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Resistance to copper (Cu) toxicity in the respiratory pathogen Streptococcus pneumoniae is regulated by the Cu-specific metallosensor CopY. CopY is structurally related to the antibiotic-resistance regulatory proteins MecI and BlaI from Staphylococcus aureus, but is otherwise poorly characterized. Here we employ a multi-pronged experimental strategy to define the Spn CopY coordination chemistry and the unique mechanism of allosteric activation by Zn(II) and allosteric inhibition by Cu(I) of cop promoter DNA binding. We show that Zn(II) is coordinated by a subunit-bridging 3S 1H2O complex formed by the same residues that coordinate Cu(I), as determined by X-ray absorption spectroscopy and ratiometric pulsed alkylation-mass spectrometry (rPA-MS). Apo- and Zn-bound CopY are homodimers by small angle X-ray scattering (SAXS); however, Zn stabilizes the dimer, narrows the conformational ensemble of the apo-state as revealed by ion mobility-mass spectroscopy (IM-MS), and activates DNA binding in vitro and in cells. In contrast, Cu(I) employs the same Cys pair to form a subunit-bridging, kinetically stable, multi-metallic Cu·S cluster (KCu ≈ 1016 M−1) that induces oligomerization beyond the dimer as revealed by SAXS, rPA-MS and NMR spectroscopy, leading to inhibition of DNA binding. These studies suggest that CopY employs conformational selection to drive Zn-activation of DNA binding, and a novel Cu(I)-mediated assembly mechanism that dissociates CopY from the DNA via ligand exchange-catalyzed metal substitution, leading to expression of Cu resistance genes. Mechanistic parallels to antibiotic resistance repressors MecI and BlaI are discussed.

In the brome mosaic virus (BMV) virion, the coat protein (CP) selectively contacts the RNA motifs that regulate translation and RNA replication (Hoover et al., 2016. J. Virol. 90, 7748). We hypothesize that the unstructured N-terminal arm (NTA) of the BMV CP can specifically recognize RNA motifs. Using ion mobility spectrometry-mass spectrometry, we demonstrate that peptides containing the NTA of the CP were found to preferentially bind to an RNA hairpin motif that directs the initiation of BMV RNA synthesis. RNA binding causes the peptide to change from heterogeneous structures to a single family of structures. Fluorescence anisotropy, fluorescence quenching and size exclusion chromatography experiments all confirm that the NTA can specific recognize the RNA motif. The peptide introduced into plants along with BMV virion increased accumulation of the BMV CP and accelerated the rate of minus-strand RNA synthesis. The intrinsically disordered BMV NTA could thus specifically recognize BMV RNAs to affect viral infection.

The cooperativity of ligand binding is central to biological regulation and new approaches are needed to quantify these allosteric relationships. Herein, we exploit a suite of mass spectrometry (MS) experiments to provide novel insights into homotropic Cu-binding cooperativity, gas- phase stabilities and conformational ensembles of the D2- symmetric, homotetrameric copper-sensitive operon repressor (CsoR) as a function of Cu I ligation state. Cu I binding is overall positively cooperative, but is characterized by distinct ligation state-specific cooperativities. Structural transitions occur upon binding the first and fourth Cu I , with the latter occurring with significantly higher cooperativity than previous steps; this results in the formation of a holo-tetramer that is markedly more resistant than apo-, and partially ligated CsoR tetramers toward surface-induced dissociation (SID). The structural, dynamic and thermodynamic origins of cooperativity of ligand binding (allostery) is a subject of considerable interest, motivated by the central role this process plays in the regulation of biological activity. (1) Cooperativity can be positive or negative and involve the binding of the same (homotropic) or different (heterotropic) ligands, often to an homooligomeric protein. (2, 3) Bacterial repressors that function to control transition metal bioavail- ability in cells are typically homodimeric or homotetrameric and minimally bind two "ligands": a DNA operator found upstream of metal-regulated genes and a specific (cognate) transition metal ion(s). (4) Although a robust thermodynamic framework capable of quantifying both homo- and hetero- tropic cooperativity in these systems is available, (5) these ensemble-based methods suffer from the limitation that a specific, partially ligated state can not be studied independ- ently of other states. Such step-wise insights are required to understand allosteric coupling beyond a generally phenom- enological description. (1)

Ion mobility spectrometry-mass spectrometry and Fourier transform infrared spectroscopy (FTIR) techniques were combined with quantum chemical calculations to examine the origin of icosahedral clusters of the amino acid proline. When enantiopure proline solutions are electrosprayed (using nanospray) from 100 mM ammonium acetate, only three peaks are observed in the mass spectrum across a concentration range of five orders of magnitude: a monomer [Pro+H](+) species, favored from 0.001 to 0.01 mM proline concentrations; a dimer [2Pro+H](+) species, the most abundant species for proline concentrations above 0.01 mM; and, the dimer and dodecamer [12Pro+2H](2+) for 1.0 mM and more concentrated proline solutions. Electrospraying racemic D/L-proline solutions from 100 mM ammonium acetate leads to a monomer at low proline concentrations (0.001 to 0.1 mM), and a dimer at higher concentrations (>0.09 mM), as well as a very small population of 8 to 15 Pro clusters that comprise

The dynamics and marginal stability of CopY enable allosteric activation of DNA binding by Zn(ii) and inhibition by Cu(i)., Resistance to copper (Cu) toxicity in the respiratory pathogen Streptococcus pneumoniae is regulated by the Cu-specific metallosensor CopY. CopY is structurally related to the antibiotic-resistance regulatory proteins MecI and BlaI from Staphylococcus aureus, but is otherwise poorly characterized. Here we employ a multi-pronged experimental strategy to define the Spn CopY coordination chemistry and the unique mechanism of allosteric activation by Zn(ii) and allosteric inhibition by Cu(i) of cop promoter DNA binding. We show that Zn(ii) is coordinated by a subunit-bridging 3S 1H2O complex formed by the same residues that coordinate Cu(i), as determined by X-ray absorption spectroscopy and ratiometric pulsed alkylation-mass spectrometry (rPA-MS). Apo- and Zn-bound CopY are homodimers by small angle X-ray scattering (SAXS); however, Zn stabilizes the dimer, narrows the conformational ensemble of the apo-state as revealed by ion mobility-mass spectroscopy (IM-MS), and activates DNA binding in vitro and in cells. In contrast, Cu(i) employs the same Cys pair to form a subunit-bridging, kinetically stable, multi-metallic Cu·S cluster (KCu ≈ 1016 M–1) that induces oligomerization beyond the dimer as revealed by SAXS, rPA-MS and NMR spectroscopy, leading to inhibition of DNA binding. These studies suggest that CopY employs conformational selection to drive Zn-activation of DNA binding, and a novel Cu(i)-mediated assembly mechanism that dissociates CopY from the DNA via ligand exchange-catalyzed metal substitution, leading to expression of Cu resistance genes. Mechanistic parallels to antibiotic resistance repressors MecI and BlaI are discussed.

Background Identifying patients with certain clinical criteria based on manual chart review of doctors’ notes is a daunting task given the massive amounts of text notes in the electronic health records (EHR). This task can be automated using text classifiers based on Natural Language Processing (NLP) techniques along with pattern recognition machine learning (ML) algorithms. The aim of this research is to evaluate the performance of traditional classifiers for identifying patients with Systemic Lupus Erythematosus (SLE) in comparison with a newer Bayesian word vector method. Methods We obtained clinical notes for patients with SLE diagnosis along with controls from the Rheumatology Clinic (662 total patients). Sparse bag-of-words (BOWs) and Unified Medical Language System (UMLS) Concept Unique Identifiers (CUIs) matrices were produced using NLP pipelines. These matrices were subjected to several different NLP classifiers: neural networks, random forests, naïve Bayes, support vector machines, and Word2Vec inversion, a Bayesian inversion method. Performance was measured by calculating accuracy and area under the Receiver Operating Characteristic (ROC) curve (AUC) of a cross-validated (CV) set and a separate testing set. Results We calculated the accuracy of the ICD-9 billing codes as a baseline to be 90.00% with an AUC of 0.900, the shallow neural network with CUIs to be 92.10% with an AUC of 0.970, the random forest with BOWs to be 95.25% with an AUC of 0.994, the random forest with CUIs to be 95.00% with an AUC of 0.979, and the Word2Vec inversion to be 90.03% with an AUC of 0.905. Conclusions Our results suggest that a shallow neural network with CUIs and random forests with both CUIs and BOWs are the best classifiers for this lupus phenotyping task. The Word2Vec inversion method failed to significantly beat the ICD-9 code classification, but yielded promising results. This method does not require explicit features and is more adaptable to non-binary classification tasks. The Word2Vec inversion is hypothesized to become more powerful with access to more data. Therefore, currently, the shallow neural networks and random forests are the desirable classifiers.

We introduce a robotic lake lander test bed that can be operated either stand-alone or as part of a Tier-Scalable Reconnaissance mission architecture to study and field test an integrated hardware and software framework for fully autonomous surface and subsurface exploration and navigation of liquid bodies. The lake lander is equipped with both surface and subsurface sensor technologies. Our particular focus is on Saturn's moon Titan with its hydrocarbon lakes with respect to future missions involving lake landers (e.g., Titan Mare Explorer (TiME) mission), potentially in conjunction with balloons/airships and orbiter-support overhead. This test bed serves as an analog to a Titan unpiloted surface vessel equipped with its own onboard realtime navigation and hazard avoidance system, surface and subsurface exploration sensor suite, and autonomous science investigation software system. As such the test bed helps map out a technical path toward true autonomy for the robotic exploration of the Solar System.

New technologies have enabled students to become active participants in computational simulations of dynamic and complex systems (called Participatory Simulations), providing a "first-person" perspective on complex systems. However, most existing Participatory Simulations have targeted older children, teens, and adults assuming that such concepts are too challenging for younger age groups. This paper, by contrast, presents a design for a Participatory Simulation, called BeeSim, which makes use of wearable computers and targets young children (7-8 years old) to model the behaviors of honeybee nectar collection. In our preliminary user studies, we found that BeeSim contributed to systems understanding and more easily managed group dynamics.