scholarly journals Characterizing a collective and dynamic component of chromatin immunoprecipitation enrichment profiles in yeast

2014 ◽  
Author(s):  
Lucas D. Ward ◽  
Junbai Wang ◽  
Harmen J. Bussemaker
Keyword(s):  
Protein Interactions ◽  
Chromatin Immunoprecipitation ◽  
Noncoding Rna ◽  
Chromatin State ◽  
Sequence Motifs ◽  
Protein Protein Interactions ◽  
Dynamic Component ◽  
Static Feature ◽  
Dna Sequence Motifs ◽  
Chip Enrichment

Recent chromatin immunoprecipitation (ChIP) experiments in fly, mouse, and human have revealed the existence of high-occupancy target (HOT) regions or “hotspots” that show enrichment across many assayed DNA-binding proteins. Similar co-enrichment observed in yeast so far has been treated as artifactual, and has not been fully characterized. Here we reanalyze ChIP data from both array-based and sequencing-based experiments to show that in the yeast S. cerevisiae, the collective enrichment phenomenon is strongly associated with proximity to noncoding RNA genes and with nucleosome depletion. DNA sequence motifs that confer binding affinity for the proteins are largely absent from these hotspots, suggesting that protein-protein interactions play a prominent role. The hotspots are condition-specific, suggesting that they reflect a chromatin state or protein state, and are not a static feature of underlying sequence. Additionally, only a subset of all assayed factors is associated with these loci, suggesting that the co-enrichment cannot be simply explained by a chromatin state that is universally more prone to immunoprecipitation. Together our results suggest that the co-enrichment patterns observed in yeast represent transcription factor co-occupancy. More generally, they make clear that great caution must be used when interpreting ChIP enrichment profiles for individual factors in isolation, as they will include factor-specific as well as collective contributions.

Metallocluster transactions: dynamic protein interactions guide the biosynthesis of Fe–S clusters in bacteria

2018 ◽  
Vol 46 (6) ◽  
pp. 1593-1603 ◽  
Author(s):  
Chenkang Zheng ◽  
Patricia C. Dos Santos
Keyword(s):  
Protein Interactions ◽  
Protein Complexes ◽  
Specific Protein ◽  
Biological Synthesis ◽  
Cluster Assembly ◽  
Sequence Motifs ◽  
Protein Protein Interactions ◽  
Cysteine Desulfurase ◽  
Wide Range ◽  
Domains Of Life

Iron–sulfur (Fe–S) clusters are ubiquitous cofactors present in all domains of life. The chemistries catalyzed by these inorganic cofactors are diverse and their associated enzymes are involved in many cellular processes. Despite the wide range of structures reported for Fe–S clusters inserted into proteins, the biological synthesis of all Fe–S clusters starts with the assembly of simple units of 2Fe–2S and 4Fe–4S clusters. Several systems have been associated with the formation of Fe–S clusters in bacteria with varying phylogenetic origins and number of biosynthetic and regulatory components. All systems, however, construct Fe–S clusters through a similar biosynthetic scheme involving three main steps: (1) sulfur activation by a cysteine desulfurase, (2) cluster assembly by a scaffold protein, and (3) guided delivery of Fe–S units to either final acceptors or biosynthetic enzymes involved in the formation of complex metalloclusters. Another unifying feature on the biological formation of Fe–S clusters in bacteria is that these systems are tightly regulated by a network of protein interactions. Thus, the formation of transient protein complexes among biosynthetic components allows for the direct transfer of reactive sulfur and Fe–S intermediates preventing oxygen damage and reactions with non-physiological targets. Recent studies revealed the importance of reciprocal signature sequence motifs that enable specific protein–protein interactions and consequently guide the transactions between physiological donors and acceptors. Such findings provide insights into strategies used by bacteria to regulate the flow of reactive intermediates and provide protein barcodes to uncover yet-unidentified cellular components involved in Fe–S metabolism.

scholarly journals The Autoregulatory and Transactivating Functions of the Human Cytomegalovirus IE86 Protein Use Independent Mechanisms for Promoter Binding

2007 ◽  
Vol 81 (11) ◽  
pp. 5807-5818 ◽  
Author(s):  
Dustin T. Petrik ◽  
Kimberly P. Schmitt ◽  
Mark F. Stinski
Keyword(s):  
Human Cytomegalovirus ◽  
Protein Interactions ◽  
Chromatin Immunoprecipitation ◽  
Viral Gene Expression ◽  
Artificial Chromosome ◽  
Viral Gene ◽  
Chip Assay ◽  
Protein Protein Interactions ◽  
Multiple Sequence ◽  
Viral Genes

ABSTRACT The functions of the human cytomegalovirus (HCMV) IE86 protein are paradoxical, as it can both activate and repress viral gene expression through interaction with the promoter region. Although the mechanism for these functions is not clearly defined, it appears that a combination of direct DNA binding and protein-protein interactions is involved. Multiple sequence alignment of several HCMV IE86 homologs reveals that the amino acids 534LPIYE538 are conserved between all primate and nonprimate CMVs. In the context of a bacterial artificial chromosome (BAC), mutation of both P535 and Y537 to alanines (P535A/Y537A) results in a nonviable BAC. The defective HCMV BAC does not undergo DNA replication, although the P535A/Y537A mutant IE86 protein appears to be stably expressed. The P535A/Y537A mutant IE86 protein is able to negatively autoregulate transcription from the major immediate-early (MIE) promoter and was recruited to the MIE promoter in a chromatin immunoprecipitation (ChIP) assay. However, the P535A/Y537A mutant IE86 protein was unable to transactivate early viral genes and was not recruited to the early viral UL4 and UL112 promoters in a ChIP assay. From these data, we conclude that the transactivation and repressive functions of the HCMV IE86 protein can be separated and must occur through independent mechanisms.

scholarly journals Targeting RNA Binding Proteins Involved in Neurodegeneration

2013 ◽  
Vol 18 (9) ◽  
pp. 967-983 ◽  
Author(s):  
Maurizio Romano ◽  
Emanuele Buratti
Keyword(s):  
Protein Interactions ◽  
Rna Processing ◽  
Noncoding Rna ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Correct Identification ◽  
Protein Protein Interactions ◽  
Aggregation Processes ◽  
Cellular Pathways ◽  
Screening Approaches

Dysfunctions at the level of RNA processing have recently been shown to play a fundamental role in the pathogenesis of many neurodegenerative diseases. Several proteins responsible for these dysfunctions (TDP-43, FUS/TLS, and hnRNP A/Bs) belong to the nuclear class of heterogeneous ribonucleoproteins (hnRNPs) that predominantly function as general regulators of both coding and noncoding RNA metabolism. The discovery of the importance of these factors in mediating neuronal death has represented a major paradigmatic shift in our understanding of neurodegenerative processes. As a result, these discoveries have also opened the way toward novel biomolecular screening approaches in our search for therapeutic options. One of the major hurdles in this search is represented by the correct identification of the most promising targets to be prioritized. These may include aberrant aggregation processes, protein-protein interactions, RNA-protein interactions, or specific cellular pathways altered by disease. In this review, we discuss these four major options together with their various advantages and drawbacks.

scholarly journals Sequence conservation, domain architectures, and phylogenetic distribution of the HD-GYP type c-di-GMP phosphodiesterases

2021 ◽  
Author(s):  
Michael Y. Galperin ◽  
Shan-Ho Chou
Keyword(s):  
Protein Interactions ◽  
Regulatory Protein ◽  
Second Messenger ◽  
Distribution Patterns ◽  
Distribution Functions ◽  
Amino Acid Residues ◽  
Sequence Motifs ◽  
Protein Protein Interactions ◽  
Conserved Sequence ◽  
Common Domain

The HD-GYP domain, named after two of its conserved sequence motifs, was first described in 1999 as a specialized version of the widespread HD phosphohydrolase domain that had additional highly conserved amino acid residues. Domain associations of HD-GYP indicated its involvement in bacterial signal transduction and distribution patterns of this domain suggested that it could serve as a hydrolase of the bacterial second messenger c-di-GMP, in addition to or instead of the EAL domain. Subsequent studies confirmed the ability of various HD-GYP domains to hydrolyze c-di-GMP to linear pGpG and/or GMP. Certain HD-GYP-containing proteins hydrolyze another second messenger, cGAMP, and some HD-GYP domains participate in regulatory protein-protein interactions. The recently solved structures of HD-GYP domains from four distinct organisms clarified the mechanisms of c-di-GMP binding and metal-assisted hydrolysis. However, the HD-GYP domain is poorly represented in public domain databases, which causes certain confusion about its phylogenic distribution, functions, and domain architectures. Here, we present a refined sequence model for the HD-GYP domain and describe the roles of its most conserved residues in metal and/or substrate binding. We also calculate the numbers of HD-GYPs encoded in various genomes and list the most common domain combinations involving HD-GYP, such as the RpfG (REC-HD-GYP), Bd1817 (DUF3391-HD-GYP), and PmGH (GAF-HD-GYP) protein families. We also provide the descriptions of six HD-GYP-associated domains, including four novel integral membrane sensor domains. This work is expected to stimulate studies of diverse HD-GYP-containing proteins, their N-terminal sensor domains, and the signals to which they respond.

scholarly journals The Human U5-220kD Protein (hPrp8) Forms a Stable RNA-Free Complex with Several U5-Specific Proteins, Including an RNA Unwindase, a Homologue of Ribosomal Elongation Factor EF-2, and a Novel WD-40 Protein

1998 ◽  
Vol 18 (11) ◽  
pp. 6756-6766 ◽  
Author(s):  
Tilmann Achsel ◽  
Katharina Ahrens ◽  
Hero Brahms ◽  
Stefan Teigelkamp ◽  
Reinhard Lührmann
Keyword(s):  
Conformational Changes ◽  
Protein Interactions ◽  
Elongation Factor ◽  
Sodium Thiocyanate ◽  
Sequence Motifs ◽  
Protein Protein Interactions ◽  
Small Nuclear Ribonucleoprotein ◽  
Core Proteins ◽  
Specific Proteins ◽  
Biochemical Analyses

ABSTRACT The human small nuclear ribonucleoprotein (snRNP) U5 is biochemically the most complex of the snRNP particles, containing not only the Sm core proteins but also 10 particle-specific proteins. Several of these proteins have sequence motifs which suggest that they participate in conformational changes of RNA and protein. Together, the specific proteins comprise 85% of the mass of the U5 snRNP particle. Therefore, protein-protein interactions should be highly important for both the architecture and the function of this particle. We investigated protein-protein interactions using both native and recombinant U5-specific proteins. Native U5 proteins were obtained by dissociation of U5 snRNP particles with the chaotropic salt sodium thiocyanate. A stable, RNA-free complex containing the 116-kDa EF-2 homologue (116kD), the 200kD RNA unwindase, the 220kD protein, which is the orthologue of the yeast Prp8p protein, and the U5-40kD protein was detected by sedimentation analysis of the dissociated proteins. By cDNA cloning, we show that the 40kD protein is a novel WD-40 repeat protein and is thus likely to mediate regulated protein-protein interactions. Additional biochemical analyses demonstrated that the 220kD protein binds simultaneously to the 40- and the 116kD proteins and probably also to the 200kD protein. Since the 220kD protein is also known to contact both the pre-mRNA and the U5 snRNA, it is in a position to relay the functional state of the spliceosome to the other proteins in the complex and thus modulate their activity.

scholarly journals Multiple Dimerizing Motifs Modulate the Dimerization of the Syndecan Transmembrane Domains

2020 ◽  
Author(s):  
J. Chen ◽  
F. Wang ◽  
C. He ◽  
S-Z. Luo
Keyword(s):  
Protein Interactions ◽  
Self Assembly ◽  
Transmembrane Domains ◽  
Integral Membrane Proteins ◽  
Sequence Motifs ◽  
Protein Protein Interactions ◽  
Dynamics Simulations ◽  
Considerable Complexity ◽  
Shed Light ◽  
Common Sequence

AbstractSyndecans(SDCs) are a family of four members of integral membrane proteins, which play important roles in cell-cell interactions. Dimerization/oligomerization generated by transmembrane domains (TMDs) appear to crucially regulate several functional behaviors of all syndecan members. The distinct hierarchy of protein-protein interactions mediated by the syndecan TMDs may give rise to considerable complexity in the functions of syndecans. The molecular mechanism of the different dimerization tendencies in each type of SDCs remains unclear. Here, the self-assembly process of syndecan TMD homodimers and heterodimers was studied in molecular details by molecular dynamics simulations. Our computational results showed that the SDC2 forms the most stable homodimer while the SDC1 TMD dimerizes weakly, which is consistent with previous experimental results. Detailed analysis suggests that instead of the conserved dimerizing motif G8XXXG12 in all four SDCs involved in homo- and hetero-dimerization of SDCs, the G3XXXA7 motif in SDC1 competes with the interface of G8XXXG12 and thus disturbs the SDC1 involved dimerization. The SDC3 which contains a G9XXXA13 motif, however, forms a more stable dimer than SDC1, indicating the complexity of the competing effect of the GXXXA motif. As GXXXG and GXXXA are two common sequence motifs in the dimerization of helices, our results shed light on the competing effect of multiple dimerizing motifs on the dimerization of transmembrane domains.

scholarly journals rec-Y2H matrix screening reveals a vast potential for direct protein-protein interactions among RNA binding proteins

2020 ◽  
Author(s):  
Benjamin Lang ◽  
Jae-Seong Yang ◽  
Mireia Garriga-Canut ◽  
Silvia Speroni ◽  
Maria Gili ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Interaction Networks ◽  
Sequence Motifs ◽  
Protein Protein Interactions ◽  
Binding Interaction ◽  
Transcriptional Gene Regulation

AbstractRNA-binding proteins (RBPs) are crucial factors of post-transcriptional gene regulation and their modes of action are intensely investigated. At the center of attention are RNA motifs that guide where RBPs bind. However, sequence motifs are often poor predictors of RBP-RNA interactions in vivo. It is hence believed that many RBPs recognize RNAs as complexes, to increase specificity and regulatory possibilities. To probe the potential for complex formation among RBPs, we assembled a library of 978 mammalian RBPs and used rec-Y2H screening to detect direct interactions between RBPs, sampling > 600 K interactions. We discovered 1994 new interactions and demonstrate that interacting RBPs bind RNAs adjacently in vivo. We further find that the mRNA binding region and motif preferences of RBPs can deviate, depending on their adjacently binding interaction partners. Finally, we reveal novel RBP interaction networks among major RNA processing steps and show that splicing impairing RBP mutations observed in cancer rewire spliceosomal interaction networks.Graphical abstract

scholarly journals Interactions of Sen1, Nrd1, and Nab3 with Multiple Phosphorylated Forms of the Rpb1 C-Terminal Domain in Saccharomyces cerevisiae

2012 ◽  
Vol 11 (4) ◽  
pp. 417-429 ◽  
Author(s):  
Karen Chinchilla ◽  
Juan B. Rodriguez-Molina ◽  
Doris Ursic ◽  
Jonathan S. Finkel ◽  
Aseem Z. Ansari ◽  
...  
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Rna Polymerase Ii ◽  
Protein Interactions ◽  
Noncoding Rna ◽  
Protein Protein Interactions ◽  
Coding Region ◽  
Protein Coding ◽  
Content Type ◽  
Protein Coding Genes ◽  
Terminal Domain

ABSTRACT The Saccharomyces cerevisiae SEN1 gene codes for a nuclear, ATP-dependent helicase which is embedded in a complex network of protein-protein interactions. Pleiotropic phenotypes of mutations in SEN1 suggest that Sen1 functions in many nuclear processes, including transcription termination, DNA repair, and RNA processing. Sen1, along with termination factors Nrd1 and Nab3, is required for the termination of noncoding RNA transcripts, but Sen1 is associated during transcription with coding and noncoding genes. Sen1 and Nrd1 both interact directly with Nab3, as well as with the C-terminal domain (CTD) of Rpb1, the largest subunit of RNA polymerase II. It has been proposed that Sen1, Nab3, and Nrd1 form a complex that associates with Rpb1 through an interaction between Nrd1 and the Ser 5 -phosphorylated (Ser 5 -P) CTD. To further study the relationship between the termination factors and Rpb1, we used two-hybrid analysis and immunoprecipitation to characterize sen1-R302W , a mutation that impairs an interaction between Sen1 and the Ser 2 -phosphorylated CTD. Chromatin immunoprecipitation indicates that the impairment of the interaction between Sen1 and Ser 2 -P causes the reduced occupancy of mutant Sen1 across the entire length of noncoding genes. For protein-coding genes, mutant Sen1 occupancy is reduced early and late in transcription but is similar to that of the wild type across most of the coding region. The combined data suggest a handoff model in which proteins differentially transfer from the Ser 5 - to the Ser 2 -phosphorylated CTD to promote the termination of noncoding transcripts or other cotranscriptional events for protein-coding genes.

scholarly journals Survey of Natural Language Processing Techniques in Bioinformatics

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Zhiqiang Zeng ◽  
Hua Shi ◽  
Yun Wu ◽  
Zhiling Hong
Keyword(s):  
Natural Language Processing ◽  
Text Mining ◽  
Natural Language ◽  
Language Processing ◽  
Protein Interactions ◽  
Noncoding Rna ◽  
Structure And Function ◽  
Protein Protein Interactions ◽  
And Function ◽  
Processing Techniques

Informatics methods, such as text mining and natural language processing, are always involved in bioinformatics research. In this study, we discuss text mining and natural language processing methods in bioinformatics from two perspectives. First, we aim to search for knowledge on biology, retrieve references using text mining methods, and reconstruct databases. For example, protein-protein interactions and gene-disease relationship can be mined from PubMed. Then, we analyze the applications of text mining and natural language processing techniques in bioinformatics, including predicting protein structure and function, detecting noncoding RNA. Finally, numerous methods and applications, as well as their contributions to bioinformatics, are discussed for future use by text mining and natural language processing researchers.

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