Hidden state prediction: a modification of classic ancestral state reconstruction algorithms helps unravel complex symbioses

Complex symbioses between animal or plant hosts and their associated microbiotas can involve thousands of species and millions of genes. Because of the number of interacting partners, it is often impractical to study all organisms or genes in these host-microbe symbioses individually. Yet new phylogenetic predictive methods can use the wealth of accumulated data on diverse model organisms to make inferences into the properties of less well-studied species and gene families. Predictive functional profiling methods use evolutionary models based on the properties of studied relatives to put bounds on the likely characteristics of an organism or gene that has not yet been studied in detail. These techniques have been applied to predict diverse features of host-associated microbial communities ranging from the enzymatic function of uncharacterized genes to the gene content of uncultured microorganisms. We consider these phylogenetically informed predictive techniques from disparate fields as examples of a general class of algorithms for Hidden State Prediction (HSP), and argue that HSP methods have broad value in predicting organismal traits in a variety of contexts, including the study of complex host-microbe symbioses.This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by the Frontiers Research Foundation. The published article can be found at: http://www.frontiersin.org/Microbiology.Keywords: phylogenetic prediction, “virtual” metagenomes, systems biology, predictive metagenomics, ecotoxicology, 16S rRNA gene copy numbe

Critical dynamics of a spin-5/2 2D isotropic antiferromagnet

We report a neutron scattering study of the dynamic spin correlations in Rb$_2$MnF$_4$, a two-dimensional spin-5/2 antiferromagnet. By tuning an external magnetic field to the value for the spin-flop line, we reduce the effective spin anisotropy to essentially zero, thereby obtaining a nearly ideal two-dimensional isotropic antiferromagnet. From the shape of the quasielastic peak as a function of temperature, we demonstrate dynamic scaling for this system and find a value for the dynamical exponent $z$. We compare these results to theoretical predictions for the dynamic behavior of the two-dimensional Heisenberg model, in which deviations from $z=1$ provide a measure of the corrections to scaling.Comment: 5 pages, 4 figures. Submitted to Physical Review B, Rapid Communication

Conductivity of quantum-spin chains: A Quantum Monte Carlo approach

We discuss zero-frequency transport properties of various spin-1/2 chains. We show, that a careful analysis of Quantum Monte-Carlo (QMC) data on the imaginary axis allows to distinguish between intrinsic ballistic and diffusive transport. We determine the Drude weight, current-relaxation life-time and the mean-free path for integrable and a non-integrable quantum-spin chain. We discuss, in addition, some phenomenological relations between various transport-coefficients and thermal response functions

Climate change promotes parasitism in a coral symbiosis.

Coastal oceans are increasingly eutrophic, warm and acidic through the addition of anthropogenic nitrogen and carbon, respectively. Among the most sensitive taxa to these changes are scleractinian corals, which engineer the most biodiverse ecosystems on Earth. Corals' sensitivity is a consequence of their evolutionary investment in symbiosis with the dinoflagellate alga, Symbiodinium. Together, the coral holobiont has dominated oligotrophic tropical marine habitats. However, warming destabilizes this association and reduces coral fitness. It has been theorized that, when reefs become warm and eutrophic, mutualistic Symbiodinium sequester more resources for their own growth, thus parasitizing their hosts of nutrition. Here, we tested the hypothesis that sub-bleaching temperature and excess nitrogen promotes symbiont parasitism by measuring respiration (costs) and the assimilation and translocation of both carbon (energy) and nitrogen (growth; both benefits) within Orbicella faveolata hosting one of two Symbiodinium phylotypes using a dual stable isotope tracer incubation at ambient (26 °C) and sub-bleaching (31 °C) temperatures under elevated nitrate. Warming to 31 °C reduced holobiont net primary productivity (NPP) by 60% due to increased respiration which decreased host %carbon by 15% with no apparent cost to the symbiont. Concurrently, Symbiodinium carbon and nitrogen assimilation increased by 14 and 32%, respectively while increasing their mitotic index by 15%, whereas hosts did not gain a proportional increase in translocated photosynthates. We conclude that the disparity in benefits and costs to both partners is evidence of symbiont parasitism in the coral symbiosis and has major implications for the resilience of coral reefs under threat of global change

A Systems Approach for Tumor Pharmacokinetics

Recent advances in genome inspired target discovery, small molecule screens, development of biological and nanotechnology have led to the introduction of a myriad of new differently sized agents into the clinic. The differences in small and large molecule delivery are becoming increasingly important in combination therapies as well as the use of drugs that modify the physiology of tumors such as anti-angiogenic treatment. The complexity of targeting has led to the development of mathematical models to facilitate understanding, but unfortunately, these studies are often only applicable to a particular molecule, making pharmacokinetic comparisons difficult. Here we develop and describe a framework for categorizing primary pharmacokinetics of drugs in tumors. For modeling purposes, we define drugs not by their mechanism of action but rather their rate-limiting step of delivery. Our simulations account for variations in perfusion, vascularization, interstitial transport, and non-linear local binding and metabolism. Based on a comparison of the fundamental rates determining uptake, drugs were classified into four categories depending on whether uptake is limited by blood flow, extravasation, interstitial diffusion, or local binding and metabolism. Simulations comparing small molecule versus macromolecular drugs show a sharp difference in distribution, which has implications for multi-drug therapies. The tissue-level distribution differs widely in tumors for small molecules versus macromolecular biologic drugs, and this should be considered in the design of agents and treatments. An example using antibodies in mouse xenografts illustrates the different in vivo behavior. This type of transport analysis can be used to aid in model development, experimental data analysis, and imaging and therapeutic agent design.National Institutes of Health (U.S.) (grant T32 CA079443

Signatures of arithmetic simplicity in metabolic network architecture

Metabolic networks perform some of the most fundamental functions in living cells, including energy transduction and building block biosynthesis. While these are the best characterized networks in living systems, understanding their evolutionary history and complex wiring constitutes one of the most fascinating open questions in biology, intimately related to the enigma of life's origin itself. Is the evolution of metabolism subject to general principles, beyond the unpredictable accumulation of multiple historical accidents? Here we search for such principles by applying to an artificial chemical universe some of the methodologies developed for the study of genome scale models of cellular metabolism. In particular, we use metabolic flux constraint-based models to exhaustively search for artificial chemistry pathways that can optimally perform an array of elementary metabolic functions. Despite the simplicity of the model employed, we find that the ensuing pathways display a surprisingly rich set of properties, including the existence of autocatalytic cycles and hierarchical modules, the appearance of universally preferable metabolites and reactions, and a logarithmic trend of pathway length as a function of input/output molecule size. Some of these properties can be derived analytically, borrowing methods previously used in cryptography. In addition, by mapping biochemical networks onto a simplified carbon atom reaction backbone, we find that several of the properties predicted by the artificial chemistry model hold for real metabolic networks. These findings suggest that optimality principles and arithmetic simplicity might lie beneath some aspects of biochemical complexity

Electron transport in TiO2 probed by THz time-domain spectroscopy

Euan Hendry, F. Wang, J. Shan, T. F. Heinz, and Mischa Bonn, Physical Review B, Vol. 69, article 081101 (2004). "Copyright © 2004 by the American Physical Society."Electron transport in crystalline TiO2 (rutile phase) is investigated by frequency-dependent conductivity measurements using THz time-domain spectroscopy. Transport is limited by electron-phonon coupling, resulting in a strongly temperature-dependent electron-optical phonon scattering rate, with significant anisotropy in the scattering process. The experimental findings can be described by Feynman polaron theory within the intermediate coupling regime and allow for a determination of electron mobility