Both Ligand- and Cell-Specific Parameters Control Ligand Agonism in a Kinetic Model of G Protein–Coupled Receptor Signaling

G protein–coupled receptors (GPCRs) exist in multiple dynamic states (e.g., ligand-bound, inactive, G protein–coupled) that influence G protein activation and ultimately response generation. In quantitative models of GPCR signaling that incorporate these varied states, parameter values are often uncharacterized or varied over large ranges, making identification of important parameters and signaling outcomes difficult to intuit. Here we identify the ligand- and cell-specific parameters that are important determinants of cell-response behavior in a dynamic model of GPCR signaling using parameter variation and sensitivity analysis. The character of response (i.e., positive/neutral/inverse agonism) is, not surprisingly, significantly influenced by a ligand's ability to bias the receptor into an active conformation. We also find that several cell-specific parameters, including the ratio of active to inactive receptor species, the rate constant for G protein activation, and expression levels of receptors and G proteins also dramatically influence agonism. Expressing either receptor or G protein in numbers several fold above or below endogenous levels may result in system behavior inconsistent with that measured in endogenous systems. Finally, small variations in cell-specific parameters identified by sensitivity analysis as significant determinants of response behavior are found to change ligand-induced responses from positive to negative, a phenomenon termed protean agonism. Our findings offer an explanation for protean agonism reported in β2-adrenergic and α2A-adrenergic receptor systems

Pathogenic DNA detection using DNA hairpins: a Non-Linear Hybridization Chain Reaction Platform

Currently, 3.2 billion people are at risk of being infected with malaria, with 1.2 billion of those being at high risk (\u3e1 in 1000 chance of getting malaria in a year). Thus, there is a need for a biosensor that is highly sensitive, cost effective, and simple to use for point-of-care diagnosis. The biosensing platform, PathVis, has achieved this by measuring changes in fluid properties after a loop-mediated isothermal amplification (LAMP). LAMP is a DNA amplification system that requires enzymes and a temperature of 65degrees C. LAMP currently limits PathVis by being costly, requiring refrigeration, and difficult to design. We seek to overcome these limitations by replacing this reaction with a non-enzymatic, low-cost, shelf stable, room temperature DNA amplification reaction. The hybridization chain reaction system (HCR) consists of two DNA hairpins that polymerize into long chains in the presence of target DNA. HCR can be designed to grow as linear polymers or branching polymers, the ladder providing exponential signal growth. We have developed an algorithm to generate hairpin systems for a given target DNA sequence. Using this algorithm, we have developed a branching HCR system for detecting malaria. We have found that this algorithm is extremely versatile and can generate hairpin systems for whole chromosomes (\u3e1,000,000 base pairs) in under five minutes. We have found that this malaria detection system theoretically amplifies in the presence of its target; resulting in a system that is ready to be optimized, experimentally tested, and validated on the PathVis biosensing platform

Competitive Tuning of Calmodulin Target Protein Activation Drives E-LTP Induction in CA1 Hippocampal Neurons

A number of neurological disorders are caused by disruptions in dynamic neuronal connections called synapses. Normally, electrical activity between neurons activates protein cascades that cause long-lasting, localized changes in the structure and molecular composition of synapses. These changes either increase or decrease the strength of synaptic connections, leading to long-term-potentiation (LTP) or long-term-depression (LTD), respectively. The protein cascades responsible for this synaptic plasticity are initiated in a stimulus-dependent manner by the Ca2+ sensor calmodulin (CaM). Ultimately, it is disruptions within these signaling pathways that cause disease. Traditionally, these protein networks are studied in the laboratory, but limitations in existing experimental technology have created demand for computational models capable of predicting molecular phenomena. These predictions can then guide focused experimental investigations. Although CaM binds and regulates over 100 different target proteins, the competitive dynamics of these proteins and their effect on LTP induction have not been investigated. Using a system of ordinary differential equations to model competition between four neuronal CaM target proteins, we found that the stimulus-dependence of target protein activation is tuned by competition and that this competitive tuning is unique to each protein. We therefore conclude that competition-free models fail to capture the true stimulus-dependence of Ca2+/calmodulin-dependent protein kinase II (CaMKII) and protein phosphatase 2B (PP2B/calcineurin/CaN) activation. Furthermore, these results suggest that competitive tuning drives early LTP (E-LTP) induction in CA1 hippocampal neurons and is an important dynamic process underlying learning and memory. Therapeutics that re-tune CaM-dependent proteins through competition may be useful in treating neurological disorders

Selective Protein Labelling to Visualize Cellular Differentiation

Protein post-translational modifications serve to give proteins new cellular function, spatial localization, or enzymatic activity. Myristoylation is a common post-translational modification where the enzyme N-myristoyltransferase adds myristic acid onto the N-terminus of a variety of proteins. In this work we use a myristic acid analog, 12-azidododecanoic acid (12ADA) to facilitate the implementation of azide-alkyne cycloaddition reactions on myristoylated proteins. Selective protein labeling methods such as these are useful in research because they can be used to help determine the biological function of this protein lipid modification and can be extended to study disregulated protein myristoylation in disease states. To validate 12ADA incorporation onto proteins, C2C12 myoblast cell lysates were reacted with an alkyne functionalized fluorophore and analyzed via SDS-PAGE. In order to visualize 12ADA tagged proteins in vivo, fixed C2C12 cells were reacted with an alkyne functionalized fluorophore and were imaged with a fluorescent microscope. The results clearly indicate selective protein tagging in in vitro lysates and in vivo. There is a distinct difference in the patterning of 12ADA protein tagging between differentiated and non-differentiated cells. The purpose of this research is to develop a selective protein labeling method. In our research, this selective protein labeling method is used to studying cellular differentiation in the context of developmental biology. Currently, there is not a clear understanding of the proteins associated with cellular differentiation related to development. Understanding this can allow scientists to track development progress and understand unique proteins associated with differentiating cells

Bioconjugation of N-terminal Functionalized Ca2+/Calmodulin-Dependent Protein Kinase II (CaMKII) on Magnetic Beads

Protein purification is a fundamental step that commonly precedes structural and functional characterization of proteins. Most of the current protein purification methods are laborious and time consuming due to the multistep nature of the process. Searching for alternative methods that are capable of shortening the purification time and simultaneously enhancing the purity of the purified proteins is therefore needed. The method described in this paper entails surface immobilization of the protein of interest on alkyne-functionalized magnetic beads following selective labeling of the protein’s N-terminus with an azide tag. The utility of this method was tested using Ca2+/calmodulin-dependent protein kinase II (CaMKII). Four variants of azide-tagged CaMKII were used in our study. The four proteins readily conjugated to alkyne-functionalized magnetic beads. Additionally, conjugated proteins retain functionality comparable to purified proteins. This method can therefore advance the research industry by providing a reliable and easy way to purify proteins and perform rapid enzyme assays. It also allows researchers to focus on the actual work instead of struggling with protein isolation

A Spatial Stochastic Model of AMPAR Trafficking and Subunit Dynamics

In excitatory neurons, the ability of a synaptic connection to strengthen or weaken is known as synaptic plasticity and is thought to be the cellular basis for learning and memory. Understanding the mechanism of synaptic plasticity is an important step towards understanding and developing treatment methods for learning and memory disorders. A key molecular process in synaptic plasticity for mammalian glutamatergic neurons is the exocytosis (delivery to the synapse) of AMPA-type glutamate receptors (AMPARs). While the protein signaling pathways responsible for exocytosis have long been investigated with experimental methods, it remains unreasonable to study the system in its full complexity via only in vitro and in vivo studies. A large number of protein interaction states are observed, creating a system both difficult to monitor and limited in spatiotemporal resolution in an experimental setting. Thus, a computational modeling approach could be employed to help elucidate the underlying protein interaction mechanisms. Here we develop a systematic model to investigate the spatiotemporal patterning of AMPARs. We replicate in silico two distinct mechanisms of AMPAR trafficking related to variation in AMPAR subunit functionality. This model is validated against current knowledge of AMPAR trafficking and used to explore spatial localization of AMPARs to specific synaptic sites, as well as to describe the differences in the spatiotemporal dynamics between the two interacting pathways. These findings help to explain how AMPAR trafficking occurs and can serve as a step towards understanding the role it plays in synaptic plasticity

Activity of Protein Kinase A Attached to Magnetic Beads

Development of high throughput assays is a crucial step in developing more efficient techniques that aid in many important areas of research today such as drug development or identification of protein structure function relationships. Integration of high throughput assays into more research efforts could drastically decrease the time and cost it takes for a new drug to hit the market. Protein Kinase A (PKA) is an extensively studied protein as it is highly upregulated in cancer and is a hot spot for drug targeting. In this work, azide-tagged PKA is covalently attached to magnetic beads using azide-alkyne cycloaddition, a well-known click chemistry reaction that selectively and covalently links two compounds. Modified PKA is attached to magnetic beads and the activity of the covalently bound PKA is determined. Significant levels of PKA activity can open the door to development of more efficient drug screening processes. It is anticipated that the azide-PKA conjugated beads will have significantly more PKA activity than beads treated with non-tagged PKA since there is specificity in binding between the azide-tagged PKA and the magnetic bead. Additionally, preliminary data using an inhibitor assay and ATP gradient scale suggests that linked PKA has similar chemical properties with native state PKA subject to the same treatments

Methods to Study Activity Dependent Protein Synthesis in Autism Spectrum Disorder

It is estimated by the World Health Organization that 1 in 100 children have autism spectrum disorder (ASD), a condition characterized by neurological differences that may impact a person’s learning or behavior. Clinically, ASD symptoms are alleviated with behavioral or pharmacological therapies, however, not all patients respond to these interventions. Deep brain stimulation (DBS) is a promising treatment of Parkinson’s disease that could also be effective in treating ASD. SynGAP1 is a protein involved in neuronal action that is crucial for regulating synaptic plasticity. Mutations in the SYNGAP1 gene causing haploinsufficiency can result in the manifestation of ASD symptoms. This study aims at gathering information on the potential of using a Syngap1+/- mouse model to determine whether DBS can counter neurological differences between mice with haploinsufficiency and wild type littermates. Histology slides were analyzed for lesioning from previous surgeries performed in which electrodes were placed for DBS. To gain baseline data before DBS, behavioral tests were conducted on both male and female wild type and Syngap1+/- mice to understand differences. To correlate behavioral results with protein synthesis, labeling of newly synthesized proteins was optimized using azidohomoalanine. Inspection of histology slides showed no evidence of brain lesioning in mice that were to have undergone DBS. Behavioral results revealed increased hyperactivity in mice with haploinsufficiency. Additionally, SDS-PAGE analysis of azidohomoalanine injections revealed more injections administered on subsequent days provides optimal proteomic labeling. With this information, further research can be conducted in which DBS is performed followed by behavioral studies and proteomic analysis

Quantitative Models of Protein Dynamics in Synaptic Plasticity: Analysis of Spatial and Stochastic Effects

Memory formation within neurons depends on complex protein signaling networks, which become dysregulated in neurological disorders such as Alzheimer’s disease. To characterize therapeutic strategies for these disorders, we require a better understanding of the how the protein interactions are regulated. Conventionally, protein interactions are studied by experimental techniques and complemented by computational models. However, most models are deterministic, limiting their biophysical accuracy. First, deterministic models exclude the stochastic effects necessitated by the small protein concentrations often observed within neurons. Second, deterministic models exclude the effects of spatial localizations on neuronal protein binding and activation. Third, many different models exclude an explicit representation of competition for binding to the essential protein calmodulin when multiple calmodulin-binding proteins are known to simultaneously coordinate the regulation of synaptic plasticity. Therefore, here we present a highly detailed model that explicitly accounts for stochastic effects, spatial localizations, and competitive binding, using the open source software MCell. Using our model, we compare against previous models and experimental data to analyze how spatial and stochastic effects determine the dynamics observed. These conclusions will be drawn from the concentrations of various neuronal protein activations and chemical modifications. In the future, our model may be used as a tool to identify and characterize therapeutic targets for neurological disorders

Bioorthogonal Chemoenzymatic Functionalization of Calmodulin for Bioconjugation Applications

Calmodulin (CaM) is a widely studied Ca^(2+)-binding protein that is highly conserved across species and involved in many biological processes, including vesicle release, cell proliferation, and apoptosis. To facilitate biophysical studies of CaM, researchers have tagged and mutated CaM at various sites, enabling its conjugation to fluorophores, microarrays, and other reactive partners. However, previous attempts to add a reactive label to CaM for downstream studies have generally employed nonselective labeling methods or resulted in diminished CaM function. Here we report the first engineered CaM protein that undergoes site-specific and bioorthogonal labeling while retaining wild-type activity levels. By employing a chemoenzymatic labeling approach, we achieved selective and quantitative labeling of the engineered CaM protein with an N-terminal 12-azidododecanoic acid tag; notably, addition of the tag did not interfere with the ability of CaM to bind Ca^(2+) or a partner protein. The specificity of our chemoenzymatic labeling approach also allowed for selective conjugation of CaM to reactive partners in bacterial cell lysates, without intermediate purification of the engineered protein. Additionally, we prepared CaM-affinity resins that were highly effective in purifying a representative CaM-binding protein, demonstrating that the engineered CaM remains active even after surface capture. Beyond studies of CaM and CaM-binding proteins, the protein engineering and surface capture methods described here should be translatable to other proteins and other bioconjugation applications