Reconstruction and analysis of genome-scale metabolic model of a photosynthetic bacterium

<p>Abstract</p> <p>Background</p> <p><it>Synechocystis </it>sp. PCC6803 is a cyanobacterium considered as a candidate photo-biological production platform - an attractive cell factory capable of using CO₂and light as carbon and energy source, respectively. In order to enable efficient use of metabolic potential of <it>Synechocystis </it>sp. PCC6803, it is of importance to develop tools for uncovering stoichiometric and regulatory principles in the <it>Synechocystis </it>metabolic network.</p> <p>Results</p> <p>We report the most comprehensive metabolic model of <it>Synechocystis </it>sp. PCC6803 available, <it>i</it>Syn669, which includes 882 reactions, associated with 669 genes, and 790 metabolites. The model includes a detailed biomass equation which encompasses elementary building blocks that are needed for cell growth, as well as a detailed stoichiometric representation of photosynthesis. We demonstrate applicability of <it>i</it>Syn669 for stoichiometric analysis by simulating three physiologically relevant growth conditions of <it>Synechocystis </it>sp. PCC6803, and through <it>in silico </it>metabolic engineering simulations that allowed identification of a set of gene knock-out candidates towards enhanced succinate production. Gene essentiality and hydrogen production potential have also been assessed. Furthermore, <it>i</it>Syn669 was used as a transcriptomic data integration scaffold and thereby we found metabolic hot-spots around which gene regulation is dominant during light-shifting growth regimes.</p> <p>Conclusions</p> <p><it>i</it>Syn669 provides a platform for facilitating the development of cyanobacteria as microbial cell factories.</p

Alignment of the ALICE Inner Tracking System with cosmic-ray tracks

37 pages, 15 figures, revised version, accepted by JINSTALICE (A Large Ion Collider Experiment) is the LHC (Large Hadron Collider) experiment devoted to investigating the strongly interacting matter created in nucleus-nucleus collisions at the LHC energies. The ALICE ITS, Inner Tracking System, consists of six cylindrical layers of silicon detectors with three different technologies; in the outward direction: two layers of pixel detectors, two layers each of drift, and strip detectors. The number of parameters to be determined in the spatial alignment of the 2198 sensor modules of the ITS is about 13,000. The target alignment precision is well below 10 micron in some cases (pixels). The sources of alignment information include survey measurements, and the reconstructed tracks from cosmic rays and from proton-proton collisions. The main track-based alignment method uses the Millepede global approach. An iterative local method was developed and used as well. We present the results obtained for the ITS alignment using about 10^5 charged tracks from cosmic rays that have been collected during summer 2008, with the ALICE solenoidal magnet switched off.Peer reviewe

Transverse momentum spectra of charged particles in proton-proton collisions at s=900\sqrt{s} = 900 GeV with ALICE at the LHC

The inclusive charged particle transverse momentum distribution is measured in proton-proton collisions at $\sqrt{s} = 900$ GeV at the LHC using the ALICE detector. The measurement is performed in the central pseudorapidity region $(|\eta|<0.8)$ over the transverse momentum range $0.15<p_{\rm T}<10$ GeV/$c$. The correlation between transverse momentum and particle multiplicity is also studied. Results are presented for inelastic (INEL) and non-single-diffractive (NSD) events. The average transverse momentum for $|\eta|<0.8$ is $\left<p_{\rm T}\right>_{\rm INEL}=0.483\pm0.001$ (stat.) $\pm0.007$ (syst.) GeV/$c$ and \left_{\rm NSD}=0.489\pm0.001 (stat.) $\pm0.007$ (syst.) GeV/$c$, respectively. The data exhibit a slightly larger $\left<p_{\rm T}\right>$ than measurements in wider pseudorapidity intervals. The results are compared to simulations with the Monte Carlo event generators PYTHIA and PHOJET.Comment: 20 pages, 8 figures, 2 tables, published version, figures at http://aliceinfo.cern.ch/ArtSubmission/node/390

Cocoa-flavanols enhance moderate-intensity pulmonary [Formula: see text] kinetics but not exercise tolerance in sedentary middle-aged adults.

INTRODUCTION: Cocoa flavanols (CF) may exert health benefits through their potent vasodilatory effects, which are perpetuated by elevations in nitric oxide (NO) bioavailability. These vasodilatory effects may contribute to improved delivery of blood and oxygen (O2) to exercising muscle. PURPOSE: Therefore, the objective of this study was to examine how CF supplementation impacts pulmonary O2 uptake ([Formula: see text]) kinetics and exercise tolerance in sedentary middle-aged adults. METHODS: We employed a double-blind cross-over, placebo-controlled design whereby 17 participants (11 male, 6 female; mean ± SD, 45 ± 6 years) randomly received either 7 days of daily CF (400 mg) or placebo (PL) supplementation. On day 7, participants completed a series of 'step' moderate- and severe-intensity exercise tests for the determination of [Formula: see text] kinetics. RESULTS: During moderate-intensity exercise, the time constant of the phase II [Formula: see text] kinetics ([Formula: see text]) was decreased by 15% in CF as compared to PL (mean ± SD; PL 40 ± 12 s vs. CF 34 ± 9 s, P = 0.019), with no differences in the amplitude of [Formula: see text] (A[Formula: see text]; PL 0.77 ± 0.32 l min-1 vs. CF 0.79 ± 0.34 l min-1, P = 0.263). However, during severe-intensity exercise, [Formula: see text], the amplitude of the slow component ([Formula: see text]) and exercise tolerance (PL 435 ± 58 s vs. CF 424 ± 47 s, P = 0.480) were unchanged between conditions. CONCLUSION: Our data show that acute CF supplementation enhanced [Formula: see text] kinetics during moderate-, but not severe-intensity exercise in middle-aged participants. These novel effects of CFs, in this demographic, may contribute to improved tolerance of moderate-activity physical activities, which appear commonly present in daily life. TRIAL REGISTRATION: Registered under ClinicalTrials.gov Identifier no. NCT04370353, 30/04/20 retrospectively registered