Enzyme-Free Exponential Amplification via Growth and Scission of Crisscross Ribbons from Single-Stranded DNA Components.

The self-assembly of DNA-based monomers into higher-order structures has significant potential for realizing various biomimetic behaviors including algorithmic assembly, ultrasensitive detection, and self-replication. For these behaviors, it is desirable to implement high energetic barriers to undesired spurious nucleation, where such barriers can be bypassed via seed-initiated assembly. Joint-neighbor capture is a mechanism enabling the construction of such barriers while allowing for algorithmic behaviors, such as bit-copying.

Representing Catalytic Mechanisms with Rule Composition.

An "imaginary transition structure" overlays the molecular graphs of the educt and product sides of an elementary chemical reaction in a single graph to highlight the changes in bond structure. We generalize this idea to reactions with complex mechanisms in a formally rigorous approach based on composing arrow-pushing steps represented as graph-transformation rules to construct an overall composite rule and a derived transition structure. This transition structure retains information about transient bond changes that are invisible at the overall level and can be constructed automatically from an existing database of detailed enzymatic mechanisms.

Probabilistic Inference with Polymerizing Biochemical Circuits.

Probabilistic inference-the process of estimating the values of unobserved variables in probabilistic models-has been used to describe various cognitive phenomena related to learning and memory. While the study of biological realizations of inference has focused on animal nervous systems, single-celled organisms also show complex and potentially "predictive" behaviors in changing environments. Yet, it is unclear how the biochemical machinery found in cells might perform inference.

Graph transformation for enzymatic mechanisms.

Motivation: The design of enzymes is as challenging as it is consequential for making chemical synthesis in medical and industrial applications more efficient, cost-effective and environmentally friendly. While several aspects of this complex problem are computationally assisted, the drafting of catalytic mechanisms, i.e.

Combinatorial protein-protein interactions on a polymerizing scaffold.

Scaffold proteins organize cellular processes by bringing signaling molecules into interaction, sometimes by forming large signalosomes. Several of these scaffolds are known to polymerize. Their assemblies should therefore not be understood as stoichiometric aggregates, but as combinatorial ensembles.

Random walker's view of networks whose growth it shapes.

We study a simple model in which the growth of a network is determined by the location of one or more random walkers. Depending on walker motility rate, the model generates a spectrum of structures situated between well-known limiting cases. We demonstrate that the average degree observed by a walker is a function of its motility rate.

The Kappa platform for rule-based modeling.

Motivation: We present an overview of the Kappa platform, an integrated suite of analysis and visualization techniques for building and interactively exploring rule-based models. The main components of the platform are the Kappa Simulator, the Kappa Static Analyzer and the Kappa Story Extractor. In addition to these components, we describe the Kappa User Interface, which includes a range of interactive visualization tools for rule-based models needed to make sense of the complexity of biological systems.

Age-Dependence and Aging-Dependence: Neuronal Loss and Lifespan in a C. elegans Model of Parkinson's Disease.

It is often assumed, but not established, that the major neurodegenerative diseases, such as Parkinson's disease, are not just age-dependent (their incidence changes with time) but actually aging-dependent (their incidence is coupled to the process that determines lifespan). To determine a dependence on the aging process requires the joint probability distribution of disease onset and lifespan. For human Parkinson's disease, such a joint distribution is not available, because the disease cuts lifespan short.

Dynamic Influence Networks for Rule-Based Models.

We introduce the Dynamic Influence Network (DIN), a novel visual analytics technique for representing and analyzing rule-based models of protein-protein interaction networks. Rule-based modeling has proved instrumental in developing biological models that are concise, comprehensible, easily extensible, and that mitigate the combinatorial complexity of multi-state and multi-component biological molecules. Our technique visualizes the dynamics of these rules as they evolve over time.

The temporal scaling of Caenorhabditis elegans ageing.

The process of ageing makes death increasingly likely, involving a random aspect that produces a wide distribution of lifespan even in homogeneous populations. The study of this stochastic behaviour may link molecular mechanisms to the ageing process that determines lifespan. Here, by collecting high-precision mortality statistics from large populations, we observe that interventions as diverse as changes in diet, temperature, exposure to oxidative stress, and disruption of genes including the heat shock factor hsf-1, the hypoxia-inducible factor hif-1, and the insulin/IGF-1 pathway components daf-2, age-1, and daf-16 all alter lifespan distributions by an apparent stretching or shrinking of time.

Regulated spatial organization and sensitivity of cytosolic protein oxidation in Caenorhabditis elegans.

Cells adjust their behaviour in response to redox events by regulating protein activity through the reversible formation of disulfide bridges between cysteine thiols. However, the spatial and temporal control of these modifications remains poorly understood in multicellular organisms. Here we measured the protein thiol-disulfide balance in live Caenorhabditis elegans using a genetically encoded redox sensor and found that it is specific to tissues and is patterned spatially within a tissue.

An insulin-to-insulin regulatory network orchestrates phenotypic specificity in development and physiology.

Insulin-like peptides (ILPs) play highly conserved roles in development and physiology. Most animal genomes encode multiple ILPs. Here we identify mechanisms for how the forty Caenorhabditis elegans ILPs coordinate diverse processes, including development, reproduction, longevity and several specific stress responses.

The Caenorhabditis elegans Lifespan Machine.

The measurement of lifespan pervades aging research. Because lifespan results from complex interactions between genetic, environmental and stochastic factors, it varies widely even among isogenic individuals. The actions of molecular mechanisms on lifespan are therefore visible only through their statistical effects on populations.

Crosstalk and competition in signaling networks.

Signaling networks have evolved to transduce external and internal information into critical cellular decisions such as growth, differentiation, and apoptosis. These networks form highly interconnected systems within cells due to network crosstalk, where an enzyme from one canonical pathway acts on targets from other pathways. It is currently unclear what types of effects these interconnections can have on the response of networks to incoming signals.

Combinatorial complexity and compositional drift in protein interaction networks.

The assembly of molecular machines and transient signaling complexes does not typically occur under circumstances in which the appropriate proteins are isolated from all others present in the cell. Rather, assembly must proceed in the context of large-scale protein-protein interaction (PPI) networks that are characterized both by conflict and combinatorial complexity. Conflict refers to the fact that protein interfaces can often bind many different partners in a mutually exclusive way, while combinatorial complexity refers to the explosion in the number of distinct complexes that can be formed by a network of binding possibilities.

Optimizing ring assembly reveals the strength of weak interactions.

Most cellular processes rely on large multiprotein complexes that must assemble into a well-defined quaternary structure in order to function. A number of prominent examples, including the 20S core particle of the proteasome and the AAA+ family of ATPases, contain ring-like structures. Developing an understanding of the complex assembly pathways employed by ring-like structures requires a characterization of the problems these pathways have had to overcome as they evolved.

Nonequilibrium phase transitions in biomolecular signal transduction.

We study a mechanism for reliable switching in biomolecular signal-transduction cascades. Steady bistable states are created by system-size cooperative effects in populations of proteins, in spite of the fact that the phosphorylation-state transitions of any molecule, by means of which the switch is implemented, are highly stochastic. The emergence of switching is a nonequilibrium phase transition in an energetically driven, dissipative system described by a master equation.

The challenges and scope of theoretical biology.

Scientific theories seek to provide simple explanations for significant empirical regularities based on fundamental physical and mechanistic constraints. Biological theories have rarely reached a level of generality and predictive power comparable to physical theories. This discrepancy is explained through a combination of frozen accidents, environmental heterogeneity, and widespread non-linearities observed in adaptive processes.

Intrinsic information carriers in combinatorial dynamical systems.

Many proteins are composed of structural and chemical features--"sites" for short--characterized by definite interaction capabilities, such as noncovalent binding or covalent modification of other proteins. This modularity allows for varying degrees of independence, as the behavior of a site might be controlled by the state of some but not all sites of the ambient protein. Independence quickly generates a startling combinatorial complexity that shapes most biological networks, such as mammalian signaling systems, and effectively prevents their study in terms of kinetic equations-unless the complexity is radically trimmed.

Curvature in metabolic scaling.

For more than three-quarters of a century it has been assumed that basal metabolic rate increases as body mass raised to some power p. However, there is no broad consensus regarding the value of p: whereas many studies have asserted that p is 3/4 (refs 1-4; 'Kleiber's law'), some have argued that it is 2/3 (refs 5-7), and others have found that it varies depending on factors like environment and taxonomy. Here we show that the relationship between mass and metabolic rate has convex curvature on a logarithmic scale, and is therefore not a pure power law, even after accounting for body temperature.

Lifespan-on-a-chip: microfluidic chambers for performing lifelong observation of C. elegans.

This article describes the fabrication of a microfluidic device for the liquid culture of many individual nematode worms (Caenorhabditis elegans) in separate chambers. Each chamber houses a single worm from the fourth larval stage until death, and enables examination of a population of individual worms for their entire adult lifespans. Adjacent to the chambers, the device includes microfluidic worm clamps, which enable periodic, temporary immobilization of each worm.

Internal coarse-graining of molecular systems.

Modelers of molecular signaling networks must cope with the combinatorial explosion of protein states generated by posttranslational modifications and complex formation. Rule-based models provide a powerful alternative to approaches that require explicit enumeration of all possible molecular species of a system. Such models consist of formal rules stipulating the (partial) contexts wherein specific protein-protein interactions occur.

Sizing up allometric scaling theory.

Metabolic rate, heart rate, lifespan, and many other physiological properties vary with body mass in systematic and interrelated ways. Present empirical data suggest that these scaling relationships take the form of power laws with exponents that are simple multiples of one quarter. A compelling explanation of this observation was put forward a decade ago by West, Brown, and Enquist (WBE).