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At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A Meta-Analysis of the Protein Components in Rattlesnake Venom

The specificity and potency of venom components give them a unique advantage in developing various pharmaceutical drugs. Though venom is a cocktail of proteins, rarely are the synergy and association between various venom components studied. Understanding the relationship between various components of venom is critical in medical research. Using meta-analysis, we observed underlying patterns and associations in the appearance of the toxin families. For Crotalus, Dis has the most associations with the following toxins: PDE; BPP; CRL; CRiSP; LAAO; SVMP P-I and LAAO; SVMP P-III and LAAO. In Sistrurus venom, CTL and NGF have the most associations. These associations can predict the presence of proteins in novel venom and understand synergies between venom components for enhanced bioactivity. Using this approach, the need to revisit the classification of proteins as major components or minor components is highlighted. The revised classification of venom components is based on ubiquity, bioactivity, the number of associations, and synergies. The revised classification can be expected to trigger increased research on venom components, such as NGF, which have high biomedical significance. Using hierarchical clustering, we observed that the genera’s venom compositions were similar, based on functional characteristics rather than phylogenetic relationships.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Identification of a PEAK1/ZEB1 signaling axis during TGFβ/fibronectin-induced EMT in breast cancer

Transforming Growth Factor beta (TGFβ) is the archetypal member of the TGFβ superfamily of ligands and has pleiotropic functions during normal development, adult tissue homeostasis and pathophysiological processes such as cancer. In epithelial cancers TGFβ signaling can either suppress tumor growth or promote metastasis via the induction of a well-characterized epithelial–mesenchymal transition (EMT) program. We recently reported that PEAK1 kinase mediates signaling cross talk between TGFβ receptors and integrin/Src/MAPK pathways and functions as a critical molecular regulator of TGFβ-induced breast cancer cell proliferation, migration, EMT and metastasis. Here, we examined the breast cancer cell contexts in which TGFβ induces both EMT and PEAK1, and discovered this event to be unique to oncogene-transformed mammary epithelial cells and triple-negative breast cancer cells. Using the Cancer BioPortal database, we identified PEAK1 co-expressors across multiple malignancies that are also common to the TGFβ response gene signature (TBRS). We then used the ScanSite database to identify predicted protein–protein binding partners of PEAK1 and the PEAK1-TBRS co-expressors. Analysis of the Cytoscape interactome and Babelomics-derived gene ontologies for a novel gene set including PEAK1, CRK, ZEB1, IL11 and COL4A1 enabled us to hypothesize that PEAK1 may be regulating TGFβ-induced EMT via its interaction with or regulation of these other genes. In this regard, we have demonstrated that PEAK1 is necessary for TGFβ to induce ZEB1-mediated EMT in the context of fibronectin/ITGB3 activation. These studies and future mechanistic studies will pave the way toward identifying the context in which TGFβ blockade may significantly improve breast cancer patient outcomes. - Highlights: • PEAK1 is upregulated in mammary epithelial cells during TGFβ-induced EMT. • TGFβ-induced EMT upregulates PEAK1 in triple negative breast cancer. • PEAK1 is necessary for TGFβ/fibronectin-induced ZEB1 expression during EMT. • The PEAK1/CRK/ZEB1 pathway is a novel target for blocking EMT in breast cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MicroRNA-1297 inhibits prostate cancer cell proliferation and invasion by targeting the AEG-1/Wnt signaling pathway

MicroRNAs (miRNAs) have been known to be implicated in tumorigenic programs. miR-1297 has been reported to be dysregulated and involved in cancer progression in many types of human cancers. However, the expression level and the role of miR-1297 in prostate cancer remain unclear. Herein, we aimed to investigate the potential role and molecular mechanism of miR-1297 in prostate cancer progression. We found that miR-1297 was significantly downregulated in human prostate cancer specimens as well as in several prostate cancer cell lines. In addition, functional experiments demonstrated that overexpression of miR-1297 remarkably inhibited prostate cancer cell proliferation and invasion whereas miR-1297 suppression significantly promoted prostate cancer cell proliferation and invasion. Bioinformatics analysis showed that the Astrocyte elevated gene-1 (AEG-1), a well-known oncogene, is a predicted target of miR-1297. Dual-luciferase reporter assay showed that miR-1297 was able to directly target the 3’-untranslated region of AEG-1. In addition, RT-qPCR and Western blot analysis showed that miR-1297 regulated the mRNA and protein expression levels of AEG-1. We also showed that miR-1297 was able to regulate the Wnt signaling pathway. Moreover, rescue assays indicated that AEG-1 contributed to miR-1297-endowed effects on cell proliferation and invasion as well as Wnt signaling pathway. Taken together, these findings suggest that miR-1297 inhibits prostate cancer proliferation and invasion by targeting AEG-1, thereby providing novel insight into understanding the pathogenesis of prostate cancer. Thus, miR-1297 may be a novel potential therapeutic candidate to treat prostate cancer. - Highlights: • miR-1297 is decreased in prostate cancer. • miR-1297 inhibits prostate cancer cell proliferation and invasion. • miR-1297 targets and inhibits AEG-1. • miR-1297 regulates AEG-1/Wnt signaling pathway.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

Resonance Assignments and Secondary Structure Analysis of Dynein Light Chain 8 by Magic-angle Spinning NMR Spectroscopy

Dynein light chain LC8 is the smallest subunit of the dynein motor complex and has been shown to play important roles in both dynein-dependent and dynein-independent physiological functions via its interaction with a number of its binding partners. It has also been linked to pathogenesis including roles in viral infections and tumorigenesis. Structural information for LC8-target proteins is critical to understanding the underlying function of LC8 in these complexes. However, some LC8-target interactions are not amenable to structural characterization by conventional structural biology techniques owing to their large size, low solubility, and crystallization difficulties. Here, we report magic-angle spinning (MAS) NMR studies of the homodimeric apo-LC8 protein as a first effort in addressing more complex, multi-partner, LC8-based protein assemblies. We have established site-specific backbone and side-chain resonance assignments for the majority of the residues of LC8, and show TALOS+-predicted torsion angles ø and ψ in close agreement with most residues in the published LC8 crystal structure. Data obtained through these studies will provide the first step toward using MAS NMR to examine the LC8 structure, which will eventually be used to investigate protein–protein interactions in larger systems that cannot be determined by conventional structural studies.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2022

Machine learning-assisted elucidation of CD81–CD44 interactions in promoting cancer stemness and extracellular vesicle integrity

Tumor-initiating cells with reprogramming plasticity or stem-progenitor cell properties (stemness) are thought to be essential for cancer development and metastatic regeneration in many cancers; however, elucidation of the underlying molecular network and pathways remains demanding. Combining machine learning and experimental investigation, here we report CD81, a tetraspanin transmembrane protein known to be enriched in extracellular vesicles (EVs), as a newly identified driver of breast cancer stemness and metastasis. Using protein structure modeling and interface prediction-guided mutagenesis, we demonstrate that membrane CD81 interacts with CD44 through their extracellular regions in promoting tumor cell cluster formation and lung metastasis of triple negative breast cancer (TNBC) in human and mouse models. In-depth global and phosphoproteomic analyses of tumor cells deficient with CD81 or CD44 unveils endocytosis-related pathway alterations, leading to further identification of a quality-keeping role of CD44 and CD81 in EV secretion as well as in EV-associated stemness-promoting function. CD81 is coexpressed along with CD44 in human circulating tumor cells (CTCs) and enriched in clustered CTCs that promote cancer stemness and metastasis, supporting the clinical significance of CD81 in association with patient outcomes. Our study highlights machine learning as a powerful tool in facilitating the molecular understanding of new molecular targets in regulating stemness and metastasis of TNBC.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

BCL::MP-fold: Membrane protein structure prediction guided by EPR restraints

For many membrane proteins, the determination of their topology remains a challenge for methods like X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy. Electron paramagnetic resonance (EPR) spectroscopy has evolved as an alternative technique to study structure and dynamics of membrane proteins. The present study demonstrates the feasibility of membrane protein topology determination using limited EPR distance and accessibility measurements. The BCL::MP-Fold (BioChemical Library membrane protein fold) algorithm assembles secondary structure elements (SSEs) in the membrane using a Monte Carlo Metropolis (MCM) approach. Sampled models are evaluated using knowledge-based potential functions and agreement with the EPR data and a knowledge-based energy function. Twenty-nine membrane proteins of up to 696 residues are used to test the algorithm. The RMSD100 value of the most accurate model is better than 8 Å for 27, better than 6 Å for 22, and better than 4 Å for 15 of the 29 proteins, demonstrating the algorithms' ability to sample the native topology. The average enrichment could be improved from 1.3 to 2.5, showing the improved discrimination power by using EPR data. Proteins 2015; 83:1947–1962. © 2015 Wiley Periodicals, Inc

Biochemistry & Molecular Biology↗
DOE OSTI2016

Principles of proteome allocation are revealed using proteomic data and genome-scale models

Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the “generalist” (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thus represents a generalist ME model reflecting both growth rate maximization and “hedging” against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σS. Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally-related protein groups) as demonstrated here. Furthermore, this flexible formalism provides an accessible approach for narrowing the gap between the complexity captured by omics data and governing principles of proteome allocation described by systems-level models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Proteome-scale Deployment of Protein Structure Prediction Workflows on the Summit Supercomputer

Deep learning has contributed to major advances in the prediction of protein structure from sequence, a fundamental problem in structural bioinformatics. With predictions now approaching the accuracy of crystallographic experiments, and with accelerators like GPUs and TPUs making inference using large models rapid, genome-level structure prediction becomes an obvious aim. Leadership-class computing resources can be used to perform genome-scale protein structure prediction using state-of-the-art deep learning models, providing a wealth of new data for systems biology applications. Here we describe our efforts to efficiently deploy the AlphaFold v.2 program, for full-proteome structure prediction, at scale on the Oak Ridge Leadership Computing Facility's resources, including the Summit supercomputer. We performed inference to produce the predicted structures for 40,526 protein sequences, corresponding to four prokaryotic proteomes and one plant proteome, using under 4,400 total Summit node hours, equivalent to using the majority of the supercomputer for a little over one hour. We also designed an optimized structure refinement that reduced the time for the relaxation stage of the AlphaFold pipeline by over 10X for longer sequences. We demonstrate the types of analyses that can be performed on proteome-scale collections of sequences, including a search for novel quaternary structures and implications for functional annotation.

Gao, Mu↗
DOE OSTI2023

The impact of physiologically relevant temperatures on physical properties of thylakoid membranes: a molecular dynamics study

Thylakoid membranes are energy-converting membranes with a unique lipid composition. Though the membranes are primarily composed of proteins, their photosynthetic function is strongly influenced by the lipid constituents. Here we characterize, with molecular dynamics (MD) simulations, lipid bilayers with compositions representative of plant thylakoid membranes. We determine, in a wide range of temperatures, the physical parameters of the model membranes which are relevant for the photosynthetic function. We found a marked impact of temperature on membrane permeability due to a combination of increased compressibility and curvature of the membrane at elevated temperatures. With increasing temperatures, we observed increasingly smeared transmembrane density profiles of the membrane forming lipid headgroups predicting increased membrane flexibility. The diffusion coefficient of the lipids increased with temperature without apparent specificity for lipid species. Instead of a comprehensive experimental dataset in the relevant temperature range, we quantitatively compared and validated our MD results with MD simulations on a dipalmitoylphosphatidylcholine model system.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

3D-Printed Hydrogel Composites for Predictive Temporal (4D) Cellular Organizations and Patterned Biogenic Mineralization

Materials chemistries for hydrogel scaffolds that are capable of programming temporal (4D) attributes of cellular decision-making in supported 3D microcultures are described. The scaffolds are fabricated using direct-ink writing (DIW)-a 3D-printing technique using extrusion to pattern scaffolds at biologically relevant diameters (<= 100 mu m). Herein, DIW is exploited to variously incorporate a rheological nanoclay, Laponite XLG (LAP), into 2-hydroxyethyl methacrylate (HEMA)-based hydrogels-printing the LAP-HEMA (LH) composites as functional modifiers within otherwise unmodified 2D and 3D HEMA microstructures. The nanoclay-modified domains, when tested as thin films, require no activating (e.g., protein) treatments to promote robust growth compliances that direct the spatial attachment of fibroblast (3T3) and preosteoblast (E1) cells, fostering for the latter a capacity to direct long-term osteodifferentiation. Cell-to-gel interfacial morphologies and cellular motility are analyzed with spatial light interference microscopy (SLIM). Through combination of HEMA and LH gels, high-resolution DIW of a nanocomposite ink (UniH) that translates organizationally dynamic attributes seen with 2D gels into dentition-mimetic 3D scaffolds is demonstrated. These analyses confirm that the underlying materials chemistry and geometry of hydrogel nanocomposites are capable of directing cellular attachment and temporal development within 3D microcultures-a useful material system for the 4D patterning of hydrogel scaffolds.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Modeling Clustered DNA Damage by Ionizing Radiation Using Multinomial Damage Probabilities and Energy Imparted Spectra

Simple and complex clustered DNA damage represent the critical initial damage caused by radiation. In this paper, a multinomial probability model of clustered damage is developed with probabilities dependent on the energy imparted to DNA and surrounding water molecules. The model consists of four probabilities: (A) direct damage of sugar-phosphate moieties leading to SSB, (B) OH− radical formation with subsequent SSB and BD formation, (C) direct damage to DNA bases, and (D) energy imparted to histone proteins and other molecules in a volume not leading to SSB or BD. These probabilities are augmented by introducing probabilities for the relative location of SSB using a ≤10 bp criteria for a double-strand break (DSB) and for the possible success of a radical attack that leads to SSB or BD. Model predictions for electrons, 4He, and 12C ions are compared to the experimental data and show good agreement. Thus, the developed model allows an accurate and rapid computational method to predict simple and complex clustered DNA damage as a function of radiation quality and to explore the resulting challenges to DNA repair.

Biochemistry & Molecular Biology↗
DOE OSTI2011

Proteomic and Functional Analysis of the Cellulase System Expressed by Postia placenta during Brown Rot of Solid Wood

Abstract Brown rot basidiomycetes have an important ecological role in lignocellulose recycling and are notable for their rapid degradation of wood polymers via oxidative and hydrolytic mechanisms. However, most of these fungi apparently lack processive (exo-acting) cellulases, such as cellobiohydrolases, which are generally required for efficient cellulolysis. The recent sequencing of the Postia placenta genome now permits a proteomic approach to this longstanding conundrum. We grew P. placenta on solid aspen wood, extracted proteins from the biodegrading substrate, and analyzed tryptic digests by shotgun liquid chromatography-tandem mass spectrometry. Comparison of the data with the predicted P. placenta proteome revealed the presence of 34 likely glycoside hydrolases, but only four of these-two in glycoside hydrolase family 5, one in family 10, and one in family 12-have sequences that suggested possible activity on cellulose. We expressed these enzymes heterologously and determined that they all exhibited endoglucanase activity on phosphoric acid-swollen cellulose. They also slowly hydrolyzed filter paper, a more crystalline substrate, but the soluble/insoluble reducing sugar ratios they produced classify them as nonprocessive. Computer simulations indicated that these enzymes produced soluble/insoluble ratios on reduced phosphoric acid-swollen cellulose that were higher than expected for random hydrolysis, which suggests that they could possess limited exo activity, but they are at best 10-fold less processive than cellobiohydrolases. It appears likely that P. placenta employs a combination of oxidative mechanisms and endo-acting cellulases to degrade cellulose efficiently in the absence of a significant processive component.

Cellulase↗
DOE OSTI2015

DNA-mediated engineering of multicomponent enzyme crystals

The ability to predictably control the coassembly of multiple nanoscale building blocks, especially those with disparate chemical and physical properties such as biomolecules and inorganic nanoparticles, has far-reaching implications in catalysis, sensing, and photonics, but a generalizable strategy for engineering specific contacts between these particles is an outstanding challenge. This is especially true in the case of proteins, where the types of possible interparticle interactions are numerous, diverse, and complex. In this paper, we explore the concept of trading protein–protein interactions for DNA–DNA interactions to direct the assembly of two nucleic-acid–functionalized proteins with distinct surface chemistries into six unique lattices composed of catalytically active proteins, or of a combination of proteins and DNA-modified gold nanoparticles. The programmable nature of DNA–DNA interactions used in this strategy allows us to control the lattice symmetries and unit cell constants, as well as the compositions and habit, of the resulting crystals. Finally, this study provides a potentially generalizable strategy for constructing a unique class of materials that take advantage of the diverse morphologies, surface chemistries, and functionalities of proteins for assembling functional crystalline materials.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Antisense targeting of decoy exons can reduce intron retention and increase protein expression in human erythroblasts

The decoy exon model has been proposed to regulate a subset of intron retention (IR) events involving predominantly larger introns (>1 kb). Splicing reporter studies have shown that decoy splice sites are essential for activity, suggesting that decoys act by engaging intron-terminal splice sites and competing with cross-intron interactions required for intron excision. The decoy model predicts that antisense oligonucleotides may be able to block decoy splice sites in endogenous pre-mRNA, thereby reducing IR and increasing productive gene expression. Indeed, we now demonstrate that targeting a decoy 5' splice site in the O-GlcNAc transferase (OGT) gene reduced IR from ~80% to ~20% in primary human erythroblasts, accompanied by increases in spliced OGT RNA and OGT protein expression. The remaining OGT IR was refractory to antisense treatment and might be mediated by independent mechanism(s). In contrast, other retained introns were strongly dependent on decoy function, since antisense targeting of decoy 5' splice sites greatly reduced (SNRNP70) or nearly eliminated (SF3B1) IR in two widely expressed splicing factors, and also greatly reduced IR in transcripts encoding the erythroid-specific structural protein, α-spectrin (SPTA1). These results show that modulating decoy exon function can dramatically alter IR and suggest that dynamic regulation of decoy exons could be a mechanism to fine-tune gene expression post-transcriptionally in many cell types.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Distinct function of Chlamydomonas CTRA-CTR transporters in Cu assimilation and intracellular mobilization

Abstract Successful acclimation to copper (Cu) deficiency involves a fine balance between Cu import and export. In the green alga Chlamydomonas reinhardtii, Cu import is dependent on a transcription factor, Copper Response Regulator 1 (CRR1), responsible for activating genes in Cu-deficient cells. Among CRR1 target genes are two Cu transporters belonging to the CTR/COPT gene family (CTR1 and CTR2) and a related soluble protein (CTR3). The ancestor of these green algal proteins was likely acquired from an ancient chytrid and contained conserved cysteine-rich domains (named the CTR-associated domains, CTRA) that are predicted to be involved in Cu acquisition. We show by reverse genetics that Chlamydomonas CTR1 and CTR2 are canonical Cu importers albeit with distinct affinities, while loss of CTR3 did not result in an observable phenotype under the conditions tested. Mutation of CTR1, but not CTR2, recapitulates the poor growth of crr1 in Cu-deficient medium, consistent with a dominant role for CTR1 in high-affinity Cu(I) uptake. On the other hand, the overaccumulation of Cu(I) (20 times the quota) in zinc (Zn) deficiency depends on CRR1 and both CTR1 and CTR2. CRR1-dependent activation of CTR gene expression needed for Cu over-accumulation can be bypassed by the provision of excess Cu in the growth medium. Over-accumulated Cu is sequestered into the acidocalcisome but can become remobilized by restoring Zn nutrition. This mobilization is also CRR1-dependent, and requires activation of CTR2 expression, again distinguishing CTR2 from CTR1 and consistent with the lower substrate affinity of CTR2. One sentence summary Regulation of Cu uptake and sequestration by members of the CTR family of proteins in Chlamydomonas.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

VirtualToxLab — A platform for estimating the toxic potential of drugs, chemicals and natural products

The VirtualToxLab is an in silico technology for estimating the toxic potential (endocrine and metabolic disruption, some aspects of carcinogenicity and cardiotoxicity) of drugs, chemicals and natural products. The technology is based on an automated protocol that simulates and quantifies the binding of small molecules towards a series of proteins, known or suspected to trigger adverse effects. The toxic potential, a non-linear function ranging from 0.0 (none) to 1.0 (extreme), is derived from the individual binding affinities of a compound towards currently 16 target proteins: 10 nuclear receptors (androgen, estrogen α, estrogen β, glucocorticoid, liver X, mineralocorticoid, peroxisome proliferator-activated receptor γ, progesterone, thyroid α, and thyroid β), four members of the cytochrome P450 enzyme family (1A2, 2C9, 2D6, and 3A4), a cytosolic transcription factor (aryl hydrocarbon receptor) and a potassium ion channel (hERG). The interface to the technology allows building and uploading molecular structures, viewing and downloading results and, most importantly, rationalizing any prediction at the atomic level by interactively analyzing the binding mode of a compound with its target protein(s) in real-time 3D. The VirtualToxLab has been used to predict the toxic potential for over 2500 compounds: the results are posted on (http://www.virtualtoxlab.org). The free platform — the OpenVirtualToxLab — is accessible (in client–server mode) over the Internet. It is free of charge for universities, governmental agencies, regulatory bodies and non-profit organizations. -- Highlights: ► In silico technology for estimating the toxic potential of drugs and chemicals. ► Simulation of binding towards 16 proteins suspected to trigger adverse effects. ► Mechanistic interpretation and real-time 3D visualization. ► Accessible over the Internet. ► Free of charge for universities, governmental agencies, regulatory bodies and NPOs.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1994

Extracellular matrix controls tubulin monomer levels in hepatocytes by regulating protein turnover

Cells have evolved an autoregulatory mechanism to dampen variations in the concentration of tubulin monomer that is available to polymerize into microtubules (MTs), a process that is known as tubulin autoregulation. However, thermodynamic analysis of MT polymerization predicts that the concentration of free tubulin monomer must vary if MTs are to remain stable under different mechanical loads that result from changes in cell adhesion to the extracellular matrix (ECM). To determine how these seemingly contradictory regulatory mechanisms coexist in cells, we measured changes in the masses of tubulin monomer and polymer that resulted from altering cell-ECM contacts. Primary rat hepatocytes were cultured in chemically defined medium on bacteriological petri dishes that were precoated with different densities of laminin (LM). Increasing the LM density from low to high (1-1000 ng/cm2), promoted cell spreading (average projected cell area increased from 1200 to 6000 microns2) and resulted in formation of a greatly extended MT network. Nevertheless, the steady-state mass of tubulin polymer was similar at 48 h, regardless of cell shape or ECM density. In contrast, round hepatocytes on low LM contained a threefold higher mass of tubulin monomer when compared with spread cells on high LM. Furthermore, similar results were obtained whether LM, fibronectin, or type I collagen were used for cell attachment. Tubulin autoregulation appeared to function normally in these cells because tubulin mRNA levels and protein synthetic rates were greatly depressed in round cells that contained the highest level of free tubulin monomer. However, the rate of tubulin protein degradation slowed, causing the tubulin half-life to increase from approximately 24 to 55 h as the LM density was lowered from high to low and cell rounding was promoted. These results indicate that the set-point for the tubulin monomer mass in hepatocytes can be regulated by altering the density of ECM contacts and changing cell shape. This finding is consistent with a mechanism of MT regulation in which the ECM stabilizes MTs by both accepting transfer of mechanical loads and altering tubulin degradation in cells that continue to autoregulate tubulin synthesis.

Non-NASA Center↗
DOE OSTI2011

Structures of segments of [alpha]-synuclein fused to maltose-binding protein suggest intermediate states during amyloid formation

Aggregates of the protein {alpha}-synuclein are the main component of Lewy bodies, the hallmark of Parkinson's disease. {alpha}-Synuclein aggregates are also found in many human neurodegenerative diseases known as synucleinopathies. In vivo, {alpha}-synuclein associates with membranes and adopts {alpha}-helical conformations. The details of how {alpha}-synuclein converts from the functional native state to amyloid aggregates remain unknown. In this study, we use maltose-binding protein (MBP) as a carrier to crystallize segments of {alpha}-synuclein. From crystal structures of fusions between MBP and four segments of {alpha}-synuclein, we have been able to trace a virtual model of the first 72 residues of {alpha}-synuclein. Instead of a mostly {alpha}-helical conformation observed in the lipid environment, our crystal structures show {alpha}-helices only at residues 1-13 and 20-34. The remaining segments are extended loops or coils. All of the predicted fiber-forming segments based on the 3D profile method are in extended conformations. We further show that the MBP fusion proteins with fiber-forming segments from {alpha}-synuclein can also form fiber-like nano-crystals or amyloid-like fibrils. Our structures suggest intermediate states during amyloid formation of {alpha}-synuclein.

59 BASIC BIOLOGICAL SCIENCES↗