The eukaryotic translation initiation factor eIF4E reprograms alternative splicing.

Aberrant splicing is typically attributed to splice-factor (SF) mutation and contributes to malignancies including acute myeloid leukemia (AML). Here, we discovered a mutation-independent means to extensively reprogram alternative splicing (AS). We showed that the dysregulated expression of eukaryotic translation initiation factor eIF4E elevated selective splice-factor production, thereby impacting multiple spliceosome complexes, including factors mutated in AML such as SF3B1 and U2AF1. These changes generated a splicing landscape that predominantly supported altered splice-site selection for ~800 transcripts in cell lines and ~4,600 transcripts in specimens from high-eIF4E AML patients otherwise harboring no known SF mutations. Nuclear RNA immunoprecipitations, export assays, polysome analyses, and mutational studies together revealed that eIF4E primarily increased SF production via its nuclear RNA export activity. By contrast, eIF4E dysregulation did not induce known SF mutations or alter spliceosome number. eIF4E interacted with the spliceosome and some pre-mRNAs, suggesting its direct involvement in specific splicing events. eIF4E induced simultaneous effects on numerous SF proteins, resulting in a much larger range of splicing alterations than in the case of mutation or dysregulation of individual SFs and providing a novel paradigm for splicing control and dysregulation.

Unique Immune Cell Coactivators Specify Locus Control Region Function and Cell Stage.

Locus control region (LCR) functions define cellular identity and have critical roles in diseases such as cancer, although the hierarchy of structural components and associated factors that drive functionality are incompletely understood. Here we show that OCA-B, a B cell-specific coactivator essential for germinal center (GC) formation, forms a ternary complex with the lymphoid-enriched OCT2 and GC-specific MEF2B transcription factors and that this complex occupies and activates an LCR that regulates the BCL6 proto-oncogene and is uniquely required by normal and malignant GC B cells. Mechanistically, through OCA-B-MED1 interactions, this complex is required for Mediator association with the BCL6 promoter. Densely tiled CRISPRi screening indicates that only LCR segments heavily bound by this ternary complex are essential for its function. Our results demonstrate how an intimately linked complex of lineage- and stage-specific factors converges on specific and highly essential enhancer elements to drive the function of a cell-type-defining LCR.

The eukaryotic translation initiation factor eIF4E elevates steady-state m7G capping of coding and noncoding transcripts.

Methyl-7-guanosine (m7G) "capping" of coding and some noncoding RNAs is critical for their maturation and subsequent activity. Here, we discovered that eukaryotic translation initiation factor 4E (eIF4E), itself a cap-binding protein, drives the expression of the capping machinery and increased capping efficiency of ∼100 coding and noncoding RNAs. To quantify this, we developed enzymatic (cap quantification; CapQ) and quantitative cap immunoprecipitation (CapIP) methods. The CapQ method has the further advantage that it captures information about capping status independent of the type of 5' cap, i.e., it is not restricted to informing on m7G caps. These methodological advances led to unanticipated revelations: 1) Many RNA populations are inefficiently capped at steady state (∼30 to 50%), and eIF4E overexpression increased this to ∼60 to 100%, depending on the RNA; 2) eIF4E physically associates with noncoding RNAs in the nucleus; and 3) approximately half of eIF4E-capping targets identified are noncoding RNAs. eIF4E's association with noncoding RNAs strongly positions it to act beyond translation. Coding and noncoding capping targets have activities that influence survival, cell morphology, and cell-to-cell interaction. Given that RNA export and translation machineries typically utilize capped RNA substrates, capping regulation provides means to titrate the protein-coding capacity of the transcriptome and, for noncoding RNAs, to regulate their activities. We also discovered a cap sensitivity element (CapSE) which conferred eIF4E-dependent capping sensitivity. Finally, we observed elevated capping for specific RNAs in high-eIF4E leukemia specimens, supporting a role for cap dysregulation in malignancy. In all, levels of capping RNAs can be regulated by eIF4E.

Features of Circulating Parainfluenza Virus Required for Growth in Human Airway.

UNLABELLED: Respiratory paramyxoviruses, including the highly prevalent human parainfluenza viruses, cause the majority of childhood croup, bronchiolitis, and pneumonia, yet there are currently no vaccines or effective treatments. Paramyxovirus research has relied on the study of laboratory-adapted strains of virus in immortalized cultured cell lines. We show that findings made in such systems about the receptor interaction and viral fusion requirements for entry and fitness-mediated by the receptor binding protein and the fusion protein-can be drastically different from the requirements for infection in vivo. Here we carried out whole-genome sequencing and genomic analysis of circulating human parainfluenza virus field strains to define functional and structural properties of proteins of circulating strains and to identify the genetic basis for properties that confer fitness in the field. The analysis of clinical strains suggests that the receptor binding-fusion molecule pairs of circulating viruses maintain a balance of properties that result in an inverse correlation between fusion in cultured cells and growth in vivo. Future analysis of entry mechanisms and inhibitory strategies for paramyxoviruses will benefit from considering the properties of viruses that are fit to infect humans, since a focus on viruses that have adapted to laboratory work provides a distinctly different picture of the requirements for the entry step of infection. IMPORTANCE: Mechanistic information about viral infection-information that impacts antiviral and vaccine development-is generally derived from viral strains grown under laboratory conditions in immortalized cells. This study uses whole-genome sequencing of clinical strains of human parainfluenza virus 3-a globally important respiratory paramyxovirus-in cell systems that mimic the natural human host and in animal models. By examining the differences between clinical isolates and laboratory-adapted strains, the sequence differences are correlated to mechanistic differences in viral entry. For this ubiquitous and pathogenic respiratory virus to infect the human lung, modulation of the processes of receptor engagement and fusion activation occur in a manner quite different from that carried out by the entry glycoprotein-expressing pair of laboratory strains. These marked contrasts in the viral properties necessary for infection in cultured immortalized cells and in natural host tissues and animals will influence future basic and clinical studies.

Aberrant DNA hypermethylation signature in acute myeloid leukemia directed by EVI1.

DNA methylation patterns are frequently dysregulated in cancer, although little is known of the mechanisms through which specific gene sets become aberrantly methylated. The ecotropic viral integration site 1 (EVI1) locus encodes a DNA binding zinc-finger transcription factor that is aberrantly expressed in a subset of acute myeloid leukemia (AML) patients with poor outcome. We find that the promoter DNA methylation signature of EVI1 AML blast cells differs from those of normal CD34(+) bone marrow cells and other AMLs. This signature contained 294 differentially methylated genes, of which 238 (81%) were coordinately hypermethylated. An unbiased motif analysis revealed an overrepresentation of EVI1 binding sites among these aberrantly hypermethylated loci. EVI1 was capable of binding to these promoters in 2 different EVI1-expressing cell lines, whereas no binding was observed in an EVI1-negative cell line. Furthermore, EVI1 was observed to interact with DNA methyl transferases 3A and 3B. Among the EVI1 AML cases, 2 subgroups were recognized, of which 1 contained AMLs with many more methylated genes, which was associated with significantly higher levels of EVI1 than in the cases of the other subgroup. Our data point to a role for EVI1 in directing aberrant promoter DNA methylation patterning in EVI1 AMLs.

GPCR-OKB: the G Protein Coupled Receptor Oligomer Knowledge Base.

SUMMARY: Rapid expansion of available data about G Protein Coupled Receptor (GPCR) dimers/oligomers over the past few years requires an effective system to organize this information electronically. Based on an ontology derived from a community dialog involving colleagues using experimental and computational methodologies, we developed the GPCR-Oligomerization Knowledge Base (GPCR-OKB). GPCR-OKB is a system that supports browsing and searching for GPCR oligomer data. Such data were manually derived from the literature. While focused on GPCR oligomers, GPCR-OKB is seamlessly connected to GPCRDB, facilitating the correlation of information about GPCR protomers and oligomers. AVAILABILITY AND IMPLEMENTATION: The GPCR-OKB web application is freely available at http://www.gpcr-okb.org

DNA methylation signatures identify biologically distinct subtypes in acute myeloid leukemia.

We hypothesized that DNA methylation distributes into specific patterns in cancer cells, which reflect critical biological differences. We therefore examined the methylation profiles of 344 patients with acute myeloid leukemia (AML). Clustering of these patients by methylation data segregated patients into 16 groups. Five of these groups defined new AML subtypes that shared no other known feature. In addition, DNA methylation profiles segregated patients with CEBPA aberrations from other subtypes of leukemia, defined four epigenetically distinct forms of AML with NPM1 mutations, and showed that established AML1-ETO, CBFb-MYH11, and PML-RARA leukemia entities are associated with specific methylation profiles. We report a 15 gene methylation classifier predictive of overall survival in an independent patient cohort (p < 0.001, adjusted for known covariates).

MDS and secondary AML display unique patterns and abundance of aberrant DNA methylation.

Increasing evidence shows aberrant hypermethylation of genes occurring in and potentially contributing to pathogenesis of myeloid malignancies. Several of these diseases, such as myelodysplastic syndromes (MDSs), are responsive to DNA methyltransferase inhibitors. To determine the extent of promoter hypermethylation in such tumors, we compared the distribution of DNA methylation of 14 000 promoters in MDS and secondary acute myeloid leukemia (AML) patients enrolled in a phase 1 trial of 5-azacytidine and the histone deacetylase inhibitor entinostat against de novo AML patients and normal CD34(+) bone marrow cells. The MDS and secondary AML patients displayed more extensive aberrant DNA methylation involving thousands of genes than did the normal CD34(+) bone marrow cells or de novo AML blasts. Aberrant methylation in MDS and secondary AML tended to affect particular chromosomal regions, occurred more frequently in Alu-poor genes, and included prominent involvement of genes involved in the WNT and MAPK signaling pathways. DNA methylation was also measured at days 15 and 29 after the first treatment cycle. DNA methylation was reversed at day 15 in a uniform manner throughout the genome, and this effect persisted through day 29, even without continuous administration of the study drugs. This trial was registered at www.clinicaltrials.gov as J0443.

Genome-wide epigenetic analysis delineates a biologically distinct immature acute leukemia with myeloid/T-lymphoid features.

Acute myeloid leukemia is a heterogeneous disease from the molecular and biologic standpoints, and even patients with a specific gene expression profile may present clinical and molecular heterogeneity. We studied the epigenetic profiles of a cohort of patients who shared a common gene expression profile but differed in that only half of them harbored mutations of the CEBPA locus, whereas the rest presented with silencing of this gene and coexpression of certain T-cell markers. DNA methylation studies revealed that these 2 groups of patients could be readily segregated in an unsupervised fashion based on their DNA methylation profiles alone. Furthermore, CEBPA silencing was associated with the presence of an aberrant DNA hypermethylation signature, which was not present in the CEBPA mutant group. This aberrant hypermethylation occurred more frequently at sites within CpG islands. CEBPA-silenced leukemias also displayed marked hypermethylation compared with normal CD34(+) hematopoietic cells, whereas CEBPA mutant cases showed only mild changes in DNA methylation compared with these normal progenitors. Biologically, CEBPA-silenced leukemias presented with a decreased response to myeloid growth factors in vitro.

Stability of eukaryotic translation initiation factor 4E mRNA is regulated by HuR, and this activity is dysregulated in cancer.

Eukaryotic translation initiation factor 4E (eIF4E) is encoded by a potent oncogene which is highly elevated in many human cancers. Few studies have investigated how the level, and thus activity, of eIF4E is regulated in healthy (noncancerous) cells and how they become elevated in malignant cells. Here, our studies reveal a novel mechanism by which eIF4E levels are regulated at the level of mRNA stability. Two factors known to modulate transcript stability, HuR and the p42 isoform of AUF1, compete for binding to the 3' untranslated regions (3'UTRs) of eIF4E mRNAs. We identified a distinct AU-rich element in the 3'UTR of eIF4E which is responsible for HuR-mediated binding and stabilization. Our studies show that HuR is upregulated in malignant cancer specimens characterized by high eIF4E levels and that its depletion leads to reduction in eIF4E levels. Further, HuR and eIF4E regulate a common set of transcripts involved in cellular proliferation (cyclin D1 and c-myc) and neoangiogenesis (vascular endothelial growth factor), which suggests a functional connection between HuR and eIF4E in the regulation of these important processes. In summary, we present a novel model for the regulation of eIF4E expression and show that this model is relevant to elevation of eIF4E levels in malignant cells.

Beyond tissueInfo: functional prediction using tissue expression profile similarity searches.

We present and validate tissue expression profile similarity searches (TEPSS), a computational approach to identify transcripts that share similar tissue expression profiles to one or more transcripts in a group of interest. We evaluated TEPSS for its ability to discriminate between pairs of transcripts coding for interacting proteins and non-interacting pairs. We found that ordering protein-protein pairs by TEPSS score produces sets significantly enriched in reported pairs of interacting proteins [interacting versus non-interacting pairs, Odds-ratio (OR) = 157.57, 95% confidence interval (CI) (36.81-375.51) at 1% coverage, employing a large dataset of about 50 000 human protein interactions]. When used with multiple transcripts as input, we find that TEPSS can predict non-obvious members of the cytosolic ribosome. We used TEPSS to predict S-nitrosylation (SNO) protein targets from a set of brain proteins that undergo SNO upon exposure to physiological levels of S-nitrosoglutathione in vitro. While some of the top TEPSS predictions have been validated independently, several of the strongest SNO TEPSS predictions await experimental validation. Our data indicate that TEPSS is an effective and flexible approach to functional prediction. Since the approach does not use sequence similarity, we expect that TEPSS will be useful for various gene discovery applications. TEPSS programs and data are distributed at http://icb.med.cornell.edu/crt/tepss/index.xml.

Scan2S: increasing the precision of PROSITE pattern motifs using secondary structure constraints.

Sequence signature databases such as PROSITE, which include protein pattern motifs indicative of a protein's function, are widely used for function prediction studies, cellular localization annotation, and sequence classification. Correct annotation relies on high precision of the motifs. We present a new and general approach for increasing the precision of established protein pattern motifs by including secondary structure constraints (SSCs). We use Scan2S, the first sequence motif-scanning program to optionally include SSCs, to augment PROSITE pattern motifs. The constraints were derived from either the DSSP secondary structure assignment or the PSIPRED predictions for PROSITE-documented true positive hits. The secondary structure-augmented motifs were scanned against all SwissProt sequences, for which secondary structure predictions were precalculated. Against this dataset, motifs with PSIPRED-derived SSCs exhibited improved performance over motifs with DSSP-derived constraints. The precision of 763 of the 782 PSIPRED-augmented motifs remained unchanged or increased compared to the original motifs; 26 motifs showed an absolute precision increase of 10-30%. We provide the complete set of augmented motifs and the Scan2S program at http://physiology.med.cornell.edu/go/scan2s. Our results suggest a general protocol for increasing the precision of protein pattern detection via the inclusion of SSCs.

Computational prediction of protein-protein interactions.

Recently a number of computational approaches have been developed for the prediction of protein-protein interactions. Complete genome sequencing projects have provided the vast amount of information needed for these analyses. These methods utilize the structural, genomic, and biological context of proteins and genes in complete genomes to predict protein interaction networks and functional linkages between proteins. Given that experimental techniques remain expensive, time-consuming, and labor-intensive, these methods represent an important advance in proteomics. Some of these approaches utilize sequence data alone to predict interactions, while others combine multiple computational and experimental datasets to accurately build protein interaction maps for complete genomes. These methods represent a complementary approach to current high-throughput projects whose aim is to delineate protein interaction maps in complete genomes. We will describe a number of computational protocols for protein interaction prediction based on the structural, genomic, and biological context of proteins in complete genomes, and detail methods for protein interaction network visualization and analysis.

Identification of GATC- and CCGG-recognizing Type II REases and their putative specificity-determining positions using Scan2S--a novel motif scan algorithm with optional secondary structure constraints.

Restriction endonucleases (REases) are DNA-cleaving enzymes that have become indispensable tools in molecular biology. Type II REases are highly divergent in sequence despite their common structural core, function and, in some cases, common specificities towards DNA sequences. This makes it difficult to identify and classify them functionally based on sequence, and has hampered the efforts of specificity-engineering. Here, we define novel REase sequence motifs, which extend beyond the PD-(D/E)XK hallmark, and incorporate secondary structure information. The automated search using these motifs is carried out with a newly developed fast regular expression matching algorithm that accommodates long patterns with optional secondary structure constraints. Using this new tool, named Scan2S, motifs derived from REases with specificity towards GATC- and CGGG-containing DNA sequences successfully identify REases of the same specificity. Notably, some of these sequences are not identified by standard sequence detection tools. The new motifs highlight potential specificity-determining positions that do not fully overlap for the GATC- and the CCGG-recognizing REases and are candidates for specificity re-engineering.

Requirements and ontology for a G protein-coupled receptor oligomerization knowledge base.

BACKGROUND: G Protein-Coupled Receptors (GPCRs) are a large and diverse family of membrane proteins whose members participate in the regulation of most cellular and physiological processes and therefore represent key pharmacological targets. Although several bioinformatics resources support research on GPCRs, most of these have been designed based on the traditional assumption that monomeric GPCRs constitute the functional receptor unit. The increase in the frequency and number of reports about GPCR dimerization/oligomerization and the implication of oligomerization in receptor function makes necessary the ability to store and access information about GPCR dimers/oligomers electronically. RESULTS: We present here the requirements and ontology (the information scheme to describe oligomers and associated concepts and their relationships) for an information system that can manage the elements of information needed to describe comprehensively the phenomena of both homo- and hetero-oligomerization of GPCRs. The comprehensive information management scheme that we plan to use for the development of an intuitive and user-friendly GPCR-Oligomerization Knowledge Base (GPCR-OKB) is the result of a community dialog involving experimental and computational colleagues working on GPCRs. CONCLUSION: Our long term goal is to disseminate to the scientific community organized, curated, and detailed information about GPCR dimerization/oligomerization and its related structural context. This information will be reported as close to the data as possible so the user can make his own judgment on the conclusions drawn for a particular study. The requirements and ontology described here will facilitate the development of future information systems for GPCR oligomers that contain both computational and experimental information about GPCR oligomerization. This information is freely accessible at http://www.gpcr-okb.org.

Mining expressed sequence tags identifies cancer markers of clinical interest.

BACKGROUND: Gene expression data are a rich source of information about the transcriptional dis-regulation of genes in cancer. Genes that display differential regulation in cancer are a subtype of cancer biomarkers. RESULTS: We present an approach to mine expressed sequence tags to discover cancer biomarkers. A false discovery rate analysis suggests that the approach generates less than 22% false discoveries when applied to combined human and mouse whole genome screens. With this approach, we identify the 200 genes most consistently differentially expressed in cancer (called HM200) and proceed to characterize these genes. When used for prediction in a variety of cancer classification tasks (in 24 independent cancer microarray datasets, 59 classifications total), we show that HM200 and the shorter gene list HM100 are very competitive cancer biomarker sets. Indeed, when compared to 13 published cancer marker gene lists, HM200 achieves the best or second best classification performance in 79% of the classifications considered. CONCLUSION: These results indicate the existence of at least one general cancer marker set whose predictive value spans several tumor types and classification types. Our comparison with other marker gene lists shows that HM200 markers are mostly novel cancer markers. We also identify the previously published Pomeroy-400 list as another general cancer marker set. Strikingly, Pomeroy-400 has 27 genes in common with HM200. Our data suggest that a core set of genes are responsive to the deregulation of pathways involved in tumorigenesis in a variety of tumor types and that these genes could serve as transcriptional cancer markers in applications of clinical interest. Finally, our study suggests new strategies to select and evaluate cancer biomarkers in microarray studies.

Modeling activated states of GPCRs: the rhodopsin template.

Activation of G Protein-Coupled Receptors (GPCRs) is an allosteric mechanism triggered by ligand binding and resulting in conformational changes transduced by the transmembrane domain. Models of the activated forms of GPCRs have become increasingly necessary for the development of a clear understanding of signal propagation into the cell. Experimental evidence points to a multiplicity of conformations related to the activation of the receptor, rendered important physiologically by the suggestion that different conformations may be responsible for coupling to different signaling pathways. In contrast to the inactive state of rhodopsin (RHO) for which several high quality X-ray structures are available, the structure-related information for the active states of rhodopsin and all other GPCRs is indirect. We have collected and stored such information in a repository we maintain for activation-specific structural data available for rhodopsin-like GPCRs, http://www.physiology.med.cornell.edu/GPCRactivation/gpcrindex.html . Using these data as structural constraints, we have applied Simulated Annealing Molecular Dynamics to construct a number of different active state models of RHO starting from the known inactive structure. The common features of the models indicate that TM3 and TM5 play an important role in activation, in addition to the well-established rearrangement of TM6. Some of the structural changes observed in these models occur in regions that were not involved in the constraints, and have not been previously tested experimentally; they emerge as interesting candidates for further experimental exploration of the conformational space of activated GPCRs. We show that none of the normal modes calculated from the inactive structure has a dominant contribution along the path of conformational rearrangement from inactive to the active forms of RHO in the models. This result may differentiate rhodopsin from other GPCRs, and the reasons for this difference are discussed in the context of the structural properties and the physiological function of the protein.

eIF4E is a central node of an RNA regulon that governs cellular proliferation.

This study demonstrates that the eukaryotic translation initiation factor eIF4E is a critical node in an RNA regulon that impacts nearly every stage of cell cycle progression. Specifically, eIF4E coordinately promotes the messenger RNA (mRNA) export of several genes involved in the cell cycle. A common feature of these mRNAs is a structurally conserved, approximately 50-nucleotide element in the 3' untranslated region denoted as an eIF4E sensitivity element. This element is sufficient for localization of capped mRNAs to eIF4E nuclear bodies, formation of eIF4E-specific ribonucleoproteins in the nucleus, and eIF4E-dependent mRNA export. The roles of eIF4E in translation and mRNA export are distinct, as they rely on different mRNA elements. Furthermore, eIF4E-dependent mRNA export is independent of ongoing RNA or protein synthesis. Unlike the NXF1-mediated export of bulk mRNAs, eIF4E-dependent mRNA export is CRM1 dependent. Finally, the growth-suppressive promyelocytic leukemia protein (PML) inhibits this RNA regulon. These data provide novel perspectives into the proliferative and oncogenic properties of eIF4E.

eIF4E promotes nuclear export of cyclin D1 mRNAs via an element in the 3'UTR.

The eukaryotic translation initiation factor eIF4E is a critical modulator of cellular growth with functions in the nucleus and cytoplasm. In the cytoplasm, recognition of the 5' m(7)G cap moiety on all mRNAs is sufficient for their functional interaction with eIF4E. In contrast, we have shown that in the nucleus eIF4E associates and promotes the nuclear export of cyclin D1, but not GAPDH or actin mRNAs. We determined that the basis of this discriminatory interaction is an approximately 100-nt sequence in the 3' untranslated region (UTR) of cyclin D1 mRNA, we refer to as an eIF4E sensitivity element (4E-SE). We found that cyclin D1 mRNA is enriched at eIF4E nuclear bodies, suggesting these are functional sites for organization of specific ribonucleoproteins. The 4E-SE is required for eIF4E to efficiently transform cells, thereby linking recognition of this element to eIF4E mediated oncogenic transformation. Our studies demonstrate previously uncharacterized fundamental differences in eIF4E-mRNA recognition between the nuclear and cytoplasmic compartments and further a novel level of regulation of cellular proliferation.

PDZBase: a protein-protein interaction database for PDZ-domains.

SUMMARY: PDZBase is a database that aims to contain all known PDZ-domain-mediated protein-protein interactions. Currently, PDZBase contains approximately 300 such interactions, which have been manually extracted from > 200 articles. The database can be queried through both sequence motif and keyword-based searches, and the sequences of interacting proteins can be visually inspected through alignments (for the comparison of several interactions), or as residue-based diagrams including schematic secondary structure information (for individual complexes).