Proteome-wide analysis of protein abundance and turnover remodelling during oncogenic transformation of human breast epithelial cells

Background: Viral oncogenes and mutated proto-oncogenes are potent drivers of cancer malignancy. Downstream of the oncogenic trigger are alterations in protein properties that give rise to cellular transformation and the acquisition of malignant cellular phenotypes. Developments in mass spectrometry enable large-scale, multidimensional characterisation of proteomes. Such techniques could provide an unprecedented, unbiased view of how oncogene activation remodels a human cell proteome. Methods: Using quantitative MS-based proteomics and cellular assays, we analysed how transformation induced by activating v-Src kinase remodels the proteome and cellular phenotypes of breast epithelial (MCF10A) cells. SILAC MS was used to comprehensively characterise the MCF10A proteome and to measure v-Src-induced changes in protein abundance across seven time-points (1-72 hrs). We used pulse-SILAC MS (Boisvert et al., 2012), to compare protein synthesis and turnover in control and transformed cells. Follow-on experiments employed a combination of cellular and functional assays to characterise the roles of selected Src-responsive proteins. Results: Src-induced transformation changed the expression and/or turnover levels of ~3% of proteins, affecting ~1.5% of the total protein molecules in the cell. Transformation increased the average rate of proteome turnover and disrupted protein homeostasis. We identify distinct classes of protein kinetics in response to Src activation. We demonstrate that members of the polycomb repressive complex 1 (PRC1) are important regulators of invasion and migration in MCF10A cells. Many Src-regulated proteins are present in low abundance and some are regulated post-transcriptionally. The signature of Src-responsive proteins is highly predictive of poor patient survival across multiple cancer types. Open access to search and interactively explore all these proteomic data is provided via the EPD database (www.peptracker.com/epd). Conclusions: We present the first comprehensive analysis measuring how protein expression and protein turnover is affected by cell transformation, providing a detailed picture at the protein level of the consequences of activation of an oncogene

Identification of small molecule inhibitors of pre-mRNA splicing

Background: There is a need for new small molecule pre-mRNA splicing inhibitors as biotools. Results: High throughput screening resulted in the identification of small molecule splicing inhibitors that are active in vitro and in cells. Conclusion: New small molecules for studying pre-mRNA splicing in vitro and in cells are identified. Significance: Small drug-like molecules are identified that modulate splicing in vitro and in cells. Eukaryotic pre-mRNA splicing is an essential step in gene expression for all genes that contain introns. In contrast to transcription and translation, few well characterized chemical inhibitors are available with which to dissect the splicing process, particularly in cells. Therefore, the identification of specific small molecules that either inhibit or modify pre-mRNA splicing would be valuable for research and potentially also for therapeutic applications. We have screened a highly curated library of 71,504 drug-like small molecules using a high throughput in vitro splicing assay. This identified 10 new compounds that both inhibit pre-mRNA splicing in vitro and modify splicing of endogenous pre-mRNA in cells. One of these splicing modulators, DDD00107587 (termed madrasin, i.e. 2-((7methoxy-4-methylquinazolin-2-yl)amino)-5,6-dimethylpyrimidin-4(3H)-one RNAsplicing inhibitor), was studied in more detail. Madrasin interferes with the early stages of spliceosome assembly and stalls spliceosome assembly at the A complex. Madrasin is cytotoxic at higher concentrations, although at lower concentrations it induces cell cycle arrest, promotes a specific reorganization of subnuclear protein localization, and modulates splicing of multiple pre-mRNAs in both HeLa and HEK293 cells

Perturbation of Chromatin Structure Globally Affects Localization and Recruitment of Splicing Factors

Chromatin structure is an important factor in the functional coupling between transcription and mRNA processing, not only by regulating alternative splicing events, but also by contributing to exon recognition during constitutive splicing. We observed that depolarization of neuroblastoma cell membrane potential, which triggers general histone acetylation and regulates alternative splicing, causes a concentration of SR proteins in nuclear speckles. This prompted us to analyze the effect of chromatin structure on splicing factor distribution and dynamics. Here, we show that induction of histone hyper-acetylation results in the accumulation in speckles of multiple splicing factors in different cell types. In addition, a similar effect is observed after depletion of the heterochromatic protein HP1α, associated with repressive chromatin. We used advanced imaging approaches to analyze in detail both the structural organization of the speckle compartment and nuclear distribution of splicing factors, as well as studying direct interactions between splicing factors and their association with chromatin in vivo. The results support a model where perturbation of normal chromatin structure decreases the recruitment efficiency of splicing factors to nascent RNAs, thus causing their accumulation in speckles, which buffer the amount of free molecules in the nucleoplasm. To test this, we analyzed the recruitment of the general splicing factor U2AF65 to nascent RNAs by iCLIP technique, as a way to monitor early spliceosome assembly. We demonstrate that indeed histone hyper-acetylation decreases recruitment of U2AF65 to bulk 3' splice sites, coincident with the change in its localization. In addition, prior to the maximum accumulation in speckles, ∼20% of genes already show a tendency to decreased binding, while U2AF65 seems to increase its binding to the speckle-located ncRNA MALAT1. All together, the combined imaging and biochemical approaches support a model where chromatin structure is essential for efficient co-transcriptional recruitment of general and regulatory splicing factors to pre-mRNA

Etablierung und Optimierung eines neuartigen Papillomvirus-Tiermodells für pharmakologische Studien

Papillomviren sind kleine nicht umhüllte DNA Viren, welche zu der Gruppe der Papovaviren gehören. Bis heute sind über 80 humanpathogene Papillomviren charakterisiert worden, welche spezifisch die Haut oder Schleimhaut infizieren und dort meist Benigne Tumore, wie z. B. vulgäre Warzen, Larynxpapillome oder genitale Warzen (Kondylome), induzieren. Bei langjähriger Persistenz des viralen Genoms und partieller Expression der viralen Gene können die Warzen jedoch maligne entarten und Karzinome bilden. Hurnane Papillomviren sind die am häufigsten sexuell übertragenen Infektionserreger, daher sind vor allem die malignen genitalen Turnore, wie das Zervixkarzinom, eine der häufigsten malignen Erkrankungen der Frau, mit 500.000 neuen Fällen jährlich weltweit, klinisch relevant. Derzeit wird zudem über eine mögliche Rolle der Papillomviren bei der Entstehung von Hautkrebs diskutiert. Der Vermehrungszyklus aller Papillomviren ist eng mit dem Differenzierungsgrad der infizierten Wirtszelle verknüpft. Die Replikation des viralen Genoms und die Synthese der Kapsidproteine findet bevorzugt in den terminal differenzierten Schichten des Epithels statt. Daher enllöglicht die Monolayer-Zellkultur keine Vermehrung von PV und erlaubt lediglich die Untersuchung begrenzter Ausschnitte im viralen Lebenszyklus. Dieser Umstand erschwert die Analyse später viraler Funktionen und ist auch eine Ursache dafiir, dass bis heute noch keine antiviral wirksame Therapie gegen Papillomviren existiert, ebenso wenig wie ein Impfstoff. Die Behandlung von Warzen beschränkt sich auf physikalische Methoden wie chirurgische Entfernung oder den Einsatz von Kryotherapie oder CO2-Laser, ohne dabei die virale DNA vollständig zu eliminieren. Zusätzlich werden fiir die Behandlung von HPV-Läsionen auch Substanzen mit immunmodulierenden Eigenschaften, wie z. B. Interferone und Imiquimod (Aldara TM), eingesetzt. Im Rahmen dieser Arbeit wurde ein Xenograft-Maus-Modell, das SCID-Bo-Modell, etabliert, bei welchem mit Bovinem Papillomvirus Typ 2 (BPV2) infizierte Kälberskrotalhaut auf den Rücken von SCID-Mäusen transplantiert wurde. Dieses Modell kann sowohl der Identifizierung von PV -inhibierenden Substanzen dienen als auch der Untersuchung des viralen Replikationszyklusses. Fünf Monate nach der Infektion bildeten sich Fibropapillome, welche die typische histologische Merkmale einer Papillomvirusinfektion (Akanthose, Papillomatose, Hyperkeratose, Koilocytose und Parakeratose) aufwiesen. Durch den Nachweis von Kapsidproteinen und der Produktion von infektiösen Viruspartikeln konnte zudem gezeigt werden, dass sich die im SCID-Bo-Modell induzierten Tumore nicht von natürlich vorkommenden Rinderwarzen unterschieden. Im Gegensatz zur nativen BPV2-DNA führte die Transfektion von einer gleich großen Menge an rekombinanter BPV2-DNA nur zu der Etablierung einer abortiven Infektion, bei welcher ausschließlich die friihen viralen Gene transkribiert und somit keine Viren produziert wurden. Diese Turnore zeigten außerdem nur einige schwach ausgeprägte morphologische Veränderungen der Epidermis und keine Proliferation der Dermis. Die Tumorbildung mittels rekombinanter virale DNA konnte weder durch die Verwendung eines Transfektions-Reagenzes noch durch die Erhöhung der Input-DNA entscheidend verbessert werden. Das E2-Protein ist das wichtigste Regulatorprotein der Papillomviren. Es ist nicht nur für die Replikation essentiell, sondern es reguliert auch die virale Transkription. Dennoch ist die Funktionen der einzelnen E2-Bindungsstellen (E2BS), welche in mehreren Kopien über das virale Genom verteilt sind, weitgehend unbekannt. Zwei in der nicht kodierenden Region liegende E2BS, E2BSS und E2BS8 wurden mutiert und in Zellkultur sowie im SCID-Bo-Modell getestet. Es konnten jedoch weder in C127-Zellen noch im Tiermodell Unterschiede zwischen Wildtyp und Mutanten in Hinblick auf die untersuchten Merkmale festgestellt werden. Auch in diesem Versuchsansatz konnte durch die Transfektion der rekombinanten viralen DNA nur eine abortive Virusinfektion etabliert werden. Das SCID-Bo-Modell eignet sich daher nur bedingt für genetische Studien mit in Bakterien synthetisierter Papillomvirus-DNA, da in dem bestehenden Modell nur die Auswirkungen auf frühe Ereignisse der Infektion untersucht werden können. Restriktionsanalysen mit den methylierungssensitiven Euzymen Hpall/Mspl und Hhal ergaben, dass die Unterschiede in der Tumorbildung bei Verwendung von rekombinanter und nativer DNA wahrscheinlich auf ein unterschiedliches Methylierungsmuster der CpG-Motive in den BPV2-Genomen zurückzuführen sind. Diese Annahme wird durch die Beobachtung gestützt, dass auch in Cl27-Zellen passagierte rekombinante BPV2-DNA nur zu der Induktion von Tumoren führt, welche keine Fibrombildung zeigten. Das hier auf Grundlage des Xenograft-Maus-Modells etablierte Tiermodellsystem ermöglicht die Untersuchung des viralen Replikationszyklus und die Produktion von Viren. Außerdem bietet das SCID-Bo-Model wegen seiner hohen Reproduzierbarkeit die idealen Bedingungen für die Identifikation antiviraler Substanzen. Für die Untersuchung von Virusmutanten eignet sich dieses Modellsystem jedoch nur bedingt. Weitere Versuche mit dem Ziel, die Tumorinduktion durch rekombinante DNA zu optimieren, und die Aufklärung der Gen-Regulation sind notwendig, um genetische Studien auch im Tiermodell durchführen zu können

Histone acetylation affects distribution of several splicing factors involved in constitutive and alternative splicing.

<p>(A) Several splicing factors tested show accumulation in nuclear speckles after a 6-hour TSA treatment of HeLa cells, including many SR proteins (SRSF2, SRSF1, SRSF3) and proteins of the U1 and U2 complexes (U1 70K, U1A, U2AF65). Top row shows control cells and bottom row shows cells treated with 0.2 ng/µl TSA. Some enlarged nuclear granules containing splicing factors in TSA-treated cells are marked by yellow arrowheads. Scale bars, 5 µm. (B) TSA treatment affects histone but not splicing factor lysine acetylation. HEK-293T cells were transfected with plasmids coding for the indicated tagged proteins (lanes 5–10) or not transfected (lanes 1–4). After one day, cells were incubated for 6 hours with or without 1 µM TSA, lysed and either histones were extracted (lanes 1–2) or proteins immunoprecipitated with antibodies against T7 tag (lanes 3–10). Purified proteins were analyzed by Western blot using an antibody that recognizes acetylated lysines (αAcLys, upper panels). As loading controls, proteins were also detected with antibodies against histone H3 or T7 tag (lower panels). In lanes 1 and 2, the two bands for the αAcLys correspond to histones H3 and H4, showing a dramatic increase of acetylation in both histones upon TSA treatment. In lanes 7 and 8, cells transfected with T7-SRSF2 were treated with the proteasome inhibitor MG132 (see text). (C) Total transcription is not affected after 6 h-TSA treatment. Global levels of nascent RNA in untreated and TSA-treated HeLa cells were measured by <i>in vivo</i> 5-FU incorporation and immunostaining with an antibody specific for 5-FU nucleotide. A representative field for each condition is shown. Brighter spots correspond to ribosomal RNA in nucleoli. Scale bars, 10 µm. Quantification of the 5-FU signal in individual cells (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048084#s3" target="_blank">Materials and Methods</a>) shows no significant change in transcription in TSA-treated vs. Control cells (<i>n</i> = 15 and 10 respectively). In contrast, treatment with the P-TEFb inhibitor DRB (<i>n</i> = 10 for each condition) and with the general transcription inhibitor actinomycin D (<i>n</i> = 5 for Control and 6 for ActD) causes a clear decrease in 5-FU incorporation, as expected from transcriptional inhibition.(D) Time course of EYFP-SRSF3 distribution in HeLa cells treated with 0.2 ng/µl TSA. A representative nucleus is shown. Images were acquired every 30 minutes. Yellow arrowheads point to a single speckle where accumulation of the tagged-SR protein is observed. Scale bars, 5 µm.</p

Chromatin relaxation affects spliceosome recruitment to nascent RNA and binding of splicing factors to ncRNAs.

<p>Binding of U2AF65 to RNA was assessed by iCLIP in 293-Flp cells, as a measure of spliceosome recruitment in Control cells or cells treated with 1 µM TSA for 2 h (before splicing factor accumulation in speckles is apparent) and 6 h. (A) TSA treatment causes an impairment of U2AF65 recruitment to the 3′ splice sites. Total U2AF65 counts in exon-intron (E-I) and intron-exon (I-E) junctions for all transcripts are plotted in a window of +/−50 nt from the junctions. The graph shows that iCLIP consistently captures U2AF65 at the expected location on the 3′ splice site (I-E junction), where only non-specific binding is detected at the E-I junction. The curve for 6 h TSA treatment (green) shows a reduction with respect to the control (blue) and 2 h TSA treatment (red). (B) A fraction of the genes show sensitivity to TSA treatment at 2 hours. Each junction was analyzed separately, and for each junction genes included in the analysis (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048084#s3" target="_blank">Materials and Methods</a>) were divided into categories of increased (Up), decreased (Down) or unchanged (less than 2-fold change in any direction) U2AF65 counts in a region of +/−100 nt around the corresponding junction. E-I junction was used as a control, assuming that variations in these counts (non-specific) were random. Analysis of changes in the junctions of individual genes after 2 h TSA treatment shows that almost 20% of the genes tend to have less U2AF65 binding in I-E junctions (and only 5% have increased binding). As a control, E-I junction shows less than 10% of the genes with decreased binding and 7% with increased binding. Distributions for the two junctions are significantly different (asterisk, chi-squared test for independence between fold-change categories and type of junction, <i>p</i> = 0.00032). (C) U2AF65 binding to lincRNAs increase upon TSA treatment. Distribution of lincRNA iCLIP counts in the three libraries, discriminating by the abundant MALAT1 and NEAT1 nuclear-retained ncRNAs and all the other lincRNAs. Inset: magnification of the binding to MALAT1 and other lincRNAs, excluding NEAT1. (D) U2AF65 increase binding to specific sites in MALAT1 and NEAT1. UCSC browser window showing a portion of MALAT1 (top) and NEAT1 (bottom) genes and the U2AF65 iCLIP counts for Control, 2 h and 6 h TSA-treated cells (complete genes with binding sequence info can be found in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048084#pone.0048084.s005" target="_blank">Fig. S5</a>). Orange boxes mark regions with peaks appearing at 2 h TSA and not further increasing, or even decreasing, at 6 h (MALAT1 peaks). Green boxes mark regions with peaks gradually increasing to their maximum at 6 h TSA (NEAT1 peaks). (E) Co-immunofluorescence analysis on untreated HEK-293 cells (top row) and cells treated with 1 µM TSA for 2 h (middle) or 6 h (bottom). For each condition, a high magnification view of speckle and paraspeckle compartments is shown (right panels). In untreated cells, the paraspeckles marker PSP1 does not colocalize with U2AF65 speckles, but after 6 h TSA co-localization of PSP1 and U2AF65 is observed. 2 h TSA treatment leads to an intermediate state were paraspeckles and U2AF65 granules are starting to be associated. Nuclei were stained with DAPI. Scale bars, 10 µm.</p

Splicing factor dynamics suggests that accumulation in speckles is due to inefficient recruitment to pre-mRNA.

<p>(A) FRAP analysis of SRSF1 and U2AF65 splicing factors fused to EYFP show that their kinetics of association to speckles are not modified after TSA treatment. For this experiment, C33A cells stably expressing the corresponding EYFP-fusion protein were used. Similar results were obtained for other splicing factors transiently transfected in HeLa cells (not shown). We show a representative cell for each group. The circle shows the speckle area where the laser pulse was applied, and where fluorescence recovery was measured afterwards. Fluorescence intensity is expressed relative to the fluorescence prior photobleaching. The length of TSA treatment was 4 h for U2AF65 and 6 h for SRSF1. The curves are averages from 10 to 15 cells. (B) Direct interaction between splicing factors and histones is detectable but not affected by TSA treatment. Interaction between the mCherry-tagged splicing factor SRSF1 and the EGFP-tagged histone H2B was analyzed by FLIM-FRET technique. A representative cell expressing both tagged proteins and its FRET efficiency map is showed. Also, the FRET efficiency map of a representative cell expressing EGFP-H2B and mCherry-C1 empty plasmid is shown as a control (NO FRET). The pixels histogram shows average FRET efficiency distributions for Control (7 cells) and TSA-treated cells (6 cells). Peaks of FRET are marked by colored arrowheads, indicating interaction between these two proteins. Nuclear regions associated to these distinct FRET populations are also marked by colored arrowheads in the E _FRET map. (C) Nucleoplasmic interaction between splicing factors is not impaired by TSA treatment. The interaction between EGFP-U1-70K and mCherry-SRSF1, a known interaction pair <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048084#pone.0048084-Ellis1" target="_blank">[51]</a> was assessed by FLIM-FRET in Control and TSA-treated cells. Upper panels: control cells, transfected with mCherry instead of mCherry-SRSF1, show no FRET signal in either speckles or nucleoplasm. Lower panels: FRET efficiency between the two splicing factors is intermediate in nucleoplasm (green) with stronger (red) areas in speckles (marked with white arrowheads in control cells). (D) Proposed model to explain how relaxation of chromatin structure affects splicing factor distribution. Nucleoplasmic free splicing factors are in dynamic equilibrium with splicing factors in speckles (<i>a</i>). Free splicing factors can also interact with other splicing factors independently of splicing (<i>b</i>), these complexes being found both in nucleoplasm and speckles. However, what we call nucleoplasmic fraction involves also splicing factors briefly interacting with other molecules (such as histones) through abundant low affinity interactions (<i>c</i>) and splicing factors recruited to RNA and engaged in productive spliceosome assembly (<i>d</i>). For model simplicity, in <i>c</i> we only included interactions with histones and in <i>d</i> we only depicted co-transcriptional splicing. The red lines and arrows symbolize the proposed system response after TSA treatment: decreased efficiency in recruitment cause an excess of free splicing factors that is buffered by the speckles compartment.</p

Membrane potential depolarization and TSA treatment of neuroblastoma cells cause splicing factors accumulation in speckles.

<p>(A) N2a cells were transiently transfected with plasmids encoding SRSF2 or SRSF1 splicing factors fused to EGFP, along with a plasmid encoding histone H3 fused to mCherry. After one day, cells were either treated for 6 hours with 0.2 ng/µl TSA (TSA), 60 mM KCl (DEPOL) or left untreated (CONTROL). Enlarged nuclear speckles in N2a cells containing the splicing factors in DEPOL or TSA-treated cells are marked by yellow arrowheads. Scale bars, 5 µm. (B) Analysis of intensity profile of EGFP-SRSF2 and mCherry-H2B signals across a line (yellow dotted lines) for a representative cell for each experimental condition. SRSF2 profile shows higher and wider peaks in DEPOL and TSA cells, corresponding to enlargement of nuclear speckles. No intensity changes are observed for mCherry-H2B profiles. The drop in mCherry-H2B signal at the SRSF2 peaks is typical of inter-chromatin granules. Scale bars, 5 µm. (C) Statistical analysis of splicing factor enrichment in speckles. Signal of EGFP-SRSF2 (top) and EGFP-SRSF1 (bottom) in speckles increases both in response to depolarization and TSA treatments. Intensity of splicing factor in all speckles of a focal plane was calculated for individual cells using automatic threshold and particle analysis (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048084#s3" target="_blank">Materials and Methods</a>). The total integrated density of speckles particles was normalized by total integrated density of the cell. For EGFP-SRSF2, 10 cells (Control), 8 cells (Depol) and 11 cells (TSA) were analyzed. For EGFP-SRSF1, 10 cells (Control), 7 cells (Depol) and 10 cells (TSA) were analyzed. * means significant differences between treated and control cells, using Mann-Whitney U test (p = 0.023 in Depol and 0.0044 in TSA for EGFP-SRSF2; p = 0.036 in Depol and 0.031 in TSA for EGFP-SRSF1).</p