120 research outputs found
A Novel Conserved Isoform of the Ubiquitin Ligase UFD2a/UBE4B Is Expressed Exclusively in Mature Striated Muscle Cells
Yeast Ufd2p was the first identified E4 multiubiquitin chain assembly factor. Its vertebrate homologues later referred to as UFD2a, UBE4B or E4B were also shown to have E3 ubiquitin ligase activity. UFD2a function in the brain has been well established in vivo, and in vitro studies have shown that its activity is essential for proper condensation and segregation of chromosomes during mitosis. Here we show that 2 alternative splice forms of UFD2a, UFD2a-7 and -7/7a, are expressed sequentially during myoblast differentiation of C2C12 cell cultures and during cardiotoxin-induced regeneration of skeletal muscle in mice. UFD2a-7 contains an alternate exon 7, and UFD2a-7/7a, the larger of the 2 isoforms, contains an additional novel exon 7a. Analysis of protein or mRNA expression in mice and zebrafish revealed that a similar pattern of isoform switching occurs during developmental myogenesis of cardiac and skeletal muscle. In vertebrates (humans, rodents, zebrafish), UFD2a-7/7a is expressed only in mature striated muscle. This unique tissue specificity is further validated by the conserved presence of 2 muscle-specific splicing regulatory motifs located in the 3′ introns of exons 7 and 7a. UFD2a interacts with VCP/p97, an AAA-type ATPase implicated in processes whose functions appear to be regulated, in part, through their interaction with one or more of 15 previously identified cofactors. UFD2a-7/7a did not interact with VCP/p97 in yeast 2-hybrid experiments, which may allow the ATPase to bind cofactors that facilitate its muscle-specific functions. We conclude that the regulated expression of these UFD2a isoforms most likely imparts divergent functions that are important for myogenisis
Genomic Characterization of Methanomicrobiales Reveals Three Classes of Methanogens
BACKGROUND:Methanomicrobiales is the least studied order of methanogens. While these organisms appear to be more closely related to the Methanosarcinales in ribosomal-based phylogenetic analyses, they are metabolically more similar to Class I methanogens. METHODOLOGY/PRINCIPAL FINDINGS:In order to improve our understanding of this lineage, we have completely sequenced the genomes of two members of this order, Methanocorpusculum labreanum Z and Methanoculleus marisnigri JR1, and compared them with the genome of a third, Methanospirillum hungatei JF-1. Similar to Class I methanogens, Methanomicrobiales use a partial reductive citric acid cycle for 2-oxoglutarate biosynthesis, and they have the Eha energy-converting hydrogenase. In common with Methanosarcinales, Methanomicrobiales possess the Ech hydrogenase and at least some of them may couple formylmethanofuran formation and heterodisulfide reduction to transmembrane ion gradients. Uniquely, M. labreanum and M. hungatei contain hydrogenases similar to the Pyrococcus furiosus Mbh hydrogenase, and all three Methanomicrobiales have anti-sigma factor and anti-anti-sigma factor regulatory proteins not found in other methanogens. Phylogenetic analysis based on seven core proteins of methanogenesis and cofactor biosynthesis places the Methanomicrobiales equidistant from Class I methanogens and Methanosarcinales. CONCLUSIONS/SIGNIFICANCE:Our results indicate that Methanomicrobiales, rather than being similar to Class I methanogens or Methanomicrobiales, share some features of both and have some unique properties. We find that there are three distinct classes of methanogens: the Class I methanogens, the Methanomicrobiales (Class II), and the Methanosarcinales (Class III)
HYPOXIC STRESS, HEPATOCYTES AND CACO-2 VIABILITY AND SUSCEPTIBILITY TO Shigella flexneri INVASION
SUMMARY Inflammation due to Shigella flexneri can cause damage to the colonic mucosa and cell death by necrosis and apoptosis. This bacteria can reach the bloodstream in this way, and the liver through portal veins. Hypoxia is a condition present in many human diseases, and it may induce bacterial translocation from intestinal lumen. We studied the ability of S. flexneri to invade rat hepatocytes and Caco-2 cells both in normoxic and hypoxic microenvironments, as well as morphological and physiological alterations in these cells after infection under hypoxia. We used the primary culture of rat hepatocytes as a model of study. We analyzed the following parameters in normoxic and hypoxic conditions: morphology, cell viability, bacterial recovery and lactate dehydrogenase (LDH) released. The results showed that there were fewer bacteria within the Caco-2 cells than in hepatocytes in normoxic and hypoxic conditions. We observed that the higher the multiplicity of infection (MOI) the greater the bacterial recovery in hepatocytes. The hypoxic condition decreased the bacterial recovery in hepatocytes. The cytotoxicity evaluated by LDH released by cells was significantly higher in cells submitted to hypoxia than normoxia. Caco-2 cells in normoxia released 63% more LDH than hepatocytes. LDH increased 164% when hepatocytes were submitted to hypoxia and just 21% when Caco-2 cells were in the same condition. The apoptosis evaluated by Tunel was significantly higher in cells submitted to hypoxia than normoxia. When comparing hypoxic cells, we obtained more apoptotic hepatocytes than apoptotic Caco-2 cells. Concluding our results contribute to a better knowledge of interactions between studied cells and Shigella flexneri. These data may be useful in the future to define strategies to combat this virulent pathogen
Genome-wide screens identify Toxoplasma gondii determinants of parasite fitness in IFNγ-activated murine macrophages
Macrophages play an essential role in the early immune response against Toxoplasma and are the cell type preferentially infected by the parasite in vivo. Interferon gamma (IFNγ) elicits a variety of anti-Toxoplasma activities in macrophages. Using a genome-wide CRISPR screen we identify 353 Toxoplasma genes that determine parasite fitness in naїve or IFNγ-activated murine macrophages, seven of which are further confirmed. We show that one of these genes encodes dense granule protein GRA45, which has a chaperone-like domain, is critical for correct localization of GRAs into the PVM and secretion of GRA effectors into the host cytoplasm. Parasites lacking GRA45 are more susceptible to IFNγ-mediated growth inhibition and have reduced virulence in mice. Together, we identify and characterize an important chaperone-like GRA in Toxoplasma and provide a resource for the community to further explore the function of Toxoplasma genes that determine fitness in IFNγ-activated macrophages
Diet of the lizard Liolaemus occipitalis in the coastal sand dunes of southern Brazil (Squamata-Liolaemidae)
Fixed and dynamic predictors of treatment process in therapeutic communities for substance abusers in Belgium
Phytoplankton responses to marine climate change – an introduction
Phytoplankton are one of the key players in the ocean and contribute approximately 50% to global primary production. They serve as the basis for marine food webs, drive chemical composition of the global atmosphere and thereby climate. Seasonal environmental changes and nutrient availability naturally influence phytoplankton species composition. Since the industrial era, anthropogenic climatic influences have increased noticeably – also within the ocean. Our changing climate, however, affects the composition of phytoplankton species composition on a long-term basis and requires the organisms to adapt to this changing environment, influencing micronutrient bioavailability and other biogeochemical parameters. At the same time, phytoplankton themselves can influence the climate with their responses to environmental changes. Due to its key role, phytoplankton has been of interest in marine sciences for quite some time and there are several methodical approaches implemented in oceanographic sciences. There are ongoing attempts to improve predictions and to close gaps in the understanding of this sensitive ecological system and its responses
The impact of data selection and fitting on SAR estimation for magnetic nanoparticle heating
Using a Machine Learning Logistic Regression Algorithm to Classify Nanomedicine Clinical Trials in a Known Repository
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