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At least 235 records · Page 13Linked to original sources
PubMed2006

Genome-wide prediction of C. elegans genetic interactions.

To obtain a global view of functional interactions among genes in a metazoan genome, we computationally integrated interactome data, gene expression data, phenotype data, and functional annotation data from three model organisms-Saccharomyces cerevisiae, Caenorhabditis elegans, and Drosophila melanogaster-and predicted genome-wide genetic interactions in C. elegans. The resulting genetic interaction network (consisting of 18,183 interactions) provides a framework for system-level understanding of gene functions. We experimentally tested the predicted interactions for two human disease-related genes and identified 14 new modifiers.

Algorithms↗
PubMed2006

Conditional knockout mice reveal distinct functions for the global transcriptional coactivators CBP and p300 in T-cell development.

The global transcriptional coactivators CREB-binding protein (CBP) and the closely related p300 interact with over 312 proteins, making them among the most heavily connected hubs in the known mammalian protein-protein interactome. It is largely uncertain, however, if these interactions are important in specific cell lineages of adult animals, as homozygous null mutations in either CBP or p300 result in early embryonic lethality in mice. Here we describe a Cre/LoxP conditional p300 null allele (p300flox) that allows for the temporal and tissue-specific inactivation of p300. We used mice carrying p300flox and a CBP conditional knockout allele (CBPflox) in conjunction with an Lck-Cre transgene to delete CBP and p300 starting at the CD4- CD8- double-negative thymocyte stage of T-cell development. Loss of either p300 or CBP led to a decrease in CD4+ CD8+ double-positive thymocytes, but an increase in the percentage of CD8+ single-positive thymocytes seen in CBP mutant mice was not observed in p300 mutants. T cells completely lacking both CBP and p300 did not develop normally and were nonexistent or very rare in the periphery, however. T cells lacking CBP or p300 had reduced tumor necrosis factor alpha gene expression in response to phorbol ester and ionophore, while signal-responsive gene expression in CBP- or p300-deficient macrophages was largely intact. Thus, CBP and p300 each supply a surprising degree of redundant coactivation capacity in T cells and macrophages, although each gene has also unique properties in thymocyte development.

Alleles↗
PubMed2004

Duplication and divergence: the evolution of new genes and old ideas.

Over 35 years ago, Susumu Ohno stated that gene duplication was the single most important factor in evolution. He reiterated this point a few years later in proposing that without duplicated genes the creation of metazoans, vertebrates, and mammals from unicellular organisms would have been impossible. Such big leaps in evolution, he argued, required the creation of new gene loci with previously nonexistent functions. Bold statements such as these, combined with his proposal that at least one whole-genome duplication event facilitated the evolution of vertebrates, have made Ohno an icon in the literature on genome evolution. However, discussion on the occurrence and consequences of gene and genome duplication events has a much longer, and often neglected, history. Here we review literature dealing with the occurrence and consequences of gene duplication, beginning in 1911. We document conceptual and technological advances in gene duplication research from this early research in comparative cytology up to recent research on whole genomes, "transcriptomes," and "interactomes."

Animals↗
PubMed2006

Bioinformatics for cancer management in the post-genome era.

Human cancer is caused by multiple factors, such as genetic predisposition, chronic persistent inflammation, environmental factors, life style, and aging. Dysregulated proliferation, dysregulated adhesion, resistance to apoptosis, resistance to senescence, and resistance to anti-cancer drugs are features of cancer cells. Accumulation of multiple epigenetic changes and genetic alterations of cancer-associated genes during multi-stage carcinogenesis results in more malignant phenotypes. Post-genome science is characterized by omics data related to genome, transcriptome, proteome, metabolome, interactome, and epigenome as well as by high-throughput technology, such as whole-genome tiling oligonucleotide array, array CGH with 32,433 overlapping BAC clones, transcriptome microarray, mass spectrometry, tissue-based expression array, and cell-based transfection array. Benchtop oncology supplies Desktop oncology with large amounts of omics data produced by high-throughput technology. Desktop oncology establishes knowledge on cancer-related biomarkers, such as predisposition markers, diagnostic markers, prognostic markers, and therapeutic markers, by using bioinformatics and human intelligence of experts for data mining and text mining. Bedside oncology applies the knowledge established by Desktop oncology to determine therapeutics for cancer patients. Antibody drugs (Trastuzumab/Herceptin, Cetuximab/Erbitux, Bevacizumab/Avastin, et cetera), small molecule inhibitors for tyrosine kinases (Gefitinib/Iressa, Erlotinib/Tarceva, Imatinib/Gleevec, et cetera), conventional cytotoxic drugs, and anti-hormonal drugs are used for cancer chemotherapy. Biomarker monitoring contributes to therapeutic optional choice and drug dosage determination for cancer patients. Knowledge on biomarkers is feedforwarded from desktop to bedside in the translational research, and then biomarker monitoring is feedbacked from bedside to desktop in the reverse translational research. Desktop oncology is indispensable for cancer research in the post-genome era. Combination of genetic screening for cancer predisposition in the general population and precise selection of therapeutic options during cancer management could contribute to the realization of personalized prevention and to dramatically improve the prognosis of cancer patients in the future.

Antineoplastic Agents↗
PubMed2005

The yeast kinome displays scale free topology with functional hub clusters.

BACKGROUND: The availability of interaction databases provides an opportunity for researchers to utilize immense amounts of data exclusively in silico. Recently there has been an emphasis on studying the global properties of biological interactions using network analysis. While this type of analysis offers a wide variety of global insights it has surprisingly not been used to examine more localized interactions based on mechanism. In as such we have particular interest in the role of key topological components in signal transduction cascades as they are vital regulators of healthy and diseased cell states. RESULTS: We have used publicly available databases and a novel software tool termed Hubview to model the interactions of a subset of the yeast interactome, specifically protein kinases and their interaction partners. Analysis of the connectivity distribution has inferred a fat-tailed degree distribution with parameters consistent with those found in other biological networks. In addition, Hubview identified a functional clustering of a large group of kinases, distributed between three separate groupings. The complexity and average degree for each of these clusters is indicative of a specialized function (cell cycle propagation, DNA repair and pheromone response) and relative age for each cluster. CONCLUSION: Using connectivity analysis on a functional subset of proteins we have evidence that reinforces the scale free topology as a model for protein network evolution. We have identified the hub components of the kinase network and observed a tendency for these kinases to cluster together on a functional basis. As such, these results suggest an inherent trend to preserve scale free characteristics at a domain based modular level within large evolvable networks.

Multigene Family↗
PubMed2006

SCOWLP: a web-based database for detailed characterization and visualization of protein interfaces.

BACKGROUND: Currently there is a strong need for methods that help to obtain an accurate description of protein interfaces in order to be able to understand the principles that govern molecular recognition and protein function. Many of the recent efforts to computationally identify and characterize protein networks extract protein interaction information at atomic resolution from the PDB. However, they pay none or little attention to small protein ligands and solvent. They are key components and mediators of protein interactions and fundamental for a complete description of protein interfaces. Interactome profiling requires the development of computational tools to extract and analyze protein-protein, protein-ligand and detailed solvent interaction information from the PDB in an automatic and comparative fashion. Adding this information to the existing one on protein-protein interactions will allow us to better understand protein interaction networks and protein function. DESCRIPTION: SCOWLP (Structural Characterization Of Water, Ligands and Proteins) is a user-friendly and publicly accessible web-based relational database for detailed characterization and visualization of the PDB protein interfaces. The SCOWLP database includes proteins, peptidic-ligands and interface water molecules as descriptors of protein interfaces. It contains currently 74,907 protein interfaces and 2,093,976 residue-residue interactions formed by 60,664 structural units (protein domains and peptidic-ligands) and their interacting solvent. The SCOWLP web-server allows detailed structural analysis and comparisons of protein interfaces at atomic level by text query of PDB codes and/or by navigating a SCOP-based tree. It includes a visualization tool to interactively display the interfaces and label interacting residues and interface solvent by atomic physicochemical properties. SCOWLP is automatically updated with every SCOP release. CONCLUSION: SCOWLP enriches substantially the description of protein interfaces by adding detailed interface information of peptidic-ligands and solvent to the existing protein-protein interaction databases. SCOWLP may be of interest to many structural bioinformaticians. It provides a platform for automatic global mapping of protein interfaces at atomic level, representing a useful tool for classification of protein interfaces, protein binding comparative studies, reconstruction of protein complexes and understanding protein networks. The web-server with the database and its additional summary tables used for our analysis are available at http://www.scowlp.org.

Algorithms↗
PubMed2006

Cluster analysis of networks generated through homology: automatic identification of important protein communities involved in cancer metastasis.

BACKGROUND: Protein-protein interactions have traditionally been studied on a small scale, using classical biochemical methods to investigate the proteins of interest. More recently large-scale methods, such as two-hybrid screens, have been utilised to survey extensive portions of genomes. Current high-throughput approaches have a relatively high rate of errors, whereas in-depth biochemical studies are too expensive and time-consuming to be practical for extensive studies. As a result, there are gaps in our knowledge of many key biological networks, for which computational approaches are particularly suitable. RESULTS: We constructed networks, or 'interactomes', of putative protein-protein interactions in the rat proteome--the rat being an organism extensively used for cancer studies. This was achieved by integrating experimental protein-protein interaction data from many species and translating this data into the reference frame of the rat. The putative rat protein interactions were given confidence scores based on their homology to proteins that have been experimentally observed to interact. The confidence score was furthermore weighted according to the extent of the experimental evidence, giving a higher weight to more frequently observed interactions. The scoring function was subsequently validated and networks constructed around key proteins, identified as being highly up- or down-regulated in rat cell lines of high metastatic potential. Using clustering methods on the networks, we have identified key protein communities involved in cancer metastasis. CONCLUSION: The protein network generation and subsequent network analysis used here, were shown to be useful for highlighting key proteins involved in metastasis. This approach, in conjunction with microarray expression data, can be extended to other species, thereby suggesting possible pathways around proteins of interest.

Algorithms↗
PubMed2006

Integrative investigation of metabolic and transcriptomic data.

BACKGROUND: New analysis methods are being developed to integrate data from transcriptome, proteome, interactome, metabolome, and other investigative approaches. At the same time, existing methods are being modified to serve the objectives of systems biology and permit the interpretation of the huge datasets currently being generated by high-throughput methods. RESULTS: Transcriptomic and metabolic data from chemostat fermentors were collected with the aim of investigating the relationship between these two data sets. The variation in transcriptome data in response to three physiological or genetic perturbations (medium composition, growth rate, and specific gene deletions) was investigated using linear modelling, and open reading-frames (ORFs) whose expression changed significantly in response to these perturbations were identified. Assuming that the metabolic profile is a function of the transcriptome profile, expression levels of the different ORFs were used to model the metabolic variables via Partial Least Squares (Projection to Latent Structures--PLS) using PLS toolbox in Matlab. CONCLUSION: The experimental design allowed the analyses to discriminate between the effects which the growth medium, dilution rate, and the deletion of specific genes had on the transcriptome and metabolite profiles. Metabolite data were modelled as a function of the transcriptome to determine their congruence. The genes that are involved in central carbon metabolism of yeast cells were found to be the ORFs with the most significant contribution to the model.

Algorithms↗
PubMed2006

A new pooling strategy for high-throughput screening: the Shifted Transversal Design.

BACKGROUND: In binary high-throughput screening projects where the goal is the identification of low-frequency events, beyond the obvious issue of efficiency, false positives and false negatives are a major concern. Pooling constitutes a natural solution: it reduces the number of tests, while providing critical duplication of the individual experiments, thereby correcting for experimental noise. The main difficulty consists in designing the pools in a manner that is both efficient and robust: few pools should be necessary to correct the errors and identify the positives, yet the experiment should not be too vulnerable to biological shakiness. For example, some information should still be obtained even if there are slightly more positives or errors than expected. This is known as the group testing problem, or pooling problem. RESULTS: In this paper, we present a new non-adaptive combinatorial pooling design: the "shifted transversal design" (STD). It relies on arithmetics, and rests on two intuitive ideas: minimizing the co-occurrence of objects, and constructing pools of constant-sized intersections. We prove that it allows unambiguous decoding of noisy experimental observations. This design is highly flexible, and can be tailored to function robustly in a wide range of experimental settings (i.e., numbers of objects, fractions of positives, and expected error-rates). Furthermore, we show that our design compares favorably, in terms of efficiency, to the previously described non-adaptive combinatorial pooling designs. CONCLUSION: This method is currently being validated by field-testing in the context of yeast-two-hybrid interactome mapping, in collaboration with Marc Vidal's lab at the Dana Farber Cancer Institute. Many similar projects could benefit from using the Shifted Transversal Design.

Algorithms↗
PubMed2026

Library-based, multiplexed strategy for mapping protein interaction networks via crosslinking.

BACKGROUND: Protein-protein interactions are fundamental to cellular function, yet resolving their interaction interfaces and dynamic behaviors in native biological contexts remains challenging, particularly for weak or transient interactions. Crosslinking strategies based on noncanonical amino acids offer an effective means to capture such interactions; however, traditional single-site incorporation provides limited coverage and may overlook critical interaction hotspots. RESULTS: By employing a mutagenesis library, multiple interaction partners and cross-linking sites of a target protein can be simultaneously screened in a single experiment, without prior knowledge of its precise structural or functional features, enabling effective and unbiased analysis of its interaction network. In this study, we constructed an amber codon-scanning mutagenesis library of PSMD10, facilitating independent incorporation of the photocrosslinking ncAA p-azido-phenylalanine at multiple distinct residues. This approach allowed us to systematically interrogate and precisely map potential interaction regions across the protein surface. Coupled with crosslinking mass spectrometry, we identified multiple residues involved in intermolecular interactions, as well as previously unreported interaction partners, including T2FA, TBA1C, and ATRIP. CONCLUSIONS: These findings expand our understanding of PSMD10-associated proteasome interactome, demonstrate a multiplexed strategy for in situ mapping of protein interaction interfaces with broad coverage, and offer a valuable platform for developing therapeutics that target protein-protein interactions.

Protein Interaction Mapping↗
PubMed2026

Multi-omics characterization of a GPRC5A+ epithelial subpopulation associated with malignant features in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) exhibits marked cellular heterogeneity, and the cellular context of malignancy-associated epithelial programs remains incompletely defined. METHODS: We integrated 2,993 CRC samples spanning bulk RNA-seq (n = 2,568; two OS/RFS cohorts), scRNA-seq (281,961 cells/152 specimens), spatial transcriptomics (n = 6), and proteomics (n = 267). Analyses included single-cell integration/annotation, GSVA/HALLMARK, interactome, pseudotime, and ligand-receptor mapping; functional CRISPR assays, EMT immunoblotting, and xenografts; TF profiling (SCENIC/JASPAR/ChIP-qPCR); and exploratory drug-response prediction (OncoPredict), cell-sensitivity assays, and docking/MD modeling. RESULTS: We constructed a stage-stratified single-cell atlas and resolved eleven malignant epithelial subsets, characterizing Epi_4 as late-stage-enriched with EMT, hypoxia, and inflammatory programs and adverse OS/RFS. GPRC5A marked this subset, which we define as GPRC5A+Epi; its expression rose from stage I→IV and was associated with poor outcomes across cohorts, with concordant spatial/proteomic observations. GPRC5A perturbation affected CRC proliferation, migration/invasion, EMT, and xenograft tumorigenicity, supporting a functionally important role in the tested models. SCENIC and ChIP-qPCR supported FOSL1 as an upstream regulator that occupies the GPRC5A promoter. Spatial and ligand-receptor analyses predicted close association and potentially reciprocal signaling between GPRC5A+Epi and POSTN+fibroblasts (COL1A1-SDC4, COL1A1/1A2-ITGA2/ITGB1, PPIA-BSG); concurrent high GPRC5A+Epi/POSTN+Fib signatures were associated with inferior OS/RFS. Drug-response analyses identified an association between GPRC5A status and trametinib sensitivity. Docking/MD produced a computational model of a possible trametinib-GPRC5A interaction, which remains experimentally unvalidated. CONCLUSIONS: GPRC5A⁺Epi is a malignancy-associated epithelial state in CRC, and GPRC5A is functionally important for malignant phenotypes in the tested models. Its inferred relationships with POSTN⁺ fibroblasts and the trametinib findings should be regarded as hypothesis-generating pending functional crosstalk, direct-binding, and therapeutic validation.

Humans↗
PubMed2026

Prenatal BPA exposure perturbs RNA-binding protein-mediated splicing regulation and synaptogenesis in the developing cerebellum in a sex-dependent manner.

BACKGROUND: Autism spectrum disorder (ASD) is a pervasive neurodevelopmental condition characterized by social communication deficits, exhibiting a male bias in prevalence. Emerging evidence suggests that prenatal exposure to bisphenol A (BPA) may perturb neurodevelopmental trajectories relevant to ASD. While the cerebellum is increasingly recognized as a brain region implicated in ASD pathophysiology, the impact of gestational BPA exposure on its post-transcriptional alternative splicing machinery remains fundamentally undefined. METHODS: Here, we investigated sex-dependent effects of prenatal BPA exposure on the alternative splicing landscape of the neonatal rat cerebellum. We utilized RNA-seq to profile differential alternative splicing (DAS) events. Ingenuity Pathway Analysis (IPA) was used to predict biological functions and canonical pathways, and to construct the interactome network of DAS genes. To explore candidate upstream regulatory mechanisms, we performed in silico molecular docking and used high-resolution melting (HRM) qRT-PCR to validate selected splicing events. Furthermore, we assessed in vitro cellular phenotypes in primary cerebellar neurons by measuring MTS-based viability and Syn1/Psd95 puncta colocalization. RESULTS: Prenatal BPA exposure was associated with widespread DAS in genes enriched for ASD-relevant pathways in the neonatal rat cerebellum. To our knowledge, this study is the first to report molecular docking analyses predicting favorable interactions between BPA and several candidate RNA-binding proteins (RBPs), including CPEB1, RALYL, HNRNPDL, and ACO1. Our findings support a model in which BPA may perturb RBP-associated splicing regulation, including altered splicing of chromatin regulators such as Ccar1 in males. These molecular and cellular findings were accompanied by sex-stratified differences in neuronal viability and synaptic puncta measurements. BPA exposure was associated with an increased MTS viability signal in male primary cerebellar neurons, together with significant reductions in Psd95 and Syn1 puncta density, whereas female neurons showed significantly increased synaptic puncta colocalization together with reduced viability. CONCLUSIONS: In this study, we propose that prenatal BPA may be relevant to ASD-related neurodevelopmental pathways through sex-dependent changes in RBP-associated alternative splicing, including altered splicing of Ccar1 in males, together with distinct cellular outcomes. Together, these findings identify the developing cerebellum as a sensitive target of prenatal BPA exposure and highlight alternative splicing as a candidate pathway relevant to ASD biology.

Animals↗
PubMed2004

Alternatively spliced protein variants as potential therapeutic targets for male infertility and contraception.

Mammalian sperm were previously shown to express the PP1gamma2 isoform of protein phosphatase 1 (PP1) as well as its regulatory proteins inhibitor 2 and glycogen synthase kinase 3. Furthermore, the development of sperm motility during transit through the epididymis correlates with changes in PP1 activity. Thus, since PP1 cellular activity is determined by the partners it binds, we embarked on a study aimed at defining the specific interactomes of PP1gamma1 and PP1gamma2 (the two known alternatively spliced variants of PP1gamma). To this end, exhaustive screens were performed on a human testis cDNA library using the yeast two-hybrid method. Among the various proteins detected, the most abundant interactors with PP1gamma2 were Nek2A and R15B. Closer sequence analysis revealed novel alternatively spliced variants of Nek2A and NIPP1, which we designated Nek2A-T and NIPP1-T, respectively. They were shown to be highly expressed in rat and human testis by Northern analysis and to result from alternative splicing events by RT-PCR. Thus, both the previously known Nek2A isoform and the novel Nek2A-T and NIPP1-T variants appear to bind PP1gamma2 in vitro (blot overlays) and in vivo by coexpression in yeast. The usefulness of testis-specific alternatively spliced proteins as targets for the development of novel therapeutic strategies for male infertility and contraception is discussed. PP1gamma2, Nek2A-T, and NIPP1-T are currently being investigated as alternatively spliced targets for signal transduction therapeutics.

Alternative Splicing↗
PubMed2025

Influenza A virus induces PI4P production at the endoplasmic reticulum in an ATG16L1-dependent manner to promote the egress of viral ribonucleoproteins.

The genomic RNAs of influenza A viruses (IAVs) are replicated in the nucleus of infected cells in the form of viral ribonucleoproteins (vRNPs) before being exported to the cytoplasm. The small GTPase RAB11A is involved in the transport of vRNPs to the sites of viral assembly at the plasma membrane, but the molecular mechanisms involved remain largely unknown. Here we show that IAV infection remodels the architecture of the endoplasmic reticulum (ER) sheets, where vRNPs tend to accumulate in the absence of RAB11A. To decipher the interplay between RAB11A, vRNPs, and the ER, we investigated viral-induced perturbations of RAB11A proximity interactome. To this end, we generated cells stably expressing a TurboID-RAB11A fusion protein and performed biotin-based proximity labeling upon viral infection. We found that cellular regulators of phophatidylinositol-4-phosphate (PI4P) homeostasis, including the autophagic and stress response protein ATG16L1, are significantly enriched at the vicinity of RAB11A in infected cells. Infection induces an increase in cellular PI4P levels in an ATG16L1-dependent manner, while ATG16L1 relocalizes to ER membranes upon infection. Depletion of ATG16L1 decreases the co-distribution of vRNPs with PI4P punctae on ER membranes, and reduces the accumulation of vRNPs at the plasma membrane as well as the production of IAV infectious particles. Our data extend to IAVs the notion that viruses can modulate the metabolism and localization of phosphoinositides to control host membrane dynamics and point to the ER as an essential platform for vRNP transport. They provide evidence for a pivotal role of ATG16L1 in regulating the identity of endomembranes and coordinating RAB11A and PI4P-enriched membranes to ensure delivery of vRNPs to the plasma membrane.

Endoplasmic Reticulum↗
PubMed2024

Identification of interaction partners of outer inflammatory protein A: Computational and experimental insights into how Helicobacter pylori infects host cells.

Outer membrane proteins (OMPs) play a key role in facilitating the survival of Helicobacter pylori within the gastric tissue by mediating adherence. Among these proteins, Outer inflammatory protein A (OipA) is a critical factor in H. pylori colonization of the host gastric epithelial cell surface. While the role of OipA in H. pylori attachment and its association with clinical outcomes have been established, the structural mechanisms underlying OipA's action in adherence to gastric epithelial cells remain limited. Our study employed experimental and computational approaches to investigate the interaction partners of OipA on the gastric epithelial cell surface. Initially, we conducted a proteomic analysis using a pull-down assay with recombinant OipA and gastric epithelial cell membrane proteins to identify the OipA interactome. This analysis revealed 704 unique proteins that interacted with OipA. We subsequently analyzed 16 of these OipA partners using molecular modeling tools. Among these 16 partners, we highlight three human proteins, namely Hepatocyte growth factor (HGF), Mesenchymal epithelial transition factor receptor (Met), and Adhesion G Protein-Coupled Receptor B1 (AGRB1) that could play a role in H. pylori adherence to the gastric epithelial cell surface with OipA. Collectively, these findings reveal novel host interactions mediated by OipA, suggesting their potential as therapeutic targets for combating H. pylori infection.

Helicobacter pylori↗
PubMed2025

Plasmodium ARK1 regulates spindle formation during atypical mitosis and forms a divergent chromosomal passenger complex.

Mitosis in Plasmodium spp., the causative agent of malaria, is fundamentally different from model eukaryotes, proceeding via a bipartite microtubule organising centre (MTOC) and lacking canonical regulators such as Polo and Bub1 kinases. During schizogony, asynchronous nuclear replication produces a multinucleate schizont, while rapid male gametogony generates an octaploid nucleus before gamete formation. Here, we identify Aurora-related kinase 1 (ARK1) as a key component of inner MTOC and spindle formation, controlling kinetochore dynamics and driving mitotic progression. Conditional ARK1 depletion disrupts spindle biogenesis, kinetochore segregation, karyokinesis and cytokinesis in both stages, and affects parasite transmission. Interactome analysis reveals ARK1 as the catalytic core of a non-canonical chromosomal passenger complex (CPC) containing two divergent inner centromere proteins (INCENPs) but lacking Survivin and Borealin. Comparative genomics indicates this CPC architecture arose early in Apicomplexa, replacing canonical centromere-targeting modules. These findings uncover a distinct mitotic machinery in Plasmodium and identify the ARK1-INCENP interface as a potential multistage target for malaria therapeutic intervention.

Aurora kinase↗
PubMed2006

Mammalian gene expression program resiliency: the roles of multiple coactivator mechanisms in hypoxia-responsive transcription.

CBP and its paralog p300 (CBP/p300 collectively) are transcriptional coactivators that are among the most interconnected proteins in the mammalian protein-protein "interactome" with over 315 described interaction partners. CBP/p300 are protein/histone acetyltransferases, but most of the protein-binding domains of CBP/p300 are unique to these two coactivators, indicating that CBP/p300 should be highly limiting. The CH1 domain of CBP/p300 was considered essential for most, if not all, hypoxia-inducible transcription by binding to hypoxia-inducible-factor-1alpha (HIF-1alpha). Mutating CH1 had little effect, however, on the hypoxia-induced transcription of the HIF-target genes Higd1a, Egln1 (prolyl-hydroxylase), Bnip3 (Bcl2-interacting-protein-3), and Pfkl (phosphofructokinase). In contrast, HIF-targets Pgf (placental growth factor) and Egln3 were strongly affected by the CH1 mutation, while Stc1 (stanniocalcin-1) and Slc2a1 (glucose-transporter-1) were moderately affected. HIF targets were also dependent on coactivation mechanisms that are sensitive to trichostatin A (TSA(S)). Paradoxically, TSA inhibits histone deacetylases (HDACs) that are usually associated with transcriptional repression, implying that HDACs can also function as coactivators. Thus, activator-specific transcription in mammals requires seemingly unrelated coactivator mechanisms, and individual target genes vary in their requirements for each mechanism. Gene expression program resiliency is therefore coupled with gene specific regulation by avoiding uniform reliance on a "keystone" coactivator interaction.

Animals↗
PubMed2001

Functional proteomics to exploit genome sequences.

The sequencing of various genomes has inaugurated a new stage in the understanding of normal and pathological cell function through the analysis of the role of proteins. Proteins, after all, that intervene in the different molecular mechanisms of life, during growth, reproduction, and in the interaction between cells, thus making it possible to describe the biology of integrated systems. In this article, we briefly describe the various stages in the progression of our knowledge, from the genome to the "functional" proteome. Emphasis is placed on a global approach to the protein-protein interactions used to describe the cellular "interactome".

Biotechnology↗