Non-specific effects of the CINNAMATE-4-HYDROXYLASE inhibitor piperonylic acid.

Chemical inhibitors are often implemented for the functional characterization of genes to overcome the limitations associated with genetic approaches. Although it is well established that the specificity of the compound is key to success of a pharmacological approach, off-target effects are often overlooked or simply neglected in a complex biological setting. Here we illustrate the cause and implications of such secondary effects by focusing on piperonylic acid (PA), an inhibitor of CINNAMATE-4-HYDROXYLASE (C4H) that is frequently used to investigate the involvement of lignin during plant growth and development. When supplied to plants, we found that PA is recognized as a substrate by GRETCHEN HAGEN 3.6 (GH3.6), an amido synthetase involved in the formation of the indole-3-acetic acid (IAA) conjugate IAA-Asp. By competing for the same enzyme, PA interferes with IAA conjugation, resulting in an increase in IAA concentrations in the plant. In line with the broad substrate specificity of the GH3 family of enzymes, treatment with PA increased not only IAA levels but also those of other GH3-conjugated phytohormones, namely jasmonic acid and salicylic acid. Finally, we found that interference with the endogenous function of GH3s potentially contributes to phenotypes previously observed upon PA treatment. We conclude that deregulation of phytohormone homeostasis by surrogate occupation of the conjugation machinery in the plant is likely a general phenomenon when using chemical inhibitors. Our results hereby provide a novel and important basis for future reference in studies using chemical inhibitors.

A case study of the Ancientbiotics collaboration.

Interdisciplinary collaboration is regarded as a desirable way of researching and, in some instances, even a requirement for academic teams and funding proposals. This paper explores the possibilities, but also the problems, of collaboration between different disciplines through a case study of the Ancientbiotics team. This team explores the potential of natural products contained in historical medical recipes. The search for clinically useful natural products in unusual places, such as historical medical practices, is a well-established endeavor in the scientific disciplines. The Ancientbiotics collaboration, largely based across UK institutions, takes this path a step forward in combining modern scientific knowledge of natural products with expertise from humanities to identify ingredient combinations. After 7 years of practice, the research has produced a variety of outcomes. This perspective will explore how the team worked within an interdisciplinary framework to advance investigation and application of historical medical recipes.

Adenylate cyclase activity of TIR1/AFB auxin receptors in plants.

The phytohormone auxin is the major coordinative signal in plant development1, mediating transcriptional reprogramming by a well-established canonical signalling pathway. TRANSPORT INHIBITOR RESPONSE 1 (TIR1)/AUXIN-SIGNALING F-BOX (AFB) auxin receptors are F-box subunits of ubiquitin ligase complexes. In response to auxin, they associate with Aux/IAA transcriptional repressors and target them for degradation via ubiquitination2,3. Here we identify adenylate cyclase (AC) activity as an additional function of TIR1/AFB receptors across land plants. Auxin, together with Aux/IAAs, stimulates cAMP production. Three separate mutations in the AC motif of the TIR1 C-terminal region, all of which abolish the AC activity, each render TIR1 ineffective in mediating gravitropism and sustained auxin-induced root growth inhibition, and also affect auxin-induced transcriptional regulation. These results highlight the importance of TIR1/AFB AC activity in canonical auxin signalling. They also identify a unique phytohormone receptor cassette combining F-box and AC motifs, and the role of cAMP as a second messenger in plants.

Structure-based modeling and dynamics of MurM, a Streptococcus pneumoniae penicillin resistance determinant present at the cytoplasmic membrane.

Branched Lipid II, required for the formation of indirectly crosslinked peptidoglycan, is generated by MurM, a protein essential for high-level penicillin resistance in the human pathogen Streptococcus pneumoniae. We have solved the X-ray crystal structure of Staphylococcus aureus FemX, an isofunctional homolog, and have used this as a template to generate a MurM homology model. Using this model, we perform molecular docking and molecular dynamics to examine the interaction of MurM with the phospholipid bilayer and the membrane-embedded Lipid II substrate. Our model suggests that MurM is associated with the major membrane phospholipid cardiolipin, and experimental evidence confirms that the activity of MurM is enhanced by this phospholipid and inhibited by its direct precursor phosphatidylglycerol. The spatial association of pneumococcal membrane phospholipids and their impact on MurM activity may therefore be critical to the final architecture of peptidoglycan and the expression of clinically relevant penicillin resistance in this pathogen.

Data Mining a Medieval Medical Text Reveals Patterns in Ingredient Choice That Reflect Biological Activity against Infectious Agents.

The pharmacopeia used by physicians and laypeople in medieval Europe has largely been dismissed as placebo or superstition. While we now recognize that some of the materia medica used by medieval physicians could have had useful biological properties, research in this area is limited by the labor-intensive process of searching and interpreting historical medical texts. Here, we demonstrate the potential power of turning medieval medical texts into contextualized electronic databases amenable to exploration by the use of an algorithm. We used established methodologies from network science to reveal patterns in ingredient selection and usage in a key text, the 15th-century Lylye of Medicynes, focusing on remedies to treat symptoms of microbial infection. In providing a worked example of data-driven textual analysis, we demonstrate the potential of this approach to encourage interdisciplinary collaboration and to shine a new light on the ethnopharmacology of historical medical texts.IMPORTANCE We used established methodologies from network science to identify patterns in medicinal ingredient combinations in a key medieval text, the 15th-century Lylye of Medicynes, focusing on recipes for topical treatments for symptoms of microbial infection. We conducted experiments screening the antimicrobial activity of selected ingredients. These experiments revealed interesting examples of ingredients that potentiated or interfered with each other's activity and that would be useful bases for future, more detailed experiments. Our results highlight (i) the potential to use methodologies from network science to analyze medieval data sets and detect patterns of ingredient combination, (ii) the potential of interdisciplinary collaboration to reveal different aspects of the ethnopharmacology of historical medical texts, and (iii) the potential development of novel therapeutics inspired by premodern remedies in a time of increased need for new antibiotics.

The Tetrazole Analogue of the Auxin Indole-3-acetic Acid Binds Preferentially to TIR1 and Not AFB5.

Indole-3-acetic acid (auxin) is considered one of the cardinal hormones in plant growth and development. It regulates a wide range of processes throughout the plant. Synthetic auxins exploit the auxin-signaling pathway and are valuable as herbicidal agrochemicals. Currently, despite a diversity of chemical scaffolds all synthetic auxins have a carboxylic acid as the active core group. By applying bio-isosteric replacement we discovered that indole-3-tetrazole was active by surface plasmon resonance spectrometry, showing that the tetrazole could initiate assembly of the Transport Inhibitor Resistant 1 (TIR1) auxin coreceptor complex. We then tested the tetrazole's efficacy in a range of whole plant physiological assays and in protoplast reporter assays, which all confirmed auxin activity, albeit rather weak. We then tested indole-3-tetrazole against the AFB5 homologue of TIR1, finding that binding was selective against TIR1, absent with AFB5. The kinetics of binding to TIR1 are contrasted to those for the herbicide picloram, which shows the opposite receptor preference, as it binds to AFB5 with far greater affinity than to TIR1. The basis of the preference of indole-3-tetrazole for TIR1 was revealed to be a single residue substitution using molecular docking, and assays using tir1 and afb5 mutant lines confirmed selectivity in vivo. Given the potential that a TIR1-selective auxin might have for unmasking receptor-specific actions, we followed a rational design, lead optimization campaign, and a set of chlorinated indole-3-tetrazoles was synthesized. Improved affinity for TIR1 and the preference for binding to TIR1 was maintained for 4- and 6-chloroindole-3-tetrazoles, coupled with improved efficacy in vivo. This work expands the range of auxin chemistry for the design of receptor-selective synthetic auxins.

Evolutionary Conserved Cysteines Function as cis-Acting Regulators of Arabidopsis PIN-FORMED 2 Distribution.

Coordination of plant development requires modulation of growth responses that are under control of the phytohormone auxin. PIN-FORMED plasma membrane proteins, involved in intercellular transport of the growth regulator, are key to the transmission of such auxin signals and subject to multilevel surveillance mechanisms, including reversible post-translational modifications. Apart from well-studied PIN protein modifications, namely phosphorylation and ubiquitylation, no further post-translational modifications have been described so far. Here, we focused on root-specific Arabidopsis PIN2 and explored functional implications of two evolutionary conserved cysteines, by a combination of in silico and molecular approaches. PIN2 sequence alignments and modeling predictions indicated that both cysteines are facing the cytoplasm and therefore would be accessible to redox status-controlled modifications. Notably, mutant pin2C-A alleles retained functionality, demonstrated by their ability to almost completely rescue defects of a pin2 null allele, whereas high resolution analysis of pin2C-A localization revealed increased intracellular accumulation, and altered protein distribution within plasma membrane micro-domains. The observed effects of cysteine replacements on root growth and PIN2 localization are consistent with a model in which redox status-dependent cysteine modifications participate in the regulation of PIN2 mobility, thereby fine-tuning polar auxin transport.

Analysis of the communities of an urban mobile phone network.

Being able to characterise the patterns of communications between individuals across different time scales is of great importance in understanding people's social interactions. Here, we present a detailed analysis of the community structure of the network of mobile phone calls in the metropolitan area of Milan revealing temporal patterns of communications between people. We show that circadian and weekly patterns can be found in the evolution of communities, presenting evidence that these cycles arise not only at the individual level but also at that of social groups. Our findings suggest that these trends are present across a range of time scales, from hours to days and weeks, and can be used to detect socially relevant events.

Tomographic docking suggests the mechanism of auxin receptor TIR1 selectivity.

We study the binding of plant hormone IAA on its receptor TIR1, introducing a novel computational method that we call tomographic docking and that accounts for interactions occurring along the depth of the binding pocket. Our results suggest that selectivity is related to constraints that potential ligands encounter on their way from the surface of the protein to their final position at the pocket bottom. Tomographic docking helps develop specific hypotheses about ligand binding, distinguishing binders from non-binders, and suggests that binding is a three-step mechanism, consisting of engagement with a niche in the back wall of the pocket, interaction with a molecular filter which allows or precludes further descent of ligands, and binding on the pocket base. Only molecules that are able to descend the pocket and bind at its base allow the co-receptor IAA7 to bind on the complex, thus behaving as active auxins. Analysing the interactions at different depths, our new method helps in identifying critical residues that constitute preferred future study targets and in the quest for safe and effective herbicides. Also, it has the potential to extend the utility of docking from ligand searches to the study of processes contributing to selectivity.

Synchronization in networks with multiple interaction layers.

The structure of many real-world systems is best captured by networks consisting of several interaction layers. Understanding how a multilayered structure of connections affects the synchronization properties of dynamical systems evolving on top of it is a highly relevant endeavor in mathematics and physics and has potential applications in several socially relevant topics, such as power grid engineering and neural dynamics. We propose a general framework to assess the stability of the synchronized state in networks with multiple interaction layers, deriving a necessary condition that generalizes the master stability function approach. We validate our method by applying it to a network of Rössler oscillators with a double layer of interactions and show that highly rich phenomenology emerges from this. This includes cases where the stability of synchronization can be induced even if both layers would have individually induced unstable synchrony, an effect genuinely arising from the true multilayer structure of the interactions among the units in the network.

Synchronization in dynamical networks with unconstrained structure switching.

We provide a rigorous solution to the problem of constructing a structural evolution for a network of coupled identical dynamical units that switches between specified topologies without constraints on their structure. The evolution of the structure is determined indirectly from a carefully built transformation of the eigenvector matrices of the coupling Laplacians, which are guaranteed to change smoothly in time. In turn, this allows one to extend the master stability function formalism, which can be used to assess the stability of a synchronized state. This approach is independent from the particular topologies that the network visits, and is not restricted to commuting structures. Also, it does not depend on the time scale of the evolution, which can be faster than, comparable to, or even secular with respect to the dynamics of the units.

Degree correlations in directed scale-free networks.

Scale-free networks, in which the distribution of the degrees obeys a power-law, are ubiquitous in the study of complex systems. One basic network property that relates to the structure of the links found is the degree assortativity, which is a measure of the correlation between the degrees of the nodes at the end of the links. Degree correlations are known to affect both the structure of a network and the dynamics of the processes supported thereon, including the resilience to damage, the spread of information and epidemics, and the efficiency of defence mechanisms. Nonetheless, while many studies focus on undirected scale-free networks, the interactions in real-world systems often have a directionality. Here, we investigate the dependence of the degree correlations on the power-law exponents in directed scale-free networks. To perform our study, we consider the problem of building directed networks with a prescribed degree distribution, providing a method for proper generation of power-law-distributed directed degree sequences. Applying this new method, we perform extensive numerical simulations, generating ensembles of directed scale-free networks with exponents between 2 and 3, and measuring ensemble averages of the Pearson correlation coefficients. Our results show that scale-free networks are on average uncorrelated across directed links for three of the four possible degree-degree correlations, namely in-degree to in-degree, in-degree to out-degree, and out-degree to out-degree. However, they exhibit anticorrelation between the number of outgoing connections and the number of incoming ones. The findings are consistent with an entropic origin for the observed disassortativity in biological and technological networks.

Endemic infections are always possible on regular networks.

We study the dependence of the largest component in regular networks on the clustering coefficient, showing that its size changes smoothly without undergoing a phase transition. We explain this behavior via an analytical approach based on the network structure, and provide an exact equation describing the numerical results. Our work indicates that intrinsic structural properties always allow the spread of epidemics on regular networks.

All scale-free networks are sparse.

We study the realizability of scale-free networks with a given degree sequence, showing that the fraction of realizable sequences undergoes two first-order transitions at the values 0 and 2 of the power-law exponent. We substantiate this finding by analytical reasoning and by a numerical method, proposed here, based on extreme value arguments, which can be applied to any given degree distribution. Our results reveal a fundamental reason why large scale-free networks without constraints on minimum and maximum degree must be sparse.

Efficient and exact sampling of simple graphs with given arbitrary degree sequence.

Uniform sampling from graphical realizations of a given degree sequence is a fundamental component in simulation-based measurements of network observables, with applications ranging from epidemics, through social networks to Internet modeling. Existing graph sampling methods are either link-swap based (Markov-Chain Monte Carlo algorithms) or stub-matching based (the Configuration Model). Both types are ill-controlled, with typically unknown mixing times for link-swap methods and uncontrolled rejections for the Configuration Model. Here we propose an efficient, polynomial time algorithm that generates statistically independent graph samples with a given, arbitrary, degree sequence. The algorithm provides a weight associated with each sample, allowing the observable to be measured either uniformly over the graph ensemble, or, alternatively, with a desired distribution. Unlike other algorithms, this method always produces a sample, without back-tracking or rejections. Using a central limit theorem-based reasoning, we argue, that for large , and for degree sequences admitting many realizations, the sample weights are expected to have a lognormal distribution. As examples, we apply our algorithm to generate networks with degree sequences drawn from power-law distributions and from binomial distributions.

Anomalous ordering in inhomogeneously strained materials.

We study a continuous quasi-two-dimensional order-disorder phase transition that occurs in a simple model of a material that is inhomogeneously strained due to the presence of dislocation lines. Performing Monte Carlo simulations of different system sizes and using finite size scaling, we measure critical exponents describing the transition of ß=0.18±0.02, γ=1.0±0.1, and α=0.10±0.02. Comparable exponents have been reported in a variety of physical systems. These systems undergo a range of different types of phase transitions, including structural transitions, exciton percolation, and magnetic ordering. In particular, similar exponents have been found to describe the development of magnetic order at the onset of the pseudogap transition in high-temperature superconductors. Their common universal critical exponents suggest that the essential physics of the transition in all of these physical systems is the same as in our simple model. We argue that the nature of the transition in our model is related to surface transitions although our model has no free surface.

Phase diagram for a two-dimensional, two-temperature, diffusive XY model.

Using Monte Carlo simulations, we determine the phase diagram of a diffusive two-temperature conserved order parameter XY model. When the two temperatures are equal the system becomes the equilibrium XY model with the continuous Kosterlitz-Thouless (KT) vortex-antivortex unbinding phase transition. When the two temperatures are unequal the system is driven by an energy flow from the higher temperature heat-bath to the lower temperature one and reaches a far-from-equilibrium steady state. We show that the nonequilibrium phase diagram contains three phases: A homogenous disordered phase and two phases with long range, spin texture order. Two critical lines, representing continuous phase transitions from a homogenous disordered phase to two phases of long range order, meet at the equilibrium KT point. The shape of the nonequilibrium critical lines as they approach the KT point is described by a crossover exponent φ=2.52±0.05. Finally, we suggest that the transition between the two phases with long-range order is first-order, making the KT-point where all three phases meet a bicritical point.