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C&SP22: Modeling T cell fate decisions

A. Collaborating Investigators: Penelope Morel, 1 Robin E. C. Lee, 2 James R. Faeder2

B. Institutions: Pitt 1Immunology and 2Computational and Systems Biology Departments

C. Funding Status of Project: Juvenile Diabetes Research Foundation 1-INO-2016-215-A-N (Morel) 06/01/2016-05/31/2017

D. Biomedical Research Problem: The T cell receptor (TCR) is an exquisitely sensitive molecular machine that can translate small differences in peptide/MHC ligands into profoundly different outcomes. Our long-term goal is to understand how T cells perceive signals of differing strengths in order to elucidate how this determines T helper (Th) cell fate. Antigen (Ag) dose affects Th differentiation; and several in vivo models have shown that low Ag dose favors T regulatory (Treg) and Th2 differentiation, whereas high Ag dose induces inflammatory Th1 cells.74-80 On the one hand, Treg cells are critical for the maintenance of self-tolerance and the prevention of autoimmune diseases such as diabetes; on the other, tumors induce Treg cells to suppress immune surveillance. Despite the powerful effect on T cell outcome, how these signals contribute to determining Th cell fate remains poorly understood.

 

 

Fig VIII.6 A. Calibrated time courses for PTEN and FoxO1 following stimulation with high dose antigen . Lines are model predictions with light and dark blue bands indicating 75% and 95% confidence regions. Points are experimental data with error bars showing +/- SEM. B. Single-cell imaging pipeline with automated segmentation and tracking from live-cell time-lapse images. Last panel displays single-cell time courses that can be extracted for hundreds of cell simultaneously. See (Hawse et al, 2015) for details.

E. Methods and Procedures: By coupling mathematical modeling with detailed in vitro activation profiling we have identified several important feedback loops that control the degree of Akt/mTOR activation.81-83 These involve the lipid phosphatase and tensin homolog (PTEN), the transcription factors Foxp3 and FoxO1 and the Ser/Thr kinase Akt.81,82 High dose Ag increases TCR stimulation resulting in PTEN degradation, which drives higher Akt/mTOR signaling and T effector development. Conversely, low TCR stimulation sustains expression of PTEN, which suppresses Akt/mTOR signaling to promote Treg development.81 Based on these and other biochemical mechanisms we have developed a rule-based model in BioNetGen and calibrated it to biochemical data for low and high dose stimulation as shown (Fig. VIII.6A) using Bayesian parameter estimation with the ptempest software, as described in TR&D3 Aim 2.3. This model predicts a sharp threshold for Akt activation with respect to antigen dose that depends on several key variables, most notably PTEN expression level, which exhibit considerable cell-to-cell variation. We are currently conducting experiments in mice that express a fluorescent reporter of TCR activation to determine whether there is a sharp activation threshold as predicted by the model, and in mice heterozygous for PTEN expression to examine how PTEN levels affect this threshold. We will use these data to refine the model and identify additional factors that can affect antigen dose thresholds. In addition, we will use the Amnis ImageStream technology available to the Morel lab and the single-cell live imaging pipeline being developed in the Lee lab (Fig. VIII.6B) to spatially resolve key signaling components, including Akt, PIP3, and NFκB. We will use these data to confirm temporal oscillations observed in preliminary data and to calibrate a coarse-grained spatial model (TR&D3 Aim 1.3).

 

C&SP21: Functional significance of the dynamics of AMPAR extracellular region

A. Collaborating Investigators: Ingo H. Greger,1 Ivet Bahar,2 Tom M. Bartol,3 Terry J.Sejnowski2

B. Institutions: 1MRC Lab of Molecular Biology, Cambridge, UK; 2Pitt, 3Salk

C. Funding Status of Project: MRC Research Institute Cambridge Core Funds (2003 - ) (Greger), BASAL BODYSRC Synaptic Role of the AMPA receptor N-terminal domain (Greger) 4/2016-4/2019

 

 

Fig VIII.4 Comparison of AMPAR and NMDAR tetrameric structures. Both structures are composed of three layers: NTD, LBD and TMD/ The dashed cyan line indicates the membrane interface. The extracellular region (NTD + LBD) of NMDAR is more tightly packed than that of AMPAR (from Dutta et al., 2015)

D. Biomedical Research Problem

Ionotropic glutamate receptor (iGluRs) are ligand-gated ion channels that allow for the flow of cations into the postsynaptic cell in response to glutamate binding, thus regulating neurotransmission upon depolarization of the cell membrane. Among iGluR subfamilies, AMPAR and NMDAR play a key role in learning and memory, and in particular the AMPAR is essential to rapid neurotransmission and synaptic plasticity.61 It preferentially functions as a heterotetramer, composed of subunits GluA1 to GluA4, with GluA2 playing a dominant role in neurosignaling. The last two years have seen an explosion in the number of intact (tetrameric) structures resolved for AMPAR and NMDAR; yet the intact structure of heterotetrameric GluA2-containing AMPAR has been elusive. A major breakthrough in the field has been the resolution of such a cryo-EM structure, that of intact GluA2/3 heteromer, by the Greger lab.62 Strikingly, the N-terminal domain (NTD) of the two Glu2/3 dimers in this heterotetramer adopts a compact 'O' shape when viewed from the top (from the ECR) (as opposed to the common 'N' shape of GluA2 homo-tetramer63), and the NTD layer is vertically compressed to make closer contacts with the ligand-binding domain (LBD), reminiscent of subunit packing64,65 in heterotetrameric NMDAR (Fig VIII.4). The NTD and LBD form the ECR of the AMPAR. Their close association suggests that the NTD may play a key role in communicating signals to the transmembrane domain (TMD) and allosterically modulate the TMD gating. Furthermore, ECR flexibility may facilitate the interactions with auxiliary subunits essential for synaptic plasticity (e.g. Fig VIII.5). This C&SP aims at exploring these hypotheses.

 

 

Fig VIII.5. ANM of the whole GluA2 AMPAR shows global bending motions that could bring the NTD into proximity with auxiliary subunit TARPs (from Krieger et al., 2015)

E. Methods and Procedures. The Greger and Bahar labs have been productively collaborating in recent years on AMPAR dynamics, first using the NTD dimer structures1,66 and more recently the intact tetrameric structures.2,3 These studies demonstrated that the NTD domains exhibit structural flexibilities comparable to those of AMPAR NTDs. Furthermore, the global modes of motions predicted by ANM67,68 (or ProDy54) revealed the propensity of homotetrameric AMPAR to assume more compact forms similar to NMDARs. The validity of these modes of motions were confirmed by cross-linking experiments between NTD sites predicted by ANM to come into close proximity.2 In the new term, we will first adopt ANM-based analysis to characterize the mode spectrum of the heterotetrameric AMPAR. ProDy analysis already revealed that the O ↔ N transition is enabled by a global ANM mode.62 We will characterize thoroughly the whole spectrum of motions and generate the energy landscape of Glu2/3 heterotetramer, using the recently introduced extension of coMD.69,70 Then we will focus on the ECR motions that induce a pore opening (or cooperative twisting) at the TMD and analyze the conformational events that enable the allosteric coupling between the ECR and the TMD with the help of accelerated MD simulations. 71 In the next phase, we plan to examine the significance of GluA2/3 ECR flexibility in adapting to its interactions with auxiliary proteins such as cornichon homologs,72 TARPs73 or in forming clusters, which will be further tested/validated with structural and single-particle tracking methods in the Greger lab.

 

C&SP20: Structural plasticity of chaperonins determined by cryo-electron microscopy: Modeling the machinery of GroEL and TRiC

A. Collaborating Investigators: Wah Chiu,1 and Ivet Bahar

B. Institutions: 1Baylor College of Medicine, 2University of Pittsburgh

C. Funding Status of Project: P01NS092525 (Chiu, Co-PI) 4/1/2016-3/31/2021; 5P41-GM103832-31 (Chiu) 12/1/96-12/31/19

Fig VIII.3. CryoEM data on apo GroEL (a) 3.7 Å map side and top views. Different colors denote each of the 14 subunits; (b) atomic model of a single subunit and its detailed side chain features. (c) 3 types of subunit conformations occurring in GroEL after focused classification analysis.

D. Biomedical Research Problem

Chaperonins are essential mediators of many functions in the cell, including protein folding. These are oligomeric machines, of ~ 1 megadalton, with two back-to-back rings enclosing a central cavity that accommodates polypeptide substrates. The Chiu lab has solved near-atomic resolution cryoEM structures of GroEL from bacteria,37 Mm-Cpn from archaea,38 and TRiC from eukaryotes.39 In addition, they have studied them in different nucleotide-binding states and with a variety of substrates.40-44 These studies show that chaperonins assume various conformations under different conditions, i.e. structural plasticity is an inherent property of chaperonins.

Recent advances in direct electron detectors used in cryoEM45,46 have made cryoEM a feasible imaging modality to record images of molecular machines with high quantum detection efficiency and high information content. Fig VIII.3 panel a is a 3.7 Å cryoEM map of GroEL using 40,000 particle images showing unambiguous resolution of backbone and side-chain densities (panel b). The time from data collection to a complete model was less than 3 weeks (Roh and Chiu, unpublished). Using a more advanced image processing method known as focused 3D classification,47 we re-analyzed each of the 14 protein subunits in each of the GroEL particle images. We were able to retrieve three types of conformations (Figure VIII.3 c), and determined that they occur randomly in each GroEL machine in variable proportions. Each of them has a characteristic apical domain structure, which coincide with different subunit structures in the PDB (chains B, J and I of PDB ID 1XCK). These findings demonstrate the power of cryoEM to reveal variable conformations of protein components in one single biological machine at a time at near-atomic resolution. A structure-based computational analysis of the dynamics of GroEL as well as TRiC can help further our understanding of the structural mechanisms underlying their function and provide insights into the role of structural plasticity in enabling their allosteric machinery.

E. Methods and Procedures. Our ongoing activity is to determine GroEL cryoEM structure with GroES and carboxylase substrate. In our newly funded program project, we will also pursue the cryoEM characterization of TRiC complexed with mutant huntingtin exon extracted from Huntington's disease (HD) cell model and mouse neuron model. These experiments will provide a mechanistic understanding of how TRiC prevents the progression of aggregation in polyQ,44 and mutant huntingtin exon48 as part of our effort to develop a TRiC-like reagent for HD therapeutics. The Bahar lab has experience on the machinery and conformational variability of GroEL-GroES,49-53 which will be further analyzed in the light of the new data generated by the Chiu lab, and with the help of novel extensions of elastic network models (ENMs) developed in TR&D1 subaim 1.1. The computationally predicted dynamics will be compared to the structural variability observed in cryoEM, and the interactions that modulate GroEL allosteric machinery will be identified. Similar methods will be used for TRiC, toward elucidating its spectrum of motions and how its dynamics relates to its chaperoning activities. Target sites whose perturbation may alter/control TRiC machinery will be identified using ProDy tools,54 toward assisting in the design of new therapeutic strategies against HD. We anticipate a productive interaction between this project and C&SP16 on the identification of neuroprotectives for HD with Dr. Friedlander (UPMC), an expert in the etiology of HD as well as discovery of neuroprotectives against HD.55-60

 

C&SP19: Mapping the Supramolecular Organization of Dendritic Spines to Model the Regulation of Synaptic Signal Transfer

A. Collaborating Investigators: Mark H. Ellisman,1 Andreas Herz,2Terry Sejnowski,3 Tom Bartol3

B. Institutions: 1University of California, San Diego, 2Ludwig-Maximilians U, Munich, and 3Salk

C. Funding Status of Project: NIDA R01-DA038896-02 ‘Deciphering the dynamical multi-scale structure-function of dendritic spines (Ellisman) 7/1/14 – 6/30/19

D. Biomedical Research Problem

Synapses are the sites of communication between neurons and most excitatory synapses occur onto specialized structures called dendritic spines.34 Generally, spines consist of a spine head and a thin spine neck. The role of spines in influencing electrical and biochemical flow at the synapse is still debated; however, spines can assume a variety of shapes and sizes, and it has recently been shown that spine size is highly correlated with synaptic activation history and network function.10 Spines are filled with a high concentration of filamentous actin, but the density of actin can vary within and across brain regions.35 The role of the actin network in spine function has not been well studied. The highly branched filamentous actin carries electrostatic charges, which causes ions to condense in its vicinity. Within the condensation profile, known as the electrical double-layer, cations, the main charge carriers for depolarizing phenomena, should propagate with great ease due to the high local concentration. Thus, a significant fraction of the current within the volume of the spines is constrained to flow in nano-slits along charged structures. The multiscale modeling of this process is to be explored in this collaboration.

Fig VIII.2 Reconstruction of actin filament network. CellBlender model of cytoskeleton (yellow) from spine head of cerebellar neuron, extracted using topologically consistent framework. Dark green: plasma membrane. Purple: spine apparatus. Red: post-synaptic density.

 

The Ellisman lab is generating high-resolution (~5 nm) serial EM tomographic volumes of entire spine heads from cerebellum, hippocampus, and striatum. The tissue is prepared using high pressure freezing / freeze substitution to optimally preserve actin network structure and membrane profiles.36 Multi-tilt acquisition and direct electron detection further improve image quality for subsequent feature extraction. Using these datasets, the Herz lab is building spatially accurate 3D models of ionic current propagation in topologically consistent segmentations of the filamentous actin network (Fig VIII.2). These models will be used to perform simulations of reaction-diffusion dynamics using MCell, and multiscale simulations of electro-diffusion dynamics, while enforcing consistent biophysical boundary conditions and accurate ion-channel kinetics.

E. Methods and Procedures

Aim 1: Create a multiscale model. Models will be generated using CellBlender that will include all relevant actors (spine apparatus, postsynaptic density) necessary to computationally reconstitute synapses and explore dynamics of Ca2+ and other molecules within spines and spine necks with MCell.

Aim 2: Determine role of actin network in spines of various sizes/strengths. Since spine size is strongly correlated with synaptic strength, we will study differences in actin morphology and its influence on diffusion in spines of various sizes. We will choose spines in the CA1 stratum radiatum that are representative of large (>0.1um3), average (0.02-0.04 um3), and small (<0.01um3) spines. MCell will be used to model diffusion in the CellBlender models created in Aim 1.

Aim 3: Compare role of actin in spines from different brain regions. Dendritic spines of the cerebellum have been found to contain considerably higher concentrations of actin than spines in CA1 stratum radiatum. Spines in the striatum appear to contain intermediate amounts of actin. We will model actin in spines from these three regions and use MCell to determine how the cytoskeleton affects diffusion in spines representing realistic variations in actin concentration.

Research Highlights

 

Direct coupling of oligomerization and oligomerization-driven endocytosis of the dopamine transporter to its conformational mechanics and activity

The Bahar (TR&D1) and Sorkin (DBP3) labs published an article in the Journal of Biological Chemistry, selected as one of JBC's "Editors' Picks. Our results demonstrate a direct coupling between conformational dynamics of DAT, functional activity of the transporter and its oligomerization leading to endocytosis. The high specificity of such coupling for DAT makes the TM4-9 hub a new target for pharmacological modulation of DAT activity and subcellular localization. (Read more)

 

 

Differences in the intrinsic spatial dynamics of the chromatin contribute to cell differentiation

Comparison with RNA-seq expression data reveals a strong overlap between highly expressed genes and those distinguished by high mobilities in the present study, in support of the role of the intrinsic spatial dynamics of chromatin as a determinant of cell differentiation. (Read more)

 

 

Nanoscale co-organization and coactivation of AMPAR, NMDAR, and mGluR at excitatory synapses

Work by TR&D2 Investigators and collaborators provide insights into the nanometer scale organization of postsynaptic glutamate receptors using a combination of dual-color superresolution imaging, electrophysiology, and computational modeling. (Read more)

 

 

Parallel Tempering with Lasso for model reduction in systems biology

TR&D3 Investigators and collaborators develop PTLasso, a Bayesian model reduction approach that combines Parallel Tempering with Lasso regularization, to automatically extract minimal subsets of detailed models that are sufficient to explain experimental data. On both synthetic and real biological data, PTLasso is an effective method to isolate distinct parts of a larger signaling model that are sufficient for specific data. (Read more)

 

Image-derived models of cell organization changes during differentiation and drug treatments

Our work on modeling PC12 cells undergoing differentiation into neuron-like morphologies (under C&SP11, completed) has been published in Molecular Biology of the Cell. We have also made the large dataset of 3D images collected in that study available through Dryad. (Read more)

 

Monoamine transporters: structure, intrinsic dynamics and allosteric regulation

T&RD1 investigators Mary Cheng and Ivet Bahar published an invited review article in Nature Structural & Molecular Biology, addressing recent progress in the elucidation of the structural dynamics of MATs and their conformational landscape and transitions, as well as allosteric regulation mechanisms. (Read more)

Trimerization of dopamine transporter triggered by AIM-100 binding

The Bahar (TR&D1) and Sorkin (DBP3) labs explored the trimerization of dopamine transporter (DAT) triggered by a furopyrimidine, AIM-100, using a combination of computational and biochemical methods, and single-molecule live-cell imaging assays. (Read more)

Pre-post synaptic alignment through neuroligin-1 tunes synaptic transmission efficiency

TR&D2 investigators and collaborators describe organizing role of neuroligin-1 to align post-synaptic AMPA Receptors with pre-synaptic release sites into trans-synaptic “nano-columns” to enhance signaling.(Read more)

Inferring the Assembly Network of Influenza Virus

In an article in PLoS Computational Biology, MMBioS TR&D4 members Xiongto Ruan and Bob Murphy collaborated with Seema Lakdawala to address this question of the assembly network of the Influenza virus.(Read more)

PINK1 Interacts with VCP/p97 and Activates PKA to Promote NSFL1C/p47 Phosphorylation and Dendritic Arborization in Neurons

Our findings highlight an important mechanism by which proteins genetically implicated in Parkinson’s disease (PD; PINK1) and frontotemporal dementia (FTD; VCP) interact to support the health and maintenance of neuronal arbors.(Read more)

Improved methods for modeling cell shape

In a recent paper in Bioinformatics, Xiongtao Ruan and Bob Murphy of TR&D4 addressed the question of how best to model cell and nuclear shape.(Read more)

New tool to predict pathogenicity of missense variants based on structural dynamics: RHAPSODY

We demonstrated that the analysis of a protein’s intrinsic dynamics can be successfully used to improve the prediction of the effect of point mutations on a protein functionality. This method employs ANM/GNM tools (Read more)

New method for investigating chromatin structural dynamics.

By adapting the Gaussian Network Model (GNM) protein-modeling framework, we were able to model chromatin dynamics using Hi-C data, which led to the identification of novel cross-correlated distal domains (CCDDs) that were found to also be associated with increased gene co-expression.  (Read more)

 

Structural elements coupling anion conductance and substrate transport identified

We identified an intermediate anion channeling state (iChS) during the global transition from the outward facing (OF) to inward facing state (IFS). Our prediction was tested and validated by experimental study conducted in the Amara lab (NIMH). Critical residues and interactions were analyzed by SCAM, electrophysiology and substrate uptake experiments (Read more)

Integrating MMBioS technologies for multiscale discovery

TR&D teams driven by individual DBPs are naturally joining forces, integrating their tools to respond to the needs of the DBP, and creating integrative frameworks for combining structural and kinetic data and computing technologies at multiple scales.  (Read more)

 

Large scale visualization of rule-based models.

Signaling in living cells is mediated through a complex network of chemical interactions. Current predictive models of signal pathways have hundreds of reaction rules that specify chemical interactions, and a comprehensive model of a stem cell or cancer cell would be expected to have many more. Visualizations of rules and their interactions are needed to navigate, organize, communicate and analyze large signaling models.  (Read more)

Integration of MCellR into MCell/CellBlender

Using spatial biochemical models of SynGAP/PSD95, MMBioS investigators were able to merge the MCellR code-base with the MCell code-base and validate its utility and correctness of this sophisticated technology now easily accessible through the MCell/CellBlender GUI.  (Read more)

 

csp29

Causal relationships of spatial distributions of T cell signaling proteins

The idea is to identify a relationship in which a change in the concentration of one protein in one cell region consistently is associated with a change in the concentration of another protein in the same or a different region. We used the data from our Science Signaling paper reported last year to construct a model for T cells undergoing stimulation by both the T cell receptor and the costimulatory receptor. (Read more...)

T-Cell Receptor Signaling

BioNetGen modeling helps reveal immune system response decision

To attack or to let be is an important decision that our immune systems must make to protect our bodies from foreign invaders or protect bodily tissues from an immune attack. Using modeling and experiments, we have painted a sharper picture of how T cells make these critical decisions.  (Read more)

 

 

distancecell

Tools for determining the spatial relationships between different cell components

An important task for understanding how cells are organized is determining which components have spatial patterns that are related to each other.Read more

 

4d rtd

Pipeline for creation of spatiotemporal maps

Using a combination of diffeomorphic methods and improved cell segmentation, we developed a CellOrganizer pipeline for use in DPB4 to construct models of the 4D distributions of actin and 8 of its regulators during the response of T cells to antigen presentation. Read more

 

Multi-scale Hybrid Methodology

The hybrid methodology, coMD, that we have recently developed [1] has been recently extended to construct the energy landscape near the functional states of LeuT (Fig 1) [2]. This is the first energy landscape constructed for this NSS family member. Read more

 


Insights into the cooperative dynamics of AMPAR

Comparative analysis of AMPAR and NMDAR dynamics reveals striking similarities, opening the way to designing new modulators of allosteric interactions. Read more


Improved Sampling of Cell-Scale Models using the WE Strategy

The WE strategy for orchestrating a large set of parallel simulations has now been extended to spatially resolved cell-scale systems. The WESTPA implementation of WE has been used to control MCell simulations, including models built using a BioNetGen-CellOrganizer pipeline for situating complex biochemistry within spatially realistic cell models. Read more

Mouse visual cortex
Anatomy and Function of an Excitatory Network in the Visual Cortex

MMBioS researcher Greg Hood’s collaboration with Wei-Chung Allen Lee of Harvard University and R. Clay Reid of the Allen Institute for Brain Science concerning the reconstruction of an excitatory nerve-cell network in the mouse brain cortex at a subcellular level using the AlignTK software has been published in Nature. Read more

 

Molecular Mechanism of Dopamine Transport by hDAT

Dopamine transporters (DATs) control neurotransmitter dopamine (DA) homeostasis by reuptake of excess DA, assisted by sodium and chloride ions. The recent resolution of DAT structure (dDAT) from Drosophila permits us for the first time to directly view the sequence of events involved in DA reuptake in human DAT (hDAT). Read more

 

 

 

figure good 170Synaptic Facilitation Revealed

An investigation of several mechanisms of short-term facilitation at the frog neuromuscular junction concludes that the presence of a second class of calcium sensor proteins distinct from synaptotagmin can explain known properties of facilitation. Read more

 

langmead2 200Sparse Graphical Models of Protein:Protein Interactions

DgSpi is a new method for learning and using graphical models that explicitly represent the amino acid basis for interaction specificity and extend earlier classification-oriented approaches to predict ΔG of binding. Read more

 

Picture1 180Advancing Parallel Bio-simulations

A new non-Markovian analysis can eliminate bias in estimates of long-timescale behavior, such as the mean first-passage time for the dissociation of methane molecules in explicit solvent. Read more

 

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