Modulation of gene expression via overlapping binding sites exerted by ZNF143, Notch1 and THAP11

ZNF143 is a zinc-finger protein involved in the transcriptional regulation of both coding and non-coding genes from polymerase II and III promoters. Our study deciphers the genome-wide regulatory role of ZNF143 in relation with the two previously unrelated transcription factors Notch1/ICN1 and thanatos-associated protein 11 (THAP11) in several human and murine cells. We show that two distinct motifs, SBS1 and SBS2, are associated to ZNF143-binding events in promoters of >3000 genes. Without co-occupation, these sites are also bound by Notch1/ICN1 in T-lymphoblastic leukaemia cells as well as by THAP11, a factor involved in self-renewal of embryonic stem cells. We present evidence that ICN1 binding overlaps with ZNF143 binding events at the SBS1 and SBS2 motifs, whereas the overlap occurs only at SBS2 for THAP11. We demonstrate that the three factors modulate expression of common target genes through the mutually exclusive occupation of overlapping binding sites. The model we propose predicts that the binding competition between the three factors controls biological processes such as rapid cell growth of both neoplastic and stem cells. Overall, our study establishes a novel relationship between ZNF143, THAP11 and ICN1 and reveals important insights into ZNF143-mediated gene regulation

Genome-wide evidence for an essential role of the human Staf/ZNF143 transcription factor in bidirectional transcription

In the human genome, ∼10% of the genes are arranged head to head so that their transcription start sites reside within <1 kbp on opposite strands. In this configuration, a bidirectional promoter generally drives expression of the two genes. How bidirectional expression is performed from these particular promoters constitutes a puzzling question. Here, by a combination of in silico and biochemical approaches, we demonstrate that hStaf/ZNF143 is involved in controlling expression from a subset of divergent gene pairs. The binding sites for hStaf/ZNF143 (SBS) are overrepresented in bidirectional versus unidirectional promoters. Chromatin immunoprecipitation assays with a significant set of bidirectional promoters containing putative SBS revealed that 93% of them are associated with hStaf/ZNF143. Expression of dual reporter genes directed by bidirectional promoters are dependent on the SBS integrity and requires hStaf/ZNF143. Furthermore, in some cases, functional SBS are located in bidirectional promoters of gene pairs encoding a noncoding RNA and a protein gene. Remarkably, hStaf/ZNF143 per se exhibits an inherently bidirectional transcription activity, and together our data provide the demonstration that hStaf/ZNF143 is indeed a transcription factor controlling the expression of divergent protein–protein and protein–non-coding RNA gene pairs

Quantitative Mass Spectrometry Analysis Using PAcIFIC for the Identification of Plasma Diagnostic Biomarkers for Abdominal Aortic Aneurysm

BACKGROUND: Abdominal aortic aneurysm (AAA) is characterized by increased aortic vessel wall diameter (>1.5 times normal) and loss of parallelism. This disease is responsible for 1-4% mortality occurring on rupture in males older than 65 years. Due to its asymptomatic nature, proteomic techniques were used to search for diagnostic biomarkers that might allow surgical intervention under nonlife threatening conditions. METHODOLOGY/PRINCIPAL FINDINGS: Pooled human plasma samples of 17 AAA and 17 control patients were depleted of the most abundant proteins and compared using a data-independent shotgun proteomic strategy, Precursor Acquisition Independent From Ion Count (PAcIFIC), combined with spectral counting and isobaric tandem mass tags. Both quantitative methods collectively identified 80 proteins as statistically differentially abundant between AAA and control patients. Among differentially abundant proteins, a subgroup of 19 was selected according to Gene Ontology classification and implication in AAA for verification by Western blot (WB) in the same 34 individual plasma samples that comprised the pools. From the 19 proteins, 12 were detected by WB. Five of them were verified to be differentially up-regulated in individual plasma of AAA patients: adiponectin, extracellular superoxide dismutase, protein AMBP, kallistatin and carboxypeptidase B2. CONCLUSIONS/SIGNIFICANCE: Plasma depletion of high abundance proteins combined with quantitative PAcIFIC analysis offered an efficient and sensitive tool for the screening of new potential biomarkers of AAA. However, WB analysis to verify the 19 PAcIFIC identified proteins of interest proved inconclusive save for five proteins. We discuss these five in terms of their potential relevance as biological markers for use in AAA screening of population at risk

Conservation of Salmonella Infection Mechanisms in Plants and Animals

Salmonella virulence in animals depends on effectors injected by Type III Secretion Systems (T3SSs). In this report we demonstrate that Salmonella mutants that are unable to deliver effectors are also compromised in infection of Arabidopsis thaliana plants. Transcriptome analysis revealed that in contrast to wild type bacteria, T3SS mutants of Salmonella are compromised in suppressing highly conserved Arabidopsis genes that play a prominent role during Salmonella infection of animals. We also found that Salmonella originating from infected plants are equally virulent for human cells and mice. These results indicate a high degree of conservation in the defense and infection mechanism of animal and plant hosts during Salmonella infection

Alliance of Genome Resources Portal: unified model organism research platform

The Alliance of Genome Resources (Alliance) is a consortium of the major model organism databases and the Gene Ontology that is guided by the vision of facilitating exploration of related genes in human and well-studied model organisms by providing a highly integrated and comprehensive platform that enables researchers to leverage the extensive body of genetic and genomic studies in these organisms. Initiated in 2016, the Alliance is building a central portal (www.alliancegenome.org) for access to data for the primary model organisms along with gene ontology data and human data. All data types represented in the Alliance portal (e.g. genomic data and phenotype descriptions) have common data models and workflows for curation. All data are open and freely available via a variety of mechanisms. Long-term plans for the Alliance project include a focus on coverage of additional model organisms including those without dedicated curation communities, and the inclusion of new data types with a particular focus on providing data and tools for the non-model-organism researcher that support enhanced discovery about human health and disease. Here we review current progress and present immediate plans for this new bioinformatics resource

Alliance of Genome Resources Portal: unified model organism research platform

The Alliance of Genome Resources (Alliance) is a consortium of the major model organism databases and the Gene Ontology that is guided by the vision of facilitating exploration of related genes in human and well-studied model organisms by providing a highly integrated and comprehensive platform that enables researchers to leverage the extensive body of genetic and genomic studies in these organisms. Initiated in 2016, the Alliance is building a central portal (www.alliancegenome.org) for access to data for the primary model organisms along with gene ontology data and human data. All data types represented in the Alliance portal (e.g. genomic data and phenotype descriptions) have common data models and workflows for curation. All data are open and freely available via a variety of mechanisms. Long-term plans for the Alliance project include a focus on coverage of additional model organisms including those without dedicated curation communities, and the inclusion of new data types with a particular focus on providing data and tools for the non-model-organism researcher that support enhanced discovery about human health and disease. Here we review current progress and present immediate plans for this new bioinformatics resource

The Gene Ontology knowledgebase in 2023

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project