Functional Analysis of a Breast Cancer-Associated FGFR2 Single Nucleotide Polymorphism Using Zinc Finger Mediated Genome Editing

The authors thank Barts Charity for funding and Breast Cancer Campaign for funding the Barts Breast Tissue Bank

Promyelocytic leukemia nuclear bodies behave as DNA damage sensors whose response to DNA double-strand breaks is regulated by NBS1 and the kinases ATM, Chk2, and ATR

The promyelocytic leukemia (PML) nuclear body (NB) is a dynamic subnuclear compartment that is implicated in tumor suppression, as well as in the transcription, replication, and repair of DNA. PML NB number can change during the cell cycle, increasing in S phase and in response to cellular stress, including DNA damage. Although topological changes in chromatin after DNA damage may affect the integrity of PML NBs, the molecular or structural basis for an increase in PML NB number has not been elucidated. We demonstrate that after DNA double-strand break induction, the increase in PML NB number is based on a biophysical process, as well as ongoing cell cycle progression and DNA repair. PML NBs increase in number by a supramolecular fission mechanism similar to that observed in S-phase cells, and which is delayed or inhibited by the loss of function of NBS1, ATM, Chk2, and ATR kinase. Therefore, an increase in PML NB number is an intrinsic element of the cellular response to DNA damage

Roles for APRIN (PDS5B) in homologous recombination and in ovarian cancer prediction

APRIN (PDS5 cohesin associated factor B) interacts with both the cohesin complex and the BRCA2 tumor suppressor. How APRIN influences cohesion and DNA repair processes is not well understood. Here, we show that APRIN is recruited to DNA damage sites. We find that APRIN interacts directly with RAD51, PALB2 and BRCA2. APRIN stimulates RAD51-mediated DNA strand invasion. APRIN also binds DNA with an affinity for D-loop structures and single-strand (ss) DNA. APRIN is a new homologous recombination (HR) mediator as it counteracts the RPA inhibitory effect on RAD51 loading to ssDNA. We show that APRIN strongly improves the annealing of complementary-strand DNA and that it can stimulate this process in synergy with BRCA2. Unlike cohesin constituents, its depletion has no impact on class switch recombination, supporting a specific role for this protein in HR. Furthermore, we show that low APRIN expression levels correlate with a better survival in ovarian cancer patients and that APRIN depletion sensitizes cells to the PARP inhibitor Olaparib in xenografted zebrafish. Our findings establish APRIN as an important and specific actor of HR, with cohesin-independent functions

“Where, O Death, Is Thy Sting?” A Brief Review of Apoptosis Biology

Apoptosis was a term introduced in 1972 to distinguish a mode of cell death with characteristic morphology and apparently regulated, endogenously driven mechanisms. The effector processes responsible for apoptosis are now mostly well known, involving activation of caspases and Bcl2 family members in response to a wide variety of physiological and injury-induced signals. The factors that lead of the decision to activate apoptosis as opposed to adaptive responses to such signals (e.g. autophagy, cycle arrest, protein synthesis shutoff) are less well understood, but the intranuclear Promyelocytic Leukaemia Body (PML body) may create a local microenvironment in which the audit of DNA damage may occur, informed by the extent of the damage, the adequacy of its repair and other aspects of cell status

The Ubiquitin E3/E4 Ligase UBE4A Adjusts Protein Ubiquitylation and Accumulation at Sites of DNA Damage, Facilitating Double-Strand Break Repair

Double-strand breaks (DSBs) are critical DNA lesions that robustly activate the elaborate DNA damage response (DDR) network. We identified a critical player in DDR fine-tuning: the E3/E4 ubiquitin ligase UBE4A. UBE4A's recruitment to sites of DNA damage is dependent on primary E3 ligases in the DDR and promotes enhancement and sustainment of K48- and K63-linked ubiquitin chains at these sites. This step is required for timely recruitment of the RAP80 and BRCA1 proteins and proper organization of RAP80- and BRCA1-associated protein complexes at DSB sites. This pathway is essential for optimal end resection at DSBs, and its abrogation leads to upregulation of the highly mutagenic alternative end-joining repair at the expense of error-free homologous recombination repair. Our data uncover a critical regulatory level in the DSB response and underscore the importance of fine-tuning the complex DDR network for accurate and balanced execution of DSB repair

Mammalian PRP4 kinase copurifies and interacts with components of both the U5 snRNP and the N-CoR deacetylase complexes

A growing body of evidence supports the coordination of pre-mRNA processing and transcriptional regulation. We demonstrate here that mammalian PRP4 kinase (PRP4K) is associated with complexes involved in both of these processes. PRP4K is implicated in pre-mRNA splicing as the homologue of the Schizosaccharomyces pombe pre-mRNA splicing kinase Prp4p, and it is enriched in SC35-containing nuclear splicing speckles. RNA interference of Caenorhabditis elegans PRP4K indicates that it is essential in metazoans. In support of a role for PRP4K in pre-mRNA splicing, we identified PRP6, SWAP, and pinin as interacting proteins and demonstrated that PRP4K is a U5 snRNP-associated kinase. In addition, BRG1 and N-CoR, components of nuclear hormone coactivator and corepressor complexes, also interact with PRP4K. PRP4K coimmunoprecipitates with N-CoR, BRG1, pinin, and PRP6, and we present data suggesting that PRP6 and BRG1 are substrates of this kinase. Lastly, PRP4K, BRG1, and PRP6 can be purified as components of the N-CoR-2 complex, and affinity-purified PRP4K/N-CoR complexes exhibit deacetylase activity. We suggest that PRP4K is an essential kinase that, in association with the both U5 snRNP and N-CoR deacetylase complexes, demonstrates a possible coordination of pre-mRNA splicing with chromatin remodeling events involved in transcriptional regulation

Amino acid classification based spectrum kernel fusion for protein subnuclear localization

<p>Abstract</p> <p>Background</p> <p>Prediction of protein localization in subnuclear organelles is more challenging than general protein subcelluar localization. There are only three computational models for protein subnuclear localization thus far, to the best of our knowledge. Two models were based on protein primary sequence only. The first model assumed homogeneous amino acid substitution pattern across all protein sequence residue sites and used BLOSUM62 to encode <it>k</it>-mer of protein sequence. Ensemble of SVM based on different <it>k</it>-mers drew the final conclusion, achieving 50% overall accuracy. The simplified assumption did not exploit protein sequence profile and ignored the fact of heterogeneous amino acid substitution patterns across sites. The second model derived the <it>PsePSSM </it>feature representation from protein sequence by simply averaging the profile PSSM and combined the <it>PseAA </it>feature representation to construct a kNN ensemble classifier <it>Nuc-PLoc</it>, achieving 67.4% overall accuracy. The two models based on protein primary sequence only both achieved relatively poor predictive performance. The third model required that GO annotations be available, thus restricting the model's applicability.</p> <p>Methods</p> <p>In this paper, we only use the amino acid information of protein sequence without any other information to design a widely-applicable model for protein subnuclear localization. We use <it>K</it>-spectrum kernel to exploit the contextual information around an amino acid and the conserved motif information. Besides expanding window size, we adopt various amino acid classification approaches to capture diverse aspects of amino acid physiochemical properties. Each amino acid classification generates a series of spectrum kernels based on different window size. Thus, (I) window expansion can capture more contextual information and cover size-varying motifs; (II) various amino acid classifications can exploit multi-aspect biological information from the protein sequence. Finally, we combine all the spectrum kernels by simple addition into one single kernel called <it>SpectrumKernel+ </it>for protein subnuclear localization.</p> <p>Results</p> <p>We conduct the performance evaluation experiments on two benchmark datasets: <it>Lei </it>and <it>Nuc-PLoc</it>. Experimental results show that <it>SpectrumKernel+ </it>achieves substantial performance improvement against the previous model <it>Nuc-PLoc</it>, with overall accuracy <it>83.47% </it>against <it>67.4%</it>; and <it>71.23% </it>against <it>50% </it>of <it>Lei SVM Ensemble</it>, against 66.50% of <it>Lei GO SVM Ensemble</it>.</p> <p>Conclusion</p> <p>The method <it>SpectrumKernel</it>+ can exploit rich amino acid information of protein sequence by embedding into implicit size-varying motifs the multi-aspect amino acid physiochemical properties captured by amino acid classification approaches. The kernels derived from diverse amino acid classification approaches and different sizes of <it>k</it>-mer are summed together for data integration. Experiments show that the method <it>SpectrumKernel</it>+ significantly outperforms the existing models for protein subnuclear localization.</p

Regulation of Stress-Inducible Phosphoprotein 1 Nuclear Retention by Protein Inhibitor of Activated STAT PIAS1

Stress-inducible phosphoprotein 1 (STI1), a cochaperone for Hsp90, has been shown to regulate multiple pathways in astrocytes, but its contributions to cellular stress responses are not fully understood. We show that in response to irradiation-mediated DNA damage stress STI1 accumulates in the nucleus of astrocytes. Also, STI1 haploinsufficiency decreases astrocyte survival after irradiation. Using yeast two-hybrid screenings we identified several nuclear proteins as STI1 interactors. Overexpression of one of these interactors, PIAS1, seems to be specifically involved in STI1 nuclear retention and in directing STI1 and Hsp90 to specific sub-nuclear regions. PIAS1 and STI1 co-immunoprecipitate and PIAS1 can function as an E3 SUMO ligase for STI. Using mass spectrometry we identified five SUMOylation sites in STI1. A STI1 mutant lacking these five sites is not SUMOylated, but still accumulates in the nucleus in response to increased expression of PIAS1, suggesting the possibility that a direct interaction with PIAS1 could be responsible for STI1 nuclear retention. To test this possibility, we mapped the interaction sites between PIAS1 and STI1 using yeast-two hybrid assays and surface plasmon resonance and found that a large domain in the N-terminal region of STI1 interacts with high affinity with amino acids 450-480 of PIAS1. Knockdown of PIAS1 in astrocytes impairs the accumulation of nuclear STI1 in response to irradiation. Moreover, a PIAS1 mutant lacking the STI1 binding site is unable to increase STI1 nuclear retention. Interestingly, in human glioblastoma multiforme PIAS1 expression is increased and we found a significant correlation between increased PIAS1 expression and STI1 nuclear localization. These experiments provide evidence that direct interaction between STI1 and PIAS1 is involved in the accumulation of nuclear STI1. This retention mechanism could facilitate nuclear chaperone activity. Molecular & Cellular Proteomics 12: 10.1074/mcp.M113.031005, 3253-3270, 2013

Functional Connection between Rad51 and PML in Homology-Directed Repair

The promyelocytic leukemia protein (PML) is a tumor suppressor critical for formation of nuclear bodies (NBs) performing important functions in transcription, apoptosis, DNA repair and antiviral responses. Earlier studies demonstrated that simian virus 40 (SV40) initiates replication near PML NBs. Here we show that PML knockdown inhibits viral replication in vivo, thus indicating a positive role of PML early in infection. SV40 large T antigen (LT) induces DNA damage and, consequently, nuclear foci of the key homologous recombination repair protein Rad51 that colocalize with PML. PML depletion abrogates LT-induced Rad51 foci. LT may target PML NBs to gain access to DNA repair factors like Rad51 that are required for viral replication. We have used the SV40 model to gain insight to DNA repair events involving PML. Strikingly, even in normal cells devoid of viral oncoproteins, PML is found to be instrumental for foci of Rad51, Mre11 and BRCA1, as well as homology-directed repair after double-strand break (DSB) induction. Following LT expression or external DNA damage, PML associates with Rad51. PML depletion also causes a loss of RPA foci following γ-irradiation, suggesting that PML is required for processing of DSBs. Immunofluorescent detection of incorporated BrdU without prior denaturation indicates a failure to generate ssDNA foci in PML knockdown cells upon γ-irradiation. Consistent with the lack of RPA and BrdU foci, γ-irradiation fails to induce Chk1 activation, when PML is depleted. Taken together, we have discovered a novel functional connection between PML and the homologous recombination-mediated repair machinery, which might contribute to PML tumor suppressor activity

Assessing protein similarity with Gene Ontology and its use in subnuclear localization prediction

BACKGROUND: The accomplishment of the various genome sequencing projects resulted in accumulation of massive amount of gene sequence information. This calls for a large-scale computational method for predicting protein localization from sequence. The protein localization can provide valuable information about its molecular function, as well as the biological pathway in which it participates. The prediction of localization of a protein at subnuclear level is a challenging task. In our previous work we proposed an SVM-based system using protein sequence information for this prediction task. In this work, we assess protein similarity with Gene Ontology (GO) and then improve the performance of the system by adding a module of nearest neighbor classifier using a similarity measure derived from the GO annotation terms for protein sequences. RESULTS: The performance of the new system proposed here was compared with our previous system using a set of proteins resided within 6 localizations collected from the Nuclear Protein Database (NPD). The overall MCC (accuracy) is elevated from 0.284 (50.0%) to 0.519 (66.5%) for single-localization proteins in leave-one-out cross-validation; and from 0.420 (65.2%) to 0.541 (65.2%) for an independent set of multi-localization proteins. The new system is available at . CONCLUSION: The prediction of protein subnuclear localizations can be largely influenced by various definitions of similarity for a pair of proteins based on different similarity measures of GO terms. Using the sum of similarity scores over the matched GO term pairs for two proteins as the similarity definition produced the best predictive outcome. Substantial improvement in predicting protein subnuclear localizations has been achieved by combining Gene Ontology with sequence information