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.Evolution occurs through mutations on existing genotypes, potentially transforming the original phenotype or trait into a novel one, with latent beneficial consequences. It is a fundamental problem in biology to understand the relationship between a genotype and the associated phenotypes accessible through mutations, in other words, its evolvability. From the many definitions of evolvability (1, 2), we refer here to the ability of genotypes to access novel phenotypes, irrespective of the subsequent process of natural selection.To understand how a phenotype evolves we need to consider that a huge number of distinct genotypes can achieve that same phenotype. For example, hundreds of distinct RNA sequences fold in the same secondary structure (3), as do proteins in their 3D structure (4). Similarly, distinct gene regulatory architectures can produce the same gene expression pattern (5, 6) or temporal behavior (7, 8). However, among these genotypes, some are more evolvable than others. The existing studies have targeted two key drivers of evolvability: a genotype’s design and a genotype’s location within a neutral space.A first class of studies focuses on a circuit’s general architectural features, such as feed-back or feed-forward loops, revealing that these distinct families of designs or motifs differ in their evolvability (9, 10). The second class of studies centers not on single designs but on the whole collection of genotypes capable of producing the same phenotype. These genotypes with a common phenotype form a region in genotype space termed a neutral space or neutral network (3), as mutations within this region produce no change in the phenotype.As revealed by many studies, the existence of neutral spaces has two major consequences to the evolutionary process. First, these neutral spaces often appear as fully connected and dense regions (11–13). Therefore, although genotypes internal to the neutral space are highly robust to mutations (i.e., not evolvable), only genotypes close to the edges of the neutral space might access novel phenotypes. From this perspective, neutral mutations and thus the process of neutral drift can generate cryptic genetic variation (14) by moving a species closer to the edges of the neutral space into a more evolvable state (12, 15). Second, different positions in genotype space give access to distinct novel phenotypes. Large neutral spaces percolate through genotype space, providing access to a diversity of novel phenotypes from different genotypes (11–13). In a nutshell, the accessible innovations are critically determined by a genotype’s position in genotype space (16) (Fig. 1).Open in a separate windowFig. 1.Phenotype-based view on evolvability. (A) Evolvability accounts for the accessible novel phenotypes, whereas developmental constraints imply that certain hypothetical forms are not possible: phenotype 2 (purple) is not available by gradual mutation. (B) Innovations accessible from a given genotype constitute its phenotypic neighborhood. The arrangement and diversity of this neighborhood is a measure of the genotype’s evolvability (16). Genotype space is high dimensional, but we schematically represent it here in 2D for illustrative purposes.Although the abovementioned features of genotype-phenotype maps have been much studied, another important aspect of the system has thus far been neglected. None of the existing studies addressed the impact of the underlying dynamical mechanism of a gene circuit on its evolvability. By mechanism, we mean the causal dynamics responsible for the trajectory of the system (i.e., the spatiotemporal course of gene expression) resulting in the final phenotype. In addition to the increasing awareness that dynamics itself is a decisive property of gene circuits (17), several specific observations led us to hypothesize that dynamics does impact on evolvability.First, to achieve a given biological function, a gene circuit uses one of few fundamental solutions referred to as dynamical mechanisms (5–7, 18–20). More specifically, circuits with the same underlying dynamical mechanism share a common arrangement of phase portraits (20, 21). Second, Cotterell and Sharpe (6) revealed that, for a simple patterning function, it is not possible to smoothly and functionally transition from one mechanism to another. That is, in contrast to the common view (11–13), this particular neutral space does not form a single fully connected region when the underlying mechanism is taken into account. Instead, the neutral space for the simple patterning function studied by Cotterell and Sharpe (6) breaks up into scattered islands of genotypes characterized by distinct underlying mechanisms. These observations suggest that evolvability may be constrained specifically by the dynamical mechanism of the gene circuit. As neutral spaces can be broken up into a discrete collection of separated islands, the process of neutral drift may be limited to these mechanism-specific regions.To assess the impact of dynamical mechanisms, we chose to study circuits that control spatial (multicellular) gene expression patterns. It is well established in developmental biology that the spatial organization of gene expression orchestrates cell differentiation. Their diversification causes evolution of both modest morphological traits, such as novel pigmentation patterns (22), and major evolutionary breakthroughs, such as new body structures (23). Here we chose to address the interpretation of a morphogen gradient by a field of cells into different cell fates (5–7, 18, 24–27) (Fig. 2A), a critical patterning event in embryo’s morphogenesis (28). We build on the work of Cotterell and Sharpe (6), who extracted six fundamental mechanisms for this patterning task: Bistable, Incoherent feed-forward, Mutual Inhibition, Overlapping Domains, Classical, and Frozen Oscillator (Fig. 2B and SI Appendix, Fig. S1).Open in a separate windowFig. 2.Alternative mechanisms to achieve a single phenotype. (A) Within the French Flag conceptual framework, a preestablished fixed concentration gradient (input) is interpreted by a one-dimensional row of cells into different cell fates through a threshold-dependent mechanism. Additionally, cells communicate to one another through diffusive gene products (dashed arrows). We exhaustively enumerate all possible three-gene circuit topologies and sample large numbers of genotypes (i.e., parameter values; SI Appendix, Methods). Solutions of our search are genotypes able to interpret the morphogen gradient into a band of gene expression (6). Similar exhaustive approaches have being adopted for exploring a variety of biological functions, such as temporal behaviors (7, 25) or other spatial patterning functions (5, 18). (B) A stripe-forming circuit uses one of six distinct mechanisms (6), each mechanism uses a distinct gene expression dynamics in space and time to reach the same phenotype. Importantly, Mutual Inhibition (bicoid-hunchback-knirps), Incoherent feed-forward (caudal-knirps-giant), and Classical (hunchback-krüppel-knirps) are involved in Drosophila anterior-posterior patterning (26), whereas Incoherent feed-forward controls the mesoderm inducer Xenopus Brachyury (27).For the current study, we analyzed each of these six mechanisms independently and obtained a mechanism-specific measure of evolvability. We found that, indeed, the likelihood of accessing distinct phenotypic innovations is different for each dynamical mechanism, despite the fact that they all produce the same phenotype. Our analysis uncovers key features of the mechanistic neutral spaces and provides useful insight into how phenotypic transitions and thus innovations occur.     

Acute administration of alprazolam, a benzodiazepine activating GABA receptors, inhibits cortisol secretion in patients with subclinical but not overt Cushing’s syndrome

The purpose of this study is to verify whether acute pre-treatment with alprazolam (ALP), a benzodiazepine that inhibits HPA secretion in normal subjects, could better characterize patients with subclinical Cushing’s syndrome (SCS) than the 1-mg dexamethasone test (DST). In 22 patients with SCS, 10 with overt Cushing’s syndrome (CS), 11 with non-functioning adrenal incidentalomas (NF) and 14 normal subjects (NS) we studied the effect of ALP (1 mg, p.o. at 2300 hours) on cortisol levels after 1-mg DST. Cortisol levels (mean ± SEM) after DST were lower (P = 0.012) in SCS (3.9 ± 0.3 μg/dl) than in overt CS (10.4 ± 1.9 μg/dl), while they were higher (P = 0.0005) than in NF (1.1 ± 0.1 μg/dl) and NS (1.5 ± 0.1 μg/dl). After ALP pre-treatment, cortisol levels further decreased (P = 0.004) in SCS (3.0 ± 0.3 μg/dl), but neither in CS (9.3 ± 1.3 μg/dl) nor in NF (1.3 ± 0.1 μg/dl) and in NS (1.3 ± 0.1 μg/dl). In SCS, cortisol levels after ALP + 1-mg DST persisted lower (P = 0.0005) than those in CS, but higher (P = 0.0005) than those in NF and NS. Considering individual cases, ALP pre-treatment reduced cortisol levels <3 and <1.8 μg/dl in 50 and 23 % of SCS patients, respectively. ALP amplifies the cortisol inhibition exerted by 1-mg DST in patients with SCS but not in those with CS. The clinical usefulness of ALP to increase the sensitivity of 1-mg DST to identify true autonomous cortisol release in patients with adrenal incidentalomas as well as to predict different clinical outcomes remains to be clarified.     

Supported Membranes Meet Flat Fluidics: Monitoring Dynamic Cell Adhesion on Pump-Free Microfluidics Chips Functionalized with Supported Membranes Displaying Mannose Domains

In this paper we demonstrate the combination of supported membranes and so-called flat microfluidics, which enables one to manipulate liquids on flat chip surfaces via “inverse piezoelectric effect”. Here, an alternating external electric field applied to the inter-digital transducers excites a surface acoustic wave on a piezoelectric substrate. Employing lithographic patterning of self-assembled monolayers of alkoxysilanes, we successfully confine a free-standing, hemi-cylindrical channel with the volume of merely 7 µL . The experimentally determined maximum flow velocity scales linearly with the acoustic power, suggesting that our current setup can drive liquids at the speed of up to 7 cm/s (corresponding to a shear rate of 280 s⁻¹) without applying high pressures using a fluidic pump. After the establishment of the functionalization of fluidic chip surfaces with supported membranes, we deposited asymmetric supported membranes displaying well-defined mannose domains and monitored the dynamic adhesion of E. Coli HB101 expressing mannose-binding receptors. Despite of the further technical optimization required for the quantitative analysis, the obtained results demonstrate that the combination of supported membranes and flat fluidics opens a large potential to investigate dynamic adhesion of cells on biofunctional membrane surfaces with the minimum amount of samples, without any fluidic pump.     

Marine and Agro-Industrial By-Products Valorization Intended for Topical Formulations in Wound Healing Applications

Over the past years, research attention has been focusing more on waste-derived, naturally derived, and renewable materials, in the view of a more sustainable economy. In this work, different topical formulations were obtained from the valorization of marine and agro-industrial by-products and the use of Carbopol 940 as gelling agent. In particular, the combination of extracts obtained from the marine snail, Rapanosa venosa, with Cladophora vagabunda and grape pomace extracts, was investigated for wound healing purposes. Rapana venosa has demonstrated wound healing properties and antioxidant activity. Similarly, grape pomace extracts have been shown to accelerate the healing process. However, their synergic use has not been explored yet. To this aim, four different formulations were produced. Three formulations differed for the presence of a different extract of Rapana venosa: marine collagen, marine gelatin, and collagen hydrolysate, while another formulation used mammalian gelatin as further control. Physico-chemical properties of the extracts as well as of the formulations were analyzed. Furthermore, thermal stability was evaluated by thermogravimetric analysis. Antioxidant capacity and biological behavior, in terms of cytocompatibility, wound healing, and antimicrobial potential, were assessed. The results highlighted for all the formulations (i) a good conservation and thermal stability in time, (ii) a neutralizing activity against free radicals, (iii) and high degree of cytocompatibility and tissue regeneration potential. In particular, collagen, gelatin, and collagen hydrolysate obtained from the Rapana venosa marine snail represent an important, valuable alternative to mammalian products.