of the cell-cell coupling strength on the light intensity, in such a way that the larger the light intensity, the weaker the coupling. Our results show a noise-induced rhythm generation for constant light intensities at which the clock is arrhythmic in the noise-free case. Importantly, the rhythm shows a resonancelike phenomenon as a function of the noise intensity. Such improved coherence can be only observed at the level of the overt rhythm and not at the level of the individual oscillators, thus suggesting a cooperative effect of noise, coupling, and the emerging synchronization between the oscillators.

A non-linear analysis of Turing pattern formation.

Reaction-diffusion schemes are widely used to model and interpret phenomena in various fields. In that context, phenomena driven by Turing instabilities are particularly relevant to describe patterning in a number of biological processes. While the conditions that determine the appearance of Turing patterns and their wavelength can be easily obtained by a linear stability analysis, the estimation of pattern amplitudes requires cumbersome calculations due to non-linear terms. Here we introduce an expansion method that makes possible to obtain analytical, approximated, solutions of the pattern amplitudes. We check and illustrate the reliability of this methodology with results obtained from numerical simulations.

A Cell Segmentation/Tracking Tool Based on Machine Learning.

The ability to gain quantifiable, single-cell data from time-lapse microscopy images is dependent upon cell segmentation and tracking. Here, we present a detailed protocol for obtaining quality time-lapse movies and introduce a method to identify (segment) and track cells based on machine learning techniques (Fiji's Trainable Weka Segmentation) and custom, open-source Python scripts. To provide a hands-on experience, we provide datasets obtained using the aforementioned protocol.

A spatial toggle switch drives boundary formation in development.

Herein we introduce a multicellular network motif that performs as a spatial toggle switch and explains how boundary formation can be faithfully accomplished in developmental processes. Importantly, we show that expression and activity patterns of proteins must be simultaneously characterized for a proper understanding and description of the underlying mechanism. Our in silico experiments, in agreement with in vivo results, evaluate different genetic backgrounds and shed light on the dynamics of boundary formation. In addition, we provide an estimation of relevant biological parameters and a robustness analysis.

A Predictive Spatial Distribution Framework for Filovirus-Infected Bats.

Tools with predictive capabilities in regards of filovirus outbreaks are mainly anthropocentric and have disregarded the ecological dimension of the problem. Here we contribute to shift the current paradigm by studying the dynamics of the putative main zoonotic niche of filoviruses, bats, and its link to environmental drivers. We propose a framework that combines data analysis, modeling, and the evaluation of sources of variability. We implement a regression analysis using factual data to correlate environmental parameters and the presence of bats to find the distribution of resources. The information inferred by the regression is fed into a compartmental model that describes the infection state. We also account for the lack of knowledge of some parameters using a sampling/averaging technique. As a result we estimate the spatio-temporal densities of bats. Importantly, we show that our approach is able to predict where and when an outbreak is likely to appear when tested against recent epidemic data in the context of Ebola. Our framework highlights the importance of considering the feedback between the ecology and the environment in zoonotic models and sheds light on the mechanisms to propagate filoviruses geographically. We expect that our methodology can help to design prevention policies and be used as a predictive tool in the context of zoonotic diseases associated to filoviruses.