LocTree3 prediction of localization

The prediction of protein sub-cellular localization is an important step toward elucidating protein function. For each query protein sequence, LocTree2 applies machine learning (profile kernel SVM) to predict the native sub-cellular localization in 18 classes for eukaryotes, in six for bacteria and in three for archaea. The method outputs a score that reflects the reliability of each prediction. LocTree2 has performed on par with or better than any other state-of-the-art method. Here, we report the availability of LocTree3 as a public web server. The server includes the machine learning-based LocTree2 and improves over it through the addition of homology-based inference. Assessed on sequence-unique data, LocTree3 reached an 18-state accuracy Q18 = 80 ± 3% for eukaryotes and a six-state accuracy Q6 = 89 ± 4% for bacteria. The server accepts submissions ranging from single protein sequences to entire proteomes. Response time of the unloaded server is about 90 s for a 300-residue eukaryotic protein and a few hours for an entire eukaryotic proteome not considering the generation of the alignments. For over 1000 entirely sequenced organisms, the predictions are directly available as downloads. The web server is available at http://www.rostlab.org/services/loctree3

Epstein–Barr virus microRNAs reduce immune surveillance by virus-specific CD8+ T cells

Infection with Epstein-Barr virus (EBV) affects most humans worldwide and persists life-long in the presence of robust virus-specific T-cell responses. In both immunocompromised and some immunocompetent people, EBV causes several cancers and lymphoproliferative diseases. EBV transforms B cells in vitro and encodes at least 44 microRNAs (miRNAs), most of which are expressed in EBV-transformed B cells, but their functions are largely unknown. Recently, we showed that EBV miRNAs inhibit CD4+ T-cell responses to infected B cells by targeting IL-12, MHC class II, and lysosomal proteases. Here we investigated whether EBV miRNAs also counteract surveillance by CD8+ T cells. We have found that EBV miRNAs strongly inhibit recognition and killing of infected B cells by EBV-specific CD8+ T cells through multiple mechanisms. EBV miRNAs directly target the peptide transporter subunit TAP2 and reduce levels of the TAP1 subunit, MHC class I molecules, and EBNA1, a protein expressed in most forms of EBV latency and a target of EBV-specific CD8+ T cells. Moreover, miRNA-mediated down-regulation of the cytokine IL-12 decreases the recognition of infected cells by EBV-specific CD8+ T cells. Thus, EBV miRNAs use multiple, distinct pathways, allowing the virus to evade surveillance not only by CD4+ but also by antiviral CD8+ T cells

FARS1

Aminoacyl‐tRNA synthetases (ARSs) catalyze the first step of protein biosynthesis (canonical function) and have additional (non‐canonical) functions outside of translation. Bi‐allelic pathogenic variants in genes encoding ARSs are associated with various recessive mitochondrial and multisystem disorders. We describe here a multisystem clinical phenotype based on bi‐allelic mutations in the two genes (FARSA, FARSB) encoding distinct subunits for tetrameric cytosolic phenylalanyl‐tRNA synthetase (FARS1). Interstitial lung disease with cholesterol pneumonitis on histology emerged as an early characteristic feature and significantly determined disease burden. Additional clinical characteristics of the patients included neurological findings, liver dysfunction, and connective tissue, muscular and vascular abnormalities. Structural modeling of newly identified missense mutations in the alpha subunit of FARS1, FARSA, showed exclusive mapping to the enzyme's conserved catalytic domain. Patient‐derived mutant cells displayed compromised aminoacylation activity in two cases, while remaining unaffected in another. Collectively, these findings expand current knowledge about the human ARS disease spectrum and support a loss of canonical and non‐canonical function in FARS1‐associated recessive disease

FARS1‐related disorders caused by bi‐allelic mutations in cytosolic phenylalanyl‐tRNA synthetase genes: Look beyond the lungs!

Aminoacyl‐tRNA synthetases (ARSs) catalyze the first step of protein biosynthesis (canonical function) and have additional (non‐canonical) functions outside of translation. Bi‐allelic pathogenic variants in genes encoding ARSs are associated with various recessive mitochondrial and multisystem disorders. We describe here a multisystem clinical phenotype based on bi‐allelic mutations in the two genes (FARSA, FARSB) encoding distinct subunits for tetrameric cytosolic phenylalanyl‐tRNA synthetase (FARS1). Interstitial lung disease with cholesterol pneumonitis on histology emerged as an early characteristic feature and significantly determined disease burden. Additional clinical characteristics of the patients included neurological findings, liver dysfunction, and connective tissue, muscular and vascular abnormalities. Structural modeling of newly identified missense mutations in the alpha subunit of FARS1, FARSA, showed exclusive mapping to the enzyme's conserved catalytic domain. Patient‐derived mutant cells displayed compromised aminoacylation activity in two cases, while remaining unaffected in another. Collectively, these findings expand current knowledge about the human ARS disease spectrum and support a loss of canonical and non‐canonical function in FARS1‐associated recessive disease

FARS1-related disorders caused by bi-allelic mutations in cytosolic phenylalanyl-tRNA synthetase genes: Look beyond the lungs!

Aminoacyl-tRNA synthetases (ARSs) catalyze the first step of protein biosynthesis (canonical function) and have additional (non-canonical) functions outside of translation. Bi-allelic pathogenic variants in genes encoding ARSs are associated with various recessive mitochondrial and multisystem disorders. We describe here a multisystem clinical phenotype based on bi-allelic mutations in the two genes (FARSA, FARSB) encoding distinct subunits for tetrameric cytosolic phenylalanyl-tRNA synthetase (FARS1). Interstitial lung disease with cholesterol pneumonitis on histology emerged as an early characteristic feature and significantly determined disease burden. Additional clinical characteristics of the patients included neurological findings, liver dysfunction, and connective tissue, muscular and vascular abnormalities. Structural modeling of newly identified missense mutations in the alpha subunit of FARS1, FARSA, showed exclusive mapping to the enzyme's conserved catalytic domain. Patient-derived mutant cells displayed compromised aminoacylation activity in two cases, while remaining unaffected in another. Collectively, these findings expand current knowledge about the human ARS disease spectrum and support a loss of canonical and non-canonical function in FARS1-associated recessive disease

The Human Phenotype Ontology in 2021.

The Human Phenotype Ontology (HPO, https://hpo.jax.org) was launched in 2008 to provide a comprehensive logical standard to describe and computationally analyze phenotypic abnormalities found in human disease. The HPO is now a worldwide standard for phenotype exchange. The HPO has grown steadily since its inception due to considerable contributions from clinical experts and researchers from a diverse range of disciplines. Here, we present recent major extensions of the HPO for neurology, nephrology, immunology, pulmonology, newborn screening, and other areas. For example, the seizure subontology now reflects the International League Against Epilepsy (ILAE) guidelines and these enhancements have already shown clinical validity. We present new efforts to harmonize computational definitions of phenotypic abnormalities across the HPO and multiple phenotype ontologies used for animal models of disease. These efforts will benefit software such as Exomiser by improving the accuracy and scope of cross-species phenotype matching. The computational modeling strategy used by the HPO to define disease entities and phenotypic features and distinguish between them is explained in detail.We also report on recent efforts to translate the HPO into indigenous languages. Finally, we summarize recent advances in the use of HPO in electronic health record systems

The Human Phenotype Ontology in 2021.

The Human Phenotype Ontology (HPO, https://hpo.jax.org) was launched in 2008 to provide a comprehensive logical standard to describe and computationally analyze phenotypic abnormalities found in human disease. The HPO is now a worldwide standard for phenotype exchange. The HPO has grown steadily since its inception due to considerable contributions from clinical experts and researchers from a diverse range of disciplines. Here, we present recent major extensions of the HPO for neurology, nephrology, immunology, pulmonology, newborn screening, and other areas. For example, the seizure subontology now reflects the International League Against Epilepsy (ILAE) guidelines and these enhancements have already shown clinical validity. We present new efforts to harmonize computational definitions of phenotypic abnormalities across the HPO and multiple phenotype ontologies used for animal models of disease. These efforts will benefit software such as Exomiser by improving the accuracy and scope of cross-species phenotype matching. The computational modeling strategy used by the HPO to define disease entities and phenotypic features and distinguish between them is explained in detail.We also report on recent efforts to translate the HPO into indigenous languages. Finally, we summarize recent advances in the use of HPO in electronic health record systems

The fundamentals of future international emissions trading system

The Human Phenotype Ontology (HPO, https://hpo.jax.org) was launched in 2008 to provide a comprehensive logical standard to describe and computationally analyze phenotypic abnormalities found in human disease. The HPO is now a worldwide standard for phenotype exchange. The HPO has grown steadily since its inception due to considerable contributions from clinical experts and researchers from a diverse range of disciplines. Here, we present recent major extensions of the HPO for neurology, nephrology, immunology, pulmonology, newborn screening, and other areas. For example, the seizure subontology now reflects the International League Against Epilepsy (ILAE) guidelines and these enhancements have already shown clinical validity. We present new efforts to harmonize computational definitions of phenotypic abnormalities across the HPO and multiple phenotype ontologies used for animal models of disease. These efforts will benefit software such as Exomiser by improving the accuracy and scope of cross-species phenotype matching. The computational modeling strategy used by the HPO to define disease entities and phenotypic features and distinguish between them is explained in detail.We also report on recent efforts to translate the HPO into indigenous languages. Finally, we summarize recent advances in the use of HPO in electronic health record systems