A Joint Venture of Ab Initio Molecular Dynamics, Coupled Cluster Electronic Structure Methods, and Liquid-State Theory to Compute Accurate Isotropic Hyperfine Constants of Nitroxide Probes in Water

The isotropic hyperfine coupling constant (HFCC, Aiso) of a pH-sensitive spin probe in a solution, HMI (2,2,3,4,5,5-hexamethylimidazolidin-1-oxyl, C9H19N2O) in water, is computed using an ensemble of state-of-the-art computational techniques and is gauged against X-band continuous wave electron paramagnetic resonance (EPR) measurement spectra at room temperature. Fundamentally, the investigation aims to delineate the cutting edge of current first-principles-based calculations of EPR parameters in aqueous solutions based on using rigorous statistical mechanics combined with correlated electronic structure techniques. In particular, the impact of solvation is described by exploiting fully atomistic, RISM integral equation, and implicit solvation approaches as offered by ab initio molecular dynamics (AIMD) of the periodic bulk solution (using the spin-polarized revPBE0-D3 hybrid functional), embedded cluster reference interaction site model integral equation theory (EC-RISM), and polarizable continuum embedding (using CPCM) of microsolvated complexes, respectively. HFCCs are obtained from efficient coupled cluster calculations (using open-shell DLPNO-CCSD theory) as well as from hybrid density functional theory (using revPBE0-D3). Re-solvation of “vertically desolvated” spin probe configuration snapshots by EC-RISM embedding is shown to provide significantly improved results compared to CPCM since only the former captures the inherent structural heterogeneity of the solvent close to the spin probe. The average values of the Aiso parameter obtained based on configurational statistics using explicit water within AIMD and from EC-RISM solvation are found to be satisfactorily close. Using either such explicit or RISM solvation in conjunction with DLPNO-CCSD calculations of the HFCCs provides an average Aiso parameter for HMI in aqueous solution at 300 K and 1 bar that is in good agreement with the experimentally determined one. The developed computational strategy is general in the sense that it can be readily applied to other spin probes of similar molecular complexity, to aqueous solutions beyond ambient conditions, as well as to other solvents in the longer run

Pipeline Comparison for the Pre-Processing of Resting-State Data in Epilepsy

Noise removal is a critical step to recover the signal of interest from resting-state fMRI data. Several pre-processing pipelines have been developed mainly based on nuisance regression or independent component analysis. The aim of this work was to evaluate the ability in removing spurious non-BO LD signals of different cleaning pipelines when applied to a dataset of healthy controls and temporal lobe epilepsy patients. Increased tSNR and power spectral density in the resting-state frequency range (0.01-0.1 Hz) were found for all pre-processing pipelines with respect to the minimally pre-processed data, suggesting a positive gain in terms of temporal properties when optimal cleaning procedures are applied to the acquired fMRI data. All the pre-processing pipelines considered were able to recover the DMN through group ICA. By visually comparing this network across all the pipelines and groups, we found that AROMA, SPM12, FIX and FIXMC were able to better delineate the posterior cingulate cortex

A method for estimation of elasticities in metabolic networks using steady state and dynamic metabolomics data and linlog kinetics

BACKGROUND: Dynamic modeling of metabolic reaction networks under in vivo conditions is a crucial step in order to obtain a better understanding of the (dis)functioning of living cells. So far dynamic metabolic models generally have been based on mechanistic rate equations which often contain so many parameters that their identifiability from experimental data forms a serious problem. Recently, approximative rate equations, based on the linear logarithmic (linlog) format have been proposed as a suitable alternative with fewer parameters. RESULTS: In this paper we present a method for estimation of the kinetic model parameters, which are equal to the elasticities defined in Metabolic Control Analysis, from metabolite data obtained from dynamic as well as steady state perturbations, using the linlog kinetic format. Additionally, we address the question of parameter identifiability from dynamic perturbation data in the presence of noise. The method is illustrated using metabolite data generated with a dynamic model of the glycolytic pathway of Saccharomyces cerevisiae based on mechanistic rate equations. Elasticities are estimated from the generated data, which define the complete linlog kinetic model of the glycolysis. The effect of data noise on the accuracy of the estimated elasticities is presented. Finally, identifiable subset of parameters is determined using information on the standard deviations of the estimated elasticities through Monte Carlo (MC) simulations. CONCLUSION: The parameter estimation within the linlog kinetic framework as presented here allows the determination of the elasticities directly from experimental data from typical dynamic and/or steady state experiments. These elasticities allow the reconstruction of the full kinetic model of Saccharomyces cerevisiae, and the determination of the control coefficients. MC simulations revealed that certain elasticities are potentially unidentifiable from dynamic data only. Addition of steady state perturbation of enzyme activities solved this problem

OptForce: An Optimization Procedure for Identifying All Genetic Manipulations Leading to Targeted Overproductions

Computational procedures for predicting metabolic interventions leading to the overproduction of biochemicals in microbial strains are widely in use. However, these methods rely on surrogate biological objectives (e.g., maximize growth rate or minimize metabolic adjustments) and do not make use of flux measurements often available for the wild-type strain. In this work, we introduce the OptForce procedure that identifies all possible engineering interventions by classifying reactions in the metabolic model depending upon whether their flux values must increase, decrease or become equal to zero to meet a pre-specified overproduction target. We hierarchically apply this classification rule for pairs, triples, quadruples, etc. of reactions. This leads to the identification of a sufficient and non-redundant set of fluxes that must change (i.e., MUST set) to meet a pre-specified overproduction target. Starting with this set we subsequently extract a minimal set of fluxes that must actively be forced through genetic manipulations (i.e., FORCE set) to ensure that all fluxes in the network are consistent with the overproduction objective. We demonstrate our OptForce framework for succinate production in Escherichia coli using the most recent in silico E. coli model, iAF1260. The method not only recapitulates existing engineering strategies but also reveals non-intuitive ones that boost succinate production by performing coordinated changes on pathways distant from the last steps of succinate synthesis

Testing Biochemistry Revisited: How In Vivo Metabolism Can Be Understood from In Vitro Enzyme Kinetics

A decade ago, a team of biochemists including two of us, modeled yeast glycolysis and showed that one of the most studied biochemical pathways could not be quite understood in terms of the kinetic properties of the constituent enzymes as measured in cell extract. Moreover, when the same model was later applied to different experimental steady-state conditions, it often exhibited unrestrained metabolite accumulation

Ecological response of Tethyan benthic foraminifera to the Middle Eocene Climatic Optimum (MECO) from the Alano section (NE Italy)

none3noneBoscolo Galazzo F.; Giusberti L.; Luciani V.BOSCOLO GALAZZO, Flavia; Giusberti, Luca; Luciani, V

Author's personal copy Paleoenvironmental changes during the Middle Eocene Climatic Optimum (MECO) and its aftermath: The benthic foraminiferal record from the Alano section (NE Italy)

This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues. Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. The Middle Eocene Climatic Optimum (MECO) was one of the most severe, short-term global climate perturbations of the Cenozoic that occurred at ca. 40 Ma and was characterized by a gradual 4-6°C temperature increase of intermediate and deep-waters. We investigated the response to the MECO of the deep-sea ecosystem in the central-western Tethys, through a quantitative study of bathyal benthic foraminiferal assemblages in the expanded and continuous Alano section (northeastern Italy), for which data on stratigraphy, lithology, isotope and trace element geochemistry, and calcareous microplankton were available. During the gradual warming of MECO (lasting between 350 and 650 kyr) marine export productivity increased, causing a significant but transient restructuring of benthic foraminiferal faunas, which changed gradually from assemblages typical for oligo-mesotrophic sea floor conditions to assemblages indicative of more eutrophic conditions. Just after the peak MECO conditions, which lasted less than 100 kyr, a prolonged phase of environmental instability (~500 kyr) occurred, marked by even more highly increased export productivity leading to bottom-water oxygen depletion, as reflected in deposition of organic-rich sediments and multiple peaks of bi-triserial opportunistic benthic foraminiferal taxa, including buliminids, bolivinids and uvigerinids. The high productivity may have been caused by a strong influx of nutrient-bearing fresh water into the basin, due to the increased vigour of the hydrological cycle during the warm period, and this increased fresh-water influx might have been a factor in enhancing water column stratification, thus exacerbating the hypoxic conditions, which persisted about 400-500 kyr. After deposition of the organic-rich layers the environmental perturbation ended, and benthic foraminiferal assemblages recovered while conditions became very similar to what they were before the MECO. The environmental disturbance during and directly after the MECO thus strongly but transiently affected benthic foraminiferal assemblages in the central western Tethys