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Item A Choose-Your-Own-Adventure-Style Virtual Lab Activity(American Chemical Society, 2021) Warning, Lauren A.; Kobylianskii, KristaEspecially in the wake of the recent COVID-19 pandemic, which has caused universities across the globe to suspend in-person classes, online alternatives for laboratory activities are needed. Here, we report a choose-your-own-adventure (CYOA)-style activity, in which undergraduate general chemistry students influence the observed outcome of a prerecorded electrochemistry lab experiment. During the activity, students decide how to build an electrochemical cell by varying experimental parameters including electrode charge, power source voltage, and salt addition. We show evidence that students’ understanding of electrochemistry concepts improved after completing the CYOA-style activity. We propose that CYOA-style activities strike a good balance between the demand for instructor time and student opportunity to develop laboratory decision-making skills. We suggest the use of CYOA-style activities as a better alternative to simply having students watch prerecorded videos of laboratory experiments when a traditional in-laboratory activity is impossible.Item A collagen glucosyltransferase drives lung adenocarcinoma progression in mice(Springer Nature, 2021) Guo, Hou-Fu; Bota-Rabassedas, Neus; Terajima, Masahiko; Leticia Rodriguez, B.; Gibbons, Don L.; Chen, Yulong; Banerjee, Priyam; Tsai, Chi-Lin; Tan, Xiaochao; Liu, Xin; Yu, Jiang; Tokmina-Roszyk, Michal; Stawikowska, Roma; Fields, Gregg B.; Miller, Mitchell D.; Wang, Xiaoyan; Lee, Juhoon; Dalby, Kevin N.; Creighton, Chad J.; Phillips, George N.Jr.; Tainer, John A.; Yamauchi, Mitsuo; Kurie, Jonathan M.Cancer cells are a major source of enzymes that modify collagen to create a stiff, fibrotic tumor stroma. High collagen lysyl hydroxylase 2 (LH2) expression promotes metastasis and is correlated with shorter survival in lung adenocarcinoma (LUAD) and other tumor types. LH2 hydroxylates lysine (Lys) residues on fibrillar collagen’s amino- and carboxy-terminal telopeptides to create stable collagen cross-links. Here, we show that electrostatic interactions between the LH domain active site and collagen determine the unique telopeptidyl lysyl hydroxylase (tLH) activity of LH2. However, CRISPR/Cas-9-mediated inactivation of tLH activity does not fully recapitulate the inhibitory effect of LH2 knock out on LUAD growth and metastasis in mice, suggesting that LH2 drives LUAD progression, in part, through a tLH-independent mechanism. Protein homology modeling and biochemical studies identify an LH2 isoform (LH2b) that has previously undetected collagen galactosylhydroxylysyl glucosyltransferase (GGT) activity determined by a loop that enhances UDP-glucose-binding in the GLT active site and is encoded by alternatively spliced exon 13 A. CRISPR/Cas-9-mediated deletion of exon 13 A sharply reduces the growth and metastasis of LH2b-expressing LUADs in mice. These findings identify a previously unrecognized collagen GGT activity that drives LUAD progression.Item A Data-Driven Perspective on the Hierarchical Assembly of Molecular Structures(American Chemical Society, 2018) Boninsegna, Lorenzo; Banisch, Ralf; Clementi, Cecilia; Center for Theoretical Biological PhysicsMacromolecular systems are composed of a very large number of atomic degrees of freedom. There is strong evidence suggesting that structural changes occurring in large biomolecular systems at long time scale dynamics may be captured by models coarser than atomistic, although a suitable or optimal coarse-graining is a priori unknown. Here we propose a systematic approach to learning a coarse representation of a macromolecule from microscopic simulation data. In particular, the definition of effective coarse variables is achieved by partitioning the degrees of freedom both in the structural (physical) space and in the conformational space. The identification of groups of microscopic particles forming dynamical coherent states in different metastable states leads to a multiscale description of the system, in space and time. The application of this approach to the folding dynamics of two proteins provides a revised view of the classical idea of prestructured regions (foldons) that combine during a protein-folding process and suggests a hierarchical characterization of the assembly process of folded structures.Item A deep learning solution for crystallographic structure determination(International Union of Crystallography, 2023) Pan, T.; Jin, S.; Miller, M. D.; Kyrillidis, A.; Phillips, G. N.The general de novo solution of the crystallographic phase problem is difficult and only possible under certain conditions. This paper develops an initial pathway to a deep learning neural network approach for the phase problem in protein crystallography, based on a synthetic dataset of small fragments derived from a large well curated subset of solved structures in the Protein Data Bank (PDB). In particular, electron-density estimates of simple artificial systems are produced directly from corresponding Patterson maps using a convolutional neural network architecture as a proof of concept.Item A deterministic model for one-dimensional excluded flow with local interactions(Public Library of Science, 2017) Zarai, Yoram; Margaliot, Michael; Kolomeisky, Anatoly B.Natural phenomena frequently involve a very large number of interacting molecules moving in confined regions of space. Cellular transport by motor proteins is an example of such collective behavior. We derive a deterministic compartmental model for the unidirectional flow of particles along a one-dimensional lattice of sites with nearest-neighbor interactions between the particles. The flow between consecutive sites is governed by a “soft” simple exclusion principle and by attracting or repelling forces between neighboring particles. Using tools from contraction theory, we prove that the model admits a unique steady-state and that every trajectory converges to this steady-state. Analysis and simulations of the effect of the attracting and repelling forces on this steady-state highlight the crucial role that these forces may play in increasing the steady-state flow, and reveal that this increase stems from the alleviation of traffic jams along the lattice. Our theoretical analysis clarifies microscopic aspects of complex multi-particle dynamic processes.Item A general theoretical framework to design base editors with reduced bystander effects(Springer Nature, 2021) Wang, Qian; Yang, Jie; Zhong, Zhicheng; Vanegas, Jeffrey A.; Gao, Xue; Kolomeisky, Anatoly B.; Center for Theoretical Biological PhysicsBase editors (BEs) hold great potential for medical applications of gene therapy. However, high precision base editing requires BEs that can discriminate between the target base and multiple bystander bases within a narrow active window (4 – 10 nucleotides). Here, to assist in the design of these optimized editors, we propose a discrete-state stochastic approach to build an analytical model that explicitly evaluates the probabilities of editing the target base and bystanders. Combined with all-atom molecular dynamic simulations, our model reproduces the experimental data of A3A-BE3 and its variants for targeting the “TC” motif and bystander editing. Analyzing this approach, we propose several general principles that can guide the design of BEs with a reduced bystander effect. These principles are then applied to design a series of point mutations at T218 position of A3G-BEs to further reduce its bystander editing. We verify experimentally that the new mutations provide different levels of stringency on reducing the bystander editing at different genomic loci, which is consistent with our theoretical model. Thus, our study provides a computational-aided platform to assist in the scientifically-based design of BEs with reduced bystander effects.Item A litmus test for classifying recognition mechanisms of transiently binding proteins(Springer Nature, 2022) Chakrabarti, Kalyan S.; Olsson, Simon; Pratihar, Supriya; Giller, Karin; Overkamp, Kerstin; Lee, Ko On; Gapsys, Vytautas; Ryu, Kyoung-Seok; de Groot, Bert L.; Noé, Frank; Becker, Stefan; Lee, Donghan; Weikl, Thomas R.; Griesinger, ChristianPartner recognition in protein binding is critical for all biological functions, and yet, delineating its mechanism is challenging, especially when recognition happens within microseconds. We present a theoretical and experimental framework based on straight-forward nuclear magnetic resonance relaxation dispersion measurements to investigate protein binding mechanisms on sub-millisecond timescales, which are beyond the reach of standard rapid-mixing experiments. This framework predicts that conformational selection prevails on ubiquitin’s paradigmatic interaction with an SH3 (Src-homology 3) domain. By contrast, the SH3 domain recognizes ubiquitin in a two-state binding process. Subsequent molecular dynamics simulations and Markov state modeling reveal that the ubiquitin conformation selected for binding exhibits a characteristically extended C-terminus. Our framework is robust and expandable for implementation in other binding scenarios with the potential to show that conformational selection might be the design principle of the hubs in protein interaction networks.Item A magnesium-induced triplex pre-organizes the SAM-II riboswitch(Public Library of Science, 2017) Roy, Susmita; Lammert, Heiko; Hayes, Ryan L.; Chen, Bin; LeBlanc, Regan; Dayie, T.Kwaku; Onuchic, José Nelson; Sanbonmatsu, Karissa Y.; Center for Theoretical Biological PhysicsOur 13C- and 1H-chemical exchange saturation transfer (CEST) experiments previously revealed a dynamic exchange between partially closed and open conformations of the SAM-II riboswitch in the absence of ligand. Here, all-atom structure-based molecular simulations, with the electrostatic effects of Manning counter-ion condensation and explicit magnesium ions are employed to calculate the folding free energy landscape of the SAM-II riboswitch. We use this analysis to predict that magnesium ions remodel the landscape, shifting the equilibrium away from the extended, partially unfolded state towards a compact, pre-organized conformation that resembles the ligand-bound state. Our CEST and SAXS experiments, at different magnesium ion concentrations, quantitatively confirm our simulation results, demonstrating that magnesium ions induce collapse and pre-organization. Agreement between theory and experiment bolsters microscopic interpretation of our simulations, which shows that triplex formation between helix P2b and loop L1 is highly sensitive to magnesium and plays a key role in pre-organization. Pre-organization of the SAM-II riboswitch allows rapid detection of ligand with high selectivity, which is important for biological function.Item A mechanism-based computational model to capture the interconnections among epithelial-mesenchymal transition, cancer stem cells and Notch-Jagged signaling(Oncotarget, 2018) Bocci, Federico; Jolly, Mohit Kumar; George, Jason Thomas; Levine, Herbert; Onuchic, José Nelson; Center for Theoretical Biological PhysicsEpithelial-mesenchymal transition (EMT) and cancer stem cell (CSCs) formation are two fundamental and well-studied processes contributing to cancer metastasis and tumor relapse. Cells can undergo a partial EMT to attain a hybrid epithelial/mesenchymal (E/M) phenotype or a complete EMT to attain a mesenchymal one. Similarly, cells can reversibly gain or lose 'stemness'. This plasticity in cell states is modulated by signaling pathways such as Notch. However, the interconnections among the cell states enabled by EMT, CSCs and Notch signaling remain elusive. Here, we devise a computational model to investigate the coupling among the core decision-making circuits for EMT, CSCs and Notch. Our model predicts that hybrid E/M cells are most likely to associate with stem-like traits and enhanced Notch-Jagged signaling – a pathway implicated in therapeutic resistance. Further, we show that the position of the 'stemness window' on the 'EMT axis' is varied by altering the coupling strength between EMT and CSC circuits, and/or modulating Notch signaling. Finally, we analyze the gene expression profile of CSCs from several cancer types and observe a heterogeneous distribution along the 'EMT axis', suggesting that different subsets of CSCs may exist with varying phenotypes along the epithelial-mesenchymal axis. We further investigate therapeutic perturbations such as treatment with metformin, a drug associated with decreased cancer incidence and increased lifespan of patients. Our mechanism-based model explains how metformin can both inhibit EMT and blunt the aggressive potential of CSCs simultaneously, by driving the cells out of a hybrid E/M stem-like state with enhanced Notch-Jagged signaling.Item A Multiplexable, Microfluidic Platform for the Rapid Quantitation of a Biomarker Panel for Early Ovarian Cancer Detection at the Point-of-Care(American Association for Cancer Research, 2015) Shadfan, Basil H.; Simmons, Archana R.; Simmons, Glennon W.; Ho, Andy; Wong, Jorge; Lu, Karen H.; Bast, Robert C. Jr.; McDevitt, John T.Point-of-care (POC) diagnostic platforms have the potential to enable low-cost, large-scale screening. As no single biomarker is shed by all ovarian cancers, multiplexed biomarker panels promise improved sensitivity and specificity to address the unmet need for early detection of ovarian cancer. We have configured the programmable bio-nano-chip (p-BNC)-a multiplexable, microfluidic, modular platform-to quantify a novel multi-marker panel comprising CA125, HE4, MMP-7, and CA72-4. The p-BNC is a bead-based immunoanalyzer system with a credit-card-sized footprint that integrates automated sample metering, bubble and debris removal, reagent storage and waste disposal, permitting POC analysis. Multiplexed p-BNC immunoassays demonstrated high specificity, low cross-reactivity, low limits of detection suitable for early detection, and a short analysis time of 43 minutes. Day-to-day variability, a critical factor for longitudinally monitoring biomarkers, ranged between 5.4% and 10.5%, well below the biologic variation for all four markers. Biomarker concentrations for 31 late-stage sera correlated well (R(2) = 0.71 to 0.93 for various biomarkers) with values obtained on the Luminex platform. In a 31 patient cohort encompassing early- and late-stage ovarian cancers along with benign and healthy controls, the multiplexed p-BNC panel was able to distinguish cases from controls with 68.7% sensitivity at 80% specificity. Utility for longitudinal biomarker monitoring was demonstrated with prediagnostic plasma from 2 cases and 4 controls. Taken together, the p-BNC shows strong promise as a diagnostic tool for large-scale screening that takes advantage of faster results and lower costs while leveraging possible improvement in sensitivity and specificity from biomarker panels.Item A Nanostructured Synthetic Collagen Mimic for Hemostasis(American Chemical Society, 2014) Kumar, Vivek A.; Taylor, Nichole L.; Jalan, Abhishek A.; Hwang, Lyahn K.; Wang, Benjamin K.; Hartgerink, Jeffrey D.Collagen is a major component of the extracellular matrix and plays a wide variety of important roles in blood clotting, healing, and tissue remodeling. Natural, animal derived, collagen is used in many clinical applications but concerns exist with respect to its role in inflammation, batch-to-batch variability, and possible disease transfection. Therefore, development of synthetic nanomaterials that can mimic the nanostructure and properties of natural collagen has been a heavily pursued goal in biomaterials. Previously, we reported on the design and multihierarchial self-assembly of a 36 amino acid collagen mimetic peptide (KOD) that forms nanofibrous triple helices that entangle to form a hydrogel. In this report, we utilize this nanofiber forming collagen mimetic peptide as a synthetic biomimetic matrix useful in thrombosis. We demonstrate that nanofibrous KOD synthetic collagen matrices adhere platelets, activate them (indicated by soluble P-selectin secretion), and clot plasma and blood similar to animal derived collagen and control surfaces. In addition to the thrombotic potential, THP-1 monocytes incubated with our KOD collagen mimetic showed minimal proinflammatory cytokine (TNF-α or IL-1β) production. Together, the data presented demonstrates the potential of a novel synthetic collagen mimetic as a hemostat.Item A New High-Performance Gadonanotube-Polymer Hybrid Material for Stem Cell Labeling and Tracking by MRI(Hindawi, 2018) Moghaddam, Sakineh E.; Hernández-Rivera, Mayra; Zaibaq, Nicholas G.; Ajala, Afis; Cabreira-Hansen, Maria da Graça; Mowlazadeh-Haghighi, Saghar; Willerson, James T.; Perin, Emerson C.; Muthupillai, Raja; Wilson, Lon J.A gentle, rapid method has been developed to introduce a polyacrylic acid (PAA) polymer coating on the surface of gadonanotubes (GNTs) which significantly increases their dispersibility in water without the need of a surfactant. As a result, the polymer, with its many carboxylic acid groups, coats the surface of the GNTs to form a new GNT-polymer hybrid material (PAA-GNT) which can be highly dispersed in water (ca. 20 mg·mL−1) at physiological pH. When dispersed in water, the new PAA-GNT material is a powerful MRI contrast agent with an extremely short water proton spin-lattice relaxation time (T1) which results in a T1-weighted relaxivity of 150 mM−1·s−1 per Gd3+ ion at 1.5 T. Furthermore, the PAA-GNTs have been used to safely label porcine bone-marrow-derived mesenchymal stem cells for magnetic resonance imaging. The labeled cells display excellent image contrast in phantom imaging experiments, and transmission electron microscopy images of the labeled cells reveal the presence of highly dispersed PAA-GNTs within the cytoplasm with 1014 Gd3+ ions per cell.Item A New Imaging Platform for Visualizing Biological Effects of Non-Invasive Radiofrequency Electric-Field Cancer Hyperthermia(Public Library of Science, 2015) Corr, Stuart J.; Shamsudeen, Sabeel; Vergara, Leoncio A.; Ho, Jason Chak-Shing; Ware, Matthew J.; Keshishian, Vazrik; Yokoi, Kenji; Savage, David J.; Meraz, Ismail M.; Kaluarachchi, Warna; Cisneros, Brandon T.; Raoof, Mustafa; Nguyen, Duy Trac; Zhang, Yingchun; Wilson, Lon J.; Summers, Huw; Rees, Paul; Curley, Steven A.; Serda, Rita E.Herein, we present a novel imaging platform to study the biological effects of non-invasive radiofrequency (RF) electric field cancer hyperthermia. This system allows for real-time in vivointravital microscopy (IVM) imaging of radiofrequency-induced biological alterations such as changes in vessel structure and drug perfusion. Our results indicate that the IVM system is able to handle exposure to high-power electric-fields without inducing significant hardware damage or imaging artifacts. Furthermore, short durations of low-power (< 200 W) radiofrequency exposure increased transport and perfusion of fluorescent tracers into the tumors at temperatures below 41°C. Vessel deformations and blood coagulation were seen for tumor temperatures around 44°C. These results highlight the use of our integrated IVM-RF imaging platform as a powerful new tool to visualize the dynamics and interplay between radiofrequency energy and biological tissues, organs, and tumors.Item A New Theoretical Approach to Analyze Complex Processes in Cytoskeleton Proteins(American Chemical Society, 2014) Li, Xin; Kolomeisky, Anatoly B.; Center for Theoretical Biological PhysicsCytoskeleton proteins are filament structures that support a large number of important biological processes. These dynamic biopolymers exist in non-equilibrium conditions stimulated by hydrolysis chemical reactions in their monomers. Current theoretical methods provide a comprehensive picture of biochemical and biophysical processes in cytoskeleton proteins. However, the description is only qualitative at biologically relevant conditions because utilized theoretical mean-field models neglect correlations. We develop a new theoretical method to describe dynamic processes in cytoskeleton proteins that takes into account spatial correlations in the chemical composition of these biopolymers. Our approach is based on analysis of probabilities of different clusters of subunits. It allows us to obtain exact analytical expressions for a variety of dynamic properties of cytoskeleton filaments. By comparing theoretical predictions with Monte Carlo computer simulations it is shown that our method provides a fully quantitative description of complex dynamic phenomena in cytoskeleton proteins at all conditions.Item A photochemical C=C cleavage process: toward access to backbone N-formyl peptides(Beilstein-Institut, 2021) Wang, Haopei; Ball, Zachary T.Photo-responsive modifications and photo-uncaging concepts are useful for spatiotemporal control of peptides structure and function. While side chain photo-responsive modifications are relatively common, access to photo-responsive modifications of backbone N–H bonds is quite limited. This letter describes a new photocleavage pathway, affording N-formyl amides from vinylogous nitroaryl precursors under physiologically relevant conditions via a formal oxidative C=C cleavage. The N-formyl amide products have unique properties and reactivity, but are difficult or impossible to access by traditional synthetic approaches.Item A room-temperature mid-infrared photodetector for on-chip molecular vibrational spectroscopy(AIP Publishing, 2018) Zheng, Bob; Zhao, Hangqi; Cerjan, Ben; Yazdi, Sadegh; Ringe, Emilie; Nordlander, Peter; Halas, Naomi J.; Laboratory for NanophotonicsInfrared (IR) photodetection is of major scientific and technical interest since virtually all molecules exhibit characteristic vibrational modes in the mid-infrared region of the spectrum, giving rise to molecular spectroscopy and chemical imaging in this wavelength range. High-resolution IR spectroscopies, such as Fourier Transform IR spectroscopy, typically require large, bulky optical measurement systems and expensive photodetector components. Here, we present a high-responsivity photodetector for the mid-IR spectral region which operates at room temperature. Fabricated from silicon and aluminum, the photodetection mechanism is based on free carrier absorption, giving rise to a photoresponse rivalling commercially available cooled IR photodetectors. We demonstrate that infrared spectra of molecules deposited on this detector can be obtained by a direct electrical read-out. This work could pave the way for simple, fully integrated chemical sensors and other applications, such as chemical imaging, which would benefit from the combination of mid-IR detection, room-temperature operation, and ultracompact portability.Item A scientific machine learning framework to understand flash graphene synthesis(Royal Society of Chemistry, 2023) Sattari, Kianoosh; Eddy, Lucas; Beckham, Jacob L.; Wyss, Kevin M.; Byfield, Richard; Qian, Long; Tour, James M.; Lin, Jian; NanoCarbon Center; Welch Institute for Advanced MaterialsFlash Joule heating (FJH) is a far-from-equilibrium (FFE) processing method for converting low-value carbon-based materials to flash graphene (FG). Despite its promises in scalability and performance, attempts to explore the reaction mechanism have been limited due to the complexities involved in the FFE process. Data-driven machine learning (ML) models effectively account for the complexities, but the model training requires a considerable amount of experimental data. To tackle this challenge, we constructed a scientific ML (SML) framework trained by using both direct processing variables and indirect, physics-informed variables to predict the FG yield. The indirect variables include current-derived features (final current, maximum current, and charge density) predicted from the proxy ML models and reaction temperatures simulated from multi-physics modeling. With the combined indirect features, the final ML model achieves an average R2 score of 0.81 ± 0.05 and an average RMSE of 12.1% ± 2.0% in predicting the FG yield, which is significantly higher than the model trained without them (R2 of 0.73 ± 0.05 and an RMSE of 14.3% ± 2.0%). Feature importance analysis validates the key roles of these indirect features in determining the reaction outcome. These results illustrate the promise of this SML to elucidate FFE material synthesis outcomes, thus paving a new avenue to processing other datasets from the materials systems involving the same or different FFE processes.Item A single molecule immunoassay by localized surface plasmon resonance(IOP Publishing, 2010) Mayer, Kathryn M.; Hao, Feng; Lee, Seunghyun; Nordlander, Peter; Hafner, Jason H.Item A structural dynamics model for how CPEB3 binding to SUMO2 can regulate translational control in dendritic spines(Public Library of Science, 2022) Gu, Xinyu; Schafer, Nicholas P.; Bueno, Carlos; Lu, Wei; Wolynes, Peter G.; Center for Theoretical Biological PhysicsA prion-like RNA-binding protein, CPEB3, can regulate local translation in dendritic spines. CPEB3 monomers repress translation, whereas CPEB3 aggregates activate translation of its target mRNAs. However, the CPEB3 aggregates, as long-lasting prions, may raise the problem of unregulated translational activation. Here, we propose a computational model of the complex structure between CPEB3 RNA-binding domain (CPEB3-RBD) and small ubiquitin-like modifier protein 2 (SUMO2). Free energy calculations suggest that the allosteric effect of CPEB3-RBD/SUMO2 interaction can amplify the RNA-binding affinity of CPEB3. Combining with previous experimental observations on the SUMOylation mode of CPEB3, this model suggests an equilibrium shift of mRNA from binding to deSUMOylated CPEB3 aggregates to binding to SUMOylated CPEB3 monomers in basal synapses. This work shows how a burst of local translation in synapses can be silenced following a stimulation pulse, and explores the CPEB3/SUMO2 interplay underlying the structural change of synapses and the formation of long-term memories.Item A symmetrical method to obtain shear moduli from microrheology(Royal Society of Chemistry, 2018) Nishi, Kengo; Kilfoil, Maria L.; Schmidt, Christoph F.; MacKintosh, F.C.Passive microrheology typically deduces shear elastic loss and storage moduli from displacement time series or mean-squared displacements (MSD) of thermally fluctuating probe particles in equilibrium materials. Common data analysis methods use either Kramers–Kronig (KK) transformation or functional fitting to calculate frequency-dependent loss and storage moduli. We propose a new analysis method for passive microrheology that avoids the limitations of both of these approaches. In this method, we determine both real and imaginary components of the complex, frequency-dependent response function χ(ω) = χ′(ω) + iχ′′(ω) as direct integral transforms of the MSD of thermal particle motion. This procedure significantly improves the high-frequency fidelity of χ(ω) relative to the use of KK transformation, which has been shown to lead to artifacts in χ′(ω). We test our method on both model and experimental data. Experiments were performed on solutions of worm-like micelles and dilute collagen solutions. While the present method agrees well with established KK-based methods at low frequencies, we demonstrate significant improvement at high frequencies using our symmetric analysis method, up to almost the fundamental Nyquist limit.