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Systematic Identification of Oncogenic EGFR Interaction Partners.

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Systematic Identification of Oncogenic EGFR Interaction Partners.

J Mol Biol. 2016 Dec 09;:

Authors: Petschnigg J, Kotlyar M, Blair L, Jurisica I, Stagljar I, Ketteler R

Abstract
The Epidermal Growth Factor Receptor (EGFR) is a receptor tyrosine kinase that - once activated upon ligand binding - leads to receptor dimerization, recruitment of protein complexes and activation of multiple signaling cascades. The EGFR is frequently overexpressed or mutated in various cancers leading to aberrant signaling and tumor growth. Hence, identification of interaction partners that bind to mutated EGFR can help identify novel targets for drug discovery. Here, we used a systematic approach to identify novel proteins that are involved in cancerous EGFR-signaling. Using a combination of high-content imaging and a mammalian membrane two-hybrid protein-protein interaction (MaMTH) method, we identified 8 novel interaction partners of EGFR, out of which half strongly interacted with oncogenic, hyperactive EGFR variants. One of these, TACC3, stabilizes EGFR on the cell surface, which results in an increase in downstream signaling via the MAPK and AKT pathway. Depletion of TACC3 from cells using shRNA knockdown or small molecule targeting reduced mitogenic signaling in non-small cell lung cancer cell lines, suggesting that targeting TACC3 has potential as a new therapeutic approach for non-small cell lung cancer.

PMID: 27956147 [PubMed - as supplied by publisher]



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Machine learning and computer vision approaches for phenotypic profiling.

Machine learning and computer vision approaches for phenotypic profiling.

J Cell Biol. 2016 Dec 09;:

Authors: Grys BT, Lo DS, Sahin N, Kraus OZ, Morris Q, Boone C, Andrews BJ

Abstract
With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach.

PMID: 27940887 [PubMed - as supplied by publisher]



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The profile of adsorbed plasma and serum proteins on methacrylic acid copolymer beads: Effect on complement activation.

The profile of adsorbed plasma and serum proteins on methacrylic acid copolymer beads: Effect on complement activation.

Biomaterials. 2016 Nov 25;118:74-83

Authors: Wells LA, Guo H, Emili A, Sefton MV

Abstract
Polymer beads made of 45% methacrylic acid co methyl methacrylate (MAA beads) promote vascular regenerative responses in contrast to control materials without methacrylic acid (here polymethyl methacrylate beads, PMMA). In vitro and in vivo studies suggest that MAA copolymers induce differences in macrophage phenotype and polarization and inflammatory responses, presumably due to protein adsorption differences between the beads. To explore differences in protein adsorption in an unbiased manner, we used high resolution shotgun mass spectrometry to identify and compare proteins that adsorb from human plasma or serum onto MAA and PMMA beads. From plasma, MAA beads adsorbed many complement proteins, such as C1q, C4-related proteins and the complement inhibitor factor H, while PMMA adsorbed proteins, such as albumin, C3 and apolipoproteins. Because of the differences in complement protein adsorption, follow-up studies focused on using ELISA to assess complement activation. When incubated in serum, MAA beads generated significantly lower levels of soluble C5b9 and C3a/C3adesarg in comparison to PMMA beads, indicating a decrease in complement activation with MAA beads. The differences in adsorbed protein on the two materials likely alter subsequent cell-material interactions that ultimately result in different host responses and local vascularization.

PMID: 27940384 [PubMed - as supplied by publisher]



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Functional characterisation of long intergenic non-coding RNAs through genetic interaction profiling in Saccharomyces cerevisiae.

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Functional characterisation of long intergenic non-coding RNAs through genetic interaction profiling in Saccharomyces cerevisiae.

BMC Biol. 2016 Dec 07;14(1):106

Authors: Kyriakou D, Stavrou E, Demosthenous P, Angelidou G, San Luis BJ, Boone C, Promponas VJ, Kirmizis A

Abstract
BACKGROUND: Transcriptome studies have revealed that many eukaryotic genomes are pervasively transcribed producing numerous long non-coding RNAs (lncRNAs). However, only a few lncRNAs have been ascribed a cellular role thus far, with most regulating the expression of adjacent genes. Even less lncRNAs have been annotated as essential hence implying that the majority may be functionally redundant. Therefore, the function of lncRNAs could be illuminated through systematic analysis of their synthetic genetic interactions (GIs).
RESULTS: Here, we employ synthetic genetic array (SGA) in Saccharomyces cerevisiae to identify GIs between long intergenic non-coding RNAs (lincRNAs) and protein-coding genes. We first validate this approach by demonstrating that the telomerase RNA TLC1 displays a GI network that corresponds to its well-described function in telomere length maintenance. We subsequently performed SGA screens on a set of uncharacterised lincRNAs and uncover their connection to diverse cellular processes. One of these lincRNAs, SUT457, exhibits a GI profile associating it to telomere organisation and we consistently demonstrate that SUT457 is required for telomeric overhang homeostasis through an Exo1-dependent pathway. Furthermore, the GI profile of SUT457 is distinct from that of its neighbouring genes suggesting a function independent to its genomic location. Accordingly, we show that ectopic expression of this lincRNA suppresses telomeric overhang accumulation in sut457Δ cells assigning a trans-acting role for SUT457 in telomere biology.
CONCLUSIONS: Overall, our work proposes that systematic application of this genetic approach could determine the functional significance of individual lncRNAs in yeast and other complex organisms.

PMID: 27927215 [PubMed - in process]



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A 17-gene stemness score for rapid determination of risk in acute leukaemia.

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A 17-gene stemness score for rapid determination of risk in acute leukaemia.

Nature. 2016 12 15;540(7633):433-437

Authors: Ng SW, Mitchell A, Kennedy JA, Chen WC, McLeod J, Ibrahimova N, Arruda A, Popescu A, Gupta V, Schimmer AD, Schuh AC, Yee KW, Bullinger L, Herold T, Görlich D, Büchner T, Hiddemann W, Berdel WE, Wörmann B, Cheok M, Preudhomme C, Dombret H, Metzeler K, Buske C, Löwenberg B, Valk PJ, Zandstra PW, Minden MD, Dick JE, Wang JC

Abstract
Refractoriness to induction chemotherapy and relapse after achievement of remission are the main obstacles to cure in acute myeloid leukaemia (AML). After standard induction chemotherapy, patients are assigned to different post-remission strategies on the basis of cytogenetic and molecular abnormalities that broadly define adverse, intermediate and favourable risk categories. However, some patients do not respond to induction therapy and another subset will eventually relapse despite the lack of adverse risk factors. There is an urgent need for better biomarkers to identify these high-risk patients before starting induction chemotherapy, to enable testing of alternative induction strategies in clinical trials. The high rate of relapse in AML has been attributed to the persistence of leukaemia stem cells (LSCs), which possess a number of stem cell properties, including quiescence, that are linked to therapy resistance. Here, to develop predictive and/or prognostic biomarkers related to stemness, we generated a list of genes that are differentially expressed between 138 LSC(+) and 89 LSC(-) cell fractions from 78 AML patients validated by xenotransplantation. To extract the core transcriptional components of stemness relevant to clinical outcomes, we performed sparse regression analysis of LSC gene expression against survival in a large training cohort, generating a 17-gene LSC score (LSC17). The LSC17 score was highly prognostic in five independent cohorts comprising patients of diverse AML subtypes (n = 908) and contributed greatly to accurate prediction of initial therapy resistance. Patients with high LSC17 scores had poor outcomes with current treatments including allogeneic stem cell transplantation. The LSC17 score provides clinicians with a rapid and powerful tool to identify AML patients who do not benefit from standard therapy and who should be enrolled in trials evaluating novel upfront or post-remission strategies.

PMID: 27926740 [PubMed - indexed for MEDLINE]



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Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism.

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Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism.

Nature. 2016 12 15;540(7633):423-427

Authors: Parikshak NN, Swarup V, Belgard TG, Irimia M, Ramaswami G, Gandal MJ, Hartl C, Leppa V, Ubieta LT, Huang J, Lowe JK, Blencowe BJ, Horvath S, Geschwind DH

Abstract
Autism spectrum disorder (ASD) involves substantial genetic contributions. These contributions are profoundly heterogeneous but may converge on common pathways that are not yet well understood. Here, through post-mortem genome-wide transcriptome analysis of the largest cohort of samples analysed so far, to our knowledge, we interrogate the noncoding transcriptome, alternative splicing, and upstream molecular regulators to broaden our understanding of molecular convergence in ASD. Our analysis reveals ASD-associated dysregulation of primate-specific long noncoding RNAs (lncRNAs), downregulation of the alternative splicing of activity-dependent neuron-specific exons, and attenuation of normal differences in gene expression between the frontal and temporal lobes. Our data suggest that SOX5, a transcription factor involved in neuron fate specification, contributes to this reduction in regional differences. We further demonstrate that a genetically defined subtype of ASD, chromosome 15q11.2-13.1 duplication syndrome (dup15q), shares the core transcriptomic signature observed in idiopathic ASD. Co-expression network analysis reveals that individuals with ASD show age-related changes in the trajectory of microglial and synaptic function over the first two decades, and suggests that genetic risk for ASD may influence changes in regional cortical gene expression. Our findings illustrate how diverse genetic perturbations can lead to phenotypic convergence at multiple biological levels in a complex neuropsychiatric disorder.

PMID: 27919067 [PubMed - indexed for MEDLINE]



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Proteomic analysis of the human KEOPS complex identifies C14ORF142 as a core subunit homologous to yeast Gon7.

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Proteomic analysis of the human KEOPS complex identifies C14ORF142 as a core subunit homologous to yeast Gon7.

Nucleic Acids Res. 2016 Nov 29;:

Authors: Wan LC, Maisonneuve P, Szilard RK, Lambert JP, Ng TF, Manczyk N, Huang H, Laister R, Caudy AA, Gingras AC, Durocher D, Sicheri F

Abstract
The KEOPS/EKC complex is a tRNA modification complex involved in the biosynthesis of N(6)-threonylcarbamoyladenosine (t(6)A), a universally conserved tRNA modification found on ANN-codon recognizing tRNAs. In archaea and eukaryotes, KEOPS is composed of OSGEP/Kae1, PRPK/Bud32, TPRKB/Cgi121 and LAGE3/Pcc1. In fungi, KEOPS contains an additional subunit, Gon7, whose orthologs outside of fungi, if existent, remain unidentified. In addition to displaying defective t(6)A biosynthesis, Saccharomyces cerevisiae strains harboring KEOPS mutations are compromised for telomere homeostasis, growth and transcriptional co-activation. To identify a Gon7 ortholog in multicellular eukaryotes as well as to uncover KEOPS-interacting proteins that may link t(6)A biosynthesis to the diverse set of KEOPS mutant phenotypes, we conducted a proteomic analysis of human KEOPS. This work identified 152 protein interactors, one of which, C14ORF142, interacted strongly with all four KEOPS subunits, suggesting that it may be a core component of human KEOPS. Further characterization of C14ORF142 revealed that it shared a number of biophysical and biochemical features with fungal Gon7, suggesting that C14ORF142 is the human ortholog of Gon7. In addition, our proteomic analysis identified specific interactors for different KEOPS subcomplexes, hinting that individual KEOPS subunits may have additional functions outside of t(6)A biosynthesis.

PMID: 27903914 [PubMed - as supplied by publisher]



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Mitochondrial control through nutritionally regulated global histone H3 lysine-4 demethylation.

Mitochondrial control through nutritionally regulated global histone H3 lysine-4 demethylation.

Sci Rep. 2016 Nov 29;6:37942

Authors: Soloveychik M, Xu M, Zaslaver O, Lee K, Narula A, Jiang R, Rosebrock AP, Caudy AA, Meneghini MD

Abstract
Histone demethylation by Jumonji-family proteins is coupled with the decarboxylation of α-ketoglutarate (αKG) to yield succinate, prompting hypotheses that their activities are responsive to levels of these metabolites in the cell. Consistent with this paradigm we show here that the Saccharomyces cerevisiae Jumonji demethylase Jhd2 opposes the accumulation of H3K4me3 in fermenting cells only when they are nutritionally manipulated to contain an elevated αKG/succinate ratio. We also find that Jhd2 opposes H3K4me3 in respiratory cells that do not exhibit such an elevated αKG/succinate ratio. While jhd2∆ caused only limited gene expression defects in fermenting cells, transcript profiling and physiological measurements show that JHD2 restricts mitochondrial respiratory capacity in cells grown in non-fermentable carbon in an H3K4me-dependent manner. In association with these phenotypes, we find that JHD2 limits yeast proliferative capacity under physiologically challenging conditions as measured by both replicative lifespan and colony growth on non-fermentable carbon. JHD2's impact on nutrient response may reflect an ancestral role of its gene family in mediating mitochondrial regulation.

PMID: 27897198 [PubMed - in process]



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Brief Report: Stage-specific differences in secretory profile of mesenchymal stromal cells (MSCs) subjected to early-vs. late-stage OA synovial fluid.

Brief Report: Stage-specific differences in secretory profile of mesenchymal stromal cells (MSCs) subjected to early-vs. late-stage OA synovial fluid.

Osteoarthritis Cartilage. 2016 Nov 25;:

Authors: Gómez-Aristizábal A, Sharma A, Bakooshli MA, Kapoor M, Gilbert PM, Viswanathan S, Gandhi R

Abstract
OBJECTIVE: Although, mesenchymal stromal cells (MSCs) are being clinically investigated for their use in osteoarthritis (OA), it is unclear whether their postulated therapeutic properties are equally effective in the early- and late-stages of OA. In this study we investigated MSC cytokine secretion post-exposure to synovial fluid (SF), obtained from early-vs. late-stage knee OA patients to justify a potential patient stratification strategy to maximize MSC-mediated treatment effects.
METHOD: Subjects were recruited and categorized into early- [Kellgren-Lawrence (KL) grade I/II, n = 12] and late-stage (KL-III/IV, n = 12) knee OA groups. SF samples were obtained, and their proteome was tested using multiplex assays, after three-days culture, with and without MSCs. SFs cultured without MSCs were used as a baseline to identify MSC-secreted factors into SFs cultured with MSCs. Linear mixed-effect models and non-parametric tests were used to identify alterations in the MSC secretome during exposure to OA SF (three-days). MSCs cultured for three-days in 0.5% fetal bovine serum-supplemented medium were used to compare SF results with culture medium.
RESULTS: Following exposure to OA SF, the MSC secretome contained proteins that are involved in tissue repair, angiogenesis, chemotaxis, matrix remodeling and the clotting process. However, CXCL8 (chemokine (C-X-C motif) ligand-8; chemoattractant), interleukin-6 and CCL2 (chemokine (C-C motif) ligand 2) were elevated in the MSC-secretome in response to early-vs. late-stage OA SF.
CONCLUSION: Early-vs. late-stage OA SF samples elicit a differential MSC secretome response, arguing for stratification of OA patients to maximize MSC-mediated therapeutic effects.

PMID: 27894935 [PubMed - as supplied by publisher]



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A Highly Diverse and Functional Naïve Ubiquitin Variant Library for Generation of Intracellular Affinity Reagents.

A Highly Diverse and Functional Naïve Ubiquitin Variant Library for Generation of Intracellular Affinity Reagents.

J Mol Biol. 2016 Nov 22;:

Authors: Leung I, Jarvik N, Sidhu S

Abstract
We report the design, construction and validation of a highly diverse phage-displayed naïve ubiquitin variant (Ubv) library. We first conducted a mutation tolerance scan of 27 residues and confirmed that 24 of these could be substituted by chemically diverse amino acids without compromising the display of Ubvs on phage. Subsequently, we constructed a library containing 6.8×10(10) unique members in which these 24 positions were diversified with a degenerate codon that encodes for six amino acids that are prevalent in protein interaction sites. To ensure optimal structural stability of the Ubvs, the library was constructed in a two-step process whereby 12 positions were randomized first, and following selection for displayed Ubvs, the resulting pool was further diversified at the other 12 positions. The resulting library was validated by conducting binding selections against a panel of 40 diverse protein antigens and was found to be as functional as a highly validated synthetic antibody library, yielding binders against 30 of the antigens. Detailed characterization of an Ubv that bound to the cell-surface receptor Her3 revealed tight binding in the single-digit nanomolar range. Moreover, Ubvs that bound to two distinct sites on the intracellular adapter Grb2 could be combined to generate a potent inhibitor that functioned in cells. These results validate ubiquitin as a robust scaffold for the construction of naïve libraries that can be used to generate Ubvs that target signaling networks both outside and inside cells.

PMID: 27887869 [PubMed - as supplied by publisher]



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