Computational Chemistry Modelling of the Oxidation of Highly Oriented Pyrolitic Graphite (HOPG)

Under high heat flux, carbon based Thermal Protection Systems (TPS) are observed to rapidly ablate and an accurate characterization is essential to their design. Dissociated oxygen atoms (from the gas phase) striking the surface of TPS could lead to several possibilites. The O atom could adsorb on the surface, recombine with another O atom to form O2 and oxidize the surface to produce CO or CO2 resulting in recession of the surface (ablation). The goal is to predict finite rate models for these reactions which could be incorporated into CFD and DSMC solvers. Our efforts are to predict the rates through large scale Molecular Dynamics (MD) simulations using the ReaxFF potential which enables accurate simulation of large chemically reacting systems of molecules. In this work, we simulate the collision of hyperthermal (5eV) O atoms on Highly Oriented Pyrolitic Graphite (HOPG) at 525K. The simulations are compared to molecular beam experiments performed by Minton and co-workers

Is mitochondrial DNA turnover slower than commonly assumed?

Mutations arise during DNA replication due to oxidative lesions and intrinsic polymerase errors. Mitochondrial DNA (mtDNA) mutation rate is therefore closely linked to the mitochondrial DNA turnover process, especially in post mitotic cells. This makes the mitochondrial DNA turnover rate critical for understanding the origin and dynamics of mtDNA mutagenesis in post mitotic cells. Experimental mitochondrial turnover quantification has been based on different mitochondrial macromolecules, such as mitochondrial proteins, lipids and DNA, and the experimental data suggested highly divergent turnover rates, ranging from over 2days to about 1year. In this article we argue that mtDNA turnover rate cannot be as fast as is often envisaged. Using a stochastic model based on the chemical master equation, we show that a turnover rate corresponding to mtDNA half-life in the order of months is the most consistent with published mtDNA mutation level

SYSTEMS BIOLOGY OF AGING: MODELING & ANALYSIS OF MITOCHONDRIAL GENOME INTEGRITY

Ph.DDOCTOR OF PHILOSOPH

Maximizing signal-to-noise ratio in the random mutation capture assay

The ‘Random Mutation Capture' assay allows for the sensitive quantitation of DNA mutations at extremely low mutation frequencies. This method is based on PCR detection of mutations that render the mutated target sequence resistant to restriction enzyme digestion. The original protocol prescribes an end-point dilution to about 0.1 mutant DNA molecules per PCR well, such that the mutation burden can be simply calculated by counting the number of amplified PCR wells. However, the statistical aspects associated with the single molecular nature of this protocol and several other molecular approaches relying on binary (on/off) output can significantly affect the quantification accuracy, and this issue has so far been ignored. The present work proposes a design of experiment (DoE) using statistical modeling and Monte Carlo simulations to obtain a statistically optimal sampling protocol, one that minimizes the coefficient of variance in the measurement estimates. Here, the DoE prescribed a dilution factor at about 1.6 mutant molecules per well. Theoretical results and experimental validation revealed an up to 10-fold improvement in the information obtained per PCR well, i.e. the optimal protocol achieves the same coefficient of variation using one-tenth the number of wells used in the original assay. Additionally, this optimization equally applies to any method that relies on binary detection of a small number of template

Instrumentation Design and Placement for KRUPS Re-Entry Capsules

Atmospheric re-entry flight tests are one of the best ways to evaluate the performance of new Thermal Protection System (TPS) materials. The flight proven Kentucky Re-Entry Payload System (KRUPS) project provides a low cost, quick turnaround platform for these evaluative missions. Following the success of the first KREPE mission, the Krups Flight Computer (KFC) and the instrumentation suite were redesigned for the next mission, KREPE-2. The original suite contained only four thermocouoples. The new design contains six thermocouples, five pressure sensors, a mini-spectrometer, an IMU and an accelerometer

Investigation of the High-Energy Oxidation of FiberForm from DSMC Analysis of Molecular Beam Experiments

A collaborative effort between the University of Illinois at Urbana-Champaign (UIUC), NASA Ames Research Center (ARC) and Montana State University (MSU) succeeded at developing a new finite-rate carbon oxidation model from molecular beam scattering experiments on vitreous carbon (VC). We now aim to use the direct simulation Monte Carlo (DSMC) code SPARTA to apply the model to each fiber of the porous fibrous Thermal Protection Systems (TPS) material FiberForm (FF). The detailed micro-structure of FF was obtained from X-ray micro-tomography and then used in DSMC. Both experiments and simulations show that the CO/O products ratio increased at all temperatures from VC to FF. We postulate this is due to the larger number of collisions an O atom encounters inside the porous FF material compared to the flat surface of VC. For the simulations, we particularly focused on the lowest and highest temperatures studied experimentally, 1023 K and 1823 K, and found good agreement between the finite-rate DSMC simulations and experiments

Single-Nucleus RNA-Seq Is Not Suitable for Detection of Microglial Activation Genes in Humans

Single-nucleus RNA sequencing (snRNA-seq) is used as an alternative to single-cell RNA-seq, as it allows transcriptomic profiling of frozen tissue. However, it is unclear whether snRNA-seq is able to detect cellular state in human tissue. Indeed, snRNA-seq analyses of human brain samples have failed to detect a consistent microglial activation signature in Alzheimer's disease. Our comparison of microglia from single cells and single nuclei of four human subjects reveals that, although most genes show similar relative abundances in cells and nuclei, a small population of genes (∼1%) is depleted in nuclei compared to whole cells. This population is enriched for genes previously implicated in microglial activation, including APOE, CST3, SPP1, and CD74, comprising 18% of previously identified microglial-disease-associated genes. Given the low sensitivity of snRNA-seq to detect many activation genes, we conclude that snRNA-seq is not suited for detecting cellular activation in microglia in human disease

Stochastic modelling, Bayesian inference, and new in vivo measurements elucidate the debated mtDNA bottleneck mechanism

Dangerous damage to mitochondrial DNA (mtDNA) can be ameliorated during mammalian development through a highly debated mechanism called the mtDNA bottleneck. Uncertainty surrounding this process limits our ability to address inherited mtDNA diseases. We produce a new, physically motivated, generalisable theoretical model for mtDNA populations during development, allowing the first statistical comparison of proposed bottleneck mechanisms. Using approximate Bayesian computation and mouse data, we find most statistical support for a combination of binomial partitioning of mtDNAs at cell divisions and random mtDNA turnover, meaning that the debated exact magnitude of mtDNA copy number depletion is flexible. New experimental measurements from a wild-derived mtDNA pairing in mice confirm the theoretical predictions of this model. We analytically solve a mathematical description of this mechanism, computing probabilities of mtDNA disease onset, efficacy of clinical sampling strategies, and effects of potential dynamic interventions, thus developing a quantitative and experimentally-supported stochastic theory of the bottleneck.Comment: Main text: 14 pages, 5 figures; Supplement: 17 pages, 4 figures; Total: 31 pages, 9 figure

The γ-secretase substrate proteome and its role in cell signaling regulation

γ-Secretases mediate the regulated intramembrane proteolysis (RIP) of more than 150 integral membrane proteins. We developed an unbiased γ-secretase substrate identification (G-SECSI) method to study to what extent these proteins are processed in parallel. We demonstrate here parallel processing of at least 85 membrane proteins in human microglia in steady-state cell culture conditions. Pharmacological inhibition of γ-secretase caused substantial changes of human microglial transcriptomes, including the expression of genes related to the disease-associated microglia (DAM) response described in Alzheimer disease (AD). While the overall effects of γ-secretase deficiency on transcriptomic cell states remained limited in control conditions, exposure of mouse microglia to AD-inducing amyloid plaques strongly blocked their capacity to mount this putatively protective DAM cell state. We conclude that γ-secretase serves as a critical signaling hub integrating the effects of multiple extracellular stimuli into the overall transcriptome of the cell.</p

Global parameter identification of stochastic reaction networks from single trajectories

We consider the problem of inferring the unknown parameters of a stochastic biochemical network model from a single measured time-course of the concentration of some of the involved species. Such measurements are available, e.g., from live-cell fluorescence microscopy in image-based systems biology. In addition, fluctuation time-courses from, e.g., fluorescence correlation spectroscopy provide additional information about the system dynamics that can be used to more robustly infer parameters than when considering only mean concentrations. Estimating model parameters from a single experimental trajectory enables single-cell measurements and quantification of cell--cell variability. We propose a novel combination of an adaptive Monte Carlo sampler, called Gaussian Adaptation, and efficient exact stochastic simulation algorithms that allows parameter identification from single stochastic trajectories. We benchmark the proposed method on a linear and a non-linear reaction network at steady state and during transient phases. In addition, we demonstrate that the present method also provides an ellipsoidal volume estimate of the viable part of parameter space and is able to estimate the physical volume of the compartment in which the observed reactions take place.Comment: Article in print as a book chapter in Springer's "Advances in Systems Biology