Niall M. Mangan

Dynamics of molecular diffusion of rhodamine 6G in silica nanochannels

We describe a method to study diffusion of rhodamine 6G dye in single silica nanochannels using arrays of silica nanochannels. Dynamics of the molecules inside single nanochannel is found from the change of the dye concentration in solution with time. A 10(8) decrease in the dye diffusion coefficient relative to water was observed. In comparison to single fluorescent molecule studies, the presented method does not require fluorescence of the diffusing molecules.

Reversible to irreversible flow transition in periodically driven vortices.

We show that periodically driven superconducting vortices in the presence of quenched disorder exhibit a transition from reversible to irreversible flow under increasing vortex density or cycle period. This type of behavior has recently been observed for periodically sheared colloidal suspensions and we demonstrate that driven vortex systems exhibit remarkably similar behavior. We also provide evidence that the onset of irreversible behavior is a dynamical phase transition.

pH determines the energetic efficiency of the cyanobacterial CO2 concentrating mechanism

Significance Cyanobacteria are responsible for roughly 10% of global photosynthetic primary production of reduced carbon. Although cyanobacteria are incredibly diverse, all known species contain a complex protein system called the CO2 concentrating mechanism (CCM), which enables rapid growth even in environments with extremely limited CO2. The CCM enables cyanobacteria to accumulate HCO3− and convert this inorganic carbon pool to utilizable CO2. We demonstrate here that a quantitative description of the CCM must include the effect of pH on the abundance of HCO3− and H2CO3. This pH-dependent description is consistent with cyanobacterial physiology. Furthermore, the model predicts that alkaline cytosolic pH reduces the energetic cost of the CCM, consistent with pH measurements of photosynthesizing cyanobacteria. Many carbon-fixing bacteria rely on a CO2 concentrating mechanism (CCM) to elevate the CO2 concentration around the carboxylating enzyme ribulose bisphosphate carboxylase/oxygenase (RuBisCO). The CCM is postulated to simultaneously enhance the rate of carboxylation and minimize oxygenation, a competitive reaction with O2 also catalyzed by RuBisCO. To achieve this effect, the CCM combines two features: active transport of inorganic carbon into the cell and colocalization of carbonic anhydrase and RuBisCO inside proteinaceous microcompartments called carboxysomes. Understanding the significance of the various CCM components requires reconciling biochemical intuition with a quantitative description of the system. To this end, we have developed a mathematical model of the CCM to analyze its energetic costs and the inherent intertwining of physiology and pH. We find that intracellular pH greatly affects the cost of inorganic carbon accumulation. At low pH the inorganic carbon pool contains more of the highly cell-permeable H2CO3, necessitating a substantial expenditure of energy on transport to maintain internal inorganic carbon levels. An intracellular pH ≈8 reduces leakage, making the CCM significantly more energetically efficient. This pH prediction coincides well with our measurement of intracellular pH in a model cyanobacterium. We also demonstrate that CO2 retention in the carboxysome is necessary, whereas selective uptake of HCO3− into the carboxysome would not appreciably enhance energetic efficiency. Altogether, integration of pH produces a model that is quantitatively consistent with cyanobacterial physiology, emphasizing that pH cannot be neglected when describing biological systems interacting with inorganic carbon pools.

Systems analysis of the CO2 concentrating mechanism in cyanobacteria

Cyanobacteria are photosynthetic bacteria with a unique CO2 concentrating mechanism (CCM), enhancing carbon fixation. Understanding the CCM requires a systems level perspective of how molecular components work together to enhance CO2 fixation. We present a mathematical model of the cyanobacterial CCM, giving the parameter regime (expression levels, catalytic rates, permeability of carboxysome shell) for efficient carbon fixation. Efficiency requires saturating the RuBisCO reaction, staying below saturation for carbonic anhydrase, and avoiding wasteful oxygenation reactions. We find selectivity at the carboxysome shell is not necessary; there is an optimal non-specific carboxysome shell permeability. We compare the efficacy of facilitated CO2 uptake, CO2 scavenging, and HCO3− transport with varying external pH. At the optimal carboxysome permeability, contributions from CO2 scavenging at the cell membrane are small. We examine the cumulative benefits of CCM spatial organization strategies: enzyme co-localization and compartmentalization. DOI: http://dx.doi.org/10.7554/eLife.02043.001

Inferring Biological Networks by Sparse Identification of Nonlinear Dynamics

Inferring the structure and dynamics of network models is critical to understanding the functionality and control of complex systems, such as metabolic and regulatory biological networks. The increasing quality and quantity of experimental data enable statistical approaches based on information theory for model selection and goodness-of-fit metrics. We propose an alternative data-driven method to infer networked nonlinear dynamical systems by using sparsity-promoting optimization to select a subset of nonlinear interactions representing dynamics on a network. In contrast to standard model selection methods-based upon information content for a finite number of heuristic models (order 10 or less), our model selection procedure discovers a parsimonious model from a combinatorially large set of models, without an exhaustive search. Our particular innovation is appropriate for many biological networks, where the governing dynamical systems have rational function nonlinearities with cross terms, thus requiring an implicit formulation and the equations to be identified in the null-space of a library of mixed nonlinearities, including the state and derivative terms. This method, implicit-SINDy, succeeds in inferring three canonical biological models: 1) Michaelis-Menten enzyme kinetics; 2) the regulatory network for competence in bacteria; and 3) the metabolic network for yeast glycolysis.

Framework to predict optimal buffer layer pairing for thin film solar cell absorbers: A case study for tin sulfide/zinc oxysulfide

An outstanding challenge in the development of novel functional materials for optoelectronic devices is identifying suitable charge-carrier contact layers. Herein, we simulate the photovoltaic device performance of various n-type contact material pairings with tin(II) sulfide (SnS), a p-type absorber. The performance of the contacting material, and resulting device efficiency, depend most strongly on two variables: conduction band offset between absorber and contact layer, and doping concentration within the contact layer. By generating a 2D contour plot of device efficiency as a function of these two variables, we create a performance-space plot for contacting layers on a given absorber material. For a simulated high-lifetime SnS absorber, this 2D performance-space illustrates two maxima, one local and one global. The local maximum occurs over a wide range of contact-layer doping concentrations (below 1016 cm−3), but only a narrow range of conduction band offsets (0 to −0.1 eV), and is highly sensitive t...

Influence of N on the electronic properties of GaAsN alloy films and heterostructures

We have investigated the effects of N on the electronic properties of Si-doped GaAs1−xNx alloy films and AlGaAs∕GaAsN modulation-doped heterostructures. For bulk-like alloy films, the electron mobility is independent of free carrier concentration and arsenic species, and decreases with increasing N composition. Thus, N-related defects are the main source of scattering in the dilute nitride alloys. For AlGaAs∕GaAsN heterostructures, gated and illuminated magnetoresistance measurements reveal a two-dimensional electron gas mobility which increases with carrier concentration to a constant value. Thus, in contrast to the long-range ionized scattering sources which are dominant in N-free heterostructures, N-induced neutral scattering sources are the dominant source of scattering in AlGaAs∕GaAsN heterostructures. Finally, a decrease in free carrier concentration with increasing N composition is apparent for bulk-like films, while the free carrier concentration is independent of N composition in modulation-doped...

Non-monotonic effect of growth temperature on carrier collection in SnS solar cells

We quantify the effects of growth temperature on material and device properties of thermally evaporated SnS thin-films and test structures. Grain size, Hall mobility, and majority-carrier concentration monotonically increase with growth temperature. However, the charge collection as measured by the long-wavelength contribution to short-circuit current exhibits a non-monotonic behavior: the collection decreases with increased growth temperature from 150 °C to 240 °C and then recovers at 285 °C. Fits to the experimental internal quantum efficiency using an opto-electronic model indicate that the non-monotonic behavior of charge-carrier collection can be explained by a transition from drift- to diffusion-assisted components of carrier collection. The results show a promising increase in the extracted minority-carrier diffusion length at the highest growth temperature of 285 °C. These findings illustrate how coupled mechanisms can affect early stage device development, highlighting the critical role of direct...

Model selection for dynamical systems via sparse regression and information criteria

We develop an algorithm for model selection which allows for the consideration of a combinatorially large number of candidate models governing a dynamical system. The innovation circumvents a disadvantage of standard model selection which typically limits the number of candidate models considered due to the intractability of computing information criteria. Using a recently developed sparse identification of nonlinear dynamics algorithm, the sub-selection of candidate models near the Pareto frontier allows feasible computation of Akaike information criteria (AIC) or Bayes information criteria scores for the remaining candidate models. The information criteria hierarchically ranks the most informative models, enabling the automatic and principled selection of the model with the strongest support in relation to the time-series data. Specifically, we show that AIC scores place each candidate model in the strong support, weak support or no support category. The method correctly recovers several canonical dynamical systems, including a susceptible-exposed-infectious-recovered disease model, Burgers’ equation and the Lorenz equations, identifying the correct dynamical system as the only candidate model with strong support.

A systems-level model reveals that 1,2-Propanediol utilization microcompartments enhance pathway flux through intermediate sequestration

The spatial organization of metabolism is common to all domains of life. Enteric and other bacteria use subcellular organelles known as bacterial microcompartments to spatially organize the metabolism of pathogenicity-relevant carbon sources, such as 1,2-propanediol. The organelles are thought to sequester a private cofactor pool, minimize the effects of toxic intermediates, and enhance flux through the encapsulated metabolic pathways. We develop a mathematical model of the function of the 1,2-propanediol utilization microcompartment of Salmonella enterica and use it to analyze the function of the microcompartment organelles in detail. Our model makes accurate estimates of doubling times based on an optimized compartment shell permeability determined by maximizing metabolic flux in the model. The compartments function primarily to decouple cytosolic intermediate concentrations from the concentrations in the microcompartment, allowing significant enhancement in pathway flux by the generation of large concentration gradients across the microcompartment shell. We find that selective permeability of the microcompartment shell is not absolutely necessary, but is often beneficial in establishing this intermediate-trapping function. Our findings also implicate active transport of the 1,2-propanediol substrate under conditions of low external substrate concentration, and we present a mathematical bound, in terms of external 1,2-propanediol substrate concentration and diffusive rates, on when active transport of the substrate is advantageous. By allowing us to predict experimentally inaccessible aspects of microcompartment function, such as intra-microcompartment metabolite concentrations, our model presents avenues for future research and underscores the importance of carefully considering changes in external metabolite concentrations and other conditions during batch cultures. Our results also suggest that the encapsulation of heterologous pathways in bacterial microcompartments might yield significant benefits for pathway flux, as well as for toxicity mitigation.