Annotation Extensions

Platinum-Based Twin Drug Modulates Tumor-Infiltrating Immune Cells to Improve Immune Checkpoint Blockade Therapy

Chemoimmunotherapy is an area of active research and development with a growing body of evidence supporting its potential benefits for the treatment of cancer. However, chemotherapy components of chemoimmunotherapy have several limitations, including systemic toxicity and poor performance in reversing the immunosuppressive tumor microenvironment. Here, we designed a twin drug, MROP, complexed with all-trans retinoic acid and oxaliplatin, and showed that the twin drug significantly enhanced the synergetic therapeutic efficacy with anti-PD-1 in a colorectal cancer mouse model. We demonstrated by mechanistic analyses of tumor tissue that the combination of anti-PD-1 and MROP induced immunogenic cell death and regulated tumor-infiltrating immune cells, including the polarization of tumor-associated macrophages toward type 1, a reduction in myeloid-derived suppressor cells, and a significant increase in the proportion of T cells, particularly CD8+ T cells. This paper provides a promising strategy for cancer treatment and new insight into the mechanism of chemoimmunotherapy.

The Gene Ontology resource: enriching a GOld mine

The Gene Ontology Consortium (GOC) provides the most comprehensive resource currently available for computable knowledge regarding the functions of genes and gene products. Here, we report the advances of the consortium over the past two years. The new GO-CAM annotation framework was notably improved, and we formalized the model with a computational schema to check and validate the rapidly increasing repository of 2838 GO-CAMs. In addition, we describe the impacts of several collaborations to refine GO and report a 10% increase in the number of GO annotations, a 25% increase in annotated gene products, and over 9,400 new scientific articles annotated. As the project matures, we continue our efforts to review older annotations in light of newer findings, and, to maintain consistency with other ontologies. As a result, 20 000 annotations derived from experimental data were reviewed, corresponding to 2.5% of experimental GO annotations. The website (http://geneontology.org) was redesigned for quick access to documentation, downloads and tools. To maintain an accurate resource and support traceability and reproducibility, we have made available a historical archive covering the past 15 years of GO data with a consistent format and file structure for both the ontology and annotations.

Comparative genomics analysis of Acinetobacter haemolyticus isolates from sputum samples of respiratory patients

Acinetobacter haemolyticus (A. haemolyticus) is a significant Acinetobacter pathogen, and the resistance of A. haemolyticus continues to rise due to abuse of antibiotics and the frequent gene exchange between bacteria in hospital. In this study, we performed complete genome sequencing of two A. haemolyticus strains TJR01 and TJS01 to improve our understanding of pathogenic and resistance of A. haemolyticus. Both TJR01 and TJS01 contain one chromosome and two plasmids. Compared to TJS01, more virulence factors (VFs) associated pathogenicity and resistant genes were predicted in TJR01 due to T4SS and integron associated with combination and transport. Antimicrobial susceptibility results were consistent with sequencing. We suppose TJS01 was a susceptive strain and TJR01 was an acquired multidrug resistance strain due to plasmid-mediated horizontal gene transfer. We hope these findings may be helpful for clinical treatment of A. haemolyticus infection and reduce the risk of potential outbreak infection.

Automated generation of gene summaries at the Alliance of Genome Resources

Short paragraphs that describe gene function, referred to as gene summaries, are valued by users of biological knowledgebases for the ease with which they convey key aspects of gene function. Manual curation of gene summaries, while desirable, is difficult for knowledgebases to sustain. We developed an algorithm that uses curated, structured gene data at the Alliance of Genome Resources (Alliance; www.alliancegenome.org) to automatically generate gene summaries that simulate natural language. The gene data used for this purpose include curated associations (annotations) to ontology terms from the Gene Ontology, Disease Ontology, model organism knowledgebase (MOK)-specific anatomy ontologies and Alliance orthology data. The method uses sentence templates for each data category included in the gene summary in order to build a natural language sentence from the list of terms associated with each gene. To improve readability of the summaries when numerous gene annotations are present, we developed a new algorithm that traverses ontology graphs in order to group terms by their common ancestors. The algorithm optimizes the coverage of the initial set of terms and limits the length of the final summary, using measures of information content of each ontology term as a criterion for inclusion in the summary. The automated gene summaries are generated with each Alliance release, ensuring that they reflect current data at the Alliance. Our method effectively leverages category-specific curation efforts of the Alliance member databases to create modular, structured and standardized gene summaries for seven member species of the Alliance. These automatically generated gene summaries make cross-species gene function comparisons tenable and increase discoverability of potential models of human disease. In addition to being displayed on Alliance gene pages, these summaries are also included on several MOK gene pages.

Phenotype annotation with the ontology of microbial phenotypes (OMP)

BACKGROUND

Microbial genetics has formed a foundation for understanding many aspects of biology. Systematic annotation that supports computational data mining should reveal further insights for microbes, microbiomes, and conserved functions beyond microbes. The Ontology of Microbial Phenotypes (OMP) was created to support such annotation.

RESULTS

We define standards for an OMP-based annotation framework that supports the capture of a variety of phenotypes and provides flexibility for different levels of detail based on a combination of pre- and post-composition using OMP and other Open Biomedical Ontology (OBO) projects. A system for entering and viewing OMP annotations has been added to our online, public, web-based data portal.

CONCLUSIONS

The annotation framework described here is ready to support projects to capture phenotypes from the experimental literature for a variety of microbes. Defining the OMP annotation standard should support the development of new software tools for data mining and analysis in comparative phenomics.