Electron bifurcation mechanism and homoacetogenesis explain products yields in mixed culture anaerobic fermentations

Anaerobic fermentation of organic wastes using microbial mixed cultures is a promising avenue to treat residues and obtain added-value products. However, the process has some important limitations that prevented so far any industrial application. One of the main issues is that we are not able to predict reliably the product spectrum (i.e. the stoichiometry of the process) because the complex microbial community behaviour is not completely understood. To address this issue, in this work we propose a new metabolic network of glucose fermentation by microbial mixed cultures that incorporates electron bifurcation and homoacetogenesis. Our methodology uses NADH balances to analyse published experimental data and evaluate the new stoichiometry proposed. Our results prove for the first time the inclusion of electron bifurcation in the metabolic network as a better description of the experimental results. Homoacetogenesis has been used to explain the discrepancies between observed and theoretically predicted yields of gaseous H2 and CO2 and it appears as the best solution among other options studied. Overall, this work supports the consideration of electron bifurcation as an important biochemical mechanism in microbial mixed cultures fermentations and underlines the importance of considering homoacetogenesis when analysing anaerobic fermentations

Effect of ZrO2 nanoparticles on thermophysical and rheological properties of three synthetic oils

This article presents an experimental study on some thermophysical properties (density, viscosity and adiabatic bulk modulus) of six nanolubricants based on synthetic oils and ZrO2 nanoparticles. Two-step method with ultrasonic disruptor was used to prepare the nanodispersions. The morphology, crystalline degree and elemental composition of nanoparticles were analyzed by electron microscopy. Visual observation, temporal variation of refractive index and dynamic light scattering were used to analyze the stability of the nanolubricants and the average size of the aggregates. The presence of new interactions between nanoparticles and base oils was studied through Fourier transform infrared spectrometer. Vibrating tube densimeters, rotational viscometer and rheometer equipped with cone-plate geometry were used within the temperature range from (278.15 to 373.15) K. The ability of some theoretical simple models to predict densities and viscosities of these nanolubricants as a function of temperature and nanoparticle concentration was also checked.This work was supported by Spanish Ministry of Economy and Competitiveness and the UE FEDER programme through ENE2014-55489-C2-1-R, ENE2014-55489-C2-2-R, ENE2017-86425- C2-1-R and ENE2017-86425-C2-2-R projects. Moreover, this work was funded by the Xunta de Galicia (AGRUP2015/11 and GRC ED431C 2016/001). D.C. was recipient of a postdoctoral fellowship from Xunta de Galicia (Spain).S

Automated calibration of FEM models using LiDAR point clouds

In present work it is pretended to estimate elastic parameters of beams through the combined use of precision geomatic techniques (laser scanning) and structural behaviour simulation tools. The study has two aims, on the one hand, to develop an algorithm able to interpret automatically point clouds acquired by laser scanning systems of beams subjected to different load situations on experimental tests; and on the other hand, to minimize differences between deformation values given by simulation tools and those measured by laser scanning. In this way we will proceed to identify elastic parameters and boundary conditions of structural element so that surface stresses can be estimated more easily.Ministerio de Interior | Ref. SPIP2017-02122Ministerio de Economía, Industria y Competitividad | Ref. EUIN2017- 87598Ministerio de Educación, Cultura y Deporte | Ref. CAS15/00126Xunta de Galicia | Ref. ED431C2016‐03

Microbial catabolic activities are naturally selected by metabolic energy harvest rate

The fundamental trade-off between yield and rate of energy harvest per unit of substrate has been largely discussed as a main characteristic for microbial established cooperation or competition. In this study, this point is addressed by developing a generalized model that simulates competition between existing and not experimentally reported microbial catabolic activities defined only based on well-known biochemical pathways. No specific microbial physiological adaptations are considered, growth yield is calculated coupled to catabolism energetics and a common maximum biomass-specific catabolism rate (expressed as electron transfer rate) is assumed for all microbial groups. Under this approach, successful microbial metabolisms are predicted in line with experimental observations under the hypothesis of maximum energy harvest rate. Two microbial ecosystems, typically found in wastewater treatment plants, are simulated, namely: (i) the anaerobic fermentation of glucose and (ii) the oxidation and reduction of nitrogen under aerobic autotrophic (nitrification) and anoxic heterotrophic and autotrophic (denitrification) conditions. The experimentally observed cross feeding in glucose fermentation, through multiple intermediate fermentation pathways, towards ultimately methane and carbon dioxide is predicted. Analogously, two-stage nitrification (by ammonium and nitrite oxidizers) is predicted as prevailing over nitrification in one stage. Conversely, denitrification is predicted in one stage (by denitrifiers) as well as anammox (anaerobic ammonium oxidation). The model results suggest that these observations are a direct consequence of the different energy yields per electron transferred at the different steps of the pathways. Overall, our results theoretically support the hypothesis that successful microbial catabolic activities are selected by an overall maximum energy harvest rate

A superfluid hydrodynamic model for the enhanced moments of inertia of molecules in liquid 4He

We present a superfluid hydrodynamic model for the increase in moment of inertia, $\Delta I$, of molecules rotating in liquid $^4$He. The static inhomogeneous He density around each molecule (calculated using the Orsay-Paris liquid $^4$He density functional) is assumed to adiabatically follow the rotation of the molecule. We find that the $\Delta I$ values created by the viscousless and irrotational flow are in good agreement with the observed increases for several molecules [ OCS, (HCN)$_2$, HCCCN, and HCCCH$_3$ ]. For HCN and HCCH, our model substantially overestimates $\Delta I$. This is likely to result from a (partial) breakdown of the adiabatic following approximation.Comment: 4 pages, 1 eps figure, corrected version of published paper. Erratum has been submitted for change

The Effect of Nanoparticles on Amyloid Aggregation Depends on the Protein Stability and Intrinsic Aggregation Rate

Nanoparticles interfere with protein amyloid formation. Catalysis of the process may occur due to increased local protein concentration and nucleation on the nanoparticle surface, whereas tight binding or a large particle/protein surface area may lead to inhibition of protein aggregation. Here we show a clear correlation between the intrinsic protein stability and the nanoparticle effect on the aggregation rate. The results were reached for a series of five mutants of single-chain monellin differing in intrinsic stability toward denaturation, for which a correlation between protein stability and aggregation propensity has been previously documented by Szczepankiewicz et al. [Mol. Biosyst 2010 7 (2), 521-532]. The aggregation process was monitored by thioflavin T fluorescence in the absence and presence of copolyrneric nanoparticles with different hydrophobic characters. For mutants with a high intrinsic stability and low intrinsic aggregation rate, we find that amyloid fibril formation is accelerated by nanoparticles. For find the opposite-a retardation of amyloid fibril formation by nanoparticles. Moreover, both catalytic and inhibitory effects are most pronounced with the least hydrophobic nanoparticles, which have a larger surface accessibility of hydrogen-bonding groups in the polymer backbone

A Condensation-Ordering Mechanism in Nanoparticle-Catalyzed Peptide Aggregation

Nanoparticles introduced in living cells are capable of strongly promoting the aggregation of peptides and proteins. We use here molecular dynamics simulations to characterise in detail the process by which nanoparticle surfaces catalyse the self- assembly of peptides into fibrillar structures. The simulation of a system of hundreds of peptides over the millisecond timescale enables us to show that the mechanism of aggregation involves a first phase in which small structurally disordered oligomers assemble onto the nanoparticle and a second phase in which they evolve into highly ordered beta-sheets as their size increases

Microbial diversity arising from thermodynamic constraints

The microbial world displays an immense taxonomic diversity. This diversity is manifested also in a multitude of metabolic pathways that can utilize different substrates and produce different products. Here, we propose that these observations directly link to thermodynamic constraints that inherently arise from the metabolic basis of microbial growth. We show that thermodynamic constraints can enable coexistence of microbes that utilise the same substrate but produce different end products. We find that this thermodynamics-driven emergence of diversity is most relevant for metabolic conversions with low free energy as seen for example under anaerobic conditions, where population dynamics is governed by thermodynamic effects rather than kinetic factors such as substrate uptake rates. These findings provide a general understanding of the microbial diversity based on the first-principles of thermodynamics. As such they provide a thermodynamics-based framework for explaining the observed microbial diversity in different natural and synthetic environments

Dimensionality of Carbon Nanomaterials Determines the Binding and Dynamics of Amyloidogenic Peptides: Multiscale Theoretical Simulations

Experimental studies have demonstrated that nanoparticles can affect the rate of protein self-assembly, possibly interfering with the development of protein misfolding diseases such as Alzheimer's, Parkinson's and prion disease caused by aggregation and fibril formation of amyloid-prone proteins. We employ classical molecular dynamics simulations and large-scale density functional theory calculations to investigate the effects of nanomaterials on the structure, dynamics and binding of an amyloidogenic peptide apoC-II(60-70). We show that the binding affinity of this peptide to carbonaceous nanomaterials such as C60, nanotubes and graphene decreases with increasing nanoparticle curvature. Strong binding is facilitated by the large contact area available for π-stacking between the aromatic residues of the peptide and the extended surfaces of graphene and the nanotube. The highly curved fullerene surface exhibits reduced efficiency for π-stacking but promotes increased peptide dynamics. We postulate that the increase in conformational dynamics of the amyloid peptide can be unfavorable for the formation of fibril competent structures. In contrast, extended fibril forming peptide conformations are promoted by the nanotube and graphene surfaces which can provide a template for fibril-growth