RESUMO
Osteoclasts are multinucleated, giant cells derived from myeloid progenitors. While receptor activator of NF-κB ligand (RANKL) stimulation is the primary driver of osteoclast differentiation, additional signaling further contributes to osteoclast maturation. Here, we demonstrate that immunoglobulin superfamily member 11 (IgSF11), whose expression increases during osteoclast differentiation, regulates osteoclast differentiation through interaction with postsynaptic density protein 95 (PSD-95), a scaffold protein with multiple protein interaction domains. IgSF11 deficiency in vivo results in impaired osteoclast differentiation and bone resorption but no observed defect in bone formation. Consequently, IgSF11-deficient mice exhibit increased bone mass. Using in vitro osteoclast culture systems, we show that IgSF11 functions through homophilic interactions. Additionally, we demonstrate that impaired osteoclast differentiation in IgSF11-deficient cells is rescued by full-length IgSF11 and that the IgSF11-PSD-95 interaction requires the 75 C-terminal amino acids of IgSF11. Our findings reveal a critical role for IgSF11 during osteoclast differentiation and suggest a role for IgSF11 in a receptor- and signal transduction molecule-containing protein complex.
RESUMO
BACKGROUND: RNA localization involves cis-motifs that are recognized by RNA-binding proteins (RBP), which then mediate localization to specific sub-cellular compartments. RNA localization is critical for many different cell functions, e.g., in neuronal dendrites, localization is a critical step for long-lasting synaptic potentiation. However, there is little consensus regarding which RNAs are localized and the role of alternative isoforms in localization. A comprehensive catalog of localized RNA can help dissect RBP/RNA interactions and localization motifs. Here, we utilize a single cell sub-cellular RNA sequencing approach to profile differentially localized RNAs from individual cells across multiple single cells to help identify a consistent set of localized RNA in mouse neurons. RESULTS: Using independent RNA sequencing from soma and dendrites of the same neuron, we deeply profiled the sub-cellular transcriptomes to assess the extent and variability of dendritic RNA localization in individual hippocampal neurons, including an assessment of differential localization of alternative 3'UTR isoforms. We identified 2225 dendritic RNAs, including 298 cases of 3'UTR isoform-specific localization. We extensively analyzed the localized RNAs for potential localization motifs, finding that B1 and B2 SINE elements are up to 5.7 times more abundant in localized RNA 3'UTRs than non-localized, and also functionally characterized the localized RNAs using protein structure analysis. CONCLUSION: We integrate our list of localized RNAs with the literature to provide a comprehensive list of known dendritically localized RNAs as a resource. This catalog of transcripts, including differentially localized isoforms and computationally hypothesized localization motifs, will help investigators further dissect the genome-scale mechanism of RNA localization.
Assuntos
Dendritos/metabolismo , Hipocampo/metabolismo , Neurônios/metabolismo , Isoformas de RNA/genética , RNA Mensageiro/genética , Regiões 3' não Traduzidas , Animais , Camundongos , Isoformas de RNA/metabolismo , RNA Mensageiro/metabolismo , Análise de Sequência de RNA , Frações Subcelulares/metabolismo , TranscriptomaRESUMO
Non-alcoholic fatty liver disease (NAFLD) is a leading form of chronic liver disease with large unmet need. Non-alcoholic steatohepatitis (NASH), a progressive variant of NAFLD, can lead to fibrosis, cirrhosis, and hepatocellular carcinoma. To identify potential new therapeutics for NASH, we used a computational approach based on Connectivity Map (CMAP) analysis, which pointed us to bromodomain and extra-terminal motif (BET) inhibitors for treating NASH. To experimentally validate this hypothesis, we tested a small-molecule inhibitor of the BET family of proteins, GSK1210151A (I-BET151), in the STAM mouse NASH model at two different dosing timepoints (onset of NASH and progression to fibrosis). I-BET151 decreased the non-alcoholic fatty liver disease activity score (NAS), a clinical endpoint for assessing the severity of NASH, as well as progression of liver fibrosis and interferon-γ expression. Transcriptional characterization of these mice through RNA-sequencing was consistent with predictions from the CMAP analysis of a human NASH signature and pointed to alterations in molecular mechanisms related to interferon signaling and cholesterol biosynthesis, as well as reversal of gene expression patterns linked to fibrotic markers. Altogether, these results suggest that inhibition of BET proteins may present a novel therapeutic opportunity in the treatment of NASH and liver fibrosis.
Assuntos
Biologia Computacional/métodos , Redes Reguladoras de Genes/efeitos dos fármacos , Compostos Heterocíclicos de 4 ou mais Anéis/administração & dosagem , Cirrose Hepática/tratamento farmacológico , Hepatopatia Gordurosa não Alcoólica/tratamento farmacológico , Animais , Colesterol/biossíntese , Modelos Animais de Doenças , Progressão da Doença , Perfilação da Expressão Gênica , Regulação da Expressão Gênica/efeitos dos fármacos , Compostos Heterocíclicos de 4 ou mais Anéis/farmacologia , Humanos , Interferon gama/metabolismo , Cirrose Hepática/genética , Cirrose Hepática/imunologia , Camundongos , Hepatopatia Gordurosa não Alcoólica/genética , Hepatopatia Gordurosa não Alcoólica/imunologia , Análise de Sequência de RNA , Índice de Gravidade de DoençaRESUMO
Recognition of protein structural fold is the starting point for many structure prediction tools and protein function inference. Fold prediction is computationally demanding and recognizing novel folds is difficult such that the majority of proteins have not been annotated for fold classification. Here we describe a new machine learning approach using a novel feature space that can be used for accurate recognition of all 1,221 currently known folds and inference of unknown novel folds. We show that our method achieves better than 94% accuracy even when many folds have only one training example. We demonstrate the utility of this method by predicting the folds of 34,330 human protein domains and showing that these predictions can yield useful insights into potential biological function, such as prediction of RNA-binding ability. Our method can be applied to de novo fold prediction of entire proteomes and identify candidate novel fold families.
Assuntos
Biologia Computacional , Proteoma , Proteômica , Biologia Computacional/métodos , Bases de Dados de Proteínas , Humanos , Modelos Moleculares , Conformação Proteica , Dobramento de Proteína , Proteômica/métodos , Reprodutibilidade dos Testes , Relação Estrutura-AtividadeRESUMO
Excessive bone resorption by osteoclasts (OCs) can result in serious clinical outcomes, including bone loss that may weaken skeletal or periodontal strength. Proper bone homeostasis and skeletal strength are maintained by balancing OC function with the bone-forming function of osteoblasts. Unfortunately, current treatments that broadly inhibit OC differentiation or function may also interfere with coupled bone formation. We therefore identified a factor, the purinergic receptor P2X5 that is highly expressed during the OC maturation phase, and which we show here plays no apparent role in early bone development and homeostasis, but which is required for osteoclast-mediated inflammatory bone loss and hyper-multinucleation of OCs. We further demonstrate that P2X5 is required for ATP-mediated inflammasome activation and IL-1ß production by OCs, and that P2X5-deficient OC maturation is rescued in vitro by addition of exogenous IL-1ß. These findings identify a mechanism by which OCs react to inflammatory stimuli, and may identify purinergic signaling as a therapeutic target for bone loss-related inflammatory conditions.
Assuntos
Inflamassomos/metabolismo , Interleucina-1beta/metabolismo , Osteoclastos/citologia , Receptores Purinérgicos P2X5/metabolismo , Trifosfato de Adenosina/metabolismo , Animais , Desenvolvimento Ósseo , Diferenciação Celular , Células Cultivadas , Técnicas de Silenciamento de Genes , Humanos , Lipopolissacarídeos/efeitos adversos , Camundongos , Osteoclastos/metabolismo , Polimorfismo de Nucleotídeo Único , Receptores Purinérgicos P2X5/genéticaRESUMO
Structures that recur across multiple different transcripts, called structure motifs, often perform a similar function-for example, recruiting a specific RNA-binding protein that then regulates translation, splicing, or subcellular localization. Identifying common motifs between coregulated transcripts may therefore yield significant insight into their binding partners and mechanism of regulation. However, as most methods for clustering structures are based on folding individual sequences or doing many pairwise alignments, this results in a tradeoff between speed and accuracy that can be problematic for large-scale data sets. Here we describe a novel method for comparing and characterizing RNA secondary structures that does not require folding or pairwise alignment of the input sequences. Our method uses the idea of constructing a distance function between two objects by their respective distances to a collection of empirical examples or models, which in our case consists of 1973 Rfam family covariance models. Using this as a basis for measuring structural similarity, we developed a clustering pipeline called NoFold to automatically identify and annotate structure motifs within large sequence data sets. We demonstrate that NoFold can simultaneously identify multiple structure motifs with an average sensitivity of 0.80 and precision of 0.98 and generally exceeds the performance of existing methods. We also perform a cross-validation analysis of the entire set of Rfam families, achieving an average sensitivity of 0.57. We apply NoFold to identify motifs enriched in dendritically localized transcripts and report 213 enriched motifs, including both known and novel structures.
Assuntos
Biologia Computacional/métodos , Conformação de Ácido Nucleico , RNA/química , Análise de Sequência de RNA/métodos , Algoritmos , Animais , Análise por Conglomerados , Dendritos/genética , Hipocampo/citologia , Hipocampo/metabolismo , Dobramento de RNA , Ratos , Reprodutibilidade dos Testes , Alinhamento de SequênciaRESUMO
BACKGROUND: Hospital emergency department (ED) clinicians will play a crucial role in responding to any terrorist incident involving radioactive materials. To date, however, there has been a paucity of research focusing specifically on ED clinicians' perspectives regarding this threat. METHODS: At the request of the Centers for Disease Control and Prevention, researchers at the University of Alabama at Birmingham conducted a series of 10 focus groups (total participants, 77) with ED physicians and nurses at hospitals in 3 US regions. Participants considered a hypothetical "dirty bomb" scenario and discussed their perceptions, concerns, information needs, preferred information sources, and views of current guidance and informational materials. RESULTS: Study participants consistently expressed the view that neither EDs nor hospital facilities are sufficiently prepared for a terrorist event involving radioactive materials. Key clinician concerns included the possibility of the hospital being overwhelmed, safety of loved ones, potential staffing problems, readiness problems, and contamination and self-protection. Participants also expressed a need for additional information, strongly disagreed with aspects of current response guidance, and in some cases indicated they would not carry out current protocols. CONCLUSIONS: This study is the first to examine the views, perceptions, and information needs of hospital ED clinicians regarding radiological terrorism. As such, the findings may be useful in informing current and future efforts to improve hospital preparedness.