Computational and Systems Biology Advances to Enable Bioagent Agnostic Signatures.

Enumerated threat agent lists have long driven biodefense priorities. The global SARS-CoV-2 pandemic demonstrated the limitations of searching for known threat agents as compared to a more agnostic approach. Recent technological advances are enabling agent-agnostic biodefense, especially through the integration of multi-modal observations of host-pathogen interactions directed by a human immunological model. Although well-developed technical assays exist for many aspects of human-pathogen interaction, the analytic methods and pipelines to combine and holistically interpret the results of such assays are immature and require further investments to exploit new technologies. In this manuscript, we discuss potential immunologically based bioagent-agnostic approaches and the computational tool gaps the community should prioritize filling.

Endotaxial stabilization of 2D charge density waves with long-range order.

Charge density waves are emergent quantum states that spontaneously reduce crystal symmetry, drive metal-insulator transitions, and precede superconductivity. In low-dimensions, distinct quantum states arise, however, thermal fluctuations and external disorder destroy long-range order. Here we stabilize ordered two-dimensional (2D) charge density waves through endotaxial synthesis of confined monolayers of 1T-TaS2. Specifically, an ordered incommensurate charge density wave (oIC-CDW) is realized in 2D with dramatically enhanced amplitude and resistivity. By enhancing CDW order, the hexatic nature of charge density waves becomes observable. Upon heating via in-situ TEM, the CDW continuously melts in a reversible hexatic process wherein topological defects form in the charge density wave. From these results, new regimes of the CDW phase diagram for 1T-TaS2 are derived and consistent with the predicted emergence of vestigial quantum order.

Multimodal analysis for human ex vivo studies shows extensive molecular changes from delays in blood processing.

Multi-omic profiling of human peripheral blood is increasingly utilized to identify biomarkers and pathophysiologic mechanisms of disease. The importance of these platforms in clinical and translational studies led us to investigate the impact of delayed blood processing on the numbers and state of peripheral blood mononuclear cells (PBMC) and on the plasma proteome. Similar to previous studies, we show minimal effects of delayed processing on the numbers and general phenotype of PBMC up to 18 hours. In contrast, profound changes in the single-cell transcriptome and composition of the plasma proteome become evident as early as 6 hours after blood draw. These reflect patterns of cellular activation across diverse cell types that lead to progressive distancing of the gene expression state and plasma proteome from native in vivo biology. Differences accumulating during an overnight rest (18 hours) could confound relevant biologic variance related to many underlying disease states.

Estimating node degree in bait-prey graphs.

MOTIVATION: Proteins work together to drive biological processes in cellular machines. Summarizing global and local properties of the set of protein interactions, the interactome, is necessary for describing cellular systems. We consider a relatively simple per-protein feature of the interactome: the number of interaction partners for a protein, which in graph terminology is the degree of the protein. RESULTS: Using data subject to both stochastic and systematic sources of false positive and false negative observations, we develop an explicit probability model and resultant likelihood method to estimate node degree on portions of the interactome assayed by bait-prey technologies. This approach yields substantial improvement in degree estimation over the current practice that naively sums observed edges. Accurate modeling of observed data in relation to true but unknown parameters of interest gives a formal point of reference from which to draw conclusions about the system under study. AVAILABILITY: All analyses discussed in this text can be performed using the ppiStats and ppiData packages available through the Bioconductor project (http://www.bioconductor.org).

Rintact: enabling computational analysis of molecular interaction data from the IntAct repository.

MOTIVATION: The IntAct repository is one of the largest and most widely used databases for the curation and storage of molecular interaction data. These datasets need to be analyzed by computational methods. Software packages in the statistical environment R provide powerful tools for conducting such analyses. RESULTS: We introduce Rintact, a Bioconductor package that allows users to transform PSI-MI XML2.5 interaction data files from IntAct into R graph objects. On these, they can use methods from R and Bioconductor for a variety of tasks: determining cohesive subgraphs, computing summary statistics, fitting mathematical models to the data or rendering graphical layouts. Rintact provides a programmatic interface to the IntAct repository and allows the use of the analytic methods provided by R and Bioconductor. AVAILABILITY: Rintact is freely available at http://bioconductor.org

Engineering of Ferroelectric HfO2-ZrO2 Nanolaminates.

In this work, the ferroelectric properties of nanolaminates made of HfO2 and ZrO2 were studied as a function of the deposition temperature and the individual HfO2/ZrO2 layer thickness before and after electrical field cycling. The ferroelectric response was found to depend on the structure of the nanolaminates before any postdeposition annealing treatment. After annealing with a TiN cap, an "antiferroelectric-like" response was obtained from nanolaminates deposited in an amorphous state at a lower temperature, whereas a ferroelectric response was obtained from nanolaminates deposited at a higher temperature, where crystallites were detected in thick films before annealing. As the individual layer thicknesses were decreased, an increased lattice distortion and a concurrent increase in remanent polarization were observed from the nanolaminates deposited at high temperatures. After field cycling, nanolaminates deposited at lower temperatures exhibited an antiferroelectric-like to ferroelectric transition, whereas those deposited at higher temperatures exhibited a larger remanent polarization. Finally, we demonstrate that by leveraging the proper choice of process conditions and layer thickness, remanent polarizations exceeding those of the HfZrO4 solid solution can be obtained.

Chromatographic behavior of oxygenated derivatives of cholesterol.

Oxygenated derivatives of cholesterol have important functions in many biochemical processes. These oxysterols are difficult to study because of their low physiological concentrations, the facile formation of cholesterol autoxidation artifacts, and lack of information on their chromatographic behavior. Focusing on metabolites and autoxidation products of cholesterol, we have documented the chromatographic mobilities of 35 oxysterols under a variety of conditions: eight solvent systems for thin-layer chromatography on silica gel, several mobile phases for reversed-phase high-performance liquid chromatography (HPLC), and two types of stationary phase for capillary gas chromatography (GC) using trimethylsilyl derivatives. Notable differences in selectivity could be obtained by modifying the stationary or mobile phases. Separations of oxysterol pairs isomeric at side-chain carbons or C-7 were achieved on normal-phase, reversed-phase, chiral, or silver-ion HPLC columns. Chromatographic behavior is also described for side-chain hexadeuterated and heptafluorinated oxysterols, which are useful as standards in isotope dilution analyses and autoxidation studies, respectively. The overall results are relevant to many problems of oxysterol analysis, including the initial separation of oxysterols from cholesterol, determination of highly polar and nonpolar oxysterols, separation of isomeric pairs, selection of derivatization conditions for GC analysis, and quantitation of the extent of cholesterol autoxidation.

A general pipeline for quality and statistical assessment of protein interaction data using R and Bioconductor.

The systematic mapping of protein interactions by bait-prey techniques, including affinity purification-mass spectrometry or the yeast two-hybrid system, contributes a unique and relevant perspective on the comprehensive picture of cellular machines. We describe here a protocol for statistical analysis of node-and-edge graph representations of these data using R and Bioconductor, recognizing that steps may be added or omitted depending on the data set at hand. The fundamental purpose of such analyses is feature estimation, defined here as the estimation of data-type-specific biological features, such as protein complex composition and the physical interaction integrity of known or estimated complexes. In preparation for feature estimation tasks, we outline a progression through three analytic components common to all bait-prey data types: preliminary setup, exploratory analysis and quality assessment. The end result is a collection of descriptive and inferred characteristics of the data, ready for biological interpretation in a computationally tractable form.

Coverage and error models of protein-protein interaction data by directed graph analysis.

Using a directed graph model for bait to prey systems and a multinomial error model, we assessed the error statistics in all published large-scale datasets for Saccharomyces cerevisiae and characterized them by three traits: the set of tested interactions, artifacts that lead to false-positive or false-negative observations, and estimates of the stochastic error rates that affect the data. These traits provide a prerequisite for the estimation of the protein interactome and its modules.