Exploiting the pathway structure of metabolism to reveal high-order epistasis

<p>Abstract</p> <p>Background</p> <p>Biological robustness results from redundant pathways that achieve an essential objective, e.g. the production of biomass. As a consequence, the biological roles of many genes can only be revealed through multiple knockouts that identify a <it>set </it>of genes as essential for a given function. The identification of such "epistatic" essential relationships between network components is critical for the understanding and eventual manipulation of robust systems-level phenotypes.</p> <p>Results</p> <p>We introduce and apply a network-based approach for genome-scale metabolic knockout design. We apply this method to uncover over 11,000 minimal knockouts for biomass production in an <it>in silico </it>genome-scale model of <it>E. coli</it>. A large majority of these "essential sets" contain 5 or more reactions, and thus represent complex epistatic relationships between components of the <it>E. coli </it>metabolic network.</p> <p>Conclusion</p> <p>The complex minimal biomass knockouts discovered with our approach illuminate robust essential systems-level roles for reactions in the <it>E. coli </it>metabolic network. Unlike previous approaches, our method yields results regarding high-order epistatic relationships and is applicable at the genome-scale.</p

Spectroscopy of 35^{35}P using the one-proton knockout reaction

The structure of $^{35}$P was studied with a one-proton knockout reaction at88~MeV/u from a $^{36}$S projectile beam at NSCL. The $\gamma$ rays from thedepopulation of excited states in $^{35}$P were detected with GRETINA, whilethe $^{35}$P nuclei were identified event-by-event in the focal plane of theS800 spectrograph. The level scheme of $^{35}$P was deduced up to 7.5 MeV using$\gamma-\gamma$ coincidences. The observed levels were attributed to protonremovals from the $sd$-shell and also from the deeply-bound $p\_{1/2}$ orbital.The orbital angular momentum of each state was derived from the comparisonbetween experimental and calculated shapes of individual ($\gamma$-gated)parallel momentum distributions. Despite the use of different reactions andtheir associate models, spectroscopic factors, $C^2S$, derived from the$^{36}$S $(-1p)$ knockout reaction agree with those obtained earlier from$^{36}$S($d$,\nuc{3}{He}) transfer, if a reduction factor $R\_s$, as deducedfrom inclusive one-nucleon removal cross sections, is applied to the knockout transitions.In addition to the expected proton-hole configurations, other states were observedwith individual cross sections of the order of 0.5~mb. Based on their shiftedparallel momentum distributions, their decay modes to negative parity states,their high excitation energy (around 4.7~MeV) and the fact that they were notobserved in the ($d$,\nuc{3}{He}) reaction, we propose that they may resultfrom a two-step mechanism or a nucleon-exchange reaction with subsequent neutronevaporation. Regardless of the mechanism, that could not yet be clarified, thesestates likely correspond to neutron core excitations in \nuc{35}{P}. Thisnewly-identified pathway, although weak, offers the possibility to selectivelypopulate certain intruder configurations that are otherwise hard to produceand identify.Comment: 5 figures, 1 table, accepted for publication in Physical Review

Computation of elementary modes: a unifying framework and the new binary approach

BACKGROUND: Metabolic pathway analysis has been recognized as a central approach to the structural analysis of metabolic networks. The concept of elementary (flux) modes provides a rigorous formalism to describe and assess pathways and has proven to be valuable for many applications. However, computing elementary modes is a hard computational task. In recent years we assisted in a multiplication of algorithms dedicated to it. We require a summarizing point of view and a continued improvement of the current methods. RESULTS: We show that computing the set of elementary modes is equivalent to computing the set of extreme rays of a convex cone. This standard mathematical representation provides a unified framework that encompasses the most prominent algorithmic methods that compute elementary modes and allows a clear comparison between them. Taking lessons from this benchmark, we here introduce a new method, the binary approach, which computes the elementary modes as binary patterns of participating reactions from which the respective stoichiometric coefficients can be computed in a post-processing step. We implemented the binary approach in FluxAnalyzer 5.1, a software that is free for academics. The binary approach decreases the memory demand up to 96% without loss of speed giving the most efficient method available for computing elementary modes to date. CONCLUSIONS: The equivalence between elementary modes and extreme ray computations offers opportunities for employing tools from polyhedral computation for metabolic pathway analysis. The new binary approach introduced herein was derived from this general theoretical framework and facilitates the computation of elementary modes in considerably larger networks

Building Near-Real-Time Processing Pipelines with the Spark-MPI Platform

Advances in detectors and computational technologies provide new opportunities for applied research and the fundamental sciences. Concurrently, dramatic increases in the three Vs (Volume, Velocity, and Variety) of experimental data and the scale of computational tasks produced the demand for new real-time processing systems at experimental facilities. Recently, this demand was addressed by the Spark-MPI approach connecting the Spark data-intensive platform with the MPI high-performance framework. In contrast with existing data management and analytics systems, Spark introduced a new middleware based on resilient distributed datasets (RDDs), which decoupled various data sources from high-level processing algorithms. The RDD middleware significantly advanced the scope of data-intensive applications, spreading from SQL queries to machine learning to graph processing. Spark-MPI further extended the Spark ecosystem with the MPI applications using the Process Management Interface. The paper explores this integrated platform within the context of online ptychographic and tomographic reconstruction pipelines.Comment: New York Scientific Data Summit, August 6-9, 201

First and second simulator evaluations of advanced integrated display and control systems

Advanced integrated visual and control systems simulator evaluations for post-Apollo manned spacecraf

Topology optimization of freeform large-area metasurfaces

We demonstrate optimization of optical metasurfaces over $10^5$--$10^6$ degrees of freedom in two and three dimensions, 100--1000+ wavelengths ($\lambda$) in diameter, with 100+ parameters per $\lambda^2$. In particular, we show how topology optimization, with one degree of freedom per high-resolution "pixel," can be extended to large areas with the help of a locally periodic approximation that was previously only used for a few parameters per $\lambda^2$. In this way, we can computationally discover completely unexpected metasurface designs for challenging multi-frequency, multi-angle problems, including designs for fully coupled multi-layer structures with arbitrary per-layer patterns. Unlike typical metasurface designs based on subwavelength unit cells, our approach can discover both sub- and supra-wavelength patterns and can obtain both the near and far fields