Allosteric response and substrate sensitivity in peptide binding of the signal recognition particle

We characterize the conformational dynamics and substrate selectivity of the signal recognition particle (SRP) using a thermodynamic free energy cycle approach and microsecond-timescale molecular dynamics simulations. The SRP is a central component of the co-translational protein targeting machinery that binds to the N-terminal signal peptide (SP) of nascent proteins. We determined the shift in relative conformational stability of the SRP upon substrate binding to quantify allosteric coupling between SRP domains. In particular, for dipeptidyl aminopeptidase, an SP that is recognized by the SRP for co-translational targeting, it is found that substrate binding induces substantial changes in the SRP towards configurations associated with targeting of the nascent protein, and it is found that the changes are modestly enhanced by a mutation that increases the hydrophobicity of the SP; however for alkaline phosphotase, an SP that is recognized for post-translational targeting, substrate binding induces the reverse change in the SRP conformational distribution away from targeting configurations. Microsecond-timescale trajectories reveal the intrinsic flexibility of the SRP conformational landscape and provide insight into recent single-molecule studies by illustrating that 10 nm lengthscale changes between FRET pairs occur via the rigid-body movement of SRP domains connected by the flexible linker region. In combination, these results provide direct evidence for the hypothesis that substrate-controlled conformational switching in the SRP provides a mechanism for discriminating between different SPs and for connecting substrate binding to downstream steps in the protein targeting pathway

Structurally detailed coarse-grained model for Sec-facilitated co-translational protein translocation and membrane integration

We present a coarse-grained simulation model that is capable of simulating the minute-timescale dynamics of protein translocation and membrane integration via the Sec translocon, while retaining sufficient chemical and structural detail to capture many of the sequence-specific interactions that drive these processes. The model includes accurate geometric representations of the ribosome and Sec translocon, obtained directly from experimental structures, and interactions parameterized from nearly 200 μs of residue-based coarse-grained molecular dynamics simulations. A protocol for mapping amino-acid sequences to coarse-grained beads enables the direct simulation of trajectories for the co-translational insertion of arbitrary polypeptide sequences into the Sec translocon. The model reproduces experimentally observed features of membrane protein integration, including the efficiency with which polypeptide domains integrate into the membrane, the variation in integration efficiency upon single amino-acid mutations, and the orientation of transmembrane domains. The central advantage of the model is that it connects sequence-level protein features to biological observables and timescales, enabling direct simulation for the mechanistic analysis of co-translational integration and for the engineering of membrane proteins with enhanced membrane integration efficiency

Protein stability engineering insights revealed by domain-wide comprehensive mutagenesis

The accurate prediction of protein stability upon sequence mutation is an important but unsolved challenge in protein engineering. Large mutational datasets are required to train computational predictors, but traditional methods for collecting stability data are either low-throughput or measure protein stability indirectly. Here, we develop an automated method to generate thermodynamic stability data for nearly every single mutant in a small 56-residue protein. Analysis reveals that most single mutants have a neutral effect on stability, mutational sensitivity is largely governed by residue burial, and unexpectedly, hydrophobics are the best tolerated amino acid type. Correlating the output of various stability-prediction algorithms against our data shows that nearly all perform better on boundary and surface positions than for those in the core and are better at predicting large-to-small mutations than small-to-large ones. We show that the most stable variants in the single-mutant landscape are better identified using combinations of 2 prediction algorithms and including more algorithms can provide diminishing returns. In most cases, poor in silico predictions were tied to compositional differences between the data being analyzed and the datasets used to train the algorithm. Finally, we find that strategies to extract stabilities from high-throughput fitness data such as deep mutational scanning are promising and that data produced by these methods may be applicable toward training future stability-prediction tools

PKCθ Regulates T-Cell Leukemia-Initiating Activity via Reactive Oxygen Species

Reactive oxygen species (ROS), a by-product of cellular metabolism, damage intracellular macromolecules and, in excess, can promote normal hematopoietic stem cell differentiation and exhaustion1–3. However, mechanisms that regulate ROS levels in leukemia-initiating cells (LICs) and the biological role of ROS in these cells remain largely unknown. We show here the ROSlow subset of CD44+ cells in T-cell acute lymphoblastic leukemia (T-ALL), a malignancy of immature T-cell progenitors, to be highly enriched in the most aggressive LICs, and that ROS are maintained at low levels by downregulation of protein kinase C theta (PKCθ). Strikingly, primary mouse T-ALLs lacking PKCθ show improved LIC activity whereas enforced PKCθ expression in both mouse and human primary T-ALLs compromised LIC activity. We also demonstrate that PKCθ is positively regulated by RUNX1, and that NOTCH1, which is frequently activated by mutation in T-ALL4–6 and required for LIC activity in both mouse and human models7,8, downregulates PKCθ and ROS via a novel pathway involving induction of RUNX3 and subsequent repression of RUNX1. These results reveal key functional roles for PKCθ and ROS in T-ALL and suggest that aggressive biological behavior in vivo could be limited by therapeutic strategies that promote PKCθ expression/activity or ROS accumulation

Harold Rosenberg diante da Morte da arte

: http://filosofiacienciaevida.uol.com.br/ESFI/edicoes/34/sumario.aspRevista filosofiaRevista filosofia Edição 34 – 200

Myocardial production and release of MCP-1 and SDF-1 following myocardial infarction: differences between mice and man

<p>Abstract</p> <p>Background</p> <p>Stem cell homing to the heart is mediated by the release of chemo-attractant cytokines. Stromal derived factor -1 alpha (SDF-1a) and monocyte chemotactic factor 1(MCP-1) are detectable in peripheral blood after myocardial infarction (MI). It remains unknown if they are produced by, and released from, the heart in order to attract stem cells to repair the damaged myocardium.</p> <p>Methods</p> <p>Murine hearts were studied for expression of MCP-1 and SDF-1a at day 3 and day 28 following myocardial infarction to determine whether production is increased following MI. In addition, we studied the coronary artery and coronary sinus (venous) blood from patients with normal coronary arteries, stable coronary artery disease (CAD), unstable angina and MI to determine whether these cytokines are released from the heart into the systemic circulation following MI.</p> <p>Results</p> <p>Both MCP-1 and SDF-1a are constitutively produced and released by the heart. MCP-1 mRNA is upregulated following murine experimental MI, but SDF-1a is suppressed. There is less release of SDF-1a into the systemic circulation in patients with all stages of CAD including MI, mimicking the animal model. However MCP-1 release from the human heart following MI is also suppressed, which is the exact opposite of the animal model.</p> <p>Conclusions</p> <p>SDF-1a and MCP-1 release from the human heart are suppressed following MI. In the case of SDF-1a, the animal model appropriately reflects the human situation. However, for MCP-1 the animal model is the exact opposite of the human condition. Human observational studies like this one are paramount in guiding translation from experimental studies to clinical trials.</p

Loss of Adenomatous polyposis coli function renders intestinal epithelial cells resistant to the cytokine IL-22

Interleukin-22 (IL-22) is a critical immune defence cytokine that maintains intestinal homeostasis and promotes wound healing and tissue regeneration, which can support the growth of colorectal tumours. Mutations in the adenomatous polyposis coli gene (Apc) are a major driver of familial colorectal cancers (CRCs). How IL-22 contributes to APC-mediated tumorigenesis is poorly understood. To investigate IL-22 signalling in wild-type (WT) and APC-mutant cells, we performed RNA sequencing (RNAseq) of IL-22-treated murine small intestinal epithelial organoids. In WT epithelia, antimicrobial defence and cellular stress response pathways were most strongly induced by IL-22. Surprisingly, although IL-22 activates signal transducer and activator of transcription 3 (STAT3) in APC-mutant cells, STAT3 target genes were not induced. Our analyses revealed that ApcMin/Min cells are resistant to IL-22 due to reduced expression of the IL-22 receptor, and increased expression of inhibitors of STAT3, particularly histone deacetylases (HDACs). We further show that IL-22 increases DNA damage and genomic instability, which can accelerate cellular transition from heterozygosity (ApcMin/+) to homozygosity (ApcMin/Min) to drive tumour formation. Our data reveal an unexpected role for IL-22 in promoting early tumorigenesis while excluding a function for IL-22 in transformed epithelial cells

Genetic association study of QT interval highlights role for calcium signaling pathways in myocardial repolarization.

The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal mendelian long-QT syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals, we identified 35 common variant loci associated with QT interval that collectively explain ∼8-10% of QT-interval variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 new QT interval-associated loci in 298 unrelated probands with LQTS identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies new candidate genes for ventricular arrhythmias, LQTS and SCD

Postoperative serum proteomic profiles may predict recurrence-free survival in high-risk primary breast cancer

Item does not contain fulltextPURPOSE: Better breast cancer prognostication may improve selection of patients for adjuvant therapy. We conducted a retrospective longitudinal study in which we investigated sera of high-risk primary breast cancer patients, to search for proteins predictive of recurrence-free survival. METHODS: Sera of 82 breast cancer patients obtained after surgery, but prior to the administration of adjuvant therapy, were fractionated using anion-exchange chromatography, to facilitate the detection of the low-abundant serum peptides. Selected fractions were subsequently analysed by surface-enhanced laser desorption/ionisation time-of-flight mass spectrometry (SELDI-TOF MS), and the resulting protein profiles were searched for prognostic markers by appropriate bioinformatics tools. RESULTS: Four peak clusters (i.e. m/z 3073, m/z 3274, m/z 4405 and m/z 7973) were found to bear significant prognostic value (P </= 0.01). The m/z 3274 candidate marker was structurally identified as inter-alpha-trypsin inhibitor heavy chain 4 fragment(658-688) in serum. Except for the m/z 7973 peak cluster, these peaks remained independently associated with recurrence-free survival upon multivariate Cox regression analysis, including clinical parameters of known prognostic value in this study population. CONCLUSION: Investigation of the postoperative serum proteome by, e.g., anion-exchange fractionation followed by SELDI-TOF MS analysis is promising for the detection of novel prognostic factors. However, regarding the rather limited study population, validation of these results by analysis of independent study populations is warranted to assess the true clinical applicability of discovered prognostic markers. In addition, structural identification of the other markers will aid in elucidation of their role in breast cancer prognosis, as well as enable development of absolute quantitative assays

DPHL: A DIA Pan-human Protein Mass Spectrometry Library for Robust Biomarker Discovery

To address the increasing need for detecting and validating protein biomarkers in clinical specimens, mass spectrometry (MS)-based targeted proteomic techniques, including the selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and massively parallel data-independent acquisition (DIA), have been developed. For optimal performance, they require the fragment ion spectra of targeted peptides as prior knowledge. In this report, we describe a MS pipeline and spectral resource to support targeted proteomics studies for human tissue samples. To build the spectral resource, we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker. We then applied the workflow to generate DPHL, a comprehensive DIA pan-human library, from 1096 data-dependent acquisition (DDA) MS raw files for 16 types of cancer samples. This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer (PCa) patients. Thereafter, PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated. As a second application, the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma (DLBCL) patients and 18 healthy control subjects. Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery. DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000