The DNA polymerases of Drosophila melanogaster.

DNA synthesis during replication or repair is a fundamental cellular process that is catalyzed by a set of evolutionary conserved polymerases. Despite a large body of research, the DNA polymerases of Drosophila melanogaster have not yet been systematically reviewed, leading to inconsistencies in their nomenclature, shortcomings in their functional (Gene Ontology, GO) annotations and an under-appreciation of the extent of their characterization. Here, we describe the complete set of DNA polymerases in D. melanogaster, applying nomenclature already in widespread use in other species, and improving their functional annotation. A total of 19 genes encode the proteins comprising three replicative polymerases (alpha-primase, delta, epsilon), five translesion/repair polymerases (zeta, eta, iota, Rev1, theta) and the mitochondrial polymerase (gamma). We also provide an overview of the biochemical and genetic characterization of these factors in D. melanogaster. This work, together with the incorporation of the improved nomenclature and GO annotation into key biological databases, including FlyBase and UniProtKB, will greatly facilitate access to information about these important proteins

Suppression of Aβ toxicity by puromycin-sensitive aminopeptidase is independent of its proteolytic activity.

The accumulation of β-amyloid (Aβ) peptide in the brain is one of the pathological hallmarks of Alzheimer's disease and is thought to be of primary aetiological significance. In an unbiased genetic screen, we identified puromycin-sensitive aminopeptidase (PSA) as a potent suppressor of Aβ toxicity in a Drosophila model system. We established that coexpression of Drosophila PSA (dPSA) in the flies' brains improved their lifespan, protected against locomotor deficits, and reduced brain Aβ levels by clearing the Aβ plaque-like deposits. However, confocal microscopy and subcellular fractionation of amyloid-expressing 7PA2 cells demonstrated that PSA localizes to the cytoplasm. Therefore, PSA and Aβ are unlikely to be in the same cellular compartment; moreover, when we artificially placed them in the same compartment in flies, we could not detect a direct epistatic interaction. The consequent hypothesis that PSA's suppression of Aβ toxicity is indirect was supported by the finding that Aβ is not a proteolytic substrate for PSA in vitro. Furthermore, we showed that the enzymatic activity of PSA is not required for rescuing Aβ toxicity in neuronal SH-SY5Y cells. We investigated whether the stimulation of autophagy by PSA was responsible for these protective effects. However PSA's promotion of autophagosome fusion with lysosomes required proteolytic activity and so its effect on autophagy is not identical to its protection against Aβ toxicity

UniProt-GOA: A central resource for data integration and GO annotation

Abstract. The Gene Ontolog

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

Testing the therapeutic potential of doxycycline in a drosophila melanogaster model of Alzheimer disease

Therapies for Alzheimer disease that reduce the production of pathogenic amyloid beta (A beta) peptides have been associated with a range of unwanted effects. For this reason, alternative strategies that promote the clearance of the peptide by preventing its aggregation and deposition in the brain have been favored. In this context we have studied doxycycline, a member of the tetracycline family of antibiotics that has shown neuroprotective effects in a number of models of neurodegenerative disease. We investigated the neuroprotective potential of doxycycline in a Drosophila model of A beta toxicity and sought to correlate any effects with the aggregation state of the peptide. We found that administration of doxycycline to A beta 42-expressing flies did not improve their lifespan but was able to slow the progression of their locomotor deficits. We also measured the rough eye phenotype of transgenic flies expressing the E22G variant of A beta 42 and showed that doxycycline administration partially rescued the toxicity of A beta in the developing eye. We correlated these in vivo effects with in vitro observations using transmission electron microscopy, dynamic light scattering, and thioflavin T binding. We found that doxycycline prevents A beta fibrillization and favors the generation of smaller, non-amyloid structures that were nontoxic as determined by the lack of caspase 3 activation in a neuroblastoma cell line. Our confirmation that doxycycline can prevent amyloid beta toxicity both in vitro and in vivo supports its therapeutic potential in AD.info:eu-repo/semantics/publishedVersio

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 non-coding 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 Gene Ontology - a computational knowledge structure describing 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, as well as guidance on how users can best make use of the data we provide. We conclude with future directions for the project

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